The Design and Development of Novel Drugs and Vaccines: Principles and Protocols

By Surendra Nimesh

The Design and Development of Novel Drugs and Vaccines: Principles and Protocols presents both in silico methods and experimental protocols for vaccine and drug design and development, critically reviewing the most current research and emphasizing approaches and technologies that accelerate and lower the cost of product development. Sections review the technologies and approaches used to identify, characterize and establish a protein as a new drug and vaccine target, cover several molecular methods for in vitro studies of the desired target, and present various physiological parameters for in vivo studies. The book includes preclinical trials and research, along with information on FDA approval.

• Covers both in silico methods and experimental protocols for vaccine and drug development in a single, accessible volume
• Offers a holistic accounting of how developments in bioinformatics and large experimental datasets can be used in the development of vaccines and drugs
• Shows researchers the entire gamut of current therapies, ranging from computational inputs to animal studies
• Reviews the most current, cutting-edge research available on vaccine and drug design and development

• Language: English
• Publisher: Academic Press
• Release date: Jan 21, 2021
• ISBN: 9780128214756

Book preview

India

Preface

Dr. Tarun Kumar Bhatt

Dr. Surendra Nimesh

Infectious diseases are a socioeconomic burden for most countries, accounting for millions of deaths annually. Reports have confirmed that, in the last decade, the number of infectious disease cases have been fourfold higher than the past. A recent outbreak of the new coronavirus is a blazing example of severe loss of lives and livelihood caused by an infectious agent. Therefore, we need to build a robust health system equipped with all the necessary tools of disease prevention and treatment. The development of potential vaccines and drugs is also essential, as these are the major weapons of the war against any fatal disease.

This book covers all aspects related to the design and development of a vaccine and drug for a disease. The book is intended to provide a complete package covering the process from initial computational prediction to in vitro/in vivo studies and ultimately the approval procedure.

The idea of putting all the processes related to the drug and vaccine development under one umbrella came in to existence due to the unavailability of such a resource. One gets a book either on vaccine development or on drug development. Either the book covers only in silico studies, or it will have only in vitro/in vivo protocols. And of course, a separate book is required for postlaboratory procedures such as clinical trials and patent filing. This book provides a holistic approach toward vaccine and drug development.

The book contains 22 chapters, and it is broadly divided into five parts. (1) Computational drug design covers all the aspects of in silico studies required prior to experimental setup of drug development. (2) Computational vaccine design describes all the protocols of vaccine design using online computational tools. (3) In vitro study provides the protocols of validating in-silico findings using lab experiments. (4) In vivo study focuses on the animal models and henceforth the protocols required for animal studies. (5) Clinical trials and FDA approval discusses issues related to clinical trials, FDA approvals, and patents.

The topics covered in the book have been selected to meet the needs of both the research and teaching communities, which are either actively involved or would like to involve themselves in the novel cause of developing vaccines/drugs. We believe that this compilation will be an indispensable tool toward vaccine/drug development and will be of high interest among not only students but also researchers. We hope that members of both academia and industry will appreciate this compilation of all the methods/protocols in a single book. We sincerely thank you for your interest.

Part A

Computational drug design

Chapter 1: Introduction of structural bioinformatics with respect to drug discovery

Hemant Aryaa; Mohane Selvaraj Coumarb; Tarun Kumar Bhatta    a Department of Biotechnology, Central University of Rajasthan, Bandarsindri, Rajasthan, India

b Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Kalapet, Puducherry, India

Abstract

Drug discovery is an arduous, time consuming and expensive process requiring several years and a huge amount of funding. Identifying a potential drug target and suitable lead molecule for drug development are critical steps in the drug discovery process. Among the various methods available for the identification of new lead molecules, structural bioinformatics has a special place. Structural bioinformatics plays a vital role in target validation, active site identification, lead optimization, drug-likeness prediction and stability analysis. The structural bioinformatics helps in identifying and designing novel leads against a selected drug target that could be tested experimentally to check the impact on the biological system.

Keywords

Bioinformatics; Computer-aided drug design; Drug discovery; Lead; Molecular docking and dynamics; Preclinical study; Virtual screening

1: Overview

1.1: Drug discovery

The drug is a chemical or natural or synthetic substance that is used to identify, diagnose, prevent, treat and cure diseases [1, 2]. Major classes of drugs interact with human's protein/DNA/RNA and alter the physiological function and produce the desired effect. For example, anti-cancer drugs interact with the overexpressed protein (responsible for causing cancer) and control its expression level which leads to cancer prevention [3]. In short, the drug is a substance that is used as a medication for the betterment of human health.

Discovery of a new drug is an expensive, tedious and time-taking process that involves the preliminary stages (target validation) to the clinical stage (approval of a chemical substance as a drug for marketing). The drug discovery program takes around 10–15 years with the costs of US $ 1.5–2.0 billion [4–6].

After the selection of potential drug target, the next step is to identify a lead molecule (chemical or natural product) against the drug target. Once a suitable lead for a drug target is identified, it is chemically optimized through medicinal chemistry and computer-aided drug design techniques to improve the biological activity, safety and drug-like properties, to make it a drug for human consumption [5]. The complete process from target identification to biological activity analysis is known as preclinical studies.

After the promising preclinical results, scientist and researchers provide detailed investigational report (Investigational New Drug application; IND application) [7, 8] of the drug candidate to the drug regulatory agency (e.g., CDSCO: Central Drug Standard Control Organization of India, US FDA: USA Food and Drug Administration, etc.) for getting approval for testing in humans, this process called as clinical studies which is divided into four clinical trial phases (phase I to IV) [9]. The purpose of the clinical trial is to evaluate the safety and effectiveness of the drug in humans and takes 6–7 years to complete (Fig. 1.1).

Fig. 1.1 Schematic representation of the drug discovery process.

1.2: Structural bioinformatics (SB)

Structural bioinformatics (SB) or computational structure bioinformatics is an important portion of bioinformatics that deals with the structure of biomolecules such as protein and nucleic acids [10, 11]. The structural bioinformatics also reveals the basic protein structure information such as three-dimensional structure, secondary structure components (α-helices and β-sheets), domain, fold, active and binding site information, the relation between 3D structure and amino acids sequence. The structural bioinformatics covers sequence analysis and molecular modeling. Besides, the SB plays a significant role in computer-aided drug design (structure-based drug design and fragment-based drug design) [12–16].

The structural bioinformatics plays a vital role in the modern drug discovery process. Several pharmaceuticals begin their drug discovery program with known drug target/protein and look for a suitable chemical/natural compound, which could be able to disturb the target structure that might leads to prevention of the disease. Drug design and discovery with the help of structural bioinformatics is a step by step event which ends with the best lead molecule that could be reported as drug after the promising preclinical and clinical result. The structural bioinformatics events of drug discovery are:

1.2.1: Target identification and validation

Target is the key component or molecular base of any disease. The target is directly or indirectly responsible for causing illness by performing specific cellular and molecular events [17]. The target should be essential for the pathogen survival and the target does not have similarity with the human proteins. The selected target should be validated through available computational methods and experimental studies. Literature also helps in choosing potential drug targets. Refer to Chapter 2 for details.

1.2.2: Collection of chemical and natural compounds

Next, chemical substances or natural products need to be retrieved from available sources like literature, chemical databases, natural product databases, chemical compounds libraries (available at specific lab or company), retrieval of disease-specific compounds libraries and deigning of new compounds with the help of a chemist [18–20]. Chapter 3 contains more information about chemical databases and retrieval of these compounds; please refer.

1.2.3: Lead identification and optimization

The critical step in the drug discovery process is to find a suitable lead molecule [21]. Lead is a chemical entity that shows potential biological activity by interacting with the drug targets. Such lead molecules can be identified through high-throughput screening (experimental approach) and computational screening (virtual screening) [22].

Virtual screening[12, 23] a computational technique helps in identifying a potential lead from a compound library against the selected target protein. Several bioinformatics tools are available to perform virtual screening (Chapter 4). After the lead identification, the selected lead could be optimized using the lead optimization approach (computer-aided drug design). The identified leads from the virtual screening method will be evaluated for Rule of five and ADME predictions [24, 25]. The computational drug-likeness prediction helps in filtering the potential leads.

Computer-aided drug design (CADD) technique includes two ways for lead identification/optimization, one is structure-based (SBDD) and another is ligand-based (LBDD). To perform SBDD [26, 27], the three-dimensional structure of the selected target must be available. The target protein structure is available in the Protein Databank (PDB); if not available, then molecular modeling needs to be done to achieve the 3D structure of the protein. The SBDD could be done using molecular docking and de novo drug designing whereas LBDD [28, 29] could be done using pharmacophore and QSAR based approach. The SBDD and LBDD provide the best-docked complex which means that how efficiently the lead is binding with the target protein [30–32]. For detail information about lead identification and optimization, refer to Chapter 4.

1.2.4: Molecular dynamics simulations (MD)

Molecular dynamics simulation [33, 34] is a powerful computer-based bioinformatics tool that is used to study the stability of biomolecules such as protein, protein-ligand complexes, protein-nucleic acid complexes, etc. In the drug discovery pipeline, the MD simulation approach is used to analyze the target‑lead complex stability, hydrogen and other non-covalent bond stability, protein conformation changes analysis, etc. Refer Chapter 5 for MD simulation run and their analysis.

1.2.5: Experimental studies

The promising outcome of the CADD and MD is in the form of selected potential leads. These potential lead(s) could be obtained from chemical suppliers or it can be synthesized by organic chemistry in the labs. Once you have the compound in your hand, the next thing would be to validate the in silico studies using in-vitro and in vivo essays. Biological assay such as enzyme inhibition, cell culture study, mouse model study, etc., would be done to prove that the identified lead using computational approach are showing biological activity in in vitro and in vivo environment [35]. Based on the preclinical data, the study can go for clinical research as a final stage of the drug discovery process. Refer part B, C and D of the book for detailed review.

Frequently asked questions (FAQs)

Question 1. What do you mean by the word ‘Drug Discovery’?

Answer: A step by step process (preclinical and clinical phases) to design and develop a molecule which used to cure disease for the betterment of human health, known as drug discovery.

Question 2. Is ‘Bioinformatics’ plays a role in drug discovery?

Answer: Yes, Bioinformatics, including genomics, proteomics, structural bioinformatics, etc., plays a vital role in target identification and validation, lead identification and optimization process of drug