Application of Screening Methods, Shape Signatures and Engineered Biosensors in Early Drug Discovery Process

2009 ◽  
Vol 26 (10) ◽  
pp. 2247-2258 ◽  
Author(s):  
Izabela Hartman ◽  
Alison R. Gillies ◽  
Sonia Arora ◽  
Christina Andaya ◽  
Nitya Royapet ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Screening Methods ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Shape Signatures ◽  
Early Drug

scholarly journals Biophysical methods in early drug discovery

ADMET & DMPK ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 222-241
Author(s):  
Geoffrey Holdgate ◽  
Kevin Embrey ◽  
Alexander Milbradt ◽  
Gareth Davies
Keyword(s):  
Mass Spectrometry ◽  
Drug Discovery ◽  
Assay Development ◽  
Titration Calorimetry ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Critical Data ◽  
Primary Screening ◽  
The Impact ◽  
Early Drug

Biophysical methods such as mass spectrometry, surface plasmon resonance, nuclear magnetic resonance, and both differential scanning isothermal titration calorimetry are now well established as key components of the early drug discovery process. These approaches are used successfully for a range of activities, including assay development, primary screening, hit confirmation and detailed mechanistic characterisation of compound binding. Matching the speed, sensitivity and information content of the various techniques to the generation of critical data and information required at each phase of the drug discovery process has been key. This review describes the framework by which these methods have been applied in the drug discovery process and provides case studies to exemplify the impact.

Forging New Scaffolds from Old: Combining Scaffold Hopping and Hierarchical Virtual Screening for Identifying Novel Bcl-2 Inhibitors

2019 ◽  
Vol 19 (13) ◽  
pp. 1162-1172 ◽  
Author(s):  
Vishnupriya Kanakaveti ◽  
Sakthivel Rathinasamy ◽  
Suresh K. Rayala ◽  
Michael Gromiha
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Physicochemical Characterization ◽  
B Cell Lymphoma ◽  
Rational Approach ◽  
Screening Methods ◽  
Scaffold Hopping ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Lead Compounds

Background: Though virtual screening methods have proven to be potent in various instances, the technique is practically incomplete to quench the need of drug discovery process. Thus, the quest for novel designing approaches and chemotypes for improved efficacy of lead compounds has been intensified and logistic approaches such as scaffold hopping and hierarchical virtual screening methods were evolved. Till now, in all the previous attempts these two approaches were applied separately. Objective: In the current work, we made a novel attempt in terms of blending scaffold hopping and hierarchical virtual screening. The prime objective is to assess the hybrid method for its efficacy in identifying active lead molecules for emerging PPI target Bcl-2 (B-cell Lymphoma 2). Method: We designed novel scaffolds from the reported cores and screened a set of 8270 compounds using both scaffold hopping and hierarchical virtual screening for Bcl-2 protein. Also, we enumerated the libraries using clustering, PAINS filtering, physicochemical characterization and SAR matching. Results: We generated a focused library of compounds towards Bcl-2 interface, screened the 8270 compounds and identified top hits for seven families upon fine filtering with PAINS algorithm, features, SAR mapping, synthetic accessibility and similarity search. Our approach retrieved a set of 50 lead compounds. Conclusions: Finding rational approach meeting the needs of drug discovery process for PPI targets is the need of the hour which can be fulfilled by an extended scaffold hopping approach resulting in focused PPI targeting by providing novel leads with better potency.

ReAction!

2009 ◽  
Author(s):  
Mark A. Griep ◽  
Marjorie L. Mikasen
Keyword(s):  
Drug Discovery ◽  
Chemical Weapons ◽  
Trial And Error ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Special Effects ◽  
Invisible Man ◽  
Feature Films ◽  
The World ◽  
Chemical Companies

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.

scholarly journals Partitioning Pattern of Natural Products Based on Molecular Properties Descriptors Representing Drug-Likeness

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 546
Author(s):  
Miroslava Nedyalkova ◽  
Vasil Simeonov
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
De Novo ◽  
Target Prediction ◽  
Natural Compounds ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Unique Source ◽  
The Times ◽  
Partitioning Pattern

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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