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3rd Annual CCP-BioSim Conference:
Frontiers of Biomolecular Simulation
21-23rd May 2014
University of Edinburgh
Programme and Abstract Booklet
2
Welcome to the 3rd
Annual conference of CCP-Biosim, we hope you have a very enjoyable
time here. Here are a few housekeeping details:
1. Conference venue: All talks will take place in the Prestonfield room on the first floor of the John
McIntyre Conference Centre (JMCC), Pollock Halls of residence.
Pollock Halls, 18 Holyrood Park Rd, Edinburgh EH16 5AY
See the maps below. The following links may also be useful to plan your trip to
Edinburgh.
http://www.edinburghfirst.co.uk/getting-here
http://www.edinburghfirst.co.uk/locations
2. Catering:
On Wednesday and Thursday sandwich lunches, refreshments and coffee breaks will
be served in the Centro room, JMCC, 1st floor.
There will be a drinks reception on Wednesday afternoon after the end of the poster
pitches session.
Cooked lunch on Friday will be served in the JMCC restaurant, ground floor.
PLEASE NOTE THAT NO DINNER IS PROVIDED FOR WEDNESDAY NIGHT
The nearest restaurant is the Salisbury Arms, on Dalkeith road opposite the Royal Commonwealth Pool. There are several other restaurants in Minto street,
in the Newington neighbourhood, ca. 10 min walk away from the conference
venue (see map).
Alternatively, the city centre is only ca. 30 min walk away from Pollock Halls. See the transport section for info about nearby bus stops.
3. Accommodation: For those who have booked it, bed and breakfast accommodation is provided in
Masson House, which is about a 5-minute walk across the campus from the John
McIntyre Conference Centre. Check-in on Wednesday 21st is from 2 pm. On Friday
23rd
you must have checked out by 10.30 am. Luggage can be stored in the reception
centre (see map).
4. Posters: All posters should be put up after registration on the 21
st, and must be taken down by
11.15 am on the 23rd
. Poster boards are available in the rooms Salisbury, Holyrood
and Duddingston in JMCC 1st floor. Please check the poster number you have been
assigned (page 9/10). There are two two minute pitch sessions for poster presenters please make sure you know which one you have been assigned to!
3
5. Conference dinner: The conference dinner, included in your registration fee, is in the Pentland room and
will start at 7.00 pm. Wine and soft drinks will be provided during the dinner. In
addition there will be a bar open on the JMCC ground floor until 11.00pm. IF FOR
ANY REASON YOU ARE UNABLE TO ATTEND THE DINNER, PLEASE
INFORM A MEMBER OF THE ORGANISING COMMITTEE AS SOON AS
POSSIBLE.
6. Internet access:
Free Wifi access is available in JMCC. Please use the keysurf network and follow the instructions on your web-browser to register on the network.
7. Transport:
For those staying at Masson House, car parking is limited and available on a first come first served basis, no spaces can be reserved. The nearest NCP car
park is about 10 min walk away, down St Leonards Street.
Edinburgh has an excellent bus service. The best place to catch buses into the city centre is from Dalkeith road (see map). Royal mile is a 25 minute walk
away.
Taxi A taxi rank is available at the reception centre.
If you have any queries, please dont hesitate to contact a member of the organising
committee.
Sponsors
CCP-BioSim is grateful for the support of the following organisations:
- The Center for Numerical Algorithms and Intelligent Software (NAIS) http://www.nais.org.uk/
- The Molecular Graphics and Modelling Society http://www.mgms.org/
- The Computational Chemistry list http://www.ccl.net/chemistry/
Organising committee
Philip Biggin, University of Oxford
Richard Henchman, University of Manchester
Charles Laughton, University of Nottingham
Julien Michel, University of Edinburgh
Martyn Winn, Daresbury Laboratory
4
Maps
John McIntyre Conference Centre, 1st floor.
5
John
McIntyre
Conference
Centre
Masson
House
6
Programme
Wednesday 21st May
11:00 Registration Open
13:00 Lunch (JMCC Centro)
Session 1 - Chair Julien Michel
14:00 Michael Gilson (UCSD)
Plumbing the Depths of Entropy and Enthalpy in Molecular Recognition
14:45 Christopher Baker (University of Cambridge)
Simulating Coupled Folding and Binding in Intrinsically Disordered Proteins
15:15 Coffee / Tea (JMCC Centro)
Session 2 - Chair Philip Biggin
15:45 Bert de Groot (MPI Gttingen)
Molecular dynamics of inhibition, permeation and recognition
16:30 Hideaki Fujitani (University of Tokyo)
Molecular dynamics simulations for pharmaceutical target proteins with refined AMBER force field
17:00 Poster pitches - Group A - Chair Martyn Winn
18:00 Posters and wine reception (JMCC Centro)
7
Thursday 22nd May
Session 3 - Chair Richard Henchman
09:00 Frauke Graeter (Heidelberg Institute for Theoretical Studies)
Protein allosteric regulation from force distribution analysis 09:45 Ferrucio Palazzesi (ETH Zurich)
The allosteric communication pathways in KIX domain
10:15 Poster pitches - Group B - Chair Martyn Winn
10:45 Coffee / Tea (JMCC Centro)
Session 4 - Chair Martyn Winn
11:15 Alexandre Bonvin (Utrecht University)
Modelling structure, affinity and specificity of biomolecular complexes 12:00 Michela Candotti (IRB Barcelona)
Urea-unfolded ubiquitin: from NMR to MD simulation 12:30 Antonija Kuzmanic (IRB Barcelona)
X-ray refinement significantly underestimates the level of microscopic heterogeneity in biomolecular crystals
13:00 Lunch and posters (JMCC Centro)
13:30 CCP-BioSim Lunchtime Bytes
James T. Gebbie (Daresbury) High-End Computing for Biomolecular Simulation
Hannes H. Loeffler (Daresbury) Automating Free Energy Simulations with FESetup
Session 5 - Chair Charles Laughton
14:30 Jochen Hub (Georg-August-University Gttingen)
Coupling atomistic simulations to wide-angle X-ray scattering data 15:00 Markus Lill (Purdue University)
Including Ligand Induced Protein Flexibility into Protein Tunnel Prediction
15:30 Coffee / Tea (ESLC Atrium)
Session 6 - Chair Adrian Mulholland
16:00 Michael Mazanetz (Evotec)
Maximising the impact of structure-based in silico design at Evotec - highlights and lessons learned 16:45 Odin Kvam (AstraZeneca)
Free energy perturbation for relative binding energy prediction: 2,4-bisanilinopyrimidine inhibitors of the tyrosine kinase EphB4
17:15 CCPBioSim annual meeting
19:00 Conference Dinner (Pentland)
8
Friday 23rd May
Session 7 - Chair Francesco Gervasio
09:00 Irina Tikhonova (Queens University Belfast) Tackling drug selective polypharmacology using molecular simulations
09:45 Jemma Trick (University of Oxford)
Designing Hydrophobic Gates into Biomimetic Nanopores
10:15 Marieke Schor (University of Edinburgh)
Exploring the role of multiple docked states in amyloid fibril formation of TTR
10:45 Coffee / Tea (JMCC Centro)
Session 8 Chair Christopher Woods
11:15 Edina Rosta (King's College London)
Catalytic Mechanism of Phosphate Cleavage Reactions
11:45 Mark Waller (WWU Mnster)
A Density Based Adaptive QM/MM Approach for Complex (Bio-)Chemical Systems
12:15 Gerhard Hummer (MPI Frankfurt)
Molecular simulation of protein dynamics and function
13:00 Lunch (JMCC restaurant, ground floor)
14:00 Departure
9
Posters - Group A
1. Philip Biggin - Regulatory ions bound at the iGluR ligand binding domain dimer interface a shared property of GluK2 and AvGluR1?
2. Michael Bodnarchuk - The Application of Constant-pH Molecular Dynamics to Polyamino Acids
3. Juan Bueren Calabuig - Impact of ligand binding on the N-terminal MDM2 lid dynamics explored by accelerated Molecular Dynamics and Umbrella Sampling simulations
4. Robin Corey - Molecular Dynamics simulations of the Sec protein translocon with its cytosolic partner SecA
5. Benjamin Cossins - Exploring IgE with molecular dynamics 6. Remi Cuchillo - Protein Druggability: the JEDI Approach 7. Erin Cutts - Evaluating crystallographic interaction interfaces through MD 8. Jacek Czub - Accumulation and transmission of energy during the rotary catalytic
cycle of F1-ATPase
9. Ioanna Danai Styliari - Simulating the coating procedure of indomethacin nanoparticles with mPEG-PCL diblock copolymers
10. Callum Dickson - Molecular dynamics simulation of lipid membranes with AMBER and application to the study of radioimaging compounds
11. Charis Georgiou - Rational design of isoform specific ligands 12. George Gerogiokas - Biomolecular hydration thermodynamics via grid cell theory
aids prediction of ligand-protein binding affinities
13. Alexander Goetz - Investigating dynamic motifs in amyloid precursor protein mutants as impact factor for Alzheimers disease
14. Jonathan Higham - Multicell theory to calculate hydration entropy 15. David Huggins - Improved Entropy Estimation Using The k-Nearest Neighbors
Algorithm
16. Mika Ito - A Rational Method for Quantum Chemical Prediction of Key Residues in Enzymatic Reactions: The Case of Proton Abstraction in Ketosteroid Isomerase
17. Pablo Jambrina - Computational Study of the phosphorylation of RAF dimers 18. Dominika Jankowska - Modelling of mechanisms of reactions catalyzed by quorum
quenching enzyme isolated from Ochrobactrum species
19. Nathjanan Jongkon - In-depth understanding into the reaction mechanism of Di-Methyl-Malate Lyase (DMML)
20. Outi Kamarainen - Dynamics of protein ligand interactions impact on drug discovery 21. Mateusz Kogut - Molecular basis of the stability of G-quadruplexes - molecular
dynamics simulation study
22. Tomas Kubar - Multi-scale simulation of biological electron transfer 23. Joanna Lee - Molecular Dynamic Simulations of the fucose transporter, FucP 24. Mickael Lelimousin - Highly enhanced conformational sampling of the
transmembrane domain of EGF receptor sheds light on the activation mechanism
25. Filip Leonarski - RedMDStream: A Tool to Design Coarse-Grained Molecular Dynamics Models and Force Fields for Proteins and RNA
26. Pete Leung - The NorM MATE transporter from N. Gonorrheae: insights into drug & ion binding from atomistic molecular dynamics simulations
27. Greg Lever - Benchmarking large-scale DFT calculations on the chorismate mutase enzyme
28. Valeria Losasso - Molecular dynamics study of Epidermal Growth Factor Receptor ectodomain
29. Silvia Lovera - Dynamic fingerprint of imatinib sensitive kinases 30. Robbert Mackenzie - Multiscale Modelling of Drug-Polymer Nanoparticle Assembly
10
Poster - Group B
31. Dmitry Osolodkin - Elucidation of intrinsic determinants of fusion initiation in flavivirus envelope proteins through molecular dynamics simulations
32. Shashank Pant - Effect of attractive interactions on the water-like anomalies of a core-softed model potential
33. Jamie Parkin - Probing the outer membrane of Pseudomonas aeruginosa using molecular dynamics simulations
34. Kevin Pinto Gill - Solvent Extension of MDmix methodology and its impact on the quality of the predictions
35. Giorgo Saladino - Accurate Prediction of the Thermodynamics and Kinetics of Drug Binding
36. Maysaa Saleh - Development of a New Series of Bis-Triazoles as Anti-Tumour Agents
37. Twana Salih - Investigating the reliability of the MM-GBSA method for predicting protein-ligand binding free energies
38. Firdaus Samsudin - Improving drug delivery: computational studies of proton dependent oligopeptide transporters
39. Lars Schaefer - Scrutinizing Hybrid AA/CG Force Fields through Free Energy Calculations
40. Christina Scharnagl - How dynamic transmembrane helices can influence peptide/lipid interactions: a molecular dynamics study
41. Pedro Sfriso - Breaking down protein conformational transitions with coarse-grained models
42. Adrita Shkurti - Towards faster-to-implement and extensible python-based tools for molecular simulation data analysis
43. ABSTRACT WITHDRAWN 44. Thana Sutthibutpong - Molecular dynamics study on the structural transition of dna
under superhelical stress
45. Siri van Keulen - Dynamics of retinal chromophore in rhodopsin: from cis/trans isomerisation to activation
46. Milosz Wieczor - A Molecular Dynamics study of mechanisms of sequence recognition and DNA binding in two telomeric proteins, TRF1 and TRF2
47. Nathalie Willems - Lipase enzyme interactions with lipid bilayers 48. Rilei Yu - Exploring the Interaction of Agonists with the human alpha1 Glycine
Receptor
11
TALKS
12
Plumbing the Depths of Entropy and Enthalpy in Molecular Recognition
Mike Gilson
UCSD Center for Drug Discovery Innovation, University of California San Diego, La Jolla, California, 92093-0736, USA
Molecular recognition is of fundamental importance in biology, and targeted molecules are
widely used as drugs and biochemical probes. However, the design of drugs and other
targeted molecules still involves a great deal of experimental trial and error. Our lab aims to
speed this process by developing a deeper understanding of molecular recognition and
building this understanding into new computational tools. I will discuss our progress in
computing and interpreting changes in entropy and enthalpy in noncovalent binding,
including the considerations of protein flexibility, motional correlations, and structured water.
13
Simulating Coupled Folding and Binding in Intrinsically Disordered Proteins
Christopher M. Baker
University of Cambridge, Department of Chemistry, Lensfield Road, Cambridge, CB2 1EW
Current Address: Syngenta, Jealotts Hill International Research Centre, Bracknell, Berkshire, RG42 6EY
Over the last twenty years, the traditional structure-function paradigm has undergone a fundamental
re-evaluation. While we have long been taught that proteins rely on their three dimensional
structure for their biological function, we now know that this is not necessarily the case.
Intrinsically disordered proteins (IDPs) are a class of protein that, in the native state, possess no
well-defined secondary or tertiary structure, existing instead as dynamic ensembles of
conformations. IDPs are also biologically important, with more than 20% of eukaryotic proteins
significantly disordered (1). The biological functions of IDPs are mediated by the process of
coupled folding and binding: while unstructured in solution, IDPs typically fold into well-defined
three-dimensional structures upon interaction with binding partners.
Despite its biological importance, the mechanism of coupled folding and binding is not well
understood, principally because it is very hard to study experimentally. At present, computer
simulation offers perhaps the best opportunity to understand this process, but is itself very
challenging, principally due to the size and complexity of the molecules involved (2). One way to
reduce this size and complexity is to use a multiscale approach, in which simplified, or coarse-
grained, computational models are combined with more detailed atomistic models. Here, I use this
approach to determine the mechanism of the sequence-specific binding of homodimers of the IDP
jun (a component of the AP-1 transcription factor) to DNA.
This work in turn raises another question: can we use results from molecular dynamics simulations
to design bioactive small molecules that control the coupled folding and binding of IDPs?
References
1. Pansca, R.; Tompa, P. PLoS One, 7, e34687, 2012
2. Baker, C. M.; Best, R. B. WIREs Comput. Mol. Sci., in press, 2014
14
Molecular dynamics of inhibition, permeation and
recognition.
Bert de Groot
Max Planck Institute for Biophysical Chemistry
Gttingen, Germany
Can we design specific membrane channel inhibitors? What is the antimicrobial mechanism of
the human antibiotic dermcidin? What are the molecular determinants of channel permeation and
gating? What is the molecular basis of protein-protein recognition, and can we alter protein
binding affinity by computational design? These are some of the questions that are addressed at
the atomic level by molecular dynamics simulations.
[1] Sren J. Wacker, Camilo Aponte-Santamaria, Per Kjellbom, Soren Nielsen, Bert L. de Groot,
Michael Rtzler. The identification of novel, high affinity AQP9 inhibitors in an intracellular
binding site. Molecular Membrane Biology 30:246-260 (2013).
[2] Ulrich Zachariae, Robert Schneider, Rodolfo Briones, Zrinka Gattin, Jean-Philippe Demers,
Karin Giller, Elke Maier, Markus Zweckstetter, Christian Griesinger, Stefan Becker, Roland
Benz, Bert L. de Groot, and Adam Lange. Beta-barrel mobility underlies closure of the voltage-
dependent anion channel. Structure. 20:1540-1549 (2012).
[3] Chen Song, Conrad Weichbrodt, Evgeniy S. Salnikov, Marek Dynowski, Bjrn O. Forsberg,
Burkhard Bechinger, Claudia Steinem, Bert L. de Groot, Ulrich Zachariae, and Kornelius
Zeth.Crystal structure and functional mechanism of a human antimicrobial membrane channel.
Proc. Nat. Acad. Sci. 110: 4586-4591 (2013).
[4] Carsten Kutzner, Helmut Grubmller, Bert L. de Groot, Ulrich Zachariae. Computational
Electrophysiology: The Molecular Dynamics of Ion Channel Permeation and Selectivity in
Atomistic Detail. Biophys. J. 101: 809-817 (2011).
[5] Jan-Henning Peters and Bert L. de Groot. Ubiquitin dynamics in complexes reveal molecular
recognition mechanisms beyond induced fit and conformational selection. PLoS Comp. Biol. 8:
e1002704 (2012).
15
Molecular dynamics simulations for pharmaceutical target proteins with refined
AMBER force field
Hideaki Fujitani
Research Center for Advanced Science and Technology, The University of Tokyo
Owing to the latest advance in the computational technology like microprocessors, high-speed
inter-processor connection, and parallelization algorithm, all-atom molecular dynamics (MD)
simulations of microsecond time scale are getting popular to study the solvated pharmaceutical
target proteins such as protease, kinase, and antigen and antibody systems. An antibody binds to its
antigen with structure changes at the binding interface including complementarity-determining
regions (CDRs). A ligand moves around the target protein and finds an entrance to gets into the
binding site. These phenomena can be observed in microsecond simulations, but an important issue
is whether the adopted force field is enough accurate to correctly describe these phenomena. We
developed FUJI force field using general AMBER (GAFF) atom types and AMBER94 van der
Waals parameters in order to describe arbitrary organic molecules in a unified manner including
proteins and nucleic acids. The point charges of AMBER94 are used for amino acids and nucleic
acids. The dihedral torsion parameters of protein backbone were determined to agree with the
torsion energy profiles calculated by high-level quantum mechanical (QM) theory DF-LCCSD(T0)
for the model systems of protein backbone. Conformational preferences of alanine dipeptides in
water were recently measured by vibrational spectroscopy. MD simulations with FUJI force field
gave distribution of Ramachandran angles / of alanine dipeptide, which agrees well with the experimental observation, while various force fields like AMBER, CHARMM, OPLS-AA and
semi-empirical QM methods cannot reproduce the experimental distribution of / angles of alanine dipeptide in water. As the torsion parameters play the most important role in the backbone
rigidity, all-atom MD simulations of microsecond time scale with FUJI force field might reveal new
flexible and complex behaviours of proteins, which could be not observed by other force fields.
The absolute binding free energies are so sensitive to the protein rigidity that other force fields
might give wrong values. We performed MD simulations to examine interfacial structures and
interaction characters of antigen and antibody systems such as an immunotherapeutic target protein
for hepatocellular carcinoma and a ligand to the epidermal growth factor receptor (EGFR), which
stimulates the proliferative signalling especially in colon cancer cells. We also performed
massively parallel computation for absolute binding free energy (MP-CAFEE) for pharmaceutical
target proteins and small molecules. These results were compared with experiments such as X-ray
crystal structures, binding constants, thermal enthalpy and entropy measured by isothermal titration
calorimetry (ITC) and surface plasmon resonance (SPR).
References
1. Fujitani, H. ; Matsuura, A. ; Sakai, S. ; Sato, S. ; Tanida, Y. J. Chem. Theory Comput. 5, 1155-
1165, 2009
2. Fujitani, H. ; Tanida, Y. ; Matsuura, A. Phys. Rev. E 79, 021914, 2009
3. Vymtal, J. ; Vondrek. J. Chem. Phys. Lett. 503, 301-304, 2011
4. Fujitani, H. ; Shinoda, K. ; Yamashita, T. ; Kodama, T. J. Phys.: Conference Series 454, 012018,
2013
16
Protein allosteric regulation from force distribution analysis
Frauke Graeter, Jing Zhou, Christian Seifert
Heidelberg Institute for Theoretical Studies, Schlosswolfsbrunnenweg 35, 69118 Heidelberg,
Germany
Tight regulation of proteins is critical for cellular life. Typical mechanisms to allosterically regulate
and thereby reversibly activate proteins are ligand binding or covalent modifications. An additional
mode of protein regulation is recently emerging, namely mechanical force. We have gained
intriguing insight into the dynamics and allosteric control of proteins using Force Distribution
Analysis (FDA). FDA is based on Molecular Dynamics simulations and reveals the propagation of
an external perturbation, being it a bound ligand or mechanical stretching, through the protein
scaffold, resulting in a connected allosteric network. Here, I will present two applications:
Hsp90 is a dimeric chaperone, which upon activation undergoes large conformational changes
triggered by nucleotide binding and release. Using FDA, we have determined the allosteric network
between the nucleotide binding site and the hinge region driving the conformation change [3].
Focal adhesion kinase is a pivotal signaling protein at focal adhesion sites, right on the spot of stress
transmission between the cell and its exterior. Our simulation results suggest a novel activation
mechanism triggered by both ligand binding and mechanical force, which leads to the detachment
of an inhibitory domain of the kinase, allowing subsequent phosphorylation events [2].
Being based on molecular forces instead of molecular coordinates, our results propose FDA to be a
promising method to elucidate the mechanism underlying protein allosteric regulation.
References
1. C. Seifert and F. Grter (2013). Biochim. Biophys. Acta - General Subjects, 1830(10):4762-8.
(review)
2. Zhou J.; Lietha D; Grter F, in preparation
2. Seifert C., Grter, Biophy. J., 103(10):2195-2202., (2012)
3. Palmai Z, Seifert C, Grter F, Balog E (2014) PLoS Comput Biol 10(1): e1003444 (2014)
17
The allosteric communication pathways in KIX domain
Palazzesi F.a, Barducci A.
b, Tollinger M.
c and Parrinello M.
a
a. Department of Chemistry and Applied Biosciences, ETH Zurich, and Facolt di Informatica,
Istituto di Scienze Computazionali, Universit della Svizzera Italiana Via G. Buffi 13, 6900
Lugano, Switzerland
b. Laboratory of Statistical Biophysics, Institute of Theoretical Physics, cole Polytechnique
Fdrale de Lausanne, Lausanne, Switzerland
c. Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University
of Innsbruck, Innrain 80/82, 6020 Innsbruck, Austria
Decades after the discovery of the allosteric phenomenas, the classical models built on static images
of proteins are being reconsidered with the knowledge that dynamics plays an important role in
their function1. Here we present an investigation on the origins of the allosteric dynamical changes
that are caused by the interaction between MLL protein and KIX domains.
In previous NMR studies2, the dynamic ensemble of the accessible states of this binary complex
(MLL:KIX) were studied using relaxation dispersion techniques. The dispersion profiles indicated
the presence of a conformational transition (on the milliseconds timescale) between two
configurations: a so called ground state which is highly populated, and an excited state which is scarcely populated. However, it was not possible to resolve the structure of this latter and,
moreover, this study did not provided any description of the allosteric mechanism.
Molecular dynamics (MD) is a natural choice for understanding the molecular origins of dynamics
allostery in this binary complex. This simulation technique allows also an accurately
characterization of the structural behaviors of the two conformational states. However, this time
demanding conformational transition is inaccessible for the typical MD simulation timescale. In
order to avoid this limitation, we have employed enhanced MD methodologies such as
Metadynamics. Indeed, to achieve the sampling of the conformations ensemble of the MLL:KIX
complex, Well-Tempered Ensemble3 combined with Parallel Tempering (WTE-PT) simulations
were performed. Using this advanced technique we have properly characterized the atomistic
configuration of the excited state for the KIX domain in the binary complex4. Other important
outcomes were obtained from the understanding of the structural nature of the communication
pathway and the energetics associated with them. Indeed we shed a light on the signal transmission
along the allosteric pathway and how the residues pass the information from one site to the other.
From these results we had also provide a new simulation protocol useful to give a better description
of many important biological process, such as allosteric phenomena.
References
1. Gunasekaran, K.; Ma, B.; Nussinov, R. Proteins 57, 433443, 2004 2. Bruschweiler, S.; Schanda, P.; Kloiber, K.; Brutscher, B.; Kontaxis, G.; Konrat, R.; Tollinger, M.
J. Am. Chem. Soc., 131, 3063-3068, 2009
3. Bonomi, M.; Parrinello, M. Phys. Rev. Lett. 104, 190601, 2010
4. Palazzesi, F.; Barducci, A.; Tollinger, M.; Parrinello, M. PNAS 110, 14237-14242, 2013
18
MODELLING STRUCTURE, AFFINITY AND SPECIFICITY OF
BIOMOLECULAR COMPLEXES.
Alexandre M.J.J. Bonvin
Utrecht University, Faculty of Science - Chemistry, Padualaan 8, 3584 CH Utrecht, the Netherlands
Biomolecular interactions underlie most cellular processes, including signal transduction and
apoptosis. Understanding how the cell works requires describing these at molecular level, which is
bound to have a dramatic impact on current and future structure-based drug design. Computational
methods may assist in this task, particularly when some experimental data can be obtained.
I will describe our information-driven docking approach HADDOCK (http://haddock.science.uu.nl),
illustrating it with various examples including results from the CAPRI blind docking experiment. I
will then discuss the problem of binding affinity prediction, showing that current scoring functions in
macromolecular docking fail at predicting the affinity of protein-protein complexes. For binding
affinity calculation, the surface buried upon complexation is not the absolute determinant and
inclusion of additional structural parameters, previously neglected is deemed mandatory for near-
accurate predictions. Related to affinity, understanding the structural determinant of specificity is
another challenging problem which I will illustrate showing how a conserved Asp to Glu mutation can
switch the specificity profile of ubiquitination enzymes. In conclusion, current biophysical models are
far more adequate in predicting accurate conformations of protein-protein complexes rather than
assessing the affinity and specificity of their interactions.
References
1. Karaca, E.; Bonvin, A.M.J.J. Methods 59, 372-381, 2013. 2. Kastritis, P.L.; Bonvin, A.M.J.J. Curr. Opin. Struct. Biol. 23, 868-877, 2013. 3. de Vries, S.J.L.; Melquiond, A.S.J.; de Vries, S.J.; Timmers, H.Th.M; Bonvin, A.M.J.J. PLoS
Comp. Biol., 8(11), e1002754, 2012.
19
Urea-unfolded ubiquitin: from NMR to MD simulation.
Candotti M, Esteban-Martin S, Salvatella X, Orozco M
Joint Research Program in Computational Biology, Institute for Research in Biomedicine and
Barcelona Supercomputing Center, C/ Baldiri Reixac 10, 08028, Barcelona, Spain,
The delicate equilibrium between the folded and functional structure of a protein and its unfolded state
is highly dependent on environmental variables such as the solvent. For example the co-solvent urea is
a well-known protein denaturant that displaces the equilibrium towards unstructured and non-
functional conformations of proteins. However the molecular mechanism behind its ability remains an
enigma and the interpretation of the experimental data is still ambiguous. In this work we present the
characterization of the structural, dynamics, and energetics of properties of the urea-denatured state of
ubiquitin, a small prototypical soluble protein. By combining molecular dynamics simulations with
nuclear magnetic resonance and small-angle X-ray scattering data, we were able to: (i) define the
unfolded state ensemble, (ii) understand the energetics stabilizing unfolded structures in urea, (iii)
describe the differential nature of the interactions of the fully unfolded proteins with urea and water,
and (iv) characterize the early stages of protein refolding when chemically denatured proteins are
transferred to native conditions. The results provide a new picture of the chemically unfolded state of
proteins and contribute to deciphering the mechanisms that stabilize the native state of proteins, as
well as those that maintain them unfolded in the presence of urea.
References
Candotti M, Esteban-Martin S, Salvatella X, Orozco M. Towards an atomistic description of the urea-denatured
state of proteins. Proc Natl Acad Sci U S A ; 110 (15) 59338, 2013
20
X-ray refinement significantly underestimates the level of microscopic
heterogeneity in biomolecular crystals
Antonija Kuzmanic,1 Navraj S. Pannu,
2 Bojan Zagrovic
3
1Structural and Computational Biology Department, IRB Barcelona, C/ Baldiri Reixac 10, 08028
Barcelona, Spain
2Biophysical Structural Chemistry, Leiden University, PO Box 9502, 2300 RA Leiden, The
Netherlands
3Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of
Vienna, Campus Vienna Biocenter 5, 1030 Vienna, Austria
Biomolecular X-ray structures typically provide a static, time- and ensemble-averaged view of
molecular ensembles in crystals. In the absence of rigid-body motions and lattice defects, B-factors are
thought to accurately reflect the structural heterogeneity of such ensembles. In order to study the
effects of averaging on B-factors, we employ molecular dynamics simulations to controllably
manipulate microscopic heterogeneity of a crystal containing 216 copies of villin headpiece. Using
average structure factors derived from simulation, we analyze how well this heterogeneity is captured
by high-resolution molecular-replacement-based model refinement. Remarkably, both isotropic and
anisotropic refined B-factors often significantly deviate from their actual values known from
simulation: even at high 1.0- resolution and Rfree of 5.9%, B-factors of some well-resolved atoms
underestimate their actual values even six-fold. Our results suggest that conformational averaging and
inadequate treatment of correlated motion considerably influence estimation of microscopic
heterogeneity via B-factors, and invite caution in their interpretation.
21
Coupling atomistic simulations to wide-angle X-ray scattering data
Jochen S. Hub, Po-chia Chen
Georg-August-University Goettingen, Institute for Microbiology and Genetics,
Justus-von-Liebig-Weg 11, 37077 Gttingen, Germany
Wide-angle X-ray scattering (WAXS) of biomolecules is a promising experimental technique that in
principle provides structural information on biomolecules in solution down to a resolution of a few
Angstrm, even in a time-resolved fashion. However, the structural interpretation of the measured
signals has remained problematic for two reasons, which are currently limiting a wider application of
WAXS. First, accurate calculations of WAXS spectra from structural models have remained
challenging. Second, because the information content of WAXS spectra is very low, a narrow prior distribution is required to avoid drastic overfitting when deriving a structural interpretation. Here, we
present solutions to overcome those two problems.
We present the methodology to compute WAXS spectra from atomistic molecular dynamics
(MD) simulations. We validated our calculations against experimental SAXS/WAXS spectra from five
different proteins, and we found excellent agreement. Our calculations require only a single fitting
parameter that accounts for experimental uncertainties due to the buffer subtraction and/or due to
detector dark currents. We further applied this new method to systematically analyse the role of the
solvation shell and of protein dynamics on WAXS spectra, and demonstrated the importance of
accurately modelling both the solvent and the atomic fluctuations in solution X-ray scattering.
In order to interpret alterations of WAXS signals due to conformational transition of
biomolecules, we have developed the methodology to couple MD simulations to experimental
SAXS/WAXS signals. In our simulations, an additional WAXS-derived potential drives the
simulations into conformations that agree with the experimental data. The MD force field ensures
physically correct conformations, thus generating the required narrow prior distribution and avoiding
overfitting. We demonstrate the new method using three different proteins: a periplasmic binding
protein, ATCase, and seminal RNase. A novel solution state of ATCase is predicted.
References
1. Hub, J.S.; Chen, P.C, Validating solution ensembles from molecular dynamics simulation by
wide-angle X-ray scattering data, submitted
2. Chen, P.C; Hub, J.S, Coupling molecular simulations to X-ray solution scattering data, in
preparation
22
Figure 1. IterTunnel method
Including Ligand Induced Protein Flexibility into Protein Tunnel Prediction Markus A. Lill, Laura J. Kingsley
Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, 575 Stadium
Mall Drive, West Lafayette, IN 47906, USA
Understanding how ligands migrate through tunnels that connect the exterior of the protein to the active
site can shed light on substrate specificity and enzyme function. We have developed a novel tunnel
prediction and evaluation method named IterTunnel1, which includes the influence of ligand-induced
protein flexibility, guarantees ligand egress, and provides detailed free energy information as the ligand
proceeds along the egress route. IterTunnel combines geometric tunnel prediction with steered MD in an
iterative process to identify tunnels that open as a result of ligand migration and calculates the potential of
mean force (PMF) of ligand egress through a given tunnel.
Our method uses the geometric tunnel prediction program,
MolAxis2, to initially identify tunnels leading out of the binding
site (Fig. 1A). Using these tunnels as a guide the ligand is then
pulled from the binding site along each initial tunnel using steered
MD (Fig. 1B). After a pre-defined time, the steered MD simulation
is stopped and tunnels are recalculated from the new position of
the ligand within the tunnel (Fig. 1C). This allows for the
identification of any new tunnels that may open or close as a result
of ligand migration. Steered MD is then resumed along the three
highest-ranked tunnels as well as the original tunnel (Fig. 1D).
This process is repeated until the ligand exits the protein at which
point the simulation is terminated. Using the steered MD
trajectories, umbrella sampling is then used to calculate the PMF
(Fig. 1E) of ligand transit.Applying this new method to
cytochrome P450 2B6 (CYP2B6), we demonstrate the influence of
protein flexibility on the shape and accessibility of tunnels. More
importantly, we demonstrate that the ligand itself, while traversing
through a tunnel, induces conformational changes of the protein
and thus can reshape tunnels due to its interaction with the protein.
This process results in the exposure of new enegetically favorable
tunnels and the closure of pre-existing tunnels as the ligand
migrates from the active site.
References
1. Kingsley, L. J.; Lill, M. A. J. Comput. Chem., submitted 2014.
2. Yaffe, E.; Fishelovitch, D.; Wolfson, H. J.; Halperin, D.;
Nussinov, R. Proteins 2008, 73, 72-86.
23
Maximising the impact of structure-based in silico design at Evotec - highlights
and lessons learned.
Michael P Mazanetz
Evotec (UK) limited, 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire, OX14 4RZ, UK
The suite of computational tools available to assist molecular modelling is vast both in terms of
computational complexity and the scope of the method. A strategy to employ the most appropriate
method to have the greatest positive impact on a drug discovery campaign within tight design-make-
analyse cycles is therefore a required skill. This talk will focus on recent structure-based approaches
developed at Evotec to guide ligand design and protocols developed to enable greater access to tools.
Specific examples will demonstrate how timely access to methods can drive ligand design and
enhance the medicinal chemists understanding of the structure-activity relationships, and the importance of method development and the transfer of knowledge.
24
Free energy perturbation for relative binding energy prediction: 2,4-bis-
anilinopyrimidine inhibitors of the tyrosine kinase EphB4
Odin Kvam1, Derek Ogg
1, Martin J. Packer
1, Daniel Robinson
2
1AstraZeneca, Mereside, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK
2Schrdinger, Quatro House, Frimley Road, Camberley GU16 7ER, UK
Direct prediction of relative binding affinity is emerging as a powerful tool for computer-aided drug
design, but currently suffers from a lack of validation. Using FEP (free energy perturbation) theory,
relative binding free energies for a set of 36 homologous 2,4-bis-anilinopyrimidine EphB4-binding
ligands[1,2]
were predicted, and canonical ensembles of bound ligand conformations generated,
allowing quantitative and qualitative assessment of FEP performance. A consensus protein system was
constructed from four X-ray crystal structures of EphB4 bound to ligands in the 2,4-bis-
anilinopyrimidine series, and used for all simulations. The full ligand series was aligned assuming
analogous binding modes, and a sparse simple graph of mutations generated based on ligand
similarity. FEP simulations were carried out using Desmond with the REST enhanced conformational
sampling algorithm[3]
. Relative binding energies correlated well with experimental values (RMSE =
0.8, pIC50 4.4 to 7.4), and simulated conformational ensembles indicated a characteristic dual
occupancy binding mode for a subset of ligands, supported by experimental X-ray electron density
maps. By delivering high-accuracy affinity and binding mode predictions for drug design FEP enables
efficient exploration of chemical space, as well as allowing rapid mapping of often synthetically
challenging ligand series such as heterocycle permutations.
References
1. Bardelle, C. ; Cross, D., Davenport, S. ; Kettle, J. G. ; Ko, E. J. ; Leach, A.G. ; Mortlock, A. ; Read,
J. ; Roberts, N. J. ; Robins, P. ; Williams, E. J. Bioorg. Med. Chem. Lett., 18, 2776-2780, 2008
2. Bardelle, C. ; Coleman, T. ; Cross, D. ; Davenport, S. ; Kettle, J. G. ; Ko, E. J. ; Leach, A.G. ;
Mortlock, A. ; Read, J. ; Roberts, N. J. ; Robins, P. ; Williams, E. J. Bioorg. Med. Chem. Lett., 18,
5717-5721, 2008
3. Wang, L. ; Deng, Y. ; Knight, J. ; Wu, Y. ; Kim, B. ; Sherman, W. ; Shelley, J. C. ; Lin, T. ; Abel,
R. J. Chem. Theory Comput., 9, 1282-1293, 2013
25
Tackling Drug Selective Polypharmacology Using Molecular Simulations
Irina Tikhonova, Balaji Selvam, Simon L. Porter
School of Pharmacy, Queen's University Belfast, Northen Ireland
Selective polypharmacology, where a drug acts on multiple rather than single molecular targets
involved in a disease, emerges to develop a structure-based system biology approach to design drugs
selectively targeting a disease-active protein network. We focus on the bioaminergic receptors that
belong to the group of integral membrane signalling proteins coupled to the G protein and represent
targets for therapeutic agents against schizophrenia and depression. Among them, it has been shown
that the serotonin (5-HT2A and 5-HT6), dopamine (D2 and D3) receptors induce a cognition-enhancing
effect (group 1), while the histamine (H1) and serotonin (5-HT2C) receptors lead to metabolic side
effects and the 5-HT2B serotonin receptor causes pulmonary hypertension (group 2). Thus, the problem
arises to develop an approach that allows identifying drugs targeting only the disease-active receptors,
i.e. group 1. The recent release of several crystal structures of the bioaminergic receptors, involving
the D3 and H1 receptors provides the possibility to model the structures of all receptors and initiate a
study of the structural and dynamic context of selective polypharmacology. In this work, we use
molecular dynamics simulations to generate a conformational space of the receptors and subsequently
characterize its binding properties applying molecular probe mapping. All-against-all comparison of
the generated probe maps of the selected diverse conformations of all receptors with the Tanimoto
similarity coefficient (Tc) enable to separate the receptors of group 1 from group 2. The
pharmacophore built based on the Tc-selected receptor conformations, using the multiple probe maps
discovers structural features that can be used to design molecules selective towards the receptors of
group 1. The importance of several predicted residues to ligand selectivity is supported by the
available mutagenesis and ligand structure-activity relationships studies. In addition, the Tc-selected
conformations of the receptors for group 1 show good performance in isolation of known ligands from
a random decoy. Our computational structure-based protocol to tackle selective polypharmacology of
antipsychotic drugs could be applied for other diseases involving multiple drug targets, such as
oncologic and infectious disorders.
26
Designing Hydrophobic Gates into Biomimetic Nanopores
Jemma L. Trick1 , E. Jayne Wallace2, Hagan Bayley3 and Mark S. P. Sansom1
1 SBCB Unit, Department of Biochemistry, University of Oxford, Oxford. OX1 3QU
2 Oxford Nanopore Technologies, Edmund Cartwright House, 4 Robert Robinson Avenue,
Oxford Science Park. OX4 4GA 3 Chemistry Research Laboratory, University of Oxford, 12 Mansfield Road, Oxford. OX1
3YA
The use of nanopores is fast being a major scientific tool in molecular analysis and detection
due to their ability to detect polynucleotides, proteins and small molecules. Biomimetic
modelling of pores allows for a specific function to be incorporated into the molecular
structure of the nanopore, based on amino acid motifs found in existing protein structures.
An initial beta barrel model was built computationally, based on the transmembrane domain
of 14-stranded beta-barrel pore, alpha-hemolysin. Hydrophobic and hydrophilic residues
were built in a specific arrangement within the structure to replicate an hourglass shape cavity
with a central constriction. From this, pore conductions were observed via Molecular
Dynamics (MD) and selected models were transformed into hybrid pores in which the
location of hydrophobic residues differed to give constricting regions surrounded by
hydrophilic residues. From All Atom MD simulations, a hydrophobic gating mechanism has
been established within these toy models with intermittent water currents through the pore
giving an insight into possible biomimetic motifs which could be biochemically integrated
into the wild type protein.
27
Exploring the role of multiple docked states in amyloid fibril formation of
TTR105-115
Marieke Schor1, Antonia S.J.M. Mey
2 and Cait E. MacPhee
1
1 School of Physics and Astronomy, University of Edinburgh, West Mains Road, Edinburgh
EH9 3JJ, UK
2 Department of Mathematics, Freie Universitt Berlin, Arnimallee 6 D-14195 Berlin,
Germany
Amyloid fibrils are long, highly ordered, insoluble protein assemblies. They are most
commonly associated with diseases like Alzheimer's and diabetes type II. However, more
recently functional amyloid-like fibrils have been discovered and material scientists have
started exploring their potential use as biocompatible nanomaterials [1].
Fibril formation is generally thought of as a nucleation and growth process but the steps
involved are not well understood at the molecular level. Once a stable nucleus (or seed) has
formed, fibrils are thought to grow through the incorporation of peptide monomers one at a
time at the growing end(s). Monomer addition is essentially a two step process that is referred
to as the dock-lock mechanism [2,3]. In the first docking step, the peptide forms an initial
contact with the fibril. In the subsequent, much slower, locking step the peptide changes
conformation to fit the fibril template. In principle, multiple docked states could lead to a
correctly fibril-incorporated peptide. On the other hand, one could imagine incorrect docking
leading to off-pathway metastable states, which would slow down the dock-lock transition
significantly.
Here, we present a Markov State Model (MSM) constructed from extensive all-atom MD
simulations aimed at assessing the role of multiple docked states in monomer addition to
TTR105-115
fibrils. Our MSM indicates that there are indeed multiple docked conformations
which can transition to the locked state via distinct pathways. We also find various
offpathway metastable states. Some of the slowest transitions in the system are between these
metastable states and the fibril-compatible docked states.
References
[1] I. Cherny and E. Gazit, Angew. Chem. Int. Ed., 2008, 47, 4062.
[2] W.P. Esler, E.R.Stimson, J.M. Jennings, H.V. Vinters, J.R. Ghilardi, J.P.Lee, P.W.
Mantyh and J.E. Maggio, Biochemistry, 2000, 39, 6288.
[3] P.H. Nguyen, M.S. Li, G. Stock, J.E. Straub and D. Thirumalai, Proc. Natl. Acad. Sci.
USA, 2007, 104, 111.
28
Catalytic Mechanism of Phosphate Cleavage Reactions
Edina Rosta
Department of Chemistry, Kings College London, London, SE1 1DB
The formation and cleavage of phosphate bonds is essential in most biological processes
including nucleic acid processing. Many enzymes that catalyze phosphate hydrolysis require
bound divalent metal ions. Most commonly, Mg2+
ions are required for catalysis, while
similar Ca2+
ion abolishes the catalytic activity. To elucidate the poorly understood
mechanism of these ubiquitous metal ion catalyzed reactions, we carry out hybrid quantum-
classical QM/MM free energy simulations. In our calculations, we focus on several systems,
including Ribonuclease H (RNase H) [1], dUTPase [2], and RAF kinases. RNase H is a
prototypical member of a large family of enzymes that use two-metal ion catalysis to process
nucleic acids. The active site of RNase H is almost identical across species with respect to
sequence and structure, including the human enzyme and the HIV Reverse Transcriptase
(HIV-RT) RNase H domain. HIV-RT is essential to viral replication, which makes it an
important target in HIV drug research. In our simulations, we combine [1] Hamiltonian
replica exchange with a finite-temperature string method to calculate the QM/MM free
energy surface underlying the catalytic reaction. We use a histogram-free reweighting method
to obtain this surface from combined multidimensional string simulations. Our method allows
us to search for the optimal pathway in multiple dimensions and, therefore, to identify the
detailed sequence of steps in the phosphate cleavage reactions. From our calculations,
coupled proton transfer reactions emerge as central factors in the catalytic phosphate cleavage
reactions.
References
1. E. Rosta, M. Nowotny, W. Yang and G. Hummer, J. Am. Chem. Soc., 133:8934, 2011
2. Barabs O, et al., Nucleic Acids Research DOI: 10.1093/nar/gkt756, 2013
29
A Density Based Adaptive QM/MM Approach for Complex (Bio-) Chemical Systems
Mark P. Waller, Sadhana Kumbhar, Jack Yang Organic Chemistry Institute, WWU Mnster, Corrensstr. 40 Mnster, Germany
QM/MM modeling has become one of the methods of choice for modeling biomacromolecular systems. This is evidenced by the awarding on the 2013 Nobel Prize in Chemistry "for the development of multiscale models for complex chemical systems"1 However, one of the limitations of QM/MM modeling is the traditional rigid partitioning of a given system into a QM and MM region. For instance, this becomes problematic during QM/MM-MD simulations, as the initial partitioning on the system eventually becomes invalid. There has been much work spanning more than almost two decades on an adaptive variant, i.e. where the partitioning occurs during the simulation. The whole-body of work can be roughly classified into two main families based on the partitioning criteria employed. Firstly, there are distance-based2 approaches, see Figure 1a, which are empirical in nature because the cut-offs must be fitted. Secondly, a number based approach3, see Figure 1b, which can circumvent this crude distance based metric, by enabling a pre-determined integer number of molecules to surround the QM core region that can be, set to experimentally known hydration numbers if, and only if, such values are available. Our approach presented here is to develop a method whereby no fitted parameters are needed to partition the system; instead the system is analyzed and partitioned based on physical arguments. This neatly circumvents the aforementioned empiricism, and makes the adaptive-QM/MM method more generally applicable. Our new adaptive-QM/MM method is based on employing an auxiliary atom-centered spherical density, which is analyzed to detect non-covalent interactions between the QM-core and the rest of the system. If non-covalent interactions are detected between a fragment and any QM-core atom, then the fragment is placed into the QM region. Based on this definition, all non-interacting fragments are placed into the MM region, see Figure 1c
a. Distance based partitioning b. Number based partitioning c. Density based partitioning.*
Figure 1: A schematic partitioning of a small water cluster: QM(vdW radii)/Transition(ball and
Stick)/MM(thin wire). *The green iso-surfaces indicate the presence of non-covalent interactions.
References
1. http://www.nobelprize.org/nobel_prizes/chemistry/laureates/2013/press.html
2. Kerdcharoen, T.; Liedl, K. R.; Rode, B. M. Chem. Phys., 211, 313323, 1996. 3. Takenaka, N.; Kitamura, Y.; Koyano, Y.; Nagaoka, M. Chem. Phys. Lett., 524, 5661, 2012.
30
Molecular simulation of protein dynamics and function
Gerhard Hummer1, Edina Rosta
2, Ville R. I. Kaila
3, Kei-ichi Okazaki
1
1Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt,
Germany (Email: [email protected])
2Department of Chemistry, Kings College London, London SE1 1DB, United Kingdom
3Department Chemie, echnische Universit t nchen, arching, ermany
Modern simulation methods make it possible to study the molecular function of proteins in
unprecedented detail. We have been using string simulations to elucidate the molecular
mechanisms and chemical reaction principles underlying the enzymatic catalysis of complex
multistep reactions, with the processing of nucleic acids using two-metal ion catalysis [1,2] as
a paradigmatic example. A combination of quantum chemical calculations and molecular
simulations also helped clarify the early time evolution of the molecular structure of the light-
activated signaling protein PYP, in combination with picosecond time-resolved X-ray
crystallography [3,4]. On larger scales of space and time, simulations help us explore the
motions and function of the molecular machines involved in biological energy transduction,
including the F1 rotary motor ATP synthase [5] and the proton pump Complex I [6].
Remarkably, common physical principles emerge in the function of these proteins, despite
large variations in their structure and function, including water and hydration effects,
extended protein motions, and long-range electrostatic couplings.
1. E. Rosta, M. Nowotny, W. Yang, G. Hummer, J. Am. Chem. Soc. 133, 8934 (2011).
2. E. Rosta, W. Yang, G. Hummer, J. Am. Chem. Soc. 136, 3137 (2014).
3. F. Schotte, H.-S. Cho, V. R. I. Kaila, H. Kamikubo, N. Dashdorj, E. Henry, T. Graber, R.
Henning, M. Wulff, G. Hummer, M. Kataoka, P. A. Anfinrud, Proc. Natl. Acad. Sci. USA
109, 19256 (2012).
4. V. R. I. Kaila, F. Schotte, H.-S. Cho, G. Hummer, P. A. Anfinrud, Nature Chemistry 6, 258
(2014).
5. K.-I. Okazaki, G. Hummer, Proc. Natl. Acad. Sci. USA 110, 16468 (2013).
6. V. R. I. Kaila, M. Wikstrm, G. Hummer, submitted.
31
LUNCHTIME
BYTES
32
High-End Computing for Biomolecular Simulation
James T. Gebbie, Hannes Loeffler, Martyn Winn.
Scientific Computing Deparment, STFC Daresbury Laboratory, Keckwick Ln, Warrington, WA4 4FS.
Simulations have proved important in aiding the development of scientific understanding in a
wide array of areas. Biomolecular simulation is a vibrant and internationally important field
that is making highly significant contributions to biology. The need for biolmolecular
simulations in order to understand biological problems is growing substantially, with this
need the computational resource demand is also growing. This is in part due to the fact that
scientists are becoming increasingly ambitious in which systems are being studied via
simulation.
The High-End Computing Consortium for Biomolecular Simulation (HECBioSim) was
formed by CCPBioSim as a result of the ongoing and increasing demand for access to
national scale facilities. The HECBioSim consortium aims to provide simplified access to
time on the Archer national facility. Working closely with CCPBioSim the consortium aims
to significantly increase participation in HEC level simulation from the wider community
including amongst those members of the community that are not of the traditional user base.
In order to accomplish this, the consortium will deliver a number of software packages aimed
at simplifying access and the use of these resources specific to biosimulation. A new website
has been constructed www.hecbiosim.ac.uk that will provide community contributed material
and knowledge sharing through the use of forums, wiki's and software repositories. The main
goal is to increase participation and knowledge sharing throughout the biosimulation
community to make HEC more accessible. A selection of these community oriented tools will
be presented during a lunchtime byte during the poster session on the second day of the conference.
33
Automating Free Energy Simulations with FESetup
Hannes H Loeffler1, Julien Michel
2, Christopher Woods3
1 Scientific Computing Department, STFC Daresbury, Keckwick Lane, Warrington WA4 4AD
2 School of Chemistry, University of Edinburgh, West Mains Road, Edinburgh EH9 3JJ
3 School of Chemistry, University of Bristol, Cantocks Close, Bristol BS8 1 S
The setup for Molecular Dynamics (MD) or Monte Carlo (MC) simulations can be very
tedious to do because large numbers of small organic ligand molecules may need to be
parameterised. In the case of mutational free energy approaches appropriate mappings
between many morph pairs may have to be drawn up. FESetup assists in automating these
steps as much as possible through simple control via a INI style input file. The aim of the
software is to minimise the human bottleneck by helping the researcher to focus more on
scientific problems and much less on software control.
FESetup[1] is a an automatic setup tool currently targeted mainly at proteinligand free energy simulations like thermodynamic integration (TI) and MMPBSA. The program currently supports simulations with Sire[2] and AMBER. Supported force fields are all
modern AMBER type force fields including GAFF for the ligand. The ligand charge model
is currently AM1/BCC.
Future goals are the support of other popular biomolecular simulation packages (Gromacs
support currently worked on), support for other free energy methods, additional force fields
and parameterisation schemes. User friendliness of the interface, robustness of the code and
generally facilitating the access to simplified simulation setup are central to our software
development efforts.
A complete, readytorun package of the FESetup code is available via [1]. FESetup is developed as part of the software support project effort within the Collaborative
Computational Project for Biomolecular Simulation (CCPBioSim) [1].
FESetup will be presented in a Lunchtime Byte during the poster session on the second day of the conference.
References
1. http://www.ccpbiosim.ac.uk/flagship
2. http://www.siremol.org
34
POSTERS
35
Regulatory ions bound at the iGluR ligand binding domain dimer interface a shared property
of GluK2 and AvGluR1?
Maria Musgaard, Jack Barber, M. Khadeesh bin Imtiaz and Philip C. Biggin
Structural Bioinformatics and Computational Biochemistry, Department of Biochemistry,
University of Oxford, South Parks Road, Oxford, OX1 3QU, United Kingdom
Email: [email protected]
Ligand-gated ion channels activated by glutamate binding, ionotropic glutamate receptor (iGluRs),
play crucial roles in our central nervous system (CNS), e.g. in learning and memory. Furthermore,
iGluRs are implicated in many CNS disorders. Binding of glutamate to the iGluR ligand-binding
domain (LBD) triggers opening of the transmembrane cation channel. In the overall tetrameric
structure, the LBDs are organized in a dimer of dimers. As opposed to other vertebrate iGluRs,
kainate-selective iGluRs (KARs) require binding of extracellular sodium and chloride ions to the
LBD dimer interface in addition to agonist binding for activation. We have recently shown that the
regulatory cations for the GluK2 KAR determine the onset of desensitization, with desensitization
not occurring until the cation site is vacated [1]. IGluRs are also found in other kingdoms of life,
structurally exemplified by AvGluR1 from a primitive eukaryote. Surprisingly, this LBD dimer
structure shows four chloride ions bound at the dimer interface. With atomistic molecular dynamics
and steered molecular dynamics simulations, we have studied the binding of these chloride ions to
elucidate whether they appear to have a regulatory effect on AvGluR1, and whether such a
regulatory mechanism could be a shared property between KARs and AvGluR1. Furthermore, we
have studied the structural changes believed to be linked to desensitization in the presence and
absence of interface-bound ions for both structures. The LBD dimer interface is thought to open up
around the ion binding sites in conjunction with desensitization. Interestingly, this interface is
packed closer in the AvGluR1 structure than observed for LBD dimer structures of vertebrate
iGluRs. Our results illustrate how this feature influences the dynamical changes of desensitization.
1. Defining the structural relationship between kainate-receptor deactivation and desensitization.
Dawe GB, Musgaard M, Andrews ED, Daniels BA, Aurousseau MR, Biggin PC, Bowie D.
Nat Struct Mol Biol. 2013 9:1054-61.
2. Anions mediate ligand binding in Adineta vaga glutamate receptor ion channels.
Lomash S1, Chittori S, Brown P, Mayer ML. Structure. 2013 21:414-25.
36
The Application of Constant-pH Molecular Dynamics to Polyamino Acids
Michael Bodnarchuk, David Heyes and Daniele Dini
Department of Mechanical Engineering, Imperial College London, Exhibition Road, London, SW7,
UK.
The assignment of fixed protonation states to protein residues in Molecular Dynamics (MD)
simulations can lead to erroneous results when the pKa of a critical residue is close to biological pH,
as the charged state of residues may be a function of conformational state and therefore time.
Constant-pH Molecular Dynamics (CpHMD) reduces this problem by allowing the protonation
state of protein residues to change with time during the simulation.1,2
CpHMD also facilitates
improved sampling in regions where the protonation state is difficult to assign, and leads to the time
average pKa from the probability the residue is protonated as a function of pH.3 Literature results
obtained using CpHMD have primarily focussed on calculating the pKa of single amino acid side
chains in proteins with various degrees of success.4,5
The extension of this method to consider
multiple identical titratable residues in the same molecule (here a polyamino acid) is described and
preliminary results presented. CpHMD calculates residue-specific pKa values along the chain, the
average of which is in very good agreement with experimental pKa values. Analysis of the
individual pKa values for each residue along the chain gives insight into the mechanism by which
polyamino acids can change their conformation, highlighting the potential for such a method to be
incorporated into protein folding models.
References
1. J. Mongan, D. A. Case and J. A. McCammon, J. Comput. Chem. 2004, 25, 2038-2048
2. R. Burgi, P. A. Kollman and W. F. van Gunsteren, Proteins: Struct. Funct. Gen. 2002, 47, 469480
3. S. Donnini, F. Tegeler, G. Groenhof and H. Grubmller, J. Chem. Theory Comput. 2011, 7(6), 19621978
4. S. L. Williams, C. A. F. de Oliveira and J. M. McCammon, J. Chem. Theory Comput. 2010, 6, 560-568
5. S. L. Williams, P. G. Blachly and J. A. McCammon, Proteins: Struct. Funct. Bioinf. 2011, 79(12), 33813388
37
Impact of ligand binding on the N-terminal MDM2 lid dynamics explored by
accelerated Molecular Dynamics and Umbrella Sampling simulations
Juan A. Bueren-Calabuig and Julien Michel
EaStCHEM School of Chemistry, Joseph Black Building, he Kings Buildings University of Edinburgh, Edinburgh, EH9 3JJ, UK
The oncoprotein MDM2 is a negative regulator of the tumor suppressor protein p53. The
disruption of the p53-MDM2 complex induced by ligand binding constitutes a very promising
strategy in cancer research.1 The N-terminal domain of MDM2 is partially folded (residues 25-119),
whereas the first 24 amino acids form a disordered lid region in the apo state that competes for the p53 binding site via a pseudo-substrate mechanism.
2 Several structural, biochemical and
theoretical experiments have shown that the lid can adopt two possible conformations: one open conformation in which p53 is able to bind MDM2, and one closed that occludes the p53 binding site. In addition, the lid can also undergo a disorder-to-order transition upon binding of small
molecules to MDM2.3 However, the exchange between the different lid conformations take place
on a very slow time scale (>10-ms)4 which is often outside the reach of canonical MD simulations.
To achieve sufficient sampling of lid conformations with reasonable computing resources, we have
combined two different enhanced sampling techniques: accelerated molecular dynamics (aMD) and
umbrella sampling (US). With the combined aMD/US protocol we have completed extensive
simulations of MDM2 with a complete lid (residues 1-119) in the absence and presence of several
ligands of pharmaceutical relevance. Our studies provide new insights into the interplay between
MDM2 lid dynamics and ligand interactions, and may contribute to the design of new and more
effective p53-MDM2 inhibitors.
MDM2 structures showing the N-terminal lid domain (green) conformations in the open state (left, apo-MDM2) and
in the closed state (right, in the presence of Nutlin 3a)
References
1. Zhang, Z., Li, M., Wang, H., Agrawal, S. & Zhang, R. Proc. Natl. Acad. Sci. U.S.A. 100, 1163611641, 2011
2. McCoy, M. A., Gesell, J. J., Senior, M. M. & Wyss, D. F. Proc. Natl. Acad. Sci. U.S.A. 100, 16451648,2003
3. Michelsen, K. Jordan J.B., Lewis J. et al. J. Am. Chem. Soc. 134, 1705917067, 2012
4. Showalter, S. A., Bruschweiler-Li, L., Johnson, E., et al. R. J. Am. Chem. Soc 130, 64726478, 2008
38
Molecular Dynamics simulations of the Sec protein translocon with its cytosolic partner SecA
Robin Corey, William Allen, Ian Collinson, Richard Sessions
School of Biochemistry, University of Bristol, Bristol, UK
The ubiquitous and highly conserved Sec translocon acts as a site of protein translocation across or into a variety of cellular membranes, from the bacterial inner membrane to the eukaryotic endoplasmic reticular membrane. Atomistic structures of the Sec translocon with and without the cytoplasmic ATPase SecA suggest a possible mechanism of activation, however the full mechanism of activation and translocation remains unknown.
Using the SecYEG-SecA crystal structure embedded in a POPC bilayer as a starting structure(1), a series of 100 ns all-atom molecular dynamics simulations were run to investigate the effects of ATP hydrolysis on the system, as well as the effect of applying both a well-characterized super-active mutant of SecYEG and a mutant previously created and tested in our group, designed to mimic a substrate activated conformation of the SecYEG channel (2). The output provided both biologically plausible and interesting results. The data has subsequently been supported using biochemical techniques.
Now that these relatively simple simulations have been run and confirmed experimentally, we are extending their complexity and breadth to investigate different features of protein translocation. Using both the crystal structure and structures based on recent EM data (2,3) as input models, simulations will be run with short peptide fragments in SecYEG or with a full peptide substrate manually threaded through the complex(4). Different conditions will be applied including a bidirectional force on the substrate and the membrane proton motive force, allowing us to test recent experimental results and confirm/amend our working model of SecA and SecYEG mediated translocation
References
1. Zimmer J, Nam Y, Rapoport TA. Structure of a complex of the ATPase SecA and the protein-
translocation channel. Nature. 2008 Oct 16;455(7215):93643.
2. Hizlan D, Robson A, Whitehouse S, Gold VA, Vonck J, Mills D, et al. Structure of the SecY
complex unlocked by a preprotein mimic. Cell Rep. 2012 Jan 26;1(1):218.
3. Park E, Mntret J-F, Gumbart JC, Ludtke SJ, Li W, Whynot A, et al. Structure of the SecY
channel during initiation of protein translocation. Nature. 2013 Oct 23.
4. Zimmer J, Rapoport TA. Conformational Flexibility and Peptide Interaction of the
Translocation ATPase SecA. J Mol Biol. 2009 Dec;394(4):60612.
39
Exploring IgE with molecular dynamics
Benjamin P. Cossins
CADD, UCB Celltech
216 Bath Road
Slough
SL1 3WE
Crystallographic and solution studies have shown that IgE molecules are acutely bent in their Fc
region. Antibody capture and crystallography now shows us that IgE-Fc is able to access less-bent
and extended conformations when interacting with Fab molecules1. We have used large
metadynamics simulations of IgE-Fc without binding Fab molecules to explore the conformational
transition from bent to extended, the possibly large conformational space of extented IgE-Fc and the
possibility of a flip between symmetrical bent conformations1. These simulations suggest that the
bent state of IgE is ~20 kJ/mol more stable than any unbent/extended states, something which is
borne out in the difficulty to detect extended states experimentally. The barrier to initial IgE-Fc
unbending is very large yet the various lower-free-energy unbent conformations are separated by
barriers which are relatively small. Some of the various extended lower-free-energy conformations
are very similar those captured by anitibodies and crystallography.
We have also carried out large metadynamics and MSM analyses focused on the bent state of IgE-
Fc. There is great flexibility within the bent state which seems to have three different conformations
separated by relatively small barriers. Interestingly, one of these conformations seems to be primed
for receptor FcRI binding.
The extraordinary flexibility and conformational diversity of IgE-Fc offers a new perspective on
IgE function in allergen recognition, as part of the B cell receptor and as a therapeutic target in
allergic disease.
References
1. Drinkwater, N. ; Cossins, B. P. ; Keeble A. H. ; Wright M. ; Cain K. ; Hailu H. ; Oxbrow A. ; Delgado J. ; Shuttleworth L. K. ; Kao M. ; McDonnell J. M. ; Beavil A. J. ; Henry A. J.
; Sutton B. J. Nature SMB., in press, 2014
40
Protein Druggability: the JEDI Approach
Rmi Cuchillo, Julien Michel
University of Edinburgh, EaStCHEM school of Chemistry, Joseph Black Building, West Mains
Road, Edinburgh, Scotland EH9 3JJ
Several scoring functions have been developed over the last decade to evaluate the druggability -or
ligandability- of a protein structure. The majority of existing methods, such as Fpocket, were
designed to assess the druggability of crystallographic structures and were not developed to be
tightly coupled to molecular dynamics (MD) simulations, in spite of the fact that post-processing of
MD trajectories is possible.1 We present JEDI, a novel computational approach for druggability
assessment using a combination of empirical descriptors that can be collected "on-the-fly" during
MD simulations.
The Druggable Cavity Directory (http://fpocket.sourceforge.net/dcd) was used to build a data set of
64 diverse proteins in order to parameterize the JEDI scoring function. JEDI is a grid-based
approach able to perform the druggability assessment of a binding site in only a few seconds
making it one of the fastest methodologies in the field. Agreement between computed and
experimental druggability estimates is comparable to literature alternatives. In addition, our
estimator is less sensitive than existing methodologies to small structural rearrangements and gives
consistent druggability predictions for similar structures of the same protein.
To facilitate evaluation of the druggability of a target at each step of a MD simulation, the JEDI
scoring function has been integrated within the PLUMED free energy plugin that supports a broad
range of MD packages.2 Preliminary results show that druggability estimates can be computed for
each step of a MD simulation with modest overheads. A unique feature of the approach is that
because our druggability function is sufficiently rapid and continuously differentiable, it is possible
to: 1) supplement typical potential energy functions with a druggability potential, and 2) exploit
information provided by the druggability force to bias molecular dynamics simulations with a
variety of free energy methods. Progress towards the identification of cryptic druggable
conformations in a range of systems will be reported.
References
1. Schmidtke, P. P.; Barril, X. X. J. Med. Chem., 53, 5858-5867, 2010
2. Bonomi, M.; Branduardi, D.; Bussi, G.; Camilloni, C. Comp. Phys. Commun., 180, 1961-1972,
2009
41
EVALUATING CRYSTALLOGRAPHIC INTERACTION INTERFACES THROUGH MD
Erin Cutts, Leanne Slater, Justyna Wojdyla, Phillip Stansfeld, Ioannis Vakonakis
Department of Biochemistry, University of Oxford, South Parks road, Oxford, OX13QU
Approximately 90% of protein structures in the protein data bank are derived using X-ray
crystallography, but how trustworthy are the interactions observed between molecules in these
structures? Presented here is our analysis of three recent crystallographic protein structures that
show interactions leading to dimers or higher order oligomers:
PFI1780w, a Plasmodium falciparum protein, whose structure was resolved as a helix swap dimer despite biophysical data suggesting it is monomeric.
TolR, an E. coli inner membrane protein that displays an intertwined beta strand swap dimer.
The structure of G-box from Danio rerio CPAP, a novel domain type, which was resolved as filaments of anti-parallel beta sheets and exhibits oligomerisation in
solution.
In each case MD simulations were performed on the monomeric and higher order structures to
investigate their stability and to provide insight into experimental observations. Although clear
conclusions can not always be drawn, MD simulations generally supported experimental
obversations and helped to resolve confusion caused by molecular interactions in crystallographic
structures.
42
Accumulation and transmission of energy during the rotary catalytic cycle of
F1-ATPase
Jacek Czub1, Milosz Wieczor
1, Pawel Wityk
1, Helmut Grubmueller
2
1Department of Physical Chemistry, Gdansk University of Technology, Narutowicza 11/12, Gdansk,
Poland 2Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical
Chemistry, Am Fassberg 11, Goettingen, Germany
F1-ATPase (F1) is the catalytic portion of ATP synthase, a rotary motor protein that couples the
proton gradient to ATP synthesis. When driven by a proton flux, the F1 asymmetric subunit (-shaft) undergoes a discrete rotation inside the 33 catalytic headpiece and causes the binding sites located at the subunits to cycle between states of different affinity for nucleotides. These concerted transitions drive the synthesis of ATP from ADP and phosphate.
It was suggested that elastic power transmission with transient storage of energy in some compliant
part of the -shaft is required for the high turnover rate to occur. To investigate the proposed mechanism in atomistic detail we used MD simulations. Analysis of the rotational fluctuations
revealed that the elasticity of the F1 -shaft, as sensed by Fo, arises from two distinct contributions: the intrinsic elasticity and an effective potential imposed by the catalytic subunit. Separation of
these two contributions provided a quantitative description of the dynamic coupling between the
rotor and the stator and enabled us to propose a minimal model of the F1 energetics near the crystal
structure resting state.
To directly study the energy transmission between the rotor and stator subunits of F1 during the
catalytic cycle we employed a force-probe MD in which the central -shaft is driven to rotate by externally applied torque within the 33 hexamer. With this approach we show that the nucleotide-free subunit, initially in the open, low-affinity state, undergoes a fast closing transition in response to the -shaft rotation in the synthesis direction. By computing a free energy profile, we further find that the initial transition to the half-open state is driven by the intrinsic elasticity of , dominated by the electrostatic interactions between elements of the active site. Therefore, our data suggest that
ADP binding to F1 occurs via conformational selection and is preceded by the transition of to the half-open state a previously unknown functional state that complements the conformational
landscape of subunits. Elastic properties of imply that the -shaft is unlikely to be pulled into the position seen in the x-ray structure by spontaneous opening of the empty . Instead, the observed position is stabilized by interactions with the two other subunits and keeps the empty in the fully open conformation. This finding supports the notion that the -shaft acts by coupling the extreme conformational states of subunits within the 33 headpiece and therefore is responsible for high efficiency of the coordinated catalysis.
To obtain a complete picture of the F1 rotary cycle, we determined the free energy profile for the -shaft rotation within the 33 headpiece using umbrella sampling approach. These simulations revealed the presence of a second minimum of the free energy at +80 with respect to the crystal
structure resting state, in agreement with single-molecule experiments. By decomposing the
observed free energies into individual interactions, we analyzed the major determinants of the
stability of this state likely corresponding to the so-called ATP-dependent pause of F1-ATPase.
43
SIMULATING THE COATING PROCEDURE OF INDOMETHACIN
NANOPARTICLES WITH MPEG-PCL DIBLOCK COPOLYMERS
Ioanna Danai Styliari1, Andrew Theophilus2, Cameron Alexander1, Martin Garnett1 and
Charles Laughton1
1Centre for Doctoral Training in Targeted Therapeutics and Formulation Sciences, School of
Pharmacy, University of Nottingham, University Park, NG7 2RD, Nottingham 2 Product Development, R&D GlaxoSmithKline, Stevenage
Nanoparticles hold a great promise as drug delivery carriers with a wide range of therapeutic
applications. Coating nanoparticles with functional entities like polymers can enhance their target
properties and their protection from the immune system1. Diblock copolymers in particular,
consisting of a hydrophobic and a hydrophilic part, have interesting potential as tunable coating agents. In this study we are examining the interaction properties of diblock copolymers formed of
the hydrophilic monomethoxy poly(ethylene)glycol (mPEG) and hydrophobic polycaprolactone
(PCL)2 in different molecular weight ratios (MwPCL/MwMPEG). We are studying, both by
experiment and simulation, a) how these polymers interact with drug nanoparticles and b) how the
coated nanoparticles interact with each other. In order to investigate this using molecular dynamics
simulations, GROMACS and AMBERtools have been used to construct different lengths of
polymer chains, in accordance with the experimental values. Indomethacin, a non-steroidal anti-
inflammatory drug has been selected as the first compound. A two-phase simulation system has
been set up, consisting of a model of an acetone drop containing an indomethacin nano-crystal and the polymers, surrounded by the water phase. The simulation, in which these two solvent
regions mix, thus models the coating method that is used experimentally. The results of these
nanoparticle coating simulations will be compared with the experimental observations and will be
the first step towards the future investigation of nanoparticle nanoparticle interactions.
References
1. Elsabahy, M. Wooley, K. L. Chem. Soc. Rev, 41, 2545-2561, 2012
2. Hou, J.; Qian, C.; Zhang, Y.; Guo, S. J. Biom. Nanotech., 9, 231-237, 2013
44
Molecular dynamics simulation of lipid membranes with AMBER and application to the study of radioimaging compounds
Callum J. Dickson1, Antony D. Gee2 and Ian R. Gould1
1 Department of Chemistry and Institute of Chemical Biology, Imperial College London, South Kensington,
SW7 2AZ, United Kingdom
2 Division of Imaging Sciences, King's College London, St Thomas' Hospital, London, SE1 7EH, United
Kingdom
Positron emission tomography (PET) scanning is a molecular imaging technique allowing the
detection and analysis of biological processes, including metabolism and disease. PET scanning is
regularly implemented in the imaging and study of diseases such as cancer, Alzheimers and
Parkinsons disease and is also becoming increasingly popular to aid the drug discovery process.
To perform a PET scan, the patient is administered a small molecule radiotracer, which emits a
trace amount of radiation and binds to the site of interest, allowing an image to be constructed. In
order to image new targets, novel radiotracers must be designed. However a limitation in the design
of new radiotracers is non-specific binding, whereby the tracer binds to off-target species, such as
cell membranes, creating an uninformative image with poor contrast. An in silico indicator, able to
predict the level of non-specific binding a new radiotracer may undergo in vivo prior to synthesis
and testing, would be extremely beneficial to the PET community.
In this work we investigate non-specific binding using molecular dynamics (MD) to study the
interaction of PET radiotracers with lipid bilayers, a simple model for the cell membrane, using the
AMBER MD package. To accurately model lipid bilayers, suitable parameters were first
constructed.[1] These parameters are currently being combined with the AMBER Lipid11 modular
lipid force field [2] to create Lipid12, an updated unified AMBER lipid force field. The potential of
mean force (PMF) method has been inserted into AMBER, in order to calculate the free energy of
transfer of radiotracers through a lipid membrane. The PMF method is currently being applied to a
dataset of well characterised PET radiotracers to investigate the relationship between membrane
permeability and non-specific binding.
References
[1] C. J. Dickson, L. Rosso, R. M. Betz, R. C. Walker and I. R. Gould, Soft Matter, 2012, 8, 9617-9627.
[2] . A. Skjevik, B. D. Madej, R. C. Walker and K. Teigen, The Journal of Physical Chemistry B, 2012,
116, 11124-11136.
45
Rational design of isoform specific ligands
Charis Georgiou, Malcolm Walkinshaw
, Julien Michel
Institute of Structural and Molecular Biology,
EastCHEM Shool of chemistry, The
University of Edinburgh, Edinburgh, EH9 3JR
Cyclophilins are proteins able to catalyze the interconversion of trans/cis isomers of proline
and belong to the peptidyl-prolyl isomerases family (PPIase). 1 In addition to their PPIase
activity, cyclophilins have diverse biological roles and have been implicated in a number of
different diseases such as HIV-1 and HCV. Although several cyclophilin inhibitors have been
reported in the literature, none are able to inhibit with high specificity selected cyclophilin
isoforms.
To facilitate the development of isoform-specific cyclophilin ligands, we are pursui
