Bioactivity of Marine-Derived Peptides and Proteins: A Review
Bibliographic record
Abstract
The marine environment, covering over 70% of the Earth's surface, serves as a reservoir of bioactive molecules, including peptides and proteins. Due to the unique and often extreme marine conditions, these molecules exhibit distinctive structural features and diverse functional properties, making them promising candidates for therapeutic applications. Marine-derived bioactive peptides, typically consisting of 3 to 40 amino acid residues-though most commonly, 2 to 20-are obtained from parent proteins through chemical or enzymatic hydrolysis, microbial fermentation, or gastrointestinal digestion. Like peptides, protein hydrolysates from collagen, a dominant protein of such materials, play an important role. Peptide bioactivities include antioxidant, antihypertensive, antidiabetic, antimicrobial, anti-inflammatory, anticoagulant, and anti-cancer effects as well as immunoregulatory and wound-healing activities. These peptides exert their effects through mechanisms such as enzyme inhibition, receptor modulation, and free radical scavenging, among others. Fish, algae, mollusks, crustaceans, microbes, invertebrates, and marine by-products such as skin, bones, and viscera are some of the key marine sources of bioactive proteins and peptides. The advancements in the extraction and purification processes, e.g., enzymatic hydrolysis, ultrafiltration, ion-exchange chromatography, high-performance liquid chromatography (HPLC), and molecular docking, facilitate easy identification and purification of such bioactive peptides in greater purity and activity. Despite their colossal potential, their production, scale-up, stability, and bioavailability are yet to be enhanced for industrial applications. Additional work needs to be carried out for optimal extraction processes, to unravel the mechanisms of action, and to discover novel marine sources. This review emphasizes the enormous scope of marine-derived peptides and proteins in the pharmaceutical, nutraceutical, cosmeceutical, and functional food industries, emphasizing their role in health promotion and risk reduction of chronic diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".