Comprehensive analysis of high-throughput screens with HiTSeekR

A high-throughput screening identifies MCM chromatin loading inhibitors targeting cells with increased replication origins

Replication origin assembly is a pivotal step in chromosomal DNA replication. In this process, the ORC complex binds DNA and, together with the CDC6 and CDT1, promotes the loading of the MCM helicase. Chemicals targeting origin assembly might be useful to sensitize highly proliferative cancer cells. However, identifying such compounds is challenging due to the multistage nature of this process. Here, using Xenopus laevis egg extract we set up a high-throughput screening to isolate MCM chromatin loading inhibitors, which led to the identification of NSC-95397 as a powerful inhibitor of replication origin assembly that targets CDC6 protein and promotes its degradation. Using systems developed to test selective drug-induced lethality we show that NSC-95397 triggers cell death both in human cells and Xenopus embryos that have higher proliferative ability. These findings demonstrate the effectiveness of molecules disrupting DNA replication processes in targeting hyperproliferating cells, highlighting their potential as anti-cancer molecules.

A series of pyrimidine-based antifungals with anti-mold activity disrupt ER function in Aspergillus fumigatus

Fungal infections are a major contributor to morbidity and mortality among immunocompromised populations. Moreover, fungal disease caused by molds are difficult to treat and are associated with particularly high mortality. To address the need for new mold-active antifungal drugs, we performed a high-throughput screen with Aspergillus fumigatus, the most common pathogenic mold. We identified a novel, pyrimidine-based chemical scaffold with broad-spectrum antifungal activity including activity against several difficult-to-treat molds. A chemical genetics screen of Saccharomyces cerevisiae suggested that this compound may target the endoplasmic reticulum (ER) and perturb ER function and/or homeostasis. Consistent with this model, this compound induces the unfolded protein response and inhibits secretion of A. fumigatus collagenases. Initial cytotoxicity and pharmacokinetic studies show favorable features including limited mammalian cell toxicity and bioavailability in vivo. Together, these data support the further medicinal chemistry and pre-clinical development of this pyrimidine scaffold toward more effective treatments for life-threatening invasive mold infections.IMPORTANCEInvasive fungal diseases are life-threatening infections caused by fungi in immunocompromised individuals. Currently, there are only three major classes of antifungal drugs available to treat fungal infections; however, these options are becoming even more limited with the global emergence of antifungal drug resistance. To address the need for new antifungal therapies, we performed a screen of chemical compounds and identified a novel molecule with antifungal activity. Initial characterization of this compound shows drug-like features and broad-spectrum activity against medically important fungi. Together, our results support the continued development of this compound as a potential future therapy for these devastating fungal infections.

Drugst.One - A plug-and-play solution for online systems medicine and network-based drug repurposing

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.

A reactive oxygen species Ca2+ signalling pathway identified from a chemical screen for modifiers of sugar-activated circadian gene expression

Sugars are essential metabolites for energy and anabolism that can also act as signals to regulate plant physiology and development. Experimental tools to disrupt major sugar signalling pathways are limited. We performed a chemical screen for modifiers of activation of circadian gene expression by sugars to discover pharmacological tools to investigate and manipulate plant sugar signalling. Using a library of commercially available bioactive compounds, we identified 75 confident hits that modified the response of a circadian luciferase reporter to sucrose in dark-adapted Arabidopsis thaliana seedlings. We validated the transcriptional effect on a subset of the hits and measured their effects on a range of sugar-dependent phenotypes for 13 of these chemicals. Chemicals were identified that appear to influence known and unknown sugar signalling pathways. Pentamidine isethionate was identified as a modifier of a sugar-activated Ca²⁺ signal that acts as a calmodulin inhibitor downstream of superoxide in a metabolic signalling pathway affecting circadian rhythms, primary metabolism and plant growth. Our data provide a resource of new experimental tools to manipulate plant sugar signalling and identify novel components of these pathways.

Image-Based Screening for Stress Granule Regulators

Stress granule (SG)-based RNA interference (RNAi) screening is a powerful method to discover factors that control protein synthesis and aggregation, as well as regulators of SG assembly and disassembly. Here, we describe how to set up and optimize a large-scale siRNA screen, and give a detailed outline for the automated quantification of SGs as a visual readout. Hit evaluation via calculated Z scores provides a list of candidates for further in-depth studies.

A Unique Dual-Readout High-Throughput Screening Assay To Identify Antifungal Compounds with Aspergillus fumigatus

Treatment of invasive mold infections is limited by the lack of adequate drug options that are effective against these fatal infections. High-throughput screening of molds using traditional antifungal assays of growth is problematic and has greatly limited our ability to identify new mold-active agents. Here, we present a high-throughput screening platform for use with Aspergillus fumigatus, the most common causative agent of invasive mold infections, for the discovery of novel mold-active antifungals. This assay detects cell lysis through the release of the cytosolic enzyme adenylate kinase and, thus, is not dependent on changes in biomass or metabolism to detect antifungal activity. The ability to specifically detect cell lysis is a unique aspect of this assay that allows identification of molecules that disrupt fungal cell integrity, such as cell wall-active molecules. We also found that germinating A. fumigatus conidia release low levels of adenylate kinase and that a reduction in this background allowed us to identify molecules that inhibit conidial germination, expanding the potential for discovery of novel antifungal compounds. Here, we describe the validation of this assay and proof-of-concept pilot screens that identified a novel antifungal compound, PIK-75, that disrupts cell wall integrity. This screening assay provides a novel platform for high-throughput screens with A. fumigatus for the identification of anti-mold drugs.

IMPORTANCE Fungal infections caused by molds have the highest mortality rates of human fungal infections. These devastating infections are hard to treat and available antifungal drugs are often not effective. Therefore, the identification of new antifungal drugs with mold activity is critical. Drug screening with molds is challenging and there are limited assays available to identify new antifungal compounds directly with these organisms. Here, we present an assay suitable for use for high-throughput screening with a common mold pathogen. This assay has exciting future potential for the identification of new drugs to treat these fatal infections.

An ABSINTH-Based Protocol for Predicting Binding Affinities between Proteins and Small Molecules

The core task in computational drug discovery is to accurately predict binding free energies in receptor-ligand systems for large libraries of putative binders. Here, the ABSINTH implicit solvent model and force field are extended to describe small, organic molecules and their interactions with proteins. We show that an automatic pipeline based on partitioning arbitrary molecules into substructures corresponding to model compounds with known free energies of solvation can be combined with the CHARMM general force field into a method that is successful at the two important challenges a scoring function faces in virtual screening work flows: it ranks known binders with correlation values rivaling that of comparable state-of-the-art methods and it enriches true binders in a set of decoys. Our protocol introduces innovative modifications to common virtual screening workflows, notably the use of explicit ions as competitors and the integration over multiple protein and ligand species differing in their protonation states. We demonstrate the value of modifications to both the protocol and ABSINTH itself. We conclude by discussing the limitations of high-throughput implicit methods such as the one proposed here.

DrugThatGene: integrative analysis to streamline the identification of druggable genes, pathways and protein complexes from CRISPR screens

MOTIVATION

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) nuclease system has allowed for high-throughput, large scale pooled screens for functional genomic studies. To aid in the translation of functional genomics to therapeutics, we developed DrugThatGene (DTG) as a web-based application that streamlines analysis of potential therapeutic targets identified from functional genetic screens.

RESULTS

Starting from a gene list as input, DTG offers automated identification of small molecules along with supporting information from human genetic and other relevant databases. Furthermore, DTG aids in the identification of common biological pathways and protein complexes in conjunction with associated small molecule inhibitors. Taken together, DTG aims to expedite the identification of small molecules from the abundance of functional genetic data generated from CRISPR screens.

AVAILABILITY AND IMPLEMENTATION

DTG is an open-source and free software available as a website at http://drugthatgene.pinellolab.org. Source code is available at: https://github.com/pinellolab/DrugThatGene, which can be downloaded in order to run DTG locally.

HTSvis: a web app for exploratory data analysis and visualization of arrayed high-throughput screens

Summary

Arrayed high-throughput screens (HTS) cover a broad range of applications using RNAi or small molecules as perturbations and specialized software packages for statistical analysis have become available. However, exploratory data analysis and integration of screening results has remained challenging due to the size of the data sets and the lack of user-friendly tools for interpretation and visualization of screening results. Here we present HTSvis, a web application to interactively visualize raw data, perform quality control and assess screening results from single to multi-channel measurements such as image-based screens. Per well aggregated raw and analyzed data of various assay types and scales can be loaded in a generic tabular format.

Availability and implementation

HTSvis is distributed as an open-source R package, downloadable from https://github.com/boutroslab/HTSvis and can also be accessed at http://htsvis.dkfz.de.

Supplementary information

Supplementary data are available at Bioinformatics online.

High-Throughput Approaches to Pinpoint Function within the Noncoding Genome

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas nuclease system is a powerful tool for genome editing, and its simple programmability has enabled high-throughput genetic and epigenetic studies. These high-throughput approaches offer investigators a toolkit for functional interrogation of not only protein-coding genes but also noncoding DNA. Historically, noncoding DNA has lacked the detailed characterization that has been applied to protein-coding genes in large part because there has not been a robust set of methodologies for perturbing these regions. Although the majority of high-throughput CRISPR screens have focused on the coding genome to date, an increasing number of CRISPR screens targeting noncoding genomic regions continue to emerge. Here, we review high-throughput CRISPR-based approaches to uncover and understand functional elements within the noncoding genome and discuss practical aspects of noncoding library design and screen analysis.

Using Docker Compose for the Simple Deployment of an Integrated Drug Target Screening Platform

Docker virtualization allows for software tools to be executed in an isolated and controlled environment referred to as a container. In Docker containers, dependencies are provided exactly as intended by the developer and, consequently, they simplify the distribution of scientific software and foster reproducible research. The Docker paradigm is that each container encapsulates one particular software tool. However, to analyze complex biomedical data sets, it is often necessary to combine several software tools into elaborate workflows. To address this challenge, several Docker containers need to be instantiated and properly integrated, which complicates the software deployment process unnecessarily. Here, we demonstrate how an extension to Docker, Docker compose, can be used to mitigate these problems by providing a unified setup routine that deploys several tools in an integrated fashion. We demonstrate the power of this approach by example of a Docker compose setup for a drug target screening platform consisting of five integrated web applications and shared infrastructure, deployable in just two lines of codes.

Efficient Management of High-Throughput Screening Libraries with SAVANAH

High-throughput screening (HTS) has become an indispensable tool for the pharmaceutical industry and for biomedical research. A high degree of automation allows for experiments in the range of a few hundred up to several hundred thousand to be performed in close succession. The basis for such screens are molecular libraries, that is, microtiter plates with solubilized reagents such as siRNAs, shRNAs, miRNA inhibitors or mimics, and sgRNAs, or small compounds, that is, drugs. These reagents are typically condensed to provide enough material for covering several screens. Library plates thus need to be serially diluted before they can be used as assay plates. This process, however, leads to an explosion in the number of plates and samples to be tracked. Here, we present SAVANAH, the first tool to effectively manage molecular screening libraries across dilution series. It conveniently links (connects) sample information from the library to experimental results from the assay plates. All results can be exported to the R statistical environment or piped into HiTSeekR ( http://hitseekr.compbio.sdu.dk ) for comprehensive follow-up analyses. In summary, SAVANAH supports the HTS community in managing and analyzing HTS experiments with an emphasis on serially diluted molecular libraries.