CoReGMC: Computational Resources for Genetically Modified Crops
Genetically Modified Crops

Anti-microbial Prediction Tools

This page provides a list of tools and databases for predicting antimicrobial peptides (AMPs). These tools help researchers analyze and identify AMPs for therapeutic and pharmaceutical applications.

Name Year Description PubMed ID
iAMP-2L 2013 A sequence-based tool for predicting AMPs using multilabel learning techniques. 23395824
amppred 2017 AMP prediction using physicochemical properties and machine learning techniques. 28205576
Daniel Veltri et al. 2018 Antimicrobial peptide prediction and classification based on sequence features. 29590297
ANFIS 2012 A fuzzy inference system for identifying antimicrobial peptides from sequences. 23193592
DBAASP 2014 A database of antimicrobial activity and structure of peptides. 24730612
AMPer 2007 A database providing predictions for antimicrobial peptides based on sequence data. 17341497
ClassAMP 2012 A classification tool for identifying antimicrobial and antiviral peptides. 22732690
CS-AMPPred 2012 A support vector machine-based predictor for antimicrobial peptides. 23240023
C-PAmP 2013 A computational database of plant antimicrobial peptides. 24244550
Jesus A. Beltran et al. 2017 A model based on advanced computational techniques for AMP prediction. Link
William Porto et al. 2015 Research focusing on the discovery and classification of antimicrobial peptides. Link
K C Chou et al. 2001 A foundational study for AMP prediction techniques. 11288174
Xin Yi Ng et al. 2015 Research focusing on AMP prediction methodologies. 25802839
IAMPE 2020 A web server for AMP prediction using advanced sequence-based techniques. 32946226
AMAP 2019 A machine learning tool for AMP classification and prediction. 30831306
Ping Wang et al. 2011 An AMP database for experimental and predicted antimicrobial peptides. 21533231
AmPEP 2018 Prediction tool using sequence-derived descriptors for AMP identification. 29374199
amPEPpy 1.0 2021 A Python-based AMP prediction tool utilizing neural networks. 33135060
Chia-Ru Chung et al. 2020 Research on AMP functional characterization and prediction. 32024233
AMPfun 2019 A web server for analyzing AMP functional activities. 31155657
APIN 2019 Prediction of AMPs using innovative neural network architectures. 31870282
Guangshun Wang et al. 2022 Comprehensive research on AMP sequences and functionalities. 35298806
Guangshun Wang et al. 2022 Comprehensive research on AMP sequences and functionalities. 35298806
AmpGram 2020 Machine learning-based AMP classification tool using natural language processing. 32560350
Ensemble-AMPPred 2021 Robust AMP prediction and recognition using ensemble learning with a new hybrid feature. 33494403
deepAMPNet 2024 A novel antimicrobial peptide predictor employing AlphaFold2 predicted structures and a bi-directional long short-term memory protein language model. 39040937
sAMPpred-GAT 2023 Prediction of antimicrobial peptides by graph attention network and predicted peptide structure. 36342186
Quang H Nguyen et al. 2024 An efficient hybrid deep learning architecture for predicting short antimicrobial peptides. 38837544
iAMPCN 2023 A deep-learning approach for identifying antimicrobial peptides and their functional activities. 37369638
AGRAMP 2024 Machine learning models for predicting antimicrobial peptides against phytopathogenic bacteria. 38516021
Target-AMP 2022 Computational prediction of antimicrobial peptides by coupling sequential information with evolutionary profiles. 36410097
PTPAMP 2023 Prediction tool for plant-derived antimicrobial peptides. 35864258
AmpClass 2024 An Antimicrobial Peptide Predictor Based on Supervised Machine Learning. 39383429
pLM4MRSA 2025 Advancing the Accuracy of Anti-MRSA Peptide Prediction Through Integrating Multi-Source Protein Language Models. 40067411
StAMPs 2025 Deep-Learning-Based Approaches for Rational Design of Stapled Peptides With High Antimicrobial Activity and Stability. 40042163
iAMP-CRA 2025 Identifying Antimicrobial Peptides Using Convolutional Recurrent Neural Network with Self-Attention. 40062190
AMP-Designer 2025 Discovery of antimicrobial peptides with notable antibacterial potency by an LLM-based foundation model. 40043127
Małgorzata Lobka et al. 2025 Design, synthesis and evaluation of lysine- and leucine-rich hydrocarbon-stapled peptides as antibacterial agents. 40101449
MSCMamba 2025 Prediction of Antimicrobial Peptide Activity Values by Fusing Multiscale Convolution with Mamba Module. 39915928
deep-AMPpred 2025 A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities. 39792442
iAMP-bert 2024 Comprehensive Assessment of BERT-Based Methods for Predicting Antimicrobial Peptides. 39316765
esm-AxP-GDL 2024 Predicting Antimicrobial Peptides Using ESMFold-Predicted Structures and ESM-2-Based Amino Acid Features with Graph Deep Learning. 38739853

Antibacterial Protein and Peptide Prediction Tools

Below is a curated list of tools and research articles focused on the prediction of antibacterial proteins and peptides. These tools leverage advanced computational methods to identify peptides with antibacterial properties for therapeutic applications.

Name Year Description PubMed ID
AntiBP2 2010 Improved version of a tool for predicting antibacterial peptides. 20122190
Bert-Protein 2021 Novel algorithm for recognizing antibacterial peptides using the BERT language model. 34037687
EnAMP 2024 Deep learning ensemble algorithm for antibacterial peptide recognition using multiple features. 38406833
Xiaofang Xu et al. 2023 Recognizes antibacterial peptides by combining BERT and Text-CNN models. 37154341
Deep-ABPpred 2021 Identifies antibacterial peptides in protein sequences using biLSTM with word2vec. 33784381
StaBle-ABPpred 2022 Stacked ensemble predictor using biLSTM and attention mechanism for discovering antibacterial peptides. 34750606
AMPActiPred 2024 Three-stage framework for predicting antibacterial peptides and their activity levels using deep forest. 38723168
PGAT-ABPp 2024 Uses protein language models and graph attention networks for highly accurate antibacterial peptide identification. 39120878
AntiBP3 2024 Predicts antibacterial peptides against Gram-positive, Gram-negative, and variable bacteria. 38391554
EnAMP 2024 Ensemble-based antibacterial peptide recognition using deep learning and multi-feature analysis. 38406833

Antifungal Protein and Peptide Prediction Tools

Below is a curated list of tools and research articles focused on the prediction of antifungal proteins and peptides. These resources are vital for understanding and identifying peptides with antifungal properties for therapeutic applications.

Name Year Description PubMed ID
Antifp 2018 In Silico Approach for Prediction of Antifungal Peptides. 29535692
MLAFP-XN 2024 Neural network-based tool for identifying antifungal peptides. 39323787
iAFPs-EnC-GA 2022 Identifies antifungal peptides using sequential and evolutionary descriptors with multi-information fusion and ensemble learning. Link
M. Mousavizadegan et al. 2018 Uses Chou's PseAAC and support vector machines for computational prediction of antifungal peptides. 30105927
DeepAFP 2023 Deep learning-based computational framework for identifying antifungal peptides. 37595093
PhytoAFP 2021 In silico approach for designing plant-derived antifungal peptides. 34356736
AFP-MFL 2023 Accurate antifungal peptide prediction using multi-view feature learning techniques. 36631407
iAFPs-Mv-BiTCN 2024 Predicts antifungal peptides using transformer embedding and multi-view features with bidirectional temporal convolutional networks. 38552379
Deep-AFPpred 2022 Identifies novel antifungal peptides using pretrained embeddings from seq2vec with 1DCNN-BiLSTM architecture. 34670278
Cycle-ESM 2024 Generates and classifies antifungal peptides using the ESM protein language model. 39437594