The unprecedented pace of the sequencing of the SARS-CoV-2 virus genomes provides us with unique information about the genetic changes in a single pathogen during ongoing pandemic. By the analysis of close to 200,000 genomes we show that the patterns of the SARS-CoV-2 virus mutations along its genome are closely correlated with the structural and functional features of the encoded proteins. Requirements of foldability of proteins' 3D structures and the conservation of their key functional regions, such as protein-protein interaction interfaces, are the dominant factors driving evolutionary selection in protein-coding genes. At the same time, avoidance of the host immunity leads to the abundance of mutations in other regions, resulting in high variability of the missense mutation rate along the genome. "Unexplained" peaks and valleys in the mutation rate provide hints on function for yet uncharacterized genomic regions and specific protein structural and functional features they code for. Some of these observations have immediate practical implications for the selection of target regions for PCR-based COVID-19 tests and for evaluating the risk of mutations in epitopes targeted by specific antibodies and vaccine design strategies.

MOTIVATION: As the COVID-19 pandemic is spreading around the world, the SARS-CoV-2 virus is evolving with mutations that potentially change and fine-tune functions of the proteins coded in its genome. RESULTS: Coronavirus3D website integrates data on the SARS-CoV-2 virus mutations with information about 3D structures of its proteins, allowing users to visually analyze the mutations in their 3D context. AVAILABILITY AND IMPLEMENTATION: Coronavirus3D server is freely available at https://coronavirus3d.org.

UNLABELLED: Protael is a JavaScript library for creating interactive visualizations of biological sequences and various associated data. It allows users to generate high-quality vector graphics (SVG) and integrate it into web pages. AVAILABILITY AND IMPLEMENTATION: Protael distribution, documentation and examples are freely available at http://protael.org; source code is hosted at https://github.com/sanshu/protaeljs.

BACKGROUND: A novel highly conserved protein domain, DUF162 [Pfam: PF02589], can be mapped to two proteins: LutB and LutC. Both proteins are encoded by a highly conserved LutABC operon, which has been implicated in lactate utilization in bacteria. Based on our analysis of its sequence, structure, and recent experimental evidence reported by other groups, we hereby redefine DUF162 as the LUD domain family. RESULTS: JCSG solved the first crystal structure [PDB:2G40] from the LUD domain family: LutC protein, encoded by ORF DR_1909, of Deinococcus radiodurans. LutC shares features with domains in the functionally diverse ISOCOT superfamily. We have observed that the LUD domain has an increased abundance in the human gut microbiome. CONCLUSIONS: We propose a model for the substrate and cofactor binding and regulation in LUD domain. The significance of LUD-containing proteins in the human gut microbiome, and the implication of lactate metabolism in the radiation-resistance of Deinococcus radiodurans are discussed.

Over the last decade, workflows have been established as a mechanism for scientific developers to create simplified views of complex scientific processes. However, there is a need for a comprehensive system architecture to link scientific developers creating workflows with researchers launching workflows in large scale computing environments. We present the architecture for the CAMERA 2.0 Cyber infrastructure platform that provides a scaffold where workflows can be uploaded into the system, and user interface components for launching and viewing results are automatically generated. In CAMERA 2.0, scientific developers and metagenomics researchers seamlessly collaborate to (i) wrap data-analysis software applications and heterogeneous tools as Resource Oriented Architecture (ROA) components integrating them using scientific workflows; (ii) publish and run scientific workflows via dynamically generated uniform portal interfaces; (iii) map heterogeneous workflow products to provenance and CAMERA semantic database through a transformation component, to save output data resulting from workflow runs based on this mapping; (iv) record and visualize the provenance of all workflow run-related data and processes; and (v) conduct queries across multiple workflow executions and link these workflow executions to each other through data and provenance related to these runs. Furthermore, workflows added to CAMERA also have access to a variety of physical resources for computation and data management. Here, we demonstrate the usability of this framework with some of the developed metagenomics workflows.

BACKGROUND: A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. RESULTS: Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. CONCLUSIONS: The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org.