AIMC Topic: Drug Evaluation, Preclinical

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Deep contrastive learning enables genome-wide virtual screening.

Science (New York, N.Y.)
Recent breakthroughs in protein structure prediction have opened new avenues for genome-wide drug discovery, yet existing virtual screening methods remain computationally prohibitive. We present DrugCLIP, a contrastive learning framework that achieve...

AttentionScore: A Target-Specific, Bias-Aware Scoring Function for Structure-Based Virtual Screening: A Case Study on METTL3.

Journal of chemical information and modeling
Target-specific scoring functions offer a promising route to improve structure-based virtual screening beyond generic, bias-prone scoring schemes. Here, we introduce AttentionScore, a deep learning-based scoring function for METTL3 that integrates li...

kinCSM-RTK: Machine Learning-Based Screening of Receptor Tyrosine Kinase Inhibitors in Drug Discovery.

Journal of chemical information and modeling
Receptor tyrosine kinases (RTKs) are key regulators of cellular functions, such as differentiation, migration and proliferation. Dysregulated RTK activity contributes to various diseases, including neurological disorders and cancer, for which small m...

Discovery of Tetrahydroisoquinoline-Based SARS-CoV-2 Helicase Inhibitors with Iterative, Deep Learning-Enhanced Virtual Screening.

Journal of chemical information and modeling
In this study, we pursued a structure-based drug discovery campaign targeting the SARS-CoV-2 helicase through three rounds of virtual screening (VS) enhanced with Artificial Intelligence (AI). The third round incorporated a deep neural network (DNN) ...

An open-source screening platform accelerates discovery of drug combinations.

Nature communications
Drug combinations are essential to modern medicine, but their discovery remains slow and inefficient as experimental complexity expands rapidly with each additional drug tested. Although modern liquid handling systems enable complex and highly custom...

Active learning framework leveraging transcriptomics identifies modulators of disease phenotypes.

Science (New York, N.Y.)
Phenotypic drug screening remains constrained by the vastness of chemical space and the technical challenges of scaling experimental workflows. To overcome these barriers, computational methods have been developed to prioritize compounds, but they re...

Predicted peptide scaffolds for drug screening in endometrial cancer organoids.

Scientific reports
AlphaFold, a deep learning-based platform widely used to predict protein and peptide structures, was employed in this study to model the self-assembling peptide RFC, which demonstrated a stable α-helical structure with high confidence. This structura...

Co-cultured sensory neuron classification using extracellular electrophysiology and machine learning approaches for enhancing analgesic screening.

Journal of neural engineering
Chronic pain affects over 20% of the adult population in the United States, posing a substantial personal as well as economic burden and contributing to the ongoing opioid crisis. Effective, non-addictive chronic pain treatments are urgently needed. ...

Identification of a novel Aurora B inhibitor using the AI-driven drug screening and docking-based traditional screening.

Bioorganic & medicinal chemistry
Aurora B, a subtype of Aurora kinases that functions as a serine/threonine kinase, playing a vital role in the process of mitosis, is often overexpressed in certain tumor cells leading to tumorigenesis and progression. Therefore, the development of s...