Protein dynamics orchestrate allosteric regulation, but elucidating the sequence of events and causal relationships within these intricate processes remains challenging. We introduce the Dynamically Perturbed Gaussian Network Model (DP-GNM), a novel approach that uncovers the directionality of information flow within proteins. DP-GNM leverages time-dependent correlations to achieve two goals: identifying driver and driven residues and revealing communities of residues exhibiting synchronized dynamics. Applied to wild type and mutated structures of Cyclophilin A, DP-GNM unveils a hierarchical network of information flow, where key residues initiate conformational changes that propagate through the protein in a directed manner. This directional causality illuminates the intricate relationship between protein dynamics and allosteric regulation, providing valuable insights into protein function and potential avenues for drug design. Furthermore, DP-GNM’s potential to elucidate dynamics under periodic perturbations like the circadian rhythm suggests its broad applicability in understanding complex biological processes governed by environmental cycles.

Histidine kinases (HKs) are a central part of bacterial environmental-sensing two component systems, providing their hosts with the ability to respond to a wide range of physical and chemical signals, being a paradigmatic example of protein diversity and molecular evolution. HK are multidomain proteins consisting of at least a sensor domain, dimerization and phosphorylation domain (DHp) and a catalytic domain. They work as homodimers, and the existence of two different autophosphorylation mechanisms (cis and trans), has been proposed as relevant for pathway specificity. Although several HKs have been intensively studied, a precise sequence-to-structure explanation of why and how either cis or trans phosphorylation occurs, is still unavailable, nor is there any evolutionary analysis on the subject. In this work we show that AlphaFold can accurately determine whether a HK dimerizes in a cis or trans structure. We then use it to explore the molecular determinants of the phosphorylation mechanism. We conclude that it is the difference in lengths of the helices surrounding the DHp loop that determines the mechanism. We also show that very small changes in these helices can cause a mechanism switch, providing these systems with a way to diverge rapidly and adapt to new stimuli.

The INTEGRATE system is a gene-editing approach that offers advantages over the widely used CRISPR-Cas9 system. It does not introduce double strand breaks in the target DNA but rather integrates the desired DNA sequence directly into it. The first step in the integration process is PAM recognition, which is critical to understanding and optimizing the system. Experimental testing revealed varying integration efficiencies of different PAM mutants, and computational simulations were carried out to gain mechanistic insight into the conformational changes of Cas8 during PAM recognition. Our results showed that the interaction between Arg246 and Guanine at position (-1) of the target strand is critical for PAM recognition. We found that unfavorable interactions in the 5’-AC-3’ PAM mutant disrupted this interaction and may be responsible for its 0% integration efficiency. Additionally, we discovered that PAM sequences not only initiate the integration process but also regulate it through an allosteric mechanism that connects the N-terminal domain and the helical bundle of Cas8. This allosteric regulation was present in all PAMs tested, even those with lower integration efficiencies, such as 5’-TC-3’ and 5’-AC-3’. We identified the Cas8 residues that are involved in this regulation. Our findings provide valuable insights into PAM recognition mechanisms in the INTEGRATE system and can help improve the gene-editing technology.

Glial fibrillary acidic protein (GFAP) is a promising biomarker for brain and spinal cord disorders. Recent studies have highlighted the differences in the reliability of GFAP measurements in different biological matrices. The reason for these discrepancies is poorly understood as our knowledge of the protein’s 3-dimensional conformation, proteoforms, and aggregation remains limited. Here, we investigate the structural properties of GFAP under different conditions. For this, we characterised recombinant GFAP proteins from various suppliers and applied hydrogen-deuterium exchange mass spectrometry (HDX-MS) to provide a snapshot of the conformational dynamics of GFAP in artificial CSF compared to the phosphate buffer. Our findings indicate that recombinant GFAP exists in various conformational species. Furthermore, we show that GFAP dimers remained intact under denaturing conditions. HDX-MS experiments show an overall decrease in H-bonding and an increase in solvent accessibility of GFAP in aCSF compared to the phosphate buffer, with clear indications of mixed EX2 and EX1 kinetics. To understand possible structural interface regions and the evolutionary conservation profiles, we combined HDX-MS results with the predicted GFAP-dimer structure by AlphaFold-Multimer. We found that deprotected regions with high structural flexibility in artificial CSF overlap with predicted conserved dimeric interface regions. Our results suggest that GFAP exists in several conformational forms. Structural property predictions combined with the HDX data show an overall deprotection and signatures of aggregation in aCSF. We anticipate that the outcomes of this research will contribute to a deeper understanding of the structural flexibility of GFAP and ultimately shed light on its behaviour in different biological matrices.

Three-dimensional structure information, now available at the proteome scale, may facilitate the detection of remote evolutionary relationships in protein superfamilies. Here, we illustrate this with the identification of a novel family of protein domains related to the ferredoxin-like superfold, by combining (i) transitive sequence similarity searches, (ii) clustering approaches and (iii) the use of AlphaFold2 3D structure models. Domains of this family called CoBaHMA, were initially identified in relation with the intracellular biomineralization of calcium carbonates by Cyanobacteria. They are part of the large heavy-metal-associated (HMA) superfamily, departing from the latter by specific sequence and structural features. In particular, most CoBaHMA domains share conserved basic amino acids, forming a positively charged surface, which is likely to interact with anionic partners. CoBaHMA domains are found in diverse modular organizations in bacteria, existing in the form of monodomain proteins or as part of larger proteins, some of which are membrane proteins involved in transport or lipid metabolism. This suggests that the CoBaHMA domains may exert a regulatory function, involving interactions with anionic lipids. This hypothesis might have a particular resonance in the context of the compartmentalization observed for cyanobacterial intracellular calcium carbonates.

Stapled peptides are a promising class of molecules with potential as highly specific probes of protein-protein interactions and as therapeutics. Hydrocarbon stapling affects the peptide properties through the interplay of two factors: enhancing the overall hydrophobicity and constraining the conformational flexibility. By constructing a series of virtual peptides, we study the role of each factor in modulating the structural properties of a hydrocarbon stapled peptide PM2 which has been shown to enter cells, engage its target MDM2 and activate p53. Hamiltonian replica exchange molecular dynamics (HREMD) simulations suggest that hydrocarbon stapling favors helical populations of PM2 through a combination of the geometric constraints and the enhanced hydrophobicity of the peptide. To further understand the conformational landscape of the stapled peptides along the binding pathway, we performed HREMD simulations by restraining the peptide at different distances from MDM2. When the peptide approaches MDM2, the binding pocket undergoes dehydration which appears to be greater in the presence of the stapled peptide compared to the linear peptide. In the binding pocket, the helicity of the stapled peptide is increased due to the favorable interactions between the peptide residues as well as the staple and the micro-environment of the binding pocket, contributing to enhanced affinity. The dissection of the multi-facet mechanism of hydrocarbon stapling into individual factors not only deepens fundamental understanding of peptide stapling, but also provides guidelines in the design of new stapled peptides.

This study focuses on investigating the effects of an oncogenic mutation (G12V) on the stability and interactions within the KRAS-RGL1 protein complex. The KRAS-RGL1 complex is of particular interest due to its relevance to KRAS-associated cancers and the potential for developing targeted drugs against the KRAS system. The stability of the complex and the allosteric effects of specific residues are examined to understand their roles as modulators of complex stability and function. Using molecular dynamics simulations, we calculate the mutual information, MI, between two neighboring residues at the interface of the KRAS-RGL1 complex, and employ the concept of interaction information, II, to measure the contribution of a third residue to the interaction between interface residue pairs. Negative II indicates synergy, where the presence of the third residue strengthens the interaction, while positive II suggests anti-cooperativity. Our findings reveal that MI serves as a dominant factor in determining the results, with the G12V mutation increasing the MI between interface residues, indicating enhanced correlations due to the formation of a more compact structure in the complex. Interestingly, although II plays a role in understanding three-body interactions and the impact of distant residues, it is not significant enough to outweigh the influence of MI in determining the overall stability of the complex. Nevertheless, II may nonetheless be a relevant factor to consider in future drug design efforts. This study provides valuable insights into the mechanisms of complex stability and function, highlighting the significance of three-body interactions and the impact of distant residues on the binding stability of the complex. Additionally, our findings demonstrate that constraining the fluctuations of a third residue consistently increases the stability of the G12V variant, making it challenging to weaken complex formation of the mutated species through allosteric manipulation. The novel perspective offered by this approach on protein dynamics, function, and allostery has potential implications for understanding and targeting other protein complexes involved in vital cellular processes. The results contribute to our understanding of the effects of oncogenic mutations on protein-protein interactions and provide a foundation for future therapeutic interventions in the context of KRAS-associated cancers and beyond.

Distinguishing between harmful and benign genetic variations is fundamental to our understanding of the relationship between genome and disease in general and for personalized medicine in particular. We investigated the relationship between predicted change in RASA and the phenotype of a missense mutation (MM). The ASAquick program was used to obtain RASA predictions for the original and mutated sequence and a parameter, δ , was introduced to assess the change in RASA for a given MM. We find that predicted RASA shows a robust, intricate signal with respect to genetic variation and that changes in RASA between variants can form a basis for a simple and quick predictor of the effect of MMs. Furthermore, we find that for hydrophobic residues, increase in the RASA corresponds to an increase in the likelihood that a MM would be harmful. For hydrophilic residues we find that a decrease in the RASA corresponds to a likelihood that a MM would be harmful. We also find that the size of the change in predicted RASA plays a role in determining the effect of a given MM. In future work we plan to use these results in developing more sophisticated forms of MM phenotype predictors.

Pathogenic bacteria attack their host by secreting virulence factors that in various ways interrupt host defenses and damage their cells. Functions of many virulence factors, even from well-studied pathogens, are still unknown. Francisella tularensis is a class A pathogen and a causative agent of tularemia, a disease that is lethal without proper treatment. Here we report the three-dimensional structure and preliminary analysis of the potential virulence factor identified by the transcriptomic analysis of the F. tularensis disease models that is encoded by the FTT_1539 gene. The structure of the FTT_1539 protein contains two sets of three stranded antiparallel beta sheets, with a helix placed between the first and the second beta strand in each sheet. This structural motif, previously seen in virulence factors from other pathogens, was named the SHS2 motif and identified to play a role in protein-protein interactions and small molecule recognition. Sequence and structure analysis identified FTT_1539 as a member of a large family of secreted proteins from a broad range of pathogenic bacteria, such as Helicobacter pylori and Mycobacterium tuberculosis. While the specific function of the proteins from this class is still unknown, their similarity to the H. pylori Tip-α protein that induces TNF-a and other chemokines through NF-kB activation suggests the existence of a common pathogen-host interference mechanism shared by multiple human pathogens.