RNA therapies hold great promise for treating cancer. High-throughput screening techniques have facilitated the development of RNA treatments

2021 ◽  
Author(s):  
Moataz Dowaidar

High throughput screening techniques have facilitated the creation of RNA treatments, and these findings have been accompanied by unique modifications of RNA structures to increase stability and minimize toxicity, as well as innovative delivery systems such as LNPs. "undruggable" targets, "swiftly construct vaccinations," and to provide therapeutic approaches that can be tailored to individual patients Like the genetic code, RNA therapies hold great promise.At the same time, our hospital launched a specialized RNA Therapeutics program that assists both our internal scientists and external academic groups or small firms aiming to apply their fundamental research discoveries to innovative treatments. mRNA is primarily stable because of our primary study in sequencing and structure. For synthesis, purification, and validation of RNA constructs, we have a contemporary GMP program with clean rooms. Our company collaborates with Nanomedicine to build LNP structures that transport mRNA constructs locally and systemically. We have an opportunity to hire and integrate first-in-man clinical trials unit, as well as a big hospital system with a clinical research infrastructure that enables industry-sponsored Phase 2 and 3 clinical trials. Additionally, we have a large-scale mRNA construction industrial sponsor for Phases 2, 3, and commercialization. Essentially, we've put up a production line for universities and small firms interested in turning their mRNA creations into revolutionary medications. One hospital, one point of entry to ensure that RNA-based drugs are created and translated into the clinic efficiently. Many tiny firms with fresh concepts for disruptive mRNA therapeutics cannot reach the clinic without new translational capabilities. We think we are the only academic organization with the infrastructure to help small academic groups and biotech enterprises, and we want to aid both internal and external translational activities in the coming years.

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>


2020 ◽  
Vol 17 (5) ◽  
pp. 716-724
Author(s):  
Yan A. Ivanenkov ◽  
Renat S. Yamidanov ◽  
Ilya A. Osterman ◽  
Petr V. Sergiev ◽  
Vladimir A. Aladinskiy ◽  
...  

Background: The key issue in the development of novel antimicrobials is a rapid expansion of new bacterial strains resistant to current antibiotics. Indeed, World Health Organization has reported that bacteria commonly causing infections in hospitals and in the community, e.g. E. Coli, K. pneumoniae and S. aureus, have high resistance vs the last generations of cephalosporins, carbapenems and fluoroquinolones. During the past decades, only few successful efforts to develop and launch new antibacterial medications have been performed. This study aims to identify new class of antibacterial agents using novel high-throughput screening technique. Methods: We have designed library containing 125K compounds not similar in structure (Tanimoto coeff.< 0.7) to that published previously as antibiotics. The HTS platform based on double reporter system pDualrep2 was used to distinguish between molecules able to block translational machinery or induce SOS-response in a model E. coli system. MICs for most active chemicals in LB and M9 medium were determined using broth microdilution assay. Results: In an attempt to discover novel classes of antibacterials, we performed HTS of a large-scale small molecule library using our unique screening platform. This approach permitted us to quickly and robustly evaluate a lot of compounds as well as to determine the mechanism of action in the case of compounds being either translational machinery inhibitors or DNA-damaging agents/replication blockers. HTS has resulted in several new structural classes of molecules exhibiting an attractive antibacterial activity. Herein, we report as promising antibacterials. Two most active compounds from this series showed MIC value of 1.2 (5) and 1.8 μg/mL (6) and good selectivity index. Compound 6 caused RFP induction and low SOS response. In vitro luciferase assay has revealed that it is able to slightly inhibit protein biosynthesis. Compound 5 was tested on several archival strains and exhibited slight activity against gram-negative bacteria and outstanding activity against S. aureus. The key structural requirements for antibacterial potency were also explored. We found, that the unsubstituted carboxylic group is crucial for antibacterial activity as well as the presence of bulky hydrophobic substituents at phenyl fragment. Conclusion: The obtained results provide a solid background for further characterization of the 5'- (carbonylamino)-2,3'-bithiophene-4'-carboxylate derivatives discussed herein as new class of antibacterials and their optimization campaign.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Takumi Kayukawa ◽  
Kenjiro Furuta ◽  
Keisuke Nagamine ◽  
Tetsuro Shinoda ◽  
Kiyoaki Yonesu ◽  
...  

Abstract Insecticide resistance has recently become a serious problem in the agricultural field. Development of insecticides with new mechanisms of action is essential to overcome this limitation. Juvenile hormone (JH) is an insect-specific hormone that plays key roles in maintaining the larval stage of insects. Hence, JH signaling pathway is considered a suitable target in the development of novel insecticides; however, only a few JH signaling inhibitors (JHSIs) have been reported, and no practical JHSIs have been developed. Here, we established a high-throughput screening (HTS) system for exploration of novel JHSIs using a Bombyx mori cell line (BmN_JF&AR cells) and carried out a large-scale screening in this cell line using a chemical library. The four-step HTS yielded 69 compounds as candidate JHSIs. Topical application of JHSI48 to B. mori larvae caused precocious metamorphosis. In ex vivo culture of the epidermis, JHSI48 suppressed the expression of the Krüppel homolog 1 gene, which is directly activated by JH-liganded receptor. Moreover, JHSI48 caused a parallel rightward shift in the JH response curve, suggesting that JHSI48 possesses a competitive antagonist-like activity. Thus, large-scale HTS using chemical libraries may have applications in development of future insecticides targeting the JH signaling pathway.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhou Fang ◽  
Junjian Chen ◽  
Ye Zhu ◽  
Guansong Hu ◽  
Haoqian Xin ◽  
...  

AbstractPeptides are widely used for surface modification to develop improved implants, such as cell adhesion RGD peptide and antimicrobial peptide (AMP). However, it is a daunting challenge to identify an optimized condition with the two peptides showing their intended activities and the parameters for reaching such a condition. Herein, we develop a high-throughput strategy, preparing titanium (Ti) surfaces with a gradient in peptide density by click reaction as a platform, to screen the positions with desired functions. Such positions are corresponding to optimized molecular parameters (peptide densities/ratios) and associated preparation parameters (reaction times/reactant concentrations). These parameters are then extracted to prepare nongradient mono- and dual-peptide functionalized Ti surfaces with desired biocompatibility or/and antimicrobial activity in vitro and in vivo. We also demonstrate this strategy could be extended to other materials. Here, we show that the high-throughput versatile strategy holds great promise for rational design and preparation of functional biomaterial surfaces.


2019 ◽  
Vol 25 (1) ◽  
pp. 9-20 ◽  
Author(s):  
Olivia W. Lee ◽  
Shelley Austin ◽  
Madison Gamma ◽  
Dorian M. Cheff ◽  
Tobie D. Lee ◽  
...  

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.


Reproduction ◽  
2021 ◽  
Author(s):  
Zoe Claire Johnston ◽  
Franz S Gruber ◽  
Sean Brown ◽  
Neil R Norcross ◽  
Jason R Swedlow ◽  
...  

Despite recent advances in male reproductive health research, there remain many elements of male (in)fertility where our understanding is incomplete. Consequently, diagnostic tools and treatments for men with sperm dysfunction, other than medically assisted reproduction, are limited. On the other hand, the gaps in our knowledge of the mechanisms which underpin sperm function have hampered the development of male non-hormonal contraceptives. The study of mature spermatozoa is inherently difficult. They are a unique and highly specialised cell type which does not actively transcribe or translate proteins and cannot be cultured for long periods of time or matured in vitro. One, large scale, approach to both increasing understanding of sperm function, and the discovery and development of compounds that can modulate sperm function, is to directly observe responses to compounds with phenotypic screening techniques. These target agnostic approaches can be developed into high-throughput screening platforms with the potential to drastically increase advances in the field. Here we discuss the rationale and development of high-throughput phenotypic screening platforms for mature human spermatozoa, and the multiple potential applications these present, as well as the current limitations and leaps in our understanding and capabilities needed to overcome them. Further development and use of these technologies could lead to the identification of compounds which positively or negatively affect sperm cell motility or function, or novel platforms for toxicology or environmental chemical testing among other applications. Ultimately, each of these potential applications is also likely to increase understanding within the field of sperm biology.


2018 ◽  
Vol 23 (9) ◽  
pp. 974-981
Author(s):  
Yu-Chi Juang ◽  
Xavier Fradera ◽  
Yongxin Han ◽  
Anthony William Partridge

Histidine decarboxylase (HDC) is the primary enzyme that catalyzes the conversion of histidine to histamine. HDC contributes to many physiological responses as histamine plays important roles in allergic reaction, neurological response, gastric acid secretion, and cell proliferation and differentiation. Small-molecule modulation of HDC represents a potential therapeutic strategy for a range of histamine-associated diseases, including inflammatory disease, neurological disorders, gastric ulcers, and select cancers. High-throughput screening (HTS) methods for measuring HDC activity are currently limited. Here, we report the development of a time-resolved fluorescence resonance energy transfer (TR-FRET) assay for monitoring HDC activity. The assay is based on competition between HDC-generated histamine and fluorophore-labeled histamine for binding to a Europium cryptate (EuK)-labeled anti-histamine antibody. We demonstrated that the assay is highly sensitive and simple to develop. Assay validation experiments were performed using low-volume 384-well plates and resulted in good statistical parameters. A pilot HTS screen gave a Z′ score > 0.5 and a hit rate of 1.1%, and led to the identification of a validated hit series. Overall, the presented assay should facilitate the discovery of therapeutic HDC inhibitors by acting as a novel tool suitable for large-scale HTS and subsequent interrogation of compound structure–activity relationships.


2002 ◽  
Vol 11 (3) ◽  
pp. 185-193 ◽  
Author(s):  
Luanne L. Peters ◽  
Eleanor M. Cheever ◽  
Heather R. Ellis ◽  
Phyllis A. Magnani ◽  
Karen L. Svenson ◽  
...  

The Mouse Phenome Project is an international effort to systematically gather phenotypic data for a defined set of inbred mouse strains. For such large-scale projects the development of high-throughput screening protocols that allow multiple tests to be performed on a single mouse is essential. Here we report hematologic and coagulation data for more than 30 inbred strains. Complete blood counts were performed using an Advia 120 analyzer. For coagulation testing, we successfully adapted the Dade Behring BCS automated coagulation analyzer for use in mice by lowering sample and reagent volume requirements. Seven automated assay procedures were developed. Small sample volume requirements make it possible to perform multiple tests on a single animal without euthanasia, while reductions in reagent volume requirements reduce costs. The data show that considerable variation in many basic hematological and coagulation parameters exists among the inbred strains. These data, freely available on the World Wide Web, allow investigators to knowledgeably select the most appropriate strain(s) to meet their individual study designs and goals.


Inventions ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 72
Author(s):  
Ryota Sawaki ◽  
Daisuke Sato ◽  
Hiroko Nakayama ◽  
Yuki Nakagawa ◽  
Yasuhito Shimada

Background: Zebrafish are efficient animal models for conducting whole organism drug testing and toxicological evaluation of chemicals. They are frequently used for high-throughput screening owing to their high fecundity. Peripheral experimental equipment and analytical software are required for zebrafish screening, which need to be further developed. Machine learning has emerged as a powerful tool for large-scale image analysis and has been applied in zebrafish research as well. However, its use by individual researchers is restricted due to the cost and the procedure of machine learning for specific research purposes. Methods: We developed a simple and easy method for zebrafish image analysis, particularly fluorescent labelled ones, using the free machine learning program Google AutoML. We performed machine learning using vascular- and macrophage-Enhanced Green Fluorescent Protein (EGFP) fishes under normal and abnormal conditions (treated with anti-angiogenesis drugs or by wounding the caudal fin). Then, we tested the system using a new set of zebrafish images. Results: While machine learning can detect abnormalities in the fish in both strains with more than 95% accuracy, the learning procedure needs image pre-processing for the images of the macrophage-EGFP fishes. In addition, we developed a batch uploading software, ZF-ImageR, for Windows (.exe) and MacOS (.app) to enable high-throughput analysis using AutoML. Conclusions: We established a protocol to utilize conventional machine learning platforms for analyzing zebrafish phenotypes, which enables fluorescence-based, phenotype-driven zebrafish screening.


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