Premium
BLAST ing away preconceptions in crystallization trials
Author(s) -
Abrahams Gabriel Jan,
Newman Janet
Publication year - 2019
Publication title -
acta crystallographica section f
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.572
H-Index - 37
ISSN - 2053-230X
DOI - 10.1107/s2053230x19000141
Subject(s) - crystallization , sequence (biology) , similarity (geometry) , protein crystallization , set (abstract data type) , computer science , computational biology , biological system , data mining , chemistry , biology , artificial intelligence , biochemistry , organic chemistry , image (mathematics) , programming language
Crystallization is in many cases a critical step for solving the three‐dimensional structure of a protein molecule. Determining which set of chemicals to use in the initial screen is typically agnostic of the protein under investigation; however, crystallization efficiency could potentially be improved if this were not the case. Previous work has assumed that sequence similarity may provide useful information about appropriate crystallization cocktails; however, the authors are not aware of any quantitative verification of this assumption. This research investigates whether, given current information, one can detect any correlation between sequence similarity and crystallization cocktails. BLAST was used to quantitate the similarity between protein sequences in the Protein Data Bank, and this was compared with three estimations of the chemical similarities of the respective crystallization cocktails. No correlation was detected between proteins of similar (but not identical) sequence and their crystallization cocktails, suggesting that methods of determining screens based on this assumption are unlikely to result in screens that are better than those currently in use.