Changes in the amino acids near binding sites can radically alter binding preferences.  Negatively charged amino acids replaced by positive ones, small amino acids changed to larger ones, or many subtler changes, can reject binding partners that might otherwise bind. This talk presents new algorithms that predict changes in steric and electrostatic characteristics that influence molecular recognition specificity.<br/><br/>Central to this approach is a volumetric representation of protein structure that mimics human intuition. Volumetric representations that describe molecular surfaces can be used to detect subtle steric clashes at atomic surfaces.  Volumes describing charged isopotentials can be used to find changes in local attractions and repulsions within electric fields.  These representations adhere more closely to long-standing intuitions than typical approaches, which describe atoms as points in space, and they present a novel alternative to physical and statistical potentials. After describing the fundamentals of these methods, we will describe how their blind prediction of a critical amino acid was recently experimentally validated.

Algorithms for discovering mutations that alter binding specificity

254th National Meeting (2017)

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