MULTICOM2 open-source protein structure prediction system powered by deep learning and distance prediction.

ABSTRACT: Protein structure prediction is an important problem in bioinformatics and has been studied for decades. However, there are still few open-source comprehensive protein structure prediction packages publicly available in the field. In this paper, we present our latest open-source protein tertiary structure prediction system-MULTICOM2, an integration of template-based modeling (TBM) and template-free modeling (FM) methods. The template-based modeling uses sequence alignment tools with deep multiple sequence alignments to search for structural templates, which are much faster and more accurate than MULTICOM1. The template-free (ab initio or de novo) modeling uses the inter-residue distances predicted by DeepDist to reconstruct tertiary structure models without using any known structure as tem

SUBMITTER: Wu T 

PROVIDER: S-EPMC8222248 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature