Computational crystallization.
Arch Biochem Biophys
; 602: 12-20, 2016 Jul 15.
Article
em En
| MEDLINE
| ID: mdl-26792536
ABSTRACT
Crystallization is a key step in macromolecular structure determination by crystallography. While a robust theoretical treatment of the process is available, due to the complexity of the system, the experimental process is still largely one of trial and error. In this article, efforts in the field are discussed together with a theoretical underpinning using a solubility phase diagram. Prior knowledge has been used to develop tools that computationally predict the crystallization outcome and define mutational approaches that enhance the likelihood of crystallization. For the most part these tools are based on binary outcomes (crystal or no crystal), and the full information contained in an assembly of crystallization screening experiments is lost. The potential of this additional information is illustrated by examples where new biological knowledge can be obtained and where a target can be sub-categorized to predict which class of reagents provides the crystallization driving force. Computational analysis of crystallization requires complete and correctly formatted data. While massive crystallization screening efforts are under way, the data available from many of these studies are sparse. The potential for this data and the steps needed to realize this potential are discussed.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Proteínas
/
Modelos Moleculares
/
Cristalização
/
Cristalografia
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Arch Biochem Biophys
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Estados Unidos