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Protein-protein docking with dynamic residue protonation states.

ABSTRACT: Protein-protein interactions depend on a host of environmental factors. Local pH conditions influence the interactions through the protonation states of the ionizable residues that can change upon binding. In this work, we present a pH-sensitive docking approach, pHDock, that can sample side-chain protonation states of five ionizable residues (Asp, Glu, His, Tyr, Lys) on-the-fly during the docking simulation. pHDock produces successful local docking funnels in approximately half (79/161) the protein complexes, including 19 cases where standard RosettaDock fails. pHDock also performs better than the two control cases comprising docking at pH 7.0 or using fixed, predetermined protonation states. On average, the top-ranked pHDock structures have lower interface RMSDs and recover more native interface residue-residue contacts and hydrogen bonds compared to RosettaDock. Addition of backbone flexibility using a computationally-generated conformational ensemble further improves native contact and hydrogen bond recovery in the top-ranked structures. Although pHDock is designed to improve docking, it also successfully predicts a large pH-dependent binding affinity change in the Fc-FcRn complex, suggesting that it can be exploited to improve affinity predictions. The approaches in the study contribute to the goal of structural simulations of whole-cell protein-protein interactions including all the environmental factors, and they can be further expanded for pH-sensitive protein design.

SUBMITTER: Kilambi KP

PROVIDER: S-EPMC4263365 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Protein-protein docking with dynamic residue protonation states.

Kilambi Krishna Praneeth KP Reddy Kavan K Gray Jeffrey J JJ

PLoS computational biology 20141211 12

Protein-protein interactions depend on a host of environmental factors. Local pH conditions influence the interactions through the protonation states of the ionizable residues that can change upon binding. In this work, we present a pH-sensitive docking approach, pHDock, that can sample side-chain protonation states of five ionizable residues (Asp, Glu, His, Tyr, Lys) on-the-fly during the docking simulation. pHDock produces successful local docking funnels in approximately half (79/161) the pro ...[more]

PMID: 25501663

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Project description:The protein docking problem has two major aspects: sampling conformations and orientations, and scoring them for fit. To investigate the extent to which the protein docking problem may be attributed to the sampling of ligand side-chain conformations, multiple conformations of multiple residues were calculated for the uncomplexed (unbound) structures of protein ligands. These ligand conformations were docked into both the complexed (bound) and unbound conformations of the cognate receptors, and their energies were evaluated using an atomistic potential function. The following questions were considered: (1) does the ensemble of precalculated ligand conformations contain a structure similar to the bound form of the ligand? (2) Can the large number of conformations that are calculated be efficiently docked into the receptors? (3) Can near-native complexes be distinguished from non-native complexes? Results from seven test systems suggest that the precalculated ensembles do include side-chain conformations similar to those adopted in the experimental complexes. By assuming additivity among the side chains, the ensemble can be docked in less than 12 h on a desktop computer. These multiconformer dockings produce near-native complexes and also non-native complexes. When docked against the bound conformations of the receptors, the near-native complexes of the unbound ligand were always distinguishable from the non-native complexes. When docked against the unbound conformations of the receptors, the near-native dockings could usually, but not always, be distinguished from the non-native complexes. In every case, docking the unbound ligands with flexible side chains led to better energies and a better distinction between near-native and non-native fits. An extension of this algorithm allowed for docking multiple residue substitutions (mutants) in addition to multiple conformations. The rankings of the docked mutant proteins correlated with experimental binding affinities. These results suggest that sampling multiple residue conformations and residue substitutions of the unbound ligand contributes to, but does not fully provide, a solution to the protein docking problem. Conformational sampling allows a classical atomistic scoring function to be used; such a function may contribute to better selectivity between near-native and non-native complexes. Allowing for receptor flexibility may further extend these results.

Project description:Experimental approaches such as fiber diffraction and cryo-electron microscopy reconstruction have defined regulatory positions of tropomyosin on actin but have not, as yet, succeeded at determining key atomic-level contacts between these proteins or fully substantiated the dynamics of their interactions at a structural level. To overcome this deficiency, we have previously employed computational approaches to deduce global dynamics of thin filament components by energy landscape determination and molecular dynamics simulations. Still, these approaches remain computationally challenging for any complex and large macromolecular assembly like the thin filament. For example, tropomyosin cable wrapping around actin of thin filaments features both head-to-tail polymeric interactions and local twisting, both of which depart from strict superhelical symmetry. This produces a complex energy surface that is difficult to model and thus to evaluate globally. Therefore, at this stage of our understanding, assessing global molecular dynamics can prove to be inherently impractical. As an alternative, we adopted a "divide and conquer" protocol to investigate actin-tropomyosin interactions at an atomistic level. Here, we first employed unbiased protein-protein docking tools to identify binding specificity of individual tropomyosin pseudorepeat segments over the actin surface. Accordingly, tropomyosin "ligand" segments were rotated and translated over potential "target" binding sites on F-actin where the corresponding interaction energetics of billions of conformational poses were ranked by the programs PIPER and ClusPro. These data were used to assess favorable interactions and then to rebuild models of seamless and continuous tropomyosin cables over the F-actin substrate, which were optimized further by flexible fitting routines and molecular dynamics. The models generated azimuthally distinct regulatory positions for tropomyosin cables along thin filaments on actin dominated by stereo-specific head-to-tail overlap linkage. The outcomes are in good agreement with current cryo-electron microscopy topology and consistent with long-thought residue-to-residue interactions between actin and tropomyosin.

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Protein-protein docking with dynamic residue protonation states.

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Protein-protein docking with dynamic residue protonation states.

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