AI Medical Compendium Journal:
Journal of molecular graphics & modelling

Showing 11 to 20 of 42 articles

Boosting the performance of molecular property prediction via graph-text alignment and multi-granularity representation enhancement.

Journal of molecular graphics & modelling Aug 5, 2024
Deep learning is playing an increasingly important role in accurate prediction of molecular properties. Prior to being processed by a deep learning model, a molecule is typically represented in the form of a text or a graph. While some methods attemp...
Algorithms Deep Learning Models, Molecular
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Combining machine learning, molecular dynamics, and free energy analysis for (5HT)-2A receptor modulator classification.

Journal of molecular graphics & modelling Aug 5, 2024
The 5-Hydroxytryptamine (5HT)-2A receptor, a key target in psychoactive drug development, presents significant challenges in the design of selective compounds. Here, we describe the construction, evaluation and validation of two machine learning (ML)...
Molecular Docking Simulation Drug Discovery Humans Machine Learning Receptor, Serotonin, 5-HT2A Thermodynamics Protein Binding Molecular Dynamics Simulation
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Uncovering substrate specificity determinants of class IIb aminoacyl-tRNA synthetases with machine learning.

Journal of molecular graphics & modelling Jul 14, 2024
Specific amino acid (AA) binding by aminoacyl-tRNA synthetases (aaRSs) is necessary for correct translation of the genetic code. Sequence and structure analyses have revealed the main specificity determinants and allowed a partitioning of aaRSs into ...
Machine Learning Amino Acyl-tRNA Synthetases Amino Acid Sequence Substrate Specificity Models, Molecular
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NPEX: Never give up protein exploration with deep reinforcement learning.

Journal of molecular graphics & modelling May 25, 2024
Elucidating unknown structures of proteins, such as metastable states, is critical in designing therapeutic agents. Protein structure exploration has been performed using advanced computational methods, especially molecular dynamics and Markov chain ...
Molecular Dynamics Simulation Markov Chains Proteins Monte Carlo Method Dipeptides Protein Conformation Algorithms Deep Learning
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ProtTrans and multi-window scanning convolutional neural networks for the prediction of protein-peptide interaction sites.

Journal of molecular graphics & modelling Apr 17, 2024
This study delves into the prediction of protein-peptide interactions using advanced machine learning techniques, comparing models such as sequence-based, standard CNNs, and traditional classifiers. Leveraging pre-trained language models and multi-vi...
Databases, Protein Binding Sites Computational Biology Proteins Protein Binding Neural Networks, Computer Machine Learning Algorithms Peptides Humans
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Target-specific novel molecules with their recipe: Incorporating synthesizability in the design process.

Journal of molecular graphics & modelling Feb 28, 2024
Application of Artificial intelligence (AI) in drug discovery has led to several success stories in recent times. While traditional methods mostly relied upon screening large chemical libraries for early-stage drug-design, de novo design can help ide...
Artificial Intelligence Drug Design Drug Discovery Proteins Small Molecule Libraries
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Fragments quantum descriptors in classification of bio-accumulative compounds.

Journal of molecular graphics & modelling Aug 2, 2023
The aim of the following research is to assess the applicability of calculated quantum properties of molecular fragments as molecular descriptors in machine learning classification task. The research is based on bio-concentration and QM9-extended dat...
Bioaccumulation Principal Component Analysis Cheminformatics Databases, Factual Machine Learning
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MD-GNN: A mechanism-data-driven graph neural network for molecular properties prediction and new material discovery.

Journal of molecular graphics & modelling May 9, 2023
Molecular properties prediction and new material discovery are significant for the pharmaceutical industry, food, chemistry, and other fields. The popular methods are theoretical mechanism calculation and machine learning. There is a deviation betwee...
Neural Networks, Computer Drug Discovery Machine Learning Reproducibility of Results
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Assessing protein homology models with docking reproducibility.

Journal of molecular graphics & modelling Feb 11, 2023
Results of the recent Critical Assessment of Protein Structure (CASP) competitions demonstrate that protein backbones can be predicted with very high accuracy. In particular, the artificial intelligence methods of AlphaFold 2 from DeepMind were able ...
Reproducibility of Results Protein Binding Protein Conformation Proteins Artificial Intelligence Binding Sites Ligands
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SuHAN: Substructural hierarchical attention network for molecular representation.

Journal of molecular graphics & modelling Dec 25, 2022
Recently, molecular representation and property exploration, with the combination of neural network, play a critical role in the field of drug design and discovery for assisting in drug related research. However, previous research in molecular repres...
Drug Design Neural Networks, Computer
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