We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Probing New Antileukemia Agents That Target FLT3 and BCL-2 from Traditional Concoctions through a Combination of Mass Spectrometry Analysis and Consensus Docking Methods.
- Authors
Adeniyi, Adebayo A.; Adeniyi, Joy Nkechinyere; Nlooto, Manimbulu; Singh, Parvesh
- Abstract
The search for new chemotherapeutics against leukemia is of great interest to researchers, owing to the limitation of the current drugs. In this research, new drug candidates against leukemia were probed through liquid chromatography-mass spectrometer (LC-MS) analysis of three traditional herbal concoctions, that provide the phytochemical profile of the samples. The identified compounds from the LC-MS were modeled for the analysis of their antileukemia activities, by using five different consensus methods, to combine the seven docking scores. The consensus methods are used to combine the docking scores to avoid losing promising drug candidates, due to a poor reproducibility of the docking scores across the different packages, due to differences in the scoring functions and training sets across the docking packages. The libraries of the potential drug candidates from the concoctions were constructed by searching the NIST database for molecules with a similar MS fragmentation. Venetoclax and gilteritinib, that target FLT3 and BCL-2 were ranked among the top hits, indicating the efficiency of this protocol without missing any potential drug. The results ranked rescinnamine and bisacodyl as new potential antileukemia agents that targets FLAT3, and BCL-2, including the mutated BCL-2 G101V receptor, that is known to be resistant to treatment with venetoclax.
- Subjects
NATIONAL Institute of Standards &; Technology (U.S.); LIQUID chromatography-mass spectrometry; SET functions; DATABASE searching
- Publication
Applied Sciences (2076-3417), 2022, Vol 12, Issue 22, p11611
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app122211611