Pandjassarame Kangueane

Editorial NeuroAIDS review

NeuroAIDS is a disease that incorporates both infectious and degenerative pathophysiologic pathways. It has a known cause, has several animal models, and is under investigation and treatment using multiple avenues, in vivo and in vitro [1–7]. Select highlights from the spectrum of NeuroAIDS research predominantly related to human immunodeficiency virus-1 clade B (HIV-1B) are reviewed below.

Identification of hot spot residues at protein-protein interface

It is known that binding free energy of protein-protein interaction is mainly contributed by hot spot (high energy) interface residues. Here, we investigate the characteristics of hot spots by examining inter-atomic sidechain-sidechain interactions using a dataset of 296 alanine-mutated interface residues. Results show that hot spots participate in strong and energetically favorable sidechain-sidechain interactions. Subsequently, we describe a novel, yet simple ‘hot spot’ prediction model with an accuracy that is similar to many available approaches. The model is also shown to efficiently distinguish specific protein-protein interactions from non-specific interactions.

A framework to sub-type HLA supertypes.

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, where different members of a supertype bind similar peptides, yet exhibiting distinct repertoires. Since the overlap between different members of a supertype appears to be extensive, it is crucial to develop a framework for grouping alleles into supertypes just from sequence information. In this report, we define sub supertypes, where members show functional overlap with identical repertoire, and describe a strategy to group HLA-A, B and C alleles into different categories of sub supertypes. The strategy grouped 47% of 295 A alleles, 44% of 540 B alleles and 35% of 156 C alleles to just 36, 71 and 18 groups, respectively. The grouping is moderately validated using available binding data. However, the validation is limited due to lack of binding data. Hence, the data presented in this article serve as a framework to test specific functional overlap between alleles. The grouping of HLA alleles into different categories of sub supertypes has profound use in the understanding of antigenic peptide selection, degeneration and discrimination during T-cell mediated immune response. A complete knowledge of this phenomenon finds utility in epitope design for the development of HLA based vaccines and immuno-therapeutics.

Protein subunit interfaces: heterodimers versus homodimers

Protein dimers are either homodimers (complexation of identical monomers) or heterodimers (complexation of non-identical monomers). These dimers are common in catalysis and regulation. However, the molecular principles of protein dimer interactions are difficult to understand mainly due to the geometrical and chemical characteristics of proteins. Nonetheless, the principles of protein dimer interactions are often studied using a dataset of 3D structural complexes determined by X-ray crystallography. A number of physical and chemical properties govern protein dimer interactions. Yet, a handful of such properties are known to dominate protein dimer interfaces. Here, we discuss the differences between homodimer and heterodimer interfaces using a selected set of interface properties.

MPID: MHC-Peptide Interaction Database for sequence-structure-function information on peptides binding to MHC molecules

SUMMARY Binding of short antigenic peptides to Major histocompatibility complex (MHC) proteins is the first step in T-cell mediated immune response. To understand the structural principles governing MHC-specific peptide recognition and binding, we have developed the MHC-Peptide Interaction Database (MPID), containing sequence-structure-function information. MPID (version 1.2) contains curated x-ray crystallographic data on 86 MHC peptide complexes, with precomputed interaction parameters (solvent accessibility, hydrogen bonds, gap volume and gap index). A user-friendly web interface and query tools will facilitate the development of predictive algorithms for MHC-peptide binding from a structural viewpoint. AVAILABILITY Freely accessible from http://surya.bic.nus.edu.sg/mpid.

Compression of Functional Space in HLA-A Sequence Diversity

The major histocompatibility complex (MHC) is highly polymorphic and more than 1500 human MHC alleles are known to date. These alleles do not bind to a given peptide with identical affinity. Although MHC alleles are functionally related, it is difficult to quantify the functional variation between them. Three-dimensional structures of known MHC-peptide (MHCp) complexes suggest that specific peptide residues bind selectively to functional pockets in the binding groove. From a set of known MHCp structures we identified 21 critical polymorphic functional residue positions (CPFRP) that significantly reduced functional pocket variability to just 189 among 212 HLA-A alleles. Interestingly 101 HLA-A alleles clustered into 29 clusters such that the six functional pockets formed by the CPFRPs are identical within the cluster.

Computational prediction of SEG (single exon gene) function in humans.

Human genes are often interrupted by non-coding, intragenic sequences called introns. Hence, the gene sequence is divided into exons (coding segments) and introns (non-coding segments). Consequently, a majority of them are multi exon genes (MEG). However, a considerable amount of single exon genes (SEG) are present in the human genome (approximately 12%). This amount is sizeable and it is important to probe their molecular function and cellular role. Hence, we performed a genome wide functional assignment to 3750 SEG sequences using PFAM (protein family database), PROSITE (database of biologically meaningful signatures or motifs) and SUPERFAMILY (a library covering all proteins of known 3 dimensional structure). PFAM assigned 13% SEG to trans-membrane receptor genes of the G-protein coupled receptor (GPCR) family and showed that a majority of SEG proteins have DNA binding function. PROSITE identified 336 unique motif types in them and this accounts for 25% of all known patterns, with a majority having PHOSPHORYLATION and ACETYLATION signals. SUPERFAMILY assigned 33% SEG to the membrane all alpha (proteins containing alpha helix structural elements according to SCOP (structural classification of proteins) definition). Functional assignment of SEG proteins at multiple levels (sequence signals, sequence families, 3D structures) using PFAM, PROSITE and SUPERFAMILY is envisioned to suggest their selective and predominant molecular function in cellular systems. Their function as DNA binding, phosphorylating, acetylating and house-keeping agents is intriguing. The analysis also showed evidence of SEG expression and retro-transposition. However, this information is inadequate to draw concerted conclusion on the prevalent role played by these proteins in cellular biology. A complete understanding of SEG function will help to explore their role in cellular environment. The derived datasets from these analyses are available at http://sege.ntu.edu.sg/wester/intronless/human/.

T-Epitope Designer: A HLA-peptide binding prediction server.

The current challenge in synthetic vaccine design is the development of a methodology to identify and test short antigen peptides as potential T-cell epitopes. Recently, we described a HLA-peptide binding model (using structural properties) capable of predicting peptides binding to any HLA allele. Consequently, we have developed a web server named T-EPITOPE DESIGNER to facilitate HLA-peptide binding prediction. The prediction server is based on a model that defines peptide binding pockets using information gleaned from X-ray crystal structures of HLA-peptide complexes, followed by the estimation of peptide binding to binding pockets. Thus, the prediction server enables the calculation of peptide binding to HLA alleles. This model is superior to many existing methods because of its potential application to any given HLA allele whose sequence is clearly defined. The web server finds potential application in T cell epitope vaccine design. Availability http://www.bioinformation.net/ted/

Towards the MHC-peptide combinatorics

The exponentially increased sequence information on major histocompatibility complex (MHC) alleles points to the existence of a high degree of polymorphism within them. To understand the functional consequences of MHC alleles, 36 nonredundant MHC-peptide complexes in the protein data bank (PDB) were examined. Induced fit molecular recognition patterns such as those in MHC-peptide complexes are governed by numerous rules. The 36 complexes were clustered into 19 subgroups based on allele specificity and peptide length. The subgroups were further analyzed for identifying common features in MHC-peptide binding pattern. The four major observations made during the investigation were: (1) the positional preference of peptide residues defined by percentage burial upon complex formation is shown for all the 19 subgroups and the burial profiles within entries in a given subgroup are found to be similar; (2) in class I specific 8- and 9-mer peptides, the fourth residue is consistently solvent exposed, however this observation is not consistent in class I specific 10-mer peptides; (3) an anchor-shift in positional preference is observed towards the C terminal as the peptide length increases in class II specific peptides; and (4) peptide backbone atoms are proportionately dominant at the MHC-peptide interface.

A report on single exon genes (SEG) in eukaryotes.

Single exon genes (SEG) are archetypical of prokaryotes. Hence, their presence in intron-rich, multi-cellular eukaryotic genomes is perplexing. Consequently, a study on SEG origin and evolution is important. Towards this goal, we took the first initiative of identifying and counting SEG in nine completely sequenced eukaryotic organisms--four of which are unicellular (E. cuniculi, S. cerevisiae, S. pombe, P. falciparum) and five of which are multi-cellular (C. elegans, A. thaliana, D. melanogaster, M. musculus, H. sapiens). This exercise enabled us to compare their proportion in unicellular and multi-cellular genomes. The comparison suggests that the SEG fraction decreases with gene count (r = -0.80) and increases with gene density (r = 0.88) in these genomes. We also examined the distribution patterns of their protein lengths in different genomes.