In-silico natural product database mining for novel neuropilin-1 inhibitors: molecular docking, molecular dynamics and binding energy computations

Abstract

In the search for new metabolite inhibitors, a natural product activity and species source (NPASS) database was virtually screened using AutoDock software to identify potential NRP1 inhibitors. NPASS compounds complexed with NRP1 were subjected to molecular dynamics (MD) simulations. Furthermore, NPASS-NRP1 binding affinities were calculated using the MM-GBSA approach. Based on calculated binding energies, kamolonol (NPC146388) demonstrated lower NRP1 binding affinity than the co-crystallized HRG/Arg-1 ligand with binding energy (ΔG_binding) values of –34.5 and –32.0 kcal/mol, respectively. Structural and energetic analysis showed high stability for kamolonol and HRG/Arg-1 with NRP1 over the 200 ns MD simulations. The studied physicochemical properties of kamolonol and HRG/Arg-1 revealed that these compounds obey Lipinski's rule of five. ADMET characteristics of kamolonol and HRG/Arg-1 were predicted, and kamolonol showed better ADMET properties compared to HRG/Arg-1. Based on these results, kamolonol is a promising NRP1 inhibitor worthy of further experimental assays as anti-carcinoma remediation.

KEYWORDS:

• Cancer
• neuropilin-1 (NRP1)
• docking calculations
• MD simulations
• pharmacokinetic study

Acknowledgements

Ahmed M. Shawky would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22UQU4331174DSR43). The computational work was completed with resources supported by the Science and Technology Development Fund (STDF-Egypt, Grants No. 5480 and 7972), and Bibliotheca Alexandrina (http://hpc.bibalex.org). Dr. Mahmoud A. A. Ibrahim extends his appreciation to the Academy of Scientific Research and Technology (ASRT), Egypt, for funding Graduation Projects conducted at CompChem Lab, Egypt.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available in the Supporting Information Material of this paper.

Additional information

Funding

This work was supported by Umm Al-Qura University: [grant no 22UQU4331174DSR43].