Background Aberrant kallikrein activity is observed in a number of inflammatory dermatoses. Up-regulation of kallikrein-5 (KLK5) activity leads to uncontrolled skin desquamation and cleavage of proteinase-activated receptor-2 (PAR2), causing the release of pro-inflammatory cytokines and disruption of epidermal barrier function. This study aimed to identify KLK5-specific small molecule inhibitors which can serve as the foundation of a novel therapeutic for inflammatory skin disorders. Methods Five chemical libraries (13,569 compounds total) were screened against recombinant KLK5 using a fluorogenic enzymatic assay. Secondary validation was performed on the top 22 primary hits. All hits were docked in the KLK5 crystal structure to rationalize their potential interactions with the protein. Results A naturally occurring compound derived from the wood of Caesalpinia sappan (Brazilin) was identified as a novel KLK5 inhibitor (IC50: 20 μM, Ki: 6.4 μM). Docking suggests that the phenolic moiety of Brazilin binds in the S1-pocket of KLK5 and forms a H-bond with S195 side chain. KLK14 was also found to be susceptible to inhibition by Brazilin with a calculated IC50 value of 14.6 μM. Conclusions Natural KLK5 small molecule inhibitors such as Brazilin, are ideal for topical skin disease drug design and remain a promising therapeutic for severe cases of inflammatory skin disorders. Optimized KLK inhibitors may have increased efficacy as therapeutics and warrant further investigation.
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http://dx.doi.org/10.1515/cclm-2019-0123 | DOI Listing |
Comb Chem High Throughput Screen
January 2025
APIGENEX s.r.o., Poděbradská 173/5, Prague 19000, Czech Republic.
Objective: In search of efficient anticancer agents, we aimed at the design and synthesis of a library of tetrasubstituted alkenes. These are structural analogues of tamoxifen, one of the widely used anticancer therapeutics.
Methods: Our small organic compound library was prepared via a chemical synthesis in the solution using the Larock three-component coupling reaction, which is known to tolerate diverse functional groups.
BMC Bioinformatics
January 2025
Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing Anzhen Hospital of Capital Medical University, Beijing, 101100, China.
Background: MicroRNAs (miRNAs) are pivotal in the initiation and progression of complex human diseases and have been identified as targets for small molecule (SM) drugs. However, the expensive and time-intensive characteristics of conventional experimental techniques for identifying SM-miRNA associations highlight the necessity for efficient computational methodologies in this field.
Results: In this study, we proposed a deep learning method called Multi-source Data Fusion and Graph Neural Networks for Small Molecule-MiRNA Association (MDFGNN-SMMA) to predict potential SM-miRNA associations.
J Chem Inf Model
January 2025
Department of Chemical and Physical Biology, Vanderbilt University, Nashville, Tennessee 37232, United States.
Machine learning (ML) models now play a crucial role in predicting properties essential to drug development, such as a drug's logscale acid-dissociation constant (p). Despite recent architectural advances, these models often generalize poorly to novel compounds due to a scarcity of ground-truth data. Further, these models lack interpretability.
View Article and Find Full Text PDFMolecules
December 2024
Department of Pharmaceutical Sciences, School of Pharmacy, University of Jordan, Amman 11942, Jordan.
Monoamine oxidase B (MAO-B) is a key enzyme in the mitochondrial outer membrane, pivotal for the oxidative deamination of biogenic amines. Its overexpression has been implicated in the pathogenesis of several cancers, including glioblastoma and colorectal, lung, renal, and bladder cancers, primarily through the increased production of reactive oxygen species (ROS). Inhibition of MAO-B impedes cell proliferation, making it a potential therapeutic target.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
University of Hong Kong, Chemistry, Department of Chemistry, Pokfulam Road, N.A., Hong Kong, HONG KONG.
Small molecules that can bind to specific cells have broad applications in cancer diagnosis and treatment. Screening large chemical libraries against live cells is an effective strategy for discovering cell-targeting ligands. The DNA-encoded chemical library (DEL or DECL) technology has emerged as a robust tool in drug discovery and has been successfully utilized in identifying ligands for biological targets.
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