Machine learning identifies candidates for drug repurposing in Alzheimer's disease.

Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of time and resources with largely negative results. Repurposing drugs already approved by the Food and Drug Administration (FDA) for another indication is a more rapid and less expensive option. We present DRIAD (Drug Repurposing In AD), a machine learning framework that quantifies potential associations between the pathology of AD severity (the Braak stage) and molecular mechanisms as encoded in lists of gene names. DRIAD is applied to lists of genes arising from perturbations in differentiated human neural cell cultures by 80 FDA-approved and clinically tested drugs, producing a ranked list of possible repurposing candidates. Top-scoring drugs are inspected for common trends among their targets. We propose that the DRIAD method can be used to nominate drugs that, after additional validation and identification of relevant pharmacodynamic biomarker(s), could be readily evaluated in a clinical trial.

The Dark Kinase Knowledgebase: an online compendium of knowledge and experimental results of understudied kinases.

Kinases form the backbone of numerous cell signaling pathways, with their dysfunction similarly implicated in multiple pathologies. Further facilitated by their druggability, kinases are a major focus of therapeutic development efforts in diseases such as cancer, infectious disease and autoimmune disorders. While their importance is clear, the role or biological function of nearly one-third of kinases is largely unknown. Here, we describe a data resource, the Dark Kinase Knowledgebase (DKK; https://darkkinome.org), that is specifically focused on providing data and reagents for these understudied kinases to the broader research community. Supported through NIH's Illuminating the Druggable Genome (IDG) Program, the DKK is focused on data and knowledge generation for 162 poorly studied or 'dark' kinases. Types of data provided through the DKK include parallel reaction monitoring (PRM) peptides for quantitative proteomics, protein interactions, NanoBRET reagents, and kinase-specific compounds. Higher-level data is similarly being generated and consolidated such as tissue gene expression profiles and, longer-term, functional relationships derived through perturbation studies. Associated web tools that help investigators interrogate both internal and external data are also provided through the site. As an evolving resource, the DKK seeks to continually support and enhance knowledge on these potentially high-impact druggable targets.

Inhibition of Haspin Kinase Promotes Cell-Intrinsic and Extrinsic Antitumor Activity.

Patients with melanoma resistant to RAF/MEK inhibitors (RMi) are frequently resistant to other therapies, such as immune checkpoint inhibitors (ICI), and individuals succumb to their disease. New drugs that control tumor growth and favorably modulate the immune environment are therefore needed. We report that the small-molecule CX-6258 has potent activity against both RMi-sensitive (RMS) and -resistant (RMR) melanoma cell lines. Haspin kinase (HASPIN) was identified as a target of CX-6258. HASPIN inhibition resulted in reduced proliferation, frequent formation of micronuclei, recruitment of cGAS, and activation of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway. In murine models, CX-6258 induced a potent cGAS-dependent type-I IFN response in tumor cells, increased IFNγ-producing CD8+ T cells, and reduced Treg frequency in vivo. HASPIN was more strongly expressed in malignant compared with healthy tissue and its inhibition by CX-6258 had minimal toxicity in ex vivo-expanded human tumor-infiltrating lymphocytes (TIL), proliferating TILs, and in vitro differentiated neurons, suggesting a potential therapeutic index for anticancer therapy. Furthermore, the activity of CX-6258 was validated in several Ewing sarcoma and multiple myeloma cell lines. Thus, HASPIN inhibition may overcome drug resistance in melanoma, modulate the immune environment, and target a vulnerability in different cancer lineages. SIGNIFICANCE: HASPIN inhibition by CX-6258 is a novel and potent strategy for RAF/MEK inhibitor-resistant melanoma and potentially other tumor types. HASPIN inhibition has direct antitumor activity and induces a favorable immune microenvironment.

Cheminformatics Tools for Analyzing and Designing Optimized Small-Molecule Collections and Libraries.

Libraries of well-annotated small molecules have many uses in chemical genetics, drug discovery, and therapeutic repurposing. Multiple libraries are available, but few data-driven approaches exist to compare them and design new libraries. We describe an approach to scoring and creating libraries based on binding selectivity, target coverage, and induced cellular phenotypes as well as chemical structure, stage of clinical development, and user preference. The approach, available via the online tool http://www.smallmoleculesuite.org, assembles sets of compounds with the lowest possible off-target overlap. Analysis of six kinase inhibitor libraries using our approach reveals dramatic differences among them and led us to design a new LSP-OptimalKinase library that outperforms existing collections in target coverage and compact size. We also describe a mechanism of action library that optimally covers 1,852 targets in the liganded genome. Our tools facilitate creation, analysis, and updates of both private and public compound collections.