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PIM-1 is a Ser/Thr kinase, which has been extensively studied as a potential target for cancer therapy due to its significant roles in various cancers, including prostate and breast cancers. Given its importance in cancer, researchers are investigating the structure of PIM-1 for pharmacological inhibition to discover therapeutic intervention. This study examines structural and conformational changes in PIM-1 across different pH using various spectroscopic and computational techniques. Spectroscopic results indicate that PIM-1 maintains its secondary and tertiary structure within the pH range of 7.0-9.0. However, protein aggregation occurs in the acidic pH range of 5.0-6.0. Additionally, kinase assays suggested that PIM-1 activity is optimal within the pH range of 7.0-9.0. Subsequently, we performed a 100 ns all-atom molecular dynamics (MD) simulation to see the effect of pH on PIM-1 structural stability at the molecular level. MD simulation analysis revealed that PIM-1 retains its native conformation in alkaline conditions, with some residual fluctuations in acidic conditions as well. A strong correlation was observed between our MD simulation, spectroscopic, and enzymatic activity studies. Understanding the pH-dependent structural changes of PIM-1 can provide insights into its role in disease conditions and cellular homeostasis, particularly regarding protein function under varying pH conditions.
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http://dx.doi.org/10.1016/j.compbiolchem.2024.108265 | DOI Listing |
Chem Commun (Camb)
September 2025
State Key Laboratory of Materials-Oriented Chemical Engineering, College of Chemical Engineering, Nanjing Tech University, Nanjing 211816, China.
For the first time, a dual-ligand MOF, Al-Fum/Asp, was synthesized by partially replacing fumarate ligands in the Al-Fum framework with l-aspartic acid and incorporated into PIM-1 to fabricate mixed-matrix membranes. Amino groups anchored on Al-Fum/Asp enhance CO-adsorption, enabling the membrane to achieve CO/N separation performance beyond the 2019 Robeson upper bound.
View Article and Find Full Text PDFAnn Geriatr Med Res
August 2025
Department of Geriatric Medicine, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan.
Aim: This study aimed to reveal demographic data for care-dependent older adults receiving home medical care and to evaluate whether potentially inappropriate medication (PIM) prescriptions were associated with hospitalization and death.
Methods: Data of health-care and long-term care insurance claims of older adults aged ≥65 years receiving home medical care of Kure City, Japan in April 2017 were obtained. They included age, sex, recorded diagnosis on medical claims, level of long-term care (LTC) needs, and medication profile.
Angew Chem Int Ed Engl
August 2025
Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Freiestrasse 3, Bern, 3012, Switzerland.
The electrochemical CO reduction reaction (ECOR) offers a promising pathway to convert CO into value-added products. While catalyst advances remain crucial, gas-diffusion electrodes (GDEs) architecture is equally vital in CO electrolyzer design. Most ECOR studies use pure CO feeds, whereas industrial sources like flue gas contain ∼15% CO, requiring costly purification.
View Article and Find Full Text PDFPharm Biol
December 2025
Jiangxi Provincial Key Laboratory of Breast Diseases (No.2024SSY06221), Nanchang People's Hospital, Nanchang, China.
Context: Sophoridine, an alkaloid quinolizidine derived from Aiton (Fabaceae), has strong anti-tumor activity in a variety of malignancies. Nevertheless, the effects and underlying mechanism of sophoridine on breast cancer are not fully understood.
Objective: To identify the key targets and potential pharmacological mechanisms of sophoridine against breast cancer.
Eur J Pharm Sci
September 2025
College of Pharmacy, Zhangzhou Health Vocational College, Zhangzhou, Fujian Province, China. Electronic address:
This study explores the therapeutic targets and mechanisms of Gynostemma pentaphyllum in non-alcoholic fatty liver disease (NAFLD). Using network analysis and bioinformatics, we identified target genes of Gynostemma's active metabolites in NAFLD through differential expression analysis, Weighted Gene Co-expression Network Analysis (WGCNA), and machine learning algorithms. From the intersection of 2,569 differentially expressed genes (DEGs), 1,279 key modular genes, and 532 target genes, 19 intersecting target genes were pinpointed, with PIM1, TYMS, and SLC29A1 identified as key targets.
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