AIMC Topic: Molecular Docking Simulation
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Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model.
Chinese medical journal
Dec 23, 2024
BACKGROUND: Retinal ganglion cell (RGC) death caused by acute ocular hypertension is an important characteristic of acute glaucoma. Receptor-interacting protein kinase 3 (RIPK3) that mediates necroptosis is a potential therapeutic target for RGC deat...
Enhanced prediction of beta-secretase inhibitory compounds with mol2vec technique and machine learning algorithms.
SAR and QSAR in environmental research
Dec 20, 2024
A comprehensive computational strategy that combined QSAR modelling, molecular docking, and ADMET analysis was used to discover potential inhibitors for β-secretase 1 (BACE-1). A dataset of 1,138 compounds with established BACE-1 inhibitory activitie...
Residue-Level Multiview Deep Learning for ATP Binding Site Prediction and Applications in Kinase Inhibitors.
Journal of chemical information and modeling
Dec 17, 2024
Accurate identification of adenosine triphosphate (ATP) binding sites is crucial for understanding cellular functions and advancing drug discovery, particularly in targeting kinases for cancer treatment. Existing methods face significant challenges d...
ChemNTP: Advanced Prediction of Neurotoxicity Targets for Environmental Chemicals Using a Siamese Neural Network.
Environmental science & technology
Dec 11, 2024
Environmental chemicals can enter the human body through various exposure pathways, potentially leading to neurotoxic effects that pose significant health risks. Many such chemicals have been identified as neurotoxic, but the molecular mechanisms und...
Docking-Informed Machine Learning for Kinome-wide Affinity Prediction.
Journal of chemical information and modeling
Dec 10, 2024
Kinase inhibitors are an important class of anticancer drugs, with 80 inhibitors clinically approved and >100 in active clinical testing. Most bind competitively in the ATP-binding site, leading to challenges with selectivity for a specific kinase, r...
Natural compounds for Alzheimer's prevention and treatment: Integrating SELFormer-based computational screening with experimental validation.
Computers in biology and medicine
Dec 9, 2024
BACKGROUND: This study aimed to develop and apply a novel computational pipeline combining SELFormer, a transformer architecture-based chemical language model, with advanced deep learning techniques to predict natural compounds (NCs) with potential i...
Effective analysis of thyroid toxicity and mechanisms of acetyltributyl citrate using network toxicology, molecular docking, and machine learning strategies.
Toxicology
Dec 8, 2024
The growing prevalence of environmental pollutants has raised concerns about their potential role in thyroid dysfunction and related disorders. Previous research suggests that various chemicals, including plasticizers like acetyl tributyl citrate (AT...
Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of rheumatoid arthritis: Virtual screening to comprehensive in silico investigation.
PloS one
Dec 5, 2024
Rheumatoid arthritis (RA) affects an estimated 0.1% to 2.0% of the world's population, leading to a substantial impact on global health. The adverse effects and toxicity associated with conventional RA treatment pathways underscore the critical need ...
Machine learning-based analysis of programmed cell death types and key genes in intervertebral disc degeneration.
Apoptosis : an international journal on programmed cell death
Dec 4, 2024
Intervertebral disc degeneration (IVDD) is intricately associated with various forms of programmed cell death (PCD). Identifying key PCD types and associated genes is essential for understanding the molecular mechanisms underlying IVDD and discoverin...
Diverse regulated cell death patterns and immune traits in kidney allograft with fibrosis: a prediction of renal allograft failure based on machine learning, single-nucleus RNA sequencing and molecular docking.
Renal failure
Dec 4, 2024
Post-transplant allograft fibrosis remains a challenge in prolonging allograft survival. Regulated cell death has been widely implicated in various kidney diseases, including renal fibrosis. However, the role of different regulated cell death (RCD) ...
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