Navegando por Palavras-chave "Computational Biology"

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    Algoritmo para Predição de Seleção de Resistência Aos Inibidores de Ns5a do Vírus da Hepatite C
    (Universidade Federal de São Paulo (UNIFESP), 2020-12-14) Almeida, Douglas De Andrade De [UNIFESP]; Janini, Luiz Mario Ramos [UNIFESP]; Universidade Federal de São Paulo
    Summary Objective: To develop an algorithm that, based on the genetic sequence of the HCV infecting virus, can estimate which are the best therapeutic treatments with the least probability of resistance selection for NS5A inhibitors. Method: A phased algorithm was created to select attributes relevant to the study and further development of a machine learning model. The attributes used in this algorithm are the population frequency of the resistance codons, the HCV codon usage and the genetic barrier between the patient's codons and the resistance codons. Results: It was possible to cross-check information from the patient's infectious virus, with information from the medical literature to structure a database with predictive variables and a response variable related to the presence or absence of drug resistance. The model was able to predict with an AUC> 0.99 which characteristics of the virus cause resistance in certain drugs. Conclusion: Codon Usage parameters, population prevalence of codons and genetic barrier, proved to be good predictors of resistance. However, the limitation of the data source implies the possibility of overfitting, which can only be discarded and / or corrected with further studies in the area using similar methodology.
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    Desenho De Novos Peptídeos Catiônicos A Partir Do Sensor De Voltagem De Canais Iônicos
    (Universidade Federal de São Paulo (UNIFESP), 2018-05-24) Lima, Estevao Carlos [UNIFESP]; Miranda Filho, Manoel De Arcisio [UNIFESP]; Universidade Federal de São Paulo (UNIFESP)
    Objective: Design Of Novel Cationic Peptides Through The Analysis Of Ion Channel Voltage Sensor Region And Analysis Of Their Bioactivity In Respect Of Anticancer And Antibacterial Activities. Methods: The Amino Acid Sequence Of 104 Ion Channels Of Nav, Cav And Kv Families Were Multialigned So That The S4 Region Could Be Identified. Based On The Distribution Frequency Of This Residues, Three Peptides Were Designed And Their Secondary Structure Was Evaluated By Circular Dichroism Technique With The Use Of Large Unilamelar Vesicles (Luvs). This Luvs Had The Biomimetic Characteristics Of: Mammal Cells [Popc:Col (70:30 Mol%)]; Tumoral Cell [Popc:Col:Pops(50:30:20)]; And Bacterial Strains [Popc:Popg (50:50)]. Anticancer Activity Was Measured By The Mtt Reduction Assay Using Tumoral (Hela; Du 145; Mcf 7) And Non Tumoral (Nih 3t3) Cell Lines Incubated With The Peptides Over A Concentration Range. The Antibacterial Activity Was Measured By An Optical Density Analysis Using Gram Negative And Gram Positive Strains. The