AIMC Topic: Molecular Docking Simulation

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Multi-omics Mendelian randomization and machine learning identify candidate therapeutic targets for Alzheimer's and Parkinson's diseases.

Mammalian genome : official journal of the International Mammalian Genome Society
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are major public health challenges lacking effective therapies. To identify potential drug targets, we integrated large-scale genome-wide association ...

Machine learning and network pharmacology identify keloid biomarkers (AMPH, TNFRSF9) and therapeutic targets (IL6, HAS2) for aloe-derived quercetin.

PloS one
OBJECTIVE: This study aimed to identify diagnostic biomarkers for keloid and explore potential therapeutic agents from traditional Chinese medicine (TCM) by integrating network pharmacology approaches. Specifically, we sought to uncover key molecular...

AI-driven peptide discovery for endometrial cancer: deep generative modeling and molecular simulation in the big data era.

Journal of computer-aided molecular design
The integration of artificial intelligence (AI) with molecular modeling offers new opportunities to accelerate therapeutic discovery. In this study, we developed an AI-driven generative pipeline combining deep reinforcement learning (DRL), generative...

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...

Leak Proof PDBBind: A Reorganized Data Set of Protein-Ligand Complexes for More Generalizable Binding Affinity Prediction.

The journal of physical chemistry. B
The majority of machine learning scoring functions used in drug discovery for predicting protein-ligand binding poses and affinities have been trained on the PDBBind data set. However, it is unclear whether these new scoring functions are actually an...

Construction of an early diagnostic model for pulmonary hypertension based on aging-related signature genes and identification of potential therapeutic targets.

Scientific reports
Pulmonary hypertension (PH) is a progressive cardiopulmonary disorder. It features elevated pulmonary arterial pressure, which leads to right ventricular failure and increased mortality. PH's insidious nature, with no specific clinical symptoms, hind...

Computational characterization and machine learning analysis of quantum optimized marine fungal metabolites targeting PD-L1 in cancer immunotherapy.

Journal of computer-aided molecular design
Cancer immune evasion is predominantly mediated through immune checkpoint pathways, such as the PD-1/PD-L1 axis. In this mechanism, PD-L1, which is often overexpressed on tumor cells, binds to PD-1 receptors on T cells, resulting in the inhibition of...

Flexible protein-ligand docking with diffusion-based side-chain packing.

Proceedings of the National Academy of Sciences of the United States of America
Understanding protein structure and dynamics is crucial for basic biology and drug design. Conventional methods often provide static conformations that inadequately capture protein flexibility. We present PackDock, a framework that integrates deep le...

Unraveling diethyl phthalate-induced prostate carcinogenesis: core targets revealed by integrated network toxicology, machine learning, and structural validation.

Human genomics
PURPOSE: Diethyl phthalate (DEP), a widely distributed environmental contaminant, is epidemiologically linked to prostate cancer (PCa). However, its molecular mechanisms beyond endocrine disruption remain poorly defined. We aimed to investigate the c...

Unraveling tissue-specific molecular targets of dihydroartemisinin in non-small cell lung cancer: an integrative machine learning and network pharmacology approach.

Medical oncology (Northwood, London, England)
Non-small cell lung cancer (NSCLC) presents significant therapeutic challenges due to resistance and immune evasion. Dihydroartemisinin (DHA), a derivative of artemisinin, exhibits broad anti-tumor activity, but its molecular targets and mechanisms i...