AI Medical Compendium Topic:
Protein Conformation

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Molecular Properties of Drugs Interacting with SLC22 Transporters OAT1, OAT3, OCT1, and OCT2: A Machine-Learning Approach.

The Journal of pharmacology and experimental therapeutics Aug 3, 2016
Statistical analysis was performed on physicochemical descriptors of ∼250 drugs known to interact with one or more SLC22 "drug" transporters (i.e., SLC22A6 or OAT1, SLC22A8 or OAT3, SLC22A1 or OCT1, and SLC22A2 or OCT2), followed by application of ma...
Protein Binding Computational Biology Models, Molecular Pharmaceutical Preparations Machine Learning Substrate Specificity Organic Anion Transport Protein 1 Organic Anion Transporters, Sodium-Independent Organic Cation Transporter 1 Hydrogen-Ion Concentration Membrane Transport Proteins Protein Conformation
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Adaptive local learning in sampling based motion planning for protein folding.

BMC systems biology Aug 1, 2016
BACKGROUND: Simulating protein folding motions is an important problem in computational biology. Motion planning algorithms, such as Probabilistic Roadmap Methods, have been successful in modeling the folding landscape. Probabilistic Roadmap Methods ...
Machine Learning Computational Biology Protein Conformation Thermodynamics Proteins Models, Molecular Movement Protein Folding
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A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces.

International journal of molecular sciences Jul 27, 2016
Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous publ...
Humans Machine Learning Protein Interaction Domains and Motifs Databases, Protein Algorithms Protein Conformation Computational Biology Protein Interaction Mapping Proteins
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Protease Inhibitors in View of Peptide Substrate Databases.

Journal of chemical information and modeling Jun 9, 2016
Protease substrate profiling has nowadays almost become a routine task for experimentalists, and the knowledge on protease peptide substrates is easily accessible via the MEROPS database. We present a shape-based virtual screening workflow using vROC...
Drug Evaluation, Preclinical Ligands Protein Conformation Peptides User-Computer Interface Models, Molecular Peptide Hydrolases Databases, Pharmaceutical Substrate Specificity Protease Inhibitors Small Molecule Libraries Machine Learning
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Toward High-Throughput Predictive Modeling of Protein Binding/Unbinding Kinetics.

Journal of chemical information and modeling May 20, 2016
One of the unaddressed challenges in drug discovery is that drug potency determined in vitro is not a reliable indicator of drug activity in vivo. Accumulated evidence suggests that in vivo activity is more strongly correlated with the binding/unbind...
Thermodynamics Ligands Protein Conformation Static Electricity Kinetics Molecular Dynamics Simulation Safety Protein Binding Computational Biology Machine Learning Drug Discovery
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Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles.

Journal of chemical information and modeling May 3, 2016
Ensemble docking can be a successful virtual screening technique that addresses the innate conformational heterogeneity of macromolecular drug targets. Yet, lacking a method to identify a subset of conformational states that effectively segregates ac...
Machine Learning User-Computer Interface Protein Conformation Molecular Dynamics Simulation Drug Evaluation, Preclinical
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Deciphering the Complexity of Ligand-Protein Recognition Pathways Using Supervised Molecular Dynamics (SuMD) Simulations.

Journal of chemical information and modeling Apr 14, 2016
Molecular recognition is a crucial issue when aiming to interpret the mechanism of known active substances as well as to develop novel active candidates. Unfortunately, simulating the binding process is still a challenging task because it requires cl...
Receptors, G-Protein-Coupled Ligands Molecular Dynamics Simulation Protein Binding Cell Membrane Supervised Machine Learning Protein Conformation
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The Virtual Screening of the Drug Protein with a Few Crystal Structures Based on the Adaboost-SVM.

Computational and mathematical methods in medicine Apr 3, 2016
Using the theory of machine learning to assist the virtual screening (VS) has been an effective plan. However, the quality of the training set may reduce because of mixing with the wrong docking poses and it will affect the screening efficiencies. To...
Protein Conformation Chemistry, Pharmaceutical Hydrogen Imaging, Three-Dimensional Reproducibility of Results Cathepsin K Humans Drug Design Area Under Curve Proteins Software ROC Curve Databases, Protein Algorithms Support Vector Machine Models, Statistical Binding Sites Combinatorial Chemistry Techniques Protein Binding Computational Biology Ligands Crystallization
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Exploiting non-linear relationships between retention time and molecular structure of peptides originating from proteomes and comparing three multivariate approaches.

Journal of pharmaceutical and biomedical analysis Jan 27, 2016
Peptides' retention time prediction is gaining increasing popularity in liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics. This is a promising approach for improving successful proteome mapping, useful both in identification ...
Quantitative Structure-Activity Relationship Protein Conformation Humans Bacterial Proteins Artificial Intelligence Tandem Mass Spectrometry Peptides HeLa Cells Bacillus subtilis Proteome Chromatography, Liquid Models, Chemical
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Benchmarking Deep Networks for Predicting Residue-Specific Quality of Individual Protein Models in CASP11.

Scientific reports Jan 14, 2016
Quality assessment of a protein model is to predict the absolute or relative quality of a protein model using computational methods before the native structure is available. Single-model methods only need one model as input and can predict the absolu...
Algorithms Proteins Models, Molecular ROC Curve Support Vector Machine Amino Acids Protein Conformation
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