Background:
The anticancer properties of natural products calactin, calotropin and calotoxin are well established.
However the mechanisms of their action are unclear and the molecular targets pertinent to them are not detailed. In this
study, potential anti-cancer targets of these compounds have been identified using reverse screening approaches that may
provide valuable insights into anti cancer drug development.
Objective:
To identify the potential anticancer targets of calactin, calotropin and calotoxin using reverse screening strategy.
Methods:
The ligands were screened for potential targets based on their shape similarity and pharmacophore model matching. The overlapping targets obtained from both methods were verified using reverse docking approach and validated by
docking analysis. MM/PBSA calculation was performed to predict binding affinities between ligand and confirmed targets.
Results:
Interleukin-2 inducible T cell kinase [ITK] was confirmed as a potential target of calactin (Ki= -10.3 kcal/mol),
calotropin (Ki= -8.7 kcal/mol) and calotoxin (Ki= -10.2 kcal/mol). The ligands interacted with hinge region residues such as
Met438 and Asp500 which occupy the highly conserved ATP binding site. Binding energies of calactin (∆Ebind = -29.18
kJ/mol), calotropin (-28.57 kJ/mol) and calotoxin (-21.21 kJ/mol) with ITK were higher than (more negative) positive control sunitinib (-15.03 kJ/mol) and standard staurosporine (-21.09 kJ/mol). Besides this, Interstitial collagenase [MMP1] was
confirmed as potential target of calotoxin (Ki= -8.2 kcal/mol).However the binding energy (∆Ebind = -11.89 kJ/mol) was
lower compared to positive control batimastat (-21.07 kJ/mol).
Conclusion:
The results of this study confirmed ITK as a potential target for calactin, calotropin and calotoxin. These compounds can therefore be used as lead molecules for the development of novel ITK inhibitors, which may have immense
therapeutic applications as immune-suppressants and as anticancer drugs.
Model-Matching type-methods and Stability of Networks consisting of non-Identical Dynamic Agents
