Clusters
Propedia is a database geared toward machine learning applications. Therefore, it presents data grouped using different clustering methods.
This category clusters all peptides with a 100% identical sequence.
| Leader | Identical peptide sequences |
|---|
This category groups together all complexes formed with protein-peptide pairs where both sequences are 100% identical.
| Leader | n | Redundant sequences (+leader) |
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This category groups entries based on the classes assigned in the PDB files.
| Class | n | Structures |
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Category inherited from Propedia v1. Check category seq100 to see how Propedia26 clusters its new entries.
| Cluster | n | Structures |
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Category inherited from Propedia v1.
| Cluster | n | Structures |
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Category inherited from Propedia v1.
| Cluster | n | Structures |
|---|
CSM-peptides is a machine learning-based prediction server for functional classification of biologically active peptides based on sequence. We built machine learning models based on the work of Rodrigues et al. (2022) to classify Propedia26 peptides into six categories: Anti-Angiogenic (AAP), Anti-Bacterial (ABP), Anti-Cancer (ACP), Anti-Inflammatory (AIP), Quorum Sensing (QSP), and Surface Binding (SBP).
Function: They inhibit angiogenesis, that is, the formation of new blood vessels. Importance: Blocking angiogenesis is a strategy used to prevent tumor growth, since cancer depends on blood supply to obtain nutrients. Example of use: Development of antitumor and antiviral therapies.
| ID | Class | Negative (Probability) | Positive (Probability) |
|---|
Function: They are antimicrobial peptides that destroy or inhibit the growth of bacteria. Common mechanism: They interact with bacterial membranes, leading to cell lysis (rupture). Importance: They are promising alternatives to traditional antibiotics, especially in the face of bacterial resistance.
| ID | Class | Negative (Probability) | Positive (Probability) |
|---|
Function: They induce selective death of tumor cells without significantly affecting normal cells. Mechanism: They can act by altering the permeability of cancer cell membranes, activating apoptosis, or modulating signaling pathways. Application: Development of next-generation antineoplastic therapies.
| ID | Class | Negative (Probability) | Positive (Probability) |
|---|
Function: They reduce or regulate exaggerated inflammatory responses. Mechanism: They can inhibit pro-inflammatory cytokines (such as TNF-α, IL-6) or modulate macrophage activity. Application: Treatment of chronic inflammatory and autoimmune diseases.
| ID | Class | Negative (Probability) | Positive (Probability) |
|---|
Function: They participate in bacterial communication (quorum sensing), regulating collective behaviors such as biofilm formation and virulence. Importance: Understanding and manipulating these peptides can lead to strategies to control bacterial infections without necessarily killing the bacteria (reducing selective pressure for resistance).
| ID | Class | Negative (Probability) | Positive (Probability) |
|---|
Function: They bind to biological surfaces or materials, such as metals, polymers, or minerals. Biotechnological use: They can be used to immobilize enzymes, design biomaterials, biosensors, or nanodevices. Example: Peptides that bind strongly to gold, silica, or metal oxides for use in nanotechnology.
| ID | Class | Negative (Probability) | Positive (Probability) |
|---|
