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The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
The Many Roles of Computation in Drug Discovery
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The Many Roles of Computation in Drug Discovery

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Overview of computer aided drug designing. …

Overview of computer aided drug designing.
Clinical and Pre-clinical trials.
Prediction of properties and Drug-likeness.
Advanced treatments of protein-ligand binding.
Summary

Published in: Education, Business
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  • 1. 1
  • 2. Outline • Overview of computer aided drug designing. • Clinical and Pre-clinical trials. • Prediction of properties and Drug-likeness. • Advanced treatments of protein-ligand binding. • Summary 2
  • 3. Computer aided drug designing. • Drug design with the help of computers may be used at any of the following stages of drug discovery: – hit identification using virtual screening (structure- or ligand-based design) – hit-to-lead optimization of affinity and selectivity (structure-based design, QSAR, etc.) – lead optimization optimization of other pharmaceutical properties while maintaining affinity 3 http://en.wikipedia.org/wiki/Drug_design#Computer-aided_drug_design
  • 4. Computer aided drug designing. 4 • the classical project-collaboration approach between chemistry, biology and drug metabolism (ADME) groups in the 1990s • a much more automated world at the start of this millennium in which combinatorial chemistry (Combi-Chem), high-throughput screening and ADME studies are linked together in a streamlined fashion. ADMET in silico modeling towards Prediction Paradise?, Nature
  • 5. Computer aided drug designing. • In order to overcome the insufficient prediction of binding affinity calculated by recent scoring functions, the protein-ligand interaction and compound 3D structure information are used to analysis. For structure-based drug design, several post-screening analysis focusing on protein-ligand interaction has been developed for improving enrichment and effectively mining potential candidates: – Consensus scoring • Selecting candidates by voting of multiple scoring functions • May lose the relationship between protein-ligand structural information and scoring criterion – Geometric analysis • Comparing protein-ligand interactions by visually inspecting individual structures • Becoming intractable when the number of complexes to be analyzed increasing – Cluster analysis • Represent and cluster candidates according to protein-ligand 3D information • Needs meaningful representation of protein-ligand interactions. 5 http://en.wikipedia.org/wiki/Drug_design#Computer-aided_drug_design
  • 6. Clinical Trials • Sets of tests in medical research and drug development that generate safety and efficacy data • Only after satisfactory information has been gathered on the quality of the nonclinical safety, and health authority/ethics committee approval is granted • The most commonly performed clinical trials evaluate new drugs, medical devices (like a new catheter), biologics, psychological therapies, or other interventions. 6 http://en.wikipedia.org/wiki/Clinical_trial
  • 7. Clinical Trials • Clinical trial may be designed to do: – Assess the safety and effectiveness of a new medication or device on a specific kind of patient – Assess the safety and effectiveness of a different dose of a medication than is commonly used – Assess the safety and effectiveness of an already marketed medication or device for a new indication – Assess whether the new medication or device is more effective for the patient's condition than the already used ("the gold standard" or "standard therapy") – Compare the effectiveness in patients with a specific disease (e.g., device A vs. device B, therapy A vs. therapy B) http://en.wikipedia.org/wiki/Clinical_trial 7
  • 8. Clinical Trials • 5 different types – Prevention trials • find better ways to prevent disease in people (medicines, vitamins, vaccines, minerals, or lifestyle changes) – Screening trials • test the best way to detect certain diseases or health conditions. – Diagnostic trials • find better tests or procedures for diagnosing a particular disease or condition. – Treatment trials • test experimental treatments, new combinations of drugs, or new approaches to surgery or radiation therapy. – Quality of life trials • ways to improve comfort and the quality of life for individuals with a chronic illness. – Compassionate use trials • provide partially tested, unapproved therapeutics to a small number of patients who have no other realistic options. http://en.wikipedia.org/wiki/Clinical_trial 8
  • 9. Clinical Trials • Clinical trials involving new drugs are commonly classified into four phases. – Phase 0: Pharmacodynamics and Pharmacokinetics – Phase 1: Screening for safety – Phase 2: Establishing the testing protocol – Phase 3: Final testing – Phase 4: Post approval studies • Each phase has a different purpose and helps scientists answer a different question: • Before pharmaceutical companies start clinical trials on a drug, they conduct extensive preclinical studies. http://en.wikipedia.org/wiki/Clinical_trial 9
  • 10. Preclinical Trials • Before clinical trials, during which important feasibility, iterative testing and drug safety data is collected • To determine a product's ultimate safety profile – Pharmacodynamics (what the drug does to the body) (PD) – pharmacokinetics (what the body does to the drug) (PK) – ADME – toxicity testing through animal testing • Both in vitro and in vivo tests will be performed • Based on pre-clinical trials, No Observable Effect Levels (NOEL) on drugs are established, which are used to determine initial phase 1 clinical trial dosage levels on a mass API per mass patient basis. http://en.wikipedia.org/wiki/Pre-clinical_development 10
  • 11. Prediction of Properties and Drug-likeness • Credits and Thanks for raising the awareness on the properties and structural features – Lipinski, Murcko, co-workers at Pfizer and Vertex • Main Goal = Apply MADE early in pre clinical development to avoid late stage failures • Analyses of classes of compounds are informative • Avoidance of the extremes seems to be safe strategy The Many Roles of Computation in Drug Discovery, Science 11
  • 12. Prediction of Properties and Drug-likeness • Why? • Which? • How? • When? • What? – Predict – Tools 12
  • 13. Why computational ADME required? • Traditional drug designing is a Multi step Time consuming process. • Adverse pharmacokinetic properties were investigated in development stage. ADMET in silico modeling towards Prediction Paradise?, Nature 13
  • 14. • The rate at which biological screening data are obtained has dramatically increased • Combinatorial chemistry feeds these hit-finding machines • Increased the demands for absorption, distribution, metabolism, excretion and toxicity data early Why computational ADME required? • Attrition in the drug development • Early decision ADMET in silico modeling towards Prediction Paradise?, Nature 14
  • 15. Why computational ADME required? • The promising compound went over the line and was abandoned in the later stage due to its oral bioavailability of only 1%. Peptide like thrombin inhibitor The Many Roles of Computation in Drug Discovery, Science 15
  • 16. Which properties make drugs different from other chemicals? • Numerous studies • Influential one = LIPINSKI’s “Rule of Five” • Mol mass < 500 da • Calc octanol/water partition coefficient < 5 • H-bond donors <5 • H-bond acceptors <10 • Physicochemical and Structural Properties characteristic of a good drug The Many Roles of Computation in Drug Discovery, Science 16
  • 17. Which properties make drugs different from other chemicals? • These properties = Build ADME models == Property based design • Similar molecules =~= Similar ADME properties • Predict properties like – Lipophilicity – Solubility – Amount absorbed ADMET in silico modeling towards Prediction Paradise?, Nature 17
  • 18. How are ADMET data obtained? • Three ways – Automated in vitro assays – In silico selection of both the relevant assays and the compounds that go through them – Predictive models that can possibly replace in vitro or in vivo experiments • The predictions come from regression equations or neural networks • QikProp – Fast and executed for large libraries – Input is 3D structure – Output is profile of • Structural features (Surf Area and H bonding potentials) • ADME properties • Undesirable functionality • Primary metabolites • Comparison with other drugs The Many Roles of Computation in Drug Discovery, Science 18
  • 19. How are ADMET data obtained? • The two drugs approach hydrophobic and Hydrophilic extremes • Hydrophobic – Poor solubility – High serum protein binding – Good Cell permeability • The Opposite is true in case of hydrophilic compounds • This is responsible for the solubility vs. permeability struggle The Many Roles of Computation in Drug Discovery, Science 19
  • 20. When is ADMET data needed? Design of New compounds Need of properties Traditional or Combo Chemistry • Predictions are not perfect at this point. • series of molecules is focused around a lead and is further optimized towards a clinical candidate, more robust mechanistic models will be required. ADMET in silico modeling towards Prediction Paradise?, Nature 20
  • 21. What ADME properties do we want to predict? DOSAGE Amount DOSAGE Frequency Volume of Distribution Volume of Distribution ClearanceClearance AbsorptionAbsorption Oral bioavailability Oral bioavailability Half LifeHalf Life ADMET in silico modeling towards Prediction Paradise?, Nature 21
  • 22. What computational tools are used? Molecular Modeling • Protein Modeling that uses Quantum mechanical methods for interaction study • 3D structural info needed • No structure available – Homology modeling (related structures) – Pharmacophore modeling (superposition of known substrates) Data Modeling • QSAR and QSPR with biological and physicochemical data – search for correlations between a given property and a set of molecular and structural descriptors of the molecules in question • QSAR – Mol size – H bonding – simple multiple linear regression to modern MULTIVARIATE ANALYSIS techniques ADMET in silico modeling towards Prediction Paradise?, Nature 22
  • 23. What computational tools are used? ADMET in silico modeling towards Prediction Paradise?, Nature 23
  • 24. What computational tools are used? • UC – 781 is most hydrophobic. It is potent in vitro. It is seen as microbicide than oral drug. – Poor solubility and high serum binding • Long BB predictions are also interesting from standpoint of potential CNS penetration. – Beneficial for attack on HIV reservoirs – Concern CNS side effects The Many Roles of Computation in Drug Discovery, Science 24
  • 25. Prediction of Properties and Drug-likeness • Good predictive models for ADMET parameters depend crucially on – selecting the right mathematical approach – the right molecular descriptors for the particular ADMET endpoint – sufficiently large set of experimental data for the validation of the model • Several published ADME data sets are available for data modeling, but the quality of the data and the number of available training examples remain important issues. ADMET in silico modeling towards Prediction Paradise?, Nature 25
  • 26. Advanced treatments of protein-ligand binding. • For obtaining better accuracy and to match computing demands • Monte Carlo statistical mechanics or Molecular Dynamics simulations are applied – Classical force field is used – Sampling all degrees of freedom of complexes – Representation of water molecule in aqueous surroundings The Many Roles of Computation in Drug Discovery, Science 26
  • 27. Advanced treatments of protein-ligand binding. • Free Energy Perturbation and Thermodynamic Integration compute free energy changes. • Perturbations are made to convert one ligand to another using Thermodynamic cycles • Δ Δ Gb = Δ GX – ΔGY = Δ GF – ΔGC gives the difference in free energies of ligands binding X and Y • Two series of mutations are performed to convert X to Y unbound in water and complexed with biomolecule which yield Δ GF and ΔGC. • Same cycle can be performed with One inhibitor and 2 proteins The Many Roles of Computation in Drug Discovery, Science 27
  • 28. Advanced treatments of protein-ligand binding. • Inclusion of water makes the representation more realistic • water molecules that form hydrogen-bonded bridges between inhibitors and protein hosts are well illustrated • Water molecules form specific clathrate-like networks around nonpolar groups • Optimization of the water structure is becoming a more common part of inhibitor design • Other Strengths – rigor – extensive sampling – binding affinities. • remains difficult to handle large structural differences between ligands as in changing the core structure The Many Roles of Computation in Drug Discovery, Science 28
  • 29. Advanced treatments of protein-ligand binding. • Hybrid Methods – Linear response theory – free energy of interaction of a solute with its environment is given by one-half the electrostatic energy plus the van der Waals energy scaled by an empirical parameter – For binding a ligand to a protein, the differences in the interactions between the ligand in the unbound state and bound in the complex then provide an estimate of the free energy of binding. – Energy components are obtained from MC or MD simulations for inhibitors in water and for the protein-inhibitor complexes in water. • Advantages – absolute free energies of binding can be approximated – only simulations at the endpoints of a mutation are required – computing demands are reduced to a few hours per compound. – Easy to treat structurally diverse ligands – Better accuracy The Many Roles of Computation in Drug Discovery, Science 29
  • 30. 30 ADMET in silico modeling towards Prediction Paradise?, Nature SUMMARY
  • 31. References • William L. Jorgensen, et al., The Many Roles of Computation in Drug Discovery, Science 303, 1813 (2004); • Han van de Waterbeemd and Eric Gifford, ADMET in silico modeling towards Prediction Paradise?, Nature reviews/drugdisc, March 2003; • Wikipedia • The future of computation in drug discovery, By Wavefunction on Monday, November 28, 2011 • anchorquery.ccbb.pitt.edu/class/lecture.pdf • http://en.wikipedia.org/wiki/Pre-clinical_development • http://en.wikipedia.org/wiki/Clinical_trial • http://en.wikipedia.org/wiki/Drug_design#Computer- aided_drug_design 31

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