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Applications of machine‐learning methods for the discovery of NDM‐1 inhibitors

https://doi.org/10.1111/cbdd.13708
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/minf.201400178openalex-snapshot
Identification and Validation Novel of VIM‐2 Metallo‐β‐lactamase Tripeptide Inhibitors
inferredcites →https://doi.org/10.1007/978-1-4939-6634-9_5openalex-snapshot
Computer-Aided Drug Design Methods
inferredcites →https://doi.org/10.1007/s10822-019-00218-8openalex-snapshot
Evaluation of different virtual screening strategies on the basis of compound sets with characteristic core distributions and dissimilarity relationships
inferredcites →https://doi.org/10.1007/s11224-019-01308-xopenalex-snapshot
Molecular docking, ADME/Tox prediction, and in vitro study of the cell growth inhibitory activity of five β-carboline alkaloids
inferredcites →https://doi.org/10.1007/s12551-016-0247-1openalex-snapshot
Software for molecular docking: a review
inferredcites →https://doi.org/10.1016/j.bioorg.2019.102953openalex-snapshot
Discovery of Baicalin as NDM-1 inhibitor: Virtual screening, biological evaluation and molecular simulation
inferredcites →https://doi.org/10.1016/j.jgar.2019.02.003openalex-snapshot
Discovery of NDM-1 inhibitors from natural products
inferredcites →https://doi.org/10.1017/9781108131704.011openalex-snapshot
Probability and Statistical Inference
inferredcites →https://doi.org/10.1021/acs.jcim.5b00559openalex-snapshot
ZINC 15 – Ligand Discovery for Everyone
inferredcites →https://doi.org/10.1021/acs.jcim.6b00740openalex-snapshot
Protein–Ligand Scoring with Convolutional Neural Networks
inferredcites →https://doi.org/10.1021/acs.jmedchem.5b00104openalex-snapshot
pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures
inferredcites →https://doi.org/10.1021/acs.jmedchem.6b00580openalex-snapshot
The Rational Design, Synthesis, and Antimicrobial Properties of Thiophene Derivatives That Inhibit Bacterial Histidine Kinases
inferredcites →https://doi.org/10.1021/acs.molpharmaceut.7b00631openalex-snapshot
ADMET Evaluation in Drug Discovery. 18. Reliable Prediction of Chemical-Induced Urinary Tract Toxicity by Boosting Machine Learning Approaches
inferredcites →https://doi.org/10.1021/acs.molpharmaceut.8b00083openalex-snapshot
Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery
inferredcites →https://doi.org/10.1021/ci800022eopenalex-snapshot
Evaluation of Virtual Screening Performance of Support Vector Machines Trained by Sparsely Distributed Active Compounds
inferredcites →https://doi.org/10.1021/mp100179topenalex-snapshot
Virtual Screening of Selective Multitarget Kinase Inhibitors by Combinatorial Support Vector Machines
inferredcites →https://doi.org/10.1038/s41597-019-0154-yopenalex-snapshot
DRAMP 2.0, an updated data repository of antimicrobial peptides
inferredcites →https://doi.org/10.1038/srep24482openalex-snapshot
DRAMP: a comprehensive data repository of antimicrobial peptides
inferredcites →https://doi.org/10.1039/c3cp55069aopenalex-snapshot
Asp120Asn mutation impairs the catalytic activity of NDM-1 metallo-β-lactamase: experimental and computational study
inferredcites →https://doi.org/10.1093/bioinformatics/bty374openalex-snapshot
Development and evaluation of a deep learning model for protein–ligand binding affinity prediction
inferredcites →https://doi.org/10.1093/bioinformatics/bty593openalex-snapshot
DeepDTA: deep drug–target binding affinity prediction
inferredcites →https://doi.org/10.1093/bioinformatics/btz111openalex-snapshot
DeepAffinity: interpretable deep learning of compound–protein affinity through unified recurrent and convolutional neural networks
inferredcites →https://doi.org/10.1093/nar/gkw1074openalex-snapshot
The ChEMBL database in 2017
inferredcites →https://doi.org/10.1109/tnnls.2016.2582924openalex-snapshot
LSTM: A Search Space Odyssey
inferredcites →https://doi.org/10.1111/cbdd.13494openalex-snapshot
A combined drug discovery strategy based on machine learning and molecular docking
inferredcites →https://doi.org/10.1111/cbdd.13526openalex-snapshot
Approaches for the discovery of metallo‐β‐lactamase inhibitors: A review
inferredcites →https://doi.org/10.1128/aac.00774-09openalex-snapshot
Characterization of a New Metallo-β-Lactamase Gene, bla NDM-1 , and a Novel Erythromycin Esterase Gene Carried on a Unique Genetic Structure in Klebsiella pneumoniae Sequence Type 14 from India
inferredcites →https://doi.org/10.1128/aac.02233-16openalex-snapshot
Plasmid-Mediated Novel bla NDM-17 Gene Encoding a Carbapenemase with Enhanced Activity in a Sequence Type 48 Escherichia coli Strain
inferredcites →https://doi.org/10.1145/1390156openalex-snapshot
Proceedings of the 25th international conference on Machine learning - ICML '08
inferredcites →https://doi.org/10.1186/s12859-017-1868-5openalex-snapshot
Long short-term memory RNN for biomedical named entity recognition
inferredcites →https://doi.org/10.1186/s40249-016-0105-1openalex-snapshot
Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus
inferredcites →https://doi.org/10.13140/rg.2.2.31161.62565openalex-snapshot
Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery
inferredcites →https://doi.org/10.1371/journal.pone.0039076openalex-snapshot
A Two-Step Target Binding and Selectivity Support Vector Machines Approach for Virtual Screening of Dopamine Receptor Subtype-Selective Ligands
inferredcites →https://doi.org/10.18637/jss.v028.i05openalex-snapshot
Building Predictive Models in R Using the caret Package
inferredcites →https://doi.org/10.2307/2987911openalex-snapshot
Probability and Statistical Inference.
inferredcites →https://doi.org/10.3389/fphar.2019.00913openalex-snapshot
Identification of Novel Antibacterials Using Machine Learning Techniques
inferredcites →https://doi.org/10.3390/s18103470openalex-snapshot
A MEMS IMU De-Noising Method Using Long Short Term Memory Recurrent Neural Networks (LSTM-RNN)
inferredcites →https://doi.org/10.4155/fmc-2016-0162openalex-snapshot
Discovery of Novel Dual Vegfr2 and Src Inhibitors Using a Multistep Virtual Screening Approach
inferredcites →https://doi.org/10.48550/arxiv.1412.3555openalex-snapshot
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/slct.74164openalex-snapshot
FtsZ‐LSTM: Generative AI Model for AntiBacterial Hits Discovery
inferred← citeshttps://doi.org/10.1007/978-3-031-17024-9_6openalex-snapshot
Multiple Instance Learning Based on Mol2vec Molecular Substructure Embeddings for Discovery of NDM-1 Inhibitors
inferred← citeshttps://doi.org/10.1007/978-981-19-9605-4_2openalex-snapshot
Applications of Computational Methods in Natural Products Based Drug Discovery
inferred← citeshttps://doi.org/10.1007/s00726-023-03245-wopenalex-snapshot
Rational design of stapled antimicrobial peptides
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c01008openalex-snapshot
DeepBLI: A Transferable Multichannel Model for Detecting β-Lactamase-Inhibitor Interaction
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5c00553openalex-snapshot
Harder than Metal: Challenging Antimicrobial Resistance with Metallo-β-lactamase Inhibitors
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6c00399openalex-snapshot
Triple Combination Therapy: A Promising Path Forward against β-Lactamase-Mediated Resistance
inferred← citeshttps://doi.org/10.1021/acsinfecdis.6c00608openalex-snapshot
Why Computational Predictions Fall Short in Subclass B1 Metallo-β-Lactamase Inhibitor Discovery: Progress, Pitfalls, and Translational Opportunities
inferred← citeshttps://doi.org/10.1080/17568919.2024.2385288openalex-snapshot
Discovery of novel ULK1 inhibitors through machine learning-guided virtual screening and biological evaluation
inferred← citeshttps://doi.org/10.1128/spectrum.00341-24openalex-snapshot
High-throughput screening identification of apigenin that reverses the colistin resistance of mcr-1-positive pathogens
inferred← citeshttps://doi.org/10.1186/s13065-024-01324-xopenalex-snapshot
Utilizing machine learning-based QSAR model to overcome standalone consensus docking limitation in beta-lactamase inhibitors screening: a proof-of-concept study
inferred← citeshttps://doi.org/10.1515/jib-2022-0050openalex-snapshot
Discovering NDM-1 inhibitors using molecular substructure embeddings representations
inferred← citeshttps://doi.org/10.2174/0115672050329828240805074938openalex-snapshot
Advances in Developing Small Molecule Drugs for Alzheimer's Disease
inferred← citeshttps://doi.org/10.3389/fmicb.2026.1934619openalex-snapshot
Advances in deep learning for antimicrobial research
inferred← citeshttps://doi.org/10.3389/fphar.2022.864412openalex-snapshot
Machine Learning in Antibacterial Drug Design
inferred← citeshttps://doi.org/10.3390/ijtm1030016openalex-snapshot
Artificial Intelligence in Translational Medicine
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