Unlocking the Power of Computational Technologies

The book covers a wide range of cutting-edge computational technologies, including artificial intelligence (AI), quantum computing, and cloud computing. These innovations are driving drug discovery forward, enabling the prediction of protein structures, virtual screening, and generative modeling for compound design.

With dedicated chapters on recent trends in computer-aided drug design, this book delves into the application of molecular dynamics, quantum mechanics (QM), and hybrid approaches such as QM/MM. It also explores techniques for navigating and visualizing the chemical space, and leveraging big data to drive drug discovery efforts.

Key Topics in Computational Drug Discovery

• Application of molecular dynamics simulations and related approaches in drug discovery
• The role of QM, hybrid approaches such as QM/MM, and fragment molecular orbital framework in understanding protein-ligand interactions
• Adoption of artificial intelligence in pre-clinical drug discovery, including protein structure prediction, generative modeling for de novo design, and virtual screening
• Techniques for navigating and visualizing the chemical space, and harnessing big data to drive drug discovery efforts
• Methods for performing ultra-large-scale virtual screening for hit identification
• Computational strategies for designing new therapeutic models, including PROTACs and molecular glues
• In silico ADMET approaches for predicting a variety of pharmacokinetic and physicochemical endpoints
• The impact of computing technologies like quantum computing and cloud computing on accelerating drug discovery