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Marine Drugs
Special Issues
Chemoinformatics for Marine Drug Discovery
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Chemoinformatics for Marine Drug Discovery

A special issue of Marine Drugs (ISSN 1660-3397). This special issue belongs to the section "Marine Pharmacology".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 5010

Special Issue Editor

Dr. Florbela Pereira

E-Mail Website
Guest Editor
LAQV, Chemistry Department, NOVA Faculty of Sciences and Technology, NOVA University of Lisbon, 2819-516 Lisbon, Portugal
Interests: chemoinformatics; machine learning and data mining tecniques; quantitative structure–activity relationship (QSAR); quantitative structure–property relationship (QSPR); big data; DFT-calculated properties; marine natural products (MNPs); virtual screening; nuclear magnetic resonance (NMR); dereplication; drug discovery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the ever-evolving landscape of pharmaceutical sciences, the integration of cutting-edge technologies and natural resources has become fundamental to groundbreaking advancements, particularly in the areas of dereplication and the prediction of bioactivities. Among these innovations, chemoinformatics and marine natural products (MNPs) stand out as pivotal elements driving the future of drug discovery.

Structure-based (SB) and ligand-based (LB) chemoinformatics approaches have become essential tools for the virtual screening of MNPs, whether in small datasets of isolated compounds or in large-scale databases. This Special Issue focuses on a comprehensive analysis of available MNP databases, the biological and chemical space defined by known MNPs, and the most common LB techniques (e.g., quantitative structure–activity relationships (QSARs), estimation of drug likeness, similarity searching, pharmacophore identification), alongside SB techniques (e.g., molecular dynamics, docking, binding cavity) in the virtual screening of MNPs.

Scientists working in this field are invited to submit their original research or review articles for publication in this Special Issue.

Dr. Florbela Pereira
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. Marine Drugs 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

  • chemoinformatics
  • dereplication
  • machine learning techniques
  • mnps databases
  • chemical space
  • quantitative structure–activity relationship (QSAR)
  • molecular docking
  • computer–aided design design (CADD)
  • computer–assisted structure elucidation (CASE)
  • drug discovery

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Published Papers (4 papers)

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Research

18 pages, 3138 KiB  
Article
Aspergillusidone G Exerts Anti-Neuroinflammatory Effects via Inhibiting MMP9 Through Integrated Bioinformatics and Experimental Analysis: Implications for Parkinson’s Disease Intervention
by Fangfang Ban, Longjian Zhou, Zhiyou Yang, Yayue Liu and Yi Zhang
Mar. Drugs 2025, 23(5), 181; https://doi.org/10.3390/md23050181 - 23 Apr 2025
Viewed by 329
Abstract
Natural products have extensive attractiveness as therapeutic agents due to their low toxicity and high efficiency. Our previous study has identified a depside-type Aspergillusidone G (Asp G) derived from Aspergillus unguis DLEP2008001, which shows excellent neuroprotective activity for 1-methyl-4-phenylpyridinium (MPP+)-induced primary [...] Read more.
Natural products have extensive attractiveness as therapeutic agents due to their low toxicity and high efficiency. Our previous study has identified a depside-type Aspergillusidone G (Asp G) derived from Aspergillus unguis DLEP2008001, which shows excellent neuroprotective activity for 1-methyl-4-phenylpyridinium (MPP+)-induced primary cortical neurons and anti-neuroinflammatory property, promising to be a potential therapeutic agent for Parkinson’s disease (PD). To further explore the anti-PD potential and mechanisms of Asp G, we employed network pharmacology, cellular experiments, and various biological techniques for analysis and validation. The analysis of network pharmacology suggested that Asp G’s anti-PD potential might be attributed to its modulation of inflammation. The data from nitric oxide (NO) detection, qRT-PCR, and Western blot confirmed that Asp G dose-dependently inhibited lipopolysaccharide (LPS)-stimulated NO production, with 40 μM Asp G suppressing 90.54% of the NO burst compared to the LPS group, and suppressed the overproduction of inflammatory-related factors in LPS-induced BV2 cells. Further protein–protein interaction analysis indicated that matrix metalloproteinase 9 (MMP9), a promising target for PD intervention, was the most likely anti-PD target of Asp G, and the results of gelatin zymography, qRT-PCR, and Western blot validated that Asp G could inhibit the active and inactive forms of MMP9 directly and indirectly, respectively. Notably, the inhibition of 67 kDa-MMP9 by Asp G is expected to compensate for the inability of TIMP-1 to inhibit this form. Furthermore, a selective inhibitor of MMP9 (20 μM SB-3CT) further potentiated the anti-inflammatory effects of Asp G (20 μM), with inhibition rate on NO increasing from 27.57% to 63.50% compared to LPS group. In summary, our study revealed that Asp G exerts anti-neuroinflammatory effects by inhibiting MMP9, which provides a valuable lead compound for the development of anti-neuroinflammatory drugs and offers insights into the intervention of PD-associated neuroinflammation. Future studies will further investigate the upstream regulatory mechanisms of Asp G-mediated MMP9 inhibition and its effects in in vivo PD models. Full article
(This article belongs to the Special Issue Chemoinformatics for Marine Drug Discovery)
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21 pages, 10431 KiB  
Article
Large-Scale AI-Based Structure and Activity Prediction Analysis of ShK Domain Peptides from Sea Anemones in the South China Sea
by Ziqiang Hua, Limin Lin, Wanting Yang, Linlin Ma, Meiling Huang and Bingmiao Gao
Mar. Drugs 2025, 23(2), 85; https://doi.org/10.3390/md23020085 - 16 Feb 2025
Viewed by 714
Abstract
Sea anemone peptides represent a valuable class of biomolecules in the marine toxin library due to their various structures and functions. Among these, ShK domain peptides are particularly notable for their selective inhibition of the Kv1.3 channel, holding great potential for applications in [...] Read more.
Sea anemone peptides represent a valuable class of biomolecules in the marine toxin library due to their various structures and functions. Among these, ShK domain peptides are particularly notable for their selective inhibition of the Kv1.3 channel, holding great potential for applications in immune regulation and the treatment of metabolic disorders. However, these peptides’ structural complexity and diversity have posed challenges for functional prediction. In this study, we compared 36 ShK domain peptides from four species of sea anemone in the South China Sea and explored their binding ability with Kv1.3 channels by combining molecular docking and dynamics simulation studies. Our findings highlight that variations in loop length, residue composition, and charge distribution among ShK domain peptides affect their binding stability and specificity. This work presents an efficient strategy for large-scale peptide structure prediction and activity screening, providing a valuable foundation for future pharmacological research. Full article
(This article belongs to the Special Issue Chemoinformatics for Marine Drug Discovery)
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21 pages, 8475 KiB  
Article
Identification of Novel LCN2 Inhibitors Based on Construction of Pharmacophore Models and Screening of Marine Compound Libraries by Fragment Design
by Ningying Zheng, Xuan Li, Nan Zhou and Lianxiang Luo
Mar. Drugs 2025, 23(1), 24; https://doi.org/10.3390/md23010024 - 5 Jan 2025
Viewed by 1103
Abstract
LCN2, a member of the lipocalin family, is associated with various tumors and inflammatory conditions. Despite the availability of known inhibitors, none have been approved for clinical use. In this study, marine compounds were screened for their ability to inhibit LCN2 using pharmacophore [...] Read more.
LCN2, a member of the lipocalin family, is associated with various tumors and inflammatory conditions. Despite the availability of known inhibitors, none have been approved for clinical use. In this study, marine compounds were screened for their ability to inhibit LCN2 using pharmacophore models. Six compounds were optimized for protein binding after being docked against the positive control Compound A. Two compounds showed promising results in ADMET screening. Molecular dynamics simulations were utilized to predict binding mechanisms, with Compound 69081_50 identified as a potential LCN2 inhibitor. MM-PBSA analysis revealed key amino acid residues that are involved in interactions, suggesting that Compound 69081_50 could be a candidate for drug development. Full article
(This article belongs to the Special Issue Chemoinformatics for Marine Drug Discovery)
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18 pages, 3504 KiB  
Article
The Discovery and Characterization of a Potent DPP-IV Inhibitory Peptide from Oysters for the Treatment of Type 2 Diabetes Based on Computational and Experimental Studies
by Zhongqin Chen, Xiaojie Su, Wenhong Cao, Mingtang Tan, Guoping Zhu, Jialong Gao and Longjian Zhou
Mar. Drugs 2024, 22(8), 361; https://doi.org/10.3390/md22080361 - 9 Aug 2024
Cited by 6 | Viewed by 2117
Abstract
The inhibition of dipeptidyl peptidase-IV (DPP-IV) is a promising approach for regulating the blood glucose levels in patients with type 2 diabetes (T2D). Oysters, rich in functional peptides, contain peptides capable of inhibiting DPP-IV activity. This study aims to identify the hypoglycemic peptides [...] Read more.
The inhibition of dipeptidyl peptidase-IV (DPP-IV) is a promising approach for regulating the blood glucose levels in patients with type 2 diabetes (T2D). Oysters, rich in functional peptides, contain peptides capable of inhibiting DPP-IV activity. This study aims to identify the hypoglycemic peptides from oysters and investigate their potential anti-T2D targets and mechanisms. This research utilized virtual screening for the peptide selection, followed by in vitro DPP-IV activity assays to validate the chosen peptide. Network pharmacology was employed to identify the potential targets, GO terms, and KEGG pathways. Molecular docking and molecular dynamics simulations were used to provide virtual confirmation. The virtual screening identified LRGFGNPPT as the most promising peptide among the screened oyster peptides. The in vitro studies confirmed its inhibitory effect on DPP-IV activity. Network pharmacology revealed that LRGFGNPPT exerts an anti-T2D effect through multiple targets and signaling pathways. The key hub targets are AKT1, ACE, and REN. Additionally, the molecular docking results showed that LRGFGNPPT exhibited a strong binding affinity with targets like AKT1, ACE, and REN, which was further confirmed by the molecular dynamics simulations showcasing a stable peptide–target interaction. This study highlights the potential of LRGFGNPPT as a natural anti-T2D peptide, providing valuable insights for potential future pharmaceutical or dietary interventions in T2D management. Full article
(This article belongs to the Special Issue Chemoinformatics for Marine Drug Discovery)
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