Rosetta Pepspec
Rosetta Pepspec - Related Videos
11:31
Metabolic Labeling of Leucine Rich Repeat Kinases 1 and 2 with Radioactive Phosphate
0 Views •
Cited by 5 •
2013
Leucine rich repeat kinases 1 and 2 (LRRK1 and LRRK2) are multidomain proteins which encode both GTPase and kinase domains and which are phosphorylated in cells. Here, we present a protocol to label LRRK1 and LRRK2 in cells with 32P orthophosphate, thereby providing a means to measure their overall cellular phophorylation levels.
05:52
An In Vitro Flow Investigation of the Effect of Stromal Cells on Leukocyte Recruitment
0 Views •
2025
The video demonstrates a method for investigating the impact of stromal cells on leukocyte recruitment. In a parallel plate flow chamber model, pro-inflammatory cytokines induce the expression of adhesion receptors by endothelial cells, facilitating neutrophil recruitment and migration. The cross-talk between stromal cells and endothelial cells diminishes neutrophil recruitment to the endothelial cells.
11:30
Analyzing the Effects of Stromal Cells on the Recruitment of Leukocytes from Flow
0 Views •
Cited by 28 •
2015
The ability of inflamed endothelium to recruit leukocytes from flow is regulated by mesenchymal stromal cells. We describe two in vitro models incorporating primary human cells that can be used to assess neutrophil recruitment from flow and examine the role that mesenchymal stromal cells play in regulating this process.
07:47
Shallow Water (Paddling) Variants of Water Maze Tests in Mice
0 Views •
Cited by 22 •
2013
Mice can swim, but many strains appear to find this activity stressful. To overcome this problem mazes have been devised where escape from shallow water is used to motivate behaviour. These have been demonstrated to support learning at least as good as the traditional and widely used Morris water maze.
09:33
A Methodological Approach to Non-invasive Assessments of Vascular Function and Morphology
0 Views •
Cited by 16 •
2015
The present article describes the methodological considerations for several non-invasive assessments of vascular function and morphology that are commonly used in medical research to assess different stages of atherosclerosis.
FAQs
Rosetta Pepspec evaluates a peptide sequence by placing candidate side-chain conformations onto a specified backbone and applying Rosetta energy functions at the protein–peptide interface. Monte Carlo sampling explores alternative residue arrangements, while the calculation considers packing, electrostatic interactions, and overall conformational compatibility. This connects sequence redesign with structural fit and helps identify peptides compatible with the modeled backbone.
Side-chain rotamer libraries supply alternative conformations for redesigned residues, giving the calculation structural choices to evaluate at the interface. Monte Carlo sampling then explores combinations of those choices rather than relying on a single arrangement. Together, these components let Rosetta Pepspec examine how sequence changes affect packing, electrostatic interactions, and compatibility with the specified backbone.
Packing, electrostatic interactions, and conformational compatibility describe different aspects of the same protein–peptide interface. Packing addresses how redesigned side chains fit together, electrostatics captures charge-related contributions, and compatibility asks whether the sequence remains suitable for the specified backbone. Considering them together provides a broader computational assessment than focusing on one interface property when selecting sequences for further study.
A researcher first specifies the peptide backbone and target-protein context. Rosetta Pepspec then redesigns peptide residues using side-chain rotamer libraries and Monte Carlo sampling, evaluates alternatives with Rosetta energy functions, and examines interface compatibility. The resulting sequence possibilities can be narrowed before synthesis, making computational screening an upstream step that supports, rather than replaces, experimental testing.
Researchers can use Rosetta Pepspec when they want to investigate molecular recognition or design peptides for a target protein. In biochemistry, it supports structure-guided design and peptide engineering by connecting a modeled protein–peptide interface to candidate sequences. Its practical value is especially apparent before synthesis, when reducing the number of sequences considered can focus subsequent experimental testing.
The protocol produces candidate peptide sequences judged compatible with a specified backbone and potentially able to bind a target protein. These computational results do not establish binding experimentally; instead, they provide a focused set of designs for testing. The output can support studies of protein interactions, molecular recognition, and structure-guided peptide engineering while keeping experimental validation in view.