Singh Amar, Tytarenko Andrii M, Ambati Vineeth Kumar, Copeland Matthew M, Kundrotas Petras J, Kasyanov Pavlo O, Feinberg Eugene A, Vakser Ilya A
Computational Biology Program, The University of Kansas, Lawrence, KS 66045, USA.
Institute for Applied System Analysis at the Igor Sikorsky Kyiv Polytechnic Institute, Kyiv 03056, Ukraine.
J Mol Biol. 2025 Aug 1;437(15):169085. doi: 10.1016/j.jmb.2025.169085. Epub 2025 Mar 12.
The environment inside biological cells is densely populated by macromolecules and other cellular components. The crowding has a significant impact on folding and stability of macromolecules, and on kinetics of molecular interactions. Computational approaches to cell modeling, such as molecular dynamics, provide details of macromolecular behavior in concentrated solutions. However, such simulations are either slow, when carried out at atomic resolution, or significantly coarse-grained. Protein docking has been widely used for predicting structures of protein complexes. Systematic docking approaches, such as those based on Fast Fourier Transform (FFT), map the entire intermolecular energy landscape by determining the position and depth of the energy minima. The GRAMMCell web server implements docking-based approach for simulating cell crowded environment by sampling the intermolecular energy landscape generated by GRAMM (Global RAnge Molecular Matching). GRAMM systematically maps the landscape by a spectrum of docking poses corresponding to stable (deep energy minima) and transient (shallow minima) protein interactions. The sampling of these energy landscapes of a large system of proteins is performed in GRAMMCell using highly optimized Markov Chain Monte Carlo protocol. The procedure allows simulation of extra-long trajectories of large, crowded protein systems with atomic resolution accuracy. GRAMMCell is available at https://grammcell.compbio.ku.edu.
生物细胞内部环境中充满了大量的大分子和其他细胞成分。这种拥挤现象对大分子的折叠和稳定性以及分子相互作用的动力学有着重大影响。细胞建模的计算方法，如分子动力学，能够提供浓缩溶液中大分子行为的详细信息。然而，此类模拟在以原子分辨率进行时速度较慢，或者显著粗粒化。蛋白质对接已被广泛用于预测蛋白质复合物的结构。系统对接方法，如基于快速傅里叶变换（FFT）的方法，通过确定能量最小值的位置和深度来绘制整个分子间能量景观。GRAMMCell网络服务器通过对GRAMM（全局范围分子匹配）生成的分子间能量景观进行采样，实现了基于对接的方法来模拟细胞拥挤环境。GRAMM通过一系列对应于稳定（深能量最小值）和瞬态（浅最小值）蛋白质相互作用的对接姿势系统地绘制景观。在GRAMMCell中，使用高度优化的马尔可夫链蒙特卡罗协议对大型蛋白质系统的这些能量景观进行采样。该程序允许以原子分辨率精度模拟大型拥挤蛋白质系统的超长轨迹。可通过https://grammcell.compbio.ku.edu访问GRAMMCell。
