LOMETS (Local Meta-Threading Server, version 3) is a next-generation meta-server approach to template-based protein structure prediction and structure-based function annotation. The new program integrates multiple deep learning-based threading methods (CEthreader, DisCovER, EigenThreader, Hybrid-CEthreader, MapAlign) and state-of-the-art profile-based programs (FFAS3D, HHpred, HHsearch, MRFsearch, MUSTER, SparksX). For the first time, LOMETS3 is extended to handling multi-domain proteins by introducing the domain partition (FUpred and ThreaDom) and assembly (DEMO) modules. It also introduces a new module for fast full-length model construction using a gradient-based optimization program (DeepFold), which is guided by restraints from deep-learning (DeepPotential) and LOMETS top templates. Protein functions in LOMETS3 are predicted by the modified COFACTOR method, which adds the LOMETS3 threading templates associated with structure analogs as templates in COFACTOR structure-based pipelines. Large-scaled benchmark tests showed that the overall template-recognition and full-length model construction accuracy is significantly beyond its predecessors (LOMETS and LOMETS2), due to the integration of deep-learning and multi-domain threading techniques. LOMETS3 participated in CASP14 as 'Zhang-TBM' and was ranked as one of the top methods for automatic protein structure prediction. A detailed description of the LOMETS3 server can be seen on the About LOMETS page. Please post your questions and comments about LOMETS at the Service System Discussion Board.
The output of the LOMETS server includes (Example output):
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