A Structure-based B-cell Epitope Prediction Model Through Combing Local and Global Features (preprint)

ABSTRACT B-cell epitopes (BCEs) are a set of specific sites on the surface of an antigen that binds to an antibody produced by B-cell. The recognition of BCEs is a major challenge for drug design and vaccines development. Compared with experimental methods, computational approaches have strong potential for BCEs prediction at much lower cost. Moreover, most of the currently methods focus on using local information around target residue without taking the global information of the whole antigen sequence into consideration. We propose a novel deep leaning method through combing local features and global features for BCEs prediction. In our model, two parallel modules are built to extract local and global features from the antigen separately. For local features, we use Graph Convolutional Networks(GCNs) to capture information of spatial neighbors of a target residue. For global features, Attention-Based Bidirectional Long Short-Term Memory(Att-BLSTM) networks are applied to extract information from the whole antigen sequence. Then the local and global features are combined to predict BCEs. The experiments show that the proposed method achieves superior performance over the state-of-the-art BCEs prediction methods on benchmark datasets. Also, we compare the performance differences between data with or without global features. The experimental results show that global features play an important role in BCEs prediction. Our detailed case study on the BCEs prediction for SARS-Cov-2 receptor binding domain confirms that our method is effective for predicting and clustering true BCEs.

Detecting epidemiological relevance among adenoid hypertrophy, rhinosinusitis, and allergic rhinitis through Internet search (preprint)

Purpose : This study aimed to verify that adenoid hypertrophy (AH) and rhinosinusitis share similar epidemiologic patterns and that AH and allergic rhinitis (AR) are not related. Methods: Internet search engine query data from January 2011 to December 2019 were retrieved from the Baidu index. Monthly search volume was obtained in China for the following search terms in Chinese: “adenoid hypertrophy,” “rhinosinusitis,” and “allergic rhinitis”; the data obtained were then presented as percentages. Pearson’s and Spearman’ s correlation coefficients were used to detect the correlation among the search volumes of AH, rhinosinusitis, and AR. We also collected search data from the first 5 months of 2020, when segregation was implemented in China due to the coronavirus disease 2019 epidemic. Then, we compared the search data to those obtained during the same period in 2019 to detect the effects of segregation on AH and AR to varying degrees. Results: Statistically significant differences were found between the search variations of AH and rhinosinusitis during 2011–2019 (R=0.643, P<0.05). However, search variations of AH and AR were negatively related (R=-0.239, P<0.05). The average monthly search volume of AH and rhinosinusitis correlated well (R=0.836, P<0.01), but no correlation was found between AH and AR. The search volume of AH and rhinosinusitis during the first 5 months in 2020 decreased, whereas that of AR increased during January–February. Conclusions: AH and rhinosinusitis are epidemiologically related, whereas AH and AR are not correlated with each other.

Protein corona critically affects the bio-behaviors of SARS-CoV-2 (preprint)

The outbreak of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a worldwide public health crisis. When the SARS-CoV-2 enters the biological fluids in the human body, different types of biomolecules (in particular proteins) may adsorb on its surface and alter its infection ability. Although great efforts have recently been devoted to the interaction of the specific antibodies with the SARS-CoV-2, it still remains largely unknown how the other serum proteins affect the infection of the SARS-CoV-2. In this work, we systematically investigate the interaction of serum proteins with the SARS-CoV-2 RBD by the molecular docking and the all-atom molecular dynamics simulations. It is found that the non-specific immunoglobulin (Ig) indeed cannot effectively bind to the SARS-CoV-2 RBD while the human serum albumin (HSA) may have some potential of blocking its infection (to ACE2). More importantly, we find that the RBD can cause the significant structural change of the Apolipoprotein E (ApoE), by which SARS-CoV-2 may hijack the metabolic pathway of the ApoE to facilitate its cell entry. The present study enhances the understanding of the role of protein corona in the bio-behaviors of SARS-CoV-2, which may aid the more precise and personalized treatment for COVID-19 infection in the clinic.

Accurate Evaluation on the Interactions of SARS-CoV-2 with Its Receptor ACE2 and Antibodies CR3022/CB6 (preprint)

The spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a global health crisis. The binding affinity of SARS-CoV-2 (in particular the receptor binding domain, RBD) to its receptor angiotensin converting enzyme 2 (ACE2) and the antibodies is of great importance in understanding the infectivity of COVID-19 and evaluating the candidate therapeutic for COVID-19. In this work, we propose a new method based on molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) to accurately calculate the free energy of SARS-CoV-2 RBD binding to ACE2 and antibodies. The calculated binding free energy of SARS-CoV-2 RBD to ACE2 is -13.3 kcal/mol, and that of SARS-CoV RBD to ACE2 is -11.4 kcal/mol, which agrees well with experimental result (-11.3 kcal/mol and -10.1 kcal/mol, respectively). Moreover, we take two recently reported antibodies as the example, and calculate the free energy of antibodies binding to SARS-CoV-2 RBD, which is also consistent with the experimental findings. Further, within the framework of the modified MM/PBSA, we determine the key residues and the main driving forces for the SARS-CoV-2 RBD/CB6 interaction by the computational alanine scanning method. The present study offers a computationally efficient and numerically reliable method to evaluate the free energy of SARS-CoV-2 binding to other proteins, which may stimulate the development of the therapeutics against the COVID-19 disease in real applications.

Modeling the Opening SARS-CoV-2 Spike: an Investigation of its Dynamic Electro-Geometric Properties (preprint)

The recent COVID-19 pandemic has brought about a surge of crowd-sourced initiatives aimed at simulating the proteins of the SARS-CoV-2 virus. A bottleneck currently exists in translating these simulations into tangible predictions that can be leveraged for pharmacological studies. Here we report on extensive electrostatic calculations done on an exascale simulation of the opening of the SARS-CoV-2 spike protein, performed by the Folding@home initiative. We compute the electric potential as the solution of the non-linear Poisson-Boltzmann equation using a parallel sharp numerical solver. The inherent multiple length scales present in the geometry and solution are reproduced using highly adaptive Octree grids. We analyze our results focusing on the electro-geometric properties of the receptor-binding domain and its vicinity. This work paves the way for a new class of hybrid computational and data-enabled approaches, where molecular dynamics simulations are combined with continuum modeling to produce high-fidelity computational measurements serving as a basis for protein bio-mechanism investigations.

Large-scale single-cell analysis reveals critical immune characteristics of COVID-19 patients (preprint)

Dysfunctional immune response in the COVID-19 patients is a recurrent theme impacting symptoms and mortality, yet the detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 205 COVID-19 patients and controls to create a comprehensive immune landscape. Lymphopenia and active T and B cell responses were found to coexist and associated with age, sex and their interactions with COVID-19. Diverse epithelial and immune cell types were observed to be virus-positive and showed dramatic transcriptomic changes. Elevation of ANXA1 and S100A9 in virus-positive squamous epithelial cells may enable the initiation of neutrophil and macrophage responses via the ANXA1-FPR1 and S100A8/9-TLR4 axes. Systemic up-regulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis and designing effective therapeutic strategies for COVID-19.

Rhabdomyolysis is Associated with Hospital Mortality in Patients with COVID-19 (preprint)

Purpose: To evaluate the clinical features and outcomes of rhabdomyolysis (RM) in patients with COVID-19. Method: A single center retrospective cohort study of 1,014 consecutive hospitalized patients with confirmed COVID-19 at the Huoshenshan hospital in Wuhan, China, between February 17 and April 12, 2020. Results: : The overall incidence of RM was 2.2%. Comparing with patients without RM, patients with RM tended to have a higher risk of deterioration, representing by higher ratio to be admitted to the intensive care unit (ICU) (90.9 % vs 5.3%, P <0.001), and to undergo mechanical ventilation (86.4 % vs 2.7% P <0.001). Compared with patients without RM, patients with RM had laboratory test abnormalities, including indicators of inflammation, coagulation activation and kidney injury. Patients with RM had a higher risk of hospital death ( P < 0.001). Cox proportional hazard regression model confirmed that RM indicators, including peak creatine kinase (CK) >1000 IU/L (HR=6.46, 95% CI: 3.02-13.86), peak serum myoglobin (MYO) >1000 ng/mL (HR=9.85, 95% CI: 5.04-19.28) were independent risk factors for in-hospital death. Additionally, patients with COVID-19 that developed RM tended to have a delayed virus clearance. Conclusion: RM might be an important factor contributing to adverse outcomes of patients with COVID-19. Early detection and effective intervention of RM may help reduce deaths of patients with COVID-19.

Single-cell RNA-seq and V(D)J profiling of immune cells in COVID-19 patients (preprint)

Coronavirus disease 2019 (COVID-19) has caused over 220,000 deaths so far and is still an ongoing global health problem. However, the immunopathological changes of key types of immune cells during and after virus infection remain unclear. Here, we enriched CD3+ and CD19+ lymphocytes from peripheral blood mononuclear cells of COVID-19 patients (severe patients and recovered patients at early or late stages) and healthy people (SARS-CoV-2 negative) and revealed transcriptional profiles and changes in these lymphocytes by comprehensive single-cell transcriptome and V(D)J recombination analyses. We found that although the T lymphocytes were decreased in the blood of patients with virus infection, the remaining T cells still highly expressed inflammatory genes and persisted for a while after recovery in patients. We also observed the potential transition from effector CD8 T cells to central memory T cells in recovered patients at the late stage. Among B lymphocytes, we analyzed the expansion trajectory of a subtype of plasma cells in severe COVID-19 patients and traced the source as atypical memory B cells (AMBCs). Additional BCR and TCR analyses revealed a high level of clonal expansion in patients with severe COVID-19, especially of B lymphocytes, and the clonally expanded B cells highly expressed genes related to inflammatory responses and lymphocyte activation. V-J gene usage and clonal types of higher frequency in COVID-19 patients were also summarized. Taken together, our results provide crucial insights into the immune response against patients with severe COVID-19 and recovered patients and valuable information for the development of vaccines and therapeutic strategies.