Solvent accessible surface area-based hot-spot detection methods for protein-protein and protein-nucleic acid interfaces

J Chem Inf Model. 2015 May 26;55(5):1077-86. doi: 10.1021/ci500760m. Epub 2015 Apr 17.


Due to the importance of hot-spots (HS) detection and the efficiency of computational methodologies, several HS detecting approaches have been developed. The current paper presents new models to predict HS for protein-protein and protein-nucleic acid interactions with better statistics compared with the ones currently reported in literature. These models are based on solvent accessible surface area (SASA) and genetic conservation features subjected to simple Bayes networks (protein-protein systems) and a more complex multi-objective genetic algorithm-support vector machine algorithms (protein-nucleic acid systems). The best models for these interactions have been implemented in two free Web tools.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • DNA / chemistry
  • DNA / metabolism*
  • Internet
  • Models, Molecular
  • Nucleic Acid Conformation
  • Protein Binding
  • Protein Conformation
  • Proteins / chemistry
  • Proteins / metabolism*
  • RNA / chemistry
  • RNA / metabolism*
  • Solvents / chemistry*
  • Support Vector Machine
  • Surface Properties


  • Proteins
  • Solvents
  • RNA
  • DNA