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Application of Natural or Synthetic Products in Computer-Aided Drugs
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Application of Natural or Synthetic Products in Computer-Aided Drugs

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Medicinal Chemistry".

Deadline for manuscript submissions: 31 October 2024 | Viewed by 5776

Special Issue Editor

Dr. Cleydson Breno Rodrigues dos Santos

E-Mail Website1 Website2
Guest Editor
Laboratory of Modeling and Computational Chemistry, Federal University of Amapá, Macapá 68902-280, Amapá, Brazil
Interests: drug design; virtual screening; molecular modeling; docking; molecular simulations; quantum chemistry

Special Issue Information

Dear Colleagues,

The most important milestone for the development of drugs from natural plant products was the discovery of salicylates obtained from Salix alba. This fascinating story begins in 1757, when Reverend Edward Stone tasted the bitter taste of willow bark (S. alba) and associated it with the flavor of Cinchona extracts. This fact aroused his curiosity and imagination, leading him to communicate to the Royal Society, six years later, the results of his clinical observations showing the analgesic and antipyretic properties of the extract of that plant. Fifty years later, France and Germany were rivals in the search for the active principle of S. alba, and in 1828, at the Institute of Pharmacology in Munich, Johann A. Buchner isolated a small amount of salicin. Several other scientists worked to improve the yields and quality of salicin obtained from natural extracts until, in 1860, Hermann Kolbe and his students synthesized salicylic acid and its sodium salt from phenol.

In 1898, Felix Hofmann, researching a cure for the arthritis that afflicted his father, who was sensitive to the side effects of sodium salicylate, discovered acetylsalicylic acid, which is less acidic than salicylic acid but retains the desired analgesic property. Since the end of the 19th century when aspirin was synthesized by modifying the structure of a natural product, scientists have been engaged in drug design and discovery.

With the development of computational methods and large databases, various drug design and in silico studies have been conducted and challenged. Current researchers can identify the molecular structures essential for biological activity more readily and screen large libraries of compounds with the help of high-performance computers and degrees of specificity. The computer-aided drug design methodology plays an increasingly important role in modern drug discovery.

This Special Issue of Molecules focuses on drug design, in silico screening, and ethnopharmacology approaches. All articles relating to drug design and discovery are welcomed, including, but not limited to, the following aspects: CADD methodology, virtual screening of compound libraries by computational methods, structural optimization of lead compounds, modeling studies on the interaction between small molecules and macromolecules, and ethnopharmacology. Cell-based or animal (zebrafish, for example) experiments are also encouraged involving any disease model, but not essential.

Dr. Cleydson Breno Rodrigues dos Santos
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. Molecules 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 2700 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

  • drug design
  • virtual screening
  • molecular modeling
  • docking
  • molecular simulations
  • quantum chemistry

Published Papers (3 papers)

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Research

19 pages, 11467 KiB  
Article
Drug Repositioning via Graph Neural Networks: Identifying Novel JAK2 Inhibitors from FDA-Approved Drugs through Molecular Docking and Biological Validation
by Muhammad Yasir, Jinyoung Park, Eun-Taek Han, Won Sun Park, Jin-Hee Han and Wanjoo Chun
Molecules 2024, 29(6), 1363; https://doi.org/10.3390/molecules29061363 - 19 Mar 2024
Viewed by 983
Abstract
The increasing utilization of artificial intelligence algorithms in drug development has proven to be highly efficient and effective. One area where deep learning-based approaches have made significant contributions is in drug repositioning, enabling the identification of new therapeutic applications for existing drugs. In [...] Read more.
The increasing utilization of artificial intelligence algorithms in drug development has proven to be highly efficient and effective. One area where deep learning-based approaches have made significant contributions is in drug repositioning, enabling the identification of new therapeutic applications for existing drugs. In the present study, a trained deep-learning model was employed to screen a library of FDA-approved drugs to discover novel inhibitors targeting JAK2. To accomplish this, reference datasets containing active and decoy compounds specific to JAK2 were obtained from the DUD-E database. RDKit, a cheminformatic toolkit, was utilized to extract molecular features from the compounds. The DeepChem framework’s GraphConvMol, based on graph convolutional network models, was applied to build a predictive model using the DUD-E datasets. Subsequently, the trained deep-learning model was used to predict the JAK2 inhibitory potential of FDA-approved drugs. Based on these predictions, ribociclib, topiroxostat, amodiaquine, and gefitinib were identified as potential JAK2 inhibitors. Notably, several known JAK2 inhibitors demonstrated high potential according to the prediction results, validating the reliability of our prediction model. To further validate these findings and confirm their JAK2 inhibitory activity, molecular docking experiments were conducted using tofacitinib—an FDA-approved drug for JAK2 inhibition. Experimental validation successfully confirmed our computational analysis results by demonstrating that these novel drugs exhibited comparable inhibitory activity against JAK2 compared to tofacitinib. In conclusion, our study highlights how deep learning models can significantly enhance virtual screening efforts in drug discovery by efficiently identifying potential candidates for specific targets such as JAK2. These newly discovered drugs hold promises as novel JAK2 inhibitors deserving further exploration and investigation. Full article
(This article belongs to the Special Issue Application of Natural or Synthetic Products in Computer-Aided Drugs)
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16 pages, 3555 KiB  
Article
Multi-Target Effect of Aloeresin-A against Bacterial and Host Inflammatory Targets Benefits Contact Lens-Related Keratitis: A Multi-Omics and Quantum Chemical Investigation
by Jency Roshni, Sheikh F. Ahmad, Abubakar Wani and Shiek S. S. J. Ahmed
Molecules 2023, 28(19), 6955; https://doi.org/10.3390/molecules28196955 - 6 Oct 2023
Viewed by 1252
Abstract
Contact lens-mediated microbial keratitis caused by Pseudomonas aeruginosa and Streptococcus pneumoniae provokes corneal damage and vision loss. Recently, natural phytochemicals have become complementary medicines for corneal destruction. Herein, we aimed to identify multi-targeting Aloe vera-derived phytochemicals capable of inhibiting bacterial and host [...] Read more.
Contact lens-mediated microbial keratitis caused by Pseudomonas aeruginosa and Streptococcus pneumoniae provokes corneal damage and vision loss. Recently, natural phytochemicals have become complementary medicines for corneal destruction. Herein, we aimed to identify multi-targeting Aloe vera-derived phytochemicals capable of inhibiting bacterial and host targets of keratitis through ADME (absorption, distribution, metabolism, and excretion), docking, molecular dynamics (MD) simulation, MMGBSA (molecular mechanics generalized Born surface area) and density functional theory (DFT) investigations. An extensive literature search revealed ExoU, ExoS, ExoT, ExoY, and PLY as virulent bacterial targets. Simultaneously, differential gene expression (DGE) and pathway enrichment analysis-specified host transcription factor (SPI1) influences keratitis pathogenesis. Molecular docking analysis uncovered aloeresin-A as a promising inhibitor against bacterial and host targets, demonstrating strong binding energies ranging from −7.59 to −6.20 kcal/mol. Further, MMGBSA and MD simulation analysis reflect higher binding free energies and stable interactions of aloeresin-A with the targets. In addition, DFT studies reveal the chemical reactiveness of aloeresin-A through quantum chemical calculations. Hence, our findings show aloeresin-A to be a promising candidate for effectively inhibiting keratitis. However, additional research is imperative for potential integration into lens care solutions. Full article
(This article belongs to the Special Issue Application of Natural or Synthetic Products in Computer-Aided Drugs)
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20 pages, 3384 KiB  
Article
A Computational Approach Applied to the Study of Potential Allosteric Inhibitors Protease NS2B/NS3 from Dengue Virus
by Renato A. da Costa, João A. P. da Rocha, Alan S. Pinheiro, Andréia do S. S. da Costa, Elaine C. M. da Rocha, Rai. C. Silva, Arlan da S. Gonçalves, Cleydson B. R. Santos and Davi do S. B. Brasil
Molecules 2022, 27(13), 4118; https://doi.org/10.3390/molecules27134118 - 27 Jun 2022
Cited by 10 | Viewed by 2616
Abstract
Dengue virus (DENV) is a danger to more than 400 million people in the world, and there is no specific treatment. Thus, there is an urgent need to develop an effective method to combat this pathology. NS2B/NS3 protease is an important biological target [...] Read more.
Dengue virus (DENV) is a danger to more than 400 million people in the world, and there is no specific treatment. Thus, there is an urgent need to develop an effective method to combat this pathology. NS2B/NS3 protease is an important biological target due it being necessary for viral replication and the fact that it promotes the spread of the infection. Thus, this study aimed to design DENV NS2B/NS3pro allosteric inhibitors from a matrix compound. The search was conducted using the Swiss Similarity tool. The compounds were subjected to molecular docking calculations, molecular dynamics simulations (MD) and free energy calculations. The molecular docking results showed that two compounds, ZINC000001680989 and ZINC000001679427, were promising and performed important hydrogen interactions with the Asn152, Leu149 and Ala164 residues, showing the same interactions obtained in the literature. In the MD, the results indicated that five residues, Lys74, Leu76, Asn152, Leu149 and Ala166, contribute to the stability of the ligand at the allosteric site for all of the simulated systems. Hydrophobic, electrostatic and van der Waals interactions had significant effects on binding affinity. Physicochemical properties, lipophilicity, water solubility, pharmacokinetics, druglikeness and medicinal chemistry were evaluated for four compounds that were more promising, showed negative indices for the potential penetration of the Blood Brain Barrier and expressed high human intestinal absorption, indicating a low risk of central nervous system depression or drowsiness as the the side effects. The compound ZINC000006694490 exhibited an alert with a plausible level of toxicity for the purine base chemical moiety, indicating hepatotoxicity and chromosome damage in vivo in mouse, rat and human organisms. All of the compounds selected in this study showed a synthetic accessibility (SA) score lower than 4, suggesting the ease of new syntheses. The results corroborate with other studies in the literature, and the computational approach used here can contribute to the discovery of new and potent anti-dengue agents. Full article
(This article belongs to the Special Issue Application of Natural or Synthetic Products in Computer-Aided Drugs)
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