Institute of Genomics and Integrative Biology
Recent publications
Background Histone deacetylases (HDACs) that catalyze removal of acetyl groups from histone proteins, are strongly associated with several diseases including diabetes, yet the precise regulatory events that control the levels and activity of the HDACs are not yet well elucidated. Methods Levels of H19 and HDACs were evaluated in skeletal muscles of normal and diabetic db/db mice by Western Blot analysis. C2C12 cells were differentiated and transfected with either the scramble or H19 siRNA and the levels of HDACs and Prkab2 , Pfkfb3 , Srebf1 , Socs2 , Irs1 and Ppp2r5b were assessed by Western Blot analysis and qRT-PCR, respectively. Levels of H9, HDAC6 and IRS1 were evaluated in skeletal muscles of scramble/ H19 siRNA injected mice and chow/HFD-fed mice. Results Our data show that the lncRNA H19 and HDAC6 exhibit inverse patterns of expression in the skeletal muscle of diabetic db/db mice and in C2C12 cells, H19 inhibition led to significant increase in HDAC activity and in the levels of HDAC6, both at the transcript and protein levels. This was associated with downregulation of IRS1 levels that were prevented in the presence of the HDAC inhibitor, SAHA, and HDAC6 siRNA suggesting the lncRNA H19-HDAC6 axis possibly regulates cellular IRS1 levels. Such patterns of H19, HDAC6 and IRS1 expression were also validated and confirmed in high fat diet-fed mice where as compared to normal chow-fed mice, H19 levels were significantly inhibited in the skeletal muscle of these mice and this was accompanied with elevated HDAC6 levels and decreased IRS1 levels. In-vivo inhibition of H19 led to significant increase in HDAC6 levels and this was associated with a decrease in IRS1 levels in the skeletal muscle. Conclusions Our results suggest a critical role for the lncRNA H19-HDAC6 axis in regulating IRS1 levels in the skeletal muscle during diabetes and therefore restoring normal H19 levels might hold a therapeutic potential for the management of aberrant skeletal muscle physiology during insulin resistance and type 2 diabetes.
Given the spasmodic increment in antimicrobial resistance (AMR), world is on the verge of “post-antibiotic era”. It is anticipated that current SARS-CoV2 pandemic would worsen the situation in future, mainly due to the lack of new/next generation of antimicrobials. In this context, nanoscale materials with antimicrobial potential have a great promise to treat deadly pathogens. These functional materials are uniquely positioned to effectively interfere with the bacterial systems and augment biofilm penetration. Most importantly, the core substance, surface chemistry, shape, and size of nanomaterials define their efficacy while avoiding the development of AMR. Here, we review the mechanisms of AMR and emerging applications of nanoscale functional materials as an excellent substitute for conventional antibiotics. We discuss the potential, promises, challenges and prospects of nanobiotics to combat AMR. Graphical Abstract
The genome of a eukaryotic cell is often vulnerable to both intrinsic and extrinsic threats owing to its constant exposure to a myriad of heterogeneous compounds. Despite the availability of innate DNA damage responses, some genomic lesions trigger malignant transformation of cells. Accurate prediction of carcinogens is an ever-challenging task owing to the limited information about bona fide (non-)carcinogens. We developed Metabokiller, an ensemble classifier that accurately recognizes carcinogens by quantitatively assessing their electrophilicity, their potential to induce proliferation, oxidative stress, genomic instability, epigenome alterations, and anti-apoptotic response. Concomitant with the carcinogenicity prediction, Metabokiller is fully interpretable and outperforms existing best-practice methods for carcinogenicity prediction. Metabokiller unraveled potential carcinogenic human metabolites. To cross-validate Metabokiller predictions, we performed multiple functional assays using Saccharomyces cerevisiae and human cells with two Metabokiller-flagged human metabolites, namely 4-nitrocatechol and 3,4-dihydroxyphenylacetic acid, and observed high synergy between Metabokiller predictions and experimental validations. Metabokiller is a novel, explainable AI-backed method for carcinogenicity prediction that leverages the biological and chemical properties associated with carcinogens.
sgRNA/Cas9 ribonucleoproteins (RNPs) provide a site-specific robust gene-editing approach avoiding the mutagenesis and unwanted off-target effects. However, the high molecular weight (∼165 kDa), hydrophilicity and net supranegative charge (∼-20 mV) hinder the intracellular delivery of these RNPs. In the present study, we have prepared cationic RNPs lipopolymeric nanoplexes that showed a size of 117.3 ± 7.64 nm with +6.17 ± 1.04 mV zeta potential and >90% entrapment efficiency of RNPs. Further, these RNPs lipopolymeric nanoplexes showed good complexation efficiency and were found to be stable for 12 h with fetal bovine serum. These RNPs lipopolymeric nanoplexes did not induce any significant cytotoxicity in HEK293T cells, and were efficiently uptaken via a clathrin-mediated pathway with optimal transfection efficiency and nuclear localization after 48 h. Further, HEK293T cells having the mGFP insert were used as a cell line model for gene editing, wherein the loss of the mGFP signal was observed as a function of gene editing after transfection with mGFP targeting RNPs lipopolymeric nanoplexes. Further, the T7 endonuclease and TIDE assay data showed a decent gene editing efficiency. Additionally, the lipopolymeric nanoplexes were able to transfect muscle cells in vivo, when injected intra-muscularly. Collectively, this study explored the potential of cationic lipopolymeric nanoplexes for delivering gene-editing endonucleases.
Background The prevalence and genetic spectrum of cardiac channelopathies exhibit population-specific differences. We aimed to understand the spectrum of cardiac channelopathy-associated variations in India, which is characterised by a genetically diverse population and is largely understudied in the context of these disorders. Results We utilised the IndiGenomes dataset comprising 1029 whole genomes from self-declared healthy individuals as a template to filter variants in 36 genes known to cause cardiac channelopathies. Our analysis revealed 186,782 variants, of which we filtered 470 variants that were identified as possibly pathogenic (440 nonsynonymous, 30 high-confidence predicted loss of function ). About 26% (124 out of 470) of these variants were unique to the Indian population as they were not reported in the global population datasets and published literature. Classification of 470 variants by ACMG/AMP guidelines unveiled 13 pathogenic/likely pathogenic (P/LP) variants mapping to 19 out of the 1029 individuals. Further query of 53 probands in an independent cohort of cardiac channelopathy, using exome sequencing, revealed the presence of 3 out of the 13 P/LP variants. The identification of p.G179Sfs*62, p.R823W and c.420 + 2 T > C variants in KCNQ1, KCNH2 and CASQ2 genes, respectively, validate the significance of the P/LP variants in the context of clinical applicability as well as for large-scale population analysis. Conclusion A compendium of ACMG/AMP classified cardiac channelopathy variants in 1029 self-declared healthy Indian population was created. A conservative genotypic prevalence was estimated to be 0.9–1.8% which poses a huge public health burden for a country with large population size like India. In the majority of cases, these disorders are manageable and the risk of sudden cardiac death can be alleviated by appropriate lifestyle modifications as well as treatment regimens/clinical interventions. Clinical utility of the obtained variants was demonstrated using a cardiac channelopathy patient cohort. Our study emphasises the need for large-scale population screening to identify at-risk individuals and take preventive measures. However, we suggest cautious clinical interpretation to be exercised by taking other cardiac channelopathy risk factors into account.
Here, a series of amphiphilic inulin‐azobenzene (IAb) conjugates has been synthesized by the reaction of inulin, a naturally occurring polysaccharide, with varying amounts of 6‐(3‐(4‐[4‐dimethylaminophenylazo]‐phenyl)‐thioureido)‐hexanoic acid (Azo‐ahx), an azobenzene linker. The resulting IAb conjugates (IAb‐1, IAb‐2 and IAb‐3 with 1, 3, and 5% substitution of the linker, respectively) self‐assembled into nanostructures in aqueous environment, which were then used to encapsulate the hydrophobic drug molecules, ornidazole (OZ) and 5‐fluorouracil (FU). Drug loaded and unloaded nanostructures were subjected to characterization by spectroscopic and dynamic light scattering (DLS) techniques. The sustained drug release behavior of these nanostructures was studied by dialysis bag method at different pH values. Enzyme‐responsive drug release behavior was investigated under the influence of inulinase. Besides, the best formulation, IAb‐1, not only showed antioxidant potential but also exhibited good wound healing properties as evidenced by in vitro scratch assay in HaCaT cells. The self‐assembled nanostructures of IAb‐1 were found be non‐toxic to cells even up to 700 μg/ml as tested by MTT assay on HEK 293 and HeLa cells. In conclusion, the potential of self‐assembled drug loaded inulin‐azo nanostructures has been demonstrated for the targeted drug delivery applications. Drug‐loaded nanostructures of amphiphilic inulin‐azobenzene conjugates exhibit stimuli‐responsive drug release.
Background In-silico mapping of epitopes by immune-informatics has simplified efforts towards understanding antigen-antibody interactions. The knowledge of allergen epitopes may help in advancing diagnosis and therapy of allergic diseases. Objective This study was intended to identify B and T cell epitopes of cysteine protease allergen of Phaseolus vulgaris. Methods Modeller 9v11 software was used for generation of three-dimensional model of cysteine protease and quality assessment was performed using SAVES webserver and other in silico software. Linear and conformational B and T cell epitopes were predicted via immuno-informatics based computational servers. Epitopes were synthesized and their immunoreactivity was analyzed using specific IgE ELISA with food allergy positive patient’s sera. Cellular immune response of peptides was determined through basophil activation assay. Consurf and SDAP (property distance) were used to examine the evolutionary conservancy and potential cross-reactivity of predicted epitopes. MSA based positional conservancy between HDM allergen epitopes and predicted peptides was also established using IEDB epitope database. Finally, population coverage for each promiscuous T cell epitope was predicted using IEDB population coverage analysis tool. Results Cysteine protease structure was derived by homology modeling and combination of bioinformatic tools predicted three B- and three T-cell peptides by consensus method and validated computationally. ELISA with kidney bean sensitive patient’s sera showed higher IgE binding of B-cell peptides as compared to T-cell or control peptides. Epitope conservancy revealed B-cell epitopes being upto 95% conserved in comparison to variable T-cell epitopes (upto 69%). B-cell peptides were cross-reactive with homologous allergens based on PD values. Structural comparison of cysteine protease with Der p 1 and Der f 1 showed similar epitopic regions, validating prediction accuracy of epitopes. Promiscuous T-cell epitopes binding to broad-spectrum class-II MHC alleles demonstrated distribution of T-cell peptides world-wide (30-98%) and in Asian population (99%). The current approach can be applied for identification of epitopes. Analysis of cross-reactive and widely-distributed specific epitopes of allergen and knowledge about their interacting surfaces will help in understanding of food allergy and related immune responses. Conclusion The current approach can be applied for identification of epitopes. Analysis of cross-reactive and widely-distributed specific epitopes of allergen and knowledge about their interactive surfaces will help in understanding of food allergy and related immune responses.
Mowat–Wilson syndrome (MWS; Online Mendelian Inheritance in Man #235730) is a rare disorder characterized by developmental delay, severe intellectual disability, distinctive facial dysmorphism, and multiple associated abnormalities caused by mutation or deletion of ZEB2 gene. Here we report a 13 months old boy with characteristic facial features of MWS, global developmental delay, peculiar behavior, microcephaly, and hypospadias. Array comparative genomic hybridization (CGH) revealed a 5.7-Mb deletion of 2q22.2q22.3 region. The deletion contains 10 genes, including LRP1B, KYNU, ARHGAP15, GTDC1, ZEB2, ZEB2-AS1, TEX41, MBD5, ORC4, and ACVR2A. Our case shows the utility of array CGH in identifying such complex phenotype.
Here, we analysed the genomic evolution in extremophilic bacteria using long simple sequence repeats (SSRs). Frequencies of occurrence, relative abundance (RA) and relative density (RD) of long SSRs were analysed in the genomes of extremophilic bacteria. Thermus aquaticus had the most RA and RD of long SSRs in its coding sequences (110.6 and 1408.3), followed by Rhodoferax antarcticus (77.0 and 1187.4). A positive correlation was observed between G + C content and the RA–RD of long SSRs. Geobacillus kaustophilus, Geobacillus thermoleovorans, Halothermothrix orenii, R. antarcticus, and T. aquaticus preferred trinucleotide repeats within their genomes, whereas others preferred a higher number of tetranucleotide repeats. Gene enrichment showed the presence of these long SSRs in metabolic enzyme encoding genes related to stress tolerance. To analyse the functional implications of SSR insertions, three-dimensional protein structure modelling of SSR containing diguanylate cyclase (DGC) gene encoding protein was carried out. Removal of SSR sequence led to an inappropriate folding and instability of the modelled protein structure.
The development of bioactive implantable materials with multi-functional properties like tissue regeneration, tumor annihilation, anti-bacterial growth and angiogenesis advancement is of great importance. In this context, mesoporous bioactive glasses (MBGs) are gaining tremendous interest in designing the next generation of biomaterials for the bone defect treatment. In this work, ternary SiO2-CaO-P2O5 MBGs have been synthesized by using the acid assisted sol-gel process. In contrast to the conventional process, we adopted an ethanol extraction process to remove surfactant, leading to superior textual properties and high silanol group density in resultant bioglass. Magic angle spinning nuclear magnetic resonance (MAS-NMR) technique has been used to elucidate the presence of different anionic species in the pristine glass samples and its variation with chemical compositions. The vibrational spectroscopy reveals the presence of high concentration of silanol group over the surface of pristine glass samples, which effectively accelerates the formation of hydroxyl carbonate apatite (HCA) layer. The MBG specimens show a good cell viability behavior without toxicity up to the concentration of 20 µg ml⁻¹. In the present results, we observed that pore size along with surface area and silanol group density play an effective role in the growth of HCA layer.
Background Disease-specific human induced pluripotent stem cells (hiPSCs) can be generated directly from individuals with known disease characteristics or alternatively be modified using genome editing approaches to introduce disease causing genetic mutations to study the biological response of those mutations. The genome editing procedure in hiPSCs is still inefficient, particularly when it comes to homology directed repair (HDR) of genetic mutations or targeted transgene insertion in the genome and single cell cloning of edited cells. In addition, genome editing processes also involve additional cellular stresses such as poor cell viability and genetic stability of hiPSCs. Therefore, efficient workflows are desired to increase genome editing application to hiPSC disease models and therapeutic applications. Methods and results To this end, we demonstrate an efficient workflow for feeder-free single cell clone generation and expansion in both CRISPR-mediated knock-out (KO) and knock-in (KI) hiPSC lines. Using StemFlex medium and CloneR supplement in conjunction with Matrigel cell culture matrix, we show that cell viability and expansion during single-cell cloning in edited and unedited cells is significantly enhanced. Keeping all factors into account, we have successfully achieved hiPSC single-cell survival and cloning in both edited and unedited cells with rates as maximum as 70% in less than 2 weeks. Conclusion This simplified and efficient workflow will allow for a new level of sophistication in generating hiPSC-based disease models to promote rapid advancement in basic research and also the development of novel cellular therapeutics.
Reversible protein phosphorylation at serine/threonine residues is one of the most common protein modifications, widely observed in all kingdoms of life. The catalysts controlling this modification are specific serine/threonine kinases and phosphatases that modulate various cellular pathways ranging from growth to cellular death. Genome sequencing and various omics studies have led to the identification of numerous serine/threonine kinases and cognate phosphatases, yet the physiological relevance of many of these proteins remain enigmatic. In Bacillus anthracis , only one ser/thr phosphatase, PrpC, has been functionally characterized; it was reported to be non-essential for bacterial growth and survival. In the present study, we characterized another ser/thr phosphatase (PrpN) of B . anthracis by various structural and functional approaches. To examine its physiological relevance in B . anthracis , a null mutant strain of prpN was generated and shown to have defects in sporulation and reduced synthesis of toxins (PA and LF) and the toxin activator protein AtxA. We also identified CodY, a global transcriptional regulator, as a target of PrpN and ser/thr kinase PrkC. CodY phosphorylation strongly controlled its binding to the promoter region of atxA , as shown using phosphomimetic and phosphoablative mutants. In nutshell, the present study reports phosphorylation-mediated regulation of CodY activity in the context of anthrax toxin synthesis in B . anthracis by a previously uncharacterized ser/thr protein phosphatase–PrpN.
Limbus-derived stromal/mesenchymal stem cells (LMSCs) are vital for corneal homeostasis and wound healing. However, despite multiple pre-clinical and clinical studies reporting the potency of LMSCs in avoiding inflammation and scarring during corneal wound healing, the molecular basis for the ability of LMSCs remains unknown. This study aimed to uncover the factors and pathways involved in LMSC-mediated corneal wound healing by employing RNA-Sequencing (RNA-Seq) in human LMSCs for the first time. We characterized the cultured LMSCs at the stages of initiation (LMSC−P0) and pure population (LMSC−P3) and subjected them to RNA-Seq to identify the differentially expressed genes (DEGs) in comparison to native limbus and cornea, and scleral tissues. Of the 28,000 genes detected, 7800 DEGs were subjected to pathway-specific enrichment Gene Ontology (GO) analysis. These DEGs were involved in Wnt, TGF-β signaling pathways, and 16 other biological processes, including apoptosis, cell motility, tissue remodeling, and stem cell maintenance, etc. Two hundred fifty-four genes were related to wound healing pathways. COL5A1 (11.81 ± 0.48) and TIMP1 (20.44 ± 0.94) genes were exclusively up-regulated in LMSC−P3. Our findings provide new insights involved in LMSC-mediated corneal wound healing.
Sickle cell disease (SCD) is the most prevalent life-threatening blood monogenic disorder. Currently, there is no cure available, apart from bone marrow transplantation. Early and efficient diagnosis of SCD is key to disease management, which would make considerable strides in alleviating morbidity and reducing mortality. However, the cost and complexity of diagnostic procedures, such as the Sanger sequencing method, impede the early detection of SCD in a resource-limited setting. To address this, the current study demonstrates a simple and efficient proof-of-concept assay for the detection of patients and carriers using extraction-free non-invasive buccal swab samples by isothermal DNA Amplification coupled Restrictase-mediated cleavage (iDAR). This study is a first of its kind reporting the use of buccal swab specimens for iDA in molecular diagnosis of a genetic disease, all the while being cost effective and time saving, with the total assay time of around 150 min at a cost of USD 5. Further, iDAR demonstrates 91.5% sensitivity and 100% specificity for detecting all three alleles: SS, AS, and AA, having a 100% concordance with Sanger sequencing. The applicability of the iDAR assay is further demonstrated with its adaptation to a one-pot reaction format, which simplifies the assay system. Overall, iDAR is a simple, cost-effective, precise, and non-invasive assay for SCD screening, with the potential for use in a limited resource setting.
The emergence of drug resistance and the limited number of approved antitubercular drugs prompted identification and development of new antitubercular compounds to cure tuberculosis (TB). In this work, an attempt was made to identify potential natural compounds that target mycobacterial proteins. Three plant extracts (A. aspera, C. gigantea and C. procera) were investigated. The ethyl acetate fraction of the aerial part of A. aspera and the flower ash of C. gigantea were found to be effective against M. tuberculosis H37Rv. Furthermore, the GC-MS analysis of the plant fractions confirmed the presence of active compounds in the extracts. The Mycobacterium target proteins, i.e., available PDB dataset proteins and proteins classified in virulence, detoxification, and adaptation, were investigated. A total of ten target proteins were shortlisted for further study, identified as follows: BpoC, RipA, MazF4, RipD, TB15.3, VapC15, VapC20, VapC21, TB31.7, and MazF9. Molecular docking studies showed that β-amyrin interacted with most of these proteins and its highest binding affinity was observed with Mycobacterium Rv1636 (TB15.3) protein. The stability of the protein-ligand complex was assessed by molecular dynamic simulation, which confirmed that β-amyrin most firmly interacted with Rv1636 protein. Rv1636 is a universal stress protein, which regulates Mycobacterium growth in different stress conditions and, thus, targeting Rv1636 makes M. tuberculosis vulnerable to host-derived stress conditions.
Pathogenic bacteria use phase variation of surface molecules and other characteristics as a significant adaptation mechanism. Repetitive sequences made up of numerous identical repeat units can be found in many phase variable genes. Here, we investigated the frequency and distribution of long-SSRs (Simple Sequence Repeats) in 15 human pathogenic Staphylococcus, Streptococcus, and Enterococcus bacteria. Long-SSRs were found to be distributed differently in the genic and inter-genic sequences. In the genic sequences, 61.3 SSRs were discovered on average, while 16.2 SSRs were found in the intergenic regions. Staphylococcus exhibited the highest frequency of SSRs, followed by Enterococcus, and Streptococcus had the lowest frequency of SSRs. Higher A+T content was found to be the best predictor of long-SSR in these human pathogens. Tetranucleotide repeats predominated in inte-rgenic regions, while trinucleotide repeats were in the majority in genic regions. In human pathogenic Streptococcus and Staphylococcus bacteria, genus-specific encoding of amino acids by tri-nucleotide SSRs was observed. Based on the presence of SSRs in housekeeping genes, a genetic relationship between these human pathogenic bacteria was constructed and compared to a phylogeny based on the 16S ribosomal RNA gene.
The use of many essential drugs is restricted due to their deleterious effects on the liver. Molecules that can prevent or protect the liver from drug-induced liver injury (DILI) would be invaluable in such situations. We used a transgenic line in zebrafish with a hepatocyte-specific expression of bacterial nitroreductase to cause temporally controlled liver damage. A whole organism-based chemical screen using the transgenic line identified BML-257, a potent small molecule AKT inhibitor, that protected the liver against metronidazole-induced liver injury. BML-257 also showed potent prophylactic and pro-regenerative activity in this liver damage model. BML-257 was tested in two independent toxicological models of liver injury caused by acetaminophen and isoniazid and was found to be protective against damage. This suggests that BML-257 has the potential to protect against multiple kinds of DILI.
Recent advances in the field of cognitive sciences have provided evidence to classify activities with different cognitive engagement levels. High cognitive load and sustained attention may predispose an individual to psychological and physical stress and may result in a lack of performance. Cognitive load monitoring of professionals in high precision fields has gathered significant attention in the current research scenario. The proposed work in continuity has tried to demonstrate the use of two non‐invasive physiological sensing modalities viz. galvanic skin response (GSR) and photoplethysmography (PPG) to elucidate effectiveness in picking up differences of two induced cognitive state categories based on machine learning and statistical methods. This paper demonstrates how GSR and PPG signals data can be effectively utilized to examine the shift in cognitive load. The present work proposes the use of general linear chirplet transform (GLCT) to evaluate the time‐frequency characteristic of GSR and PPG signals and utilize the statistical features in classification. Random Forest, Decision Tree, and k‐Nearest Neighbours demonstrated an accuracy of 92.13%, 88.0%, and 86.13% respectively on a dataset of 20 subjects against an optimized feature set, thus demonstrating the effectiveness of the proposed methodology for differentiating pre‐defined categories of cognitive load. The study shows the potential of GSR and PPG signals attributes and time‐frequency representation using GLCT to monitor cognitive load in real‐life conditions. The proposed work also indicates the possibility to extend the same to attention‐demanding fields such as aviation, medicine, and manufacturing for effective remediation of fatigue periods with increased cognitive demand, which, if sustained, may lead to cognitive decline in the long run.
Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inacti-vated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective , indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concor-dant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.
Inhibition of carbohydrate digestion and modulation of glucose uptake are the major mechanisms of anti-hyperglycemic potential known to be played by phenolics; but the role of archaeologically relevant staple pearl millet (Pennisetum glaucum; PM), is still much unknown. A combined approach using in vitro inhibitory data and in silico docking of PM phenolics against key players of glucose homeostasis (salivary α-amylase: SA; pancreatic α-amylase: PA; α-glucosidase, maltase-glucoamylase: MGAM and GLUT2) were carried out. Observed notable inhibition with HHB299 having the most relevant effect (IC50: 73.06 ± 0.37 μg/mL for α-amylase; IC50: 73.80 ± 0.12 μg/mL for α-glucosidase). The role of phenolics on basal glucose uptake into hepatocytes, revealed a maximum of 241.25% in PC612 and the least of 198.1% in HHB67imp. Virtual screening via docking found that 3, 4-Di-OMe luteolin, acacetin as the major flavonoids while salicylic acid, melilotic acid as the key phenolic acids contributing towards the observed anti-diabetic effect. Further, structure-activity relationship (SAR) identified the critical functional groups required for the protein-phenolic molecular interactions. This report validates the role of PM phenolics in inhibiting carbolytic enzymes and regulating GLUT and thus probes the link towards the anti-diabetic potential.
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Pradip Nahar
  • Low cost innovative diagnostics; Chemical and Systems Biology Research Area (IGIB)
Kausik Chakraborty
  • Chemical and Systems Biology Research Area (IGIB)
Vinod Scaria
  • Genome Informatics and Structural Biology Research Area (IGIB)
Debojyoti Chakraborty
  • Chemical and Systems Biology Research Area (IGIB)
Saakshi Jalali
  • Genome Informatics and Structural Biology Research Area (IGIB)
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