HopDock: a probabilistic search algorithm for decoy sampling in protein-protein docking

Background: Elucidating the three-dimensional structure of a higher-order molecular assembly formed by interacting molecular units, a problem commonly known as docking, is central to unraveling the molecular basis of cellular activities. Though protein assemblies are ubiquitous in the cell, it is currently challenging to predict the native structure of a protein assembly in silico. Methods: This work proposes HopDock, a novel search algorithm for protein-protein docking. HopDock efficiently obtains an ensemble of low-energy dimeric configurations, also known as decoys, that can be effectively used by ab-initio docking protocols. HopDock is based on the Basin Hopping (BH) framework which perturbs the structure of a dimeric configuration and then follows it up with an energy minimization to explicitly sample a local minimum of a chosen energy function. This process is repeated in order to sample consecutive energy minima in a trajectory-like fashion. HopDock employs both geometry and evolutionary conservation analysis to narrow down the interaction search space of interest for the purpose of efficiently obtaining a diverse decoy ensemble. Results and conclusions: A detailed analysis and a comparative study on seventeen different dimers shows HopDock obtains a broad view of the energy surface near the native dimeric structure and samples many near-native configurations. The results show that HopDock has high sampling capability and can be employed to effectively obtain a large and diverse ensemble of decoy configurations that can then be further refined in greater structural detail in ab-initio docking protocols.