AIMC Topic: Models, Molecular

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CSM-Potential2: A comprehensive deep learning platform for the analysis of protein interacting interfaces.

Proteins Oct 23, 2023
Proteins are molecular machinery that participate in virtually all essential biological functions within the cell, which are tightly related to their 3D structure. The importance of understanding protein structure-function relationship is highlighted...
Humans Software Databases, Protein Deep Learning Models, Molecular Computational Biology Protein Binding Proteins Binding Sites Protein Interaction Mapping Ligands Protein Interaction Domains and Motifs Protein Conformation
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Molecular geometric deep learning.

Cell reports methods Oct 23, 2023
Molecular representation learning plays an important role in molecular property prediction. Existing molecular property prediction models rely on the de facto standard of covalent-bond-based molecular graphs for representing molecular topology at the...
Deep Learning Models, Molecular
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CryoREAD: de novo structure modeling for nucleic acids in cryo-EM maps using deep learning.

Nature methods Oct 2, 2023
DNA and RNA play fundamental roles in various cellular processes, where their three-dimensional structures provide information critical to understanding the molecular mechanisms of their functions. Although an increasing number of nucleic acid struct...
Deep Learning DNA Models, Molecular Protein Conformation Cryoelectron Microscopy RNA Nucleic Acids
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XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm.

Journal of biomolecular structure & dynamics Sep 18, 2023
Determining the structure-odor relationship has always been a very challenging task. The main challenge in investigating the correlation between the molecular structure and its associated odor is the ambiguous and obscure nature of verbally defined o...
Smell Quantitative Structure-Activity Relationship Molecular Structure Odorants Machine Learning Algorithms Models, Molecular
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Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15.

Proteins Aug 31, 2023
We report the results of the "UM-TBM" and "Zheng" groups in CASP15 for protein monomer and complex structure prediction. These prediction sets were obtained using the D-I-TASSER and DMFold-Multimer algorithms, respectively. For monomer structure pred...
Software Protein Conformation Sequence Alignment Proteins Models, Molecular Algorithms Deep Learning
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Development and validation of machine learning models for the prediction of SH-2 containing protein tyrosine phosphatase 2 inhibitors.

Molecular diversity Aug 8, 2023
Discovery and development of a new drug to the market is a highly challenging and resource consuming process. Although, modern drug discovery technologies have enabled the rapid identification of lead compounds, translation of the lead compounds into...
Protein Tyrosine Phosphatase, Non-Receptor Type 11 Enzyme Inhibitors Small Molecule Libraries Drug Discovery Models, Molecular Machine Learning Humans Reproducibility of Results
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AndroPred: an artificial intelligence-based model for predicting androgen receptor inhibitors.

Journal of biomolecular structure & dynamics Jul 26, 2023
Androgen receptor (AR), a steroid receptor, plays a pivotal role in the pathogenesis of prostate cancer (PCa). AR controls the transcription of genes that help cells avoid apoptosis and proliferate, thereby contributing to the development of PCa. Und...
Prostatic Neoplasms Artificial Intelligence Humans Receptors, Androgen Machine Learning Algorithms Drug Discovery Quantitative Structure-Activity Relationship Male Models, Molecular Androgen Receptor Antagonists
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Improving protein structure prediction with extended sequence similarity searches and deep-learning-based refinement in CASP15.

Proteins Jul 24, 2023
The human predictor team PEZYFoldings got first place with the assessor's formulae (3rd place with Global Distance Test Total Score [GDT-TS]) in the single-domain category and 10th place in the multimer category in Critical Assessment of Structure Pr...
Models, Molecular Computational Biology Humans Protein Conformation Deep Learning Proteins
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VoroIF-GNN: Voronoi tessellation-derived protein-protein interface assessment using a graph neural network.

Proteins Jul 21, 2023
We present VoroIF-GNN (Voronoi InterFace Graph Neural Network), a novel method for assessing inter-subunit interfaces in a structural model of a protein-protein complex, relying solely on the input structure without any additional information. Given ...
Neural Networks, Computer Proteins Models, Molecular
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Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15.

Proteins Jun 26, 2023
Estimating the accuracy of quaternary structural models of protein complexes and assemblies (EMA) is important for predicting quaternary structures and applying them to studying protein function and interaction. The pairwise similarity between struct...
Deep Learning Models, Molecular Proteins
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