Molecular modelling (1)

MOLECULAR MODELING

Presented by: BHARATESHA.S 9th semester13th october,2015

Guided by:Dr. Amruthavalli

“To develop a sufficient accurate model of the system so that physical experiment may not be necessary”

HISTORY ABOUT MOLECULAR MODELING

Plastic Ball and stick model of Proline

“ISIS draw program “

“3D biological macromolecular structural data”

Spacefill ball & stick

cartoon

CONTENTS• INTRODUCTION

• HISTORY ABOUT MOLECULAR MODELING

• TEMPLATE MODELING -Homology modeling -Threading

• TEMPLATE FREE MODELING(ab initio methods)

• CONCLUSION

• REFERENCES

INTRODUCTION

• Molecular modeling describes the generation ,manipulation or representation of 3 –dimensional structure of molecules and associated physico-chemical properties.

• It involves a range of computerized technique based on theoretical chemistry methods and experimental data to predict molecular and biological properties.

• The three most common computational methods are: - Molecular mechanics - Quantum mechanics - Molecular dynamics

Template Modeling

Homology modeling

Protein Threading

Homology Modeling

Based on two major observations:

1)The structure of a protein is determined by its amino acid sequence

2) Structure is much more conserved than sequence during evolution.

In general, 30% sequence identity is required to generate an useful model.

Steps in Homology Modeling

Step 1: Template Recognition and Initial Alignment

In practice, one just feeds the query sequence to one of the countless BLAST servers on the web, selects a search of the PDB, and obtains a list of hits—the modeling templates and corresponding alignments

Step 2: Alignment Correction

Sometimes it may be difficult to align two sequences in a region where the percentage sequence identity is very low.

One can then use other sequences from homologous proteins to find a solution.

Known structure FDICRLPGSAEAV

Model FNVCRMP---EAI

Model FNVCR---MPEAI

S

G

P

L

A

E

R

C

I V

C

R

M

P

EV

C

R M

P

E

Correct alignment

F-D--A-V

Step 3: Backbone Generation

• One simply copies the coordinates of those template residues that show up in the alignment with the model sequence.

• If two aligned residues differ, only the backbone coordinates (N,Cα,C and O) can be copied.

• If they are the same, one can also include the side chain.

Step 4: Loop Modeling

There are two main approaches to loop modeling:-

1). Knowledge based: one searches the PDB for known loops with endpoints that match the residues between which the loop has to be inserted and simply copies the loop conformation.

2). Energy based: as in true ab initio fold prediction, an energy function is used to judge the quality of a loop

Step 5: Side-Chain Modeling

• Comparing the side-chain conformations (rotamers) of residues that are conserved in structurally similar proteins.

• Similar torsion angle about the Cα −Cβ bond.

• It is therefore possible to simply copy conserved residues entirely from the template to the model.

Fig 01 :Prefered rotamers of this tyrosin (colored sticks) the real side-chain (cyan) fits in one of them.

Step 6: Model Optimization

Energy = Stretching Energy +Bending Energy +Torsion Energy +Non-Bonded Interaction Energy

Step 7: Model Validation

Model should be evaluated for:

- correctness of the overall fold/structure

- errors over localized regions

- stereochemical parameters: bond lengths, angles, etc

Model!

1: Template recognition and initial alignment

2: Alignment correction

3: Backbone generation

4: Loop modeling

5: Sidechain modeling

6: Model optimization

7: Model validation

8: Iteration8: Iteration

8: Iteration

8: Iteration

Protein Threading

protein A threadedon template template

protein B threadedon template

Template-Free Modeling Ab initio methods

• Physics Based

• Knowledge Based

ab initio(from the beginning) methods

If the structure homologues(occasionally analogues) do not exist, or exist but cannot be identified, models have to be constructed from scratch.

Three key factors of the modeling algorithms are:

• Energy function

• Conformational search

• Model selection

Physics Based

Knowledge Based

QUANTUM MECHANICS

• It provides information about the nuclear position and distribution.

• It is based on study of arrangement and interaction of electrons and nuclei of a molecular system.

• It is based on the wave properties of electrons and material particles.

Total energy= Potential energy + Kinetic energy

• To calculate the value of potential, electron affinities, heat of formation, dipole moment.

• To find the electron density in a structure.

• To determine the point at which a structure will react with electrophiles and nucleophiles.

Physics based energy function

MOLECULAR MECHANICS

• Calculation of energy of atoms, force on atoms and their resulting motion.

• Used to model the geometry of the molecule, motion of the molecule and to get the global minimum energy structures.

Methods:

• Force field

• Study of electrostatics

• Molecular dynamics

• Conformation analysis

Software :

• AMBER

• CHARMM

• GROMOS96

Knowledge based energy function

• It refers to the empirical energy terms derived from the statistics of the solved structures in deposited PDB. Examples: ROSETTA,TASSER

Conformation search methods

• To find the global minimum energy structure for a given energy function with complicated energy landscape.

Advantage

ab initio modeling can help us to understand the underlying principles on how proteins fold in nature.

Limitation100-120 residue protein structures can be determined using ab initio methods.

CONCLUSION

• Visualize the 3D shape of a molecule

• Carryout a complete analysis of all possible conformation and their relative energies.

• Predict the binding energy for docking a small molecule i.e. a drug candidate, with a receptor or enzyme target.

• It is necessary to have standard models which are applicable to very large systems.

• Nevertheless, molecular modeling if used with caution, can provide very useful information to the chemist and biologist involved in medicinal research.

REFERENCES

• Alan Hinchliffe,(2003)Molecular modeling for beginners,John wiley &sons ltd,England-407pp.

• Ramachandran, Gopakumar Deepa,(2008)Computational chemistry and molecular modeling,Springer science and business media,398pp.

• Holtje.H.D. Folkers(1996)Molecular modeling ,Basic principle and applications,VCH publishers,Newyork-177pp.