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Brownian dynamics simulations of biomolecular diffusional association processes

Abstract (Expand)

Abstract Brownian dynamics (BD) is a computational method to simulate molecular diffusion processes. Although the BD method has been developed over several decades and is well established, new …d is well established, new methodological developments are improving its accuracy, widening its scope, and increasing its application. In biological applications, BD is used to investigate the diffusive behavior of molecules subject to forces due to intermolecular interactions or interactions with material surfaces. BD can be used to compute rate constants for diffusional association, generate structures of encounter complexes for molecular binding partners, and examine the transport properties of geometrically complex molecules. Often, a series of simulations is performed, for example, for different protein mutants or environmental conditions, so that the effects of the changes on diffusional properties can be estimated. While biomolecules are commonly described at atomic resolution and internal molecular motions are typically neglected, coarse‐graining and the treatment of conformational flexibility are increasingly employed. Software packages for BD simulations of biomolecules are growing in capabilities, with several new packages providing novel features that expand the range of questions that can be addressed. These advances, when used in concert with experiment or other simulation methods, such as molecular dynamics, open new opportunities for application to biochemical and biological systems. Here, we review some of the latest developments in the theory, methods, software, and applications of BD simulations to study biomolecular diffusional association processes and provide a perspective on their future use and application to outstanding challenges in biology, bioengineering, and biomedicine. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Software > Simulation Methods

Authors: Abraham Muñiz‐Chicharro, Lane W. Votapka, Rommie E. Amaro, Rebecca C. Wade

Date Published: 1st May 2023

Publication Type: Journal

Scaling Protein–Water Interactions in the Martini 3 Coarse-Grained Force Field to Simulate Transmembrane Helix Dimers in Different Lipid Environments

Abstract

Not specified

Authors: Ainara Claveras Cabezudo, Christina Athanasiou, Alexandros Tsengenes, Rebecca C. Wade

Date Published: 11th Apr 2023

Publication Type: Journal

Glycosaminoglycans: What Remains To Be Deciphered?

Abstract

Not specified

Authors: Serge Perez, Olga Makshakova, Jesus Angulo, Emiliano Bedini, Antonella Bisio, Jose Luis de Paz, Elisa Fadda, Marco Guerrini, Michal Hricovini, Milos Hricovini, Frederique Lisacek, Pedro M. Nieto, Kevin Pagel, Giulia Pairardi, Ralf Richter, Sergey A. Samsonov, Romain A. Vivès, Dragana Nikitovic, Sylvie Ricard Blum

Date Published: 27th Mar 2023

Publication Type: Journal

An artificial neural network model to predict structure-based protein–protein free energy of binding from Rosetta-calculated properties

Abstract

An artificial neural network protocol to compute protein–protein free energy of binding.

Authors: Matheus V. F. Ferraz, José C. S. Neto, Roberto D. Lins, Erico S. Teixeira

Date Published: 8th Mar 2023

Publication Type: Journal

Multiscale molecular simulations to investigate adenylyl cyclase‐based signaling in the brain

Abstract (Expand)

Abstract Adenylyl cyclases (ACs) play a key role in many signaling cascades. ACs catalyze the production of cyclic AMP from ATP and this function is stimulated or inhibited by the binding of their …ed by the binding of their cognate stimulatory or inhibitory Gα subunits, respectively. Here we used simulation tools to uncover the molecular and subcellular mechanisms of AC function, with a focus on the AC5 isoform, extensively studied experimentally. First, quantum mechanical/molecular mechanical free energy simulations were used to investigate the enzymatic reaction and its changes upon point mutations. Next, molecular dynamics simulations were employed to assess the catalytic state in the presence or absence of Gα subunits. This led to the identification of an inactive state of the enzyme that is present whenever an inhibitory Gα is associated, independent of the presence of a stimulatory Gα. In addition, the use of coevolution‐guided multiscale simulations revealed that the binding of Gα subunits reshapes the free‐energy landscape of the AC5 enzyme by following the classical population‐shift paradigm. Finally, Brownian dynamics simulations provided forward rate constants for the binding of Gα subunits to AC5, consistent with the ability of the protein to perform coincidence detection effectively. Our calculations also pointed to strong similarities between AC5 and other AC isoforms, including AC1 and AC6. Findings from the molecular simulations were used along with experimental data as constraints for systems biology modeling of a specific AC5‐triggered neuronal cascade to investigate how the dynamics of downstream signaling depend on initial receptor activation. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Software > Molecular Modeling

Authors: Siri C. van Keulen, Juliette Martin, Francesco Colizzi, Elisa Frezza, Daniel Trpevski, Nuria Cirauqui Diaz, Pietro Vidossich, Ursula Rothlisberger, Jeanette Hellgren Kotaleski, Rebecca C. Wade, Paolo Carloni

Date Published: 2023

Publication Type: Journal

Enhanced sampling simulations and machine learning to address infectious diseases

Abstract

Not specified

Author: Matheus Ferraz

Date Published: 2023

Publication Type: Doctoral Thesis

Computational Investigation of the Structure Kinetics Relationship of Small-Molecule Compounds Binding the Histamine-1-Receptor

Abstract

Not specified

Author: Melanie Kaeser

Date Published: 9th Dec 2022

Publication Type: Master's Thesis

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