OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery

The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses.The Zika virus (ZIKV) has emerged as a major public health threat to the Americas as of 2015 [1]. We have previously suggested that it represents an opportunity for scientific collaboration and open scientific exchange [2]. The health of future generations may very well depend on the decisions we make, our willingness to share our findings quickly, and open collaboration to rapidly find a cure for this disease. Since February 1, 2016, when the World Health Organization deemed the cluster of microcephaly cases, Guillain-Barré, and other neurological disorders associated with ZIKV in Latin America and the Caribbean as constituting a Public Health Emergency of International Concern [3] (PHEIC), we have seen a rapid increase in publications (S1 References and main references). We [2] and others [4,5] described steps that could be taken to initiate a drug discovery program on ZIKV. For example, computational approaches, such as virtual screening of chemical libraries or focused screening to repurpose FDA and/or EU-approved drugs, can be used to help accelerate the discovery of an anti-ZIKV drug. An antiviral drug discovery program can be initiated using structure-based design, based on homology models of the key ZIKV proteins. With the lack of structural information regarding the proteins of ZIKV, we built homology models for all the ZIKV proteins, based on close homologs such as dengue virus, using freely available software [6] (S1 Table). These were made available online on March 3, 2016. We also predicted the site of glycosylation of glycoprotein E as Asn154, which was recently experimentally verified [7].Since the end of March 2016, we have now seen two cryo-EM structures and 16 crystal structures of five target classes (S1 Table). These structures, alongside the homology models, represent potential starting points for docking-based virtual screening campaigns to help find molecules that are predicted to have high affinity with ZIKV proteins. These predictions can then be tested against the virus in cell-based assays and/or using individual protein-based assays. There are millions of molecules available that can be assayed, but which ones are likely to work, and how should we prioritize them?In March, we initiated a new open collaborative project called OpenZika (Fig 1), with IBM’s World Community Grid (WCG, worldcommunitygrid.org), which has been used previously for distributed computing projects (S2 Table). On May 18, 2016, the OpenZika project began the virtual screening of ~6 million compounds that are in the ZINC database (Fig 1), as well as the FDA-approved drugs and the NIH clinical collection, using AutoDock Vina and the homology models and crystal structures (S1 Table, S1 Text, S1 References), to discover novel candidate compounds that can potentially be developed into new drugs for treating ZIKV. These will be followed by additional virtual screens with a new ZINC library of ~38 million compounds, and the PubChem database (at most ~90 million compounds), after their structures are prepared for docking.Open in a separate windowFig 1Workflow for the OpenZika project.A. Docking input files of the targets and ligands are prepared, and positive control docking studies are performed. The crystallographic binding mode of a known inhibitor is shown as sticks with dark purple carbon atoms, while the docked binding mode against the NS5 target from HCV has cyan carbons. Our pdbqt files of the libraries of compounds we screen are also openly accessible (http://zinc.docking.org/pdbqt/). B. We have already prepared the docking input files for ~6 million compounds from ZINC (i.e., the libraries that ALP previously used in the GO Fight Against Malaria project on World Community Grid), which are currently being used in the initial set of virtual screens on OpenZika. C. IBM’s World Community Grid is an internet-distributed network of millions of computers (Mac, Windows, and Linux) and Android-based tablets or smartphones in over 80 countries. Over 715,000 volunteers donate their dormant computer time (that would otherwise be wasted) towards different projects that are both (a) run by an academic or nonprofit research institute, and (b) are devoted to benefiting humanity. D. OpenZika is harnessing World Community Grid to dock millions of commercially available compounds against multiple ZIKV homology models and crystal structures (and targets from related viruses) using AutoDock Vina (AD Vina). This ultimately produces candidates (virtual hits that produced the best docking scores and displayed the best interactions with the target during visual inspection) against individual proteins, which can then be prioritized for in vitro testing by collaborators. After it is inspected, all computational data against ZIKV targets will be made open to the public on our website (http://openzika.ufg.br/experiments/#tab-id-7), and OpenZika results are also available upon request. The computational and experimental data produced will be published as quickly as possible.Initially, compounds are being screened against the ZIKV homologs of drug targets that have been well-validated in research against dengue and hepatitis C viruses, such as NS5 and Glycoprotein E (S1 Table, S1 Text, S1 References). These may allow us to identify broad-spectrum antivirals against multiple flaviviruses, such as dengue virus, West Nile virus, and yellow fever virus. In addition, docking against the crystal structure of a related protein from a different pathogen can sometimes discover novel hits against the pathogen of interest [8].As well as applying docking-based filters, the compounds virtually screened on OpenZika will also be filtered using machine learning models (S1 Text, S1 References). These should be useful selection criteria for subsequent tests by our collaborators in whole-cell ZIKV assays, to verify their antiviral activity for blocking ZIKV infection or replication. Since all OpenZika docking data will be in the public domain soon after they are completed and verified, we and other labs can then advance the development of some of these new virtual candidates into experimentally validated hits, leads, and drugs through collaborations with wet labs.This exemplifies open science, which should help scientists around the world as they address the long and arduous process of discovering and developing new drugs. Screening millions of compounds against many different protein models in this way would take far more resources and time than any academic researcher could generally obtain or spend. As of August 16, 2016, we have submitted 894 million docking jobs. Over 6,934 CPU years have been donated to us, enabling over 439 million different docking jobs. We recently selected an initial batch of candidates for NS3 helicase (data openly available at http://openzika.ufg.br/experiments/#tab-id-7), for in vitro testing. Without the unique community of volunteers and tremendous resources provided by World Community Grid, this project would have been very difficult to initiate in a reasonable time frame at this scale.The OpenZika project will ultimately generate several billion docking results, which could make it the largest computational drug discovery project ever performed in academia. The potential challenges we foresee will be finding laboratories with sufficient funding to pursue compounds, synthesize analogs, and develop target-based assays to validate our predictions and generate SAR (Structure-Activity Relationship) data to guide the process of developing the new hits into leads and then drugs. Due to the difficult nature of drug discovery and the eventual evolution of drug resistance, funding of ZIKV research once initiated will likely need to be sustained for several years, if not longer (e.g., HIV research has been funded for decades). As with other WCG projects, once scientists identify experimentally validated leads, finding a company to license them and pursue them in clinical trials and beyond will need incentives such as the FDA Tropical Disease Priority voucher, [9] which has a financial value on the open market [10].By working together and opening our research to the scientific community, many other labs will also be able to take promising molecular candidates forward to accelerate progress towards defeating the ZIKV outbreak. We invite any interested researcher to join us (send us your models or volunteer to assay the candidates we identify through this effort against any of the flaviviruses), and we hope new volunteers in the general public will donate their dormant, spare computing cycles to this cause. We will ultimately report the full computational and experimental results of this collaboration.

Advantages and Disadvantages of OpenZika

Advantages

• Open Science could accelerate the discovery of new antivirals using docking and virtual screening
• Docking narrows down compounds to test, which saves time and money
• Free to use distributed computing on World Community Grid, and the workflow is simpler than using conventional supercomputers

Disadvantages

• Concern around intellectual property ownership and whether companies will develop drugs coming from effort
• Need for experimental assays will always be a factor
• Testing in vitro and in vivo is not free, nor are the samples of the compounds

     

Glucose Metabolism Disorder Is Associated with Pulmonary Tuberculosis in Individuals with Respiratory Symptoms from Brazil

BackgroundDiabetes mellitus (DM) has been associated with increased risk for pulmonary tuberculosis (PTB) in endemic settings but it is unknown whether PTB risk is also increased by pre-DM. Here, we prospectively examined the association between glucose metabolism disorder (GMD) and PTB in patients with respiratory symptoms at a tuberculosis primary care reference center in Brazil.MethodsOral glucose tolerance test was performed and levels of fasting plasma glucose and glycohemoglobin (HbA1c) were measured in a cohort of 892 individuals presenting with respiratory symptoms of more than two weeks duration. Patients were also tested for PTB with sputum cultures. Prevalence of pre-DM and DM (based on HbA1c) was estimated and tested for association with incident PTB. Other TB risk factors including smoking history were analyzed.ResultsThe majority of the study population (63.1%) exhibited GMD based on HbA1c ≥5.7%. Patients with GMD had higher prevalence of PTB compared to normoglycemic patients. Individuals with DM exhibited increased frequency of TB-related symptoms and detection of acid-fast bacilli in sputum smears. Among patients with previous DM diagnosis, sustained hyperglycemia (HbA1c ≥7.0%) was associated with increased TB prevalence. Smoking history alone was not significantly associated with TB in our study population but the combination of smoking and HbA1c ≥7.0% was associated with 6 times higher odds for PTB.ConclusionsSustained hyperglycemia and pre-DM are independently associated with active PTB. This evidence raises the question whether improving glycemic control in diabetic TB patients would reduce the risk of TB transmission and simultaneously reduce the clinical burden of disease. A better understanding of mechanisms underlying these associations, especially those suggesting that pre-DM may be a factor driving susceptibility to TB is warranted.     

Central Coherence in Eating Disorders: A Synthesis of Studies Using the Rey Osterrieth Complex Figure Test

BackgroundLarge variability in tests and differences in scoring systems used to study central coherence in eating disorders may lead to different interpretations, inconsistent findings and between study discrepancies. This study aimed to address inconsistencies by collating data from several studies from the same research group that used the Rey Osterrieth Complex Figure Test (Rey Figure) in order to produce norms to provide benchmark data for future studies.MethodData was collated from 984 participants in total. Anorexia Nervosa, Bulimia Nervosa, recovered Anorexia Nervosa, unaffected family members and healthy controls were compared using the Rey Figure.ResultsPoor global processing was observed across all current eating disorder sub-groups and in unaffected relatives. There was no difference in performance between recovered AN and HC groups.ConclusionsThis is the largest dataset reported in the literature and supports previous studies implicating poor global processing across eating disorders using the Rey Figure. It provides robust normative data useful for future studies.     

Functional Dentition in Brazilian Adults: An Investigation of Social Determinants of Health (SDH) Using a Multilevel Approach

Objectives

Estimate the prevalence of functional dentition among Brazilian adults using four different definitions and identify associated factors.

Methods

A cross-sectional study was conducted involving 9564 Brazilian adults aged 35–44 years who participated in the 2010 National Oral Health Survey. Data collection involved oral examinations and the administration of questionnaires. The following definitions were used: 1—WHO Functional Dentition (FDWHO: ≥ 20 teeth present); 2—well-distributed teeth (WDT: ≥ 10 teeth in each arch); 3 –Functional dentition classified by esthetics and occlusion (FD_Class5: dentitions that sequentially exhibit at least one tooth in each arch, at least 10 teeth in each arch, all maxillary and mandibular anterior teeth, three or four premolar posterior occluding pairs [POPs], and at least one molar POP bilaterally); 4—Functional dentition classified by esthetics, occlusion and periodontal status (FD_Class6: corresponds to FD_Class5 with the addition of periodontal status of all sextants in the oral cavity with, at most, shallow pockets and/or clinical attachment level of 5 mm (CPI ≤ 3 and/or CAL ≤ 1). The independent variables were individual factors (gender, self-declared skin color, schooling, monthly household income, age group, self-rated treatment need, dental pain, dental appointment in the previous 12 months and dental services) and contextual factors (Municipal Human Development Index [MHDI]), Gini coefficient, fluoridated water supply and oral health coverage). Multilevel mixed-effect Poisson regression analyses were performed.

Results

The prevalence of functional dentition based on the FDWHO, WDT, FD_Class5 and FD_Class6 definitions was 77.9%, 72.9%, 42.6% and 40.3%, respectively. Adults with ≥12 years of schooling and monthly household income from US$ 853 to 2557 had higher prevalence rates of FDWHO (PR: 1.41 and 1.10, respectively), WDT (PR: 1.58 and 1.14, respectively), FD_Class5 (PR: 2.03 and 1.27, respectively) and FD_Class6 (PR: 2.15 and 1.35, respectively). These values in the final models were adjusted for gender, self-declared skin color (FD_Class5), age group, self-rated treatment need (FDWHO, FD_Class5 and FD_Class6), dental appointment in the previous 12 months (FDWHO and WDT), dental services (FDWHO and WDT) and contextual factors. A very high MHDI and presence of fluoridated water supply were associated with higher prevalence rates of the four outcomes.

Conclusions

The incorporation of the criteria of new definitions of functional dentition led to a lower prevalence rate among Brazilian adults. Striking individual and contextual inequalities were identified with regard to the four definitions analyzed, which need to be addressed through inter-sector efforts.     

Laser Doppler Flare Imaging and Quantitative Thermal Thresholds Testing Performance in Small and Mixed Fiber Neuropathies

IntroductionSmall fiber neuropathy might be a part of typical mixed small and large fiber neuropathy, or a distinct entity, affecting exclusively small nerve fibers.ObjectivesExplore the utility of small nerve fiber testing in patients with clinical presentation suggesting small fiber neuropathy, with and without evidence for concomitant large fiber neuropathy.MethodsPatients attending the neuromuscular clinic from 2012 to 2015 with a clinical presentation suggesting small nerve fiber impairment, who had Laser Doppler flare imaging (LDI_Flare) and quantitative thermal testing (QTT) were evaluated for this study. Patients with clinical or electrophysiological evidence for concomitant large fiber neuropathy were not excluded.ResultsThe sensitivities of LDI_Flare, cooling and heat threshold testing were 64%, 36%, and 0% respectively for clinically highly suggestive small fiber neuropathy, 64%, 56%, and 19% respectively for mixed fiber neuropathy, and 86%, 79%, and 29% respectively for diabetic mixed fiber neuropathy.DiscussionLDI_Flare and cooling thresholds testing are non-invasive small nerve fiber testing modalities, with moderate performance in patients with small and mixed fiber neuropathy, and excellent performance in diabetic mixed fiber neuropathy.     

High Resolution Melting Analysis Targeting hsp70 as a Fast and Efficient Method for the Discrimination of Leishmania Species

Background

Protozoan parasites of the genus Leishmania cause a large spectrum of clinical manifestations known as Leishmaniases. These diseases are increasingly important public health problems in many countries both within and outside endemic regions. Thus, an accurate differential diagnosis is extremely relevant for understanding epidemiological profiles and for the administration of the best therapeutic protocol.

Methods/Principal Findings

Exploring the High Resolution Melting (HRM) dissociation profiles of two amplicons using real time polymerase chain reaction (real-time PCR) targeting heat-shock protein 70 coding gene (hsp70) revealed differences that allowed the discrimination of genomic DNA samples of eight Leishmania species found in the Americas, including Leishmania (Leishmania) infantum chagasi, L. (L.) amazonensis, L. (L.) mexicana, L. (Viannia) lainsoni, L. (V.) braziliensis, L. (V.) guyanensis, L. (V.) naiffi and L. (V.) shawi, and three species found in Eurasia and Africa, including L. (L.) tropica, L. (L.) donovani and L. (L.) major. In addition, we tested DNA samples obtained from standard promastigote culture, naturally infected phlebotomines, experimentally infected mice and clinical human samples to validate the proposed protocol.

Conclusions/Significance

HRM analysis of hsp70 amplicons is a fast and robust strategy that allowed for the detection and discrimination of all Leishmania species responsible for the Leishmaniases in Brazil and Eurasia/Africa with high sensitivity and accuracy. This method could detect less than one parasite per reaction, even in the presence of host DNA.     

Distribution and Diversity of Pathogenic Leptospira Species in Peri-domestic Surface Waters from South Central Chile

BackgroundLeptospirosis is a neglected zoonosis affecting animals and humans caused by infection with Leptospira. The bacteria can survive outside of hosts for long periods of time in soil and water. While identification of Leptospira species from human cases and animal reservoirs are increasingly reported, little is known about the diversity of pathogenic Leptospira species in the environment and how surveillance of the environment might be used for monitoring and controlling disease.ConclusionsThis study reports the presence of pathogenic Leptospira in the peri-domestic environment of households in three community types and the differences in Leptospira diversity at the community level. Systematic environmental surveillance of Leptospira can be used for detecting changes in pathogen diversity and to identify and monitor contaminated areas where an increased risk of human infection exists.