Squalomix: shark and ray genome analysis consortium and its data sharing platform.

The taxon Elasmobranchii (sharks and rays) contains one of the long-established evolutionary lineages of vertebrates with a tantalizing collection of species occupying critical aquatic habitats. To overcome the current limitation in molecular resources, we launched the Squalomix Consortium in 2020 to promote a genome-wide array of molecular approaches, specifically targeting shark and ray species. Among the various bottlenecks in working with elasmobranchs are their elusiveness and low fecundity as well as the large and highly repetitive genomes. Their peculiar body fluid composition has also hindered the establishment of methods to perform routine cell culturing required for their karyotyping. In the Squalomix consortium, these obstacles are expected to be solved through a combination of in-house cytological techniques including karyotyping of cultured cells, chromatin preparation for Hi-C data acquisition, and high fidelity long-read sequencing. The resources and products obtained in this consortium, including genome and transcriptome sequences, a genome browser powered by JBrowse2 to visualize sequence alignments, and comprehensive matrices of gene expression profiles for selected species are accessible through https://github.com/Squalomix/info.

AbAdapt: an adaptive approach to predicting antibody-antigen complex structures from sequence.

Motivation: The scoring of antibody-antigen docked poses starting from unbound homology models has not been systematically optimized for a large and diverse set of input sequences. Results: To address this need, we have developed AbAdapt, a webserver that accepts antibody and antigen sequences, models their 3D structures, predicts epitope and paratope, and then docks the modeled structures using two established docking engines (Piper and Hex). Each of the key steps has been optimized by developing and training new machine-learning models. The sequences from a diverse set of 622 antibody-antigen pairs with known structure were used as inputs for leave-one-out cross-validation. The final set of cluster representatives included at least one 'Adequate' pose for 550/622 (88.4%) of the queries. The median (interquartile range) ranks of these 'Adequate' poses were 22 (5-77). Similar results were obtained on a holdout set of 100 unrelated antibody-antigen pairs. When epitopes were repredicted using docking-derived features for specific antibodies, the median ROC AUC increased from 0.679 to 0.720 in cross-validation and from 0.694 to 0.730 in the holdout set. Availability and implementation: AbAdapt and related data are available at https://sysimm.org/abadapt/. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Analysis of Protein Intermolecular Interactions with MAFFT-DASH.

The Database of Aligned Structural Homologs (DASH) is a tool for efficiently navigating the Protein Data Bank (PDB) by means of pre-computed pairwise structural alignments. We recently showed that, by integrating DASH structural alignments with the multiple sequence alignment (MSA) software MAFFT, we were able to significantly improve MSA accuracy without dramatically increasing manual or computational complexity. In the latest DASH update, such queries are not limited to PDB entries but can also be launched from user-provided protein coordinates. Here, we describe a further extension of DASH that retrieves intermolecular interactions of all structurally similar domains in the PDB to a query domain of interest. We illustrate these new features using a model of the NYN domain of the ribonuclease N4BP1 as an example. We show that the protein-nucleotide interactions returned are distributed on the surface of the NYN domain in an asymmetric manner, roughly centered on the known nuclease active site.

Flexible, Functional, and Familiar: Characteristics of SARS-CoV-2 Spike Protein Evolution.

The SARS-CoV-2 S protein is a major point of interaction between the virus and the human immune system. As a consequence, the S protein is not a static target but undergoes rapid molecular evolution. In order to more fully understand the selection pressure during evolution, we examined residue positions in the S protein that vary greatly across closely related viruses but are conserved in the subset of viruses that infect humans. These "evolutionarily important" residues were not distributed evenly across the S protein but were concentrated in two domains: the N-terminal domain and the receptor-binding domain, both of which play a role in host cell binding in a number of related viruses. In addition to being localized in these two domains, evolutionary importance correlated with structural flexibility and inversely correlated with distance from known or predicted host receptor-binding residues. Finally, we observed a bias in the composition of the amino acids that make up such residues toward more human-like, rather than virus-like, sequence motifs.

Methods for sequence and structural analysis of B and T cell receptor repertoires.

B cell receptors (BCRs) and T cell receptors (TCRs) make up an essential network of defense molecules that, collectively, can distinguish self from non-self and facilitate destruction of antigen-bearing cells such as pathogens or tumors. The analysis of BCR and TCR repertoires plays an important role in both basic immunology as well as in biotechnology. Because the repertoires are highly diverse, specialized software methods are needed to extract meaningful information from BCR and TCR sequence data. Here, we review recent developments in bioinformatics tools for analysis of BCR and TCR repertoires, with an emphasis on those that incorporate structural features. After describing the recent sequencing technologies for immune receptor repertoires, we survey structural modeling methods for BCR and TCRs, along with methods for clustering such models. We review downstream analyses, including BCR and TCR epitope prediction, antibody-antigen docking and TCR-peptide-MHC Modeling. We also briefly discuss molecular dynamics in this context.

Structural Modeling of Lymphocyte Receptors and Their Antigens.

Structural modeling plays a key role in protein function prediction on a genome-wide scale. For B and T lymphocyte receptors, the critical functional question is: which antigens and epitopes are targeted? With emerging B cell receptor (BCR) and T cell receptor (TCR) sequencing methods improving in both breadth and depth, there is a growing need for methods that can help answer this question. Since lymphocyte-antigen recognition depends on complementarity, structural modeling is likely to play an important role in understanding antigen specificity and affinity. In the case of BCRs, such modeling methods have a long history in the study and design of antibodies. However, for TCRs there are relatively few publicly available modeling tools, and, to our knowledge, none that incorporate interaction between TCRs and peptide-MHC (pMHC) complexes. Here, we provide a web-based tool, ImmuneScape ( https://sysimm.org/immune-scape/ ), to carry out TCR-pMHC modeling as a first step toward structure-based function prediction.

MAFFT-DASH: integrated protein sequence and structural alignment.

Here, we describe a web server that integrates structural alignments with the MAFFT multiple sequence alignment (MSA) tool. For this purpose, we have prepared a web-based Database of Aligned Structural Homologs (DASH), which provides structural alignments at the domain and chain levels for all proteins in the Protein Data Bank (PDB), and can be queried interactively or by a simple REST-like API. MAFFT-DASH integration can be invoked with a single flag on either the web (https://mafft.cbrc.jp/alignment/server/) or command-line versions of MAFFT. In our benchmarks using 878 cases from the BAliBase, HomFam, OXFam, Mattbench and SISYPHUS datasets, MAFFT-DASH showed 10-20% improvement over standard MAFFT for MSA problems with weak similarity, in terms of Sum-of-Pairs (SP), a measure of how well a program succeeds at aligning input sequences in comparison to a reference alignment. When MAFFT alignments were supplemented with homologous sequences, further improvement was observed. Potential applications of DASH beyond MSA enrichment include functional annotation through detection of remote homology and assembly of template libraries for homology modeling.

MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization.

This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract biologically relevant information from such data, sophistication of algorithms is necessary but not sufficient. Intuitive and interactive tools for experimental biologists to semiautomatically handle large data are becoming important. We are working on development of MAFFT toward these two directions. Here, we explain (i) the Web interface for recently developed options for large data and (ii) interactive usage to refine sequence data sets and MSAs.