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Pharmacophore modeling, molecular docking, and molecular dynamics simulation approaches for identifying new lead compounds for inhibiting aldose reductase 2

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Abstract

Aldose reductase 2 (ALR2), which catalyzes the reduction of glucose to sorbitol using NADP as a cofactor, has been implicated in the etiology of secondary complications of diabetes. A pharmacophore model, Hypo1, was built based on 26 compounds with known ALR2-inhibiting activity values. Hypo1 contains important chemical features required for an ALR2 inhibitor, and demonstrates good predictive ability by having a high correlation coefficient (0.95) as well as the highest cost difference (128.44) and the lowest RMS deviation (1.02) among the ten pharmacophore models examined. Hypo1 was further validated by Fisher’s randomization method (95%), test set (r = 0.91), and the decoy set shows the goodness of fit (0.70). Furthermore, during virtual screening, Hypo1 was used as a 3D query to screen the NCI database, and the hit leads were sorted by applying Lipinski’s rule of five and ADME properties. The best-fitting leads were subjected to docking to identify a suitable orientation at the ALR2 active site. The molecule that showed the strongest interactions with the critical amino acids was used in molecular dynamics simulations to calculate its binding affinity to the candidate molecules. Thus, Hypo1 describes the key structure–activity relationship along with the estimated activities of ALR2 inhibitors. The hit molecules were searched against PubChem to find similar molecules with new scaffolds. Finally, four molecules were found to satisfy all of the chemical features and the geometric constraints of Hypo1, as well as to show good dock scores, PLPs and PMFs. Thus, we believe that Hypo1 facilitates the selection of novel scaffolds for ALR2, allowing new classes of ALR2 inhibitors to be designed.

Pharmacophore model was generated and validated using various potent techniques. The validated Hypo1 was used in virtual screening to find a novel compounds and subjected to molecular docking and dynamics simulations

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Abbreviations

ADME:

Absorption, distribution, metabolism, and excretion

ALR2:

Aldose reductase 2

BBB:

Blood–brain barrier

DS:

Discovery Studio v.2.5

EF:

Enrichment factor

GF:

Goodness of fit

HBA:

Hydrogen bond acceptor

HAli:

Hydrophobic aliphatic

HAro:

Hydrophobic aromatic

MD:

Molecular dynamics

NI:

Negative ionization

NADPH:

Nicotinamide dinucleotide

53N:

3-[5-(3-Nitrophenyl) thiophen-2-yl] propanoic acid

PME:

Particle mesh Ewald

PLP:

Piecewise linear potential

PMF:

Potential of mean force

RA:

Ring aromatic

RMS:

Root mean square

RMSD:

Root mean square deviation

RMSF:

Root mean square fluctuation

TIM:

Triose phosphate isomerase

VMD:

Visual molecular dynamics

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Acknowledgments

This research was supported by the Basic Science Research Program (2009–0073267), the Pioneer Research Center Program (2009–0081539), and the Management of Climate Change Program (2010–0029084) through the National Research Foundation of Korea (NRF), as funded by the Ministry of Education, Science and Technology (MEST) of the Republic of Korea. This work was also supported by the Next-Generation BioGreen21 Program (PJ008038) from the Rural Development Administration (RDA) of the Republic of Korea.

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Authors and Affiliations

  1. Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center (SSAC), Plant Molecular Biology and Biotechnology Research Center (PMBBRC)f, Research Institute of Natural Science (RINS), Gyeongsang National University (GNU), 501 Jinju-daero, Gazha-dong, Jinju, 660-701, Republic of Korea

    Sugunadevi Sakkiah, Sundarapandian Thangapandian & Keun Woo Lee

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  1. Sugunadevi Sakkiah
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  2. Sundarapandian Thangapandian
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Correspondence to Keun Woo Lee.

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Sakkiah, S., Thangapandian, S. & Lee, K.W. Pharmacophore modeling, molecular docking, and molecular dynamics simulation approaches for identifying new lead compounds for inhibiting aldose reductase 2. J Mol Model 18, 3267–3282 (2012). https://doi.org/10.1007/s00894-011-1247-5

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