Literature DB >> 30415281

In silico assessment of new progesterone receptor inhibitors using molecular dynamics: a new insight into breast cancer treatment.

Vahid Zarezade1, Marzie Abolghasemi2, Fakher Rahim3, Ali Veisi4, Mohammad Behbahani5.   

Abstract

Nowadays, breast cancer is one of the most widespread malignancies in women, and the second leading cause of cancer death among women. The progesterone receptor (PR) is one of the treatment targets in breast cancer, and can be blocked with selective progesterone receptor modulators (SPRMs). Since administration of chemical drugs can cause serious side effects, and patients, especially those undergoing long-term treatment, can suffer harmful consequences, there is an urgent need to discover novel potent drugs. Large-scale structural diversity is a feature of natural compounds. Accordingly, in the present study, we selected a library of 20,000 natural compounds from the ZINC database, and screened them against the PR for binding affinity and efficacy. In addition, we evaluated the pharmacodynamics and ADMET properties of the compounds and performed molecular docking. Moreover, molecular dynamics (MD) simulation was carried out in order to examine the stability of the protein. In addition, principal component analysis (PCA) was performed to study the motions of the protein. Finally, the MMPBSA method was applied in order to estimate the binding free energy. Our docking results reveal that compounds ZINC00936598, ZINC00869973 and ZINC01020370 have the highest binding energy into the PR binding site, comparable with that of Levonorgestrel (positive control). Moreover, RMSD, RMSF, Rg and H-bond analysis demonstrate that the lead compounds preserve stability in complex with PR during simulation. Our PCA analysis results were in accordance with MD results and the binding free energies support the docking results. This study paves the way for discovery of novel drugs from natural sources and with optimal efficacy, targeting the PR. Graphical Abstract The binding mode of new progesterone receptor inhibitors.

Entities:  

Keywords:  Breast cancer; Docking; Inhibitor; Molecular dynamics simulation; Progesterone receptor; Virtual screening

Mesh:

Substances:

Year:  2018        PMID: 30415281     DOI: 10.1007/s00894-018-3858-6

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  47 in total

1.  Electrostatics of nanosystems: application to microtubules and the ribosome.

Authors:  N A Baker; D Sept; S Joseph; M J Holst; J A McCammon
Journal:  Proc Natl Acad Sci U S A       Date:  2001-08-21       Impact factor: 11.205

2.  Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation.

Authors:  Araz Jakalian; David B Jack; Christopher I Bayly
Journal:  J Comput Chem       Date:  2002-12       Impact factor: 3.376

3.  Development and testing of a general amber force field.

Authors:  Junmei Wang; Romain M Wolf; James W Caldwell; Peter A Kollman; David A Case
Journal:  J Comput Chem       Date:  2004-07-15       Impact factor: 3.376

4.  A pathway-based classification of human breast cancer.

Authors:  Michael L Gatza; Joseph E Lucas; William T Barry; Jong Wook Kim; Quanli Wang; Matthew D Crawford; Michael B Datto; Michael Kelley; Bernard Mathey-Prevot; Anil Potti; Joseph R Nevins
Journal:  Proc Natl Acad Sci U S A       Date:  2010-03-24       Impact factor: 11.205

5.  Automatic atom type and bond type perception in molecular mechanical calculations.

Authors:  Junmei Wang; Wei Wang; Peter A Kollman; David A Case
Journal:  J Mol Graph Model       Date:  2006-02-03       Impact factor: 2.518

6.  Anti-HIV-1 Activity Prediction of Novel Gp41 Inhibitors Using Structure-Based Virtual Screening and Molecular Dynamics Simulation.

Authors:  Saghi Sepehri; Lotfollah Saghaie; Afshin Fassihi
Journal:  Mol Inform       Date:  2016-10-12       Impact factor: 3.353

7.  Stereoselectivity and the potential endocrine disrupting activity of di-(2-ethylhexyl)phthalate (DEHP) against human progesterone receptor: a computational perspective.

Authors:  Ishfaq Ahmad Sheikh
Journal:  J Appl Toxicol       Date:  2016-02-16       Impact factor: 3.446

8.  AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility.

Authors:  Garrett M Morris; Ruth Huey; William Lindstrom; Michel F Sanner; Richard K Belew; David S Goodsell; Arthur J Olson
Journal:  J Comput Chem       Date:  2009-12       Impact factor: 3.376

9.  Virtual screening, molecular dynamics, and binding free energy calculations on human carbonic anhydrase IX catalytic domain for deciphering potential leads.

Authors:  Arun John; Muthukumaran Sivashanmugam; Vetrivel Umashankar; Sulochana Konerirajapuram Natarajan
Journal:  J Biomol Struct Dyn       Date:  2016-08-02

10.  Control of progesterone receptor transcriptional synergy by SUMOylation and deSUMOylation.

Authors:  Hany A Abdel-Hafiz; Kathryn B Horwitz
Journal:  BMC Mol Biol       Date:  2012-03-22       Impact factor: 2.946

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  3 in total

1.  Exploring safe and potent bioactives for the treatment of non-small cell lung cancer.

Authors:  Muthu Kumar Thirunavukkarasu; Woong-Hee Shin; Ramanathan Karuppasamy
Journal:  3 Biotech       Date:  2021-04-26       Impact factor: 2.406

2.  The Identification of Novel Inhibitors of Human Angiotensin-converting Enzyme 2 and Main Protease of Sars-Cov-2: A Combination of in silico Methods for Treatment of COVID-19.

Authors:  Vahid Zarezade; Hamzeh Rezaei; Ghodratollah Shakerinezhad; Arman Safavi; Zahra Nazeri; Ali Veisi; Omid Azadbakht; Mahdi Hatami; Mohamad Sabaghan; Zeinab Shajirat
Journal:  J Mol Struct       Date:  2021-04-06       Impact factor: 3.196

Review 3.  Review of in silico studies dedicated to the nuclear receptor family: Therapeutic prospects and toxicological concerns.

Authors:  Asma Sellami; Manon Réau; Matthieu Montes; Nathalie Lagarde
Journal:  Front Endocrinol (Lausanne)       Date:  2022-09-13       Impact factor: 6.055

  3 in total

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