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| 001 | 16597 | ||
| 005 | 20200402205502.0 | ||
| 024 | 7 | _ | |2 pmid |a pmid:20851219 |
| 024 | 7 | _ | |2 DOI |a 10.1016/j.bbapap.2010.09.006 |
| 024 | 7 | _ | |2 WOS |a WOS:000292350200007 |
| 037 | _ | _ | |a PreJuSER-16597 |
| 041 | _ | _ | |a eng |
| 082 | _ | _ | |a 570 |
| 084 | _ | _ | |2 WoS |a Biochemistry & Molecular Biology |
| 084 | _ | _ | |2 WoS |a Biophysics |
| 100 | 1 | _ | |0 P:(DE-HGF)0 |a Klenin, K. |b 0 |
| 245 | _ | _ | |a Modelling Proteins: Conformational Sampling and Reconstruction of Folding Kinetics |
| 260 | _ | _ | |a Amsterdam [u.a.] |b Elsevier |c 2011 |
| 300 | _ | _ | |a 977 - 1000 |
| 336 | 7 | _ | |a Journal Article |0 PUB:(DE-HGF)16 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a article |2 DRIVER |
| 440 | _ | 0 | |0 19421 |a BBA - Proteins and Proteomics |v 1814 |x 1570-9639 |y 8 |
| 500 | _ | _ | |3 POF3_Assignment on 2016-02-29 |
| 500 | _ | _ | |a KK and WW acknowledge the support from the DFG Center for Functional Nanostructures (C5.1) and the Landesstiftung Baden-Wurttemberg (Biomaterials program and HPC program). |
| 520 | _ | _ | |a In the last decades biomolecular simulation has made tremendous inroads to help elucidate biomolecular processes in-silico. Despite enormous advances in molecular dynamics techniques and the available computational power, many problems involve long time scales and large-scale molecular rearrangements that are still difficult to sample adequately. In this review we therefore summarise recent efforts to fundamentally improve this situation by decoupling the sampling of the energy landscape from the description of the kinetics of the process. Recent years have seen the emergence of many advanced sampling techniques, which permit efficient characterisation of the relevant family of molecular conformations by dispensing with the details of the short-term kinetics of the process. Because these methods generate thermodynamic information at best, they must be complemented by techniques to reconstruct the kinetics of the process using the ensemble of relevant conformations. Here we review recent advances for both types of methods and discuss their perspectives to permit efficient and accurate modelling of large-scale conformational changes in biomolecules. This article is part of a Special Issue entitled: Protein Dynamics: Experimental and Computational Approaches. |
| 536 | _ | _ | |0 G:(DE-Juel1)FUEK409 |2 G:(DE-HGF) |a Funktion und Dysfunktion des Nervensystems |c P33 |x 0 |
| 536 | _ | _ | |0 G:(DE-Juel1)FUEK505 |2 G:(DE-HGF) |a BioSoft: Makromolekulare Systeme und biologische Informationsverarbeitung |c P45 |x 1 |
| 588 | _ | _ | |a Dataset connected to Web of Science, Pubmed |
| 650 | _ | 2 | |2 MeSH |a Algorithms |
| 650 | _ | 2 | |2 MeSH |a Evolution, Molecular |
| 650 | _ | 2 | |2 MeSH |a Kinetics |
| 650 | _ | 2 | |2 MeSH |a Models, Molecular |
| 650 | _ | 2 | |2 MeSH |a Monte Carlo Method |
| 650 | _ | 2 | |2 MeSH |a Protein Conformation |
| 650 | _ | 2 | |2 MeSH |a Protein Folding |
| 650 | _ | 2 | |2 MeSH |a Proteins: chemistry |
| 650 | _ | 7 | |0 0 |2 NLM Chemicals |a Proteins |
| 650 | _ | 7 | |2 WoSType |a J |
| 653 | 2 | 0 | |2 Author |a Protein dynamics |
| 653 | 2 | 0 | |2 Author |a Conformational ensemble |
| 653 | 2 | 0 | |2 Author |a Advanced sampling |
| 653 | 2 | 0 | |2 Author |a Markov models |
| 700 | 1 | _ | |0 P:(DE-Juel1)132024 |a Strodel, B. |b 1 |u FZJ |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Wales, D.J. |b 2 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Wenzel, W. |b 3 |
| 773 | _ | _ | |0 PERI:(DE-600)2209540-8 |a 10.1016/j.bbapap.2010.09.006 |g Vol. 1814, p. 977 - 1000 |p 977 - 1000 |q 1814<977 - 1000 |t Biochimica et biophysica acta / Proteins and proteomics |v 1814 |x 1570-9639 |y 2011 |
| 856 | 7 | _ | |u http://dx.doi.org/10.1016/j.bbapap.2010.09.006 |
| 909 | C | O | |o oai:juser.fz-juelich.de:16597 |p VDB |
| 913 | 1 | _ | |0 G:(DE-Juel1)FUEK409 |a DE-HGF |b Gesundheit |k P33 |l Funktion und Dysfunktion des Nervensystems |v Funktion und Dysfunktion des Nervensystems |x 0 |
| 913 | 1 | _ | |0 G:(DE-Juel1)FUEK505 |a DE-HGF |b Schlüsseltechnologien |k P45 |l Biologische Informationsverarbeitung |v BioSoft: Makromolekulare Systeme und biologische Informationsverarbeitung |x 1 |
| 913 | 2 | _ | |a DE-HGF |b Key Technologies |l BioSoft – Fundamentals for future Technologies in the fields of Soft Matter and Life Sciences |1 G:(DE-HGF)POF3-550 |0 G:(DE-HGF)POF3-559H |2 G:(DE-HGF)POF3-500 |v Addenda |x 0 |
| 914 | 1 | _ | |y 2011 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0010 |a JCR/ISI refereed |
| 920 | 1 | _ | |0 I:(DE-Juel1)ICS-6-20110106 |g ICS |k ICS-6 |l Strukturbiochemie |x 0 |
| 970 | _ | _ | |a VDB:(DE-Juel1)130762 |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a ConvertedRecord |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a I:(DE-Juel1)ICS-6-20110106 |
| 980 | _ | _ | |a UNRESTRICTED |
| 981 | _ | _ | |a I:(DE-Juel1)IBI-7-20200312 |
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