Preface

The rise of chemical information and development of structure databases, as well as the need for new therapeutic agents or improved specific materials with controlled properties, has led to the development of chemoinformatic tools. These tools can be used to design new molecules and to model their chemical and/or biochemical environment and interactions. Molecular docking and dynamic simulations are such approaches whose methodologies have evolved in terms of accuracy. Thus, today researchers benefit from important *in silico* studies and new opportunities to identify and propose new hit molecules further to chemical synthesis or isolation from vegetal materials, as first step in the introduction in therapeutic practice of new agents.

This book clearly explains the principles of molecular docking and molecular dynamics. It includes examples of algorithms and procedures proposed by different software programs for visualizing and identifying potential interactions in complexes of biochemical interest.

The book is organized into six chapters, each one discussing different molecular simulation methodologies and providing concrete examples of complex interactions. In each chapter, the authors provide an overview of the treated subject, a description of the methodologies used, and a discussion of the results.

Chapter 1 is an introductory chapter, familiarizing the reader with basic principles and terminology of docking and dynamic simulations.

Chapter 2 addresses one of the most common cancer diagnoses in women, breast cancer. The authors use homology modeling, ligand docking, and molecular dynamic simulations to explore aryl hydrocarbon receptor (AhR) structure and to identify its suitable binding site for some aromatic acrylonitrile ligands, potential drug candidates in therapeutics of breast malignancies. The work highlights the usefulness of homology modeling in cases when the protein domain of interest is not yet described and characterized by X-ray crystallography. The employed methodologies could serve to assess other compounds' potency as anticancer agents, in virtual screening, before chemical synthesis, evaluation, and pre-clinical trials.

In Chapter 3, the authors report results of docking simulations using quinolone derivatives to evaluate their potential antitumoral and antimycobacterial activity, compared to the standard therapeutic compounds of topotecan and levofloxacin.

Chapter 4 gives a detailed overview of molecular recognition occurring in proteinligand complexes, based on various type of interactions and other factors (surrounding solvent, ionization effects, conformational changes, entropy, desolvation, etc.) important for the understanding of biological functions and therapeutic action. The authors underline the importance of proper selection of modeling protocols to obtain desired accuracy. A virtual screening of sesquiterpenoid alcohols against cyclooxygenase isoenzymes is realized in an attempt to design and develop new nonsteroidal anti-inflammatory drugs.

In Chapter 5, the authors describe a new implemented methodology to perform protein-protein docking by introducing map objects. This approach should solve the problem of molecular description of very large biomolecular assemblies. Authors use as an example a T-cell receptor variable domain to illustrate the modeling process with map objects and acetylcholine binding protein (ACHBP) to construct its pentamer using protein-protein docking methodology. Their molecular modeling results can be further extended to large biomolecular assemblies.

Chapter 6 refers to theoretical aspects of computational methodologies regarding the design and development of radiopharmaceuticals and their specific applications, especially in assessment of their structure details and parameters. The authors highlight the possible advantages of the use of such methods to increase the personalization of dosimetry in nuclear medicine administration.

These structure-based design approaches offer students and researchers a general idea of the current state-of-the-art docking and dynamic simulations tools and their capability to predict ligand binding modes in various complexes and assemblies. I hope readers will find these studies instructive and inspirational for further research ideas, contributing to the inter-disciplinary efforts in bio- and chemoinformatics, pharmacology, and medicine.
