Fast Mek1 Hit Identification with TRIC Technology Correlates Well with Other Biophysical Methods

2021 ◽  
pp. 247255522110262
Author(s):  
Semir Jeridi ◽  
Alexey Rak ◽  
Amit Gupta ◽  
Pierre Soule
Keyword(s):  
High Throughput Screening ◽  
Drug Targets ◽  
Rational Design ◽  
Weak Interactions ◽  
Chemical Space ◽  
Intensity Variation ◽  
Building Blocks ◽  
Intensity Change ◽  
Drug Candidates ◽  
Ideal Tool

The variety and complexity of drug targets are expanding rapidly. At the same time, there is significant interest in exploring a larger chemical space to identify new candidates. Fragment-based screening (FBS) has emerged as a popular alternative to traditional high-throughput screening campaigns to identify such drug candidates. FBS identifies hit fragments that exhibit weak interactions with the target of interest, thereby enabling the rational design of small-molecule compounds from the identified hit fragments, which serve as building blocks. This strategy reduces the number of molecules to screen while also allowing the exploration of a greater chemical space. Here we use temperature-related intensity change (TRIC) technology to perform FBS against the target MAPK/ERK kinase-1 (Mek1). TRIC describes the change in fluorescence intensity of a fluorescently labeled molecule upon a change in temperature. This intensity variation is dependent on the physicochemical environment in the vicinity of the dye and strongly affected by binding events. Thus, the detection of binding events is independent of mass, making TRIC an ideal tool for FBS. Using only 150 pmol of labeled Mek1, the authors screened 193 fragments from a prescreened library in less than 1 h of measurement time, leading to 66 hits. Among those hits, they identified more than 80% of the published top hits found using orthogonal techniques. Furthermore, TRIC allowed the identification of fragments that were of poor solubility but could be mistaken as false-positive hits in other methods.

scholarly journals Research fronts of Chemical Biology

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shanshan Lv
Keyword(s):  
High Throughput Screening ◽  
Drug Targets ◽  
Chemical Biology ◽  
Rational Design ◽  
Future Research ◽  
Design Strategies ◽  
Binding Assays ◽  
Cellular Mechanisms ◽  
Diagnostic Technologies

Abstract Over the past decades, researchers have witnessed substantially increasing and ever-growing interests and efforts in Chemical Biology studies, thanks to the development of genome and epi-genome sequencing (revealing potential drug targets), synthetic chemistry (producing new medicines), bioorthogonal chemistry (chemistry in living systems) and high-throughput screening technologies (in vitro cell systems, protein binding assays and phenotypic assays). This report presents literature search results for current research in Chemical Biology, to explore basic principles, summarize recent advances, identify key challenges, and provide suggestions for future research (with a focus on Chemical Biology in the context of human health and diseases). Chemical Biology research can positively contribute to delivering a better understanding of the molecular and cellular mechanisms that accompany pathology underlying diseases, as well as developing improved methods for diagnosis, drug discovery, and therapeutic delivery. While much progress has been made, as shown in this report, there are still further needs and opportunities. For instance, pressing challenges still exist in selecting appropriate targets in biological systems and adopting more rational design strategies for the development of innovative and sustainable diagnostic technologies and medical treatments. Therefore, more than ever, researchers from different disciplines need to collaborate to address the challenges in Chemical Biology.

scholarly journals Natural Products as Modulators of Sirtuins

Molecules ◽  
2020 ◽  
Vol 25 (14) ◽  
pp. 3287 ◽  
Author(s):  
Berin Karaman Mayack ◽  
Wolfgang Sippl ◽  
Fidele Ntie-Kang
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Histone Deacetylases ◽  
High Throughput Screening ◽  
Chemical Space ◽  
Class Iii ◽  
Drug Candidates ◽  
Starting Point ◽  
Recent Developments ◽  
Potent Drug

Natural products have been used for the treatment of human diseases since ancient history. Over time, due to the lack of precise tools and techniques for the separation, purification, and structural elucidation of active constituents in natural resources there has been a decline in financial support and efforts in characterization of natural products. Advances in the design of chemical compounds and the understanding of their functions is of pharmacological importance for the biomedical field. However, natural products regained attention as sources of novel drug candidates upon recent developments and progress in technology. Natural compounds were shown to bear an inherent ability to bind to biomacromolecules and cover an unparalleled chemical space in comparison to most libraries used for high-throughput screening. Thus, natural products hold a great potential for the drug discovery of new scaffolds for therapeutic targets such as sirtuins. Sirtuins are Class III histone deacetylases that have been linked to many diseases such as Parkinson`s disease, Alzheimer’s disease, type II diabetes, and cancer linked to aging. In this review, we examine the revitalization of interest in natural products for drug discovery and discuss natural product modulators of sirtuins that could serve as a starting point for the development of isoform selective and highly potent drug-like compounds, as well as the potential application of naturally occurring sirtuin inhibitors in human health and those in clinical trials.

scholarly journals Machine Learning Methods in Drug Discovery

Molecules ◽  
2020 ◽  
Vol 25 (22) ◽  
pp. 5277
Author(s):  
Lauv Patel ◽  
Tripti Shukla ◽  
Xiuzhen Huang ◽  
David W. Ussery ◽  
Shanzhi Wang
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Drug Discovery ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Learning Algorithms ◽  
Machine Learning Techniques ◽  
Online Information ◽  
Drug Candidates ◽  
Novel Drug

The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been used for the development of novel drug candidates. The methods for designing drug targets and novel drug discovery now routinely combine machine learning and deep learning algorithms to enhance the efficiency, efficacy, and quality of developed outputs. The generation and incorporation of big data, through technologies such as high-throughput screening and high through-put computational analysis of databases used for both lead and target discovery, has increased the reliability of the machine learning and deep learning incorporated techniques. The use of these virtual screening and encompassing online information has also been highlighted in developing lead synthesis pathways. In this review, machine learning and deep learning algorithms utilized in drug discovery and associated techniques will be discussed. The applications that produce promising results and methods will be reviewed.

In Silico Chemogenomics Drug Repositioning Strategies for Neglected Tropical Diseases

2019 ◽  
Vol 26 (23) ◽  
pp. 4355-4379 ◽  
Author(s):  
Carolina Horta Andrade ◽  
Bruno Junior Neves ◽  
Cleber Camilo Melo-Filho ◽  
Juliana Rodrigues ◽  
Diego Cabral Silva ◽  
...  
Keyword(s):  
High Throughput Screening ◽  
Drug Targets ◽  
Neglected Tropical Diseases ◽  
Drug Repositioning ◽  
Tropical Diseases ◽  
Systematic Screening ◽  
Drug Candidates ◽  
Lead Compounds ◽  
The One ◽  
Approved Drugs

Only ~1% of all drug candidates against Neglected Tropical Diseases (NTDs) have reached clinical trials in the last decades, underscoring the need for new, safe and effective treatments. In such context, drug repositioning, which allows finding novel indications for approved drugs whose pharmacokinetic and safety profiles are already known, emerging as a promising strategy for tackling NTDs. Chemogenomics is a direct descendent of the typical drug discovery process that involves the systematic screening of chemical compounds against drug targets in high-throughput screening (HTS) efforts, for the identification of lead compounds. However, different to the one-drug-one-target paradigm, chemogenomics attempts to identify all potential ligands for all possible targets and diseases. In this review, we summarize current methodological development efforts in drug repositioning that use state-of-the-art computational ligand- and structure-based chemogenomics approaches. Furthermore, we highlighted the recent progress in computational drug repositioning for some NTDs, based on curation and modeling of genomic, biological, and chemical data. Additionally, we also present in-house and other successful examples and suggest possible solutions to existing pitfalls.

scholarly journals Colchicine-Binding Site Inhibitors from Chemistry to Clinic: A Review

2020 ◽  
Vol 13 (1) ◽  
pp. 8 ◽  
Author(s):  
Eavan C. McLoughlin ◽  
Niamh M. O’Boyle
Keyword(s):  
Binding Site ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Rational Design ◽  
Clinical Status ◽  
Cancer Therapies ◽  
Colchicine Binding Site ◽  
Anti Cancer ◽  
Recent Developments ◽  
Important Drug

It is over 50 years since the discovery of microtubules, and they have become one of the most important drug targets for anti-cancer therapies. Microtubules are predominantly composed of the protein tubulin, which contains a number of different binding sites for small-molecule drugs. There is continued interest in drug development for compounds targeting the colchicine-binding site of tubulin, termed colchicine-binding site inhibitors (CBSIs). This review highlights CBSIs discovered through diverse sources: from natural compounds, rational design, serendipitously and via high-throughput screening. We provide an update on CBSIs reported in the past three years and discuss the clinical status of CBSIs. It is likely that efforts will continue to develop CBSIs for a diverse set of cancers, and this review provides a timely update on recent developments.

scholarly journals Natural Products as Modulators of Sirtuins

2020 ◽  
Author(s):  
Berin Karaman Mayack ◽  
Wolfgang Sippl ◽  
Fidele Ntie-Kang
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Histone Deacetylases ◽  
High Throughput Screening ◽  
Chemical Space ◽  
Class Iii ◽  
Drug Candidates ◽  
Starting Point ◽  
Recent Developments ◽  
Potent Drug

Natural products have been used for the treatment of human diseases since ancient history. Over time, due to the lack of precise tools and techniques for the separation, purification, and structural elucidation of active constituents in natural resources there has been a decline in financial support and efforts in characterization of natural products. Advances in the design of chemical compounds and the understanding of their functions is of pharmacological importance for the biomedical field. However, natural products regained attention as sources of novel drug candidates upon recent developments and progress in technology. Natural compounds were shown to bear an inherent ability to bind to biomacromolecules and cover an unparalleled chemical space in comparison to most libraries used for high-throughput screening. Thus, natural products hold a great potential for the drug discovery of new scaffolds for therapeutic targets such as Sirtuins. Sirtuins are Class III histone deacetylases that have been linked to many diseases such as Parkinson`s disease, Alzheimer’s disease, type II diabetes, and cancer linked to aging. In this review, we examine the revitalization of interest in natural products for drug discovery and discuss natural product modulators of Sirtuins that could serve as a starting point for the development of isoform selective and highly potent drug-like compounds.

Modular, Stereocontrolled Cβ–H/Cα–C Activation of Alkyl Carboxylic Acids

2019 ◽  
Author(s):  
Ming Shang ◽  
Karla S. Feu ◽  
Julien C. Vantourout ◽  
Lisa M. Barton ◽  
Heather L. Osswald ◽  
...  
Keyword(s):  
Carboxylic Acid ◽  
Heterocyclic Compounds ◽  
Cross Coupling ◽  
Building Blocks ◽  
Enantioselective Synthesis ◽  
Carbon Centers ◽  
Drug Candidates ◽  
Rapid Diversification ◽  
Directing Group ◽  
Compound Series

<div> <div> <div> <p>The union of two powerful transformations, directed C–H activation and decarboxylative cross-coupling, for the enantioselective synthesis of vicinally functionalized alkyl, carbocyclic, and heterocyclic compounds is described. Starting from simple carboxylic acid building blocks, this modular sequence exploits the residual directing group to access more than 50 scaffolds that would be otherwise extremely difficult to prepare. The tactical use of these two transformations accomplishes a formal vicinal difunctionalization of carbon centers in a way that is modular and thus amenable to rapid diversity incorporation. A simplification of routes to known preclinical drug candidates is presented along with the rapid diversification of an antimalarial compound series. </p> </div> </div> </div>

Covid 19 – Structural proteins and prospective drug candidates (Preprint)

2020 ◽  
Author(s):  
A.N Anoopkumar ◽  
Sharrel Rebello ◽  
Embalil Mathachan Aneesh
Keyword(s):  
Causative Agent ◽  
Protein Level ◽  
Drug Targets ◽  
Current Paper ◽  
Structural Proteins ◽  
Drug Candidates ◽  
Propagation Properties

UNSTRUCTURED Covid 19 the causative agent of the current devastating pandemic has turned out to be a notorious virus to all men-irrespective of either common to scientific calibre. Attempts to combat this deadly virus are the need of the hour and quite often the best way to defeat an opponent is to keenly study about its structural and propagation properties. The current paper describes briefly Covid 19 at the genomic, structural and protein level to the best of our knowledge. Furthermore, the prospects of possible drug targets that could aid in the control of this virus are also discussed.

scholarly journals Development of a Novel High-Throughput Screen and Identification of Small-Molecule Inhibitors of the Gα–RGS17 Protein–Protein Interaction Using AlphaScreen

2011 ◽  
Vol 16 (8) ◽  
pp. 869-877 ◽  
Author(s):  
Duncan I. Mackie ◽  
David L. Roman
Keyword(s):  
Small Molecule ◽  
High Throughput ◽  
Protein Interaction ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Screening Method ◽  
Fold Increase ◽  
Rgs Proteins ◽  
High Throughput Screen ◽  
Protein Protein Interaction

In this study, the authors used AlphaScreen technology to develop a high-throughput screening method for interrogating small-molecule libraries for inhibitors of the Gαo–RGS17 interaction. RGS17 is implicated in the growth, proliferation, metastasis, and the migration of prostate and lung cancers. RGS17 is upregulated in lung and prostate tumors up to a 13-fold increase over patient-matched normal tissues. Studies show RGS17 knockdown inhibits colony formation and decreases tumorigenesis in nude mice. The screen in this study uses a measurement of the Gαo–RGS17 protein–protein interaction, with an excellent Z score exceeding 0.73, a signal-to-noise ratio >70, and a screening time of 1100 compounds per hour. The authors screened the NCI Diversity Set II and determined 35 initial hits, of which 16 were confirmed after screening against controls. The 16 compounds exhibited IC50 <10 µM in dose–response experiments. Four exhibited IC50 values <6 µM while inhibiting the Gαo–RGS17 interaction >50% when compared to a biotinylated glutathione-S-transferase control. This report describes the first high-throughput screen for RGS17 inhibitors, as well as a novel paradigm adaptable to many other RGS proteins, which are emerging as attractive drug targets for modulating G-protein-coupled receptor signaling.

scholarly journals High-throughput screening and rational design of biofunctionalized surfaces with optimized biocompatibility and antimicrobial activity

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhou Fang ◽  
Junjian Chen ◽  
Ye Zhu ◽  
Guansong Hu ◽  
Haoqian Xin ◽  
...  
Keyword(s):  
Antimicrobial Activity ◽  
High Throughput ◽  
High Throughput Screening ◽  
Rational Design ◽  
Click Reaction ◽  
Reaction Times ◽  
Great Promise ◽  
Biomaterial Surfaces

AbstractPeptides are widely used for surface modification to develop improved implants, such as cell adhesion RGD peptide and antimicrobial peptide (AMP). However, it is a daunting challenge to identify an optimized condition with the two peptides showing their intended activities and the parameters for reaching such a condition. Herein, we develop a high-throughput strategy, preparing titanium (Ti) surfaces with a gradient in peptide density by click reaction as a platform, to screen the positions with desired functions. Such positions are corresponding to optimized molecular parameters (peptide densities/ratios) and associated preparation parameters (reaction times/reactant concentrations). These parameters are then extracted to prepare nongradient mono- and dual-peptide functionalized Ti surfaces with desired biocompatibility or/and antimicrobial activity in vitro and in vivo. We also demonstrate this strategy could be extended to other materials. Here, we show that the high-throughput versatile strategy holds great promise for rational design and preparation of functional biomaterial surfaces.

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