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School of Physical and Chemical Sciences

From data to discovery: development of a comprehensive bioinformatic toolkit for myosin studies

Research Group: Chemistry
Number of Students: 1
Length of Study in Years: 4 Years
Full-time Project: yes


Funding is provided via the China Scholarship Council.  

  • Available to Chinese applicants only.
  • Applicant required to start in September 2024.
  • The studentship arrangement will cover overseas tuition fees for the duration of the studentship.


Project Description

Myosins form a large and important superfamily of molecular motors1. While they share some common structural features, they cover a wide and diverse range of functions from muscle contraction to cell motility. Myosin studies have known a surge in the last decades. Several myosin mutations have been found to be associated with diseases such as cadiomyopathies and congenital myopathies, while the breakthrough discovery of omecamtiv mecarbil has highlighted the potential of myosin modulators for clinical applications2.

A large amount of information covering different aspects of myosins is now available, including data on sequence, structure, function, dynamics, genetic variants, post-translational modifications and small molecule modulators. The aim of the present project is to develop a comprehensive set of computational tools to integrate different information sources and perform advanced bioinformatics and structural analyses, which will enable researchers to test hypotheses, interpret existing data, design new experiments and develop AI-based tools to understand the molecular basis of disease and discover new therapeutics.  

Supervisory team: Dr Arianna Fornili (first supervisor) has unique expertise in the computational study of biomolecular structure and dynamics and in particular of proteins involved in muscle contraction. Recent contributions from the lab include extensive modelling studies of myosin dynamics for drug discovery and the development of methods for the prediction of rescue binding pockets in proteins3-8. More information can be found at Prof Conrad Bessant (second supervisor) is a leading expert in data science and AI solutions for biomedical research9-11. His lab is based in the Digital Environment Research Institute at QMUL ( More information can be found at

Environment: Queen Mary University of London (QMUL) is part of the Russell Group and it has been ranked joint 7th in the UK for the quality of its research in the last Research Excellence Framework (REF21) exercise. The proposed research will be performed at the Department of Chemistry (School of Physical and Chemical Sciences) and in collaboration with Prof Conrad Bessant’s lab at the Digital Environment Research Institute. The REF21 QMUL Chemistry submission was ranked 8th for impact and 9th in the UK for research outputs. Computational research at QMUL is supported by the shared High Performance Computing facility Apocrita ( QMUL is also partner in the Materials and Molecular Modelling (MMM) Hub, a UK-wide consortium that provides Tier-2 resources to the computational community in UK. All PhD students and Post-doctoral researchers are part of the QMUL Doctoral College (, which provides support with high-quality training and career development activities.


  1. B. J. Foth, M. C. Goedecke and D. Soldati, New insights into myosin evolution and classification, Proc. Natl. Acad. Sci. U.S.A., 2006, 103:3681–3686.
  2. S. M. Day, J. C. Tardiff and E. M. Ostap, Myosin modulators: emerging approaches for the treatment of cardiomyopathies and heart failure, Journal of Clinical Investigation, 2022, 132:e148557.
  3. Sonne, et al. Abnormal myosin post‐translational modifications and ATP turnover time associated with human congenital myopathy‐related RYR1 mutations. Acta Physiologica, 2023, 239:e14035.
  4. A. K. Antonovic, J. Ochala and A. Fornili, Comparative study of binding pocket structure and dynamics in cardiac and skeletal myosin, Biophysical Journal, 2023, 122:54–62.
  5. F. Akter, J. Ochala and A. Fornili, Binding pocket dynamics along the recovery stroke of human β-cardiac myosin, PLoS Comput Biol, 2023, 19:e1011099.
  6. S. Hashem, W. G. Davies, A. Fornili. Heart Failure Drug Modifies the Intrinsic Dynamics of the Pre-Power Stroke State of Cardiac Myosin. J. Chem. Inf. Model. 2020, 60:6438–46.
  7. M. Tiberti, A. Pandini, F. Fraternali, A. Fornili. In Silico Identification of Rescue Sites by Double Force Scanning. Bioinformatics, 2018, 34: 207–14.
  8. S. Hashem, M. Tiberti and A. Fornili, Allosteric modulation of cardiac myosin dynamics by omecamtiv mecarbil, PLoS Comput Biol, 2017, 13:e1005826.
  9. C. Basanta, et al. Community Detection in Empirical Kinase Networks Identifies New Potential Members of Signalling Pathways. PLoS Comput Biol, 2023, 19:e1010459.
  10. M. Hijazi, R. Smith, V. Rajeeve, C. Bessant, P. R. Cutillas. Reconstructing Kinase Network Topologies from Phosphoproteomics Data Reveals Cancer-Associated Rewiring. Nat Biotechnol, 2020, 38:493–502.
  11. S. Saha, D.A. Matthews, C. Bessant. High Throughput Discovery of Protein Variants Using Proteomics Informed by Transcriptomics. Nucleic Acids Res, 2018, 10:4893–4902.

Application Method:

To apply for this studentship and for entry on to the Chemistry programme (Full Time) please follow the instructions detailed on the following webpage:

Deadline for application - 31st of January 2024

Supervisor Contact Details:

For informal enquiries about this position, please contact Arianna Fornili



Applications are welcome from outstanding students with or expecting to obtain a degree in Chemistry, Pharmaceutical Chemistry, Bioinformatics, Biochemistry, Biophysics or related disciplines. Previous experience with biomolecular modelling and use/development of bioinformatics tools is desirable.

The minimum requirement for this studentship opportunity is a good Honours degree (minimum 2:1 honours or equivalent) and MSc/MRes in a relevant discipline (minimum 2:1 honours or equivalent).

You will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of 6.0 in Writing and 5.5 in all sections (Reading, Listening, Speaking) at the time of application to the CSC.


SPCS Academics: Dr Arianna Fornili