The COVID-19 PHARMACOME: A method for the rational selection of drug repurposing candidates from multimodal knowledge harmonization

Abstract

The SARS-CoV-2 pandemic has challenged researchers at a global scale. The scientific community's massive response has resulted in a flood of experiments, analyses, hypotheses, and publications, especially in the field drug repurposing. However, many of the proposed therapeutic compounds obtained from SARS-CoV-2 specific assays are not in agreement and thus demonstrate the need for a singular source of COVID-19 related information from which a rational selection of drug repurposing candidates can be made. In this paper, we present the COVID-19 PHARMACOME, a comprehensive drug-target-mechanism graph generated from a compilation of several disease maps and experimental data focused on SARS-CoV-2 / COVID-19 pathophysiology. By applying a systematic approach, we were able to predict the effect of drug pairs on SARS-CoV-2 infection. Experimental validation of our results demonstrate that our graph can be used to not only explore the involved mechanistic pathways, but also to identify novel combinations of drug repurposing candidates.

The role of human C5a as a non-genomic target in corticosteroid therapy for management of severe COVID19

“…In this regard, our recent studies ( Mishra et al, 2020 ) suggest that raloxifene, which is prescribed to alleviate the pain and inflammation in rheumatoid arthritis can be explored as a non-specific immunomodulator either as monotherapy or in combination with other synergistic drugs, as an alternative polytherapy for possible management of COVID19. In fact, raloxifene’s potential as an antiviral agent ( Hong et al, 2021 ) has recently been explored and repurposing of raloxifene alone or in synergistic combination with nelfinavir ( Schultz et al, 2021 ) for treatment of SARS-CoV2 infection is currently being explored. Among all non-specific immunomodulators being tested, corticosteroids have shown remarkable results in managing severe COVID19 ( Sterne et al, 2020 ) so far across the globe.…”

Neurosymbolic AI for Reasoning on Graph Structures: A Survey

“…KG completion (KGC) denotes a series of methods which can be used to refine the graphs and uncover novel information. For example, such completion can reveal unknown molecular functions in a biological KG [133,38] or predict user connections in a social KG [69].…”

“…K NOWLEDGE GRAPHS (KGs) are becoming an increasingly popular way to represent information because they are multi-relational, easily queried, and can store various types of data in a similar, consistent format [154]. Furthermore, numerous methods have been developed to mine information and make novel predictions from KGs [71,158], leading to advancements in drug discovery [133,173], improved user recommendation systems [163], and more efficient traffic forecasting [57,159,165], amongst many other applications. Traditionally, to make novel predictions about a knowledge base, such approaches utilized either a set of rules or generated low-dimensional, numerical representations from which patterns could be extracted.…”

“…Some of the best known KGs, such as YAGO [144], Google's KG [139], and DBpedia [6] contain millions of entities and relations representing general information about people, places, and other general items such as movies and music and are widely used as benchmark datasets. Other smaller KGs exist to store information about niche areas, such as the recent COVID-19 pandemic [38,133,157].…”

Estrogen Receptor Modulators in Viral Infections Such as SARS−CoV−2: Therapeutic Consequences

“…These mechanisms were also dependent on the interaction of hormones with their receptors. The inhibitory effect of estrogens on replication was documented [ 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 ]. in a panel of viruses (for particulars see Table 1 ).…”