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Molecular Docking Simulation

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Artificial-Intelligence Bio-Inspired Peptide for Salivary Detection of SARS-CoV-2 in Electrochemical Biosensor Integrated with Machine Learning Algorithms.

Biosensors
Developing affordable, rapid, and accurate biosensors is essential for SARS-CoV-2 surveillance and early detection. We created a bio-inspired peptide, using the SAGAPEP AI platform, for COVID-19 salivary diagnostics via a portable electrochemical dev...

Unveiling the molecular mechanisms of Haitang-Xiaoyin Mixture in psoriasis treatment based on bioinformatics, network pharmacology, machine learning, and molecular docking verification.

Computational biology and chemistry
OBJECTIVE: Psoriasis is a common clinical skin inflammatory disease. Haitang-Xiaoyin Mixture (HXM) represents a traditional Chinese medicine formulation utilized clinically for the management of psoriasis, which can reduce the psoriasis area and seve...

Computational approaches for decoding structure-saltiness enhancement and aroma perception mechanisms of odorants: From machine learning to molecular simulation.

Food research international (Ottawa, Ont.)
The unclear relationship between structure and saltiness enhancement limits the development and application of savory odorants. The structure characteristic-saltiness enhancement perception (SEP) mechanisms of savory odorants were investigated by mac...

Air pollution and prostate cancer: Unraveling the connection through network toxicology and machine learning.

Ecotoxicology and environmental safety
BACKGROUND: In recent years, air pollution has been demonstrated to be associated with the occurrence of various diseases. This study aims to explore the potential association between air pollutants and prostate cancer (PCa) and to identify key genes...

Compact Assessment of Molecular Surface Complementarities Enhances Neural Network-Aided Prediction of Key Binding Residues.

Journal of chemical information and modeling
Predicting interactions between proteins is fundamental for understanding the mechanisms underlying cellular processes, since protein-protein complexes are crucial in physiological conditions but also in many diseases, for example by seeding aggregat...

The Mechanism of Bisphenol S-Induced Atherosclerosis Elucidated Based on Network Toxicology, Molecular Docking, and Machine Learning.

Journal of applied toxicology : JAT
The increasing prevalence of environmental pollutants has raised public concern about their potential role in diseases such as atherosclerosis (AS). Existing studies suggest that chemicals, including bisphenol S (BPS), may adversely affect cardiovasc...

A semiempirical and machine learning approach for fragment-based structural analysis of non-hydroxamate HDAC3 inhibitors.

Biophysical chemistry
Interest in HDAC3 inhibitors (HDAC3i) for pharmacological applications outside of cancer is growing. However, concerns regarding the possible mutagenicity of the commonly used hydroxamates (zinc-binding groups, ZBGs) are also increasing. Considering ...

Discovery of New HER2 Inhibitors via Computational Docking, Pharmacophore Modeling, and Machine Learning.

Molecular informatics
The human epidermal growth factor receptor 2 (HER2) is a critical oncogene implicated in the development of various aggressive cancers, particularly breast cancer. Discovering novel HER2 inhibitors is crucial for expanding therapeutic options for HER...

A dataset for machine learning-based QSAR models establishment to screen beta-lactamase inhibitors using the FARM -BIOMOL chemical library.

BMC research notes
OBJECTIVES: Beta-lactamase is a bacterial enzyme that deactivates beta-lactam antibiotics, and it is one of the leading causes of antibiotic resistance problems globally. In current drug discovery research, molecular simulation, like molecular dockin...

Increase Docking Score Screening Power by Simple Fusion With CNNscore.

Journal of computational chemistry
Scoring functions (SFs) of molecular docking is a vital component of structure-based virtual screening (SBVS). Traditional SFs yield their inherent shortage for idealized approximations and simplifications predicting the binding affinity. Complementa...