Cytoview: development of a cell modelling framework

The biological cell, a natural self-contained unit of prime biological importance, is an enormously complex machine that can be understood at many levels. A higher-level perspective of the entire cell requires integration of various features into coherent, biologically meaningful descriptions. There are some efforts to model cells based on their genome, proteome or metabolome descriptions. However, there are no established methods as yet to describe cell morphologies, capture similarities and differences between different cells or between healthy and disease states. Here we report a framework to model various aspects of a cell and integrate knowledge encoded at different levels of abstraction, with cell morphologies at one end to atomic structures at the other. The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves as a first step in integrating different levels of data available for a biological cell and has the potential to lead to development of computational models in our pursuit to model cell structure and function, from which several applications can flow out

Parallel implementation of AutoDock

Computational docking of ligands to protein structures is a key step in structure-based drug design. Currently, the time required for each docking run is high and thus limits the use of docking in a high-throughput manner, warranting parallelization of docking algorithms. AutoDock, a widely used tool, has been chosen for parallelization. Near-linear increases in speed were observed with 96 processors, reducing the time required for docking ligands to HIV-protease from 81 min, as an example, on a single IBM Power-5 processor ( 1.65 GHz), to about 1 min on an IBM cluster, with 96 such processors. This implementation would make it feasible to perform virtual ligand screening using AutoDock

Cytoview: Development of a cell modelling framework

The biological cell, a natural self-contained unit of prime biological importance, is an enormously complex machine that can be understood at many levels. A higher-level perspective of the entire cell requires integration of various features into coherent, biologically meaningful descriptions. There are some efforts to model cells based on their genome, proteome or metabolome descriptions. However, there are no established methods as yet to describe cell morphologies, capture similarities and differences between different cells or between healthy and disease states. Here we report a framework to model various aspects of a cell and integrate knowledge encoded at different levels of abstraction, with cell morphologies at one end to atomic structures at the other. The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves as a fi rst step in integrating different levels of data available for a biological cell and has the potential to lead to development of computational models in our pursuit to model cell structure and function, from which several applications can fl ow out

``On demand'' redox buffering by H2S contributes to antibiotic resistance revealed by a bacteria-specific H2S donor

Understanding the mechanisms of antimicrobial resistance (AMR) will help launch a counter-offensive against human pathogens that threaten our ability to effectively treat common infections. Herein, we report bis(4-nitrobenzyl)sulfanes, which are activated by a bacterial enzyme to produce hydrogen sulfide (H2S) gas. We found that H2S helps maintain redox homeostasis and protects bacteria against antibiotic-triggered oxidative stress ``on demand'', through activation of alternate respiratory oxidases and cellular antioxidants. We discovered, a hitherto unknown role for this gas, that chemical inhibition of H2S biosynthesis reversed antibiotic resistance in multidrug-resistant (MDR) uropathogenic Escherichia coli strains of clinical origin, whereas exposure to the H2S donor restored drug tolerance. Together, our study provides a greater insight into the dynamic defence mechanisms of this gas, modes of antibiotic action as well as resistance while progressing towards new pharmacological targets to address AMR