Potential inhibitory activity of phytoconstituents against black fungus: In silico ADMET, molecular docking and MD simulation studies

Narmin Hamaamin Hussen; Aso Hameed Hasan; Joazaizulfazli Jamalis; Sonam Shakya; Subhash Chander; Harsha Kharkwal; Sankaranaryanan Murugesan; Virupaksha Ajit Bastikar; Pramodkumar Pyarelal Gupta

doi:10.1016/j.comtox.2022.100247

Potential inhibitory activity of phytoconstituents against black fungus: In silico ADMET, molecular docking and MD simulation studies

Comput Toxicol. 2022 Nov:24:100247. doi: 10.1016/j.comtox.2022.100247. Epub 2022 Sep 24.

Authors

Narmin Hamaamin Hussen¹, Aso Hameed Hasan^{2

3}, Joazaizulfazli Jamalis³, Sonam Shakya⁴, Subhash Chander⁵, Harsha Kharkwal⁵, Sankaranaryanan Murugesan⁶, Virupaksha Ajit Bastikar⁷, Pramodkumar Pyarelal Gupta⁸

Affiliations

¹ Department of Pharmacognosy and Pharmaceutical Chemistry, College of Pharmacy, University of Sulaimani, Sulaimani 46001, Iraq.
² Department of Chemistry, College of Science, University of Garmian, Kalar 46021, Kurdistan Region, Iraq.
³ Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia.
⁴ Department of Chemistry, Faculty of Science, Aligarh Muslim University, Aligarh 202002, India.
⁵ Amity Institute of Phytochemistry and Phytomedicine, Amity Univ Uttar Pradesh, Noida 201313, India.
⁶ Medicinal Chemistry Research Laboratory, Department of Pharmacy, Birla Institute of Technology and Science Pialni, Pilani Campus, Pilani 333031, Rajasthan, India.
⁷ Amity Institute of Biotechnology, Amity University Maharashtra, Mumbai-Pune Expressway, India.
⁸ School of Biotechnology and Bioinformatics, D Y Patil Deemed to be University, Navi Mumbai, Maharashtra, India.

Abstract

Mucormycosis or "black fungus" has been currently observed in India, as a secondary infection in COVID-19 infected patients in the post-COVID-stage. Fungus is an uncommon opportunistic infection that affects people who have a weak immune system. In this study, 158 antifungal phytochemicals were screened using molecular docking against glucoamylase enzyme of Rhizopus oryzae to identify potential inhibitors. The docking scores of the selected phytochemicals were compared with Isomaltotriose as a positive control. Most of the compounds showed lower binding energy values than Isomaltotriose (-6.4 kcal/mol). Computational studies also revealed the strongest binding affinity of the screened phytochemicals was Dioscin (-9.4 kcal/mol). Furthermore, the binding interactions of the top ten potential phytochemicals were elucidated and further analyzed. In-silico ADME and toxicity prediction were also evaluated using SwissADME and admetSAR online servers. Compounds Piscisoflavone C, 8-O-methylaverufin and Punicalagin exhibited positive results with the Lipinski filter and drug-likeness and showed mild to moderate of toxicity. Molecular dynamics (MD) simulation (at 300 K for 100 ns) was also employed to the docked ligand-target complex to explore the stability of ligand-target complex, improve docking results, and analyze the molecular mechanisms of protein-target interactions.

Keywords: ADMET prediction; Black fungus; COVID-19; Molecular docking; Molecular dynamics; Rhizopus oryzae.