Study of MDM2 as Prognostic Biomarker in Brain-LGG Cancer and Bioactive Phytochemicals Inhibit the p53-MDM2 Pathway: A Computational Drug Development Approach

Abstract

An evaluation of the expression and predictive significance of the MDM2 gene in brain lower-grade glioma (LGG) cancer was carried out using onco-informatics pipelines. Several transcriptome servers were used to measure the differential expression of the targeted MDM2 gene and search mutations and copy number variations. GENT2, Gene Expression Profiling Interactive Analysis, Onco-Lnc, and PrognoScan were used to figure out the survival rate of LGG cancer patients. The protein–protein interaction networks between MDM2 gene and its co-expressed genes were constructed by Gene-MANIA tool. Identified bioactive phytochemicals were evaluated through molecular docking using Schrödinger Suite Software, with the MDM2 (PDB ID: 1RV1) target. Protein–ligand interactions were observed with key residues of the macromolecular target. A molecular dynamics simulation of the novel bioactive compounds with the targeted protein was performed. Phytochemicals targeting MDM2 protein, such as Taxifolin and (-)-Epicatechin, have been shown with more highly stable results as compared to the control drug, and hence, concluded that phytochemicals with bioactive potential might be alternative therapeutic options for the management of LGG patients. Our once informatics-based designed pipeline has indicated that the MDM2 gene may have been a predictive biomarker for LGG cancer and selected phytochemicals possessed outstanding interaction results within the macromolecular target’s active site after utilizing in silico approaches. In vitro and in vivo experiments are recommended to confirm these outcomes.

Identification of antidiabetic inhibitors from Allophylus villosus and Mycetia sinensis by targeting α-glucosidase and PPAR-γ: In-vitro, in-vivo, and computational evidence

“…The radius of gyration (Rg), hydrogen bond number, solvent accessible surface area (SASA), MolSA, and PSA have also been looked at. In complex systems, the lowest root means square deviation (RMSD) values suggest the best stability of the compounds, whereas the higher root means square fluctuation (RMSF) values indicate the lower compactness of the protein–ligand complex ( Al Saber et al, 2022 , Biswas et al, 2023a , Biswas et al, 2023b ). The drug candidate Compound CID-102506517 (blue) showed the potent RMSD and RMSF values with the targeted proteins human alpha-glucosidase (PDB ID: 3WY1) compared to the Control Drug (CID-441314) (ash).…”

“…The RCSB protein data bank (PDB) ( https://www.rcsb.org/ , accessed on 27 October 2022) was used to retrieve the target protein in 3D format. The target protein structure (PDB ID: 8B8Z and 3WY1) is used as a receptor in molecular docking analysis ( Biswas et al, 2023a , Jabin et al, 2023 , Shiau et al, 1998 ). After the file has been downloaded, the Protein Preparation Wizard 12.5 that is included with the Maestro Application (Schrödinger 2020–3 Schrödinger, LLC, New York, NY, USA, 2020) was utilized in order to carry out the process of preparing the protein.…”

A clathrin-related protein FaRRP1/SCD2 integrates ABA trafficking and signaling to regulate strawberry fruit ripening

“…Protein construction is the basis of its biological function ( 32 ); strikingly, Schrödinger has been used extensively, especially in molecular docking or virtual screening ( 52 , 53 ). FaPYL2 and FaABAR are previously reported to be candidate receptors for ABA ( 24 , 54 ), and now together with FaRRP1, they all have been shown to bind to ABA ( Fig.…”

Antibacterial activity and antibacterial mechanism of flavaspidic acid BB against Staphylococcus haemelyticus

“…With the rapid development of modern scientific research technology, molecular docking and molecular dynamics (MD) simulations have become important methods of studying the interaction between compound molecules and receptors [ 18 , 19 ]. Molecular docking can predict the interaction between the receptor and the ligand.…”