In silico Identification and Characterization of Novel Drug Targets in Treponema denticola (strain ATCC 35405 / DSM 14222 / CIP 103919 / JCM 8153 / KCTC 15104): A Subtractive Genomics Approach - Chowdhury, Ashiqur Rahman Khan; Billah, Sajid Mehran; Meem, Maksuda Begum; Mahi, Mahiea Hossain; Zaman, Tonima; Onia, Sumaiya Khanam; Ishita, Afsana Ferdousi; Hossain, M Mahboob (Community Based Medical Journal, 2024)
Treponema denticola is a gram-negative, highly drug resistant bacterium found in primary dentition infections and around teeth. It causes inflammation and tissue homeostasis, linked to periodontal diseases like earlyonset periodontitis, necrotizing ulcerative gingivitis, and acute pericoronitis. Research is needed to develop powerful, cost-effective, secure, and environmentally friendly antibiotics and techniques to control and manage infections caused by this bacterium. This study exploits the sophisticated in silico subtractive genomics approach to investigate potential therapeutic targets that are exclusive to the pathogen T. denticola. The full sequencing data of the Treponema denticola (strain ATCC 35405 / DSM 14222 / CIP 103919 / JCM 8153 / KCTC 15104) proteome has facilitated the computational analysis of its genome. Our analysis found 126 proteins of the pathogen that had no resemblance to the human genome. The Database of Essential Genes (DEG) identified 12 bacterial proteins which were indispensable to the pathogen, while the KEGG Automated Annotation Server (KAAS) found in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways database analysis of the non-homologous proteins revealed 11 T. denticola enzymes that can be targeted for drug development. Moreover, based on sub-cellular localization prediction, all selected proteins were cytoplasmic proteins and the no outer membrane proteins were present among the non-homologous proteins, and virulent protein predictions revealed no virulent proteins among the selected proteins. Therefore, eleven proteins were selected based on their involvement in unique metabolic pathways inside the pathogen that were not present in the host. The study further revealed the protein-protein interactions of these eleven essential proteins, and successfully anticipated, assessed, and verified the three-dimensional structures of these proteins. Undertaking a screening process to detect functional inhibitors for these newly revealed targets may lead to the discovery of novel therapeutic drugs that can effectively combat Treponema denticola. CBMJ 2024 July: vol. 13 no. 02 P: 251-264