AIMC Topic: Quantitative Structure-Activity Relationship

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Prediction of reproductive and developmental toxicity using an attention and gate augmented graph convolutional network.

Scientific reports
Due to the diverse molecular structures of chemical compounds and their intricate biological pathways of toxicity, predicting their reproductive and developmental toxicity remains a challenge. Traditional Quantitative Structure-Activity Relationship ...

Novel Computational Approaches in the Discovery and Identification of Bioactive Peptides: A Bioinformatics Perspective.

Journal of agricultural and food chemistry
Bioactive peptides are protein molecules known for their specific biological functions, offering promising applications across various fields including medicine, food, and cosmetics. Traditional approaches to the investigation of bioactive peptides t...

QSPR analysis of physico-chemical and pharmacological properties of medications for Parkinson's treatment utilizing neighborhood degree-based topological descriptors.

Scientific reports
Topological indices are invariant quantitative metrics associated with a molecular graph, which characterize the bonding topology of a molecule. The main aim of analyzing topological indices is to summarize and transform chemical structural informati...

Unraveling potent Glycyrrhiza glabra flavonoids as AKT1 inhibitors using network pharmacology and machine learning-assisted QSAR.

Molecular diversity
Glycyrrhiza glabra (G. glabra) phytocompounds have been reported to interact with neurological targets, including those implicated in epilepsy, and may modulate epilepsy-related targets. While substantial evidence supports their potential antiepilept...

Predicting biomolecule adsorption on nanomaterials: a hybrid framework of molecular simulations and machine learning.

Nanoscale
The adsorption of biomolecules on the surface of nanomaterials (NMs) is a critical determinant of their behavior, toxicity, and efficacy in biological systems. Experimental testing of these phenomena is often costly or complicated. Computational appr...

Machine learning models for predicting configuration of modified knuckle epitope peptides of BMP-2 protein using mesoscale simulation data.

Physical chemistry chemical physics : PCCP
The high doses of bone morphogenetic proteins (BMPs) cause undesired side effects in skeletal tissue regeneration. An alternative approach is to use the bioactive knuckle epitope domain of BMP-2 (BMP2-KEP) with an open-arm structure as part of the pr...

Rosmarinic acid in Perilla frutescens L. as a potential adenosine deaminase inhibitor: Preparation, machine learning validation and binding mechanism study.

Food chemistry
Gout, a prevalent arthritic disease, can be mitigated by adenosine deaminase (ADA) inhibitors that reduce uric acid production. In this study, the extraction process of rosmarinic acid (RA) from Perilla frutescens L. (P. frutescens) was optimized, an...

Comprehensive insights into carbonic anhydrase inhibition: A triad of In vitro, In silico, and In vivo perspectives.

Enzyme and microbial technology
Carbonic anhydrases (CAs) are zinc-dependent metalloenzymes essential for sustaining physiological balance by facilitating the reversible conversion of carbon dioxide to its hydrated form. Their biological significance, coupled with their involvement...

Decoding the quantitative structure-activity relationship and astringency formation mechanism of oxygenated aromatic compounds.

Food research international (Ottawa, Ont.)
Astringency is a common sensory experience in the mouth, characterized by dryness, roughness, and puckering. Due to the inefficiency and expense of conventional astringency evaluation methods, the quantitative structure-activity relationship (QSAR) m...

Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms.

Toxicology mechanisms and methods
Alga toxins have recently emerged as environmental risk factors to multiple human health issues. Mitochondrial toxicity is an essential element in the field of ecotoxicology, it is necessary to screen and manage mitochondrial toxicants from common al...