RAPID: MolSSI COVID-19 Biomolecular Simulation Data and Algorithm Consortium

为了应对日益严重的新冠肺炎疫情，分子科学软件研究所将利用其作为中性商品资源的地位，帮助全球计算分子科学界迅速提供他们的科学数据和专业知识，以应对新冠肺炎危机。MolSSI由高级网络基础设施办公室和化学和材料研究司联合支持。该项目的核心将是(1)针对病毒、宿主蛋白质和潜在药物的与模拟相关的数据的中央储存库，以及(2)为博士生和博士后提供的一套精选的MolSSI软件种子奖学金，其目标是对储存库中开发的数据进行操作的新冠肺炎相关软件工具。这两个组成部分将使生物分子模拟界能够共享和利用关键数据和其他资源，以帮助确定宿主-病毒复合体的结构和动态特征，从而为治疗学产生潜在的线索。虽然这个项目的目的是解决严重的新冠肺炎危机，但在短期内，它也将影响研究界和下一代计算分子科学家对未来世界问题的对抗和主动解决。MolSSI将创建和管理一个大型存储库，其中包含：有组织的模拟输入文件(结构、配置、脚本、Jupyter笔记本)；MD轨迹、分析工具和现成的药物发现模型；指向预印服务器(如arxiv、BioRxiv和ChemRxiv)的指针；关于SARS-CoV-2生物分子模拟研究的指针；以及创建可引用数据的DOI服务。此外，它还将通过一系列面向研究生和博士后的软件奖学金与分子科学界接触，以进行软件开发，例如大规模MD模拟、药物发现工具的设计(如对接)、用于小分子毒性预测的机器学习，以及确定新药是否可用于生物利用或可合成的方法。总的来说，这些资源将加速确定和开发抗病毒药物的线索，分析SARS-CoV-2病毒遗传变异的结构效应，以及可以破坏蛋白质-蛋白质相互作用的抑制剂，使病毒进入细胞并附着在导致疾病传播的表面。该奖项由CARE Act补充资金资助，分配给CEISE和MPS。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

In response to the growing COVID-19 pandemic, the Molecular Sciences Software Institute (MolSSI) will leverage its position as a neutral commodity resource to help the global computational molecular sciences community quickly provide their scientific data and expertise to address the COVID-19 crisis. The MolSSI is jointly supported by the Office of Advanced Cyberinfrastructure and the Divisions of Chemistry and Materials Research. The centerpieces of this engagement will be (1) a centralized repository for simulation-related data targeting the virus and host proteins and potential pharmaceuticals, and (2) a select set of MolSSI Software Seed Fellowships for Ph.D. students and postdocs targeting COVID-19 related software tools that operate on the data developed in the repository. These two components will enable the biomolecular simulation community to share and utilize key data and other resources to help identify the structural and dynamic characteristics of the host-virus complex to generate potential leads for therapeutics. Although this project is intended to address the acute COVID-19 crisis, in the near term, it also will impact research communities and the next generation of computational molecular scientists in the confrontation and proactive resolution of future world problems.The MolSSI will create and curate a large-scale repository containing: simulation input files (structures, configurations, scripts, Jupyter notebooks) in an organized structure; MD trajectories, analysis tools, and ready models for drug discovery; pointers to preprint servers such as arXiv, bioRxiv, and ChemRxiv on biomolecular simulation research in regards SARS-CoV-2; and DOI services that create citable data. In addition, it will engage the molecular sciences community through a set of Software Fellowships for graduate student and postdocs to carry out software development, such as large-scale MD simulations, design of drug discovery tools such as docking, machine learning for small molecule toxicity predictions, and methods for determining whether new drugs are bioavailable or can be synthesized. Collectively, these resources will speed the identification and development of leads for antiviral drugs, analyzing structural effects of genetic variation in the SARS-CoV-2 virus, and inhibitors that can disrupt protein-protein interactions to viral entry into cells and adherence to surfaces that cause disease spread.This award is being funded by the CARES Act supplemental funds allocated to CISE and MPS.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.