VoroMQA: Assessment of protein structure quality using interatomic contact areas

Abstract

In the absence of experimentally determined protein structure many biological questions can be addressed using computational structural models. However, the utility of protein structural models depends on their quality. Therefore, the estimation of the quality of predicted structures is an important problem. One of the approaches to this problem is the use of knowledge-based statistical potentials. Such methods typically rely on the statistics of distances and angles of residue-residue or atom-atom interactions collected from experimentally determined structures. Here, we present VoroMQA (Voronoi tessellation-based Model Quality Assessment), a new method for the estimation of protein structure quality. Our method combines the idea of statistical potentials with the use of interatomic contact areas instead of distances. Contact areas, derived using Voronoi tessellation of protein structure, are used to describe and seamlessly integrate both explicit interactions between protein atoms and implicit interactions of protein atoms with solvent. VoroMQA produces scores at atomic, residue, and global levels, all in the fixed range from 0 to 1. The method was tested on the CASP data and compared to several other single-model quality assessment methods. VoroMQA showed strong performance in the recognition of the native structure and in the structural model selection tests, thus demonstrating the efficacy of interatomic contact areas in estimating protein structure quality. The software implementation of VoroMQA is freely available as a standalone application and as a web server at http://bioinformatics.lt/software/voromqa. Proteins 2017; 85:1131-1145. © 2017 Wiley Periodicals, Inc.

Blind prediction of homo‐ and hetero‐protein complexes: The CASP13‐CAPRI experiment

“…But the type of functions differed substantially between participants. Examples are the VoroMQA score developed by the Venclovas group, the combined use of three scoring functions, GOAP, Dfire, and ITScore by the Kihara group, or the multiterm scoring function of the Vakser group, additionally complemented with sequence‐based measures for individual subunits and with functional annotations. The quite successful scoring performance of the Oliva group relied on their CONSRANK‐based methods to score and rank multiple models, based on the most frequent interface residue contacts observed in these models …”

Estimation of model accuracy in CASP13

“…For CASP13, our emphasis was on increasing the accuracy of per‐residue assessments for single models, single model ranking and score consistency. Each model was considered individually using six previously described pure‐single model methods: CDA, SSA, ProQ2, ProQ2D, ProQ3D and VoroMQA . Additionally, reference 3D‐models sets were generated using the IntFOLD5 server and these were used to score models using four previously described quasi‐single model methods: DBA, MF5s, MFcQs and ResQ .…”

Structural modeling of protein complexes: Current capabilities and challenges

“…When no templates or only low reliability templates could be identified for protein complexes, free docking was used. First, five best CASP server models were selected using Voronoi tessellation‐based Model Quality Assessment (VoroMQA) for each subunit of the protein complex. These models were then docked using symmetry‐assisted docking by Sam for homo‐multimers and Hex or PyDockWEB for hetero‐multimers.…”

“…For model evaluation and selection, we employed VoroMQA (“Voronoi tessellation‐based Model Quality Assessment”) . This method combines the idea of knowledge‐based statistical potentials with the use of the Voronoi tessellation of atomic balls.…”