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Molecules
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Computational Methods in Drug Design and Discovery
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Computational Methods in Drug Design and Discovery

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

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 4681

Special Issue Editor

Prof. Dr. Pedro Silva

E-Mail Website
Guest Editor
I3ID/Faculdade de Ciências da Saúde, Universidade Fernando Pessoa, Porto, Portugal
Interests: computational chemistry; reaction mechanisms; enzymology; drug design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

When properly applied, computational chemistry methods can provide unmatched detail regarding chemical reactivity, mechanistic pathways, and the formation of supramolecular complexes today. This Special Issue aims at collecting outstanding contributions of cutting-edge computational methodologies to the broad field of medicinal chemistry. We welcome manuscripts describing original research on the computational development of novel drugs, the analysis of the molecular interaction between known drugs and their cellular targets, as well as the computationally assisted exploration of   the chemical space  for medicinal purposes (such as in silico screening, QSAR, etc.). We are especially interested in manuscripts describing the reaction mechanisms of covalent drugs, the computational improvement of current drugs toward higher selectivity/better pharmacokinetic parameters, and the detailed analysis of the interactions underlying the stability of novel protein/ligand complexes.

Prof. Dr. Pedro Silva
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • computational screening
  • reverse screening
  • molecular dynamics
  • reaction mechanisms
  • covalent inhibitors

Published Papers (2 papers)

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Research

26 pages, 11662 KiB  
Article
In Silico Targeting of Fascin Protein for Cancer Therapy: Benchmarking, Virtual Screening and Molecular Dynamics Approaches
by Heba H. A. Hassan, Muhammad I. Ismail, Mohammed A. S. Abourehab, Frank M. Boeckler, Tamer M. Ibrahim and Reem K. Arafa
Molecules 2023, 28(3), 1296; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules28031296 - 29 Jan 2023
Cited by 2 | Viewed by 1797
Abstract
Fascin is an actin-bundling protein overexpressed in various invasive metastatic carcinomas through promoting cell migration and invasion. Therefore, blocking Fascin binding sites is considered a vital target for antimetastatic drugs. This inspired us to find new Fascin binding site blockers. First, we built [...] Read more.
Fascin is an actin-bundling protein overexpressed in various invasive metastatic carcinomas through promoting cell migration and invasion. Therefore, blocking Fascin binding sites is considered a vital target for antimetastatic drugs. This inspired us to find new Fascin binding site blockers. First, we built an active compound set by collecting reported small molecules binding to Fascin’s binding site 2. Consequently, a high-quality decoys set was generated employing DEKOIS 2.0 protocol to be applied in conducting the benchmarking analysis against the selected Fascin structures. Four docking programs, MOE, AutoDock Vina, VinaXB, and PLANTS were evaluated in the benchmarking study. All tools indicated better-than-random performance reflected by their pROC-AUC values against the Fascin crystal structure (PDB: ID 6I18). Interestingly, PLANTS exhibited the best screening performance and recognized potent actives at early enrichment. Accordingly, PLANTS was utilized in the prospective virtual screening effort for repurposing FDA-approved drugs (DrugBank database) and natural products (NANPDB). Further assessment via molecular dynamics simulations for 100 ns endorsed Remdesivir (DrugBank) and NANPDB3 (NANPDB) as potential binders to Fascin binding site 2. In conclusion, this study delivers a model for implementing a customized DEKOIS 2.0 benchmark set to enhance the VS success rate against new potential targets for cancer therapies. Full article
(This article belongs to the Special Issue Computational Methods in Drug Design and Discovery)
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21 pages, 10457 KiB  
Article
Docking, Binding Free Energy Calculations and In Vitro Characterization of Pyrazine Linked 2-Aminobenzamides as Novel Class I Histone Deacetylase (HDAC) Inhibitors
by Emre F. Bülbül, Jelena Melesina, Hany S. Ibrahim, Mohamed Abdelsalam, Anita Vecchio, Dina Robaa, Matthes Zessin, Mike Schutkowski and Wolfgang Sippl
Molecules 2022, 27(8), 2526; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules27082526 - 14 Apr 2022
Cited by 5 | Viewed by 2336
Abstract
Class I histone deacetylases, HDAC1, HDAC2, and HDAC3, represent potential targets for cancer treatment. However, the development of isoform-selective drugs for these enzymes remains challenging due to their high sequence and structural similarity. In the current study, we applied a computational approach to [...] Read more.
Class I histone deacetylases, HDAC1, HDAC2, and HDAC3, represent potential targets for cancer treatment. However, the development of isoform-selective drugs for these enzymes remains challenging due to their high sequence and structural similarity. In the current study, we applied a computational approach to predict the selectivity profile of developed inhibitors. Molecular docking followed by MD simulation and calculation of binding free energy was performed for a dataset of 2-aminobenzamides comprising 30 previously developed inhibitors. For each HDAC isoform, a significant correlation was found between the binding free energy values and in vitro inhibitory activities. The predictive accuracy and reliability of the best preforming models were assessed on an external test set of newly designed and synthesized inhibitors. The developed binding free-energy models are cost-effective methods and help to reduce the time required to prioritize compounds for further studies. Full article
(This article belongs to the Special Issue Computational Methods in Drug Design and Discovery)
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