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Computational Studies in Drug Design and Discovery

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 May 2025 | Viewed by 4389

Special Issue Editor


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Guest Editor
Department of Pharmacy, University of Genoa, Viale Benedetto XV, 16132 Genoa, Italy
Interests: medicinal chemistry; GPCR; enzyme; neuroprotective agents; cystic fibrosis; cancer; molecular modeling; virtual screening; homology modeling; repositioning
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Special Issue Information

Dear Colleagues,

Molecular modelling approaches in drug design, such as ligand- and structure-based computational methods, represent widely exploited tools to guide the discovery of novel bioactive molecules.

The identification of novel putative drugs requires experimental assays to validate the therapeutic effectiveness as well as the safety profile of the newly developed compounds. In this context, computational studies represent an intriguing opportunity to accelerate the hit-to-lead and lead optimization process and to lower the costs of drug discovery.

The rapid development of new approaches to better explore novel druggable targets has uncovered new promising perspectives for the rational design and optimization of drug candidates. Structure-based strategies including homology modelling and molecular dynamics techniques as well as ligand-based methods are known exploited tools in the modern medicinal chemistry scenario. Drug repositioning also has emerged as a promising approach to accelerate the drug design and development process. This kind of strategy offers a cost-effective and time-efficient solution for the identification of novel bioactive compounds endowed with a broader spectrum of activity with respect to those already known or described in the literature.

This Special Issue will cover all different aspects of computational methods in drug design leading to the identification of novel hit compounds or optimized analogues, as confirmed by following experimental data. This Special Issue invites both reviews and original articles that shed light on the rational design and hit-to-lead optimization process aided by molecular modelling techniques. Experimental assays validating the whole study are required, giving strong support to the applied strategy. This Special Issue aims to summarize the state of the art, and the latest findings published in medicinal chemistry thanks to the computer-assisted drug design. 

Dr. Elena Cichero
Guest Editor

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Keywords

  • molecular docking
  • homology modeling
  • repositioning
  • virtual screening
  • QSAR
  • molecular dynamics
  • ADME prediction
 

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Published Papers (2 papers)

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Research

20 pages, 4383 KiB  
Article
Discovery of Novel Thiazole-Based SIRT2 Inhibitors as Anticancer Agents: Molecular Modeling, Chemical Synthesis and Biological Assays
by Francesco Piacente, Giorgia Guccione, Naomi Scarano, Dario Lunaccio, Caterina Miro, Elena Abbotto, Annalisa Salis, Bruno Tasso, Monica Dentice, Santina Bruzzone, Elena Cichero and Enrico Millo
Int. J. Mol. Sci. 2024, 25(20), 11084; https://doi.org/10.3390/ijms252011084 - 15 Oct 2024
Viewed by 1252
Abstract
The search and development of effective sirtuin small molecule inhibitors (SIRTIs) continues to draw great attention due to their wide range of pharmacological applications. Based on SIRTs’ involvement in different biological pathways, their ligands were investigated for many diseases, such as cancer, neurodegenerative [...] Read more.
The search and development of effective sirtuin small molecule inhibitors (SIRTIs) continues to draw great attention due to their wide range of pharmacological applications. Based on SIRTs’ involvement in different biological pathways, their ligands were investigated for many diseases, such as cancer, neurodegenerative disorders, diabetes, cardiovascular diseases and autoimmune diseases. The elucidation of a substantial number of SIRT2–ligand complexes is steering the identification of novel and more selective modulators. Among them, SIRT2 in the presence of the SirReal2 analog series was the most studied. On this basis, we recently reported structure-based analyses leading to the discovery of thiazole-based compounds acting as SIRT2 inhibitors (T1, SIRT2 IC50 = 17.3 µM). Herein, ligand-based approaches followed by molecular docking simulations allowed us to evaluate in silico a novel small series of thiazoles (3a3d and 5a, 5d) as putative SIRT2 inhibitors. Results from the computational studies revealed comparable molecular interaction fields (MIFs) and docking positionings of most of these compounds with respect to reference SIRT2Is. Biochemical and biological assays validated this study and pointed to compound 5a (SIRT2 IC50 = 9.0 µM) as the most interesting SIRT2I that was worthy of further development as an anticancer agent. Full article
(This article belongs to the Special Issue Computational Studies in Drug Design and Discovery)
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23 pages, 10610 KiB  
Article
Rationally Designed Novel Antimicrobial Peptides Targeting Chitin Synthase for Combating Soybean Phytophthora Blight
by Yue Ran, Kiran Shehzadi, Jian-Hua Liang and Ming-Jia Yu
Int. J. Mol. Sci. 2024, 25(6), 3512; https://doi.org/10.3390/ijms25063512 - 20 Mar 2024
Viewed by 2107
Abstract
Soybean phytophthora blight is a severe menace to global agriculture, causing annual losses surpassing USD 1 billion. Present crop loss mitigation strategies primarily rely on chemical pesticides and disease-resistant breeding, frequently surpassed by the pathogens’ quick adaptive evolution. In this urgent scenario, our [...] Read more.
Soybean phytophthora blight is a severe menace to global agriculture, causing annual losses surpassing USD 1 billion. Present crop loss mitigation strategies primarily rely on chemical pesticides and disease-resistant breeding, frequently surpassed by the pathogens’ quick adaptive evolution. In this urgent scenario, our research delves into innovative antimicrobial peptides characterized by low drug resistance and environmental friendliness. Inhibiting chitin synthase gene activity in Phytophthora sojae impairs vital functions such as growth and sporulation, presenting an effective method to reduce its pathogenic impact. In our study, we screened 16 previously tested peptides to evaluate their antimicrobial effects against Phytophthora using structure-guided drug design, which involves molecular docking, saturation mutagenesis, molecular dynamics, and toxicity prediction. The in silico analysis identified AMP_04 with potential inhibitory activity against Phytophthora sojae’s chitin synthase. Through three rounds of saturation mutagenesis, we pin-pointed the most effective triple mutant, TP (D10K, G11I, S14L). Molecular dynamic simulations revealed TP’s stability in the chitin synthase-TP complex and its transmembrane mechanism, employing an all-atom force field. Our findings demonstrate the efficacy of TP in occupying the substrate-binding pocket and translocation catalytic channel. Effective inhibition of the chitin synthase enzyme can be achieved. Specifically, the triple mutant demonstrates enhanced antimicrobial potency and decreased toxicity relative to the wild-type AMP_04, utilizing a mechanism akin to the barrel-stave model during membrane translocation. Collectively, our study provides a new strategy that could be used as a potent antimicrobial agent in combatting soybean blight, contributing to sustainable agricultural practices. Full article
(This article belongs to the Special Issue Computational Studies in Drug Design and Discovery)
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