Assessing structural insights into in-house arylsulfonyl L-(+) glutamine MMP-2 inhibitors as promising anticancer agents through structure-based computational modelling approaches

MMP-2 is potentially contributing to several cancer progressions including leukaemias. Therefore, considering MMP-2 as a promising target, novel anticancer compounds may be designed. Here, 32 in-house arylsulfonyl L-(+) glutamines were subjected to various structure-based computational modelling approaches to recognize crucial structural attributes along with the spatial orientation for higher MMP-2 inhibition. Again, the docking-based 2D-QSAR study revealed that the Coulomb energy conferred by Tyr142 and total interaction energy conferred by Ala84 was crucial for MMP-2 inhibition. Importantly, the docking-dependent CoMFA and CoMSIA study revealed the importance of favourable steric, electrostatic, and hydrophobic substituents at the terminal phenyl ring. The MD simulation study revealed a lower fluctuation in the RMSD, RMSF, and Rg values indicating stable binding interactions of MMP-2 and these molecules. Moreover, the residual hydrogen bond and their interaction analysis disclosed crucial amino acid residues responsible for forming potential hydrogen bonding for higher MMP-2 inhibition. The results can effectively aid in the design and discovery of promising small-molecule drug-like MMP-2 inhibitors with greater anticancer potential in the future.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:34

Enthalten in:

SAR and QSAR in environmental research - 34(2023), 10 vom: 16. Okt., Seite 805-830

Sprache:

Englisch

Beteiligte Personen:

Baidya, S K [VerfasserIn]
Banerjee, S [VerfasserIn]
Ghosh, B [VerfasserIn]
Jha, T [VerfasserIn]
Adhikari, N [VerfasserIn]

Links:

Volltext

Themen:

0RH81L854J
Antineoplastic Agents
Arylsulfonamide
CoMFA
CoMSIA
EC 3.4.24.24
Glutamine
Journal Article
MMP-2
Matrix Metalloproteinase 2
Matrix Metalloproteinase Inhibitors
Molecular docking-based QSAR
Molecular dynamics simulation

Anmerkungen:

Date Completed 29.11.2023

Date Revised 29.11.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1080/1062936X.2023.2261842

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM363432809