It is widely understood that QSAR models greatly improve if more data are used. However, irrespective of model quality, once chemical structures diverge too far from the initial data set, the predictive performance of a model degrades quickly. To increase the applicability domain we need to increase the diversity of the training set. This can be achieved by combining data from diverse sources. Public data can be easily included; however, proprietary data may be more difficult to add due to intellectual property concerns. In this contribution, we will present a method for the collaborative development of linear regression models that addresses this problem. The method differs from other past approaches, because data are only shared in an aggregated form. This prohibits access to individual data points and therefore avoids the disclosure of confidential structural information. The final models are equivalent to models that were built with combined data sets.
Department of Chemistry, Wuhan University, Wuhan, 430072, China; School of Bioengineering and Health, Wuhan Textile University, Wuhan, 430200, China; Frontier Science Center for Immunology and Metabolism, Wuhan University, Wuhan, 430071, China. Electronic address:
Branched fatty acid esters of hydroxy fatty acids (FAHFAs) represent a novel class of bioactive lipids with significant physiological roles. However, their identification, particularly of low-abundance FAHFA regioisomers, remains challenging due to their high structural similarity, low natural abundance, and the limited availability of reliable FAHFA standards. In this study, we present a QSAR-based FAHFA annotation strategy that integrates a QSAR model with an ester bond position (EP) rule to determine the EPs of FAHFA regioisomers.
Selective inhibition of histone deacetylase 8 (HDAC8) has emerged as a promising approach for treating various diseases, including cancer. However, finding key structural features for HDAC8 inhibition and developing effective and selective HDAC8 inhibitors (HDAC8s) pose significant challenges. In the past few years, the development of various scaffolds for inhibiting HDAC8 has significantly risen and the quest continues.
RET receptor tyrosine kinase is crucial for nerve and tissue development but can be an important oncogenic driver. This study focuses on exploring the design principles of potent RET inhibitors through molecular docking and 3D-QSAR modeling of 5,6-fused bicyclic heteroaromatic derivatives. First of all, RET inhibitors of 49 different bicyclic substructures were collected from five different data sources and selected through molecular docking simulations.
Histone deacetylase 3 (HDAC3) inhibitors keep significant therapeutic promise for treating oncological, neurodegenerative, and inflammatory diseases. In this work, we developed robust QSAR regression models for HDAC3 inhibitory activity and acute toxicity (LD, intravenous administration in mice). A total of 1751 compounds were curated for HDAC3 activity, and 15,068 for toxicity.
Polychlorinated dibenzo-p-dioxins (PCDDs) are persistent organic pollutants that pose considerable threats to ecological and human health owing to their high toxicity potential. Understanding the mechanisms for underlying the base-catalyzed hydrolysis of PCDDs in aquatic environments is essential for assessing their environmental behaviour and ecological risks. Herein, we combined quantitative structure-activity relationship (QSAR) models with density functional theory calculations to analyse the base-catalyzed hydrolysis mechanisms of PCDDs.
