Amanote Research
Register
Sign In
Synergistic Use of Compound Properties and Docking Scores in Neural Network Modeling of CYP2D6 Binding: Predicting Affinity and Conformational Sampling
doi 10.1021/ci600267k.s002
Full Text
Open PDF
Abstract
Available in
full text
Date
Unknown
Authors
Unknown
Publisher
American Chemical Society (ACS)
Related search
Synergistic Use of Compound Properties and Docking Scores in Neural Network Modeling of CYP2D6 Binding: Predicting Affinity and Conformational Sampling
Predicting RNA–protein Binding Affinity
Nature Methods
Biochemistry
Biotechnology
Cell Biology
Molecular Biology
The Effect of CYP2B6, CYP2D6, and CYP3A4 Alleles on Methadone Binding: A Molecular Docking Study
Journal of Chemistry
Chemistry
Using Multiple Linear Regression and Artificial Neural Network Techniques for Predicting CCR5 Binding Affinity of Substituted 1-(3, 3-Diphenylpropyl)-Piperidinyl Amides and Ureas
Open Journal of Medicinal Chemistry
Targeting Conformational Entropy to Modulate Binding Affinity
Biophysical Journal
Biophysics
Predictive Modeling of Discharge of Flow in Compound Open Channel Using Radial Basis Neural Network
Modeling Earth Systems and Environment
Artificial Neural Network Modeling for Predicting Pore Size and Its Distribution for Melt Blown Nonwoven
Sen'i Gakkaishi
Materials Science
Industrial
Polymers
Manufacturing Engineering
Plastics
Chemical Engineering
Binding Affinity and Conformational Preferences Influence Kinetic Stability of Short Oligonucleotides on Carbon Nanotubes
Conformational Changes in Antibody Fab Fragments Upon Binding and Their Consequences on the Performance of Docking Algorithms
Immunology Letters
Allergy
Immunology
