In-silico Drug designing

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Drug designing is a process used in biopharmaceutical industry to discover and develop new drug compounds.
Variety of computational methods are used to identify novel compounds ,design compounds for selectivity and safety.
Structure-based drug design, ligand-based drug design , homology based methods are used depending on how much information is available about drug targets and potential drug compounds.

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In-silico Drug designing

  1. 1. Vikas Sinhmar 2K9/BT/8028
  2. 2. Various sectors of IBI:
  3. 3. CONTENTS:  Drug designing  Tuberculosis - an overview  Target Identification  Target Validation  Structure Retrieval  Structure Validation  Final Model  Active Site Identification  Lead Identification
  4. 4.  Lead Insertion In Active Site  Development Of Lead In Active Site  Docking  Proposal to Final Molecule  Bibliography
  5. 5. Drug Designing: Drug designing is a process used in biopharmaceutical industry to discover and develop new drug compounds.  Variety of computational methods are used to identify novel compounds ,design compounds for selectivity and safety. Structure-based drug design, ligand-based drug design , homology based methods are used depending on how much information is available about drug targets and potential drug compounds.
  6. 6. Tuberculosis:  Tuberculosis is a infectious disease caused by various strains of mycobacteria ,usually mycobacterium tuberculosis.  Tuberculosis typically attacks the lungs , but can also affect other parts of the body.  It is spread through the air when the people who have an active TB infection cough , sneeze or otherwise transmit their saliva through air.
  7. 7. Chest X-ray:infetion in lungs
  8. 8. Symptoms of active TB:  Chronic cough  Fever  Night Sweats  Blood-tinged sputum  Unusual weight loss
  9. 9. TARGET IDENTIFICATION:  A “DRUG TARGET” is a key molecule involved in a particular metabolic and signaling pathway that is specific to disease condition and pathology , or to the infectivity or survival of a microbial pathogen.  Some steps are involved:  search for all the molecules ,enzymes and proteins involved in disease. Found all these sequence on :http//www.ncbi.nlm.nih.gov Got the sequences in FASTA format
  10. 10. TARGET VALIDATION: Perform the protein blast for all the genes/proteins w.r.t homosapiens . Select the least matching molecule in human and again perform the BLAST now in protein(sub-heading) category. As the query sequence matched best with Rv0554 , so we selected our target molecule and its structure can be obtained from RCSB(The Research Collaboratory for Structural Bioinformatics) protein data bank.
  11. 11. BLAST against homo-sapiens
  12. 12. Structure of Rv0554 on spdbv:
  13. 13. STRUCTURE RETRIVAL: Homology modeling using software modeller 3 files of different format were made of extension .atm, .ali, .py Final five models were obtained.
  14. 14. STRUCTURE VALIDATION:  Five best models were ready .  We viewed these models in SPDB viewer software to select the best model .we analyzed all models in the structure analysis and verification server.  All these five models were prochecked.  Upload pdb file then procheck.  Pdb file with least warning selected.
  15. 15. FINAL MODEL/STRUCTURE VALIDATION:
  16. 16. LEAD IDENIFICATION:  By using the software ligsite buliding pocket sites were created for the resulting molecule.
  17. 17. DEVELOPMENT OF LEAD TO ACTIVE SITE:  Software named LIGBUILDER used for development of lead to active site.  Best hex file(pocket file made by software hex) and file with extracted heat atoms .  Pocket command pocket(space)pocket.index grow Process
  18. 18. DOCKING: The basic assumption underlying in-silico(SBDD) based Drug designing is that a good ligand molecule bind tightly to its target. Hence ,these ligand molecules are analyzed for their binding affinity . The molecule having maximum negative value of free energy and minimum root mean square value is selected. This will be done by a software AUTODOCK.
  19. 19. Ligand before and after docking
  20. 20. 3-D structure in SPDB viewer
  21. 21. BIOSAFETY:MOLSOFT LLC
  22. 22. PROPOSAL FOR FINAL MOLECULE:  PASS(Prediction of activity spectra for substance), this online tool predict over 3500 kinds of biological activity including pharmacological effect, mechanism of action , toxic and adverse effects, interaction with metabolic enzymes and transporters , influence on gene expression etc.  Ligand possesses all the properties predicted by Lipinski’s rule of five and ability to solublised in the body & the drug likeness is 0.31 , which indicates , it is very much similar to know drug , hence supporting it to be as prospective drug.
  23. 23. BIBLOGRAPHY:  SITE ACCESSED *RCSB PDB-www.pdb.org/ *LIGSITEcsc – projects.biotec.tu-dresden.de/pocket/ *NCBI www.ncbi.nlm.nih.gov/ *PubMed.home-NCBI www.ncbi.nlm.nih.gov>NCBI>literature *SAVes-NIH MBI Laboratory for Structural Genomics And Proteomics *nihserver.mbi.ucla.edu/SAVES/Server
  24. 24. SOTWARES USED: *Modellar9v8 *Procheck *Ligsite *Auto dock tools 1.5.4 *Python 2.5 *Ligbuilderv1.2 *Hex6.3 *Spdb-viewer *Marvin-sketch *OpenBabel GUI *Mol Inspiration *Molsoft LLC *PASS (Prediction of Activity Spectra for Substances)

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