Combating Ebola with Repurposed Therapeutics Using the CANDO Platform
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molecules Article Combating Ebola with Repurposed Therapeutics Using the CANDO Platform Gaurav Chopra 1,*, Sashank Kaushik 2,3, Peter L. Elkin 2,3 and Ram Samudrala 2,* 1 Department of Chemistry; Purdue Institute for Drug Discovery; Purdue Institute for Inflammation, Immunology, and Infectious Disease; Purdue Institute for Integrative Neuroscience; Purdue Center for Cancer Research, Purdue University, West Lafayette, IN 47907, USA 2 Department of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA; [email protected] (S.K.); [email protected] (P.L.E.) 3 Department of Internal Medicine, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA * Correspondence: [email protected] (G.C.); [email protected] (R.S.); Tel.: +1-765-496-6108 (G.C.); +1-206-251-8852 (R.S.) Academic Editor: Derek J. McPhee Received: 29 July 2016; Accepted: 28 October 2016; Published: 25 November 2016 Abstract: Ebola virus disease (EVD) is extremely virulent with an estimated mortality rate of up to 90%. However, the state-of-the-art treatment for EVD is limited to quarantine and supportive care. The 2014 Ebola epidemic in West Africa, the largest in history, is believed to have caused more than 11,000 fatalities. The countries worst affected are also among the poorest in the world. Given the complexities, time, and resources required for a novel drug development, finding efficient drug discovery pathways is going to be crucial in the fight against future outbreaks. We have developed a Computational Analysis of Novel Drug Opportunities (CANDO) platform based on the hypothesis that drugs function by interacting with multiple protein targets to create a molecular interaction signature that can be exploited for rapid therapeutic repurposing and discovery. We used the CANDO platform to identify and rank FDA-approved drug candidates that bind and inhibit all proteins encoded by the genomes of five different Ebola virus strains. Top ranking drug candidates for EVD treatment generated by CANDO were compared to in vitro screening studies against Ebola virus-like particles (VLPs) by Kouznetsova et al. and genetically engineered Ebola virus and cell viability studies by Johansen et al. to identify drug overlaps between the in virtuale and in vitro studies as putative treatments for future EVD outbreaks. Our results indicate that integrating computational docking predictions on a proteomic scale with results from in vitro screening studies may be used to select and prioritize compounds for further in vivo and clinical testing. This approach will significantly reduce the lead time, risk, cost, and resources required to determine efficacious therapies against future EVD outbreaks. Keywords: drug repurposing and discovery; multitarget docking; compound–proteome interaction; candock 1. Introduction The 2014 Ebola epidemic was caused by a divergent strain of the Zaire Ebola Virus [1] and is believed to have affected more than 28,000 individuals globally, with an estimated mortality of 74% in confirmed Ebola cases [2]. The mainstay of EBV prevention and treatment is infection control precautions and supportive care to the affected individual(s) in order to maintain cardiovascular function while their immune system mobilizes an adaptive response. Considering the complexity [3] and cost [4] of developing a new drug combined with the fact that countries worst affected were also Molecules 2016, 21, 1537; doi:10.3390/molecules21121537 www.mdpi.com/journal/molecules Molecules 2016, 21, 1537 2 of 11 among the poorest in the world, finding an alternate cheaper route for future EVD outbreak treatments is of paramountMolecules 2016, 21 importance., 1537 2 of 12 Traditional approaches to drug discovery are highly specific to single targets (molecules and indications),among the focusing poorest in on the a world, limited find seting of an interactions alternate cheaper between route for individual future EVD protein outbreak targets treatments and is small moleculeof paramount compounds, importance. but applying the resulting treatments universally to all patients. The goal Traditional approaches to drug discovery are highly specific to single targets (molecules and generally is to target an essential protein responsible for pathogenesis so as to completely inhibit its indications), focusing on a limited set of interactions between individual protein targets and small function, and then determine its toxicity or side effect profile for human use. Almost all current drugs molecule compounds, but applying the resulting treatments universally to all patients. The goal havegenerally been developed is to target by an this essential approach. protein However, responsible the for number pathogenesis of novel so drugsas to completely being discovered inhibit its every year hasfunction, been reducedand then todetermine a handful. its toxicity Currently, or side less effect than profile 50 new for drugs human are use. approved Almost all each current year, drugs and most of themhave are been analogues developed to by other this existing approach. drugs However, or other the number patentworkarounds of novel drugs [being5]. The discovered estimated every average costsyear for developinghas been reduced a novel to a drug handful. and Currently, bringing itless to than market 50 new can drugs be up are to approved $2.6 billion each [6 ].year, Thus, and there is a dearthmost of of them novel are druganalogues development, to other existing which drug is time-s or other and patent cost-prohibitive workarounds [7 [5].–10 ],The particularly estimated for rapidlyaverage emerging costs for indications developing such a novel as divergent drug and bringing strain EVD it to outbreaksmarket can orbe neglectedup to $2.6 billion indications [6]. Thus, such as orphanthere diseases is a dearth [11]. of novel drug development, which is time- and cost-prohibitive [7–10], particularly for rapidly emerging indications such as divergent strain EVD outbreaks or neglected indications One solution is to repurpose and reposition existing drugs that are relatively benign in terms of such as orphan diseases [11]. side effects for new indications [11–19]. We were one of the first to propose shotgun drug repurposing One solution is to repurpose and reposition existing drugs that are relatively benign in terms of for malariaside effects based for new on computational indications [11–19]. multitarget We were one docking of the first with to dynamicspropose shotgun [15]. drug Since repurposing then, we have validatedfor malaria our predictive based on computational models numerous multitarget times docking [9,16– 18with,20 –dynamics22]. This [15]. repurposing Since then, canwe have be made morevalidated accurate our by predictive considering models variations numerous (mutations) times [9,16–18,20–22]. in proteins This encoded repurposing by can individual be made more genomes. Systematicaccurate exploration by considering of drug variations repurposing (mutations) opportunities in proteins is hindered encoded by extensiveby individual competition genomes. in the pharmaceuticalSystematic exploration industry. We of drug utilize repurposing this repurposing opportunities paradigm is hindered along withby extensive a computational competition platform in we havethe developedpharmaceutical that industry. evaluates We relationships utilize this repurposing between compound–proteome paradigm along with interaction a computational signatures to predictplatform genome- we have and developed indication-specific that evaluates drug relationships regimens between for particular compound–proteome individuals in interaction a shotgun and signatures to predict genome- and indication-specific drug regimens for particular individuals in a holistic manner (i.e., against all indications simultaneously). To assess and improve the accuracy of shotgun and holistic manner (i.e., against all indications simultaneously). To assess and improve the our platform, we collaborate with experimental investigators for preclinical and clinical validation of accuracy of our platform, we collaborate with experimental investigators for preclinical and clinical our topvalidation ranking of drug our top candidates ranking drug (see Figurecandidates1). The (see experimental Figure 1). The resultsexperimental obtained results are obtained integrated are back into theintegrated modeling back platform into the modeling to iteratively platform improve to iteratively its accuracy. improve its accuracy. FigureFigure 1. The 1. The Computational Computational Analysis Analysis of of Novel Novel DrugDrug Opportunities (CANDO) (CANDO) platform platform as applied as applied to fiveto Ebolafive Ebola proteomes. proteomes. ( A(A)) GeneralGeneral version version of ofthe the platform platform used usedto determine to determine drug behavior drug behaviorand similarity by performing a virtual screen to predict interactions between “all” known drugs and “all” and similarity by performing a virtual screen to predict interactions between “all” known drugs protein structures; (B) CANDO platform as applied to Ebola, where the known drugs are docked to and “all” protein structures; (B) CANDO platform as applied to Ebola, where the known drugs are structures of five Ebola proteomes to identify the strongest multitarget inhibitors. Credit: Vignettes dockedderived to structures from Protein of five Data Ebola Bank (PDB) proteomes structures to identify depicting the Ebola strongest