This study predicts that the SARS-CoV-2 XBB.1.5 variant may spread more widely and faster than other variants based on molecular docking and evolutionary analysis.

5 citations

humanstatistical model

𝕏 PostBluesky

BioinformaticsMicrobial Risk AnalysisPeer-reviewedDec 1, 2022

Prediction of infectivity of SARS-CoV2: Mathematical model with analysis of docking simulation for spike proteins and angiotensin-converting enzyme 2

Yutaka Takaoka, Aki Sugano, Yoshitomo Morinaga…·Yoshimasa Maniwa

The paper predicts SARS-CoV-2 infectivity using a mathematical model combining molecular docking simulations and phylogenetic analysis of spike protein variants.

7 citations

virusprotein structure

𝕏 PostBluesky

BioinformaticsbioRxivPreprintAug 25, 2022

SARS-CoV-2 Omicron BA.2.75 variant may be much more infective than preexisting variants

Aki Sugano, Yutaka Takaoka, Haruyuki Kataguchi…·Yoshihiro Yamamoto

The paper predicts that the SARS-CoV-2 BA.2.75 variant has higher infectivity than previous variants due to increased spike protein evolutionary distance and docking affinity with ACE2.

3 citations

humanstatistical model

𝕏 PostBluesky