High-throughput Screening Techniques Research Articles

Fluorescence-based screening for engineered aldo-keto reductase KmAKR with improved catalytic performance and extended substrate scope.

Aldo-keto reductases-catalyzed transformations of ketones to chiral alcohols have become an established biocatalytic process step in the pharmaceutical industry. Previously, we have discovered an aldo-keto reductase (AKR) from Kluyveromyces marxianus that is active to the aliphatic tert-butyl 6-substituted (5R/S)-hydroxy-3-oxohexanoates, but it is inactive to aromatic ketones. In order to acquire an excellent KmAKRmutant for ensuring the simultaneous improvement of activity-thermostability toward tert-butyl 6-cyano-(5R)-hydroxy-3-oxohexanoate ((5R)-1) and broadening the universal application prospects toward more substrates covering both aliphatic and aromatic ketones, a fluorescence-based high-throughput (HT) screening technique was established. The directed evolution of KmAKR variant M5 (KmAKR-W297H/Y296W/K29H/Y28A/T63M) produced the "best" variant M5-Q213A/T23V. It exhibited enhanced activity-thermostability toward (5R)-1, improved activity toward all 18 test substrates and strict R-stereoselectivity toward 10 substrates in comparison to M5. The enhancement of enzymatic activity and the extension of substrate scope covering aromatic ketones are proposed to be largely attributed to pushing the binding pocket of M5-Q213A/T23V to the enzyme surface, decreasing the steric hindrance at the entrance and enhancing the flexibility of loops surrounding the active center. In addition, combined with 0.94g dry cell weight (DCW) L-1 glucose dehydrogenase from Exiguobacterium sibiricum (EsGDH) for NADPH regeneration, 2.81g DCW L-1 M5-Q213A/T23V completely converted (5R)-1 of up to 450g L-1 at 120g g-1 substrates/catalysts (S/C), yielding the corresponding optically pure tert-butyl 6-cyano-(3R,5R)-dihydroxyhexanoate ((3R,5R)-2,>99.5% d.e.p ) with a space-time yield (STY) of 1.08kg L-1 day-1 . A fluorescence-based HT screening system was developed to tailor KmAKR's activity, thermostability and substrate scope. The "best" variant M5-Q213A/T23V holds great potential application for the synthesis of aliphatic/aromatic R-configuration alcohols.

Anti-body antibodies in COVID-19.

A new high-throughput screening technique detected autoantibodies in COVID-19 patients specific for many different immunomodulatory extracellular and cell surface proteins, several of which were associated with disease severity and clinical outcomes.

Development of Single-Walled Carbon Nanotube-Based Optical Sensors Via Data Analytics

The photoluminescence of single-walled carbon nanotubes (SWCNTs) offers unique advantages for the development of biological sensors, including the potential to sensitize emission to many classes of analytes. Methods to selectively transduce the local concentration of an analyte via an optical signal often involve the attachment of existing molecular recognition elements to the nanotube surface, or the development of selectivities by high-throughput screening or selection techniques. Due to the existence of several mechanisms of optical modulation of SWCNTs, as well as multiple carbon nanotube species with differing bandgaps, and the increasing number of excipients and polymers that can be used for colloidal suspension and non-covalent functionalization, data analytics can be used to facilitate selective recognition of bioanalytes to detect and process multi-parametric spectroscopic fingerprints. These strategies will be discussed for the detection of single and multiplexed analytes.

Two-Dimensional and Three-Dimensional Cartilage Model Platforms for Drug Evaluation and High-Throughput Screening Assays.

Osteoarthritis (OA) is a severely painful and debilitating disease of the joint, which brings about degradation of the articular cartilage and currently has few therapeutic solutions. Two-dimensional (2D) high-throughput screening (HTS) assays have been widely used to identify candidate drugs with therapeutic potential for the treatment of OA. A number of small molecules which improve the chondrogenic differentiation of progenitor cells for tissue engineering applications have also been discovered in this way. However, due to the failure of these models to accurately represent the native joint environment, the efficacy of these drugs has been limited in vivo. Screening systems utilizing three-dimensional (3D) models, which more closely reflect the tissue and its complex cell and molecular interactions, have also been described. However, the vast majority of these systems fail to recapitulate the complex, zonal structure of articular cartilage and its unique cell population. This review summarizes current 2D HTS techniques and addresses the question of how to use existing 3D models of tissue-engineered cartilage to create 3D drug screening platforms with improved outcomes. Impact statement Currently, the use of two-dimensional (2D) screening platforms in drug discovery is common practice. However, these systems often fail to predict efficacy in vivo, as they do not accurately represent the complexity of the native three-dimensional (3D) environment. This article describes existing 2D and 3D high-throughput systems used to identify small molecules for osteoarthritis treatment or in vitro chondrogenic differentiation, and suggests ways to improve the efficacy of these systems based on the most recent research.

Machine learning and descriptor selection for the computational discovery of metal-organic frameworks

ABSTRACT Metal-organic frameworks (MOFs), crystalline materials with high internal surface area and pore volume, have demonstrated great potential for many applications. In the past decade, as large number of MOFs have come into existence, there has been an effort to model them using computers. High-throughput screening techniques in tandem with molecular simulations or ab-initio calculations are being used to calculate their properties. However, the number of MOFs that can be hypothetically created are in the millions, and thoughcomputer simulations have shown remarkable accuracy, we cannot deploy them for all structures due to their high-computational cost. In this regard, machine learning (ML)-based algorithms have proven to be effective in predicting material properties and reducing the need for expensive calculations. Adopting this methodology can save time and allow researchers to explore materials in unchartered chemical space, thus ushering an era of high-throughput in-silico material design using ML. In this work, we present what is ML, its associated workflow, selecting descriptors, and how it can help build reliable models for discovering MOFs. We present somepopular and novel ones. Thereafter, we review some of the recent studies with respect to ML-based implementation for MOF discovery emphasizing descriptors selected and the workflow adopted.

Experimental investigation of cross-flow regime in novel high throughput set-up for liquid separations

High throughput (HT) screening techniques for pressure-driven membrane processes allow simultaneous screening of multiple membrane samples under similar conditions, and are thus labour-, time- and consumables efficient. HT-modules have so far all been set-up in dead-end configuration. A new filtration set-up for cross-flow filtration has now been designed, allowing to simultaneously perform 16 pressure-driven separations with a membrane surface of 15 cm² each. The potential of the developed equipment and of the HT-screening concept in general was validated by demonstrating the reliability and reproducibility of the measurement of membrane performances, and by comparing flow simulations and experimental data. These data were obtained with 2 types of commercially available membrane: a nanofiltration membrane (NF 270, DowDuPont, USA) and a reverse osmosis membrane 73AC-UTC (Toray Industries Inc., Japan). Additionally, the flow-regime inside the cross-flow channel was studied by varying the hydrodynamic parameters and by applying feed spacers. The reproducibility of the data proved that this HT-approach can be a useful tool to rapidly screen a large array of operational parameters in membrane processes.

Inhibitor development of MTH1 via high-throughput screening with fragment based library and MTH1 substrate binding cavity

MutT Homolog 1 (MTH1) has been proven to hydrolyze oxidized nucleotide triphosphates during DNA repair. It can prevent the incorporation of wrong nucleotides during DNA replication and mitigate cell apoptosis. In a cancer cell, abundant reactive oxygen species can lead to substantial DNA damage and DNA mutations by base-pairing mismatch. MTH1 could eliminate oxidized dNTP and prevent cancer cells from entering cell death. Therefore, inhibition of MTH1 activity is considered to be an anti-cancer therapeutic target. In this study, high-throughput screening techniques were combined with a fragment-based library containing 2,313 compounds, which were used to screen for lead compounds with MTH1 inhibitor activity. Four compounds with MTH1 inhibitor ability were selected, and compound MI0639 was found to have the highest effective inhibition. To discover the selectivity and specificity of this action, several derivatives based on the MTH1 and MI0639 complex structure were synthesized. We compared 14 complex structures of MTH1 and the various compounds in combination with enzymatic inhibition and thermodynamic analysis. Nanomolar-range IC50 inhibition abilities by enzyme kinetics and Kd values by thermodynamic analysis were obtained for two compounds, named MI1020 and MI1024. Based on structural information and compound optimization, we aim to provide a strategy for the development of MTH1 inhibitors with high selectivity and specificity.

Interactions of HIV-1 Capsid with Host Factors and Their Implications for Developing Novel Therapeutics.

The Human Immunodeficiency Virus type 1 (HIV-1) virion contains a conical shell, termed capsid, encasing the viral RNA genome. After cellular entry of the virion, the capsid is released and ensures the protection and delivery of the HIV-1 genome to the host nucleus for integration. The capsid relies on many virus–host factor interactions which are regulated spatiotemporally throughout the course of infection. In this paper, we will review the current understanding of the highly dynamic HIV-1 capsid–host interplay during the early stages of viral replication, namely intracellular capsid trafficking after viral fusion, nuclear import, uncoating, and integration of the viral genome into host chromatin. Conventional anti-retroviral therapies primarily target HIV-1 enzymes. Insights of capsid structure have resulted in a first-in-class, long-acting capsid-targeting inhibitor, GS-6207 (Lenacapavir). This inhibitor binds at the interface between capsid protein subunits, a site known to bind host factors, interferes with capsid nuclear import, HIV particle assembly, and ordered assembly. Our review will highlight capsid structure, the host factors that interact with capsid, and high-throughput screening techniques, specifically genomic and proteomic approaches, that have been and can be used to identify host factors that interact with capsid. Better structural and mechanistic insights into the capsid–host factor interactions will significantly inform the understanding of HIV-1 pathogenesis and the development of capsid-centric antiretroviral therapeutics.

Phage Display Screening for Alba Superfamily Proteins from the Human Malaria Parasite, Plasmodium falciparum Reveals a High Level of Association with Protein Modification Pathways and Hints at New Drug Targets.

A 2016 study estimated that over 3 billion people are currently at risk of contracting malaria. Although a wide variety of medications are available to treat malaria, the parasites have started to exhibit resistance to many commonly used therapeutics necessitating a push for new investigations to identify novel drug targets. In this study, nucleic acid-binding Alba superfamily proteins of the human malaria parasite, Plasmodium falciparum were investigated to identify interacting protein motifs. A high-throughput molecular screening technique, phage display, coupled with next-generation sequencing was applied to assess large data sets. Four P. falciparum Alba proteins were used for screening which appear to have distinct roles in parasite biology based on the results of this work. The majority of the peptide motifs identified from phage display were involved in post-translational modification pathways, thus suggesting that parasite-specific gene regulatory mechanisms are involved which could serve as drug targets for novel therapeutics. This study found 18 peptide motifs which potentially have strong interactions with one or more of the Alba superfamily proteins from P. falciparum. Considering the large fraction of post-translational modification-related peptide motifs identified from this work, one or more of the protein modification pathways could serve as a good target for malaria treatment.

Lipidome of cricket species used as food

The variation in lipidome of house cricket, banded cricket, Jamaican field cricket and two-spotted cricket was studied using high-throughput screening techniques for fingerprinting (MALDI TOF MS, GC–MS and LC MS-MS) and well-stablished chromatographic techniques for quantification (HPLC-ELSD, GC- FID). Although the four cricket species were reared in identical conditions, two-spotted & banded crickets had a lipid content 1.5 fold higher than house cricket. The lipids were high in UFA (>63%) and unsaturated TAG (>98%) making them liquid at room temperature, thus an oil. Cholesterol and several phytosterols were profiled finding high cholesterol concentration which is a point of concern. Eight phospholipid types (211 species) were identified with no major differences among cricket species. Using high-throughput screening techniques we demonstrate the complexity of cricket lipidome. Information on the lipidome of these crickets with high commercial value is important to estimate its nutritional value and their potential food applications.

A multivariate approach to chlorophyll a fluorescence data for trace element ecotoxicological trials using a model marine diatom

The increasing uncontrolled development of human activities and consequent increase in the production and release into the marine realm of potentially harmful substances highlights the need to develop efficient and high-throughput screening (HTS) tools. Bio-optical tools, such as laser-induced fluorescence (LIF) and pulse amplitude modulated (PAM) fluorometry, emerge as efficient non-invasive techniques for toxicophenomic evaluation in ecotoxicological trials. Both techniques generate large datasets that can be applied in multivariate analysis to evaluate canonical classification efficiency of the exposure types and levels to which photosynthetic organisms, such as diatoms, are subjected to. In the present work, marine diatom cultures were exposed to two trace elements known to have physiological roles and different toxicity ranges (Zn and Cu), and to two other trace elements without known metabolic functions and very different toxicological profiles (Cr and Hg). All the tested approaches were able to disentangle the control groups from the test groups. Moreover, the application of LIF raw-data showed that this technique had the higher classification efficiency, providing very good separation of the different doses applied of each trace element tested. Additionally, PAM chlorophyll fast induction kinetics raw data also produced good classification efficiencies and provided data that can be useful for interpreting the physiological shifts induced by trace element exposure. In sum, LIF and PAM techniques appear as completely non-invasive HTS techniques that, when applied together, produce a correct toxicophenomic classification and disentangle the physiological effects behind the observed phenomic changes. Therefore, they are worth to be included in future ecotoxicological assessment test protocols.

Preparation of a modified g-C3N4catalyst library and realization of a two-dimensional screening reaction

A color inkjet printing technique and high through-put screening technique were combined to establish a polymetallic sulphide composite g-C3N4catalyst library and screen out high efficiency catalysts.

Phenoxazine pseudonucleotides in DNA i-motifs allow precise profiling of small molecule binders by fluorescence monitoring.

The lack of high throughput screening (HTS) techniques for small molecules that stabilize DNA iMs limits their development as perspective drug candidates. Here we showed that fluorescence monitoring for probing the effects of ligands on the iM stability using the FAM-BHQ1 pair provides incorrect results due to additional dye-related interactions. We developed an alternative system with fluorescent phenoxazine pseudonucleotides in loops that do not alter iM unfolding. At the same time, the fluorescence of phenoxazine residues is sensitive to iM unfolding that enables accurate evaluation of ligand-induced changes of iM stability. Our results provide the basis for new approaches for HTS of iM ligands.

Lipids as versatile solvents for chemical synthesis

From now on transition metal catalyzed cross-coupling reactions can be performed in food grade and waste vegetable oils. Appropriate methodologies for high-throughput screening and isolation techniques applicable for vegetable oils are described.

Deciphering Intracellular Signaling Pathways in Tumoral Pathologies.

The heterogeneity of diseases such as cancer makes it necessary to use high-throughput screening techniques to obtain the maximum number of parameters and characteristics of tumors. These obtained biomarkers can be used for the prediction, prognosis, and treatment or search for new therapeutic targets. In this sense, microarray technology allows exhaustive analysis in a short time and from a great variety of biological samples, becoming a fundamental tool in biomedical research projects. Here, operational process of protein microarrays based on the antibody-antigen interaction is described, emphasizing their application in intracellular signaling pathways in tumoral pathologies. In addition, a final validation using nucleic acid programmable protein array (NAPPA) technology in a simple ELISA assay was included to decipher functional characterization of featured proteins from microarray screening.

Application of high throughput screening techniques in evaluation of mitochondrial toxicity in vitro

Application of high throughput screening techniques in evaluation of mitochondrial toxicity in vitro

Predicting and Quantifying Antagonistic Effects of Natural Compounds Given with Chemotherapeutic Agents: Applications for High-Throughput Screening.

Simple SummaryIncreasing numbers of cancer patients are turning to complementary and alternative medicines (CAM) to facilitate or replace their cancer treatments, or they are obtaining natural products in their diet. This is concerning, as there is evidence of molecular interactions between these bioactive compounds and cancer drugs that can impede or reverse their efficacy and prevent cancer regression. High-throughput drug screening and deep learning techniques have successfully been applied in the past to evaluate synergistic cancer drug and natural product combinations. However, these techniques should be applied more commonly in the context of drug antagonism to uncover potentially harmful interactions and drive safer recommendations for cancer patients. In this review, we evaluate the antagonistic interactions between natural products and chemotherapeutics and highlight how the application of high-throughput screening and deep learning techniques can strengthen this area of research. Natural products have been used for centuries to treat various human ailments. In recent decades, multi-drug combinations that utilize natural products to synergistically enhance the therapeutic effects of cancer drugs have been identified and have shown success in improving treatment outcomes. While drug synergy research is a burgeoning field, there are disagreements on the definitions and mathematical parameters that prevent the standardization and proper usage of the terms synergy, antagonism, and additivity. This contributes to the relatively small amount of data on the antagonistic effects of natural products on cancer drugs that can diminish their therapeutic efficacy and prevent cancer regression. The ability of natural products to potentially degrade or reverse the molecular activity of cancer therapeutics represents an important but highly under-emphasized area of research that is often overlooked in both pre-clinical and clinical studies. This review aims to evaluate the body of work surrounding the antagonistic interactions between natural products and cancer therapeutics and highlight applications for high-throughput screening (HTS) and deep learning techniques for the identification of natural products that antagonize cancer drug efficacy.

Examining the evidence of non-monotonic dose-response in Androgen Receptor agonism high-throughput screening assay

Modern High-Throughput Screening (HTS) techniques allow to determine in vitro bioactivity of tens of thousands of chemicals within a relatively short period of time and tested compounds are usually interpreted as either active or inactive. The interpretation is mostly based on the assumption of monotonic dose-response. This approach ignores potential abnormal dose-response relationships, such as non-monotonic dose-response (NMDR). NMDR presents a serious challenge to toxicologists and pharmacologists, since they undermine the usefulness of such concepts as lowest-observed-adverse-effect level (LOAEL) and no-observed-adverse-effect level (NOAEL). The possible presence of the NMDR in Androgen receptor (AR) agonism was examined for a structurally diverse set of chemicals (~8 300 unique compounds) from Tox21 project library. The source of activity data is Tox21 AR agonism luciferase-based HTS on the MDA-MB-453 cell line. The examination of curve fitting for 35,328 dose-response data entries was based on modified version of existing criteria for determination of NMDR. The bias that arises from compounds' cytotoxicity and interference with firefly luciferase protein was also studied. The examination has shown evidence of NMDR for several compounds, including known AR antagonists (e. g. Cyproterone acetate) and other known endocrine disruptors (e. g. Tranilast). Compounds were divided into 3 groups based on chemical class, known biological activity profile and the shape of dose-response curve. The challenges of using HTS data to determine NMDR and benefits of this analysis are discussed

Exploring new targets and chemical space with affinity selection-mass spectrometry.

Affinity selection-mass spectrometry (AS-MS) is a high-throughput screening (HTS) technique for drug discovery that enables rapid screening of large collections of compounds to identify ligands for a specific biomolecular target. AS-MS is a binding assay that is insensitive to the functional effects a ligand might have, which is important because it lets us identify novel ligands irrespective of their binding site. This approach is gaining popularity, notably due to its role in the emergence of useful agents for targeted protein degradation. This Perspective highlights the use of AS-MS techniques to explore broad chemical space and identify small-molecule ligands for biological targets that have proven challenging to address with other screening paradigms. We present chemical structures of reported AS-MS hits to illustrate the potential of this screening approach to deliver high-quality hits for further optimization. AS-MS has, thus, evolved from being an infrequent alternative to traditional HTS or DNA-encoded library strategies to now firmly establishing itself as a HTS approach for drug discovery.

Characterization of the Mercapturic Acid Pathway, an Important Phase II Biotransformation Route, in a Zebrafish Embryo Cell Line.

In view of the steadily increasing number of chemical compounds used in various products and applications, high-throughput toxicity screening techniques can help meeting the needs of 21st century risk assessment. Zebrafish (Danio rerio), especially its early life stages, are increasingly used in such screening efforts. In contrast, cell lines derived from this model organism have received less attention so far. A conceivable reason is the limited knowledge about their overall capacity to biotransform chemicals and the spectrum of expressed biotransformation pathways. One important biotransformation route is the mercapturic acid pathway, which protects organisms from harmful electrophilic compounds. The fully functional pathway involves a succession of several enzymatic reactions. To investigate the mercapturic acid pathway performance in the zebrafish embryonic cell line, PAC2, we analyzed the biotransformation products of the reactions comprising this pathway in the cells exposed to a nontoxic concentration of the reference substrate, 1-chloro-2,4-dinitrobenzene (CDNB). Additionally, we used targeted proteomics to measure the expression of cytosolic glutathione S-transferases (GSTs), the enzyme family catalyzing the first reaction in this pathway. Our results reveal that the PAC2 cell line expresses a fully functional mercapturic acid pathway. All but one of the intermediate CDNB biotransformation products were identified. The presence of the active mercapturic acid pathway in this cell line was further supported by the expression of a large palette of GST enzyme classes. Although the enzymes of the class alpha, one of the dominant GST classes in the zebrafish embryo, were not detected, this did not seem to affect the capacity of the PAC2 cells to biotransform CDNB. Our data provide an important contribution toward using zebrafish cell lines, specifically PAC2, for animal-free high- throughput screening in toxicology and chemical hazard assessment.