Activity cliffs (ACs) are formed by structurally similar active compounds with large potency differences. In medicinal chemistry, ACs are of high interest because they reveal structure-activity relationship (SAR) information and SAR determinants. Herein, we introduce a new type of ACs that consist of analog pairs with different substitutions at multiple sites (multi-site ACs; msACs). A systematic search for msACs across different classes of bioactive compounds identified more than 4000 of such ACs, most of which had substitutions at two sites (dual-site ACs; dsACs). A hierarchical analog data structure was designed to analyze contributions of individual substitutions to AC formation. Single substitutions were frequently found to determine potency differences captured by dsACs. Hence, in such cases, there was redundancy of AC information. In instances where both substitutions made significant contributions to dsACs, additive, synergistic, and compensatory effects were observed. Taken together, the results of our analysis revealed the prevalence of single-site ACs (ssACs) in analog series, followed by dsACs, which reveal different ways in which paired substitutions contribute to the formation of ACs and modulate SARs.
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http://dx.doi.org/10.1016/j.bmc.2019.06.045 | DOI Listing |
Proc Biol Sci
January 2025
Department of Forest and Wildlife Ecology, US Geological Survey, Wisconsin Cooperative Wildlife Research Unit, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706, USA.
Anthropogenically driven environmental change has imposed substantial threats on biodiversity, including the emergence of infectious diseases that have resulted in declines of wildlife globally. In response to pathogen invasion, maintaining diversity within host populations across heterogenous environments is essential to facilitating species persistence. White-nose syndrome is an emerging fungal pathogen that has caused mass mortalities of hibernating bats across North America.
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January 2025
University of Pittsburgh, Department of Computer Science, Pittsburgh, PA, 15260, USA.
Reliable molecular property prediction is essential for various scientific endeavors and industrial applications, such as drug discovery. However, the data scarcity, combined with the highly non-linear causal relationships between physicochemical and biological properties and conventional molecular featurization schemes, complicates the development of robust molecular machine learning models. Self-supervised learning (SSL) has emerged as a popular solution, utilizing large-scale, unannotated molecular data to learn a foundational representation of chemical space that might be advantageous for downstream tasks.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Brain Diseases and Cognition, School of Medicine, Xiamen University, Xiamen, 361102, Fujian, China.
Altitude training has been widely adopted. This study aimed to establish a mice model to determine the time point for achieving the best endurance at the lowland. C57BL/6 and BALB/c male mice were used to establish a mice model of hypoxic training with normoxic training mice, hypoxic mice, and normoxic mice as controls.
View Article and Find Full Text PDFCureus
November 2024
Respiratory Medicine, Royal Free London NHS Foundation Trust, London, GBR.
We present a case of a 37-year-old gentleman diagnosed with post-infectious Guillain-Barré syndrome (GBS) secondary to a Mycoplasma pneumoniae infection. This case highlights the subclinical presentation of neurological symptoms, often overlooked as a complication of M. pneumoniae infection.
View Article and Find Full Text PDFJ Mol Graph Model
March 2025
Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh,11623, Saudi Arabia. Electronic address:
The work being presented now combines severe gradient boosting with Shapley values, a thriving merger within the field of explainable artificial intelligence. We also use a genetic algorithm to analyse the HDAC1 inhibitory activity of a broad pool of 1274 molecules experimentally reported for HDAC1 inhibition. We conduct this analysis to ascertain the HDAC1 inhibitory activity of these molecules.
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