EXSCALATE: An Extreme-Scale Virtual Screening Platform for Drug Discovery Targeting Polypharmacology to Fight SARS-CoV-2

The social and economic impact of the COVID-19 pandemic demands a reduction of the time required to find a therapeutic cure. In this paper, we describe the EXSCALATE molecular docking platform capable to scale on an entire modern supercomputer for supporting extreme-scale virtual screening campaigns. Such virtual experiments can provide in short time information on which molecules to consider in the next stages of the drug discovery pipeline, and it is a key asset in case of a pandemic. The EXSCALATE platform has been designed to benefit from heterogeneous computation nodes and to reduce scaling issues. In particular, we maximized the accelerators' usage, minimized the communications between nodes, and aggregated the I/O requests to serve them more efficiently. Moreover, we balanced the computation across the nodes by designing an ad-hoc workflow based on the execution time prediction of each molecule. We deployed the platform on two HPC supercomputers, with a combined computational power of 81 PFLOPS, to evaluate the interaction between 70 billion of small molecules and 15 binding-sites of 12 viral proteins of SARS-CoV-2. The experiment lasted 60 hours and it performed more than one trillion ligand-pocket evaluations, setting a new record on the virtual screening scale.

Secondary infections in critically ill patients with COVID-19: effects of intravenous IgM-enriched immunoglobulin therapy

Introduction: Critically ill patients with severe COVID-19 have an increased risk of bacterial and fungal superinfections due to a dysregulated immune response characterized by lymphopenia and low immunoglobulins levels. The intravenous immunoglobulins are involved in pathogen/toxin scavenging and inhibition of inflammatory mediators gene transcription with anti-apoptotic effects on immune system cells. This research aimed to describe the effects of intravenous IgM-enriched immunoglobulins in COVID-19 patients with sepsis due to secondary infections and low IgM levels. Method(s): We performed an observational retrospective study, including patients admitted to our intensive care unit (ICU) between March 2020 and February 2021 with severe COVID-19 and sepsis due to a superinfection (known or suspected) treated with intravenous IgM-enriched immunoglobulins. We collected demographic data and comorbidities. We noted hemodinamic data, antimicrobial and adiuvant therapies, laboratory results at ICU admission (T0), at the beginning (T1) and at the end (T2) of the IgM-enriched immunoglobulins infusion and at ICU discharge (T3). Result(s): In our cohort of 36 patients (Table 1) the prevalence of documented secondary infections was 83%. We observed a significant reduction of leukocytes from T0 to T3 (10.4 [8.3-14.5] x 103/ mmc vs 7.1 [4.8-11.2] x 103/ mmc, p < 0.01) and the SOFA score from T0 to T2 (7 [6-19] vs 5 [3-7], p < 0.01) and from T0 to T3 (7 [6-10] vs 4 [2-9], p < 0.01);from T1 to T2 (7 [6-9] vs 5 [3-7], p < 0.01) and from T1 to T3 (7 [6-9] vs 4 [2-9], p < 0.01). Cardiovascular SOFA showed a statistically significant reduction from T1 to T2 (4 [3-4] vs 0 [0-3], p < 0.01). Conclusion(s): The IgM-enriched immunoglobulins could improve organ function, as evidenced by the reduction of the SOFA score. Although the latest Surviving Sepsis Campaign guidelines suggest against using of IgM-enriched immunoglobulins, our study supports its use as an adjunctive therapy in COVID-19 patients with septic shock.

Mortality in patients with COVID-19-related ARDS treated with venovenous extracorporeal membrane oxygenation: a retrospective observational study

Introduction: Venovenous extracorporeal membrane oxygenation (VV ECMO) is a technique that provides blood oxygenation and CO2 removal, allowing a protective ventilation strategy until the resolution of respiratory failure. A delay in ECMO initiation could worsen the outcome and prolong the duration of treatment. The study aims to describe the incidence of mortality in our intensive care unit (ICU) in patients with severe COVID-19-related acute respiratory distress syndrome (ARDS) treated with VV ECMO. Method(s): We performed an observational retrospective study, including patients with severe COVID-19-related ARDS admitted to our ICU and treated with VV ECMO between February 2020 and February 2022. We collected data on demographic characteristics, comorbidities, mechanical ventilation, therapies, laboratory results, VV ECMO and ICU mortality. SOFA score, SAPS II and Charlson Comorbidity Index were calculated at ICU admission. Result(s): The average age of our cohort of 60 patients was 54.4 +/- 7.7 years and 51 (85%) were males. The mean value of the SOFA score at ICU admission was 7 +/- 2.3 points, and the median value of the SAPS II score was 41 [31-48] points. The incidence of mortality in the whole cohort was 48.3%. The differences between the two groups of patients, Survivors and Non-survivors, are presented in Table 1. Through a multivariate logistic regression model we found that age (OR 1.09 [95% CI 1.00-1.19], p = 0.03) and lymphocytes (OR 0.09 [95% CI 0.01-0.59], p = 0.01) were significantly associated with ICU mortality. Mechanical ventilation before ECMO placement higher than 10 days and superinfections at ICU admission were not significantly associated with the outcome in the same model. Conclusion(s): In patients with COVID-19-related ARDS treated with VV ECMO, advanced age and lymphopenia at ICU admission are risk factors for ICU mortality. A longer duration of mechanical ventilation before ECMO placement and traditional ICU prognostic scores seem not to be relevant for the prognosis.

Poster: An Extreme-Scale Virtual Screening Platform for Drug Discovery

Virtual screening is one of the early stages that aims to select a set of promising ligands from a vast chemical library. Molecular Docking is a crucial task in the process of drug discovery and it consists of the estimation of the position of a molecule inside the docking site. In the contest of urgent computing, we designed from scratch the EXSCALATE molecular docking platform to benefit from heterogeneous computation nodes and to avoid scaling issues. This poster presents the achievements and ongoing development of the EXSCALATE platform, together with an example of usage in the context of the COVID-19 pandemic.

EXSCALATE: An Extreme-Scale Virtual Screening Platform for Drug Discovery Targeting Polypharmacology to Fight SARS-CoV-2

The social and economic impact of the COVID-19 pandemic demands a reduction of the time required to find a therapeutic cure. In this paper, we describe the EXSCALATE molecular docking platform capable to scale on an entire modern supercomputer for supporting extreme-scale virtual screening campaigns. Such virtual experiments can provide in short time information on which molecules to consider in the next stages of the drug discovery pipeline, and it is a key asset in case of a pandemic. The EXSCALATE platform has been designed to benefit from heterogeneous computation nodes and to reduce scaling issues. In particular, we maximized the accelerators’usage, minimized the communications between nodes, and aggregated the I/O requests to serve them more efficiently. Moreover, we balanced the computation across the nodes by designing an ad-hoc workflow based on the execution time prediction of each molecule. We deployed the platform on two HPC supercomputers, with a combined computational power of 81 PFLOPS, to evaluate the interaction between 70 billion of small molecules and 15 binding-sites of 12 viral proteins of SARS-CoV-2. The experiment lasted 60 hours and it performed more than one trillion ligand-pocket evaluations, setting a new record on the virtual screening scale. IEEE