Alexander Tropsha

The paper introduces EC-KG, a unified biomedical knowledge graph for drug repurposing that integrates multiple existing knowledge graphs to enhance coverage and uncover novel mechanistic pathways.

This paper identifies broad-spectrum filovirus inhibitors using computational screening and validates them against multiple viral species, finding synergistic compound pairs effective against Ebola and Marburg viruses.

This paper develops a computational pipeline to identify conserved antiviral target sites in alphaviruses using AI-driven methods, validating potential drug targets through mutagenesis.

This study identifies conserved binding sites in filovirus proteins to guide the development of broad-spectrum antivirals, finding high conservation in L and VP40 proteins and validating existing drugs like Remdesivir.

This paper develops a machine learning framework using Bayesian optimization to enhance the yield and purity of AAV vectors in gene therapy.

TARRAGON prioritizes and validates therapeutic targets for non-muscle invasive urinary bladder cancer using a computational framework integrating knowledge graphs and large language models.

This study identifies synergistic combinations of quorum-sensing inhibitors and antibiotics to combat antibiotic-resistant bacteria, finding that piperacillin with ketoprofen, indomethacin, and piroxicam shows broad antimicrobial action.

The paper curates a database of helicase inhibitors, Heli-SMACC, and tests selected compounds against SARS-CoV-2 NSP13 ATPase, finding twelve inhibitors with dose-response activity.

The paper curates a database of antiviral compounds tested against 13 emerging viruses, identifies potential broad-spectrum antivirals, and highlights the need for coordinated research efforts.

The paper identifies five compounds that inhibit SARS-CoV-2 replication by binding to ACE2 without disrupting its enzymatic function, serving as potential acute treatments for COVID-19.