Crystine: fibrous biomolecular material from protein crystals cross-linked in a specific geometry

Identification and Characterization of Bioactive Compounds Targeting UropathogenicEscherichia colifrom Sanjin Tablets

Sanjin Tablets are completely natural preparation with significant efficacy in treating urinary tract infection. To identify the bioactive compounds from Sanjin Tablets, we separated components capable of binding to the soluble proteins of uropathogenicEscherichia coli(UPEC) by affinity binding and characterized their identities using liquid chromatography-mass spectrometry (LC-MS) analysis. Our study discovered eight compounds withE. coliprotein-binding capabilities, and all these compounds were tracked back to the original natural ingredients of Sanjin Tablets. These compounds presented essentially no antibacteria activity, indicating that they affect UPEC by means other than directly killing the cells. Further molecular modeling analysis predicted molecular targets for these compounds and mapped the residues potentially involved in compound-target interactions. All the predicted targets turned out to be critical proteins regulating the metabolisms ofE. coli, suggesting that these compounds may affect metabolic pathways in UPEC and inhibit pathogenesis. These data will benefit future design of drugs with higher efficacy and specificity on targeting pathogenic bacteria.

SIMS: a hybrid method for rapid conformational analysis

Proteins are at the root of many biological functions, often performing complex tasks as the result of large changes in their structure. Describing the exact details of these conformational changes, however, remains a central challenge for computational biology due the enormous computational requirements of the problem. This has engendered the development of a rich variety of useful methods designed to answer specific questions at different levels of spatial, temporal, and energetic resolution. These methods fall largely into two classes: physically accurate, but computationally demanding methods and fast, approximate methods. We introduce here a new hybrid modeling tool, the Structured Intuitive Move Selector (sims), designed to bridge the divide between these two classes, while allowing the benefits of both to be seamlessly integrated into a single framework. This is achieved by applying a modern motion planning algorithm, borrowed from the field of robotics, in tandem with a well-established protein modeling library. sims can combine precise energy calculations with approximate or specialized conformational sampling routines to produce rapid, yet accurate, analysis of the large-scale conformational variability of protein systems. Several key advancements are shown, including the abstract use of generically defined moves (conformational sampling methods) and an expansive probabilistic conformational exploration. We present three example problems that sims is applied to and demonstrate a rapid solution for each. These include the automatic determination of “active” residues for the hinge-based system Cyanovirin-N, exploring conformational changes involving long-range coordinated motion between non-sequential residues in Ribose-Binding Protein, and the rapid discovery of a transient conformational state of Maltose-Binding Protein, previously only determined by Molecular Dynamics. For all cases we provide energetic validations using well-established energy fields, demonstrating this framework as a fast and accurate tool for the analysis of a wide range of protein flexibility problems.

Bioengineered flagella protein nanotubes with cysteine loops: self-assembly and manipulation in an optical trap

An E. coli flagellin protein, termed FliTrx, was investigated for use as a novel form of self-assembling protein nanotube. This protein was genetically engineered to display constrained peptide loops with a series of different thiol, cationic, anionic, and imidazole functional groups. "Cys-loop" thiol variants consisting of 6 and 12 cysteine residues were isolated in the form of disulfide-linked nanotube bundles, a novel nanomaterial. Bundles were characterized by fluorescence microscopy, transmission electron microscopy, and optical trapping.