Philip M. Gribbon

The paper identifies host-targeting antivirals against SARS-CoV-2 using morphological profiling, finding compounds that reverse infected cell phenotypes and validate host processes hijacked by viruses.

The paper optimizes and evaluates two cell-based assays for degrader discovery, finding that the signal rescue assay reliably identifies active degraders and filters out non-specific compounds.

The paper develops a machine learning model to predict drug-induced phospholipidosis using a large dataset of repurposed drugs tested across multiple cell lines.

The paper develops ML models to predict antimicrobial activity of small molecules using a knowledge graph, achieving 75.9% accuracy in identifying active compounds.

The paper develops two annotation pipelines and dashboards to integrate chemical and bioactivity data for drug repurposing, validated on a compound library with over 5000 compounds.

This paper describes a journey towards implementing FAIR data practices in antimicrobial resistance research, transitioning from spreadsheet-based data to a knowledge graph framework.

The paper analyzes patent data from SureChEMBL to assess the drug-likeness and clinical development stage of compounds, providing insights into their relevance for pharmaceutical discovery.

The paper identifies CPI-169 as a competitive inhibitor of SARS-CoV-2 PLpro that targets the same binding site as GRL-0617, through a drug repurposing screening approach that accounts for redox-sensitivity.

This study identifies ADAMTS-7 as a risk factor for atherosclerosis by degrading TIMP-1, reducing its inhibition of MMP-9 and promoting collagen degradation.

PEMT extracts patent information linked to chemical structures and gene names from public databases to support drug discovery and research.

This paper constructs a Monkeypox knowledge graph to represent chemical entities and biological aspects of MPXV, integrating data for comprehensive analysis.

MICHA is a pipeline that FAIRifies chemosensitivity assays by automatically annotating compounds, samples, reagents, and data processing methods, enabling interoperable and reusable drug screening data.

The paper identifies 62 new inhibitors of SARS-CoV-2 3CL-Pro through a compound repurposing screen and validates their activity using X-ray crystallography.

The paper presents a drug-target-mechanism graph to identify synergistic drug combinations for SARS-CoV-2 treatment, validated through experimental testing.