The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1,499 proteins of F. nucleatum, which have no homolog's in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the three dimensional structure of these three proteins. Finally, determination of ligand binding sites of the 2 key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against F. nucleatum.
Anti-Bacterial Agents ; Bacteria ; Binding Sites ; Colonic Neoplasms ; Colorectal Neoplasms ; Computer Simulation* ; Drug Delivery Systems ; Drug Discovery ; Fusobacterium nucleatum* ; Fusobacterium* ; Genes, Essential ; Genome ; Genome, Human ; Genomics ; Humans ; Ligands ; Mass Screening ; Mining* ; Proteome*

Introduction: One of the commonly used techniques for mutation screening is High Resolution Melting (HRM) analysis. HRM is a post PCR method that relies on the detection of the fluorescent signals acquired due to the release of DNA intercalated dyes upon the melting of dsDNA to ssDNA. The method is simple, inexpensive and does not require post PCR-handling, making it suitable for high throughput screening. Methods: This study aimed to develop and validate HRM technique for the screening of two disease-associated single nucleotide polymorphisms (SNPs) namely BDNF rs6265 and DAT1 rs40184 using a total of 30 gDNA samples. The obtained results were confirmed and validated by sequencing. Results: HRM analysis showed that the predicted genotypes of BDNF rs6265 and DAT1 rs40184 among all the gDNA samples were in 100% concordance with the sequencing results, making it an accurate and sensitive method for the detection of SNPs. Conclusions: The application of HRM can accurately determine the genotype of BDNF rs6265 and DAT1 rs40184 SNPs, making it a promising tool for rapid and high-throughput screening of targeted SNPs in a large population study.