3D-QSAR, Pharmacophore Modeling, ADMET, and DFT Studies ofHalogenated Conjugated Dienones as Potent MAO-B Inhibitors

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Tarih

2024

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Yayıncı

Bentham Science Publ Ltd

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Introduction It has been reported that the extension of conjugation in chalcone scaffolds considerably enhanced the potency, selectivity, reversibility, and competitive mode of MAO-B inhibition. In this study, using the experimental results of IC50 values of fifteen halogenated conjugated dienone derivatives (MK1-MK15) against MAO-B, we developed a 3DQSAR model.Methods Further, we created a 3D pharmacophore model in active compounds in the series. The built model selected three variables (G2U, RDF115m, RDF155m) among the 653 AlvaDesc molecular descriptors, with a r2 value of 0.87 and a Q2 cv for cross-validation equal to 0.82. The three variables were mostly associated with the direction of symmetry and the likelihood of discovering massive atoms at great distances. The evaluated molecules exhibited a good correlation between experimental and predicted data, indicating that the IC50 value of the structure MK2 was related to the interatomic distances of 15.5 & Aring; between bromine and chloro substituents. Furthermore, the molecules in the series with the highest activity were those with enhanced second component symmetry directional index from the 3D representation, which included the structures MK5 and MK6.Results Additionally, a pharmacophore hypothesis was developed and validated using the decoy Schrodinger dataset, with an ROC score of 0.87 and an HHRR 1 fitness score that ranged from 2.783 to 3.00. The MK series exhibited a significant blood-brain barrier (BBB) permeability, according to exploratory analyses and in silico projections, and almost all analogues were expected to have strong BBB permeability.Conclusion Further DFT research revealed that electrostatics were important in the interactions with MAO-B.

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Anahtar Kelimeler

Monoamine oxidase, conjugated dienone, 3D-QSAR, DFT

Kaynak

Current Computer-Aided Drug Design

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N/A

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