Microtubule affinity-regulating kinase 4 (MARK4) has recently been identified as a potential drug target for several complex diseases including cancer, diabetes and neurodegenerative disorders. Inhibition of MARK4 activity is an appealing therapeutic option to treat such diseases. Here, we have performed structure-based virtual high-throughput screening of 100,000 naturally occurring compounds from ZINC database against MARK4 to find its potential inhibitors. The resulted hits were selected, based on the binding affinities, docking scores and selectivity. Further, binding energy calculation, Lipinski filtration and ADMET prediction were carried out to find safe and better hits against MARK4. Best 10 compounds bearing high specificity and binding efficiency were selected, and their binding pattern to MARK4 was analyzed in detail. Finally, 100 ns molecular dynamics simulation was performed to evaluate; the dynamics stability of MARK4-compound complex. In conclusion, these selected natural compounds from ZINC database might be potential leads against MARK4, and can further be exploited in drug design and development for associated diseases.
Keywords: , radius of gyration; ADMET; MAP kinases; MARK4 inhibitors; MARK4, microtubule affinity-regulating kinase 4; MD, molecular dynamics; MMPBSA, molecular mechanics Poisson Boltzmann surface area; NPs, natural products; PCA, principal component analysis; PSA, polar surface area; SASA, solvent accessible surface area; binding affinity; drug design & discovery; molecular dynamics simulations; vHTS, virtual high-throughput screening; virtual high throughput screening.