- Title
- Enhancing protein contact map prediction accuracy via ensembles of inter-residue distance predictors
- Creator
- Newton, M. A. Hakim; Rahman, Julia; Zaman, Rianon; Sattar, Abdul
- Relation
- Computational Biology and Chemistry Vol. 99, Issue August 2022, no. 107700
- Publisher Link
- http://dx.doi.org/10.1016/j.compbiolchem.2022.107700
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2022
- Description
- Protein contact maps capture coevolutionary interactions between amino acid residue pairs that are spatially within certain proximity threshold. Predicted contact maps are used in many protein related problems that include drug design, protein design, protein function prediction, and protein structure prediction. Contact map prediction has achieved significant progress lately but still further challenges remain with prediction of contacts between residues that are separated in the amino acid residue sequence by large numbers of other residues. In this paper, with experimental results on 5 standard benchmark datasets that include membrane proteins, we show that contact map prediction could be significantly enhanced by using ensembles of various state-of-the-art short distance predictors and then by converting predicted distances into contact probabilities. Our program along with its data is available from https://gitlab.com/mahnewton/ecp.
- Subject
- protein contact prediction; inter-residue real-valued distances; residual networks; ensembling
- Identifier
- http://hdl.handle.net/1959.13/1483021
- Identifier
- uon:51067
- Identifier
- ISSN:1476-9271
- Language
- eng
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