Identification of site-specific evolutionary trajectories shared across human betacoronaviruses

Comparison of evolution among related viruses can provide insights into shared adaptive processes, for example following host switching to a mutual host species. Whilst phylogenetic methods can help identify mutations that may be important for evolutionary processes such as adaptation to a new host, these can be enhanced by positioning candidate mutations to known functional sites on protein structures. Over the past two decades, three zoonotic betacoronaviruses have significantly impacted human public health: SARS-CoV-1, MERS-CoV and SARS-CoV-2, whilst two other betacoronaviruses, HKU1 and OC43, have circulated endemically in the human population for over 100 years. In this study, we use a comparative approach to prospectively search for potentially evolutionarily-relevant mutations within the Orf1ab and S genes across betacoronavirus species that have demonstrated sustained human-to-human transmission (HKU1, OC43, SARS-CoV-1 and SARS-CoV-2). We used a combination of molecular evolution methods to identify 30 sites that display evidence of homoplasy and/or stepwise evolution, that may be suggestive of adaptation across emerging and endemic betacoronaviruses. Of these, seven sites also display evidence of being selectively relevant. Drawing upon known protein structure data, we find that four of the identified mutations [18121 (exonuclease/27), 21623 (spike/21), 21635 (spike/25) and 23948 (spike/796), in SARS-CoV-2 genome coordinates] are proximal to regions of known functionality. Our results provide a molecular-level context for common evolutionary pathways that betacoronaviruses may undergo during adaptation to the human host.

A Negative Feedback Model to Explain Regulation of SARS-CoV-2 Replication and Transcription

BackgroundCoronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although a preliminary understanding of the replication and transcription of SARS-CoV-2 has recently emerged, their regulation remains unknown.ResultsBy comprehensive analysis of genome sequence and protein structure data, we propose a negative feedback model to explain the regulation of CoV replication and transcription, providing a molecular basis of the “leader-to-body fusion” model. The key step leading to the proposal of our model was that the transcription regulatory sequence (TRS) motifs were identified as the cleavage sites of nsp15, a nidoviral RNA uridylate-specific endoribonuclease (NendoU). According to this model, nsp15 regulates the synthesis of subgenomic RNAs (sgRNAs), and genomic RNAs (gRNAs) by cleaving TRSs. The expression level of nsp15 controls the relative proportions of sgRNAs and gRNAs, which in turn change the expression level of nsp15 to reach equilibrium between the CoV replication and transcription.ConclusionThe replication and transcription of CoVs are regulated by a negative feedback mechanism that influences the persistence of CoVs in hosts. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, and provide new clues for future studies. One important clue is that nsp15 may be an important and ideal target for the development of drugs (e.g., uridine derivatives) against CoVs.

Prediction of Protein Structural Classes: Features Extraction to Classification Algorithm

: The fast growing of protein sequencing and protein structure data has promoted the development of the protein structural class prediction. Several prediction methods have been proposed to study protein folding rate, DNA binding sites, as well as reducing the search of conformational space and realizing the prediction of tertiary structure. This paper introduces the current approaches of protein structural class prediction and emphasize their steps from information extraction to classification algorithms.

TactViz: A VMD Plugin for Tactile Visualization of Protein Structures

Scientific disciplines spanning biology, biochemistry, and biophysics involve the study of proteins and their functions. Visualization of protein structures represents a barrier to education and research in these disciplines for students who are blind or visually impaired. Here, we present a software plugin for readily producing variable-height tactile graphics of proteins using the free biomolecular visualization software Visual Molecular Dynamics (VMD) and protein structure data that is publicly available through the Protein Data Bank. Our method also supports interactive tactile visualization of proteins with VMD on electronic refreshable tactile display devices. Employing our method in an academic laboratory has enabled an undergraduate student who is blind to carry out research alongside her sighted peers. By making the study of protein structures accessible to students who are blind or visually impaired, we aim to promote diversity and inclusion in STEM education and research.

PDB-2-PBv3.0: An updated protein block database

Our protein block (PB) sequence database PDB-2-PBv1.0 provides PB sequences and dihedral angles for 74,297 protein structures comprising of 103,252 protein chains of Protein Data Bank (PDB) as on 2011. Since there are a lot of practical applications of PB and also as the size of PDB database increases, it becomes necessary to provide the PB sequences for all PDB protein structures. The current updated PDB-2-PBv3.0 contains PB sequences for 147,602 PDB structures comprising of 400,355 protein chains as on October 2019. When compared to our previous version PDB-2-PBv1.0, the current PDB-2-PBv3.0 contains 2- and 4-fold increase in the number of protein structures and chains, respectively. Notably, it provides PB information for any protein chain, regardless of the missing atom records of protein structure data in PDB. It includes protein interaction information with DNA and RNA along with their corresponding functional classes from Nucleic Acid Database (NDB) and PDB. Now, the updated version allows the user to download multiple PB records by parameter search and/or by a given list. This database is freely accessible at http://bioinfo.bdu.ac.in/pb3 .

Structural topology defines protective CD8+ T cell epitopes in the HIV proteome

Mutationally constrained epitopes of variable pathogens represent promising targets for vaccine design but are not reliably identified by sequence conservation. In this study, we employed structure-based network analysis, which applies network theory to HIV protein structure data to quantitate the topological importance of individual amino acid residues. Mutation of residues at important network positions disproportionately impaired viral replication and occurred with high frequency in epitopes presented by protective human leukocyte antigen (HLA) class I alleles. Moreover, CD8+ T cell targeting of highly networked epitopes distinguished individuals who naturally control HIV, even in the absence of protective HLA alleles. This approach thereby provides a mechanistic basis for immune control and a means to identify CD8+ T cell epitopes of topological importance for rational immunogen design, including a T cell–based HIV vaccine.