Protein Variant Library
Protein Variant Library - Related Videos
10:58
Combinatorial Synthesis of and High-throughput Protein Release from Polymer Film and Nanoparticle Libraries
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Cited by 7 •
2012
This method describes the combinatorial synthesis of biodegradable polyanhydride film and nanoparticle libraries and the high-throughput detection of protein release from these libraries.
11:36
A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing
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Cited by 6 •
2016
We present a protocol for the functional assessment of comprehensive single-site saturation mutagenesis libraries of proteins utilizing high-throughput sequencing. Importantly, this approach uses orthogonal primer pairs to multiplex library construction and sequencing. Representative results using TEM-1 β-lactamase selected at a clinically relevant dosage of ampicillin are provided.
07:44
An Electrochemiluminescence-Based Assay for MeCP2 Protein Variants
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Cited by 2 •
2020
The electrochemiluminescence immunoassay (ECLIA) is a novel approach for quantitative detection of endogenous and exogenously applied MeCP2 protein variants, which produces highly quantitative, accurate and reproducible measurements with low intra- and inter-assay error over a wide working range. Here, the protocol for the MeCP2-ECLIA in a 96-well format is described.
02:30
Histone Variants at the Centromere
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2020
Histone variants are the histone proteins with structural and sequence variations. These variants may be regarded as “mutant” forms that replace their canonical histone counterparts in the nucleosomes. Specific post-translational modifications on the histone variants enable further chromatin complexity and regulate tissue-specific gene expression. The most common histone variants are from histone H2A, H2B, and linker histone H1 families. However, several variants of histone H3 variants are also...
14:06
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Cited by 10 •
2012
Pooled DNA sequencing is a fast and cost-effective strategy to detect rare variants associated with complex phenotypes in large cohorts. Here we describe the computational analysis of pooled, next-generation sequencing of 32 cancer-related genes using the SPLINTER software package. This method is scalable, and applicable to any phenotype of interest.
FAQs
The choice of library-generation strategy determines what kinds of sequence changes can be explored. Targeted mutagenesis focuses variation on selected positions, random mutagenesis broadens sequence changes without restricting them to predefined sites, and DNA recombination combines sequence material. These approaches create different search spaces, allowing researchers to pursue focused improvements or broader discovery.
Comparing variants connects sequence differences with changes in protein behavior. This analysis can reveal sequence-function relationships and show which changes improve catalytic activity, stability, binding affinity, or specificity. The resulting information helps researchers understand how sequence variation affects performance and guides subsequent efforts to develop proteins with more suitable properties.
Host cells provide the biological setting in which library sequences can be expressed as proteins. Introducing the variants into cells converts genetic diversity into protein products that can be evaluated for functional differences. This step is essential because sequence comparisons alone do not show whether a particular change improves the desired protein property.
A typical workflow begins by generating sequence diversity through targeted mutagenesis, random mutagenesis, or DNA recombination. The resulting sequences are introduced into host cells for protein expression, followed by screening or selection. Comparing the evaluated variants then identifies sequence changes associated with improved activity, stability, binding affinity, specificity, or another intended function.
Evaluation can identify variants with improved catalytic activity, greater stability, stronger binding affinity, or altered specificity. Beyond finding a better-performing sequence, the comparison provides evidence about how particular sequence changes influence function. These outcomes support both practical protein optimization and a broader understanding of sequence-function relationships in related proteins.
This approach is useful when researchers need to improve or tailor protein performance systematically. Supported applications include enzyme optimization, biosensor development, therapeutic protein engineering, and the creation of biological systems with selected properties. In each case, comparing variants helps connect genetic changes to functional outcomes and supports the choice of more suitable protein designs.