In silico identification and in vitro assessment of a potential anti-breast cancer activity of antimicrobial peptide retrieved from the ATMP1 Anabas testudineus fish peptide.

A previous study has shown that synthetic antimicrobial peptides (AMPs) derived from Anabas testudineus (ATMP1) could in-vitro inhibit the progression of breast cancer cell lines. In this study, we are interested in studying altered versions of previous synthetic AMPs to gain some insight into the peptides functions. The AMPs were altered and subjected to bioinformatics prediction using four databases (ADP3, CAMP-R3, AMPfun, and ANTICP) to select the highest anticancer activity. The bioinformatics in silico analysis led to the selection of two AMPs, which are ATMP5 (THPPTTTTTTTTTTTYTAAPATTT) and ATMP6 (THPPTTTTTTTTTTTTTAAPARTT). The in silico analysis predicted that ATMP5 and ATMP6 have anticancer activity and lead to cell death. The ATMP5 and ATMP6 were submitted to deep learning databases (ToxIBTL and ToxinPred2) to predict the toxicity of the peptides and to (AllerTOP & AllergenFP) check the allergenicity. The results of databases indicated that AMPs are non-toxic to normal human cells and allergic to human immunoglobulin. The bioinformatics findings led to select the highest active peptide ATMP5, which was synthesised and applied for in-vitro experiments using cytotoxicity assay MTT Assay, apoptosis detection using the Annexin V FTIC-A assay, and gene expression using Apoptosis PCR Array to evaluate the AMP's anticancer activity. The antimicrobial activity is approved by the disc diffusion method. The in-vitro experiments analysis showed that ATMP5 had the activity to inhibit the growth of the breast cancer cell line (MDA-MB-231) after 48 h and managed to arrest the cell cycle of the MDA-MB-231, apoptosis induction, and overexpression of the p53 by interaction with the related apoptotic genes. This research opened up new opportunities for developing potential and selective anticancer agents relying on antimicrobial peptide properties.

Screening of high-risk deleterious missense variations in the CYP1B1 gene implicated in the pathogenesis of primary congenital glaucoma: A comprehensive in silico approach.

Background: Primary congenital glaucoma (PCG) is the most common subtype of glaucoma caused by defects in the cytochrome P450 1B1 (CYP1B1) gene. It is developing among infants in more than 80% of cases who exhibit impairments in the anterior chamber angle and the trabecular meshwork. Thus, a comprehensive in silico approach was performed to evaluate the effect of high-risk deleterious missense variations in the CYP1B1 gene. Material and methods: All the information for CYP1B1 missense variants was retrieved from the dbSNP database. Seven different tools, namely: SIFT, PolyPhen-2, PROVEAN, SNAP2, PANTHER, PhD-SNP, and Predict-SNP, were used for functional annotation, and two packages, which were I-Mutant 2.0 and MUpro, were used to predict the effect of the variants on protein stability. A phylogenetic conservation analysis using deleterious variants was performed by the ConSurf server. The 3D structures of the wild-type and mutants were generated using the I-TASSER tool, and a 50 ns molecular dynamic simulation (MDS) was executed using the GROMACS webserver to determine the stability of mutants compared to the native protein. Co-expression, protein-protein interaction (PPI), gene ontology (GO), and pathway analyses were additionally performed for the CYP1B1 in-depth study. Results: All the retrieved data from the dbSNP database was subjected to functional, structural, and phylogenetic analysis. From the conducted analyses, a total of 19 high-risk variants (P52L, G61E, G90R, P118L, E173K, D291G, Y349D, G365W, G365R, R368H, R368C, D374N, N423Y, D430E, P442A, R444Q, F445L, R469W, and C470Y) were screened out that were considered to be deleterious to the CYP1B1 gene. The phylogenetic analysis revealed that the majority of the variants occurred in highly conserved regions. The MD simulation analysis exhibited that all mutants' average root mean square deviation (RMSD) values were higher compared to the wild-type protein, which could potentially cause CYP1B1 protein dysfunction, leading to the severity of the disease. Moreover, it has been discovered that CYP1A1, VCAN, HSD17B1, HSD17B2, and AKR1C3 are highly co-expressed and interact with CYP1B1. Besides, the CYP1B1 protein is primarily involved in the metabolism of xenobiotics, chemical carcinogenesis, the retinal metabolic process, and steroid hormone biosynthesis pathways, demonstrating its multifaceted and important roles. Discussion: This is the first comprehensive study that adds essential information to the ongoing efforts to understand the crucial role of genetic signatures in the development of PCG and will be useful for more targeted gene-disease association studies.

In silico study of missense variants of FANCA, FANCC and FANCG genes reveals high risk deleterious alleles predisposing to Fanconi anemia pathogenesis.

Among the 22 Fanconi anemia (FA) reported genes, 90% of mutational spectra were found in three genes, namely FANCA (64%), FANCC (12%) and FANCG (8%). Therefore, this study aimed to identify the high-risk deleterious variants in three selected genes (FANCA, FANCC, and FANCG) through various computational approaches. The missense variant datasets retrieved from the UCSC genome browser were analyzed for their pathogenicity, stability, and phylogenetic conservancy. A total of 23 alterations, of which 16 in FANCA, 6 in FANCC and one variant in FANCG, were found to be highly deleterious. The native and mutant structures were generated, which demonstrated a profound impact on the respective proteins. Besides, their pathway analysis predicted many other pathways in addition to the Fanconi anemia pathway, homologous recombination, and mismatch repair pathways. Hence, this is the first comprehensive study that can be useful for understanding the genetic signatures in the development of FA.