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Pharmaceuticals
Special Issues
Application of 2D and 3D-QSAR Models in Drug Design
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Application of 2D and 3D-QSAR Models in Drug Design

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

Deadline for manuscript submissions: 24 December 2024 | Viewed by 3813

Special Issue Editor

Dr. Jaime Mella Raipan

E-Mail Website
Guest Editor
Instituto de Química y Bioquímica, Universidad de Valparaíso, Valparaíso, Chile
Interests: 2D-QSAR; 3D-QSAR; Hansch analysis; Free–Wilson; structure–activity relationships; CoMFA; CoMSIA; drug design; molecular docking; molecular dynamics; medicinal chemistry; heterocycles, benzimidazole; organic synthesis; cancer
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Quantitative structure–activity relationship (QSAR) studies enable the correlation of the experimental biological activity of a series of molecules with their physicochemical properties. This allows for a) understanding the structure–activity relationship, and b) predicting the biological activity of new molecules before their synthesis. Therefore, QSAR studies make efficient the design and synthesis of new drugs. Another great advantage of QSAR studies is their versatility, as it is not necessary to know the structure of the target where the molecules act in order to formulate the equation.

We invite the scientific community to publish their work on the design and synthesis of new bioactive molecules in this Special Issue. All works that have direct or indirect applications of QSAR are welcome, such as:

- Formulation of retrospective QSAR studies that discover the pharmacophore of a family of compounds.
- QSAR studies that enable the systematization of the structure–activity relationship of new compounds or databases obtained from the literature.
- Studies that propose the creation of classical Hansch equations, Free–Wilson equations, combined equations, and 3D-QSAR studies such as CoMFA and CoMSIA.
- Works that propose new methodologies or the use of new descriptors.
- Works that employ the integrated use of QSAR techniques, docking, and molecular dynamics for the design of new drugs.
- General design of new bioactive molecules using QSAR equations and prediction of the biological activity value of the compounds, plus a retrosynthesis approach to assess their synthetic feasibility.

Dr. Jaime Mella Raipan
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. 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

  • 2D-QSAR
  • 3D-QSAR
  • Hansch analysis
  • Free–Wilson
  • structure-activity relationships
  • CoMFA
  • CoMSIA
  • drug design
  • molecular docking
  • molecular dynamics.

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Published Papers (3 papers)

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Research

20 pages, 6138 KiB  
Article
Employing Machine Learning-Based QSAR for Targeting Zika Virus NS3 Protease: Molecular Insights and Inhibitor Discovery
by Hisham N. Altayb and Hanan Ali Alatawi
Pharmaceuticals 2024, 17(8), 1067; https://doi.org/10.3390/ph17081067 - 15 Aug 2024
Viewed by 540
Abstract
Zika virus infection is a mosquito-borne viral disease that has become a global health concern recently. Zika virus belongs to the Flavivirus genus and is primarily transmitted by Aedes mosquitoes. Prevention of Zika virus infection involves avoiding mosquito bites by using repellent, wearing [...] Read more.
Zika virus infection is a mosquito-borne viral disease that has become a global health concern recently. Zika virus belongs to the Flavivirus genus and is primarily transmitted by Aedes mosquitoes. Prevention of Zika virus infection involves avoiding mosquito bites by using repellent, wearing protective clothing, and staying in screened areas, especially for pregnant women. Treatment focuses on managing symptoms with rest, fluids, and acetaminophen, with close monitoring for pregnant women. Currently, there is no specific antiviral treatment or vaccine for the Zika virus, highlighting the importance of prevention strategies to control its spread. Therefore, in this study, the Zika virus non-structural protein NS3 was targeted to inhibit Zika infection by identifying the novel inhibitor through an in silico approach. Here, 2864 natural compounds were screened using a machine learning-based QSAR model, and later docking was performed to select the potential target. Subsequently, Tanimoto similarity and clustering were performed to obtain the potential target. The three most potential compounds were obtained: (a) 5297, (b) 432449, and (c) 85137543. The protein–ligand complex’s stability and flexibility were then investigated by dynamic modelling. The 300 ns simulation showed that 5297 exhibited the steadiest deviation and constant creation of hydrogen bonds. Compared to the other compounds, 5297 demonstrated a superior binding free energy (ΔG = −20.81 kcal/mol) with the protein when the MM/GBSA technique was used. The study determined that 5297 showed significant therapeutic potential and justifies further experimental investigation as a possible inhibitor of the NS2B-NS3 protease target implicated in Zika virus infection. Full article
(This article belongs to the Special Issue Application of 2D and 3D-QSAR Models in Drug Design)
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23 pages, 14661 KiB  
Article
An In Silico Study Based on QSAR and Molecular Docking and Molecular Dynamics Simulation for the Discovery of Novel Potent Inhibitor against AChE
by Meriem Khedraoui, Oussama Abchir, Hassan Nour, Imane Yamari, Abdelkbir Errougui, Abdelouahid Samadi and Samir Chtita
Pharmaceuticals 2024, 17(7), 830; https://doi.org/10.3390/ph17070830 - 25 Jun 2024
Viewed by 871
Abstract
Acetylcholinesterase (AChE) is one of the main drug targets for treating Alzheimer’s disease. This current study relies on multiple molecular modeling approaches to develop new potent inhibitors of AChE. We explored a 2D QSAR study using the statistical method of multiple linear regression [...] Read more.
Acetylcholinesterase (AChE) is one of the main drug targets for treating Alzheimer’s disease. This current study relies on multiple molecular modeling approaches to develop new potent inhibitors of AChE. We explored a 2D QSAR study using the statistical method of multiple linear regression based on a set of substituted 5-phenyl-1,3,4-oxadiazole and N-benzylpiperidine analogs, which were recently synthesized and proved their inhibitory activities against acetylcholinesterase (AChE). The molecular descriptors, polar surface area, dipole moment, and molecular weight are the key structural properties governing AChE inhibition activity. The MLR model was selected based on its statistical parameters: R2 = 0.701, R2test = 0.76, Q2CV = 0.638, and RMSE = 0.336, demonstrating its predictive reliability. Randomization tests, VIF tests, and applicability domain tests were adopted to verify the model’s robustness. As a result, 11 new molecules were designed with higher anti-Alzheimer’s activities than the model molecule. We demonstrated their improved pharmacokinetic properties through an in silico ADMET study. A molecular docking study was conducted to explore their AChE inhibition mechanisms and binding affinities in the active site. The binding scores of compounds M1, M2, and M6 were (−12.6 kcal/mol), (−13 kcal/mol), and (−12.4 kcal/mol), respectively, which are higher than the standard inhibitor Donepezil with a binding score of (−10.8 kcal/mol). Molecular dynamics simulations over 100 ns were used to validate the molecular docking results, indicating that compounds M1 and M2 remain stable in the active site, confirming their potential as promising anti-AChE inhibitors. Full article
(This article belongs to the Special Issue Application of 2D and 3D-QSAR Models in Drug Design)
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16 pages, 1774 KiB  
Article
QSAR Studies, Synthesis, and Biological Evaluation of New Pyrimido-Isoquinolin-Quinone Derivatives against Methicillin-Resistant Staphylococcus aureus
by Juan Andrades-Lagos, Javier Campanini-Salinas, Gianfranco Sabadini, Victor Andrade, Jaime Mella and David Vásquez-Velásquez
Pharmaceuticals 2023, 16(11), 1621; https://doi.org/10.3390/ph16111621 - 17 Nov 2023
Cited by 1 | Viewed by 1338
Abstract
According to the WHO, antimicrobial resistance is among the top 10 threats to global health. Due to increased resistance rates, an increase in the mortality and morbidity of patients has been observed, with projections of more than 10 million deaths associated with infections [...] Read more.
According to the WHO, antimicrobial resistance is among the top 10 threats to global health. Due to increased resistance rates, an increase in the mortality and morbidity of patients has been observed, with projections of more than 10 million deaths associated with infections caused by antibacterial resistant microorganisms. Our research group has developed a new family of pyrimido-isoquinolin-quinones showing antibacterial activities against multidrug-resistant Staphylococcus aureus. We have developed 3D-QSAR CoMFA and CoMSIA studies (r2 = 0.938; 0.895), from which 13 new derivatives were designed and synthesized. The compounds were tested in antibacterial assays against methicillin-resistant Staphylococcus aureus and other bacterial pathogens. There were 12 synthesized compounds active against Gram-positive pathogens in concentrations ranging from 2 to 32 µg/mL. The antibacterial activity of the derivatives is explained by the steric, electronic, and hydrogen-bond acceptor properties of the compounds. Full article
(This article belongs to the Special Issue Application of 2D and 3D-QSAR Models in Drug Design)
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