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.
The output model of LOMETS server is given by both PDB format and ModelCIF format
now.
Please post your questions and comments about LOMETS at the
Service System Discussion Board.
The output of the LOMETS server includes (Example output):
yangzhanglabumich.edu
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