LOMETS3: A improved meta-server approach for template detection using deep-learning-based geometric restraints

1. LOMETS3 Top Templates:
    LOMETS_[1-10].pdb       is/are the structure of the aligned region of query and top templates from LOMES3 program.

2. Templates from Individual threading programs:
    XXX_[1-10].pdb          is/are the structure of aligned region of query and each template selected by the threading program.
    XXX_[1-10].fasta        is/are the fasta format and full length alignment of each aligned template and query. 
                            it also shows the functional annotation information for ligand binding residues, GO (Gene Ontology) and EC (Enzyme Commission) terms.

    here XXX is the component threading program specified below:
    CET = CEthreader
    hCE = Hybrid-CEthreader
    MAP = MapAlign
    DOV = DisCovER
    EIG = EigenThreader
    HHW = HHpred
    HHP/HHPcmo = HHsearch
    SPX/SPCcmo = SparksX
    FF3/FF3cmo = FFAS3D
    RAPM/RAPMcmo = MRFsearch
    MUS/MUScmo = MUSTER

    Where cmo (contact map overlap score) indicates that the target was hard or very hard
    and threaders with the cmo suffix were reranked by their contact map overlap score.

3. LOMETS3 final model(s)
    model[1-5].pdb        is/are the final model generated by LOMETS3.

4. TM-align Structural Alignment
    model1_[1-10].pdb     provide the structure of the alignment between templates and LOMETS3 first model (model1.pdb) by TM-align.
    model1_[1-10].fasta   provide the fasta format of the alignment between templates and LOMETS3 first model (model1.pdb) by TM-align,
                          and the functional annotation information for ligand binding residues, GO (Gene Ontology) and EC (Enzyme Commission) terms.

5. Figures for Contact-Map and Distance-Map from DeepPotential
    contact.map.jpg       predicted contact-map for query
    distance.map.jpg      predicted distance-map for query

6. Summary file
    index.html            a html style summary file that inculding all information same with the LOMETS3 server output page.

If you are using the LOMETS program, you can cite:

    W Zheng, Q Wuyun, X Zhou, Y Li, P Freddolino, Y Zhang. LOMETS3: Integrating 
    deep-learning and profile-alignment for advanced protein template recognition 
    and function annotation. in preparation, (2021)

    W Zheng, C Zhang, Q Wuyun, R Pearce, Y Li, Y Zhang. LOMETS2: improved 
    meta-threading server for fold-recognition and structure-based function 
    annotation for distant-homology proteins. Nucleic Acids Research, 47: W429-W436 (2019).

    S Wu, Y Zhang. LOMETS: A local meta-threading-server for protein 
    structure prediction. Nucleic Acids Research, 35: 3375-3382 (2007).

