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Predicting resistance mutations using protein design algorithms

Predicting resistance mutations using protein design algorithms

http://www.wikidata.org/entity/Q27663576

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Computational design of a PDZ domain peptide inhibitor that rescues CFTR activity Toward New Therapeutics for Skin and Soft Tissue Infections: Propargyl-Linked Antifolates Are Potent Inhibitors of MRSA and Streptococcus pyogenes Protein design using continuous rotamers Calculating ensemble averaged descriptions of protein rigidity without sampling Correlated electrostatic mutations provide a reservoir of stability in HIV protease Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design Protein side-chain modeling with a protein-dependent optimized rotamer library.Computational approaches for rational design of proteins with novel functionalities comets (Constrained Optimization of Multistate Energies by Tree Search): A Provable and Efficient Protein Design Algorithm to Optimize Binding Affinity and Specificity with Respect to Sequence.LUTE (Local Unpruned Tuple Expansion): Accurate Continuously Flexible Protein Design with General Energy Functions and Rigid Rotamer-Like Efficiency.Achievements and Challenges in Computational Protein Design.Multistate Computational Protein Design with Backbone Ensembles.Parallel Computational Protein Design.A Bayesian approach for determining protein side-chain rotamer conformations using unassigned NOE data.Dead-end elimination with perturbations (DEEPer): a provable protein design algorithm with continuous sidechain and backbone flexibility.An efficient parallel algorithm for accelerating computational protein design.Protein loop closure using orientational restraints from NMR data Antifolate agents: a patent review (2006 - 2010).An energy-based conformer library for side chain optimization: improved prediction and adjustable sampling.OSPREY: protein design with ensembles, flexibility, and provable algorithms.The role of local backrub motions in evolved and designed mutations Binding pocket optimization by computational protein design.Computational design of protein-small molecule interfaces.Protein design algorithms predict viable resistance to an experimental antifolate Analysis of Somatic Mutations in Cancer: Molecular Mechanisms of Activation in the ErbB Family of Receptor Tyrosine Kinases.A geometric arrangement algorithm for structure determination of symmetric protein homo-oligomers from NOEs and RDCs Acetylenic linkers in lead compounds: a study of the stability of the propargyl-linked antifolates.A critical analysis of computational protein design with sparse residue interaction graphs.Rosetta:MSF: a modular framework for multi-state computational protein design.Nonracemic Antifolates Stereoselectively Recruit Alternate Cofactors and Overcome Resistance in S. aureus.BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design.Winning the arms race by improving drug discovery against mutating targets.Multistate approaches in computational protein design.Exploitation of genomics in fungicide research: current status and future perspectives.OSPREY Predicts Resistance Mutations Using Positive and Negative Computational Protein Design.Algorithms for protein design.Do we have the tools to manage resistance in the future?Fast search algorithms for computational protein design.MRSA Isolates from United States Hospitals Carry dfrG and dfrK Resistance Genes and Succumb to Propargyl-Linked Antifolates.cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design.

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P2860

Predicting resistance mutations using protein design algorithms

http://www.wikidata.org/entity/Q27663576

description

2010 nî lūn-bûn

@nan

2010 թուականի Օգոստոսին հրատարակուած գիտական յօդուած

@hyw

2010 թվականի օգոստոսին հրատարակված գիտական հոդված

@hy

2010年の論文

@ja

2010年論文

@yue

2010年論文

@zh-hant

2010年論文

@zh-hk

2010年論文

@zh-mo

2010年論文

@zh-tw

2010年论文

@wuu

name

Predicting resistance mutations using protein design algorithms

@ast

Predicting resistance mutations using protein design algorithms

@en

Predicting resistance mutations using protein design algorithms

@nl

type

label

Predicting resistance mutations using protein design algorithms

@ast

Predicting resistance mutations using protein design algorithms

@en

Predicting resistance mutations using protein design algorithms

@nl

prefLabel

Predicting resistance mutations using protein design algorithms

@ast

Predicting resistance mutations using protein design algorithms

@en

Predicting resistance mutations using protein design algorithms

@nl

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Proceedings of the National Academy of Sciences of the United States of America

P1476

Predicting resistance mutations using protein design algorithms

@en

P2093

Amy C Anderson

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Bruce R Donald

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Kathleen M Frey

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P2860

Design of a Novel Globular Protein Fold with Atomic-Level Accuracy

De novo computational design of retro-aldol enzymes

PROCHECK: a program to check the stereochemical quality of protein structures

Processing of X-ray diffraction data collected in oscillation mode

Computational design and experimental study of tighter binding peptides to an inactivated mutant of HIV-1 protease

Kemp elimination catalysts by computational enzyme design

Crystal Structures of Wild-type and Mutant Methicillin-resistant Staphylococcus aureus Dihydrofolate Reductase Reveal an Alternate Conformation of NADPH That May Be Linked to Trimethoprim Resistance

Towards the understanding of resistance mechanisms in clinically isolated trimethoprim-resistant, methicillin-resistant Staphylococcus aureus dihydrofolate reductase

Coot: model-building tools for molecular graphics

Relationship between the inhibition constant (K1) and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an enzymatic reaction

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107

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Ivelin S. Georgiev

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45275126

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20643959

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