scholarly journals A widespread role for SLC transmembrane transporters in resistance to cytotoxic drugs

2019 ◽  
Author(s):  
Enrico Girardi ◽  
Adrián César-Razquin ◽  
Konstantinos Papakostas ◽  
Sabrina Lindinger ◽  
Justyna Konecka ◽  
...  
Keyword(s):  
Chemical Space ◽  
Functional Dependence ◽  
Significant Proportion ◽  
Nucleoside Analogs ◽  
Human Cell Line ◽  
Cellular Systems ◽  
Cytotoxic Drugs ◽  
Artemisinin Derivatives ◽  
Approved Drugs ◽  
Transmembrane Transporters

AbstractThe activity and potency of a drug is inherently affected by the metabolic state of its target cell. Solute Carriers (SLCs) represent the largest family of transmembrane transporters in humans and constitute major determinants of cellular metabolism. Several SLCs have been shown to be required for the uptake of individual chemical compounds into cellular systems, but systematic surveys of transporter-drug relationships in human cells are currently lacking. We performed a series of genetic screens in the haploid human cell line HAP1 using a set of 60 cytotoxic compounds representative of the chemical space populated by approved drugs. By using a SLC-focused CRISPR/Cas9 lentiviral library, we identified transporters whose absence induced resistance to the drugs tested. Among the hundreds of drug-SLC relationships identified, we confirmed the role of the folate transporter SLC19A1 on the activity of antifolates and of SLC29A1 on several nucleoside analogs. Among the newly discovered dependencies, we identified the transporters SLC11A2/SLC16A1 for artemisinin derivatives and SLC35A2/SLC38A5 for cisplatin. The functional dependence on SLCs observed for a significant proportion of the compounds screened suggested a widespread role for SLCs in the uptake and cellular activity of cytotoxic drugs and provided an experimentally validated set of SLC-drug associations for a number of clinically relevant compounds.

scholarly journals The Brazilian Compound Library (BraCoLi) Database: A Brazilian Repository of Chemical and Biological Information for Drug Design

2021 ◽  
Author(s):  
Gabriel Corrêa Veríssimo ◽  
Valtair Severino dos Santos Junior ◽  
Ingrid Ariela do Rosário de Almeida ◽  
Marina Sant'Anna Mitraud Ruas ◽  
Lukas Galuppo Coutinho ◽  
...  
Keyword(s):  
Drug Design ◽  
Chemical Space ◽  
Principal Component ◽  
Chemical Diversity ◽  
Biological Information ◽  
Virtual Library ◽  
Compound Library ◽  
Computer Aided Drug Design ◽  
Approved Drugs ◽  
Fda Approved Drugs

The Brazilian Compound Library (BraCoLi) is a novel virtual library of manually curated compounds developed by Brazilian research groups to support further computer-aided drug design works. Herein, the first version of the database is described comprising 1,176 compounds. Also, the chemical diversity and drug-like profile of BraCoLi were defined to analyze its chemical space. A significant amount of the compounds fitted Lipinski and Veber’s rules, alongside other drug-likeness properties. Principal component analysis showed that BraCoLi is similar to other databases (FDA-approved drugs and NuBBEDB) regarding structural and physicochemical patterns. Finally, a scaffold analysis showed that BraCoLi presents several privileged chemical skeletons with great diversity.

scholarly journals Combinatorial drug discovery in nanoliter droplets

2018 ◽  
Vol 115 (26) ◽  
pp. 6685-6690 ◽  
Author(s):  
Anthony Kulesa ◽  
Jared Kehe ◽  
Juan E. Hurtado ◽  
Prianca Tawde ◽  
Paul C. Blainey
Keyword(s):  
Biological Networks ◽  
Chemical Space ◽  
Treatment Strategies ◽  
Therapeutic Effects ◽  
Phenotypic Screening ◽  
Chemical Library ◽  
Gram Negative ◽  
Gram Positive Bacteria ◽  
Approved Drugs ◽  
Advanced Treatments

Combinatorial drug treatment strategies perturb biological networks synergistically to achieve therapeutic effects and represent major opportunities to develop advanced treatments across a variety of human disease areas. However, the discovery of new combinatorial treatments is challenged by the sheer scale of combinatorial chemical space. Here, we report a high-throughput system for nanoliter-scale phenotypic screening that formulates a chemical library in nanoliter droplet emulsions and automates the construction of chemical combinations en masse using parallel droplet processing. We applied this system to predict synergy between more than 4,000 investigational and approved drugs and a panel of 10 antibiotics againstEscherichia coli, a model gram-negative pathogen. We found a range of drugs not previously indicated for infectious disease that synergize with antibiotics. Our validated hits include drugs that synergize with the antibiotics vancomycin, erythromycin, and novobiocin, which are used against gram-positive bacteria but are not effective by themselves to resolve gram-negative infections.

scholarly journals A general approach for retrosynthetic molecular core analysis

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
J. Jesús Naveja ◽  
B. Angélica Pilón-Jiménez ◽  
Jürgen Bajorath ◽  
José L. Medina-Franco
Keyword(s):  
Single Molecule ◽  
Chemical Space ◽  
Significant Proportion ◽  
Bipartite Network ◽  
Data Sets ◽  
Structure Property ◽  
Data Set ◽  
Chemical Structures ◽  
Structure Property Relationships ◽  
Analog Series

Abstract Scaffold analysis of compound data sets has reemerged as a chemically interpretable alternative to machine learning for chemical space and structure–activity relationships analysis. In this context, analog series-based scaffolds (ASBS) are synthetically relevant core structures that represent individual series of analogs. As an extension to ASBS, we herein introduce the development of a general conceptual framework that considers all putative cores of molecules in a compound data set, thus softening the often applied “single molecule–single scaffold” correspondence. A putative core is here defined as any substructure of a molecule complying with two basic rules: (a) the size of the core is a significant proportion of the whole molecule size and (b) the substructure can be reached from the original molecule through a succession of retrosynthesis rules. Thereafter, a bipartite network consisting of molecules and cores can be constructed for a database of chemical structures. Compounds linked to the same cores are considered analogs. We present case studies illustrating the potential of the general framework. The applications range from inter- and intra-core diversity analysis of compound data sets, structure–property relationships, and identification of analog series and ASBS. The molecule–core network herein presented is a general methodology with multiple applications in scaffold analysis. New statistical methods are envisioned that will be able to draw quantitative conclusions from these data. The code to use the method presented in this work is freely available as an additional file. Follow-up applications include analog searching and core structure–property relationships analyses.

Screening Thousands of Drugs in Leukemia Patient Samples to Identify Novel Uses for Approved Drugs.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 4414-4414
Author(s):  
Teresa A Bennett ◽  
Sandra Sapia ◽  
Daniel Primo ◽  
Lilia Suarez ◽  
Santiago Lago ◽  
...  
Keyword(s):  
B Cell ◽  
Research Funding ◽  
Ex Vivo ◽  
Lymphocytic Leukemia ◽  
Cytotoxic Drugs ◽  
Intravenous Bolus ◽  
Malignant Cells ◽  
B Cell Malignancies ◽  
Technology Platform ◽  
Approved Drugs

Abstract Abstract 4414 Introduction Discovery of novel non cytotoxic drugs for cancer focuses on targets selectively expressed in malignant cells, only testing at the end if they are toxic to patients. We have developed a novel approach to discover these drugs starting at the end; we screen 2.000 approved drugs with proven safety, directly on freshly extracted (ex vivo) blood samples of patients with Chronic Lymphocytic Leukemia (CLL). These screens are enabled by a novel technology platform based on automated flow cytometry we call ExviTech for ex vivo technology. Patients and Methods All screening studies were performed directly on either peripheral blood or bone marrow samples from 44 patients diagnosed with various subtypes of B-cell malignancies, after informed consent. Patient samples were diluted and plated with each of the 2.000 drugs individually, retaining the erythrocyte population and serum proteins to enable clinically relevant concentrations. The experimental assay was setup the same or a day after sample extraction. Each sample was diluted to achieve a leukemic cell concentration of approximately 3,000 cells/μl; then 45μl of the suspension is added to each well of 96-well plates that contain the pharmacological agents (final concentration of 30μM). The compound plates were then sequentially incubated for 24 hours at 37°C with 5% CO2 for screening (sterile conditions). After incubation, the erythrocytes were lysed and the leucocytes incubated with Annexin V-FITC, anti-CD45-APC and anti-CD19-PE added to each well. The plates were then transferred to an automated flow cytometry system where the contents of each well were aspirated and analyzed by a CyAn flow cytometer. Candidates from the primary screens were validated in additional samples with dose-responses, combinations with approved drugs, multiple incubation times, etc… Results Analyzing primary screens from 24 CLL patients, three related compounds (Vivia007, Vivia008 and Vivia009) were found to consistently induce apoptosis of nearly all leukemic B-cells from most of the patient samples diagnosed with B-cell chronic lymphocytic leukemia at levels equal to or greater than known CLL active cytotoxic agents. Notably, these candidates are equally effective against samples of p53 mutated patients. These 3 drugs are pharmacologically me-too drugs sharing the same target and mechanism of action, and are non cytotoxic drugs with a known and good safety profile, administered to millions of patients over many years. Validation experiments were done on 20 additional CLL patients and Vivia009 emerged as the most effective agent with an average EC50 of 18.2μM. The mechanism of action is different than the known mechanism of Vivia009 and its class members for their approved indications. Consistent with this observation, only 3 of 15 members of the same pharmacological drug class were efficacious against CLL malignant cells. All 3 Vivia′s candidates were equally efficacious against other B-Cell Malignancies such as B-ALL (pediatric and adult), and Multiple Myeloma. These drugs are not effective in their current oral formulation and require a novel intravenous formulation. Interestingly, kinetics of induction of apoptosis were faster for Vivia009 than for fludarabine, cyclophosphamide and mitoxantrone. Vivia009 requires only 1 hour of incubation with fresh cells to induce maximal apoptosis. This timeline is less than the 3 hours in which Vivia009 was found present at high concentrations in bone marrow of rats using a single intravenous bolus. Thus, Vivia009 seems to fulfill the pharmacokinetic criteria to eliminate all leukemic cells with a single intravenous bolus, which would be a major advantage over current treatments (5-days fludarabine or 3 days FCR). Animal models are ongoing to confirm the non cytotoxic nature of the candidates in the novel IV formulation and the fewer days needed to reach remission, both compared with fludarabine monotherapy. Conclusions In summary, our results demonstrate the potential of the ExviTech technology platform as a successful model for the systematic search of new uses for already existing approved drugs directly on patient samples of hematological malignancies. A new drug candidate with excellent safety profile has been identified with similar efficacy ex vivo as the best approved cytotoxic drugs, which is a non-cytotoxic drug with fast kinetics that might enable significantly safer and shorter treatments. Disclosures: Bennett: Vivia Biotech: Employment. Sapia:Vivia Biotech SL: Employment. Primo:Vivia Biotech SL: Employment. Suarez:Vivia Biotech SL: Employment. Lago:Vivia Biotech SL: Employment. Matoses:Vivia Biotech: Employment. Espinosa:Vivia Biotech: Ana Espinosa, Employment. Tudela:Vivia Biotech SL: Employment. Arroyo:Vivia Biotech SL: Employment. Jackson:Vivia Biotech SL: Employment. Okun:Vivia Biotech SL: Research Funding. Lopez:Vivia Biotech SL: Employment. Gornemann:Vivia Biotech SL: Employment. Diez:Vivia Biotech SL: Employment. González:Vivia Biotech SL: Consultancy. Dominguez-Gil:Vivia Biotech SL: Consultancy. Troconiz:Vivia Biotech SL: Consultancy. Rodriguez de Fonseca:Vivia Biotech SL: Consultancy. Saunders:Vivia Biotech: Consultancy. Montejo:Vivia Biotech SL: Consultancy. Caveda:Vivia Biotech SL: Employment. Orfao:Vivia Biotech SL: Research Funding. Ballesteros:Vivia Biotech SL: Equity Ownership.

scholarly journals Combinatorial Drug Discovery in Nanoliter Droplets

2017 ◽  
Author(s):  
Anthony Kulesa ◽  
Jared Kehe ◽  
Juan Hurtado ◽  
Prianca Tawde ◽  
Paul C. Blainey
Keyword(s):  
Biological Networks ◽  
Chemical Space ◽  
Treatment Strategies ◽  
Therapeutic Effects ◽  
Chemical Library ◽  
Gram Negative ◽  
E Coli ◽  
Gram Positive Bacteria ◽  
Approved Drugs ◽  
Advanced Treatments

AbstractCombinatorial drug treatment strategies perturb biological networks synergistically to achieve therapeutic effects and represent major opportunities to develop advanced treatments across a variety of human disease areas. However, the discovery of new combinatorial treatments is challenged by the sheer scale of combinatorial chemical space. Here we report a high-throughput system for nanoliter-scale phenotypic screening that stabilizes a chemical library in nanoliter droplet emulsions and automates the formulation of chemical combinationsen massusing parallel droplet processing. We apply this system to predict synergy between more than 4,000 investigational and approved drugs and a panel of 10 antibiotics againstE. coli, a model Gram-negative pathogen. We found a range of drugs not previously indicated for infectious disease that synergize with antibiotics. Our validated hits include drugs that synergize with the antibiotics vancomycin, erythromycin, and novobiocin, which are used against Gram-positive bacteria but are not effective by themselves to resolve Gram-negative infections.

scholarly journals Yeast Models for Amyloids and Prions: Environmental Modulation and Drug Discovery

Molecules ◽  
2019 ◽  
Vol 24 (18) ◽  
pp. 3388 ◽  
Author(s):  
Tatiana A. Chernova ◽  
Yury O. Chernoff ◽  
Keith D. Wilkinson
Keyword(s):  
Neurodegenerative Diseases ◽  
High Throughput Screening ◽  
Protein Quality ◽  
Ubiquitin Proteasome System ◽  
Cellular Systems ◽  
Protein Isoforms ◽  
Pharmacological Intervention ◽  
Amyloid Formation ◽  
Yeast Prions ◽  
Approved Drugs

Amyloids are self-perpetuating protein aggregates causing neurodegenerative diseases in mammals. Prions are transmissible protein isoforms (usually of amyloid nature). Prion features were recently reported for various proteins involved in amyloid and neural inclusion disorders. Heritable yeast prions share molecular properties (and in the case of polyglutamines, amino acid composition) with human disease-related amyloids. Fundamental protein quality control pathways, including chaperones, the ubiquitin proteasome system and autophagy are highly conserved between yeast and human cells. Crucial cellular proteins and conditions influencing amyloids and prions were uncovered in the yeast model. The treatments available for neurodegenerative amyloid-associated diseases are few and their efficiency is limited. Yeast models of amyloid-related neurodegenerative diseases have become powerful tools for high-throughput screening for chemical compounds and FDA-approved drugs that reduce aggregation and toxicity of amyloids. Although some environmental agents have been linked to certain amyloid diseases, the molecular basis of their action remains unclear. Environmental stresses trigger amyloid formation and loss, acting either via influencing intracellular concentrations of the amyloidogenic proteins or via heterologous inducers of prions. Studies of environmental and physiological regulation of yeast prions open new possibilities for pharmacological intervention and/or prophylactic procedures aiming on common cellular systems rather than the properties of specific amyloids.

scholarly journals RNA-Targeting Splicing Modifiers: Drug Development and Screening Assays

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2263
Author(s):  
Zhichao Tang ◽  
Junxing Zhao ◽  
Zach J. Pearson ◽  
Zarko V. Boskovic ◽  
Jingxin Wang
Keyword(s):  
Small Molecule ◽  
Rna Splicing ◽  
Messenger Rna ◽  
Drug Targets ◽  
Chemical Space ◽  
Muscular Atrophy ◽  
Screening Methods ◽  
Pathogenic Genes ◽  
Rna Targeting ◽  
Approved Drugs

RNA splicing is an essential step in producing mature messenger RNA (mRNA) and other RNA species. Harnessing RNA splicing modifiers as a new pharmacological modality is promising for the treatment of diseases caused by aberrant splicing. This drug modality can be used for infectious diseases by disrupting the splicing of essential pathogenic genes. Several antisense oligonucleotide splicing modifiers were approved by the U.S. Food and Drug Administration (FDA) for the treatment of spinal muscular atrophy (SMA) and Duchenne muscular dystrophy (DMD). Recently, a small-molecule splicing modifier, risdiplam, was also approved for the treatment of SMA, highlighting small molecules as important warheads in the arsenal for regulating RNA splicing. The cellular targets of these approved drugs are all mRNA precursors (pre-mRNAs) in human cells. The development of novel RNA-targeting splicing modifiers can not only expand the scope of drug targets to include many previously considered “undruggable” genes but also enrich the chemical-genetic toolbox for basic biomedical research. In this review, we summarized known splicing modifiers, screening methods for novel splicing modifiers, and the chemical space occupied by the small-molecule splicing modifiers.

scholarly journals A widespread role for SLC transmembrane transporters in resistance to cytotoxic drugs

2020 ◽  
Vol 16 (4) ◽  
pp. 469-478 ◽  
Author(s):  
Enrico Girardi ◽  
Adrián César-Razquin ◽  
Sabrina Lindinger ◽  
Konstantinos Papakostas ◽  
Justyna Konecka ◽  
...  
Keyword(s):  
Cytotoxic Drugs ◽  
Transmembrane Transporters

scholarly journals Predicting protein targets for drug-like compounds using transcriptomics

2018 ◽  
Author(s):  
Nicolas A. Pabon ◽  
Yan Xia ◽  
Samuel K. Estabrooks ◽  
Zhaofeng Ye ◽  
Amanda K. Herbrand ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Network Effects ◽  
Chemical Space ◽  
Target Prediction ◽  
Cell Types ◽  
Supervised Machine Learning ◽  
Human Interactome ◽  
Protein Targets ◽  
Drug Treatments ◽  
Approved Drugs

AbstractThe development of an expanded chemical space for screening is an essential step in the challenge of identifying chemical probes for new, genomic-era protein targets. However, the difficulty of identifying targets for novel compounds leads to the prioritization of synthesis linked to known active scaffolds that bind familiar protein families, slowing the exploration of available chemical space. To change this paradigm, we validated a new pipeline capable of identifying compound-protein interactions even for compounds with no similarity to known drugs. Based on differential mRNA profiles from drug treatments and gene knockdowns across multiple cell types, we show that drugs cause gene regulatory network effects that correlate with those produced by silencing their target protein-coding gene. Applying supervised machine learning to exploit compound-knockdown signature correlations and enriching our predictions using an orthogonal structure-based screen, we achieved top-10/top-100 target prediction accuracies of 26%/41%, respectively, on a validation set 152 FDA-approved drugs and 3104 potential targets. We further predicted targets for 1680 compounds and validated a total of seven novel interactions with four difficult targets, including non-covalent modulators of HRAS and KRAS. We found that drug-target interactions manifest as gene expression correlations between drug treatment and both target gene knockdown and up/down-stream knockdowns. These correlations provide biologically relevant insight on the cell-level impact of disrupting protein interactions, highlighting the complex genetic phenotypes of drug treatments. Our pipeline can accelerate the identification and development of novel chemistries with potential to become drugs by screening for compound-target interactions in the full human interactome.

scholarly journals DNMT3A harboring leukemia-associated mutations directs sensitivity to DNA damage at replication forks

2021 ◽  
Author(s):  
Kartika Venugopal ◽  
Pawel Nowialis ◽  
Yang Feng ◽  
Daniil E Shabashvili ◽  
Cassandra M Berntsen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Dna Damage ◽  
Replication Fork ◽  
Dna Methyltransferase ◽  
De Novo ◽  
Nucleoside Analogs ◽  
Cellular Systems ◽  
Double Labeling ◽  
In Cells

Mutations in the DNA methyltransferase 3A (DNMT3A) gene are recurrent in de novo acute myeloid leukemia (AML) and are associated with resistance to standard chemotherapy, disease relapse, and poor prognosis, especially in advanced-age patients. Previous gene expression studies in cells with DNMT3A mutations identified deregulation of cell cycle-related signatures implicated in DNA damage response and replication fork integrity, suggesting sensitivity to replication stress. Here we tested whether pharmacologically-induced replication fork stalling creates a therapeutic vulnerability in cells with DNMT3A(R882) mutations. We observed increased sensitivity to nucleoside analogs such as cytarabine in multiple cellular systems expressing mutant DNMT3A, ectopically or endogenously, in vitro and in vivo. Analysis of DNA damage signaling in response to cytarabine revealed persistent intra-S phase checkpoint activation, accompanied by accumulation of DNA damage in the DNMT3A(R882) overexpressing cells, which was only partially resolved after drug removal and carried through mitosis, resulting in micronucleation. Pulse-chase double-labeling experiments with EdU and BrdU after cytarabine wash-out demonstrated that cells with DNMT3A(mut) were able to restart replication but showed a higher rate of fork collapse. Gene expression profiling by RNA-seq identified deregulation of pathways associated with cell cycle progression and p53 activation, as well as metabolism and chromatin. Together, our studies show that cells with DNMT3A mutations have a defect in recovery from replication fork arrest and subsequent accumulation of unresolved DNA damage, which may have therapeutic tractability. These results demonstrate that, in addition to its role in epigenetic control, DNMT3A contributes to preserving genome integrity during DNA replication.

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