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Computational Modeling of Protein Targets & Therapeutic Molecules

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: 30 September 2025 | Viewed by 867

Special Issue Editor


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Guest Editor
Department of Medicine, Loyola University Medical Center, Loyola University Chicago, Maywood, IL 60153, USA
Interests: biophysics; bioengineering; chemistry; drug discovery; computer-aided drug design
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Special Issue Information

Dear Colleagues,

We invite submissions of original research, reviews, short communications, and perspectives for our Special Issue focusing on biophysics, medicinal chemistry, novel therapeutic agents, drug delivery systems, and computer-aided drug design (CADD). This issue aims to highlight the latest advancements in these fields, with particular emphasis on identifying new protein targets through homology modeling. We welcome studies that employ structural and functional analyses of biomolecules to uncover novel drug targets, leveraging computational approaches to predict protein structures, interactions, and functional sites. Additionally, we encourage research that integrates artificial intelligence (AI) and machine learning (ML) into homology modeling to enhance the accuracy and efficiency of protein target identification. By showcasing innovative methodologies and collaborative approaches, this issue aims to enhance the rational design and optimization of therapeutic agents, cutting-edge drug delivery systems, and structure-activity relationships. Our objective is to emphasize studies that connect foundational biophysical and computational insights with practical applications in drug discovery and development. We invite contributions from researchers in biophysics, computational biology, medicinal chemistry, pharmacology, and related disciplines to promote innovation and expedite the translation of scientific discoveries into therapeutic solutions. Manuscripts should be submitted through the online system per journal guidelines. We look forward to your pioneering contributions.

Dr. Whelton Miller
Guest Editor

Manuscript Submission Information

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Keywords

  • biophysics
  • chemistry
  • drug discovery
  • computer-aided drug design
  • protein target

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Published Papers (1 paper)

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Research

24 pages, 4074 KB  
Article
Computational and Experimental Insights into Tyrosinase and Antioxidant Activities of Resveratrol and Its Derivatives: Molecular Docking, Molecular Dynamics Simulation, DFT Calculation, and In Vitro Evaluation
by Ployvadee Sripadung, Chananya Rajchakom, Nadtanet Nunthaboot, Xinwei Jiang and Bunleu Sungthong
Int. J. Mol. Sci. 2025, 26(18), 8827; https://doi.org/10.3390/ijms26188827 - 10 Sep 2025
Viewed by 753
Abstract
Resveratrol, a natural stilbene found in various plants, is mainly known for its strong antioxidant activities exhibiting a comprehensive range of treatments for some skin disorders such as skin cancer, photoaging, dermatitis, and melanogenesis. However, few studies have been conducted on the differences [...] Read more.
Resveratrol, a natural stilbene found in various plants, is mainly known for its strong antioxidant activities exhibiting a comprehensive range of treatments for some skin disorders such as skin cancer, photoaging, dermatitis, and melanogenesis. However, few studies have been conducted on the differences in biological activities between resveratrol and its derivatives. Therefore, we aimed to investigate the effects of resveratrol (Re) and its derivatives acetyl-resveratrol (Are), cis-trismethoxy resveratrol (Cre), dihydroresveratrol (Dre), and oxyresveratrol (Ore) on antioxidant and anti-tyrosinase effects using in vitro and in silico methods. In the in vitro results, Ore showed the highest antioxidant activity among the resveratrol derivatives and displayed stronger inhibitory activity against natural tyrosinase compared with that of kojic acid. Density functional theory (DFT) was used to calculate quantum chemical descriptors to understand the compounds’ electronic and physicochemical properties. Molecular docking and molecular dynamics simulations were also performed to explore the corresponding binding mode and structural behavior, revealing that Ore exhibited the strongest binding interactions among resveratrol derivatives, primarily through hydrogen bonds and hydrophobic interactions with key amino acid residues. Moreover, all the resveratrol compounds demonstrated drug-likeness properties with predicted safe skin toxicity profiles. In conclusion, Ore exhibited the strongest tyrosinase inhibition and antioxidant activity among resveratrol derivatives in both in vitro and in silico assessments. Further research on the development of medicines, cosmetics, and food supplements of such compounds should be conducted. Full article
(This article belongs to the Special Issue Computational Modeling of Protein Targets & Therapeutic Molecules)
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