Bioinformatics and drug discovery

Bioinformatics involves both the automatic processing of large amounts of existing data and the creation of new types of information resource. Both will be required if the data are to be transformed into information and used to help in the discovery of drugs.     

Bioinformatics approaches for new drug discovery: a review

Prolonged antibiotic therapy for the bacterial infections has resulted in high levels of antibiotic resistance. Initially, bacteria are susceptible to the antibiotics, but can gradually develop resistance. Treating such drug-resistant bacteria remains difficult or even impossible. Hence, there is a need to develop effective drugs against bacterial pathogens. The drug discovery process is time-consuming, expensive and laborious. The traditionally available drug discovery process initiates with the identification of target as well as the most promising drug molecule, followed by the optimization of this, in-vitro, in-vivo and in pre-clinical studies to decide whether the compound has the potential to be developed as a drug molecule. Drug discovery, drug development and commercialization are complicated processes. To overcome some of these problems, there are many computational tools available for new drug discovery, which could be cost effective and less time-consuming. In-silico approaches can reduce the number of potential compounds from hundreds of thousands to the tens of thousands which could be studied for drug discovery and this results in savings of time, money and human resources. Our review is on the various computational methods employed in new drug discovery processes.     

Open discovery: An integrated live Linux platform of Bioinformatics tools

Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery ‐ a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD.     

Bioinformatics approaches in the discovery and understanding of reproduction-related biomarkers

The emerging field of bioinformatics in proteomics is introducing new algorithms in order to handle large and heterogeneous datasets and improve the knowledge-discovery process. Management systems, software construction and application, database population and leverage, as well as computed prediction, have crafted bioinformatics into a valuable tool for basic research. Human reproduction is one of many fields proteomics has been extensively studying over the last decade, accumulating complex experimental data at a rate far exceeding the ability to assimilate them. Transformation of the rapidly proliferating quantities of experimental information into a usable form in order to facilitate their analysis is a challenging task. On this track, bioinformatics, an essential part of proteomics research, aspires to amend inquiries into a better manipulated, a better handled and a better understood form so as to enhance existing knowledge expansion.     

Bioinformatics and data-intensive scientific discovery in the beginning of the 21st century

This article is a summary of the bioinformatics issues and challenges of data-intensive science as discussed in the NSF-funded Data-Intensive Science (DIS) workshop in Seattle, September 19-20, 2010.     

Calcium signalling: IP3 rises again...and again

Recent results indicate that 'regulators of G-protein signalling' may contribute to the generation of receptor-specific patterns of cytosolic Ca2+ oscillations by associating with specific receptors, accelerating G-protein inactivation and responding to changes in cytosolic Ca2+.     

Hearing it again and again: on-line subcortical plasticity in humans

Background

Human brainstem activity is sensitive to local sound statistics, as reflected in an enhanced response in repetitive compared to pseudo-random stimulus conditions [1]. Here we probed the short-term time course of this enhancement using a paradigm that assessed how the local sound statistics (i.e., repetition within a five-note melody) interact with more global statistics (i.e., repetition of the melody).

Methodology/Principal Findings

To test the hypothesis that subcortical repetition enhancement builds over time, we recorded auditory brainstem responses in young adults to a five-note melody containing a repeated note, and monitored how the response changed over the course of 1.5 hrs. By comparing response amplitudes over time, we found a robust time-dependent enhancement to the locally repeating note that was superimposed on a weaker enhancement of the globally repeating pattern.

Conclusions/Significance

We provide the first demonstration of on-line subcortical plasticity in humans. This complements previous findings that experience-dependent subcortical plasticity can occur on a number of time scales, including life-long experiences with music and language, and short-term auditory training. Our results suggest that the incoming stimulus stream is constantly being monitored, even when the stimulus is physically invariant and attention is directed elsewhere, to augment the neural response to the most statistically salient features of the ongoing stimulus stream. These real-time transformations, which may subserve humans'' strong disposition for grouping auditory objects, likely reflect a mix of local processes and corticofugal modulation arising from statistical regularities and the influences of expectation. Our results contribute to our understanding of the biological basis of statistical learning and initiate a new investigational approach relating to the time-course of subcortical plasticity. Although the reported time-dependent enhancements are believed to reflect universal neurophysiological processes, future experiments utilizing a larger array of stimuli are needed to establish the generalizability of our findings.     

Bioinformatics: alive and kicking

Bioinformatics has become too central to biology to be left to specialist bioinformaticians. Biologists are all bioinformaticians now.     

Bioinformatics: alive and kicking

Bioinformatics has become too central to biology to be left to specialist bioinformaticians. Biologists are all bioinformaticians now.     

Chromothripsis: Breakage-fusion-bridge over and over again

The acquisition of massive but localized chromosome translocations, a phenomenon termed chromothripsis, has received widespread attention since its discovery over a year ago. Until recently, chromothripsis was believed to originate from a single catastrophic event, but the molecular mechanisms leading to this event are yet to be uncovered. Because a thorough interpretation of the data are missing, the phenomenon itself has wrongly acquired the status of a mechanism used to justify many kinds of complex rearrangements. Although the assumption that all translocations in chromothripsis originate from a single event has met with criticism, satisfactory explanations for the intense but localized nature of this phenomenon are still missing. Here, we show why the data used to describe massive catastrophic rearrangements are incompatible with a model comprising a single event only and propose a molecular mechanism in which a combination of known cellular pathways accounts for chromothripsis. Instead of a single traumatic event, the protection of undamaged chromosomes by telomeres can limit repetitive breakage-fusion-bridge events to a single chromosome arm. Ultimately, common properties of chromosomal instability, such as aneuploidy and centromere fission, might establish the complex genetic pattern observed in this genomic state.