The theoretical, computational and cultural challenges that need to be overcome to gain an understanding of the biological mesoscale are described and potential solutions are offered.
Abstract
Physics-based models of biomolecular systems that explicitly represent biomolecular structure and mechanics, such as atomistic molecular dynamics simulations are well-established because experimental data has been available to iteratively improve and validate models. Now, simulations of the biological mesoscale are growing in importance because of the improvements in experimental tools to visualise this regime. This includes techniques such as cryo-electron microscopy and tomography, microscopies that follow individual proteins in their cellular contexts, in situ scattering to follow the dynamic evolution of biomolecular assembly, and -omics tools. Together, these approaches alone and in combination have revealed the importance of interactomes that bridge multiple scales. Here we describe the theoretical, computational and cultural challenges that need to be overcome to gain an understanding of the biological mesoscale and offer potential solutions. This commentary is the result of a joint CECAM/CCPBioSim discussion workshop on how the community should address the challenges of biomolecular simulations at the mesoscale held in Trento, Italy in the summer of 2024. The aim is to provide a broad overview of the tools and techniques relevant to the biological mesoscale, and to signpost the reader to more detailed discussions within the cited literature.
Protein–protein interactions are stochastic and play a central role in determining the structural and dynamic properties of biological systems. Computational approaches that account for the probabilistic nature of these interactions are therefore essential for understanding processes ranging from molecular self-assembly to biomolecular phase separation. Among these approaches, Monte Carlo (MC) methods have become important tools for investigating protein systems across multiple spatial and temporal scales. This review examines the application of MC simulations to protein–protein interactions, with particular emphasis on Metropolis Monte Carlo (MMC) and kinetic Monte Carlo (KMC) methods as complementary approaches for investigating equilibrium properties and dynamic molecular processes. Applications ranging from receptor organization and protein aggregation to biomolecular condensation and liquid–liquid phase separation are discussed together with the evolution of coarse-grained models, from isotropic particles to anisotropic patchy particles and polymer representations that capture directional, multivalent, and sequence-dependent interactions. Finally, the integration of MC simulations with experimental techniques is reviewed through applications involving Small Angle X-ray and Neutron Scattering (SAXS/SANS), single-molecule tracking, and fluorescence-based methods, highlighting how experimentally accessible observables can be directly compared with simulation results to characterize protein interactions and estimate molecular parameters.
L. D. de Oliveira, Luiz Fernando de Camargo Rodrigues, R. Itri· Biophysical Reviews· 0 citations
Mechanically interlocked molecules, such as rotaxanes and catenanes, display complex internal dynamics and reciprocal motions that are central to their use as artificial molecular machines. Revealing how these motions occur, the key interactions, and the rate-limiting steps determining their kinetics is essential for understanding and designing functional systems. However, due to scale-, space-, and time-resolution limits, this is typically not easy to access via experimental techniques. In this Personal Account, we discuss representative examples from our recent work using classical molecular dynamics and metadynamics simulations to investigate the key mechanisms, the thermodynamics, and kinetics of the internal dynamics of rotaxanes and catenanes. This allows access to the dynamics of mechanically interlocked systems at atomistic resolution, disentangling bound, unbound, and intermediate states and the dynamical interconversion between them, and providing information on kinetic barriers and characteristic timescales. Such atomistic-scale simulations provide results that are reliable and in very good agreement with the available experimental measurements. Overall, this account illustrates the value of molecular simulations as a predictive and complementary tool for understanding mechanically interlocked molecules in motion.
Clara Sabrià, Luigi Leanza, Massimo Delle Piane et al.· The chemical record· 0 citations
Molecular dynamics (MD) simulations are widely used to investigate membrane properties and their interactions with various plastic particles. In this tutorial, we provide guidelines for both atomistic and coarse-grained MD simulations to investigate interactions between a POPC membrane and a polystyrene (PS) nanoplastic. This tutorial is organized into a few exercises focusing on three systems: (i) PS in water, (ii) POPC membrane in water, and (iii) POPC–PS complex in water, each simulated at atomistic and coarse-grained levels. The aim of this tutorial is to familiarize readers with the process of modeling nanoplastic and membrane systems using CHARMM-GUI and performing MD simulations with GROMACS. In addition, we calculate a few biophysical properties, including the radius of gyration of PS, membrane thickness, area per lipid, order parameters, and diffusion coefficient of POPC lipids, using GROMACS analysis tools and tcl scripts. Overall, the workflow presented here provides a practical guide for readers to model, simulate, and analyze their own complex biophysical systems involving membranes and nanoplastics.
Sasthi C. Mandal, Atanu Acharya· Journal of Physical Chemistr...· 1 citation
Understanding and controlling chemical reactivity in biological systems require atomic-level insight into processes that are often inaccessible to experiments. Hybrid quantum mechanics/molecular mechanics (QM/MM) simulations provide a powerful framework for describing chemical reactions in complex environments, but their practical application remains limited by fragmented software ecosystems, restricted accessibility, and methodological approximations that can compromise accuracy and reproducibility. In particular, many existing QM/MM implementations rely on ad hoc couplings, proprietary software, or truncated treatments of long-range electrostatic interactions. Here, we present a robust and fully periodic QM/MM interface between the open-source molecular dynamics engine GROMACS and the electronic structure theory code CP2K. The implementation enables efficient and reproducible QM/MM molecular dynamics and enhanced sampling simulations with a consistent treatment of long-range electrostatics under periodic boundary conditions. By combining the strengths of two widely used community codes, this interface provides a general and scalable platform for studying chemical reactivity in biological systems and establishes a transparent reference implementation for QM/MM simulations.
D. Morozov, C. Blau, Ole Schütt et al.· Journal of Chemical Informat...· 0 citations
Classical molecular dynamics is a theoretical method useful for investigating noncovalent intermolecular interactions and conformational flexibility, enabling the simulation of processes such as aggregation/dissolution and adsorption. Molecular dynamics and quantum chemistry are increasingly introduced in chemistry curricula, yet students may encounter difficulties when translating theoretical concepts into robust simulation protocols, particularly outside biomolecular systems. Here, we present a tutorial designed to guide students through the preparation, execution, and analysis of the simulations of small organic molecules in nonaqueous solvents, followed by the calculation of ultraviolet–visible (UV–vis) absorption spectra using time-dependent density functional theory. This tutorial focuses on several practical issues: obtaining force-field parameters, building simulation cells, selecting ensembles, and interpreting critical simulation parameters. Custom solvent models are validated against reference density and radial distribution functions, demonstrating how selected observables can be used to assess simulation reliability. We illustrate the usefulness of molecular dynamics by showing that molecular flexibility and solvent interactions broaden the UV–vis absorption band of indigo in chloroform. This contribution is intended as a hands-on educational resource for upper-level undergraduate and graduate students enrolled in physical chemistry and computational chemistry courses, as well as for Ph.D. students working in chemistry, physics, or material science, who are approaching molecular simulations. To support dissemination, we have released a ready-to-use package on GitHub that includes solvent boxes and all the necessary files and data for incorporating new molecules into GROMACS simulations: https://github.com/cippee/SolventSafari-for-GROMACS.
C. Picarelli, G. Raffaini, M. Tommasini· Journal of Chemical Educatio...· 0 citations
Macromolecular crowding is a fundamental feature of the cellular environment that strongly influences biomolecular structure, dynamics, and phase behavior. Despite its significance, it has been a challenge to represent and capture the effects of the crowded environment accurately and sufficiently in molecular simulations. This review discusses the challenges and recent progress in the development of computational approaches for modelling and simulating biomolecular processes in a crowded milieu. The review focuses on the new view of crowding, which highlights the interplay of entropic and enthalpic effects. Emerging data-driven strategies are discussed for improving force-field representations and predicting biomolecular behavior in crowded media, with particular emphasis on generating synthetic datasets, using simulation-derived descriptors, and employing combinatorial frameworks for unravelling microscopic origins of crowding.
Shivnandi, Divya Nayar· Current Opinion in Structura...· 0 citations
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