Protocol to identify host-viral protein interactions between coagulation-related proteins and their genetic variants with SARS-CoV-2 proteins.

Here, we describe a bioinformatics pipeline that evaluates the interactions between coagulation-related proteins and genetic variants with SARS-CoV-2 proteins. This pipeline searches for host proteins that may bind to viral protein and identifies and scores the protein genetic variants to predict the disease pathogenesis in specific subpopulations. Additionally, it is able to find structurally similar motifs and identify potential binding sites within the host-viral protein complexes to unveil viral impact on regulated biological processes and/or host-protein impact on viral invasion or reproduction. For complete details on the use and execution of this protocol, please refer to Holcomb et al. (2021).

New approaches to predict the effect of co-occurring variants on protein characteristics.

Predicting the effect of a mutated gene before the onset of symptoms of genetic diseases would greatly facilitate diagnosis and potentiate early intervention. There have been myriad attempts to predict the effects of single-nucleotide variants. However, the applicability of these efforts does not scale to co-occurring variants. Furthermore, an increasing number of protein therapeutics contain co-occurring nucleotide variations, adding uncertainty during development to the safety and efficiency of these drugs. Co-occurring nucleotide variants may often have synergistic, additive, or antagonistic effects on protein attributes, further complicating the task of outcome prediction. We tested four models based on the cooperative and antagonistic effects of co-occurring variants to predict pathogenicity and effectiveness of protein therapeutics. A total of 30 attributes, including amino acid and nucleotide features, as well as existing single-variant effect prediction tools, were considered on the basis of previous studies on single-nucleotide variants. Importantly, the effects of synonymous variants, often seen in protein therapeutics, were also included in our models. We used 12 datasets of people with monogenic diseases and controls with co-occurring genetic variants to evaluate the accuracy of our models, accomplishing a degree of accuracy comparable to that of prediction tools for single-nucleotide variants. More importantly, our framework is generalizable to new, well-curated datasets of monogenic diseases and new variant scoring tools. This approach successfully assists in addressing the challenging task of predicting the effect of co-occurring variants on pathogenicity and protein effectiveness and is applicable for a wide range of protein therapeutics and genetic diseases.

In Silico Evaluation of Cyclophilin Inhibitors as Potential Treatment for SARS-CoV-2.

BACKGROUND: The advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provoked researchers to propose multiple antiviral strategies to improve patients' outcomes. Studies provide evidence that cyclosporine A (CsA) decreases SARS-CoV-2 replication in vitro and decreases mortality rates of coronavirus disease 2019 (COVID-19) patients. CsA binds cyclophilins, which isomerize prolines, affecting viral protein activity. METHODS: We investigated the proline composition from various coronavirus proteomes to identify proteins that may critically rely on cyclophilin's peptidyl-proline isomerase activity and found that the nucleocapsid (N) protein significantly depends on cyclophilin A (CyPA). We modeled CyPA and N protein interactions to demonstrate the N protein as a potential indirect therapeutic target of CsA, which we propose may impede coronavirus replication by obstructing nucleocapsid folding. RESULTS: Finally, we analyzed the literature and protein-protein interactions, finding evidence that, by inhibiting CyPA, CsA may impact coagulation proteins and hemostasis. CONCLUSIONS: Despite CsA's promising antiviral characteristics, the interactions between cyclophilins and coagulation factors emphasize risk stratification for COVID patients with thrombosis dispositions.

Gene variants of coagulation related proteins that interact with SARS-CoV-2.

Thrombosis is a recognized complication of Coronavirus disease of 2019 (COVID-19) and is often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms, by which some of these variants may contribute to disease, are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches.

Potential impact on coagulopathy of gene variants of coagulation related proteins that interact with SARS-CoV-2.

Thrombosis has been one of the complications of the Coronavirus disease of 2019 (COVID-19), often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms by which some of these variants may contribute to disease are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches. AUTHOR SUMMARY: Increased blood clotting, especially in the lungs, is a common complication of COVID-19. Infectious diseases cause inflammation which in turn can contribute to increased blood clotting. However, the extent of clot formation that is seen in the lungs of COVID-19 patients suggests that there may be a more direct link. We identified three human proteins that are involved indirectly in the blood clotting cascade and have been shown to interact with proteins of SARS virus, which is closely related to the novel coronavirus. We examined computationally the interaction of these human proteins with the viral proteins. We looked for genetic variants of these proteins and examined how these variants are distributed across populations. We investigated whether variants of these genes could impact severity of COVID-19. Further investigation around these variants may provide clues for the pathogenesis of COVID-19 particularly in minority groups.