Review on modern drug discovery process

Author(s):  
Shraddha P. Amrutkar ◽  
Paresh A. Patil ◽  
Rajshri S. Patel
Author(s):  
Gurusamy Mariappan ◽  
Anju Kumari

Virtual screening plays an important role in the modern drug discovery process. The pharma companies invest huge amounts of money and time in drug discovery and screening. However, at the final stage of clinical trials, several molecules fail, which results in a large financial loss. To overcome this, a virtual screening tool was developed with super predictive power. The virtual screening tool is not only restricted tool small molecules but also to macromolecules such as protein, enzyme, receptors, etc. This gives an insight into structure-based and Ligand-based drug design. VS gives reliable information to direct the process of drug discovery (e.g., when the 3D image of the receptor is known, structure-based drug design is recommended). The pharmacophore-based model is advisable when the information about the receptor or any macromolecule is unknown. In this ADME, parameters such as Log P, bioavailability, and QSAR can be used as filters. This chapter shows both models with various representative examples that facilitate the scientist to use computational screening tools in modern drug discovery processes.


2013 ◽  
Vol 1 (02) ◽  
pp. 60-73 ◽  
Author(s):  
Lakhyajit Boruah ◽  
Aparoop Das ◽  
Lalit Mohan Nainwal ◽  
Neha Agarwal ◽  
Brajesh Shankar

Computational methods play a central role in modern drug discovery process. It includes the design and management of small molecule libraries, initial hit identification through virtual screening, optimization of the affinity as well as selectivity of hits and improving the physicochemical properties of the lead compounds. In this review article, computational drug designing approaches have been elucidated and discussed. The key considerations and guidelines for virtual chemical library design and whole drug discovery process. Traditional approach for discovery of a new drug is a costly and time consuming affair besides not being so productive. A number of potential reasons witness choosing the In-silico method of drug design to be a more wise and productive approach. There is a general perception that applied science has not kept pace with the advances of basic science. Therefore, there is a need for the use of alternative tools to get answers on efficacy and safety faster, with more certainty and at lower cost. In-silico drug design can play a significant role in all stages of drug development from the initial lead designing to final stage clinical development.


2000 ◽  
Vol 22 (6) ◽  
pp. 169-170 ◽  
Author(s):  
Charles J. Manly

Drug discovery today requires the focused use of laboratory automation and other resources in combinatorial chemistry and high-throughput screening (HTS). The ultimate value of both combinatorial chemistry and HTS technologies and the lasting impact they will have on the drug discovery process is a chapter that remains to be written. Central to their success and impact is how well they are integrated with each other and with the rest of the drug discovery processes-informatics is key to this success. This presentation focuses on informatics and the integration of the disciplines of combinatorial chemistry and HTS in modern drug discovery. Examples from experiences at Neurogen from the last five years are described.


2013 ◽  
Vol 1 (02) ◽  
pp. 74-82
Author(s):  
Aarti Rawat ◽  
Rakesh Roshan Mali

Computational methods play a central role in modern drug discovery process. It includes the design and management of small molecule libraries, initial hit identification through virtual screening, optimization of the affinity as well as selectivity of hits and improving the physicochemical properties of the lead compounds. In this review article, computational drug designing approaches have been elucidated and discussed. The key considerations and guidelines for virtual chemical library design and whole drug discovery process. Traditional approach for discovery of a new drug is a costly and time consuming affair besides not being so productive. A number of potential reasons witness choosing the In-silico method of drug design to be a more wise and productive approach. There is a general perception that applied science has not kept pace with the advances of basic science. Therefore, there is a need for the use of alternative tools to get answers on efficacy and safety faster, with more certainty and at lower cost. In-silico drug design can play a significant role in all stages of drug development from the initial lead designing to final stage clinical development.


Author(s):  
Mark A. Griep ◽  
Marjorie L. Mikasen

ReAction! gives a scientist's and artist's response to the dark and bright sides of chemistry found in 140 films, most of them contemporary Hollywood feature films but also a few documentaries, shorts, silents, and international films. Even though there are some examples of screen chemistry between the actors and of behind-the-scenes special effects, this book is really about the chemistry when it is part of the narrative. It is about the dualities of Dr. Jekyll vs. inventor chemists, the invisible man vs. forensic chemists, chemical weapons vs. classroom chemistry, chemical companies that knowingly pollute the environment vs. altruistic research chemists trying to make the world a better place to live, and, finally, about people who choose to experiment with mind-altering drugs vs. the drug discovery process. Little did Jekyll know when he brought the Hyde formula to his lips that his personality split would provide the central metaphor that would come to describe chemistry in the movies. This book explores the two movie faces of this supposedly neutral science. Watching films with chemical eyes, Dr. Jekyll is recast as a chemist engaged in psychopharmaceutical research but who becomes addicted to his own formula. He is balanced by the often wacky inventor chemists who make their discoveries by trial-and-error.


Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 546
Author(s):  
Miroslava Nedyalkova ◽  
Vasil Simeonov

A cheminformatics procedure for a partitioning model based on 135 natural compounds including Flavonoids, Saponins, Alkaloids, Terpenes and Triterpenes with drug-like features based on a descriptors pool was developed. The knowledge about the applicability of natural products as a unique source for the development of new candidates towards deadly infectious disease is a contemporary challenge for drug discovery. We propose a partitioning scheme for unveiling drug-likeness candidates with properties that are important for a prompt and efficient drug discovery process. In the present study, the vantage point is about the matching of descriptors to build the partitioning model applied to natural compounds with diversity in structures and complexity of action towards the severe diseases, as the actual SARS-CoV-2 virus. In the times of the de novo design techniques, such tools based on a chemometric and symmetrical effect by the implied descriptors represent another noticeable sign for the power and level of the descriptors applicability in drug discovery in establishing activity and target prediction pipeline for unknown drugs properties.


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