Amino Acid Interactions (INTAA) web server v2.0: a single service for computation of energetics and conservation in biomolecular 3D structures

Sequence-Based Protein Design: A Review of Using Statistical Models to Characterize Coevolutionary Traits for Developing Hybrid Proteins as Genetic Sensors

Statistical analyses of homologous protein sequences can identify amino acid residue positions that co-evolve to generate family members with different properties. Based on the hypothesis that the coevolution of residue positions is necessary for maintaining protein structure, coevolutionary traits revealed by statistical models provide insight into residue-residue interactions that are important for understanding protein mechanisms at the molecular level. With the rapid expansion of genome sequencing databases that facilitate statistical analyses, this sequence-based approach has been used to study a broad range of protein families. An emerging application of this approach is to design hybrid transcriptional regulators as modular genetic sensors for novel wiring between input signals and genetic elements to control outputs. Among many allosterically regulated regulator families, the members contain structurally conserved and functionally independent protein domains, including a DNA-binding module (DBM) for interacting with a specific genetic element and a ligand-binding module (LBM) for sensing an input signal. By hybridizing a DBM and an LBM from two different family members, a hybrid regulator can be created with a new combination of signal-detection and DNA-recognition properties not present in natural systems. In this review, we present recent advances in the development of hybrid regulators and their applications in cellular engineering, especially focusing on the use of statistical analyses for characterizing DBM-LBM interactions and hybrid regulator design. Based on these studies, we then discuss the current limitations and potential directions for enhancing the impact of this sequence-based design approach.

Deciphering a crucial dimeric interface governing Norrin dimerization and the pathogenesis of familial exudative vitreoretinopathy

Familial exudative vitreoretinopathy (FEVR) is a hereditary eye disease that could cause blindness. It has been established that Norrin forms dimers to activate β-catenin signaling, yet the core interface for Norrin dimerization and the precise mechanism by which Norrin dimerization contributes to the pathogenesis of FEVR remain elusive. Here, we report an NDP variant, c.265T>C (p.Phe89Leu), that interrupted β-catenin signaling by disrupting Norrin dimerization. Structural and functional analysis revealed that the Phe-89 of one Norrin monomer interacts with Pro-98, Ser-101, Arg-121, and Ile-123 of another, forming two core symmetrical dimerization interfaces that are pivotal for the formation of a "hand-by-arm" dimer. Intriguingly, we proved that one of the two core symmetrical interfaces is sufficient for dimerization and activation of β-catenin signaling, with a substantial contribution from the Phe-89/Pro-98 interaction. Further functional analysis revealed that the disruption of both dimeric interfaces eliminates potential binding sites for LRP5, which could be partially restored by over-expression of TSPAN12. In conclusion, our findings unveil a core dimerization interface that regulates Norrin/LRP5 interaction, highlighting the essential role of Norrin dimerization on β-catenin signaling and providing potential therapeutic avenues for the treatment of FEVR.

Computational identification of key residues regulating fluorescence emission in a red/green cyanobacteriochrome

Cyanobacteriochromes (CBCRs) are linear tetrapyrrole bilin-binding photoreceptors of cyanobacteria that exhibit high spectral diversity, gaining attention in optogenetics and bioimaging applications. Several engineering studies on CBCRs were attempted, especially for designing near-infrared (NIR) fluorescent proteins with longer fluorescence wavelengths. However, despite continuous efforts, a key component regulating fluorescence emission property in CBCRs is still poorly understood. As a model system, we focused on red/green CBCR Slr1393g3, from the unicellular cyanobacterium Synechocystis sp. PCC 6803 to engineer Pr to get far-red light-emitting property. Energy profiling and pairwise structural comparison of Slr1393g3 variants effectively reveal the mutations that are critical to the fluorescence changes. H497 seems to play a key role in stabilizing the chromophore environment, especially the α3 helix, while H495, T499, and Q502 are potential key residues determining fluorescence emission peak wavelength. We also found that mutations of α2 and α4 helical regions are closely related to the chromophore binding stability and likely affect fluorescence properties. Taken together, our computational analysis suggests that the fluorescence of Slr1393g3 is mainly controlled by the stabilization of the chromophore binding pocket. The predicted key residues potentially regulating the fluorescence emission property of a red/green CBCR will be advantageous for designing improved NIR fluorescent protein when combined with in vitro molecular evolution approaches.

NDP52 acts as a redox sensor in PINK1/Parkin-mediated mitophagy

Mitophagy, the elimination of mitochondria via the autophagy-lysosome pathway, is essential for the maintenance of cellular homeostasis. The best characterised mitophagy pathway is mediated by stabilisation of the protein kinase PINK1 and recruitment of the ubiquitin ligase Parkin to damaged mitochondria. Ubiquitinated mitochondrial surface proteins are recognised by autophagy receptors including NDP52 which initiate the formation of an autophagic vesicle around the mitochondria. Damaged mitochondria also generate reactive oxygen species (ROS) which have been proposed to act as a signal for mitophagy, however the mechanism of ROS sensing is unknown. Here we found that oxidation of NDP52 is essential for the efficient PINK1/Parkin-dependent mitophagy. We identified redox-sensitive cysteine residues involved in disulphide bond formation and oligomerisation of NDP52 on damaged mitochondria. Oligomerisation of NDP52 facilitates the recruitment of autophagy machinery for rapid mitochondrial degradation. We propose that redox sensing by NDP52 allows mitophagy to function as a mechanism of oxidative stress response.

Analysis of critical protein-protein interactions of SARS-CoV-2 capping and proofreading molecular machineries towards designing dual target inhibitory peptides

In recent years, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as the cause of the coronavirus disease (COVID-19) global pandemic, and its variants, especially those with higher transmissibility and substantial immune evasion, have highlighted the imperative for developing novel therapeutics as sustainable solutions other than vaccination to combat coronaviruses (CoVs). Beside receptor recognition and virus entry, members of the SARS-CoV-2 replication/transcription complex are promising targets for designing antivirals. Here, the interacting residues that mediate protein-protein interactions (PPIs) of nsp10 with nsp16 and nsp14 were comprehensively analyzed, and the key residues' interaction maps, interaction energies, structural networks, and dynamics were investigated. Nsp10 stimulates both nsp14's exoribonuclease (ExoN) and nsp16's 2'O-methyltransferase (2'O-MTase). Nsp14 ExoN is an RNA proofreading enzyme that supports replication fidelity. Nsp16 2'O-MTase is responsible for the completion of RNA capping to ensure efficient replication and translation and escape from the host cell's innate immune system. The results of the PPIs analysis proposed crucial information with implications for designing SARS-CoV-2 antiviral drugs. Based on the predicted shared protein-protein interfaces of the nsp16-nsp10 and nsp14-nsp10 interactions, a set of dual-target peptide inhibitors was designed. The designed peptides were evaluated by molecular docking, peptide-protein interaction analysis, and free energy calculations, and then further optimized by in silico saturation mutagenesis. Based on the predicted evolutionary conservation of the interacted target residues among CoVs, the designed peptides have the potential to be developed as dual target pan-coronavirus inhibitors.

PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures

Knowledge of protein-ligand binding sites (LBSs) enables research ranging from protein function annotation to structure-based drug design. To this end, we have previously developed a stand-alone tool, P2Rank, and the web server PrankWeb (https://prankweb.cz/) for fast and accurate LBS prediction. Here, we present significant enhancements to PrankWeb. First, a new, more accurate evolutionary conservation estimation pipeline based on the UniRef50 sequence database and the HMMER3 package is introduced. Second, PrankWeb now allows users to enter UniProt ID to carry out LBS predictions in situations where no experimental structure is available by utilizing the AlphaFold model database. Additionally, a range of minor improvements has been implemented. These include the ability to deploy PrankWeb and P2Rank as Docker containers, support for the mmCIF file format, improved public REST API access, or the ability to batch download the LBS predictions for the whole PDB archive and parts of the AlphaFold database.