Emerging strengths in Asia Pacific bioinformatics

The 2008 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation set up in 1998, was organized as the 7th International Conference on Bioinformatics (InCoB), jointly with the Bioinformatics and Systems Biology in Taiwan (BIT 2008) Conference, Oct. 20–23, 2008 at Taipei, Taiwan. Besides bringing together scientists from the field of bioinformatics in this region, InCoB is actively involving researchers from the area of systems biology, to facilitate greater synergy between these two groups. Marking the 10th Anniversary of APBioNet, this InCoB 2008 meeting followed on from a series of successful annual events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea), New Delhi (India) and Hong Kong. Additionally, tutorials and the Workshop on Education in Bioinformatics and Computational Biology (WEBCB) immediately prior to the 20th Federation of Asian and Oceanian Biochemists and Molecular Biologists (FAOBMB) Taipei Conference provided ample opportunity for inducting mainstream biochemists and molecular biologists from the region into a greater level of awareness of the importance of bioinformatics in their craft. In this editorial, we provide a brief overview of the peer-reviewed manuscripts accepted for publication herein, grouped into thematic areas. As the regional research expertise in bioinformatics matures, the papers fall into thematic areas, illustrating the specific contributions made by APBioNet to global bioinformatics efforts

PeptX: Using Genetic Algorithms to optimize peptides for MHC binding

<p>Abstract</p> <p>Background</p> <p>The binding between the major histocompatibility complex and the presented peptide is an indispensable prerequisite for the adaptive immune response. There is a plethora of different <it>in silico </it>techniques for the prediction of the peptide binding affinity to major histocompatibility complexes. Most studies screen a set of peptides for promising candidates to predict possible T cell epitopes. In this study we ask the question vice versa: Which peptides do have highest binding affinities to a given major histocompatibility complex according to certain <it>in silico </it>scoring functions?</p> <p>Results</p> <p>Since a full screening of all possible peptides is not feasible in reasonable runtime, we introduce a heuristic approach. We developed a framework for Genetic Algorithms to optimize peptides for the binding to major histocompatibility complexes. In an extensive benchmark we tested various operator combinations. We found that (1) selection operators have a strong influence on the convergence of the population while recombination operators have minor influence and (2) that five different binding prediction methods lead to five different sets of "optimal" peptides for the same major histocompatibility complex. The consensus peptides were experimentally verified as high affinity binders.</p> <p>Conclusion</p> <p>We provide a generalized framework to calculate sets of high affinity binders based on different previously published scoring functions in reasonable runtime. Furthermore we give insight into the different behaviours of operators and scoring functions of the Genetic Algorithm.</p

Manipulation of Costimulatory Molecules by Intracellular Pathogens: Veni, Vidi, Vici!!

Some of the most successful pathogens of human, such as Mycobacterium tuberculosis (Mtb), HIV, and Leishmania donovani not only establish chronic infections but also remain a grave global threat. These pathogens have developed innovative strategies to evade immune responses such as antigenic shift and drift, interference with antigen processing/presentation, subversion of phagocytosis, induction of immune regulatory pathways, and manipulation of the costimulatory molecules. Costimulatory molecules expressed on the surface of various cells play a decisive role in the initiation and sustenance of immunity. Exploitation of the “code of conduct” of costimulation pathways provides evolutionary incentive to the pathogens and thereby abates the functioning of the immune system. Here we review how Mtb, HIV, Leishmania sp., and other pathogens manipulate costimulatory molecules to establish chronic infection. Impairment by pathogens in the signaling events delivered by costimulatory molecules may be responsible for defective T-cell responses; consequently organisms grow unhindered in the host cells. This review summarizes the convergent devices that pathogens employ to tune and tame the immune system using costimulatory molecules. Studying host-pathogen interaction in context with costimulatory signals may unveil the molecular mechanism that will help in understanding the survival/death of the pathogens. We emphasize that the very same pathways can potentially be exploited to develop immunotherapeutic strategies to eliminate intracellular pathogens

Inhibition Mechanism and Model of an Angiotensin I-Converting Enzyme (ACE)-Inhibitory Hexapeptide from Yeast (Saccharomyces cerevisiae)

Angiotensin I-converting enzyme (ACE) has an important function in blood pressure regulation. ACE-inhibitory peptides can lower blood pressure by inhibiting ACE activity. Based on the sequence of an ACE-inhibitory hexapeptide (TPTQQS) purified from yeast, enzyme kinetics experiments, isothermal titration calorimetry (ITC), and a docking simulation were performed. The hexapeptide was found to inhibit ACE in a non-competitive manner, as supported by the structural model. The hexapeptide bound to ACE via interactions of the N-terminal Thr1, Thr3, and Gln4 residues with the residues on the lid structure of ACE, and the C-terminal Ser6 attracted the zinc ion, which is vital for ACE catalysis. The displacement of the zinc ion from the active site resulted in the inhibition of ACE activity. The structural model based on the docking simulation was supported by experiments in which the peptide was modified. This study provides a new inhibitory mechanism of ACE by a peptide which broads our knowledge for drug designing against enzyme targets

Antiviral propierties of 5,5'-dithiobis-2-nitrobenzoic acid and bacitracin against T-tropic human immunodeficiency virus type 1

<p>Abstract</p> <p>Bacitracin and the membrane-impermeant thiol reagent 5,5'-dithiobis-2-nitrobenzoic acid (DTNB) are agents known to inhibit protein disulfide isomerase (PDI), a cell-surface protein critical in HIV-1 entry therefore they are fusion inhibitors (FI). Here we investigated the possibility that Bacitracin and or DTNB might have other antiviral activities besides FI. By means of residual activity assays, we found that both compounds showed antiviral activity only to viruses T-tropic HIV-1 strain. Cell-based fusion assays showed inhibition on HeLa-CD4-LTR-β-gal (CD4) and HL2/3 cells treated with Bacitracin, and DTNB with the latest compound we observed fusion inhibition on both cells but strikingly in HL2/3 cells (expressing Env) indicating a possible activity on both, the cell membrane and the viral envelope. A time-of-addition experiment showed that both compounds act on HIV entry inhibition but DTNB also acts at late stages of the viral cycle. Lastly, we also found evidence of long-lasting host cell protection <it>in vitro </it>by DTNB, an important pharmacodynamic parameter for a topical microbicide against virus infection, hours after the extracellular drug was removed; this protection was not rendered by Bacitracin. These drugs proved to be leading compounds for further studies against HIV showing antiviral characteristics of interest.</p

Footprints of antigen processing boost MHC class II natural ligand predictions

Abstract Background Major histocompatibility complex class II (MHC-II) molecules present peptide fragments to T cells for immune recognition. Current predictors for peptide to MHC-II binding are trained on binding affinity data, generated in vitro and therefore lacking information about antigen processing. Methods We generate prediction models of peptide to MHC-II binding trained with naturally eluted ligands derived from mass spectrometry in addition to peptide binding affinity data sets. Results We show that integrated prediction models incorporate identifiable rules of antigen processing. In fact, we observed detectable signals of protease cleavage at defined positions of the ligands. We also hypothesize a role of the length of the terminal ligand protrusions for trimming the peptide to the MHC presented ligand. Conclusions The results of integrating binding affinity and eluted ligand data in a combined model demonstrate improved performance for the prediction of MHC-II ligands and T cell epitopes and foreshadow a new generation of improved peptide to MHC-II prediction tools accounting for the plurality of factors that determine natural presentation of antigens