Identification of Dual Natural Inhibitors for Chronic Myeloid Leukemia by Virtual Screening, Molecular Dynamics Simulation and ADMET Analysis

Abstract

Chronic myeloid leukemia (CML) is a disease of bone marrow stem cells caused by excessive growth and accumulation of granulocytes in the blood. Aberrant expression of the BCR-ABL proteins in bone marrow stem cells have found out in 95 % cases of CML. Tyrosine Kinase domains (SH2 and SH3) of BCR-ABL proteins are the potent targets to inhibit the process. Initially, imatinib is preferred as an efficient inhibitor to control functional activity of disease. Recently, it has been reported that the advanced stage of CML developed resistance against imatinib. In continuation, dasatinib is the first drug to combat against this disease by targeting multiple receptors and proven better as compared to imatinib. Here, an attempt has been made to identify similar analogs of dasatinib. Virtual screening was performed against various natural compound databases to get some potent natural compounds which are able to inhibit more than one receptor. Binding affinity of screened natural compounds was compared with some of the well-known inhibitors like imatinib, dasatinib, nilotinib etc., by analyzing their docking score and binding efficiency with the receptor. Stability of the best ligand-receptor complex was checked by performing 10 ns molecular dynamics simulation. ADMET properties of the obtained screened compounds were analyzed to check drug like property. Based on the aforementioned analysis, it has been suggested that these screened potent compounds are capable to inhibit multiple receptor proteins like ABL and SRC and consequently combat against the deadly disease CML.

The interaction of the bioflavonoids with five SARS-CoV-2 proteins targets: An in silico study

“…Thus, it is possible that bioflavonoids could have efficacy in the treatment of SARS-CoV-2 by decreasing viral infectivity and replication and/or decreasing the inflammatory response. The identification of naturally-derived anti-SARS-CoV-2 compounds can be done by screening various databases/libraries using computational approaches, such as molecular docking, pharmacophore mapping, 3D-QSAR and molecular dynamics (MD) simulations [ [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] ]. The computational screening approach is advantageous at this time due to the limited access to laboratories and researchers can focus on the outcome of these studies, which could represent a platform for the design and development of novel compounds within a relatively short period of time [ 42 ].…”

In silicoframeworks for systematic pre-clinical screening of potential anti-leukemia therapeutics

“…These studies and several others 27, 28 demonstrate that molecular docking simulations can provide rapid screening of large compound libraries. However, these studies are most effective when the structure of the drug and the target be known a priori .…”

Fisetin 8-C-glucoside as entry inhibitor in SARS CoV-2 infection: molecular modelling study

“…We have used 250 phytochemicals compiled from published literature with antimicrobial properties. Compounds were ranked based on GlideScore and the best pose of the ligand and chosen for further study (Friesner et al., 2004 , 2006 ; Halgren et al., 2004 ; Jacobson et al., 2004 ; Kumar et al., 2016 ; Sastry et al., 2013 ).…”