Minimal information for chemosensitivity assays (MICHA): a next-generation pipeline to enable the FAIRification of drug screening experiments.

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of Minimal Information for Chemosensitivity Assays (MICHA), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies as well as six recently conducted COVID-19 studies. With the MICHA web server and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.

Exploration of databases and methods supporting drug repurposing: a comprehensive survey.

Drug development involves a deep understanding of the mechanisms of action and possible side effects of each drug, and sometimes results in the identification of new and unexpected uses for drugs, termed as drug repurposing. Both in case of serendipitous observations and systematic mechanistic explorations, confirmation of new indications for a drug requires hypothesis building around relevant drug-related data, such as molecular targets involved, and patient and cellular responses. These datasets are available in public repositories, but apart from sifting through the sheer amount of data imposing computational bottleneck, a major challenge is the difficulty in selecting which databases to use from an increasingly large number of available databases. The database selection is made harder by the lack of an overview of the types of data offered in each database. In order to alleviate these problems and to guide the end user through the drug repurposing efforts, we provide here a survey of 102 of the most promising and drug-relevant databases reported to date. We summarize the target coverage and types of data available in each database and provide several examples of how multi-database exploration can facilitate drug repurposing.

A combination treatment based on drug repurposing demonstrates mutation-agnostic efficacy in pre-clinical retinopathy models.

Inherited retinopathies are devastating diseases that in most cases lack treatment options. Disease-modifying therapies that mitigate pathophysiology regardless of the underlying genetic lesion are desirable due to the diversity of mutations found in such diseases. We tested a systems pharmacology-based strategy that suppresses intracellular cAMP and Ca2+ activity via G protein-coupled receptor (GPCR) modulation using tamsulosin, metoprolol, and bromocriptine coadministration. The treatment improves cone photoreceptor function and slows degeneration in Pde6ßrd10 and RhoP23H/WT retinitis pigmentosa mice. Cone degeneration is modestly mitigated after a 7-month-long drug infusion in PDE6A-/- dogs. The treatment also improves rod pathway function in an Rpe65-/- mouse model of Leber congenital amaurosis but does not protect from cone degeneration. RNA-sequencing analyses indicate improved metabolic function in drug-treated Rpe65-/- and rd10 mice. Our data show that catecholaminergic GPCR drug combinations that modify second messenger levels via multiple receptor actions provide a potential disease-modifying therapy against retinal degeneration.

Minimal information for Chemosensitivity assays (MICHA): A next-generation pipeline to enable the FAIRification of drug screening experiments.

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of MICHA (Minimal Information for Chemosensitivity Assays), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents, and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets, and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies, as well as six recently conducted COVID-19 studies. With the MICHA webserver and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.

Silver, titanium dioxide, and zinc oxide nanoparticles trigger miRNA/isomiR expression changes in THP-1 cells that are proportional to their health hazard potential.

After over a decade of nanosafety research, it is indisputable that the vast majority of nano-sized particles induce a plethora of adverse cellular responses - the severity of which is linked to the material's physicochemical properties. Differentiated THP-1 cells were previously exposed for 6 h and 24 h to silver, titanium dioxide, and zinc oxide nanoparticles at the maximum molar concentration at which no more than 15% cellular cytotoxicity was observed. All three nanoparticles differed in extent of induction of biological pathways corresponding to immune response signaling and metal ion homeostasis. In this study, we integrated gene and miRNA expression profiles from the same cells to propose miRNA biomarkers of adverse exposure to metal-based nanoparticles. We employed RNA sequencing together with a quantitative strategy that also enables analysis of the overlooked repertoire of length and sequence miRNA variants called isomiRs. Whilst only modest changes in expression were observed within the first 6 h of exposure, the miRNA/isomiR (miR) profiles of each nanoparticle were unique. Via canonical correlation and pathway enrichment analyses, we identified a co-regulated miR-mRNA cluster, predicted to be highly relevant for cellular response to metal ion homeostasis. These miRs were annotated to be canonical or variant isoforms of hsa-miR-142-5p, -342-3p, -5100, -6087, -6894-3p, and -7704. Hsa-miR-5100 was differentially expressed in response to each nanoparticle in both the 6 h and 24 h exposures. Taken together, this co-regulated miR-mRNA cluster could represent potential biomarkers of sub-toxic metal-based nanoparticle exposure.

Prediction of structure of human WNT-CRD (FZD) complex for computational drug repurposing.

The observed genetic alterations of various extracellular and intracellular WNT (Wingless, Int-1 proto-oncogene) signaling components can result in an increase or decrease in gene expression, and hence can be obstructed proficiently. These genetics target sites may include the prevention of WNT-FZD (Frizzled) binding, destruction of ß-catenin and formation of Axin, APC and GSK-3ß complex. Hence, the localized targeting of these interacting partners can help in devising novel inhibitors against WNT signaling. Our present study is an extension of our previous work, in which we proposed the co-regulated expression pattern of the WNT gene cluster (WNT-1, WNT-6, WNT-10A and WNT-10B) in human breast carcinoma. We present here the computationally modeled three dimensional structure of human WNT-1 in complex with the FZD-1 CRD (Cysteine Rich Domain) receptor. The dimeric cysteine-rich domain was found to fit into the evolutionarily conserved U-shaped groove of WNT protein. The two ends of the U- shaped cleft contain N-terminal and C-terminal hydrophobic residues, thus providing a strong hydrophobic moiety for the frizzled receptor and serving as the largest binding pocket for WNT-FZD interaction. Detailed structural analysis of this cleft revealed a maximum atomic distance of ~28 Å at the surface, narrowing down to ~17 Å and again increasing up to ~27 Å at the bottom. Altogether, structural prediction analysis of WNT proteins was performed to reveal newer details about post-translational modification sites and to map the novel pharmacophore models for potent WNT inhibitors.

MotViz: a tool for sequence motif prediction in parallel to structural visualization and analyses.

Linking similar proteins structurally is a challenging task that may help in finding the novel members of a protein family. In this respect, identification of conserved sequence can facilitate understanding and classifying the exact role of proteins. However, the exact role of these conserved elements cannot be elucidated without structural and physiochemical information. In this work, we present a novel desktop application MotViz designed for searching and analyzing the conserved sequence segments within protein structure. With MotViz, the user can extract a complete list of sequence motifs from loaded 3D structures, annotate the motifs structurally and analyze their physiochemical properties. The conservation value calculated for an individual motif can be visualized graphically. To check the efficiency, predicted motifs from the data sets of 9 protein families were analyzed and MotViz algorithm was more efficient in comparison to other online motif prediction tools. Furthermore, a database was also integrated for storing, retrieving and performing the detailed functional annotation studies. In summary, MotViz effectively predicts motifs with high sensitivity and simultaneously visualizes them into 3D strucures. Moreover, MotViz is user-friendly with optimized graphical parameters and better processing speed due to the inclusion of a database at the back end. MotViz is available at http://www.fi-pk.com/motviz.html.

TrFAST: a tool to predict signaling pathway-specific transcription factor binding sites.

Recent advances in the development of high-throughput tools have significantly revolutionized our understanding of molecular mechanisms underlying normal and dysfunctional biological processes. Here we present a novel computational tool, transcription factor search and analysis tool (TrFAST), which was developed for the in silico analysis of transcription factor binding sites (TFBSs) of signaling pathway-specific TFs. TrFAST facilitates searching as well as comparative analysis of regulatory motifs through an exact pattern matching algorithm followed by the graphical representation of matched binding sites in multiple sequences up to 50kb in length. TrFAST is proficient in reducing the number of comparisons by the exact pattern matching strategy. In contrast to the pre-existing tools that find TFBS in a single sequence, TrFAST seeks out the desired pattern in multiple sequences simultaneously. It counts the GC content within the given multiple sequence data set and assembles the combinational details of consensus sequence(s) located at these regions, thereby generating a visual display based on the abundance of unique pattern. Comparative regulatory region analysis of multiple orthologous sequences simultaneously enhances the features of TrFAST and provides a significant insight into study of conservation of non-coding cis-regulatory elements. TrFAST is freely available at http://www.fi-pk.com/trfast.html.

Integrative analyses of conserved WNT clusters and their co-operative behaviour in human breast cancer.

In human, WNT gene clusters are highly conserved at specie level and associated with carcinogenesis. Among them, WNT-10A and WNT-6 genes clustered in chromosome 2q35 are homologous to WNT-10B and WNT-1 located in chromosome 12q13, respectively. In an attempt to study co-regulation, the coordinated expression of these genes was monitored in human breast cancer tissues. As compared to normal tissue, both WNT-10A and WNT-10B genes exhibited lower expression while WNT-6 and WNT-1 showed increased expression in breast cancer tissues. The co-expression pattern was elaborated by detailed phylogenetic and syntenic analyses. Moreover, the intergenic and intragenic regions for these gene clusters were analyzed for studying the transcriptional regulation. In this context, adequate conserved binding sites for SOX and TCF family of transcriptional factors were observed. We propose that SOX9 and TCF4 may compete for binding at the promoters of WNT family genes thus regulating the disease phenotype.