Department of Drug Sciences, University of Catania, 95125, Catania, Italy.
Computer Science Institute, DiSIT, University of Eastern Piedmont, 15125, Alessandria, Italy.
BMC Bioinformatics. 2020 Dec 14;21(Suppl 17):527. doi: 10.1186/s12859-020-03872-0.
SARS-CoV-2 is a severe respiratory infection that infects humans. Its outburst entitled it as a pandemic emergence. To get a grip on this outbreak, specific preventive and therapeutic interventions are urgently needed. It must be said that, until now, there are no existing vaccines for coronaviruses. To promptly and rapidly respond to pandemic events, the application of in silico trials can be used for designing and testing medicines against SARS-CoV-2 and speed-up the vaccine discovery pipeline, predicting any therapeutic failure and minimizing undesired effects.
We present an in silico platform that showed to be in very good agreement with the latest literature in predicting SARS-CoV-2 dynamics and related immune system host response. Moreover, it has been used to predict the outcome of one of the latest suggested approach to design an effective vaccine, based on monoclonal antibody. Universal Immune System Simulator (UISS) in silico platform is potentially ready to be used as an in silico trial platform to predict the outcome of vaccination strategy against SARS-CoV-2.
In silico trials are showing to be powerful weapons in predicting immune responses of potential candidate vaccines. Here, UISS has been extended to be used as an in silico trial platform to speed-up and drive the discovery pipeline of vaccine against SARS-CoV-2.
SARS-CoV-2 是一种严重的呼吸道感染病毒，会感染人类。它的爆发使其成为一种大流行事件。为了控制这种疫情，急需采取特定的预防和治疗干预措施。必须指出的是，到目前为止，还没有针对冠状病毒的现有疫苗。为了迅速应对大流行事件，可以应用计算机模拟试验来设计和测试针对 SARS-CoV-2 的药物，并加快疫苗发现的管道，预测任何治疗失败的可能性并最小化不良影响。
我们提出了一个计算机模拟平台，该平台在预测 SARS-CoV-2 动力学及其相关免疫系统宿主反应方面与最新文献非常吻合。此外，它还被用于预测最近提出的一种设计有效疫苗的方法的结果，该方法基于单克隆抗体。通用免疫系统模拟器（UISS）计算机模拟平台已准备好用作计算机模拟试验平台，以预测针对 SARS-CoV-2 的疫苗接种策略的结果。
计算机模拟试验正在成为预测潜在候选疫苗免疫反应的有力武器。在这里，UISS 已被扩展为一种计算机模拟试验平台，用于加速和推动针对 SARS-CoV-2 的疫苗发现管道。
