%0 Journal Article
%T QSAR, Docking Studies and in Silico Admet Prediction of 1,10-Phenanthrolinone Derivatives with Antitubercular Activities
%A Coulibaly Songuigama
%A Abdulrahim A. Alzain
%A Koné Soleymane
%A Deto U. Jean-Paul N’Guessan
%A Brigitte Gicquel
%A Christophe Rochais
%A Patrick Dallemagne
%A Mahama Ouattara
%J Journal of Biochemical Technology
%@ 0974-2328
%D 2024
%V 15
%N 4
%R 10.51847/cop0vCTgXX
%P 17-25
%X Research for new drugs to combat drug resistance in tuberculosis bacilli is one of the solutions to overcome this disease. In this sense, we have designed, synthesized, and fully characterized the chemical structures of about 20 derivatives of 1,10-phenanthrolinone. The evaluation of the antitubercular activities of Mycobacterium tuberculosis revealed that some of these compounds are highly active. Furthermore, the research of the structure-activity connection showed that the derivatives with the nitro group at C6, a carboxylic acid, ester, amide, or hydrazine-like function at C3, and a methyl or ethyl alkylated pyrrolic nitrogen atom at C3 had the best antitubercular activities. The QSAR studies undertaken showed that it is possible to establish a mathematical relationship between antitubercular activities and chemical structures. The obtained QSAR model highlighted that antitubercular activity was significantly affected by chemical softness (s), chemical hardness (η) and chemical potential (μ). In other words, substituents that increase the overall molecular reactivity of 1,10-phenanthrolinone will lead to good antitubercular activities. Furthermore, the prediction of ADMET properties showed that 1,10-phenanthrolinones possess good pharmacokinetic properties. Further, molecular docking confirmed the importance of the carboxylic acid chemical function in position 3 and the nitro group in position 6 for a good affinity of 6-nitro 1,10-phenanthrolinones with deazaflavin-dependent nitroreductase, chosen as a potential target.
%U https://jbiochemtech.com/article/qsar-docking-studies-and-in-silico-admet-prediction-of-110-phenanthrolinone-derivatives-with-antit-zrnteyl1je2ar1x