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Siva Sankari G, James R, Payva F, Sivaramakrishnan V, Vineeth Kumar TV, Kanchi S, Santhy KS. Computational analysis of sodium-dependent phosphate transporter SLC20A1/PiT1 gene identifies missense variations C573F, and T58A as high-risk deleterious SNPs. J Biomol Struct Dyn 2024; 42:4072-4086. [PMID: 37286379 DOI: 10.1080/07391102.2023.2218939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 05/21/2023] [Indexed: 06/09/2023]
Abstract
SLC20A1/PiT1 is a sodium-dependent inorganic phosphate transporter, initially recognized as the retroviral receptor for Gibbon Ape Leukemia Virus in humans. SNPs in SLC20A1 is associated with Combined Pituitary Hormone Deficiency and Sodium Lithium Counter transport. Using in silico techniques, we have screened the nsSNPs for their deleterious effect on the structure and function of SLC20A1. Screening with sequence and structure-based tools on 430 nsSNPs, filtered 17 nsSNPs which are deleterious. To evaluate the role of these SNPs, protein modeling and MD simulations were performed. A comparative analysis of model generated with SWISS-MODEL and AlphaFold shows that many residues are in the disallowed region of Ramachandran plot. Since SWISS-MODEL structure has a 25-residue deletion, the AlphaFold structure was used to perform MD simulation for equilibration and structure refinement. Further, to understand perturbation of energetics, we performed in silico mutagenesis and ΔΔG calculation using FoldX on MD refined structures, which yielded SNPs that are neutral (3), destabilizing (12) and stabilizing (2) on protein structure. Furthermore, to elucidate the impact of SNPs on structure, we performed MD simulations to discern the changes in RMSD, Rg, RMSF and LigPlot of interacting residues. RMSF profiles of representative SNPs revealed that A114V (neutral) and T58A (positive) were more flexible & C573F (negative) was more rigid compared to wild type, which is also reflected in the changes in number of local interacting residues in LigPlot and ΔΔG. Taken together, our results show that SNPs can lead to structural perturbations and impact the function of SLC20A1 with potential implications for disease.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- G Siva Sankari
- Centre for Wildlife Studies, Kerala Veterinary and Animal Sciences University, Wayanad, Kerala, India
| | - Remya James
- St. Joseph's College for Women, Alappuzha, Kerala, India
- Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
| | - Febby Payva
- St. Joseph's College for Women, Alappuzha, Kerala, India
- Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
| | - Venketesh Sivaramakrishnan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Puttaparthi, Andhra Pradesh, India
| | | | - Subbarao Kanchi
- Department of Physics, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Puttaparthi, Andhra Pradesh, India
| | - K S Santhy
- Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
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Rathnakumar S, Bhaskar S, Sivaramakrishnan V, Kambhampati NSV, Srinivasan V, Ramamurthy SS. Tecoma stans Floral Extract-Based Biosynthesis for Enhanced Surface Plasmon-Coupled Emission and a Preliminary Study on Fluoroimmunoassay. Anal Chem 2024; 96:4005-4012. [PMID: 38415592 DOI: 10.1021/acs.analchem.3c01441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
We demonstrate the synthesis of biogenic supported silver spiked star architectures and their application to increase the electromagnetic field intensity at its tips that enhance plasmon-coupled emission. Tecoma stans floral extract has been used to synthesize silver nanocubes and spiked stars. We observe ∼445-fold and ∼680-fold enhancements in spacer and cavity configurations, respectively, in the SPCE platform. The hotspot intensity and Purcell factor are evaluated by carrying out finite-difference time-domain (FDTD) simulations. Time-based studies are presented to modulate the sharpness of the edges wherein an increase in the tip sharpness with the increase in reaction time up to 5 h is observed. The unique morphology of the silver architectures allowed us to utilize them in biosensing application. A SPCE-based fluoroimmunoassay was performed, achieving a 1.9 pg/mL limit of detection of TNF-α cytokine. This combination of anisotropic architectures, SPCE and immunoassay prove to be a powerful platform for the ultrasensitive detection of biomarkers in surface-bound assays.
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Affiliation(s)
- Sriram Rathnakumar
- Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam Campus, Puttaparthi, 515134, Andhra Pradesh, India
| | - Seemesh Bhaskar
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory (HMNTL), University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Venketesh Sivaramakrishnan
- Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam Campus, Puttaparthi, 515134, Andhra Pradesh, India
| | - Naga Sai Visweswar Kambhampati
- Department of Chemistry, STAR Laboratory, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam Campus, Puttaparthi, 515134, Andhra Pradesh, India
| | - Venkatesh Srinivasan
- Department of Chemistry, STAR Laboratory, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam Campus, Puttaparthi, 515134, Andhra Pradesh, India
| | - Sai Sathish Ramamurthy
- Department of Chemistry, STAR Laboratory, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam Campus, Puttaparthi, 515134, Andhra Pradesh, India
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Rajaratnam S, Pradhan SS, Naik AA, Sivaramakrishnan V. Integrated Multi-Omics Analysis and Validation in Yeast Model of Amyotrophic Lateral Sclerosis. Methods Mol Biol 2024; 2761:397-419. [PMID: 38427252 DOI: 10.1007/978-1-0716-3662-6_28] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
Transcriptomics is a complex process that involves raw data extraction, normalization, differential gene expression, and analysis. The Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information (NCBI) is a repository of experimental datasets. Amyotrophic lateral sclerosis (ALS) datasets are deposited by various scientists and research investigators to expand the horizon of scientific knowledge. R-statistical tools are the most common ways for conducting these kinds of studies. The first step is the identification of appropriate datasets. Since the raw data is available in a variety of formats, a large array of software is used for extraction and analysis. Normalization is conducted for the datasets using NetworkAnalyst. Differential analysis is further conducted on the normalized data to identify significantly enriched genes. The significant genes are then grouped into pathways. The results were validated using yeast model of ALS in which the yeast is transformed with ALS plasmids encoding genes associated with ALS. The resulting GFP-tagged protein aggregates are imaged using fluorescence microscopy and subsequently validated using filter retardation assay and quantified using ImageJ software. Functional role of different genes is studied using metabolite treatment and knockout studies.
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Affiliation(s)
- Saiswaroop Rajaratnam
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Anantapur, Andhra Pradesh, India
| | - Sai Sanwid Pradhan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Anantapur, Andhra Pradesh, India
| | - Ashwin Ashok Naik
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Anantapur, Andhra Pradesh, India
| | - Venketesh Sivaramakrishnan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Anantapur, Andhra Pradesh, India.
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Liu M, Li S, Cao N, Wang Q, Liu Y, Xu Q, Zhang L, Sun C, Xiao X, Yao J. Intestinal flora, intestinal metabolism, and intestinal immunity changes in complete Freud's adjuvant-rheumatoid arthritis C57BL/6 mice. Int Immunopharmacol 2023; 125:111090. [PMID: 37866312 DOI: 10.1016/j.intimp.2023.111090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/10/2023] [Accepted: 10/16/2023] [Indexed: 10/24/2023]
Abstract
Rheumatoid arthritis (RA) is an inflammatory-mediated autoimmune disease characterized by persistent joint enlargement, synovial cartilage damage, and inflammatory infiltrates. Although the pathogenesis and treatment of RA are still currently insufficient, the importance of the intestine flora, metabolism and immunity for RA has been gradually recognized, and many intestine regulatory strategies have been used to treat RA. However, the relationship between RA and intestine flora, metabolism and immunity has not been fully expounded. In this study, Complete Freund's Adjuvant (CFA) was used to establish RA model, CyTOF technology was used to study the changes of intestinal immune cell types, 16S rRNA technology was used to analyze the differences of intestinal flora, and LC-MS technology was used to explain the effects of metabolites produced by the changed intestinal flora on RA. Moreover, we systematically explored how the imbalance of intestinal flora changed the intestinal immune status through its metabolites in RA mice. Our results showed that the intestinal flora of RA mice changed significantly, and the bacteria producing short-chain fatty acids (SCFAs), indole classes and secondary bile acids were significantly reduced. The abundance of SCFAs, indole classes and secondary bile acids in the intestine were significantly decreased. The balance of immune cells in the intestine of RA mice was significantly disrupted, with an overall decrease in immune cells. This work reveals the possible relationship between intestinal flora, metabolism and immunity and RA in mice, which will provide new therapeutic strategies for RA.
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Affiliation(s)
- Mingfei Liu
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Shirong Li
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Ningning Cao
- Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine 300250, China
| | - Qingguo Wang
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Yuhao Liu
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Qianqian Xu
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Lin Zhang
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China
| | - Chenghong Sun
- State Key Laboratory of Integration and Innovation of Classic Formula and Modern Chinese Medicine, Lunan Pharmaceutical Group Co. LTD., Linyi 276005, China; Linyi Key Laboratory for Immunopharmacology and Immunotoxicology of Natural Medicine, Lunan Pharmaceutical Group Co. LTD., Linyi 273400, China.
| | - Xuefeng Xiao
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
| | - Jingchun Yao
- State Key Laboratory of Integration and Innovation of Classic Formula and Modern Chinese Medicine, Lunan Pharmaceutical Group Co. LTD., Linyi 276005, China; Linyi Key Laboratory for Immunopharmacology and Immunotoxicology of Natural Medicine, Lunan Pharmaceutical Group Co. LTD., Linyi 273400, China.
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5
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Fiocchi C. Omics and Multi-Omics in IBD: No Integration, No Breakthroughs. Int J Mol Sci 2023; 24:14912. [PMID: 37834360 PMCID: PMC10573814 DOI: 10.3390/ijms241914912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/27/2023] [Accepted: 10/02/2023] [Indexed: 10/15/2023] Open
Abstract
The recent advent of sophisticated technologies like sequencing and mass spectroscopy platforms combined with artificial intelligence-powered analytic tools has initiated a new era of "big data" research in various complex diseases of still-undetermined cause and mechanisms. The investigation of these diseases was, until recently, limited to traditional in vitro and in vivo biological experimentation, but a clear switch to in silico methodologies is now under way. This review tries to provide a comprehensive assessment of state-of-the-art knowledge on omes, omics and multi-omics in inflammatory bowel disease (IBD). The notion and importance of omes, omics and multi-omics in both health and complex diseases like IBD is introduced, followed by a discussion of the various omics believed to be relevant to IBD pathogenesis, and how multi-omics "big data" can generate new insights translatable into useful clinical tools in IBD such as biomarker identification, prediction of remission and relapse, response to therapy, and precision medicine. The pitfalls and limitations of current IBD multi-omics studies are critically analyzed, revealing that, regardless of the types of omes being analyzed, the majority of current reports are still based on simple associations of descriptive retrospective data from cross-sectional patient cohorts rather than more powerful longitudinally collected prospective datasets. Given this limitation, some suggestions are provided on how IBD multi-omics data may be optimized for greater clinical and therapeutic benefit. The review concludes by forecasting the upcoming incorporation of multi-omics analyses in the routine management of IBD.
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Affiliation(s)
- Claudio Fiocchi
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland, OH 44195, USA;
- Department of Gastroenterology, Hepatology and Nutrition, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, OH 44195, USA
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Pradhan SS, R SS, Kanikaram SP, V M DD, Pargaonkar A, Dandamudi RB, Sivaramakrishnan V. Metabolic deregulation associated with aging modulates protein aggregation in the yeast model of Huntington's disease. J Biomol Struct Dyn 2023:1-18. [PMID: 37732342 DOI: 10.1080/07391102.2023.2257322] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 09/05/2023] [Indexed: 09/22/2023]
Abstract
Huntington's disease is associated with increased CAG repeat resulting in an expanded polyglutamine tract in the protein Huntingtin (HTT) leading to its aggregation resulting in neurodegeneration. Previous studies have shown that N-terminal HTT with 46Q aggregated in the stationary phase but not the logarithmic phase in the yeast model of HD. We carried out a metabolomic analysis of logarithmic and stationary phase yeast model of HD expressing different polyQ lengths attached to N-terminal HTT tagged with enhanced green fluorescent protein (EGFP). The results show significant changes in the metabolic profile and deregulated pathways in stationary phase cells compared to logarithmic phase cells. Comparison of metabolic pathways obtained from logarithmic phase 46Q versus 25Q with those obtained for presymptomatic HD patients from our previous study and drosophila model of HD showed considerable overlap. The arginine biosynthesis pathway emerged as one of the key pathways that is common in stationary phase yeast compared to logarithmic phase and HD patients. Treatment of yeast with arginine led to a significant decrease, while transfer to arginine drop-out media led to a significant increase in the size of protein aggregates in both logarithmic and stationary phase yeast model of HD. Knockout of arginine transporters in the endoplasmic reticulum and vacuole led to a significant decrease in mutant HTT aggregation. Overall our results highlight arginine as a critical metabolite that modulates the aggregation of mutant HTT and disease progression in HD.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Sai Sanwid Pradhan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, India
| | - Sai Swaroop R
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, India
| | - Sai Phalguna Kanikaram
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, India
| | - Datta Darshan V M
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, India
| | - Ashish Pargaonkar
- Application Division, Agilent Technologies Ltd., Bengaluru, Karnataka, India
| | | | - Venketesh Sivaramakrishnan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, India
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Rathnakumar S, Kambhampati NSV, Saiswaroop R, Pradhan SS, Ramkumar G, Beeraka N, Muddu GK, Kumar S, Javvaji SK, Parangoankar A, Sivaramakrishnan V, Ramamurthy SS. Integrated clinical and metabolomic analysis of dengue infection shows molecular signatures associated with host-pathogen interaction in different phases of the disease. Metabolomics 2023; 19:47. [PMID: 37130982 DOI: 10.1007/s11306-023-02011-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 04/20/2023] [Indexed: 05/04/2023]
Abstract
PURPOSE Dengue is a mosquito vector-borne disease caused by the dengue virus, which affects 125 million people globally. The disease causes considerable morbidity. The disease, based on symptoms, is classified into three characteristic phases, which can further lead to complications in the second phase. Molecular signatures that are associated with the three phases have not been well characterized. We performed an integrated clinical and metabolomic analysis of our patient cohort and compared it with omics data from the literature to identify signatures unique to the different phases. METHODS The dengue patients are recruited by clinicians after standard-of-care diagnostic tests and evaluation of symptoms. Blood from the patients was collected. NS1 antigen, IgM, IgG antibodies, and cytokines in serum were analyzed using ELISA. Targeted metabolomics was performed using LC-MS triple quad. The results were compared with analyzed transcriptomic data from the GEO database and metabolomic data sets from the literature. RESULTS The dengue patients displayed characteristic features of the disease, including elevated NS1 levels. TNF-α was found to be elevated in all three phases compared to healthy controls. The metabolic pathways were found to be deregulated compared to healthy controls only in phases I and II of dengue patients. The pathways represent viral replication and host response mediated pathways. The major pathways include nucleotide metabolism of various amino acids and fatty acids, biotin, etc. CONCLUSION: The results show elevated TNF-α and metabolites that are characteristic of viral infection and host response. IL10 and IFN-γ were not significant, consistent with the absence of any complications.
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Affiliation(s)
- Sriram Rathnakumar
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Puttaparthi, Andhra Pradesh, 515134, India
| | - Naga Sai Visweswar Kambhampati
- STAR Laboratory, Central Research Instruments Facility, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Puttaparthi, Andhra Pradesh, 515134, India
| | - R Saiswaroop
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Puttaparthi, Andhra Pradesh, 515134, India
| | - Sai Sanwid Pradhan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Puttaparthi, Andhra Pradesh, 515134, India
| | - G Ramkumar
- Department of General Medicine, Sri Sathya Sai General Hospital, Sri Sathya Sai Institute of Higher Medical Sciences Campus, Whitefield, Bengaluru, Karnataka, 560066, India
| | - Nirmala Beeraka
- Department of General Medicine, Sri Sathya Sai General Hospital, Sri Sathya Sai Institute of Higher Medical Sciences Campus, Whitefield, Bengaluru, Karnataka, 560066, India
| | - Gopi Krishna Muddu
- Department of Pediatrics, Sri Sathya Sai General Hospital, Puttaparthi, Andhra Pradesh, 515134, India
| | - Sandeep Kumar
- Department of General Medicine, Sri Sathya Sai General Hospital, Puttaparthi, Andhra Pradesh, 515134, India
| | - Sai Kiran Javvaji
- Department of Laboratory Medicine and Cardiology, Sri Sathya Sai Institute of Higher Medical Sciences, Whitefield, Bengaluru, Karnataka, 560066, India
| | | | - Venketesh Sivaramakrishnan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Puttaparthi, Andhra Pradesh, 515134, India.
| | - Sai Sathish Ramamurthy
- STAR Laboratory, Central Research Instruments Facility, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Puttaparthi, Andhra Pradesh, 515134, India.
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V M DD, Sivaramakrishnan V, Arvind Kumar K. Structural systems biology approach delineate the functional implications of SNPs in exon junction complex interaction network. J Biomol Struct Dyn 2023; 41:11969-11986. [PMID: 36617892 DOI: 10.1080/07391102.2022.2164355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 12/26/2022] [Indexed: 01/10/2023]
Abstract
In eukaryotes, transcripts that carry premature termination codons (PTC) leading to truncated proteins are degraded by the Nonsense Mediated Decay (NMD) machinery. Missense and nonsense Single Nucleotide Polymorphisms (SNPs) in proteins belonging to Exon junction complex (EJC) and up-frameshift protein (UPF) will compromise NMD leading to the accumulation of truncated proteins in various diseases. The EJC and UPF which are involved in NMD is a good model system to study the effect of SNPs at a system level. Despite the availability of crystal structures, computational tools, and data on mutational and deletion studies, with functional implications, an integrated effort to understand the impact of SNPs at the systems level is lacking. To study the functional consequences of missense SNPs, sequence-based techniques like SIFT and PolyPhen which classify SNPs as deleterious or non-deleterious and structure-based methods like FoldX which calculate the Delta Delta G, (ddGs, ∆∆G) are used. Using FoldX, the ddG for mutations with experimentally validated functional effects is calculated and compared with those calculated for SNPs in the same protein-protein interaction interface. Further, a model is conceived to explain the functional implications of SNPs based on the effects observed for known mutants. The results are visualized in a network format. The effects of nonsense mutations are discerned by comparing with deletion mutation studies and loss of interaction in the crystal structure. The present work not only integrates genomics, proteomics, and classical genetics with 'Structural Biology' but also helps to integrate it into a 'systems-level functional network'.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Datta Darshan V M
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, India
| | - Venketesh Sivaramakrishnan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, India
| | - K Arvind Kumar
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, India
- Department of Physiology and Biophysics, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
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Swaroop RS, Pradhan SS, Darshan VMD, Phalguna KS, Sivaramakrishnan V. Integrated network pharmacology approach shows a potential role of Ginseng catechins and ginsenosides in modulating protein aggregation in Amyotrophic Lateral Sclerosis. 3 Biotech 2022; 12:333. [PMID: 36330377 PMCID: PMC9622974 DOI: 10.1007/s13205-022-03401-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 10/12/2022] [Indexed: 11/29/2022] Open
Abstract
Amyotrophic lateral Sclerosis is an incurable, progressive neurodegenerative motor neuron disease. The disease is characterized by protein aggregates. The symptoms include weakness, denervation of muscles, atrophy and progressive paralysis of bulbar and respiratory muscles and dysphagia. Various secondary metabolites are evaluated for their ability to improve symptoms in ALS. Ginseng has been traditionally used for treating several neurodegenerative diseases. Several studies using model systems have shown a potential role of Ginseng catechins and Ginsenosides in clearing protein aggregation associated with ALS. We focus on Network pharmacology approach to understand the effect of Ginseng catechins or ginsenosides on protein aggregation associated with ALS. A catechin/ginsenoside-protein interaction network was generated and the pathways obtained were compared with those obtained from transcriptomic datasets of ALS from GEO database. Knock out of MAPK14, AKT and GSK from Catechin and BACE 1 from ginsenoside modulated pathways inhibited protein aggregation. Catechins and ginsenosides have potential as therapeutic agents in the management of ALS. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-022-03401-1.
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Affiliation(s)
- R. Sai Swaroop
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh 515134 India
| | - Sai Sanwid Pradhan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh 515134 India
| | - V. M. Datta Darshan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh 515134 India
| | - Kanikaram Sai Phalguna
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh 515134 India
| | - Venketesh Sivaramakrishnan
- Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh 515134 India
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