Drug discovery is a highly complex and costly process, which demands integrated efforts in several relevant aspects involving innovation, knowledge, information, technologies, expertise, R investments and management skills. The shift from traditional to genomics- and proteomics-based drug research has fundamentally transformed key R strategies in the pharmaceutical industry addressed to the design of new chemical entities as drug candidates against a variety of biological targets. Therefore, drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. The combination of available knowledge of several 3D protein structures with hundreds of thousands of small-molecules have attracted the attention of scientists from all over the world for the application of structure- and ligand-based drug design approaches. In this context, virtual screening technologies have largely enhanced the impact of computational methods applied to chemistry and biology and the goal of applying such methods is to reduce large compound databases and to select a limited number of promising candidates for drug design. This review provides a perspective of the utility of virtual screening in drug design and its integration with other important drug discovery technologies such as high-throughput screening (HTS) and QSAR, highlighting the present challenges, limitations, and future perspectives in medicinal chemistry.

SARS-CoV-2 is the causative agent of COVID-19. The main viral protease (M^pro) is an attractive target for antivirals. The clinically approved drug nirmatrelvir and the clinical candidate ensitrelvir have so far showed great potential for treatment of viral infection. However, the broad use of antivirals is often associated with resistance generation. Herein, we enzymatically characterized 14 naturally occurring M^pro polymorphisms that are close to the binding site of these antivirals. Nirmatrelvir retained its potency against most polymorphisms tested, while mutants G143S and Q189K were associated with diminished inhibition constants. For ensitrelvir, diminished inhibition constants were observed for polymorphisms M49I, G143S, and R188S, but not for Q189K, suggesting a distinct resistance profile between inhibitors. In addition, the crystal structures of selected polymorphisms revealed interactions that were critical for loss of potency. In conclusion, our data will assist the monitoring of potential resistant strains, support the design of combined therapy, as well as assist the development of the next generation of M^pro inhibitors.

The current Zika virus (ZIKV) outbreak became a global health threat of complex epidemiology and devastating neurological impacts, therefore requiring urgent efforts towards the development of novel efficacious and safe antiviral drugs. Due to its central role in RNA viral replication, the non-structural protein 5 (NS5) RNA-dependent RNA-polymerase (RdRp) is a prime target for drug discovery. Here we describe the crystal structure of the recombinant ZIKV NS5 RdRp domain at 1.9 Å resolution as a platform for structure-based drug design strategy. The overall structure is similar to other flaviviral homologues. However, the priming loop target site, which is suitable for non-nucleoside polymerase inhibitor design, shows significant differences in comparison with the dengue virus structures, including a tighter pocket and a modified local charge distribution.