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Presentation of Recent Trends in Computer-aided Drug Discovery By Alexander Tropsha

Presentation of Recent Trends in Computer-aided Drug Discovery By Alexander Tropsha. Current Opinion in Drug Discovery & Development, 2000. Nancy Baker SILS Bioinformatics Seminar January 21, 2004. Terminology Overview.

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Presentation of Recent Trends in Computer-aided Drug Discovery By Alexander Tropsha

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  1. Presentation of Recent Trends in Computer-aided Drug DiscoveryBy Alexander Tropsha Current Opinion in Drug Discovery & Development, 2000 Nancy Baker SILS Bioinformatics Seminar January 21, 2004

  2. Terminology Overview • “ics” : genetics, genomics, proteomics, bioinformatics, chemoinformatics • Modifiers • Structural • Functional • Pharmaco • Informatics – general scientific discipline dealing with storage, analysis, and retrieval of information

  3. Genetics Review DNA: TACGCTTCCGGATTCAA transcription RNA: AUGCGAAGGCCUAAGUU translation Amino Acids: PIRLMQTS Protein

  4. Overview Continued –A simple example Protein Small molecule drug

  5. Overview Continued –A simple example Protein Small molecule drug Protein Protein disabled … disease cured

  6. Chemoinformatics Bioinformatics Protein Small molecule drug • Large databases • Large databases

  7. Size of databases • Millions of entries in databases • CAS : 23 million • GeneBank : 5 million • Total number of drugs worldwide: 60,000 • Fewer than 500 characterized molecular targets • Potential targets : 5,000-10,000

  8. Some Numbers • Millions of entries in databases • CAS : 23 million • GeneBank : 5 million • Total number of drugs worldwide: 60,000 • Fewer than 500 characterized molecular targets • Potential targets : 5,000-10,000 Lots of stuff – not much information.

  9. Chemoinformatics Bioinformatics Protein Small molecule drug • Large databases • Not all can be drugs • Large databases • Not all can be drug targets

  10. Chemoinformatics Bioinformatics Protein Small molecule drug • Large databases • Not all can be drugs • Opportunity for data mining techniques • Large databases • Not all can be drug targets • Opportunity for data mining techniques

  11. Trends in Chemoinformatics • New methods need to establish QSAR for thousands of molecules • Database mining and pharmacophore searching techniques • Non-linear analytical methods applicable to large databases • Design of new molecules with drug-like properties rather than mere high-affinity ligands for existing targets.

  12. Trends in Bioinformatics • Traditional: sequence to function • New thought: structure to function. (Same structure – different sequences; Structure more conserved than sequence.)

  13. Vision: Integration of Chemoinformatics and Bioinformatics • CADD: computer-aided drug discovery (instead of computer-aided drug design) • “Start with a gene sequence and using computational procedures design a molecule capable of affecting the activity of this gene or its product”

  14. Questions? • Once a scientist find thousands of potentially interacting molecules/proteins … then what? • Proof of concept?

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