Targeting Essential Hypothetical Proteins of Pseudomonas aeruginosa PAO1 for Mining of Novel Therapeutics: An In Silico Approach.

As an omnipresent opportunistic bacterium, Pseudomonas aeruginosa PAO1 is responsible for acute and chronic infection in immunocompromised individuals. Currently, this bacterium is on WHO's red list where new antibiotics are urgently required for the treatment. Finding essential genes and essential hypothetical proteins (EHP) can be crucial in identifying novel druggable targets and therapeutics. This study is aimed at characterizing these EHPs and analyzing subcellular and physiochemical properties, PPI network, nonhomologous analysis against humans, virulence factor and novel drug target prediction, and finally structural analysis of the identified target employing around 42 robust bioinformatics tools/databases, the output of which was evaluated using the ROC analysis. The study discovered 18 EHPs from 336 essential genes, with domain and functional annotation revealing that 50% of these proteins belong to the enzyme category. The majority are cytoplasmic and cytoplasmic membrane proteins, with half being stable proteins subjected to PPIs network analysis. The network contains 261 nodes and 269 edges for 9 proteins of interest, with 11 hubs containing at least three nodes each. Finally, a pipeline builder predicts 7 proteins with novel drug targets, 5 nonhomologous proteins against human proteome, human antitargets, and human gut flora, and 3 virulent proteins. Among these, homology modeling of NP_249450 and NP_251676 was done, and the Ramachandran plot analysis revealed that more than 94% of the residues were in the preferred region. By analyzing functional attributes and virulence characteristics, the findings of this study may facilitate the development of innovative antibacterial drug targets and drugs of Pseudomonas aeruginosa PAO1.

Analysis of SYK Gene as a Prognostic Biomarker and Suggested Potential Bioactive Phytochemicals as an Alternative Therapeutic Option for Colorectal Cancer: An In-Silico Pharmaco-Informatics Investigation.

BACKGROUND: SYK gene regulates the expression of SYK kinase (Spleen tyrosine kinase), an important non-receptor protein-tyrosine kinase for immunological receptor-mediated signaling, which is also considered a tumor growth metastasis initiator. An onco-informatics analysis was adopted to evaluate the expression and prognostic value of the SYK gene in colorectal cancer (CRC), the third most fatal cancer type; of late, it may be a biomarker as another targeted site for CRC. In addition, identify the potential phytochemicals that may inhibit the overexpression of the SYK kinase protein and minimize the human CRC. MATERIALS & METHODS: The differential expression of the SYK gene was analyzed using several transcriptomic databases, including Oncomine, UALCAN, GENT2, and GEPIA2. The server cBioPortal was used to analyze the mutations and copy number alterations, whereas GENT2, Gene Expression Profiling Interactive Analysis (GEPIA), Onco-Lnc, and PrognoScan were used to examine the survival rate. The protein-protein interaction network of SYK kinase and its co-expressed genes was conducted via Gene-MANIA. Considering the SYK kinase may be the targeted site, the selected phytochemicals were assessed by molecular docking using PyRx 0.8 packages. Molecular interactions were also observed by following the Ligplot+ version 2.2. YASARA molecular dynamics simulator was applied for the post-validation of the selected phytochemicals. RESULTS: Our result reveals an increased level of mRNA expression of the SYK gene in colorectal adenocarcinoma (COAD) samples compared to those in normal tissues. A significant methylation level and various genetic alterations recurrence of the SYK gene were analyzed where the fluctuation of the SYK alteration frequency was detected across different CRC studies. As a result, a lower level of SYK expression was related to higher chances of survival. This was evidenced by multiple bioinformatics platforms and web resources, which demonstrated that the SYK gene can be a potential biomarker for CRC. In this study, aromatic phytochemicals, such as kaempferol and glabridin that target the macromolecule (SYK kinase), showed higher stability than the controls, and we have estimated that these bioactive potential phytochemicals might be a useful option for CRC patients after the clinical trial. CONCLUSIONS: Our onco-informatics investigation suggests that the SYK gene can be a potential prognostic biomarker of CRC. On the contrary, SYK kinase would be a major target, and all selected compounds were validated against the protein using in-silico drug design approaches. Here, more in vitro and in vivo analysis is required for targeting SYK protein in CRC.

Prognostic and clinicopathological insights of phosphodiesterase 9A gene as novel biomarker in human colorectal cancer.

BACKGROUND: PDE9A (Phosphodiesterase 9A) plays an important role in proliferation of cells, their differentiation and apoptosis via intracellular cGMP (cyclic guanosine monophosphate) signaling. The expression pattern of PDE9A is associated with diverse tumors and carcinomas. Therefore, PDE9A could be a prospective candidate as a therapeutic target in different types of carcinoma. The study presented here was designed to carry out the prognostic value as a biomarker of PDE9A in Colorectal cancer (CRC). The present study integrated several cancer databases with in-silico techniques to evaluate the cancer prognosis of CRC. RESULTS: The analyses suggested that the expression of PDE9A was significantly down-regulated in CRC tissues than in normal tissues. Moreover, methylation in the DNA promoter region might also manipulate PDE9A gene expression. The Kaplan-Meier curves indicated that high level of expression of PDE9A gene was associated to higher survival in OS, RFS, and DSS in CRC patients. PDE9A demonstrated the highest positive correlation for rectal cancer recurrence with a marker gene CEACAM7. Furtheremore, PDE9A shared consolidated pathways with MAPK14 to induce survival autophagy in CRC cells and showed interaction with GUCY1A2 to drive CRPC. CONCLUSIONS: Overall, the prognostic value of PDE9A gene could be used as a potential tumor biomarker for CRC.