AIMC Topic: Models, Molecular

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Role of environmental specificity in CASP results.

BMC bioinformatics Nov 11, 2023
BACKGROUND: Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence techniques, as shown by the results of the CASP13 and CASP14 (Critical Assessment of Structure Predict...
Protein Folding Hydrophobic and Hydrophilic Interactions Protein Conformation Proteins Models, Molecular Artificial Intelligence
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The bad and the good of trends in model building and refinement for sparse-data regions: pernicious forms of overfitting versus good new tools and predictions.

Acta crystallographica. Section D, Structural biology Nov 3, 2023
Model building and refinement, and the validation of their correctness, are very effective and reliable at local resolutions better than about 2.5 Å for both crystallography and cryo-EM. However, at local resolutions worse than 2.5 Å both the procedu...
Artificial Intelligence Crystallography, X-Ray Peptides Proteins Protein Conformation Models, Molecular Cryoelectron Microscopy
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Small-Molecule Conformer Generators: Evaluation of Traditional Methods and AI Models on High-Quality Data Sets.

Journal of chemical information and modeling Oct 26, 2023
Small-molecule conformer generation (SMCG) is an extremely important task in both ligand- and structure-based computer-aided drug design, especially during the hit discovery phase. Recently, a multitude of artificial intelligence (AI) models tailored...
Ligands Molecular Conformation Drug Design Models, Molecular Artificial Intelligence
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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 Computational Biology Proteins Databases, Protein Deep Learning Protein Binding Protein Interaction Mapping Protein Interaction Domains and Motifs Protein Conformation Binding Sites Models, Molecular Ligands
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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...
Models, Molecular Deep Learning
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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...
Protein Conformation Cryoelectron Microscopy RNA Nucleic Acids DNA Deep Learning Models, Molecular
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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 Machine Learning Algorithms Odorants 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 Algorithms Models, Molecular Protein Conformation Sequence Alignment Deep Learning Proteins
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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...
Models, Molecular Enzyme Inhibitors Protein Tyrosine Phosphatase, Non-Receptor Type 11 Small Molecule Libraries Reproducibility of Results Drug Discovery Humans Machine Learning
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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...
Quantitative Structure-Activity Relationship Androgen Receptor Antagonists Male Humans Machine Learning Prostatic Neoplasms Models, Molecular Artificial Intelligence Drug Discovery Receptors, Androgen Algorithms
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