Exscalate4CoV

Despite recent advancements, biopharma drug research and development remains expensive and time-consuming. However, there are numerous opportunities to build capabilities that enhance productivity and improve the probability of success.

The COVID-19 pandemic highlighted an urgent need for streamlined drug development processes. Enhanced virtual screening methods could expedite drug discovery via rapid screening of large virtual compound libraries to identify high-priority drug candidates. The EXSCALATE4CoV (EXaSCale smArt pLatform Against paThogEns for CoronaVirus) consortium (E4C) research team developed EXSCALATE (EXaSCale smArt pLatform Against paThogEns), the most complex screening simulation to date, containing a virtual library of >500 billion compounds and a high-throughput docking software, LiGen (Ligand Generator). Additionally, E4C developed a smaller virtual screen of a “safe-in-man” drug library to identify optimal candidates for drug repurposing. To identify compounds targeting SARS-CoV-2, EXSCALATE performed >1 trillion docking simulations to optimize the probability of identifying successful drug candidates. Ligands identified in simulations underwent subsequent in vitro experimentation to determine drug candidates that have anti-SARS-CoV-2 agency and have probable in-human efficacy. While many compound candidates were validated to have anti-SARS-CoV-2 properties, raloxifene had the best outcome and subsequently demonstrated efficacy in a phase 2 clinical trial in patients with early mild-to-moderate COVID-19, providing proof of concept that the in silico approaches used here are a valuable resource during emergencies. After its emergence in 2019, the SARS-CoV-2 coronavirus spread internationally at a rapid pace, leading to the designation of COVID-19 as a pandemic in March 2020. In addition to a devastating impact on public health, COVID-19 has resulted in extensive negative social and economic effects in every corner of the globe. When the pandemic arrived, the medical and scientific communities identified an urgent need to establish more rapid therapeutic and vaccine development processes for COVID-19. However, it was clear that any new measures needed to be implemented in a way that also supported rapid mobilization to fight potential future pandemics. Therapeutic discovery is a complicated and prolonged process, often taking 10–15 years to complete all stages, and typically involves a linear workflow starting with in silico investigations, followed by increasingly complex and correspondingly expensive in vitro, in vivo, and clinical studies. In the context of the pandemic, the importance of the in silico stage increased because of the capacity of exascale computational methods to identify and prioritize small molecule (and biological) agents with the greatest therapeutic potential. Better in silico-generated starting points for drug-discovery efforts increase the likelihood of success in downstream laboratory-based experimental stages and can contribute to vitally needed reductions in costs and time to market for new therapies.

Drug repurposing is a cost-effective process to identify therapeutic candidates during a medical crisis or pandemic. The supercomputing platform, EXaSCale smArt pLatform Against paThogEns for CoronaVirus (EXSCALATE4CoV; E4C), was used to identify drug candidates for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. E4C identified raloxifene as having great therapeutic potential, confirmed by in vitro data, which led to the progression of clinical trials to assess its efficacy. Raloxifene met the primary virologic endpoint in the treatment of early mild coronavirus disease 2019 (COVID-19), and although additional clinical trials are needed to confirm these results, there is evidence in support of in silico drug repurposing to provide cost-effective and rapid drug screening to identify treatment options for the pandemic and future pandemics.

The coronavirus disease 2019 pandemic not only precipitated a digital revolution but also led to one of the largest scientific collaborative open-source initiatives. The EXaSCale smArt pLatform Against paThogEns for CoronaVirus (EXSCALATE4CoV) consortium, led by Dompé farmaceutici S.p.A., brought together 18 global organizations to counter international pandemics more rapidly and efficiently. The consortium also partnered with Nanome, an extended reality software company whose software facilitates the visualization, modification, and simulation of molecules via augmented reality, mixed reality, and virtual reality applications. To characterize the molecular structure of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to identify promising drug targets, the EXSCALATE4CoV team utilized methods such as homology modeling, molecular dynamics simulations, high-throughput virtual screening, docking, and other computational procedures. Nanome provided analysis of those computational procedures and supplied virtual reality headsets to help scientists better understand and interact with the molecular dynamics and key chemical interactions of SARS-CoV-2. Nanome’s collaborative ideation platform enables scientific breakthroughs across research institutions in the fight against the coronavirus pandemic and other diseases.

The large amount of genetic, phenotypic, and structural data from diverse conditions and environments offers opportunities for new groundbreaking research. Today, the major scientific task is to interpret the vast number of genetic variants within these data. As described in this chapter, identifying relevant variants and connecting them with the associated protein structural and environmental information is a powerful approach to biological discoveries. The unified view of the data brings us a step closer to understanding genetic variation, which is also fundamental for achieving the goals of personalized medicine and the planet’s environment.

The main protease (Mpro) of SARS-CoV-2, a cysteine protease that plays a key role in generating the active proteins essential for coronavirus replication, is a validated drug target for treating COVID-19. The structure of Mpro has been elucidated by macromolecular crystallography, but owing to its conformational flexibility, finding effective inhibitory ligands was challenging. Screening libraries of ligands as part of EXaSCale smArt pLatform Against paThogEns (ExScalate4CoV) yielded several potential drug molecules that inhibit SARS-CoV-2 replication in vitro. We solved the crystal structures of Mpro in complex with repurposed drugs like myricetin, a natural flavonoid, and MG-132, a synthetic peptide aldehyde. We found that both inhibitors covalently bind the catalytic cysteine. Notably, myricetin has an unexpected binding mode, showing an inverted orientation with respect to that of the flavonoid baicalein. Moreover, the crystallographic model validates the docking pose suggested by molecular dynamics experiments. The mechanism of MG-132 activity against SARS-CoV-2 Mpro was elucidated by comparison of apo and inhibitor-bound crystals, showing that regardless of the redox state of the environment and the crystalline symmetry, this inhibitor binds covalently to Cys145 with a well-preserved binding pose that extends along the whole substrate binding site. MG-132 also fits well into the catalytic pocket of human cathepsin L, as shown by computational docking, suggesting that it might represent a good start to developing dual-targeting drugs against COVID-19.

Technology and artificial intelligence, alongside the COVID-19 pandemic vastly increasing technology use in health care, have precipitated an escalation of big data. Although real-world data (RWD) and real-world evidence (RWE) have contributed to determining outcomes outside the scope of randomized clinical trials (RCTs), RWD and RWE are underutilized in demonstrating drug effectiveness. Utilizing RWD may enhance the ability of regulatory agencies to approve drugs, provide drug effectiveness insight to payers, and improve personalized medicine. Additionally, RWD and RWE may assist in overcoming the limitations of RCT data such as treatment adherence and underrepresented patient subgroups and may support and expedite drug repositioning. Even though the limitations of using RWE and RWD include fragmented data context, poor data quality, and information governance, healthcare analytics hubs such as the European Health Data Space are designed to foster synergy among private and public healthcare players and may assist in overcoming these potential limitations. Such healthcare analytics hubs may enhance the utilization of RWE and/or RWD, which could ultimately result in better patient outcomes.

Sustained and innovative communication is needed to engage citizens as science and technology rapidly evolve to meet global challenges. The role of science in society has become a role of science for society, underscoring the importance of effective communication in fostering scientific literacy. Informal science education experiences, facilitated by the more widespread implementation of information technologies, are becoming increasingly relevant to science understanding over time. Additionally, social media provides opportunities for learners to interact with content and to become active creators of information. The life sciences have pioneered innovative educational programs, particularly virtual reality techniques, that represent a successful approach to learning and teaching chemical interactions.

In the last 2 years, the SARS-CoV-2 (COVID-19) pandemic demonstrated that rapid response to outbreaks with readily effective treatments represents a primary health and societal priority. At the same time, we became conscious that technological resources are often not used in the most efficient manner. The LIGATE and REpurposing MEDIcines For All (REMEDI4ALL) projects started on the large-scale mobilization efforts of the EXaSCale smArt pLatform Against paThogEns (Exscalate4Cov) project with the aim to apply cutting-edge technologies in drug discovery, sustain the fight against future pandemics, and promote the everyday fight against rare diseases. In particular, the LIGATE project, using the drug-discovery platform Exscalate, intends to boost the virtual screening of drug campaigns at an extreme scale in terms of performance and streamline the drug-development process. The aim of the REMEDI4ALL project is to collect sciQ1entific expertise and innovative technology platforms for the repurposing of medicines to treat rare diseases or other pathologic conditions with no current therapy.