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Designing Studies in Pharmaceutical and Medicinal Chemistry

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Abstract

The discovery of medicine started years ago with the use of medicinal plant parts for the benefit or improvement of physiological conditions. The traditional uses of medicinal plants grew tremendously with Indian medicine and the Chinese medicine system. Later on, with time, researchers tried to isolate and synthesize the lead molecule of a natural product to increase its potency. The major source of drugs was plants, microorganisms, animals, and marine. With changes in time and environment, the need for quick recovery from a disease condition was felt for many reasons and thus synthetic-based drugs came to market with many regulations. In the initial days, the cost of drug development was a very high and costly process which may go up to $400-$600 million with the investment of 10-12 years of time. With the development of computer programs, some part of the drug discovery process was made easy with different software and programs. Many in-silico methods were developed by many researchers and scientists which boosted the drug design method and reduced the cost and time. The two main approaches of computer-aided drug design i.e., structure-based drug design and ligand-based drug design changed the process of drug discovery completely. Different visualization techniques of the 3D structure of a protein helped the researchers to understand the nature of the protein and the way to inhibit that protein and receptor. Structure-based drug design tools like homology modeling, molecular docking, and de-novo drug design helped in the discovery of drug molecules based on the detailed structure of protein whereas the structure-based drug design tools like pharmacophore mapping and QSAR techniques contributed to the discovery of drug molecules based on the nature of the previously reported drug and lead molecules. The in-silico ADMET properties prediction of a molecule based on the structural basis of the compound with the application of different rules like Lipinski's rule of five, Veber's rule, Ghosh rule, etc helped to develop a drug molecule with better pharmacokinetic and pharmacodynamic properties, which resists the easy rejection of a developed molecule in the clinical trials. Later with the advancement of computers, several artificial intelligence approaches were developed such as machine learning and deep learning. These techniques have many applications such as drug-target interactions, drug repurposing, prediction of synthesis and retrosynthesis, etc. Illustration about all these aspects is presented in a systematic way in this chapter.

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Acknowledgment

We sincerely thank funding agencies ICMR (File No. 5/13/79/2020/NCD-III), AICTE (File No. 8-125/FDC/RPS (POLICY-1)/2019-20), and RGUHS (Project code: 19PHA339) for their financial and moral support. We are also grateful to the management and staff of Acharya Institutes and College of Pharmaceutical Sciences of Dayananda Sagar University for their constant support and encouragement.

Conflict of Interest

The corresponding author on behalf of all authors declares no conflict of interest.

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Authors and Affiliations

  1. College of Pharmaceutical Sciences, Dayananda Sagar University, Bengaluru, Karnataka, India

    N. M. Raghavendra & B. Sajeev Kumar

  2. JSS College of Pharmacy, Constituent College of JSS Academy of Higher Education and Research, Mysuru, India

    B. R. Prashantha Kumar

  3. Acharya & BM Reddy College of Pharmacy, Bengaluru, Karnataka, India

    Pujan Sasmal, Ghanshyam Teli, Rohit Pal & P. M. Gurubasavaraja Swamy

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  1. N. M. Raghavendra
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  2. B. R. Prashantha Kumar
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  3. Pujan Sasmal
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  4. Ghanshyam Teli
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  5. Rohit Pal
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  6. P. M. Gurubasavaraja Swamy
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  7. B. Sajeev Kumar
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Corresponding author

Correspondence to N. M. Raghavendra .

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Editors and Affiliations

  1. Retired Senior Expert Pharmacologist at the Office of Cardiology, Hematology, Endocrinology, and Nephrology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA

    Gowraganahalli Jagadeesh

  2. Professor & Director, Research Training and Publications, The Office of Research and Development, Periyar Maniammai Institute of Science & Technology (Deemed to be University), Vallam, Tamil Nadu, India

    Pitchai Balakumar

  3. Division Cardiology & Nephrology, Office of Cardiology, Hematology, Endocrinology and Nephrology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA

    Fortunato Senatore

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Raghavendra, N.M. et al. (2023). Designing Studies in Pharmaceutical and Medicinal Chemistry. In: Jagadeesh, G., Balakumar, P., Senatore, F. (eds) The Quintessence of Basic and Clinical Research and Scientific Publishing. Springer, Singapore. https://doi.org/10.1007/978-981-99-1284-1_9

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