AIMC Topic: Drug Discovery

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Improving Anticancer Drug Selection and Prioritization via Neural Learning to Rank.

Journal of chemical information and modeling May 13, 2024
Personalized cancer treatment requires a thorough understanding of complex interactions between drugs and cancer cell lines in varying genetic and molecular contexts. To address this, high-throughput screening has been used to generate large-scale dr...
Drug Discovery Humans Antineoplastic Agents Cell Line, Tumor Neural Networks, Computer
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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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Lessons learnt from machine learning in early stages of drug discovery.

Expert opinion on drug discovery May 10, 2024
Humans Machine Learning Drug Discovery Drug Development
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Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules.

Expert opinion on drug discovery May 10, 2024
INTRODUCTION: Prediction of pharmacokinetic (PK) properties is crucial for drug discovery and development. Machine-learning (ML) models, which use statistical pattern recognition to learn correlations between input features (such as chemical structur...
Pharmacokinetics Drug Discovery Drug Development Pharmaceutical Preparations Machine Learning Models, Biological Humans Animals
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Emerging opportunities of using large language models for translation between drug molecules and indications.

Scientific reports May 10, 2024
A drug molecule is a substance that changes an organism's mental or physical state. Every approved drug has an indication, which refers to the therapeutic use of that drug for treating a particular medical condition. While the Large Language Model (L...
Pharmaceutical Preparations Artificial Intelligence Drug Discovery Humans
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MISATO: machine learning dataset of protein-ligand complexes for structure-based drug discovery.

Nature computational science May 10, 2024
Large language models have greatly enhanced our ability to understand biology and chemistry, yet robust methods for structure-based drug discovery, quantum chemistry and structural biology are still sparse. Precise biomolecule-ligand interaction data...
Machine Learning Quantum Theory Drug Discovery Molecular Dynamics Simulation Ligands Proteins
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Prediction of Drug-Target Affinity Using Attention Neural Network.

International journal of molecular sciences May 8, 2024
Studying drug-target interactions (DTIs) is the foundational and crucial phase in drug discovery. Biochemical experiments, while being the most reliable method for determining drug-target affinity (DTA), are time-consuming and costly, making it chall...
Drug Discovery Humans Neural Networks, Computer Pharmaceutical Preparations Deep Learning Algorithms
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GraphEGFR: Multi-task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family proteins on data scarcity.

Journal of computational chemistry May 7, 2024
The proteins within the human epidermal growth factor receptor (EGFR) family, members of the tyrosine kinase receptor family, play a pivotal role in the molecular mechanisms driving the development of various tumors. Tyrosine kinase inhibitors, key c...
Neural Networks, Computer Protein Kinase Inhibitors Machine Learning ErbB Receptors Drug Discovery Deep Learning Humans
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The role and future prospects of artificial intelligence algorithms in peptide drug development.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie May 6, 2024
Peptide medications have been more well-known in recent years due to their many benefits, including low side effects, high biological activity, specificity, effectiveness, and so on. Over 100 peptide medications have been introduced to the market to ...
Humans Artificial Intelligence Animals Peptides Machine Learning Algorithms Drug Development Drug Discovery
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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 Models, Molecular Deep Learning Pharmaceutical Preparations Proteins
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