The druggability of small-molecule binding sites can be significantly affected by protein motions and conformational changes. Ligand binding, protein dynamics and protein function have been shown to be closely interconnected in myosins. The breakthrough discovery of omecamtiv mecarbil (OM) has led to an increased interest in small molecules that can target myosin and modulate its function for therapeutic purposes (myosin modulators). In this work, we use a combination of computational methods, including steered molecular dynamics, umbrella sampling and binding pocket tracking tools, to follow the evolution of the OM binding site during the recovery stroke transition of human β-cardiac myosin. We found that steering two internal coordinates of the motor domain can recapture the main features of the transition and in particular the rearrangements of the binding site, which shows significant changes in size, shape and composition. Possible intermediate conformations were also identified, in remarkable agreement with experimental findings. The differences in the binding site properties observed along the transition can be exploited for the future development of conformation-selective myosin modulators.

Motivation: A deleterious amino acid change in a protein can be compensated by a second-site rescue mutation. These compensatory mechanisms can be mimicked by drugs. In particular, the location of rescue mutations can be used to identify protein regions that can be targeted by small molecules to reactivate a damaged mutant. Results: We present the first general computational method to detect rescue sites. By mimicking the effect of mutations through the application of forces, the double force scanning (DFS) method identifies the second-site residues that make the protein structure most resilient to the effect of pathogenic mutations. We tested DFS predictions against two datasets containing experimentally validated and putative evolutionary-related rescue sites. A remarkably good agreement was found between predictions and experimental data. Indeed, almost half of the rescue sites in p53 was correctly predicted by DFS, with 65% of remaining sites in contact with DFS predictions. Similar results were found for other proteins in the evolutionary dataset. Availability and implementation: The DFS code is available under GPL at https://fornililab.github.io/dfs/. Supplementary information: Supplementary data are available at Bioinformatics online.

New promising avenues for the pharmacological treatment of skeletal and heart muscle diseases rely on direct sarcomeric modulators, which are molecules that can directly bind to sarcomeric proteins and either inhibit or enhance their activity. A recent breakthrough has been the discovery of the myosin activator omecamtiv mecarbil (OM), which has been shown to increase the power output of the cardiac muscle and is currently in clinical trials for the treatment of heart failure. While the overall effect of OM on the mechano-chemical cycle of myosin is to increase the fraction of myosin molecules in the sarcomere that are strongly bound to actin, the molecular basis of its action is still not completely clear. We present here a Molecular Dynamics study of the motor domain of human cardiac myosin bound to OM, where the effects of the drug on the dynamical properties of the protein are investigated for the first time with atomistic resolution. We found that OM has a double effect on myosin dynamics, inducing a) an increased coupling of the motions of the converter and lever arm subdomains to the rest of the protein and b) a rewiring of the network of dynamic correlations, which produces preferential communication pathways between the OM binding site and distant functional regions. The location of the residues responsible for these effects suggests possible strategies for the future development of improved drugs and the targeting of specific cardiomyopathy-related mutations.

MOTIVATION: GSATools is a free software package to analyze conformational ensembles and to detect functional motions in proteins by means of a structural alphabet. The software integrates with the widely used GROMACS simulation package and can generate a range of graphical outputs. Three applications can be supported: (i) investigation of the conformational variability of local structures; (ii) detection of allosteric communication; and (iii) identification of local regions that are critical for global functional motions. These analyses provide insights into the dynamics of proteins and allow for targeted design of functional mutants in theoretical and experimental studies. AVAILABILITY: The C source code of the GSATools, along with a set of pre-compiled binaries, is freely available under GNU General Public License from http://mathbio.nimr.mrc.ac.uk/wiki/GSATools.

BACKGROUND: The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis. RESULTS: A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness. CONCLUSIONS: The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics.