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Ontomine Scaffold Hop

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Ontomine, a US Patent pending software algorithm is used to search for novel non-nucleoside reverse transcriptase inhibitors of HIV.

An sdf database of about 900,000 small molecules from pubchem is screened using information derived from 4 well known inhibitors.

It is shown that the results are novel, highly accurate with reference to known biological activity from assays and that the method is better than docking.

Ontomine based scaffold hopping identifies diverse molecules starting with a few known drugs and can be used instead of OR alongside docking methodologies.

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Ontomine Scaffold Hop

  1. 1. Scaffold Hopping using ONTOMINE TM
  2. 2. Scaffold Hopping: Define <ul><li>It’s a process of designing small molecules against </li></ul><ul><li>Drug Targets </li></ul><ul><li>Bio-process/Pathways </li></ul><ul><li>Organism Micro biology </li></ul><ul><li>Therapeutic indication/disease or phenotype </li></ul><ul><li>The goal of scaffold Hopping is that to find chemical patterns representative of NNRT inhibitors and search for potential NNRTI’s in a large database with sufficiently distinct scaffolds and </li></ul><ul><li>should be diverse and patentable. Our Insilico approach is satisfying the above criteria successfully, </li></ul><ul><li>Some of the characteristics that we looks off on the resultant scaffolds are. </li></ul><ul><li>The molecules should have minimum Drug targets. </li></ul><ul><li>It’s should be non-toxic. </li></ul><ul><li>It’s should not be promiscuous </li></ul><ul><li>It’s should have good Physico chemical (ADME) properties. </li></ul>
  3. 3. <ul><li>Scaffold Hopping-Pattern Development Using Ontomine </li></ul><ul><li>Data in Hand and Method:- </li></ul><ul><li>Training Set : (4 known NNRTI Drugs) </li></ul><ul><li>[Delavirdine, Etravirine, Efavirenz, Nevirapine] </li></ul><ul><li>2) Test Set : 1 million molecules from Pubchem {Having </li></ul><ul><li>potential bioactivity profile reported in Pubchem and </li></ul><ul><li>Pubmed } </li></ul><ul><li>3) Scaffold Hopping using Ontomine </li></ul><ul><li>4) Validation of Ontomine Hits: NIAID@NIH has Anti-HIV Cellular </li></ul><ul><li>and Anti-HIV enzyme assay Information. </li></ul>
  4. 5. Distribution of 3297 Categorized “High, Medium, Low” Ontomine Hits
  5. 6. Categorized distribution (High, Medium and Low) of 268 active compounds in a Bio-assay with respect to the 4 known NNRTI compounds
  6. 7. Computational ADMET using ONTOMINE TM
  7. 8. Development time and Expense factors in Drug Discovery The attrition rate is unacceptably high. Only 1 out of 12 drugs entering clinical trials becomes a new drug Lacking appropriate bioavailability, exhibit poor pharmacokinetics or cause adverse events With the increasing pressure on reducing animal experiments, Computational toxicology and ADME have an increasingly important role to play. Why ADME-Tox Prediction? Ontomine (vHTS & ADMET)
  8. 9. ADMET Physicochemical Property Prediction Scaffold Hopping Bio Assay Screening Active Compound With Good ADMET Features Ontomine ADMET
  9. 10. <ul><li>The software holds potential to perform high-throughput screening of high dimension chemical compound database on the basis of ADME (Adsorption, Distribution, Metabolism and Excretion) properties for the following predictive values: </li></ul><ul><li>logS </li></ul><ul><li>logP </li></ul><ul><li>logD </li></ul><ul><li>pKa </li></ul>OntoMine ADME predicts physicochemical properties of organic/inorganic compounds at 25 degree C and neutral pH at present. Ontomine - ADME Predicted Physicochemical Properties Test Mol - Aspirin
  10. 11. Few Example Predictions Aspirin: Well known analgesic drug Experimental Values Ontomine-ADME Prediction Solubility: Soluble Solubility: Soluble (logS=-1.42 LogP: 1.4 LogP: 1.51 Pka: 3.48 Pka: 3.48 Camphor: Chemical used in perfume Experimental values Ontomine-ADME Prediction Solubility: Soluble Solubility: Soluble (logS=-1.42 LogS: -1.98 LogP: 1.51 LogP: 2.38 Pka: 3.48
  11. 12. Few More... Name Exp_logS Pred_logS Exp_logP Pred_logP Exp_pKa Pred_pKa Aspirin -1.59 -1.41 1.19 1.51 3.49 3.45 (Acidic pKa) Camphor -1.98 -2.55 2.38 2.86 No pKa Ciprofloxacin -1.04 -0.46 0.28 0.58 6.09 5.33 (Acidic pKa), 7.7 (Base pKa) Rifampicin -2.77 -3.56 4.24 2.55 6.74 (Acid pKa), 5.65 (Base pKa) Cloroquine -4.48 -5.16 4.63 4.47 10.1 10.1 (Base pKa)
  12. 13. ADME Based Lead Optimization A Case Study - Curcumin
  13. 14. Principal curcuminoid of the popular Indian spice turmeric Induce apoptosis in cancer cells Functional groups characteristic of curcumin scaffold are aromatic ring systems specifically polyphenols that are connected by two α,β-unsaturated carbonyl groups Curcumin – A Case Study Curcumin Water Insoluble Poor Bioavailability Limiting its medicinal use for humans when it is taken orally or injected
  14. 15. Obtaining Curcumin analogues Searching Curcumin – structurally similar molecules in Pubchem retrieves 15697 hits (Searching Criteria : More than 80% similarity) Finding solubility using Ontomine-ADME Molecules are grouped based on solubility level Highly Soluble – 395 Soluble – 3555 Partially Soluble – 6933 Insoluble – 4813
  15. 16. Curcumin 2D Structural Pattern Solubility Level Confidence Level Ontomine-ADME
  16. 17. Bioactivity Studies on curcumin results Tissue-nonspecific alkaline phosphatase precursor Inhibitor Analgesics,NonNarcotic Anti-Rheumatic Agents Anti-InflammatoryAgents,NonSteroidal Enzyme Inhibitors Anti-Neoplastic Agents Analogues are explored for Anti-Inflammatory and Anti-Neoplastic activities (Key features of Curcumin) Analogues are checked for Toxicity using Ontomine-Tox
  17. 18. High Confident Hits with Better ADME Features
  18. 19. Analogue with Priority One Ranking Analogues based on ADME Features, Bioactivity, and Toxicity Mol ID: 16722486 Solubility: Soluble logP: 4.56 Bioactivity: Anti-InflammatoryAgents,NonSteroidal, Anti-Neoplastic Agents Toxicity: No toxicity Predicted Differ from Curcumin: Added two COOH groups SMILE: O=C(O)C=2C=C(C=CC(=O)CC(=O)C=CC=1C=C(OC)C(O)=C(C=1)C(=O)O)C=C(OC)C=2(O)
  19. 20. Thank You

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