Structure–activity relationships for ruthenium and osmium anticancer agents – towards clinical development

2018 ◽  
Vol 47 (3) ◽  
pp. 909-928 ◽  
Author(s):  
Samuel M. Meier-Menches ◽  
Christopher Gerner ◽  
Walter Berger ◽  
Christian G. Hartinger ◽  
Bernhard K. Keppler
Keyword(s):  
Drug Discovery ◽  
Anticancer Agents ◽  
Clinical Development ◽  
Global Structure ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Anticancer Therapeutics

The drug discovery process of ruthenium and osmium anticancer therapeutics is described, including global structure–activity relationships.

Computational techniques for designing new lead molecules in the process of drug discovery

2017 ◽  
Vol 3 (01) ◽  
Author(s):  
Suresh Kumar ◽  
Samiyara Begum ◽  
Hemant Kumar Srivastava
Keyword(s):  
Drug Discovery ◽  
Quantitative Structure Activity Relationship ◽  
Pharmacophore Modeling ◽  
Computational Techniques ◽  
Scoring Functions ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Qsar Studies ◽  
Structure Activity ◽  
Sampling Algorithms

Computational techniques are important in the field of drug discovery. These techniques are generally categorized in two methods namely ‘structure-based’ and ‘ligand-based’ methods. The present review discusses the theory of the most important methods, recent successful applications, pharmacophore modeling and quantitative structure-activity relationship (QSAR) studies. A brief introduction of molecular docking methods and their development and applications in drug discovery process is also included. Basic theories and fundamental techniques including sampling algorithms and scoring functions are discussed.

scholarly journals Hit-Optimization Using Target-Directed Dynamic Combinatorial Chemistry: Development of Inhibitors of the Anti-Infective Target 1-Deoxy-D-Xylulose-5-Phosphate Synthase

2020 ◽  
Author(s):  
Ravindra P. Jumde ◽  
Melissa Guardigni ◽  
Robin M. Gierse ◽  
Alaa Alhayek ◽  
Di Zhu ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Combinatorial Chemistry ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Biological Targets ◽  
Dynamic Combinatorial Chemistry ◽  
Structure Activity ◽  
Chemistry Development ◽  
Relationship Of ◽  
Phosphate Synthase

<p>Target-directed dynamic combinatorial chemistry (tdDCC) enables the identification, as well as optimization of ligands for un(der)explored targets such as the anti-infective target 1‑deoxy‑d‑xylulose-5-phosphate synthase (DXS). We report the unprecedented use of tdDCC to first identify and subsequently optimize inhibitors of the anti-infective target DXS. Using tdDCC, we were able to generate acylhydrazone-based inhibitors for DXS. The tailored tdDCC runs also provided insights into the structure–activity relationship of this novel class of DXS inhibitors. This approach holds the potential to expedite the drug discovery process and could be generally applied to a range of biological targets.</p>

scholarly journals Hit-Optimization Using Target-Directed Dynamic Combinatorial Chemistry: Development of Inhibitors of the Anti-Infective Target 1-Deoxy-D-Xylulose-5-Phosphate Synthase

2020 ◽  
Author(s):  
Ravindra P. Jumde ◽  
Melissa Guardigni ◽  
Robin M. Gierse ◽  
Alaa Alhayek ◽  
Di Zhu ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Combinatorial Chemistry ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Biological Targets ◽  
Dynamic Combinatorial Chemistry ◽  
Structure Activity ◽  
Chemistry Development ◽  
Relationship Of ◽  
Phosphate Synthase

<p>Target-directed dynamic combinatorial chemistry (tdDCC) enables the identification, as well as optimization of ligands for un(der)explored targets such as the anti-infective target 1‑deoxy‑d‑xylulose-5-phosphate synthase (DXS). We report the unprecedented use of tdDCC to first identify and subsequently optimize inhibitors of the anti-infective target DXS. Using tdDCC, we were able to generate acylhydrazone-based inhibitors for DXS. The tailored tdDCC runs also provided insights into the structure–activity relationship of this novel class of DXS inhibitors. This approach holds the potential to expedite the drug discovery process and could be generally applied to a range of biological targets.</p>

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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