Structure-based predictive models for allosteric hot spots.
about
Allosteric activation transitions in enzymes and biomolecular motors: insights from atomistic and coarse-grained simulationsCommon Internal Allosteric Network Links Anesthetic Binding Sites in a Pentameric Ligand-Gated Ion ChannelDesigning Allosteric Control into Enzymes by Chemical Rescue of StructureThe Designability of Protein Switches by Chemical Rescue of Structure: Mechanisms of Inactivation and ReactivationRigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein AllosteryExploiting protein flexibility to predict the location of allosteric sitesData-driven models for protein interaction and design.Computational modeling of allosteric communication reveals organizing principles of mutation-induced signaling in ABL and EGFR kinases.Allosteric communication across the native and mutated KIT receptor tyrosine kinase.Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions.AlloPred: prediction of allosteric pockets on proteins using normal mode perturbation analysis.Impact of mutations on the allosteric conformational equilibrium.CryptoSite: Expanding the Druggable Proteome by Characterization and Prediction of Cryptic Binding Sites.Solution NMR Spectroscopy for the Study of Enzyme Allostery.TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions.Integration of element specific persistent homology and machine learning for protein-ligand binding affinity prediction.Dynamic profile analysis to characterize dynamics-driven allosteric sites in enzymes.Prediction of allosteric sites and mediating interactions through bond-to-bond propensities.Cutoff lensing: predicting catalytic sites in enzymes.Sparse networks of directly coupled, polymorphic, and functional side chains in allosteric proteins.Discerning intersecting fusion-activation pathways in the Nipah virus using machine learning.Dissecting Dynamic Allosteric Pathways Using Chemically Related Small-Molecule Activators.A Random Forest Model for Predicting Allosteric and Functional Sites on Proteins.Allosteric sites can be identified based on the residue-residue interaction energy difference.Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening.Are there physicochemical differences between allosteric and competitive ligands?The emergence of protein complexes: quaternary structure, dynamics and allostery. Colworth Medal Lecture.Identification of functional motions in the adenylate kinase (ADK) protein family by computational hybrid approaches.
P2860
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P2860
Structure-based predictive models for allosteric hot spots.
description
2009 nî lūn-bûn
@nan
2009 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
Structure-based predictive models for allosteric hot spots.
@ast
Structure-based predictive models for allosteric hot spots.
@en
type
label
Structure-based predictive models for allosteric hot spots.
@ast
Structure-based predictive models for allosteric hot spots.
@en
prefLabel
Structure-based predictive models for allosteric hot spots.
@ast
Structure-based predictive models for allosteric hot spots.
@en
P2093
P2860
P1476
Structure-based predictive models for allosteric hot spots.
@en
P2093
Julie C Mitchell
Michael D Daily
Omar N A Demerdash
P2860
P304
P356
10.1371/JOURNAL.PCBI.1000531
P577
2009-10-09T00:00:00Z