Ab initio folding of terminal segments with secondary structures reveals the fine difference between two closely related all-atom statistical energy functions
about
Analyzing effects of naturally occurring missense mutationsModeling large regions in proteins: applications to loops, termini, and foldingImproving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templatesPredicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure predictionDesigning and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experimentA global machine learning based scoring function for protein structure prediction.Direct prediction of profiles of sequences compatible with a protein structure by neural networks with fragment-based local and energy-based nonlocal profilesAre distance-dependent statistical potentials considering three interacting bodies superior to two-body statistical potentials for protein structure prediction?Random forest-based protein model quality assessment (RFMQA) using structural features and potential energy termsBhageerath-H: a homology/ab initio hybrid server for predicting tertiary structures of monomeric soluble proteins.The origin of consistent protein structure refinement from structural averaging.Large-scale model quality assessment for improving protein tertiary structure prediction.Selective refinement and selection of near-native models in protein structure prediction.Analyses on hydrophobicity and attractiveness of all-atom distance-dependent potentials.A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11.Achievements and Challenges in Computational Protein Design.Trends in template/fragment-free protein structure predictionNewProt - a protein engineering portal.De novo protein structure prediction by dynamic fragment assembly and conformational space annealing.Statistical mechanics-based method to extract atomic distance-dependent potentials from protein structures.PackHelix: a tool for helix-sheet packing during protein structure prediction.MUFOLD-WQA: A new selective consensus method for quality assessment in protein structure prediction.GOAP: a generalized orientation-dependent, all-atom statistical potential for protein structure prediction.Protein structure prediction: challenging targets for CASP10.Recursive protein modeling: a divide and conquer strategy for Protein Structure Prediction and its case study in CASP9GalaxyTBM: template-based modeling by building a reliable core and refining unreliable local regions.Protein Structure Idealization: How accurately is it possible to model protein structures with dihedral angles?A simple probabilistic model of multibody interactions in proteins.Protein Structure Refinement through Structure Selection and Averaging from Molecular Dynamics Ensembles.Physics-based protein structure refinement through multiple molecular dynamics trajectories and structure averaging.Determining effects of non-synonymous SNPs on protein-protein interactions using supervised and semi-supervised learning.A novel side-chain orientation dependent potential derived from random-walk reference state for protein fold selection and structure prediction.Computational and experimental approaches to reveal the effects of single nucleotide polymorphisms with respect to disease diagnosticsStructure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy functionCommunity-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions.Mimicking the action of folding chaperones by Hamiltonian replica-exchange molecular dynamics simulations: application in the refinement of de novo models.Modeling proteins using a super-secondary structure library and NMR chemical shift informationStructure-based prediction of RNA-binding domains and RNA-binding sites and application to structural genomics targets.The scoring of poses in protein-protein docking: current capabilities and future directionsOn simplified global nonlinear function for fitness landscape: a case study of inverse protein folding.
P2860
Q21284966-7E227C8E-60ED-48CD-AE84-E8696B2F4B9EQ24598781-B68B2D55-CF8D-48FD-BD46-08B2AD18D9C7Q24632911-5FB08912-737E-4979-9FD4-6BFA57683572Q24655241-5F25BF97-5E71-4D6A-95CF-F53C81DF0BBDQ28658493-A7A8E54D-B5F8-48A5-9980-BAD571970521Q30355895-4526072C-AA10-4C2E-B5BD-26194389D42CQ30363288-D29E6141-ADE2-465E-A0FC-C097562E24DFQ30366706-A7C3328B-53BC-40E5-9B4C-2BDB9E3E9830Q30366792-B5EA8DB1-A822-4AB6-BDD4-409C7DE7DE05Q30369944-4C603F4D-0DE1-4D01-8660-836110184109Q30374559-89E552FD-760E-4577-80E7-2046337B73DDQ30375635-7070B53C-4F5E-43FD-B288-85700BB64951Q30377216-11D5CBFD-9858-4495-85C3-F78B7D1594BEQ30378786-5B936A9F-84F4-4CCD-BC23-CB924C103585Q30380582-3D0170B1-1106-4DBD-8149-F56F8811B3C3Q30395939-6CE33158-BF05-41E4-ACC2-9BB71D2CE8AFQ30400985-4707A1F4-BFD0-4C44-BB13-3D919F67ABFEQ30401707-C18133DC-FEC6-4511-A4D1-4EBCC28262D6Q30403052-33B9DD43-2A70-4214-B722-899371753DF9Q30404525-46AA54E2-DEE5-44E4-8FDA-9B28FDF3A6ACQ30406911-6EFC4C2B-32DC-44CC-A7D7-199BB6D1F870Q30408138-5979C812-8AE6-4761-89E7-543C7567CD3CQ30408272-8813430D-B69D-4F0E-A2DE-AA5375CCE4DAQ30418498-DEA29EBF-4A93-4670-AF5C-E6A9D3C32C36Q30419327-3337E906-5F42-4E6A-8F64-E06646619874Q30420248-5922C61E-C8AF-4522-83C6-A338E528FB4AQ30427623-92C827F8-5AF6-4E43-BA41-563833DD88D3Q30427943-3639D8E0-91DE-42DB-AE32-705BA930A8B5Q30428682-122332F9-7297-4467-AC0A-F524421A28CAQ30431472-AD280DBD-2F4D-494E-8369-6314FAB42E4FQ33552939-1CCA8F15-67D3-4B32-91D9-891B2584BDFFQ33742190-E96D80E4-3CB0-40B0-B4DD-C6B1CEF79B86Q33907569-D682AAA2-DEEC-40DA-BF6D-ECFCF7D55A0FQ34001405-6C5CC64B-16CB-4548-968A-C53F62EAABE1Q34083289-2F40126D-F08E-4DB5-92A1-B2982A18A970Q34192586-73D5EA5E-C12A-4256-8ABB-DB6F56780FD4Q34727938-BB91A9B2-E1AB-4526-8FCC-79DAEBF88385Q34865111-A5E0FB86-7AA2-4832-A8F6-BD1C414EF040Q35002283-4AB6D123-929D-403A-9596-42D34638D6C1Q35222696-148EE699-D36A-48EF-9A14-DAE16F720DFE
P2860
Ab initio folding of terminal segments with secondary structures reveals the fine difference between two closely related all-atom statistical energy functions
description
2008 nî lūn-bûn
@nan
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
2008年论文
@zh
2008年论文
@zh-cn
name
Ab initio folding of terminal ...... m statistical energy functions
@en
Ab initio folding of terminal ...... statistical energy functions.
@nl
type
label
Ab initio folding of terminal ...... m statistical energy functions
@en
Ab initio folding of terminal ...... statistical energy functions.
@nl
prefLabel
Ab initio folding of terminal ...... m statistical energy functions
@en
Ab initio folding of terminal ...... statistical energy functions.
@nl
P2860
P356
P1433
P1476
Ab initio folding of terminal ...... m statistical energy functions
@en
P2860
P304
P356
10.1110/PS.033480.107
P577
2008-05-09T00:00:00Z