Banca de QUALIFICAÇÃO: CARLA CAROLINE RIBEIRO DE MENDONCA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : CARLA CAROLINE RIBEIRO DE MENDONCA
DATE: 27/05/2022
TIME: 09:00
LOCAL: Link de acesso para videoconferência: https://meet.google.com/xcx-dgvp-vxy
TITLE:
QSAR Models Study of a Series of TRPM8 Inhibitors

KEY WORDS:
Melastatin 8 Transient Potential Receptor; TRPM8; Antagonist; Rational planning; QSAR.

PAGES: 80
BIG AREA: Ciências da Saúde
AREA: Farmácia
SUMMARY:
In this work, 53 α-phenylglycine amides described by Kobayashi (2016) and
(2021) were subjected to analysis by a diverse range of in silico approaches such as
activity cliff, molecular docking, molecular dynamics and QSAR-3D model building.
This with the objective of optimizing its structure for the elaboration of more assertive
prototypes to inhibit TRPM8. It is a non-selective multimodal ion channel receptor that
has a nexus with some diseases such as migraine, overactive bladder and prostate
cancer. The structures have a consolidated synthetic route, as well as the proposed
prototypes. In silico studies were used to predict the 3D properties of structures derived
from existing ones with the hybrid QSAR model that presented acceptable statistical
results (R2Adj = 0.87 and Q2loo = 0.86). Therefore, the results obtained indicate that
it can describe the relationship between structure and activity. With all the information,
it was seen that four prototypes for having a predictive pIC50 > 7.0, with one highlighted
for having a predictive pIC50 > 8.1, and other interesting pharmacokinetic properties
are options for optimizing the most promising compound with pIC50= 6.68 activity
described by Kobayashi (2021). Therefore, such compounds can be synthesized and
studied for the development of new drugs.

BANKING MEMBERS:
Externa à Instituição - DARIZY FLAVIA SILVA AMORIM DE VASCONCELOS - UFBA
Externa ao Programa - 2938129 - LAURA EMMANUELLA ALVES DOS SANTOS SANTANA DE OLIVEIRA
Presidente - 2275890 - MARCELO DE SOUSA DA SILVA
Notícia cadastrada em: 10/05/2022 12:04
SIGAA | Superintendência de Tecnologia da Informação - (84) 3342 2210 | Copyright © 2006-2024 - UFRN - sigaa11-producao.info.ufrn.br.sigaa11-producao