ReviewMarine drugs2018
Computational Methodologies in the Exploration of Marine Natural Product Leads.
Review in Marine drugs, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Pooled it
- Colombian Contributions Fighting Leishmaniasis: A Systematic Review on Antileishmanials Combined with Chemoinformatics Analysis.Molecules (Basel, Switzerland) · 2020Pooled it
- A Systematic Review of Recently Reported Marine Derived Natural Product Kinase Inhibitors.Marine drugs · 2019Pooled it
- Structure-guided discovery of novel ERα-binding peptides with in vitro antiproliferative activity.Journal of enzyme inhibition and medicinal chemistry · 2026Article
- Sustainable Biocatalytic Cascades: A Versatile Tool in the Synthesis of Natural Products With Therapeutic Potential.Chembiochem : a European journal of chemical biology · 2026Review
- Effect of Algal Lectin Siye on Proliferation and Apoptosis of Breast and Colon Cancer Cells.Marine drugs · 2026Article
- Nature meets machine: the AI renaissance in natural product drug discovery.Natural products and bioprospecting · 2026Review
- Reviewing Marine Bioactive Compounds From the Red Sea: Advancing Therapeutic Applications While Navigating Translational and Conservation Challenges.Chemistry & biodiversity · 2026Review
- Geraniin Alleviates High-Fat Diet-Induced Atherosclerosis inFood science & nutrition · 2025Article
- Article
- Artificial Intelligence in Natural Product Drug Discovery: Current Applications and Future Perspectives.Journal of medicinal chemistry · 2025Review
- Advanced Technologies for Large Scale Supply of Marine Drugs.Marine drugs · 2025Review
- Article
- Technology Readiness Level Roadmap for Developing Innovative Herbal Medicinal Products.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Marine Drug Discovery through Computer-Aided Approaches.Marine drugs · 2023Article
- Review
- Unveiling the Efficacy of Sesquiterpenes from Marine SpongeMolecules (Basel, Switzerland) · 2023Article
- Asperopiperazines A and B: Antimicrobial and Cytotoxic Dipeptides from a Tunicate-Derived FungusMarine drugs · 2022Article
- Discovery of Anti-MRSA Secondary Metabolites from a Marine-Derived FungusMarine drugs · 2022Article
- Recent Achievements in Total Synthesis for Integral Structural Revisions of Marine Natural Products.Marine drugs · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computational methodologies are assisting the exploration of marine natural products (MNPs) to make the discovery of new leads more efficient, to repurpose known MNPs, to target new metabolites on the basis of genome analysis, to reveal mechanisms of action, and to optimize leads. In silico efforts in drug discovery of NPs have mainly focused on two tasks: dereplication and prediction of bioactivities. The exploration of new chemical spaces and the application of predicted spectral data must be included in new approaches to select species, extracts, and growth conditions with maximum probabilities of medicinal chemistry novelty. In this review, the most relevant current computational dereplication methodologies are highlighted. Structure-based (SB) and ligand-based (LB) chemoinformatics approaches have become essential tools for the virtual screening of NPs either in small datasets of isolated compounds or in large-scale databases. The most common LB techniques include Quantitative Structure⁻Activity Relationships (QSAR), estimation of drug likeness, prediction of adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, similarity searching, and pharmacophore identification. Analogously, molecular dynamics, docking and binding cavity analysis have been used in SB approaches. Their significance and achievements are the main focus of this review.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.