Protein-ligand binding with the coarse-grained Martini model

被引:143
作者
Souza, Paulo C. T. [1 ,2 ]
Thallmair, Sebastian [1 ,2 ]
Conflitti, Paolo [3 ]
Ramirez-Palacios, Carlos [1 ,2 ]
Alessandri, Riccardo [1 ,2 ]
Raniolo, Stefano [3 ]
Limongelli, Vittorio [3 ,4 ]
Marrink, Siewert J. [1 ,2 ]
机构
[1] Univ Groningen, Groningen Biomol Sci & Biotechnol Inst, Nijenborgh 7, NL-9747 AG Groningen, Netherlands
[2] Univ Groningen, Zernike Inst Adv Mat, Nijenborgh 7, NL-9747 AG Groningen, Netherlands
[3] Univ Svizzera Italiana USI, Inst Computat Sci, Fac Biomed Sci, Via G Buffi 13, CH-6900 Lugano, Switzerland
[4] Univ Naples Federico II, Dept Pharm, Via D Montesano 49, I-80131 Naples, Italy
基金
瑞士国家科学基金会;
关键词
MOLECULAR-DYNAMICS SIMULATIONS; ADENOSINE A(2A) RECEPTOR; COMPUTATIONAL DESIGN; T4; LYSOZYME; CRYSTAL-STRUCTURE; NONPOLAR CAVITY; DRUG DISCOVERY; FREE-ENERGIES; FXR; MECHANISM;
D O I
10.1038/s41467-020-17437-5
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The detailed understanding of the binding of small molecules to proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of protein-ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein-ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of ligand libraries or protein mutations using the coarse-grained Martini model. Computer-aided design of protein-ligand binding is important for the development of novel drugs. Here authors present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein-ligand binding interactions of small drug-like molecules.
引用
收藏
页数:11
相关论文
共 99 条
[1]   A Critical Review of Validation, Blind Testing, and Real-World Use of Alchemical Protein-Ligand Binding Free Energy Calculations [J].
Abel, Robert ;
Wang, Lingle ;
Mobley, David L. ;
Friesner, Richard A. .
CURRENT TOPICS IN MEDICINAL CHEMISTRY, 2017, 17 (23) :2577-2585
[2]   Gromacs: High performance molecular simulations through multi-level parallelism from laptops to supercomputers [J].
Abraham, Mark James ;
Murtola, Teemu ;
Schulz, Roland ;
Páll, Szilárd ;
Smith, Jeremy C. ;
Hess, Berk ;
Lindah, Erik .
SoftwareX, 2015, 1-2 :19-25
[3]   Accurate Estimation of Ligand Binding Affinity Changes upon Protein Mutation [J].
Aldeghi, Matteo ;
Gapsys, Vytautas ;
de Groot, Bert L. .
ACS CENTRAL SCIENCE, 2018, 4 (12) :1708-1718
[4]  
Alessandri R., 2019, THESIS
[5]   Pitfalls of the Martini Model [J].
Alessandri, Riccardo ;
Souza, Paulo C. T. ;
Thallmair, Sebastian ;
Melo, Manuel N. ;
de Vries, Alex H. ;
Marrink, Siewert J. .
JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2019, 15 (10) :5448-5460
[6]   Evidence for Cardiolipin Binding Sites on the Membrane-Exposed Surface of the Cytochrome bc1 [J].
Arnarez, Clement ;
Mazat, Jean-Pierre ;
Elezgaray, Juan ;
Marrink, Siewert-J ;
Periole, Xavier .
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 2013, 135 (08) :3112-3120
[7]   Holo-like and Druggable Protein Conformations from Enhanced Sampling of Binding Pocket Volume and Shape [J].
Basciu, Andrea ;
Malloci, Giuliano ;
Pietrucci, Fabio ;
Bonvin, Alexandre M. J. J. ;
Vargiu, Attilio V. .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2019, 59 (04) :1515-1528
[8]   Automated Parametrization of the Coarse-Grained Martini Force Field for Small Organic Molecules [J].
Bereau, Tristan ;
Kremer, Kurt .
JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2015, 11 (06) :2783-2791
[9]   Molecular Mechanism of Peroxisome Proliferator-Activated Receptor α Activation by WY14643: a New Mode of Ligand Recognition and Receptor Stabilization [J].
Bernardes, Amanda ;
Souza, Paulo C. T. ;
Muniz, Joao R. C. ;
Ricci, Clarisse G. ;
Ayers, Stephen D. ;
Parekh, Nili M. ;
Godoy, Andre S. ;
Trivella, Daniela B. B. ;
Reinach, Peter ;
Webb, Paul ;
Skaf, Munir S. ;
Polikarpov, Igor .
JOURNAL OF MOLECULAR BIOLOGY, 2013, 425 (16) :2878-2893
[10]   How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding? [J].
Betz, Robin M. ;
Dror, Ron O. .
JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2019, 15 (03) :2053-2063