Okuno Yasushi
Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University.
Nihon Yakurigaku Zasshi. 2022;157(2):111-114. doi: 10.1254/fpj.21085.
The expansion of COVID-19 in the world has not ended yet, and the situation in Japan is still unpredictable. Under these circumstances, the development of SARS-CoV-2 treatments such as vaccines and medicines is still underway. We have been conducting research on the drug screening for SARS-CoV-2 using the supercomputer "Fugaku". Specifically, we searched for and identified therapeutic drug candidates that showed high affinity to the target protein (main protease) related to the multiplication of SARS-CoV-2 from among about 2,000 existing drugs by performing molecular dynamics calculations using Fugaku. This is the first attempt in the world to screen drugs on a scale of several thousand using molecular dynamics calculations, and it is a case where we were able to take on the challenge because Fugaku is ranked No. 1 in the world. In this chapter, we will show the impact of the supercomputer "Fugaku" on drug discovery using our search for therapeutic agents for SARS-CoV-2 as an example.
新型冠状病毒肺炎(COVID-19)在全球的传播尚未结束,日本的情况仍难以预测。在这种情况下,疫苗和药物等严重急性呼吸综合征冠状病毒2(SARS-CoV-2)治疗方法的研发仍在进行中。我们一直在使用超级计算机“富岳”对SARS-CoV-2进行药物筛选研究。具体来说,我们通过使用富岳进行分子动力学计算,从约2000种现有药物中搜索并确定了对与SARS-CoV-2增殖相关的靶蛋白(主要蛋白酶)具有高亲和力的治疗药物候选物。这是世界上首次使用分子动力学计算在数千种规模上进行药物筛选,并且因为富岳在世界上排名第一,我们才有能力迎接这一挑战。在本章中,我们将以寻找SARS-CoV-2治疗药物为例,展示超级计算机“富岳”对药物研发的影响。