Journal of Computer-Aided Molecular Design

, Volume 10, Issue 5, pp 427–440 | Cite as

Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities

  • Ajay N. Jain
Research Papers


Exploitation of protein structures for potential drug leads by molecular docking is critically dependent on methods for scoring putative protein-ligand interactions. An ideal function for scoring must exhibit predictive accuracy and high computational speed, and must be tolerant of variations in the relative protein-ligand molecular alignment and conformation. This paper describes the development of an empirically derived scoring function, based on the binding affinities of protein-ligand complexes coupled with their crystallographically determined structures. The function's primary terms involve hydrophobic and polar complementarity, with additional terms for entropic and solvation effects. The issue of alignment/conformation dependence was solved by constructing a continuous differentiable nonlinear function with the requirement that maxima in ligand conformation/alignment space corresponded closely to crystallographically determined structures. The expected error in the predicted affinity based on cross-validation was 1.0 log unit. The function is sufficiently fast and accurate to serve as the objective function of a molecular-docking search engine. The function is particularly well suited to the docking problem, since it has spatially narrow maxima that are broadly accessible via gradient descent.


Molecular docking Protein-ligand interaction Scoring function 


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Copyright information

© ESCOM Science Publishers B.V 1996

Authors and Affiliations

  • Ajay N. Jain
    • 1
  1. 1.Arris Pharmaceutical CorporationSan FranciscoU.S.A.

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