Identification of best protein crystallization methods by molecular dynamics (MD)

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.