In summary, these findings strongly suggest that local structural properties influence antigen processing and/or the accessibility of peptides to the MHC class II molecule.Īdvances in criticality predictions for EBR- II We also tried to integrate N- and O-glycosylation in our prediction methods but this additional information was found not to improve prediction performance. This combined prediction method was shown to significantly outperform the state-of-the-art MHC class II peptide binding prediction method when used to identify MHC class II ligands. We next exploited this observation to derive an improved prediction method for MHC class II ligands by integrating prediction of MHC- peptide binding with prediction of surface exposure and protein secondary structure. We demonstrated that MHC class II ligands are significantly more exposed and have significantly more coil content than other peptides in the same protein with similar predicted binding affinity.

A large set of SYFPEITHI MHC class II ligands covering more than 20 different HLA-DR molecules was analyzed in terms of their secondary structure and surface exposure characteristics in the context of the native structure of the corresponding source protein. Here, we perform one such large-scale analysis. Little work has been performed characterizing structural properties of MHC class II ligands. Furthermore, only a few HLA-DR alleles have been characterized with a sufficient number of peptides (100-200 peptides per allele to derive accurate description of their binding motif. Prediction of MHC class II ligands is complicated by the open binding cleft of the MHC class II molecule, allowing binding of peptides extending out of the binding groove. Structural properties of MHC class II ligands, implications for the prediction of MHC class II epitopes.ĭirectory of Open Access Journals (Sweden)įull Text Available Major Histocompatibility class II (MHC- II molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from this compartment. Although both the APACHE II and SAPS II systems can be used to measure performance in the neurosurgical ICU setting, the accuracy of APACHE II in hemorrhagic stroke patients and SAPS II in ischemic stroke patients was superior. The GCS and NIHSS were inferior in predicting mortality in both patient groups. The ROC curve showed a slightly better prediction of mortality for APACHE II in hemorrhagic stroke patients and SAPS II in ischemic stroke patients. The calibration curve was close to the line of perfect prediction. The mean GCS and NIHSS scores were 9.43 and 21.63, respectively. The observed mortality was 26.3%, whereas APACHE II and SAPS II-predicted mortalities were 35.12% and 35.34%, respectively. Overall 498 patients were included in this study.

APACHE II and SAPS II-predicted mortalities were compared using a calibration curve, the Hosmer-Lemeshow goodness-of-fit test, and the receiver operating characteristic (ROC) curve, and the results were compared with the GCS and NIHSS.

Between January 2011 and December 2012, ischemic or hemorrhagic stroke patients admitted to the ICU were included in the study. We also conducted a comparative study of accuracy for predicting hemorrhagic and ischemic stroke mortality. We studied the applicability of the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) in patients admitted to the intensive care unit (ICU) with acute stroke and compared the results with the Glasgow Coma Scale (GCS) and National Institutes of Health Stroke Scale (NIHSS). Moon, Byeong Hoo Park, Sang Kyu Jang, Dong Kyu Jang, Kyoung Sool Kim, Jong Tae Han, Yong Min Use of APACHE II and SAPS II to predict mortality for hemorrhagic and ischemic stroke patients.

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