Structure-based computational methods are popular tools for designing proteins and interactions between proteins because they provide the necessary insight and details required for rational engineering. Here, we first argue that large-scale databases of fragments contain a discrete but complete set of building blocks that can be used to design structures. We show that these structural alphabets can be saturated to provide conformational ensembles that sample the native structure space around energetic minima. Second, we show that catalogs of interaction patterns hold the key to overcome the lack of scaffolds when computationally designing protein interactions. Finally, we illustrate the power of database-driven computational protein design methods by recent successful applications and discuss what challenges remain to push this field forward.
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http://dx.doi.org/10.1016/j.sbi.2011.05.002 | DOI Listing |
J Vis Exp
January 2025
State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University;
The extent of functional sequences within the human genome is a pivotal yet debated topic in biology. Although high-throughput reverse genetic screens have made strides in exploring this, they often limit their scope to known genomic elements and may introduce non-specific effects. This underscores the urgent need for novel functional genomics tools that enable a deeper, unbiased understanding of genome functionality.
View Article and Find Full Text PDFJ Anim Sci
January 2025
Department of Animal Science, South Dakota State University, Brookings, SD, 57007, USA.
The utilization of exogenous fiber-degrading enzymes in commercial swine diets is a strategy to increase the nutrient and energy density of poorly digestible ingredients. In a prior set of studies, dietary multienzyme blend (MEblend) supplementation increased the apparent total tract digestibility (ATTD) of nutrients, non-starch polysaccharides, and energy in complete high-fibrous gestation diets by 6% when fed to gestating sows. The current study aimed to determine the effects of MEblend (containing xylanase, β-glucanase, cellulase, amylase, protease, pectinase, and invertase activities) supplementation on ATTD of energy and nutrients of individual feedstuffs commonly used in gestating sow diets across major pork-producing regions worldwide, which differ in their fibrous components.
View Article and Find Full Text PDFJ Vis Exp
January 2025
Department of Biomedical Engineering, Washington University in St. Louis; Department of Obstetrics & Gynecology, Washington University in St. Louis;
For noninvasive light-based physiological monitoring, optimal wavelengths of individual tissue components can be identified using absorption spectroscopy. However, because of the lack of sensitivity of hardware at longer wavelengths, absorption spectroscopy has typically been applied for wavelengths in the visible (VIS) and near-infrared (NIR) range from 400 to 1,000 nm. Hardware advancements in the short-wave infrared (SWIR) range have enabled investigators to explore wavelengths in the ~1,000 nm to 3,000 nm range in which fall characteristic absorption peaks for lipid, protein, and water.
View Article and Find Full Text PDFArch Microbiol
January 2025
Department of Microbiology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, Serdang, Selangor, 43400, Malaysia.
Bacteriophages produce endolysins at the end of the lytic cycle, which are crucial for lysing the host cells and releasing virion progeny. This lytic feature allows endolysins to act as effective antimicrobial alternatives when applied exogenously. Staphylococcal endolysins typically possess a modular structure with one or two enzymatically active N-terminal domains (EADs) and a C-terminal cell wall binding domain (CBD).
View Article and Find Full Text PDFJ Virol
January 2025
MRC-University of Glasgow Centre for Virus Research, Glasgow, Scotland, United Kingdom.
The unprecedented sequencing efforts during the COVID-19 pandemic paved the way for genomic surveillance to become a powerful tool for monitoring the evolution of circulating viruses. Herein, we discuss how a state-of-the-art artificial intelligence approach called protein language models (pLMs) can be used for effectively analyzing pathogen genomic data. We highlight examples of pLMs applied to predicting viral properties and evolution and lay out a framework for integrating pLMs into genomic surveillance pipelines.
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