The application of artificial intelligence in cheminformatics highlights the necessity of comprehensive datasets that fully utilize all available chemical information. While generalist databases such as PubChem provide extensive compound coverage, sp...
Journal of chemical information and modeling
Oct 9, 2025
In this work, we introduce an automated methodology for the efficient and relatively inexpensive exploration of large high-dimensional chemical spaces, with particular focus on number-of-atoms-conserving processes, such as in mechanochemical reaction...
Journal of chemical information and modeling
Aug 4, 2025
Machine learning (ML) has become a standard tool for the exploration of the chemical space. Much of the performance of such models depends on the chosen database for a given task. Here, this aspect is investigated for "chemical tasks" including the p...
Abraham's solvation parameter model has been widely used to model retention in capillary micellar and microemulsion electrokinetic chromatography systems. To fit or predict retention factors in separation systems experimentally determined compound de...
OBJECTIVES: Beta-lactamase is a bacterial enzyme that deactivates beta-lactam antibiotics, and it is one of the leading causes of antibiotic resistance problems globally. In current drug discovery research, molecular simulation, like molecular dockin...
The NLRP3 inflammasome, plays a critical role in the pathogenesis of rheumatoid arthritis (RA) by activating inflammatory cytokines such as IL1β and IL18. Targeting NLRP3 has emerged as a promising therapeutic strategy for RA. In this study, a multid...
Journal of chemical information and modeling
Dec 10, 2024
While data curation principles and practices are a major topic in data science, they are often not explicitly considered in machine learning (ML) applications in chemistry. We have been interested in evaluating the potential effects of data curation ...
Journal of chemical information and modeling
Nov 27, 2024
Cyanobacteria strains have the potential to produce bioactive compounds that can be used in therapeutics and bioremediation. Therefore, compiling all information about these compounds to consider their value as bioresources for industrial and researc...
Journal of molecular graphics & modelling
Nov 14, 2024
Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynami...
Journal of chemical information and modeling
Sep 20, 2024
A knowledge graph (KG) is a technique for modeling entities and their interrelations. Knowledge graph embedding (KGE) translates these entities and relationships into a continuous vector space to facilitate dense and efficient representations. In the...
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