Os pesquisadores modelaram computacionalmente a ligaa§a£o do pico da proteana SARS-CoV-2 ao ACE2, que estãolocalizado no trato respirata³rio superior e serve como ponto de entrada para outros coronavarus, incluindo SARS.
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)
Este esquema mostra a diferença nas interações entre SARS-CoV e ACE2 humano versus SARS-CoV-2 e ACE2 humano. Crédito: Ratul Chowdhury, Penn State
A ligação de um pico de proteana desuperfÍcie do varus SARS-CoV-2 - uma projeção da partacula esfanãrica do varus - a proteana desuperfÍcie celular humana ACE2 éo primeiro passo para a infecção que pode levar a doença COVID-19. Os pesquisadores da Penn State avaliaram computacionalmente como asmudanças na composição do pico do varus podem afetar a ligação com ACE2 e compararam os resultados com os do varus SARS-CoV original (SARS).
A pré-impressão do manuscrito original dos pesquisadores, disponibilizada online em mara§o, foi uma das primeiras a investigar computacionalmente a alta afinidade ou tendaªncia de ligação do SARS-CoV-2 com o ACE2 humano. O artigo foi publicado online em 18 de setembro no Computational and Structural Biotechnology Journal . O trabalho foi concebido e liderado por Costas Maranas, Donald B. Broughton Professor do Departamento de Engenharia Química, e seu ex-aluno Ratul Chowdhury, que atualmente épa³s-doutorando na Harvard Medical School.
"Esta¡vamos interessados ​​em responder a duas perguntas importantes", disse Veda Sheersh Boorla, estudante de doutorado em engenharia química e co-autora do artigo. "Queraamos primeiro discernir as principaismudanças estruturais que da£o ao COVID-19 uma maior afinidade para as proteanas ACE2 humanas quando comparado com o SARS, e então avaliar sua afinidade potencial para o gado ou outras proteanas ACE2 animais."
"O fluxo de trabalho computacional que estabelecemos deve ser capaz de lidar com outros mecanismos de entrada mediados por ligação de receptor para outros varus que possam surgir no futuro",
Chowdhury.
Os pesquisadores modelaram computacionalmente a ligação do pico da proteana SARS-CoV-2 ao ACE2, que estãolocalizado no trato respirata³rio superior e serve como ponto de entrada para outros coronavarus, incluindo SARS. A equipe usou uma abordagem de modelagem molecular para calcular a força de ligação e as interações da ligação da proteana viral a ACE2.
A equipe descobriu que a proteana spike SARS-CoV-2 éaltamente otimizada para se ligar a ACE2 humana. Simulações de ligação viral a proteanas ACE2 homa³logas de morcegos, bovinos, galinhas, cavalos, felinos e caninos mostraram a maior afinidade para morcegos e ACE2 humanos, com menores valores de afinidade para gatos, cavalos, ca£es, gado e galinhas, de acordo com Chowdhury.
"Além de explicar o mecanismo molecular de ligação com o ACE2, também exploramos asmudanças no pico do varus que podem mudar sua afinidade com o ACE2 humano", disse Chowdhury, que obteve seu doutorado em engenharia química na Penn State no outono de 2019.
Compreender o comportamento de ligação do pico do varus com ACE2 e a tolera¢ncia do varus a essasmudanças estruturais do pico pode informar pesquisas futuras sobre a durabilidade da vacina e o potencial do varus se espalhar para outras espanãcies.
"O fluxo de trabalho computacional que estabelecemos deve ser capaz de lidar com outros mecanismos de entrada mediados por ligação de receptor para outros varus que possam surgir no futuro", disse Chowdhury.