Elucidating the structure and dynamics of insulin and its analogs has been of broad interest, while presenting challenges due to the unique structural dynamics of insulin (composed itself of two multiply cross-linked peptides A and B) and its ability to assemble in a variety of oligomeric structures under physiological conditions. Here, we present two distinct X-ray crystallographic structures of the long-acting human insulin analog detemir (INSD) resolved in hexameric and dodecameric (or dihexameric) states at 2.85 Å and 2.70 Å resolution, respectively, using diffraction data collected under ambient temperature conditions. Characterization of the collective dynamics of these oligomers using the Gaussian Network Model (GNM) reveals several key features: (i) Oligomerization imparts high cooperativity in structural dynamics evidenced by dissection of the cross-correlations at various hierarchical levels; (ii) detemir monomers' conformational flexibility is highly suppressed within oligomeric constructs, the effect being particularly strong in the dihexamer due to the asymmetric packing of the hexamers and the presence of myristoyl groups at B peptides termini whose interactions imparts further heterogeneities; and (iii) a number of key residues retain, however, their intrinsic dynamics, to be deployed upon release from the oligomers. We distinguish in particular residues serving as hinge sites that mediates the conformational dynamics of the asymmetric units (dimers) and monomers (I2 A -V3 A and Y19 A -C20 A, and L11 B -L15 B and Y26 B of the respective peptides A and B), or as anchors supporting structural stability (disulfide-bridge forming cysteines, plus selected residues such as L16 A, G8 B and R22 B -F24 B . Overall, this study provides a structural-dynamic framework for gaining new insights into the dynamics of long-acting analog INSD and helps identify actionable sites for modulating insulin (analogs) dynamics toward designing more effective therapeutics.

Understanding the conformational dynamics of proteins, particularly small GTPases like Rac1, is vital for elucidating their functional mechanisms and developing targeted therapies. Rac1, pivotal in cellular processes, toggles between inactive GDP-bound and active GTP-bound states, regulated by guanine nucleotide exchange factors (GEFs) and GTPase-activating proteins (GAPs). Mutations, such as Rac1’s spontaneously activating oncogenic gain-of-function mutation P29S, associated with cancer, disrupt this equilibrium, leading to aberrant signaling. Traditional drug targeting of Rac1 is challenging due to its biological complexity and the lack of accessible active sites on its surface, necessitating alternative strategies. We propose a computational framework integrating Molecular Dynamics (MD) simulations and Elastic Network Models (ENM) to explore conformational dynamics. Our findings highlight the interplay between Mg2+ binding and conformational ensembles, revealing enhanced conformational heterogeneity in both inactive and active states upon P29S mutation. The critical location of P29S, Mg2+ coordination site, and GDP/GTP binding pocket with respect to global hinges provides mechanistic insight into how this mutation disrupts normal protein function through altered metal coordination dynamics. Furthermore, we identified strategic positions as potential “ rescue mutation ” sites, with T75A showing particular promise in mitigating the destabilizing conformational effects of P29S. Overall, this work provides insights into Rac1’s dynamic behavior and offers a foundation for targeted drug design strategies. ### Competing Interest Statement The authors have declared no competing interest.

Allosteric regulation, driven by conformational and dynamic changes, is fundamental to many biological processes. A major challenge in disease genomics is understanding how specific somatic missense mutations affect protein function, especially when their impact structurally and functionally indirect. In this study, we investigate the link between such mutations and intrinsic protein dynamics, focusing on their allosteric roles. We have analyzed 2549 mutations across 190 human proteins from the ClinVar dataset, using the Gaussian Network Model (GNM) based Transfer Entropy (TE) method. Using the Transient Receptor Potential Mucolipin 1 (TRPML1) channel as a case study, we demonstrate that sequential removal of global modes reveals layered, causal allosteric interactions, where functional sites recur or emerge across various dynamic contexts. Pathogenic mutations significantly coincide with key information sources or sinks within collective information flow. Insights gained from TRPML1 served to inform a large-dataset analysis, providing a topographical view of mutation patterns across a wide range of human proteins and demonstrating broader applicability of this framework Our results provide mechanistic insights into how disease-associated mutations perturb protein dynamics, highlighting distinct components of functional motion and diverse dynamic behaviors offering a path toward allosteric-based interpretation of mutational impact in human disease.

Background/aim:The Kelch-like-ECH associated protein 1 (Keap1) is an integral component of the E3-ubiquitin ligase complex, which binds to Nuclear factor erythroid 2-related factor 2 (Nrf2) and facilitates its degradation by the 26S proteasome. The Kelch domain of Keap1, composed of six repeated structural motifs, plays a key role in this interaction. This study aims to investigate the dimeric structure of the Keap1 Kelch domain at ambient temperature and to examine its implications for conformational dynamics, particularly in relation to the DMF and Nrf2 binding sites. Materials and methods:The dimeric crystal structure of the Keap1 Kelch domain was determined at 3.0 Å resolution using data collected at the Turkish Light Source 'Turkish DeLight.' To analyze structural dynamics, Gaussian Network Model (GNM) analysis was applied, and molecular docking studies were performed using the ambient temperature structure to evaluate the binding of compounds acting as inhibitors of the Keap1/Nrf2 complex. Results:The study reveals significant potential conformational changes in Keap1 residues, especially at the DMF and Nrf2 binding sites, driven by temperature-induced shifts. GNM analysis suggests that the allosteric behavior of DMF binding residues is fully realized in the ambient temperature structure. Molecular docking of various compounds, including CNN (a hybrid of L-carnosine and L-histidyl hydrazide), ZINC 12433145, and ZINC 105508677, demonstrated favorable binding interactions with key Keap1 residues, highlighting their potential as inhibitors. Conclusion:Our in silico and crystallo results suggest that CNN is a promising lead compound for Keap1 inhibition. Understanding the dimeric form of the Keap1 Kelch domain and its conformational changes at ambient temperature is crucial for elucidating the dynamics of the Keap1-Nrf2 interaction.

Enzymes are inherently dynamic entities, with their functions intricately governed by the interplay between conformational dynamics - ranging from local residue fluctuations to global motions - and biochemical activity. Deciphering how such dynamics coordinate higher-order cooperativity across multiple timescales to drive catalysis remains a fundamental challenge. This mini-review highlights the role of large-scale, collective motions involving domain-level displacements and hinge-based rearrangements, which not only facilitate substrate recognition, transformation, and release, but also emerge from and propagate through multidirectional allosteric interactions. Such dynamic mechanochemical coupling reflects evolutionary memory and provides a blueprint for enzyme design innovations.

Transition metals (e.g., Fe2/3+, Zn2+, Mn2+) are essential enzymatic cofactors in all organisms. Their environmental scarcity led to the evolution of high-affinity uptake systems. Our research focuses on two bacterial manganese ABC importers, Streptococcus pneumoniae PsaBC and Bacillus anthracis MntBC, both critical for virulence. Both importers share a similar homodimeric structure, where each protomer comprises a transmembrane domain (TMD) linked to a cytoplasmic nucleotide-binding domain (NBD). Due to their size and slow turnover rates, the utility of conventional molecular simulation approaches to reveal functional dynamics is limited. Thus, we employed a novel, computationally efficient method integrating Gaussian Network Models (GNM) with information theory Transfer Entropy (TE) calculations. Our calculations are in remarkable agreement with previous functional studies. Furthermore, based on the calculations, we generated 10 point-mutations and experimentally tested their effects, finding excellent concordance between computational predictions and experimental results. We identified "allosteric hotspots" in both transporters, in the transmembrane translocation pathway, at the coupling helices linking the TMDs and NBDs, and in the ATP binding sites. In both PsaBC and MntBC, we observed bi-directional information flow between the two TMDs, with minimal allosteric transmission to the NBDs. Conversely, the NBDs exhibited almost no NBD-NBD allosteric crosstalk but showed pronounced information flow from the NBD of one protomer towards the TMD of the other protomer. This unique allosteric "footprint" distinguishes ABC importers of transition metals from other members of the ABC transporter superfamily establishing them as a distinct functional class. This study offers the first comprehensive insight into the conformational dynamics of these vital virulence determinants, providing potential avenues for developing urgently needed novel antibacterial agents.

Protein space is characterized by extensive recurrence, or "reuse," of parts, suggesting that new proteins and domains can evolve by mixing-and-matching of existing segments. From an evolutionary perspective, for a given combination to persist, the protein segments should presumably not only match geometrically but also dynamically communicate with each other to allow concerted motions that are key to function. Evidence from protein space supports the premise that domains indeed combine in this manner; we explore whether a similar phenomenon can be observed at the sub-domain level. To this end, we use Gaussian Network Models (GNMs) to calculate the so-called soft modes, or low-frequency modes of motion for a dataset of 150 protein domains. Modes of motion can be used to decompose a domain into segments of consecutive amino acids that we call "dynamic elements", each of which belongs to one of two parts that move in opposite senses. We find that, in many cases, the dynamic elements, detected based on GNM analysis, correspond to established "themes": Sub-domain-level segments that have been shown to recur in protein space, and which were detected in previous research using sequence similarity alone (i.e. completely independently of the GNM analysis). This statistically significant correlation hints at the importance of dynamics in evolution. Overall, the results are consistent with an evolutionary scenario where proteins have emerged from themes that need to match each other both geometrically and dynamically, e.g. to facilitate allosteric regulation.

The Kelch like ECH associated protein 1 (Keap1) is a part of the E3 ubiquitin ligase complex that binds to Nuclear factor erythroid 2-related factor 2 (Nrf2) protein and facilitates its degradation by the eukaryotic 26S proteasome. The Kelch domain of Keap1 includes six repeated structural signature motifs, approximately 45 to 55 amino acid residues in length. Each Kelch repeat contains highly conserved residues and is known to form one blade of beta-propeller structure. Here, we report the dimeric Kelch domain of Keap1 determined at 3.0 A resolution at the Turkish Light Source Turkish DeLight at ambient temperature. Our structure provides new structural dynamics information of the dimeric Keap1 kelch domain at ambient temperature. It displays potential conformational changes of Keap1 residues, particularly at the Dimethyl fumarate (DMF) and Nrf2 binding regions, due to observed temperature shifts. Supported by the Gaussian Network Model (GNM) analysis, the dynamics of the Kelch domain revealed that the allosteric behavior of DMF binding residues is fully established in the ambient temperature structure. We also performed complementary molecular docking studies using our ambient temperature structure for numerous compounds acting as electrophilic irreversible indirect or non-covalent direct inhibitors of the Keap1/Nrf2 complex. Our data suggest that our previously reported novel compound, a hybrid of L carnosine and L histidyl hydrazide (CNN), revealed the most favorable scoring functions and prominent interactions with critical Keap1 residues. Collectively, our in silico and in crystallo results suggest a new potential lead compound for Keap1 inhibition. Additionally, understanding the dimeric form of the Keap1 kelch domain and conformational changes around the DMF and Nrf2 binding sites at ambient temperature is critical for understanding Keap1 Nrf2 interaction dynamics. ### Competing Interest Statement The authors have declared no competing interest.

Motivation Proteins are dynamic entities that undergo conformational changes critical for their functions. Understanding the communication pathways and information transfer within proteins is crucial for elucidating allosteric interactions in their mechanisms. This study utilizes mutual information (MI) analysis to probe dynamic allostery. Using two cases, Ubiquitin and PLpro, we have evaluated the accuracy and limitations of different approximations including the exact anisotropic and isotropic models, multivariate Gaussian model, isotropic Gaussian model, and the Gaussian Network Model (GNM) in revealing allosteric interactions.Results Our findings emphasize the required trajectory length for capturing accurate mutual information profiles. Long molecular dynamics trajectories, 1 ms for Ubiquitin and 100 mu s for PLpro are used as benchmarks, assuming they represent the ground truth. Trajectory lengths of approximately 5 mu s for Ubiquitin and 1 mu s for PLpro marked the onset of convergence, while the multivariate Gaussian model accurately captured mutual information with trajectories of 5 ns for Ubiquitin and 350 ns for PLpro. However, the isotropic Gaussian model is less successful in representing the anisotropic nature of protein dynamics, particularly in the case of PLpro, highlighting its limitations. The GNM, however, provides reasonable approximations of long-range information exchange as a minimalist network model based on a single crystal structure. Overall, the optimum trajectory lengths for effective Gaussian approximations of long-time dynamic behavior depend on the inherent dynamics within the protein's topology. The GNM, by showcasing dynamics across relatively diverse time scales, can be used either as a standalone method or to gauge the adequacy of MD simulation lengths.Availability and implementation Mutual information codes are available at https://github.com/kemaldemirtas/prc-MI.git.

Malfunction of the CFTR protein results in cystic fibrosis, one of the most common hereditary diseases. CFTR functions as an anion channel, the gating of which is controlled by long-range allosteric communications. Allostery also has direct bearings on CF treatment: the most effective CFTR drugs modulate its activity allosterically. Herein, we integrated Gaussian network model, transfer entropy, and anisotropic normal mode-Langevin dynamics and investigated the allosteric communications network of CFTR. The results are in remarkable agreement with experimental observations and mutational analysis and provide extensive novel insight. We identified residues that serve as pivotal allosteric sources and transducers, many of which correspond to disease-causing mutations. We find that in the ATP-free form, dynamic fluctuations of the residues that comprise the ATP-binding sites facilitate the initial binding of the nucleotide. Subsequent binding of ATP then brings to the fore and focuses on dynamic fluctuations that were present in a latent and diffuse form in the absence of ATP. We demonstrate that drugs that potentiate CFTR's conductance do so not by directly acting on the gating residues, but rather by mimicking the allosteric signal sent by the ATP-binding sites. We have also uncovered a previously undiscovered allosteric 'hotspot' located proximal to the docking site of the phosphorylated regulatory (R) domain, thereby establishing a molecular foundation for its phosphorylation-dependent excitatory role. This study unveils the molecular underpinnings of allosteric connectivity within CFTR and highlights a novel allosteric 'hotspot' that could serve as a promising target for the development of novel therapeutic interventions.

MOTIVATION:Allostery in proteins is an essential phenomenon in biological processes. In this article, we present a computational model to predict paths of maximum information transfer between active and allosteric sites. In this information theoretic study, we use mutual information as the measure of information transfer, where transition probability of information from one residue to its contacting neighbors is proportional to the magnitude of mutual information between the two residues. Starting from a given residue and using a Hidden Markov Model, we successively determine the neighboring residues that eventually lead to a path of optimum information transfer. The Gaussian approximation of mutual information between residue pairs is adopted. The limits of validity of this approximation are discussed in terms of a nonlinear theory of mutual information and its reduction to the Gaussian form.RESULTS:Predictions of the model are tested on six widely studied cases, CheY Bacterial Chemotaxis, B-cell Lymphoma extra-large (Bcl-xL), Human proline isomerase cyclophilin A (CypA), Dihydrofolate reductase (DHFR), HRas GTPase and Caspase-1. The communication transmission rendering the propagation of local fluctuations from the active sites throughout the structure in multiple paths correlate well with the known experimental data. Distinct paths originating from the active site may likely represent a multi functionality such as involving more than one allosteric site and/or pre-existence of some other functional states. Our model is computationally fast and simple and can give allosteric communication pathways, which are crucial for the understanding and control of protein functionality.SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

Allostery is a key biological control mechanism, and dynamic information flow provides a perspective to describe allosteric interactions in causal relationships. Here, as a novel implementation of the Gaussian Network Model (GNM) based Transfer Entropy (TE) calculations, we show that the dissection of dynamic information into subsets of slow dynamic modes discloses different layers of multi-directional allosteric pathways inherent in a given protein structure. In these subsets of slow modes, the degree of collectivity (Col) in the information transfer of residues with their TE values (TECol score) identifies distinct residues as powerful effectors, global information sources; showing themselves with a high dynamic capacity to collectively disseminate information to others. As exemplified on aspartate transcarbamoylase (ATCase), Na+/K+-adenosine triphosphatase (Na+/K+-ATPase), and human transient receptor potential melastatin 2 (TRPM2) along with a dataset of 20 proteins, these specific residues are associated with known active and allosteric sites. These information source residues, which collectively control others and lead allosteric communication pathways, hint at plausible binding sites for structure-based rational drug design.

ABSTRACT HIV-1 continues to be a global health concern since AIDS was first recognized by the World Health Organization (WHO). It is estimated that there were 38 million people infected with HIV-1 and 1.5 million deaths in 2019 alone. A better understanding of the details of the HIV late-stage life cycle, involving Pr55 Gag attachment to the membrane for the further oligomerization to release virion, will provide us new avenues for potential treatment. Inositol hexakisphosphate (IP6) is an abundant endogenous cyclitol molecule and its binding was linked to the oligomerization of Pr55 Gag via the MA domain. However, the binding site of IP6 on MA was unknown and the structural details of this interaction were missing. Here, we present three high-resolution crystal structures of the MA domain in complex with IP6 molecules to reveal its binding mode. Additionally, extensive Differential Scanning Fluorimetry analysis combined with cryo- and ambient-temperature X-ray crystallography and computational biology identify the key residues that participate in IP6 binding. Our data provide novel insights about the multilayered HIV-1 virion assembly process that involves the interplay of IP6 with PIP2, a phosphoinositide essential for the membrane binding of Pr55 Gag . IP6 and PIP2 have neighboring alternate binding sites within the same highly basic region (residues 18-33). This indicates that IP6 and PIP2 bindings are not mutually exclusive and may play a key role in coordinating virion particles’ membrane localization. Based on our three different IP6-MA complex crystal structures, we propose a new model that involves the IP6 coordination of the oligomerization of outer MA and inner CA domain 2D layers during assembly and budding.

Recently, it has been showed that cancer missense mutations selectively target the neighborhood of hinge residues, which are key sites in protein dynamics. Here, we show that this approach can be extended to find previously unknown candidate mutations and genes. To this aim, we developed a computational pipeline to detect significantly enriched three-dimensional (3D) clustering of missense mutations around hinge residues. The hinge residues were detected by applying a Gaussian network model. By systematically analyzing the PanCancer compendium of somatic mutations in nearly 10 000 tumors from the Cancer Genome Atlas, we identified candidate genes and mutations in addition to well known ones. For instance, we found significantly enriched 3D clustering of missense mutations in known cancer genes including CDK4, CDKN2A, TCL1A, and MAPK1. Beside these known genes, we also identified significantly enriched 3D clustering of missense mutations around hinge residues in PLA2G4A, which may lead to excessive phosphorylation of the extracellular signal-regulated kinases. Furthermore, we demonstrated that hinge-based features improves pathogenicity prediction for missense mutations. Our results show that the consideration of clustering around hinge residues can help us explain the functional role of the mutations in known cancer genes and identify candidate genes.

Rac1 is a small member of the Rho GTPase family. One of the most important downstream effectors of Rac1 is a serine/threonine kinase, p21-activated kinase 1 (PAK1). Mutational activation of PAK1 by Rac1 has oncogenic signaling effects. Here, although we focus on Rac1-PAK1 interaction by atomic-force-microscopy-based single-molecule force spectroscopy experiments, we explore the effect of active mutations on the intrinsic dynamics and binding interactions of Rac1 by Gaussian network model analysis and molecular dynamics simulations. We observe that Rac1 oncogenic mutations are at the hinges of three global modes of motion, suggesting the mechanical changes as potential markers of oncogenicity. Indeed, the dissociation of wild-type Rac1-PAK1 complex shows two distinct unbinding dynamic states that are reduced to one with constitutively active Q61L and oncogenic Y72C mutant Rac1, as revealed by single-molecule force spectroscopy experiments. Q61L and Y72C mutations change the mechanics of the Rac1-PAK1 complex by increasing the elasticity of the protein and slowing down the transition to the unbound state. On the other hand, Rac1's intrinsic dynamics reveal more flexible GTP and PAK1-binding residues on switches I and II with Q61L, Y72C, oncogenic P29S and Q61R, and negative T17N mutations. The cooperativity in the fluctuations of GTP-binding sites around the p-loop and switch I decreases in all mutants, mostly in Q61L, whereas some PAK1-binding residues display enhanced coupling with GTP-binding sites in Q61L and Y72C and within each other in P29S. The predicted binding free energies of the modeled Rac1-PAK1 complexes show that the change in the dynamic behavior likely means a more favorable PAK1 interaction. Overall, these findings suggest that the active mutations affect intrinsic functional dynamic events and alter the mechanics underlying the binding of Rac1 to GTP and upstream and downstream partners including PAK1.

Oligomerization of Pr55 Gag is a critical step of the late stage of the HIV life cycle. It has been known that the binding of IP6, an abundant endogenous cyclitol molecule at the MA domain, has been linked to the oligomerization of Pr55 Gag . However, the exact binding site of IP6 on MA remains unknown and the structural details of this interaction are missing. Here, we present three high-resolution crystal structures of the MA domain in complex with IP6 molecules to reveal its binding mode. Additionally, extensive Differential Scanning Fluorimetry analysis combined with cryo- and ambient-temperature X-ray crystallography and GNM-based transfer entropy calculations identify the key residues that participate in IP6 binding. Our data provide novel insights about the multilayered HIV-1 virion assembly process that involves the interplay of IP6 with PIP2, a phosphoinositide essential for the binding of Pr55 Gag to membrane. IP6 and PIP2 have neighboring alternate binding sites within the same highly basic region (residues 18–33). This indicates that IP6 and PIP2 bindings are not mutually exclusive and may play a key role in coordinating virion particles’ membrane localization. Based on our three different IP6-MA complex crystal structures, we propose a new model that involves IP6 coordination of the oligomerization of outer MA and inner CA domain’s 2D layers during assembly and budding.

Deep mutational scanning enables examination of the effects of many mutations at each amino acid position in a query protein, readily disclosing positions that are particularly sensitive. Mutations in these positions alter protein function the most. Here, on the premise that dynamics underlie function, we explore to what extent the measured sensitivity to mutations could be linked to-perhaps be explained by-the structural dynamics of the protein. We employ a minimalist perturbation-response approach based on the Gaussian Network Model (GNM) on a data set of seven proteins with deep mutational scanning data. The analysis shows that the mutation-sensitive positions are often of capacity to modulate the global dynamics and to intermediate allosteric interactions in the structure. With that, upon strain perturbation, these positions decrease residue fluctuations the most, affecting function via entropy changes. This is particularly relevant for positions that are distant from binding sites or other functional regions of the protein and are sensitive to mutations, nevertheless. Our results indicate that mutations in these positions allosterically manipulate protein function.

Allostery is an intrinsic dynamic phenomenon that underlies functional long-distance interactions in proteins, which we study here by stochastic calculus approach to elastic network models (ENMs). We show that once you drop the usually accepted high friction limit and include hydrodynamic interactions in ENMs, a simple measure that uses the pairwise difference in the time-delayed correlations of residue fluctuations provides insight about functional sites and their dynamical behaviour in allosteric communication. We present this with three exemplary cases Aspartate Carbamoyl transferase, Insulin Receptor and DNA-dependent Protein Kinase. We show that proteins possess characteristic pathways operating at different time-delay windows with slow to faster motions underlying the protein function. As these pathways help communication between key residues of functionality, they can also be used to identify their locations without any prior knowledge other than the protein crystal structure.