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Computational Method in Drug Design and Food Chemistry II

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Medicinal Chemistry".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 4152

Special Issue Editors


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Guest Editor
1. Dipartimento di Scienze della Salute, Università “Magna Græcia” di Catanzaro, 88100 Catanzaro, Italy
2. Net4Science Academic Spin-Off, Università “Magna Græcia” di Catanzaro, 88100 Catanzaro, Italy
Interests: computational chemistry; medicinal chemistry; infectiouse disease; drug repurposing; virtual screening; molecular dynamics; antioxidant activity
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Special Issue Information

Dear Colleagues,

Today, the contribution of computational methodologies to drug discovery is no longer in doubt, and all major world pharmaceutical, academic, and biotechnology companies use computational design tools. Computer-aided drug design includes computational methods and resources that are used to facilitate the design and discovery of new bioactive chemical entities, including natural compounds with potentially nutraceutical activity.

The confirmation of the usefulness of these methodologies came in 2013, when the Nobel prize for chemistry was awarded to Martin Karplus, Michael Levitt, and Arieh Warshel “for the development of multiscale models for complex chemical systems”; thus, from this point of view, chemistry is an experimental science, but theoretical chemists are providing answers to questions about how to design drugs to fit with their target molecules.

In this Special Issue, we encourage authors to submit manuscripts in the form of a research paper, review, or communication that contributes positively in each aspect of medicinal chemistry and drug discovery, from the design of high-throughput screening libraries to providing estimations of the molecular properties required for drug molecules, improving our understanding of how they interact with biological targets of pharmaceutical interest.

This Special Issue will accept original research papers, high-quality reviews, and communications in the field of computational methods in drug design and food chemistry.

Dr. Giosuè Costa
Dr. Isabella Romeo
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • molecular docking and structure-based virtual screening
  • fragment-based drug design
  • advances in molecular dynamics simulations and free-energy
  • calculations applicable in drug design
  • QM applications in drug discovery
  • pharmacophore modeling
  • in silico absorption, distribution, metabolism, and excretion (ADME)
  • computational methods for drug target profiling and polypharmacology
  • integrating structure- and ligand-based approaches for computer-aided drug design
  • multi-target rational drug design
  • computer-aided drug repurposing
  • in silico toxicology

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Published Papers (2 papers)

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Research

17 pages, 5984 KiB  
Article
Pyronaridine as a Bromodomain-Containing Protein 4-N-Terminal Bromodomain (BRD4-BD1) Inhibitor: In Silico Database Mining, Molecular Docking, and Molecular Dynamics Simulation
by Mahmoud A. A. Ibrahim, Mahmoud M. H. Abdelhamid, Khlood A. A. Abdeljawaad, Alaa H. M. Abdelrahman, Gamal A. H. Mekhemer, Peter A. Sidhom, Shaban R. M. Sayed, Paul W. Paré, Mohamed-Elamir F. Hegazy and Tamer Shoeib
Molecules 2023, 28(15), 5713; https://doi.org/10.3390/molecules28155713 - 28 Jul 2023
Cited by 2 | Viewed by 1784
Abstract
BRD4 (bromodomain-containing protein 4) is an epigenetic reader that realizes histone proteins and promotes the transcription of genes linked to cancer progression and non-cancer diseases such as acute heart failure and severe inflammation. The highly conserved N-terminal bromodomain (BD1) recognizes acylated lysine [...] Read more.
BRD4 (bromodomain-containing protein 4) is an epigenetic reader that realizes histone proteins and promotes the transcription of genes linked to cancer progression and non-cancer diseases such as acute heart failure and severe inflammation. The highly conserved N-terminal bromodomain (BD1) recognizes acylated lysine residues to organize the expression of genes. As such, BD1 is essential for disrupting BRD4 interactions and is a promising target for cancer treatment. To identify new BD1 inhibitors, a SuperDRUG2 database that contains more than 4600 pharmaceutical compounds was screened using in silico techniques. The efficiency of the AutoDock Vina1.1.2 software to anticipate inhibitor-BRD4-BD1 binding poses was first evaluated based on the co-crystallized R6S ligand in complex with BRD4-BD1. From database screening, the most promising BRD4-BD1 inhibitors were subsequently submitted to molecular dynamics (MD) simulations integrated with an MM-GBSA approach. MM-GBSA computations indicated promising BD1 binding with a benzonaphthyridine derivative, pyronaridine (SD003509), with an energy prediction (ΔGbinding) of −42.7 kcal/mol in comparison with −41.5 kcal/mol for a positive control inhibitor (R6S). Pharmacokinetic properties predicted oral bioavailability for both ligands, while post-dynamic analyses of the BRD4-BD1 binding pocket demonstrated greater stability for pyronaridine. These results confirm that in silico studies can provide insight into novel protein–ligand regulators, specifically that pyronaridine is a potential cancer drug candidate. Full article
(This article belongs to the Special Issue Computational Method in Drug Design and Food Chemistry II)
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24 pages, 42476 KiB  
Article
Novel Isosteviol-Based FXa Inhibitors: Molecular Modeling, In Silico Design and Docking Simulation
by Marcin Gackowski, Burhanuddin Madriwala, Renata Studzińska and Marcin Koba
Molecules 2023, 28(13), 4977; https://doi.org/10.3390/molecules28134977 - 24 Jun 2023
Cited by 3 | Viewed by 1848
Abstract
Direct oral anticoagulants are an important and relatively new class of synthetic anticoagulant drugs commonly used for the pharmacotherapy of thromboembolic disorders. However, they still have some limitations and serious side effects, which continuously encourage medicinal chemists to search for new active compounds [...] Read more.
Direct oral anticoagulants are an important and relatively new class of synthetic anticoagulant drugs commonly used for the pharmacotherapy of thromboembolic disorders. However, they still have some limitations and serious side effects, which continuously encourage medicinal chemists to search for new active compounds acting as human-activated coagulation factor X (FXa) inhibitors. Isosteviol is a nontoxic hydrolysis product of naturally occurring stevioside and possesses a wide range of therapeutic properties, including anticoagulant activity. The present contribution describes the in silico design of novel oxime ether isosteviol derivatives as well as a molecular modeling approach based on QSAR analysis and a docking simulation for searching for novel isosteviol-based compounds as potential FXa inhibitors. The elaborated ANN model, encompassing topological and geometrical information, exhibited a significant correlation with FXa-inhibitory activity. Moreover, the docking simulation indicated six of the most promising isosteviol-like compounds for further investigation. Analysis showed that the most promising derivatives contain heterocyclic, aromatic, five-membered moieties, with substituents containing chlorine or fluorine atoms. It is anticipated that the findings reported in the present work may provide useful information for designing effective FXa inhibitors as anticoagulant agents. Full article
(This article belongs to the Special Issue Computational Method in Drug Design and Food Chemistry II)
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