Home About us Contact
|
Home About us Contact | ||
|
|
||
Putative Interactions (putative + interaction)
Selected AbstractsRapid Identification of a Putative Interaction between ,2 -Adrenoreceptor Agonists and ATF4 using a Chemical Genomics ApproachCHEMMEDCHEM, Issue 5 2008Sweta Chemical genomics. We have uncovered a specific interaction between the ,2 -adrenoreceptor agonist salbutamol and the DNA binding region of transcription factor ATF4 in a chemical genomics approach using phage display combined with photoimmobilisation. [source] Do G protein-coupled receptors expressed in human lingual epithelium interact with HPV11?JOURNAL OF MEDICAL VIROLOGY, Issue 10 2007Lukasz Durzy Abstract Human papillomaviruses infect epithelia but little is known about the nature of cell surface receptors interacting with the viral particles. It has been proposed that glycosaminoglycans and integrins may be involved in the attachment process. In the present study, the putative interactions of virus-like particles of human papillomavirus type 11 (HPV11), which present a tropism for nasopharyngeal epithelia, with olfactory and taste receptors expressed in the human lingual epithelium were studied. The L1 protein of HPV11 was produced in insect cells. The presence of L1 virus-like particles was analyzed by ELISA using monoclonal antibodies specific for full-size particles and by electron microscopy. Using immunofluorescence, it was observed that virus-like particles interacted with taste buds from murine tongue, with the tagged human olfactory receptor hJCG5 expressed in HEK-293 but not with the tagged taste receptor hT2R4. This therefore suggests that hJCG5 may be involved in the adsorption process of HPV11 to lingual epithelium serving as a so-called "adsorption-adhesive molecule." J. Med. Virol. 79:1545,1554, 2007. © Wiley-Liss, Inc. [source] Melanocortin ligands: 30 years of structure,activity relationship (SAR) studiesMEDICINAL RESEARCH REVIEWS, Issue 3 2004Jerry Ryan Holder Abstract The challenge of peptide and peptidomimetic research is the development of methods and techniques to improve the biological properties of native peptides and to convert peptide ligands into non-peptide compounds. Improved biological properties of peptides includes enhancement of stability, potency, and receptor selectivity, for both in vivo and in vitro applications. The design of a ligand with specific activity and desired biological properties is a complex task, and, to accomplish this objective, knowledge about putative interactions between a ligand and the corresponding receptor will be valuable. This includes interactions for both the binding and signal transduction processes. Structure,activity relationship (SAR) studies involve systematic modification of a lead peptide and are designed to provide insight into potential interactions involved in the formation of the ligand,receptor complex. It is desirable to have knowledge about both favorable and unfavorable processes that may occur in putative ligand,receptor interactions that result in either receptor stimulation or inhibition. Herein, we discuss various SAR studies that have involved melanocortin peptides over three decades and the information these studies have provided to the melanocortin field. © 2004 Wiley Periodicals, Inc. Med Res Rev, 24, No. 3, 325,356, 2004 [source] Host,pathogen protein interactions predicted by comparative modelingPROTEIN SCIENCE, Issue 12 2007Fred P. Davis Abstract Pathogens have evolved numerous strategies to infect their hosts, while hosts have evolved immune responses and other defenses to these foreign challenges. The vast majority of host,pathogen interactions involve protein,protein recognition, yet our current understanding of these interactions is limited. Here, we present and apply a computational whole-genome protocol that generates testable predictions of host,pathogen protein interactions. The protocol first scans the host and pathogen genomes for proteins with similarity to known protein complexes, then assesses these putative interactions, using structure if available, and, finally, filters the remaining interactions using biological context, such as the stage-specific expression of pathogen proteins and tissue expression of host proteins. The technique was applied to 10 pathogens, including species of Mycobacterium, apicomplexa, and kinetoplastida, responsible for "neglected" human diseases. The method was assessed by (1) comparison to a set of known host,pathogen interactions, (2) comparison to gene expression and essentiality data describing host and pathogen genes involved in infection, and (3) analysis of the functional properties of the human proteins predicted to interact with pathogen proteins, demonstrating an enrichment for functionally relevant host,pathogen interactions. We present several specific predictions that warrant experimental follow-up, including interactions from previously characterized mechanisms, such as cytoadhesion and protease inhibition, as well as suspected interactions in hypothesized networks, such as apoptotic pathways. Our computational method provides a means to mine whole-genome data and is complementary to experimental efforts in elucidating networks of host,pathogen protein interactions. [source] | ||||||||||