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Combinatorial computational method gives new picomolar ligands for a known enzyme

Combinatorial computational method gives new picomolar ligands for a known enzyme. Bartosz A. Grzybowski, Alexey V. Ishchenko, Chu-Young Kim, George Topalov, Robert Chapman, David W. Christianson, George M. Whitesides, and Eugene I. Shakhnovich. Outline.

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Combinatorial computational method gives new picomolar ligands for a known enzyme

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  1. Combinatorial computational method gives new picomolar ligands for a known enzyme Bartosz A. Grzybowski, Alexey V. Ishchenko, Chu-Young Kim, George Topalov, Robert Chapman, David W. Christianson, George M. Whitesides, and Eugene I. Shakhnovich

  2. Outline • Objective: Design a new method for generating and screening drug leads • CombiSMoG combines facets of combinatorial and rational drug design • Tested on human carbonic anhydrase II (HCA) • Knowledge base derived from 1,000 protein-ligand complexes in PDB • Verification • Two of the best compounds were synthesized and evaluated in vivo • X-crystallography showed agreement with predicted binding mode

  3. algorithm • Scoring function • Locates two atoms (on ligand and protein) closer than 5 Å • Contacts classified by atom types, frequency of occurrence • Ligands are generated from 100 common functional groups • Starting from a seed, program grows a ligand, evaluating after each iteration • If ligand has lower score than before, piece is rejected • Can generate 50,000 ligands/day

  4. algorithm • Seed = benzenesulfonamide (binds zinc in active site)

  5. Top compounds

  6. Verification of results • Two of top five compounds (enantiomers) were synthesized • R stereoisomer most potent HCA II inhibitor known (Kd = 30 pM) • X-ray crystal structure showed docking similar to predicted

  7. Verification • Binding constants (Kd) of other ligands also correlates with CombiSMoG score

  8. Conclusions • Study carried out under ideal circumstances • Large knowledge base • Known pharmacophore • CombiSMoG generated 100,000 ligands in 60 h • Simulations essentially correlate with experimental results

  9. Discussion • Would this program be as useful in the absence of a known pharmacophore? Without ample crystallographic knowledge? • What advantages come with having a specified set of building blocks?

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