Towards De Novo Drug Design for the Coronavirus: A Drug-Target Interaction Prediction Approach using Atom-enhanced Graph Neural Network with Multi-hop Gating Mechanism

For humans, the COVID-19 pandemic and Coronavirus have undeniably been a nightmare. Although there are effective vaccines, specific drugs are still urgent. Normally, to identify potential drugs, one needs to design and then test interactions between the drug and the virus in an in silico manner for determining candidates. This Drug-Target Interaction (DTI) process, can be done by molecular docking, which is too complicated and time-consuming for manual works. Therefore, it opens room for applying Artificial Intelligence (AI) techniques. In particular, Graph Neural Network (GNN) attracts recent attention since its high suitability for the nature of drug compounds and virus proteins. However, to introduce such a representation well-reflecting biological structures of biological compounds is not a trivial task. Moreover, since available datasets of Coronavirus are still not highly popular, the recently developed GNNs have been suffering from overfitting on them. We then address those issues by proposing a novel model known as Atom-enhanced Graph Neural Network with Multi-hop Gating Mechanism. On one hand, our model can learn more precise features of compounds and proteins. On the other hand, we introduce a new gating mechanism to create better atom representation from non-neighbor information. Once applying transfer learning from very large databanks, our model enjoys promising performance, especially when experimenting with Coronavirus. © 2022 IEEE.

The SARS-CoV-2 accessory protein Orf3a is not an ion channel, but does interact with trafficking proteins.

The severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) and SARS-CoV-1 accessory protein Orf3a colocalizes with markers of the plasma membrane, endocytic pathway, and Golgi apparatus. Some reports have led to annotation of both Orf3a proteins as viroporins. Here, we show that neither SARS-CoV-2 nor SARS-CoV-1 Orf3a form functional ion conducting pores and that the conductances measured are common contaminants in overexpression and with high levels of protein in reconstitution studies. Cryo-EM structures of both SARS-CoV-2 and SARS-CoV-1 Orf3a display a narrow constriction and the presence of a positively charged aqueous vestibule, which would not favor cation permeation. We observe enrichment of the late endosomal marker Rab7 upon SARS-CoV-2 Orf3a overexpression, and co-immunoprecipitation with VPS39. Interestingly, SARS-CoV-1 Orf3a does not cause the same cellular phenotype as SARS-CoV-2 Orf3a and does not interact with VPS39. To explain this difference, we find that a divergent, unstructured loop of SARS-CoV-2 Orf3a facilitates its binding with VPS39, a HOPS complex tethering protein involved in late endosome and autophagosome fusion with lysosomes. We suggest that the added loop enhances SARS-CoV-2 Orf3a's ability to co-opt host cellular trafficking mechanisms for viral exit or host immune evasion.

Forecast of the Development of COVID-19 Based on the Small-World Network

This world has faced a severe challenge since the breakout of the novel Coronavirus-2019 (COVID-19) has started for more than one year. With the mutation of the virus, the measures of epidemic prevention are keeping upgrading. Various vaccines have been created and brought into operation. To accurately describe and predict the spread of COVID-19, we improve the traditional Susceptible-Exposed-Infected-Removed-Dead model(SEIRD), forecast the development of COVID-19 based on small-world network. A small-world network is a type of mathematical graph in which most nodes are not neighbors of one another, but the neighbors of any given node are likely to be neighbors of each other, and most nodes can be reached from every other node by a small number of hops or steps. We introduce new parameters, Vaccination(V) and Quarantine(Q), into this model. Based on this, through regressing and analyzing the epidemic in the UK, we get the simulation that fits well with the observed data in other countries. © 2021 ACM.

Does Multi-Hop Crowdsourcing Work? A Case Study on Collecting COVID-19 Local Information

The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe from the beginning of 2020 and people worldwide have been receiving news about the same from government offices, press conferences and various other media outlets. The COVID-19 Information Watcher Project started in 2020 to collect and organize reliable information sources worldwide. However, it is difficult to automatically identify reliable information sources in foreign countries for several reasons. First, what kind of information sources are reliable heavily depend on each county situation. In some countries people trust their government's official information but in other countries they do not. Secondly, such reliable information sources often provide information in their local languages. Reliable information sources are not necessarily top-ranked by search engines. Crowdsourcing is a promising way to deal with such a case. However, crowd-sourcing platforms do not cover crowds in all countries. In this study, we report some results of our attempt to collect local information regarding COVID-19 from several countries through multi-hop crowdsourcing, in which we allow crowd workers on a crowdsourcing platform to use other platforms in other countries. We show two case studies, Russia and Afghanistan. Our results show that the multi-hop crowdsourcing is a promising way to collect COVID-19 information from different countries. © 2021 IEEE.

Saving Bavarian Hops in a "Parallel Universe": Lessons on the Biopolitics of Agricultural Labor in Germany During the Corona Pandemic

When countries closed their borders to curb the spread of COVID-19 in spring 2020, seasonal migrant workers in agriculture were either unable to travel or faced unsafe conditions when performing "essential" field work. Some countries, like Germany, subsequently implemented policies to let them travel to work, and simultaneously, called on their residents to temporarily help farmers harvest crops. This paper explores the case of these temporary pandemic workers on Bavarian hops farms. Based on ethnographic research and interviews, this paper discusses the complex relationships between temporary pandemic workers, farmers, and the mostly absent seasonal workers in the exceptional moment of a global pandemic. We argue that in the state of exception of the Corona pandemic in Germany, biopolitical sorting highlighted migrant workers' indispensability and disposability in a peculiar way: their short-term replaceability through recruited temporary pandemic workers formed a self-ascribed "parallel universe" or "Coronal bubble". Through new encounters (with farmers) and hands-on experiences in agricultural fields, the parallel universe often also meant uncomfortable insights into an unjust agricultural system. For those widely unexposed to agriculture, the state of exception revealed both the general and temporary biopolitics of seasonal migrant workers in agriculture and the key role they play for German agriculture as a whole.

Structural similarity-based prediction of host factors associated with SARS-CoV-2 infection and pathogenesis.

The current pandemic resulted from SARS-CoV-2 still remains as the major public health concern globally. The precise mechanism of viral pathogenesis is not fully understood, which remains a major hurdle for medical intervention. Here we generated an interactome profile of protein-protein interactions based on host and viral protein structural similarities information. Further computational biological study combined with Gene enrichment analysis predicted key enriched pathways associated with viral pathogenesis. The results show that axon guidance, membrane trafficking, vesicle-mediated transport, apoptosis, clathrin-mediated endocytosis, Vpu mediated degradation of CD4 T cell, and interferon-gamma signaling are key events associated in SARS-CoV-2 life cycle. Further, degree centrality analysis reveals that IRF1/9/7, TP53, and CASP3, UBA52, and UBC are vital proteins for IFN-γ-mediated signaling, apoptosis, and proteasomal degradation of CD4, respectively. We crafted chronological events of the virus life cycle. The SARS-CoV-2 enters through clathrin-mediated endocytosis, and the genome is trafficked to the early endosomes in a RAB5-dependent manner. It is predicted to replicate in a double-membrane vesicle (DMV) composed of the endoplasmic reticulum, autophagosome, and ERAD machinery. The SARS-CoV-2 down-regulates host translational machinery by interacting with protein kinase R, PKR-like endoplasmic reticulum kinase, and heme-regulated inhibitor and can phosphorylate eIF2a. The virion assembly occurs in the ER-Golgi intermediate compartment (ERGIC) organized by the spike and matrix protein. Collectively, we have established a spatial link between viral entry, RNA synthesis, assembly, pathogenesis, and their associated diverse host factors, those could pave the way for therapeutic intervention.

ORF3a of the COVID-19 virus SARS-CoV-2 blocks HOPS complex-mediated assembly of the SNARE complex required for autolysosome formation.

Autophagy acts as a cellular surveillance mechanism to combat invading pathogens. Viruses have evolved various strategies to block autophagy and even subvert it for their replication and release. Here, we demonstrated that ORF3a of the COVID-19 virus SARS-CoV-2 inhibits autophagy activity by blocking fusion of autophagosomes/amphisomes with lysosomes. The late endosome-localized ORF3a directly interacts with and sequestrates the homotypic fusion and protein sorting (HOPS) component VPS39, thereby preventing HOPS complex from interacting with the autophagosomal SNARE protein STX17. This blocks assembly of the STX17-SNAP29-VAMP8 SNARE complex, which mediates autophagosome/amphisome fusion with lysosomes. Expression of ORF3a also damages lysosomes and impairs their function. SARS-CoV-2 virus infection blocks autophagy, resulting in accumulation of autophagosomes/amphisomes, and causes late endosomal sequestration of VPS39. Surprisingly, ORF3a from the SARS virus SARS-CoV fails to interact with HOPS or block autophagy. Our study reveals a mechanism by which SARS-CoV-2 evades lysosomal destruction and provides insights for developing new strategies to treat COVID-19.