Automatic Prediction of Protein 3D Structures by Probabilistic Multi-template Homology Modeling.

ABSTRACT: Homology modeling predicts the 3D structure of a query protein based on the sequence alignment with one or more template proteins of known structure. Its great importance for biological research is owed to its speed, simplicity, reliability and wide applicability, covering more than half of the residues in protein sequence space. Although multiple templates have been shown to generally increase model quality over single templates, the information from multiple templates has so far been combined using empirically motivated, heuristic approaches. We present here a rigorous statistical framework for multi-template homology modeling. First, we find that the query proteins' atomic distance restraints can be accurately described by two-component Gaussian mixtures. This insight allowed us to appl

SUBMITTER: Meier A 

PROVIDER: S-EPMC4619893 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature