Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations

Polishchuk, Pavel; Kutlushina, Alina; Bashirova, Dayana; Mokshyna, Olena; Madzhidov, Timur

doi:10.3390/ijms20235834

Open AccessArticle

Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations

by

Pavel Polishchuk

^1,*

,

Alina Kutlushina

¹,

Dayana Bashirova

²,

Olena Mokshyna

¹

and

Timur Madzhidov

²

¹

Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University and University Hospital in Olomouc, Hnevotinska 5, 77900 Olomouc, Czech Republic

²

A.M. Butlerov Institute of Chemistry, Kazan Federal University, Kremlyovskaya Str. 18, 420008 Kazan, Russia

^*

Author to whom correspondence should be addressed.

Int. J. Mol. Sci. 2019, 20(23), 5834; https://doi.org/10.3390/ijms20235834

Submission received: 2 November 2019 / Revised: 16 November 2019 / Accepted: 18 November 2019 / Published: 20 November 2019

(This article belongs to the Special Issue Recent Developments on Protein–Ligand Interactions: From Structure, Function to Applications)

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Abstract

Pharmacophore models are widely used for the identification of promising primary hits in compound large libraries. Recent studies have demonstrated that pharmacophores retrieved from protein-ligand molecular dynamic trajectories outperform pharmacophores retrieved from a single crystal complex structure. However, the number of retrieved pharmacophores can be enormous, thus, making it computationally inefficient to use all of them for virtual screening. In this study, we proposed selection of distinct representative pharmacophores by the removal of pharmacophores with identical three-dimensional (3D) pharmacophore hashes. We also proposed a new conformer coverage approach in order to rank compounds using all representative pharmacophores. Our results for four cyclin-dependent kinase 2 (CDK2) complexes with different ligands demonstrated that the proposed selection and ranking approaches outperformed the previously described common hits approach. We also demonstrated that ranking, based on averaged predicted scores obtained from different complexes, can outperform ranking based on scores from an individual complex. All developments were implemented in open-source software pharmd.

Keywords: pharmacophore; molecular dynamics; virtual screening

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MDPI and ACS Style

Polishchuk, P.; Kutlushina, A.; Bashirova, D.; Mokshyna, O.; Madzhidov, T. Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations. Int. J. Mol. Sci. 2019, 20, 5834. https://doi.org/10.3390/ijms20235834

AMA Style

Polishchuk P, Kutlushina A, Bashirova D, Mokshyna O, Madzhidov T. Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations. International Journal of Molecular Sciences. 2019; 20(23):5834. https://doi.org/10.3390/ijms20235834

Chicago/Turabian Style

Polishchuk, Pavel, Alina Kutlushina, Dayana Bashirova, Olena Mokshyna, and Timur Madzhidov. 2019. "Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations" International Journal of Molecular Sciences 20, no. 23: 5834. https://doi.org/10.3390/ijms20235834

APA Style

Polishchuk, P., Kutlushina, A., Bashirova, D., Mokshyna, O., & Madzhidov, T. (2019). Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations. International Journal of Molecular Sciences, 20(23), 5834. https://doi.org/10.3390/ijms20235834

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations

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