QSAR and QSPR: Recent Developments and Applications 2021

A special issue of Chemistry (ISSN 2624-8549). This special issue belongs to the section "Theoretical and Computational Chemistry".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 6413

Special Issue Editor


E-Mail Website
Guest Editor
Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milano, Italy
Interests: QSPR/QSAR; Monte Carlo method; nanoinformatics; toxicology; nanotoxicology; drug discovery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

QSPR/QSAR analysis is a widely used tool for improving knowledge in the fields of natural sciences such as chemistry, biochemistry, medicinal chemistry, and nanochemistry, as well as chemical technology and ecology. There are followers of the above scientific fields. There are opponents in this regard. There are disagreements between researchers who are experts in this large segment of modern science. It is important to integrate different opinions to reach a consensus. It is important to integrate different conceptions of QSPR/QSAR to determine the advantages and disadvantages of various approaches. Most of the problems of QSPR/QSAR persist for a long period of time, e.g., the validation of a model and the definition of the domain of applicability. Besides the mentioned ones, new problems are realized, e.g., how to use the Internet for QSPR/QSAR applications, how to connect traditional experiments and computational experiments, and how to apply data on molecular structures to build up a predictive model. These "simple" questions have not been completely answered yet. Moreover, complete answers to the above questions have hardly even been suggested at all. The joint consideration of organic, inorganic, and metal-organic compounds is impossible. Each of the above classes of compounds requires an individual approach. Special paradigms are necessary for developing predictive QSPR/QSAR models for polymers. Factually, each kind of nanomaterial—such as a fullerene derivative, nanotube, multiwalled nanotube, or quantum dot—again requires a special approach and even a special paradigm, since most nanomaterials have no molecular structure according to "classic" interpretation at all. Nevertheless, the above tasks can be at least partially discussed in this Special Issue.

You may choose our Joint Special Issue in Molecules.

Prof. Dr. Alla P. Toropova
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. Chemistry 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 1800 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

  • Combinatorial Chemistry
  • Drug Discovery
  • Risk Assessment
  • Toxicity of Industrial Pollutants
  • Physicochemical Descriptors
  • Quantum Mechanics Descriptors
  • Optimal Descriptors
  • Topological Indices
  • Monte Carlo Method
  • Nanoinformatics
  • Molecular Docking.

Related Special Issue

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

11 pages, 38798 KiB  
Article
QSAR Modelling of Peptidomimetic Derivatives towards HKU4-CoV 3CLpro Inhibitors against MERS-CoV
by Imad Hammoudan, Soumaya Matchi, Mohamed Bakhouch, Salah Belaidi and Samir Chtita
Chemistry 2021, 3(1), 391-401; https://doi.org/10.3390/chemistry3010029 - 9 Mar 2021
Cited by 11 | Viewed by 2920
Abstract
In this paper, we report the relationship between the anti-MERS-CoV activities of the HKU4 derived peptides for some peptidomimetic compounds and various descriptors using the quantitative structure activity relationships (QSAR) methods. The used descriptors were computed using ChemSketch, Marvin Sketch and ChemOffice software. [...] Read more.
In this paper, we report the relationship between the anti-MERS-CoV activities of the HKU4 derived peptides for some peptidomimetic compounds and various descriptors using the quantitative structure activity relationships (QSAR) methods. The used descriptors were computed using ChemSketch, Marvin Sketch and ChemOffice software. The principal components analysis (PCA) and the multiple linear regression (MLR) methods were used to propose a model with reliable predictive capacity. The original data set of 41 peptidomimetic derivatives was randomly divided into training and test sets of 34 and 7 compounds, respectively. The predictive ability of the best MLR model was assessed by determination coefficient R2 = 0.691, cross-validation parameter Q2cv = 0.528 and the external validation parameter R2test = 0.794. Full article
(This article belongs to the Special Issue QSAR and QSPR: Recent Developments and Applications 2021)
Show Figures

Figure 1

9 pages, 11911 KiB  
Article
Discovery of Novel 1,2,4-Oxadiazole Derivatives as Potent Caspase-3 Activator for Cancer Treatment
by Ankur Vaidya
Chemistry 2021, 3(1), 373-381; https://doi.org/10.3390/chemistry3010027 - 8 Mar 2021
Cited by 3 | Viewed by 2433
Abstract
In the present study, a quantitative structure–activity relationship (QSAR) and docking studies were accomplished on a series of 1,2,4-oxadiazoles. The results of QSARs are reliable and have high predictive ability for both the internal (q2 = 0.610) and external (pred_r2 = [...] Read more.
In the present study, a quantitative structure–activity relationship (QSAR) and docking studies were accomplished on a series of 1,2,4-oxadiazoles. The results of QSARs are reliable and have high predictive ability for both the internal (q2 = 0.610) and external (pred_r2 = 0.553) datasets with least standard error (SE; i.e., 0.130) and four principal components, which signifies the reliability of the generated model. Molecular docking was also reported by the GOLD docking program, which showed that the hydrogen bonding may be responsible for the activity, and may be further increased upon adding high electronegative substitutions. Full article
(This article belongs to the Special Issue QSAR and QSPR: Recent Developments and Applications 2021)
Show Figures

Figure 1

Back to TopTop