AIMC Topic: Models, Molecular

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Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning.

Nature methods Jul 29, 2019
Although structures determined at near-atomic resolution are now routinely reported by cryo-electron microscopy (cryo-EM), many density maps are determined at an intermediate resolution, and extracting structure information from these maps is still a...
Deep Learning Proteins Models, Molecular Cryoelectron Microscopy Protein Structure, Secondary Humans Neural Networks, Computer Software
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Artificial Intelligence Approach to Find Lead Compounds for Treating Tumors.

The journal of physical chemistry letters Jul 22, 2019
It has been demonstrated that MMP13 enzyme is related to most cancer cell tumors. The world's largest traditional Chinese medicine database was applied to screen for structure-based drug design and ligand-based drug design. To predict drug activity, ...
Cyclin-Dependent Kinase Inhibitor p16 Proteins Databases, Protein Drug Design Antineoplastic Agents Deep Learning Proto-Oncogene Proteins c-bcl-2 Tumor Suppressor Protein p53 Binding Sites Proto-Oncogene Proteins c-mdm2 Models, Molecular Mutation Ligands Machine Learning Algorithms Peptides Cyclin-Dependent Kinase 6 Databases, Pharmaceutical Matrix Metalloproteinase 13
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Targeting HIV/HCV Coinfection Using a Machine Learning-Based Multiple Quantitative Structure-Activity Relationships (Multiple QSAR) Method.

International journal of molecular sciences Jul 22, 2019
Human immunodeficiency virus type-1 and hepatitis C virus (HIV/HCV) coinfection occurs when a patient is simultaneously infected with both human immunodeficiency virus type-1 (HIV-1) and hepatitis C virus (HCV), which is common today in certain popul...
Quantitative Structure-Activity Relationship Databases, Pharmaceutical Polypharmacology Humans Machine Learning Models, Molecular Molecular Structure Bayes Theorem HIV-1 Molecular Conformation Hepacivirus Hepatitis C Anti-HIV Agents Antiviral Agents Protein Binding Algorithms Drug Discovery HIV Infections
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Finding Needles in a Haystack: Determining Key Molecular Descriptors Associated with the Blood-brain Barrier Entry of Chemical Compounds Using Machine Learning.

Molecular informatics Jul 19, 2019
In this paper we used two sets of calculated molecular descriptors to predict blood-brain barrier (BBB) entry of a collection of 415 chemicals. The set of 579 descriptors were calculated by Schrodinger and TopoCluj software. Polly and Triplet softwar...
Blood-Brain Barrier Organic Chemicals Models, Molecular Quantitative Structure-Activity Relationship Machine Learning Software Algorithms
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Deep Reinforcement Learning for Multiparameter Optimization in Drug Design.

Journal of chemical information and modeling Jul 5, 2019
In medicinal chemistry programs it is key to design and make compounds that are efficacious and safe. This is a long, complex, and difficult multiparameter optimization process, often including several properties with orthogonal trends. New methods f...
Drug Discovery Neural Networks, Computer Models, Theoretical Machine Learning Models, Molecular Drug Design Molecular Structure
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Evaluating Polymer Representations via Quantifying Structure-Property Relationships.

Journal of chemical information and modeling Jul 3, 2019
Machine learning techniques are being applied in quantifying structure-property relationships for a wide variety of materials, where the properly represented materials play key roles. Although algorithms for representation learning are extensively st...
Molecular Structure Polymers Structure-Activity Relationship Models, Molecular Machine Learning
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Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins.

Neural computation Jul 1, 2019
A restricted Boltzmann machine (RBM) is an unsupervised machine learning bipartite graphical model that jointly learns a probability distribution over data and extracts their relevant statistical features. RBMs were recently proposed for characterizi...
Models, Statistical Proteins Unsupervised Machine Learning Computer Simulation Probability Static Electricity Stochastic Processes Sequence Alignment Principal Component Analysis Models, Molecular Amino Acid Sequence
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A Self-Consistent Sonification Method to Translate Amino Acid Sequences into Musical Compositions and Application in Protein Design Using Artificial Intelligence.

ACS nano Jun 26, 2019
We report a self-consistent method to translate amino acid sequences into audible sound, use the representation in the musical space to train a neural network, and then apply it to generate protein designs using artificial intelligence (AI). The soni...
Sound Protein Conformation Protein Folding Models, Molecular Mutation Amino Acid Sequence Humans Artificial Intelligence Proteins
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DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences.

PLoS computational biology Jun 14, 2019
Identification of drug-target interactions (DTIs) plays a key role in drug discovery. The high cost and labor-intensive nature of in vitro and in vivo experiments have highlighted the importance of in silico-based DTI prediction approaches. In severa...
Amino Acid Sequence Ligands Binding Sites Computational Biology Computer Simulation Proteins Drug Discovery Models, Molecular Deep Learning Sequence Analysis, Protein
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Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index.

Nature communications Jun 7, 2019
Chemical shifts (CS) are determined from NMR experiments and represent the resonance frequency of the spin of atoms in a magnetic field. They contain a mixture of information, encompassing the in-solution conformations a protein adopts, as well as th...
Proteins Neural Networks, Computer Amino Acids Models, Molecular Biophysical Phenomena Magnetic Resonance Imaging Nuclear Magnetic Resonance, Biomolecular Magnetic Resonance Spectroscopy Protein Structure, Secondary
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