Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning- and physics-based simulations on high-performance computers.

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods, in this case, developed for linear accelerators, and physics-based methods. The two in silico methods, each have their own advantages and limitations which, interestingly, complement each other. Here, we present an innovative infrastructural development that combines both approaches to accelerate drug discovery. The scale of the potential resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput. We have demonstrated the viability of this workflow for the study of inhibitors for four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead antiviral compounds through repurposing on a variety of supercomputers.

Lessons learned from urgent computing in Europe: Tackling the COVID-19 pandemic.

PRACE (Partnership for Advanced Computing in Europe), an international not-for-profit association that brings together the five largest European supercomputing centers and involves 26 European countries, has allocated more than half a billion core hours to computer simulations to fight the COVID-19 pandemic. Alongside experiments, these simulations are a pillar of research to assess the risks of different scenarios and investigate mitigation strategies. While the world deals with the subsequent waves of the pandemic, we present a reflection on the use of urgent supercomputing for global societal challenges and crisis management.

Computational assessment of the entropy of solvation of small-sized hydrophobic entities.

A high level polarizable force field is used to study the temperature dependence of hydrophobic hydration of small-sized molecules from computer simulations. Molecular dynamics (MD) simulations of liquid water at various temperatures form the basis of free energy perturbation calculations that consider the onset and growth of a repulsive sphere. This repulsive sphere acts as a model construct for the hydrophobic species. In the present study, an extension is pursued for seven independent target temperatures, ranging from close to the freezing point almost up to the boiling point of liquid water under standard conditions. Care is taken to maintain proper physico-chemical model descriptions by cross-checking with experimental water densities at the selected target temperatures. The polarizable force field description of molecular water turns out to be suitable throughout the entire temperature domain considered. Derivatives of the computed free energies of hydrophobic hydration with respect to the temperature give access to the changes in entropy. In practice the entropy differential is determined from the negative of the slope of tangential lines formed at a certain target temperature in the free energy profile. The obtained changes in entropy are negative for small-sized cavities, and hence reconfirm the basic ideas of the Lum-Chandler-Weeks theory on hydrophobic hydration of small-sized solutes.

New trends in the virtualization of hospitals--tools for global e-Health.

The development of virtual hospitals and digital medicine helps to bridge the digital divide between different regions of the world and enables equal access to high-level medical care. Pre-operative planning, intra-operative navigation and minimally-invasive surgery require a digital and virtual environment supporting the perception of the physician. As data and computing resources in a virtual hospital are distributed over many sites the concept of the Grid should be integrated with other communication networks and platforms. A promising approach is the implementation of service-oriented architectures for an invisible grid, hiding complexity for both application developers and end-users. Examples of promising medical applications of Grid technology are the real-time 3D-visualization and manipulation of patient data for individualized treatment planning and the creation of distributed intelligent databases of medical images.

Virtual hospital and digital medicine--why is the GRID needed?

The promise of telemedicine to enable equal access to high-level medical care can only be realised by the development of virtual hospitals, digital medicine and a bridging of the digital divide between the various regions of the world. For this, the concept of the Grid should be integrated with other communication networks and platforms. A promising approach is the implementation of service-oriented architectures for an invisible grid, hiding complexity for both application developers and end-users. Therefore integrated Grid Tools Suites for application programmers must be developed. Thus enhancing development and deployment of Grid applications can bring us closer to the simplicity of use that is desired for grid infrastructures not only within the medico-clinical field.