Integrative bioinformatics approaches for the identification of novel targets and therapeutics for cell cycle changes and cell death

Secondary Supervisor(s): TBC

University of Registration: University of Birmingham

BBSRC Research Themes: Integrated Understanding of Health (Ageing, Regenerative Biology)

Project Outline

This project focuses on using integrative bioinformatics approaches and next-generation sequencing technologies to develop an in-silico framework for the identification of new targets (genes and proteins), as well as potential novel therapies that target cell cycle changes (cellular oscillation), cell plasticity, and cell apoptosis. Cell growth and invasion is a fundamental mechanism of many diseases, and plays a key role in other notable cell changes such as ageing. By investigating genetic and protein changes at different points of the cell cycle, we can identify how these different molecules are active at different stages of the cycle, and how they change during cell development. This has wide-reaching applications, as it can lead to the identification of potential markers that can be targeted at specific stages of cell development, changes related to ageing or to specific disease, and changes that should be targeted to prevent cell death.

The first axis of the project involves the development of a large-scale repository of single-cell RNA sequencing (scRNAseq) data and spatial transcriptomic data, and high-throughput ‘omic technologies (whole genome sequencing, whole exome sequencing). In particular, the project will focus on single-cell sequencing, and spatial transcriptomics, to probe genetic changes at a cellular level, using data from several large-scale scRNAaseq repositories (ex: BROAD scRNAseq portal). Development and implementation of analytical pipelines for next-generation sequencing data analysis (RNA-Seq, scRNA, etc) will be needed. Screening of genetic changes that play a role in cell oscillation will also be conducted on a large scale, involving thousands of cells. A representative example of assessing cell changes using scRNAseq can be found here: (https://doi.org/10.1101/2020.10.20.346643).

The second axis of the project focuses on 3D protein information and protein interaction data pertaining to cell-cycle oscillations and cell death. Lists of target proteins involved in key pathways pertaining to apoptosis and cell death will be selected using MSigDB, which contains curated genesets for canonical pathways, as well as relevant cellular pathways databases (KEGG and Reactome). The candidate will then develop networks of protein interactions for target proteins, based on 3D protein domain and structural information from structural databases such as the Protein Databank (PDB). These approaches will aid in the identification of new proteins that are involved in these biological and cellular processes. Where not available, the candidate will develop 3D models for proteins of interest, using a range of protein folding methods, including fold-recognition and threading, as well as ab-initio protein structure generation. A representative example of similar work can be found here: (https://www.nature.com/articles/srep08028). Collectively, a repository of protein structures will be generated, including scores for potential and novel protein-protein interactions. Protein structures of the repository will be used as part of virtual high-throughput screening approaches to identify novel therapeutics against cell apoptosis. The candidate will conduct these screens at an unprecedented large-scale: Both FDA-approved and experimental compounds from in-silico libraries will be tested against all of the protein targets from the repository. A variety of docking programs will be employed to assess drug-target interactions, and filter meaningful drug candidates. Further filtering of candidate hits will be assessed via molecular dynamics (MD) simulations of protein-drug interactions. These findings will be cross-referenced against pathways, to highlight potential compounds that can perturb biological mechanisms of apoptosis.

Both axes of the project will allow the candidate to develop an in-silico pipeline for rapid identification of potential therapeutics against genetic and proteins targets involved in cell death.