The secondary structure of some protein segments may vary between α-helix and β-strand. To predict these switchable segments, we have developed an algorithm, Switch-P, based solely on the protein sequence. This algorithm was used on the extracellular parts of FGF receptors. For FGFR2, it predicted that β4 and β5 strands of the third Ig-like domain were highly switchable. These two strands possess a high number of somatic mutations associated with cancer. Analysis of PDB structures of FGF receptors confirmed the switchability prediction for β5. We thus evaluated if compound-driven α-helix/β-strand switching of β5 could modulate FGFR2 signaling. We performed the virtual screening of a library containing 1.4 million of chemical compounds with two models of the third Ig-like domain of FGFR2 showing different secondary structures for β5, and we selected 32 compounds. Experimental testing using proliferation assays with FGF7-stimulated SNU-16 cells and a FGFR2-dependent Erk1/2 phosphorylation assay with FGFR2-transfected L6 cells, revealed activators and inhibitors of FGFR2. Our method for the identification of switchable proteinic regions, associated with our virtual screening approach, provides an opportunity to discover new generation of drugs with under-explored mechanism of action.
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http://dx.doi.org/10.1002/prot.24657 | DOI Listing |
Simul Healthc
January 2025
From the Department of Human Factors (H.S., Y.P., E.T., L.D.W.), Center for the Simulation, Research, and Patient Safety, Carilion Clinic, Roanoke, VA; and Health Systems and Implementation Science (S.H.P.), Virginia Tech Carilion School of Medicine, Roanoke, VA.
Introduction: Virtual Monitor Technicians (VMTs) are crucial in remotely monitoring inpatient telemetry. However, little is known about VMT workload and intratask performance changes, and their potential impact on patient safety. This exploratory study used a high-fidelity simulation aimed to evaluate VMTs' workload and performance changes over time in telemetry monitoring and identify future research directions for performance improvement.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Computer Science, Yonsei University, Yonsei-ro 50, Seodaemun-gu, 03722, Seoul, Republic of Korea.
Identifying new compounds that interact with a target is a crucial time-limiting step in the initial phases of drug discovery. Compound-protein complex structure-based affinity prediction models can expedite this process; however, their dependence on high-quality three-dimensional (3D) complex structures limits their practical application. Prediction models that do not require 3D complex structures for binding-affinity estimation offer a theoretically attractive alternative; however, accurately predicting affinity without interaction information presents significant challenges.
View Article and Find Full Text PDFEuroasian J Hepatogastroenterol
December 2024
Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine, Ehime, Japan.
Objectives: To predict and characterize the three-dimensional (3D) structure of protein arginine methyltransferase 2 (PRMT2) using homology modeling, besides, the identification of potent inhibitors for enhanced comprehension of the biological function of this protein arginine methyltransferase (PRMT) family protein in carcinogenesis.
Materials And Methods: An method was employed to predict and characterize the three-dimensional structure. The bulk of PRMTs in the PDB shares just a structurally conserved catalytic core domain.
J Adv Pract Oncol
July 2024
Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania.
Background: The accessibility and quality of network support for people living with lung cancer (PLW) and their support partners (SP) can vary. Virtual platforms provide unique opportunities for PLW/SP peer support and disease education.
Methods: Using a novel dual approach, we determined the user-perceived impact of the AstraZeneca-sponsored Facebook community, (facebook.
RSC Adv
January 2025
Innovative Informatica Technologies Hyderabad Telangana India.
Non-Small Cell Lung Cancer (NSCLC) is a formidable global health challenge, responsible for the majority of cancer-related deaths worldwide. The Platelet-Derived Growth Factor Receptor (PDGFR) has emerged as a promising therapeutic target in NSCLC, given its crucial involvement in cell growth, proliferation, angiogenesis, and tumor progression. Among PDGFR inhibitors, avapritinib has garnered attention due to its selective activity against mutant forms of PDGFR, particularly PDGFRA D842V and KIT exon 17 D816V, linked to resistance against conventional tyrosine kinase inhibitors.
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