AIMC Journal:
Journal of chemical information and modeling

Showing 271 to 280 of 934 articles

Predicting Serotonin Detection with DNA-Carbon Nanotube Sensors across Multiple Spectral Wavelengths.

Journal of chemical information and modeling May 13, 2024
Owing to the value of DNA-wrapped single-walled carbon nanotube (SWNT)-based sensors for chemically specific imaging in biology, we explore machine learning (ML) predictions DNA-SWNT serotonin sensor responsivity as a function of DNA sequence based o...
Base Sequence Serotonin Spectrometry, Fluorescence Machine Learning Nanotubes, Carbon Biosensing Techniques DNA
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Predicting Antimicrobial Peptides Using ESMFold-Predicted Structures and ESM-2-Based Amino Acid Features with Graph Deep Learning.

Journal of chemical information and modeling May 13, 2024
Currently, antimicrobial resistance constitutes a serious threat to human health. Drugs based on antimicrobial peptides (AMPs) constitute one of the alternatives to address it. Shallow and deep learning (DL)-based models have mainly been built from a...
Deep Learning Protein Conformation Amino Acids Antimicrobial Peptides Models, Molecular Amino Acid Sequence
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CNSMolGen: A Bidirectional Recurrent Neural Network-Based Generative Model for De Novo Central Nervous System Drug Design.

Journal of chemical information and modeling May 13, 2024
Central nervous system (CNS) drugs have had a significant impact on treating a wide range of neurodegenerative and psychiatric disorders. In recent years, deep learning-based generative models have shown great potential for accelerating drug discover...
Serotonin Plasma Membrane Transport Proteins Central Nervous System Agents Humans Neural Networks, Computer Molecular Docking Simulation Drug Design
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Quantifying the Hardness of Bioactivity Prediction Tasks for Transfer Learning.

Journal of chemical information and modeling May 13, 2024
Today, machine learning methods are widely employed in drug discovery. However, the chronic lack of data continues to hamper their further development, validation, and application. Several modern strategies aim to mitigate the challenges associated w...
Machine Learning Drug Discovery Humans
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Machine Learning Models Identify Inhibitors of New Delhi Metallo-β-lactamase.

Journal of chemical information and modeling May 10, 2024
The worldwide spread of the metallo-β-lactamases (MBL), especially New Delhi metallo-β-lactamase-1 (NDM-1), is threatening the efficacy of β-lactams, which are the most potent and prescribed class of antibiotics in the clinic. Currently, FDA-approved...
Klebsiella pneumoniae Escherichia coli Microbial Sensitivity Tests beta-Lactamase Inhibitors beta-Lactamases High-Throughput Screening Assays Machine Learning Molecular Docking Simulation
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Prediction of Transcription Factor Binding Sites on Cell-Free DNA Based on Deep Learning.

Journal of chemical information and modeling May 9, 2024
Transcription factors (TFs) are important regulatory elements for vital cellular activities, and the identification of transcription factor binding sites (TFBS) can help to explore gene regulatory mechanisms. Research studies have proved that cfDNA (...
Humans Transcription Factors Cell-Free Nucleic Acids DNA Deep Learning Binding Sites
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MolLoG: A Molecular Level Interpretability Model Bridging Local to Global for Predicting Drug Target Interactions.

Journal of chemical information and modeling May 6, 2024
Developing new pharmaceuticals is a costly and time-consuming endeavor fraught with significant safety risks. A critical aspect of drug research and disease therapy is discerning the existence of interactions between drugs and proteins. The evolution...
Drug Discovery Pharmaceutical Preparations Proteins Models, Molecular Deep Learning
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Breaking the Barriers: Machine-Learning-Based c-RASAR Approach for Accurate Blood-Brain Barrier Permeability Prediction.

Journal of chemical information and modeling May 3, 2024
The intricate nature of the blood-brain barrier (BBB) poses a significant challenge in predicting drug permeability, which is crucial for assessing central nervous system (CNS) drug efficacy and safety. This research utilizes an innovative approach, ...
Quantitative Structure-Activity Relationship Discriminant Analysis Permeability Humans Machine Learning Blood-Brain Barrier
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SAF: Smart Aggregation Framework for Revealing Atoms Importance Rank and Improving Prediction Rates in Drug Discovery.

Journal of chemical information and modeling May 2, 2024
Machine learning, and representation learning in particular, has the potential to facilitate drug discovery by screening a large chemical space in silico. A successful approach for representing molecules is to treat them as graphs and utilize graph n...
Drug Discovery Neural Networks, Computer beta-Lactams Machine Learning Anti-Bacterial Agents
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Deciphering the Coevolutionary Dynamics of L2 β-Lactamases via Deep Learning.

Journal of chemical information and modeling Apr 30, 2024
L2 β-lactamases, serine-based class A β-lactamases expressed by , play a pivotal role in antimicrobial resistance (AMR). However, limited studies have been conducted on these important enzymes. To understand the coevolutionary dynamics of L2 β-lactam...
beta-Lactamases Evolution, Molecular Deep Learning Protein Conformation Molecular Dynamics Simulation Stenotrophomonas maltophilia
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