Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach

Rao, Allam Appa; Thota, Hanuman; Adapala, Ramamurthy; Changalasetty, Suresh Babu; Gumpeny, Ramachandra Sridhar; Akula, Annapurna; Thota, Lalitha Saroja; Challa, Siva Reddy; Rao, Manlong; Das, Undurti N.

doi:10.4137/bbi.s313

Cited by 3 publications

(4 citation statements)

References 20 publications

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“…25 Diabetic cardiomyopathy is the most dangerous complication facing patients with diabetes and is characterized by myocardial hypertrophy, impairment of contractile proteins, accumulation of ECM proteins, formation of advanced glycation end products and decreased left ventricular compliance. 26 It has been suggested that the accumulation of ECM proteins (in particular collagen fibres) may have an important role in the pathological changes associated with diabetic cardiomyopathy. 27 The present study showed that the classical features of diabetes (including disorder and collapse of diabetic cardiac muscle fibres, decreases in heart function and elevated blood glucose concentrations) were successfully induced in STZ-treated rats.…”

Section: Discussionmentioning

confidence: 99%

Myocardial Protection bySalvia MiltiorrhizaInjection in Streptozotocin-Induced Diabetic Rats through Attenuation of Expression of Thrombospondin-1 and Transforming Growth Factor-β1

Fei

Azad

et al. 2012

J Int Med Res

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Section: Discussionmentioning

confidence: 99%

Myocardial Protection bySalvia MiltiorrhizaInjection in Streptozotocin-Induced Diabetic Rats through Attenuation of Expression of Thrombospondin-1 and Transforming Growth Factor-β1

Fei

Azad

et al. 2012

J Int Med Res

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“…Fang et al [ 75 ], by simultaneously using real-time PCR and bioinformatics tools, identified genes associated with the cellular processes closely related to AD progression. Rao et al [ 76 ] used bioinformatics tools to identify almost 74 genes strongly involved in AD. The authors retrieved the encoded functional protein sequences in FASTA format from NCBI (National Center for Biotechnology Information) [ 61 ] and determined their role based on ClustalW multiple sequence alignments.…”

Section: Brief Overview Of Bioinformatics and Cheminformatics Tools Amentioning

confidence: 99%

“…In addition, they constructed a phylogenetic tree using the functional protein sequences. This study reported once more that the genetic components of AD are more important in comparison to environmental, metabolic and age related factors [ 76 ].…”

Section: Brief Overview Of Bioinformatics and Cheminformatics Tools Amentioning

confidence: 99%

Potential Therapeutic Approaches to Alzheimer’s Disease By Bioinformatics, Cheminformatics And Predicted Adme-Tox Tools

Avram

Mernea

Limban

et al. 2020

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Background: Alzheimer’s disease (AD) is considered a severe, irreversible and progressive neurodegenerative disorder. Currently, the pharmacological management of AD is based on a few clinically approved acethylcholinesterase (AChE) and N-methyl-D-aspartate (NMDA) receptor ligands, with unclear molecular mechanisms and severe side effects. Methods: Here, we reviewed the most recent bioinformatics, cheminformatics (SAR, drug design, molecular docking, friendly databases, ADME-Tox) and experimental data on relevant structure-biological activity relationships and molecular mechanisms of some natural and synthetic compounds with possible anti-AD effects (inhibitors of AChE, NMDA receptors, beta-secretase, amyloid beta (Aβ), redox metals) or acting on multiple AD targets at once. We considered: (i) in silico supported by experimental studies regarding the pharmacological potential of natural compounds as resveratrol, natural alkaloids, flavonoids isolated from various plants and donepezil, galantamine, rivastagmine and memantine derivatives, (ii) the most important pharmacokinetic descriptors of natural compounds in comparison with donepezil, memantine and galantamine. Results: In silico and experimental methods applied to synthetic compounds led to the identification of new AChE inhibitors, NMDA antagonists, multipotent hybrids targeting different AD processes and metal-organic compounds acting as Aβ inhibitors. Natural compounds appear as multipotent agents, acting on several AD pathways: cholinesterases, NMDA receptors, secretases or Aβ, but their efficiency in vivo and their correct dosage is to be determined. Conclusion: Bioinformatics, cheminformatics and ADME-Tox methods can be very helpful in the quest for an effective anti-AD treatment, allowing the identification of novel drugs, enhancing the druggability of molecular targets and providing a deeper understanding of AD pathological mechanisms.

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“…Similarly aldose reductase and nitric oxide synthase were shown to be associated with diabetic retinopathy, suggesting they may do so by modulating aldose reductase and nitric oxide synthase [6]. Employing multiple sequence alignment using ClustalW to construct a phylogenetic tree, a causal relationship was suggested between altered calcium homeostasis and diabetic cardiomyopathy [7].…”

mentioning

confidence: 99%

Emerging face of genetics, genomics and diabetes

Sridhar¹,

Duggirala

Padmanabhan

2013

Int J Diabetes Dev Ctries

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Type 2 diabetes mellitus (T2DM) has become a global public health issue encompassing even children and youth in recent decades. It is a complex disease influenced by genetic and environmental factors. Although much attention is paid to environmental factors since they are identifiable and potentially modifiable, beginning the turn of the 21st century, there has been an explosion of activities that are aimed to screen the genome for identifying T2DM susceptibility genes. This gained momentum with a confluence of different scientific disciplines that was showcased by the millennial Human Genome Project and its aftermath. Currently, the next generation sequencing accelerated the identification of potential causal genes/variants (especially low frequency and rare variants) influencing complex diseases such as T2DM. Also, the other technologies such as transcriptomics, proteomics, metabolomics and epigenomics have emerged as additional tools to identify the molecular factors underling the phenotypic expression of T2DM. The voluminous biological data generated by these studies has necessitated or contributed to bioinformatics, a confluence of biology and its various flavours, information technology, computational biology, algorithms, matching, statistics, mathematics, nanotechnology, ethics among others.The areas of analysis using bioinformatics in diabetes can be approached as employing datasets from genome or amino acid sequences, structures of biological molecules and functional genomics experiments. Nevertheless analyses extend to other types of data including evolutionary trees, metabolic pathways and the semantics of published literature.Mathematical models and analysis and statistical analyses are required to obtain critical information from the large amounts of data that is generated by genomic and other approaches. Newer algorithms to cluster data from a wide scatter will be relevant: for example, K-means can select best density in a self-adoptive manner and initialize r empirically; an improved method over K means, the Automatic Generation of Distance for Density based Clustering (AGDDC) was developed by Karteeka Pavan et al. to optimize number of clusters [1]. This was developed to find initial optimum centroids based on density clustering. It can be applied to relevant genes related to the pathogenesis of T2DM.The challenge in modern biology and of modern diabetes, is a profusion of data. Bioinformatic methods aid in curating and synthesizing the deluge [2]. The Human Genomics Project (HGP) which heralded the situation where data overran the capacity to cull out the information, simultaneously saw sequencing of genes of other species including vertebrates, invertebrates, fungi, bacteria and plants. The underlying theme was to know how genetic architecture and genes evolved over time. Considering that the basic building blocks were the four nucleotides across all life forms, it was logical to compare the genomes of different species to identify where and how divergence of genes occurred and how newer metabo...

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Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach

Cited by 3 publications

References 20 publications

Myocardial Protection bySalvia MiltiorrhizaInjection in Streptozotocin-Induced Diabetic Rats through Attenuation of Expression of Thrombospondin-1 and Transforming Growth Factor-β1

Myocardial Protection bySalvia MiltiorrhizaInjection in Streptozotocin-Induced Diabetic Rats through Attenuation of Expression of Thrombospondin-1 and Transforming Growth Factor-β1

Potential Therapeutic Approaches to Alzheimer’s Disease By Bioinformatics, Cheminformatics And Predicted Adme-Tox Tools

Emerging face of genetics, genomics and diabetes

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