Banca de QUALIFICAÇÃO: PRISCILA CAROLINE DE SOUSA COSTA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : PRISCILA CAROLINE DE SOUSA COSTA
DATE: 21/12/2021
TIME: 20:00
LOCAL: https://meet.google.com/pei-ebdz-mqq
TITLE:

Functional annotation of domains with unknown function (DUF) aided by in silico prediction data of their three- dimensional structure

KEY WORDS:

DUF, protein domains, AlphaFold, structural similarity of proteins, FATCAT

PAGES: 36
BIG AREA: Ciências Biológicas
AREA: Biologia Geral
SUMMARY:

Proteomics studies have shown a large number of discovered proteins and their importance for the study of life. However, there is still a high percentage of these proteins that have not been functionally annotated and for health and biotechnological advances this definition of unknown proteins is essential. The functions of proteins are defined by their conformity and change in the three-dimensional structure of the protein, therefore, data on the three-dimensional structure of these proteins help to define their functions. Currently, there is a large amount and diversity of proteins that have their sequence characterized, but there is still a methodological difficulty for obtaining their structural data. With the recent development of the AlphaFold program, which accurately predicts the three-dimensional structure of proteins from their amino acid sequence, this difficulty can be overcomed. Thus, the aim of this project is to evaluate the impact of using these structural prediction tools on functional annotations of proteins. In this work, we sought to functionally annotate protein domains of unknown function (DUF). For this, predicted data of its three-dimensional structure were submitted to computational tools that perform a search for other structures that share structural similarity. Preliminary analyzes have shown that many domains can benefit from this analysis. In addition, we generate a classification model that identifies whether two proteins that share structural similarity are remote homologous. This classifier will be used in the future to analyze the similarity results and suggest functions to these domains.

BANKING MEMBERS:
Presidente - 3063244 - TETSU SAKAMOTO
Interno - 059.501.268-07 - JOSÉ MIGUEL ORTEGA - UFMG
Interno - 3083298 - RENAN CIPRIANO MOIOLI