AI Medical Compendium Topic

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Molecular Conformation

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Fusing 2D and 3D molecular graphs as unambiguous molecular descriptors for conformational and chiral stereoisomers.

Briefings in bioinformatics
The rapid progress of machine learning (ML) in predicting molecular properties enables high-precision predictions being routinely achieved. However, many ML models, such as conventional molecular graph, cannot differentiate stereoisomers of certain t...

Accounting Conformational Dynamics into Structural Modeling Reflected by Cryo-EM with Deep Learning.

Combinatorial chemistry & high throughput screening
With the continuous development of structural biology, the requirement for accurate threedimensional structures during functional modulation of biological macromolecules is increasing. Therefore, determining the dynamic structures of bio-macromolecul...

epitope3D: a machine learning method for conformational B-cell epitope prediction.

Briefings in bioinformatics
The ability to identify antigenic determinants of pathogens, or epitopes, is fundamental to guide rational vaccine development and immunotherapies, which are particularly relevant for rapid pandemic response. A range of computational tools has been d...

Co-evolutionary distance predictions contain flexibility information.

Bioinformatics (Oxford, England)
MOTIVATION: Co-evolution analysis can be used to accurately predict residue-residue contacts from multiple sequence alignments. The introduction of machine-learning techniques has enabled substantial improvements in precision and a shift from predict...

Machine-learning scoring functions trained on complexes dissimilar to the test set already outperform classical counterparts on a blind benchmark.

Briefings in bioinformatics
The superior performance of machine-learning scoring functions for docking has caused a series of debates on whether it is due to learning knowledge from training data that are similar in some sense to the test data. With a systematically revised met...

A deep autoencoder framework for discovery of metastable ensembles in biomacromolecules.

The Journal of chemical physics
Biomacromolecules manifest dynamic conformational fluctuation and involve mutual interconversion among metastable states. A robust mapping of their conformational landscape often requires the low-dimensional projection of the conformational ensemble ...

A spatial-temporal gated attention module for molecular property prediction based on molecular geometry.

Briefings in bioinformatics
MOTIVATION: Geometry-based properties and characteristics of drug molecules play an important role in drug development for virtual screening in computational chemistry. The 3D characteristics of molecules largely determine the properties of the drug ...

A sequence-based deep learning approach to predict CTCF-mediated chromatin loop.

Briefings in bioinformatics
Three-dimensional (3D) architecture of the chromosomes is of crucial importance for transcription regulation and DNA replication. Various high-throughput chromosome conformation capture-based methods have revealed that CTCF-mediated chromatin loops a...

Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties.

Advances in experimental medicine and biology
Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas. Although several approaches have been proposed for antibody clustering, still no consensus has been reached. Numerous attempts use information from g...

Bacillus methylotrophicus ASWU-C2, a strain inhabiting hot desert soil, a new source for antibacterial bacillopyrone, pyrophen, and cyclopeptides.

Zeitschrift fur Naturforschung. C, Journal of biosciences
A strain of Bacillus methylotrophicus was isolated from a soil sample collected in Aswan eastern desert, which is known for its extremely arid climate. After fermentation of the strain in liquid culture and subsequent extraction, a bioassay-guided is...