This is a project which is currently making use of HPC facilities at Newcastle University. It is active.
For further information about this project, please contact:
This project investigates small molecules associated with the human translation elongation factors eEF1A1 and eEF1A2. The work is adapted from Ken McGarry's RESKO approach and combines bioinformatics, cheminformatics, and pharmacological data analysis to identify candidate compounds, resolve molecular targets, curate quantitative activity data, assess isoform preference, evaluate alternative-target specificity, and prioritise compounds for in vitro experimental validation.
The project integrates large-scale compound activity datasets from databases with target metadata, protein annotations, and literature-derived evidence. Computational workflows are used to classify molecular and contextual activity records, analyse direct binding evidence, compare isoform affinity measurements, and evaluate off-target profiles across human proteins.
Further phases of the project include candidate prioritisation, structural analysis of eEF1A isoforms, molecular descriptor calculation, chemical similarity analysis, literature validation, protein-ligand docking studies, and development of evidence-based frameworks for compound ranking and influencing of future experimental design.
The project will be primarily written in R for data processing, statistical analysis and workflow automation. Computational tasks include large-scale data integration, processing of molecular activity and interaction datasets, structural bioinformatics, cheminformatics and selectivity analysis, protein docking simulations, and machine-learning-assisted prioritisation of candidate compounds.
Expected software and tools to be used: R, Python, pandas, openpyxl, tidyverse, data.table, bioconductor packages, RDKit, Jupyter notebooks, Autodock vina, MGLTools, Git and VS Code.