The Construction of Two and Three Dimensional Molecular Models for the miR-31 and Its Silencer as the Triple Negative Breast Cancer Biomarkers

Parikesit, Arli Aditya

doi:10.3844/ojbsci.2018.424.431

Cited by 3 publications

(3 citation statements)

References 37 publications

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“…Thus, the computational environment is the fittest approach in order to observe this phenomenon. The total amount of structure in the Figure 3 is almost similar to the one that was detected in other experiments with other species and biomarkers (Parikesit 2018c). Hence, it could be inferred that the typical miRNA structures pool could always be detected in a certain amount.…”

Section: Discussionsupporting

confidence: 82%

The Structural Annotations of The Mir-122 Non-Coding RNA from The Tilapia Fish (Oreochromis niloticus)

Parikesit

Imron²,

Nurdiansyah

et al. 2022

HAYATI J Biosci

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Tilapia (Oreochromis niloticus) is an important fisheries commodity. Scientific efforts have been done to increase its quality. One of them is staging a premium diet such as a fat-enriched diet. The transcriptomics approach is able to provide the signatures of the diet outcomes by observing the micro(mi)RNA signature in transcriptional regulation. Hence, it was found that the availability of mir-122 is essential in the regulation of a high-fat diet in tilapia. However, this transcriptomics signature is lacking structural annotations and the complete interaction annotations with its silencing(si)RNA. RNAcentral website was navigated for the latest annotation of mir-122 from tilapia and other species as a comparison. MEGA X was employed to comprehend the miRNA evolutionary repertoire. The RNA secondary structure prediction tools from the Vienna RNA package and the RNA tertiary structure prediction tools from simRNA and modeRNA are secured with default parameters. The HNADOCK tools were leveraged to observe the interaction between mir-122 and its siRNA. The post-processing was conducted with the Chimera visualization tool. The secondary and tertiary structure of the mir-122 and its siRNA could be elucidated, docked, and visualized. In this end, further effort to develop a comprehensive molecular breeding tool could be secured with the structural annotation information.

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Section: Discussionsupporting

confidence: 82%

The Structural Annotations of The Mir-122 Non-Coding RNA from The Tilapia Fish (Oreochromis niloticus)

Parikesit

Imron²,

Nurdiansyah

et al. 2022

HAYATI J Biosci

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“…The pipeline of this research was inspired from the previously published method that employ CADD-based approach from structural bioinformatics studies (Arifin et al, 2020;Parikesit, 2018). The BRCA2 breast cancer genes were downloaded from the NCBI website (https://www.ncbi.nlm.nih.gov/) in the FASTA format.…”

Section: Methodsmentioning

confidence: 99%

3D And 2D RNA Structure Prediction Of The BRCA2 Gene And Its Silencing RNA In The Breast Cancer

Wijaya

Parikesit

Nurdiansyah

2020

WJC

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Breast cancer is one of the most threatening diseases for women. It is found that BRCA2 gene plays a significant role in breast cancer, provided that mutations occurred. The objective of this study is to determine whether the bioinformatics approach could provide the gene networking, molecular simulation, and computational metabolomics information to shed the relation between BRCA2 gene mutation with breast cancer progression. The methods are utilizing molecular simulation tools to comprehend the biochemical interaction of BRCA2 gene with other oncogenic genes. Lastly, the molecular docking tool is devised to provide the molecular interactions information. It could be implied that the Computer-Aided Drug Design (CADD)-based in silico transcriptomics tools could provide the fine-grained information on the exact role of BRCA2 gene in the progression of breast cancer. The clinical impact of this study could only be measured after the wet laboratory experiment is conducted to validate the computational approach results

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“…This effort has been strengthened by the more fine-grained annotation of protein-protein interaction networks of cancer-related proteins [30][31][32]. To this end, these efforts should be solidified as a basis for developing a blueprint for constraining the menace of breast cancer and developing drug designs for breast cancer [34,35]. The development of proteomics information pipelines will facilitate the examination of the protein domain repertoire in the progression of breast cancer.…”

Section: Introductionmentioning

confidence: 99%

Protein Annotation of Breast-cancer-related Proteins with Machine-learning Tools

Parikesit¹,

Agustriawan²,

Nurdiansyah³

2020

Makara J. Sci.

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One of the primary contributors to the mortality of women is breast cancer. Several approaches are used to cure it, but recurrence occurs in 79% of the cases because the underlying mechanism of the protein molecules is not carefully examined. The goal of this research was to use machine-learning tools is to elucidate conserved regions and to obtain functional annotations of breast-cancer-related proteins. The sequences of five breast-cancer-related proteins (BRCA2, BCAR1, BCAR3, BCAR4, and BRMS1) and their annotations were retrieved from the UniProt and TCGA databases, respectively. Conserved regions were extracted using CLUSTALX. We constructed a phylogenetic tree using the MEGA 7.0. SUPERFAMILY database to obtain fine-grained domain annotation. The tree revealed that the BRCA2 and BCAR4 protein sequences are located in a clade, which indicates that they have overlapping functions. Several protein domains were identified, including the SH2 and Ras GEF domains in BCAR3, the SH3 domain in BCAR1, and the BRCA2 helical domain, the nucleic-acid-binding protein, and tower domain. We found that no protein domains could be annotated for BCAR4 or BRMS1, which may indicate the presence of a disordered protein state. We suggest that each protein has distinct functionalities that are complementary in regulating the progression of breast cancer, although further study is necessary for confirmation. This protein-domain annotation project could be leveraged by the complete integration of mapping with respect to gene and disease ontology. This type of leverage is vital for obtaining biochemical insights regarding breast cancer.

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The Construction of Two and Three Dimensional Molecular Models for the miR-31 and Its Silencer as the Triple Negative Breast Cancer Biomarkers

Cited by 3 publications

References 37 publications

The Structural Annotations of The Mir-122 Non-Coding RNA from The Tilapia Fish (Oreochromis niloticus)

The Structural Annotations of The Mir-122 Non-Coding RNA from The Tilapia Fish (Oreochromis niloticus)

3D And 2D RNA Structure Prediction Of The BRCA2 Gene And Its Silencing RNA In The Breast Cancer

Protein Annotation of Breast-cancer-related Proteins with Machine-learning Tools

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