AIMC Topic: Models, Molecular

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I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction.

Nature protocols Aug 5, 2022
Most proteins in cells are composed of multiple folding units (or domains) to perform complex functions in a cooperative manner. Relative to the rapid progress in single-domain structure prediction, there are few effective tools available for multi-d...
Protein Conformation Cryoelectron Microscopy Databases, Protein Models, Molecular Algorithms Deep Learning Computational Biology Proteins
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Mapping Simulated Two-Dimensional Spectra to Molecular Models Using Machine Learning.

The journal of physical chemistry letters Aug 5, 2022
Two-dimensional (2D) spectroscopy encodes molecular properties and dynamics into expansive spectral data sets. Translating these data into meaningful chemical insights is challenging because of the many ways chemical properties can influence the spec...
Spectrum Analysis Vibration Machine Learning Models, Molecular
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Model building of protein complexes from intermediate-resolution cryo-EM maps with deep learning-guided automatic assembly.

Nature communications Jul 13, 2022
Advances in microscopy instruments and image processing algorithms have led to an increasing number of cryo-electron microscopy (cryo-EM) maps. However, building accurate models into intermediate-resolution EM maps remains challenging and labor-inten...
Cryoelectron Microscopy Models, Molecular Protein Conformation Reproducibility of Results Deep Learning
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Molecule Design Using Molecular Generative Models Constrained by Ligand-Protein Interactions.

Journal of chemical information and modeling Jul 6, 2022
In recent years, molecular deep generative models have attracted much attention for its application in drug design. The data-driven molecular deep generative model approximates the high dimensional distribution of the chemical space through learning...
Neural Networks, Computer Models, Molecular Ligands Drug Design Proteins
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Explainable machine learning for medicinal chemistry: exploring multi-target compounds.

Future medicinal chemistry Jul 1, 2022
Models, Molecular Chemistry, Pharmaceutical Machine Learning
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Factor analysis of error in oxidation potential calculation: A machine learning study.

Journal of computational chemistry Jun 28, 2022
The conductor-like polarizable continuum model (C-PCM), which is a low-cost solvation model, cannot treat characteristic interactions between the solvent and substructure(s) of the solute. Moreover, the error in a charged system is significant. Using...
Factor Analysis, Statistical Thermodynamics Models, Molecular Solvents Machine Learning Solutions
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Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation.

Journal of chemical information and modeling Jun 17, 2022
Creating a wide range of new compounds that not only have ideal pharmacological properties but also easily pass long-term toxicity evaluation is still a challenging task in current drug discovery. In this study, we developed a conditional generative ...
Deep Learning Models, Molecular Drug Design Drug Discovery
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Sequence-assignment validation in cryo-EM models with checkMySequence.

Acta crystallographica. Section D, Structural biology Jun 7, 2022
The availability of new artificial intelligence-based protein-structure-prediction tools has radically changed the way that cryo-EM maps are interpreted, but it has not eliminated the challenges of map interpretation faced by a microscopist. Models w...
Artificial Intelligence COVID-19 SARS-CoV-2 Proteins Humans Cryoelectron Microscopy Models, Molecular RNA, Viral
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Capturing surface complementarity in proteins using unsupervised learning and robust curvature measure.

Proteins Apr 23, 2022
The structure of a protein plays a pivotal role in determining its function. Often, the protein surface's shape and curvature dictate its nature of interaction with other proteins and biomolecules. However, marked by corrugations and roughness, a pro...
Ligands Models, Molecular Proteins Unsupervised Machine Learning Algorithms
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Accurate positioning of functional residues with robotics-inspired computational protein design.

Proceedings of the National Academy of Sciences of the United States of America Mar 7, 2022
SignificanceComputational protein design promises to advance applications in medicine and biotechnology by creating proteins with many new and useful functions. However, new functions require the design of specific and often irregular atom-level geom...
Protein Conformation Computational Biology Structure-Activity Relationship Reproducibility of Results Protein Engineering Algorithms Robotics Computer-Aided Design Proteins Models, Molecular Isomerases Amino Acids
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