RNA Structure Prediction

According to WHO, breast cancer is one of the main causes of mortality in women. To overcome this malady, molecular biomedical research is carried out intensively. Anomalies in the lincRNA-RoR/miR-145/ARF6 expression pathway were found to play a very important role in breast cancer, especially in the type of Triple-Negative Breast Cancer (TNBC), which is the most dangerous variant of the deadly disease. Bioinformatics research has found the existence of non-coding RNA (ncRNA) in these expression pathways, whose interactions are worth studying with 3-dimensional prediction methods. The 3-D prediction method for biomolecules has been widely developed and has been successfully applied to DNA and protein. However, for the structure of RNA, it has just been developed, due to its low stability and very high dynamics on the biomolecule. Our aim is to apply the latest computational method for predicting the 3-dimensional structure of ncRNA, which can be applied as key information in biomedi...

Inhibition of ADP-ribosylation factor 6 messenger RNA (ARF6 mRNA) by microRNA-145 (miR-145), mediated by Argonaute (AGO) protein, has been found to play essential roles in several types of cancer and cellular processes. This study aimed to model the molecular interaction between miR-145 and ARF6 mRNA with AGO protein. The sequences of miR-145 and the 3’ untranslated region (UTR) of ARF6 mRNA were retrieved from miRTarBase, followed by miRNA target-site and structure predictions were done using RNAhybrid, RNAfold, and simRNAweb, respectively. The interaction between the miRNA-mRNA duplex and AGO was further assessed via molecular docking, interaction analysis, and dynamics, using PatchDock Server, PLIP, and VMD/NAMD, respectively. The models between miR-145, predicted target site of ARF6 mRNA, and AGO protein returned stable thermodynamic variables with negative free energy. Specifically, the RNA duplex had an energy of -19.80 kcal/mol, while the docking had -84.58 atomic contact ene...

This research focuses on an innovative approach utilizing in silico methods to design small interfering RNA (siRNA) targeting the HER2 splice variant mRNA in Homo sapiens. HER2 is known to be overexpressed in certain types of breast cancer, contributing to tumor progression and poor prognosis. By designing siRNA molecules that can specifically bind to and degrade HER2 mRNA, this study aims to reduce HER2 protein levels, thereby hindering the growth and spread of breast cancer cells. The in-silico design process involves identifying optimal siRNA sequences that maximize target specificity and minimize off-target effects, which is crucial for potential therapeutic applications. This approach represents a promising step towards personalized medicine in the treatment of breast cancer, offering a targeted strategy to combat this variant associated with aggressive disease. The methodology comprises the RNA computational tools used for the design, the selection criteria for siRNA candidates, and the potential implications of this research in a clinical setting. The resulting outcomes are 2D and 3D siRNA designs that could potentially silence HER2 mRNA through an in-silico approach. The leads were generated using a de novo modeling approach, with no existing template available in GenBank. Moreover, it is concluded that computational tools can generate sufficiently stable 2D and 3D RNA models that could be advanced for further molecular simulation studies. The benefit of this outcome is that it facilitates better preparation for wet laboratory experiments in siRNA assays, with future implementation in vivo and clinical trial settings.

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 wer...

Triple Negative Breast Cancer (TNBC) is considered as the most dangerous breast cancer type in women and the most difficult to be medicated due to its unresponsive nature towards drug treatments. However, as transcriptomics studies are becoming more advanced, the research on non-coding (nc)RNAs like miRNA and siRNA is being considered as a more feasible approach to deal with TNBC. The mir-135b, a newly found miRNA that has a role in the molecular mechanism of TNBC, is studied mainly for its function as a possible biomarker and a drug candidate. The molecular interaction and structures are still unknown and determining them is the objective of this research. This research utilizes the RNAComposer webservice for 3D RNA structure prediction and the AutoDockTool for molecular docking to determine their interaction. The result shows satisfactory illustration of mir-135b and its siRNA structures with feasible bindings between them. It is shown that the bindings are strong enough to maintain silencing of the gene. However, the molecular docking result shows reversible interaction based on the binding energy meaning its biomarker potential requires combination with other special drug delivery systems. It could be inferred that the siRNAs have potential to be developed in the wet laboratory settings.

Triple-negative breast cancer is one of the deadliest diseases for women, according to the World Health Organization. The most common drugs used and in development for this disease are based upon the proteomics approach, but this so far has not accounted for the whole repertoire of human genome expression. However, a novel approach is currently under development to model the molecular interaction between miR-145 and the 3′ untranslated region (UTR) of ARF6 mRNA. This approach should eventually be useful for transcriptomicsbased drug development. The utilized methods are molecular-docking and dynamics based, using open-source software. It was found that there was a fine-grained molecular interaction between miR-145 and the 3′ UTR of ARF6 mRNA. It is concluded that the information from the interaction could be utilized as the basis for drug development.

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.

According to WHO, breast cancer is one of the main causes of mortality in women. To overcome this malady, molecular biomedical research is carried out intensively. Anomalies in the lincRNA-RoR/miR-145/ARF6 expression pathway were found to play a very important role in breast cancer, especially in the type of Triple-Negative Breast Cancer (TNBC), which is the most dangerous variant of the deadly disease. Bioinformatics research has found the existence of non-coding RNA (ncRNA) in these expression pathways, whose interactions are worth studying with 3-dimensional prediction methods. The 3-D prediction method for biomolecules has been widely developed and has been successfully applied to DNA and protein. However, for the structure of RNA, it has just been developed, due to its low stability and very high dynamics on the biomolecule. Our aim is to apply the latest computational method for predicting the 3-dimensional structure of ncRNA, which can be applied as key information in biomedi...

Abstrak: Berdasarkan data WHO, kanker adalah penyakit yang paling berbahaya. Dewasa ini para peneliti sedang berusaha memahami mekanisme molekular kanker. Berdasarkan dogma sentral, hanya protein coding gene yang diketahui fungsinya, sementara non-coding gene belum dapat dijelaskan. Kemudian, diketahui bahwa non-coding RNA (ncRNA) berperan dominan dalam regulasi molekular sel, sehingga berpengaruh secara langsung kepada proliferasi kanker. Dalam hal ini, instrumen RNA-seq maupun Tiling Array sudah mengumpulkan banyak data biologis dan mendeposisikannya kepada database genom. Diketahui bahwa, ncRNA tidak hanya dapat berperan sebagai biomarker untuk diagnostik kanker, namun juga akan dapat dikembangkan sebagai agen terapeutik. Kanker payudara memiliki empat subtipe molekular, yaitu luminal A, luminal B, Her-2 dan triple negative/basal-like. Kanker Payudara Triple-negative (TNBC) merupakan penyakit yang sangat berbahaya dan belum ditemukan pengobatan yang efektif. Memahami mekanisme da...

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 t...

Inhibition of ADP-ribosylation factor 6 messenger RNA (ARF6 mRNA) by microRNA-145 (miR-145), mediated by Argonaute (AGO) protein, has been found to play essential roles in several types of cancer and cellular processes. This study aimed to model the molecular interaction between miR-145 and ARF6 mRNA with AGO protein. The sequences of miR-145 and the 3' untranslated region (UTR) of ARF6 mRNA were retrieved from miRTarBase, followed by miRNA target-site and structure predictions were done using RNAhybrid, RNAfold, and simRNAweb, respectively. The interaction between the miRNA-mRNA duplex and AGO was further assessed via molecular docking, interaction analysis, and dynamics, using PatchDock Server, PLIP, and VMD/NAMD, respectively. The models between miR-145, predicted target site of ARF6 mRNA, and AGO protein returned stable thermodynamic variables with negative free energy. Specifically, the RNA duplex had an energy of-19.80 kcal/mol, while the docking had-84.58 atomic contact energy supported by 70 hydrogen bonds and 14 hydrophobic interactions. However, the stability of the RMSD plot was still unclear due to limited computational resources. Nevertheless, these results computationally confirm favorable interaction of the three molecules, which can be utilized for further transcriptomics-based drugs or treatments.

Triple-negative breast cancer is one of the deadliest diseases for women, according to the World Health Organization. The most common drugs used and in development for this disease are based upon the proteomics approach, but this so far has not accounted for the whole repertoire of human genome expression. However, a novel approach is currently under development to model the molecular interaction between miR-145 and the 3′ untranslated region (UTR) of ARF6 mRNA. This approach should eventually be useful for transcriptomics-based drug development. The utilized methods are molecular-docking and dynamics based, using open-source software. It was found that there was a fine-grained molecular interaction between miR-145 and the 3′ UTR of ARF6 mRNA. It is concluded that the information from the interaction could be utilized as the basis for drug development.

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

The SARS-CoV-2 or COVID-19 pandemic has reached a new height with an unprecedented infection rate and mortality post-world war II history. However, there is no particular designed drug for COVID-19 up to this point. Thus, there exist three strategies for COVID-19 drug design; drug repurposing option, herbal medicine development, and transcriptomics-based drug lead. As the most underutilized option, transcriptomics-based drug lead could be leveraged to deal with SARS-CoV-2 infection. One of the main methods to block the SARS-CoV-2 infection is to inhibit the RNA polymerase enzyme that is responsible to the viral replication. In this regard, the objective of the strategy is to design the anti-sense siRNA drug and lead to inhibit the mRNA of the RNA Polymerase Enzyme (RdRp) gene that encodes the viral RNA Polymerase of the SARS-CoV-2. The Computer-Aided Drug Design (CADD)-based method was leveraged with sequence retrieval of 24 RdRp gene sequences, multiple sequence alignment, phylogenetic tree reconstruction, 2D/3D RNA structure predictions, and RNA-RNA docking. Both the RNAalifold conserved structure from the RdRp genes and the RNAfold structure of the siRNA for blocking the conserved structure are negative or less than 0 kcal/mol. The predicted RNA docking occurred with the best RMSD score of 22.53 Å, which is beyond the accepted threshold of 10-20 Å. Based on the findings, the 2D/3D structures of both the siRNA and mRNA could be elucidated, and the docking between them is feasible. However, this finding should be elucidated in the wet laboratory setting for the final lead validation.

Berdasarkan data WHO dan Kemenkes, kanker payudara merupakan salah satu penyakit yang berbahaya bagi perempuan. Sejauh ini, diagnosis berbasis kedokteran yang tersedia adalah mamografi. Sementara itu, pengobatan yang ada menggunakan radio dan kemoterapi. Walaupun diagnosis dan pengobatan konvensional tersebut membantu penderita kanker payudara, namun masih harus disempurnakan. Diagnosis dan pengobatan berbasis kedokteran molekuler sudah mulai dikembangkan, terutama yang menggunakan kajian transkriptomik. Sebagai kajian yang baru, transkriptomik mempelajari seluruh transkriptome atau RNA dari organisme secara utuh. Sekarang, diagnosis dan pengobatan kanker payudara menggunakan silencing(si)RNA, micro(mi)RNA, dan produk transkriptomik lainnya sedang dikembangkan. Jalur ekspresi transkriptomik lincRNA-RoR/miR- 145/ARF6 diketahui berperan dalam proliferasi kanker payudara, sehingga inhibitor maupun mekanismenya sedang dipelajari secara menyeluruh. Tidak hanya itu, strategi penghantaran obat juga sudah dilakukan supaya obat mencapai sasaran yang diinginkan, misalnya menggunakan pro-drug berbasis peptida, liposom, nanopartikel, dan lainnya. Metode kerja yang dikembangkan pada dasarnya berbasis anotasi genomik, simulasi molekuler, dan anotasi metabolik. Telaah sistematik ini dilakukan dengan pencaharian kata kunci „breast cancer and transcriptomics‟ pada PUBMED, Mendeley dan Google Scholar. Trend kedepan akan lebih banyak pengembangan diagnosis maupun pengobatan berbasis transkriptomik. Namun banyaknya data yang dihasilkan dari eksperimen ini mengharuskan pengembangan infrastruktur yang lebih baik, terutama dalam konteks „big data‟

The Triple Negative Breast Cancer (TNBC) is considered as the most difficult Breast Cancer type to be medicated. So far, the acceptable medication and diagnostics measure are based upon the proteomics-world view, especially with utilizing the natural products and their derivatives as drug candidates. However, as the transcriptomics-studies are getting more advanced, the research on non-coding (nc)RNA is being considered as a more feasible approach to deal with the TNBC. The miR-31, as the ncRNA that play part in the molecular mechanism of the TNBC, is extensively studied mainly for providing the biomarker and drug candidate. However, the molecular interaction and structures are mainly unknown and it is subject of investigation of this research. This research is utilizing the interplay of pipelines that consist of the Vienna RNA package for 2D RNA structure prediction and the simRNA/modeRNA packages for 3D RNA structure prediction. The result is a blueprint that satifactionary illustrates the RNA structure in a fine-grained manner. The miR-31 and its respective silencing (si)RNA are indeed could be useful to be biomarkers and blueprint for the drug design of the TNBC.

Cervical cancer is one of the primary causes of mortality in women due to human papilloma virus (HPV) infection. The fingerprint of an HPV infection could be detected using a long non-coding RNA (lncRNA) biomarker, enabling it to be utilized in molecular diagnostics. The primary structure or sequences of RNA should be annotated within conventional bioinformatics tools. Therefore, this study aimed to determine the fine-grained 2D and 3D structures of lncRNA PVT1 and its respective siRNA inhibitors. lncRNA PVT1 sequences from Homo sapiens, Mus musculus, and Rattus norvegicus were retrieved from Genbank (NCBI). Prediction of the 2D structure and analysis of the interactions of the lncRNA and siRNA were performed using the Vienna RNA package. The 3D structure of the RNA was computed using the SimRNA and ModeRNA software programs. The results showed that lncRNA PVT1 from H. sapiens and M. musculus had a conserved region. However, the lncRNA from both H. sapiens and M. musculus showed a low conserved region, and the 2D structure could not be determined; thus, the annotation and 2D model focused only on H. sapiens. Both of their lncRNA PVT1 also had a short half-life in the cell. Based on the 3D modeling pipeline, the 3D model of lncRNA PVT1 showed the stability and possible function as molecules, while the PVT1 siRNA-lncRNA interaction analysis revealed that the molecules could bind well. Based on these findings, the structures of both lncRNA PVT1 and its siRNA have the potential to be utilized as biomarkers.

According to WHO, breast cancer is one of the main causes of mortality in women. To overcome this malady, molecular biomedical research is carried out intensively. Anomalies in the lincRNA-RoR/miR-145/ARF6 expression pathway were found to play a very important role in breast cancer, especially in the type of Triple-Negative Breast Cancer (TNBC), which is the most dangerous variant of the deadly disease. Bioinformatics research has found the existence of non-coding RNA (ncRNA) in these expression pathways, whose interactions are worth studying with 3-dimensional prediction methods. The 3-D prediction method for biomolecules has been widely developed and has been successfully applied to DNA and protein. However, for the structure of RNA, it has just been developed, due to its low stability and very high dynamics on the biomolecule. Our aim is to apply the latest computational method for predicting the 3-dimensional structure of ncRNA, which can be applied as key information in biomedical application research. Extrapolation of kinetics and thermodynamic indicators of ncRNA ultimately yields the siRNA Linc-ROR 3-Dimensional structure and siRNA mRNA-ARF6, each having 13 and 8 hydrogen bonds. The existence of these hydrogen bonds is very important in maintaining the stability of the compounds and shows its efficacy as drug candidates. It is expected that preliminary information from the predicted 3-dimensional structure of ncRNA is useful for optimization of laboratory experiments in the field of crystallographic biomolecules.

The research for finding the cure for breast cancer is currently entering the interesting phase of the transcriptomics based method. With the application of Next Generation Sequencing (NGS), molecular information on breast cancer could be gathered. Thus, both in silico and wet lab research has determined that the role of lincRNA-RoR/miR-145/ARF6 expression Pathway could not be ignored as one of the cardinal starting points for Triple-Negative Breast Cancer (TNBC). As the most hazardous type of breast cancer, TNBC should be treated with the most advanced approach that available in the scientific community. Bioinformatics approach has found the possible siRNA-based drug candidates for TNBC. It was found that siRNA that interfere with lincRNA-ROR and mRNA ARF6 could be a feasible opportunity as the drug candidate for TNBC. However, this claim should be validated with more thorough thermodynamics and kinetics computational approach as the comprehensive way to comprehend their molecular repertoire. In this respect, the claim was validated using various tools such as the RNAfold server to determine the 2D structure, Barriers server to comprehend the RNA folding kinetics, RNAeval server to validate the siRNA-target interaction. It was found that the thermodynamics and kinetics repertoire of the siRNA are indeed rational and feasible. In this end, our computation approach has proven that our designed siRNA could interact with lincRNA-RoR/miR-145/ARF6 expression Pathway.

Abstrak: Berdasarkan data WHO, kanker adalah penyakit yang paling berbahaya. Dewasa ini para peneliti sedang berusaha memahami mekanisme molekular kanker. Berdasarkan dogma sentral, hanya protein coding gene yang diketahui fungsinya, sementara non-coding gene belum dapat dijelaskan. Kemudian, diketahui bahwa non-coding RNA (ncRNA) berperan dominan dalam regulasi molekular sel, sehingga berpengaruh secara langsung kepada proliferasi kanker. Dalam hal ini, instrumen RNA-seq maupun Tiling Array sudah mengumpulkan banyak data biologis dan mendeposisikannya kepada database genom. Diketahui bahwa, ncRNA tidak hanya dapat berperan sebagai biomarker untuk diagnostik kanker, namun juga akan dapat dikembangkan sebagai agen terapeutik. Kanker payudara memiliki empat subtipe molekular, yaitu luminal A, luminal B, Her-2 dan triple negative/basal-like. Kanker Payudara Triple-negative (TNBC) merupakan penyakit yang sangat berbahaya dan belum ditemukan pengobatan yang efektif. Memahami mekanisme dan struktur ncRNA pada Biomarker TNBC merupakan langkah awal untuk menentukan agen terapeutik dan propilaksis terbaik. Diketahui bahwa jalur ekspresi lincRNA-RoR/miR-145/ARF6 berperan dalam proliferasi TNBC. Berdasarkan pencarian di GenBank, ditemukan lema-lema ncRNA untuk jalur tersebut. Hasil pencarian diolah dengan software ViennaRNA Package, untuk ditentukan struktur 2 dimensi (2-D) yang solid. Kedepannya, diharapkan dengan mencegah terbentuknya struktur 2-D tersebut, maka semua gen tersebut akan menjadi tidak aktif dan menghentikan proliferasi kanker. Abstract: Based on data from the World Health Organization, cancer is the most dangerous disease. Now, researchers are trying to understand the molecular mechanisms of cancer. Based on the central dogma, only protein coding gene of known function, while non-coding gene cannot be explained. Then, it is known that non-coding RNA (ncRNA) plays a dominant role in the molecular regulation of the cell, and therefore contributes directly to the proliferation of cancer. In this case, the instrument of RNA-seq and Tiling Array already garnered a lot of data. It is known that ncRNA not only can serve as biomarkers for cancer diagnostics but also will be developed as a therapeutic agent. Understanding the mechanisms and structures of ncRNAs on Triple-Negative Breast Cancer (TNBC) Biomarker is the first step to determine the therapeutic and prophylactic agents best. It is known that the lincRNA-RoR/miR-145/ARF6 pathway plays the role in the proliferation of TNBC. Based on the search in GenBank, the pathway has been found. The ViennaRNA Package software processed the search results to determine the two-dimensional (2-D) structure. In the future, preventing the formation of the 2-D structure will be expected to inactivate that pathway, and stop the proliferation of cancer.