Minimalistic predictor of protein binding energy: Contribution of solvation factor to protein binding

Jeong Mo Choi, Adrian W.R. Serohijos, Sean Murphy, Dennis Lucarelli, Leo L. Lofranco, Andrew Feldman, Eugene I. Shakhnovich

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


It has long been known that solvation plays an important role in protein-protein interactions. Here, we use a minimalistic solvation-based model for predicting protein binding energy to estimate quantitatively the contribution of the solvation factor in protein binding. The factor is described by a simple linear combination of buried surface areas according to amino-acid types. Even without structural optimization, our minimalistic model demonstrates a predictive power comparable to more complex methods, making the proposed approach the basis for high throughput applications. Application of the model to a proteomic database shows that receptor-substrate complexes involved in signaling have lower affinities than enzyme-inhibitor and antibody-antigen complexes, and they differ by chemical compositions on interfaces. Also, we found that protein complexes with components that come from the same genes generally have lower affinities than complexes formed by proteins from different genes, but in this case the difference originates from different interface areas. The model was implemented in the software PYTHON, and the source code can be found on the Shakhnovich group webpage:

Original languageEnglish (US)
Pages (from-to)795-798
Number of pages4
JournalBiophysical journal
Issue number4
StatePublished - Feb 17 2015

ASJC Scopus subject areas

  • Biophysics


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