Front Matter

Molecular simulations allow us to see the “invisible” biological world with super high time and spatial resolution. Molecular modeling and molecular dynamics (MD) simulation of biomolecules have increasingly become essential and irreplaceable tools to investigate biological problems, thanks to the continuous improvement of hardware and software. The development of advanced multiscale/coarse-grained (CG) modeling and enhanced sampling algorithms makes it especially possible to reach the interested biological timescale and study the dynamics and function of massive biomolecular systems outpacing Moore's law. The ongoing COVID-19 pandemic has even created an urgent and high demand for using molecular modeling and simulations in an unprecedented manner to understand the novel SARS-COV-2 coronavirus at the molecular level.

The purpose of this book is to provide practical guidance on advanced multiscale modeling and machine-learning-aided molecular simulations to enable nonspecialists to apply them to their own biological problems. In addition to a general introduction to the theoretical background, the chapters in this book will provide in a readily reproducible step-by-step fashion, a list of the scripts and codes needed to complete the simulations, followed by a detailed procedure that is supported with helpful notes section offering tips and tricks on using these methods as well as troubleshooting advice. We sought the help of experts with an established reputation in the development and application of these models and methods and asked them to contribute their state-of-the-art views and guidance on modeling and simulation of biomolecules.

The first part of the book (Chaps. 1–3) is focused on the development of CG models that reduce the computational burden while keeping an acceptable resolution in the structural representation and intermolecular interactions. We will introduce the latest version of Martini, one of the most popular CG models with many applications in diverse fields, as well as SIRAH for modeling transmembrane proteins and the multi-basin structure-based Go model that has been applied for simulating molecular motors walking along cytoskeletons.

Chapters 4 and 5 are dedicated to a special version of MD simulation, constant-pH MD, in both coarse-grained and all-atom levels. Different from standard MD simulations in which the protonation states of all titratable residues are fixed, it allows the residue protonation states to be adjustable on the fly, therefore is a powerful tool to study the pH dependence of conformational dynamics.

Chapter 6 introduces the readers to a state-of-the-art machine-learning driven MD method, named Deep Potential MD (DeePMD), which has won the 2020 ACM Gordon Bell Prize for “pushing the limit of molecular dynamics with ab initio accuracy to 100 × 10⁶ atoms with machine learning.” The usage of the corresponding open-source package, DeePMD-kit, will also be introduced.

The last part of the book (Chaps. 7–11) is meant to introduce the enhanced sampling techniques and free energy calculation methods that have literally flourished in the last decades. Methods belonging to this class aim at quantifying the conformation dynamics in high accuracy but still with affordable computational cost. Different approaches to determine thermodynamics and kinetics, as well as the pathways of conformational change, will be presented.

Overall, the topics in this book were carefully chosen so as to focus on the latest developments in molecular modeling and simulations of biomolecules, although it is impossible to cover all of these recently developed methods due to the limited pages of this book. We managed to include the methods that have been applied and published in very recent peer-reviewed papers, but step-by-step instructions for using these methods are still lacking in the publications. We believe the topics we have chosen in this book will become an essential resource for students and researchers in this field.

Finally, we would like to conclude this Preface by thanking all the authors who devoted their precious time to contributing to the book, as well as Martine Felton, Development Editor at AIP Publishing, who provided a lot of help in preparing the book. Special thanks goes to Xubo Lin, who assisted us in reviewing part of the book.

We acknowledge the financial support from the National Key Research and Development Program of China (No. 2021YFF1200404) and the Fundamental Research Funds for the Central Universities of China (No. K20220228).

Yong Wang and Ruhong Zhou

Hangzhou, China

Riccardo Alessandri

Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL 60637, USA

Exequiel E. Barrera

Laboratorio de Integración de Señales Celulares, IHEM, Universidad Nacional de Cuyo, CONICET, Mendoza, Argentina, CP 5500

Institut Pasteur de Montevideo, Montevideo, Uruguay, Mataojo 2020, CP 11400

Wensheng Cai

College of Chemistry, Nankai University, Tianjin 300071, China

Siqin Cao

Department of Chemistry, University of Wisconsin−Madison, Madison, WI 53706, USA

Christophe Chipot

Laboratoire International Associé CNRS and University of Illinois at Urbana−Champaign, UMR n°7019, Université de Lorraine, BP 70239, F-54506 Vandœuvre-lès-Nancy, France

Mei Feng

College of Life Sciences, Shanghai Institute for Advanced Study, Institute of Quantitative Biology, Zhejiang University, Hangzhou, China

Haohao Fu

College of Chemistry, Nankai University, Tianjin 300071, China

Cristina Gil Herrero

Frankfurt Institute for Advanced Studies, Ruth-Moufang-Str. 1, 60438 Frankfurt am Main, Germany

Fabian Grünewald

Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands

Xuhui Huang

Department of Chemistry, University of Wisconsin−Madison, Madison, WI 53706, USA

Yandong Huang

College of Computer Engineering, JimeiUniversity, Xiamen 361021, China

Wenshuo Liang

DP Technology, Beijing 100080, China

Siewert J. Marrink

Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands

Raúl Mera-Adasme

Departamento de Ciencias del Ambiente, Facultad de Qúímica y Biología, Universidad de Santiago de Chile (USACH), Chile

Sergio Pantano

Institut Pasteur de Montevideo, Montevideo, Uruguay, Mataojo 2020, CP 11400

Yunrui Qiu

Department of Chemistry, University of Wisconsin−Madison, Madison, WI 53706, USA

Selim Sami

Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands

Xueguang Shao

College of Chemistry, Nankai University, Tianjin 300071, China

Tiefeng Song

College of Life Sciences, Institute of Quantitative Biology, Zhejiang University, Hangzhou, China

Yi Song

College of Life Sciences, Shanghai Institute for Advanced Study, Institute of Quantitative Biology, Zhejiang University, Hangzhou, China

Paulo C. T. Souza

Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS and University of Lyon, Lyon, France

Sebastian Thallmair

Frankfurt Institute for Advanced Studies, Ruth-Moufang-Str. 1, 60438 Frankfurt am Main, Germany

Ilona Christy Unarta

Department of Chemistry, University of Wisconsin−Madison, Madison, WI 53706, USA

Han Wang

Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Fenghao East Road 2, Beijing 100094, China

Liangdong Wang

College of Life Sciences, Institute of Quantitative Biology, Zhejiang University, Hangzhou, China

Qian Wang

Department of Physics, University of Science and Technology of China, Hefei, Anhui 230026, China

Yong Wang

College of Life Sciences, Shanghai Institute for Advanced Study, Institute of Quantitative Biology, Zhejiang University, Hangzhou, China

Kun Xi

Warshel Institute for Computational Biology, School of Life and Health Sciences, The Chinese University of Hong Kong (Shenzhen), Shenzhen, Guangdong, 518172, China

Kewei Xie

Department of Physics, University of Science and Technology of China, Hefei, Anhui 230026, China

Lingyuan Ye

Zhejiang University–University of Edinburgh Institute (ZJU–UoE Institute), International Campus of Zhejiang University, Haining 314400, China

Andrew Kai-hei Yik

Department of Chemistry, University of Wisconsin−Madison, Madison, WI 53706, USA

Darrin M. York

Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine, and Department of Chemistry and Chemical Biology, Rutgers the State University of New Jersey, New Brunswick, NJ 08901-8554, United States

Jinzhe Zeng

Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine, and Department of Chemistry and Chemical Biology, Rutgers the State University of New Jersey, New Brunswick, NJ 08901-8554, United States

Linfeng Zhang

DP Technology, Beijing 100080, China, AI for Science Institute, Beijing 100080, China

Ruhong Zhou

College of Life Sciences, Shanghai Institute for Advanced Study, Institute of Quantitative Biology, Zhejiang University, Hangzhou, China

Lizhe Zhu

Warshel Institute for Computational Biology, School of Life and Health Sciences, The Chinese University of Hong Kong (Shenzhen), Shenzhen, Guangdong, 518172, China

Rongfeng Zou

Shenzhen Jingtai Technology Co., Ltd. (XtalPi), Floor 3, Sf Industrial Plant, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen 518045, China