Protein Structure Prediction Using Coarse-Grained Models

SBMOpenMM: A Builder of Structure-Based Models for OpenMM

Molecular dynamics (MD) simulations have become a standard tool to correlate the structure and function of biomolecules and significant advances have been made in the study of proteins and their complexes. A major drawback of conventional MD simulations is the difficulty and cost of obtaining converged results, especially when exploring potential energy surfaces containing considerable energy barriers. This limits the wide use of MD calculations to determine the thermodynamic properties of biomolecular processes. Indeed, this is true when considering the conformational entropy of such processes, which is ultimately critical in assessing the simulations' convergence. Alternatively, a wide range of structure-based models (SBMs) has been used in the literature to unravel the basic mechanisms of biomolecular dynamics. These models introduce simplifications that focus on the relevant aspects of the physical process under study. Because of this, SBMs incorporate the need to modify the force field definition and parameters to target specific biophysical simulations. Here we introduce SBMOpenMM, a Python library to build force fields for SBMs, that uses the OpenMM framework to create and run SBM simulations. The code is flexible and user-friendly and profits from the high customizability and performance provided by the OpenMM platform.

Behavior of Proteins under Pressure from Experimental Pressure-Dependent Structures

Structure-based models are coarse-grained representations of the interactions responsible for the protein folding process. In their simplest form, they use only the native contact map of a given protein to predict the main features of its folding process by computer simulation. Given their limitations, these models are frequently complemented with sequence-dependent contributions or additional information. Specifically, to analyze the effect of pressure on the folding/unfolding transition, special forms of these interaction potentials are employed, which may a priori determine the outcome of the simulations. In this work, we have tried to keep the original simplicity of structure-based models. Therefore, we have used folded structures that have been experimentally determined at different pressures to define native contact maps and thus interactions dependent on pressure. Despite the apparently tiny structural differences induced by pressure, our simulation results provide different thermodynamic and kinetic behaviors, which roughly correspond to experimental observations (when there is a possible comparison) of two proteins used as benchmarks, hen egg-white lysozyme and dihydrofolate reductase. Therefore, this work shows the feasibility of using experimental native structures at different pressures to analyze the global effects of this physical property on the protein folding process.