Predicting protein-ligand binding affinities: a low scoring game?

P M Marsden, D Puvanendrampillai, John Blayney Owen Mitchell, R C Glen

Research output: Contribution to journalArticlepeer-review

48 Citations (Scopus)

Abstract

We have investigated the performance of five well known scoring functions in predicting the binding affinities of a diverse set of 205 protein-ligand complexes with known experimental binding constants, and also on subsets of mutually similar complexes. We have found that the overall performance of the scoring functions on the diverse set is disappointing, with none of the functions achieving r(2) values above 0.32 on the whole dataset. Performance on the subsets was mixed, with four of the five functions predicting fairly well the binding affinities of 35 proteinases, but none of the functions producing any useful correlation on a set of 38 aspartic proteinases. We consider two algorithms for producing consensus scoring functions, one based on a linear combination of scores from the five individual functions and the other on averaging the rankings produced by the five functions. We find that both algorithms produce consensus functions that generally perform slightly better than the best individual scoring function on a given dataset.

Original languageEnglish
Pages (from-to)3267-3273
Number of pages7
JournalOrganic & Biomolecular Chemistry
Volume2
Issue number22
DOIs
Publication statusPublished - 2004

Keywords

  • 3-DIMENSIONAL STRUCTURES
  • MOLECULAR DOCKING
  • FLEXIBLE DOCKING
  • COMPLEXES
  • DISCOVERY
  • DATABASE
  • RECEPTOR
  • SEARCH
  • VALIDATION
  • DESIGN

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