@article { ISI:000353720700004, title = {Distinct molecular features facilitating ice-binding mechanisms in hyperactive antifreeze proteins closely related to an Antarctic sea ice bacterium}, journal = {Journal of Biomolecular Structure \& Dynamics}, volume = {33}, number = {7}, year = {2015}, month = {JUL}, pages = {1424-1441}, publisher = {TAYLOR \& FRANCIS INC}, address = {530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA}, abstract = {

Antifreeze proteins or ice-binding proteins (IBPs) facilitate the survival of certain cellular organisms in freezing environment by inhibiting the growth of ice crystals in solution. Present study identifies orthologs of the IBP of Colwellia sp. SLW05, which were obtained from a wide range of taxa. Phylogenetic analysis on the basis of conserved regions (predicted as the {\textquoteleft}ice-binding domain{\textquoteright} [IBD]) present in all the orthologs, separates the bacterial and archaeal orthologs from that of the eukaryotes{\textquoteright}. Correspondence analysis pointed out that the bacterial and archaeal IBDs have relatively higher average hydrophobicity than the eukaryotic members. IBDs belonging to bacterial as well as archaeal AFPs contain comparatively more strands, and therefore are revealed to be under higher evolutionary selection pressure. Molecular docking studies prove that the ice crystals form more stable complex with the bacterial as well as archaeal proteins than the eukaryotic orthologs. Analysis of the docked structures have traced out the ice-binding sites (IBSs) in all the orthologs which continue to facilitate ice-binding activity even after getting mutated with respect to the well-studied IBSs of Typhula ishikariensis and notably, all these mutations performing ice-binding using {\textquoteleft}anchored clathrate mechanism{\textquoteright} have been found to prefer polar and hydrophilic amino acids. Horizontal gene transfer studies point toward a strong selection pressure favoring independent evolution of the IBPs in some polar organisms including prokaryotes as well as eukaryotes because these proteins facilitate the polar organisms to acclimatize to the adversities in their niche, thus safeguarding their existence.

}, keywords = {antifreeze proteins, horizontal gene transfer, ice-recrystallization inhibition, Molecular docking, Phylogenetic analysis}, issn = {0739-1102}, doi = {10.1080/07391102.2014.952665}, author = {Banerjee, Rachana and Chakraborti, Pratim and Bhowmick, Rupa and Mukhopadhyay, Subhasish} } @article {43047, title = {Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach}, journal = {Systems and Synthetic Biology}, volume = {9}, year = {2015}, month = {DEC}, pages = {159-177}, doi = {10.1007/s11693-015-9183-9}, author = {Bhowmick, Rupa and Subramanian, Abhishek and Sarkar, Ram Rup} } @article { ISI:000363023500010, title = {Temporal protein expression pattern in intracellular signalling cascade during T-cell activation: a computational study}, journal = {Journal of Biosciences}, volume = {40}, number = {4}, year = {2015}, month = {OCT}, pages = {769-789}, publisher = {INDIAN ACAD SCIENCES}, address = {C V RAMAN AVENUE, SADASHIVANAGAR, P B \#8005, BANGALORE 560 080, INDIA}, abstract = {

Various T-cell co-receptor molecules and calcium channel CRAC play a pivotal role in the maintenance of cell{\textquoteright}s functional responses by regulating the production of effector molecules (mostly cytokines) that aids in immune clearance and also maintaining the cell in a functionally active state. Any defect in these co-receptor signalling pathways may lead to an altered expression pattern of the effector molecules. To study the propagation of such defects with time and their effect on the intracellular protein expression patterns, a comprehensive and largest pathway map of T-cell activation network is reconstructed manually. The entire pathway reactions are then translated using logical equations and simulated using the published time series microarray expression data as inputs. After validating the model, the effect of in silico knock down of co-receptor molecules on the expression patterns of their downstream proteins is studied and simultaneously the changes in the phenotypic behaviours of the T-cell population are predicted, which shows significant variations among the proteins expression and the signalling routes through which the response is propagated in the cytoplasm. This integrative computational approach serves as a valuable technique to study the changes in protein expression patterns and helps to predict variations in the cellular behaviour.

}, keywords = {Boolean model, co-receptors and CRAC channel, synchronous and asynchronous simulation, T-cell signalling pathway, temporal gene expression patterns}, issn = {0250-5991}, doi = {10.1007/s12038-015-9561-1}, author = {Ganguli, Piyali and Chowdhury, Saikat and Bhowmick, Rupa and Sarkar, Ram Rup} } @article {46814, title = {Differential suitability of reactive oxygen species and the role of glutathione in regulating paradoxical behavior in gliomas: a mathematical perspective}, journal = {PloS One}, volume = {15}, year = {2020}, month = {JUN}, pages = {e0235204}, type = {Article}, abstract = {

Manipulative strategies of ROS in cancer are often exhibited as changes in the redox and thiol ratio of the cells. Cellular responses to oxidative insults are generated in response to these changes which are triggered due to the rerouting of the metabolic framework to maintain survival under stress. However, mechanisms of these metabolic re-routing are not clearly understood and remained debatable. In the present work, we have designed a context-based dynamic metabolic model to establish that the coordinated functioning of glutathione peroxidase (GTHP), glutathione oxidoreductase (GTHO) and NADPH oxidase (NOX) is crucial in determining cancerous transformation, specifically in gliomas. Further, we propose that the puzzling duality of ROS (represented by changes inh(2)o(2)in the present model) in exhibiting varying cellular fates can be determined by considering simultaneous changes innadph/nadp(+)andgsh/gssgthat occur during the reprogramming of metabolic reactions. This will be helpful in determining the pro-apoptotic or anti-apoptotic fate of gliomas and can be useful in designing effective pro-oxidant and/or anti-oxidant therapeutic approaches against gliomas.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0235204}, author = {Bhowmick, Rupa and Sarkar, Ram Rup} } @article {47993, title = {Emerging landscape of molecular interaction networks: opportunities, challenges and prospects}, journal = {Journal of Biosciences}, volume = {47}, year = {2022}, month = {APR}, pages = {24}, type = {Review}, abstract = {

Network biology finds application in interpreting molecular interaction networks and providing insightful inferences using graph theoretical analysis of biological systems. The integration of computational bio-modelling approaches with different hybrid network-based techniques provides additional information about the behaviour of complex systems. With increasing advances in high-throughput technologies in biological research, attempts have been made to incorporate this information into network structures, which has led to a continuous update of network biology approaches over time. The newly minted centrality measures accommodate the details of omics data and regulatory network structure information. The unification of graph network properties with classical mathematical and computational modelling approaches and technologically advanced approaches like machine-learning- and artificial intelligence-based algorithms leverages the potential application of these techniques. These computational advances prove beneficial and serve various applications such as essential gene prediction, identification of drug-disease interaction and gene prioritization. Hence, in this review, we have provided a comprehensive overview of the emerging landscape of molecular interaction networks using graph theoretical approaches. With the aim to provide information on the wide range of applications of network biology approaches in understanding the interaction and regulation of genes, proteins, enzymes and metabolites at different molecular levels, we have reviewed the methods that utilize network topological properties, emerging hybrid network-based approaches and applications that integrate machine learning techniques to analyse molecular interaction networks. Further, we have discussed the applications of these approaches in biomedical research with a note on future prospects.

}, keywords = {Centrality, disease mechanisms, hybrid network-based models, machine learning, molecular interaction networks, network topology, systems biology}, issn = {0250-5991}, doi = {10.1007/s12038-022-00253-y}, author = {Panditrao, Gauri and Bhowmick, Rupa and Meena, Chandrakala and Sarkar, Ram Rup} } @article {48449, title = {Identification of potential microRNAs regulating metabolic plasticity and cellular phenotypes in glioblastoma}, journal = {Molecular Genetics and Genomics}, volume = {298}, year = {2023}, month = {JAN}, pages = {161-181}, type = {Article}, abstract = {

MicroRNAs (miRNAs) play important role in regulating cellular metabolism, and are currently being explored in cancer. As metabolic reprogramming in cancer is a major mediator of phenotypic plasticity, understanding miRNA-regulated metabolism will provide opportunities to identify miRNA targets that can regulate oncogenic phenotypes by taking control of cellular metabolism. In the present work, we studied the effect of differentially expressed miRNAs on metabolism, and associated oncogenic phenotypes in glioblastoma (GBM) using patient-derived data. Networks of differentially expressed miRNAs and metabolic genes were created and analyzed to identify important miRNAs that regulate major metabolism in GBM. Graph network-based approaches like network diffusion, backbone extraction, and different centrality measures were used to analyze these networks for identification of potential miRNA targets. Important metabolic processes and cellular phenotypes were annotated to trace the functional responses associated with these miRNA-regulated metabolic genes and associated phenotype networks. miRNA-regulated metabolic gene subnetworks of cellular phenotypes were extracted, and important miRNAs regulating these phenotypes were identified. The most important outcome of the study is the target miRNA combinations predicted for five different oncogenic phenotypes that can be tested experimentally for miRNA-based therapeutic design in GBM. Strategies implemented in the study can be used to generate testable hypotheses in other cancer types as well, and design context-specific miRNA-based therapy for individual patient. Their usability can be further extended to other gene regulatory networks in cancer and other genetic diseases.

}, keywords = {Cellular phenotypes, Functional analysis, Glioblastoma metabolism, microRNA, miRNA-based therapy, Network analysis, Transcriptome}, issn = {1617-4615}, doi = {10.1007/s00438-022-01966-3}, author = {Bhowmick, Rupa and Sarkar, Ram Rup} }