Pub Date : 2023-10-30DOI: 10.3389/fddsv.2023.1289314
Manisha Padmakumar, Steven Biesmans, Jorge S. Valadas, Jan R. Detrez, Gaëlle Gillet, Priscillia Bresler, Marie-Laure Clénet, Irena Kadiu
Neuroscience drug discovery has faced significant challenges due to restricted access to relevant human cell models and limited translatability of existing preclinical findings to human pathophysiology. Induced pluripotent stem cells (iPSCs) have emerged as a promising solution, offering the potential to generate patient-specific cell types, including in the recent years, iPSC-derived microglia (iMGL). Current methods rely on complex and time-consuming differentiation procedures, leading to considerable batch-to-batch variability consequently hindering the establishment of standardized and reproducible high-throughput functional screening approaches. Addressing these challenges is critical in ensuring the generation of homogenous iMGL populations with consistent functional properties. In this study we describe an improved high-yield protocol for generating iMGL, which allows for increased reproducibility and flexibility in the execution of high-throughput functional screens. We introduce a two-step process in embryoid bodie (EB) maintenance and a stop point allowing for cryopreservation at the hematopoietic progenitor cell (iHPC) stages. Furthermore, we demonstrate inter-operator robustness of this modified protocol in a range of high-throughput functional assays including phagocytosis, lysosomal acidification, chemotaxis, and cytokine release. Our study underscores the importance of quality control checks at various stages of iPSC-differentiation and functional assay set up, highlighting novel workarounds to the existing challenges such as limited yield, flexibility, and reproducibility, all critical in drug discovery.
{"title":"An improved method for large scale generation and high-throughput functional characterization of human iPSC-derived microglia","authors":"Manisha Padmakumar, Steven Biesmans, Jorge S. Valadas, Jan R. Detrez, Gaëlle Gillet, Priscillia Bresler, Marie-Laure Clénet, Irena Kadiu","doi":"10.3389/fddsv.2023.1289314","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1289314","url":null,"abstract":"Neuroscience drug discovery has faced significant challenges due to restricted access to relevant human cell models and limited translatability of existing preclinical findings to human pathophysiology. Induced pluripotent stem cells (iPSCs) have emerged as a promising solution, offering the potential to generate patient-specific cell types, including in the recent years, iPSC-derived microglia (iMGL). Current methods rely on complex and time-consuming differentiation procedures, leading to considerable batch-to-batch variability consequently hindering the establishment of standardized and reproducible high-throughput functional screening approaches. Addressing these challenges is critical in ensuring the generation of homogenous iMGL populations with consistent functional properties. In this study we describe an improved high-yield protocol for generating iMGL, which allows for increased reproducibility and flexibility in the execution of high-throughput functional screens. We introduce a two-step process in embryoid bodie (EB) maintenance and a stop point allowing for cryopreservation at the hematopoietic progenitor cell (iHPC) stages. Furthermore, we demonstrate inter-operator robustness of this modified protocol in a range of high-throughput functional assays including phagocytosis, lysosomal acidification, chemotaxis, and cytokine release. Our study underscores the importance of quality control checks at various stages of iPSC-differentiation and functional assay set up, highlighting novel workarounds to the existing challenges such as limited yield, flexibility, and reproducibility, all critical in drug discovery.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":"110 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136067492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-18DOI: 10.3389/fddsv.2023.1254656
Adetutu Akinnuwesi, Samuel Egieyeh, Ruben Cloete
Tuberculosis remains one of the causes of death from a single infectious bacterium. The inappropriate use of antibiotics and patients’ non-compliance among other factors drive the emergence of drug-resistant tuberculosis. Multidrug-resistant and extensively drug-resistant strains of tuberculosis pose significant challenges to current treatment regimens, as their reduced efficacy against these strains limits successful patient outcomes. Furthermore, the limited effectiveness and associated toxicity of second-line drugs further compound the issue. Moreover, the scarcity of novel pharmacological targets and the subsequent decline in the number of anti-TB compounds in the drug development pipeline has further hindered the emergence of new therapies. As a result, researchers need to develop innovative approaches to identify potential new anti-TB drugs. The evolution of technology and the breakthrough in omics data allow the use of computational biology approaches, for example, metabolomic analysis to uncover pharmacological targets for structured-based drug design. The role of metabolism in pathogen development, growth, survival, and infection has been established. Therefore, this review focuses on the M. tb metabolic network as a hub for novel target identification and highlights a step-by-step subtractive genomics approach for target prioritization.
{"title":"State-of-the-art strategies to prioritize Mycobacterium tuberculosis drug targets for drug discovery using a subtractive genomics approach","authors":"Adetutu Akinnuwesi, Samuel Egieyeh, Ruben Cloete","doi":"10.3389/fddsv.2023.1254656","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1254656","url":null,"abstract":"Tuberculosis remains one of the causes of death from a single infectious bacterium. The inappropriate use of antibiotics and patients’ non-compliance among other factors drive the emergence of drug-resistant tuberculosis. Multidrug-resistant and extensively drug-resistant strains of tuberculosis pose significant challenges to current treatment regimens, as their reduced efficacy against these strains limits successful patient outcomes. Furthermore, the limited effectiveness and associated toxicity of second-line drugs further compound the issue. Moreover, the scarcity of novel pharmacological targets and the subsequent decline in the number of anti-TB compounds in the drug development pipeline has further hindered the emergence of new therapies. As a result, researchers need to develop innovative approaches to identify potential new anti-TB drugs. The evolution of technology and the breakthrough in omics data allow the use of computational biology approaches, for example, metabolomic analysis to uncover pharmacological targets for structured-based drug design. The role of metabolism in pathogen development, growth, survival, and infection has been established. Therefore, this review focuses on the M. tb metabolic network as a hub for novel target identification and highlights a step-by-step subtractive genomics approach for target prioritization.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135203072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-05DOI: 10.3389/fddsv.2023.1249507
Hannah J. Gleneadie, Andrew Dimond, Amanda G. Fisher
The naturally occurring phenomenon of bioluminescence has intrigued on-lookers for decades and is now being developed as a powerful tool for medical research and preclinical imaging. Luciferase enzymes emit light upon substrate encounter, enabling their activity to be visualised and dynamically tracked. By inserting luciferase genes into specific sites in the genome, it is possible to engineer reporters to monitor gene expression in its native context, and to detect epigenetic change in vivo. Endogenous bioluminescent reporters provide a highly sensitive, quantitative read-out of gene expression that is both well suited to longitudinal studies and can be adapted for high-throughput drug screens. In this article we outline some of the applications and benefits of bioluminescent reporters for epigenetic research, with a particular focus on revealing new therapeutic options for treating genetic and epigenetic disorders.
{"title":"Harnessing bioluminescence for drug discovery and epigenetic research","authors":"Hannah J. Gleneadie, Andrew Dimond, Amanda G. Fisher","doi":"10.3389/fddsv.2023.1249507","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1249507","url":null,"abstract":"The naturally occurring phenomenon of bioluminescence has intrigued on-lookers for decades and is now being developed as a powerful tool for medical research and preclinical imaging. Luciferase enzymes emit light upon substrate encounter, enabling their activity to be visualised and dynamically tracked. By inserting luciferase genes into specific sites in the genome, it is possible to engineer reporters to monitor gene expression in its native context, and to detect epigenetic change in vivo. Endogenous bioluminescent reporters provide a highly sensitive, quantitative read-out of gene expression that is both well suited to longitudinal studies and can be adapted for high-throughput drug screens. In this article we outline some of the applications and benefits of bioluminescent reporters for epigenetic research, with a particular focus on revealing new therapeutic options for treating genetic and epigenetic disorders.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44486379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-03DOI: 10.3389/fddsv.2023.1216516
I-Yen Lin, P. Rupert, K. Pilat, Raymond O. Ruff, D. Friend, M. Chan, Midori Clarke, B. Hoffstrom, Jane Carter, S. Meshinchi, A. Bandaranayake, C. Mehlin, James M. Olson, R. Strong, C. Correnti
Mesothelin is a glypiated, cell-surface glycoprotein expressed at low levels on normal mesothelium but overexpressed by many cancers. Implicated in cell adhesion and multiple signaling pathways, mesothelin’s precise biological function and overall structure remain undefined. Antibodies targeting mesothelin have been engineered into immunotoxins, antibody-drug conjugates, CAR-T cells, or bispecific T cell engagers as candidate therapeutics but most face challenges, including binding epitopes that are not optimal for selected modalities. Here we describe the isolation and characterization of a novel anti-mesothelin antibody, 1A12, including crystallographic mapping of the 1A12 epitope in relation to other antibodies (amatuximab, anetumab). 1A12 possesses uniquely favorable properties, including a membrane-proximal epitope, and enabled structure determination of the complete mesothelin ectodomain. We incorporated 1A12 into two different bispecific T cell engaging architectures with various anti-CD3 co-targeting elements as candidate therapeutics, demonstrating in vitro functionality and potency.
{"title":"Novel mesothelin antibodies enable crystallography of the intact mesothelin ectodomain and engineering of potent, T cell-engaging bispecific therapeutics","authors":"I-Yen Lin, P. Rupert, K. Pilat, Raymond O. Ruff, D. Friend, M. Chan, Midori Clarke, B. Hoffstrom, Jane Carter, S. Meshinchi, A. Bandaranayake, C. Mehlin, James M. Olson, R. Strong, C. Correnti","doi":"10.3389/fddsv.2023.1216516","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1216516","url":null,"abstract":"Mesothelin is a glypiated, cell-surface glycoprotein expressed at low levels on normal mesothelium but overexpressed by many cancers. Implicated in cell adhesion and multiple signaling pathways, mesothelin’s precise biological function and overall structure remain undefined. Antibodies targeting mesothelin have been engineered into immunotoxins, antibody-drug conjugates, CAR-T cells, or bispecific T cell engagers as candidate therapeutics but most face challenges, including binding epitopes that are not optimal for selected modalities. Here we describe the isolation and characterization of a novel anti-mesothelin antibody, 1A12, including crystallographic mapping of the 1A12 epitope in relation to other antibodies (amatuximab, anetumab). 1A12 possesses uniquely favorable properties, including a membrane-proximal epitope, and enabled structure determination of the complete mesothelin ectodomain. We incorporated 1A12 into two different bispecific T cell engaging architectures with various anti-CD3 co-targeting elements as candidate therapeutics, demonstrating in vitro functionality and potency.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45451457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-25DOI: 10.3389/fddsv.2023.1237655
M. Serafim, S. Q. Pantaleão, E. B. da Silva, J. McKerrow, A. O’Donoghue, B. E. Mota, K. M. Honório, V. Maltarollo
Computer-Aided Drug Design (CADD) approaches, such as those employing quantitative structure-activity relationship (QSAR) methods, are known for their ability to uncover novel data from large databases. These approaches can help alleviate the lack of biological and chemical data, but some predictions do not generate sufficient positive information to be useful for biological screenings. QSAR models are often employed to explain biological data of chemicals and to design new chemicals based on their predictions. In this review, we discuss the importance of data set size with a focus on false hits for QSAR approaches. We assess the challenges and reliability of an initial in silico strategy for the virtual screening of bioactive molecules. Lastly, we present a case study reporting a combination approach of hologram-based quantitative structure-activity relationship (HQSAR) models and random forest-based QSAR (RF-QSAR), based on the 3D structures of 25 synthetic SARS-CoV-2 Mpro inhibitors, to virtually screen new compounds for potential inhibitors of enzyme activity. In this study, optimal models were selected and employed to predict Mpro inhibitors from the database Brazilian Compound Library (BraCoLi). Twenty-four compounds were then assessed against SARS-CoV-2 Mpro at 10 µM. At the time of this study (March 2021), the availability of varied and different Mpro inhibitors that were reported definitely affected the reliability of our work. Since no hits were obtained, the data set size, parameters employed, external validations, as well as the applicability domain (AD) could be considered regarding false hits data contribution, aiming to enhance the design and discovery of new bioactive molecules.
{"title":"The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study","authors":"M. Serafim, S. Q. Pantaleão, E. B. da Silva, J. McKerrow, A. O’Donoghue, B. E. Mota, K. M. Honório, V. Maltarollo","doi":"10.3389/fddsv.2023.1237655","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1237655","url":null,"abstract":"Computer-Aided Drug Design (CADD) approaches, such as those employing quantitative structure-activity relationship (QSAR) methods, are known for their ability to uncover novel data from large databases. These approaches can help alleviate the lack of biological and chemical data, but some predictions do not generate sufficient positive information to be useful for biological screenings. QSAR models are often employed to explain biological data of chemicals and to design new chemicals based on their predictions. In this review, we discuss the importance of data set size with a focus on false hits for QSAR approaches. We assess the challenges and reliability of an initial in silico strategy for the virtual screening of bioactive molecules. Lastly, we present a case study reporting a combination approach of hologram-based quantitative structure-activity relationship (HQSAR) models and random forest-based QSAR (RF-QSAR), based on the 3D structures of 25 synthetic SARS-CoV-2 Mpro inhibitors, to virtually screen new compounds for potential inhibitors of enzyme activity. In this study, optimal models were selected and employed to predict Mpro inhibitors from the database Brazilian Compound Library (BraCoLi). Twenty-four compounds were then assessed against SARS-CoV-2 Mpro at 10 µM. At the time of this study (March 2021), the availability of varied and different Mpro inhibitors that were reported definitely affected the reliability of our work. Since no hits were obtained, the data set size, parameters employed, external validations, as well as the applicability domain (AD) could be considered regarding false hits data contribution, aiming to enhance the design and discovery of new bioactive molecules.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46875160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-20DOI: 10.3389/fddsv.2023.1138461
P. Wohlfart, Mounir Chehtane, E. Luna, R. Mehta, M. Korn, A. Konkar, U. Schwahn, S. Petry, N. Tennagels, M. Bielohuby
Introduction: 9-PAHSA belongs to a class of endogenous mammalian bioactive lipids, fatty acid esters of hydroxy fatty acids (FAHFA), that are present in circulation at nanomolar concentrations in mice and humans. Published preclinical data suggest beneficial effects of 9-PAHSA treatment on glucose metabolism as well as modulation of immune function. However, receptor molecules with high affinity towards these lipids have not been identified so far.Methods: In a broad screen of a panel of G protein-coupled receptors (GPCRs) we discovered that 9-PAHSA displays antagonist activity with an IC50 in the micromolar range on selected chemokine receptors, namely, CCR6, CCR7, CXCR4, and CXCR5. The potential immunomodulatory activities in a human cellular model of innate immunity were then investigated.Results and discussion: In our in vitro experiments, a weak anti-inflammatory potential for high concentrations of 9-PAHSA (10–100 µM) could be detected, as treatment reduced the LPS-induced secretion of certain chemokines, such as CXCL10, MIP-1 beta and MCP. Regarding metabolic effects, we re-investigated 9-PAHSA on glucose metabolism and insulin sensitivity in vitro and in mice confirming conclusions from our earlier study that FAHFAs lack glucoregulatory activity following an acute treatment. In conclusion, the specific interactions with a subset of chemokine receptors may contribute to weak anti-inflammatory properties of 9-PAHSA, but further studies are needed to confirm its in anti-inflammatory potential in vivo.
{"title":"9-PAHSA displays a weak anti-inflammatory potential mediated by specific antagonism of chemokine G protein-coupled receptors","authors":"P. Wohlfart, Mounir Chehtane, E. Luna, R. Mehta, M. Korn, A. Konkar, U. Schwahn, S. Petry, N. Tennagels, M. Bielohuby","doi":"10.3389/fddsv.2023.1138461","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1138461","url":null,"abstract":"Introduction: 9-PAHSA belongs to a class of endogenous mammalian bioactive lipids, fatty acid esters of hydroxy fatty acids (FAHFA), that are present in circulation at nanomolar concentrations in mice and humans. Published preclinical data suggest beneficial effects of 9-PAHSA treatment on glucose metabolism as well as modulation of immune function. However, receptor molecules with high affinity towards these lipids have not been identified so far.Methods: In a broad screen of a panel of G protein-coupled receptors (GPCRs) we discovered that 9-PAHSA displays antagonist activity with an IC50 in the micromolar range on selected chemokine receptors, namely, CCR6, CCR7, CXCR4, and CXCR5. The potential immunomodulatory activities in a human cellular model of innate immunity were then investigated.Results and discussion: In our in vitro experiments, a weak anti-inflammatory potential for high concentrations of 9-PAHSA (10–100 µM) could be detected, as treatment reduced the LPS-induced secretion of certain chemokines, such as CXCL10, MIP-1 beta and MCP. Regarding metabolic effects, we re-investigated 9-PAHSA on glucose metabolism and insulin sensitivity in vitro and in mice confirming conclusions from our earlier study that FAHFAs lack glucoregulatory activity following an acute treatment. In conclusion, the specific interactions with a subset of chemokine receptors may contribute to weak anti-inflammatory properties of 9-PAHSA, but further studies are needed to confirm its in anti-inflammatory potential in vivo.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47300131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-13DOI: 10.3389/fddsv.2023.1223140
Ankita Tehlan, A. Saha, S. Dhar
More than sesquicentennial years of malarial research, however the unique malarial parasite, Plasmodium still bewilders us with its atypical characteristic features. Elimination strategies, deeper knowledge of the parasite biology and pathways can help combat this global health concern that affects ∼250 million people annually. In this review, we unveil an unusual phenomenon observed in the parasite proteome, N-terminal extensions in proteins and highlight that the proteases that may be involved in their processing events, are potential candidates to target this pathogen. Plasmodium encodes larger proteins as compared to its eukaryotic counterparts with homology regions present in the C-terminus of the protein. In contrast, the function of unusual extensions in the N-terminus remains mostly elusive. This novelty observed in Plasmodium proteins is collated here with a focus on replication proteins. The plausible functions and prevalence of these extensions, despite the reduction in genome size, through the parasite evolution are also mentioned. We hypothesize that these extensions, propagated via the energy consuming cellular processes in the otherwise host-dependent obligate parasite, are beneficial to the parasite in ways that are yet to be explored. Consequently, targeting the proteolytic processing of these proteins and the involved proteases would serve as a new drug development regimen to tackle the emerging resistance in parasites to existing antimalarials.
{"title":"Targeting proteases and proteolytic processing of unusual N-terminal extensions of Plasmodium proteins: parasite peculiarity","authors":"Ankita Tehlan, A. Saha, S. Dhar","doi":"10.3389/fddsv.2023.1223140","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1223140","url":null,"abstract":"More than sesquicentennial years of malarial research, however the unique malarial parasite, Plasmodium still bewilders us with its atypical characteristic features. Elimination strategies, deeper knowledge of the parasite biology and pathways can help combat this global health concern that affects ∼250 million people annually. In this review, we unveil an unusual phenomenon observed in the parasite proteome, N-terminal extensions in proteins and highlight that the proteases that may be involved in their processing events, are potential candidates to target this pathogen. Plasmodium encodes larger proteins as compared to its eukaryotic counterparts with homology regions present in the C-terminus of the protein. In contrast, the function of unusual extensions in the N-terminus remains mostly elusive. This novelty observed in Plasmodium proteins is collated here with a focus on replication proteins. The plausible functions and prevalence of these extensions, despite the reduction in genome size, through the parasite evolution are also mentioned. We hypothesize that these extensions, propagated via the energy consuming cellular processes in the otherwise host-dependent obligate parasite, are beneficial to the parasite in ways that are yet to be explored. Consequently, targeting the proteolytic processing of these proteins and the involved proteases would serve as a new drug development regimen to tackle the emerging resistance in parasites to existing antimalarials.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45716501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.3389/fddsv.2023.1226727
Yojana Gadiya, V. Ioannidis, David Henderson, P. Gribbon, P. Rocca-Serra, V. Satagopam, Susanna-Assunta Sansone, Wei Gu
The drug discovery community faces high costs in bringing safe and effective medicines to market, in part due to the rising volume and complexity of data which must be generated during the research and development process. Fully utilising these expensively created experimental and computational data resources has become a key aim of scientists due to the clear imperative to leverage the power of artificial intelligence (AI) and machine learning-based analyses to solve the complex problems inherent in drug discovery. In turn, AI methods heavily rely on the quantity, quality, consistency, and scope of underlying training data. While pre-existing preclinical and clinical data cannot fully replace the need for de novo data generation in a project, having access to relevant historical data represents a valuable asset, as its reuse can reduce the need to perform similar experiments, therefore avoiding a “reinventing the wheel” scenario. Unfortunately, most suitable data resources are often archived within institutes, companies, or individual research groups and hence unavailable to the wider community. Hence, enabling the data to be Findable, Accessible, Interoperable, and Reusable (FAIR) is crucial for the wider community of drug discovery and development scientists to learn from the work performed and utilise the findings to enhance comprehension of their own research outcomes. In this mini-review, we elucidate the utility of FAIR data management across the drug discovery pipeline and assess the impact such FAIR data has made on the drug development process.
{"title":"FAIR data management: what does it mean for drug discovery?","authors":"Yojana Gadiya, V. Ioannidis, David Henderson, P. Gribbon, P. Rocca-Serra, V. Satagopam, Susanna-Assunta Sansone, Wei Gu","doi":"10.3389/fddsv.2023.1226727","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1226727","url":null,"abstract":"The drug discovery community faces high costs in bringing safe and effective medicines to market, in part due to the rising volume and complexity of data which must be generated during the research and development process. Fully utilising these expensively created experimental and computational data resources has become a key aim of scientists due to the clear imperative to leverage the power of artificial intelligence (AI) and machine learning-based analyses to solve the complex problems inherent in drug discovery. In turn, AI methods heavily rely on the quantity, quality, consistency, and scope of underlying training data. While pre-existing preclinical and clinical data cannot fully replace the need for de novo data generation in a project, having access to relevant historical data represents a valuable asset, as its reuse can reduce the need to perform similar experiments, therefore avoiding a “reinventing the wheel” scenario. Unfortunately, most suitable data resources are often archived within institutes, companies, or individual research groups and hence unavailable to the wider community. Hence, enabling the data to be Findable, Accessible, Interoperable, and Reusable (FAIR) is crucial for the wider community of drug discovery and development scientists to learn from the work performed and utilise the findings to enhance comprehension of their own research outcomes. In this mini-review, we elucidate the utility of FAIR data management across the drug discovery pipeline and assess the impact such FAIR data has made on the drug development process.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42341615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-07DOI: 10.3389/fddsv.2023.1181637
Marion T. J. van den Bosch, Bryony J. Telford, S. Yahyanejad, Thijs de Gunst, Harm C. den Boer, R. Vos, C. Duurland, R. Biemans, L. Dubois, L. V. van Pinxteren, R. Schaapveld, M. Janicot
As cancer is a multifactorial disease, the multimodal action of microRNAs makes them an attractive tool for novel therapeutic approaches. The tumor suppressive miR-7-5p has been shown to act on many aspects of oncogenesis, including cell proliferation, migration and angiogenesis, by targeting a spectrum of key genes. We developed a synthetic chemically modified miR-7-5p mimic, 5A2, and performed a comprehensive functional characterization in a panel of human cancer cell lines. 5A2 reduced cell proliferation in most cell lines by inducing cell cycle arrest. To enable systemic delivery of 5A2 to tumors, it was formulated in a novel lipid nanoparticle (INT-5A2) and we demonstrated the anti-tumor activity of INT-5A2 in an experimental human liver tumor-bearing mouse model. Next, RNA-sequencing was used to gain more insight into the molecular mechanism of action of 5A2 and demonstrated a broad repression of target mRNAs. Interestingly, Ingenuity Pathway Analysis revealed a new role for 5A2 in metabolic pathways. Validation experiments in vitro showed that 5A2 reduced the expression of key glycolysis and glutaminolysis enzymes, leading to a decrease in glycolysis, lactate secretion and intracellular glutamate availability. Taken together, these data strongly suggest that miR-7-5p/5A2 is a potent tumor suppressor that targets various key cellular pathways across cancer types. Therefore, 5A2 may represent a promising novel treatment strategy in oncology.
{"title":"The tumor suppressor 5A2, a synthetic miR-7-5p mimic, targets oncogenic and metabolic pathways, as revealed by transcriptome-wide analysis","authors":"Marion T. J. van den Bosch, Bryony J. Telford, S. Yahyanejad, Thijs de Gunst, Harm C. den Boer, R. Vos, C. Duurland, R. Biemans, L. Dubois, L. V. van Pinxteren, R. Schaapveld, M. Janicot","doi":"10.3389/fddsv.2023.1181637","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1181637","url":null,"abstract":"As cancer is a multifactorial disease, the multimodal action of microRNAs makes them an attractive tool for novel therapeutic approaches. The tumor suppressive miR-7-5p has been shown to act on many aspects of oncogenesis, including cell proliferation, migration and angiogenesis, by targeting a spectrum of key genes. We developed a synthetic chemically modified miR-7-5p mimic, 5A2, and performed a comprehensive functional characterization in a panel of human cancer cell lines. 5A2 reduced cell proliferation in most cell lines by inducing cell cycle arrest. To enable systemic delivery of 5A2 to tumors, it was formulated in a novel lipid nanoparticle (INT-5A2) and we demonstrated the anti-tumor activity of INT-5A2 in an experimental human liver tumor-bearing mouse model. Next, RNA-sequencing was used to gain more insight into the molecular mechanism of action of 5A2 and demonstrated a broad repression of target mRNAs. Interestingly, Ingenuity Pathway Analysis revealed a new role for 5A2 in metabolic pathways. Validation experiments in vitro showed that 5A2 reduced the expression of key glycolysis and glutaminolysis enzymes, leading to a decrease in glycolysis, lactate secretion and intracellular glutamate availability. Taken together, these data strongly suggest that miR-7-5p/5A2 is a potent tumor suppressor that targets various key cellular pathways across cancer types. Therefore, 5A2 may represent a promising novel treatment strategy in oncology.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43596813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-21DOI: 10.3389/fddsv.2023.1222655
Ana L. Chávez‐Hernández, E. López-López, J. Medina‐Franco
Chemical and biological data are the cornerstone of modern drug discovery programs. Finding qualitative yet better quantitative relationships between chemical structures and biological activity has been long pursued in medicinal chemistry and drug discovery. With the rapid increase and deployment of the predictive machine and deep learning methods, as well as the renewed interest in the de novo design of compound libraries to enlarge the medicinally relevant chemical space, the balance between quantity and quality of data are becoming a central point in the discussion of the type of data sets needed. Although there is a general notion that the more data, the better, it is also true that its quality is crucial despite the size of the data itself. Furthermore, the active versus inactive compounds ratio balance is also a major consideration. This review discusses the most common public data sets currently used as benchmarks to develop predictive and classification models used in de novo design. We point out the need to continue disclosing inactive compounds and negative data in peer-reviewed publications and public repositories and promote the balance between the positive (Yang) and negative (Yin) bioactivity data. We emphasize the importance of reconsidering drug discovery initiatives regarding both the utilization and classification of data.
{"title":"Yin-yang in drug discovery: rethinking de novo design and development of predictive models","authors":"Ana L. Chávez‐Hernández, E. López-López, J. Medina‐Franco","doi":"10.3389/fddsv.2023.1222655","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1222655","url":null,"abstract":"Chemical and biological data are the cornerstone of modern drug discovery programs. Finding qualitative yet better quantitative relationships between chemical structures and biological activity has been long pursued in medicinal chemistry and drug discovery. With the rapid increase and deployment of the predictive machine and deep learning methods, as well as the renewed interest in the de novo design of compound libraries to enlarge the medicinally relevant chemical space, the balance between quantity and quality of data are becoming a central point in the discussion of the type of data sets needed. Although there is a general notion that the more data, the better, it is also true that its quality is crucial despite the size of the data itself. Furthermore, the active versus inactive compounds ratio balance is also a major consideration. This review discusses the most common public data sets currently used as benchmarks to develop predictive and classification models used in de novo design. We point out the need to continue disclosing inactive compounds and negative data in peer-reviewed publications and public repositories and promote the balance between the positive (Yang) and negative (Yin) bioactivity data. We emphasize the importance of reconsidering drug discovery initiatives regarding both the utilization and classification of data.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47887205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：