ArticleIEEE transactions on nanobioscience2016
Optimizing Associative Experimental Design for Protein Crystallization Screening.
Article in IEEE transactions on nanobioscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Article
- Ionic Liquids as Protein Crystallization Additives.Crystals · 2021Article
- Design of Experiments As a Tool for Optimization in Recombinant Protein Biotechnology: From Constructs to Crystals.Molecular biotechnology · 2019Review
- Feature analysis for classification of trace fluorescent labeled protein crystallization images.BioData mining · 2017Article
- Schema Matching and Data Integration with Consistent Naming on Protein Crystallization Screens.IEEE/ACM transactions on computational biology and bioinformaticsArticle
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3 authors.
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Abstract
The goal of protein crystallization screening is the determination of the main factors of importance to crystallizing the protein under investigation. One of the major issues about determining these factors is that screening is often expanded to many hundreds or thousands of conditions to maximize combinatorial chemical space coverage for maximizing the chances of a successful (crystalline) outcome. In this paper, we propose an experimental design method called "Associative Experimental Design (AED)" and an optimization method includes eliminating prohibited combinations and prioritizing reagents based on AED analysis of results from protein crystallization experiments. AED generates candidate cocktails based on these initial screening results. These results are analyzed to determine those screening factors in chemical space that are most likely to lead to higher scoring outcomes, crystals. We have tested AED on three proteins derived from the hyperthermophile Thermococcus thioreducens, and we applied an optimization method to these proteins. Our AED method generated novel cocktails (count provided in parentheses) leading to crystals for three proteins as follows: Nucleoside diphosphate kinase (4), HAD superfamily hydrolase (2), Nucleoside kinase (1). After getting promising results, we have tested our optimization method on four different proteins. The AED method with optimization yielded 4, 3, and 20 crystalline conditions for holo Human Transferrin, archaeal exosome protein, and Nucleoside diphosphate kinase, respectively.
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