文献类型：期刊文献

英文题名：Multi-body effects in a coarse-grained protein force field

作者：Wang, Jiang Charron, Nicholas Husic, Brooke Olsson, Simon Noe, Frank Clementi, Cecilia

第一作者：王江;Wang, Jiang

通信作者：Clementi, C[1];Clementi, C[2];Clementi, C[3];Clementi, C[4]

机构：[1]Rice Univ, Ctr Theoret Biol Phys, Houston, TX 77005 USA;[2]Rice Univ, Dept Chem, Houston, TX 77005 USA;[3]Guizhou Inst Technol, Coll Sci, Guiyang 550000, Guizhou, Peoples R China;[4]Rice Univ, Dept Phys, Houston, TX 77005 USA;[5]Free Univ Berlin, Dept Phys, Arnimallee 14, D-14195 Berlin, Germany;[6]Free Univ Berlin, Dept Math & Comp Sci, Arnimallee 6, D-14195 Berlin, Germany;[7]Chalmers Univ Technol, Dept Comp Sci & Engn, Gothenburg, Sweden

第一机构：Rice Univ, Ctr Theoret Biol Phys, Houston, TX 77005 USA

通信机构：corresponding author), Rice Univ, Ctr Theoret Biol Phys, Houston, TX 77005 USA;corresponding author), Rice Univ, Dept Chem, Houston, TX 77005 USA;corresponding author), Rice Univ, Dept Phys, Houston, TX 77005 USA;corresponding author), Free Univ Berlin, Dept Phys, Arnimallee 14, D-14195 Berlin, Germany.

年份：2021

卷号：154

期号：16

外文期刊名：JOURNAL OF CHEMICAL PHYSICS

收录：;EI(收录号：20211910314147);Scopus(收录号：2-s2.0-85105121888);WOS:【SCI-EXPANDED(收录号:WOS:000692814300005)】；

基金：We thank Francesco Paesani for insightful discussions and Gianni de Fabritiis and Adria Perez for the chignolin atomistic trajectories. This work was supported by the National Science Foundation (Grant Nos. CHE-1738990, CHE-1900374, and PHY-1427654), the Welch Foundation (Grant No. C-1570), the German MATH+ Excellence Cluster (Grant Nos. AA1-6 and EF1-2), the Deutsche Forschungsgemeinschaft (Grant Nos. SFB 1114/C03, SFB/TRR 186/A12, and SFB 1078/C7), the European Commission (Grant No. ERC CoG 772230 "ScaleCell"), and the Einstein Foundation Berlin. Simulations have been performed on the computer clusters of the Center for Research Computing at Rice University, supported, in part, by the Big-Data Private-Cloud Research Cyberinfrastructure MRI-award (NSF, Grant No. CNS-1338099).

语种：英文

外文关键词：Expansion - Free energy - Proteins

摘要：The use of coarse-grained (CG) models is a popular approach to study complex biomolecular systems. By reducing the number of degrees of freedom, a CG model can explore long time- and length-scales inaccessible to computational models at higher resolution. If a CG model is designed by formally integrating out some of the system's degrees of freedom, one expects multi-body interactions to emerge in the effective CG model's energy function. In practice, it has been shown that the inclusion of multi-body terms indeed improves the accuracy of a CG model. However, no general approach has been proposed to systematically construct a CG effective energy that includes arbitrary orders of multi-body terms. In this work, we propose a neural network based approach to address this point and construct a CG model as a multi-body expansion. By applying this approach to a small protein, we evaluate the relative importance of the different multi-body terms in the definition of an accurate model. We observe a slow convergence in the multi-body expansion, where up to five-body interactions are needed to reproduce the free energy of an atomistic model.