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Virtual screening of PEBP1 inhibitors by combining 2D/3D-QSAR analysis, hologram QSAR, homology modeling, molecular docking analysis, and molecular dynamic simulations

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Abstract

Human phosphatidylethanolamine binding protein 1 (hPEBP1) is a novel target affecting many cellular signaling pathways involved in the formation of metastases. It can be used in the treatment of many cases of cancer. For these reasons, pharmaceutical companies use computational approaches, including multi-QSAR (2D, 3D, and hologram QSAR) analysis, homology modeling, molecular docking analysis, and molecular dynamic simulations, to speed up the drug discovery process. In this paper, QSAR modeling was conducted using two quantum chemistry optimization methods (AM1 and DFT levels). As per PLS results, we found that the DFT/B3LYP method presents high predictability according to 2D-QSAR, CoMFA, CoMSIA, and hologram QSAR studies, with Q2 of 0.81, 0.67, 0.79, and 0.67, and external power with R2pred of 0.78, 0.58, 0.66, and 0.56, respectively. This result has been validated by CoMFA/CoMSIA graphics, which suggests that electrostatic fields combined with hydrogen bond donor/acceptor fields are beneficial to the antiproliferative activity. While the hologram QSAR models show the contributions of each fragment in improving the activity. The results from QSAR analyses revealed that ursolic acids with heterocyclic rings could improve the activities. Ramachandran plot validated the modeled PEBP1 protein. Molecular docking and MD simulations revealed that the hydrophobic and hydrogen bond interactions are dominant in the PEBP1’s pocket. These results were used to predict in silico structures of three new compounds with potential anticancer activity. Similar molecular docking stability studies and molecular dynamics simulations were conducted.

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The data is integrated into the manuscript.

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Abbreviations

hPEBP1:

Human phosphatidylethanolamine binding protein 1

QSARs:

Quantitative structure–activity relationships

2D:

Two dimensional

3D:

Three dimensional

DFT:

Density functional theory

AM1:

Austin model 1

MDs:

Molecular dynamics

CoMFA:

Comparative molecular field analysis

CoMSIA:

Comparative molecular similarity indices analysis

HQSAR:

Hologram quantitative structure–activity relationships

GMQE score:

Global Model Quality Estimation

OECD:

Organization for Economic Co-operation and Development

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Funding

This work was supported by the National Center for Scientific and Technical Research (CNRST — Morocco) as part of the Research Excellence Awards Program (no. 34USMBA2017).

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  1. Laboratory of Natural Substances, Pharmacology, Environment, Modeling, Health & Quality of Life (SNAMOPEQ), Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University of Fez, Taza Gare, B.P 1223, Taza, Morocco

    Mourad Stitou, Hamid Toufik, Taoufik Akabli & Fatima Lamchouri

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Stitou, M., Toufik, H., Akabli, T. et al. Virtual screening of PEBP1 inhibitors by combining 2D/3D-QSAR analysis, hologram QSAR, homology modeling, molecular docking analysis, and molecular dynamic simulations. J Mol Model 28, 145 (2022). https://doi.org/10.1007/s00894-022-05143-6

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