NovaLead Pharma, a Pune-based company has utilised its experience of drug repurposing has deployed computational technology to identify 42 existing drugs which may be potentially effective against the SARS-Cov2 virus. Supreet Deshpande, CEO, NovaLead Pharma shares more insights on how computational technologies can revolutionise pharma R&D and help gain significant advantages to tackle health threats like the coronavirus pandemic, in an exclusive interaction with Lakshmipriya Nair.
How can the current models of drug discovery and development be revamped to make pharma R&D more predictable, reliable, and less costly?
Pharma R&D can become more predictable, reliable, less costly and more productive by:
– Making smart use of the techniques and technologies in molecular sciences, coupled with data mining
– Leveraging the advancements in computational technologies, especially molecular simulations, neural networks, artificial intelligence and machine learning
– Using scientific algorithms for molecular library generation and virtual screening
What are the methods/strategies that can effectively predict or prioritise which targets to go after to treat or cure diseases which have emerged as a priority, especially as the Covid19 pandemic plays out?
Computational methodologies like molecular modelling and protein-ligand docking can be effective in predicting as well as prioritising key targets related to Covid19. Scientific literature is being made available about the important coronavirus targets (like spike proteins) as well the human proteins (like ACE2). Using computational homology models, drug molecules can be screened against these targets, to come out with useful hits. Genomic and proteomic analysis to understand biological pathways are important in this effort. For new viruses like SARS-CoV-2, where its proteins are not all known and even where they are known, their crystal structure may not be available so soon. In such cases, computational techniques of homology modelling are highly useful for drug screening. Accuracy of homology models depends on the underlying algorithms and expertise.
How are computational methodologies helping transform drug discovery and repurposing of existing drugs? How can they be especially useful in the fight against zoonosis or infectious diseases?
Over the last two decades, computational technologies have been making huge inroads into drug discovery. Use of various structure-based, as well as ligand-based computational strategies, are being employed in the drug discovery process, by large global pharma companies as well as innovator drug discovery companies in the West. Drug repurposing is a relatively new field and there are not many innovator companies which use computational technologies to the fullest. NovaLead is one such innovator company, with its indigenously developed computational technology platform. The main challenge in infectious diseases is of pathogen mutations and new pathogens. A newly mutated virus or new virus may not have a potent vaccine or drug that effectively fights it. This scenario opens the potential for the rapid proliferation of the disease, potentially making into a pandemic. The recent COVID-19 is a case-in-point. Drug repurposing strategies with computational technologies can rapidly screen promising drugs against a range of viral and human targets, specific to the infectious diseases, and come up with the potential drug candidates. Being a known drug, such candidates can then be fast-tracked through the regulatory process to make into viable medicinal options to fight the disease.
Can you elaborate on a few computational methods and tools applied to predict or validate drugs’ efficacy with a couple of real-life examples?
Methods such as structure-based design, molecular docking, quantitative structure-activity relationship (QSAR), pharmacophore modelling are some of the methods used in predicting drug binding to selected protein targets. Above methods have been used in drug discovery of several successful drugs that have reached the market. Specific examples are anti-viral drugs such as Indinavir, Nelfinavir, Lopinavir, etc. where the above methods were used during the discovery of these drugs.
What ar...
(All Rights Reserved)