Virtual screening of GPCRs: An <Emphasis Type="Italic">in silico</Emphasis> chemogenomics approach

Background  

The G-protein coupled receptor (GPCR) superfamily is currently the largest class of therapeutic targets. In silico prediction of interactions between GPCRs and small molecules in the transmembrane ligand-binding site is therefore a crucial step in the drug discovery process, which remains a daunting task due to the difficulty to characterize the 3D structure of most GPCRs, and to the limited amount of known ligands for some members of the superfamily. Chemogenomics, which attempts to characterize interactions between all members of a target class and all small molecules simultaneously, has recently been proposed as an interesting alternative to traditional docking or ligand-based virtual screening strategies.     

Chromato-panning: an efficient new mode of identifying suitable ligands from phage display libraries

Background  

Phage Display technology is a well established technique for high throughput screening of affinity ligands. Here we describe a new compact chromato-panning procedure for selection of suitable binders from a phage peptide display library.     

A novel prokaryotic vector for identification and selection of recombinants: Direct use of the vector for expression studies in <Emphasis Type="Italic">E. coli</Emphasis>

Background  

The selection of bacterial recombinants that harbour a desired insert, has been a key factor in molecular cloning and a series of screening procedures need to be performed for selection of clones carrying the genes of interest. The conventional cloning techniques are reported to have problems such as screening high number of colonies, generation of false positives, setting up of control ligation mix with vector alone etc.     

DOVIS: an implementation for high-throughput virtual screening using AutoDock

Background  

Molecular-docking-based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated. In addition to the selection of a sound docking strategy with appropriate scoring functions, another technical challenge is to in silico screen millions of compounds in a reasonable time. To meet this challenge, it is necessary to use high performance computing (HPC) platforms and techniques. However, the development of an integrated HPC system that makes efficient use of its elements is not trivial.     

Scoring functions and enrichment: a case study on Hsp90

Background  

The need for fast and accurate scoring functions has been driven by the increased use of in silico virtual screening twinned with high-throughput screening as a method to rapidly identify potential candidates in the early stages of drug development. We examine the ability of some the most common scoring functions (GOLD, ChemScore, DOCK, PMF, BLEEP and Consensus) to discriminate correctly and efficiently between active and non-active compounds among a library of ~3,600 diverse decoy compounds in a virtual screening experiment against heat shock protein 90 (Hsp90).     

SVRMHC prediction server for MHC-binding peptides

Background  

The binding between antigenic peptides (epitopes) and the MHC molecule is a key step in the cellular immune response. Accurate in silico prediction of epitope-MHC binding affinity can greatly expedite epitope screening by reducing costs and experimental effort.     

NERVE: New Enhanced Reverse Vaccinology Environment

Background  

Since a milestone work on Neisseria meningitidis B, Reverse Vaccinology has strongly enhanced the identification of vaccine candidates by replacing several experimental tasks using in silico prediction steps. These steps have allowed scientists to face the selection of antigens from the predicted proteome of pathogens, for which cell culture is difficult or impossible, saving time and money. However, this good example of bioinformatics-driven immunology can be further developed by improving in silico steps and implementing biologist-friendly tools.     

Raw starch–degrading α‐amylase from Bacillus aquimaris MKSC 6.2: isolation and expression of the gene,bioinformatics and biochemical characterization of the recombinant enzyme

Aims

The aims were to isolate a raw starch–degrading α‐amylase gene baqA from Bacillus aquimaris MKSC 6.2, and to characterize the gene product through in silico study and its expression in Escherichia coli.

Methods and Results

A 1539 complete open reading frame of a starch–degrading α‐amylase gene baqA from B. aquimaris MKSC 6·2 has been determined by employing PCR and inverse PCR techniques. Bioinformatics analysis revealed that B. aquimaris MKSC 6.2 α‐amylase (BaqA) has no starch‐binding domain, and together with a few putative α‐amylases from bacilli may establish a novel GH13 subfamily most closely related to GH13_1. Two consecutive tryptophans (Trp201 and Trp202, BaqA numbering) were identified as a sequence fingerprint of this novel GH13 subfamily. Escherichia coli cells produced the recombinant BaqA protein as inclusion bodies. The refolded recombinant BaqA protein degraded raw cassava and corn starches, but exhibited no activity with soluble starch.

Conclusions

A novel raw starch–degrading B. aquimaris MKSC 6.2 α‐amylase BaqA is proposed to be a member of new GH13 subfamily.

Significance and Impact of the Study

This study has contributed to the overall knowledge and understanding of amylolytic enzymes that are able to bind and digest raw starch directly.     

A genetic screen for modifiers of <Emphasis Type="Italic">Drosophila</Emphasis> caspase Dcp-1 reveals caspase involvement in autophagy and novel caspase-related genes

Background  

Caspases are cysteine proteases with essential functions in the apoptotic pathway; their proteolytic activity toward various substrates is associated with the morphological changes of cells. Recent reports have described non-apoptotic functions of caspases, including autophagy. In this report, we searched for novel modifiers of the phenotype of Dcp-1 gain-of-function (GF) animals by screening promoter element- inserted Drosophila melanogaster lines (EP lines).     

Coherent pipeline for biomarker discovery using mass spectrometry and bioinformatics

Background  

Robust biomarkers are needed to improve microbial identification and diagnostics. Proteomics methods based on mass spectrometry can be used for the discovery of novel biomarkers through their high sensitivity and specificity. However, there has been a lack of a coherent pipeline connecting biomarker discovery with established approaches for evaluation and validation. We propose such a pipeline that uses in silico methods for refined biomarker discovery and confirmation.     

Experimental annotation of the human pathogen <Emphasis Type="Italic">Candida albicans</Emphasis> coding and noncoding transcribed regions using high-resolution tiling arrays

Background  

Compared to other model organisms and despite the clinical relevance of the pathogenic yeast Candida albicans, no comprehensive analysis has been done to provide experimental support of its in silico-based genome annotation.     

Genome-scale metabolic reconstruction and <Emphasis Type="Italic">in silico</Emphasis> analysis of methylotrophic yeast <Emphasis Type="Italic">Pichia pastoris</Emphasis> for strain improvement

Background  

Pichia pastoris has been recognized as an effective host for recombinant protein production. A number of studies have been reported for improving this expression system. However, its physiology and cellular metabolism still remained largely uncharacterized. Thus, it is highly desirable to establish a systems biotechnological framework, in which a comprehensive in silico model of P. pastoris can be employed together with high throughput experimental data analysis, for better understanding of the methylotrophic yeast's metabolism.     

Using in silico models to simulate dual perturbation experiments: procedure development and interpretation of outcomes

Background  

A growing number of realistic in silico models of metabolic functions are being formulated and can serve as 'dry lab' platforms to prototype and simulate experiments before they are performed. For example, dual perturbation experiments that vary both genetic and environmental parameters can readily be simulated in silico. Genetic and environmental perturbations were applied to a cell-scale model of the human erythrocyte and subsequently investigated.     

Representation of target-bound drugs by computed conformers: implications for conformational libraries

Background  

The increasing number of known protein structures provides valuable information about pharmaceutical targets. Drug binding sites are identifiable and suitable lead compounds can be proposed. The flexibility of ligands is a critical point for the selection of potential drugs. Since computed 3D structures of millions of compounds are available, the knowledge of their binding conformations would be a great benefit for the development of efficient screening methods.     

Evaluation of an <Emphasis Type="Italic">in silico</Emphasis> predicted specific and immunogenic antigen from the OmcB protein for the serodiagnosis of <Emphasis Type="Italic">Chlamydia trachomatis</Emphasis> infections

Background  

The OmcB protein is one of the most immunogenic proteins in C. trachomatis and C. pneumoniae infections. This protein is highly conserved leading to serum cross reactivity between the various chlamydial species. Since previous studies based on recombinant proteins failed to identify a species specific immune response against the OmcB protein, this study evaluated an in silico predicted specific and immunogenic antigen from the OmcB protein for the serodiagnosis of C. trachomatis infections.     

GuiTope: an application for mapping random-sequence peptides to protein sequences

Background  

Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task.     

An <Emphasis Type="Italic">in silico</Emphasis> analysis of the mitochondrial protein import apparatus of plants

Background  

An in silico analysis of the mitochondrial protein import apparatus from a variety of species; including Chlamydomonas reinhardtii, Chlorella variabilis, Ectocarpus siliculosus, Cyanidioschyzon merolae, Physcomitrella patens, Selaginella moellendorffii, Picea glauca, Oryza sativa and Arabidopsis thaliana was undertaken to determine if components differed within and between plant and non-plant species.     

Extraction of consensus protein patterns in regions containing non-proline <Emphasis Type="Italic">cis</Emphasis> peptide bonds and their functional assessment

Background  

In peptides and proteins, only a small percentile of peptide bonds adopts the cis configuration. Especially in the case of amide peptide bonds, the amount of cis conformations is quite limited thus hampering systematic studies, until recently. However, lately the emerging population of databases with more 3D structures of proteins has produced a considerable number of sequences containing non-proline cis formations (cis-nonPro).