Sequence and structure alignments in post-AlphaFold era

AHoJ-DB: A PDB-wide Assignment of apo & holo Relationships Based on Individual Protein-Ligand Interactions

A single protein structure is rarely sufficient to capture the conformational variability of a protein. Both bound and unbound (holo and apo) forms of a protein are essential for understanding its geometry and making meaningful comparisons. Nevertheless, docking or drug design studies often still consider only single protein structures in their holo form, which are for the most part rigid. With the recent explosion in the field of structural biology, large, curated datasets are urgently needed. Here, we use a previously developed application (AHoJ) to perform a comprehensive search for apo-holo pairs for 468,293 biologically relevant protein-ligand interactions across 27,983 proteins. In each search, the binding pocket is captured and mapped across existing structures within the same UniProt, and the mapped pockets are annotated as apo or holo, based on the presence or absence of ligands. We assemble the results into a database, AHoJ-DB (www.apoholo.cz/db), that captures the variability of proteins with identical sequences, thereby exposing the agents responsible for the observed differences in geometry. We report several metrics for each annotated pocket, and we also include binding pockets that form at the interface of multiple chains. Analysis of the database shows that about 24% of the binding sites occur at the interface of two or more chains and that less than 50% of the total binding sites processed have an apo form in the PDB. These results can be used to train and evaluate predictors, discover potentially druggable proteins, and reveal protein- and ligand-specific relationships that were previously obscured by intermittent or partial data. Availability: www.apoholo.cz/db.

The modification landscape of Pseudomonas aeruginosa tRNAs

RNA modifications have a substantial impact on tRNA function, with modifications in the anticodon loop contributing to translational fidelity and modifications in the tRNA core impacting structural stability. In bacteria, tRNA modifications are crucial for responding to stress and regulating the expression of virulence factors. Although tRNA modifications are well-characterized in a few model organisms, our knowledge of tRNA modifications in human pathogens, such as Pseudomonas aeruginosa, remains limited. Here, we leveraged two orthogonal approaches to build a reference landscape of tRNA modifications in Escherichia coli, which enabled us to identify similar modifications in P. aeruginosa Our analysis supports a substantial degree of conservation between the two organisms, while also uncovering potential sites of tRNA modification in P. aeruginosa tRNAs that are not present in E. coli The mutational signature at one of these sites, position 46 of tRNAGln1(UUG) is dependent on the P. aeruginosa homolog of TapT, the enzyme responsible for the 3-(3-amino-3-carboxypropyl) uridine (acp3U) modification. Identifying which modifications are present on different tRNAs will uncover the pathways impacted by the different tRNA-modifying enzymes, some of which play roles in determining virulence and pathogenicity.

Large-scale structure-informed multiple sequence alignment of proteins with SIMSApiper

SUMMARY

SIMSApiper is a Nextflow pipeline that creates reliable, structure-informed MSAs of thousands of protein sequences faster than standard structure-based alignment methods. Structural information can be provided by the user or collected by the pipeline from online resources. Parallelization with sequence identity-based subsets can be activated to significantly speed up the alignment process. Finally, the number of gaps in the final alignment can be reduced by leveraging the position of conserved secondary structure elements.

AVAILABILITY AND IMPLEMENTATION

The pipeline is implemented using Nextflow, Python3, and Bash. It is publicly available on github.com/Bio2Byte/simsapiper.