## 4 Conclusions  
A total of 262 potential antileukemia candidates were identified from the three samples, using LC-MS and were screened against leukemia targets FLAT3, BCL-2, and the mutated BCL-2 G101V, after excluding those that have inorganic metals, such as silicon.  
The results from the ECR offered a better ranking of the potential drug candidates without excluding the benchmark molecules ventoclax and gilteritinib, which are known antileukemia drugs that target BCL-2 and FLAT3, respectively.  
Among the top hit inhibitors from both the docking and consensus results, are 24815245 (rescinnamine) and 101757 (benzenamine, N-phenyl-4-(phenylazo)) that target FLAT3, as well as 865043 (methoserpidine) and 603509 (bisacodyl), that target BCL-2.  
Methoserpidine and rescinamine, which were found to be potential inhibitors of BCL-2 and FLAT3, respectively, were also predicted to be the top two promising inhibitors of the mutated BCL-2 G101V.  
The binding interactions of the top hit potential drug candidates from the traditional concoctions are demonstrated to have similar residue interactions as the known drugs that target FLAT3 and BCL-2. This is an indication that the proposed potential drugs explored have similar binding pockets that define the activity of the known inhibitors of  
Figure 6: The docking pose binding site interaction of the rescinamine (24815245) with FLAT 3 (6 il3) and the mutated BCL-2 G101V (6o0I) and the interaction of bisacodyl (603509) with BCL-2 (6o0k), comparing the residue interaction with that of the crystal structure of the gilteritinib interaction with FLAT3 and the ventoclax interaction with BCL-2 and the mutated BCL-2 G101V.  
these targets. A different study on the experimental anticancer activities of the conoctions using leukemia cancer cell lines is also under consideration.  
The following supporting information can be download at: [[https://www.mdpi.com/article/10.3390/app122211611/s1](https://www.mdpi.com/article/10.3390/app122211611/s1)]([https://www.mdpi.com/article/10.3390/app122211611/s1](https://www.mdpi.com/article/10.3390/app122211611/s1)).  
Conceptualization, A.A.A.; Formal analysis, J.N.A.; Investigation, A.A.A. and M.N.; Project administration, M.N.; Supervision, P.S.; Writing--original draft, A.A.A.; Writing--review & editing, P.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Research Foundation (Grant No. 121276).  
Not applicable.  
All of the necessary data that can help in the reproducibility of the results are included in the manuscript and also in the Supplementary Materials. The experimental LC-MS raw files were analyzed using the automatic mass spectral deconvolution and identification system (AMDIS) package version 2.73. The docking study was accomplished using Moledock version 2013.6.0, Autodock vina version 1.1.2, Glide in Schrodinger package version 2020, and Haddock docking package version 2.2. In all software used, the default parameters were used and all of the modifications are clearly stated in the methodology. Most of the data analysis and plotting are accomplished using Gnuplot version 5.2.  
The authors would like to acknowledge the University of Kwazulu-Natal financial support and the Centre for High-Performance Computing (CHPC), Cape Town (South Africa), for the supercomputing facilities. P.S. thanks the National Research Foundation (NRF) South Africa for a Competitive Grant for unrated Researchers (Grant No. 121276).  
The authors declare no conflict of interest.