Frontiers in Computational Chemistry: Volume 5

Zaheer-Ul-Haq Qasmi, Angela K. Wilson, Zaheer-Ul-Haq Qasmi, Angela K. Wilson

• Publisher: Bentham Science Publishers
• Year: 2020
• Print ISBN: 9789811457777
• eBook ISBN: 9789811457791
• Topic: Ciencias físicas
• Subtopic: Química

Frontiers in Computational Chemistry presents contemporary research on molecular modeling techniques used in drug discovery and the drug development process: computer aided molecular design, drug discovery and development, lead generation, lead optimization, database management, computer and molecular graphics, and the development of new computational methods or efficient algorithms for the simulation of chemical phenomena including analyses of biological activity. The fifth volume of this series features these six chapters:
- Recent Advances and Role of Computational Chemistry in Drug Designing and Development on Viral Diseases
- Molecular Modeling Applied to Design of Cysteine Protease Inhibitors – A Powerful Tool for the Identification of Hit Compounds Against Neglected Tropical Diseases
- Application of Systems Biology Methods in Understanding the Molecular Mechanism of Signalling Pathways in the Eukaryotic System
- Implementation of the Molecular Electrostatic Potential over GPUs: Large Systems as Main Target
- Molecular Electron Density Theory: A New Theoretical Outlook on Organic Chemistry
- Frontier Molecular Orbital Approach to the Cycloaddition Reactions

Recent Advances and Role of Computational Chemistry in Drug Designing and Development on Viral Diseases

Amit Lochab¹, Rakhi Thareja², Sangeeta D. Gadre³, Reena Saxena^{1, *}

¹ Department of Chemistry, Kirori Mal College, University of Delhi, Delhi, India

² Department of Chemistry, St. Stephens College, University of Delhi, Delhi, India

³ Department of Physics, Kirori Mal College, University of Delhi, Delhi, India

Abstract

The growing number of contagious viral diseases among different geographic regions has become a threat to human health and the economy on a global scale. Various viral epidemics in the past have caused huge casualties due to lack of effective vaccine, the recent outbreak of COVID-19 is a good example of it. Drug designing and development is a lengthy, tedious and expensive process that is always associated with a high level of uncertainty as the success rate of their approval as a drug is very low. Computer-aided drug designing by utilizing in silico methods has shown prominent ways to develop novel drugs in a cost-efficient manner and has evolved as a rescue in the past few years. Interestingly, the highest FDA approval reached a maximum (59 drugs) in 2018 for which a lot of credit goes to the successful development of computational chemistry tools for drug designing in the last two decades. These methods provide better chances of getting hit compounds in a far more accurate and faster way. Drug designing is a cyclic optimization process that involves various steps like creating a molecule, selecting the target for this molecule, analysing the binding pattern and estimating the pharmacokinetics of the molecule. The final development of a drug candidate is cumulative of positive results obtained in each aforementioned step. Various computational techniques/approaches such as molecular dynamic studies, homology modelling, ligand docking, pharmacophore modelling and QSAR can be utilized in each phase of the drug discovery cycle. In this chapter, we aim to highlight the recent advances that have taken place in developing tools and methodologies that lead to in silico preparation of novel drugs against various viral infections like Ebola, Zika, Hepatitis C and Coronavirus.

Keywords: Computational chemistry, Homology modeling, In Silico, Ligand-based drug designing, Ligand docking, Multi target drug designing, Pharmacophore modeling, Protein target, Quantum mechanics, Structure-based drug designing, Viral infection, Virtual screening.

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^* Corresponding author Saxena Reena: Department of Chemistry, Kirori Mal College, University of Delhi, Delhi, India; E-mails: [email protected]; [email protected]

INTRODUCTION

There is a huge global effort indulged in wiping out the infectious viral diseases. Viral infections include various contagious diseases like Ebola, Hepatitis, HIV-AIDS, Rabies, Zika and Corona viruses. These ailments cause a huge impact on both the economy and health. Methods in controlling these diseases like vaccination, public awareness through advertisement and campaigns cause a reduction in the budget which is not that effective also. The current available drugs for the disease have their own limitations of being toxic, less potent and high cost. There are several viral microbes that gain resistance toward these drugs and there is always a continuous need for developing new effective drugs. Studies show that the traditional path for discovering drugs and bringing it to market costs around 2 billion USD. In addition, they require a long time, and the process is highly laborious to establish their safety and effectiveness. At the starting of the 20^th century, the drug industry was used to screen out various natural and synthetic compounds experimentally in search of therapeutic characteristics for a particular target. Then the compound was optimized for better pharmacological properties having less toxicity which after clinical trials used to take on an average of ~15 years to come in the market [1]. The concerns over various incurable diseases and an inadequate number of potent drugs have forced us to develop innovative drugs with high specificity and potency for the respective target. The ways in which these microbes are mutating their genes to make a come back in our world have proved to be hazardous in an irreparable fashion as is evident from the outbreak of the pandemic of Covid-19 in December, 2019. This has further added the interests of the researchers in fast and efficient drug discovery tools.

Drug discovery using computational chemistry is established very well from the past few years due to development in combinatorial chemistry with computational screening and optimizing tools, with enhanced, fast and efficacious results. The computational methods help in predicting the conformational interactions of active drugs with the target sites. High throughput screening (HTS) and Computer Aided Drug Discovery (CADD) techniques have helped in suggesting favourable drugs out of huge libraries in a short time by understanding the interaction between the target molecule and the proposed drug. The drug discovery process includes several computational approaches before the clinical trials, right from the beginning in which identification of target and their association with a particular disease is considered for studies. The second step is to investigate the interaction of proposed drug molecules with validated target which is followed by the optimization of lead molecules for the improvement in their potency and biological toxicity [2, 3].

This chapter aims to give an overview of different computational approaches and tools for the development in drug designing based on explanation from quantum mechanics. This covers various optimization procedures for enhancing potency of lead compounds. Finally, recent applications of CADD in designing drugs for viral diseases such as Ebola, Zika, Hepatitis C and Coronavirus are discussed.

The first modelling approach in computational drug development method is to identify the probable target related to particular disease. Generally, these targets can be proteins, enzymes or complex bio molecules having specific bioactivity. CADD can be divided into Structure based drug design (SBDD) and Ligand based drug design (LBDD) based on the availability of the structures of the above bio molecule targets as shown in Fig. (1). Both approaches are complimentary to each other as SBDD employs known structure of the target moiety for the screening of active new compounds. The structural information of target is used to find new lead compounds by suggesting a design of potent molecule or through screening from virtual libraries and databases. Whereas LBDD is a suitable approach, when the crystal structure of drug target is not available. However, one must clearly understand that SBDD is based on the drug-target structure where in the binding efficiency by a specific ligand/drug is given major importance which may be stu...

Table of contents

• Welcome
• Table of Content
• Title
• BENTHAM SCIENCE PUBLISHERS LTD.
• PREFACE
• List of Contributors
• Recent Advances and Role of Computational Chemistry in Drug Designing and Development on Viral Diseases
• Molecular Modeling Applied to Design of Cysteine Protease Inhibitors – A Powerful Tool for the Identification of Hit Compounds Against Neglected Tropical Diseases
• Application of Systems Biology Methods in Understanding the Molecular Mechanism of Signalling Pathways in the Eukaryotic System
• Implementation of the Molecular Electrostatic Potential over GPUs: Large Systems as Main Target
• Molecular Electron Density Theory: A New Theoretical Outlook on Organic Chemistry
• Frontier Molecular Orbital Approach to the Cycloaddition Reactions