AIMC Topic: Crystallography, X-Ray

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Exploring fragment-based target-specific ranking protocol with machine learning on cathepsin S.

Journal of computer-aided molecular design Nov 15, 2019
Cathepsin S (CatS), a member of cysteine cathepsin proteases, has been well studied due to its significant role in many pathological processes, including arthritis, cancer and cardiovascular diseases. CatS inhibitors have been included in D3R-GC3 for...
Machine Learning Molecular Docking Simulation Computer-Aided Design Protein Binding Humans Protein Conformation Binding Sites Thermodynamics Cathepsins Databases, Protein Ligands Crystallography, X-Ray
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Analysis of distance-based protein structure prediction by deep learning in CASP13.

Proteins Sep 13, 2019
This paper reports the CASP13 results of distance-based contact prediction, threading, and folding methods implemented in three RaptorX servers, which are built upon the powerful deep convolutional residual neural network (ResNet) method initiated by...
Sequence Alignment Sequence Analysis, Protein Deep Learning Computational Biology Machine Learning Proteins Software Algorithms Models, Molecular Protein Conformation Crystallography, X-Ray Protein Folding
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Machine Learning Models for Accurate Prediction of Kinase Inhibitors with Different Binding Modes.

Journal of medicinal chemistry Aug 30, 2019
Noncovalent inhibitors of protein kinases have different modes of action. They bind to the active or inactive form of kinases, compete with ATP, stabilize inactive kinase conformations, or act through allosteric sites. Accordingly, kinase inhibitors ...
Machine Learning Protein Binding Protein Kinases Protein Kinase Inhibitors Datasets as Topic Databases, Chemical Crystallography, X-Ray
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Deeper Profiles and Cascaded Recurrent and Convolutional Neural Networks for state-of-the-art Protein Secondary Structure Prediction.

Scientific reports Aug 26, 2019
Protein Secondary Structure prediction has been a central topic of research in Bioinformatics for decades. In spite of this, even the most sophisticated ab initio SS predictors are not able to reach the theoretical limit of three-state prediction acc...
Neural Networks, Computer Algorithms Computational Biology Crystallography, X-Ray Magnetic Resonance Spectroscopy Protein Structure, Secondary
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Sequence assignment for low-resolution modelling of protein crystal structures.

Acta crystallographica. Section D, Structural biology Jul 31, 2019
The performance of automated model building in crystal structure determination usually decreases with the resolution of the experimental data, and may result in fragmented models and incorrect side-chain assignment. Presented here are new methods for...
Datasets as Topic Crystallography, X-Ray Protein Conformation Machine Learning Software Algorithms Databases, Protein Amino Acid Sequence Molecular Docking Simulation Proteins
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A combined drug discovery strategy based on machine learning and molecular docking.

Chemical biology & drug design Mar 7, 2019
Data mining methods based on machine learning play an increasingly important role in drug design and discovery. In the current work, eight machine learning methods including decision trees, k-Nearest neighbor, support vector machines, random forests,...
Crystallography, X-Ray Binding Sites Protein Structure, Tertiary Principal Component Analysis Area Under Curve Inhibitory Concentration 50 Machine Learning Drug Discovery Databases, Factual ROC Curve Molecular Docking Simulation
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Integration of virtual screening and susceptibility test to discover active-site subpocket-specific biogenic inhibitors of Helicobacter pylori shikimate dehydrogenase.

International microbiology : the official journal of the Spanish Society for Microbiology Aug 24, 2018
Shikimate dehydrogenase (HpSDH) (EC 1.1.1.25) is a key enzyme in the shikimate pathway of Helicobacter pylori (H. pylori), which catalyzes the NADPH-dependent reversible reduction of 3-dehydroshikimate to shikimate. Targeting HpSDH has been recognize...
Enzyme Inhibitors Computational Biology Anti-Bacterial Agents Crystallography, X-Ray Helicobacter pylori Catalytic Domain Molecular Docking Simulation Drug Evaluation, Preclinical Protein Conformation Alcohol Oxidoreductases Microbial Sensitivity Tests
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Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges.

Journal of computer-aided molecular design Aug 16, 2018
Advanced mathematics, such as multiscale weighted colored subgraph and element specific persistent homology, and machine learning including deep neural networks were integrated to construct mathematical deep learning models for pose and binding affin...
Protein Conformation Receptors, Cytoplasmic and Nuclear Binding Sites Thermodynamics Cathepsins Protein Kinases Ligands Molecular Docking Simulation Deep Learning Crystallography, X-Ray Computer-Aided Design Protein Binding Databases, Protein Drug Design
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General Method for the Identification of Crystal Faces Using Raman Spectroscopy Combined with Machine Learning and Application to the Epitaxial Growth of Acetaminophen.

Langmuir : the ACS journal of surfaces and colloids Aug 9, 2018
Crystal morphology is one of the key crystallographic characteristics that governs the macroscopic properties of crystalline materials. The identification of crystal faces, or face indexing, is an important technique that is used to get information r...
Machine Learning Algorithms Mannitol Crystallography, X-Ray Xylitol Spectrum Analysis, Raman Galactose Crystallization Acetaminophen X-Ray Diffraction
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Insight Analysis of Promiscuous Estrogen Receptor α-Ligand Binding by a Novel Machine Learning Scheme.

Chemical research in toxicology Jul 30, 2018
Estrogen receptor α (ERα) plays a significant role in occurrence of breast cancer and may cause various adverse side-effects when ERα is an off-target protein. A theoretical model was derived to predict the binding affinity of ERα using the pharmacop...
Support Vector Machine Models, Molecular Ligands Computer Simulation Reproducibility of Results Protein Binding Estrogen Receptor alpha Humans Machine Learning Quantitative Structure-Activity Relationship Crystallography, X-Ray Protein Conformation
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