抗体应用

The inhibition of bacterial ribosomal subunit formation is a novel target for translational inhibitors. Inhibition of subunit biogenesis has been shown to be equivalent to the inhibition of protein biosynthesis for many antibiotics. This chapter describes three methods for exami ...

In Escherichia coli, the molecular chaperone HSP70 (DnaK) is necessary for 30S and 50S ribosomal subunit assembly at temperatures above 37�C. Inhibitors of DnaK should therefore hinder ribosome biogenesis, in addition to all of the other DnaK-dependent cellular functions. An easily te ...

While bacterial protein synthesis is the target of about half of the known antibiotics, the great structural-functional complexity of the translational machinery still offers remarkable opportunities for identifying novel and specific inhibitors of unexploited targets. We ...

The formation of peptide bonds is the central chemical reaction during protein synthesis and is catalyzed by the peptidyl transferase center residing in the large ribosomal subunit. This active site is composed of universally conserved rRNA nucleosides. The peptidyl transferase ce ...

The human leukocyte antigen (HLA) complex is located within the 6p21.3 region on the short arm of human chromosome 6 and contains more than 220 genes of diverse function. Many of the genes encode proteins of the immune system and include many highly polymorphic HLA genes. The naming of new HLA genes and all ...

This chapter describes searching and mapping tools of MHCBN database, which is a curated database. It comprises over 23,000 peptide sequences, whose binding affinity with major histocompatibility complex (MHC) or transporter associated with antigen processing (TAP) molecules h ...

One of the major challenges in the field of subunit vaccine design is to identify the antigenic regions in an antigen, which can activate B cell. These antigenic regions are called B-cell epitopes. In this chapter, we describe how to use Bcipep, which is a database of experimentally determined linear B ...

The human leukocyte antigen (HLA) alleles are extremely polymorphic among ethnic population, and the peptide-binding specificity varies for different alleles in a combinatorial manner. However, it has been suggested that majority of alleles can be covered within few HLA supertypes, ...

Haptens are small molecules that are usually nonimmunogenic unless coupled to some carrier proteins. The generation of anti-hapten antibodies is important for the development of immunodiagnostics and therapeutics. Recently, our group has developed a database called HaptenDB, ...

Identification of peptides that can bind to major histocompatibility complex (MHC) molecules is important for anticipation of T-cell epitopes and for the design of epitope-based vaccines. Population coverage of epitope vaccines is, however, compromised by the extreme polymorph ...

Human leukocyte antigen (HLA) molecules involved in immune function by binding to short peptides (8–20 residues) have different sequences in different individuals belonging to distinct ethnic population. Hence, the peptide-binding function of HLA alleles is specific. Class I HLA a ...

Biological experiments often produce enormous amount of data, which are usually analyzed by data clustering. Cluster analysis refers to statistical methods that are used to assign data with similar properties into several smaller, more meaningful groups. Two commonly used cluster ...

Prediction of peptide binding to major histocompatibility complex (MHC) molecules is a basis for anticipating T-cell epitopes. Peptides that bind to a given MHC molecule are related by sequence similarity. Therefore, a position-specific scoring matrix (PSSM)—also known as profile ...

The machine learning techniques are playing a vital role in the field of immunoinformatics. In the past, a number of methods have been developed for predicting major histocompatibility complex (MHC)-binding peptides using machine learning techniques. These methods allow predict ...

Identifying epitopes that elicit a major histocompatibility complex (MHC)-restricted T-cell response is critical for designing vaccines for infectious diseases and cancers. We have applied two artificial intelligence approaches to build models for predicting T-cell epit ...

The ligand–receptor interaction between some peptidomimetic inhibitors and a class II major histocompatibility complex (MHC)–peptide presenting molecule, the HLA-DR4 receptor, can be modeled using some 3D quantitative structure-activity relationship (QSAR) methods s ...

The challenge of predicting which peptide sequences bind to which major histocompatibility complex (MHC) molecules has been met with various computational techniques. Scoring matrices, hidden Markov models, and artificial neural networks are examples of algorithms that have b ...

The use of major histocompatibility complex (MHC) class I binding peptides for immunotherapeutic purposes has shown promising results in recent years. The identification of such peptides mostly starts with predicting MHC-binding peptides, given a protein of interest. An accurate ...

The binding between peptide epitopes and major histocompatibility complex (MHC) proteins is a major event in the cellular immune response. Accurate prediction of the binding between short peptides and class I or class II MHC molecules is an important task in immunoinformatics. SVRMHC wh ...

Short peptides binding to specific human leukocyte antigen (HLA) alleles elicit immune response. These candidate peptides have potential utility in peptide vaccine design and development. The binding of peptides to allele-specific HLA molecule is estimated using competitive b ...