New 111In labeling of IgG: 111In-oxine mediated chelation

Current methods of ¹¹¹In chelate conjugation labeling of antibodies expose the protein to pH 5–6 during ¹¹¹In chelation. These conditions could be detrimental if the antibody is acid labile. We have successfully labeled human IgG via the cyclic anhydride of DPTA and ¹¹¹In-oxyquinoline(oxine). Chelation was achieved at pH 6.9–8.4 and was complete within 1 min at room temperature. The chelation was sensitive to trace metal contamination on labware and in some reagents (including commercial ¹¹¹In-oxine).     

PLANET-SNP pipeline: PLants based ANnotation and Establishment of True SNP pipeline

Acute prediction of SNPs (Single Nucleotide Polymorphisms) from high throughput sequencing data is a challenging problem, having potential to explore possible variation within plants species. For the extraction of profitable information from bulk of data, machine learning (ML) could lead to development of accurate model based on the learning of prior information. We performed state of art, in-depth learning on six different plant species. Comparative evaluation of five different algorithms showed that Random Forest substantially outperformed in selection of potential SNPs, with markedly improved prediction accuracy via 10-fold cross validation technique and integrated in system known as PLANET-SNP. We present the accurate method to extract the potential SNPs with user specific customizable parameters. It will facilitate the identification of efficient and functional SNPs in most easy and intuitive way. PLANET-SNP pipeline is very flexible in terms of data input and output formats. PLANET-SNP Pipeline is available at http://www.ncgd.nbri.res.in/PLANET-SNP-Pipeline.aspx     

Antifungals: what's in the pipeline

The therapeutic landscape for mycotic infections is shifting. New generation azoles that are active against clinically relevant, drug-resistant fungal pathogens have improved bioavailability, half-lives and safety profiles. Acylated cyclic peptide inhibitors of beta(1,3)glucan synthesis with origins as fungal metabolites provide an alternative and highly-selective mode of action, targeting cell-wall biogenesis in important pathogens such as Candida and Aspergillus species. The development, in each structural class, of compounds that have advanced to late-stage clinical trials is summarized in this review.     

PseudoPipe: an automated pseudogene identification pipeline

MOTIVATION: Mammalian genomes contain many 'genomic fossils' i.e. pseudogenes. These are disabled copies of functional genes that have been retained in the genome by gene duplication or retrotransposition events. Pseudogenes are important resources in understanding the evolutionary history of genes and genomes. RESULTS: We have developed a homology-based computational pipeline ('PseudoPipe') that can search a mammalian genome and identify pseudogene sequences in a comprehensive and consistent manner. The key steps in the pipeline involve using BLAST to rapidly cross-reference potential "parent" proteins against the intergenic regions of the genome and then processing the resulting "raw hits" -- i.e. eliminating redundant ones, clustering together neighbors, and associating and aligning clusters with a unique parent. Finally, pseudogenes are classified based on a combination of criteria including homology, intron-exon structure, and existence of stop codons and frameshifts.     

The antibiotic R&D pipeline: an update

There is an urgent need for new antibacterials to target emerging multidrug-resistant bacteria. The need for such agents is rising while the efforts in antibacterial research have declined dramatically in the past few decades with the result of only four compounds belonging to new chemical classes being approved for clinical use. The main reasons that led to this critical situation are shortly described. A renewed interest in the research of new effective antimicrobials is nonetheless delivering compounds deriving mainly from modification of existing drugs, yet new chemical classes are appearing. Because many of these activities have started relatively recently, we should expect a long period before new antibiotics are added to the medical armamentarium.     

MethylCoder: software pipeline for bisulfite-treated sequences

MOTIVATION: MethylCoder is a software program that generates per-base methylation data given a set of bisulfite-treated reads. It provides the option to use either of two existing short-read aligners, each with different strengths. It accounts for soft-masked alignments and overlapping paired-end reads. MethylCoder outputs data in text and binary formats in addition to the final alignment in SAM format, so that common high-throughput sequencing tools can be used on the resulting output. It is more flexible than existing software and competitive in terms of speed and memory use. AVAILABILITY: MethylCoder requires only a python interpreter and a C compiler to run. Extensive documentation and the full source code are available under the MIT license at: https://github.com/brentp/methylcode. CONTACT: bpederse@gmail.com.