Native structure-based modeling and simulation of biomolecular systems per mouse click

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

The Trimeric Major Capsid Protein of Mavirus is stabilized by its Interlocked N-termini Enabling Core Flexibility for Capsid Assembly

Icosahedral viral capsids assemble with high fidelity from a large number of identical buildings blocks. The mechanisms that enable individual capsid proteins to form stable oligomeric units (capsomers) while affording structural adaptability required for further assembly into capsids are mostly unknown. Understanding these mechanisms requires knowledge of the capsomers' dynamics, especially for viruses where no additional helper proteins are needed during capsid assembly like for the Mavirus virophage that despite its complexity (triangulation number T = 27) can assemble from its major capsid protein (MCP) alone. This protein forms the basic building block of the capsid namely a trimer (MCP₃) of double-jelly roll protomers with highly intertwined N-terminal arms of each protomer wrapping around the other two at the base of the capsomer, secured by a clasp that is formed by part of the C-terminus. Probing the dynamics of the capsomer with HDX mass spectrometry we observed differences in conformational flexibility between functional elements of the MCP trimer. While the N-terminal arm and clasp regions show above average deuterium incorporation, the two jelly-roll units in each protomer also differ in their structural plasticity, which might be needed for efficient assembly. Assessing the role of the N-terminal arm in maintaining capsomer stability showed that its detachment is required for capsomer dissociation, constituting a barrier towards capsomer monomerisation. Surprisingly, capsomer dissociation was irreversible since it was followed by a global structural rearrangement of the protomers as indicated by computational studies showing a rearrangement of the N-terminus blocking part of the capsomer forming interface.

Rapid interpretation of small-angle X-ray scattering data

The fundamental aim of structural analyses in biophysics is to reveal a mutual relation between a molecule’s dynamic structure and its physiological function. Small-angle X-ray scattering (SAXS) is an experimental technique for structural characterization of macromolecules in solution and enables time-resolved analysis of conformational changes under physiological conditions. As such experiments measure spatially averaged low-resolution scattering intensities only, the sparse information obtained is not sufficient to uniquely reconstruct a three-dimensional atomistic model. Here, we integrate the information from SAXS into molecular dynamics simulations using computationally efficient native structure-based models. Dynamically fitting an initial structure towards a scattering intensity, such simulations produce atomistic models in agreement with the target data. In this way, SAXS data can be rapidly interpreted while retaining physico-chemical knowledge and sampling power of the underlying force field. We demonstrate our method’s performance using the example of three protein systems. Simulations are faster than full molecular dynamics approaches by more than two orders of magnitude and consistently achieve comparable accuracy. Computational demands are reduced sufficiently to run the simulations on commodity desktop computers instead of high-performance computing systems. These results underline that scattering-guided structure-based simulations provide a suitable framework for rapid early-stage refinement of structures towards SAXS data with particular focus on minimal computational resources and time.

Proteins are the molecular nanomachines in biological cells and thus vital to any known form of life. From the evolutionary perspective, viable protein structure emerges on the basis of a ‘form-follows-function’ principle. A protein’s designated function is inextricably linked to dynamic conformational changes, which can be observed by small-angle X-ray scattering. Intensities from SAXS contain low-resolution information on the protein’s shape at different steps of its functional cycle. We are interested in directly getting an atomistic model of this encoded structure. One powerful approach is to include the experimental data into computational simulations of the protein’s function-related physical motions. We combine scattering intensities with coarse-grained native structure-based models. These models are computationally highly efficient yet describe the system’s dynamics realistically. Here, we present our method for rapid interpretation of scattering intensities from SAXS to derive structural models, using minimal computational resources and time.

Using the folding landscapes of proteins to understand protein function

Proteins fold on a biologically-relevant timescale because of a funnel-shaped energy landscape. This landscape is sculpted through evolution by selecting amino-acid sequences that stabilize native interactions while suppressing stable non-native interactions that occur during folding. However, there is strong evolutionary selection for functional residues and these cannot be chosen to optimize folding. Their presence impacts the folding energy landscape in a variety of ways. Here, we survey the effects of functional residues on folding by providing several examples. We then review how such effects can be detected computationally and be used as assays for protein function. Overall, an understanding of how functional residues modulate folding should provide insights into the design of natural proteins and their homeostasis.