A ligand-based computational drug repurposing pipeline using KNIME and Programmatic Data Access: case studies for rare diseases and COVID-19

Biomedical information mining is increasingly recognized as a promising technique to accelerate drug discovery and development. Especially, integrative approaches which mine data from several (open) data sources have become more attractive with the increasing possibilities to programmatically access data through Application Programming Interfaces (APIs). The use of open data in conjunction with free, platform-independent analytic tools provides the additional advantage of flexibility, re-usability, and transparency. Here, we present a strategy for performing ligand-based in silico drug repurposing with the analytics platform KNIME. We demonstrate the usefulness of the developed workflow on the basis of two different use cases: a rare disease (here: Glucose Transporter Type 1 (GLUT-1) deficiency), and a new disease (here: COVID 19). The workflow includes a targeted download of data through web services, data curation, detection of enriched structural patterns, as well as substructure searches in DrugBank and a recently deposited data set of antiviral drugs provided by Chemical Abstracts Service. Developed workflows, tutorials with detailed step-by-step instructions, and the information gained by the analysis of data for GLUT-1 deficiency syndrome and COVID-19 are made freely available to the scientific community. The provided framework can be reused by researchers for other in silico drug repurposing projects, and it should serve as a valuable teaching resource for conveying integrative data mining strategies.

Recommendations for standardizing nomenclature for dietary (poly)phenol catabolites

ABSTRACT There is a lack of focus on the protective health effects of phytochemicals in dietary guidelines. Although a number of chemical libraries and databases contain dietary phytochemicals belonging to the plant metabolome, they are not entirely relevant to human health because many constituents are extensively metabolized within the body following ingestion. This is especially apparent for the highly abundant dietary (poly)phenols, for which the situation is compounded by confusion regarding their bioavailability and metabolism, partially because of the variety of nomenclatures and trivial names used to describe compounds arising from microbial catabolism in the gastrointestinal tract. This confusion, which is perpetuated in online chemical/metabolite databases, will hinder future discovery of bioactivities and affect the establishment of future dietary guidelines if steps are not taken to overcome these issues. In order to resolve this situation, a nomenclature system for phenolic catabolites and their human phase II metabolites is proposed in this article and the basis of its format outlined. Previous names used in the literature are cited along with the recommended nomenclature, International Union of Pure and Applied Chemistry terminology, and, where appropriate, Chemical Abstracts Service numbers, InChIKey, and accurate mass.

An Integrative Drug Repurposing Pipeline Using KNIME and Programmatic Data Access: A Case Study on COVID-19 Data

Biomedical information mining is increasingly recognized as a promising technique to accelerate drug discovery and development. Especially, integrative approaches which mine data from several (open) data sources have become more attractive with the increasing possibilities to programmatically access data through Application Programming Interfaces. The use of open data in conjunction with free, platform-independent analytic tools provides the additional advantage<br>of flexibility, re-usability, and transparency. Here, we present a strategy for performing in silico drug repurposing with the analytics platform KNIME, using data for 38 suggested COVID-19 drug targets as a timely use case. The workflow includes a targeted download of data through web services, data curation (including chemical structure standardization), detection of enriched structural patterns, as well as substructure searches in DrugBank and a recently deposited dataset of antiviral drugs provided by Chemical Abstracts Service. Developed workflows, tutorials with detailed step-by-step instructions, and the information gained by the analysis of COVID-19 data are made freely available to the scientific community. The provided framework can be reused by researchers for other in silico drug repurposing projects, and it should serve as a valuable teaching resource for conveying integrative data mining strategies.

An Integrative Drug Repurposing Pipeline Using KNIME and Programmatic Data Access: A Case Study on COVID-19 Data

Biomedical information mining is increasingly recognized as a promising technique to accelerate drug discovery and development. Especially, integrative approaches which mine data from several (open) data sources have become more attractive with the increasing possibilities to programmatically access data through Application Programming Interfaces. The use of open data in conjunction with free, platform-independent analytic tools provides the additional advantage<br>of flexibility, re-usability, and transparency. Here, we present a strategy for performing in silico drug repurposing with the analytics platform KNIME, using data for 38 suggested COVID-19 drug targets as a timely use case. The workflow includes a targeted download of data through web services, data curation (including chemical structure standardization), detection of enriched structural patterns, as well as substructure searches in DrugBank and a recently deposited dataset of antiviral drugs provided by Chemical Abstracts Service. Developed workflows, tutorials with detailed step-by-step instructions, and the information gained by the analysis of COVID-19 data are made freely available to the scientific community. The provided framework can be reused by researchers for other in silico drug repurposing projects, and it should serve as a valuable teaching resource for conveying integrative data mining strategies.

Análisis del potencial genotóxico y carcinógeno asociado a los cigarrillos electrónicos

Diferentes estudios que comparan riesgos a la salud asociados a los usos de cigarrillos electrónicos y convencionales, se enfocan principalmente en compuesto quí­micos en común entre ambos sistemas. Por lo tanto, realizamos una revisión de compuestos quí­micos exclusivos de cigarrillos electrónicos. Los criterios de selección incluyeron artí­culos que reporten composición quí­mica y riesgos asociados a la salud, sin conflictos de interés. Todos los compuestos quí­micos fueron clasificados según el código del "Chemical Abstracts Service" para sustancias quí­micas. Un total de 57 compuestos fueron identificados en cigarrillos electrónicos. Para analizar los efectos carcinogénicos, un set de genes, previamente reportados como desregulados en el epitelio oral de usuarios de cigarrillos electrónicos, fueron genómicamente analizados en 32 estudios del "PanCancer Atlas". Los riesgos a la salud más importantes incluyen: irritación de tracto respiratorio, ojos y piel con un 50% de incidencia. Los tipos de cáncer con mayor riesgo identificados fueron: ovario, útero, vejiga, pulmón, esófago y estómago. A pesar de ser considerados como menos dañinos que los cigarrillos convencionales, el uso de cigarrillos electrónicos no es recomendado para ningún usuario, debido a falta de evidencia experimental.

Análisis del potencial genotóxico y carcinógeno asociado a los cigarrillos electrónicos

Diferentes estudios que comparan riesgos a la salud asociados a los usos de cigarrillos electrónicos y convencionales, se enfocan principalmente en compuesto quí­micos en común entre ambos sistemas. Por lo tanto, realizamos una revisión de compuestos quí­micos exclusivos de cigarrillos electrónicos. Los criterios de selección incluyeron artí­culos que reporten composición quí­mica y riesgos asociados a la salud, sin conflictos de interés. Todos los compuestos quí­micos fueron clasificados según el código del "Chemical Abstracts Service" para sustancias quí­micas. Un total de 57 compuestos fueron identificados en cigarrillos electrónicos. Para analizar los efectos carcinogénicos, un set de genes, previamente reportados como desregulados en el epitelio oral de usuarios de cigarrillos electrónicos, fueron genómicamente analizados en 32 estudios del "PanCancer Atlas". Los riesgos a la salud más importantes incluyen: irritación de tracto respiratorio, ojos y piel con un 50% de incidencia. Los tipos de cáncer con mayor riesgo identificados fueron: ovario, útero, vejiga, pulmón, esófago y estómago. A pesar de ser considerados como menos dañinos que los cigarrillos convencionales, el uso de cigarrillos electrónicos no es recomendado para ningún usuario, debido a falta de evidencia experimental.