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Bioinformatics. 2015 Jul 1;31(13):2098-105. doi: 10.1093/bioinformatics/btv092. Epub 2015 Feb 19.

AIDA: ab initio domain assembly for automated multi-domain protein structure prediction and domain-domain interaction prediction.

Author information

1
Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093-0446, USA and Center of Excellence in Genomic Medicine Research (CEGMR), King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.
2
Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093-0446, USA and Center of Excellence in Genomic Medicine Research (CEGMR), King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093-0446, USA and Center of Excellence in Genomic Medicine Research (CEGMR), King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.
3
Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093-0446, USA and Center of Excellence in Genomic Medicine Research (CEGMR), King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093-0446, USA and Center of Excellence in Genomic Medicine Research (CEGMR), King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093-0446, USA and Center of Excellence in Genomic Medicine Research (CEGMR), King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.

Abstract

MOTIVATION:

Most proteins consist of multiple domains, independent structural and evolutionary units that are often reshuffled in genomic rearrangements to form new protein architectures. Template-based modeling methods can often detect homologous templates for individual domains, but templates that could be used to model the entire query protein are often not available.

RESULTS:

We have developed a fast docking algorithm ab initio domain assembly (AIDA) for assembling multi-domain protein structures, guided by the ab initio folding potential. This approach can be extended to discontinuous domains (i.e. domains with 'inserted' domains). When tested on experimentally solved structures of multi-domain proteins, the relative domain positions were accurately found among top 5000 models in 86% of cases. AIDA server can use domain assignments provided by the user or predict them from the provided sequence. The latter approach is particularly useful for automated protein structure prediction servers. The blind test consisting of 95 CASP10 targets shows that domain boundaries could be successfully determined for 97% of targets.

AVAILABILITY AND IMPLEMENTATION:

The AIDA package as well as the benchmark sets used here are available for download at http://ffas.burnham.org/AIDA/.

CONTACT:

adam@sanfordburnham.org

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
25701568
PMCID:
PMC4481839
DOI:
10.1093/bioinformatics/btv092
[Indexed for MEDLINE]
Free PMC Article

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