Er basic residues), one with chymotrypsin-like activity (cleavagePage 1 of(page number
Er basic residues), one with chymotrypsin-like activity (cleavagePage 1 of(page number not PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28499442 for citation purposes)BMC Bioinformatics 2006, 7:http://www.biomedcentral.com/1471-2105/7/after hydrophobic residues), and another with peptidylglutamyl-peptide hydrolytic activity (cleavage after acidic residues) [6-8]. In addition, in vertebrates there are three -interferon-inducible subunits that replace the constitutive subunits [9] and assemble the immunoproteasome. The immunoproteasomes have an altered hierarchy of proteosomal cleavage, enhancing cleavage after basic and hydrophobic residues and inhibiting cleavage after acidic residues [10,11]. This is in accord with the amino acid preferences for binding to MHC class I molecules at the C terminus [12]. TAP is an ATP-dependent peptide transport protein that belongs to the ATP-binding cassette (ABC) family of transporters. This family transports across membranes a wide range of molecules, from small sugars to large polypeptides [13]. There are two TAP proteins (TAP-1 and TAP-2) which form a transmembrane (TM) heterodimer. Both proteins encode one hydrophobic TM domain and one ATP-binding domain [14]. Extant experimental studies have shown that TAP prefers peptides of eight or more amino acids with hydrophobic or basic residues at the carboxy terminus [15,16]. TAP-mediated antigen presentation is important not only for cytosolic antigens but also for most epitopes within membrane/secretory proteins [17]. The TAP-dependent pathway is the principal processing route for peptides binding HLA-A1, HLA-A3, HLA-A11, HLA-A24, HLA-B15 and HLA-B27 [18-20]. Some peptides are able to access the ER via other, TAPindependent mechanisms. Examples of alleles exhibiting only partial dependence on TAP include HLA-A2, HLAA23, HLA-B7 and HLA-B8 [21-24]. Proteins of the MHC are both polygenic (i.e. there are more than one MHC class I and MHC class II genes) and polymorphic (i.e. there are many alleles of each gene) [25]. Each class of MHC has several loci: HLA-A, HLA-B and HLA-C for class I and HLA-DR, HLA-DQ and HLA-DP for class II. MHC alleles may differ by as many as 30 amino acid PX-478 web substitutions, most of them are found within the binding site and are critical for the specificity of peptide binding and therefore for T cell recognition [26-28]. Such an uncommon degree of polymorphism implies a selective pressure to create and PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28404814 maintain it. Different polymorphic MHC alleles have different peptide specificities: each allele binds peptides exhibiting particular sequence patterns. Successful T cell epitope prediction has always challenged bioinformatics. A wide range of computer-based algorithms have been developed to predict T-cell epitopes [2931]. Initially, methods for direct T cell epitope prediction were developed based on amphipathicy [32], epitope pattern motifs [33], or on a combination there of [34]. These direct epitope prediction methods have relatively lowaccuracy [35]. Later, a broad spectrum of indirect predictive methods have been developed to predict MHC binders instead of T cell epitopes [reviewed in ref. [36]]. They are based on motif patterns [37,38], motif profiles [39,40], quantitative matrices (QM) [41-43], neural networks (ANN) [44-47], free energy scoring functions (Fresno) [48], MHC-peptide threading [49], 3D-QSAR studies [50-52] and support vector machines (SVM) [53,54]. In general, methods of this type have out-performed older methods. In the meantime, methods for the prediction of proteasome.