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FAMSD: A powerful protein modeling platform that combines alignment methods, homology modeling, 3D structure quality estimation and molecular dynamics
- Source :
- Chemicalpharmaceutical bulletin. 57(12)
- Publication Year :
- 2009
-
Abstract
- The prediction of a protein three-dimensional (3D) structure is one of the most important challenges in computational structural biology. We have developed an automatic protein 3D structure prediction method called FAMSD. FAMSD is based on a comparative modeling method which consists of the following four steps: (1) generating and selecting sequence alignments between target and template proteins; (2) constructing 3D structure models based on each selected alignment; (3) selecting the best 3D structure model and (4) refining the selected model. In the FAMSD method, sequence alignment programs such as a series of BLAST programs, SP3 and SPARKS2 programs, the homology modeling program FAMS (Full Automatic Modeling System), the model quality estimation program CIRCLE and the molecular dynamics program APRICOT were used in combination to construct high quality protein models. To assess the FAMSD method we have participated in the 8th Critical Assessment of Techniques for Protein Structure Prediction (CASP8) experiment. The results of our original assessment indicate that the FAMSD method offers excellent capability in packing side-chains with the correct torsion angles while avoiding the formation of atom-atom collisions. Since side-chain packing plays a significant role in defining the biological function of proteins, this method is a valuable resource in biological, pharmaceutical and medicinal research efforts.
- Subjects :
- Structure (mathematical logic)
Models, Molecular
Sequence
Series (mathematics)
Chemistry
Protein Conformation
Sequence alignment
General Chemistry
General Medicine
Construct (python library)
Protein structure prediction
Molecular Dynamics Simulation
Bioinformatics
computer.software_genre
Resource (project management)
Drug Discovery
Homology modeling
Data mining
computer
Sequence Alignment
Subjects
Details
- ISSN :
- 13475223
- Volume :
- 57
- Issue :
- 12
- Database :
- OpenAIRE
- Journal :
- Chemicalpharmaceutical bulletin
- Accession number :
- edsair.doi.dedup.....0ec4d0cedb7a402144362f8e66a6edee