Sigmoid Accelerated Molecular Dynamics: An Efficient Enhanced Sampling Method for Biosystems

被引:7
作者
Zhao, Yihao [1 ]
Zhang, Jintu [1 ,2 ]
Zhang, Haotian [1 ,2 ]
Gu, Shukai [1 ]
Deng, Yafeng [2 ]
Tu, Yaoquan [3 ]
Hou, Tingjun [1 ]
Kang, Yu [1 ]
机构
[1] Zhejiang Univ, Coll Pharmaceut Sci, Hangzhou 310058, Zhejiang, Peoples R China
[2] CarbonSilicon AI Technol Co Ltd, Hangzhou 310018, Zhejiang, Peoples R China
[3] KTH Royal Inst Technol, Dept Chem, Div Theoret Chem & Biol, S-11428 Stockholm, Sweden
基金
中国国家自然科学基金;
关键词
FREE-ENERGY LANDSCAPE; HIV-1; PROTEASE; BINDING; MECHANISM; METADYNAMICS; ACTIVATION; SIMULATION; CHIGNOLIN; PATHWAYS; NETWORK;
D O I
10.1021/acs.jpclett.2c03688
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Gaussian accelerated molecular dynamics (GaMD) is recognized as a popular enhanced sampling method for tackling longstanding challenges in biomolecular simulations. Inspired by GaMD, Sigmoid accelerated molecular dynamics (SaMD) is proposed in this work by adding a Sigmoid boost potential to improve the balance between the highest acceleration and accurate reweighting. Compared with GaMD, SaMD extends the accessible time scale and improves the computational efficiency as tested in three tasks. In the alanine dipeptide task, SaMD can produce the free energy landscape with better accuracy and efficiency. In the chignolin folding task, the estimated Gibbs free energy difference can converge to the experimental value similar to 30% faster. In the protein-ligand binding task, the bound conformations are closer to the crystal structure with a minimal ligand root-mean-square deviation of 1.7 angstrom. The binding of the ligand XK263 to the HIV protease is reproduced by SaMD in similar to 60% less simulation time.
引用
收藏
页码:1103 / 1112
页数:10
相关论文
共 59 条
[1]   Enhanced Sampling in Molecular Dynamics Using Metadynamics, Replica-Exchange, and Temperature-Acceleration [J].
Abrams, Cameron ;
Bussi, Giovanni .
ENTROPY, 2014, 16 (01) :163-199
[2]   MOLECULAR-DYNAMICS WITH COUPLING TO AN EXTERNAL BATH [J].
BERENDSEN, HJC ;
POSTMA, JPM ;
VANGUNSTEREN, WF ;
DINOLA, A ;
HAAK, JR .
JOURNAL OF CHEMICAL PHYSICS, 1984, 81 (08) :3684-3690
[3]   Mechanisms of γ-Secretase Activation and Substrate Processing [J].
Bhattarai, Apurba ;
Devkota, Sujan ;
Bhattarai, Sanjay ;
Wolfe, Michael S. ;
Miao, Yinglong .
ACS CENTRAL SCIENCE, 2020, 6 (06) :969-983
[4]   G-Protein-Coupled Receptor-Membrane Interactions Depend on the Receptor Activation State [J].
Bhattarai, Apurba ;
Wang, Jinan ;
Miao, Yinglong .
JOURNAL OF COMPUTATIONAL CHEMISTRY, 2020, 41 (05) :460-471
[5]   Targeting the open-flap conformation of HIV-1 protease with pyrrolidine-based inhibitors [J].
Boettcher, Jark ;
Blum, Andreas ;
Doerr, Stefanie ;
Heine, Andreas ;
Diederich, Wibke E. ;
Klebe, Gerhard .
CHEMMEDCHEM, 2008, 3 (09) :1337-1344
[6]   The automated optimisation of a coarse-grained force field using free energy data [J].
Caceres-Delpiano, Javier ;
Wang, Lee-Ping ;
Essex, Jonathan W. .
PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2021, 23 (43) :24842-24851
[7]   Importance Sampling Methods and Free Energy Calculations [J].
Chen, Haochuan ;
Fu, Haohao ;
Shao, Xueguang ;
Cai, Wensheng .
PROGRESS IN CHEMISTRY, 2018, 30 (07) :921-931
[8]   A Computational Approach to the Study of the Binding Mode of S1P1R Agonists Based on the Active-Like Receptor Model [J].
Chen, Yonghui ;
Liu, Tianqi ;
Xi, Qiumu ;
Jia, Wenqiang ;
Yin, Dali ;
Wang, Xiaojian .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2019, 59 (04) :1624-1633
[9]   Adaptive biasing force method for scalar and vector free energy calculations [J].
Darve, Eric ;
Rodriguez-Gomez, David ;
Pohorille, Andrew .
JOURNAL OF CHEMICAL PHYSICS, 2008, 128 (14)
[10]   Exploring the Conformational Transitions of Biomolecular Systems Using a Simple Two-State Anisotropic Network Model [J].
Das, Avisek ;
Gur, Mert ;
Cheng, Mary Hongying ;
Jo, Sunhwan ;
Bahar, Ivet ;
Roux, Benoit .
PLOS COMPUTATIONAL BIOLOGY, 2014, 10 (04)