Preface

Computational Chemistry continues to play a transformative role in modern scientific research, integrating diverse computational strategies to address challenges in drug discovery, materials design, and molecular-level understanding of complex biological systems. The Frontiers in Computational Chemistry series aims to provide a platform for the dissemination of cutting-edge research and applications of computational techniques in chemistry and biology. This includes advancements in computer-aided drug design, quantum and molecular simulations, peptide modeling, and the development of novel computational algorithms that contribute to the efficient exploration of chemical and biological phenomena.

In this eighth volume, we present seven chapters that collectively highlight the latest progress and methodological innovations across different domains of computational chemistry—from broad overviews of computer-aided drug discovery to specialized approaches using quantum mechanical and molecular dynamics simulations.

Chapter 1, “Advancements in Computer-Aided Drug Discovery and Development: A Comprehensive Overview,” provides an integrated understanding of the computational tools and strategies used in modern drug discovery. It emphasizes the pivotal role of artificial intelligence and machine learning in streamlining target identification, virtual screening, and lead optimization.

Chapter 2, “Recent Advances in In-Silico Drug Repurposing: Leveraging Computational Tools for Enhanced Therapeutic Discovery,” discusses how computational modeling, network pharmacology, and data-driven approaches are revolutionizing the repurposing of existing drugs for new therapeutic indications, significantly reducing time and cost in the development pipeline.

Chapter 3, “Computational Design of Therapeutic Peptides,” explores the growing importance of peptide-based drugs, focusing on computational methods for peptide design, optimization, and molecular simulation. It highlights how computational strategies help overcome challenges of stability, delivery, and bioavailability in peptide therapeutics.

Chapter 4, “Advancing Drug Discovery through Molecular Dynamics Simulations: A Comprehensive Approach,” demonstrates how molecular dynamics simulations serve as an essential bridge between static molecular structures and dynamic biological function. The chapter presents applications of MD in understanding conformational flexibility, binding mechanisms, and drug stability.

Chapter 5, “Advances in Quantum Mechanical Methods for the Computation of Protein-Ligand Binding Free Energy,” delves into the recent progress in quantum chemical techniques, emphasizing accurate modeling of binding energetics and electronic interactions. The discussion provides valuable insight into hybrid and fragmentation-based approaches that enhance prediction reliability.

Chapter 6, “Current Trends in Computational Methods to Discover New Anti-inflammatory Agents Targeting NLRP3 Complex,” focuses on the computational exploration of inflammasome biology and presents novel approaches for identifying NLRP3 inhibitors using structure-based drug design and molecular modeling strategies.

Chapter 7, “Computational Modelling of Photophysical Processes,” broadens the scope of this volume by addressing photophysical and photochemical properties of molecules through quantum chemical simulations. This chapter highlights how computational modeling aids in the understanding of excited-state processes relevant to biotechnology, medicine, and energy materials.

We hope that this volume serves as a valuable contribution to the growing body of computational chemistry literature and provides readers with both conceptual clarity and practical insights into current research trends. Together, these chapters reinforce the pivotal role of computational methods in driving innovation across molecular sciences and pharmaceutical research.