VoroMQA-dark method for model quality assessment
VoroMQA-dark is a new model quality assessment method based on the previously published VoroMQA34 method (which will be referred to as VoroMQA-light). VoroMQA-dark uses a neural network (NN) trained to predict local (per-residue) CAD-score31values. The global structure score is computed by averaging the predicted local scores. The NN input vector for each residue is computed from the Voronoi tessellation-based contact areas and the corresponding contact potential values from VoroMQA-light. See Supplementary information for more details on VoroMQA-dark. The VoroMQA-dark standalone software is included in the extension of the Voronota35 package freely available from https://kliment-olechnovic.github.io/voronota/expansion_js/.