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Gaussian field-based comparative 3D QSAR modelling for the identification of favourable pharmacophoric features of chromene derivatives as selective inhibitors of ALR2 over ALR1

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Abstract

Aldehyde reductase (ALR1) and aldose reductase (ALR2) are both oxo-reductase enzymes of aldo-keto reductase (AKR) superfamily involved in several cellular processes. ALR1 plays an important role in colorectal cancer, lungs, and hepatic carcinoma, while ALR2 is involved in diabetic complications like retinopathy, neuropathy, and nephropathy cataract. Both the enzymes take part in distinct physiological processes, however, share more > 70% structural homology. This is the major cause behind the unachieved target selectivity of molecules that entered the development pipeline as ALR2 inhibitors. Chromene analogues have been widely explored for diverse biological activities, including antioxidant and diabetic complication prevention potential. For the identification of spatial fingerprints of target-specific chromene bearing ALR2 inhibitors over ALR1, Gaussian field-based comparative 3D QSAR models were generated on a dataset having ALR1 and ALR2 inhibitory activity. Both the ALR1 and ALR2 3D QSAR models were statistically fit with good predictive ability concerning PLS generated validation constraints. The comparative steric, electrostatic, hydrophobic, HBA, and HBD features were elucidated using respective contour maps for selective target specific favourable activity against ALR2 over ALR1. In addition, the five-point pharmacophores for ALR1 and ALR2 favourable features were also generated using the DHHRR_1 hypothesis for better insight on the distinctive features of ALR2 inhibitors compared to ALR1.

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Abbreviations

3D QSAR:

three-dimensional quantitative structural activity relationship

ACCA:

acetyl-CoA Carboxylase-A

AGEs:

advance glycation end products

AKR:

aldo-keto reductase

ALR1:

aldehyde reductase

ALR2:

aldose reductase

AM1:

Austin Model 1

CNS:

central nervous system

GSH:

glutathione

HBA:

hydrogen bond acceptor

HBD:

hydrogen bond donor

MM2:

molecular mechanics

MOPAC:

molecular orbital package

PLS:

partial least square

RMSD:

root mean square deviation

RMSE:

root mean square error

RNA:

ribonucleic acid

ROS:

reactive oxygen species

SD:

standard deviation

SDH:

sorbitol dehydrogenase

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Acknowledgments

Niraj Kumar is grateful to All India Council for Technical Education (AICTE) for providing GPAT fellowship.

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Author notes

  1. Niraj Kumar contributed equally and designated as first authors.

Authors and Affiliations

  1. ISF College of Pharmacy, Moga, Punjab, 142 001, India

    Sant Kumar Verma

  2. Department of Pharmaceutical Sciences and Natural Products, School of Basic and Applied Sciences, Central University of Punjab, Bathinda, Punjab, 151 019, India

    Niraj Kumar & Suresh Thareja

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  1. Sant Kumar Verma
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  2. Niraj Kumar
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  3. Suresh Thareja
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Contributions

Suresh Thareja conceptualized the present research. The computational methodology and formal analysis were performed by Niraj Kumar. The interpretation of all the results and original draft of manuscript was prepared by Sant Kumar Verma.

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Correspondence to Suresh Thareja.

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Verma, S.K., Kumar, N. & Thareja, S. Gaussian field-based comparative 3D QSAR modelling for the identification of favourable pharmacophoric features of chromene derivatives as selective inhibitors of ALR2 over ALR1. Struct Chem 32, 1289–1298 (2021). https://doi.org/10.1007/s11224-020-01714-6

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