Award details

In silico tools to study compensatory mechanisms in proteins: the novel double-force scanning method.

Reference	BB/M019829/1
Principal Investigator / Supervisor	Dr Arianna Fornili
Co-Investigators / Co-Supervisors	Professor Franca Fraternali
Institution	Queen Mary University of London
Department	Sch of Biological and Chemical Sciences
Funding type	Research
Value (£)	139,315
Status	Completed
Type	Research Grant
Start date	30/06/2015
End date	29/12/2016
Duration	18 months

Abstract

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). A remarkable aspect of rescue sites is that they can be directly exploited for drug discovery. In particular, the location and composition of rescue sites, especially when clustered in specific regions of the protein, can be used to design new drugs mimicking their compensatory effect. In this project, we propose to develop a novel computational method for the identification of mutations that can be rescued, together with the corresponding set of candidate rescue sites. The proposed method is unique in that a) it is based on first principles and thus general, b) it specifically identifies second sites that can rescue first site mutations through intra-molecular mechanisms, i.e. without involving interactions with partners, and c) it is not limited to the identification of rescue mutants but it can also detect compensatory mechanisms mediated by PTM and ligand binding. 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. The database will serve as a reference tool for theoreticians and experimentalists in designing new drugs against cardiovascular and skeletal muscle diseases.

Summary

Mutations in the amino acidic sequence of proteins can significantly alter their properties, including their 3D-structure, their motion and their ability to interact with other proteins. These modifications can be so dramatic that the protein is no longer able to perform its function. Indeed, many diseases have been associated with protein amino acidic mutations. The damaging effect of a disease-related mutation can be reversed or compensated by a second mutation in a different part of the protein. One important aspect of these so-called compensatory or rescue mutations is that they can be used to guide the discovery of new drugs. Indeed, the location on the protein and the characteristics of rescue mutations can inspire the design of drugs that can mimic their compensatory effect. The molecular basis of such compensatory mechanisms is not completely understood and it is difficult to predict whether a disease-related mutation can be rescued and how. Moreover, a systematic search of all the possible combinations of disease-related and rescue mutations is unrealistic to perform with experiments. In this project, we propose to develop a novel computational method for the identification of mutations that can be rescued, together with the corresponding set of candidate rescue mutations. The method is based on the simulation of the effects of many possible combinations of double mutations and makes use of parallel computing resources. After its implementation, the method will be applied to a set of proteins with known disease-related mutations from the skeletal and heart muscle. The rescue mutations identified by the method will be available to the scientific community and they will serve as a guide to design new drugs against cardiovascular and skeletal muscle diseases.

Impact Summary

The main outcomes of the project will be a) a novel computational method (double-force scanning or DFS method) to identify disease-related mutations whose damaging effects can be reversed, together with the corresponding set of rescue mutants and b) a complete and state-of-the-art database of candidate rescue sites in skeletal and cardiac muscle proteins. Scientific Advances and Knowledge. The immediate impact of the proposed research will be a deeper understanding of compensatory mechanisms at the atomistic level. The first direct beneficiaries of the research will be computational and experimental biochemists and biophysicists investigating the molecular basis of compensatory mechanisms to rescue disease phenotypes. The database of rescue sites in muscle proteins is expected to have a wide impact on the biomedical and pharmacological research of skeletal and cardiac muscle diseases. The database will also benefit the research of experimental biophysicists studying muscle regulation. Impact on Tools and Technology. The research will provide a complete set of tools and resources for the discovery of new compensatory sites in proteins. These will be delivered to the academic community and industry, in the UK and internationally, with traditional dissemination media (publications and congress communications) as well as by a centralised comprehensive web site. Since the location and composition of rescue sites can be directly used to build pharmacophoric models for drug design, we expect that the database of rescue sites in muscle proteins will serve as a reference tool for researchers in pharmaceutical companies. Moreover, the DFS method could be easily used in integrated computational/experimental approaches to rescue mutant discovery, where in vitro mutagenesis screenings are interactively guided by DFS predictions to reduce the cost and time of the overall process. e-tools. The computational methodologies and the software will be provided by a web interface integrating open standards and the most recent web technologies. The Co-Investigator (Prof. Fraternali) has co-developed several web services (POPS*, POPSCOMP, MinSet) and is maintaining the programs as well as the required infrastructure. It is predicted that UK-based and international users will profit from this centralised resource and the electronic delivery of tools and contents. Impact on Health. Understanding compensatory mechanisms can effectively boost the discovery of new drugs. In particular, knowledge of rescue mutants can be exploited on one side to focus the development of reactivating drugs on those pathogenic mutations that can be effectively rescued and on the other to define the regions in the protein that can be targeted by drugs. Therapeutic approaches based on rescuing disease-related mutations can be foreseen to become increasingly important, considering the wealth of data that large-scale genome projects are currently generating on genome variability and its association with either normal or disease phenotypes. In particular, the discovery of drugs targeting and reactivating proteins of the cardiac muscle affected by pathogenic mutations can effectively advance the treatment of hereditary cardiomyopathies. Impact on People. The post-doctoral research assistant (PDRA) will be trained in a highly rated and interdisciplinary environment at the boundaries with biophysics, biology and biomedicine, with the opportunity to develop a key core specialisation in molecular mechanisms that compensate pathogenic mutations in muscle proteins. The PDRA will also profit from the possibility to build a network of contacts with experts in muscle contraction and regulation at the Randall Division and from the opportunity to receive specialised training in scientific programming for molecular simulation. These skills will be essential in pursuing a scientific career and in improving prospects in both industry or academia.

Committee	Research Committee D (Molecules, cells and industrial biotechnology)
Research Topics	Structural Biology, Technology and Methods Development
Research Priority	X – Research Priority information not available
Research Initiative	Tools and Resources Development Fund (TRDF) [2006-2015]
Funding Scheme	X – not Funded via a specific Funding Scheme

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