Nanomechanics of heart disease: investigating the effects of phosphorylation and HCM- causing mutations at the head-tail junction in cardiac myosin
Hypertrophic cardiomyopathy (HCM) is a genetic disease of the heart muscle and the primary identifiable cause of sudden cardiac death in young people. Excluding cardiac transplantation, HCM cannot be currently cured.
To date, about 300 HCM- related mutations have been reported in the cardiac sarcomere, the repeating unit of heart muscle cells. Part of these mutations are found in the Regulatory Light Chain (RLC) of Myosin II, the most important contractile protein in muscle. RLC is located at the myosin head-junction and it is part of the lever arm, whose power stroke is the result of the amplification of conformational changes occurring in the motor domain during the contractile cycle.
Several findings suggest that the phosphorylation state of RLC can influence the mechanical properties of myosin. Moreover, HCM-causing mutations in RLC have been shown to affect its phosphorylation levels. However, the molecular events triggered by RLC phosphorylation are still unknown.
In this project, we are using a combination of Molecular Modelling and Molecular Simulation techniques to study the effect of HCM-related mutations and of phosphorylation in RLC onto myosin mechanics. Results from simulations are being complemented with experimental NMR data. Funding and support: British Heart Foundation. Collaborators: Dr. Sergi Garcia-Manyes (KCL), Prof. Franca Fraternali (KCL), Dr. Mark Pfuhl (KCL).
In silico tools to study compensatory mechanisms in proteins
Many inherited and somatic diseases can be traced down to single nucleotide variations in coding regions of DNA. Indeed, mutations of single amino acids can significantly disrupt the function of a protein by affecting its structure, dynamics and interaction with partners. To date, several methods have been developed to predict the effect of mutations and their association with disease. A less studied phenomenon is the reversal or compensation of the effects of a mutation by modifications occurring at a second site of the protein. Second-site modifications can include mutations (rescue mutants), ligand binding or post-translational modifications (PTMs).
In this project, we will develop a novel computational method for the identification of mutations that can be rescued, together with the corresponding set of candidate rescue sites. After being implemented and tested on a set of proteins with known compensatory effects, the method will be applied to identify new candidate compensatory sites in a dataset of proteins with known pathogenic mutations from the skeletal and cardiac muscle. Funding and support: BBSRC. Collaborators: Prof. Franca Fraternali (KCL).
Collective variables from Structural Alphabets for the simulation of conformational changes and protein model refinement
The improvements illustrated in the recent literature and in the last CASP experiment suggest that model refinement methods based on Molecular Dynamics simulations may be finally coming of age. A big role in these developments is being played by the increased availability of computational power. However, an efficient model refinement method that can systematically and significantly improve the predictions of template-based modelling is still missing.
The present project aims at combining knowledge-based methods based on Structural Alphabets and enhanced sampling techniques to efficiently exploit high performance computing resources for model refinement. In many cases, improving the quality of models is essential for real life problems and effective refinement methods are expected to have a large impact on biological and pharmacological applications. Funding and support: HPC-EUROPA2, Red Española de Supercomputación. Collaborators: Dr. Alessandro Pandini (Brunel University).