In silico and in vitro evaluation of extract derived from Dunaliella salina, a halotolerant microalga for its antifungal and antibacterial activity

Abstract

In the present study little explored halotolerant wall-less green alga Dunaliella salina was found to be a potent source of antibacterial and antifungal biomolecules. Both the target pathogens, bacteria (Escherischia coli, Klebsiella pneumoniae, and Acinetobacter baumannii) and fungi (Candida albicans, C. tropicalis, and Cryptococus sp.) were WHO prioritized. The bioassay guided approach led us to evaluate antibacterial and antifungal lead molecule(s) from an array of compounds using spectroscopic and in silico studies. The methanol derived crude extract was purified via thin layer chromatography (TLC) using solvent system methanol: chloroform (1:19). Maximum antimicrobial activity was observed in fractions D5, D6 and D7, the components of which were then recognized using high resolution-liquid chromatography/mass spectroscopy (Orbitrap) (HR-LC/MS). The screened compounds were then docked with target enzymes sterol-14-alpha demethylase and OmpF porin protein. The energy scores revealed that amongst all, lariciresinol-4-O-glucoside showed better binding affinity, in silico, using the Schrödinger Maestro 2018-1 platform. The 3-dimensional crystal structures of both the proteins were retrieved from the protein data bank (PDB), and showed binding energies of −14.35 kcal/mol, and −11.0 kcal/mol against respective drug targets. The molecular dynamics (MD) simulations were performed for 100 ns, using Desmond package, Schrödinger to evaluate the conformational stability and alteration of protein-ligand complexes during the simulation. Thus, our findings confirmed that lariciresinol-4-O-glucoside, a lignan derivative and known strong antioxidant, may be used as an important “lead” molecule to be developed as antibacterial and antifungal drugs in the future.

Communicated by Ramaswamy H. Sarma

Keywords:

• Dunaliella salina
• antimicrobial
• HR-LC/MS (Orbitrap)
• In silico
• molecular dynamics simulation

Acknowledgements

We greatly acknowledge Head and Programme Coordinator, CAS in Botany, DST-FIST, ISLS, BHU for providing research facilities and IOE (SCHEME No-6031) for partial funding and Ministry of Science and Technology. The financial supports are also acknowledged by US (09/013/(0597)/2015-EMR-I), PS (DSKPDF; No. F. 4-2/2006 (BSR)/BL/19-20/0162), AS (22/12/2013(ii)EU-V), Laxmi (1012/(OBC) (CSIR-UGC NET DEC. 2016), SS (BHU RET fellowship), and Nidhi Pandey, Institute of Medical Science, Banaras Hindu University, Varanasi for providing pathogenic fungal strains.

Disclosure statement

No potential conflict of interest was reported by the authors.

Author contributions

Conception and Design: Prof. Ravi K. Asthana, and Urmilesh Singh. Data curation: Urmilesh Singh, Laxmi, Ankit K. Singh, and Sweksha Singh. Formal analysis: Prof. Ravi K. Asthana, Prof. Sushant K. Shrivastava, and Urmilesh Singh. Methodology: Urmilesh Singh, Prabhakar Singh, and Dr. Deepak Kumar. Project administration: Prof. Ravi K. Asthana. Resources: Prof. Ravi K. Asthana, Prof. Sushant K. Shrivastava, and Dr. Deepak Kumar. Supervision: Prof. Ravi K. Asthana. Writing (original draft): Urmilesh Singh. Writing (Review and editing): Prof. Ravi K. Asthana, Prof. Sushant K. Shrivastava, and Prabhakar Singh

Additional information

Funding

We greatly acknowledge Head and Programme Coordinator, CAS in Botany, DST-FIST, ISLS, BHU for providing research facilities and IOE (SCHEME No-6031) for partial funding and Ministry of Science and Technology. The financial supports are also acknowledged by US (09/013/(0597)/2015-EMR-I), PS (DSKPDF; No. F. 4-2/2006 (BSR)/BL/19-20/0162), AS (22/12/2013(ii)EU-V), Laxmi (1012/(OBC) (CSIR-UGC NET DEC. 2016), SS (BHU RET fellowship), and Nidhi Pandey, Institute of Medical Science, Banaras Hindu University, Varanasi for providing pathogenic fungal strains.