Protein Crystallizability.
Obtaining diffracting quality crystals remains a major challenge in protein structure research. We summarize and compare methods for selecting the best protein targets for crystallization, construct optimization and crystallization condition design. Target selection methods are divided into algorithms predicting the chance of successful progression through all stages of structural determination (from cloning to solving the structure) and those focusing only on the crystallization step. We tried to highlight pros and cons of different approaches examining the following aspects: data size, redundancy and representativeness, overfitting during model construction, and results evaluation. In summary, although in recent years progress was made and several sequence properties were reported to be relevant for crystallization, the successful prediction of protein crystallization behavior and selection of corresponding crystallization conditions continue to challenge structural researchers.
Biomedical Center Munich, Ludwig-Maximilians-University, Großhaderner Strasse 9, 82152, Martinsried, Germany. pawelsm@gmail.com.
Pawel
P
Smialowski
Biomedical Center Munich, Ludwig-Maximilians-University, Großhaderner Strasse 9, 82152, Martinsried, Germany.
Philip
P
Wong
D000465:Algorithms; D003460:Crystallization; D018360:Crystallography, X-Ray; D030562:Databases, Protein; D023281:Genomics / Q000379:methods*; D009682:Magnetic Resonance Spectroscopy; D008854:Microscopy, Electron; D011506:Proteins / Q000737:chemistry*; D040901:Proteomics
D011506:Proteins
Construct optimization; Crystallization conditions; Improving crystallization; Protein crystallization