Preface

Cheminformatics has emerged as an applied branch of Chemistry that involves multidisciplinary knowledge, connecting related fields such as chemistry, computer science, biology, pharmacology, physics, and mathematical statistics. Computational methods are used to visualize simple structures or macromolecular assemblies, to model properties by mathematical and statistical models, to create, store and process chemical data (databases, data mining), to realize virtual screening of large compound libraries and to analyze the chemical information and optimize structure in order to develop novel compounds, materials, or processes.

The book is organized in two sections, covering plural aspects related to advances in the development of informatic tools and their specific use in compound databases and concerted efforts to link them in research platforms and networks with various purposes and applications in life sciences. Applications in medicinal chemistry, for identification and development of new therapeutically active molecules are described, but the book is not limited to these topics. For instance, the chapter titled "Visible Evolution from Primitive Organisms to Homo sapiens" covers the area of genomic analysis and development of evolutionary equations based on genome structure. It represents an important approach to explain the origin and evolution of life, providing mathematical proofs on the genomic amino acid composition homogeneity. It illustrates the use of mathematics to explain biological organisms' evolution and reduces complex structural genetic information to simple linear regression relationships. This chapter allows inexperienced readers to understand the basic concepts and theory, but also invites them to go forward, offering deep biological and chemical molecular insights.

The chapter titled "Semantic similarity in cheminformatics" presents a great overview of chemical ontologies, explaining how it works, how the relationships between different chemical or biological entities are constructed in order to bind chemical information given by structures with other aspects as chemical classifications, reaction mechanisms, metabolites, toxicity, biological pathways and so on. The authors describe the fundamental concepts of ontology-based semantic similarity, pointing to the applications in cheminformatics and discussing the efforts in ontology development to link chemical databases with related fields such as medical chemistry, genomics, or proteomics.

Computational tools of chemometrics and pattern recognition techniques are used for the design of various compounds. Such examples are illustrated in the chapter titled "Molecular Electrostatic Potential and Chemometric Techniques as Tools to Design of Bioactive Compounds", where authors use *ab initio* calculation of properties based on charge density and topological indices for the design of nitrofurans derivatives. The key features and descriptors, acting in the recognition process with the biological target, are elucidated and can be further used to design new biologically active molecules.

**II**

**Section 2**

*by Azhar Rasul*

Identification

Models

Drug Design and Develpment by Chemical Tools **107**

**Chapter 7 109**

**Chapter 8 113**

**Chapter 9 127**

**Chapter 10 147**

**Chapter 11 165**

Accelerating Chemical Tool Discovery by Academic Collaborative

Chemical Biology Toolsets for Drug Discovery and Target

*by Ammara Riaz, Azhar Rasul, Iqra Sarfraz, Javaria Nawaz,* 

Artificial Intelligence-Based Drug Design and Discovery *by Yu-Chen Lo, Gui Ren, Hiroshi Honda and Kara L. Davis*

Cell-Penetrating Peptides: A Challenge for Drug Delivery

*Ayesha Sadiqa, Rabia Zara, Samreen Gul Khan and Zeliha Selamoglu*

Prologue: Cheminformatics and Its Applications

*by Bahne Stechmann and Wolfgang Fecke*

*by Sonia Aroui and Abderraouf Kenani*

The next chapter ("Chemical reactivity properties and bioactivity scores of the Angiotensin II vasoconstrictor octapeptide") emphasizes the reactivity descriptors, drug-likeness assessment, and prediction of oral bioavailability scores as preliminary steps for the development of new drugs based on specific peptide analogues, achieving a comparison of prediction realized with different quantum mechanical modelling methods.

Molecular complexity, flexibility, and other structural features and properties are used in a cheminformatic analysis of natural and synthetic compounds, based on similarity, in a case study of products originating from Panama, in an attempt to find and optimize lead compounds with antimalarial activity, in the chapter "Cheminformatic Approach: The Case of Natural Products of Panama".

In the chapter titled "Accelerating chemical tool discovery by academic collaborative models", the authors highlight the international efforts of academia and industrial pharmacists to generate consortia in the interdisciplinary field of chemical biology, to connect their knowledge, compound libraries and facilities, having the important goal to create open access information. The principal aim remains the development of new therapeutic compounds using the knowledge from multidisciplinary fields in academic and public and private media, thus helping researchers to solve mechanistical issues in life sciences.

The chapter "Chemical Biology Toolsets for Drug Discovery and Target Identification" is an overview of chemical techniques and methodologies implemented in the study of biological systems, metabolic pathways, drug-target complex interactions, and other biochemical process, all with the common goal to understand the action and all biochemical implications of the introduction in therapeutics of a new drug. Different complementary instrumental techniques and methodologies aiming to provide deep insights into the chemical structure are discussed alongside validation methods and techniques of selection of a new drug candidate.

Machine learning and deep learning are aspects covered in the chapter titled "Machine-learning based drug discovery and design", presenting a detailed view of their theoretical aspects and applications related to *de novo* drug design, QSAR analysis, and chemical space visualization

The chapter titled "Cell Penetrating Peptides", as its title suggests, emphasizes their biomedical applications as transport vectors for different therapeutic agents across cell membranes. The authors describe the origin and the classifications of CPPs, their uptake mechanisms, and their promising clinical efficacity in various cancer therapies.

With all information and conclusive examples presented above, this book is a valuable learning resource for readers from the scientific community, students, researchers both beginners and experienced in the field of chemistry/bioinformatics and related domains. By taking note of these chapters, I hope readers will feel encouraged, inspired, and motivated to continue new research and discoveries.

**V**

I thank all authors for their substantial contributions to this book, for sharing their knowledge, and for opening new opportunities and perspectives in such an

National Institute for Chemical - Pharmaceutical Research and

Laboratory of Molecular Design and Molecular Docking,

Government College University Faisalabad (GCUF),

Government College University Faisalabad (GCUF),

Development – ICCF Bucharest (Romania), Department of Pharmaceutical Biotechnologies,

**Amalia Stefaniu**

Bucharest, Romania

Faisalabad, Pakistan

Faisalabad, Pakistan

**Ghulam Hussain** 

Department of Zoology, Faculty of Life Sciences,

Department of Physiology, Faculty of Life Sciences,

**Dr. Azhar Rasul**

evolving field as cheminformatics is.

I thank all authors for their substantial contributions to this book, for sharing their knowledge, and for opening new opportunities and perspectives in such an evolving field as cheminformatics is.

## **Amalia Stefaniu**

National Institute for Chemical - Pharmaceutical Research and Development – ICCF Bucharest (Romania), Department of Pharmaceutical Biotechnologies, Laboratory of Molecular Design and Molecular Docking, Bucharest, Romania
