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真核基因表达评论综述™
影响因子: 1.841 5年影响因子: 1.927 SJR: 0.649 SNIP: 0.516 CiteScore™: 1.96

ISSN 打印: 1045-4403
ISSN 在线: 2162-6502

真核基因表达评论综述™

DOI: 10.1615/CritRevEukaryotGeneExpr.2014010201
pages 311-324

Identification of Best Protein Crystallization Methods by Molecular Dynamics (MD)

Marine Bozdaganyan
Nanoworld Institute Fondazione EL.B.A Nicolini (FEN), Pradalunga, Largo Redaelli 7, Bergamo 24100, Italy; Lomonosov Moscow State University, Biological Faculty, 119991 Moscow, Leninskie Gory, 1/19, Russia
Nicola Luigi Bragazzi
Nanoworld Institute Fondazione EL.B.A Nicolini (FEN), Pradalunga, Largo Redaelli 7, Bergamo 24100, Italy; Biophysics and Nanobiotechnology Laboratories (BNL), Department of Experimental Medicine (DIMES), University of Genoa, Via Antonio Pastore 3, Genoa
Eugenia Pechkova
Nanoworld Institute Fondazione ELBA Nicolini, Pradalunga, Bergamo 24100, Italy ; Biophysics and Nanobiotechnology Laboratories, Department of Experimental Medicine, University of Genova, Genoa 16121-16167, Italy; European Synchrotron Radiation Facility
Konstantin V. Shaitan
Lomonosov Moscow State University, Biological Faculty, 119991 Moscow, Leninskie Gory, 1/19, Russia; Semenov Institute of Chemical Physics, 119991 Moscow, Kosygina str. 2, Russia
Claudio Nicolini
Nanoworld Institute Fondazione ELBA Nicolini, Pradalunga, Bergamo 24100, Italy; Biophysics and Nanobiotechnology Laboratories, Department of Experimental Medicine, University of Genova, Genoa 16121-16167, Italy; European Synchrotron Radiation Facility

ABSTRACT

A full-atom structure of a protein provides an important piece of information for molecular biologists, but has to be complemented by further knowledge concerning its conformational mobility and functional properties. Some scholars have proposed to integrate proteomics-derived data (mainly obtained with techniques like X-ray and NMR crystallography) with protein bioinformatics and computational approaches, above all molecular dynamics (MD), in order to gain better elucidations about proteins. MD simulations have been applied to different areas of protein sciences, but so far few efforts have been made to couple MD with an understanding of the different crystallization techniques that have been proposed during the decades, like classical vapor diffusion hanging drop and its variants (such as sitting drop), in space- and LB (Langmuir-Blodgett)-based crystallization procedures. Using MD, we show here that the optimal protein crystallization techniques prove to be significantly those based on the LB nanotemplate and on space when compared to the classical vapour diffusion hanging drop and its variants.


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