Computational Software Assisted Multiple Therapeutic Targets Oriented Screening of Some Natural Alkaloid Compounds

Abstract

The current efforts endeavor towards the computational exploration of some interesting
pharmacological potentials of some natural alkaloids by using the Schrodinger Maestro 9.1
software. The excellence in therapeutics was screened against five most imperative targets:
Cyclin-Dependent Kinase-5 (anti-cancer), Cycloxygenase-2 (anti-inflammatory), Protein
kinase C (anti-cancer), Dipeptidyl peptidase (anti-diabetic), and Angiotensin-1-Converting
Enzyme (anti-hypertensive). The alkaloids which were previously reported to possess
antibiotic activities against Bacillus subtilis, Staphylococcus aureus, and Mycobacterium
smegmatis and anti-photo-oxidative, have now perceived to be multi-dimensional compounds
with better pharmacodynamics expression. From the obtained impressive Glide score for the
compounds against the biological target and the dock poses featuring the formation of strong
hydrogen bonding, π-π interactions, and Van der Waals forces through -NH and -OH groups
with several amino acid residues, eventually concluded anti-cancer, anti-diabetic, and antiinflammatory
activities in newer contexts. A new angle of therapeutic excellence can be
noticed from this validated computational study which in larger context rejuvenates and opens
better perspectives for researchers, academicians, and modern scientists towards the
development of dual inhibitors in future. The study explored new applications of various
natural products and has recently developed a perception towards the development of multitargeted
ligands that are not restricted to only one therapeutic response.
Keywords: Alkaloid, molecular docking, in silico, therapeutic target, multi-targeted, inhibitors