We would pick fewer targets to dock molecules into as the OpenZika project created billions of docking results for tens of targets that will take many years to process. scientists involved in drug discovery. A lack of available antivirals to treat the infected patients leads to a clamoring to test anything available, and some pharmaceutical companies charge in LY317615 (Enzastaurin) to offer their drugs. We also seem to see similar patterns in response across outbreaks. There is a rush LY317615 (Enzastaurin) to be first and this sense of priority might not lead to the best or even any outcome for patients. Always, there is the immediate proposal to create a vaccine and pronouncements that this will be available in a short time or by the end of the year of HIST1H3G the actual outbreak in question; and it never happens within these optimistic artificial deadlines. Again, we have experienced this with the current outbreak. For Ebola the vaccine was ready for the second outbreak and has now been approved [6] . Governments are out to calm their populations while, at the same time, needing to be seen to do something that will vanquish the virus. In the case of SARS-CoV-2 it results in pneumonia [7] and shares aspects of pathology and pathogenesis with severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) [8]. SARS-CoV-2, SARS-CoV and MERS-CoV belong to the same family and genus against SARS-CoV-2 (Table 1 ) and shown to be active [14]. Some researchers had also suggested as early as January 2020 what treatment options might be most likely and these included lopinavir/ritonavir, remdesivir, favilavir, arbidol, as well as a broad array of nucleoside analogs, neuraminidase inhibitors, peptides, RNA synthesis inhibitors, anti-inflammatory drugs and traditional Chinese medicines 15, 16, 17. Table 1 Compounds screened SARS-CoV-2: Vero E6 cells were infected with nCoV- 2019BetaCoV/Wuhan/WIV04/2019 at a multiplicity of infection (MOI) of 0.05 [14] Ebola active compounds [22]. This was followed by identifying and summarizing all the FDA-approved drugs that could be used against the virus 23, 24 and highlighting various strategies for the next virus outbreak [21]. These steps preceded a pivotal point for us in developing machine learning models for the Ebola virus derived from data 25, 26. An early drug [22] identified by these screens was the antimalarial amodiaquine, which was subsequently shown to be associated with decreased mortality [27], as the drug (artesunate/amodiaquine) was used for malaria treatment in some Ebola patients, whereas others took a different malaria medicine (artemether/lumefantrine) [27] . Our Ebola machine learning models were used to select three molecules for testing [28]. We identified pyronaridine, tilorone and quinacrine as having good activity (nM) against the Ebola virus [28]. These preliminary data enabled us to obtain funding from LY317615 (Enzastaurin) the NIH to take one of the compounds through testing. We also leveraged NIH support to a collaborator to test the other two compounds as well. These molecules were then each tested in the mouse model for Ebola infection and demonstrated significant efficacy 29, 30, 31. Pyronaridine is currently being pursued in larger animal models of Ebola disease illness. Working on computational models through to screening happened in the space of a few weeks, whereas it required several years to obtain funding for our 1st mouse studies. This is by no means a LY317615 (Enzastaurin) streamlined approach to drug discovery but it was cost effective for the amount of data ultimately generated and led to revitalized desire for these molecules. The OpenZika drug discovery encounter In 2016 we drawn together a team of experts in Brazil and the USA to provide some suggestions for an open drug discovery effort for the Zika disease. These included numerous computational strategies to repurpose molecules and docking into the Zika proteins [32]. We also explained resources and molecules that may be prioritized for screening. This was followed by our homology modeling of every Zika disease protein [33] weeks before the.