Elena Díaz Santiago ¹ Aurelio Moya Garcia ¹ Jesús Pérez-García ¹ Raquel Yahyaoui ^2,3 Christine Orengo ⁴ Florencio Pazos ⁵ James Richard Perkins ^1,6* Juan A Ranea ^1,6,7

• ¹ Faculty of Science, University of Malaga, Malaga, Spain
• ² Biomedical Research Institute of Malaga, University of Malaga, Málaga, Andalusia, Spain
• ³ Laboratory of Inherited Metabolic Diseases and Newborn Screening. Malaga Regional University Hospital, Malaga, Spain
• ⁴ Research Department of Structural and Molecular Biology, University College London, London, England, United Kingdom
• ⁵ National Center for Biotechnology, Spanish National Research Council (CSIC), Madrid, Madrid, Spain
• ⁶ Andalusian Centre for Nanomedicine and Biotechnology (BIONAND), Málaga, Andalusia, Spain
• ⁷ Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Madrid Community, Spain

Most drugs fail during development and there is a clear and unmet need for approaches to better understand mechanistically how drugs exert both their intended and adverse effects. Gaining traction in this field is the use of disease data linking genes with pathological phenotypes and combining this with drug-target interaction data. In this study, we introduce methodology to associate drugs with effects, both intended and adverse, using a tripartite network approach that combines drug-target and target-phenotype data, in which targets can be represented as proteins and protein domains. We were able to detect associations for over 140,000 ChEMBL drugs and 3,800 phenotypes, represented as HPO terms. The overlap of these results with the SIDER databases of known drug side effects was up to 10 times higher than random, depending on the target type, disease database and score threshold used. In terms of overlap with drugphenotype pairs extracted from the literature, the performance of our methodology was up to 17.47 times greater than random. The top results included phenotype-drug associations that represent intended effects, particularly for cancers such as chronic myelogenous leukemia, which was linked with nilotinib. They also included adverse side effects, such as blurred vision being linked with tetracaine. This work represents an important advance in our understanding of how 1 Díaz-Santiago et al.drugs cause intended and adverse side effects through their action on disease causing genes and has potential applications for drug development and repositioning.