4.3 Article

Quantitative high-throughput phenotypic screening of pediatric cancer cell lines identifies multiple opportunities for drug repurposing

Journal

ONCOTARGET
Volume 9, Issue 4, Pages 4758-4772

Publisher

IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.23462

Keywords

drug repurposing; quantitative high-throughput screening; pediatric cancer; 3D cultures

Funding

  1. National Center for Advancing Translational Sciences

Ask authors/readers for more resources

Drug repurposing approaches have the potential advantage of facilitating rapid and cost-effective development of new therapies. Particularly, the repurposing of drugs with known safety profiles in children could bypass or streamline toxicity studies. We employed a phenotypic screening paradigm on a panel of well-characterized cell lines derived from pediatric solid tumors against a collection of similar to 3,800 compounds spanning approved drugs and investigational agents. Specifically, we employed titration-based screening where compounds were tested at multiple concentrations for their effect on cell viability. Molecular and cellular target enrichment analysis indicated that numerous agents across different therapeutic categories and modes of action had an antiproliferative effect, notably antiparasitic/protozoal drugs with non-classic antineoplastic activity. Focusing on active compounds with dosing and safety information in children according to the Children's Pharmacy Collaborative database, we identified compounds with therapeutic potential through further validation using 3D tumor spheroid models. Moreover, we show that antiparasitic agents induce cell death via apoptosis induction. This study demonstrates that our screening platform enables the identification of chemical agents with cytotoxic activity in pediatric cancer cell lines of which many have known safety/toxicity profiles in children. These agents constitute attractive candidates for efficacy studies in pre-clinical models of pediatric solid tumors.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Review Pharmacology & Pharmacy

Defining clinical outcome pathways

Daniel Korn, Andrew J. Thieme, Vinicius M. Alves, Michael Yeakey, Joyce V. V. B. Borba, Stephen J. Capuzzi, Karamarie Fecho, Chris Bizon, Stephen W. Edwards, Rada Chirkova, Christine M. Colvis, Noel T. Southall, Christopher P. Austin, Eugene N. Muratov, Alexander Tropsha

Summary: COPs are a series of key molecular and cellular events underlying therapeutic effects of drug molecules, and their broader use with the help of biomedical knowledge graph mining is likely to accelerate drug discovery and repurposing efforts.

DRUG DISCOVERY TODAY (2022)

Review Pharmacology & Pharmacy

Knowledge-based approaches to drug discovery for rare diseases

Vinicius M. Alves, Daniel Korn, Vera Pervitsky, Andrew Thieme, Stephen J. Capuzzi, Nancy Baker, Rada Chirkova, Sean Ekins, Eugene N. Muratov, Anthony Hickey, Alexander Tropsha

Summary: This article discusses recent advances in biomedical knowledge mining for drug discovery in rare diseases, emphasizing the effectiveness of machine learning and biomedical knowledge graph mining. The power of these methodologies is illustrated through a case study on chordoma.

DRUG DISCOVERY TODAY (2022)

Article Environmental Sciences

STopTox: An in Silico Alternative to Animal Testing for Acute Systemic and Topical Toxicity

Joyce V. B. Borba, Vinicius M. Alves, Rodolpho C. Braga, Daniel R. Korn, Kirsten Overdahl, Arthur C. Silva, Steven U. S. Hall, Erik Overdahl, Nicole Kleinstreuer, Judy Strickland, David Allen, Carolina Horta Andrade, Eugene N. Muratov, Alexander Tropsha

Summary: Modern chemical toxicology is in need of reducing, refining, and replacing animal tests. In this study, a collection of computational models called STopTox was developed to predict the toxicity hazard of small organic molecules. The models were validated and shown to have high accuracy. A web portal was also established to assist scientists and regulators in identifying potential toxicants or non-toxicants in chemical libraries of interest.

ENVIRONMENTAL HEALTH PERSPECTIVES (2022)

Article Pharmacology & Pharmacy

Conserved coronavirus proteins as targets of broad-spectrum antivirals

Cleber C. Melo-Filho, Tesia Bobrowski, Holli-Joi Martin, Zoe Sessions, Konstantin I. Popov, Nathaniel J. Moorman, Ralph S. Baric, Eugene N. Muratov, Alexander Tropsha

Summary: This study identified highly conserved binding sites in key coronavirus proteins, providing important information for the development of broad-spectrum anti-coronaviral medications, and validated the significance of this conservation for drug discovery with existing experimental data.

ANTIVIRAL RESEARCH (2022)

Article Chemistry, Medicinal

Natural Products from Annonaceae as Potential Antichagasic Agents

Renata Priscila Barros de Menezes, Josean Fechine Tavares, Massuo Jorge Kato, Francisco Alex da Rocha Coelho, Airton Lucas Sousa dos Santos, Klinger Antonio da Franca Rodrigues, Zoe L. Sessions, Eugene N. Muratov, Luciana Scotti, Marcus Tullius Scotti

Summary: Chagas disease is a neglected tropical disease endemic in 21 Latin American countries, with a high prevalence in Brazil. This study identified and validated natural products from the Annonaceae family as potential antichagasic agents. The compound 13-Epicupressic acid showed promising activity against the disease.

CHEMMEDCHEM (2022)

Article Chemistry, Medicinal

MolPredictX: Online Biological Activity Predictions by Machine Learning Models

Marcus Tullius Scotti, Chonny Herrera-Acevedo, Renata Priscila Barros de Menezes, Holli-Joi Martin, Eugene N. Muratov, Avilla Italo de Souza Silva, Emmanuella Faustino Albuquerque, Lucas Ferreira Calado, Ericsson Coy-Barrera, Luciana Scotti

Summary: We introduce MolPredictX, an innovative and freely accessible web interface for predicting the biological activity of query molecules. MolPredictX utilizes in-house QSAR models to provide qualitative predictions and quantitative probabilities for a variety of diseases-related bioactivities.

MOLECULAR INFORMATICS (2022)

Article Chemistry, Applied

Four diterpenes identified in silico were isolated from Hyptidinae and demonstrated in vitro activity against Mycobacterium tuberculosis

Andreza Barbosa Silva Cavalcanti, Mayara Dos Santos Maia, Pedro Thiago Ramalho de Figueiredo, Renata Priscila Barros de Menezes, Alex France Messias Monteiro, Roseana Araujo Ramos Meireles, Gabriela Cristina Soares Rodrigues, Ana Rita Rodrigues de Almeida Silva, Jociano da Silva Lins, Laisa Vilar Cordeiro, Valnes S. Rodrigues Junior, Ana Paula O. T. Castelo Branco, Maria de Fatima Agra, Zoe L. Sessions, Eugene N. Muratov, Luciana Scotti, Marcelo Sobral da Silva, Vicente Carlos de Oliveira Costa, Josean Fechine Tavares, Marcus Tullius Scotti

Summary: Plants of the Hyptidinae subtribe, such as Mesosphaerum sidifolium, have been found to contain bioactive molecules with potential as new drug candidates. In this study, the chemical composition of diterpenes isolated from M. sidifolium was analyzed using NMR spectral data. In silico modeling predicted 48 diterpenes with potential biological activity against Mycobacterium tuberculosis. In vitro testing revealed that four compounds showed antimicrobial activity against M. tuberculosis, with Pomiferin D and 1 exhibiting the strongest effect.

NATURAL PRODUCT RESEARCH (2023)

Article Toxicology

PreS/MD: Predictor of Sensitization Hazard for Chemical Substances Released From Medical Devices

Vinicius M. Alves, Joyce V. B. Borba, Rodolpho C. Braga, Daniel R. Korn, Nicole Kleinstreuer, Kevin Causey, Alexander Tropsha, Diego Rua, Eugene N. Muratov

Summary: This study developed a computational tool called PreS/MD for rapid and accurate prediction of the guinea pig maximization test (GPMT) outcome. By collecting the largest GPMT results dataset, predictive models were successfully developed using machine learning algorithms, and a publicly accessible web portal was created to predict GPMT outcomes for any molecule of interest. It is expected that this tool will be widely used in medical device safety assessments, helping to replace, reduce, or refine the use of animals in toxicity testing.

TOXICOLOGICAL SCIENCES (2022)

Article Microbiology

Selene-Ethylenelacticamides and N-Aryl-Propanamides as Broad-Spectrum Leishmanicidal Agents

Natalia Ferreira de Sousa, Helivaldo Diogenes da Silva Souza, Renata Priscila Barros de Menezes, Francinara da Silva Alves, Chonny Alexander Herrera Acevedo, Thais Amanda de Lima Nunes, Zoe L. Sessions, Luciana Scotti, Eugene N. Muratov, Francisco Jaime Bezerra Mendonca-Junior, Klinger Antonio da Franca Rodrigues, Petronio Filgueiras de Athayde Filho, Marcus Tullius Scotti

Summary: The World Health Organization classifies Leishmania as one of the 17 neglected diseases. We analyzed organoselenides for potential anti-leishmanial effects due to their reduced toxicity and displayed biological activity. In silico models predicted the activity of 77 compounds, and subsequent experimental validation confirmed the effectiveness of the methodology, with several compounds showing strong inhibition profiles.

PATHOGENS (2023)

Article Pharmacology & Pharmacy

Small molecule antiviral compound collection (SMACC): A comprehensive, highly curated database to support the discovery of broad-spectrum antiviral drug molecules

Holli-Joi Martin, Cleber C. Melo-Filho, Daniel Korn, Richard T. Eastman, Ganesha Rai, Anton Simeonov, Alexey V. Zakharov, Eugene Muratov, Alexander Tropsha

Summary: We have created a database called SMACC that includes chemogenomics data from ChEMBL for 13 emerging viruses. By solving annotation accuracy challenges, we have collected data for over 32,500 compounds with antiviral properties. This database provides valuable reference for researchers in developing novel drugs to prevent future viral outbreaks.

ANTIVIRAL RESEARCH (2023)

Article Chemistry, Medicinal

Cheminformatics-driven discovery of hit compounds against Paracoccidioides spp.

Amanda Alves de Oliveira, Livia do Carmo Silva, Bruno Junior Neves, Vinicius Alexandre Fiaia Costa, Eugene N. Muratov, Carolina Horta Andrade, Celia Maria de Almeida Soares, Vinicius M. Alves, Maristela Pereira

Summary: This study aims to discover new anti-Paracoccidioides compounds through computational strategies. The researchers collected and curated a library of compounds tested against Paracoccidioides spp., conducted experimental evaluations, and used computational tools to identify potential targets for the most active compounds. Seven compounds showed activity against Paracoccidioides spp., making them potential candidates for developing new compounds.

FUTURE MEDICINAL CHEMISTRY (2023)

Article Chemistry, Medicinal

Multitask learning-driven identification of novel antitrypanosomal compounds

Jade Milhomem Lemos, Meryck Felipe Brito da Silva, Alexandra Maria dos Santos Carvalho, Henric Pietro Vicente Gil, Vinicius Alexandre Fiaia Costa, Carolina Horta Andrade, Rodolpho Campos Braga, Philippe Grellier, Eugene N. Muratov, Sebastien Charneau, Jose Teofilo Moreira-Filho, Izabela Marques Dourado Bastos, Bruno Junior Neves

Summary: This study created an explainable multitask pipeline to profile the activity of compounds against three trypanosomes, successfully discovering four new experimental hits, among which LC-6 showed promising results. The results demonstrate that the multitask protocol offers predictivity and interpretability in virtual screening, potentially improving hit rates in Chagas and human African trypanosomiasis projects.

FUTURE MEDICINAL CHEMISTRY (2023)

Article Chemistry, Medicinal

Allosteric Binders of ACE2 Are Promising Anti-SARS-CoV-2 Agents

Joshua E. Hochuli, Sankalp Jain, Cleber Melo-Filho, Zoe L. Sessions, Tesia Bobrowski, Jun Choe, Johnny Zheng, Richard Eastman, Daniel C. Talley, Ganesha Rai, Anton Simeonov, Alexander Tropsha, Eugene N. Muratov, Bolormaa Baljinnyam, Alexey Zakharov

Summary: This study investigates whether compounds that bind the human angiotensin-converting enzyme 2 (ACE2) protein can reduce SARS-CoV-2 replication without affecting ACE2's enzymatic function. Through screening and in silico techniques, 73 ACE2 binders were identified, and five of them were found to inhibit the viral life cycle in human cells. These compounds serve as valuable starting points for the development of acute treatments for COVID-19 and research into host-directed therapy.

ACS PHARMACOLOGY & TRANSLATIONAL SCIENCE (2022)

Article Chemistry, Medicinal

Annonaceae Terpenoids as Potential Leishmanicidal Agents

Renata Priscila Barros de Menezes, Josean Fechine Tavares, Massuo Jorge Kato, Francisco Alex da Rocha Coelho, Holli-Joi Martin, Eugene Muratov, Airton Lucas Sousa dos Santos, Klinger Antonio da Franca Rodrigues, Luciana Scotti, Marcus Tullius Scotti

Summary: Leishmaniasis is a neglected tropical disease with outdated and variable drug treatments. This study utilized predictive models to screen potentially active compounds from specialized metabolites of Annonaceae against Leishmania amazonensis. Several substances showed leishmanicidal activity, with lupeol exhibiting the best activity. These findings hold promise for the development of new therapeutical agents for leishmaniasis based on natural products.

REVISTA BRASILEIRA DE FARMACOGNOSIA-BRAZILIAN JOURNAL OF PHARMACOGNOSY (2022)

Article Biochemistry & Molecular Biology

Computer-Assisted Discovery of Alkaloids with Schistosomicidal Activity

Renata Priscila Barros de Menezes, Jessika de Oliveira Viana, Eugene Muratov, Luciana Scotti, Marcus Tullius Scotti

Summary: This study combined ligand-based and structure-based virtual screening techniques to select five potentially active alkaloids against S. mansoni. Two of these alkaloids showed plausible toxicity, metabolomics, and toxicity profiles, making them promising candidates for the development of new schistosomicidal compounds based on natural products.

CURRENT ISSUES IN MOLECULAR BIOLOGY (2022)

No Data Available