Some case studies on application of "r(m)2" metrics for judging quality of quantitative structure-activity relationship predictions: emphasis on scaling of response data.
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HomoSAR: bridging comparative protein modeling with quantitative structural activity relationship to design new peptides.Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.Estimation of Anti-HIV Activity of HEPT Analogues Using MLR, ANN, and SVM Techniques.Encompassing receptor flexibility in virtual screening using ensemble docking-based hybrid QSAR: discovery of novel phytochemicals for BACE1 inhibition.Receptor-guided 3D-QSAR studies, molecular dynamics simulation and free energy calculations of Btk kinase inhibitorsAdvances in quantitative structure-activity relationship models of anti-Alzheimer's agents.QSAR studies in the discovery of novel type-II diabetic therapies.A structure-activity relationship study of the toxicity of ionic liquids using an adapted Ferreira-Kiralj hydrophobicity parameter.Highly predictive hologram QSAR models of nitrile-containing cruzain inhibitors.Probing the origins of human acetylcholinesterase inhibition via QSAR modeling and molecular docking3D-QSAR and molecular docking study of LRRK2 kinase inhibitors by CoMFA and CoMSIA methods.Predicting binding affinities of diverse pharmaceutical chemicals to human serum plasma proteins using QSPR modelling approaches.Geometry optimization method versus predictive ability in QSPR modeling for ionic liquids.Beware of R(2): Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models.Use of the Monte Carlo Method for OECD Principles-Guided QSAR Modeling of SIRT1 Inhibitors.In silico modeling of β-carbonic anhydrase inhibitors from the fungus Malassezia globosa as antidandruff agents.Searching for anthranilic acid-based thumb pocket 2 HCV NS5B polymerase inhibitors through a combination of molecular docking, 3D-QSAR and virtual screening.A Predictive HQSAR Model for a Series of Tricycle Core Containing MMP-12 Inhibitors with Dibenzofuran Ring.Receptor- and ligand-based study of fullerene analogues: comprehensive computational approach including quantum-chemical, QSAR and molecular docking simulations.In-silico combinatorial design and pharmacophore modeling of potent antimalarial 4-anilinoquinolines utilizing QSAR and computed descriptors.Modeling bioconcentration factor (BCF) using mechanistically interpretable descriptors computed from open source tool "PaDEL-Descriptor".Predictive QSAR modelling of algal toxicity of ionic liquids and its interspecies correlation with Daphnia toxicity.Exploring QSARs of the interaction of flavonoids with GABA (A) receptor using MLR, ANN and SVM techniques.QSAR Study of 17β-HSD3 Inhibitors by Genetic Algorithm-Support Vector Machine as a Target Receptor for the Treatment of Prostate Cancer.QSAR, docking, ADMET, and system pharmacology studies on tormentic acid derivatives for anticancer activity.In Silico Drug-Designing Studies on Flavanoids as Anticolon Cancer Agents: Pharmacophore Mapping, Molecular Docking, and Monte Carlo Method-Based QSAR Modeling.Insights into the Structural Requirements of Potent Brassinosteroids as Vegetable Growth Promoters Using Second-Internode Elongation as Biological Activity: CoMFA and CoMSIA Studies.Quantifying ligand-receptor interactions for gorge-spanning acetylcholinesterase inhibitors for the treatment of Alzheimer's disease.Nano-QSAR Model for Predicting Cell Viability of Human Embryonic Kidney Cells.Discovery of novel urokinase plasminogen activator (uPA) inhibitors using ligand-based modeling and virtual screening followed by in vitro analysis.Global and local QSPR models to predict supercooled vapour pressure for organic compounds.Exploring molecular fingerprints of selective PPARδ agonists through comparative and validated chemometric techniques.Screening for High Conductivity/Low Viscosity Ionic Liquids Using Product Descriptors.Chemometric design to explore pharmacophore features of BACE inhibitors for controlling Alzheimer's disease.Identification of molecular descriptors for design of novel Isoalloxazine derivatives as potential Acetylcholinesterase inhibitors against Alzheimer's disease.Identification of novel antifungal lead compounds through pharmacophore modeling, virtual screening, molecular docking, antimicrobial evaluation, and gastrointestinal permeation studies.Docking-based 3D-QSAR study of pyridyl aminothiazole derivatives as checkpoint kinase 1 inhibitors.Molecular modeling studies on series of Btk inhibitors using docking, structure-based 3D-QSAR and molecular dynamics simulation: a combined approach.Analysis of B-Raf[Formula: see text] inhibitors using 2D and 3D-QSAR, molecular docking and pharmacophore studies.Insight into the Structural Requirements of Protoporphyrinogen Oxidase Inhibitors: Molecular Docking and CoMFA of Diphenyl Ether, Isoxazole Phenyl, and Pyrazole Phenyl Ether
P2860
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P2860
Some case studies on application of "r(m)2" metrics for judging quality of quantitative structure-activity relationship predictions: emphasis on scaling of response data.
description
2013 nî lūn-bûn
@nan
2013 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
Some case studies on applicati ...... s on scaling of response data.
@ast
Some case studies on applicati ...... s on scaling of response data.
@en
type
label
Some case studies on applicati ...... s on scaling of response data.
@ast
Some case studies on applicati ...... s on scaling of response data.
@en
prefLabel
Some case studies on applicati ...... s on scaling of response data.
@ast
Some case studies on applicati ...... s on scaling of response data.
@en
P2093
P50
P356
P1476
Some case studies on applicati ...... s on scaling of response data.
@en
P2093
Indrani Mitra
Pratim Chakraborty
Probir Kumar Ojha
P304
P356
10.1002/JCC.23231
P577
2013-01-08T00:00:00Z