Alessandro Gallo1, Alberto E. Maraolo2
1General Manager, Springer Healthcare Italia
2First Division of Infectious Diseases, AORN dei Colli – Cotugno Hospital, Naples, Italy
Exscalate4CoV, High-Performance Computing for COVID Drug Discovery (editors Silvano Coletti and Gabriella Bernardi) is a newly published monograph by Springer Nature, part of the Springer Book Series in Applied Sciences and Technology. The book discusses the use of computer modeling in drug discovery and design, focusing on the challenges and advancements in estimating binding affinity between proteins and ligands. The authors note that progress has been slow in accurately predicting binding energies, but there have been promising developments in macroscopic and semi-macroscopic models, as well as in the use of machine learning. This kind of approach allows not only the discovery of novel drugs, but also the repurposing of old molecules for new indications. Even the use of virtual reality was taken into account as instrumental tool in drug discovery.
The book also highlights the challenge of evaluating the effect of water penetration and suggests the “water flooding” approach as a solution. Despite current limitations, the authors believe that computer-aided calculations will eventually become the key tool in rational drug design, and that educating the scientific community about the power of computers in drug design is crucial to advancing the field.
The Exscalate4CoV project analysed in the monograph has the potential to benefit several groups, including biotech and pharmaceutical companies, clinicians, pharmacologists, and patients:
- for biotech and pharmaceutical companies, the project could provide a faster and more cost-effective way to identify potential drugs for COVID-19. Using high-performance computing, the project can quickly screen a vast number of molecules and identify those that may have potential for treating COVID-19. This could speed up the drug development process and reduce the costs associated with traditional drug discovery methods.
- Clinicians and pharmacologists could benefit from the project by having access to potential drugs that could be used to treat COVID-19. With the ongoing pandemic, there is a great need for effective treatments for COVID-19, and the Exscalate4CoV project could help identify new treatments that could be used to save lives.
- Patients could benefit from the project by having access to new treatments for COVID-19 that could potentially save lives. The project’s high-performance computing capabilities can help identify potential drugs that may not have been discovered through traditional drug discovery methods. This could lead to the development of new treatments that are more effective than current treatments, improving patient outcomes.
Dompé, as a pharmaceutical company engaged in the research and development of new drugs, has played a significant role in the Exscalate4CoV project. The company has contributed to this project by providing scientific expertise and resources to identify potentially active chemical compounds against the virus. Leveraging its experience in pharmaceutical research, Dompé has also contributed to the evaluation of pharmacological candidates, assisting in the selection of promising molecules for further studies and development. Additionally, Dompé has made its infrastructure and production capacity available to support the manufacturing of potential therapies identified during the project, ensuring rapid availability in case they prove effective and safe for the treatment of COVID-19.
Dompé’s commitment to the Exscalate4CoV project represents an important contribution to seeking innovative solutions to combat the pandemic and provide effective therapies for patients with COVID-19. In order to learn additional insights about the strategic implications of this project and its direct implications in the field of clinical practice and infectious diseases, we interviewed Dr. Marcello Allegretti, Scientific Director of Dompé.
Dr. Allegretti, how quickly can we keep pace with the evolution of SARS-CoV-2 in light of the rapid emergence of new variants?
The evolution and discovery of new variants of SARS-CoV-2 are closely monitored by researchers, who track their appearance and spread to be prepared for designing vaccines with improved characteristics compared to previous ones. It is known that the virus has transitioned from a regime of continuous evolution to a discrete regime characterized by large evolutionary leaps and has ultimately returned to the current state of continuous evolution. It has developed recent variants that seem to have very similar forms in terms of mutations. The observed similarity, including in the receptor binding domain of the viral spike protein, which helps the virus infect human cells and presents mutations correlated with new subvariants, confirms, according to experts, that the virus is continually activating new immune evasion strategies more frequently than in the past. This scenario highlights that the protection offered by current vaccines will gradually diminish as variants emerge and establish themselves, underscoring the need to promptly update vaccine compositions in response to mutations.
In this context, the use of a “platform” approach is considered relevant by regulatory authorities (WHO, EMA/ECDC), especially if it predicts the clinical immunogenicity of the new vaccine based on data generated from previously studied variant strains. This approach potentially allows for the rapid approval of “updated” vaccines (https://www.ema.europa.eu/en/news/ema-ecdc-statement-updating-covid-19-vaccines-target-new-sars-cov-2-virus-variants). A timely and preemptive warning from medical and regulatory authorities regarding the need to adapt vaccine compositions would enable different stakeholders in the process to prepare for new vaccination campaigns at the right time.
Could this platform also be used for the discovery of new anti-SARS-CoV-2 vaccines?
Indeed! The combination of artificial intelligence and high-performance computing (HPC), which are key features of the Exscalate platform, integrated with the use of chemo and bioinformatics tools developed over time, enables the design and development of new vaccines with improved safety profiles compared to existing ones. This is achieved by predicting potential interactions of the spike protein or other viral antigens with various, sometimes unconventional, targets within the host cell. Thanks to the characteristics of the Exscalate platform, the concept previously applied to the design of anti-SARS-CoV-2 vaccines can also be extended to the design of pan-coronavirus vaccines, targeting different SARS-CoV-2 variants as well as other viruses belonging to the coronavirus family, always focusing on the spike protein. Furthermore, the Exscalate approach, based on knowledge of the binding sites of biological targets, is also well-suited for designing new vaccines targeting antigens other than the spike protein.
Could Exscalate be repurposed for the discovery of new antibiotics or the repurposing of old antibiotics to counter antibiotic resistance?
Once again, yes! Exscalate was created as a virtual screening platform to accelerate the process of drug discovery and development. It combines one of the most advanced AI-based virtual screening platforms with one of the largest annotated libraries for the selection of new preclinical and clinical candidates. The goal is to make the process of discovering new drugs and repurposing known drugs faster, more efficient, and less costly compared to traditional standards. This applies not only to the discovery of new drugs but also to the repurposing of drugs that are already known or used, based on new knowledge about molecular targets and mechanisms of action. Studies can be initiated for their reuse, perhaps in new clinical indications. The search for new antibiotics, using new therapeutic tools to overcome some of the known challenges associated with antibiotic resistance, is precisely in line with this approach. Dompé is already collaborating with public and private research organisations in this area, using the Exscalate platform.
In summary, the Exscalate4CoV project could be beneficial for biotech and pharmaceutical companies, clinicians, pharmacologists, and patients by providing a faster and more cost-effective way to identify potential drugs for COVID-19, improving access to potential treatments, and potentially saving lives.
We are certain that this Springer Nature publication will support researchers in this field even further, by facilitating the dissemination of complex concepts largely beyond the field of computer science.