Experimental Assays: Chemical Properties, Biochemical and Cellular Assays,and In Vivo Evaluations

The design and discovery of new bioactive compounds have been essential for the development of potential new inhibitors and drug candidates. In this regard, the use of computational simulations has proven to play an important role in achieving new drugs. Throughout history and most recently, new drugs, e.g., protease inhibitors, have benefited from the so-called computer-aided drug discovery (CADD) approaches, providing available therapeutic options to emerging or re-emerging diseases, such as the coronavirus disease 2019 (COVID-19). These in silico models and methods can be employed for different purposes, such as prediction of various biological activities, toxicity, pharmacokinetics, target specificity, and even the synthesis of new analogs. Ultimately, such predictions can select or disregard a given compound for an in vitro or in vivo evaluation. However, translating a simulation to an experimental validation may be challenging. For instance, one should consider chemical properties and solubility, different biochemical and cellular assays, and the availability of data or methods to assess bioactive compounds and potentially reach a successful candidate. This chapter aims to provide a detailed overview of the many computational possibilities to achieve or improve experimental feasibility. Furthermore, we address the challenges and pitfalls regarding such approaches, which may contribute to a successful drug design and discovery campaign in the field.