Eugene N. Muratov

This paper introduces a contrastive graph neural network to discover novel larvicidal compounds against Aedes aegypti, identifying LC-79 as a potent and selective candidate.

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.

The paper introduces a semantic-aware graph neural network framework for drug discovery, identifying LC-61 as a potent antileishmanial compound with nanomolar activity.

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.

The paper presents a framework that predicts endocrine disruptors using a multimodal cross-attentive graph model, achieving high accuracy and providing mechanistic explanations.

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 uses machine learning to identify novel HDAC6/AKT2 inhibitors for myeloid cancer treatment, finding compounds with potent anticancer activity.

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.