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Granzymes are serine proteases synthesized by CTL and NK cells. Five granzyme genes (GzmA, -B, -H, -K, -M) are present in humans, which are located at three different chromosomal loci. Being serine proteases, the binding pocket constitutes a catalytic triad (i.e., His59, Asp103 and Ser197). Granzymes are released into target (cancerous and virally infected) cells by a specialized process known as granule exocytosis pathway. After internalization, these proteases initiate apoptosis. Granzymes are also involved in other non-apoptotic immune associated roles like ECM remodeling, cytokine modulation, killing of pathogens through generation of phagosomes. Their intracellular activity is regulated by specialized inhibitors knows as SERPINs. However, if these proteases are secreted in excess into the extracellular environment, their regulation becomes important as otherwise they start self-damage to the tissues thereby worsening the disease conditions. Efforts are being made to identify potential inhibitors for regulation of these proteases in an extracellular environment. Physiological and synthetic inhibitors have been reported against some members however there is no known inhibitor against extracellular human GzmH. Thus, in the current study, we investigated small molecule databases for the identification of potential molecules having the ability to inhibit GzmH by combined molecular simulations, which can ultimately be used as a potential therapeutic agent.
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http://dx.doi.org/10.1016/j.jmgm.2021.107876 | DOI Listing |
J Chem Inf Model
September 2025
Department of Chemistry, Delaware State University, Dover, Delaware 19901, United States.
The calculation of the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap for chemical molecules is computationally intensive using quantum mechanics (QM) methods, while experimental determination is often costly and time-consuming. Machine Learning (ML) offers a cost-effective and rapid alternative, enabling efficient predictions of HOMO-LUMO gap values across large data sets without the need for extensive QM computations or experiments. ML models facilitate the screening of diverse molecules, providing valuable insights into complex chemical spaces and integrating seamlessly into high-throughput workflows to prioritize candidates for experimental validation.
View Article and Find Full Text PDFOrg Lett
September 2025
Istanbul Technical University, Chemistry Department, Maslak, Istanbul 34469, Turkey.
A donor-acceptor-donor type π-conjugated small molecule, , having an oligoether-functionalized azaisoindigo unit as an acceptor and triphenylamine units as donor groups was designed and synthesized. Its opto-electrochemical properties and charge transport applications were investigated. demonstrated p-type transport behavior with a maximum carrier mobility of 0.
View Article and Find Full Text PDFJ Am Chem Soc
September 2025
Department of Chemistry, Zhejiang University, Hangzhou 310027, China.
Narrow electrochemical windows and high reactivity of aqueous solutions remain critical bottlenecks for the practical application of aqueous batteries. However, the mechanisms for tuning microscopic reactivity of HO molecules in aqueous electrolytes remain elusive. This study employs six ether molecules with distinct structures and solvation powers to regulate the microstructure of aqueous solutions.
View Article and Find Full Text PDFBioinformatics
September 2025
Biocomputation and Complex Systems Physics Institute (BIFI)-Joint Unit GBsC-CSIC, University of Zaragoza, Zaragoza, 50018, Spain.
Motivation: The stability of protein interfaces influences protein dynamics and unfolding cooperativity. Although in some cases the dynamics of proteins can be deduced from their topology, much of the stability of an interface is related to the complementarity of the interacting parts. It is also important to note that proteins that display non-cooperative unfolding cannot be rationally stabilized unless the regions that unfold first are known.
View Article and Find Full Text PDFJ Med Chem
September 2025
Encoded Technologies, Molecular Modalities Discovery, GSK, Cambridge, Massachusetts 02140, United States.
DNA-encoded libraries (DELs) are used throughout small-molecule drug discovery to identify new lead compounds for protein targets. DEL hits are traditionally evaluated via off-DNA resynthesis and subsequent biological testing. This approach can be time- and resource-intensive, limiting the number of putative hits selected for follow-up.
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