Title |
Structural Basis for Recognition of Cellular and Viral Ligands by NK Cell Receptors
|
---|---|
Published in |
Frontiers in immunology, March 2014
|
DOI | 10.3389/fimmu.2014.00123 |
Pubmed ID | |
Authors |
Yili Li, Roy A. Mariuzza |
Abstract |
Natural killer (NK) cells are key components of innate immune responses to tumors and viral infections. NK cell function is regulated by NK cell receptors that recognize both cellular and viral ligands, including major histocompatibility complex (MHC), MHC-like, and non-MHC molecules. These receptors include Ly49s, killer immunoglobulin-like receptors, leukocyte immunoglobulin-like receptors, and NKG2A/CD94, which bind MHC class I (MHC-I) molecules, and NKG2D, which binds MHC-I paralogs such as the stress-induced proteins MICA and ULBP. In addition, certain viruses have evolved MHC-like immunoevasins, such as UL18 and m157 from cytomegalovirus, that act as decoy ligands for NK receptors. A growing number of NK receptor-ligand interaction pairs involving non-MHC molecules have also been identified, including NKp30-B7-H6, killer cell lectin-like receptor G1-cadherin, and NKp80-AICL. Here, we describe crystal structures determined to date of NK cell receptors bound to MHC, MHC-related, and non-MHC ligands. Collectively, these structures reveal the diverse solutions that NK receptors have developed to recognize these molecules, thereby enabling the regulation of NK cytolytic activity by both host and viral ligands. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 20% |
Unknown | 4 | 80% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 2% |
Netherlands | 1 | 1% |
Montenegro | 1 | 1% |
Germany | 1 | 1% |
Brazil | 1 | 1% |
Austria | 1 | 1% |
Czechia | 1 | 1% |
Mexico | 1 | 1% |
Unknown | 91 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 23 | 23% |
Student > Ph. D. Student | 17 | 17% |
Student > Master | 16 | 16% |
Student > Bachelor | 11 | 11% |
Other | 8 | 8% |
Other | 13 | 13% |
Unknown | 12 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 28 | 28% |
Biochemistry, Genetics and Molecular Biology | 20 | 20% |
Immunology and Microbiology | 16 | 16% |
Medicine and Dentistry | 10 | 10% |
Engineering | 5 | 5% |
Other | 7 | 7% |
Unknown | 14 | 14% |