scholarly journals Development of a chemogenomics library for phenotypic screening

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Bryan Dafniet ◽  
Natacha Cerisier ◽  
Batiste Boezio ◽  
Anaelle Clary ◽  
Pierre Ducrot ◽  
...  
Keyword(s):  
Small Molecules ◽  
Drug Target ◽  
Drug Targets ◽  
Chemical Biology ◽  
Target Identification ◽  
Biological Effects ◽  
Phenotypic Screening ◽  
High Content Imaging ◽  
Advanced Technologies ◽  
System Pharmacology

AbstractWith the development of advanced technologies in cell-based phenotypic screening, phenotypic drug discovery (PDD) strategies have re-emerged as promising approaches in the identification and development of novel and safe drugs. However, phenotypic screening does not rely on knowledge of specific drug targets and needs to be combined with chemical biology approaches to identify therapeutic targets and mechanisms of actions induced by drugs and associated with an observable phenotype. In this study, we developed a system pharmacology network integrating drug-target-pathway-disease relationships as well as morphological profile from an existing high content imaging-based high-throughput phenotypic profiling assay known as “Cell Painting”. Furthermore, from this network, a chemogenomic library of 5000 small molecules that represent a large and diverse panel of drug targets involved in diverse biological effects and diseases has been developed. Such a platform and a chemogenomic library could assist in the target identification and mechanism deconvolution of some phenotypic assays. The usefulness of the platform is illustrated through examples.

scholarly journals From Phenotypic Hit to Chemical Probe: Chemical Biology Approaches to Elucidate Small Molecule Action in Complex Biological Systems

Molecules ◽  
2020 ◽  
Vol 25 (23) ◽  
pp. 5702
Author(s):  
Quentin T. L. Pasquer ◽  
Ioannis A. Tsakoumagkos ◽  
Sascha Hoogendoorn
Keyword(s):  
Small Molecules ◽  
Chemical Biology ◽  
Target Identification ◽  
Biologically Active ◽  
Phenotypic Screening ◽  
Biological Processes ◽  
Chemical Probes ◽  
Target Deconvolution ◽  
Cellular Target ◽  
Screening Approaches

Biologically active small molecules have a central role in drug development, and as chemical probes and tool compounds to perturb and elucidate biological processes. Small molecules can be rationally designed for a given target, or a library of molecules can be screened against a target or phenotype of interest. Especially in the case of phenotypic screening approaches, a major challenge is to translate the compound-induced phenotype into a well-defined cellular target and mode of action of the hit compound. There is no “one size fits all” approach, and recent years have seen an increase in available target deconvolution strategies, rooted in organic chemistry, proteomics, and genetics. This review provides an overview of advances in target identification and mechanism of action studies, describes the strengths and weaknesses of the different approaches, and illustrates the need for chemical biologists to integrate and expand the existing tools to increase the probability of evolving screen hits to robust chemical probes.

A Review of Recent Advances and Research on Drug Target Identification Methods

2019 ◽  
Vol 20 (3) ◽  
pp. 209-216 ◽  
Author(s):  
Yang Hu ◽  
Tianyi Zhao ◽  
Ningyi Zhang ◽  
Ying Zhang ◽  
Liang Cheng
Keyword(s):  
Machine Learning ◽  
Computational Methods ◽  
Drug Target ◽  
Drug Targets ◽  
Target Identification ◽  
Machine Learning Algorithms ◽  
Topological Features ◽  
Drug Target Identification ◽  
Incomplete Datasets ◽  
Optimal Set

Background:From a therapeutic viewpoint, understanding how drugs bind and regulate the functions of their target proteins to protect against disease is crucial. The identification of drug targets plays a significant role in drug discovery and studying the mechanisms of diseases. Therefore the development of methods to identify drug targets has become a popular issue.Methods:We systematically review the recent work on identifying drug targets from the view of data and method. We compiled several databases that collect data more comprehensively and introduced several commonly used databases. Then divided the methods into two categories: biological experiments and machine learning, each of which is subdivided into different subclasses and described in detail.Results:Machine learning algorithms are the majority of new methods. Generally, an optimal set of features is chosen to predict successful new drug targets with similar properties. The most widely used features include sequence properties, network topological features, structural properties, and subcellular locations. Since various machine learning methods exist, improving their performance requires combining a better subset of features and choosing the appropriate model for the various datasets involved.Conclusion:The application of experimental and computational methods in protein drug target identification has become increasingly popular in recent years. Current biological and computational methods still have many limitations due to unbalanced and incomplete datasets or imperfect feature selection methods

scholarly journals A Systems-Level Framework for Drug Discovery Identifies Csf1R As A Novel Anti-Epileptic Drug Target

2017 ◽  
Author(s):  
Prashant K Srivastava ◽  
Jonathan van Eyll ◽  
Patrice Godard ◽  
Manuela Mazzuferi ◽  
Benedicte Danis ◽  
...  
Keyword(s):  
Causal Reasoning ◽  
Drug Target ◽  
Drug Targets ◽  
Target Identification ◽  
Analytical Framework ◽  
Membrane Receptors ◽  
New Drugs ◽  
Tyrosine Kinase Receptor ◽  
Drug Target Identification ◽  
Novel Therapeutic

ABSTRACTThe identification of mechanistically novel drug targets is highly challenging, particularly for diseases of the central nervous system. To address this problem we developed and experimentally validated a new computational approach to drug target identification that combines gene-regulatory information with a causal reasoning framework (“causal reasoning analytical framework for target discovery” – CRAFT). Starting from gene expression data, CRAFT provides a predictive functional genomics framework for identifying membrane receptors with a direction-specified influence over network expression. As proof-of-concept we applied CRAFT to epilepsy, and predicted the tyrosine kinase receptor Csf1R as a novel therapeutic target for epilepsy. The predicted therapeutic effect of Csf1R blockade was validated in two pre-clinical models of epilepsy using a small molecule inhibitor of Csf1R. These results suggest Csf1R blockade as a novel therapeutic strategy in epilepsy, and highlight CRAFT as a systems-level framework for predicting mechanistically new drugs and targets. CRAFT is applicable to disease settings other than epilepsy.

Target identification of small molecules based on chemical biology approaches

2013 ◽  
Vol 9 (5) ◽  
pp. 897 ◽  
Author(s):  
Yushi Futamura ◽  
Makoto Muroi ◽  
Hiroyuki Osada
Keyword(s):  
Small Molecules ◽  
Chemical Biology ◽  
Target Identification

Photo-cross-linked small-molecule affinity matrix as a tool for target identification of bioactive small molecules

2016 ◽  
Vol 33 (5) ◽  
pp. 709-718 ◽  
Author(s):  
Naoki Kanoh
Keyword(s):  
Small Molecules ◽  
Small Molecule ◽  
Drug Target ◽  
Target Identification ◽  
Affinity Matrix ◽  
Industrial Chemical ◽  
Drug Target Identification ◽  
The Status

This review describes the status of the photo-cross-linked small-molecule affinity matrix while providing a useful tutorial for academic and industrial chemical biologists who are involved or interested in drug target identification.

Natural products-prompted chemical biology: phenotypic screening and a new platform for target identification

2016 ◽  
Vol 33 (5) ◽  
pp. 648-654 ◽  
Author(s):  
Hideaki Kakeya
Keyword(s):  
Cell Membrane ◽  
Cancer Cells ◽  
Chemical Biology ◽  
Target Identification ◽  
Chemical Genetics ◽  
Phenotypic Screening ◽  
Cancer Microenvironment ◽  
Microbial Metabolites ◽  
Cellular Targets ◽  
Target Cancer

This highlight focuses on our recent discoveries and chemical genetics approaches for bioactive microbial metabolites that target cancer cells, the cancer microenvironment, and cell membrane signalling. In addition, the development of two new platforms to identify the cellular targets of these molecules is also discussed.

scholarly journals LiP-Quant, an automated chemoproteomic approach to identify drug targets in complex proteomes

2019 ◽  
Author(s):  
Ilaria Piazza ◽  
Nigel Beaton ◽  
Roland Bruderer ◽  
Thomas Knobloch ◽  
Crystel Barbisan ◽  
...  
Keyword(s):  
Small Molecule ◽  
Binding Sites ◽  
Drug Target ◽  
Drug Targets ◽  
Target Identification ◽  
Limited Proteolysis ◽  
Drug Binding ◽  
Homologous Proteins ◽  
Protein Targets ◽  
Drug Target Identification

Chemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in developing optimized small-molecule compounds. Current unbiased approaches cannot directly pinpoint the interaction surfaces between ligands and protein targets. To address his limitation we have developed a new drug target deconvolution approach based on limited proteolysis coupled with mass spectrometry that works across species including human cells (LiP-Quant). LiP-Quant features an automated data analysis pipeline and peptide-level resolution for the identification of any small-molecule binding sites, Here we demonstrate drug target identification by LiP-Quant across compound classes, including compounds targeting kinases and phosphatases. We demonstrate that LiP-Quant estimates the half maximal effective concentration (EC50) of compound binding sites in whole cell lysates. LiP-Quant identifies targets of both selective and promiscuous drugs and correctly discriminates drug binding to homologous proteins. We finally show that the LiP-Quant technology identifies targets of a novel research compound of biotechnological interest.

Synthesis of New 3-Arylaminophthalides and 3-Indolyl-phthalides using Ammonium Chloride, Evaluation of their Anti-Mycobacterial Potential and Docking Study

2020 ◽  
Vol 23 (8) ◽  
pp. 723-739 ◽  
Author(s):  
Avinash Patil ◽  
Harleen Duggal ◽  
Kamini T. Bagul ◽  
Sonali Kamble ◽  
Pradeep Lokhande ◽  
...  
Keyword(s):  
Ammonium Chloride ◽  
In Silico ◽  
Drug Target ◽  
Drug Targets ◽  
Antioxidant Activities ◽  
Target Identification ◽  
Docking Study ◽  
Structural Level ◽  
Current Series ◽  
Microtiter Assay

Objective: The study aims at the derivatization of “Phthalides” and synthesizes 3- arylaminophthalides & 3-indolyl-phthalides compounds, and evaluates their anti-tubercular and antioxidant activities. The study has also intended to employ the in silico methods for the identification of possible drug targets in Mycobacterium and evaluate the binding affinities of synthesized compounds. Methods: This report briefly explains the synthesis of phthalide derivatives using ammonium chloride. The synthesized compounds were characterized using spectral analysis. Resazurin Microtiter Assay (REMA) plate method was used to demonstrate the anti-mycobacterial activity of the synthesized compounds. An in-silico pharmacophore probing approach was used for target identification in Mycobacterium. The structural level interaction between the identified putative drug target and synthesized phthalides was studied using Lamarckian genetic algorithm-based software. Results and Discussion: In the present study, we report an effective, environmentally benign scheme for the synthesis of phthalide derivatives. Compounds 5c and 5d from the current series appear to possess good anti-mycobacterial activity. dCTP: deaminasedUTPase was identified as a putative drug target in Mycobacterium. The docking results clearly showed the interactive involvement of conserved residues of dCTP with the synthesized phthalide compounds. Conclusion: On the eve of evolving anti-TB drug resistance, the data on anti-tubercular and allied activities of the compounds in the present study demonstrates the enormous significance of these newly synthesized derivatives as possible candidate leads in the development of novel anti-tubercular agents. The docking results from the current report provide a structural rationale for the promising anti-tubercular activity demonstrated by 3-arylaminophthalides and 3-indolyl-phthalides compounds.

Sign in / Sign up

Export Citation Format

Share Document