Decoding Enzyme–Inhibitor Kinetic Mechanisms by Isothermal Titration Calorimetry: The Case of SARS-CoV-2 3CL pro
Abstract
High Resolution Image Download MS PowerPoint Slide Accurate kinetic and thermodynamic characterization of enzyme inhibitors remains difficult because conventional activity assays can miss nonequilibrium behavior and provide limited mechanistic resolution. Here, we present an inverse single-injection isothermal titration calorimetry (ITC) workflow that extracts qualitative and quantitative inhibition parameters directly from heat-flow traces by distinguishing rapid reversible, tight-, or slow-binding, and covalent inhibition within a single experimental format. The inhibition of SARS-CoV-2 main protease (3CL pro ) with ML300, X77, Nirmatrelvir, and Ensitrelvir was used as a benchmark. 3CL pro is pivotal for viral replication, catalyzing polyprotein cleavage into functional nonstructural proteins and representing a key target for structure-based drug design. Despite the development of potent inhibitors, their inhibition mechanisms remain incompletely understood, as conventional assays often lack the resolution to capture the details of enzyme kinetics that are critical for accurate pharmacological characterization and therapy optimization. Model-based fitting of raw calorimetric transients yielded inhibition constants together with mechanistically informative kinetic and thermodynamic parameters without relying on end point readouts. Equilibrium ITC binding measurements on wild-type and mutant 3CL pro variants provided independent validation, revealing distinct affinity and thermodynamic parameters that complemented the inferred inhibitory pathway. These results establish inverse single-injection kinetic ITC as a robust and versatile analytical platform for dissecting complex enzyme inhibition mechanisms, supporting the rational optimization of next-generation SARS-CoV-2 3CL pro inhibitors, and offering broad applicability in drug discovery.
Fields of Study & Subjects
thermodynamics and calorimetric analyses
Computational Drug Discovery Methods
SARS-CoV-2 and COVID-19 Research
Publication details
- Journal / source
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Volume
- 98
- Issue
- 26
- Pages
- 19520–19532
- Publication date
- 23 June 2026
- Language
- EN