PAR-3D: a server to predict protein active site residues

PAR-3D (http://sunserver.cdfd.org.in:8080/protease/PAR_3D/index.html) is a web-based tool that exploits the fact that relative juxtaposition of active site residues is a conserved feature in functionally related protein families. The server uses previously calculated and stored values of geometrical parameters of a set of known proteins (training set) for prediction of active site residues in a query protein structure. PAR-3D stores motifs for different classes of proteases, the ten glycolytic pathway enzymes and metal-binding sites. The server accepts the structures in the pdb format. The first step during the prediction is the extraction of probable active site residues from the query structure. Spatial arrangement of the probable active site residues is then determined in terms of geometrical parameters. These are compared with stored geometries of the different motifs. Its speed and efficiency make it a beneficial tool for structural genomics projects, especially when the biochemical function of the protein has not been characterized

Protein chaperones and non-protein substrates: on substrate promiscuity of GroEL

Chaperonins are a group of molecular chaperones that form large multi subunit structures and are found in all forms of life. Encoded by the groEL and groES genes, bacterial chaperonins are required for appropriate folding of many cellular proteins. A significant number of bacterial species are known to express multiple copies of chaperonin genes, possibly to confer redundancy of GroEL function in these species. It is also likely that the paralogous GroELs might be undergoing diversification of function as a consequence of gene duplication. We argue in this article that different chaperonins in an organism might be involved in distinct biochemical functions that remain to be discovered, some of which might be modulated by different oligomeric states of the chaperonins

On parity decision trees for Fourier-sparse Boolean functions

We study parity decision trees for Boolean functions. The motivation of our study is the log-rank conjecture for XOR functions and its connection to Fourier analysis and parity decision tree complexity. Our contributions are as follows: Let $f : \mathbb {F}_2^n \rightarrow \lbrace -1, 1\rbrace$ be a Boolean function with Fourier support � and Fourier sparsity k . </jats:p

75 Years of India's Independence and 80 Years of CSIR

38-44The 75th year of Indian independence is even more special to CSIR because CSIR enters its 80 years of gloriously serving the Indian society through S&T interventions

A novel nucleoid-associated protein of Mycobacterium tuberculosis is a sequence homolog of GroEL

The Mycobacterium tuberculosis genome sequence reveals remarkable absence of many nucleoid-associated proteins (NAPs), such as HNS, Hfq or DPS. In order to characterize the nucleoids of M. tuberculosis, we have attempted to identify NAPs, and report an interesting finding that a chaperonin-homolog, GroEL1, is nucleoid associated. We report that M. tuberculosis GroEL1 binds DNA with low specificity but high affinity, suggesting that it might have naturally evolved to bind DNA. We are able to demonstrate that GroEL1 can effectively function as a DNA-protecting agent against DNase I or hydroxyl-radicals. Moreover, Atomic Force Microscopic studies reveal that GroEL1 can condense a large DNA into a compact structure. We also provide in vivo evidences that include presence of GroEL1 in purified nucleoids, in vivo crosslinking followed by Southern hybridizations and immunofluorescence imaging in M. tuberculosis confirming that GroEL1: DNA interactions occur in natural biological settings. These findings therefore reveal that M. tuberculosis GroEL1 has evolved to be associated with nucleoids

Dynamic Changes in Protein Functional Linkage Networks Revealed by Integration with Gene Expression Data

Response of cells to changing environmental conditions is governed by the dynamics of intricate biomolecular interactions. It may be reasonable to assume, proteins being the dominant macromolecules that carry out routine cellular functions, that understanding the dynamics of protein∶protein interactions might yield useful insights into the cellular responses. The large-scale protein interaction data sets are, however, unable to capture the changes in the profile of protein∶protein interactions. In order to understand how these interactions change dynamically, we have constructed conditional protein linkages for Escherichia coli by integrating functional linkages and gene expression information. As a case study, we have chosen to analyze UV exposure in wild-type and SOS deficient E. coli at 20 minutes post irradiation. The conditional networks exhibit similar topological properties. Although the global topological properties of the networks are similar, many subtle local changes are observed, which are suggestive of the cellular response to the perturbations. Some such changes correspond to differences in the path lengths among the nodes of carbohydrate metabolism correlating with its loss in efficiency in the UV treated cells. Similarly, expression of hubs under unique conditions reflects the importance of these genes. Various centrality measures applied to the networks indicate increased importance for replication, repair, and other stress proteins for the cells under UV treatment, as anticipated. We thus propose a novel approach for studying an organism at the systems level by integrating genome-wide functional linkages and the gene expression data

Understanding Communication Signals during Mycobacterial Latency through Predicted Genome-Wide Protein Interactions and Boolean Modeling

About 90% of the people infected with Mycobacterium tuberculosis carry latent bacteria that are believed to get activated upon immune suppression. One of the fundamental challenges in the control of tuberculosis is therefore to understand molecular mechanisms involved in the onset of latency and/or reactivation. We have attempted to address this problem at the systems level by a combination of predicted functional protein∶protein interactions, integration of functional interactions with large scale gene expression studies, predicted transcription regulatory network and finally simulations with a Boolean model of the network. Initially a prediction for genome-wide protein functional linkages was obtained based on genome-context methods using a Support Vector Machine. This set of protein functional linkages along with gene expression data of the available models of latency was employed to identify proteins involved in mediating switch signals during dormancy. We show that genes that are up and down regulated during dormancy are not only coordinately regulated under dormancy-like conditions but also under a variety of other experimental conditions. Their synchronized regulation indicates that they form a tightly regulated gene cluster and might form a latency-regulon. Conservation of these genes across bacterial species suggests a unique evolutionary history that might be associated with M. tuberculosis dormancy. Finally, simulations with a Boolean model based on the regulatory network with logical relationships derived from gene expression data reveals a bistable switch suggesting alternating latent and actively growing states. Our analysis based on the interaction network therefore reveals a potential model of M. tuberculosis latency

Harnessing Science, Technology & Innovation : Making India a Global Player

14-19As India aspires to become the global economic leader, the role of Science, Technology and Innovation will play a major role, in achieving the dreams of 1.3 billion people

The Ethos of CSIR

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Is SARS-CoV-2 Airborne?

22-23While we are now past the first six months of the COVID-19 pandemic, some new ideas of the transmission of SARS-CoV-2 have begun to emerge. Some are still being debated