Significance: COVID-19 has caused more than 2.5 million deaths worldwide. It is imperative that we develop therapies that can mitigate the effect of the disease. While searching for individual drugs for this purpose has been met with difficulties, synergistic drug combinations offer a promising alternative. However, the lack of high-quality training data pertaining to drug combinations makes it challenging to use existing machine learning methods for effective novel combination prediction tasks. Our proposed approach addresses this challenge by leveraging additional readily available data, such as drug−target interactions, thus enabling an effective in silico search for synergistic combinations against SARS-CoV-2.

The combination of piperaquine and dihydroartemisinin has recently become the official first-line therapy in several Southeast Asian countries. The pharmacokinetic mismatching of these drugs, whose plasma half-lives are ∼20 days and ∼1 h, respectively, implies that recrudescent or new infections emerging shortly after treatment cessation will encounter piperaquine as a monotherapy agent. This creates substantial selection pressure for the emergence of resistance. To elucidate potential resistance determinants, we subjected cloned Plasmodium falciparum Dd2 parasites to continuous piperaquine pressure in vitro (47 nM; ∼2-fold higher than the Dd2 50% inhibitory concentration [IC ₅₀ ]). The phenotype of outgrowth parasites was assayed in two clones, revealing an IC ₅₀ against piperaquine of 2.1 μM and 1.7 μM, over 100-fold greater than that of the parent. To identify the genetic determinant of resistance, we employed comparative whole-genome hybridization analysis. Compared to the Dd2 parent, this analysis found (in both resistant clones) a novel single-nucleotide polymorphism in P. falciparum crt ( pfcrt ), deamplification of an 82-kb region of chromosome 5 (that includes pfmdr1 ), and amplification of an adjacent 63-kb region of chromosome 5. Continued propagation without piperaquine selection pressure resulted in “revertant” piperaquine-sensitive parasites. These retained the pfcrt polymorphism and further deamplified the chromosome 5 segment that encompasses pfmdr1 ; however, these two independently generated revertants both lost the neighboring 63-kb amplification. These results suggest that a copy number variation event on chromosome 5 (825600 to 888300) is associated with piperaquine resistance. Transgene expression studies are underway with individual genes in this segment to evaluate their contribution to piperaquine resistance.

The National Center for Advancing Translational Sciences (NCATS) has developed an online open science platform – named the NCATS OpenData Portal (ODP) – for quickly and freely sharing complete NCATS translational datasets via an open-access, user-friendly interface. This paper describes the establishment of the ODP, initially deployed during the COVID-19 crisis, and provides a detailed analysis of COVID-19 drug repurposing screening datasets that served as the first large-scale use case for the platform. Over 10,000 compounds were tested across 17 quantitative high-throughput assays, covering a wide spectrum of the SARS-CoV-2 life cycle. In total, over 87,000 concentration-response curves and 426,000 data points were made publicly available on ODP in near real-time, enabling immediate access to complete datasets. The resource is flexible in accommodating various types and structures of data, and it has already expanded since its launch to host additional datasets for COVID-19, other viruses of pandemic potential, and beyond. The OpenData Portal has been designed as a scalable platform for real-time data sharing across drug discovery campaigns, regardless of disease area, with the overarching goal of accelerating discovery at NCATS, the NIH, and the greater scientific community.

Significance: Infection with Zika virus can cause severe consequences in a subset of the patient population. When infection occurs during pregnancy, congenital abnormalities can occur. Additionally, the onset of Guillain–Barré syndrome, encephalitis, and myelitis are associated with Zika virus infection. We have identified several small molecules with favorable clinical profiles, including the five-lipoxygenase–activating protein inhibitor, MK-591, and the tetracycline antibiotic, methacycline, as inhibitors of Zika virus infection, the latter of which reduced neurological deficits in a Zika virus mouse model. These compounds have the potential to be used as prophylactics or for the treatment of the neurological complications of Zika virus infection.