ArticleInternational journal of molecular sciences2019
Investigation of Phospholipase Cγ1 Interaction with SLP76 Using Molecular Modeling Methods for Identifying Novel Inhibitors.
Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Characterisation of an allosteric site in PLCγ enzymes and implications for development of their specific inhibitors.The Biochemical journal · 2025Article
- Impaired degradation of PLCG1 by chaperone-mediated autophagy promotes cellular senescence and intervertebral disc degeneration.Autophagy · 2025Article
- A kinetic model of phospholipase C-γ1 linking structure-based insights to dynamics of enzyme autoinhibition and activation.The Journal of biological chemistry · 2022Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
The enzyme phospholipase C gamma 1 (PLCγ1) has been identified as a potential drug target of interest for various pathological conditions such as immune disorders, systemic lupus erythematosus, and cancers. Targeting its SH3 domain has been recognized as an efficient pharmacological approach for drug discovery against PLCγ1. Therefore, for the first time, a combination of various biophysical methods has been employed to shed light on the atomistic interactions between PLCγ1 and its known binding partners. Indeed, molecular modeling of PLCγ1 with SLP76 peptide and with previously reported inhibitors (ritonavir, anethole, daunorubicin, diflunisal, and rosiglitazone) facilitated the identification of the common critical residues (Gln805, Arg806, Asp808, Glu809, Asp825, Gly827, and Trp828) as well as the quantification of their interaction through binding energies calculations. These features are in agreement with previous experimental data. Such an in depth biophysical analysis of each complex provides an opportunity to identify new inhibitors through pharmacophore mapping, molecular docking and MD simulations. From such a systematic procedure, a total of seven compounds emerged as promising inhibitors, all characterized by a strong binding with PLCγ1 and a comparable or higher binding affinity to ritonavir (∆G
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Registered trials
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