Correlated motions are a fundamental property of β-sheets

Classical molecular dynamics simulation identifies catechingallate as a promising antiviral polyphenol against MPOX palmitoylated surface protein

Cumulative global prevalence of the emergent monkeypox (MPX) infection in the non-endemic countries has been professed as a global public health predicament. Lack of effective MPX-specific treatments sets the baseline for designing the current study. This research work uncovers the effective use of known antiviral polyphenols against MPX viral infection, and recognises their mode of interaction with the target F13 protein, that plays crucial role in formation of enveloped virions. Herein, we have employed state-of-the-art machine learning based AlphaFold2 to predict the three-dimensional structure of F13 followed by molecular docking and all-atoms molecular dynamics (MD) simulations to investigate the differential mode of F13-polyphenol interactions. Our extensive computational approach identifies six potent polyphenols Rutin, Epicatechingallate, Catechingallate, Quercitrin, Isoquecitrin and Hyperoside exhibiting higher binding affinity towards F13, buried inside a positively charged binding groove. Intermolecular contact analysis of the docked and MD simulated complexes divulges three important residues Asp134, Ser137 and Ser321 that are observed to be involved in ligand binding through hydrogen bonds. Our findings suggest that ligand binding induces minor conformational changes in F13 to affect the conformation of the binding site. Concomitantly, essential dynamics of the six-MD simulated complexes reveals Catechin gallate, a known antiviral agent as a promising polyphenol targeting F13 protein, dominated with a dense network of hydrophobic contacts. However, assessment of biological activities of these polyphenols need to be confirmed through in vitro and in vivo assays, which may pave the way for development of new novel antiviral drugs.

Native dynamics and allosteric responses in PTP1B probed by high-resolution HDX-MS

Protein tyrosine phosphatase 1B (PTP1B) is a validated therapeutic target for obesity, diabetes, and certain types of cancer. In particular, allosteric inhibitors hold potential for therapeutic use, but an incomplete understanding of conformational dynamics and allostery in this protein has hindered their development. Here, we interrogate solution dynamics and allosteric responses in PTP1B using high-resolution hydrogen-deuterium exchange mass spectrometry (HDX-MS), an emerging and powerful biophysical technique. Using HDX-MS, we obtain a detailed map of backbone amide exchange that serves as a proxy for the solution dynamics of apo PTP1B, revealing several flexible loops interspersed among more constrained and rigid regions within the protein structure, as well as local regions that exchange faster than expected from their secondary structure and solvent accessibility. We demonstrate that our HDX rate data obtained in solution adds value to estimates of conformational heterogeneity derived from a pseudo-ensemble constructed from ~200 crystal structures of PTP1B. Furthermore, we report HDX-MS maps for PTP1B with active-site versus allosteric small-molecule inhibitors. These maps suggest distinct and widespread effects on protein dynamics relative to the apo form, including changes in locations distal (>35 Å) from the respective ligand binding sites. These results illuminate that allosteric inhibitors of PTP1B can induce unexpected changes in dynamics that extend beyond the previously understood allosteric network. Together, our data suggest a model of BB3 allostery in PTP1B that combines conformational restriction of active-site residues with compensatory liberation of distal residues that aid in entropic balancing. Overall, our work showcases the potential of HDX-MS for elucidating aspects of protein conformational dynamics and allosteric effects of small-molecule ligands and highlights the potential of integrating HDX-MS alongside other complementary methods, such as room-temperature X-ray crystallography, NMR spectroscopy, and molecular dynamics simulations, to guide the development of new therapeutics.

Exploring optimal drug targets through subtractive proteomics analysis and pangenomic insights for tailored drug design in tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis, ranks among the top causes of global human mortality, as reported by the World Health Organization's 2022 TB report. The prevalence of M. tuberculosis strains that are multiple and extensive-drug resistant represents a significant barrier to TB eradication. Fortunately, having many completely sequenced M. tuberculosis genomes available has made it possible to investigate the species pangenome, conduct a pan-phylogenetic investigation, and find potential new drug targets. The 442 complete genome dataset was used to estimate the pangenome of M. tuberculosis. This study involved phylogenomic classification and in-depth analyses. Sequential filters were applied to the conserved core genome containing 2754 proteins. These filters assessed non-human homology, virulence, essentiality, physiochemical properties, and pathway analysis. Through these intensive filtering approaches, promising broad-spectrum therapeutic targets were identified. These targets were docked with FDA-approved compounds readily available on the ZINC database. Selected highly ranked ligands with inhibitory potential include dihydroergotamine and abiraterone acetate. The effectiveness of the ligands has been supported by molecular dynamics simulation of the ligand-protein complexes, instilling optimism that the identified lead compounds may serve as a robust basis for the development of safe and efficient drugs for TB treatment, subject to further lead optimization and subsequent experimental validation.

Study of Correlated Motions to Detect the Conformational Transitions of the Intrinsically Disordered Sheep Prion Peptide

Intrinsically disordered proteins (IDPs) are known for their random structural changes throughout their sequence based on the environment. The mechanism underlying these structural changes is difficult to explain. All biological processes are known to follow the direction through which they act. A study of the correlated motion can help to understand the direction of the change. Herein, we introduced the multivariate statistical analysis (MSA) technique to study the correlated motion of the peptide. The correlated motion of the sheep prion peptide was studied with the change in the temperature and solvent. These techniques helped to identify the contributing residual motions that helped to form the different secondary structures of the protein and also the triggering factors that drive these sorts of residual motions. The structural details match the experimentally reported data. It was found that the direction of the change of the secondary structure for this peptide shifted from the C-terminal to the N-terminal with an increase in the temperature. It was found that the involvement of the hydrophobic residues present at the C-terminal and the middle residues (residues 12-17) is responsible for forming a β-sheet at the normal temperature. Hydration water was found to play an important role in this change. Insights gained from this study can be used to design strategies for desirable structural changes in the IDPs.

Computational study on Schiff base derived salicylaldehyde and furfuraldehyde derivatives as potent anti-tubercular agents: prospect to dihydropteroate synthase inhibitors

Nowadays, bacterial multidrug resistance has become a commonplace problem in clinics due to several intrinsic factors mediated through resistance to antibacterials obtained via bacterial consortia and extrinsic factors, such as non-uniform antibacterial policy and migration of resistant bacteria through human and other routes. The development of newer, effective anti-mycobacterial candidate(s) is coveted by clinics. Hybrid molecules would be comparatively more emulating against invasive bacterial strains; nevertheless, newer antibiotics are continually added. Herein, designing and developments of two series of Schiff-based salicylaldehyde S1-S7 and furfuraldehyde F1-F7 molecules individually bearing sulfonamide group are described; and those were synthesized and their structures by spectral characterization were confirmed. Concomitantly, molecule dynamic simulations of all atoms had been performed to fathom the mechanism of the action with these leading complexes. These data imply that the synthesized Schiff-based salicylaldehyde hybrids would be promising anti-tubercular compounds, which further need potent pharmacological evaluations.Communicated by Ramaswamy H. Sarma.

Elucidating the reversible and irreversible self-assembly mechanisms of low-complexity aromatic-rich kinked peptides and steric zipper peptides

Many RNA-binding proteins such as fused-in sarcoma (FUS) can self-assemble into reversible liquid droplets and fibrils through the self-association of their low-complexity (LC) domains. Recent experiments have revealed that SYG-rich segments in the FUS LC domains play critical roles in the reversible self-assembly behaviors of FUS. These FUS LC segments alone can self-assemble into reversible kinked fibrils, which are markedly different from the canonical irreversible steric zipper β-sheet fibrils. However, the molecular determinants underlying the reversible and irreversible self-assembly are poorly understood. Herein we conducted extensive all-atom and coarse-grained molecular dynamics simulations of four representative hexapeptides: two low-complexity aromatic-rich kinked peptides from the amyotrophic lateral sclerosis-related FUS protein, FUS37-42 (SYSGYS) and FUS54-59 (SYSSYG); and two steric zipper peptides from Alzheimer's-associated Aβ and Tau proteins, Aβ16-21 (KLVFFA) and Tau306-311 (VQIVYK). We dissected their reversible and irreversible self-assembly dynamics, predicted their phase separation behaviors, and elucidated the underpinning molecular interactions. Our simulations showed that alternating stickers (Tyr) and spacers (Gly and Ser) in FUS37-42 and FUS54-59 facilitate the formation of highly dynamic coil-rich oligomers and lead to reversible self-assembly, while consecutive hydrophobic residues of LVFF in Aβ16-21 and IVY in Tau306-311 act as hydrophobic patches, favoring the formation of stable β-sheet-rich oligomers and driving the irreversible self-assembly. Intriguingly, we found that FUS37-42 and FUS54-59 peptides, possessing the same amino acid composition and the same number of sticker and spacer residues, display differential self-assembly propensities. This finding suggests that the self-assembly behaviors of FUS peptides are fine-tuned by the site-specific patterning of spacer residues (Ser and Gly). This study provides significant mechanistic insights into reversible and irreversible peptide self-assembly, which would be helpful for understanding the molecular mechanisms underlying the formation of biological liquid condensates and pathological solid amyloid fibrils.

Uncovering allostery and regulation in SORCIN through molecular dynamics simulations

Soluble resistance-related calcium-binding protein or Sorcin is an allosteric, calcium-binding Penta-EF hand (PEF) family protein implicated in multi-drug resistant cancers. Sorcin is known to bind chemotherapeutic molecules such as Doxorubicin. This study uses in-silico molecular dynamics simulations to explore the dynamics and allosteric behavior of Sorcin in the context of Ca2+ uptake and Doxorubicin binding. The results show that Ca2+ binding induces large, but reversible conformational changes in the Sorcin structure which manifest as rigid body reorientations that preserve the local secondary structure. A reciprocal allosteric handshake centered around the EF5 hand is found to be key in Sorcin dimer formation and stabilization. Binding of Doxorubicin results in rearrangement of allosteric communities which disrupts long-range allosteric information transfer from the N-terminal domain to the middle lobe. However, this binding does not result in secondary structure destabilization. Sorcin does not appear to have a distinct Ca2+ activated mode of Doxorubicin binding.Communicated by Ramaswamy H. Sarma.

Native dynamics and allosteric responses in PTP1B probed by high-resolution HDX-MS

Protein tyrosine phosphatase 1B (PTP1B) is a validated therapeutic target for obesity, diabetes, and certain types of cancer. In particular, allosteric inhibitors hold potential for therapeutic use, but an incomplete understanding of conformational dynamics and allostery in this protein has hindered their development. Here, we interrogate solution dynamics and allosteric responses in PTP1B using high-resolution hydrogen-deuterium exchange mass spectrometry (HDX-MS), an emerging and powerful biophysical technique. Using HDX-MS, we obtain a detailed map of the solution dynamics of apo PTP1B, revealing several flexible loops interspersed among more constrained and rigid regions within the protein structure, as well as local regions that exchange faster than expected from their secondary structure and buriedness. We demonstrate that our HDX rate data obtained in solution adds value to predictions of dynamics derived from a pseudo-ensemble constructed from ~200 crystal structures of PTP1B. Furthermore, we report HDX-MS maps for PTP1B with active-site vs. allosteric small-molecule inhibitors. These maps reveal distinct, dramatic, and widespread effects on protein dynamics relative to the apo form, including changes to dynamics in locations distal (>35 Å) from the respective ligand binding sites. These results help shed light on the allosteric nature of PTP1B and the surprisingly far-reaching consequences of inhibitor binding in this important protein. Overall, our work showcases the potential of HDX-MS for elucidating protein conformational dynamics and allosteric effects of small-molecule ligands, and highlights the potential of integrating HDX-MS alongside other complementary methods to guide the development of new therapeutics.

From random to rational: improving enzyme design through electric fields, second coordination sphere interactions, and conformational dynamics

Enzymes are versatile and efficient biological catalysts that drive numerous cellular processes, motivating the development of enzyme design approaches to tailor catalysts for diverse applications. In this perspective, we investigate the unique properties of natural, evolved, and designed enzymes, recognizing their strengths and shortcomings. We highlight the challenges and limitations of current enzyme design protocols, with a particular focus on their limited consideration of long-range electrostatic and dynamic effects. We then delve deeper into the impact of the protein environment on enzyme catalysis and explore the roles of preorganized electric fields, second coordination sphere interactions, and protein dynamics for enzyme function. Furthermore, we present several case studies illustrating successful enzyme-design efforts incorporating enzyme strategies mentioned above to achieve improved catalytic properties. Finally, we envision the future of enzyme design research, spotlighting the challenges yet to be overcome and the synergy of intrinsic electric fields, second coordination sphere interactions, and conformational dynamics to push the state-of-the-art boundaries.

Free-Energy Landscape and Rate Estimation of the Aromatic Ring Flips in Basic Pancreatic Trypsin Inhibitors Using Metadynamics

Aromatic side chains (phenylalanine and tyrosine) of a protein flip by 180° around the Cβ-Cγ axis (χ2 dihedral of the side chain), producing two symmetry-equivalent states. The study of ring flip dynamics with nuclear magnetic resonance (NMR) experiments helps to understand local conformational fluctuations. Ring flips are categorized as slow (milliseconds and onward) or fast (nanoseconds to near milliseconds) based on timescales accessible to NMR experiments. In this study, we investigated the ability of the infrequent metadynamics approach to estimate the flip rate and discriminate between slow and fast ring flips for eight individual aromatic side chains (F4, Y10, Y21, F22, Y23, F33, Y35, and F45) of the basic pancreatic trypsin inhibitor. Well-tempered metadynamics simulations were performed to estimate the ring-flipping free-energy surfaces for all eight aromatic residues. The results indicate that χ2 as a standalone collective variable (CV) is not sufficient to obtain computationally consistent results. Inclusion of a complementary CV, such as χ1(Cα-Cβ), solved the problem for most residues and enabled us to classify fast and slow ring flips. This indicates the importance of librational motions in ring flips. Multiple pathways and mechanisms were observed for residues F4, Y10, and F22. Recrossing events were observed for residues F22 and F33, indicating a possible role of friction effects in ring flipping. The results demonstrate the successful application of infrequent metadynamics to estimate ring flip rates and identify certain limitations of the approach.

Catalysis by KDM6 Histone Demethylases - A Synergy between the Non-Heme Iron(II) Center, Second Coordination Sphere, and Long-Range Interactions

KDM6A (UTX) and KDM6B (JMJD3) are human non-heme Fe(II) and 2-oxoglutarate (2OG) dependent JmjC oxygenases that catalyze the demethylation of trimethylated lysine 27 in the N-terminal tail of histone H3, a post-translational modification that regulates transcription. A Combined Quantum Mechanics/ Molecular Mechanics (QM/MM) and Molecular Dynamics (MD) study on the catalytic mechanism of KDM6A/B reveals that the transition state for the rate-limiting hydrogen atom transfer (HAT) reaction in KDM6A catalysis is stabilized by polar (Asn217) and aromatic (Trp369)/non-polar (Pro274) residues in contrast to KDM4, KDM6B and KDM7 demethylases where charged residues (Glu, Arg, Asp) are involved. KDM6A employs both σ- and π-electron transfer pathways for HAT, whereas KDM6B employs the σ-electron pathway. Differences in hydrogen bonding of the Fe-chelating Glu252(KDM6B) contribute to the lower energy barriers in KDM6B vs. KDM6A. The study reveals a dependence of the activation barrier of the rebound hydroxylation on the Fe-O-C angle in the transition state of KDM6A. Anti-correlation of the Zn-binding domain with the active site residues is a key factor distinguishing KDM6A/B from KDM7/4s. The results reveal the importance of communication between the Fe center, second coordination sphere, and long-range interactions in catalysis by KDMs and, by implication, other 2OG oxygenases.

Refinement of multiconformer ensemble models from multi-temperature X-ray diffraction data

Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363 K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.

Mapping N- to C-terminal allosteric coupling through disruption of a putative CD74 activation site in D-dopachrome tautomerase

The macrophage migration inhibitory factor (MIF) protein family consists of MIF and D-dopachrome tautomerase (also known as MIF-2). These homologs share 34% sequence identity while maintaining nearly indistinguishable tertiary and quaternary structure, which is likely a major contributor to their overlapping functions, including the binding and activation of the cluster of differentiation 74 (CD74) receptor to mediate inflammation. Previously, we investigated a novel allosteric site, Tyr99, that modulated N-terminal catalytic activity in MIF through a "pathway" of dynamically coupled residues. In a comparative study, we revealed an analogous allosteric pathway in MIF-2 despite its unique primary sequence. Disruptions of the MIF and MIF-2 N termini also diminished CD74 activation at the C terminus, though the receptor activation site is not fully defined in MIF-2. In this study, we use site-directed mutagenesis, NMR spectroscopy, molecular simulations, in vitro and in vivo biochemistry to explore the putative CD74 activation region of MIF-2 based on homology to MIF. We also confirm its reciprocal structural coupling to the MIF-2 allosteric site and N-terminal enzymatic site. Thus, we provide further insight into the CD74 activation site of MIF-2 and its allosteric coupling for immunoregulation.

Selecting Features for Markov Modeling: A Case Study on HP35

Markov state models represent a popular means to interpret molecular dynamics trajectories in terms of memoryless transitions between metastable conformational states. To provide a mechanistic understanding of the considered biomolecular process, these states should reflect structurally distinct conformations and ensure a time scale separation between fast intrastate and slow interstate dynamics. Adopting the folding of villin headpiece (HP35) as a well-established model problem, here we discuss the selection of suitable input coordinates or "features", such as backbone dihedral angles and interresidue distances. We show that dihedral angles account accurately for the structure of the native energy basin of HP35, while the unfolded region of the free energy landscape and the folding process are best described by tertiary contacts of the protein. To construct a contact-based model, we consider various ways to define and select contact distances and introduce a low-pass filtering of the feature trajectory as well as a correlation-based characterization of states. Relying on input data that faithfully account for the mechanistic origin of the studied process, the states of the resulting Markov model are clearly discriminated by the features, describe consistently the hierarchical structure of the free energy landscape, and─as a consequence─correctly reproduce the slow time scales of the process.

Refinement of Multiconformer Ensemble Models from Multi-temperature X-ray Diffraction Data

Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.

Ligand-induced conformational changes enable intersubunit communications in D-dopachrome tautomerase

D-Dopachrome tautomerase (D-DT; or MIF-2) is a multifunctional protein with immunomodulatory properties and a documented pathogenic role in inflammation and cancer that is associated with activation of the cell surface receptor CD74. Alongside D-DT, macrophage migration inhibitory factor (MIF) is also known to activate CD74, promoting pathogenesis. While the role of the MIF/CD74 axis has been extensively studied in various disease models, the late discovery of the D-DT/CD74 axis has led to a poor investigation into the D-DT-induced activation mechanism of CD74. A previous study has identified 4-(3-carboxyphenyl)-2,5-pyridinedicarboxylic acid (4-CPPC) as the first selective and reversible inhibitor of D-DT and reported its potency to block the D-DT-induced activation of CD74 in a cell-based model. In this study, we employ molecular dynamics simulations and nuclear magnetic resonance experiments to study 4-CPPC-induced changes to the dynamic profile of D-DT. We found that binding of the inhibitor remarkably promotes the conformational flexibility of C-terminal without impacting the structural stability of the biological assembly. Consequently, long-range intrasubunit (>11 Å) and intersubunit (>30 Å) communications are enabled between distal regions. Communication across the three subunits is accomplished via 4-CPPC, which serves as a communication bridge after Val113 is displaced from its hydrophobic pocket. This previously unrecognized structural property of D-DT is not shared with its human homolog, MIF, which exhibits an impressive C-terminal rigidity even in the presence of an inhibitor. Considering the previously reported role of MIF's C-terminal in the activation of CD74, our results break new ground for understanding the functionality of D-DT in health and disease.

N-terminal β-strand in YAP is critical for stronger binding to scalloped relative to TEAD transcription factor

The yes-associated protein (YAP) regulates the transcriptional activity of the TEAD transcription factors that are key in the control of organ morphogenesis. YAP interacts with TEAD via three secondary structure elements: a β-strand, an α-helix, and an Ω-loop. Earlier results have shown that the β-strand has only a marginal contribution in the YAP:TEAD interaction, but we show here that it significantly enhances the affinity of YAP for the Drosophila homolog of TEAD, scalloped (Sd). Nuclear magnetic resonance shows that the β-strand adopts a more rigid conformation once bound to Sd; pre-steady state kinetic measurements show that the YAP:Sd complex is more stable. Although the crystal structures of the YAP:TEAD and YAP:Sd complexes reveal no differences at the binding interface that could explain these results. Molecular Dynamics simulations are in line with our experimental findings regarding β-strand stability and overall binding affinity of YAP to TEAD and Sd. In particular, RMSF, correlated motion and MMGBSA analyses suggest that β-sheet fluctuations play a relevant role in YAP53-57 β-strand dissociation from TEAD4 and contribute to the lower affinity of YAP for TEAD4. Identifying a clear mechanism leading to the difference in YAP's β-strand stability proved to be challenging, pointing to the potential relevance of multiple modest structural changes or fluctuations for regulation of binding affinity.

Explicit versus implicit consideration of binding partners in protein-protein complex to elucidate intrinsic dynamics

The binding of many proteins to their protein partners is tightly regulated via control of their relative intrinsic dynamics during the binding process, a phenomenon which can in turn be modulated. Therefore, investigating the intrinsic dynamics of proteins is necessary to understand function in a comprehensive way. By intrinsic dynamics herein, we principally refer to the vibrational signature of a protein molecule popularly obtained from normal modes or essential modes. For normal modes, one often considers that the molecule under investigation is a collection of springs in a solvent-free or implicit-solvent medium. In the context of a protein-binding partner, the analysis of vibration of the target protein is often complicated due to molecular interaction within the complex. Generally, it is assumed that the isolated bound conformation of the target protein captures the implicit effect of the binding partner on the intrinsic dynamics, therefore suggesting that any influence of the partner molecule is also already integrated. Such an assumption allows large-scale studies of the conservation of protein flexibility. However, in cases where a partner protein directly influences the vibration of the target via critical contacts at the protein-protein interface, the above assumption falls short of providing a detailed view. In this review article, we discuss the implications of considering the dynamics of a protein in a protein-protein complex, as modelled implicitly and explicitly with methods dependent on elastic network models. We further propose how such an explicit consideration can be applied to understand critical protein-protein contacts that can be targeted in future studies.

Detecting the Hydrogen Bond Cooperativity in a Protein β-Sheet by H/D Exchange

The hydrogen bond (H-bond) cooperativity in the β-sheet of GB3 is investigated by a NMR hydrogen/deuterium (H/D) exchange method. It is shown that the weakening of one backbone N-H…O=C H-bond between two β-strands, β1 and β2, due to the exchange of NH to ND of the H-bond donor in β1, perturbs the chemical shift of ¹³C_α, ¹³C_β, ¹H_α, ¹H_N, and ¹⁵N of the H-bond acceptor and its following residue in β2. Quantum mechanical calculations suggest that the -H-bond chemical shift isotope effect is caused by the structural reorganization in response to the H-bond weakening. This structural reorganization perturbs four neighboring H-bonds, with three being weaker and one being stronger, indicating that three H-bonds are cooperative and one is anticooperative with the perturbed H-bond. The sign of the cooperativity depends on the relative position of the H-bonds. This H-bond cooperativity, which contributes to β-sheet stability overall, can be important for conformational coupling across the β-sheet.

Atomic resolution protein allostery from the multi-state structure of a PDZ domain

Recent methodological advances in solution NMR allow the determination of multi-state protein structures and provide insights into structurally and dynamically correlated protein sites at atomic resolution. This is demonstrated in the present work for the well-studied PDZ2 domain of protein human tyrosine phosphatase 1E for which protein allostery had been predicted. Two-state protein structures were calculated for both the free form and in complex with the RA-GEF2 peptide using the exact nuclear Overhauser effect (eNOE) method. In the apo protein, an allosteric conformational selection step comprising almost 60% of the domain was detected with an "open" ligand welcoming state and a "closed" state that obstructs the binding site by changing the distance between the β-sheet 2, α-helix 2, and sidechains of residues Lys38 and Lys72. The observed induced fit-type apo-holo structural rearrangements are in line with the previously published evolution-based analysis covering ~25% of the domain with only a partial overlap with the protein allostery of the open form. These presented structural studies highlight the presence of a dedicated highly optimized and complex dynamic interplay of the PDZ2 domain owed by the structure-dynamics landscape.

Correlation-Based Feature Selection to Identify Functional Dynamics in Proteins

To interpret molecular dynamics simulations of biomolecular systems, systematic dimensionality reduction methods are commonly employed. Among others, this includes principal component analysis (PCA) and time-lagged independent component analysis (TICA), which aim to maximize the variance and the time scale of the first components, respectively. A crucial first step of such an analysis is the identification of suitable and relevant input coordinates (the so-called features), such as backbone dihedral angles and interresidue distances. As typically only a small subset of those coordinates is involved in a specific biomolecular process, it is important to discard the remaining uncorrelated motions or weakly correlated noise coordinates. This is because they may exhibit large amplitudes or long time scales and therefore will be erroneously considered important by PCA and TICA, respectively. To discriminate collective motions underlying functional dynamics from uncorrelated motions, the correlation matrix of the input coordinates is block-diagonalized by a clustering method. This strategy avoids possible bias due to presumed functional observables and conformational states or variation principles that maximize variance or time scales. Considering several linear and nonlinear correlation measures and various clustering algorithms, it is shown that the combination of linear correlation and the Leiden community detection algorithm yields excellent results for all considered model systems. These include the functional motion of T4 lysozyme to demonstrate the successful identification of collective motion, as well as the folding of the villin headpiece to highlight the physical interpretation of the correlated motions in terms of a functional mechanism.

Conformational spread drives the evolution of the calcium-calmodulin protein kinase II

The calcium calmodulin (Ca²⁺/CaM) dependent protein kinase II (CaMKII) decodes Ca²⁺ frequency oscillations. The CaMKIIα isoform is predominantly expressed in the brain and has a central role in learning. I matched residue and organismal evolution with collective motions deduced from the atomic structure of the human CaMKIIα holoenzyme to learn how its ring architecture abets function. Protein dynamic simulations showed its peripheral kinase domains (KDs) are conformationally coupled via lateral spread along the central hub. The underlying β-sheet motions in the hub or association domain (AD) were deconvolved into dynamic couplings based on mutual information. They mapped onto a coevolved residue network to partition the AD into two distinct sectors. A second, energetically stressed sector was added to ancient bacterial enzyme dimers for assembly of the ringed hub. The continued evolution of the holoenzyme after AD–KD fusion targeted the sector’s ring contacts coupled to the KD. Among isoforms, the α isoform emerged last and, it alone, mutated rapidly after the poikilotherm–homeotherm jump to match the evolution of memory. The correlation between dynamics and evolution of the CaMKII AD argues single residue substitutions fine-tune hub conformational spread. The fine-tuning could increase CaMKIIα Ca²⁺ frequency response range for complex learning functions.

Towards the Idea of Molecular Brains

How can single cells without nervous systems perform complex behaviours such as habituation, associative learning and decision making, which are considered the hallmark of animals with a brain? Are there molecular systems that underlie cognitive properties equivalent to those of the brain? This review follows the development of the idea of molecular brains from Darwin’s “root brain hypothesis”, through bacterial chemotaxis, to the recent discovery of neuron-like r-protein networks in the ribosome. By combining a structural biology view with a Bayesian brain approach, this review explores the evolutionary labyrinth of information processing systems across scales. Ribosomal protein networks open a window into what were probably the earliest signalling systems to emerge before the radiation of the three kingdoms. While ribosomal networks are characterised by long-lasting interactions between their protein nodes, cell signalling networks are essentially based on transient interactions. As a corollary, while signals propagated in persistent networks may be ephemeral, networks whose interactions are transient constrain signals diffusing into the cytoplasm to be durable in time, such as post-translational modifications of proteins or second messenger synthesis. The duration and nature of the signals, in turn, implies different mechanisms for the integration of multiple signals and decision making. Evolution then reinvented networks with persistent interactions with the development of nervous systems in metazoans. Ribosomal protein networks and simple nervous systems display architectural and functional analogies whose comparison could suggest scale invariance in information processing. At the molecular level, the significant complexification of eukaryotic ribosomal protein networks is associated with a burst in the acquisition of new conserved aromatic amino acids. Knowing that aromatic residues play a critical role in allosteric receptors and channels, this observation suggests a general role of π systems and their interactions with charged amino acids in multiple signal integration and information processing. We think that these findings may provide the molecular basis for designing future computers with organic processors.

Probing allosteric regulations with coevolution-driven molecular simulations

Protein-mediated allosteric regulations are essential in biology, but their quantitative characterization continues to posit formidable challenges for both experiments and computations. Here, we combine coevolutionary information, multiscale molecular simulations, and free-energy methods to interrogate and quantify the allosteric regulation of functional changes in protein complexes. We apply this approach to investigate the regulation of adenylyl cyclase (AC) by stimulatory and inhibitory G proteins—a prototypical allosteric system that has long escaped from in-depth molecular characterization. We reveal a surprisingly simple ON/OFF regulation of AC functional dynamics through multiple pathways of information transfer. The binding of G proteins reshapes the free-energy landscape of AC following the classical population-shift paradigm. The model agrees with structural and biochemical data and reveals previously unknown experimentally consistent intermediates. Our approach showcases a general strategy to explore uncharted functional space in complex biomolecular regulations.

Weakening of interaction networks with aging in tip-link protein induces hearing loss

Age-related hearing loss (ARHL) is a common condition in humans marking the gradual decrease in hearing with age. Perturbations in the tip-link protein cadherin-23 that absorbs the mechanical tension from sound and maintains the integrity of hearing is associated with ARHL. Here, in search of molecular origins for ARHL, we dissect the conformational behavior of cadherin-23 along with the mutant S47P that progresses the hearing loss drastically. Using an array of experimental and computational approaches, we highlight a lower thermodynamic stability, significant weakening in the hydrogen-bond network and inter-residue correlations among β-strands, due to the S47P mutation. The loss in correlated motions translates to not only a remarkable two orders of magnitude slower folding in the mutant but also to a proportionately complex unfolding mechanism. We thus propose that loss in correlated motions within cadherin-23 with aging may trigger ARHL, a molecular feature that likely holds true for other disease-mutations in β-strand-rich proteins.

Protein Allostery at Atomic Resolution

Protein allostery is a phenomenon involving the long range coupling between two distal sites in a protein. In order to elucidate allostery at atomic resoluion on the ligand-binding WW domain of the enzyme Pin1, multistate structures were calculated from exact nuclear Overhauser effect (eNOE). In its free form, the protein undergoes a microsecond exchange between two states, one of which is predisposed to interact with its parent catalytic domain. In presence of the positive allosteric ligand, the equilibrium between the two states is shifted towards domain-domain interaction, suggesting a population shift model. In contrast, the allostery-suppressing ligand decouples the side-chain arrangement at the inter-domain interface thereby reducing the inter-domain interaction. As such, this mechanism is an example of dynamic allostery. The presented distinct modes of action highlight the power of the interplay between dynamics and function in the biological activity of proteins.

Allosteric Priming of E. coli CheY by the Flagellar Motor Protein FliM

Phosphorylation of Escherichia coli CheY protein transduces chemoreceptor stimulation to a highly cooperative flagellar motor response. CheY binds to the N-terminal peptide of the FliM motor protein (FliM_N). Constitutively active D13K-Y106W CheY has been an important tool for motor physiology. The crystal structures of CheY and CheY ⋅ FliM_N with and without D13K-Y106W have shown FliM_N-bound CheY contains features of both active and inactive states. We used molecular dynamics (MD) simulations to characterize the CheY conformational landscape accessed by FliM_N and D13K-Y106W. Mutual information measures identified the central features of the long-range CheY allosteric network between D57 phosphorylation site and the FliM_N interface, namely the closure of the α4-β4 hinge and inward rotation of Y- or W106 with W58. We used hydroxy-radical foot printing with mass spectroscopy (XFMS) to track the solvent accessibility of these and other side chains. The solution XFMS oxidation rate correlated with the solvent-accessible area of the crystal structures. The protection of allosteric relay side chains reported by XFMS confirmed the intermediate conformation of the native CheY ⋅ FliM_N complex, the inactive state of free D13K-Y106W CheY, and the MD-based network architecture. We extended the MD analysis to determine temporal coupling and energetics during activation. Coupled aromatic residue rotation was a graded rather than a binary switch, with Y- or W106 side-chain burial correlated with increased FliM_N affinity. Activation entrained CheY fold stabilization to FliM_N affinity. The CheY network could be partitioned into four dynamically coordinated sectors. Residue substitutions mapped to sectors around D57 or the FliM_N interface according to phenotype. FliM_N increased sector size and interactions. These sectors fused between the substituted K13-W106 residues to organize a tightly packed core and novel surfaces that may bind additional sites to explain the cooperative motor response. The community maps provide a more complete description of CheY priming than proposed thus far.

Regulation of MIF Enzymatic Activity by an Allosteric Site at the Central Solvent Channel

In proteins with multiple functions, such as macrophage migration inhibitory factor (MIF), the study of its intramolecular dynamic network can offer a unique opportunity to understand how a single protein is able to carry out several nonoverlapping functions. A dynamic mechanism that controls the MIF-induced activation of CD74 was recently discovered. In this study, the regulation of tautomerase activity was explored. The catalytic base Pro1 is found to form dynamic communications with the same allosteric node that regulates CD74 activation. Signal transmission between the allosteric and catalytic sites take place through intramolecular aromatic interactions and a hydrogen bond network that involves residues and water molecules of the MIF solvent channel. Once thought to be a consequence of trimerization, a regulatory function for the solvent channel is now defined. These results provide mechanistic insights into the regulation of catalytic activity and the role of solvent channel water molecules in MIF catalysis.

Dynamics-function relationship in the catalytic domains of N-terminal acetyltransferases

N-terminal acetyltransferases (NATs) belong to the superfamily of acetyltransferases. They are enzymes catalysing the transfer of an acetyl group from acetyl coenzyme A to the N-terminus of polypeptide chains. N-terminal acetylation is one of the most common protein modifications. To date, not much is known on the molecular basis for the exclusive substrate specificity of NATs. All NATs share a common fold called GNAT. A characteristic of NATs is the β6β7 hairpin loop covering the active site and forming with the α1α2 loop a narrow tunnel surrounding the catalytic site in which cofactor and polypeptide meet and exchange an acetyl group. We investigated the dynamics-function relationships of all available structures of NATs covering the three domains of Life. Using an elastic network model and normal mode analysis, we found a common dynamics pattern conserved through the GNAT fold; a rigid V-shaped groove formed by the β4 and β5 strands and splitting the fold in two dynamical subdomains. Loops α1α2, β3β4 and β6β7 all show clear displacements in the low frequency normal modes. We characterized the mobility of the loops and show that even limited conformational changes of the loops along the low-frequency modes are able to significantly change the size and shape of the ligand binding sites. Based on the fact that these movements are present in most low-frequency modes, and common to all NATs, we suggest that the α1α2 and β6β7 loops may regulate ligand uptake and the release of the acetylated polypeptide.

Structural analyses of the Group A flavin-dependent monooxygenase PieE reveal a sliding FAD cofactor conformation bridging OUT and IN conformations

Group A flavin-dependent monooxygenases catalyze the cleavage of the oxygen-oxygen bond of dioxygen, followed by the incorporation of one oxygen atom into the substrate molecule with the aid of NADPH and FAD. These flavoenzymes play an important role in many biological processes, and their most distinct structural feature is the choreographed motions of flavin, which typically adopts two distinct conformations (OUT and IN) to fulfill its function. Notably, these enzymes seem to have evolved a delicate control system to avoid the futile cycle of NADPH oxidation and FAD reduction in the absence of substrate, but the molecular basis of this system remains elusive. Using protein crystallography, size-exclusion chromatography coupled to multi-angle light scattering (SEC-MALS), and small-angle X-ray scattering (SEC-SAXS) and activity assay, we report here a structural and biochemical characterization of PieE, a member of the Group A flavin-dependent monooxygenases involved in the biosynthesis of the antibiotic piericidin A1. This analysis revealed that PieE forms a unique hexamer. Moreover, we found, to the best of our knowledge for the first time, that in addition to the classical OUT and IN conformations, FAD possesses a "sliding" conformation that exists in between the OUT and IN conformations. This observation sheds light on the underlying mechanism of how the signal of substrate binding is transmitted to the FAD-binding site to efficiently initiate NADPH binding and FAD reduction. Our findings bridge a gap currently missing in the orchestrated order of chemical events catalyzed by this important class of enzymes.

Intraresidual Correlated Motions in Peptide Chains

We investigate the interresidual and intraresidual correlations between dihedral displacements of adjacent residues within model polyalanine peptides by analyzing extensive molecular dynamics trajectories. Correlations are evaluated individually at different residue conformations covering the whole (ϕ_i,ψ_i)-space. From these, we draw maps that unveil an unprecedented strong intramolecular correlation displaying opposite (correlated/anticorrelated) behaviors at different conformations. Both interresidual and intraresidual correlations arise from the propensity of the peptide to minimize the overall atomic displacements.

Large-Scale Conformational Changes and Protein Function: Breaking the in silico Barrier

Large-scale conformational changes are essential to link protein structures with their function at the cell and organism scale, but have been elusive both experimentally and computationally. Over the past few years developments in cryo-electron microscopy and crystallography techniques have started to reveal multiple snapshots of increasingly large and flexible systems, deemed impossible only short time ago. As structural information accumulates, theoretical methods become central to understand how different conformers interconvert to mediate biological function. Here we briefly survey current in silico methods to tackle large conformational changes, reviewing recent examples of cross-validation of experiments and computational predictions, which show how the integration of different scale simulations with biological information is already starting to break the barriers between the in silico, in vitro, and in vivo worlds, shedding new light onto complex biological problems inaccessible so far.

Analysis of mutations leading to para-aminosalicylic acid resistance in Mycobacterium tuberculosis

Thymidylate synthase A (ThyA) is the key enzyme involved in the folate pathway in Mycobacterium tuberculosis. Mutation of key residues of ThyA enzyme which are involved in interaction with substrate 2′-deoxyuridine-5′-monophosphate (dUMP), cofactor 5,10-methylenetetrahydrofolate (MTHF), and catalytic site have caused para-aminosalicylic acid (PAS) resistance in TB patients. Focusing on R127L, L143P, C146R, L172P, A182P, and V261G mutations, including wild-type, we performed long molecular dynamics (MD) simulations in explicit solvent to investigate the molecular principles underlying PAS resistance due to missense mutations. We found that these mutations lead to (i) extensive changes in the dUMP and MTHF binding sites, (ii) weak interaction of ThyA enzyme with dUMP and MTHF by inducing conformational changes in the structure, (iii) loss of the hydrogen bond and other atomic interactions and (iv) enhanced movement of protein atoms indicated by principal component analysis (PCA). In this study, MD simulations framework has provided considerable insight into mutation induced conformational changes in the ThyA enzyme of Mycobacterium.

Inter-Active Site Communication Mediated by the Dimer Interface β-Sheet in the Half-the-Sites Enzyme, Thymidylate Synthase

Thymidylate synthase (TS) is a dimeric enzyme conserved in all life forms that exhibits the allosteric feature of half-the-sites activity. Neither the reason for nor the mechanism of this phenomenon is understood. We used a combined nuclear magnetic resonance (NMR) and molecular dynamics approach to study a stable intermediate preceding hydride transfer, which is the rate-limiting and half-the-sites step. In NMR titrations with ligands leading to this intermediate, we measured chemical shifts of the apoenzyme (lig₀), the saturated holoenzyme (lig₂), and the typically elusive singly bound (lig₁) states. Approximately 40 amides showed quartet patterns providing direct NMR evidence of coupling between the active site and probes >30 Å away in the distal subunit. Quartet peak patterns have symmetrical character, indicating reciprocity in communicating the first and second binding events to the distal protomer. Quartets include key catalytic residues and map to the dimer interface β-sheet, which also represents the shortest path between the two active sites. Simulations corroborate the coupling observed in solution in that there is excellent overlap between quartet residues and main-chain atoms having intersubunit cross-correlated motions. Simulations identify five hot spot residues, three of which lie at the kink in the unique β-bulge abutting the active sites on either end of the sheet. Interstrand cross-correlated motions become more organized and pronounced as the enzyme progresses from lig₀ to lig₁ and ultimately lig₂. Coupling in the apparently symmetrical complex has implications for half-the-sites reactivity and potentially resolves the paradox of inequivalent TS active sites despite the vast majority of X-ray structures appearing to be symmetrical.

Na+-binding modes involved in thrombin's allosteric response as revealed by molecular dynamics simulations, correlation networks and Markov modeling

The monovalent sodium ion (Na+) is a critical modulator of thrombin. However, the mechanism of thrombin's activation by Na+ has been widely debated for more than twenty years. Details of the linkage between thrombin and Na+ remain vague due to limited temporal and spatial resolution in experiments. In this work, we combine microsecond scale atomic-detailed molecular dynamics simulations with correlation network analyses and hidden Markov modeling to probe the detailed thermodynamic and kinetic picture of Na+-binding events and their resulting allosteric responses in thrombin. We reveal that ASP189 and ALA190 comprise a stable Na+-binding site (referred as "inner" Na+-binding site) along with the previously known one (referred as "outer" Na+-binding site). The corresponding newly identified Na+-binding mode introduces significant allosteric responses in thrombin's regulatory regions by stabilizing selected torsion angles of residues responsive to Na+-binding. Our Markov model indicates that the bound Na+ prefers to transfer between the two Na+-binding sites when an unbinding event takes place. These results suggest a testable hypothesis of a substrate-driven Na+ migration (ΔG ∼ 1.7 kcal mol-1) from the "inner" Na+-binding site to the "outer" one during thrombin's catalytic activities. The binding of a Na+ ion at the "inner" Na+-binding site should be inferred as a prerequisite for thrombin's efficient recognition to the substrate, which opens a new angle for our understanding of Na+-binding's allosteric activation on thrombin and sheds light on detailed processes in thrombin's activation.

Journey to the center of the protein: allostery from multitemperature multiconformer X-ray crystallography

Proteins inherently fluctuate between conformations to perform functions in the cell. For example, they sample product-binding, transition-state-stabilizing and product-release states during catalysis, and they integrate signals from remote regions of the structure for allosteric regulation. However, there is a lack of understanding of how these dynamic processes occur at the basic atomic level. This gap can be at least partially addressed by combining variable-temperature (instead of traditional cryogenic temperature) X-ray crystallography with algorithms for modeling alternative conformations based on electron-density maps, in an approach called multitemperature multiconformer X-ray crystallography (MMX). Here, the use of MMX to reveal alternative conformations at different sites in a protein structure and to estimate the degree of energetic coupling between them is discussed. These insights can suggest testable hypotheses about allosteric mechanisms. Temperature is an easily manipulated experimental parameter, so the MMX approach is widely applicable to any protein that yields well diffracting crystals. Moreover, the general principles of MMX are extensible to other perturbations such as pH, pressure, ligand concentration etc. Future work will explore strategies for leveraging X-ray data across such perturbation series to more quantitatively measure how different parts of a protein structure are coupled to each other, and the consequences thereof for allostery and other aspects of protein function.

Developing Biopolymer Mesocrystals by Crystallization of Secondary Structures

Particle-based mesocrystals have been known for over 10 years; however, examples of biopolymer mesocrystals are rather scarce. The synthesis of particle precursors of biopolymers, the identification of particle-mediated crystallization processes, and thus the synthesis of mesocrystals of biopolymers are challenging. Here, we summarize the existing examples of biopolymer crystallization based on self-assembly of the secondary structures, which could induce the formation of biopolymer mesocrystals. As basic building units, simple secondary structures such as β-sheets or α-helixes could provide a useful tool for the design of biopolymer mesocrystals.

Fluctuation correlations as major determinants of structure- and dynamics-driven allosteric effects

Both structure- and dynamics-driven allosteric effects are determined by the correlation of distance fluctuations in proteins.

Significance of triple torsional correlations in proteins

The free energy landscape (FEL) of a given complex molecular system is fundamentally the joint probability density of its many comprising degrees of freedom (DOFs). Computation of a complete FEL at atomistic scale is unfortunately intractable for a typical biomolecular system. The challenge of entropy calculation comes from various correlations among different DOFs. The common strategy to treat such complexity is expansion of the full correlation into various orders of local correlations. In reality, expansion is usually cut off at the second order (i.e. pairwise interactions) for protein torsional correlations without reliable estimation of the resulting error. Here, we estimated the mutual information of different torsion sets and found that triple correlations were significant for both local/distant residue pairs and consecutive backbone torsional segments. As expected, the third order approximations were found to be consistently better than the second order approximations. These findings were true for all analyzed proteins with different folds, were independent of the two different force fields utilized to generate trajectory sets, and were therefore likely to be of general importance for proteins. Additionally, binning strategies are of universal importance for numerical computation of correlations, we here provided a detailed comparison between equal-width and equal-sample binning for different bin numbers and demonstrated the impact of binning strategies on variances and biases of calculated mutual information. Our observation suggested that caution should be taken when quantitative comparison of correlations were intended between different studies with different binning strategies.

Torsional mutual information for 10 typical residue pairs calculated with full joint distributions (MI), second order expansion (MI₂), third order expansions (MI₃), and their linear recombinations (MI_LR).

Propagated Perturbations from a Peripheral Mutation Show Interactions Supporting WW Domain Thermostability

Inter-residue interactions stabilize protein folds and facilitate allosteric communication. Predicting which interactions are crucial and understanding why remain challenging. We highlight this through studies of a single peripheral mutation (Q33E) on the surface of the Pin1 WW domain that causes an unexpected loss of thermostability. Nuclear magnetic resonance studies attribute the loss to reorganizations of electrostatic and hydrophobic interactions, resulting in propagated conformational perturbations. The propagation demonstrates the cooperative response of Pin1 WW to external perturbations, consistent with its allosteric behavior within Pin1. Microsecond molecular dynamics simulations suggest the wild-type fold relies on couplings between a surface electrostatic network and a highly conserved hydrophobic core; Q33E directly perturbs the former, thereby disrupting the latter. These couplings suggest that predictions of mutation consequences that assume dominance of a single interaction type can be limiting, and highlight challenges in predicting protein mutational landscapes.

Nanosecond Dynamics Regulate the MIF-Induced Activity of CD74

Macrophage migration inhibitory factor (MIF) activates CD74, which leads to severe disorders including inflammation, autoimmune diseases and cancer under pathological conditions. Molecular dynamics (MD) simulations up to one microsecond revealed dynamical correlation between a residue located at the opening of one end of the MIF solvent channel, previously thought to be a consequence of homotrimerization, and residues in a distal region responsible for CD74 activation. Experiments verified the allosteric regulatory site and identified a pathway to this site via the MIF β-strands. The reported findings provide fundamental insights on a dynamic mechanism that controls the MIF-induced activation of CD74.

Visualizing correlated motion with HDBSCAN clustering

Correlated motion analysis provides a method for understanding communication between and dynamic similarities of biopolymer residues and domains. The typical equal-time correlation matrices-frequently visualized with pseudo-colorings or heat maps-quickly convey large regions of highly correlated motion but hide more subtle similarities of motion. Here we propose a complementary method for visualizing correlations within proteins (or general biopolymers) that quickly conveys intuition about which residues have a similar dynamic behavior. For grouping residues, we use the recently developed non-parametric clustering algorithm HDBSCAN. Although the method we propose here can be used to group residues using correlation as a similarity matrix-the most straightforward and intuitive method-it can also be used to more generally determine groups of residues which have similar dynamic properties. We term these latter groups "Dynamic Domains", as they are based not on spatial closeness but rather closeness in the column space of a correlation matrix. We provide examples of this method across three human proteins of varying size and function-the Nf-Kappa-Beta essential modulator, the clotting promoter Thrombin and the mismatch repair protein (dimer) complex MutS-alpha. Although the examples presented here are from all-atom molecular dynamics simulations, this visualization technique can also be used on correlations matrices built from any ensembles of conformations from experiment or computation.