Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Introduction

The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.

Methods

Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.

Results

Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19.

Discussion

The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

Automated assembly of molecular mechanisms at scale from text mining and curated databases

The analysis of omic data depends on machine-readable information about protein interactions, modifications, and activities as found in protein interaction networks, databases of post-translational modifications, and curated models of gene and protein function. These resources typically depend heavily on human curation. Natural language processing systems that read the primary literature have the potential to substantially extend knowledge resources while reducing the burden on human curators. However, machine-reading systems are limited by high error rates and commonly generate fragmentary and redundant information. Here, we describe an approach to precisely assemble molecular mechanisms at scale using multiple natural language processing systems and the Integrated Network and Dynamical Reasoning Assembler (INDRA). INDRA identifies full and partial overlaps in information extracted from published papers and pathway databases, uses predictive models to improve the reliability of machine reading, and thereby assembles individual pieces of information into non-redundant and broadly usable mechanistic knowledge. Using INDRA to create high-quality corpora of causal knowledge we show it is possible to extend protein-protein interaction databases and explain co-dependencies in the Cancer Dependency Map.

Automated Network Assembly of Mechanistic Literature for Informed Evidence Identification to Support Cancer Risk Assessment

BACKGROUND

Mechanistic data is increasingly used in hazard identification of chemicals. However, the volume of data is large, challenging the efficient identification and clustering of relevant data.

OBJECTIVES

We investigated whether evidence identification for hazard assessment can become more efficient and informed through an automated approach that combines machine reading of publications with network visualization tools.

METHODS

We chose 13 chemicals that were evaluated by the International Agency for Research on Cancer (IARC) Monographs program incorporating the key characteristics of carcinogens (KCCs) approach. Using established literature search terms for KCCs, we retrieved and analyzed literature using Integrated Network and Dynamical Reasoning Assembler (INDRA). INDRA combines large-scale literature processing with pathway databases and extracts relationships between biomolecules, bioprocesses, and chemicals into statements (e.g., "benzene activates DNA damage"). These statements were subsequently assembled into networks and compared with the KCC evaluation by the IARC, to evaluate the informativeness of our approach.

RESULTS

We found, in general, larger networks for those chemicals which the IARC has evaluated the evidence to be strong for KCC induction. Larger networks were not directly linked to publication count, given that we retrieved small networks for several chemicals with little support for KCC activation according to the IARC, despite the significant volume of literature for these specific chemicals. In addition, interpreting networks for genotoxicity and DNA repair showed concordance with the IARC KCC evaluation.

DISCUSSION

Our method is an automated approach to condense mechanistic literature into searchable and interpretable networks based on an a priori ontology. The approach is no replacement of expert evaluation but, instead, provides an informed structure for experts to quickly identify which statements are made in which papers and how these could connect. We focused on the KCCs because these are supported by well-described search terms. The method needs to be tested in other frameworks as well to demonstrate its generalizability. https://doi.org/10.1289/EHP9112.

Author-sourced capture of pathway knowledge in computable form using Biofactoid

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a web-based platform that allows scientists to specify networks of interactions between genes, their products, and chemical compounds, and then translates this information into a representation suitable for computational analysis, search and discovery. We also report the results of a pilot study to encourage the wide adoption of Biofactoid by the scientific community.

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

shinyDepMap, a tool to identify targetable cancer genes and their functional connections from Cancer Dependency Map data

Individual cancers rely on distinct essential genes for their survival. The Cancer Dependency Map (DepMap) is an ongoing project to uncover these gene dependencies in hundreds of cancer cell lines. To make this drug discovery resource more accessible to the scientific community, we built an easy-to-use browser, shinyDepMap (https://labsyspharm.shinyapps.io/depmap). shinyDepMap combines CRISPR and shRNA data to determine, for each gene, the growth reduction caused by knockout/knockdown and the selectivity of this effect across cell lines. The tool also clusters genes with similar dependencies, revealing functional relationships. shinyDepMap can be used to (1) predict the efficacy and selectivity of drugs targeting particular genes; (2) identify maximally sensitive cell lines for testing a drug; (3) target hop, that is, navigate from an undruggable protein with the desired selectivity profile, such as an activated oncogene, to more druggable targets with a similar profile; and (4) identify novel pathways driving cancer cell growth and survival.

GeneWalk identifies relevant gene functions for a biological context using network representation learning

A bottleneck in high-throughput functional genomics experiments is identifying the most important genes and their relevant functions from a list of gene hits. Gene Ontology (GO) enrichment methods provide insight at the gene set level. Here, we introduce GeneWalk ( github.com/churchmanlab/genewalk ) that identifies individual genes and their relevant functions critical for the experimental setting under examination. After the automatic assembly of an experiment-specific gene regulatory network, GeneWalk uses representation learning to quantify the similarity between vector representations of each gene and its GO annotations, yielding annotation significance scores that reflect the experimental context. By performing gene- and condition-specific functional analysis, GeneWalk converts a list of genes into data-driven hypotheses.

Synthetic Lethal Interaction of SHOC2 Depletion with MEK Inhibition in RAS-Driven Cancers

The mitogen-activated protein kinase (MAPK) pathway is a critical effector of oncogenic RAS signaling, and MAPK pathway inhibition may be an effective combination treatment strategy. We performed genome-scale loss-of-function CRISPR-Cas9 screens in the presence of a MEK1/2 inhibitor (MEKi) in KRAS-mutant pancreatic and lung cancer cell lines and identified genes that cooperate with MEK inhibition. While we observed heterogeneity in genetic modifiers of MEKi sensitivity across cell lines, several recurrent classes of synthetic lethal vulnerabilities emerged at the pathway level. Multiple members of receptor tyrosine kinase (RTK)-RAS-MAPK pathways scored as sensitizers to MEKi. In particular, we demonstrate that knockout, suppression, or degradation of SHOC2, a positive regulator of MAPK signaling, specifically cooperated with MEK inhibition to impair proliferation in RAS-driven cancer cells. The depletion of SHOC2 disrupted survival pathways triggered by feedback RTK signaling in response to MEK inhibition. Thus, these findings nominate SHOC2 as a potential target for combination therapy.

INDRA-IPM: interactive pathway modeling using natural language with automated assembly

SUMMARY

INDRA-IPM (Interactive Pathway Map) is a web-based pathway map modeling tool that combines natural language processing with automated model assembly and visualization. INDRA-IPM contextualizes models with expression data and exports them to standard formats.

AVAILABILITY AND IMPLEMENTATION

INDRA-IPM is available at: http://pathwaymap.indra.bio. Source code is available at http://github.com/sorgerlab/indra_pathway_map. The underlying web service API is available at http://api.indra.bio:8000.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

FamPlex: a resource for entity recognition and relationship resolution of human protein families and complexes in biomedical text mining

Background

For automated reading of scientific publications to extract useful information about molecular mechanisms it is critical that genes, proteins and other entities be correctly associated with uniform identifiers, a process known as named entity linking or “grounding.” Correct grounding is essential for resolving relationships among mined information, curated interaction databases, and biological datasets. The accuracy of this process is largely dependent on the availability of machine-readable resources associating synonyms and abbreviations commonly found in biomedical literature with uniform identifiers.

Results

In a task involving automated reading of ∼215,000 articles using the REACH event extraction software we found that grounding was disproportionately inaccurate for multi-protein families (e.g., “AKT”) and complexes with multiple subunits (e.g.“NF- κB”). To address this problem we constructed FamPlex, a manually curated resource defining protein families and complexes as they are commonly encountered in biomedical text. In FamPlex the gene-level constituents of families and complexes are defined in a flexible format allowing for multi-level, hierarchical membership. To create FamPlex, text strings corresponding to entities were identified empirically from literature and linked manually to uniform identifiers; these identifiers were also mapped to equivalent entries in multiple related databases. FamPlex also includes curated prefix and suffix patterns that improve named entity recognition and event extraction. Evaluation of REACH extractions on a test corpus of ∼54,000 articles showed that FamPlex significantly increased grounding accuracy for families and complexes (from 15 to 71%). The hierarchical organization of entities in FamPlex also made it possible to integrate otherwise unconnected mechanistic information across families, subfamilies, and individual proteins. Applications of FamPlex to the TRIPS/DRUM reading system and the Biocreative VI Bioentity Normalization Task dataset demonstrated the utility of FamPlex in other settings.

Conclusion

FamPlex is an effective resource for improving named entity recognition, grounding, and relationship resolution in automated reading of biomedical text. The content in FamPlex is available in both tabular and Open Biomedical Ontology formats at https://github.com/sorgerlab/famplex under the Creative Commons CC0 license and has been integrated into the TRIPS/DRUM and REACH reading systems.

From word models to executable models of signaling networks using automated assembly

Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. We present an approach to building computational models directly from natural language using automated assembly. Molecular mechanisms described in simple English are read by natural language processing algorithms, converted into an intermediate representation, and assembled into executable or network models. We have implemented this approach in the Integrated Network and Dynamical Reasoning Assembler (INDRA), which draws on existing natural language processing systems as well as pathway information in Pathway Commons and other online resources. We demonstrate the use of INDRA and natural language to model three biological processes of increasing scope: (i) p53 dynamics in response to DNA damage, (ii) adaptive drug resistance in BRAF‐V600E‐mutant melanomas, and (iii) the RAS signaling pathway. The use of natural language makes the task of developing a model more efficient and it increases model transparency, thereby promoting collaboration with the broader biology community.

Atopic dermatitis: a case report and current clinical review of systemic and ocular manifestations

PURPOSE

Atopic dermatitis is a relatively common hereditary dermatologic condition. Ocular sequellae are commonly seen in this disorder and may include involvement of both the anterior and posterior segments of the eye. Clinical symptoms and presentation may vary, as well as visual prognosis.

METHOD

A 48-year-old black woman came to us with a sudden exacerbation of atopic disease with ocular complications-most notably, the classic "shield-like" anterior subcapsular cataract seen in patients with this disease. Extensive diagnostic and management considerations specific to this disorder are highlighted.

RESULTS

A careful history and clinical examination will help direct appropriate diagnosis and management in this population. Although chronic in nature, acute exacerbations of the disease may require specific management. Proposed pathophysiologic mechanisms, including new aspects of treatment, are discussed.

CONCLUSION

Ocular manifestations of atopic disease may be visually debilitating. Therefore, specific consideration relating to clinical course, effective diagnosis, and medical and surgical management of this disorder are discussed.

A World Wide Web-based health resource. Survey of Missouri school nurses to determine priority health information resources for SchoolhealthLink

Two hundred ninety-two school nurses in Missouri participated in a mailed survey to aid in the design of SchoolhealthLink, a World Wide Web (WWW)-based information service for Missouri school nurses and children. The nurses identified specific health information resources likely to benefit school nurses and school children and prioritized these resources. The school nurses assigned high priority to 11 types of health information resources: individualized health care plans, emergency care plans, communicable disease control plans, acute illness, injuries, communicable diseases, hotline numbers, medications in schools, immunization protocols and standards, community-based health care resources, and Department of Elementary and Secondary Education regulations that affect school nurse practice. The four most common health problems school nurses identified were asthma, attention deficit disorder, diabetes, and head lice. SchoolhealthLink will provide a one-stop WWW-based resource for school nurses and school children.

Juvenile onset primary open-angle glaucoma: three case studies and review

BACKGROUND

Common clinical characteristics of juvenile onset primary open-angle glaucoma (JPOAG) include increased intraocular pressure, optic nervehead damage, visual-field loss, and a normal-appearing iridocorneal angle by gonioscopy. Histologic analysis of the angle structures may show varying developmental abnormalities that are observed to be less obvious as age of onset increases. Individuals who are African-American, male in gender, and myopio, are at highest risk--particularly if a positive family history exists. A genetic locus for juvenile onset primary open-angle glaucoma has been isolated to the long arm of chromosome 1.

CASE REPORTS

Three separate cases of JPOAG diagnosed in a 16-year-old African-American girl, a 9-year-old African-American boy, and a 28-year-old African-American woman are presented and reviewed. The symptoms, clinical presentation, disease progression, and treatment options are discussed in detail.

CONCLUSION

Early recognition of this disease is possible through screening on all patients--particularly those who exhibit increased cupping with increased intraocular pressures and risk factors, such as youthful age, male gender, myopic refractive error, and African-American heritage with a positive family history of glaucoma. Family members should also be examined.

Enabling Student Nurses to Use the Information Superhighway

Nursing graduates must be sophisticated in the use of information technologies and understand how these technologies interface with various health care systems. The purpose of this project was to evaluate the impact of a newly developed Internet course, focusing on current information technologies, on 20 RN-to-MSN students. Author-developed instruments were used to measure weekly computer use, perceived computer skill, and knowledge related to the information superhighway. The Stronge & Brodt Nurses Attitudes Toward Computerization Questionnaire was used to assess attitudes toward computerization. Qualitative data was elicited using weekly evaluation forms. When compared to 23 students at a similar stage of their nursing program, quantitative findings indicated that, at the end of the semester, students in the pilot course had more computer knowledge, reported greater computer skill, and used computers more. Qualitative findings suggested that pilot students: * Were connected with nursing networks and expressed their intent to maintain these networks. * Were able to use current health information found on the Internet in their nursing practices. * Used skills learned in the pilot class to complete projects in other classes. * Communicated with classmates via the Internet, thus forming a potentially valuable professional support system. * Used the library and librarians early in their programs. * Understood the relevancy of telemedicine and the Internet to the future survival of nursing in a changing health care arena. While the authors caution that an adequate infrastructure must be available to support such an endeavor, they emphasize that knowledge of the relevancy and use of the information superhighway is crucial to the future survival of nursing in a rapidly changing health care arena.

Preteaching developmentally delayed preschoolers to aid vision screening

Early identification and treatment of vision problems is a key element in learning. For preschool children already identified with developmental delay, vision screening and visual correction are particularly essential. Participants drawn from a public Special School District were 105 preschoolers ages 3 to 5 years identified as having developmental delay. Examples included autism, Down syndrome, physical handicap, or cognitive impairment. A partnership was created between the public preschool and the University Schools of Nursing and Optometry to implement vision screening. Teachers/teacher assistants were asked to characterize the children before and after preteaching and after vision screening. Using a semantic differential scale of bipolar descriptors, planned comparisons within a repeated measures MANOVA were statistically significant for all pairs before teaching vs. the mean of after teaching/after screening (p = 0.027) but not statistically significant for after teaching vs. after vision screening (p = 1.000). Results of this preliminary study suggest preteaching could be an important part of a successful vision screening partnership in that 102 (97%) of developmentally delayed children successfully completed screening for vision problems.

Postoperative complications of subconjunctival THC-YAG (Holmium) laser sclerostomy

BACKGROUND

The THC-YAG (Holmium) laser is currently being used to create thermal sclerostomies, an alternate method of intraocular pressure control with poorly regulated glaucoma. A significant advantage of this procedure is the ab externo approach, which utilizes a small fiberoptic laser probe that is advanced subconjunctivally to the limbus. Surgical intraocular trauma is minimized, decreasing the amount of scarring and ultimate bleb failure. Complications may be seen with the THC-YAG sclerostomy and include: conjunctival burn, filtration bleb leak, posterior corneal striae, peaked pupil, iris incarceration, infection, hyphema, cataracts and ocular hypotony.

METHODS

This paper presents four glaucoma patients, co-managed at the Illinois Eye Institute, who developed complications following THC-YAG laser sclerostomy. A discussion of other possible postoperative complications and their management is included.

RESULTS

While the holmium laser has shown positive results in lowering intraocular pressure in patients with uncontrolled refractory glaucoma, complications are inherent in this procedure. The most common are posterior corneal striae, iris incarceration with secondary peaked pupil, and ocular hypotony. Conjunctival burn with secondary filtration bleb leak, limbal pigment deposition and hyphema may also be seen.

CONCLUSION

Early diagnosis and treatment of postoperative complications may help in maintaining the long term filtration ability of the sclerostomy.

Self-described learning needs of pregnant teen participants in an innovative university/community partnership

The author of this descriptive study investigated self-described learning needs and preferences for teaching methods of pregnant 7th-12th-grade students in an alternative school setting who participated in health classes taught by nursing students. Subjects (N = 121) completed the Learning Needs Assessment for Pregnant Adolescents questionnaire. Results indicated that teens were most interested in learning about infant illnesses, along with complications during pregnancy and labor and delivery. The Evaluation of Health Class tool indicated that teaching strategies preferred by subjects (n = 83), were hospital visits, parties, videotapes, films, records, and games. These results suggest that teaching topics and strategies are important considerations when providing health information for pregnant teens.

State board requirements for CPR certification for licensure in independent health professions

CPR certification requirements for licensure were obtained from 50 states and the District of Columbia for the fields of medicine, osteopathy, podiatry, chiropractic, dentistry, and optometry. It was found that none of the states required CPR certification for initial medical, osteopathic or chiropractic licensure or license renewal, while 4 percent required certification for initial podiatric licensure and license renewal. For initial licensure in dentistry, 25 percent of the boards required CPR certification while 29 percent required CPR certification to renew dental licensure. For initial optometric licensure with diagnostic pharmaceutical agents, 44 percent of the states required CPR certification.

Assessment of Learning Needs of Nurse Educators: Continuing Education Implications

Because of current structure, content, and outcomes of master's nursing curricula, administrators responsible for hiring nurse educators often have no choice but to employ clinical experts as teachers. This article reports on the results of an investigation designed to ascertain the self-reported learning needs of nurse educators in a southern state. This investigation confirmed that nurse educators have numerous learning needs specific to fulfillment of the nurse educator role. Findings suggest that learning needs differed according to the educator's level of academic preparation and type of employment setting. The results provide useful insights for individuals planning continuing educational offerings for nurse educators with varied backgrounds.

Dissociation of autonomic and cognitive effects of THC in man

Intravenous THC, 30--44.8 microgram/kg, was administered to four subjects. Each received THC on four occasions preceded by either i.v. saline, 0.04 mg/kg atropine sulfate, 0.2 mg/kg propranolol, or both drugs together. Heart rates, subjective intoxication and symptom ratings, time productions, and EEG activity were measured. In the absence of autonomic blocking drugs, THC produced characteristic tachycardia, subjective intoxication, and EEG effects. After combined autonomic blockade, THC had no effect on heart rate, while subjective and EEG changes remained as intense. These findings argue against the hypothesis that the subjective and EEG effects of THC are mediated by autonomic receptors or by interoception of peripheral autonomic actions of THC.

Training and performance of rhesus monkeys as operators in a compensatory manual control system

Two rhesus monkeys were trained as operators in a compensatory manual control system similar to systems used in human studies. Training procedures used to shape compensatory tracking behavior included a multiple shock-avoidance technique, the gradual introduction of the system input, and sharpening visual stimulus control of tracking behavior. Time-on-target scores for the monkeys were 95% to 98% while responding to three different frequency bandwidths of the system input. As frequency bandwidth increased, no significant increase in error was noted, the monkeys returned the target element to the center target area at increasing rates, and the number of shocks delivered to each subject remained low. Bode plots and stripouts of input, output, and error signals resembled those typically obtained in human studies. Through extrapolations based on nonhuman primate performance, the conclusion was that the task development and training procedures of the present study provided a means for estimating human performance in manual control systems under environmental stress or in hazardous environments.

Human and nonhuman operators in manual control systems

The human operator in manual control systems is well known from a control theory point of view. The need for highly specialized data in an area which does not permit using human subjects resulted in the study of rhesus monkeys in manual control systems. The performances of monkey and human operators in a simple compensatory control system were similar.