Workshop031211
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Presentation on March 12, 2011 at the Skaggs School of Pharmacy and Pharmaceutical Sciences (UCSD) during the Workshop in Allosteric and Orthosteric Ligands in Drug Action

Presentation on March 12, 2011 at the Skaggs School of Pharmacy and Pharmaceutical Sciences (UCSD) during the Workshop in Allosteric and Orthosteric Ligands in Drug Action

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  • P distance to environmental boundary; Pi Di and alphai D distance to central atom alpha direction to central atom
  • 3,996 proteins in TB proteome 749 solved structures in the PDB, representing a total of 284 proteins (7.2% coverage) ModBase contains homology models for entire TB proteome 1,446 ‘high quality’ homology models were added to the data set Structural coverage increased to 43.8% Retained only those models with a model score of > 0.7 and a Modpipe quality score of > 1.1 (2818 models). There were multiple models per protein. For each TB protein, chose the model with the best model score, and if they were equal, chose the model with the best Modpipe quality score (1703 models). However, 251 (+6) models were removed since they correspond to TB proteins that already have solved structures. 1446 models remained) Score for the reliability of a Model, derived from statistical potentials (F. Melo, R. Sanchez, A. Sali,2001 PDF ). A model is predicted to be good when the model score is higher than a pre-specified cutoff (0.7). A reliable model has a probability of the correct fold that is larger than 95%. A fold is correct when at least 30% of its Calpha atoms superpose within 3.5A of their correct positions. The ModPipe Protein Quality Score is a composite score comprising sequence identity to the template, coverage , and the three individual scores evalue , z-Dope and GA341 . We consider a MPQS of >1.1 as reliable
  • (nutraceuticals excluded)
  • Multi-target therapy may be more effective than single-target therapy to treat infectious diseases Most of the proteins listed are potential novel drug targets for the development of efficient anti-tuberculosis chemotherapeutics. GSMN-TB : Genome Scale Metabolic Reaction Network of M.tb (http://sysbio/sbs.surrey.ac.uk/tb) 849 reactions, 739 metabolites, 726 genes Can optimize the model for in vivo growth Carry out multiple gene inhibition and compute the maximal theoretical growth rate (if close to zero, that combination of genes is essential for growth)

Workshop031211 Workshop031211 Presentation Transcript

  • Mining databases for understanding target recognition Philip E. Bourne 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
  • Mining databases for understanding target recognition – well the PDB anyway Philip E. Bourne 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
  • “ If you remember 3 things from a lecture a week later it was a good lecture” from Ten Simple Rules for Making Good Oral Presentations PLoS Comp Biol 2007 3(4): e77 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
  • 1. The PDB services almost 200,000 scientists per month, but you are special – take advantage of this offer 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
  • “ I want to review all multimeric quaternary complexes in the PDB that may be of interest in the understanding of allosteric mechanisms exhibited by such complexes” Jean-Pierre Changeux
  • 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
  • Its not as easy as it sounds.. Group II Chaperonins - Open and Closed Conformation
    • all chains are sequence identical within one chaperone and 95% similar between the two PDB entries
    3KFK 3KFB
  • Identify biological relatedness even if quaternary structures show variability
  • Methodology
    • Take all chains from a PDB95 sequence cluster
    • Fetch the (1st) Biological Assembly (BA) for the PDB ID of the chain
    • Align the whole BAs against each other using CE-CP
    Prlic et al 2010 Bioinformatics 10.1093/bioinformatics/btq572
  • Our scores allow to pick out unusual ones: 1Y01 Z-score: 6.23 Coverage 1:22 Coverage 2:59 TM-Score: 0.56 4HHB (self) Z-score: 8.49 Coverage 1:100 Coverage 2:100 TM-Score: 1.0 2W72 Distal site hemoglobin mutant AHSP bound to Fe(II) alpha-hemoglobin Z-score: 7.02 Coverage 1:76 Coverage 2:100 TM-Score: 0.98
  • Long Term Goal
    • Characterize all quaternary structures found in the PDB according to level of structural similarity
    • Where structural similarity exists classify according to ligands bound
    • Characterize those with drug binding sites at the subunit boundaries
    • Better characterize allosteric mechanisms associated with quaternary structures
    03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
  • 2. We have research tools, not part of the PDB (yet), which are important for discovering and characterizing protein receptors 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
    • Initially assign C  atom with a value that is the distance to the environmental boundary
    • Update the value with those of surrounding C  atoms dependent on distances and orientation – atoms within a 10A radius define i
    • Conceptually similar to hydrophobicity
    • or electrostatic potential that is
    • dependant on both global and local
    • environments
    Characterization of the Ligand Binding Site - The Geometric Potential Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl 4):S9
  • Discrimination Power of the Geometric Potential
    • Geometric potential can distinguish binding and non-binding sites
    100 0 Geometric Potential Scale Xie and Bourne 2007 BMC Bioinformatics, 8(Suppl 4):S9
  • Search for Similar Ligand Binding Sites L E R V K D L L E R V K D L Structure A Structure B
    • Build an associated graph from the graph representations of two structures being compared. Each of the nodes is assigned with a weight from the similarity matrix
    • The maximum-weight clique corresponds to the optimum alignment of the two structures
    Xie and Bourne 2008 PNAS , 105(14) 5441 http://funsite.sdsc.edu
  • 3. We can undertake high-throughput hypothesis generation for protein-drug interactions on a proteome-wide scale 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
  • The TB-Drugome
    • Determine the TB structural proteome
    • Determine all known drug binding sites from the PDB
    • Determine which of the sites found in 2 exist in 1
    • Call the result the TB-drugome
    Kinnings et al 2010 PLoS Comp Biol 6(11): e1000976 Workshop in Allosteric and Orthosteric Ligands in Drug Action 03/12/11
  • 1. Determine the TB Structural Proteome
    • High quality homology models from ModBase (http://modbase.compbio.ucsf.edu) increase structural coverage from 7.1% to 43.3%
    284 1, 446 3, 996 2, 266 TB proteome homology models solved structures 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
  • 2. Determine all Known Drug Binding Sites in the PDB
    • Searched the PDB for protein crystal structures bound with FDA-approved drugs
    • 268 drugs bound in a total of 931 binding sites
    No. of drug binding sites Methotrexate Chenodiol Alitretinoin Conjugated estrogens Darunavir Acarbose 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action
  • Map 2 onto 1 – The TB-Drugome http://funsite.sdsc.edu/drugome/TB/ Similarities between the binding sites of M.tb proteins (blue), and binding sites containing approved drugs (red).
  • From a Drug Repositioning Perspective
    • Similarities between drug binding sites and TB proteins are found for 61/268 drugs
    • 41 of these drugs could potentially inhibit more than one TB protein
    No. of potential TB targets raloxifene alitretinoin conjugated estrogens & methotrexate ritonavir testosterone levothyroxine chenodiol 03/12/11
  • Top 5 Most Highly Connected Drugs 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action Drug Intended targets Indications No. of connections TB proteins levothyroxine transthyretin, thyroid hormone receptor α & β -1, thyroxine-binding globulin, mu-crystallin homolog, serum albumin hypothyroidism, goiter, chronic lymphocytic thyroiditis, myxedema coma, stupor 14 adenylyl cyclase, argR , bioD, CRP/FNR trans. reg ., ethR , glbN , glbO, kasB , lrpA , nusA , prrA , secA1 , thyX , trans. reg. protein alitretinoin retinoic acid receptor RXR- α , β & γ , retinoic acid receptor α , β & γ -1&2, cellular retinoic acid-binding protein 1&2 cutaneous lesions in patients with Kaposi's sarcoma 13 adenylyl cyclase, aroG , bioD, bpoC, CRP/FNR trans. reg. , cyp125 , embR , glbN , inhA , lppX , nusA , pknE , purN conjugated estrogens estrogen receptor menopausal vasomotor symptoms, osteoporosis, hypoestrogenism, primary ovarian failure 10 acetylglutamate kinase, adenylyl cyclase, bphD , CRP/FNR trans. reg. , cyp121 , cysM, inhA , mscL , pknB , sigC methotrexate dihydrofolate reductase, serum albumin gestational choriocarcinoma, chorioadenoma destruens, hydatidiform mole, severe psoriasis, rheumatoid arthritis 10 acetylglutamate kinase, aroF , cmaA2 , CRP/FNR trans. reg. , cyp121 , cyp51 , lpd , mmaA4 , panC , usp raloxifene estrogen receptor, estrogen receptor β osteoporosis in post-menopausal women 9 adenylyl cyclase, CRP/FNR trans. reg., deoD, inhA, pknB , pknE , Rv1347c , secA1, sigC
  • Acknowledgements Funding Agencies: NSF, NIGMS, DOE, NLM, NCI, NCRR, NIBIB, NINDS, NIDDK 03/12/11 Workshop in Allosteric and Orthosteric Ligands in Drug Action