Predicting class II MHC-Peptide binding:a kernel based approach using similarity scores

Background - Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epitopes. For Class II MHC alleles, the binding groove is open at both ends, causing ambiguity in the positional alignment between the groove and peptide, as well as creating uncertainty as to what parts of the peptide interact with the MHC. Moreover, the antigenic peptides have variable lengths, making naive modelling methods difficult to apply. This paper introduces a kernel method that can handle variable length peptides effectively by quantifying similarities between peptide sequences and integrating these into the kernel. Results - The kernel approach presented here shows increased prediction accuracy with a significantly higher number of true positives and negatives on multiple MHC class II alleles, when testing data sets from MHCPEP [1], MCHBN [2], and MHCBench [3]. Evaluation by cross validation, when segregating binders and non-binders, produced an average of 0.824 AROC for the MHCBench data sets (up from 0.756), and an average of 0.96 AROC for multiple alleles of the MHCPEP database. Conclusion - The method improves performance over existing state-of-the-art methods of MHC class II peptide binding predictions by using a custom, knowledge-based representation of peptides. Similarity scores, in contrast to a fixed-length, pocket-specific representation of amino acids, provide a flexible and powerful way of modelling MHC binding, and can easily be applied to other dynamic sequence problems.

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).

Two years survival rate of Class II ART restorations in primary molars using two ways to avoid saliva contamination

AIM To compare the survival rates of Class II Atraumatic Restorative Treatment (ART) restorations placed in primary molars using cotton rolls or rubber dam as isolation methods. METHODS A total of 232 children, 6-7 years old, both genders, were selected having one primary molar with proximal dentine lesion. The children were randomly assigned into two groups: control group with Class II ART restoration made using cotton rolls and experimental group using rubber dam. The restorations were evaluated by eight calibrated evaluators (Kappa > 0.8) after 6, 12, 18 and 24 months. RESULTS A total of 48 (20.7%) children were considered dropout, after 24 months. The cumulative survival rate after 6, 12, 18 and 24 months was 61.4%, 39.0%, 29.1% and 18.0%, respectively for the control group, and 64.1%, 55.1%, 40.1% and 32.1%, respectively for the rubber dam group. The log rank test for censored data showed no statistical significant difference between the groups (P = 0.07). The univariate Cox Regression showed no statistical significant difference after adjusting for independent variables (P > 0.05). CONCLUSION Both groups had similar survival rates, and after 2 years, the use of rubber dam does not increase the success of Class II ART restorations significantly.

Yellow perch population assessment in southwestern Lake Michigan, including the identification of factors that determine yellow perch year-class strength April 1, 2001 - March 31, 2002

Issued June 2002 F-123-R-8; NOTE: Two different reports numbered 02/06 were issued from the CAE.

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and the Identification Factors that Determine Yellow Perch Year-Class Strength April 1, 1996 - March 31, 1997

F-123-R; issued June 1, 1997; two different reports were issued from the Center for Aquatic Ecology with report number 1997 (9)

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including the Identification Factors that Determine Yellow Perch Year-Class Strength April 1, 2000 - March 31, 2001

issued June 2001

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Identification of Factors that Determine Yellow Perch Year-Class Strength April 1, 2002 - March 31, 2003

INHS Technical Report prepared for unspecified recipient

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including the Identification of Factors that Determine Yellow Perch Year-Class Strength April 1, 2003 - March 31, 2004

Annual Report to Division of Fisheries, Illinois Department of Natural Resources. F-123-R-10

Yellow Perch population assessment in Southwestern Lake Michigan, including evaluation of sampling techniques and identification of the factors that determine Yellow Perch year-class strength April 1, 2004 - March 31, 2005

ID: 8528; Annual Report to Division of Fisheries, Illinois Department of Natural Resources; F-123-R-11

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and Identification of factors that Determine Yellow Perch Year-Class Strength April 1, 2005 - March 31, 2006

Annual Report, Federal Aid Project F-123-R-12, April 1, 2005 - March 31, 2006

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and the Identification Factors that Determine Yellow Perch Year-Class Strength April 1,1997 - March 31, 1998

ID: 8827; issued June 1, 1998

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and the identification Factors that Determine Yellow Perch Year-Class Strength April 1, 1998 - March 31, 1999

ID: 8863; issued June 1, 1999

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and Identification of the Factors that Determine Yellow Perch Year-Class Strength April 1, 2007 – March 31, 2008

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: F-123 R-14

Yellow perch population assessment in southwestern Lake Michigan, including evaluation of sampling techniques and identification of the factors that determine yellow perch year-class strength April 1, 2006 – March 31, 2007

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: F-123 R-13

Yellow Perch Population Assessment in Southwestern Lake Michigan, Including Evaluation of Sampling Techniques and Identification of the Factors that Determine Yellow Perch Year-Class Strength April 1, 2008 – June 30, 2009

Division of Fisheries, Illinois Department of Natural Resources Grant/Contract No: Federal Aid Project F-123 R-15