TY - JOUR
T1 - In-silico studies of novel triazole derivatives as inhibitor of 14α demethylase cyp51
AU - Rao, Shrusti
AU - Bhat, Varadaraj
AU - Fathima, Fajeelath
AU - Kumar, Santosh
AU - Verma, Ruchi
N1 - Publisher Copyright:
© RJPT All right reserved.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/12
Y1 - 2020/12
N2 - An antifungal agent is a drug that eliminates fungal pathogens selectively from host with negligible toxicity to the host. Antifungal agents are classified into classes like antibiotics, antimetabolite, azole, and allyl amine. In this present work, the binding mode of novel designed triazole analogues with CYP51 has been investigated by flexible molecular docking. The molecular modeling, which gives the utilization of structural information of CYP51 can enhance the discovery of novel antifungal agents. Further in silico studies were performed in order to see their drug likeness properties and possible mode of interaction with target protein residue. Molecular docking of novel molecules was done by Schrodinger software using following steps like protein preparation, ligand preparation, grid generation, molecular docking. The protein PDB selected was 5V5Z. AZ3 analogue showed the best dock score. The docking value varied from-2.578 to-8.19 for the designed ligands. All the molecules showed good ADME properties and followed Lipinski rule of five. The designed molecules can serve as a lead for future antifungal drug discovery.
AB - An antifungal agent is a drug that eliminates fungal pathogens selectively from host with negligible toxicity to the host. Antifungal agents are classified into classes like antibiotics, antimetabolite, azole, and allyl amine. In this present work, the binding mode of novel designed triazole analogues with CYP51 has been investigated by flexible molecular docking. The molecular modeling, which gives the utilization of structural information of CYP51 can enhance the discovery of novel antifungal agents. Further in silico studies were performed in order to see their drug likeness properties and possible mode of interaction with target protein residue. Molecular docking of novel molecules was done by Schrodinger software using following steps like protein preparation, ligand preparation, grid generation, molecular docking. The protein PDB selected was 5V5Z. AZ3 analogue showed the best dock score. The docking value varied from-2.578 to-8.19 for the designed ligands. All the molecules showed good ADME properties and followed Lipinski rule of five. The designed molecules can serve as a lead for future antifungal drug discovery.
UR - http://www.scopus.com/inward/record.url?scp=85100382377&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85100382377&partnerID=8YFLogxK
U2 - 10.5958/0974-360X.2020.01012.4
DO - 10.5958/0974-360X.2020.01012.4
M3 - Article
AN - SCOPUS:85100382377
SN - 0974-3618
VL - 13
SP - 5806
EP - 5810
JO - Research Journal of Pharmacy and Technology
JF - Research Journal of Pharmacy and Technology
IS - 12
ER -