scholarly journals Developments of bioorthogonal handle-containing photo-crosslinkers for photoaffinity labeling

MedChemComm ◽  
2017 ◽  
Vol 8 (8) ◽  
pp. 1585-1591 ◽  
Author(s):  
Haijun Guo ◽  
Zhengqiu Li
Keyword(s):  
Small Molecules ◽  
Target Identification ◽  
Photoaffinity Labeling ◽  
Proteome Profiling

“Minimalist” photo-crosslinkers (L3–L6) applied in affinity-based proteome profiling and bioimaging for target identification of small molecules.

scholarly journals A New Big-Data Paradigm for Target Identification and Drug Discovery

2017 ◽  
Author(s):  
Neel S. Madhukar ◽  
Prashant K. Khade ◽  
Linda Huang ◽  
Kaitlyn Gayvert ◽  
Giuseppe Galletti ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Clinical Application ◽  
Small Molecule ◽  
Target Identification ◽  
Clinical Development ◽  
Data Types ◽  
Public Data ◽  
Drug Target Identification ◽  
Approved Drugs

AbstractDrug target identification is one of the most important aspects of pre-clinical development yet it is also among the most complex, labor-intensive, and costly. This represents a major issue, as lack of proper target identification can be detrimental in determining the clinical application of a bioactive small molecule. To improve target identification, we developed BANDIT, a novel paradigm that integrates multiple data types within a Bayesian machine-learning framework to predict the targets and mechanisms for small molecules with unprecedented accuracy and versatility. Using only public data BANDIT achieved an accuracy of approximately 90% over 2000 different small molecules – substantially better than any other published target identification platform. We applied BANDIT to a library of small molecules with no known targets and generated ∼4,000 novel molecule-target predictions. From this set we identified and experimentally validated a set of novel microtubule inhibitors, including three with activity on cancer cells resistant to clinically used anti-microtubule therapies. We next applied BANDIT to ONC201 – an active anti- cancer small molecule in clinical development – whose target has remained elusive since its discovery in 2009. BANDIT identified dopamine receptor 2 as the unexpected target of ONC201, a prediction that we experimentally validated. Not only does this open the door for clinical trials focused on target-based selection of patient populations, but it also represents a novel way to target GPCRs in cancer. Additionally, BANDIT identified previously undocumented connections between approved drugs with disparate indications, shedding light onto previously unexplained clinical observations and suggesting new uses of marketed drugs. Overall, BANDIT represents an efficient and highly accurate platform that can be used as a resource to accelerate drug discovery and direct the clinical application of small molecule therapeutics with improved precision.

Drug Target Identification in Tissues by Thermal Proteome Profiling

2021 ◽  
Vol 62 (1) ◽  
Author(s):  
André Mateus ◽  
Nils Kurzawa ◽  
Jessica Perrin ◽  
Giovanna Bergamini ◽  
Mikhail M. Savitski
Keyword(s):  
Drug Target ◽  
Target Identification ◽  
Annual Review ◽  
Publication Date ◽  
Proteome Profiling ◽  
Biological Phenomena ◽  
Target Deconvolution ◽  
Drug Target Identification ◽  
Recent Developments ◽  
Fundamental Biology

Drug target deconvolution can accelerate the drug discovery process by identifying a drug's targets (facilitating medicinal chemistry efforts) and off-targets (anticipating toxicity effects or adverse drug reactions). Multiple mass spectrometry–based approaches have been developed for this purpose, but thermal proteome profiling (TPP) remains to date the only one that does not require compound modification and can be used to identify intracellular targets in living cells. TPP is based on the principle that the thermal stability of a protein can be affected by its interactions. Recent developments of this approach have expanded its applications beyond drugs and cell cultures to studying protein-drug interactions and biological phenomena in tissues. These developments open up the possibility of studying drug treatment or mechanisms of disease in a holistic fashion, which can result in the design of better drugs and lead to a better understanding of fundamental biology. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Clickable gold-nanoparticles as generic probe precursors for facile photoaffinity labeling application

2021 ◽  
Author(s):  
Kanna Mori ◽  
Kaori Sakurai
Keyword(s):  
Gold Nanoparticles ◽  
Small Molecules ◽  
Photoaffinity Labeling ◽  
Protein Analysis ◽  
Target Protein ◽  
Photoaffinity Probes ◽  
One Step

Clickable photoreactive gold nanoparticles have been developed to facilitate one-step preparation of photoaffinity probes for bioactive small molecules and their application to target protein analysis.

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.

scholarly journals Extending the small molecule similarity principle to all levels of biology

2019 ◽  
Author(s):  
Miquel Duran-Frigola ◽  
Eduardo Pauls ◽  
Oriol Guitart-Pla ◽  
Martino Bertoni ◽  
Víctor Alcalde ◽  
...  
Keyword(s):  
Small Molecules ◽  
Biological Networks ◽  
Target Identification ◽  
Chemical Properties ◽  
Chemical Information ◽  
Chemical Similarity ◽  
Similarity Principle ◽  
Genetic Perturbations ◽  
Chemical Descriptors ◽  
Library Characterization

AbstractWe present the Chemical Checker (CC), a resource that provides processed, harmonized and integrated bioactivity data on 800,000 small molecules. The CC divides data into five levels of increasing complexity, ranging from the chemical properties of compounds to their clinical outcomes. In between, it considers targets, off-targets, perturbed biological networks and several cell-based assays such as gene expression, growth inhibition and morphological profilings. In the CC, bioactivity data are expressed in a vector format, which naturally extends the notion of chemical similarity between compounds to similarities between bioactivity signatures of different kinds. We show how CC signatures can boost the performance of drug discovery tasks that typically capitalize on chemical descriptors, including target identification and library characterization. Moreover, we demonstrate and experimentally validate that CC signatures can be used to reverse and mimic biological signatures of disease models and genetic perturbations, options that are otherwise impossible using chemical information alone.

scholarly journals A Bayesian Semi-Parametric Model for Thermal Proteome Profiling

2020 ◽  
Author(s):  
Siqi Fang ◽  
Paul Kirk ◽  
Marcus Bantscheff ◽  
Kathryn Lilley ◽  
Oliver Crook
Keyword(s):  
Thermal Stability ◽  
Small Molecules ◽  
Functional Data ◽  
Protein Function ◽  
Drug Targets ◽  
Single Experiment ◽  
Proteome Profiling ◽  
Relative Solubility ◽  
Complex Temperature ◽  
Thermal Stability Of

Abstract The thermal stability of proteins can be altered when they interact with small molecules. Thus monitoring the thermal stability of proteins under various cellular perturbations can provide insights into protein function, as well as potentially determine drug targets and off-targets. Thermal proteome profiling is a multiplexed mass-spectrommetry method for monitoring the melting behaviour of thousands of proteins in a single experiment. In essence, thermal proteome profiling assumes that proteins denature upon heating and hence become insoluble. Thus, by tracking the relative solubility of proteins at sequentially increasing temperatures, one can report on protein thermal stability. Standard thermodynamics predicts a sigmoidal relationship between temperature and relative solubility and this is the basis of current statistical procedures. However, current methods do not model deviations from this behaviour and they do not quantify uncertainty in the melting profiles. To overcome these challenges, we propose Bayesian functional data analysis tools which allow complex temperature-solubility behaviours. Our methods have improved sensitivity over the state-of-the art, identify new drug-protein associations and have less restrictive assumptions than current approaches. Our methods allows for comprehensive analysis of proteins that deviate from the predicted sigmoid behaviour and we uncover potentially biphasic phenomena with a series of published datasets.

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