SBDD

Views:
 
Category: Entertainment
     
 

Presentation Description

No description available.

Comments

Presentation Transcript

Slide 1: 

Structure Based Drug Design Prestended by:- Nikhil A. Khisti SHITAL S. BHANDARI (M.PHARMACY) 1

Basics : 

Basics Drug:- It is a molecule, which on interaction with receptor or enzyme will show the pharmacological action. Drug Design:- Drug design is the effort to develop drugs on as rational basis as possible. This implies a reduction of the trial & error factor in the procedure to absolute minimum. 2

Basic Principles of Drug Design : 

Basic Principles of Drug Design Minimize binding entropy cost (minimize rigidification of ligand upon binding by selecting a fairly rigid molecule). Maximize enthalpic favorability through attaining good ligand-protein complementarily in surface: • shape (may involve interfacial bound water). • chemistry: – Hydrogen bond donor groups at the protein surface should match H-bond acceptors at the ligand surface ,and vice versa. – Charge-charge interactions should be complementary. – Hydrophobic (e.g., hydrocarbon) groups on the protein and ligand surfaces should match each other. 3

Traditional Approach Rational Approach : 

Traditional Approach Rational Approach Vast majority of drugs still on the market were developed by a mixture of rational design, trial and error, hard graft and pure luck. 4 Rational – Reason-based Not based on chance alone. May not involve computers. Traditional – Screening -based Based on chance alone. Time consuming & laborious.

Rational Drug Discovery : 

Rational Drug Discovery Types of Drug Discovery Searches Structure – based Drug Design (structure of the receptor, binding site, AA residues, thermodynamics) Pharmacophore – based Drug Design (structure of the ligand, SAR, QSAR) Mechanism – based Drug Design (molecular mechanism of action, transition state) Combinatorial chemistry – based Drug Design (chemical synthesis in laboratory ) Random screening – based Drug Design (Laboratory synthesis and randomly tested in animals) 5

Molecular Modeling : 

Molecular Modeling ? 6

Structure and Ligand Based Design : 

Structure and Ligand Based Design 7

Much Ado About Structure : 

Much Ado About Structure Structure Function Structure Mechanism Structure Origins/Evolution Structure-based Drug Design 8

Introduction to Structure based drug design (SBDD) : 

Introduction to Structure based drug design (SBDD) Utilizes the 3D structure of protein target to direct the search for new drug leads and optimize their design. A rational approach that maintains critical protein ligand interactions while trying to optimize specificity of binding and favorable pharmacokinetics More accurately: ligand design, not drug design. Attracted widespread interests in ’80s. Appeared less fruitful in ’90s relative to HTP screening. Rejuvenated by many technological advances. Integration of SBDD with combinatorial, HTP screening is the effective approach. 9

Schematic diagram of SBDD : 

Schematic diagram of SBDD 11/21/2011 10 Schematic of the structure-based drug design process. The figure maps out the iterative steps that make use of X-ray crystallography, molecular modeling, organic synthesis, and biological testing to identify and optimize ligand-protein interactions.

Lock And Key Model : 

Lock And Key Model 11

Lock & Key Model (contd.) : 

Lock & Key Model (contd.) Some “Locks” are known but not all !! Study of protein crystals give the details of the “lock”. Knowing the “lock” structure, we can DESIGN some “keys”. This is achieved by COMPUTER Algorithms This is called “STRUCTURE BASED DRUG DESIGN” Algorithms “Lock” structure (from experiment) “Key "constructed by computer 11/21/2011 12

Goal: Predict Free Energy of Binding : 

Goal: Predict Free Energy of Binding PL P + L 13

Numerous Examples of SBDD : 

Numerous Examples of SBDD Human enzymes: DHFR (methotrexate; cancer), carbonic anhydrase (dorzolamide; glaucoma), matrix metalloproteinase , phospholipase A (inflammation), ACTase (donepezil; Alzheimer’s). Influenza virus, rhinovirus, poliovirus. HIV proteins (RT, protease, integrase). Glycolytic enzymes in trypanosomes. 14

Slide 15: 

15

Technological advances : 

Technological advances Structure determination – X-ray, NMR , prediction – Molecular biology for production of protein Bound ligand conformation – Energetic of binding from mutagenesis coupled with thermodynamic and structural analysis Computational tools – Hardware speeds – Software for docking, scoring, screening Information – Quantity of information – Accessibility of information 16

Different Cycles in SBDD : 

Different Cycles in SBDD The central assumption of structure-based drug design is an iterative & often proceeds through multiple cycles before an optimized lead goes into clinical trials. The first cycle includes structure determination of the target protein. Then lead selection. These compounds are scored & ranked based on their steric & electrostatic interactions with the target site & the best compounds are tested further with biochemical assays. In the second cycle, structure determination of the target in complex with a promising lead from the first cycle, one with at least micromolar inhibition in vitro, reveals sites on the compound that can be optimized to increase potency. Additional cycles include synthesis of the optimized lead, structure determination of the new target: lead complex, and further optimization of the lead compound. 17

Definition of site : 

Definition of site The availability of 3D structural Information target does not guarantee identification of the site of action of the substrate, or inhibitor, unless the structure of a relevant complex has been determined. Conformational changes often occur during binding of ligands to enzymes that are not reflected in the 3D structure of the enzyme alone. In other cases of therapeutic targets, allosteric sites are involved in regulation of binding and cannot clearly be discerned from the crystal structure available. One significant concern of structure-based design is the dynamics of the target itself. How stable is the active site to modifications in the ligand? Are there alternative potential binding sites that could compete for the ligand? 18

Characterization of Site : 

Characterization of Site Volume & Shape Most substrate-enzyme or receptor-ligand interaction occur within pockets, or cavities, buried within proteins. Inside these invaginations, a microenvironment is established that favours desolvation and binding of the ligand. Knowledge of the three-dimensional structure of such cavities can assist the study of binding interactions and the design of novel ligands as potential therapeutics. Dock- Volumetric representation ,Cavity- To isolate single cavity. 19

Characterization of Site (contd.) : 

Characterization of Site (contd.) Hydrogen Bonding & other Group Binding Sites In evaluating potential ligands, knowledge of optimal position of particular atoms or functional groups ,with in the site can provide valuable insight. GRID-allows the probe group to explore the receptor site cavity on a lattice or grid, while estimating the enthalpy of interaction. Ideal position for hydrogen bond donors or acceptors can be mapped in this fashion as a preface to ligand design. 20

Characterization of Site (contd.) : 

Characterization of Site (contd.) Electrostatic & Hydrophobic Fields Because the concept of complementarity underlies much of our design of ligands, surface display of properties such as hydrophobicity & electrostatic potential offers a synopsis of properties of the active site. At every cavity-pocket interface point, the electrostatic potential of both the atoms forming the cavity and those of the binding ligand are calculated. A rough approximation of complementarity is computed by multiplying these potentials together. A favourable electrostatic interaction is produced when the electrostatic potentials are opposite in sign. Therefore, favourable interactions are indicated when the product of these values is a negative number. 21

Computational Screening to Discover a Lead Compound : 

Computational Screening to Discover a Lead Compound 22

Different Ways….. : 

Different Ways….. 23

Design of Ligands : 

Design of Ligands Visually Assisted Design. For the process of optimization of a lead, one needs to ascertain where modification is feasible. Although visualization of the excess space available in the active-site cavity by directly examining ligands is useful for locating selected regions where ligand modifications may be made, it is not well suited for fully characterizing the void that exists between the ligand and the receptor. 24

Design of Ligands (contd.) : 

Design of Ligands (contd.) Three Dimensional Database. Medicinal chemists have recognized the potential of searching three-dimensional chemical databases to aid in the process of designing drugs for known, or hypothetical, receptor sites. Cambridge Crystallographic database, Brookhaven Protein databank. The three-dimensional orientation of the key regions of the drug that are crucial for molecular recognition and binding are termed the pharmacophore. The investigator searches the three-dimensional database through a query for fragments that contains the pharmacophoric functional groups in the proper three dimensional orientation. Using these fragments as "building blocks," completely novel structures may be constructed through assembly and pruning. MOLPAT,CAVEAT,ALADDIN,CHEM-X 25

Three Dimensional Databases : 

Three Dimensional Databases 26 O O O H H O O O H H O O O H DB Search Define Pharmaco phore Ligand Design 26

Design of Ligands (contd.) : 

Design of Ligands (contd.) De Novo Design It has become quite evident that much of a molecule acts simply as a scaffold to align the appropriate groups in the three-dimensional arrangement that is crucial for molecular recognition. By understanding the pattern for a particular receptor, one can transcend a given chemical series by replacing ones caffold with another of geometric equivalence. This offers a logical way to dramatically change the side-effect profile of the drug as well as its physical and metabolic attributes. caffold with another of geometric equivalence. Various software tools are already under development to assist the chemist in this design objective. Like BRIDGE,CAVEAT,LUDI,CSD. 27

Design of Ligands (contd.) : 

Design of Ligands (contd.) Docking The search for the global minimum, or the complete set of low energy minima, on the free energy surface when two molecules come in contact is commonly referred to as the "docking" problem. 28

Molecular Docking (contd.) : 

Molecular Docking (contd.) The process of “docking” a ligand to a binding site mimics the natural course of interaction of the ligand and its receptor via a lowest energy pathway. Put a compound in the approximate area where binding occurs and evaluate the following: Do the molecules bind to each other? If yes, how strong is the binding? How does the molecule (or) the protein-ligand complex look like. (understand the intermolecular interactions) Quantify the extent of binding. 29

Molecular Docking (contd…) : 

Molecular Docking (contd…) Computationally predict the structures of protein-ligand complexes from their conformations and orientations. The orientation that maximizes the interaction reveals the most accurate structure of the complex. The first approximation is to allow the substrate to do a random walk in the space around the protein to find the lowest energy. Another approach focusing on complementary surface maximization uses a grid representation of the surface in a series of slices. The slices from the target molecule are processed against the slices from the other molecules by use of a variant of the fast-Fourier transform to identify those sections with the greatest complementarity. 30

Scoring function : 

Scoring function At the beginning of a project, or when three dimensional information on a novel target first becomes available, such data on a diverse set of chemical ligands are usually not available. For this reason, one would like to capitalize as much as possible on the physical chemistry of the possible interactions between the ligand and its receptor when the structure of the receptor is available. Bohm analyzed 45 protein-ligand complexes (affinity range = -9 to - 76 kJ/mol) and found the equation by multiple regression analysis. Krystek et al. analyzed protein ligand complexes in an update of the Novotny approach.

Algorithms used while docking : 

Algorithms used while docking Fast shape matching (e.g., DOCK and Eudock), Incremental construction (e.g., FlexX, Hammerhead, and SLIDE), Tabu search (e.g., PRO_LEADS and SFDock), Genetic algorithms (e.g., GOLD, AutoDock, and Gambler), Monte Carlo simulations (e.g., MCDock and QXP), 32

Some Available Programs to Perform Docking : 

Some Available Programs to Perform Docking Affinity Auto Dock BioMedCAChe CAChe for Medicinal Chemists DOCK Dock Vision FlexX Glide GOLD Hammerhead PRO LEADS SLIDE VRDD 33

Calculation of Affinity : 

Calculation of Affinity Components of Binding Affinity. Binding Energetic & Comparisons. Atom-Pair Interaction Potential. Simulations & the Thermodynamic cycle. Multiple Binding Modes.

Steps in Lead Optimization : 

Steps in Lead Optimization Start with lead compounds from in vitro high-throughput screening or from known substrates/inhibitors. Analyze their structures and activities to define which chemical groups of the ligands are critical for binding and specificity for that protein. Modify, as needed, to attain specificity for the target protein. Essential to minimize toxic side-effects (example: ATP-binding proteins, such as kinases). Test the “structure-activity relationship” hypotheses regarding which chemical groups give strong binding and/or specificity by designing and synthesizing a series of compounds. Test their activity by enzymatic and pharmacologic assays. Solve crystal structures in complex with the new ligands to confirm or refine binding hypotheses. 35

Advantages of Docking/Virtual Screening over HTS : 

Advantages of Docking/Virtual Screening over HTS Advantages of virtual screening relative to in-vitro high-throughput screening (HTS) for lead discovery: - “Hit” or success rate can be 10-30%, whereas in HTS it is usually < 0.1% - Avoids the cost of assaying compounds that do not fit the binding site. - Provides a clear structural hypothesis for ligand binding mode and interactions with the protein. 36

New Advances : 

New Advances 37 New Techniques in SBDD

SLIDE : 

SLIDE Screening for Ligands with Induced–Fit Docking, Efficiently • Docking based on shape & chemical complementarity. • SLIDE is free to academic groups. • SLIDE screens, docks and scores 100,000 molecules in ~2 days on a single workstation. 38

What distinguishes SLIDE from other docking tools? : 

What distinguishes SLIDE from other docking tools? • Low-energy ligand conformers generated by Omega* or crystallographic low-energy conformations from Cambridge Structural Database are screened. • Ligand and protein side-chain conformations are adjusted by SLIDE, as needed, during docking. • Source code is provided, allowing modifications. 39

The way SLIDE works : 

The way SLIDE works 40

Computational Challenges of Structure-based Virtual Screening : 

Computational Challenges of Structure-based Virtual Screening Need to evaluate many ligand candidates in many orientations in the binding site. Typically 10-100 low-energy conformations exist for even a relatively rigid candidate (with 4 rotate table bonds). The molecule may fit in hundreds or thousands of orientations. Typically want to screen 10,000’s – 1,000,000 candidates in a project to find several chemically diverse, low-micro molar leads. Cannot use force-field based methods (energy minimization or molecular dynamics) for scoring, due to computational intensity. Even 1 min/cpd 69 days to screen 100,000 cpds (too long!). Therefore, the sampling of conformations & orientations, and the scoring of their complementarity w/ protein need to be simplified. 41

Limitations : 

Limitations In many diseases we don't no the exact target molecule like in case of Epilepsy & other neurological disease in such cases we cannot use SBDD as a drug design tool. Flexibility of target molecule.

Why it is important to model molecularflexibility during screening? : 

Why it is important to model molecularflexibility during screening? • Using unbiased conformations of protein and ligand molecules provides a realistic test of the quality of docking and screening. • Bias towards known ligand classes is removed when docking into apo protein structures discover new chemical classes of ligands. • Flexibility is needed to dock even the known ligand conformation into an unbiased (apo) protein structure: - Ex: Only 9 of 42 thrombin known ligands and 9 of 15 glutathione S-transferase (GST) ligands could be docked into their apo protein structures with a rigid protein model - 90% could be docked (1.3 Å avg RMSD) with side-chain flexibility*. • Conformational differences between proteins can be a useful way to gain specificity for the target. -Ex: P38 kinase, MMP trap door, Asn-tRNA synthetase hinge. 43

Review (SBDD) : 

Review (SBDD) Molecular Biology & Protein Chemistry 3D Structure Determination of Target and Target-Ligand Complex Modeling Structure Analysis and Compound Design Biological Testing Synthesis of New Compounds If promising Pre-Clinical Studies Drug Design Cycle Natural ligand / Screening 44

Therefore… : 

Therefore… Molecular Modeling and Computational Chemistry are essential to understand the molecular basis for biological activity and has Tremendous Potential to aid Drug Discovery . A healthy interaction between computational chemists and pharmaceutical industry seem indispensable. 45

Slide 46: 

THANK YOU 46

authorStream Live Help