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Soluble protein expression is a key requirement for biochemical and structural biology approaches to study biological systems in vitro. Production of sufficient quantities may not always be achievable if proteins are poorly soluble which is frequently determined by physico-chemical parameters such as intrinsic disorder. It is well known that discrete protein domains often have a greater likelihood of high-level soluble expression and crystallizability. Determination of such protein domain boundaries can be challenging for novel proteins. Here, we outline the application of bioinformatics tools to facilitate the prediction of potential protein domain boundaries, which can then be used in designing expression construct boundaries for parallelized screening in a range of heterologous expression systems.

Original publication





Publication Date





11 - 31


Alignment, BLAST, Bioinformatics, Domain, Hidden Markov Model (HMM), PSIPRED, Protein expression, Protein solubility, Protein structure, Secondary structure, Amino Acid Sequence, Animals, Computational Biology, Crystallization, Databases, Protein, Humans, Markov Chains, Models, Biological, Models, Molecular, Protein Conformation, Protein Domains, Proteins, Software, Solubility