AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking

Abstract

BackgroundComputational analysis of protein-protein interaction provided the crucial information to increase the binding affinity without a change in basic conformation. Several docking programs were used to predict the near-native poses of the protein-protein complex in 10 top-rankings. The universal criteria for discriminating the near-native pose are not available since there are several classes of recognition protein. Currently, the explicit criteria for identifying the near-native pose of ankyrin-protein complexes (APKs) have not been reported yet.ResultsIn this study, we established an ensemble computational model for discriminating the near-native docking pose of APKs named “AnkPlex”. A dataset of APKs was generated from seven X-ray APKs, which consisted of 3 internal domains, using the reliable docking tool ZDOCK. The dataset was composed of 669 and 44,334 near-native and non-near-native poses, respectively, and it was used to generate eleven informative features. Subsequently, a re-scoring rank was generated by AnkPlex using a combination of a decision tree algorithm and logistic regression. AnkPlex achieved superior efficiency with ≥1 near-native complexes in the 10 top-rankings for nine X-ray complexes compared to ZDOCK, which only obtained six X-ray complexes. In addition, feature analysis demonstrated that the van der Waals feature was the dominant near-native pose out of the potential ankyrin-protein docking poses.ConclusionThe AnkPlex model achieved a success at predicting near-native docking poses and led to the discovery of informative characteristics that could further improve our understanding of the ankyrin-protein complex. Our computational study could be useful for predicting the near-native poses of binding proteins and desired targets, especially for ankyrin-protein complexes. The AnkPlex web server is freely accessible at http://ankplex.ams.cmu.ac.th.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1628-6) contains supplementary material, which is available to authorized users.

Selection of Ankyrin Targeting HIV-1 Matrix and Identification of Its Binding Domain

“…The 3D structure of Ank GAG G31 and MA were prepared by energy minimization with CHARMm force field and without incorporating solvent and salt concentrations. The algorithm for minimization began using 5,000-step energy minimization with 0.1 Å of rootmean-square deviation (RMSD) and Conjugate Gradient (CONJ) (Chen et al, 2003;Wiehe et al, 2008;Wisitponchai et al, 2017). Following ZDOCK protocol, the variable residues on each repeat of Ank GAG G31 were specified as binding residues, and atoms of MA within the region of binding interface at a distance cutoff of 10 Å were selected (Halperin et al, 2002;Wiehe et al, 2008;Wisitponchai et al, 2013).…”

Immunoreactivity of Humanized Single-Chain Variable Fragment Against Its Functional Epitope On Domain 1 of CD147

“…As the functions of proteins are crucially related to their molecular assembly, molecular modelling techniques used to determine binding structures have been comprehensively explored to exemplify possible complex-forming mechanisms 26,27 . An accountable design of novel antibodies together with binding in protein-protein complexes can be initialized using protein docking 28,29 . A predicted HuScFvM61B9-CD147 binding structure from the Schrödinger BioLuminate module was characterized in this study 30 .…”