Hidden electrostatic basis of dynamic allostery in a PDZ domain

Rational Design of Formate Dehydrogenase for Enhanced Thermal Stability and Catalytic Activity in Bioelectrocatalysis

Formate dehydrogenase can be utilized as a biocatalyst in the bioelectrocatalysis of converting CO2 into formic acid. However, its industrial application has been hindered by limited thermal stability. This study successfully obtained a mutant (D533S/E684I) with enhanced thermal stability and catalytic activity through the rational design of flexible regions. The mutant exhibited a half-life (t1/2) 1.5 times longer than the wild type (WT) at 35 °C, along with a specific enzyme activity 7.46 times higher than that of the WT. Additionally, the catalytic efficiency (kcat/Km value) of the mutant toward the substrate was 2.72 s-1·mM-1, representing a 19.4-fold increase compared to the WT (0.14 s-1·mM-1). Formic acid production reached 53.4 mM through bioelectrocatalysis after 10 h, utilizing the mutant as the biocatalyst. Molecular dynamics simulations and structural analysis were employed to investigate the molecular mechanisms behind the enhanced thermal stability and activity. The displacement of a highly flexible region in the mutant may counteract the stability-activity trade-off. This study proposed a method for improving both thermal stability and activity in enzyme evolution.

Modulation of the conformational landscape of the PDZ3 domain by perturbation on a distal non-canonical α3 helix: decoding the microscopic mechanism of allostery in the PDZ3 domain

While allosteric signal transduction is crucial for protein signaling and regulation, the dynamic process of allosteric communication remains poorly understood. The third PDZ domain (PDZ stands for the common structural domain shared by the postsynaptic density protein (PSD95), Drosophila disc large tumor suppressor (DlgA), and zonula occludens-1 protein (ZO-1)) serves as a classic example of a single-domain allosteric protein, demonstrating a long-range coupling between the C-terminal α helix (known as the α3 helix) and ligand binding. A molecular level understanding of how the α3 helix modulates the ligand binding affinity of the PDZ3 domain is still lacking. In this study, extensive molecular dynamics simulations corroborated with principal component analysis (PCA), ligand binding free energy calculations, energetic frustration analysis and Markov state model analysis are employed to uncover such molecular details. We demonstrate the definite presence of a binding competent closed-like state in the conformational landscape of wild-type PDZ3. The population modulations of this closed state and other binding incompetent states in the landscape due to α3-truncation/mutation of PDZ3 are explored. A correlation between the closed state population and calculated binding free energy is established, which supports the conformation selection mechanism. Covariance analysis identified the presence of correlated motion between two distant loops (β1-β2 and β2-β3) in the wild-type PDZ3 system, which weakened due to truncation/mutation in the distant α3 helix. It has also been observed that whenever the α3 helix was perturbed, the β2-β3 loop got further away from the binding groove and it is found to be correlated with the binding free energy values. Energetic frustration analysis of the PDZ3 domain also showed that the β2-β3 loop is highly frustrated. Finally, MSM analysis revealed a relevant timescale (closed to open state transition), which is similar to the observed experimental signal transduction timescale for the system. These observations led to the conclusion that the distantly located α3 helix plays a pivotal role in regulating the conformational landscape of the PDZ3 domain, determining the ligand binding affinity and resulting in allosteric behavior of the domain.

RNA's Dynamic Conformational Selection and Entropic Allosteric Mechanism in Controlling Cascade Protein Binding Events

In the TAR RNA of immunodeficiency viruses, an allosteric communication exists between a distant loop and a bulge. The bulge interacts with the TAT protein vital for transactivating viral RNA, while the loop interacts with cyclin-T1, contingent on TAT binding. Through extensive atomistic and free energy simulations, we investigate TAR-TAT binding in nonpathogenic bovine immunodeficiency virus (BIV) and pathogenic human immunodeficiency virus (HIV). Thermodynamic analysis reveals enthalpically driven binding in BIV and entropically favored binding in HIV. The broader global basin in HIV is attributed to binding-induced loop fluctuation, corroborated by nuclear magnetic resonance (NMR), indicating classical entropic allostery onset. While this loop fluctuation affects the TAT binding affinity, it generates a binding-competent conformation that aids subsequent effector (cyclin-T1) binding. This study underscores how two structurally similar apo-RNA scaffolds adopt distinct conformational selection mechanisms to drive enthalpic and entropic allostery, influencing protein affinity in the signaling cascade.

Leveraging Bidirectional Nature of Allostery To Inhibit Protein-Protein Interactions (PPIs): A Case Study of PCSK9-LDLR Interaction

The protein PCSK9 (proprotein convertase subtilisin/Kexin type 9) negatively regulates the recycling of LDLR (low-density lipoprotein receptor), leading to an elevated plasma level of LDL. Inhibition of PCSK9-LDLR interaction has emerged as a promising therapeutic strategy to manage hypercholesterolemia. However, the large interaction surface area between PCSK9 and LDLR makes it challenging to identify a small molecule competitive inhibitor. An alternative strategy would be to identify distal cryptic sites as targets for allosteric inhibitors that can remotely modulate PCSK9-LDLR interaction. Using several microseconds long molecular dynamics (MD) simulations, we demonstrate that on binding with LDLR, there is a significant conformational change (population shift) in a distal loop (residues 211-222) region of PCSK9. Consistent with the bidirectional nature of allostery, we establish a clear correlation between the loop conformation and the binding affinity with LDLR. Using a thermodynamic argument, we establish that the loop conformations predominantly present in the apo state of PCSK9 would have lower LDLR binding affinity, and they would be potential targets for designing allosteric inhibitors. We elucidate the molecular origin of the allosteric coupling between this loop and the LDLR binding interface in terms of the population shift in a set of salt bridges and hydrogen bonds. Overall, our work provides a general strategy toward identifying allosteric hotspots: compare the conformational ensemble of the receptor between the apo and bound states of the protein and identify distal conformational changes, if any. The inhibitors should be designed to bind and stabilize the apo-specific conformations.

Molecular mechanism of regulation of RhoA GTPase by phosphorylation of RhoGDI

Rho-specific guanine nucleotide dissociation inhibitors (RhoGDIs) play a crucial role in the regulation of Rho family GTPases. They act as negative regulators that prevent the activation of Rho GTPases by forming complexes with the inactive GDP-bound state of GTPase. Release of Rho GTPase from the RhoGDI-bound complex is necessary for Rho GTPase activation. Biochemical studies provide evidence of a "phosphorylation code," where phosphorylation of some specific residues of RhoGDI selectively releases its GTPase partner (RhoA, Rac1, Cdc42, etc.). This work attempts to understand the molecular mechanism behind this specific phosphorylation-induced reduction in binding affinity. Using several microseconds long atomistic molecular dynamics simulations of the wild-type and phosphorylated states of the RhoA-RhoGDI complex, we propose a molecular-interaction-based mechanistic model for the dissociation of the complex. Phosphorylation induces major structural changes, particularly in the positively charged polybasic region (PBR) of RhoA and the negatively charged N-terminal region of RhoGDI that contribute most to the binding affinity. Molecular mechanics Poisson-Boltzmann surface area binding energy calculations show a significant weakening of interaction on phosphorylation at the RhoA-specific site of RhoGDI. In contrast, phosphorylation at a Rac1-specific site does not affect the overall binding affinity significantly, which confirms the presence of a phosphorylation code. RhoA-specific phosphorylation leads to a reduction in the number of contacts between the PBR of RhoA and the N-terminal region of RhoGDI, which manifests a reduction of the binding affinity. Using hydrogen bond occupancy analysis and energetic perturbation network, we propose a mechanistic model for the allosteric response, i.e., long-range signal propagation from the site of phosphorylation to the PBR and buried geranylgeranyl group in the form of rearrangement and rewiring of hydrogen bonds and salt bridges. Our results highlight the crucial role of specific electrostatic interactions in manifestation of the phosphorylation code.

Allosteric Determinants in High Temperature Requirement A Enzymes Are Conserved and Regulate the Population of Active Conformations

High temperature requirement A (HtrA) are allosterically regulated enzymes wherein effector binding to the PDZ domain triggers proteolytic activity. Yet, it remains unclear if the inter-residue network governing allostery is conserved across HtrA enzymes. Here, we investigated and identified the inter-residue interaction networks by molecular dynamics simulations on representative HtrA proteases, Escherichia coli DegS and Mycobacterium tuberculosis PepD, in effector-bound and free forms. This information was used to engineer mutations that could potentially perturb allostery and conformational sampling in a different homologue, M. tuberculosis HtrA. Mutations in HtrA perturbed allosteric regulation─a finding consistent with the hypothesis that the inter-residue interaction network is conserved across HtrA enzymes. Electron density from data collected on cryo-protected HtrA crystals revealed that mutations altered the topology of the active site. Ensemble models fitted into electron density calculated from room-temperature diffraction data showed that only a fraction of these models had a catalytically competent active site conformation alongside a functional oxyanion hole thus providing experimental evidence that these mutations influenced conformational sampling. Mutations at analogous positions in the catalytic domain of DegS perturbed the coupling between effector binding and proteolytic activity, thus confirming the role of these residues in the allosteric response. The finding that a perturbation in the conserved inter-residue network alters conformational sampling and the allosteric response suggests that an ensemble allosteric model best describes regulated proteolysis in HtrA enzymes.

Allostery Frustrates the Experimentalist

Proteins interact with other proteins, with nucleic acids, lipids, carbohydrates and various small molecules in the living cell. These interactions have been quantified and structurally characterized in numerous studies such that we today have a comprehensive picture of protein structure and function. However, proteins are dynamic and even folded proteins are likely more heterogeneous than they appear in most descriptions. One property of proteins that relies on dynamics and heterogeneity is allostery, the ability of a protein to change structure and function upon ligand binding to an allosteric site. Over the last decades the concept of allostery was broadened to embrace all types of long-range interactions across a protein including purely entropic changes without a conformational change in single protein domains. But with this re-definition came a problem: How do we measure allostery? In this opinion, we discuss some caveats arising from the quantitative description of single-domain allostery from an experimental perspective and how the limitations cannot be separated from the definition of allostery per se. Furthermore, we attempt to tie together allostery with the concept of frustration in an effort to investigate the links between these two complex, and yet general, properties of proteins. We arrive at the conclusion that the sensitivity to perturbation of allosteric networks in single protein domains is too large for the networks to be of significant biological relevance.

Allosteric Signaling in PDZ Energetic Networks: Embedding Error Analysis

Allosteric signaling in proteins has been known for some half a century, yet how the signal traverses the protein remains an active area of research. Recently, the importance of electrostatics to achieve long-range signaling has become increasingly appreciated. Our laboratory has been working on developing network approaches to capture such interactions. In this study, we turn our attention to the well-studied allosteric model protein, PDZ. We study the allosteric dynamics on a per-residue basis in key constructs involving the PDZ domain, its allosteric effector, and its peptide ligand. We utilize molecular dynamics trajectories to create the networks for the constructs to explore the allosteric effect by plotting the heat kernel results onto axes defined by principal components. We introduce a new metric to quantitate the volume sampled by a residue in the latent space. We relate our findings to PDZ and the greater field of allostery.

Investigating the allosteric response of the PICK1 PDZ domain to different ligands with all-atom simulations

The PDZ family is comprised of small modular domains that play critical roles in the allosteric modulation of many cellular signaling processes by binding to the C-terminal tail of different proteins. As dominant modular proteins that interact with a diverse set of peptides, it is of particular interest to explore how different binding partners induce different allosteric effects on the same PDZ domain. Because the PICK1 PDZ domain can bind different types of ligands, it is an ideal test case to answer this question and explore the network of interactions that give rise to dynamic allostery. Here, we use all-atom molecular dynamics simulations to explore dynamic allostery in the PICK1 PDZ domain by modeling two PICK1 PDZ systems: PICK1 PDZ-DAT and PICK1 PDZ-GluR2. Our results suggest that ligand binding to the PICK1 PDZ domain induces dynamic allostery at the αA helix that is similar to what has been observed in other PDZ domains. We found that the PICK1 PDZ-ligand distance is directly correlated with both dynamic changes of the αA helix and the distance between the αA helix and βB strand. Furthermore, our work identifies a hydrophobic core between DAT/GluR2 and I35 as a key interaction in inducing such dynamic allostery. Finally, the unique interaction patterns between different binding partners and the PICK1 PDZ domain can induce unique dynamic changes to the PICK1 PDZ domain. We suspect that unique allosteric coupling patterns with different ligands may play a critical role in how PICK1 performs its biological functions in various signaling networks.

Nonequilibrium Modeling of the Elementary Step in PDZ3 Allosteric Communication

While allostery is of paramount importance for protein signaling and regulation, the underlying dynamical process of allosteric communication is not well understood. The PDZ3 domain represents a prime example of an allosteric single-domain protein, as it features a well-established long-range coupling between the C-terminal α₃-helix and ligand binding. In an intriguing experiment, Hamm and co-workers employed photoswitching of the α₃-helix to initiate a conformational change of PDZ3 that propagates from the C-terminus to the bound ligand within 200 ns. Performing extensive nonequilibrium molecular dynamics simulations, the modeling of the experiment reproduces the measured time scales and reveals a detailed picture of the allosteric communication in PDZ3. In particular, a correlation analysis identifies a network of contacts connecting the α₃-helix and the core of the protein, which move in a concerted manner. Representing a one-step process and involving direct α₃-ligand contacts, this cooperative transition is considered as the elementary step in the propagation of conformational change.

Phenol sensing in nature is modulated via a conformational switch governed by dynamic allostery

The NtrC family of proteins senses external stimuli and accordingly stimulates stress and virulence pathways via activation of associated σ⁵⁴-dependent RNA polymerases. However, the structural determinants that mediate this activation are not well understood. Here, we establish using computational, structural, biochemical, and biophysical studies that MopR, an NtrC protein, harbors a dynamic bidirectional electrostatic network that connects the phenol pocket to two distal regions, namely the “G-hinge” and the “allosteric linker.” While the G-hinge influences the entry of phenol into the pocket, the allosteric linker passes the signal to the downstream ATPase domain. We show that phenol binding induces a rewiring of the electrostatic connections by eliciting dynamic allostery and demonstrates that perturbation of the core relay residues results in a complete loss of ATPase stimulation. Furthermore, we found a mutation of the G-hinge, ∼20 Å from the phenol pocket, promotes altered flexibility by shifting the pattern of conformational states accessed, leading to a protein with 7-fold enhanced phenol binding ability and enhanced transcriptional activation. Finally, we conducted a global analysis that illustrates that dynamic allostery-driven conserved community networks are universal and evolutionarily conserved across species. Taken together, these results provide insights into the mechanisms of dynamic allostery-mediated conformational changes in NtrC sensor proteins.

Three Binding Conformations of BIO124 in the Pocket of the PICK1 PDZ Domain

The PDZ family has drawn attention as possible drug targets because of the domains’ wide ranges of function and highly conserved binding pockets. The PICK1 PDZ domain has been proposed as a possible drug target because the interactions between the PICK1 PDZ domain and the GluA2 subunit of the AMPA receptor have been shown to progress neurodegenerative diseases. BIO124 has been identified as a sub µM inhibitor of the PICK1–GluA2 interaction. Here, we use all-atom molecular dynamics simulations to reveal the atomic-level interaction pattern between the PICK1 PDZ domain and BIO124. Our simulations reveal three unique binding conformations of BIO124 in the PICK1 PDZ binding pocket, referred to here as state 0, state 1, and state 2. Each conformation is defined by a unique hydrogen bonding network and a unique pattern of hydrophobic interactions between BIO124 and the PICK1 PDZ domain. Interestingly, each conformation of BIO124 results in different dynamic changes to the PICK1 PDZ domain. Unlike states 1 and 2, state 0 induces dynamic coupling between BIO124 and the αA helix. Notably, this dynamic coupling with the αA helix is similar to what has been observed in other PDZ–ligand complexes. Our analysis indicates that the interactions formed between BIO124 and I35 may be the key to inducing dynamic coupling with the αA helix. Lastly, we suspect that the conformational shifts observed in our simulations may affect the stability and thus the overall effectiveness of BIO124. We propose that a physically larger inhibitor may be necessary to ensure sufficient interactions that permit stable binding between a drug and the PICK1 PDZ domain.

Resonance assignment of the Shank1 PDZ domain

Shank proteins are among the most abundant and well-studied postsynaptic scaffold proteins. Their PDZ domain has unique characteristics as one of its loop regions flanking the ligand-binding site is uniquely long and has also been implicated in the formation of PDZ dimers. Here we report the initial characterization of the Shank1 PDZ domain by solution NMR spectroscopy. The assigned chemical shifts are largely consistent with the common features of PDZ domains in general and the available Shank PDZ crystal structures in particular. Our analysis suggests that under the conditions investigated, the domain is monomeric and the unique loop harbors a short helical segment, observed in only one of the known X-ray structures so far. Our work stresses the importance of solution-state investigations to fully decipher the functional relevance of the structural and dynamical features unique to Shank PDZ domains.

Structural dynamics support electrostatic interactions in the active site of Adenylate Kinase

Electrostatic preorganization as well as structural and dynamic heterogeneity are often used to rationalize the remarkable catalytic efficiency of enzymes. However, they are often presented as incompatible because the generation of permanent electrostatic effects implies that the protein structure remains rigid. Here, we use a metric, electric fields, that can treat electrostatic contributions and dynamics effects on equal footing, for a unique perspective on enzymatic catalysis. We find that the residues that contribute the most to electrostatic interactions with the substrate in the active site of Adenylate Kinase (our working example) are also the most flexible residues. Further, entropy-tuning mutations raise flexibility at the picosecond timescale where more conformations can be visited on short time periods, thereby softening the sharp heterogeneity normally visible at the microsecond timescale.

Molecular Insights into Phosphorylation-Induced Allosteric Conformational Changes in a β2-Adrenergic Receptor

The large conformational flexibility of G protein-coupled receptors (GPCRs) has been a puzzle in structural and pharmacological studies for the past few decades. Apart from structural rearrangements induced by ligands, enzymatic phosphorylations by GPCR kinases (GRKs) at the carboxy-terminal tail (C-tail) of a GPCR also make conformational alterations to the transmembrane helices and facilitates the binding of one of its transducer proteins named β-arrestin. The phosphorylation-induced conformational transition of the receptor that causes specific binding to β-arrestin but prevents the association of other transducers such as G proteins lacks atomistic understanding and is elusive to experimental studies. Using microseconds of all-atom conventional and Gaussian accelerated molecular dynamics (GaMD) simulations, we investigate the allosteric mechanism of phosphorylation induced-conformational changes in β₂-adrenergic receptor, a well-characterized GPCR model system. Free energy profiles reveal that the phosphorylated receptor samples a new conformational state in addition to the canonical active state corroborating with recent nuclear magnetic resonance experimental findings. The new state has a smaller intracellular cavity that is likely to accommodate β-arrestin better than G protein. Using contact map and inter-residue interaction energy calculations, we found the phosphorylated C-tail adheres to the cytosolic surface of the transmembrane domain of the receptor. Transfer entropy calculations show that the C-tail residues drive the correlated motions of TM residues, and the allosteric signal is relayed via several residues at the cytosolic surface. Our results also illustrate how the redistribution of inter-residue nonbonding interaction couples with the allosteric communication from the phosphorylated C-tail to the transmembrane. Atomistic insight into phosphorylation-induced β-arrestin specific conformation is therapeutically important to design drugs with higher efficacy and fewer side effects. Our results, therefore, open novel opportunities to fine-tune β-arrestin bias in GPCR signaling.

Allosterism in the PDZ Family

Dynamic allosterism allows the propagation of signal throughout a protein. The PDZ (PSD-95/Dlg1/ZO-1) family has been named as a classic example of dynamic allostery in small modular domains. While the PDZ family consists of more than 200 domains, previous efforts have primarily focused on a few well-studied PDZ domains, including PTP-BL PDZ2, PSD-95 PDZ3, and Par6 PDZ. Taken together, experimental and computational studies have identified regions of these domains that are dynamically coupled to ligand binding. These regions include the αA helix, the αB lower-loop, and the αC helix. In this review, we summarize the specific residues on the αA helix, the αB lower-loop, and the αC helix of PTP-BL PDZ2, PSD-95 PDZ3, and Par6 PDZ that have been identified as participants in dynamic allostery by either experimental or computational approaches. This review can serve as an index for researchers to look back on the previously identified allostery in the PDZ family. Interestingly, our summary of previous work reveals clear consistencies between the domains. While the PDZ family has a low sequence identity, we show that some of the most consistently identified allosteric residues within PTP-BL PDZ2 and PSD-95 PDZ3 domains are evolutionarily conserved. These residues include A46/A347, V61/V362, and L66/L367 on PTP-BL PDZ2 and PSD-95 PDZ3, respectively. Finally, we expose a need for future work to explore dynamic allostery within (1) PDZ domains with multiple binding partners and (2) multidomain constructs containing a PDZ domain.

Hidden electrostatic energy contributions define dynamic allosteric communications within p53 during molecular recognition

Molecular recognition is fundamental to transcription regulation. As a transcription factor, the tumor suppressor p53 has to recognize either specific DNA sequences or repressor protein partners. However, the molecular mechanism underlying the p53 conformational switch from the DNA-bound to repressor-bound states is not fully characterized. The highly charged nature of these interacting molecules prompted us to explore the nonbonded energy contributions behind molecular recognition of either a DNA or the repressor protein iASPP by p53 DNA binding domain (p53DBD), using molecular dynamics simulation followed by rigorous analyses of energy terms. Our results illuminate the allosteric pathway by which iASPP binding to p53 diminishes binding affinity between p53 and DNA. Even though the p53DBD uses a common framework of residues for recognizing both DNA and iASPP, a comparison of the electrostatics in the two p53DBD complexes revealed significant differences in residue-wise contributions to the electrostatic energy. We found that an electrostatic allosteric communication path exists in the presence of both substrates. It consists of evolutionarily conserved residues, from residue K120 of the binding loop L1 to a distal residue R213 of p53DBD. K120 is near the DNA in the p53DBD-DNA complex, whereas iASPP binding moves it away from its DNA binding position in the p53DBD-iASPP complex. The "energy hubs" (the residues show a higher degree of connectivity with other residues in the electrostatic networks) determined from the electrostatic network analysis established that this conformational change in K120 completely rewires the electrostatic network from K120 to R213, thereby impeding DNA binding. Furthermore, we found shifting populations of hydrogen bonds and salt bridges reduce pairwise electrostatic energies within p53DBD in its DNA-bound state.

Allosteric Mechanism of Human Mitochondrial Phenylalanyl-tRNA Synthetase: An Atomistic MD Simulation and a Mutual Information-Based Network Study

Aminoacyl-tRNA synthetases (aaRSs), a family of ubiquitous and essential enzymes, can bind target tRNAs and catalyze the aminoacylation reaction in genetic code translation. In this work, we explore the dynamic properties and allosteric communication of human mitochondrial phenylalanyl-tRNA synthetase (hmPheRS) in free and bound states to understand the mechanisms of its tRNA^Phe recognition and allostery using molecular dynamics simulations combined with the torsional mutual information-based network model. Our results reveal that hmPheRS's residue mobility and inter-residue motional coupling are significantly enhanced by tRNA^Phe binding, and there occurs a strong allosteric communication which is critical for the aminoacylation reaction, suggesting the vital role of tRNA^Phe binding in the enzyme's function. The identified signaling pathways mainly make the connections between the anticodon binding domain (ABD) and catalytic domain (CAD), as well as within the CAD composed of many functional fragments and active sites, revealing the co-regulation role of them to act coordinately and achieve hmPheRS's aminoacylation function. Besides, several key residues along the communication pathways are identified to be involved in mediating the coordinated coupling between anticodon recognition at the ABD and activation process at the CAD, showing their pivotal role in the allosteric network, which are well consistent with the experimental observation. This study sheds light on the allosteric communication mechanism in hmPheRS and can provide important information for the structure-based drug design targeting aaRSs.

The Speed of Allosteric Signaling Within a Single-Domain Protein

While much is known about different allosteric regulation mechanisms, the nature of the allosteric signal and the time scale on which it propagates remains elusive. The PDZ3 domain from postsynaptic density-95 protein is a small protein domain with a terminal third α-helix, i.e., the α3-helix, which is known to be allosterically active. By cross-linking the allosteric helix with an azobenzene moiety, we obtained a photocontrollable PDZ3 variant. Photoswitching triggers its allosteric transition, resulting in a change in binding affinity of a peptide to the remote binding pocket. Using time-resolved infrared and UV/vis spectroscopy, we follow the allosteric signal transduction and reconstruct the timeline in which the allosteric signal propagates through the protein within 200 ns.

Dynamic energy correlation analysis of E. coli aspartokinase III and alteration of allosteric regulation by manipulating energy transduction pathways

Conformational change associated with allosteric regulation in a protein is ultimately driven by energy transformation. However, little is known about the latter process. In this work, we combined steered molecular dynamics simulations and sequence conservation analysis to investigate the conformational changes and energy transformation in the allosteric enzyme aspartokinase III (AK III) from Escherichia coli. Correlation analysis of energy change at residue level indicated significant transformation between electrostatic energy and dihedral angle energy during the allosteric regulation. Key amino acid residues located in the corresponding energy transduction pathways were identified by dynamic energy correlation analysis. To verify their functions, residues with a high energy correlation in the pathways were altered and their effects on allosteric regulation of AKIII were determined. This study sheds new insights into energy transformation during allosteric regulation of AK III and proposes a strategy to identify key residues that are involved in intramolecular energy transduction and thus in driving the allosteric process.

On the Emergence of Orientational Order in Folded Proteins with Implications for Allostery

The beautiful structures of single- and multi-domain proteins are clearly ordered in some fashion but cannot be readily classified using group theory methods that are successfully used to describe periodic crystals. For this reason, protein structures are considered to be aperiodic, and may have evolved this way for functional purposes, especially in instances that require a combination of softness and rigidity within the same molecule. By analyzing the solved protein structures, we show that orientational symmetry is broken in the aperiodic arrangement of the secondary structure elements (SSEs), which we deduce by calculating the nematic order parameter, P2. We find that the folded structures are nematic droplets with a broad distribution of P2. We argue that a non-zero value of P2, leads to an arrangement of the SSEs that can resist external forces, which is a requirement for allosteric proteins. Such proteins, which resist mechanical forces in some regions while being flexible in others, transmit signals from one region of the protein to another (action at a distance) in response to binding of ligands (oxygen, ATP, or other small molecules).

Dynamic allostery controls the peptide sensitivity of the Ly49C natural killer receptor

Using a variety of activating and inhibitory receptors, natural killer (NK) cells protect against disease by eliminating cells that have downregulated class I major histocompatibility complex (MHC) proteins, such as in response to cell transformation or viral infection. The inhibitory murine NK receptor Ly49C specifically recognizes the class I MHC protein H-2K^b. Unusual among NK receptors, Ly49C exhibits a peptide-dependent sensitivity to H-2K^b recognition, which has not been explained despite detailed structural studies. To gain further insight into Ly49C peptide sensitivity, we examined Ly49C recognition biochemically and through the lens of dynamic allostery. We found that the peptide sensitivity of Ly49C arises through small differences in H-2K^b-binding affinity. Although molecular dynamics simulations supported a role for peptide-dependent protein dynamics in producing these differences in binding affinity, calorimetric measurements indicated an enthalpically as opposed to entropically driven process. A quantitative linkage analysis showed that this emerges from peptide-dependent dynamic tuning of electrostatic interactions across the Ly49C–H-2K^b interface. We propose a model whereby different peptides alter the flexibility of H-2K^b, which in turn changes the strength of electrostatic interactions across the protein–protein interface. Our results provide a quantitative assessment of how peptides alter Ly49C-binding affinity, suggest the underlying mechanism, and demonstrate peptide-driven allostery at work in class I MHC proteins. Lastly, our model provides a solution for how dynamic allostery could impact binding of some, but not all, class I MHC partners depending on the structural and chemical composition of the interfaces.

Theoretical Studies of the Acid-Base Equilibria in a Model Active Site of the Human 20S Proteasome

The 20S proteasome is a macromolecule responsible for the chemical step in the ubiquitin-proteasome system of degrading unnecessary and unused proteins of the cell. It plays a central role both in the rapid growth of cancer cells and in viral infection cycles. Herein, we present a computational study of the acid-base equilibria in an active site of the human proteasome (caspase-like), an aspect which is often neglected despite the crucial role protons play in the catalysis. As example substrates, we take the inhibition by epoxy- and boronic acid-containing warheads. We have combined cluster quantum mechanical calculations, replica exchange molecular dynamics, and Bayesian optimization of nonbonded potential terms in the inhibitors. In relation to the latter, we propose an easily scalable approach for the reevaluation of nonbonded potentials making use of the hybrid quantum mechanics molecular mechanics dynamics information. Our results show that coupled acid-base equilibria need to be considered when modeling the inhibition mechanism. The coupling between a neighboring lysine and the reacting threonine is not affected by the presence of the studied inhibitors.

Dynamic Community Composition Unravels Allosteric Communication in PDZ3

The third domain of PSD-95 (PDZ3) is a model for investigating allosteric communication in protein and ligand interactions. While motifs contributing to its binding specificity have been scrutinized, a conformational dynamical basis is yet to be established. Despite the miniscule structural changes due to point mutants, the observed significant binding affinity differences have previously been assessed with a focus on two α-helices located at the binding groove (α₂) and the C-terminus (α₃). Here, we employ a new computational approach to develop a generalized view on the molecular basis of PDZ3 binding selectivity and interaction communication for a set of point mutants of the protein (G330T, H372A, G330T-H372A) and its ligand (CRIPT, named L₁, and its T-2F variant, L₂) along with the wild type (WT). To analyze the dynamical aspects hidden in the conformations that are produced by molecular dynamics simulations, we utilize variations in community composition calculated based on the betweenness centrality measure from graph theory. We find that the highly charged N-terminus, which is located far from the ligand, has the propensity to share the same community with the ligand in the biologically functional complexes, indicating a distal segment might mediate the binding dynamics. N- and C-termini of PDZ3 share communities, and α₃ acts as a hub for the whole protein by sustaining the communication with all structural segments, albeit being a trait not unique to the functional complexes. Moreover, α₂ which lines the binding cavity frequently parts communities with the ligand and is not a controller of the binding but is rather a slave to the overall dynamics coordinated by the N-terminus. Thus, ligand binding fate in PDZ3 is traced to the population of community compositions extracted from dynamics despite the lack of significant conformational changes.

FMODB: The World's First Database of Quantum Mechanical Calculations for Biomacromolecules Based on the Fragment Molecular Orbital Method

We developed the world's first web-based public database for the storage, management, and sharing of fragment molecular orbital (FMO) calculation data sets describing the complex interactions between biomacromolecules, named FMO Database (https://drugdesign.riken.jp/FMODB/). Each entry in the database contains relevant background information on how the data was compiled as well as the total energy of each molecular system and interfragment interaction energy (IFIE) and pair interaction energy decomposition analysis (PIEDA) values. Currently, the database contains more than 13 600 FMO calculation data sets, and a comprehensive search function implemented at the front-end. The procedure for selecting target proteins, preprocessing the experimental structures, construction of the database, and details of the database front-end were described. Then, we demonstrated a use of the FMODB by comparing IFIE value distributions of hydrogen bond, ion-pair, and XH/π interactions obtained by FMO method to those by molecular mechanics approach. From the comparison, the statistical analysis of the data provided standard reference values for the three types of interactions that will be useful for determining whether each interaction in a given system is relatively strong or weak compared to the interactions contained within the data in the FMODB. In the final part, we demonstrate the use of the database to examine the contribution of halogen atoms to the binding affinity between human cathepsin L and its inhibitors. We found that the electrostatic term derived by PIEDA greatly correlated with the binding affinities of the halogen containing cathepsin L inhibitors, indicating the importance of QM calculation for quantitative analysis of halogen interactions. Thus, the FMO calculation data in FMODB will be useful for conducting statistical analyses to drug discovery, for conducting molecular recognition studies in structural biology, and for other studies involving quantum mechanics-based interactions.

Interplay among Structural Stability, Plasticity, and Energetics Determined by Conformational Attuning of Flexible Loops in PD-1

The dynamics and plasticity of the PD-1/PD-L1 axis are the bottlenecks for the discovery of small-molecule antagonists to perturb this interaction interface significantly. Understanding the process of this protein-protein interaction (PPI) is of fundamental biological interest in structure-based drug designing. Food and Drug Administration (FDA)-approved anti-PD-1 monoclonal antibodies (mAbs) are the first-in-class with distinct binding modes to access this axis clinically; however, their mechanistic aspects remain elusive. Here, we have unveiled the interactive interfaces with PD-L1 and mAbs to investigate the native plasticity of PD-1 at global (structural and dynamical) and local (residue side-chain orientations) levels. We found that the structural stability and coordinated C_α movements are increased in the presence of PD-1's binding partners. The rigorous analysis of these PPIs using computational biophysical approaches revealed PD-1's intrinsic plasticity, its concerted loops' movement (BC, FG, and CC'), distal side-chain motions, and the thermodynamic landscape, which are perturbed remarkably from its unbound to bound states. Based on intra-/inter-residues' contact networks and energetics, the hot-spots have been identified that were found to be essential to arrest the dynamical motions of PD-1 significantly for the rational design of therapeutic agents by mimicking the mAbs mechanism.

N-Terminus of the Third PDZ Domain of PSD-95 Orchestrates Allosteric Communication for Selective Ligand Binding

PDZ domains constitute common models to study single-domain allostery without significant structural changes. The third PDZ domain of PSD-95 (PDZ3) is known to have selective structural features that confer unique modulatory roles to this unit. In this model system, two residues, H372 directly connected to the binding site and G330 holding an off-binding-site position, were designated to assess the effect of mutations on binding selectivity. It has been observed that the H372A and G330T-H372A mutations change ligand preferences from class I (T/S amino acid at position -2 of the ligand) to class II (hydrophobic amino acid at the same position). Alternatively, the G330T single mutation leads to the recognition of both ligand classes. We have performed a series of molecular dynamics (MD) simulations for wild-type, H372A, and G330T single mutants and a double mutant of PDZ3 in the absence and presence of both types of ligands. With the combination of free-energy difference calculations and a detailed analysis of MD trajectories, "class switching" and "class bridging" behavior of PDZ3 mutants, as well as their effects on ligand selection and binding affinities are explained. We show that the dynamics of the charged N-terminus plays a fundamental role in determining the binding preferences in PDZ3 by altering the electrostatic energy. These findings are corroborated by simulations on N-terminus-truncated versions of these systems. The dynamical allostery orchestrated by the N-terminus offers a fresh perspective to the study of communication pathways in proteins.

Ensemble-Based Analysis of the Dynamic Allostery in the PSD-95 PDZ3 Domain in Relation to the General Variability of PDZ Structures

PDZ domains are abundant interaction hubs found in a number of different proteins and they exhibit characteristic differences in their structure and ligand specificity. Their internal dynamics have been proposed to contribute to their biological activity via changes in conformational entropy upon ligand binding and allosteric modulation. Here we investigate dynamic structural ensembles of PDZ3 of the postsynaptic protein PSD-95, calculated based on previously published backbone and side-chain S2 order parameters. We show that there are distinct but interdependent structural rearrangements in PDZ3 upon ligand binding and the presence of the intramolecular allosteric modulator helix α3. We have also compared these rearrangements in PDZ1-2 of PSD-95 and the conformational diversity of an extended set of PDZ domains available in the PDB database. We conclude that although the opening-closing rearrangement, occurring upon ligand binding, is likely a general feature for all PDZ domains, the conformer redistribution upon ligand binding along this mode is domain-dependent. Our findings suggest that the structural and functional diversity of PDZ domains is accompanied by a diversity of internal motional modes and their interdependence.

Protonation-Induced Dynamic Allostery in PDZ Domain: Evidence of Perturbation-Independent Universal Response Network

Dynamic allostery is a relatively new paradigm where certain external perturbations may lead to modulation of conformational dynamics at a distant part of a protein without significant changes in the overall structure. While most well-characterized examples of dynamic allostery involve binding with other entities like small molecules, peptides, or nucleic acids, in this work we demonstrate that chemical modifications like protonation may lead to significant dynamical allosteric response in a PDZ domain protein. Tuning the protonation states of two histidine residues (H317 and H372), we identify the allosteric pathways responsible for the dynamic response. Interestingly, the same set of residues that constitute the allosteric response network upon ligand binding seem to be responsible for protonation-induced dynamic allostery. Thus, we propose the existence of an inherent universal response network in signaling proteins, where the same set of residues can respond to varying types of external perturbations in terms of rearrangement of hydrogen-bonded network and redistribution of electrostatic interaction energies.

Adaptability and specificity: how do proteins balance opposing needs to achieve function?

Many proteins select from a small repertoire of 3-dimensional folds retained over evolutional timescales and recruited for different functions, with changes in local structure and sequence to enable specificity. Recent studies have revealed the evolutionary constraints on protein dynamics to achieve function. The significance of protein dynamics in simultaneously satisfying conformational flexibility/malleability and stability/precision requirements becomes clear upon dissecting the spectrum of equilibrium motions accessible to fold families. Accessibility to highly conserved global modes of motions shared by family members, to low-to-intermediate-frequency modes that distinguish subfamilies and confer specificity, and to conserved high-frequency modes ensuring chemical precision and core stability underlies functional specialization while exploiting highly versatile folds. These design principles are illustrated for the family of PDZ domains.

Supertertiary protein structure affects an allosteric network

Protein function can be allosterically regulated by changes in structure or dynamics. PDZ domains are classic examples for studies of allostery in single protein domains. However, PDZ domains are often found in multidomain proteins; in particular, PDZ3 is located in a supramodule containing three domains. The allosteric network in PDZ3 has never been studied in the presence of the adjacent domains. Here we map the allosteric network for a PDZ3:ligand complex, both in isolation and in the context of a supramodule. We demonstrate that the allosteric network is highly dependent on this supertertiary structure, with broad implications for studies of allostery in single domains.

The notion that protein function is allosterically regulated by structural or dynamic changes in proteins has been extensively investigated in several protein domains in isolation. In particular, PDZ domains have represented a paradigm for these studies, despite providing conflicting results. Furthermore, it is still unknown how the association between protein domains in supramodules, consitituting so-called supertertiary structures, affects allosteric networks. Here, we experimentally mapped the allosteric network in a PDZ:ligand complex, both in isolation and in the context of a supramodular structure, and show that allosteric networks in a PDZ domain are highly dependent on the supertertiary structure in which they are present. This striking sensitivity of allosteric networks to the presence of adjacent protein domains is likely a common property of supertertiary structures in proteins. Our findings have general implications for prediction of allosteric networks from primary and tertiary structures and for quantitative descriptions of allostery.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.

Demonstration of Binding Induced Structural Plasticity in a SH2 Domain

SH2 domains are common protein interaction domains able to recognize short aminoacidic sequences presenting a phosphorylated tyrosine (pY). In spite of their fundamental importance for cell physiology there is a lack of information about the mechanism by which these domains recognize and bind their natural ligands. The N-terminal SH2 (N-SH2) domain of PI3K mediates the interaction with different scaffolding proteins and is known to recognize a specific pY-X-X-M consensus sequence. These interactions are at the cross roads of different molecular pathways and play a key role for cell development and division. By combining mutagenesis, chemical kinetics and NMR, here we provide a complete characterization of the interaction between N-SH2 and a peptide mimicking the scaffolding protein Gab2. Our results highlight that N-SH2 is characterized by a remarkable structural plasticity, with the binding reaction being mediated by a diffused structural region and not solely by the residues located in the binding pocket. Furthermore, the analysis of kinetic data allow us to pinpoint an allosteric network involving residues far from the binding pocket involved in specificity. Results are discussed on the light of previous works on the binding properties of SH2 domains.

Variance of Atomic Coordinates as a Dynamical Metric to Distinguish Proteins and Protein-Protein Interactions in Molecular Dynamics Simulations

Protein dynamics is a manifestation of the complex trajectories of these biomolecules on a multidimensional rugged potential energy surface (PES) driven by thermal energy. At present, computational methods such as atomistic molecular dynamics (MD) simulations can describe thermal protein conformational changes in fully solvated environments over millisecond timescales. Despite these advances, a quantitative assessment of protein dynamics remains a complicated topic, intricately linked to issues such as sampling convergence and the identification of appropriate reaction coordinates/structural features to describe protein conformational states and motions. Here, we present the cumulative variance of atomic coordinate fluctuations (CVCF) along trajectories as an intuitive PES sensitive metric to assess both the extent of sampling and protein dynamics captured in MD simulations. We first examine the sampling problem in model one- (1D) and two-dimensional (2D) PES to demonstrate that the CVCF when traced as a function of the sampling variable (time in MD simulations) can identify local and global equilibria. Further, even far from global equilibrium, a situation representative of standard MD trajectories of proteins, the CVCF can distinguish different PES and therefore resolve the resultant protein dynamics. We demonstrate the utility of our CVCF analysis by applying it to distinguish the dynamics of structurally homologous proteins from the ubiquitin family (ubiquitin, SUMO1, SUMO2) and ubiquitin protein-protein interactions. Our CVCF analysis reveals that differential side-chain dynamics from the structured part of the protein (the conserved β-grasp fold) present distinct protein PES to distinguish ubiquitin from SUMO isoforms. Upon binding to two functionally distinct protein partners (UBCH5A and UEV), intrinsic ubiquitin dynamics changes to reflect the binding context even though the two proteins have similar binding modes, which lead to negligible (sub-angstrom scale) structural changes.

Support Vector Regression-Based Monte Carlo Simulation of Flexible Water Clusters

Molecular simulations based on classical force fields are computationally efficient but lack accuracy due to the empirical formulation of non-bonded interactions. Quantum mechanical (QM) methods, albeit accurate, have inhibitory computational costs for large molecules and clusters. Hence, to overcome the bottleneck, machine learning (ML)-based methods have been employed in the recent years. We had earlier reported a combined scheme of many-body expansion (MBE) and ML to predict the interaction energies of rigid water clusters. In this work, we proceed toward building a flexible water model using the ML-MBE scheme. This ML-MBE scheme has an error of <1% for interaction energy prediction in comparison to the parent QM method for flexible water decamers. Machine learning-based Monte Carlo simulations (MLMC) are performed with this water model, and the structural properties of these configurations are compared with those obtained from ab initio molecular dynamics (AIMD) and the TIP3P classical force field. The radial distribution functions, tetrahedral order parameters, and number of hydrogen bonds in AIMD and MLMC have a similar qualitative and quantitative trend, whereas the classical force fields show a significant deviation.

Specificity in PDZ-peptide interaction networks: Computational analysis and review

Globular PDZ domains typically serve as protein-protein interaction modules that regulate a wide variety of cellular functions via recognition of short linear motifs (SLiMs). Often, PDZ mediated-interactions are essential components of macromolecular complexes, and disruption affects the entire scaffold. Due to their roles as linchpins in trafficking and signaling pathways, PDZ domains are attractive targets: both for controlling viral pathogens, which bind PDZ domains and hijack cellular machinery, as well as for developing therapies to combat human disease. However, successful therapeutic interventions that avoid off-target effects are a challenge, because each PDZ domain interacts with a number of cellular targets, and specific binding preferences can be difficult to decipher. Over twenty-five years of research has produced a wealth of data on the stereochemical preferences of individual PDZ proteins and their binding partners. Currently the field lacks a central repository for this information. Here, we provide this important resource and provide a manually curated, comprehensive list of the 271 human PDZ domains. We use individual domain, as well as recent genomic and proteomic, data in order to gain a holistic view of PDZ domains and interaction networks, arguing this knowledge is critical to optimize targeting selectivity and to benefit human health.

Intrinsic dynamics is evolutionarily optimized to enable allosteric behavior

Allosteric behavior is central to the function of many proteins, enabling molecular machinery, metabolism, signaling and regulation. Recent years have shown that the intrinsic dynamics of allosteric proteins defined by their 3-dimensional architecture or by the topology of inter-residue contacts favors cooperative motions that bear close similarity to structural changes they undergo during their allosteric actions. These conformational motions are usually driven by energetically favorable or soft modes at the low frequency end of the mode spectrum, and they are evolutionarily conserved among orthologs. These observations brought into light evolutionary adaptation mechanisms that help maintain, optimize or regulate allosteric behavior as the evolution from bacterial to higher organisms introduces sequential heterogeneities and structural complexities.

Probing Protein Allostery as a Residue-Specific Concept via Residue Response Maps

Allosteric regulation is a well-established phenomenon defined as a distal conformational or dynamical change of the protein upon allosteric effector binding. Here, we developed a novel approach to delineate allosteric effects in proteins. In this approach, we applied robust machine learning methods, including deep neural network and random forest, on extensive molecular dynamics (MD) simulations to distinguish otherwise similar allosteric states of proteins. Using the PDZ3 domain of PDS-95 as a model protein, we demonstrated that the allosteric effects could be represented as residue-specific properties through two-dimensional property-residue maps, which we refer to as "residue response maps". These maps were constructed through two machine learning methods and could accurately describe how different properties of various residues are affected upon allosteric perturbation on protein. Based on the "residue response maps", we propose allostery as a residue-specific concept, suggesting that all residues could be considered as allosteric residues because each residue "senses" the allosteric events through changing its single or multiple attributes in a quantitatively unique way. The "residue response maps" could be used to fingerprint a protein based on the unique patterns of residue responses upon binding events, providing a novel way to systematically describe the protein allosteric effects of each residue upon perturbation.

Molecular Dynamics Simulations Reveal the Inhibitory Mechanism of Dopamine against Human Islet Amyloid Polypeptide (hIAPP) Aggregation and Its Destabilization Effect on hIAPP Protofibrils

The aberrant self-assembly of human islet amyloid polypeptide (hIAPP) into toxic oligomers, protofibrils, and mature fibrils is associated with the pathogenesis of type 2 diabetes (T2D). Inhibition of hIAPP aggregation and destabilization of preformed hIAPP fibrils are considered as two major therapeutic strategies for treating T2D. Previous experimental studies reported that dopamine prevented the formation of hIAPP oligomers and fibrils. However, the underlying inhibitory mechanism at the atomic level remains elusive. Herein we investigated the conformational ensembles of hIAPP dimer with and without dopamine using replica-exchange molecular dynamics simulations. The simulations demonstrated that dopamine preferentially bound to R11, L12, F15, H18, F23, I26, L27, and Y37 residues, inhibited the formation of β-sheets in the amyloidogenic regions spanning residues ¹¹RLANFLVH¹⁸, ²²NFGAIL²⁷, and ³⁰TNVGSNT³⁶, and resulted in more disordered hIAPP dimers, thus hindering the amyloid formation of hIAPP. Protonated and deprotonated dopamine molecules displayed distinct binding capabilities but bound to similar residue sites on hIAPP. Additional microsecond molecular dynamics simulations showed that dopamine mainly bound to the β1 and turn regions of hIAPP protofibril and destabilized the protofibril structure. This study not only revealed the molecular mechanism of dopamine toward the inhibition of hIAPP aggregation but also demonstrated the protofibril-destabilizing effects of dopamine, which may be helpful for the design of drug candidates to treat T2D.

Differential Dynamics Underlying the Gln27Glu Population Variant of the β2-Adrenergic Receptor

The β₂-adrenergic receptor (β₂AR) is a membrane-bound G-protein-coupled receptor and an important drug target for asthma. Clinical studies report that the population variant Gln27Glu is associated with a differential response to common asthma drugs, such as albuterol, isoproterenol and terbutaline. Interestingly, the 27th amino acid is positioned on the N-terminal region that is the most flexible and consequently the least studied part of the receptor. In this study, we probe the molecular origin of the differential drug binding by performing structural modeling and simulations of the wild-type (Gln) and variant (Glu) receptors followed by ensemble docking with the ligands, albuterol, isoproterenol and terbutaline. In line with clinical studies, the ligands were observed to interact preferentially with the Glu variant. Our results indicate that the Glu residue at the 27th position perturbs the network of electrostatic interactions that connects the N-terminal region to the binding site in the wild-type receptor. As a result, the Glu variant is observed to bind better to the three ligands tested in this study. Our study provides a structural basis to explain the variable drug response associated with the 27th position polymorphism in the β₂AR and is a starting step to identify genotype-specific therapeutics.

gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations

Atomistic molecular dynamics (MD) simulations generate a wealth of information related to the dynamics of proteins. If properly analyzed, this information can lead to new insights regarding protein function and assist wet-lab experiments. Aiming to identify interactions between individual amino acid residues and the role played by each in the context of MD simulations, we present a stand-alone software called gRINN (get Residue Interaction eNergies and Networks). gRINN features graphical user interfaces (GUIs) and a command-line interface for generating and analyzing pairwise residue interaction energies and energy correlations from protein MD simulation trajectories. gRINN utilizes the features of NAMD or GROMACS MD simulation packages and automatizes the steps necessary to extract residue-residue interaction energies from user-supplied simulation trajectories, greatly simplifying the analysis for the end-user. A GUI, including an embedded molecular viewer, is provided for visualization of interaction energy time-series, distributions, an interaction energy matrix, interaction energy correlations and a residue correlation matrix. gRINN additionally offers construction and analysis of Protein Energy Networks, providing residue-based metrics such as degrees, betweenness-centralities, closeness centralities as well as shortest path analysis. gRINN is free and open to all users without login requirement at http://grinn.readthedocs.io.

The archaeal LDH-like malate dehydrogenase from Ignicoccus islandicus displays dual substrate recognition, hidden allostery and a non-canonical tetrameric oligomeric organization

The NAD(P)-dependent malate dehydrogenases (MalDHs) and NAD-dependent lactate dehydrogenases (LDHs) are homologous enzymes involved in central metabolism. They display a common protein fold and the same catalytic mechanism, yet have a stringent capacity to discriminate between their respective substrates. The MalDH/LDH superfamily is divided into several phylogenetically related groups. It has been shown that the canonical LDHs and LDH-like group of MalDHs are primarily tetrameric enzymes that diverged from a common ancestor. In order to gain understanding of the evolutionary history of the LDHs and MalDHs, the biochemical properties and crystallographic structure of the LDH-like MalDH from the hyperthermophilic archaeon Ignicoccus islandicus (I. isl) were determined. I. isl MalDH recognizes oxaloacetate as main substrate, but it is also able to use pyruvate. Surprisingly, with pyruvate, the enzymatic activity profile looks like that of allosteric LDHs, suggesting a hidden allosteric capacity in a MalDH. The I. isl MalDH tetrameric structure in the apo state is considerably different from those of canonical LDH-like MalDHs and LDHs, representing an alternative oligomeric organization. A comparison with MalDH and LDH counterparts provides strong evidence that the divergence between allosteric and non-allosteric members of the superfamily involves homologs with intermediate, atypical properties.

Nervous-Like Circuits in the Ribosome Facts, Hypotheses and Perspectives

In the past few decades, studies on translation have converged towards the metaphor of a “ribosome nanomachine”; they also revealed intriguing ribosome properties challenging this view. Many studies have shown that to perform an accurate protein synthesis in a fluctuating cellular environment, ribosomes sense, transfer information and even make decisions. This complex “behaviour” that goes far beyond the skills of a simple mechanical machine has suggested that the ribosomal protein networks could play a role equivalent to nervous circuits at a molecular scale to enable information transfer and processing during translation. We analyse here the significance of this analogy and establish a preliminary link between two fields: ribosome structure-function studies and the analysis of information processing systems. This cross-disciplinary analysis opens new perspectives about the mechanisms of information transfer and processing in ribosomes and may provide new conceptual frameworks for the understanding of the behaviours of unicellular organisms.

Mechanism of Solvent Control of Protein Dynamics

We find that the coupled interactions between protein and water polarization fluctuations play a dominant role in driving the configuration space random walk of solvated proteins. We perform atomistic molecular dynamics simulations on five proteins. Owing to a very low dielectric constant of protein, its dipolar groups experience forces from water along with local forces due to protein atoms. Energy fluctuations reveal a pronounced anticorrelation between protein and water contributions. The protein energy spectrum shows bimodal 1/f noise, which can be attributed to the influence of water on the dynamics of protein.