Literature DB >> 15244414

OptiDock: virtual HTS of combinatorial libraries by efficient sampling of binding modes in product space.

Dennis G Sprous1, David R Lowis, Joseph M Leonard, Trevor Heritage, Steven N Burkett, David S Baker, Robert D Clark.   

Abstract

Products from combinatorial libraries generally share a common core structure that can be exploited to improve the efficiency of virtual high-throughput screening (vHTS). In general, it is more efficient to find a method that scales with the total number of reagents (Sigma growth) rather with the number of products (Pi growth). The OptiDock methodology described herein entails selecting a diverse but representative subset of compounds that span the structural space encompassed by the full library. These compounds are docked individually using the FlexX program (Rarey, M.; Kramer, B.; Lengauer, T.; Klebe, G. J. Mol. Biol. 1995, 251, 470-489) to define distinct docking modes in terms of reference placements for combinatorial core atoms. Thereafter, substituents in R-cores (consisting of the core structure substituted at a single variation site) are docked, keeping the core atoms fixed at the coordinates dictated by each reference placement. Interaction energies are calculated for each docked R-core with respect to the target protein, and energies for whole compounds are calculated by finding the reference core placement for which the sum of corresponding R-core energies is most negative. The use of diverse whole compounds to define binding modes is a key advantage of the protocol over other combinatorial docking programs. As a result, OptiDock returns better-scoring conformers than does serially applied FlexX. OptiDock is also better able to find a viable docked pose for each library member than are other combinatorial approaches.

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Year:  2004        PMID: 15244414     DOI: 10.1021/cc034068x

Source DB:  PubMed          Journal:  J Comb Chem        ISSN: 1520-4766


  4 in total

1.  Surrogate docking: structure-based virtual screening at high throughput speed.

Authors:  Sukjoon Yoon; Andrew Smellie; David Hartsough; Anton Filikov
Journal:  J Comput Aided Mol Des       Date:  2005-11-16       Impact factor: 3.686

2.  Balancing focused combinatorial libraries based on multiple GPCR ligands.

Authors:  Farhad Soltanshahi; Tamsin E Mansley; Sun Choi; Robert D Clark
Journal:  J Comput Aided Mol Des       Date:  2006-10-13       Impact factor: 3.686

Review 3.  From laptop to benchtop to bedside: structure-based drug design on protein targets.

Authors:  Lu Chen; John K Morrow; Hoang T Tran; Sharangdhar S Phatak; Lei Du-Cuny; Shuxing Zhang
Journal:  Curr Pharm Des       Date:  2012       Impact factor: 3.116

4.  Combinatorial library-based design with Basis Products.

Authors:  Joe Zhongxiang Zhou; Shenghua Shi; Jim Na; Zhengwei Peng; Tom Thacher
Journal:  J Comput Aided Mol Des       Date:  2009-07-11       Impact factor: 3.686

  4 in total

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