Sector of Crystallography and Cheminformatics, Institute of Biotechnology, Life Sciences Center, Vilnius University, 7 Saulėtekio Ave, Vilnius, LT- 10257, Lithuania.
Bioinformatics. 2023 Jul 1;39(7). doi: 10.1093/bioinformatics/btad429.
Identifying the probable positions of the protein side-chains is one of the protein modelling steps that can improve the prediction of protein-ligand and protein-protein interactions. Most of the strategies predicting the side-chain conformations use predetermined dihedral angle lists, also called rotamer libraries, that are usually generated from a subset of high-quality protein structures. Although these methods are fast to apply, they tend to average out geometries instead of taking into account the surrounding atoms and molecules and ignore structures not included in the selected subset. Such simplifications can result in inaccuracies when predicting possible side-chain atom positions.
We propose an approach that takes into account both of these circumstances by scanning through sterically accessible side-chain conformations and generating dihedral angle libraries specific to the target proteins. The method avoids the drawbacks of lacking conformations due to unusual or rare protein structures and successfully suggests potential rotamers with average RMSD closer to the experimentally determined side-chain atom positions than other widely used rotamer libraries.
The technique is implemented in open-source software package rotag and available at GitHub: https://www.github.com/agrybauskas/rotag, under GNU Lesser General Public License.
确定蛋白质侧链的可能位置是蛋白质建模步骤之一，可提高蛋白质-配体和蛋白质-蛋白质相互作用的预测能力。预测侧链构象的大多数策略都使用预定的二面角列表，也称为构象文库，这些文库通常是从高质量蛋白质结构的子集生成的。尽管这些方法应用起来很快，但它们往往会平均化几何形状，而不是考虑周围的原子和分子，并忽略所选子集中未包含的结构。这种简化可能会导致在预测可能的侧链原子位置时产生不准确的结果。
我们提出了一种方法，通过扫描空间可及的侧链构象并生成特定于目标蛋白质的二面角文库来考虑这两种情况。该方法避免了由于异常或罕见的蛋白质结构而缺乏构象的缺点，并成功地提出了潜在的构象体，其平均 RMSD 比其他广泛使用的构象文库更接近实验确定的侧链原子位置。
该技术在开源软件包 rotag 中实现，并可在 GitHub 上获得：https://www.github.com/agrybauskas/rotag，根据 GNU Lesser General Public License 授权。
