AIMC Topic: Molecular Docking Simulation

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Computational methods for modeling protein-protein interactions in the AI era: Current status and future directions.

Drug discovery today
The modeling of protein-protein interactions (PPIs) has been revolutionized by artificial intelligence, with deep learning and end-to-end frameworks such as AlphaFold and its derivatives now dominating the field. This review surveys the current compu...

Predicted and Explained: Transforming drug discovery with AI for high-precision receptor-ligand interaction modeling and binding analysis.

Computers in biology and medicine
The pharmaceutical industry faces persistent challenges in developing effective treatments for complex diseases, creating an urgent need for innovative approaches to accelerate drug discovery. A pivotal factor in this process is the accurate predicti...

Integrative network and computational toxicology reveal the molecular mechanisms in PFOA-induced spermatogenic disorder.

Journal of environmental management
Perfluorooctanoic acid (PFOA), a widely used industrial chemical, poses significant environmental and biological toxicity, particularly affecting reproductive health. This study aimed to integrate network toxicology, machine learning, and molecular d...

KDELR3 and YOD1 proteins as critical endoplasmic reticulum stress mediators and potential therapeutic targets in diabetic foot ulcers: An integrated bioinformatics analysis.

International journal of biological macromolecules
BACKGROUND: Diabetic foot ulcers (DFU) represent one of the most severe complications of diabetes mellitus and are closely associated with persistent hyperglycemia. Endoplasmic reticulum stress response proteins play critical roles in the development...

Design and molecular mechanism investigation of ALK inhibitors based on virtual screening and structural descriptor modeling.

Journal of receptor and signal transduction research
To address the challenges of target specificity and drug resistance in Anaplastic lymphoma kinase (ALK) inhibition, this study conducted a virtual screening of the BindingDB database, yielding 711 potential ALK inhibitors. Four QSAR models were estab...

Deciphering the mechanism of baicalein in cervical cancer via bioinformatics, machine learning and computational simulations: PIM1 and CDK2 are key target proteins.

International journal of biological macromolecules
Cervical cancer is one of the leading causes of death among women worldwide. Current treatments are limited by chemoresistance and chemotherapeutic agents' adverse effects, prompting the search for better therapeutic alternatives. Baicalein, a natura...

Identification of therapeutics against PfPK6 protein of Plasmodium falciparum: Structure and Deep Learning approach.

Experimental parasitology
The Plasmodium falciparum Protein Kinase 6 (PfPK6) is a serine/threonine protein kinase categorized under the CMGC group, displaying both cyclin-dependent kinases (CDKs) and mitogen-activated protein kinases (MAPKs) activity. Previous research has in...

Exploring pesticide risk in autism via integrative machine learning and network toxicology.

Ecotoxicology and environmental safety
Autism Spectrum Disorder (ASD) is a prevalent neurodevelopmental condition influenced by both genetic and environmental factors, including pesticide exposure. This study aims to investigate the pathogenic mechanisms of ASD and identify potential caus...

Artificial intelligence-driven microRNA signature for early detection of gastric cancer: discovery and clinical functional exploration.

British journal of cancer
BACKGROUND: Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide, with late-stage diagnoses frequently leading to poor outcomes. This underscores the need for effective early-stage gastric cancer (ESGC) diagnostics.

Computational screening of natural products as tryptophan 2,3-dioxygenase inhibitors: Insights from CNN-based QSAR, molecular docking, ADMET, and molecular dynamics simulations.

Computers in biology and medicine
Parkinson's disease (PD) is characterised by a complex array of motor, psychiatric, and gastrointestinal symptoms, many of which are linked to disruptions in neuroactive metabolites. Dysregulated activity of tryptophan 2,3-dioxygenase (TDO), a key en...