AIMC Topic: Molecular Docking Simulation

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Triclosan exposure potentiates ischemic stroke risk: Multi-omics integration and molecular docking unveil neurotoxic mechanisms.

Ecotoxicology and environmental safety
This study applied network toxicology and multimodal biological approaches integrated with machine learning to systematically identify four TCS-IS-related genes, providing a comprehensive understanding of the pathophysiological relationship between t...

Artificial intelligence-driven discovery of novel scaffolds for selective TLR7 antagonists and their application in enhancing mRNA translation efficiency.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Toll-like receptor 7 (TLR7) is crucial in the innate immune response, responsible for recognizing single-stranded RNA from external pathogens and initiating the production of inflammatory cytokines and type I interferons. Despite the potential therap...

Multi-omics reveals the polyethylene terephthalate carcinogenicity: Cancer progression and immune microenvironment.

Ecotoxicology and environmental safety
Polyethylene terephthalate (PET), a polymer widely used in consumer products, has recently been implicated in cancer progression, though its mechanistic underpinnings remain elusive. This multidisciplinary study systematically investigates PET's carc...

Next-generation cancer therapeutics: unveiling the potential of liposome-based nanoparticles through bioinformatics.

Mikrochimica acta
Cancer remains one of the most deadly diseases in the world, requiring constant growth and improvements in therapeutic strategies. Traditional cancer treatments, such as chemotherapy, radiotherapy, and surgery, have limitations like off-target releas...

Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.

Drug design, development and therapy
OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medicines, while alleviate symptoms, fail to reverse the disease progression or reduce its harmful effects, and exhibit toxicity and side effects such as ga...

A novel predictive model and therapeutic potential of quercetin derivatives in chronic kidney disease progression.

Biochemical pharmacology
Chronic kidney disease (CKD) remains a pressing global health issue with limited therapeutic options. The loss of nephrons is a crucial pathological change driving CKD progression, influenced by diverse programmed cell death (PCD) pathways, yet the p...

Integrated network toxicology, machine learning and molecular docking reveal the mechanism of benzopyrene-induced periodontitis.

BMC pharmacology & toxicology
BACKGROUND: Environmental pollutants, particularly from air pollution and tobacco smoke, have emerged as significant risk factors. Benzopyrene (BaP), a Group 1 carcinogen, is ubiquitously present in these pollutants, yet its molecular mechanisms in p...

Improving Covalent and Noncovalent Molecule Generation via Reinforcement Learning with Functional Fragments.

Journal of chemical information and modeling
Small-molecule drugs play a critical role in cancer therapy by selectively targeting key signaling pathways that drive tumor growth. While deep learning models have advanced drug discovery, there remains a lack of generative frameworks for covalent ...

Machine learning framework coupled with CADD for predicting sphingosine kinase 1 inhibitors.

Computers in biology and medicine
Sphingosine kinase 1 (SphK1) plays a pivotal role in cancer progression, metastasis, and chemotherapy resistance, making it a key target for therapeutic interventions in cancer, cardiovascular diseases, and inflammation. Machine learning models, incl...

Discovery of novel umami peptides and their bitterness masking effects from yellowfin tuna (Thunnus albacares) via peptidomics, multisensory evaluation, and molecular docking approaches.

Food chemistry
In this study, we identified and screened nine novel umami peptides derived from yellowfin tuna (Thunnus albacares) utilizing peptidomics combined with various machine learning based umami screening methodologies, including UMPred-FRL, TPDM, Umami-MR...