Improving computational efficiency and tractability of protein design using a piecemeal approach. A strategy for parallel and distributed protein design.

Bioinformatics

Department of Biology, Rensselaer Polytechnic Institute, Troy, NY 12180, Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94143, Department of Computer Science and Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY 12180, USA Department of Biology, Rensselaer Polytechnic Institute, Troy, NY 12180, Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94143, Department of Computer Science and Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY 12180, USA Department of Biology, Rensselaer Polytechnic Institute, Troy, NY 12180, Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94143, Department of Computer Science and Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.

Published: April 2014

Motivation: Accuracy in protein design requires a fine-grained rotamer search, multiple backbone conformations, and a detailed energy function, creating a burden in runtime and memory requirements. A design task may be split into manageable pieces in both three-dimensional space and in the rotamer search space to produce small, fast jobs that are easily distributed. However, these jobs must overlap, presenting a problem in resolving conflicting solutions in the overlap regions.

Results: Piecemeal design, in which the design space is split into overlapping regions and rotamer search spaces, accelerates the design process whether jobs are run in series or in parallel. Large jobs that cannot fit in memory were made possible by splitting. Accepting the consensus amino acid selection in conflict regions led to non-optimal choices. Instead, conflicts were resolved using a second pass, in which the split regions were re-combined and designed as one, producing results that were closer to optimal with a minimal increase in runtime over the consensus strategy. Splitting the search space at the rotamer level instead of at the amino acid level further improved the efficiency by reducing the search space in the second pass.

Availability And Implementation: Programs for splitting protein design expressions are available at www.bioinfo.rpi.edu/tools/piecemeal.html CONTACT: bystrc@rpi.edu Supplementary information: Supplementary data are available at Bioinformatics online.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3982153PMC
http://dx.doi.org/10.1093/bioinformatics/btt735DOI Listing

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