Table 3.
Online AMPs prediction tools
| Acronym | Features | Method | Validation Method | Years | URL |
|---|---|---|---|---|---|
| Ensemble-AMPPred | 517 features and a hybrid feature Amino acid composition, pseudo amino acid composition (PseAAC) in parallel and series correlation, and the details of the secondary structure conformation, composition–transition–distribution (CTD), various physical-chemical properties, antimicrobial propensity scale, and the percentage of different conformations in the peptide sequence. |
Ensemble learning method | 10-fold CV, Independent test | 2021 | http://ncrna-pred.com/Hybrid_AMPPred.htm |
| DBAASP | Physicochemical characteristics of peptides: normalized hydrophobic moment, normalized hydrophobicity, net charge, isoelectric point, penetration depth, tilt angle, disordered conformation propensity, linear moment, and propensity for in vitro aggregation | Cutoff discriminator | 5-fold CV, Independent test | 2021 | http://dbaasp.org/home |
| Deep-AmPEP30 | AMPs in sequences Pseudo K-tuple RAAC |
Deep Learning | 10-fold CV, Independent test | 2020 | http://cbbio.online/AxPEP/ |
| AntiCP | ACPs in sequences Amino acid composition, dipeptide composition, terminus composition, binary profile, and hybrid features |
Support Vector Machine | 5-fold CV, Independent dataset | 2020 | https://webs.iiitd.edu.in/raghava/anticp2/ |
| AmpGram | AMPs in sequences | Random Forest | 5-fold CV, Independent dataset | 2020 | http://biongram.biotech.uni.wroc.pl/AmpGram/ |
| AMPScanner | Numerical matrix from deep neural network (DNN) | Deep Learning | 10-fold CV, Independent dataset | 2018 | https://www.dveltri.com/ascan/ |
| AntiMPmod | AMPs in structures | Support Vector Machine | 5-fold CV Independent dataset | 2018 | https://webs.iiitd.edu.in/raghava/antimpmod/ |
| PscAAC | AFPs in sequences and structures | Support Vector Machine | 10-fold CV, Independent dataset | 2018 | http://www.csbio.sjtu.edu.cn/bioinf/PseAAC/ |
| MLAMP | PseAAC with the gray model (GM) | ML-SMOTE | Independent dataset | 2016 | http://www.jci-bioinfo.cn/MLAMP |
| CAMPR3 | Sequence composition, physicochemical properties, and structural characteristics of amino acids | Support Vector Machine, Random Forests, and | 10-fold CV, Independent dataset | 2016 | http://www.camp.bicnirrh.res.in/prediction.php |
| CPPpred | cell-penetrating peptides in sequences | N-to-1 neural networks | 5-fold CV, Independent dataset | 2013 | http://bioware.ucd.ie/∼compass/biowareweb/Server_pages/cpppred.php |
| iAMP-2 L | Pseudo amino acid composition (PseAAC) incorporating five physicochemical properties | fuzzy K-nearest neighbor | Independent dataset | 2013 | http://www.jci-bioinfo.cn/iAMP-2L |
| PeptideLocator | Bioactive peptides in sequences | Bidirectional Recursive Neural Networks | 5-fold CV, Independent dataset | 2013 | http://bioware.ucd.ie/∼compass/biowareweb/ |
| BAGEL3 | Bacteriocins in DNA sequences | BLAST ORFs prediction tools |
—- | 2013 | http://bagel.molgenrug.nl/ |
| CS-AMPPred | cysteine-stabilized AMPs in sequences | Support Vector Machine | 5-fold CV | 2012 | http://sourceforge.net/projects/csamppred/ |
| AMPA | Antimicrobial index based on IC50 value | Antimicrobial propensity scale threshold | —— | 2011 | http://tcoffee.crg.cat/apps/ampa/guide.html |