School of Information and Physical Sciences, The University of Newcastle, Australia; Institute for Integrated and Intelligent Systems (IIIS), Griffith University, Australia.
School of Information and Communication Technology, Griffith University, Australia.
Comput Biol Chem. 2022 Aug;99:107700. doi: 10.1016/j.compbiolchem.2022.107700. Epub 2022 May 23.
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.
蛋白质接触图捕捉到空间上处于一定接近阈值内的氨基酸残基对之间的共进化相互作用。预测的接触图用于许多与蛋白质相关的问题，包括药物设计、蛋白质设计、蛋白质功能预测和蛋白质结构预测。接触图预测最近取得了重大进展，但对于预测在氨基酸序列中被大量其他残基隔开的残基之间的接触仍然存在进一步的挑战。在本文中，通过对包括膜蛋白在内的 5 个标准基准数据集的实验结果，我们表明，通过使用各种最先进的短距离预测器的集合，然后将预测的距离转换为接触概率，可以显著增强接触图预测。我们的程序及其数据可从 https://gitlab.com/mahnewton/ecp 获得。
