Publications by authors named "Romana Ishrat"

25 Publications

  • Page 1 of 1

Network-based analysis of key regulatory genes implicated in Type 2 Diabetes Mellitus and Recurrent Miscarriages in Turner Syndrome.

Sci Rep 2021 May 21;11(1):10662. Epub 2021 May 21.

Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, 110025, India.

The information on the genotype-phenotype relationship in Turner Syndrome (TS) is inadequate because very few specific candidate genes are linked to its clinical features. We used the microarray data of TS to identify the key regulatory genes implicated with TS through a network approach. The causative factors of two common co-morbidities, Type 2 Diabetes Mellitus (T2DM) and Recurrent Miscarriages (RM), in the Turner population, are expected to be different from that of the general population. Through microarray analysis, we identified nine signature genes of T2DM and three signature genes of RM in TS. The power-law distribution analysis showed that the TS network carries scale-free hierarchical fractal attributes. Through local-community-paradigm (LCP) estimation we find that a strong LCP is also maintained which means that networks are dynamic and heterogeneous. We identified nine key regulators which serve as the backbone of the TS network. Furthermore, we recognized eight interologs functional in seven different organisms from lower to higher levels. Overall, these results offer few key regulators and essential genes that we envisage have potential as therapeutic targets for the TS in the future and the animal models studied here may prove useful in the validation of such targets.
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http://dx.doi.org/10.1038/s41598-021-90171-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140125PMC
May 2021

Identification of the Key Regulators of Spina Bifida Through Graph-Theoretical Approach.

Front Genet 2021 6;12:597983. Epub 2021 Apr 6.

Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.

Spina Bifida (SB) is a congenital spinal cord malformation. Efforts to discern the key regulators (KRs) of the SB protein-protein interaction (PPI) network are requisite for developing its successful interventions. The architecture of the SB network, constructed from 117 manually curated genes was found to self-organize into a scale-free fractal state having a weak hierarchical organization. We identified three modules/motifs consisting of ten KRs, namely, , , , , , , , , , and . These KRs serve as the backbone of the network, they propagate signals through the different hierarchical levels of the network to conserve the network's stability while maintaining low popularity in the network. We also observed that the SB network exhibits a rich-club organization, the formation of which is attributed to our key regulators also except for and . The KRs that were found to ally with each other and emerge in the same motif, open up a new dimension of research of studying these KRs together. Owing to the multiple etiology and mechanisms of SB, a combination of several biomarkers is expected to have higher diagnostic accuracy for SB as compared to using a single biomarker. So, if all the KRs present in a single module/motif are targetted together, they can serve as biomarkers for the diagnosis of SB. Our study puts forward some novel SB-related genes that need further experimental validation to be considered as reliable future biomarkers and therapeutic targets.
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http://dx.doi.org/10.3389/fgene.2021.597983DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056047PMC
April 2021

Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach.

Brief Bioinform 2021 03;22(2):1309-1323

Centre for Interdisciplinary Research in Basic Science, Jamia Millia Islamia University, New Delhi, India.

The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4+) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8+) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are $80\hbox{--} 90\%$ identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo.
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http://dx.doi.org/10.1093/bib/bbaa340DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7799329PMC
March 2021

Human gene expression profiling identifies key therapeutic targets in tuberculosis infection: A systematic network meta-analysis.

Infect Genet Evol 2021 01 1;87:104649. Epub 2020 Dec 1.

Center for Interdisciplinary Research in Basic sciences, Jamia Millia Islamia University, New Delhi 110025, India. Electronic address:

Tuberculosis (TB) is one of the deadliest diseases since ancient times and is still a global health problem. So, there is a need to develop new approaches for early detection of TB and understand the host-pathogen relationship. In the present study, we have analyzed microarray data sets and compared the transcriptome profiling of the healthy individual with latent infection (LTBI) and active TB (TB) patients, and identified the differentially expressed genes (DEGs). Next, we performed the systematic network meta-analysis of the DEGs, which identified the seven most influencing hub genes (IL6, IL1B, TNF, NFKB1, STAT1, JAK2, and MAPK8) as the potential therapeutic target in the tuberculosis disease. These target genes are involved in many biological processes like cell cycle control, apoptosis, complement signalling, enhanced cytokine & chemokine signalling, pro-inflammatory responses, and host immune responses. Additionally, we also identified 22 inferred genes that are mainly engaged in the induction of innate immune response, cellular response to interleukin-6, inflammatory response, apoptotic process, I-kappaB-phosphorylation, JAK-STAT signalling pathway, macrophage activation, cell growth, and cell signalling. The proper attention of these inferred genes may open up a new horizon to understand the defensive mechanisms of TB disease. The transcriptome profiling and network approach can enhance the understanding of the molecular pathogenesis of tuberculosis infection and have implications for the plan and execution of mRNA expression tools to support early diagnostics and treatment of Mycobacterium tuberculosis (M.tb).
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http://dx.doi.org/10.1016/j.meegid.2020.104649DOI Listing
January 2021

Identification and Validation of Potential miRNAs, as Biomarkers for Sepsis and Associated Lung Injury: A Network-Based Approach.

Genes (Basel) 2020 11 10;11(11). Epub 2020 Nov 10.

Translational Research Lab, Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi 110025, India.

Sepsis is a dysregulated immune response disease affecting millions worldwide. Delayed diagnosis, poor prognosis, and disease heterogeneity make its treatment ineffective. miRNAs are imposingly involved in personalized medicine such as therapeutics, due to their high sensitivity and accuracy. Our study aimed to reveal the biomarkers that may be involved in the dysregulated immune response in sepsis and lung injury using a computational approach and in vivo validation studies. A sepsis miRNA Gene Expression Omnibus (GEO) dataset based on the former analysis of blood samples was used to identify differentially expressed miRNAs (DEMs) and associated hub genes. Sepsis-associated genes from the Comparative Toxicogenomics Database (CTD) that overlapped with identified DEM targets were utilized for network construction. In total, 317 genes were found to be regulated by 10 DEMs (three upregulated, namely miR-4634, miR-4638-5p, and miR-4769-5p, and seven downregulated, namely miR-4299, miR-451a, miR181a-2-3p, miR-16-5p, miR-5704, miR-144-3p, and miR-1290). Overall hub genes (HIP1, GJC1, MDM4, IL6R, and ERC1) and for miR-16-5p (SYNRG, TNRC6B, and LAMTOR3) were identified based on centrality measures (degree, betweenness, and closeness). In vivo validation of miRNAs in lung tissue showed significantly downregulated expression of miR-16-5p corroborating with our computational findings, whereas expression of miR-181a-2-3p and miR-451a were found to be upregulated in contrast to the computational approach. In conclusion, the differential expression pattern of miRNAs and hub genes reported in this study may help to unravel many unexplored regulatory pathways, leading to the identification of critical molecular targets for increased prognosis, diagnosis, and drug efficacy in sepsis and associated organ injuries.
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http://dx.doi.org/10.3390/genes11111327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696689PMC
November 2020

A Systems View of the Genome Guardians: Mapping the Signaling Circuitry Underlying Oligonucleotide/Oligosaccharide-Binding Fold Proteins.

OMICS 2020 09 11;24(9):518-530. Epub 2020 Aug 11.

Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.

The oligonucleotide/oligosaccharide-binding (OB)-fold domain proteins are considered as genome guardians, whose functions are extending beyond genomic stability. The broad functional diversity of the OB-fold proteins is attributed to their protein-DNA, protein-RNA, and protein-protein interactions (PPI). To understand the connectivity of the human OB-fold proteins, we report here a systems-level approach. Specifically, we mapped all human OB-fold PPI networks and evaluated topological features such as network robustness and network hub, among others. We found that the OB-fold network comprised of 227 nodes forming 5523 interactions, and has a scale-free topology having UBA52, ATR, and TP53 as leading hub proteins that control efficient communication within the network. Furthermore, four different clusters and subclusters have been identified, which are implicated in diverse cellular processes, including DNA replication, repair, maintenance of genomic stability, RNA processing, spermatogenesis, complement system, and telomere maintenance. The importance of these clusters is further strengthened by knockout studies, which showed a significant decrease in topological properties. In summary, this study provides new insights on the role of OB-fold protein as genome guardians in regard to the underlying mechanism of signaling pathways, the roles of key regulators, and thus, offers new prospects as potential targets for diagnostics and therapeutics purposes.
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http://dx.doi.org/10.1089/omi.2020.0072DOI Listing
September 2020

Covid-19: current knowledge, disease potential, prevention and clinical advances.

Turk J Biol 2020 21;44(3):121-131. Epub 2020 Jun 21.

Center for Interdisciplinary Research in Basic Sciences, JMI University, New Delhi India.

The top priority of any nation is to lead the nation towards prosperity, progress, and economic growth, confronting several challenges and concerns arisen from global situations. The sudden outbreak of any disease defies the health care systems and economy of nations. COVID-19 is one of the viral diseases which broke out in Wuhan city of China in 2019. COVID-19 outbreak intermittently prevailed all over the world. It exposes the fragility of the established health care systems across the world in spite of comprising modern science and technology. Unfortunately, there is no chemotherapeutic agent in the regimen of antiviral drugs or no vaccine available to curb this infectious disease. As a consequence, this deadly infection has prevailed all over the world. The antiviral drugs used for viral diseases excluding COVID-19 infection are Ramdesvir, Favipiravir, and Ribavarin, and antimalarial agents (Chloroquine & Hydroxychloroquine) are being administered to the patients for redemption of this infection. Fortunately, these existing drugs have been found clinically active and are being used. In this review, we present the current scenario and status of epidemiology, diagnosis, treatment, vaccine development for COVID-19, and its impact on the socio-economic structure.
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http://dx.doi.org/10.3906/biy-2005-29DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314501PMC
June 2020

Structure-Guided Approach to Identify Potential Inhibitors of Large Envelope Protein to Prevent Hepatitis B Virus Infection.

Oxid Med Cell Longev 2019 4;2019:1297484. Epub 2019 Sep 4.

Center for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India.

Hepatitis B virus (HBV) infection is one of the major causes of liver diseases, which can lead to hepatocellular carcinoma. The role of HBV envelope proteins is crucial in viral morphogenesis, infection, and propagation. Thus, blocking the pleiotropic functions of these proteins especially the PreS1 and PreS2 domains of the large surface protein (LHBs) is a promising strategy for designing efficient antivirals against HBV infection. Unfortunately, the structure of the LHBs protein has not been elucidated yet, and it seems that any structure-based drug discovery is critically dependent on this. To find effective inhibitors of LHBs, we have modeled and validated its three-dimensional structure and subsequently performed a virtual high-throughput screening against the ZINC database using RASPD and ParDOCK tools. We have identified four compounds, ZINC11882026, ZINC19741044, ZINC00653293, and ZINC15000762, showing appreciable binding affinity with the LHBs protein. The drug likeness was further validated using ADME screening and toxicity analysis. Interestingly, three of the four compounds showed the formation of hydrogen bonds with amino acid residues lying in the capsid binding region of the PreS1 domain of LHBs, suggesting the possibility of inhibiting the viral assembly and maturation process. The identification of potential lead molecules will help to discover more potent inhibitors with significant antiviral activities.
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http://dx.doi.org/10.1155/2019/1297484DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6854180PMC
April 2020

Methodology of predicting novel key regulators in ovarian cancer network: a network theoretical approach.

BMC Cancer 2019 Nov 21;19(1):1129. Epub 2019 Nov 21.

School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110067, India.

Background: Identification of key regulator/s in ovarian cancer (OC) network is important for potential drug target and prevention from this cancer. This study proposes a method to identify the key regulators of this network and their importance.

Methods: The protein-protein interaction (PPI) network of ovarian cancer (OC) is constructed from curated 6 hundred genes from standard six important ovarian cancer databases (some of the genes are experimentally verified). We proposed a method to identify key regulators (KRs) from the complex ovarian cancer network based on the tracing of backbone hubs, which participate at all levels of organization, characterized by Newmann-Grivan community finding method. Knockout experiment, constant Potts model and survival analysis are done to characterize the importance of the key regulators in regulating the network.

Results: The PPI network of ovarian cancer is found to obey hierarchical scale free features organized by topology of heterogeneous modules coordinated by diverse leading hubs. The network and modular structures are devised by fractal rules with the absence of centrality-lethality rule, to enhance the efficiency of signal processing in the network and constituting loosely connected modules. Within the framework of network theory, we device a method to identify few key regulators (KRs) from a huge number of leading hubs, that are deeply rooted in the network, serve as backbones of it and key regulators from grassroots level to complete network structure. Using this method we could able to identify five key regulators, namely, AKT1, KRAS, EPCAM, CD44 and MCAM, out of which AKT1 plays central role in two ways, first it serves as main regulator of ovarian cancer network and second serves as key cross-talk agent of other key regulators, but exhibits disassortive property. The regulating capability of AKT1 is found to be highest and that of MCAM is lowest.

Conclusions: The popularities of these key hubs change in an unpredictable way at different levels of organization and absence of these hubs cause massive amount of wiring energy/rewiring energy that propagate over all the network. The network compactness is found to increase as one goes from top level to bottom level of the network organization.
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http://dx.doi.org/10.1186/s12885-019-6309-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6869253PMC
November 2019

Identification and Classification of Differentially Expressed Genes and Network Meta-Analysis Reveals Potential Molecular Signatures Associated With Tuberculosis.

Front Genet 2019 4;10:932. Epub 2019 Nov 4.

Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.

Tuberculosis (TB) is one of deadly transmissible disease that causes death worldwide; however, only 10% of people infected with develop disease, indicating that host genetic factors may play key role in determining susceptibility to TB disease. In this way, the analysis of gene expression profiling of TB infected individuals can give us a snapshot of actively expressed genes and transcripts under various conditions. In the present study, we have analyzed microarray data set and compared the gene expression profiles of patients with different datasets of healthy control, latent infection, and active TB. We observed the transition of genes from normal condition to different stages of the TB and identified and annotated those genes/pathways/processes that have important roles in TB disease during its cyclic interventions in the human body. We identified 488 genes that were differentially expressed at various stages of TB and allocated to pathways and gene set enrichment analysis. These pathways as well as GSEA's importance were evaluated according to the number of DEGs presents in both. In addition, we studied the gene regulatory networks that may help to further understand the molecular mechanism of immune response against the TB infection and provide us a new angle for future biomarker and therapeutic targets. In this study, we identified 26 leading hubs which are deeply rooted from top to bottom in the gene regulatory network and work as the backbone of the network. These leading hubs contains 31 key regulator genes, of which 14 genes were up-regulated and 17 genes were down-regulated. The proposed approach is based on gene-expression profiling, and network analysis approaches predict some unknown TB-associated genes, which can be considered (or can be tested) as reliable candidates for further (/) studies.
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http://dx.doi.org/10.3389/fgene.2019.00932DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6844239PMC
November 2019

characterization of hypothetical proteins from str. Karp uncovers virulence genes.

Heliyon 2019 Oct 1;5(10):e02734. Epub 2019 Nov 1.

Centre for Interdisciplinary Research in Basic Science, Jamia Millia Islamia, New Delhi, India.

Scrub typhus also known as bush typhus is a disease with symptoms similar to Chikungunya infection. It is caused by a gram-negative bacterium which resides in its vertebrate host, Mites. The genome of str. Karp encodes for 1,563 proteins, of which 344 are characterized as hypothetical ones. In the present study, we tried to identify the probable functions of these 344 hypothetical proteins (HPs). All the characterized hypothetical proteins (HPs) belong to the various protein classes like enzymes, transporters, binding proteins, metabolic process and catalytic activity and kinase activity. These hypothetical proteins (HPs) were further analyzed for virulence factors with 62 proteins identified as the most virulent proteins among these hypothetical proteins (HPs). In addition, we studied the protein sequence similarity network for visualizing functional trends across protein superfamilies from the context of sequence similarity and it shows great potential for generating testable hypotheses about protein structure-function relationships. Furthermore, we calculated toplogical properties of the network and found them to obey network power law distributions showing a fractal nature. We also identifed two highly interconnected modules in the main network which contained five hub proteins (KJV55465, KJV56211, KJV57212, KJV57203 and KJV57216) having 1.0 clustering coefficient. The structural modeling (2D and 3D structure) of these five hub proteins was carried out and the catalytic site essential for its functioning was analyzed. The outcome of the present study may facilitate a better understanding of the mechanism of virulence, pathogenesis, adaptability to host and up-to-date annotations will make unknown genes easy to identify and target for experimentation. The information on the functional attributes and virulence characteristic of these hypothetical proteins (HPs) are envisaged to facilitate effective development of novel antibacterial drug targets of .
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http://dx.doi.org/10.1016/j.heliyon.2019.e02734DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838952PMC
October 2019

Assessment of the key regulatory genes and their Interologs for Turner Syndrome employing network approach.

Sci Rep 2018 07 4;8(1):10091. Epub 2018 Jul 4.

Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, 110025, India.

Turner Syndrome (TS) is a condition where several genes are affected but the molecular mechanism remains unknown. Identifying the genes that regulate the TS network is one of the main challenges in understanding its aetiology. Here, we studied the regulatory network from manually curated genes reported in the literature and identified essential proteins involved in TS. The power-law distribution analysis showed that TS network carries scale-free hierarchical fractal attributes. This organization of the network maintained the self-ruled constitution of nodes at various levels without having centrality-lethality control systems. Out of twenty-seven genes culminating into leading hubs in the network, we identified two key regulators (KRs) i.e. KDM6A and BDNF. These KRs serve as the backbone for all the network activities. Removal of KRs does not cause its breakdown, rather a change in the topological properties was observed. Since essential proteins are evolutionarily conserved, the orthologs of selected interacting proteins in C. elegans, cat and macaque monkey (lower to higher level organisms) were identified. We deciphered three important interologs i.e. KDM6A-WDR5, KDM6A-ASH2L and WDR5-ASH2L that form a triangular motif. In conclusion, these KRs and identified interologs are expected to regulate the TS network signifying their biological importance.
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http://dx.doi.org/10.1038/s41598-018-28375-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6031616PMC
July 2018

Exploring novel key regulators in breast cancer network.

PLoS One 2018 21;13(6):e0198525. Epub 2018 Jun 21.

School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi-110067, India.

The breast cancer network constructed from 70 experimentally verified genes is found to follow hierarchical scale free nature with heterogeneous modular organization and diverge leading hubs. The topological parameters (degree distributions, clustering co-efficient, connectivity and centralities) of this network obey fractal rules indicating absence of centrality lethality rule, and efficient communication among the components. From the network theoretical approach, we identified few key regulators out of large number of leading hubs, which are deeply rooted from top to down of the network, serve as backbone of the network, and possible target genes. However, p53, which is one of these key regulators, is found to be in low rank and keep itself at low profile but directly cross-talks with important genes BRCA2 and BRCA3. The popularity of these hubs gets changed in unpredictable way at various levels of organization thus showing disassortive nature. The local community paradigm approach in this network shows strong correlation of nodes in majority of modules/sub-modules (fast communication among nodes) and weak correlation of nodes only in few modules/sub-modules (slow communication among nodes) at various levels of network organization.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0198525PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013121PMC
December 2018

Fractal rules in brain networks: Signatures of self-organization.

J Theor Biol 2018 01 18;437:58-66. Epub 2017 Sep 18.

School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110067, India. Electronic address:

We study brain network data of three species, namely, C. elegans, cat and macaque monkey within the framework of network theory and Potts Hamiltonian model, and explore rich fractal nature in it, which could be an important signature of self-organization, and a simple rule to be obeyed in complex patterns of brain networks. Further, this fractal behaviors in topological parameters of brain networks at various network levels could be an indicator of systems level organization in complicated brain functionality. Again, Rich-club formation of leading hubs in brain networks becomes unpredictable as one goes down to different levels of organization. The popularity of these leading hubs in main modules or sub-modules also gets changed at different network levels, with varied attitudes at each level. Moreover, distribution of edges, which involves intra- and inter-modular/sub-modular interactions, inherited from one level of organization to another level follows fractal law. In addition to this, the Hamiltonian function at each network level, which may correspond to the energy cost in network organization at that level, shows fractal nature. Significant motifs, which are building blocks of networks and related to basic functionalities, in brain networks is found to be triangular motif, and its probability distribution at various levels as a function of size of modules or sub-modules follows fractal law.
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http://dx.doi.org/10.1016/j.jtbi.2017.09.014DOI Listing
January 2018

Recent trends in ZikV research: A step away from cure.

Biomed Pharmacother 2017 Jul 17;91:1152-1159. Epub 2017 May 17.

Centre for Interdisciplinary Research in Basic Science, Jamia Millia Islamia, New Delhi, India. Electronic address:

Zika virus (ZikV) is a member of the Flaviviridae virus family, genus Flavivirus has emerged as a potential threat to human health worldwide. Consequences of vertical infections includes microcephaly with brain and eye anomalies, and adult infections includes Guillain-Barr├ęsyndrome (GBS), brain ischemia, myelitis and meningoencephalitis. To develop a better treatment, many efforts are being made, like drug-repurposing concept for FDA-approved drugs for antiviral activity are screened against ZikV infection and emerging as a promising alternative to expedite drug development and various vaccines like DNA, ZPIV, LAIV, mRNA and AGS-v vaccines have been designed and in under clinical trial phases. Moreover, few pharmacological agents like Mycophenolicacid, Niclosamide, PHA-690509, Emricasan and Bortezomib are most potent anti-ZikV candidates and highly effective single or combining treatment with these drugs. This article reviews the ZikV illness, transmission patterns, pathophysiology of disease, global efforts, challenges and the prospects for the development of vaccines and antiviral agents.
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http://dx.doi.org/10.1016/j.biopha.2017.05.045DOI Listing
July 2017

Potential entry inhibitors of the envelope protein (E2) of Chikungunya virus: in silico structural modeling, docking and molecular dynamic studies.

Virusdisease 2017 Mar 9;28(1):39-49. Epub 2017 Feb 9.

Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, 110025 India.

Chikungunya fever is an arboviral infection caused by the Chikungunya virus (CHIKV) and is transmitted by mosquito. The envelope protein (E2) of Chikungunya virus is involved in attachment of virion with the host cell. The present study was conceptualized to determine the structure of E2 protein of CHIKV and to identify the potential viral entry inhibitors. The secondary and tertiary structure of E2 protein was determined using bioinformatics tools. The mutational analysis of the E2 protein suggested that mutations may stabilize or de-stabilize the structure which may affect the structure-function relationship. In silico screening of various compounds from different databases identified two lead molecules i.e. phenothiazine and bafilomycin. Molecular docking and MD simulation studies of the E2 protein and compound complexes was carried out. This analysis revealed that bafilomycin has high docking score and thus high binding affinity with E2 protein suggesting stable protein-ligand interaction. Further, MD simulations suggested that both the compounds were stabilizing E2 protein. Thus, bafilomycin and phenothiazine may be considered as the lead compounds in terms of potential entry inhibitor for CHIKV. Further, these results should be confirmed by comprehensive cell culture, cytotoxic assays and animal experiments. Certain derivatives of phenothiazines can also be explored in future studies for entry inhibitors against CHIKV. The present investigation thus provides insight into protein structural dynamics of the envelope protein of CHIKV. In addition the study also provides information on the dynamics of interaction of E2 protein with entry inhibitors that will contribute towards structure based drug design.
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http://dx.doi.org/10.1007/s13337-016-0356-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5377863PMC
March 2017

Dynamical states, possibilities and propagation of stress signal.

Sci Rep 2017 01 20;7:40596. Epub 2017 Jan 20.

School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110067, India.

The stress driven dynamics of Notch-Wnt-p53 cross-talk is subjected to a few possible dynamical states governed by simple fractal rules, and allowed to decide its own fate by choosing one of these states which are contributed from long range correlation with varied fluctuations due to active molecular interaction. The topological properties of the networks corresponding to these dynamical states have hierarchical features with assortive structure. The stress signal driven by nutlin and modulated by mediator GSK3 acts as anti-apoptotic signal in this system, whereas, the stress signal driven by Axin and modulated by GSK3 behaves as anti-apoptotic for a certain range of Axin and GSK3 interaction, and beyond which the signal acts as favor-apoptotic signal. However, this stress system prefers to stay in an active dynamical state whose counterpart complex network is closest to hierarchical topology with exhibited roles of few interacting hubs. During the propagation of stress signal, the system allows the propagator pathway to inherit all possible properties of the state to the receiver pathway/pathways with slight modifications, indicating efficient information processing and democratic sharing of responsibilities in the system via cross-talk. The increase in the number of cross-talk pathways in the system favors to establish self-organization.
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http://dx.doi.org/10.1038/srep40596DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5247771PMC
January 2017

Control of apoptosis by SMAR1.

Mol Biosyst 2017 Jan;13(2):350-362

School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110067, India.

The nuclear matrix associated protein SMAR1 is sensitive to p53 and acts as a stress inducer as well as a regulator in the p53 regulatory network. Depending on the amount of stress SMAR1 stimulates, it can drive the p53 dynamics in the system to various dynamical states which correspond to various cellular states. The behavior of p53 in these dynamical states is found to be multifractal, due to the mostly long range correlations and large scale fluctuations imparted by stress. This fractal behavior is exhibited in the topological properties of the networks constructed from these dynamical states, and is a signature of self-organization to optimize information flow in the dynamics. The assortativity found in these networks is due to perturbation induced by stress, and indicates that the hubs in the time series play a significant role in stress management. SMAR1 can also regulate apoptosis in the presence of HDAC1, depending on the stress induced by it.
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http://dx.doi.org/10.1039/c6mb00525jDOI Listing
January 2017

From ZikV genome to vaccine: in silico approach for the epitope-based peptide vaccine against Zika virus envelope glycoprotein.

Immunology 2016 Dec 7;149(4):386-399. Epub 2016 Sep 7.

Centre for Interdisciplinary Research in Basic Science, Jamia Millia Islamia, New Delhi, India.

Zika virus (ZikV) has emerged as a potential threat to human health worldwide. A member of the Flaviviridae, ZikV is transmitted to humans by mosquitoes. It is related to other pathogenic vector-borne flaviviruses including dengue, West Nile and Japanese encephalitis viruses, but produces a comparatively mild disease in humans. As a result of its epidemic outbreak and the lack of potential medication, there is a need for improved vaccine/drugs. Computational techniques will provide further information about this virus. Comparative analysis of ZikV genomes should lead to the identification of the core characteristics that define a virus family, as well as its unique properties, while phylogenetic analysis will show the evolutionary relationships and provide clues about the protein's ancestry. Envelope glycoprotein of ZikV was obtained from a protein database and the most immunogenic epitope for T cells and B cells involved in cell-mediated immunity, whereas B cells are primarily responsible for humoral immunity. We mainly focused on MHC class I potential peptides. YRIMLSVHG, VLIFLSTAV and MMLELDPPF, GLDFSDLYY are the most potent peptides predicted as epitopes for CD4 and CD8 T cells, respectively, whereas MMLELDPPF and GLDFSDLYY had the highest pMHC-I immunogenicity score and these are further tested for interaction against the HLA molecules, using in silico docking techniques to verify the binding cleft epitope. However, this is an introductory approach to design an epitope-based peptide vaccine against ZikV; we hope that this model will be helpful in designing and predicting novel vaccine candidates.
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http://dx.doi.org/10.1111/imm.12656DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5095496PMC
December 2016

Scaling in topological properties of brain networks.

Sci Rep 2016 04 26;6:24926. Epub 2016 Apr 26.

School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110067, India.

The organization in brain networks shows highly modular features with weak inter-modular interaction. The topology of the networks involves emergence of modules and sub-modules at different levels of constitution governed by fractal laws that are signatures of self-organization in complex networks. The modular organization, in terms of modular mass, inter-modular, and intra-modular interaction, also obeys fractal nature. The parameters which characterize topological properties of brain networks follow one parameter scaling theory in all levels of network structure, which reveals the self-similar rules governing the network structure. Further, the calculated fractal dimensions of brain networks of different species are found to decrease when one goes from lower to higher level species which implicates the more ordered and self-organized topography at higher level species. The sparsely distributed hubs in brain networks may be most influencing nodes but their absence may not cause network breakdown, and centrality parameters characterizing them also follow one parameter scaling law indicating self-similar roles of these hubs at different levels of organization in brain networks. The local-community-paradigm decomposition plot and calculated local-community-paradigm-correlation co-efficient of brain networks also shows the evidence for self-organization in these networks.
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http://dx.doi.org/10.1038/srep24926DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4845066PMC
April 2016

Human Disease Insight: An integrated knowledge-based platform for disease-gene-drug information.

J Infect Public Health 2016 May-Jun;9(3):331-8. Epub 2015 Nov 27.

Centre for Interdisciplinary Research In Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India. Electronic address:

The scope of the Human Disease Insight (HDI) database is not limited to researchers or physicians as it also provides basic information to non-professionals and creates disease awareness, thereby reducing the chances of patient suffering due to ignorance. HDI is a knowledge-based resource providing information on human diseases to both scientists and the general public. Here, our mission is to provide a comprehensive human disease database containing most of the available useful information, with extensive cross-referencing. HDI is a knowledge management system that acts as a central hub to access information about human diseases and associated drugs and genes. In addition, HDI contains well-classified bioinformatics tools with helpful descriptions. These integrated bioinformatics tools enable researchers to annotate disease-specific genes and perform protein analysis, search for biomarkers and identify potential vaccine candidates. Eventually, these tools will facilitate the analysis of disease-associated data. The HDI provides two types of search capabilities and includes provisions for downloading, uploading and searching disease/gene/drug-related information. The logistical design of the HDI allows for regular updating. The database is designed to work best with Mozilla Firefox and Google Chrome and is freely accessible at http://humandiseaseinsight.com.
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http://dx.doi.org/10.1016/j.jiph.2015.10.018DOI Listing
January 2017

Dynamics of p53 and Wnt cross talk.

Comput Biol Chem 2015 Dec 23;59 Pt B:55-66. Epub 2015 Aug 23.

School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India. Electronic address:

We present the mechanism of interaction of Wnt network module, which is responsible for periodic somitogenesis, with p53 regulatory network, which is one of the main regulators of various cellular functions, and switching of various oscillating states by investigating p53-Wnt model. The variation in Nutlin concentration in p53 regulating network drives the Wnt network module to different states, stabilized, damped and sustain oscillation states, and even to cycle arrest. Similarly, the change in Axin2 concentration in Wnt could able to modulate the p53 dynamics at these states. We then solve the set of coupled ordinary differential equations of the model using quasi steady state approximation. We, further, demonstrate the change of p53 and GSK3 interaction rate, due to hypothetical catalytic reaction or external stimuli, can able to regulate the dynamics of the two network modules, and even can control their dynamics to protect the system from cycle arrest (apoptosis).
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http://dx.doi.org/10.1016/j.compbiolchem.2015.07.014DOI Listing
December 2015

Molecular characterization of dengue and chikungunya virus strains circulating in New Delhi, India.

Microbiol Immunol 2014 Dec;58(12):688-96

Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, 110025, India.

Dengue and chikungunya are acute viral infections with overlapping clinical symptoms. Both diseases are transmitted by common mosquito vectors resulting in their co-circulation in a region. Molecular and serological tests specific for both dengue and chikungunya infections were performed on 87 acute phase blood samples collected from patients with suspected dengue/chikungunya infections in Delhi from September to December, 2011. RT-PCR and IgM ELISA were performed to detect dengue virus (DENV) and chikungunya virus (CHIKV). NS1 and IgG ELISA were also performed to detect DENV specific antigen and secondary DENV infection. DENV infection was detected in 49%, CHIKV infection in 29% and co-infection with DENV and CHIKV in 10% of the samples by RT-PCR. DENV serotypes 1, 2 and 3 were detected in this study. Nine DENV-1 strains, six DENV-2 strains and 20 CHIKV strains were characterized by DNA sequencing and phylogenetic analysis of their respective envelope protein genes. DENV-1 strains grouped in the American African genotype, DENV-2 strains in the Cosmopolitan genotype and CHIKV strains in the East Central South African genotype by phylogenetic analysis. This is one of the few studies reporting the phylogeny of two dengue virus serotypes (DENV-1 and DENV-2) and CHIKV. Surveillance and monitoring of DENV and CHIKV strains are important for design of strategies to control impending epidemics.
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http://dx.doi.org/10.1111/1348-0421.12209DOI Listing
December 2014

Intercellular synchronization of coupled smooth muscle cells via Ca2+ propagation.

J Nanosci Nanotechnol 2012 Nov;12(11):8303-15

Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India.

The propagation of Ca2+ wave through gap junction in smooth muscle cell is studied as a function of electrical coupling parameter (g) modulated by Ca2+ level in the cell. The range of activation time of Ca2+ propagation with amplitude is found to increase as increase in electrical coupling parameter g, which is identified by increase in critical time of activation, T(F) as a function of g. Then identical Ca2+ oscillators are allowed to interact via electrical and diffusive coupling of Ca2+ ions diffused through gap junctions, and rate of intercellular synchronization among them is studied. The phase diagrams in (T(F) - g) and (T(F) - epsilon) parameter spaces separate oscillation death and damped oscillations regimes which correspond to deactivated and activated regimes of Ca2+ level. The effect of on T(F) is significantly very slow, however it enhances the rate of synchronization among the coupled oscillators. The increase in g comparatively slows down the rate of synchronization of the coupled oscillators as shown in the phase diagram in (epsilon - g) parameter space which separates desynchronized and synchronized regimes.
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http://dx.doi.org/10.1166/jnn.2012.6632DOI Listing
November 2012

Switching p53 states by calcium: dynamics and interaction of stress systems.

Mol Biosyst 2013 Mar 29;9(3):508-21. Epub 2013 Jan 29.

Center for Interdisciplinary Research in Basic Science, Jamia Millia Islamia, New Delhi, 110025, India.

The integration of calcium and a p53-Mdm2 oscillator model is studied using a deterministic as well as a stochastic approach, to investigate the impact of a calcium wave on single cell dynamics and on the inter-oscillator interaction. The high dose of calcium in the system activates the nitric oxide synthase, synthesizing nitric oxide which then downregulates Mdm2 and influences drastically the p53-Mdm2 network regulation, lifting the system from a normal to a stressed state. The increase in calcium level switches the system to different states, as identified by the different behaviours of the p53 temporal dynamics, i.e. oscillation death to sustain the oscillation state via a mixed state of dampened and oscillation death states. Further increase of the calcium dose in the system switches the system from sustained to oscillation death state again, while an excess of calcium shifts the cell to an apoptotic state. Another important property of the calcium ion is its ability to behave as a synchronizing agent among the interacting systems. The time evolution of the p53 dynamics of the two diffusively coupled systems at stress condition via Ca(2+) shows synchronization between the two systems. The noise contained in the system interestingly helps the system to maintain its stabilized state (normal condition). However, noise has the tendency to destruct the synchronization effect, which means that it tries to restrict the system from external signals to maintain its normal condition. However, at the stress condition, the synchronization rate is found to be faster.
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http://dx.doi.org/10.1039/c3mb25277aDOI Listing
March 2013