Computational feasibility of an exhaustive search of side-chain conformations in protein-protein docking
Open accessAbstract
Protein-protein docking procedures typically perform the global scan of the proteins relative positions, followed by the local refinement of the putative matches. Because of the size of the search space, the global scan is usually implemented as rigid-body search, using computationally inexpensive intermolecular energy approximations. An adequate refinement has to take into account structural flexibility. Since the refinement performs conformational search of the interacting proteins, it is extremely computationally challenging, given the enormous amount of the internal degrees of freedom. Different approaches limit the search space by restricting the search to the side chains, rotameric states, coarse-grained structure representation, principal normal modes, and so on. Still, even with the approximations, the refinement presents an extreme computational challenge due to the very large number of the remaining degrees of freedom. Given the complexity of the search space, the advantage of the exhaustive search is obvious. The obstacle to such search is computational feasibility. However, the growing computational power of modern computers, especially due to the increasing utilization of Graphics Processing Unit (GPU) with large amount of specialized computing cores, extends the ranges of applicability of the brute-force search methods. This proof-of-concept study demonstrates computational feasibility of an exhaustive search of side-chain conformations in protein pocking. The procedure, implemented on the GPU architecture, was used to generate the optimal conformations in a large representative set of protein-protein complexes. © 2018 Wiley Periodicals, Inc.
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Despite significant progress, the local refinement problem remains a challenge, especially in cases of conformational changes in the backbone.
“However, despite significant progress in this direction [26–29], the problem remains a challenge, especially in cases of conformational changes in the backbone.”
From Challenges in protein docking (2020) · cites this paper as [26]
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- Authors
- Dauzhenka, T., Kundrotas, P. J., & Vakser, I. A.
- Affiliations
- University of Kansas (US)
- Corresponding author
- Kundrotas, Petras J.
- Vakser, Ilya A.
- Venue
- Journal of Computational Chemistry
- Publisher
- Wiley
- Published
- 2018-09-15
- Volume
- 39
- Issue
- 24
- Pages
- 2012-2021
- ISSN
- 0192-8651 (ISSN-L)
- 1096-987X
- PMC
- PMC6186188
- OpenAlex
- W2891474722
- Cited by
- 17
- References
- 43
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 3 · 2023: 2 · 2022: 4 · 2021: 1 · 2020: 2 · 2019: 2
- FWCI
- 0.44
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Computational Chemistry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (R01GM074255)
- National Science Foundation (DBI1262621, DBI1565107, CNS133789)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- protein-protein docking, exhaustive search, GPU acceleration, structural flexibility, protein-protein complex, search space complexity
- MeSH terms
- Algorithms, Feasibility Studies, Protein Binding, Protein Conformation, Proteins, Computational Biology
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