scholarly journals Taking chance out of drug discovery

2009 ◽  
Vol 31 (6) ◽  
pp. 40-42
Author(s):  
Simon Pearce
Keyword(s):  
Drug Discovery ◽  
Research And Development ◽  
Phenyl Ring ◽  
Reactive Intermediates ◽  
Building Blocks ◽  
Bioactive Molecules ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Drug Discovery And Development ◽  
Compound Screening

Searching for bioactive molecules, using rapid compound screening, fragment-based design and unique building blocks, should not be like looking for a needle in a haystack. This article describes a range of innovative and diverse screening compounds for drug discovery and development. Available at both research and development scales, the line includes special products associated with new heterocyclic and phenyl ring-based chemical building blocks, including an exclusive and expanding range of reactive intermediates specifically designed for lead optimization, as well as a growing fragment collection. I explain how these products and services are helping to accelerate the search for bioactive molecules and are shortening the drug discovery process by reducing the element of chance.

Marine Genetic Resources. A Source of New Drugs The Experience of the Biotechnology Sector

2009 ◽  
Vol 24 (2) ◽  
pp. 209-220 ◽  
Author(s):  
Fernando de la Calle
Keyword(s):  
Drug Discovery ◽  
Genetic Resources ◽  
Dna Analysis ◽  
Marine Organisms ◽  
New Drugs ◽  
Bioactive Molecules ◽  
Scale Production ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
The Status

AbstractThis article provides an overview of the conversion of marine genetic resources into new drugs. Three marine organisms suitable for application in human health and steps in the drug discovery process are described. Specific supply problems resulting from the minute concentration of required compounds for medicine in the natural marine source are examined. Three case studies illustrate different strategies enabling an industrial-scale production: chemical synthesis, biotechnology and fermentation. Future concepts for marine scientific research which could lead to new medical applications are considered. Besides research in unexplored deep sea areas, the “metagenomic approach” particularly might lead to significant new achievements. This DNA analysis of marine organisms facilitates the drug discovery process because it requires significantly less marine material than current approaches. Because this process, starting with the search for bioactive molecules and continuing with the production of drug-like molecules before finally reaching the status of medicine, can take up to 20 years, the development of medicine is a very long and risky venture.

scholarly journals Supporting secondary research in early drug discovery process through a Natural Language Processing based system

2020 ◽  
Vol 2 (1) ◽  
pp. 254-267
Author(s):  
Alina Popa
Keyword(s):  
Natural Language Processing ◽  
Drug Discovery ◽  
Natural Language ◽  
Research And Development ◽  
Language Processing ◽  
Entity Recognition ◽  
Topic Modelling ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Secondary Research

Abstract Last decades were characterised by a constant decline in the productivity of research and development activities of pharmaceutical companies. This is due to the fact that the drug discovery process contains an intrinsic risk that should be managed efficiently. Within this process, the early phase projects could be streamlined by doing more secondary research. These activities would involve the integration of chemical and biological knowledge from scientific literature in order to extract an overview and the evolution of a certain research area. This would then help refine the research and development operations. Considering the vast amount of pharmaceutical studies publications, it is not easy to identify the important information. For this task, a series of projects leveraged the advantages of the open pharmacological space through state-of-the-art technologies. The most popular are Knowledge Graphs methods. Although extremely useful, this technology requires increased investments of time and human resources. An alternative would be to develop a system that uses Natural Language Processing blocks. Still, there is no defined framework and reusable code template for the use-case of compounds development. In this study, it is presented the design and development of a system that uses Dynamic Topic Modelling and Named Entity Recognition modules in order to extract meaningful information from a large volume of unstructured texts. Moreover, the dynamic character of the topic modelling technique allows to analyse the evolution of different subject areas over time. In order to validate the system, a collection of articles from the Pharmaceutical Research Journal was used. Our results show that the system is able to identify the main research areas in the last 20 years, namely crystalline and amorphous systems, insulin resistance, paracellular permeability. Additionally, the evolution of the subjects is a highly valuable resource and should be used to get an in-depth understanding about the shifts that happened in a specific domain. However, a limitation of this system is that it cannot detect association between two concepts or entities if they are not involved in the same document.

scholarly journals The iterative application of a large chemical space in the drug discovery process

2021 ◽  
Vol 19 (4(76)) ◽  
pp. 3-11
Author(s):  
Olena V. Savych ◽  
Anastasia V. Gryniukova ◽  
Diana O. Alieksieieva ◽  
Igor M. Dziuba ◽  
Petro O. Borysko ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Large Scale ◽  
Chemical Space ◽  
Building Blocks ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Thermal Shift Assay ◽  
Virtual Libraries ◽  
Thermal Shift

Aim. To demonstrate the advantages of large-scale virtual libraries generated using chemical protocols previously validated in primary steps of the drug discovery process.Results and discussion. Two validated parallel chemistry protocols reported earlier were used to create the chemical space. It was then sampled based on diversity metric, and the sample was subjected to the virtual screening on BRD4 target. Hits of virtual screening were synthesized and tested in the thermal shift assay.Experimental part. The chemical space was generated using commercially available building blocks and synthetic protocols suitable for parallel chemistry and previously reported. After narrowing it down, using MedChem filters, the resulting sub-space was clustered based on diversity metrics. Centroids of the clusters were put to the virtual screening against the BRD4 active center. 29 Hits from the docking were synthesized and subjected to the thermal shift assay with BRD4, and 2 compounds showed noticeable dTm.Conclusions. A combination of cheminformatics and molecular docking was applied to find novel potential binders for BRD4 from a large chemical space. The selected set of predicted molecules was synthesized with a 72 % success rate and tested in a thermal shift assay to reveal a 6 % hit rate. The selection can be performed iteratively to fast support of the drug discovery.

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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