Biology subjects

Sharma, M.

Publications and source records attributed to Sharma, M..

11 recordsLinked to original sources

bioRxiv2018

Enumeration, Antagonism and Enzymatic Activities of Microorganisms Isolated from Railway Station Soil

Soil is the well-known hotspot for microbial diversity. Therefore, for our investigation, we isolated, characterized, and identified microorganisms from railway station soil. Sampling was done subsequently after every 15 days interval, and from two different soil depths i.e. 0-15 cm and below during March to May of 2013. Further, soil isolates were examined for their antagonistic activity, against four soil born plant pathogens namely, Rhizoctonia solani, Aspergillus niger, Fusarium f sp pisi, and Sclerotinia sclerotiorum. Subsequently, isolates were screened for the presence of amylases, proteases, lipases and cellulases. For each interval of soil sampling, a gradual reduction in the microbial count was noticed from month March to May. Mucor species was observed only in the rainy days. The most promising enzymes producers were Bacillus sp., Aspergillus and Penicillium sp. Overall, the fungal isolates were better producers of enzymes as compared to bacterial isolates.

microbiology↗

bioRxiv2018

Parkinson disease age of onset GWAS: defining heritability, genetic loci and a-synuclein mechanisms

Increasing evidence supports an extensive and complex genetic contribution to Parkinsons disease (PD). Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age of onset are largely unknown. Here we performed an age of onset GWAS based on 28,568 PD cases. We estimated that the heritability of PD age of onset due to common genetic variation was ~0.11, lower than the overall heritability of risk for PD (~0.27) likely in part because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni corrected significant effect at other known PD risk loci, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. In addition, we identified that GBA coding variant carriers had an earlier age of onset compared to non-carriers. Notably, SNCA, TMEM175, SCARB2, BAG3 and GBA have all been shown to either directly influence alpha-synuclein aggregation or are implicated in alpha-synuclein aggregation pathways. Remarkably, other well-established PD risk loci such as GCH1, MAPT and RAB7L1/NUCKS1 (PARK16) did not show a significant effect on age of onset of PD. While for some loci, this may be a measure of power, this is clearly not the case for the MAPT locus; thus genetic variability at this locus influences whether but not when an individual develops disease. We believe this is an important mechanistic and therapeutic distinction. Furthermore, these data support a model in which alpha-synuclein and lysosomal mechanisms impact not only PD risk but also age of disease onset and highlights that therapies that target alpha-synuclein aggregation are more likely to be disease-modifying than therapies targeting other pathways.

genetics↗

bioRxiv2018

Pharmacophore-driven Identification of N-Methyl-D-Receptor Antagonists as Potent Neuroprotective Agents Validated Using In-Vivo Studies

Alzheimers disease (AD), the most widespread cause of dementia is delineated by progressive cognitive impairment in the elderly people. During its progression, N-Methyl-D-Aspartate receptor antagonists are known to play a key role in the mechanisms of learning and memory. Extensive side effects alongside other effects on learning and memory have limited the therapeutic significance of various blockers and antagonists of the NMDA receptor. In this study, we identify potential compounds targeted against NMDA. In order to reveal the essential structural features for NMDA receptor, three-dimensional pharmacophore models are constructed based on a set of known NMDA inhibitors. This is followed by virtual screening which results in novel chemical compounds having the potential to inhibit NMDA. The lead compounds are then subjected to molecular docking and assessed by a scoring function, which results in two compounds with high Libdock scores. These compounds also show interactions with important residues at the active site. The compounds are shortlisted on the basis of high estimated activity, fit values, LibDock score, no violation to Lipinskis and availability for procuring.\n\nOf the shortlisted compounds, one compound satisfying the entire aforementioned criterion is further tested using in-vivo studies on mice with the help of an eight-arm radial maze. The pharmacophore-based virtual screening protocol presented in this study pave the way forward to address the unmet medical need of Alzheimer disease.

bioinformatics↗

bioRxiv2018

Structural insights into unique features of the human mitochondrial ribosome recycling

Mammalian mitochondrial ribosomes (mitoribosomes) are responsible for synthesizing proteins that are essential for oxidative phosphorylation or energy (ATP) generation. Despite their proposed bacterial origin, the composition and structure of the human mitoribosome and its translational factors are dramatically different from their bacterial counterparts. The mammalian mitoribosome recycling factor (RRFmt) carries a mito-specific N-terminus extension (NTE), which is necessary for the function of RRFmt. Here we present a 3.7 [A] resolution cryo-EM structure of the human 55S mitoribosome-RRFmt complex, which reveals -helix and loop structures for a portion of the NTE that makes multiple mito-specific interactions with functionally critical regions of the mitoribosome. These include ribosomal RNAs segments that constitute the peptidyl transferase center (PTC), those that connect PTC with the GTPase-associated center, and with multiple mitoribosomal proteins. Our structure also reveals novel conformational changes in mitoribosome due to RRFmt binding. Together, these findings help understand the unique features of mitoribosome recycling.

biophysics↗

bioRxiv2018

Atomic-level characterization of conformational transition and substrate binding of xCT transporter

xCT is a component of heterodimeric amino acids transporter system Xc- that has been known to work at the cross-roads of maintaining neurological processes and regulating antioxidant defense. xCT is a sodium-independent amino acid antiporter, that imports L- cystine and exports L-glutamate in a 1:1 ratio. The transporter has 12 transmembrane domains with intracellular N- and C-termini, which can undergo various conformational changes while switching the ligand accessibilities from intracellular to extracellular site. In the present study, we generated two homology models of human xCT in two distinct conformations: inward facing occluded state and outward facing open state. We investigated the conformational transitions within these two states by employing series of targeted molecular dynamics simulations. Our results indicated the substrate translocation channel composed of transmembrane helices TMs 1, 3, 6, 8, and 10. Further, we analyzed the ligand binding within the intermediate conformations obtained from the transition simulations. We docked anionic L-cystine and L-glutamate within the cavities alone or in combination to assess the two distinct binding scenarios for xCT as antiporter. We also assessed the interactions between the ligand and xCT and observed that ligands bind to similar residues within the channel, and these residues are essential for substrate binding/permeation. In addition, we analyzed the correlations between ligand binding and conformational transition and observed conformations that are representatives for intermediate ligand bound states. The results presented in the study provide insights into the interplay of conformational transition and ligand binding as xCT goes from one probable conformation to another while transporting the ligand. And the data thus adds to the existing evidence of alternating access mechanism pertaining to the functioning of transporters.

biophysics↗

bioRxiv2018

Parkinson’s disease genetics: identifying novel risk loci, providing causal insights and improving estimates of heritable risk

We performed the largest genome-wide association study of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases, and 1.4M controls. We identified 90 independent genome-wide significant signals across 78 loci, including 38 independent risk signals in 37 novel loci. These variants explained 26-36% of the heritable risk of PD. Tests of causality within a Mendelian randomization framework identified putatively causal genes for 70 risk signals. Tissue expression enrichment analysis suggested that signatures of PD loci were heavily brain-enriched, consistent with specific neuronal cell types being implicated from single cell expression data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. In sum, these data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified.

genetics↗

bioRxiv2018

Identification of novel and structurally diverse N-Methyl-D-Aspartate Receptor Antagonists: Successful Application of Pharmacophore Modeling, Virtual Screening and Molecular Docking

In view of \"excitotoxic\" effects of glutamate, wherein excessive excitatory input causes increase in intracellular Ca2+ and ultimately cell death, NMDA receptor has emerged as an important target for treatment and prevention of several neurological disorders, like Alzheimer disease. Prompted by the successful application of in-silico pharmacophore-based virtual screening in lead identification, we have made an effort to implement in-silico protocols to identify novel NMDA receptor antagonist. A series of novel benzo[b]quinolizinium cations as NMDA receptor antagonists have been used as a starting point to develop prognostic pharmacophore models. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, one hydrogen bond acceptor, one hydrophobic and two ring aromatic, showed a correlation (r) of 0.89, root mean square of 0.259, and the cost difference of 43.01 bits between null and fixed cost. The model was thoroughly validated and subjected to a chemical database search, which lead to the identification of 400 hits from NCI and Maybridge databases which were checked for Lipinskis violation and predictive potency.\n\nThis reduced the list to 10 compounds, out of which, two most potent compounds were subjected to molecular docking using Libdock software and interestingly, all the docked conformations showed hydrogen bond interactions with important amino acids Tyr214, His88, Thr174, Val169 and Arg121. In summary, through our validated pharmacophore-based virtual screening protocol, we have identified two potent, structurally diverse, druggable and novel NMDA receptor antagonist which might be of great help to address the unmet medical need of Alzheimer disease.

bioinformatics↗

bioRxiv2018

Assignment of the resting state of the secondary active transporter BetP by integrating spectroscopic measurements and molecular simulations

The glycine betaine symporter BetP regulates the osmotic stress response of Corynebacterium glutamicum, a soil bacterium used extensively in biotechnology. Although BetP is a homotrimer, biochemical studies have shown that each protomer is able to transport its substrate independently. Crystallographic structures of BetP have been determined in several conformations, seemingly capturing outward-open, inward-open and occluded states, both loaded with the substrate and in the apo form. However, it has been challenging to establish a correspondence between each of these structures and specific states in the mechanism of the transporter under more physiological conditions. To this end, we examined the dynamics of spin-labelled BetP using pulsed electron-electron double resonance (PELDOR) under different stimuli. We then carried out molecular simulations of structures of the BetP monomer to interpret the PELDOR data, using the enhanced-sampling methodology EBMetaD (1), whereby the dynamics of the protein are minimally biased so as to reproduce the experimental data. Comparison of the magnitude of the biasing work required for different input structures permitted us to assign them to specific states of the transport cycle under each of the experimental conditions. In particular, this analysis showed that BetP adopts inward-facing conformations in the presence of excess sodium, and a mixture of states when betaine is added. These studies better delineate the major conformations adopted by BetP in its transport cycle, and therefore provide important insights into its mechanism. More broadly, we illustrate how integrative simulations can aid interpretation of ambiguous structural and spectroscopic data on membrane proteins.\n\nAbbreviations

biophysics↗

bioRxiv2018

AchE-OGT dual inhibitors: Potential Partners in Handling Alzheimer’s Disease

The emerging role of O-GlcNAc Transferase (OGT) and tau protein in Alzheimers disease (AD) holds promises for the treatment of this life-threatening neurodegenerative disorder. In view of the availability of 3D structure of OGT, we attempted to develop structure-based pharmacophore model to elucidate specific structural requirements for binding of inhibitors to the active site of OGT. During the course of study we discovered that donepezil, an old and trusted Acetylcholinesterase (AchE) inhibitor also possess the pharmacophoric sites important for interaction with OGT active site. To further explore the specific interactions of donepezil with OGT, we performed molecular docking studies using CDocker. The results of molecular docking and structure-based pharmacophore mapping revealed that donepezil has the required structural features to interact with various OGT active site amino acids like Lys842, His920, Leu653, Gly654, Asn838, and Thr921 in addition to its AchE interaction abilities. Our findings could be an important breakthrough in the design of OGT specific and/or AchE OGT dual inhibitors.

bioinformatics↗

bioRxiv2017

A Web-resource for Nutrient Use Efficiency related Genes, QTLs, and microRNA in important cereals and model plants

Cereals are the key contributors to global food security. Genes involved in uptake (transport), assimilation and utilization of macro- and micro-nutrients are responsible for their content in grain and straw. Although many cereal genomic databases are available, currently there is no cohesive web-resource of manually curated nutrient use efficiency (NtUE) related genes and QTLs, etc. In this study, we present a web-resource containing information on NtUE related genes/QTLs and the corresponding available microRNAs for some of these genes in four major cereal crops [wheat (Triticum aestivum), rice (Oryza sativa), maize (Zea mays), barley (Hordeum vulgare)], two alien species (Triticum urartu and Aegilops tauschii) related to wheat, and two model species including Brachypodium distachyon and Arabidopsis thaliana. Gene annotations integrated in the current web-resource were collected from the existing databases and the available literature. The primary goal of developing this web-resource is to provide descriptions of the NtUE related genes and their functional annotation. MicroRNA targeting some of the NtUE related genes and the quantitative trait loci (QTLs) for NtUE related traits are also included. The available information in the web-resource should help the users to readily search the desired information.\n\nWeb-resource URLhttp://bioclues.org/NtUE/

bioinformatics↗

bioRxiv2017

FORKS: Finding Orderings Robustly using K-means and Steiner trees

Recent advances in single cell RNA-seq technologies have provided researchers with unprecedented details of transcriptomic variation across individual cells. However, it has not been straightforward to infer differentiation trajectories from such data, due to the parameter-sensitivity of existing methods. Here, we present Finding Orderings Robustly using k-means and Steiner trees (FORKS), an algorithm that pseudo-temporally orders cells and thereby infers bifurcating state trajectories. FORKS, which is a generic method, can be applied to both single-cell and bulk differentiation data. It is a semi-supervised approach, in that it requires the user to specify the starting point of the time course. We systematically benchmarked FORKS and eight other pseudo-time estimation algorithms on six benchmark datasets, and found it to be more accurate, more reproducible, and more memory-efficient than existing methods for pseudo-temporal ordering. Another major advantage of our approach is its robustness - FORKS can be used with default parameter settings on a wide range of datasets.

bioinformatics↗