![What is drug ??
▪ The term "drug" means [any] particles intended for use in the
diagnosis, cure, mitigation, treatment, or prevention of disease
in man or other animals
▪ A drug is any chemical or biological substance, synthetic or
non-synthetic](https://image.slidesharecdn.com/chapter1-cadd-240902044002-7dcc05f8/85/computer-aided-drug-design-chapter-1-unit-1-3-320.jpg)
computer aided drug design chapter 1 unit 1
- 2. Outline of the Seminar ▪ Drug ▪ Drug Discovery and Development ▪ What is CADD ▪ Computer-Aided Drug Design Approaches ▪ What is Molecular Docking ▪ Applications of Molecular Docking in Drug designing ▪ Success stories in Molecular Docking ▪ Conclusion
- 3. What is drug ?? ▪ The term "drug" means [any] particles intended for use in the diagnosis, cure, mitigation, treatment, or prevention of disease in man or other animals ▪ A drug is any chemical or biological substance, synthetic or non-synthetic
- 4. Animal Plant insulin (pig, cow) growth hormone (man) (Creutzfeldt- Jakob) digitalis (digitalis purpurea - foxglove) morphine (papaver somniferum) Inorganic arsenic mercury lithium Synthetic chemical (propranolol) biological (penicillin) biotechnology (human insulin) Sources of drugs
- 5. Drug Discovery and Development How are drugs discovered and developed?
- 6. New drugs ▪ Occasional new drugs found by accident (Serendipity). ▪ More frequently they are developed as part of an organized effort to discover new ways to treat specific disease.
- 7. Drug Discovery One way to “discover” drugs 7 Richard.B.Silverman
- 8. Drug discovery by serendipity ▪ 1928 Fleming studied Staph, but contamination of plates with airborne mold. Noticed bacteria were lysed in the area of mold. A mold product inhibited the growth of bacteria: the antibiotic penicillin. ▪ Development of propanolol (β-blocking) have unexpected give a benefit of discover Practolol. Propanolol is a β-blocker but it is a lipophilic drug and can enter CNS and cause side effect, by introducing hydrophilic amide group inhibit passage the blood-brain barrier and Practolol produced more selective cardioselective β1 inhibitor with fewer side effects on CNS. ▪ Sulfonamides and tolbutamide
- 9. ▪ Workers in TNT factories always complained from headache due to dilatation of brain blood vessels. TNT was the basis to prepare nitro derivatives which were used in angina to dilate coronary blood vessels and alleviate pain. ▪ Mustard gas tanks used in second world war exploded in italian harbor. They discovered that persons who survived and inhaled this gas lost their defense against microorganisms due to destruction of white blood cells. This led to the discovery of mustard like drugs which were used in leukemia to inhibit excessive proliferation of white blood cells. Drug discovery by serendipity
- 10. ▪ Acetylsalicylic acid was thought to be just a better tolerable prodrug of salicylic acid, but turned out to have a unique mechanism. ▪ Phenolphthalein was considered as a useful dye for cheap wines; after a heroic self-experiment, a pharmacologist experienced its drastic diarrhoic activity. ▪ Warfarin was used a rat poison. 10 Drug discovery by serendipity
- 11. Candidate Medicine Tested in 3-10,000 Patients (Phase III) Studies in 100-300 Patients – POC (Phase II) Clinical Data Analysis New Medicine Idea * 10-15 Year Process Discovery Exploratory Development Registration Full Development Formulations Developed Large Amounts of Candidate Medicine Synthesized Extensive Safety Studies Studies in Healthy Volunteers – safety and POM (Phase I) Project Team and Plans Synthesis of Compounds Early Safety Studies Candidate Screening The Long Road to a New Medicine
- 12. Involves high cost and time 7,000,000 Compounds Screened Preclinical Pharmacology Preclinical Safety 10 - 15 Years ~100 Discovery Approaches 1 - 2 Products Discovery Exploratory Development Phase I Phase II Full Development Phase III 0 Idea 15 Drug 5 10 Clinical Pharmacology & Safety
- 13. Drug Discovery approaches 13 April 2020 •Serendipity (luck) •Screening •Chemical Modification •Rational drug design
- 14. Screen a large number of synthetic chemical compounds or natural products for desired effect. Although this approach for the development of new drugs has been successful in the past, it is not ideal for a number of reasons. It is inherently repetitious and time consuming. It is Trial & error approach One does not need to know the structure of the drug nor the structure of the target upon which the drug will act. One does not need to know about the underlying mechanism of the disease process itself. Random Screening
- 15. Chemical modification Lead generation: Natural ligand / Screening Synthesis of New Compounds Biological Testing Drug Design Cycle (Lead modication) If promising Pre-Clinical Studies
- 16. Chemical Modification Traditional method. An analog of a known, active compound is synthesized with a minor modification, that will lead to improved biological activity. Advantage and Limitation: you end up with something very similar to what you start with. 13 April 2020
- 17. MECHANISM BASED DRUG- DESIGN Most rational approach employed today. Disease process is understood at molecular level & targets are well defined. Drug can then be designed to effectively bind these targets & disrupt the disease process Very complex & intellectual approach & therefore requires detailed knowledge & information retrieval. (CADD Holds Great Future)
- 18. Methodologies and strategies of CADD: 13 April 2020 ▪ Structure based drug design(SBDD) “DIRECT DESIGN” ▪ Followed when the spatial structure of the target is known. ▪ Ligand based drug design (LBDD) “INDIRECT DESIGN” ▪ Followed when the structure of the target is unknown.
- 19. Structure Based Drug Design Determine Protein Structure Identify Interaction Sites De Novo Design 3D Database Evaluate Structure Synthesize Candidate Test Candidate Lead Compound Discovery or design of molecules that interact with biochemical targets of known 3D structure
- 20. The term “Molecular modeling” expanded over the last decades from a tool to visualize three- dimensional structures and to simulate , predict and analyze the properties and the behavior of the molecules on an atomic level to data mining and platform to organize many compounds and their properties into database and to perform virtual drug screening via 3D database screening for novel drug compounds . 13 April 2020 Molecular modeling
- 21. Molecular mechanics refers to the use of classical mechanics to model the geometry and motions of molecules. Molecular mechanics methods are based on the following principles: 1) Nuclei and electrons are lumped into atom-like particles. 2) Atom-like particles are spherical and have a net charge. 3) Interactions are based on springs and classical potentials. 4) Interactions must be preassigned to specific sets of atoms. 5)Interactions determine the spatial distribution of atom-like particles and their energies. Molecular mechanics
- 22. Structure-based library screening 13 April 2020 What do we need: 1) Compounds libraries 2) Protein target 3) Binding site in the protein 4) Docking: generate different (many) possible conformations of the compounds in the binding site 5)Scoring: evaluate the strength of the protein/ligand interactions (score). 6)Select preferred ligands to propose a list of prioritized compounds for experimental screening.
- 23. Drug Targets Molecule or structure within the organism linked to a particular disease, whose activity can be modified by a drug.
- 24. J. Drews Science 287, 1960 -1964 (2000) P 1ub 3li Ash pe rid l 2b 0y 2A 0AAS Currently used drug targets
- 25. ▪ unmet medical need; new diseases (Corona Virus, Swine flu; AIDS, Alzheimer’s; obesity); low efficacy (dementia, cancer); side effects (antidepressants, antipsychotics) ▪ downstream health costs; (Alzheimer’s; spinal injury) ▪ cost of therapy; (Interleukins) ▪ sustain industrial activity; pharmaceutical industry employs thousands and makes a massive contribution to overseas earnings); patent expiry ▪ Drug resistance: Why are new drugs needed?
- 26. 10,000 Drug Candidates 1 Drug Molecule Valid Biomedical Hypothesis? Complexity of Drug Discovery patentable non-teratogenic Finding a Molecule that Satisfies Multiple Criteria 13 April 2020
- 27. Drug Discovery & Development Identify disease Isolate protein involved in disease (2-5 years) Preclinical testing (1-3 years) Formulation Human clinical trials (2-10 years) Find a drug effective against disease protein (2-5 years) Scale-up FDA approval (2-3 years)
- 28. Modern drug discovery process Target identification Target validation Lead Lead identification optimization Preclinical phase Drug discovery 2-5 years •Drug discovery is an expensive process involving high R & D cost and extensive clinical testing • A typical development time is estimated to be 10-25 years. •Costs an average of 1000 to 1500 million U.S. dollars per drug 6-9 years
- 29. Technology is impacting this process Identify disease Isolate protein Find drug Preclinical testing GENOMICS, PROTEOMICS & BIOPHARM. Potentially producing many more targets and “personalized” targets HIGH THROUGHPUT SCREENING Screening up to 100,000 compounds a day for activity against a target protein VIRTUAL SCREENING Using a computer to predict activity COMBINATORIAL CHEMISTRY Rapidly producing vast numbers of compounds MOLECULAR MODELING Computer graphics & models help improve activity IN VITRO & IN SILICO ADME MODELS 13 ATpirsil s20u2e0 and computer models begin to replace animal testing
- 30. Drug discovery technologies ▪ Target identification ▪ Genomics, gene expression profiling and proteomics ▪ Target Validation ▪ Gene knock-out, inhibition assay ▪ Lead Identification ▪ High throughput screening, fragment based screening, combinatorial libraries ▪ Lead Optimization ▪ Medicinal chemistry driven optimization, X-ray crystallography, QSAR, ADME profiling (bioavailability) ▪ Pre Clinical Phase ▪ Pharmacodynamics (PD), Pharmacokinetics (PK), ADME, and toxicity testing through animals ▪ Clinical Phase 13 April ▪ 20 H 20 uman trials
- 31. Drug Targets ▪ Enzyme – inhibitors ▪ Receptors - agonists or antagonists ▪ Ion channel – blockers ▪ Transporter –inhibitors ▪ DNA - blocker This information is used by bio-informaticians to narrow the search in the groups 13 April 2020
- 32. 13 April 2020
- 33. What is CADD????? 13 April 2020 Computational Chemistry/CADD is the chemistry whose major goals are to create efficient mathematical approximations and computer programs that calculate the properties of future drug molecules and thus helping in the process of drug design and discovery.
- 34. Why CADD…? 13 April 2020 Drug Discovery today are facing a serious challenge because of the increased cost and enormous amount of time taken to discover a new drug, and also because of rigorous competition amongst different pharmaceutical companies
- 35. 13 April 2020
- 36. Molecular Docking L R ❖ Docking is the identification of the low-energy binding modes of a small molecule or ligand within the active site of a macromolecule, or receptor, whose structure is known. ❖ Docking is the computational determination of binding affinity between molecules (protein structure and ligand). ❖ Given a protein and a ligand find out the binding free energy of the complex formed by docking them. L R 13 April 2020
- 37. Why Modeling? 13 April 2020 ▪ Experimental determination of structure is still a time consuming and expensive process. ▪ Number of known sequences are more than number of known structures. ▪ Structure information is essential in understanding function.
- 38. Molecular Docking: classification Docking or Computer aided drug designing can be broadly classified ▪ Receptor based methods- make use of the structure of the target protein. ▪ Ligand based methods- based on the known inhibitors 13 April 2020
- 39. Receptor based methods 13 April 2020 ▪ Uses the 3D structure of the target receptor to search for the potential candidate compounds that can modulate the target function. ▪ These involve molecular docking of each compound in the chemical database into the binding site of the target and predicting the electrostatic fit between them. ▪ The compounds are ranked using an appropriate scoring function such that the scores correlate with the binding affinity. ▪ Receptor based method has been successfully applied in many targets
- 40. Ligand based strategy 13 April 2020 ▪ In the absence of the structural information of the target, ligand based method make use of the information provided by known inhibitors for the target receptor. ▪ Structures similar to the known inhibitors are identified from chemical databases by variety of methods, ▪ Some of the methods widely used are similarity and substructure searching, pharmacophore matching or 3D shape matching. ▪ Numerous successful applications of ligand based methods have been reported
- 41. Basic binding mechanism 13 April 2020 Complementarities between the ligand and the binding site: • Steric complementarities, i.e. the shape of the ligand is mirrored in the shape of the binding site. • Physicochemical complementarities
- 42. Categories of docking 13 April 2020 ▪ Protein-Protein Docking: Both molecules are rigid Interaction produces no change in conformation ▪ Protein-Ligand Docking: Ligand is flexible but the receptor protein is rigid Interaction produces conformational changes in ligand
- 43. Protein – Protein Docking ▪ Computational modelling of the quaternary structure of complexes formed by two or more interacting biological macromolecules. ▪ Protein–protein complexes are the most commonly attempted targets of such modelling, followed by protein– nucleic acid complexes. 13 April 2020
- 44. Protein - Ligand Docking Protein-ligand docking is to predict the position and orientation of a ligand (a small molecule) when it is bound to a protein receptor or enzyme 13 April 2020
- 45. What are Docking & Scoring? To place a ligand (small molecule) into the binding site of a receptor in the manners appropriate for optimal interactions with a receptor. To evaluate discriminate the ligand-receptor interactions in a way the experimentally observed mode from that may others and estimate the binding affinity 13 April 2020
- 46. Available Docking Programs 13 April 2020 ▪ Schrodinger ▪ Acelerys Pro ▪ GOLD ▪ DOCK ▪ MOE-Dock ▪ FlexX ▪ AutoDOCK ▪ FRED ▪ Hammerhead ▪ Argus Lab
- 47. Components of docking software 13 April 2020 Typically, protein-ligand docking software consist of two main binding components which work together: Search algorithm Generates a large number of poses of a molecule in the site Scoring function Calculates a score or binding affinity for a particular pose The binding affinity or a score representing the strength of binding
- 48. Docking Flow Chart using Autodock 13 April 2020
- 49. ▪ Assign charges ▪ Define rotatable bonds ▪ Rename aromatic carbons ▪ Write .pdbqt ligand file 13 April 2020 Ligand Preparation for Docking using Autodock Preparation of Protein using Autodock ▪ Add essential hydrogen's ▪ Load charges ▪ Remove Water Molecules ▪ Write .pdbqt protein file
- 50. 13 April 2020
- 51. 13 April 2020
- 52. Application of Molecular Docking in Modern Drug Discovery 13 April 2020 ▪ Determine the lowest free energy structures for the receptor - ligand complex ▪ Search database and rank hits for lead generation ▪ Calculate the differential binding of a ligand to two different macromolecular receptors ▪ Study the geometry of a particular complex ▪ Propose modification of a lead molecules to optimize potency or other properties de novo design for lead generation ▪ Library design ▪ Screening for the side effects that can be caused by the interactions with other proteins, like proteases, Cytochrome P450 and others can be done.
- 53. ▪ It is also possible to check the specificity of the potential drug against homologous proteins through docking. ▪ Docking is also a widely used tool in predicting protein-protein interactions. ▪ Knowledge of the molecular associations aids in understanding a variety of pathways taking place in the living and in revealing of the possible pharmacological targets. ▪ Docking-Based Virtual High Throughput Screening 13 April 2020
- 54. ▪ Less expensive than High Throughput Screening ▪ Faster than conventional screening ▪ Scanning a large number of potential drug like molecules in very less time. ▪ HTS itself is a trial and error approach but can be better complemented by virtual screening. 13 April 2020
- 55. Growing Evidence of Success…. !! 13 April 2020 Drug Target Disease Dorzolamide Carbonic anhydrase Diuretics Saquinavir HIV protease AIDS Relenza Neuraminidas e AIDS AG85, ag337, ag331 Thymidylate synthase Cancer
- 56. ✔ Discovery of Indinavir, the HIV protease inhibitor. ✔ Identification of Haloperidol as a lead compound in a structure-based design for non-peptide inhibitor of HIV. ✔ Carbonic Anhydrase (treatment of glaucoma) ✔ Renin (treatment of hypertension) ✔ Dyhrofolate reductase (antibacterial) ✔ Neuraminidase (antiviral) ✔ HIV-1 aspartic proteinase (anti-acquired
- 57. ✔ Trypanosomal 13 April 2020 glyceraldehyde-3-phosphate dehydrogenase parasitic) ✔ Thymidylate synthase and purine nucleoside phosphorylase ✔ Collagenase (Rheumatoid and Osteoarthritis) ✔ Phospholipase A2 (anti inflammatory) ✔ Glycogen phosphorylase (treatment of diabetes mellitus)
- 58. ▪ Molecular docking give the promising effect on identification and optimization in modern drug discovery ▪ The combination of the chemical information of natural products with docking-based virtual screening will play an important role in drug discovery in the post-genomic era as more and more new potential targets are emerging from the functional genomic studies. ▪ Docking-based virtual screening lead to much higher hit rate than traditional screening methods (e.g., HTS) 13 April 2020 Summary of CADD
- 59. ▪ Docking method provides an opportunity for the designing of active compounds. ▪ However, it has to be emphasized that docking-based virtual screening is not the replacement of the actual experimental fact, these two methods are highly screening. ▪ As a matter of
- 60. Future Directions ▪ Pharmaceutical history indicated that natural products provided a large number of drugs to the market. But, even for the currently used drug targets, available natural products have not been tested completely. ▪ Computational medicinal methods, can contribute its unique role in achieving the task of examining the interaction of all existing natural products with all possible targets.