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Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

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In Vivo drug discovery process

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Page 1: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Bioinformatics in Drug Design and DiscoveryUnit 1

By,Tanusree Bhattacharya

Page 2: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Drug design - Compound searching,

• Target discovery, which comprises identification and validation of disease-modifying targets, is an essential early step in the drug discovery pipeline.

Target-based drug discovery. Four step overview (top arrows) and detailed schematic outline. Target-based drug discovery may be divided into molecular- (path A) and system-based (path B) approaches. Each approach is composed of three steps: the provision of disease models/tissues (red), target identification (purple), and target validation (blue). The molecular approach (path A) comprises techniques such as genomics, proteomics, genetic association, and reverse genetics, whereas systems approach (path B) comprises clinical and other in vivo studies to identify targets. Target validation covers conformational experiments in cell and/or animal models. Subsequently, the drug discovery process is commenced.

Page 3: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

In Vivo drug discovery process

Page 4: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Compound searching from HIT to LEAD

Typically, the term “hit” refers to compounds identified in some initial rounds of screening.

Compounds identified as hits typically go through additional rounds of screening. Once screening results have been verified, some readily obtained derivatives will be synthesized or purchased and tested.

Once a compound, or often a series of compounds, meets a certain set of criteria, the series will be designated as a lead series.

The lead series is then used as the basis for a more comprehensive synthesis of many derivatives and more in-depth analysis, both computational and experimental.

Page 5: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Criteria that are necessary to move a compoundseries onto the lead development stage

concentration-dependent activity active in both biochemical and cell-based assay below some IC50 threshold (perhaps low micromolar, or down to the nanomolar range) some understanding of the series’ structure–activity relationships known binding kinetics selectivity assessment well-established structure and purity stability assessment synthetically tractable series is patentable some path for optimization (creating derivatives) is apparent solubility measured log D measured metabolic liabilities predicted pharmacokinetics predicted or measured toxicity issues predicted potential for significant side effects considered (e.g., whether the drug will block hERG channels, thus

resulting in drug-induced cardiac arrhythmia

Page 6: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Target Identification

2-D structure identificationX ray crystallography :NMR:Homology modelling:

3-D structureProtein folding:

Page 7: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Diffraction pattern

Electron density

Model

Overview of X-ray Crystallography

Page 8: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Nuclear Magnetic Resonance Spectroscopy

Page 9: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Structure Identification steps

Page 10: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Target Characterization

It is also important to understand themechanism of chemical reactions involving that protein, where it is expressed in the body, the pharmacophoric description, and the mechanism by which inhibitors can bind to it.

• ANALYSIS OF TARGET MECHANISM: understanding similarities to other proteins in the same family, as well as differences from the most structurally similar proteins.

the techniques utilized for this purpose are:

Kinetics and Crystallography: For the purpose of determining the target mechanism, the primary value comes from comparing crystal structures that contain a soaked ligand to the apo structure. If there is an induced fit of the ligand in the active site, this will show any conformational changes that the protein undergoes. If several dissimilar classes of compounds all inhibit the target, crystal structures may be determined with a representative molecule from each group soaked into the crystal. This gives a firm verification that all are binding at the same site, and whether there are any differences in the geometry of the active site.Determining whether a reaction exhibits second-order, third-order, or a fractional-order kinetics is one step in understanding its mechanism

Page 11: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

• Automated Crevice Detection:If no experimental data is available then we use this method, where, software packages look for concave regions on the protein’s surface and categorize them, usually by their volume. This is based on the (usually correct) premise that the largest crevice is most likely to be the active site.• Transition Structures and Reaction Coordinates: Most analysis of transition structures and reaction coordinates is performed with quantum mechanical calculations. Transition state optimization algorithms are used to determine the transition structures. Then intrinsic reaction coordinate (IRC) calculations are used to show the energy and nuclear positions as the molecule traverses the potential energy surface between those points.• Molecular Dynamics Simulations:The, statistical mechanics and molecular dynamics give a more realistic description of the process , how molecules vibrate, but usually not perfectly in just one of the normal vibrational modes and how Molecules enter and leave proteins’ active sites, but not necessarily following the reaction coordinate exactly.WHERE THE TARGET IS EXPRESSED:The location in which the drug target is expressed will determine some of the bioavailability concerns that must be addressed in the drug design process. If the target is only expressed in the central nervous system (CNS), then blood–brain barrier permeability must be addressed, either through lipophilicity or through a prodrug approach. Since the blood–brain barrier functions to keep unwanted compounds out of the sensitive CNS, this is a major concern in CNS drug design efforts. The easiest targets for a drug to reach are cell surface receptors. This is why many drugs are designed to interfere with these receptors, sometimes even when metabolic pathway concerns would suggest that a different target is a better choice. It is not impossible to design a drug to reach a target inside a cell; it simply requires a more delicate lipophilicity balancing act.

Page 12: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

• PHARMACOPHORE IDENTIFICATION:The pharmacophore is the three-dimThe pharmacophore is the three-dimensional geometry of interaction features that a molecule must have in order to bind in a protein’s active site. These include such features as hydrogen bond donors and acceptors, aromatic groups, and bulky hydrophobic groups. The pharmacophore can be used to search through databases of compounds to identify those that should be assayed.

• CHOOSING AN INHIBITOR MECHANISM:Competitive inhibition:Most drugs bind by this mechanism only. This means that they bind reversibly to the target’s active site. While the drug is in the active site, it is impossible for the native substrate to bind. Because reversibly bound inhibitors are constantly being cycled through the system, they are also susceptible to being eliminated from the bloodstream quickly by the liver, thus requiring frequent dosages.Suicide inhibitor:Suicide inhibitors bind irreversibly to the target’s active site. This makes them inactivators of the target. Completely removing a target from the biological system can have severe side effects.Uncompetitive inhibitors:Uncompetitive inhibitors bind to the enzyme–substrate complex, but not to the free enzyme. This also acts to downregulate protein activity. However, it is more difficult to design uncompetitive inhibitors with specificity for one target.Noncompetitive inhibitors:They can bind to either the enzyme–substrate complex or the free enzyme.

Page 13: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Study of molecular interactions between target and compound(docking)

Docking attempts to find the “best” matching between two molecules

Given two biological molecules determine:• Whether the two molecules “interact”• If so, what is the orientation that

maximizes the “interaction” while minimizing the total “energy” of the complex

• Goal: To be able to search a database of molecular structures and retrieve all molecules that can interact with the query structure

Page 14: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Why is docking important?

• It is of extreme relevance in cellular biology, where function is accomplished by proteins interacting with themselves and with other molecular components

• It is the key to rational drug design: The results of docking can be used to find inhibitors for specific target proteins and thus to design new drugs. It is gaining importance as the number of proteins whose structure is known increases.

Docking Challenge• Identification of the ligand’s correct binding geometry in the binding site

(Binding Mode)

• Observation: – Similar ligands can bind at quite different orientations in the active site.

Parameters to be considered:Hydrogen bonds, lipophilic properties, van der Waals interactionsPossible metal ionsTensions of the ligand backbone

Conformation

Page 15: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Types of Docking studies

• Protein-Protein Docking• Both molecules usually considered rigid• 6 degrees of freedom• First apply steric constraints to limit search space and the

examine energetics of possible binding conformations

• Protein-Ligand Docking• Flexible ligand, rigid-receptor• Search space much larger• Either reduce flexible ligand to rigid fragments connected by one

or several hinges, or search the conformational space using monte-carlo methods or molecular dynamics

Page 16: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Rigid-body docking algorithms

• Historically the first approaches. • Protein and ligand fixed. • Search for the relative orientation of the two molecules with lowest energy.• FLOG (Flexible Ligands Oriented on Grid): each ligand represented by up to 25

low energy conformations.

Introducing flexibility: Whole molecule docking

• Monte Carlo methods (MC)• Molecular Dynamics (MD)• Simulated Annealing (SA)• Genetic Algorithms (GA)

Available in packages:AutoDock (MC,GA,SA)GOLD (GA)Sybyl (MD)

Page 17: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

ADMET(Absorption, distribution, metabolism, and excretion) Studies and Study of drug Resistance

In drug discovery projects, an issue of major importance is the design of drug molecules capable of penetrating different biological membranes effectively and rapidly enough to allow effective concentrations to build up at the therapeutic target. The structure and physiochemical properties of the drug molecule obviously are of decisive importance, and it is possible to establish the following empirical rules:• Some small and rather water soluble substances pass in and out of cells through water llined

transmembrane pores.• Other polar agents are conducted into or out of cells by membrane associated and energy

consumin proteins• The blood–brain barrier (BBB) normally is not easily permeable by neutral amino acids. • Molecules that are partially water soluble and partially lipid soluble can pass through cell

membranes by passive diffusion and are driven in the direction of the lowest concentration.• In cells lining the intestinal tract, it is possible for molecules with these characteristics to pass

into the body through the cell membrane alone.• Finally, it is also possible for molecules with suitable water solubility, small size, and compact

shape to pass into the body between cells.

Page 18: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

The majority of effective oral drugs obey the Lipinski rule of five:

• Partition coefficient log P in −0.4 to +5.6 range

• Molar refractivity from 40 to 130

• Molecular weight from 160 to 500

• Number of atoms from 20 to 70 (includes H-bond donors [e.g.;OH's and NH's] and H-bond acceptors [e.g.; N's and O's])

• Polar surface area no greater than 140 Ǻ2

Page 19: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Drug design process for aknown protein target – Structure based drug design

process

Page 20: Bioinformatics in Drug Design and Discovery Unit 1 By, Tanusree Bhattacharya

Drug designing process for unknown protein target – Ligand based drug design process.