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Molecular Docking Simulation

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1,3,4-oxadiazole derivatives: synthesis, characterization, antifungal activity, DNA binding investigations, TD-DFT calculations, and molecular modelling.

Journal of biomolecular structure & dynamics
1,3,4-Oxadiazole-based heterocyclic analogs (3a-3m) were synthesized cyclization of Schiff bases with substituted aldehydes in the presence of bromine and acetic acid. The structural clarification of synthesized molecules was carried out with variou...

Machine learning discovery of novel antihypertensive peptides from highland barley protein inhibiting angiotensin I-converting enzyme (ACE).

Food research international (Ottawa, Ont.)
Hypertension is a major global health concern, and there is a need for new antihypertensive agents derived from natural sources. This study aims to identify novel angiotensin I-converting enzyme (ACE) inhibitors from bioactive peptides derived from f...

Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials.

Scientific reports
Membrane incompatibility poses significant health risks, including severe complications and potential fatality. Surface modification of membranes has emerged as a pivotal technology in the membrane industry, aiming to improve the hemocompatibility an...

Identification of lipid metabolism-related gene markers and construction of a diagnostic model for multiple sclerosis: An integrated analysis by bioinformatics and machine learning.

Analytical biochemistry
BACKGROUND: Multiple sclerosis (MS) is an autoimmune inflammatory disorder that causes neurological disability. Dysregulated lipid metabolism contributes to the pathogenesis of MS. This study aimed to identify lipid metabolism-related gene markers an...

DisDock: A Deep Learning Method for Metal Ion-Protein Redocking.

Proteins
The structures of metalloproteins are essential for comprehending their functions and interactions. The breakthrough of AlphaFold has made it possible to predict protein structures with experimental accuracy. However, the type of metal ion that a met...

Identification of potent phytochemicals against Magnaporthe oryzae through machine learning aided-virtual screening and molecular dynamics simulation approach.

Computers in biology and medicine
Magnaporthe oryzae stands as a notorious fungal pathogen responsible for causing devastating blast disease in cereals, leading to substantial reductions in grain production. Despite the usage of chemical fungicides to combat the pathogen, their effec...

Identification of benzo(a)pyrene-related toxicological targets and their role in chronic obstructive pulmonary disease pathogenesis: a comprehensive bioinformatics and machine learning approach.

BMC pharmacology & toxicology
BACKGROUND: Chronic obstructive pulmonary disease (COPD) pathogenesis is influenced by environmental factors, including Benzo(a)pyrene (BaP) exposure. This study aims to identify BaP-related toxicological targets and elucidate their roles in COPD dev...

Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation.

International journal of molecular sciences
Transient receptor potential vanilloid 4 (TRPV4) is a calcium-permeable cation channel critical for maintaining intracellular Ca homeostasis and is essential in regulating immune responses, metabolic processes, and signal transduction. Recent studies...

Rational design and synthesis of pyrazole derivatives as potential SARS-CoV-2 M inhibitors: An integrated approach merging combinatorial chemistry, molecular docking, and deep learning.

Bioorganic & medicinal chemistry
The global impact of SARS-CoV-2 has highlighted the urgent need for novel antiviral therapies. This study integrates combinatorial chemistry, molecular docking, and deep learning to design, evaluate and synthesize new pyrazole derivatives as potentia...

In-silico exploring pathway and mechanism-based therapeutics for allergic rhinitis: Network pharmacology, molecular docking, ADMET, quantum chemistry and machine learning based QSAR approaches.

Computers in biology and medicine
Allergic rhinitis is a devastating health complication that interrupts the quality of daily life and significantly affects around 40 % of the population worldwide. Despite the availability of various treatment options, many patients continue to strug...