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Updated: Aug 8, 2026

Hot Biological Catalysis: Isothermal Titration Calorimetry to Characterize Enzymatic Reactions
Published on: April 4, 2014
Computational Study of Enzyme Inhibition
Francisco das Chagas Pereira de Andrade1,2, Mateus Henrique de Almeida da Costa1,2, Anderson Nogueira Mendes3,4
1Laboratory of Innovation in Science and Technology-LACITEC, Department of Biophysics and Physiology, Federal University of Piauí, 64049-550, Teresina, Piauí, Brazil.
Abstract:
Computational approaches have become essential in modern drug discovery, significantly reducing the time and cost associated with identifying and optimizing new enzyme inhibitors. This chapter explores key computational techniques, including molecular docking, molecular dynamics, and QSAR modeling, which enhance the accuracy and efficiency of drug design. Furthermore, advancements in artificial intelligence and machine learning are increasingly integrated into these methodologies, improving predictive modeling and target validation. Despite challenges, such as system complexity and algorithm limitations, computational methods continue to evolve, bridging the gap between theoretical predictions and experimental validation. This chapter discusses the latest trends, software tools, and case studies, emphasizing their role in accelerating drug development and improving therapeutic outcomes.
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