AIMC Topic: Quantitative Structure-Activity Relationship

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Optimal Descriptor Subset Search via Chemical Information and Target Activity-Guided Algorithm for Antimicrobial Peptide Prediction.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) have emerged as a promising alternative to conventional drugs due to their potential applications in combating multidrug-resistant pathogens. Various computational approaches have been developed for AMP prediction, rangi...

Integrating AI/ML and multi-omics approaches to investigate the role of TNFRSF10A/TRAILR1 and its potential targets in pancreatic cancer.

Computers in biology and medicine
Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival of under 10 % despite current therapies. Aggressive tumor biology, a desmoplastic stroma that limits drug delivery and immune cell infiltra...

On the application of artificial intelligence in virtual screening.

Expert opinion on drug discovery
INTRODUCTION: Artificial intelligence (AI) has emerged as a transformative tool in drug discovery, particularly in virtual screening (VS), a crucial initial step in identifying potential drug candidates. This article highlights the significance of AI...

Machine learning-driven insights into retention mechanism in IAM chromatography of anticancer sulfonamides: Implications for biological efficacy.

Journal of chromatography. A
Machine learning (ML) tools offer new opportunities in drug discovery, especially for enhancing our understanding of molecular interactions with biological systems. This study develops a comprehensive quantitative structure-retention relationship (QS...

Decoding the Structure-Activity Relationship of the Dopamine D3 Receptor-Selective Ligands Using Machine and Deep Learning Approaches.

Journal of chemical information and modeling
Dysfunctions of the dopamine D2 and D3 receptors (D2 and D3) are implicated in neuropsychiatric conditions such as Parkinson's disease, schizophrenia, and substance use disorders (SUDs). Evidence indicates that D3-selective ligands can effectively mo...

Band Gap and Reorganization Energy Prediction of Conducting Polymers by the Integration of Machine Learning and Density Functional Theory.

Journal of chemical information and modeling
The performance and reliability of machine learning (ML)-quantitative structure-property relationship (QSPR) models depend on the quality, size, and diversity of the data set used for model training. In this study, we manually curated a large-scale d...

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...

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...

Drug repurposing targeting COVID-19 3CL protease using molecular docking and machine learning regression approaches.

Scientific reports
The COVID-19 pandemic has initiated a global health emergency, with an exigent need for an effective cure. Progressively, drug repurposing is emerging as a promising solution for saving time, cost, and labor. However, the number of drug candidates th...

AI-Driven Design and Development of Nontoxic DYRK1A Inhibitors.

Journal of medicinal chemistry
Dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) is implicated in several human diseases, including DYRK1A syndrome, cancer, and neurodegenerative disorders such as Alzheimer's disease, making it a relevant therapeutic target. I...