Property Prediction Tools
AMPlify
Date: 25-Jan-22
Target: AMPs
Paper: AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1186/s13104-023-06279-1
Code/Server: https://github.com/bcgsc/AMPlify
TPpred-ATMV
Date: 7-Apr-22
Target: AMPs
Paper: TPpred-ATMV: therapeutic peptide prediction by adaptive multi-view tensor learning model
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1093/bioinformatics/btac200
Code/Server: https://github.com/cokeyk/TPpred-ATMV
KreinAMP
Date: 27-Feb-23
Target: AMPs
Paper: Krein support vector machine classification of antimicrobial peptides
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1039/D3DD00004D
Code/Server: https://github.com/Mrjoeybux/KreinAMP
TriNet
Date: 10-Mar-23
Target: AMPs
Paper: TriNet: A tri-fusion neural network for the prediction of anticancer and antimicrobial peptides
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1016/j.patter.2023.100702
Code/Server: https://github.com/wanyunzh/TriNet
HydrAMP
Date: 15-Mar-23
Target: AMPs
Paper: Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1038/s41467-023-36994-z
Code/Server: https://github.com/szczurek-lab/hydramp
AMPFinder
Date: 24-May-23
Target: AMPs
Paper: AMPFinder: A computational model to identify antimicrobial peptides and their functions based on sequence-derived information
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1016/j.ab.2023.115196
Code/Server: https://github.com/abcair/AMPFinder
AMPpred-MFA
Date: 6-Oct-23
Target: AMPs
Paper: AMPpred-MFA: An Interpretable Antimicrobial Peptide Predictor with a Stacking Architecture, Multiple Features, and Multihead Attention
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1021/acs.jcim.3c01017
Code/Server: https://github.com/Jiangle525/AMPpred-MFA
iAMP-DL
Date: 4-Jun-24
Target: AMPs
Paper: An efficient hybrid deep learning architecture for predicting short antimicrobial peptides
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1002/pmic.202300382
Code/Server: https://github.com/mldlproject/2022-iAMP-DL
AMP-RNNpro
Date: 5-Jun-24
Target: AMPs
Paper: AMP-RNNpro: a two-stage approach for identification of antimicrobials using probabilistic features
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1038/s41598-024-63461-6
Code/Server: https://github.com/Shazzad-Shaon3404/Antimicrobials_
tAMPer
Date: 22-Jun-24
Target: AMPs
Paper: Structure-aware deep learning model for peptide toxicity prediction
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1002/pro.5076
Code/Server: https://github.com/bcgsc/tAMPer
TP-LMMSG
Date: 26-Jun-24
Target: AMPs
Paper: TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1093/bib/bbae308
Code/Server: https://github.com/NanjunChen37/TP_LMMSG
AMP
Date: 7-Jul-24
Target: AMPs
Paper: Ensemble Machine Learning and Predicted Properties Promote Antimicrobial Peptide Identification
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1007/s12539-024-00640-z
Code/Server: https://github.com/researchprotein/amp
TriStack
Date: 17-Jul-24
Target: AMPs
Paper: TriStack enables accurate identification of antimicrobial and anti-inflammatory peptides by combining machine learning and deep learning approaches
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1016/j.future.2024.07.024
Code/Server: https://github.com/hjy23/TriStack
deepAMPNet
Date: 19-Jul-24
Target: AMPs
Paper: deepAMPNet: a novel antimicrobial peptide predictor employing AlphaFold2 predicted structures and a bi-directional long short-term memory protein language model
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.7717/peerj.17729
Code/Server: https://github.com/Iseeu233/deepAMPNet
DMAMP
Date: 6-Aug-24
Target: AMPs
Paper: DMAMP: A Deep-Learning Model for Detecting Antimicrobial Peptides and Their Multi-Activities
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1109/TCBB.2024.3439541
Code/Server: https://github.com/guofei-tju/DMAMP
PepNet
Date: 28-Sep-24
Target: AMPs
Paper: PepNet: an interpretable neural network for anti-inflammatory and antimicrobial peptides prediction using a pre-trained protein language model
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1038/s42003-024-06911-1
Code/Server: https://zenodo.org/records/13734258
PepMNet
Date: 11-Dec-24
Target: AMPs
Paper: PepMNet: a hybrid deep learning model for predicting peptide properties using hierarchical graph representations
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1039/D4ME00172A
Code/Server: https://github.com/danielgarzonotero/PepMNet
deep-AMPpred
Date: 10-Jan-25
Target: AMPs
Paper: deep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities
Task: Peptide antimicrobial activity prediction
DOI: https://pubs.acs.org/doi/10.1021/acs.jcim.4c01913
Code/Server: https://github.com/JunZhao-hash/deep-AMPpred
UniAMP
Date: 11-Jan-25
Target: AMPs
Paper: UniAMP: enhancing AMP prediction using deep neural networks with inferred information of peptides
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1186/s12859-025-06033-3
Code/Server: https://github.com/quietbamboo/UniAMP
EvoGradient
Date: 17-Jan-25
Target: AMPs
Paper: Explainable deep learning and virtual evolution identifies antimicrobial peptides with activity against multidrug-resistant human pathogens
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1038/s41564-024-01907-3
Code/Server: https://github.com/MicroResearchLab/AMP-potency-prediction-EvoGradient
PLAPD
Date: 4-Mar-25
Target: AMPs
Paper: Leveraging protein language models for robust antimicrobial peptide detection
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1016/j.ymeth.2025.03.002
Code/Server: https://github.com/lichaozhang2/PLAPD
AMP-Designer
Date: 5-Mar-25
Target: AMPs
Paper: Discovery of antimicrobial peptides with notable antibacterial potency by an LLM- based foundation model
Task: Peptide antimicrobial activity prediction
DOI: https://doi.org/10.1126/sciadv.ads8932
Code/Server: https://github.com/jkwang93/AMP-Designer
TCN-AFPpred
Date: 11-Feb-22
Target: Antifungal peptides
Paper: Accelerating the discovery of antifungal peptides using deep temporal convolutional networks
Task: Antifungal peptides activity prediction
DOI: https://doi.org/10.1093/bib/bbac008
Code/Server: https://tcn-afppred.anvil.app/
MoLFormer
Date: 21-Dec-22
Target: LBVS
Paper: Large-scale chemical language representations capture molecular structure and properties
Task: A pretrained-on-SMILES transformer that can be finetuned for downstream molecular property prediction
DOI: https://doi.org/10.48550/arXiv.2106.09553
Code/Server: https://github.com/IBM/molformer
pLM4CPPs
Date: 29-Jan-25
Target: Peptides
Paper: pLM4CPPs: Protein Language Model-Based Predictor for Cell Penetrating Peptides
Task: cell penetration prediction
DOI: https://doi.org/10.1021/acs.jcim.4c01338
Code/Server: https://github.com/drkumarnandan/pLM4CPPs
GEMS
Date: 1-Dec-24
Target: Protein-small molecules
Paper: GEMS: A Generalizable GNN Framework For Protein-Ligand Binding Affinity Prediction Through Robust Data Filtering and Language Model Integration
Task: Affinity prediction
DOI: https://doi.org/10.1101/2024.12.09.627482
Code/Server: https://github.com/camlab-ethz/GEMS
MHAN-DTA
Date: 16-Dec-24
Target: Protein-small molecules
Paper: MHAN-DTA: A Multiscale Hybrid Attention Network for Drug-Target Affinity Prediction
Task: Affinity prediction
DOI: https://doi.org/10.1109/JBHI.2024.3518619
Code/Server: https://github.com/anxiangbiye1231/MHAN-DTA
BlendNet
Date: 13-Jan-25
Target: Protein-small molecules
Paper: Exploring the potential of compound?protein complex structure-free models in virtual screening using BlendNet
Task: Affinity prediction
DOI: https://doi.org/10.1093/bib/bbae712
Code/Server: https://github.com/Blue1993/BlendNet
MMPD-DTA
Date: 20-Jan-25
Target: Protein-small molecules
Paper: MMPD-DTA: Integrating Multi-Modal Deep Learning with Pocket-Drug Graphs for Drug-Target Binding Affinity Prediction
Task: Affinity prediction
DOI: https://doi.org/10.1021/acs.jcim.4c01528
Code/Server: https://github.com/zhc-moushang/MMPD-DTA
MutualDTA
Date: 29-Jan-25
Target: Protein-small molecules
Paper: MutualDTA: An Interpretable Drug?Target Affinity Prediction Model Leveraging Pretrained Models and Mutual Attention
Task: Affinity prediction
DOI: https://doi.org/10.1021/acs.jcim.4c01893
Code/Server: https://github.com/yydhYYDH/MutualDTA
Chemprop
Date: 30-Jul-19
Target: Small molecule
Paper: Analyzing Learned Molecular Representations for Property Prediction
Task: a framework for classification or regression tasks
DOI: http://dx.doi.org/10.1021/acs.jcim.9b00237
Code/Server: https://github.com/chemprop/chemprop
ChemBERTa
Date: 19-Oct-20
Target: Small molecule
Paper: ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
Task: A pretrained-on-SMILES transformer that can be finetuned for downstream molecular property prediction
DOI: https://doi.org/10.48550/arXiv.2010.09885
Code/Server: https://github.com/deepchem/deepchem
X-Mol
Date: 1-Feb-22
Target: Small molecule
Paper: X-MOL: large-scale pre-training for molecular understanding and diverse molecular analysis
Task: A pretrained-on-SMILES transformer that can be finetuned for downstream molecular property prediction
DOI: https://doi.org/10.1016/j.scib.2022.01.029
Code/Server: https://github.com/bm2-lab/X-MOL
MBP
Date: 11-Dec-23
Target: Small molecule
Paper: Multi-task bioassay pre-training for protein-ligand binding affinity prediction
Task: Affinity prediction
DOI: https://doi.org/10.1093/bib/bbad451
Code/Server: https://huggingface.co/spaces/jiaxianustc/mbp
MulinforCPI
Date: 4-Jan-24
Target: Small molecule
Paper: MulinforCPI: enhancing precision of compound?protein interaction prediction through novel perspectives on multi-level information integration
Task: Affinity prediction
DOI: https://doi.org/10.1093/bib/bbad484
Code/Server: https://github.com/dmis-lab/MulinforCPI
graphLambda
Date: 17-Feb-24
Target: Small molecule
Paper: graphLambda: Fusion Graph Neural Networks for Binding Affinity Prediction
Task: Affinity prediction
DOI: https://doi.org/10.1021/acs.jcim.3c00771
Code/Server: https://github.com/i-Molecule/graphLambda
MultiChem
Date: 16-Jan-25
Target: Small molecule
Paper: MultiChem: predicting chemical properties using multi-view graph attention network
Task: a framework for classification or regression tasks
DOI: https://doi.org/10.1186/s13040-024-00419-4
Code/Server: https://github.com/DMnBI/MultiChem
T-ALPHA
Date: 18-Feb-25
Target: Small molecule
Paper: T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein?Ligand Binding Affinity Prediction with Uncertainty-Aware Self-Learning for Protein-Specific Alignment
Task: Affinity prediction
DOI: https://doi.org/10.1021/acs.jcim.4c02332
Code/Server: https://github.com/gregory-kyro/T-ALPHA
DTIAM
Date: 15-Mar-25
Target: Small molecule
Paper: DTIAM: a unified framework for predicting drug-target interactions, binding affinities and drug mechanisms
Task: Multi-task framework for prediction of interaction, affinity, & mechanism
DOI: https://doi.org/10.1038/s41467-025-57828-0
Code/Server: https://github.com/CSUBioGroup/DTIAM