scholarly journals In-Silico Screening of Prime PCOS Biomarkers for the Identification of a Potential Model Organism

2021 ◽  
pp. 448-454
Author(s):  
Shruti Shastry ◽  
Soumyashree Ghosh ◽  
Ruqayya Manasawala
Keyword(s):  
In Silico ◽  
Structure Prediction ◽  
Potential Model ◽  
Secondary Structure Prediction ◽  
Model Organism ◽  
Gorilla Gorilla ◽  
Reproductive Age ◽  
Global Alignment ◽  
Suitable Model ◽  
Polycystic Ovaries

Polycystic ovarian syndrome (PCOS) is a multigenic endocrine disorder observed in women of reproductive age. Although the condition is characterized by the presence of polycystic ovaries and excess production of androgens, the exact aetiology has not been well deciphered due to the unavailability of a suitable model organism. Defects in the two prime biomarkers namely CYP11A and CYP19A1, have been found to play a role in disease progression. The objective of this study was to carry out an in-silico assessment of these two genes to identify a potential model organism for the efficacious study of PCOS. Bioinformatics tools such as BLAST and EMBOSS were used for local and global alignment respectively, to find sequence homology and thereby, establish a model organism. Sequence comparison was followed by phylogenetic analysis and secondary structure prediction of the enzymes encoded by the respective genes. Our in-silico study revealed Gorilla gorilla to be an ideal candidate for the study of PCOS owing to its high sequence and structural similarities with the human gene counterparts. Future prospects of the research include in-vitro analysis of the biomarkers on Gorilla gorilla ovarian theca cell line to pave the way for therapy.

scholarly journals Predicting the effects of the single nucleotide polymorphism A122V on CXC chemokine receptor type 1 of Bos taurus (Artiodactyla: Bovidae) cattle by in silico analyses

Biotemas ◽  
2017 ◽  
Vol 30 (4) ◽  
pp. 1-6 ◽  
Author(s):  
Anete Ferraz Guzzi ◽  
Felipe Santos de Luna Oliveira ◽  
Márcia Maria de Souza Amaro ◽  
Paulo Fernando Tavares Filho ◽  
Jane Eyre Gabriel
Keyword(s):  
In Silico ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Bos Taurus ◽  
Protein Secondary Structure ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Cxc Chemokine ◽  
In Silico Analyses

Este estudo objetivou predizer bioquimicamente as estruturas primárias e secundárias da proteína receptora de quimiocina CXCR1 bovina não polimórfica e polimórfica carreando o polimorfismo A122V por análises in silico. Duas sequências da proteína CXCR1 de bovino Bos taurus foram selecionadas a partir da base de dados de sequências de proteínas UniProtKB/Swiss-Prot: a) uma sequência não polimórfica (A7KWG0), contendo o aminoácido alanina (A) na posição 122, e b) uma sequência polimórfica, apresentando o aminoácido valina (V) na mesma posição. As estruturas primárias e secundárias da proteína foram preditas empregando os programas ProtParam e Chou & Fasman Protein Secondary Structure Prediction CFSSP. Diferenças nos parâmetros físicos e químicos não foram previstas a partir da estrutura primária de ambas as proteínas analisadas. A presença de um domínio helicoidal, situado nas posições 100 e 150, foi exclusivamente encontrada na proteína CXCR1 não polimórfica. Resíduos de aminoácidos de propriedades bioquímicas variáveis foram detectados na posição 122 na proteína CXCR1 dos ruminantes e humana, sugerindo que esse peptídeo é altamente polimórfico em vertebrados. Os resultados aqui descritos predizem diferenças no padrão da estrutura secundária da proteína CXCR1 bovina não polimórfica e polimórfica A122V empregando ferramentas de Bioinformática. 

scholarly journals Homology modeling of actin protein in Leishmania donovani and in silico prediction of active drugs

2020 ◽  
Vol 2 ◽  
pp. 52-57
Author(s):  
Dimpal Rani Bansal ◽  
Hanumanthrao Chandershekar Patil ◽  
Rajesh Kumari Patil
Keyword(s):  
Homology Modeling ◽  
Binding Affinity ◽  
In Silico ◽  
Structure Prediction ◽  
Leishmania Donovani ◽  
Secondary Structure Prediction ◽  
3D Structure ◽  
Data Bank ◽  
Discovery Studio ◽  
Actin Protein

Objectives: Leishmaniasis is a disease caused by leishmania parasite which is genus of trypanosome protozoa. Leishmania donovani promastigote inhibits biogenesis of phagolysosome due to the accumulation of periphagosomal F-actin. This inhibition of phagosome maturation gives favorable environment for differentiation of promastigote-to-amastigote and causes disease progression. L. donovani actin (LdACT) has been found to have unconventional biochemical behavior due to the different amino acid region in its sequence suggesting that it must have a three-dimensional (3D) structure different from eukaryotic actins making it a more specific for predication of antileishmanial drugs which is main objective of this study. Material and Methods: For carrying out this study, protein sequence was retrieved from the database SWISSPROT, analyzed by BIOEDIT software followed by primary and secondary structure prediction by PROTPARAM and SOPMA. A 3D structure of same was constructed by homology modeling using the yeast actin-human gelsolin segment 1 complex (protein data bank [PDB] ID:1yag) as a template with the help of Swiss model. The final model obtained was further accessed by PROCHECK and VERIFY 3D software which ensured the reliability of the model. This model of actin protein was further used for screening different chemical compounds with high binding affinity by GOLD and DISCOVERY STUDIO. Results: The results give information about the some inhibitors having highest binding affinity to the actin protein. Conclusion: This study will be useful for the development of pharmacophore models for in silico predication of active drugs as a part of antileishmanial drug therapy.

scholarly journals Caracterización in silico de la proteína Dpr de Streptococcus mutans asociada a la formación de caries dental humana

2015 ◽  
Vol 1 (1) ◽  
pp. 26
Author(s):  
Malú Chavez-Gamarra ◽  
Gustavo A. Sandoval
Keyword(s):  
Secondary Structure ◽  
Streptococcus Mutans ◽  
In Silico ◽  
Structure Prediction ◽  
Secondary Structure Prediction

<p>Objetivo: Realizar la caracterización in silico de la protína Dpr de Streptococcus mutans relacionada con su tolerancia al daño oxidativo durante la formación de caries dental humana. Material y métodos: Para llevar a cabo esta caracterización se ha empleado la secuencia aminoacídica de la proteína Dpr de S. mutans cepa GS-5 obtenida a partir de la base de datos del GenBank (código de accesión BAA96472.1), la cual fue utilizada para la determinación de sus parámetros bioquímicos, dominios conservados, predicción de estructuras<br />secundarias y modelamiento por homología, empleando las herramientas bioinformáticas ProtParam, Prosite, PHD Secondary Structure Prediction y SWISS-MODEL, respectivamente. La visualización de modelos tridimensionales se realizó empleando PyMol. Resultados: La proteína Dpr de S. mutans es una molécula ácida y de bajo peso molecular y además presenta un dominio altamente conservado involucrado en la unión al hierro. A partir de la predicción de su estructura tridimensional, la proteína Dpr presenta una conformación dodecamérica que estaría implicada en su alta afinidad por hierro así como por otros iones divalentes. Conclusión: La proteína Dpr de S. mutans resulta importante para el proceso infectivo de esta bacteria la cual debe generar una variedad de estrategias para la inhibición de la colonización de la cavidad bucal.</p>

scholarly journals Caracterización in silico y análisis filogenético de la malato sintasa de Paracoccidioides brasiliensis asociada a su proceso de infección

2017 ◽  
Vol 3 (2) ◽  
pp. 381
Author(s):  
Julio K. Huayhua ◽  
Luis A. Rodriguez ◽  
Gustavo A. Sandoval
Keyword(s):  
Secondary Structure ◽  
In Silico ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Paracoccidioides Brasiliensis ◽  
Para Determinar ◽  
Clustal Omega

Objetivo: Realizar la caracterización in silico de la proteína malato sintasa de Paracoccidioides brasiliensis relacionada con su proceso de infección. Materiales y métodos: Se obtuvo la secuencia aminoacídica de malato sintasa de P. brasiliensis (código de accesión: AQ75800.3) del GenBank. Dicha secuencia fue utilizada para determinar sus principales parámetros bioquímicos, dominios y regiones conservadas, predicción de estructuras secundarias y modelamiento tridimensional, empleando las herramientas bioinformáticas ProtParam, Clustal Omega, PHD Secondary Structure Prediction, SWISSMODEL, Phyre2 y Robetta, respectivamente. La visualización y comparación de los modelos tridimensionales se realizó empleando PyMol. Finalmente, se buscó el modelo de sustitución aminoacídica con modelgenerator_v_85 y se usó para generar una filogenia de máxima verosimilitud en PHYML, la cual se visualizó en FigTree.

scholarly journals IRSS: a web-based tool for automatic layout and analysis of IRES secondary structure prediction and searching system in silico

2009 ◽  
Vol 10 (1) ◽  
pp. 160 ◽  
Author(s):  
Tzong-Yuan Wu ◽  
Chi-Chun Hsieh ◽  
Jun-Jie Hong ◽  
Chung-Yung Chen ◽  
Yuh-Show Tsai
Keyword(s):  
Secondary Structure ◽  
In Silico ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Web Based ◽  
Automatic Layout

scholarly journals Computational modeling of molecular structure of microRNA inhibitors selected against microRNA over-expressed in thyroid cancer

2021 ◽  
Author(s):  
Luis Jesuino de Oliveira Andrade ◽  
Alcina Maria Vinhaes Bittencourt ◽  
Luis Matos de Oliveira ◽  
Gabriela Correia Matos de Oliveira
Keyword(s):  
Molecular Structure ◽  
Thyroid Cancer ◽  
Nucleotide Sequence ◽  
In Silico ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Malignant Neoplasm ◽  
Endocrine System ◽  
Rna Secondary Structure Prediction ◽  
Alignment Algorithms

Introduction: Thyroid cancer is the most prevalent malignant neoplasm of endocrine system and advances in thyroid molecular biology studies demonstrate that microRNAs (miRNAs) seem to play a fundamental role in tumor triggering and progression. The miRNAs inhibitors are nucleic acid-based molecules that blockade miRNAs function, making unavailable for develop their usual function, also acting as gene expression controlling molecules. Objective: To develop in silico projection of molecular structure of miRNA inhibitors against miRNA over-expressed in thyroid cancer. Methods: We conducted a search of the nucleotide sequence of 12 miRNAs already defined as inhibitors against miRNA over-expressed in thyroid cancer, realizing in silico projection of the molecular structure of following miRNAs: miRNA-101, miRNA-126, miRNA-126-3p, miRNA-141, miRNA-145, miRNA-146b, miRNA-206, miRNA-3666, miRNA-497, miRNA-539, miRNA-613, and miRNA-618. The nucleotides were selected using GenBank that is the NIH genetic sequence database. The sequences obtained were aligned with the Clustal W multiple alignment algorithms. For the molecular modeling, the structures were generated with the RNAstructure, a fully automated miRNAs structure modelling server, accessible via the Web Servers for RNA Secondary Structure Prediction. Results: We demonstrated a search for nucleotide sequence and the projection of the molecular structure of the following miRNA inhibitors against miRNA over-expressed in thyroid cancer: miRNA-101, miRNA-126, miRNA-126-3p, miRNA-141, miRNA-145, miRNA-146b, miRNA-206, miRNA-3666, miRNA-497, miRNA-539, miRNA-613, and miRNA-618. Conclusion: In this study we show in silico secondary structures projection of selected of 12 miRNA inhibitors against miRNA over-expressed in thyroid cancer through computational biology. Keywords: microRNA; nucleotide analysis; molecular structure; thyroid cancer.

The Role of Vitamin B6 in Reducing Serum Prolactin in Comparison to Cabergoline

2019 ◽  
Vol 10 (01) ◽  
Author(s):  
Suha J. Witwit
Keyword(s):  
Prolactin Level ◽  
Vitamin B6 ◽  
Reproductive Age ◽  
Serum Prolactin ◽  
Polycystic Ovaries ◽  
Endocrine Disorder ◽  
Hypothalamic Pituitary Axis

Hyperprolactinemia is a common endocrine disorder of hypothalamic-pituitary axis. It affect about 4-17% of women in reproductive age and about 3-10% of patients with polycystic ovaries. Vitamin B6 is an effective prolactin inhibitor that is extremely cheap and safe.it exerts hypothalamic dopaminergic effect which causes a significant reduction in prolactin level. The aim of the study is To evaluate the effectiveness of vitamin B6 in reducing serum prolactin in Hyperprolactinemic patient. Compare this effect to that of cabergoline.

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