Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
9.0
5.7
Journals
Pharmaceuticals
Special Issues
Drug Target Exploration and Drug Design & Development Based on...
share announcement

Drug Target Exploration and Drug Design & Development Based on Small Molecule: 2nd Edition

A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Pharmacology".

Deadline for manuscript submissions: 25 December 2026 | Viewed by 2377

Editors

Dr. Marco Tutone

E-Mail Website
Guest Editor
Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF), Università degli Studi di Palermo, Via Archirafi 32, 90123 Palermo, Italy
Interests: oxidative stress; nutraceuticals; anticancer drugs; medicinal chemistry; drug design and discovery; molecular modeling; QSAR; pharmacophore modeling; molecular dynamics; docking; HTVS; cystic fibrosis translational readthrough inducing drugs (TRIDs)
Special Issues, Collections and Topics in MDPI journals
Dr. Giulia Culletta

E-Mail Website
Guest Editor
Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo, 90123 Palermo, Italy
Interests: medicinal chemistry; drug design; computational chemistry; drug repurposing; green chemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The development of novel therapeutics represents a significant area of scientific interest, with small-molecule compounds offering a promising frontier in this field of research. On a global scale, approximately 90% of all drugs sold are small molecules. Of the 293 new chemical entities that the FDA approved in 2017–22, 182 were small-molecule drugs (10.1016/j.med (idd.2020.100075)). It is also known that of all the 175 small molecules approved for cancer therapy from 1940 to 2014, 49% (85) were natural products or their derivatives, and these include vinca alkaloids, epipodophyllotoxin derivatives, taxanes, and camptothecin derivatives (https://doi.org/10.1007/s42977-022-00110-x). The ability of small molecules to modulate the functionality of diverse targets (proteins or nucleic acids) through the process of activation or inhibition provides a potential strategy for the treatment of conditions such as cancer, autoimmune disorders, infectious diseases, and inflammatory diseases (10.3390/ijms21155262).

The recent advancements in medicinal chemistry have facilitated the identification and development of small molecules by using classical and green methods. Moreover, the application of computational approaches such as docking and molecular dynamics has been crucial in the exploration of potential targets, including those that are traditionally considered 'undruggable' or orphans (https://doi.org/10.3390/books978-3-0365-2778-9). This Special Issue aims to provide a comprehensive overview of the latest advances in the research on drug target exploration as well as drug design and development based on small molecules. We welcome submissions from researchers in the field of drug discovery and design, including original research and review articles related to pharmaceutical sciences, pharmacology, chemical biology, and bioinformatics.  

The first edition of our Special Issue, titled "Drug Target Exploration and Drug Design & Development Based on Small Molecule," garnered significant scholarly interest. Building upon this success, we are pleased to announce the release of its second edition “Drug Target Exploration and Drug Design & Development Based on Small Molecule: 2nd Edition”. This Special Issue aims to provide a comprehensive overview of the latest advances in the research on drug target exploration as well as drug design and development based on small molecules. We welcome submissions from researchers in the field of drug discovery and design, including original research and review articles related to pharmaceutical sciences, pharmacology, chemical biology, and bioinformatics.

Dr. Marco Tutone
Dr. Giulia Culletta
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceuticals is an international peer-reviewed open access monthly 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 2900 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

  • small molecules
  • drug design and development
  • target exploration
  • anticancer drugs
  • anti-inflammatory drugs
  • neuromodulation
  • natural compounds
  • nutraceuticals
  • virtual screenings

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

29 pages, 7585 KB  
Article
Computational Evaluation of Novel PARP-1 Inhibitors for Breast Cancer: Docking, Molecular Dynamics, MM/GBSA, DFT and ADMET Calculations
by Charmy Twala, Penny Govender, Ephraim Marondedze and Krishna Govender
Pharmaceuticals 2026, 19(6), 914; https://doi.org/10.3390/ph19060914 - 10 Jun 2026
Viewed by 686
Abstract
Background/Objectives: Poly (ADP-ribose) polymerase (PARP1) has emerged as a promising therapeutic target in human breast cancer particularly in BRCA1/2 mutation carriers where a synthetic lethal interaction leads to massive tumor cell death upon specific inhibitors’ administration. Current clinically approved PARP inhibitors (Talazoparib [...] Read more.
Background/Objectives: Poly (ADP-ribose) polymerase (PARP1) has emerged as a promising therapeutic target in human breast cancer particularly in BRCA1/2 mutation carriers where a synthetic lethal interaction leads to massive tumor cell death upon specific inhibitors’ administration. Current clinically approved PARP inhibitors (Talazoparib and Olaparib) show outstanding therapeutic capabilities but suffer from severe side effects. Most importantly, some of them can cause life-threatening cardiotoxicity through hERG off-target effects. Here, we performed an extensive study to identify lead compounds with improved binding modes and favorable predicted pharmacokinetics using an integrated computational strategy. Methods: An artificial intelligence-driven drug design (AIDDISON™ v2023) workflow was employed to search ultra-large chemical space libraries for active compounds, which were then optimized via computer-aided methods to form a PARP-Tailored Database (PTD). This database was then analyzed through a virtual screening workflow, molecular docking studies, molecular dynamics (MD) simulations, MM/GBSA binding free energy calculations, DFT analysis and ADME/Tox predictions using the Schrödinger suite (v2023-2), MobaXterm v25.2, Gaussian 16.0, ProTox-3 and Pred-hERG v5.0 respectively. Results: Three compounds (1a–1c) were identified as promising candidates. Among them 1a appeared to be the most active compound with a favorable docking score (−9.488 kcal/mol) that is not only higher than 1b and 1c but also higher than that of Talazoparib (−6.778 kcal/mol). MD simulations of 1a–1c in the active site revealed an average RMSD of ~2.5–3.6 Å which is better compared to the parent Talazoparib (5.6 Å). Interestingly, on the 250 ns extended MD study, 1a exhibited a slightly reduced RMSD between 2.4 and 3.2 Å, whereas Talazoparib retained higher fluctuations of ~5 Å to 6 Å. MM/GBSA binding energy analysis indicated 1a to have better predicted binding affinity (−67.820 kcal/mol), which is also better than Talazoparib (−63.734 kcal/mol). DFT calculations showed good electronic properties and in silico ADMET studies also indicated 1a to have good drug-likeness and lower predicted hepatotoxicity and cardiotoxicity risk. Conclusions: These findings identify compound 1a as a promising lead, while compounds 1b and 1c remain viable candidates for further optimization. However, experimental validation is critical to confirm the predicted biological activity and safety profiles. Full article
(This article belongs to the Special Issue Drug Target Exploration and Drug Design & Development Based on Small Molecule: 2nd Edition)
►▼ Show Figures

Graphical abstract

32 pages, 2609 KB  
Article
QSAR-Guided Design of Serotonin Transporter Inhibitors Supported by Molecular Docking and Biased Molecular Dynamics
by Aleksandar M. Veselinović, Giulia Culletta, Jelena V. Živković, Slavica Sunarić, Žarko Mitić, Muhammad Sohaib Roomi and Marco Tutone
Pharmaceuticals 2026, 19(3), 444; https://doi.org/10.3390/ph19030444 - 10 Mar 2026
Viewed by 1219
Abstract
Background/Objectives: Serotonin transporter (SERT) inhibition represents a central pharmacological strategy in the treatment of major depressive disorder. In this study, an integrated computational framework combining quantitative structure–activity relationship (QSAR) modeling, molecular docking analysis, and in silico ADMET profiling was applied to identify [...] Read more.
Background/Objectives: Serotonin transporter (SERT) inhibition represents a central pharmacological strategy in the treatment of major depressive disorder. In this study, an integrated computational framework combining quantitative structure–activity relationship (QSAR) modeling, molecular docking analysis, and in silico ADMET profiling was applied to identify and prioritize novel candidate structures. Methods: Conformation-independent QSAR models were developed using local molecular graph invariants and SMILES-based descriptors optimized through a Monte Carlo learning procedure, while a genetic algorithm–multiple linear regression (GA–MLR) was employed to derive statistically robust predictive models from a large descriptor pool. Model quality, robustness, and external predictivity were rigorously evaluated using multiple statistical validation criteria. In parallel, a field-based contribution analysis was applied to construct a three-dimensional QSAR model, enabling spatial interpretation of structure–activity relationships. Fragment-level contributions associated with activity enhancement or attenuation were subsequently identified and used to design new candidate inhibitor structures. Results: The designed compounds were further evaluated by molecular docking, InducedFit Docking and Binding Pose MetaDynamics (BPMD) into the SERT binding site, providing a structure-based assessment consistent with the trends observed in QSAR modeling. In addition, in silico ADMET analysis was performed to assess key pharmacokinetic and safety-related properties relevant to central nervous system drug development. Conclusions: The proposed workflow demonstrates the utility of combining data-driven QSAR modeling with structure-based and pharmacokinetic considerations to rationalize and prioritize novel serotonin transporter-focused scaffold optimization, offering a transferable strategy for early-stage antidepressant drug discovery. Full article
(This article belongs to the Special Issue Drug Target Exploration and Drug Design & Development Based on Small Molecule: 2nd Edition)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop