A computational analysis reveals eight novel high-risk single nucleotide variants of human tumor suppressor LHPP gene.

Background: LHPP is a tumor suppressor protein associated with various malignancies like liver, oral, pharyngeal, bladder, cervical, and gastric cancers through controlling various pathways. Several single nucleotide variants have been reported to cause cancers. The main objectives of our study were to investigate the impact of the deleterious non-synonymous single nucleotide variants on structure and functions of the LHPP protein. Results: We used nine computational tools (SNAP2, PROVEAN, POLYPHEN 2, PREDICT SNP, MAPP, PhD-SNP, SIFT, PANTHER, and PMUT) to find out the deleterious SNPs. These nine computational algorithms predicted 34 nsSNPs to be deleterious as a result of their computational analysis. Using ConSurf, I-Mutant, SDM, MUpro, and Mutpred, we emphasized more how those harmful nsSNPs negatively affect the structure and function of the LHPP protein. Furthermore, we predicted the mutant protein structures and assessed the total energy value deviation in comparison with LHPP original structure and also calculated RMSD values and TM scores. By comparing the result from all these computational approaches, we shortlisted a total eight novel nsSNPs (D214G, D219N, Q224P, L231P, G236W, R234C, R234P, and V233G) that impose high risks to the structure and functions of LHPP protein. To analyze the mutant protein's behavior in physiological condition, we performed 50 ns molecular dynamic simulation using WebGro online tool and found that the mutants values vary from the wild type in terms of RMSD, RMSF, Rg, SASA, and H-bond numbers. Prognostic significance analysis by Kaplan–Meier plotter showed that abnormal regulation of LHPP can also serve as a prognostic marker for the patient with breast, ovarian, and gastric cancers. Additionally, ligand binding sites analysis revealed the presence of D214G and D219N mutants in the binding site one which means these two nsSNPs can disturb the binding capacity of the LHPP protein. Protein–protein interaction analysis revealed LHPP proteins' interactions with PPA1, ATP12A, ATP4A, ATP4B, ATP5F1, ATP5J, PPA2, ATP6V0A4, ATP6V0A2, and MT-ATP8 with different degree of connectivity. Conclusion: These results demonstrate a computational understanding of the harmful effect of nsSNPs in LHPP, which may be useful for molecular approaches. [ABSTRACT FROM AUTHOR]

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