Targeting SARS-CoV-2 papain-like protease in the postvaccine era

• Published in: Trends in Pharmacological Sciences 2022-11, Vol.43 (11), p.906-919
• Main Authors: Ton, Anh-Tien, Pandey, Mohit, Smith, Jason R., Ban, Fuqiang, Fernandez, Michael, Cherkasov, Artem
• Format: Article
• Language: English
• Subjects: Antiviral Agents - pharmacology; Antiviral Agents - therapeutic use; artificial intelligence; computer-aided drug design; Coronavirus Papain-Like Proteases - antagonists & inhibitors; COVID-19; COVID-19 Drug Treatment; Humans; Opinion; papain-like protease; SARS-CoV-2; small molecules
• ISSN: 0165-6147; 1873-3735
• DOI: 10.1016/j.tips.2022.08.008

While vaccines remain at the forefront of global healthcare responses, pioneering therapeutics against SARS-CoV-2 are expected to fill the gaps for waning immunity. Rapid development and approval of orally available direct-acting antivirals targeting crucial SARS-CoV-2 proteins marked the beginning of the era of small-molecule drugs for COVID-19. In that regard, the papain-like protease (PLpro) can be considered a major SARS-CoV-2 therapeutic target due to its dual biological role in suppressing host innate immune responses and in ensuring viral replication. Here, we summarize the challenges of targeting PLpro and innovative early-stage PLpro-specific small molecules. We propose that state-of-the-art computer-aided drug design (CADD) methodologies will play a critical role in the discovery of PLpro compounds as a novel class of COVID-19 drugs. New emergency-approved drugs against COVID-19 represent the beginning of powerful oral anti-COVID-19 inhibitors in the postvaccine era. Vaccines remain at the forefront of global healthcare response, but oral drugs can fill the gaps when immunity starts waning.The papain-like protease (PLpro) ensures viral replication by processing viral polyproteins and host post-translational modifications. However, a lack of diverse high-quality scaffolds against the protease hinders drug development. Promising compounds are derived from an older noncovalent compound previously identified for SARS-CoV-1.There is a methodological transition focusing on computational screening complimented by experimental validation of inhibitory activity and on-target effects. Deploying machine-learning-enhanced in silico methods should increase the success of identifying diverse and new scaffolds against PLpro.