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FIGHTING ANTIMICROBIAL RESISTANCE using a cross-Disciplinary approach
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Property Prediction Tools
Date
Name
Title
Target
What it does
Code/Server
25-Jan-22
AMPlify
AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens
AMPs
Activity prediction
Link
7-Apr-22
TPpred-ATMV
TPpred-ATMV: therapeutic peptide prediction by adaptive multi-view tensor learning model
AMPs
Activity prediction
Link
27-Feb-23
KreinAMP
Krein support vector machine classification of antimicrobial peptides
AMPs
Activity prediction
Link
10-Mar-23
TriNet
TriNet: A tri-fusion neural network for the prediction of anticancer and antimicrobial peptides
AMPs
Activity prediction
Link
15-Mar-23
HydrAMP
Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
AMPs
Activity prediction
Link
24-May-23
AMPFinder
AMPFinder: A computational model to identify antimicrobial peptides and their functions based on sequence-derived information
AMPs
Activity prediction
Link
6-Oct-23
AMPpred-MFA
AMPpred-MFA: An Interpretable Antimicrobial Peptide Predictor with a Stacking Architecture, Multiple Features, and Multihead Attention
AMPs
Activity prediction
Link
4-Jun-24
iAMP-DL
An efficient hybrid deep learning architecture for predicting short antimicrobial peptides
AMPs
Activity prediction
Link
5-Jun-24
AMP-RNNpro
AMP-RNNpro: a two-stage approach for identification of antimicrobials using probabilistic features
AMPs
Activity prediction
Link
22-Jun-24
tAMPer
Structure-aware deep learning model for peptide toxicity prediction
AMPs
Activity prediction
Link
26-Jun-24
TP-LMMSG
TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation
AMPs
Activity prediction
Link
7-Jul-24
AMP
Ensemble Machine Learning and Predicted Properties Promote Antimicrobial Peptide Identification
AMPs
Activity prediction
Link
17-Jul-24
TriStack
TriStack enables accurate identification of antimicrobial and anti-inflammatory peptides by combining machine learning and deep learning approaches
AMPs
Activity prediction
Link
19-Jul-24
deepAMPNet
deepAMPNet: a novel antimicrobial peptide predictor employing AlphaFold2 predicted structures and a bi-directional long short-term memory protein language model
AMPs
Activity prediction
Link
6-Aug-24
DMAMP
DMAMP: A Deep-Learning Model for Detecting Antimicrobial Peptides and Their Multi-Activities
AMPs
Activity prediction
Link
28-Sep-24
PepNet
PepNet: an interpretable neural network for anti-inflammatory and antimicrobial peptides prediction using a pre-trained protein language model
AMPs
Activity prediction
Link
11-Dec-24
PepMNet
PepMNet: a hybrid deep learning model for predicting peptide properties using hierarchical graph representations
AMPs
Activity prediction
Link
10-Jan-25
deep-AMPpred
deep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities
AMPs
Activity prediction
Link
11-Jan-25
UniAMP
UniAMP: enhancing AMP prediction using deep neural networks with inferred information of peptides
AMPs
Activity prediction
Link
17-Jan-25
EvoGradient
Explainable deep learning and virtual evolution identifies antimicrobial peptides with activity against multidrug-resistant human pathogens
AMPs
Activity prediction
Link
4-Mar-25
PLAPD
Leveraging protein language models for robust antimicrobial peptide detection
AMPs
Activity prediction
Link
5-Mar-25
AMP-Designer
Discovery of antimicrobial peptides with notable antibacterial potency by an LLM- based foundation model
AMPs
Activity prediction
Link
21-Dec-22
MoLFormer
Large-scale chemical language representations capture molecular structure and properties
LBVS
A framework
Link
29-Jan-25
pLM4CPPs
pLM4CPPs: Protein Language Model-Based Predictor for Cell Penetrating Peptides
Peptides
Penetration prediction
Link
1-Dec-24
GEMS
GEMS: A Generalizable GNN Framework For Protein-Ligand Binding Affinity Prediction Through Robust Data Filtering and Language Model Integration
Protein-lig
Affinity prediction
Link
16-Dec-24
MHAN-DTA
MHAN-DTA: A Multiscale Hybrid Attention Network for Drug-Target Affinity Prediction
Protein-lig
Affinity prediction
Link
13-Jan-25
BlendNet
Exploring the potential of compound?protein complex structure-free models in virtual screening using BlendNet
Protein-lig
Affinity prediction
Link
20-Jan-25
MMPD-DTA
MMPD-DTA: Integrating Multi-Modal Deep Learning with Pocket-Drug Graphs for Drug-Target Binding Affinity Prediction
Protein-lig
Affinity prediction
Link
29-Jan-25
MutualDTA
MutualDTA: An Interpretable Drug?Target Affinity Prediction Model Leveraging Pretrained Models and Mutual Attention
Protein-lig
Affinity prediction
Link
30-Jul-19
Chemprop
Analyzing Learned Molecular Representations for Property Prediction
Small molecule
A framework
Link
19-Oct-20
ChemBERTa
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
Small molecule
A framework
Link
1-Feb-22
X-Mol
X-MOL: large-scale pre-training for molecular understanding and diverse molecular analysis
Small molecule
A framework
Link
11-Dec-23
MBP
Multi-task bioassay pre-training for protein-ligand binding affinity prediction
Small molecule
Affinity prediction
Link
4-Jan-24
MulinforCPI
MulinforCPI: enhancing precision of compound?protein interaction prediction through novel perspectives on multi-level information integration
Small molecule
Affinity prediction
Link
17-Feb-24
graphLambda
graphLambda: Fusion Graph Neural Networks for Binding Affinity Prediction
Small molecule
Affinity prediction
Link
16-Jan-25
MultiChem
MultiChem: predicting chemical properties using multi-view graph attention network
Small molecule
A framework
Link
18-Feb-25
T-ALPHA
T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein?Ligand Binding Affinity Prediction with Uncertainty-Aware Self-Learning for Protein-Specific Alignment
Small molecule
Affinity prediction
Link
15-Mar-25
DTIAM
DTIAM: a unified framework for predicting drug-target interactions, binding affinities and drug mechanisms
Small molecule
A framework
Link