Peptidic recognition features

Tsigelny, I., Grant, B. D., Taylor, S. S., Ten Eyck, L. F. Catalytic subunit of cAMP-dependent protein kinase Electrostatic features and peptide recognition. Biopolymers 39 (1996) 353-365. 

Conjugates of nano tubes and peptides also feature some beneficial properties for diagnostics. For example, peptides thus immobilized are bound more easily to ELISA plates, and they are better accessible for the recognition process. Carbon... 

The small size of hevein (43 residues), and the ease of its availability by biochemical purification or methods of peptide synthesis make this domain an excellent model system for the study of carbohydrate recognition by proteins. Herein, and taking the hevein domain as a model, we focus on the study of those molecular-recognition features relevant for the interactions between carbohydrates and proteins. We detail all of the techniques that are instrumental for tackling this problem, and how these can strategically be combined in an efficient manner. Particular emphasis is placed on the acquisition and analysis of data at atomic resolution (by NMR and/or X-ray ), and how these structural data relate with thermodynamic and kinetic information in reaching an understanding of the forces and interactions that play decisive roles in the interactions between carbohydrates and proteins. 

Tendamistat is a 74-residue protein that inhibits a-amylase with a of 0.2 nM. It has been suggested that a surface loop formed by Trp-18, Arg-19, and Tyr-20 is a key recognition feature in the interaction of tendamistat with the enzyme. In the crystal structure of tendamistat,Trp-18, Arg-19 and Tyr-20 are at the i+ to i-t-3 positions of a somewhat distorted type 1 p-turn. ITie NMR structure of tendamistati is is similar to the X-ray in terms of peptide backbone conformation. However, the solution structure indicates considerable flexibility in the amino acid side chains. Preliminary information from the... 

Bartlett and co-workers at the University of California at Berkeley targeted the development of a peptide mimetic scaffold that would present the key molecular recognition features of the three amino acid binding loop to a-amylase. The cyclic peptides cyclo(D-Pro-Phe-Ala-Trp-Arg-Tyr) and cyclo(D-Pro-Phe-Ser-Trp-Arg-Tyr) were found to exhibit fC values of 14 and 32 pM, respectively, against a-amylase. The objective was then to locate a suitable mimic for the -turn region for incorporation into these cyclic peptides. 

To maintain the spatial orientation of the pharmacophore elements while not extending beyond the geometric boundaries of THR itself, researchers" at Hoffmann-La Roche selected the 1,3,5-ds-trisubstituted cyclohexane framework to replace the peptide backbone. This structure was then substituted with the appropriate recognition features to yield Ro 24-9975 (87). Superposition of... 

Most researchers find it useful to employ three-dimensional graphics representations of peptides and proposed mimetics in their studies. This rudimentary level of molecular modeling allows for manipulation and geometric comparison of complex molecular structures. Using standard molecular bonding parameters, this level of analysis can test whether the proposed mimetic has the possibility of adopting the desired conformation, so that it can present important molecular recognition features in the appropriate orientation. 

Various techniques have been explored for the purposes of array-based differentiation of the more complex analyte targets peptides and proteins. Peptide recognition commonly incorporates into its array design features that primarily focus on the binding of a few specific amino acids. For example, the amino acids histidine, cysteine, and methionine are all known to bind to various transition metals. This enables the sensing of portions of peptides that contain these specific amino acids. 

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