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New Avenues in Molecular Docking for Drug Design 2023
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New Avenues in Molecular Docking for Drug Design 2023

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 3712

Special Issue Editor

Prof. Dr. Giulio Vistoli

E-Mail Website
Guest Editor
Department of Pharmaceutical Sciences, Università degli Studi di Milano, via Mangiagalli 25, 20133 Milano, Italy
Interests: computational chemistry; drug design; cheminformatics; molecular docking; ADME predictions; lipophilicity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Molecular docking is gaining increased interest in drug design approaches, especially considering its noteworthy potentialities in performing successful virtual screening campaigns. Currently available computing resources allow for simulations involving huge molecular libraries on extended panels of targets in a reasonable time, and these extremely extended simulations appear to be particularly fruitful in the field of multi-target ligand design as well as in the repurposing studies. Clearly, these powerful simulations require new algorithms and new methodological approaches to optimize their performances and to match the advancements in the hardware architectures. Molecular docking requires continuous improvements especially focused on the algorithms for scoring function and pose evaluation. Molecular docking is often combined with other computational approaches to further improve the reliability of the obtained results in terms of both computed complexes and predictive power, and, in this context, machine learning techniques can offer new avenues with which to improve docking simulations and virtual screening campaigns.

On these grounds, this Special Issue seeks manuscripts dealing with novel approaches of molecular docking in drug design by considering both methodological and applicative studies with a view to offering a picture of the areas in which docking simulations can have an ever-increasing impact in the drug discovery pipeline, as well as with the new trends that will impact on such a field in the next future.

Prof. Dr. Giulio Vistoli
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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

  • structure-based drug design
  • molecular targets
  • molecular recognition
  • ligand binding
  • virtual screening
  • drug repositioning
  • multi-target ligands
  • scoring function
  • pose generation and evaluation
  • big data

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Published Papers (2 papers)

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Research

21 pages, 3635 KiB  
Article
Unveiling the Anticancer Potential: Computational Exploration of Nitrogenated Derivatives of (+)-Pancratistatin as Topoisomerase I Inhibitors
by Magdi Awadalla Mohamed, Tilal Elsaman, Abozer Y. Elderdery, Abdullah Alsrhani, Heba Bassiony Ghanem, Majed Mowanes Alruwaili, Siddiqa M. A. Hamza, Salma Elhadi Ibrahim Mekki, Hazim Abdullah Alotaibi and Jeremy Mills
Int. J. Mol. Sci. 2024, 25(19), 10779; https://doi.org/10.3390/ijms251910779 - 7 Oct 2024
Viewed by 821
Abstract
Cancer poses a substantial global health challenge, driving the need for innovative therapeutic solutions that offer improved effectiveness and fewer side effects. Topoisomerase I (Topo I) has emerged as a validated molecular target in the pursuit of developing anticancer drugs due to its [...] Read more.
Cancer poses a substantial global health challenge, driving the need for innovative therapeutic solutions that offer improved effectiveness and fewer side effects. Topoisomerase I (Topo I) has emerged as a validated molecular target in the pursuit of developing anticancer drugs due to its critical role in DNA replication and transcription. (+)-Pancratistatin (PST), a naturally occurring compound found in various Amaryllidaceae plants, exhibits promising anticancer properties by inhibiting Topo I activity. However, its clinical utility is hindered by issues related to limited chemical availability and aqueous solubility. To address these challenges, molecular modelling techniques, including virtual screening, molecular docking, molecular mechanics with generalised born and surface area solvation (MM-GBSA) calculations, and molecular dynamics simulations were utilised to evaluate the binding interactions and energetics of PST analogues with Topo I, comparing them with the well-known Topo I inhibitor, Camptothecin. Among the compounds screened for this study, nitrogenated analogues emerged as the most encouraging drug candidates, exhibiting improved binding affinities, favourable interactions with the active site of Topo I, and stability of the protein-ligand complex. Structural analysis pinpointed key molecular determinants responsible for the heightened potency of nitrogenated analogues, shedding light on essential structural modifications for increased activity. Moreover, in silico absorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions highlighted favourable drug-like properties and reduced toxicity profiles for the most prominent nitrogenated analogues, further supporting their potential as effective anticancer agents. In summary, this screening study underscores the significance of nitrogenation in augmenting the anticancer efficacy of PST analogues targeting Topo I. The identified lead compounds exhibit significant potential for subsequent experimental validation and optimisation, thus facilitating the development of novel and efficacious anticancer therapeutics with enhanced pharmacological profiles. Full article
(This article belongs to the Special Issue New Avenues in Molecular Docking for Drug Design 2023)
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16 pages, 5943 KiB  
Article
In Silico Search for Drug Candidates Targeting the PAX8–PPARγ Fusion Protein in Thyroid Cancer
by Kaori Sakaguchi, Yoshio Okiyama and Shigenori Tanaka
Int. J. Mol. Sci. 2024, 25(10), 5347; https://doi.org/10.3390/ijms25105347 - 14 May 2024
Viewed by 1148
Abstract
The PAX8/PPARγ rearrangement, producing the PAX8–PPARγ fusion protein (PPFP), is thought to play an essential role in the oncogenesis of thyroid follicular tumors. To identify PPFP-targeted drug candidates and establish an early standard of care for thyroid tumors, we performed ensemble-docking-based compound screening. [...] Read more.
The PAX8/PPARγ rearrangement, producing the PAX8–PPARγ fusion protein (PPFP), is thought to play an essential role in the oncogenesis of thyroid follicular tumors. To identify PPFP-targeted drug candidates and establish an early standard of care for thyroid tumors, we performed ensemble-docking-based compound screening. Specifically, we investigated the pocket structure that should be adopted to search for a promising ligand compound for the PPFP; the position of the ligand-binding pocket on the PPARγ side of the PPFP is similar to that of PPARγ; however, the shape is slightly different between them due to environmental factors. We developed a method for selecting a PPFP structure with a relevant pocket and high prediction accuracy for ligand binding. This method was validated using PPARγ, whose structure and activity values are known for many compounds. Then, we performed docking calculations to the PPFP for 97 drug or drug-like compounds registered in the DrugBank database with a thiazolidine backbone, which is one of the characteristics of ligands that bind well to PPARγ. Furthermore, the binding affinities of promising ligand candidates were estimated more reliably using the molecular mechanics Poisson–Boltzmann surface area method. Thus, we propose promising drug candidates for the PPFP with a thiazolidine backbone. Full article
(This article belongs to the Special Issue New Avenues in Molecular Docking for Drug Design 2023)
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