scholarly journals In Silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization

2019 ◽  
Author(s):  
Maurice Michel ◽  
Evert J. Homan ◽  
Elisee Wiita ◽  
Kia Pedersen ◽  
Ingrid Almlöf ◽  
...  
Keyword(s):  
Ligand Binding ◽  
In Silico ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Large Scale ◽  
Protein Family ◽  
Nudix Hydrolase ◽  
In Silico Docking ◽  
Glide Docking ◽  
User Friendly

Computational chemistry has now been widely accepted as a useful tool for shortening lead times in early drug discovery. When selecting new potential drug targets, it is important to assess the likelihood of finding suitable starting points for lead generation before pursuing costly high-throughput screening campaigns. By exploiting available high-resolution crystal structures, an in silico druggability assessment can facilitate the decision of whether, and in cases where several protein family members exist, which of these to pursue experimentally. Many of the algorithms and software suites commonly applied for in silico druggability assessment are complex, technically challenging and not always user-friendly. Here we applied the intuitive open access servers of DoGSite, FTMap and CryptoSite to comprehensively predict ligand binding pockets, druggability scores and conformationally active regions of the NUDIX protein family. In parallel we analyzed potential ligand binding sites, their druggability and hydrophobic-hydrophilic ratio using Schrödinger’s SiteMap. Then an in silico docking cascade of a subset of the ZINC FragNow library using the Glide docking program was performed to assess identified pockets for large-scale small molecule binding. Subsequently, this initial dual ranking of druggable sites within the NUDIX protein family was benchmarked against experimental hit rates obtained both in-house and by others from traditional biochemical and fragment screening campaigns. The observed correlation suggests that the presented user-friendly workflow of a dual parallel in silico druggability assessment is applicable as a standalone method for decision on target prioritization in future screening campaigns. <br>

scholarly journals In Silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization

2019 ◽  
Author(s):  
Maurice Michel ◽  
Evert J. Homan ◽  
Elisee Wiita ◽  
Kia Pedersen ◽  
Ingrid Almlöf ◽  
...  
Keyword(s):  
Ligand Binding ◽  
In Silico ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Large Scale ◽  
Protein Family ◽  
Nudix Hydrolase ◽  
In Silico Docking ◽  
Glide Docking ◽  
User Friendly

Computational chemistry has now been widely accepted as a useful tool for shortening lead times in early drug discovery. When selecting new potential drug targets, it is important to assess the likelihood of finding suitable starting points for lead generation before pursuing costly high-throughput screening campaigns. By exploiting available high-resolution crystal structures, an in silico druggability assessment can facilitate the decision of whether, and in cases where several protein family members exist, which of these to pursue experimentally. Many of the algorithms and software suites commonly applied for in silico druggability assessment are complex, technically challenging and not always user-friendly. Here we applied the intuitive open access servers of DoGSite, FTMap and CryptoSite to comprehensively predict ligand binding pockets, druggability scores and conformationally active regions of the NUDIX protein family. In parallel we analyzed potential ligand binding sites, their druggability and hydrophobic-hydrophilic ratio using Schrödinger’s SiteMap. Then an in silico docking cascade of a subset of the ZINC FragNow library using the Glide docking program was performed to assess identified pockets for large-scale small molecule binding. Subsequently, this initial dual ranking of druggable sites within the NUDIX protein family was benchmarked against experimental hit rates obtained both in-house and by others from traditional biochemical and fragment screening campaigns. The observed correlation suggests that the presented user-friendly workflow of a dual parallel in silico druggability assessment is applicable as a standalone method for decision on target prioritization in future screening campaigns. <br>

scholarly journals Cytotoxic Profiling of Annotated and Diverse Chemical Libraries Using Quantitative High-Throughput Screening

2019 ◽  
Vol 25 (1) ◽  
pp. 9-20 ◽  
Author(s):  
Olivia W. Lee ◽  
Shelley Austin ◽  
Madison Gamma ◽  
Dorian M. Cheff ◽  
Tobie D. Lee ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
High Throughput ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Large Scale ◽  
Early Stage ◽  
Cancer Cell Line ◽  
Hek 293 ◽  
Cytotoxic Compounds

Cell-based phenotypic screening is a commonly used approach to discover biological pathways, novel drug targets, chemical probes, and high-quality hit-to-lead molecules. Many hits identified from high-throughput screening campaigns are ruled out through a series of follow-up potency, selectivity/specificity, and cytotoxicity assays. Prioritization of molecules with little or no cytotoxicity for downstream evaluation can influence the future direction of projects, so cytotoxicity profiling of screening libraries at an early stage is essential for increasing the likelihood of candidate success. In this study, we assessed the cell-based cytotoxicity of nearly 10,000 compounds in the National Institutes of Health, National Center for Advancing Translational Sciences annotated libraries and more than 100,000 compounds in a diversity library against four normal cell lines (HEK 293, NIH 3T3, CRL-7250, and HaCat) and one cancer cell line (KB 3-1, a HeLa subline). This large-scale library profiling was analyzed for overall screening outcomes, hit rates, pan-activity, and selectivity. For the annotated library, we also examined the primary targets and mechanistic pathways regularly associated with cell death. To our knowledge, this is the first study to use high-throughput screening to profile a large screening collection (>100,000 compounds) for cytotoxicity in both normal and cancer cell lines. The results generated here constitute a valuable resource for the scientific community and provide insight into the extent of cytotoxic compounds in screening libraries, allowing for the identification and avoidance of compounds with cytotoxicity during high-throughput screening campaigns.

scholarly journals Cytotoxic Profiling of Annotated and Diverse Chemical Libraries Using Quantitative High-Throughput Screening

2018 ◽  
Author(s):  
Olivia W. Lee ◽  
Shelley Austin ◽  
Madison Gamma ◽  
Dorian M. Cheff ◽  
Tobie D. Lee ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
High Throughput ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Large Scale ◽  
Early Stage ◽  
Cancer Cell Line ◽  
Hek 293 ◽  
Cytotoxic Compounds

AbstractCell-based phenotypic screening is a commonly used approach to discover biological pathways, novel drug targets, chemical probes and high-quality hit-to-lead molecules. Many hits identified from high-throughput screening campaigns are ruled out through a series of follow-up potency, selectivity/specificity, and cytotoxicity assays. Prioritization of molecules with little or no cytotoxicity for downstream evaluation can influence the future direction of projects, so cytotoxicity profiling of screening libraries at an early stage is essential for increasing the likelihood of candidate success. In this study, we assessed cell-based cytotoxicity of nearly 10,000 compounds in NCATS annotated libraries, and over 100,000 compounds in a diversity library, against four ‘normal’ cell lines (HEK 293, NIH 3T3, CRL-7250 and HaCat) and one cancer cell line (KB 3-1, a HeLa subline). This large-scale library profiling was analyzed for overall screening outcomes, hit rates, pan-activity and selectivity. For the annotated library, we also examined the primary targets and mechanistic pathways regularly associated with cell death. To our knowledge, this is the first study to use high-throughput screening to profile a large screening collection (>100,000 compounds) for cytotoxicity in both normal and cancer cell lines. The results generated here constitutes a valuable resource for the scientific community and provides insight on the extent of cytotoxic compounds in screening libraries, identifying and avoiding compounds with cytotoxicity during high-throughput screening campaigns.

An in silico structure-based approach to anti-infective drug discovery

Parasitology ◽  
2013 ◽  
Vol 141 (1) ◽  
pp. 17-27 ◽  
Author(s):  
FRASER CUNNINGHAM ◽  
MARTIN J. McPHILLIE ◽  
A. PETER JOHNSON ◽  
COLIN W. G. FISHWICK
Keyword(s):  
Drug Discovery ◽  
In Silico ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Enzyme Inhibitors ◽  
Cell Activity ◽  
Structure Based Drug Design ◽  
Lead Compounds ◽  
Target Mode ◽  
Screening Approaches

SUMMARYIn light of the low success rate of target-based genomics and HTS (High Throughput Screening) approaches in anti-infective drug discovery, in silico structure-based drug design (SBDD) is becoming increasingly prominent at the forefront of drug discovery. In silico SBDD can be used to identify novel enzyme inhibitors rapidly, where the strength of this approach lies with its ability to model and predict the outcome of protein-ligand binding. Over the past 10 years, our group have applied this approach to a diverse number of anti-infective drug targets ranging from bacterial D-ala-D-ala ligase to Plasmodium falciparum DHODH. Our search for new inhibitors has produced lead compounds with both enzyme and whole-cell activity with established on-target mode of action. This has been achieved with greater speed and efficiency compared with the more traditional HTS initiatives and at significantly reduced cost and manpower.

scholarly journals Flexibility and mobility of SARS-CoV-2-related protein structures

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rudolf A. Römer ◽  
Navodya S. Römer ◽  
A. Katrine Wallis
Keyword(s):  
In Silico ◽  
Drug Targets ◽  
Large Scale ◽  
Structural Information ◽  
Protein Structures ◽  
Antiviral Drug ◽  
Docking Studies ◽  
Related Protein

AbstractThe worldwide CoVid-19 pandemic has led to an unprecedented push across the whole of the scientific community to develop a potent antiviral drug and vaccine as soon as possible. Existing academic, governmental and industrial institutions and companies have engaged in large-scale screening of existing drugs, in vitro, in vivo and in silico. Here, we are using in silico modelling of possible SARS-CoV-2 drug targets, as deposited on the Protein Databank (PDB), and ascertain their dynamics, flexibility and rigidity. For example, for the SARS-CoV-2 spike protein—using its complete homo-trimer configuration with 2905 residues—our method identifies a large-scale opening and closing of the S1 subunit through movement of the S$${}^\text{B}$$ B domain. We compute the full structural information of this process, allowing for docking studies with possible drug structures. In a dedicated database, we present similarly detailed results for the further, nearly 300, thus far resolved SARS-CoV-2-related protein structures in the PDB.

scholarly journals An integrated in silico-in vitro approach for identification of therapeutic drug targets for osteoarthritis

2021 ◽  
Author(s):  
Raphaëlle Lesage ◽  
Mauricio N. Ferrao Blanco ◽  
Roberto Narcisi ◽  
Tim Welting ◽  
Gerjo J.V.M. van Osch ◽  
...  
Keyword(s):  
Network Model ◽  
In Silico ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Articular Chondrocytes ◽  
Cartilage Degeneration ◽  
Therapeutic Drug ◽  
Disease Modifying Drugs ◽  
Chondrocyte Phenotype

ABSTRACTWithout the availability of disease-modifying drugs, there is an unmet therapeutic need for osteoarthritic patients. During osteoarthritis, the homeostasis of articular chondrocytes is dysregulated and a phenotypical transition called hypertrophy occurs, leading to cartilage degeneration. Targeting this phenotypic transition has emerged as a potential therapeutic strategy. Chondrocyte phenotype maintenance and switch are controlled by an intricate network of intracellular factors, each influenced by a myriad of feedback mechanisms, making it challenging to intuitively predict treatment outcomes. In this study, we developed a regulatory network model using knowledge-based and data-driven modelling technologies. The in silico high-throughput screening of (pairwise) perturbations operated with that network model highlighted conditions impacting the hypertrophic switch. Several combinations were tested in a murine cell line and primary chondrocytes to validate the predicted conditions’ potential. Our in silico-in vitro strategy opens a new route for developing osteoarthritis targeting therapies by refining the early stages of drug discovery.

scholarly journals Cholesterol Interaction with the MAGUK Protein Family Member, MPP1, via CRAC and CRAC-Like Motifs: An In Silico Docking Analysis

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0133141 ◽  
Author(s):  
Marcin A. Listowski ◽  
Jacek Leluk ◽  
Sebastian Kraszewski ◽  
Aleksander F. Sikorski
Keyword(s):  
Family Member ◽  
In Silico ◽  
Protein Family ◽  
Docking Analysis ◽  
In Silico Docking ◽  
Maguk Protein

scholarly journals In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization

2020 ◽  
Vol 8 ◽  
Author(s):  
Maurice Michel ◽  
Evert J. Homan ◽  
Elisée Wiita ◽  
Kia Pedersen ◽  
Ingrid Almlöf ◽  
...  
Keyword(s):  
In Silico ◽  
Protein Family ◽  
Nudix Hydrolase

scholarly journals Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data

Blood ◽  
2008 ◽  
Vol 111 (12) ◽  
pp. 5654-5662 ◽  
Author(s):  
Duane C. Hassane ◽  
Monica L. Guzman ◽  
Cheryl Corbett ◽  
Xiaojie Li ◽  
Ramzi Abboud ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
High Throughput ◽  
In Silico ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Expression Profiles ◽  
Gene Expression Signature ◽  
Myelogenous Leukemia ◽  
Expression Signature

Abstract Increasing evidence indicates that malignant stem cells are important for the pathogenesis of acute myelogenous leukemia (AML) and represent a reservoir of cells that drive the development of AML and relapse. Therefore, new treatment regimens are necessary to prevent relapse and improve therapeutic outcomes. Previous studies have shown that the sesquiterpene lactone, parthenolide (PTL), ablates bulk, progenitor, and stem AML cells while causing no appreciable toxicity to normal hematopoietic cells. Thus, PTL must evoke cellular responses capable of mediating AML selective cell death. Given recent advances in chemical genomics such as gene expression-based high-throughput screening (GE-HTS) and the Connectivity Map, we hypothesized that the gene expression signature resulting from treatment of primary AML with PTL could be used to search for similar signatures in publicly available gene expression profiles deposited into the Gene Expression Omnibus (GEO). We therefore devised a broad in silico screen of the GEO database using the PTL gene expression signature as a template and discovered 2 new agents, celastrol and 4-hydroxy-2-nonenal, that effectively eradicate AML at the bulk, progenitor, and stem cell level. These findings suggest the use of multicenter collections of high-throughput data to facilitate discovery of leukemia drugs and drug targets.

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