Normal mode analysis of biomolecular structures: functional mechanisms of membrane proteins

Preproteins couple the intrinsic dynamics of SecA to its ATPase cycle to translocate via a catch and release mechanism

Protein machines undergo conformational motions to interact with and manipulate polymeric substrates. The Sec translocase promiscuously recognizes, becomes activated, and secretes >500 non-folded preprotein clients across bacterial cytoplasmic membranes. Here, we reveal that the intrinsic dynamics of the translocase ATPase, SecA, and of preproteins combine to achieve translocation. SecA possesses an intrinsically dynamic preprotein clamp attached to an equally dynamic ATPase motor. Alternating motor conformations are finely controlled by the γ-phosphate of ATP, while ADP causes motor stalling, independently of clamp motions. Functional preproteins physically bridge these independent dynamics. Their signal peptides promote clamp closing; their mature domain overcomes the rate-limiting ADP release. While repeated ATP cycles shift the motor between unique states, multiple conformationally frustrated prongs in the clamp repeatedly "catch and release" trapped preprotein segments until translocation completion. This universal mechanism allows any preprotein to promiscuously recognize the translocase, usurp its intrinsic dynamics, and become secreted.

The Inherent Coupling of Intrinsically Disordered Regions in the Multidomain Receptor Tyrosine Kinase KIT

RTK KIT regulates a variety of crucial cellular processes via its cytoplasmic domain (CD), which is composed of the tyrosine kinase domain, crowned by the highly flexible domains—the juxtamembrane region, kinase insertion domain, and C-tail, which are key recruitment regions for downstream signalling proteins. To prepare a structural basis for the characterization of the interactions of KIT with its signalling proteins (KIT INTERACTOME), we generated the 3D model of the full-length CD attached to the transmembrane helix. This generic model of KIT in inactive state was studied by molecular dynamics simulation under conditions mimicking the natural environment of KIT. With the accurate atomistic description of the multidomain KIT dynamics, we explained its intrinsic (intra-domain) and extrinsic (inter-domain) disorder and represented the conformational assemble of KIT through free energy landscapes. Strongly coupled movements within each domain and between distant domains of KIT prove the functional interdependence of these regions, described as allosteric regulation, a phenomenon widely observed in many proteins. We suggested that KIT, in its inactive state, encodes all properties of the active protein and its post-transduction events.

In silico studies of interactions of peptide-conjugated cholesterol metabolites and betulinic acid with EGFR, LDR, and N-terminal fragment of CCKA receptors

In this work, we designed three new ligands by conjugating cholesterol metabolites 3-hydroxy-5-cholestenoic acid (3-HC) and 3-oxo-4-cholestenoic acid (3-OC) and the natural tri-terpenoid betulinic acid with the tumor-targeting peptide YHWYGYTPQNVI. Molecular interactions with the unconjugated peptide and the conjugates were examined with three receptors that are commonly overexpressed in pancreatic adenocarcinoma cells using ligand docking and molecular dynamics. This study demonstrated the utility of the designed conjugates as a valuable scaffold for potentially targeting EGFR and LDLR receptors. Our results indicate that the conjugates showed strong binding affinities and formation of stable complexes with EGFR, while the unconjugated peptide, BT-peptide conjugate, an 3-HC-peptide conjugate showed the formation of fairly stable complexes with LDLR receptor. For EGFR, two receptor kinase domains were explored. Interactions with the N-terminal domain of CCKA-R were relatively weaker. For LDLR, binding occurred in the beta-propeller region. For the N-terminal fragment of CCKA-R, the conjugates induced significant conformational changes in the receptor. The molecular dynamic simulations for 100 ns demonstrate that BT-peptide conjugates and the unconjugated peptide had the highest binding and formed the most stable complexes with EGFR. RMSD and trajectory analyses indicate that these molecules transit to a dynamically stable configuration in most cases within 60 ns. NMA analysis indicated that amongst the conjugates that showed relatively higher interactions with the respective receptors, the highest potential for deformability was seen for the N-terminal-47 amino acid region of the CCKA-R receptor with and the lowest for the LDLR-receptor. Thus, the newly designed compounds may be evaluated in the future toward developing drug delivery materials for targeting tumor cells overexpressing LDLR or EGFR.

Specific osteogenesis imperfecta-related Gly substitutions in type I collagen induce distinct structural, mechanical, and dynamic characteristics

The stiffnesses, β-structures, hydrogen bonds, and vibrational modes of wild-type collagen triple helices are compared with osteogenesis imperfecta-related mutants using integrative structural and dynamic analysis via molecular dynamics simulations and Markov state models. Differences in these characteristics are strongly related to the unwound structural states in the mutated regions that are specific to each mutation.

Mechanical couplings of protein backbone and side chains exhibit scale-free network properties and specific hotspots for function

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Statistical learning from protein dynamics unravels rigidities in interaction network.

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Backbone and side-chain mechanical couplings exhibit scale-free network properties.

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Graphical depiction of network rigidities captures sequence co-evolution patterns.

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Functional sites at secondary structure peripheries are mechanical hotspots.

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Our rigidity scores are compelling metrics for residue biological significance.

A backbone-side-chain elastic network model (bsENM) is devised in this contribution to decipher the network of molecular interactions during protein dynamics. The chemical details in 5 μs all-atom molecular dynamics (MD) simulation are mapped onto the bsENM spring constants by self-consistent iterations. The elastic parameters obtained by this structure-mechanics statistical learning are then used to construct inter-residue rigidity graphs for the chemical components in protein amino acids. A key discovery is that the mechanical coupling strengths of both backbone and side chains exhibit heavy-tailed distributions and scale-free network properties. In both rat trypsin and PDZ3 proteins, the statistically prominent modes of rigidity graphs uncover the sequence-specific coupling patterns and mechanical hotspots. Based on the contributions to graphical modes, our residue rigidity scores in backbone and side chains are found to be very useful metrics for the biological significance. Most functional sites have high residue rigidity scores in side chains while the biologically important glycines are generally next to mechanical hotspots. Furthermore, prominent modes in the rigidity graphs involving side chains oftentimes coincide with the co-evolution patterns due to evolutionary restraints. The bsENM specifically devised to resolve the protein chemical character thus provides useful means for extracting functional information from all-atom MD.

Modeling coronavirus spike protein dynamics: implications for immunogenicity and immune escape

The ongoing COVID-19 pandemic is a global public health emergency requiring urgent development of efficacious vaccines. While concentrated research efforts have focused primarily on antibody-based vaccines that neutralize SARS-CoV-2, and several first-generation vaccines have either been approved or received emergency use authorization, it is forecasted that COVID-19 will become an endemic disease requiring updated second-generation vaccines. The SARS-CoV-2 surface spike (S) glycoprotein represents a prime target for vaccine development because antibodies that block viral attachment and entry, i.e., neutralizing antibodies, bind almost exclusively to the receptor-binding domain. Here, we develop computational models for a large subset of S proteins associated with SARS-CoV-2, implemented through coarse-grained elastic network models and normal mode analysis. We then analyze local protein domain dynamics of the S protein systems and their thermal stability to characterize structural and dynamical variability among them. These results are compared against existing experimental data and used to elucidate the impact and mechanisms of SARS-CoV-2 S protein mutations and their associated antibody binding behavior. We construct a SARS-CoV-2 antigenic map and offer predictions about the neutralization capabilities of antibody and S mutant combinations based on protein dynamic signatures. We then compare SARS-CoV-2 S protein dynamics to SARS-CoV and MERS-CoV S proteins to investigate differing antibody binding and cellular fusion mechanisms that may explain the high transmissibility of SARS-CoV-2. The outbreaks associated with SARS-CoV, MERS-CoV, and SARS-CoV-2 over the last two decades suggest that the threat presented by coronaviruses is ever-changing and long term. Our results provide insights into the dynamics-driven mechanisms of immunogenicity associated with coronavirus S proteins and present a new, to our knowledge, approach to characterize and screen potential mutant candidates for immunogen design, as well as to characterize emerging natural variants that may escape vaccine-induced antibody responses.

Single-molecule imaging with cell-derived nanovesicles reveals early binding dynamics at a cyclic nucleotide-gated ion channel

Ligand binding to membrane proteins is critical for many biological signaling processes. However, individual binding events are rarely directly observed, and their asynchronous dynamics are occluded in ensemble-averaged measures. For membrane proteins, single-molecule approaches that resolve these dynamics are challenged by dysfunction in non-native lipid environments, lack of access to intracellular sites, and costly sample preparation. Here, we introduce an approach combining cell-derived nanovesicles, microfluidics, and single-molecule fluorescence colocalization microscopy to track individual binding events at a cyclic nucleotide-gated TAX-4 ion channel critical for sensory transduction. Our observations reveal dynamics of both nucleotide binding and a subsequent conformational change likely preceding pore opening. Kinetic modeling suggests that binding of the second ligand is either independent of the first ligand or exhibits up to ~10-fold positive binding cooperativity. This approach is broadly applicable to studies of binding dynamics for proteins with extracellular or intracellular domains in native cell membrane.

Pseudokinases repurpose flexibility signatures associated with the protein kinase fold for noncatalytic roles

The bilobal protein kinase-like fold in pseudokinases lack one or more catalytic residues, conserved in canonical protein kinases, and are considered enzymatically deficient. Tertiary structures of pseudokinases reveal that their loops topologically equivalent to activation segments of kinases adopt contracted configurations, which is typically extended in active conformation of kinases. Herein, anisotropic network model based normal mode analysis (NMA) was conducted on 51 active conformation structures of protein kinases and 26 crystal structures of pseudokinases. Our observations indicate that although backbone fluctuation profiles are similar for individual kinase-pseudokinase families, low intensity mean square fluctuations in pseudo-activation segment and other sub-structures impart rigidity to pseudokinases. Analyses of collective motions from functional modes reveal that pseudokinases, compared to active kinases, undergo distinct conformational transitions using the same structural fold. All-atom NMA of protein kinase-pseudokinase pairs from each family, sharing high amino acid sequence identities, yielded distinct community clusters, partitioned by residues exhibiting highly correlated fluctuations. It appears that atomic fluctuations from equivalent activation segments guide community membership and network topologies for respective kinase and pseudokinase. Our findings indicate that such adaptations in backbone and side-chain fluctuations render pseudokinases competent for catalysis-independent roles.

Mapping Function from Dynamics: Future Challenges for Network-Based Models of Protein Structures

Proteins fulfill complex and diverse biological functions through the controlled atomic motions of their structures (functional dynamics). The protein composition is given by its amino-acid sequence, which was assumed to encode the function. However, the discovery of functional sequence variants proved that the functional encoding does not come down to the sequence, otherwise a change in the sequence would mean a change of function. Likewise, the discovery that function is fulfilled by a set of structures and not by a unique structure showed that the functional encoding does not come down to the structure either. That leaves us with the possibility that a set of atomic motions, achievable by different sequences and different structures, encodes a specific function. Thanks to the exponential growth in annual depositions in the Protein Data Bank of protein tridimensional structures at atomic resolutions, network models using the Cartesian coordinates of atoms of a protein structure as input have been used over 20 years to investigate protein features. Combining networks with experimental measures or with Molecular Dynamics (MD) simulations and using typical or ad-hoc network measures is well suited to decipher the link between protein dynamics and function. One perspective is to consider static structures alone as alternatives to address the question and find network measures relevant to dynamics that can be subsequently used for mining and classification of dynamic sequence changes functionally robust, adaptable or faulty. This way the set of dynamics that fulfill a function over a diversity of sequences and structures will be determined.

Spatial bias in cAMP generation determines biological responses to PTH type 1 receptor activation

[Figure: see text].

Structural definition of the discrete hotspot sites of BMP-2 conformational wrist epitope and rational design of the hotspot-derived osteogenic peptides against chondrocyte senescence

The bone morphogenetic protein-2 (BMP-2) is an essential regulator of bone formation and remodeling, which has also been implicated in the pathogenesis of osteoarthritis and its closely related chondrocyte senescence. The BMP-2 uses a conformational wrist epitope and a linear knuckle epitope to interact with type-I (BMPR-I) and type-II (BMPR-II) receptors, respectively. Previously, the knuckle epitope has been intensely studied, but the wrist epitope still remains largely unexplored due to its discontinuous nature. In the present work, the intermolecular interaction of BMP-2 with BMPR-I was investigated systematically at structural, energetic and dynamic levels. Three discrete hotspots that represent the key BMPR-I recognition sites of BMP-2 were identified; they are spatially dispersed over the two monomers of BMP-2 dimer and totally account for 83.5 % binding potency of BMP-2 to BMPR-I (hotspot 1: residues 49-70 in monomer 1; hotspot 2: residues 24-31 in monomer 2; hotspot 3: residues 88-107 in monomer 2). Therefore, we defined the three discrete hotspot sites as the core region of wrist epitope; their contribution to the binding increases in the order: hotspot 2 < hotspot 3 < hotspot 1. We demonstrated that the primary hotspot 1 site has a native U-shaped conformation in the full-length BMP-2 protein context, but it cannot maintain in the native conformation when split from the context to obtain a free hotspot-1 peptide, thus largely impairing its binding potency to BMPR-I. We further employed disulfide-bonded cyclization and head-to-tail cyclization to constrain the peptide conformation, and found that only the former can effectively constrain the peptide into native conformation, thus considerably improving its binding affinity to BMPR-I, whereas the latter totally disorders the native conformation, thus rendering the peptide as a full nonbinder of BMPR-I.

Mutational analysis to explore long-range allosteric couplings involved in a pentameric channel receptor pre-activation and activation

Pentameric ligand-gated ion channels (pLGICs) mediate chemical signaling through a succession of allosteric transitions that are yet not completely understood as intermediate states remain poorly characterized by structural approaches. In a previous study on the prototypic bacterial proton-gated channel GLIC, we generated several fluorescent sensors of the protein conformation that report a fast transition to a pre-active state, which precedes the slower process of activation with pore opening. Here, we explored the phenotype of a series of allosteric mutations, using simultaneous steady-state fluorescence and electrophysiological measurements over a broad pH range. Our data, fitted to a three-state Monod-Wyman-Changeux model, show that mutations at the subunit interface in the extracellular domain (ECD) principally alter pre-activation, while mutations in the lower ECD and in the transmembrane domain principally alter activation. We also show that propofol alters both transitions. Data are discussed in the framework of transition pathways generated by normal mode analysis (iModFit). It further supports that pre-activation involves major quaternary compaction of the ECD, and suggests that activation involves principally a reorganization of a ‘central gating region’ involving a contraction of the ECD β-sandwich and the tilt of the channel lining M2 helix.

GTP Cyclohydrolase I as a Potential Drug Target: New Insights into Its Allosteric Modulation via Normal Mode Analysis

Guanosine triphosphate (GTP) cyclohydrolase I (GCH1) catalyzes the conversion of GTP into dihydroneopterin triphosphate (DHNP). DHNP is the first intermediate of the folate de novo biosynthesis pathway in prokaryotic and lower eukaryotic microorganisms and the tetrahydrobiopterin (BH4) biosynthesis pathway in higher eukaryotes. The de novo folate biosynthesis provides essential cofactors for DNA replication, cell division, and synthesis of key amino acids in rapidly replicating pathogen cells, such as Plasmodium falciparum (P. falciparum), a causative agent of malaria. In eukaryotes, the product of the BH4 biosynthesis pathway is essential for the production of nitric oxide and several neurotransmitter precursors. An increased copy number of the malaria parasite P. falciparum GCH1 gene has been reported to influence antimalarial antifolate drug resistance evolution, whereas mutations in the human GCH1 are associated with neuropathic and inflammatory pain disorders. Thus, GCH1 stands as an important and attractive drug target for developing therapeutics. The GCH1 intrinsic dynamics that modulate its activity remains unclear, and key sites that exert allosteric effects across the structure are yet to be elucidated. This study employed the anisotropic network model to analyze the intrinsic motions of the GCH1 structure alone and in complex with its regulatory partner protein. We showed that the GCH1 tunnel-gating mechanism is regulated by a global shear motion and an outward expansion of the central five-helix bundle. We further identified hotspot residues within sites of structural significance for the GCH1 intrinsic allosteric modulation. The obtained results can provide a solid starting point to design novel antineuropathic treatments for humans and novel antimalarial drugs against the malaria parasite P. falciparum GCH1 enzyme.

In silico drug discovery for a complex immunotherapeutic target - human c-Rel protein

Target evaluation and rational drug design rely on identifying and characterising small-molecule binding sites on therapeutically relevant target proteins. Immunotherapeutics development is especially challenging because of complex disease etiology and heterogenous nature of targets. c-Rel protein, a promising target in many human inflammatory and cancer pathologies, was selected as a case study for an effective in silico screening platform development since this transcription factor currently has no successful therapeutic inhibitors or modulators. This study introduces a novel in silico screening approach to probe binding sites using structural validation sets, molecular modelling and describes a method of a computer-aided drug design when a crystal structure is not available for the target of interest. In addition, we showed that binding sites can be analysed with the machine learning as well as molecular simulation approaches to help assess and systematically analyse how drug candidates can exert their mode of action. Finally, this cutting-edge approach was subjected to a high through-put virtual screen of selected 34 M drug-like compounds filtered from a library of 659 M compounds by identifying the most promising structures and proposing potential action mechanisms for the future development of highly selective human c-Rel inhibitors and/or modulators.

The Archaeal Na+/Ca2+ Exchanger (NCX_Mj) as a Model of Ion Transport for the Superfamily of Ca2+/CA Antiporters

The superfamily of Calcium/Cation (Ca²⁺/CA) antiporters extrude Ca²⁺ from the cytosol or subcellular compartments in exchange with Na⁺, K⁺, H⁺, Li⁺, or Mg²⁺ and thereby provide a key mechanism for Ca²⁺ signaling and ion homeostasis in biological systems ranging from bacteria to humans. The structure-dynamic determinants of ion selectivity and transport rates remain unclear, although this is of primary physiological significance. Despite wide variances in the ion selectivity and transport rates, the Ca²⁺/CA proteins share structural motifs, although it remains unclear how the ion recognition/binding is coupled to the ion translocation events. Here, the archaeal Na⁺/Ca²⁺ exchanger (NCX_Mj) is considered as a structure-based model that can help to resolve the ion transport mechanisms by using X-ray, HDX-MS, ATR-FTIR, and computational approaches in conjunction with functional analyses of mutants. Accumulating data reveal that the local backbone dynamics at ion-coordinating residues is characteristically constrained in apo NCX_Mj, which may predefine the affinity and stability of ion-bound species in the ground and transition states. The 3Na⁺ or 1Ca²⁺ binding to respective sites of NCX_Mj rigidify the backbone dynamics at specific segments, where the ion-dependent compression of the ion-permeating four-helix bundle (TM2, TM3, TM7, and TM8) induces the sliding of the two-helix cluster (TM1/TM6) on the protein surface to switch the OF (outward-facing) and IF (inward-facing) conformations. Taking into account the common structural elements shared by Ca²⁺/CAs, NCX_Mj may serve as a model for studying the structure-dynamic and functional determinants of ion-coupled alternating access, transport catalysis, and ion selectivity in Ca²⁺/CA proteins.

Comparative Analysis of Structural and Dynamical Features of Ribosome Upon Association With mRNA Reveals Potential Role of Ribosomal Proteins

Ribosomes play a critical role in maintaining cellular proteostasis. The binding of messenger RNA (mRNA) to the ribosome regulates kinetics of protein synthesis. To generate an understanding of the structural, mechanistic, and dynamical features of mRNA recognition in the ribosome, we have analysed mRNA-protein interactions through a structural comparison of the ribosomal complex in the presence and absence of mRNA. To do so, we compared the 3-Dimensional (3D) structures of components of the two assembly structures and analysed their structural differences because of mRNA binding, using elastic network models and structural network-based analysis. We observe that the head region of 30S ribosomal subunit undergoes structural displacement and subunit rearrangement to accommodate incoming mRNA. We find that these changes are observed in proteins that lie far from the mRNA-protein interface, implying allostery. Further, through perturbation response scanning, we show that the proteins S13, S19, and S20 act as universal sensors that are sensitive to changes in the inter protein network, upon binding of 30S complex with mRNA and other initiation factors. Our study highlights the significance of mRNA binding in the ribosome complex and identifies putative allosteric sites corresponding to alterations in structure and/or dynamics, in regions away from mRNA binding sites in the complex. Overall, our work provides fresh insights into mRNA association with the ribosome, highlighting changes in the interactions and dynamics of the ribosome assembly because of the binding.

Near-physiological-temperature serial crystallography reveals conformations of SARS-CoV-2 main protease active site for improved drug repurposing

The COVID-19 pandemic has resulted in 198 million reported infections and more than 4 million deaths as of July 2021 (covid19.who.int). Research to identify effective therapies for COVID-19 includes: (1) designing a vaccine as future protection; (2) de novo drug discovery; and (3) identifying existing drugs to repurpose them as effective and immediate treatments. To assist in drug repurposing and design, we determine two apo structures of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease at ambient temperature by serial femtosecond X-ray crystallography. We employ detailed molecular simulations of selected known main protease inhibitors with the structures and compare binding modes and energies. The combined structural and molecular modeling studies not only reveal the dynamics of small molecules targeting the main protease but also provide invaluable opportunities for drug repurposing and structure-based drug design strategies against SARS-CoV-2.

Helical reconstruction of Salmonella and Shigella needle filaments attached to type 3 basal bodies

Gram-negative pathogens evolved a syringe-like nanomachine, termed type 3 secretion system, to deliver protein effectors into the cytoplasm of host cells. An essential component of this system is a long helical needle filament that protrudes from the bacterial surface and connects the cytoplasms of the bacterium and the eukaryotic cell. Previous structural research was predominantly focused on reconstituted type 3 needle filaments, which lacked the biological context. In this work we introduce a facile procedure to obtain high-resolution cryo-EM structure of needle filaments attached to the basal body of type 3 secretion systems. We validate our approach by solving the structure of Salmonella PrgI filament and demonstrate its utility by obtaining the first high-resolution cryo-EM reconstruction of Shigella MxiH filament. Our work paves the way to systematic structural characterization of attached type 3 needle filaments in the context of mutagenesis studies, protein structural evolution and drug development.

Mechanistic Insights into the Allosteric Inhibition of Androgen Receptors by Binding Function 3 Antagonists from an Integrated Molecular Modeling Study

An androgen receptor (AR) is an intensively studied treatment target for castration-resistant prostate cancer that is irresponsive to conventional antiandrogen therapeutics. Binding function 3 (BF3) inhibitors with alternative modes of action have emerged as a promising approach to overcoming antiandrogen resistance. However, how these BF3 inhibitors modulate AR function remains elusive, hindering the development of BF3-targeting agents. Here, we performed an integrated computational study to interrogate the binding mechanism of several known BF3 inhibitors with ARs. Our results show that the inhibitory effect of the BF3 antagonists arises from their allosteric modulation of the activation function (AF2) site, which alters the dynamic coupling between the BF3 and AF2 sites as well as the AF2-coactivator (SRC2-3) interaction. Moreover, the per-residue binding energy analyses reveal the "anchor" role of the linker connecting the phenyl ring and benzimidazole/indole in these BF3 inhibitors. Furthermore, the allosteric driver-interacting residues are found to include both "positive", e.g., Phe673 and Asn833, and "negative" ones, e.g., Phe826, and the differential interactions with these residues provide an explanation why stronger binding does not necessarily result in higher inhibitory activities. Finally, our allosteric communication pathway analyses delineate how the allosteric signals triggered by BF3 binding are propagated to the AF2 pocket through multiple short- and/or long-ranged transmission pathways. Collectively, our combined computational study provides a comprehensive structural mechanism underlying how the selected set of BF3 inhibitors modulate AR function, which will help guide future development of BF3 antagonists.

Structure and Sequence-based Computational Approaches to Allosteric Signal Transduction: Application to Electromechanical Coupling in Voltage-gated Ion Channels

Allosteric signaling underlies the function of many biomolecules, including membrane proteins such as ion channels. Experimental methods have enabled specific quantitative insights into the coupling between the voltage sensing domain (VSD) and the pore gate of voltage-gated ion channels, located tens of Ångström apart from one another, as well as pinpointed specific residues and domains that participate in electromechanical signal transmission. Nevertheless, an overall atomic-level resolution picture is difficult to obtain from these methods alone. Today, thanks to the cryo-EM resolution revolution, we have access to high resolution structures of many different voltage-gated ion channels in various conformational states, putting a quantitative description of the processes at the basis of these changes within our close reach. Here, we review computational methods that build on structures to detect and characterize allosteric signaling and pathways. We then examine what has been learned so far about electromechanical coupling between VSD and pore using such methods. While no general theory of electromechanical coupling in voltage-gated ion channels integrating results from all these methods is available yet, we outline the types of insights that could be achieved in the near future using the methods that have not yet been put to use in this field of application.

Normal mode analysis of membrane protein dynamics using the vibrational subsystem analysis

The vibrational subsystem analysis is a useful approach that allows for evaluating the spectrum of modes of a given system by integrating out the degrees of freedom accessible to the environment. The approach could be utilized for exploring the collective dynamics of a membrane protein (system) coupled to the lipid bilayer (environment). However, the application to membrane proteins is limited due to high computational costs of modeling a sufficiently large membrane environment unbiased by end effects, which drastically increases the size of the investigated system. We derived a recursive formula for calculating the reduced Hessian of a membrane protein embedded in a lipid bilayer by decomposing the membrane into concentric cylindrical domains with the protein located at the center. The approach allows for the design of a time- and memory-efficient algorithm and a mathematical understanding of the convergence of the reduced Hessian with respect to increasing membrane sizes. The application to the archaeal aspartate transporter GltPh illustrates its utility and efficiency in capturing the transporter's elevator-like movement during its transition between outward-facing and inward-facing states.

Probing Structural Dynamics of Membrane Proteins Using Electron Paramagnetic Resonance Spectroscopic Techniques

Membrane proteins are essential for the survival of living organisms. They are involved in important biological functions including transportation of ions and molecules across the cell membrane and triggering the signaling pathways. They are targets of more than half of the modern medical drugs. Despite their biological significance, information about the structural dynamics of membrane proteins is lagging when compared to that of globular proteins. The major challenges with these systems are low expression yields and lack of appropriate solubilizing medium required for biophysical techniques. Electron paramagnetic resonance (EPR) spectroscopy coupled with site directed spin labeling (SDSL) is a rapidly growing powerful biophysical technique that can be used to obtain pertinent structural and dynamic information on membrane proteins. In this brief review, we will focus on the overview of the widely used EPR approaches and their emerging applications to answer structural and conformational dynamics related questions on important membrane protein systems.

Analytical Hessians for Ewald and particle mesh Ewald electrostatics

The particle mesh Ewald (PME) method has become ubiquitous in the molecular simulation community due to its ability to deliver long range electrostatics accurately with ON  ⁡log(N) complexity. Despite this widespread use, spanning more than two decades, second derivatives (Hessians) have not been available. In this work, we describe the theory and implementation of PME Hessians, which have applications in normal mode analysis, characterization of stationary points, phonon dispersion curve calculation, crystal structure prediction, and efficient geometry optimization. We outline an exact strategy that requires O(1) effort for each Hessian element; after discussing the excessive memory requirements of such an approach, we develop an accurate, efficient approximation that is far more tractable on commodity hardware.

State-dependent sequential allostery exhibited by chaperonin TRiC/CCT revealed by network analysis of Cryo-EM maps

The eukaryotic chaperonin TRiC/CCT plays a major role in assisting the folding of many proteins through an ATP-driven allosteric cycle. Recent structures elucidated by cryo-electron microscopy provide a broad view of the conformations visited at various stages of the chaperonin cycle, including a sequential activation of its subunits in response to nucleotide binding. But we lack a thorough mechanistic understanding of the structure-based dynamics and communication properties that underlie the TRiC/CCT machinery. In this study, we present a computational methodology based on elastic network models adapted to cryo-EM density maps to gain a deeper understanding of the structure-encoded allosteric dynamics of this hexadecameric machine. We have analysed several structures of the chaperonin resolved in different states toward mapping its conformational landscape. Our study indicates that the overall architecture intrinsically favours cooperative movements that comply with the structural variabilities observed in experiments. Furthermore, the individual subunits CCT1-CCT8 exhibit state-dependent sequential events at different states of the allosteric cycle. For example, in the ATP-bound state, subunits CCT5 and CCT4 selectively initiate the lid closure motions favoured by the overall architecture; whereas in the apo form of the heteromer, the subunit CCT7 exhibits the highest predisposition to structural change. The changes then propagate through parallel fluxes of allosteric signals to neighbours on both rings. The predicted state-dependent mechanisms of sequential activation provide new insights into TRiC/CCT intra- and inter-ring signal transduction events.

Revisiting bone morphogenetic protein-2 knuckle epitope and redesigning the epitope-derived peptides

The bone morphogenetic protein-2 (BMP2) plays a crucial role in bone formation, growth and regeneration, which adopts a conformational wrist epitope and a linear knuckle epitope to interact with its type-I (BRI) and type-II (BRII) receptors, respectively. In this study, we systematically examine the BRII-recognition site of BMP2 at structural, energetic and dynamic levels and accurately locate hotspots of the recognition at BMP2-BRII complex interface. It is revealed that the traditional knuckle epitope (BMP2 residue range 73-92) do fully match the identified hotspots; the BMP2-recognition site includes the C-terminal region of traditional knuckle epitope as well as its flanked β-strands. In addition, the protein context of full-length BMP2 is also responsible for the recognition by addressing conformational constraint on the native epitope segment. Therefore, we herein redefine the knuckle epitope to BMP2 residue range 84-102, which has a similar sequence length but is slid along the protein sequence by ~10 residues as compared to traditional knuckle epitope. The redefined one is also a linear epitope that is natively a double-stranded β-sheet with two asymmetric arms as compared to the natively single β-strand of the traditional version, although their sequences are partially overlapped to each other. It is revealed that the redefined epitope-derived peptide LN^84-102 exhibits an improved affinity by >3-fold relative to the traditional epitope-derived peptide KL^73-92 . Even so, the LN^84-102 peptide still cannot fully represent the BMP2 recognition event by BRII that has been reported to have a nanomolar affinity. We further introduce a disulfide bond across the two arms of double-stranded β-sheet to constrain the free LN^84-102 peptide conformation, which mimics the conformational constraint addressed by protein context. Consequently, several cyclic peptides are redesigned, in which the LN^84-102 (cyc89-101) is determined to exhibit a sub-micromolar affinity; this value is ~5-fold higher than its linear counterpart. Structural analysis also reveals that the cyclic peptide can interact with BRII in a similar binding mode with the redefined knuckle epitope region in full-length BMP2 protein.

Residue Interaction Network Analysis Predicts a Val24-Ile31 Interaction May be Involved in Preventing Amyloid-Beta (1-42) Primary Nucleation

Alzheimer's disease (AD) patients could benefit from a more effective treatment than the current FDA-approved options. Because amyloid-beta (Aβ) is thought to play a central role in AD pathogenesis, many experimental drugs attempt to reduce Aβ-induced pathology. Preventing amyloid accumulation may be a more effective strategy than clearing Aβ plaques after they form. If preventing Aβ accumulation can treat or prevent AD, then understanding Aβ primary nucleation may aid rational drug design. This study examines Aβ residue interaction networks and reports network and structural observations that may provide insight into primary nucleation. While many studies identify structural features of Aβ that promote aggregation, this study reports features that may resist primary nucleation by examining Aβ42 studies in more and less polar solvents. In Aβ42 in a less polar solvent (PDB ID: 1IYT), Val24 and Ile31 have higher betweenness and residue centrality values. This may be due to a predicted interaction between Val24 and Ile31. Residues in the central hydrophobic cluster (CHC) of Aβ40 and Aβ42 had significantly higher betweenness values compared to the average betweenness of the structures, highlighting the CHC's reported role in oligomerization. The predicted interaction between Val24 and Ile31 may reduce the likelihood of primary nucleation of Aβ.

Computational investigations of allostery in aromatic amino acid biosynthetic enzymes

Allostery, in which binding of ligands to remote sites causes a functional change in the active sites, is a fascinating phenomenon observed in enzymes. Allostery can occur either with or without significant conformational changes in the enzymes, and the molecular basis of its mechanism can be difficult to decipher using only experimental techniques. Computational tools for analyzing enzyme sequences, structures, and dynamics can provide insights into the allosteric mechanism at the atomic level. Combining computational and experimental methods offers a powerful strategy for the study of enzyme allostery. The aromatic amino acid biosynthesis pathway is essential in microorganisms and plants. Multiple enzymes involved in this pathway are sensitive to feedback regulation by pathway end products and are known to use allostery to control their activities. To date, four enzymes in the aromatic amino acid biosynthesis pathway have been computationally investigated for their allosteric mechanisms, including 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase, anthranilate synthase, chorismate mutase, and tryptophan synthase. Here we review the computational studies and findings on the allosteric mechanisms of these four enzymes. Results from these studies demonstrate the capability of computational tools and encourage future computational investigations of allostery in other enzymes of this pathway.

Study on functional sites in human multidrug resistance protein 1 (hMRP1)

Human multidrug resistance protein 1 (hMRP1) is an important member of the ATP-binding cassette (ABC) transporter superfamily. It can extrude a variety of anticancer drugs and physiological organic anions across the plasma membrane, which is activated by substrate binding, and is accompanied by large-scale cooperative movements between different domains. Currently, it remains unclear completely about how the specific interactions between hMRP1 and its substrate are and which critical residues are responsible for allosteric signal transduction. To the end, we first construct an inward-facing state of hMRP1 using homology modeling method, and then dock substrate proinflammatory agent leukotriene C4 (LTC4) to hMRP1 pocket. The result manifests LTC4 interacts with two parts of hMRP1 pocket, namely the positively charged pocket (P pocket) and hydrophobic pocket (H pocket), similar to its binding mode with bMRP1 (bovine MRP1). Additionally, we use the Gaussian network model (GNM)-based thermodynamic method proposed by us to identify the key residues whose perturbations markedly alter their binding free energy. Here the conventional GNM is improved with covalent/non-covalent interactions and secondary structure information considered (denoted as sscGNM). In the result, sscGNM improves the flexibility prediction, especially for the nucleotide binding domains with rich kinds of secondary structures. The 46 key residue clusters located in different subdomains are identified which are highly consistent with experimental observations. Furtherly, we explore the long-range cooperation within the transporter. This study is helpful for strengthening the understanding of the work mechanism in ABC exporters and can provide important information to scientists in drug design studies.

Mapping the DNA-Binding Motif of Scabin Toxin, a Guanine Modifying Enzyme from Streptomyces scabies

Scabin is a mono-ADP-ribosyltransferase toxin/enzyme and possible virulence factor produced by the agriculture pathogen, Streptomyces scabies. Recently, molecular dynamic approaches and MD simulations revealed its interaction with both NAD⁺ and DNA substrates. An Essential Dynamics Analysis identified a crab-claw-like mechanism, including coupled changes in the exposed motifs, and the R_β1-R_La-N_Lc-STT_β2-W_PN-W_ARTT-(QxE)_ARTT sequence motif was proposed as a catalytic signature of the Pierisin family of DNA-acting toxins. A new fluorescence assay was devised to measure the kinetics for both RNA and DNA substrates. Several protein variants were prepared to probe the Scabin-NAD-DNA molecular model and to reveal the reaction mechanism for the transfer of ADP-ribose to the guanine base in the DNA substrate. The results revealed that there are several lysine and arginine residues in Scabin that are important for binding the DNA substrate; also, key residues such as Asn110 in the mechanism of ADP-ribose transfer to the guanine base were identified. The DNA-binding residues are shared with ScARP from Streptomyces coelicolor but are not conserved with Pierisin-1, suggesting that the modification of guanine bases by ADP-ribosyltransferases is divergent even in the Pierisin family.

Multibasin Quasi-Harmonic Approach for the Calculation of the Configurational Entropy of Small Molecules in Solution

Entropy is a key thermodynamic property governing most biomolecular processes, including binding. Nonetheless, quantification of the configurational entropy of a single molecule in solution remains a grand challenge. Here, we present an original approach for the calculation of absolute molecular entropies based on the analysis of converged molecular dynamics (MD) simulations. Our method, named quasi-harmonic multibasin (QHMB), relies on a multibasin decomposition of the simulated trajectory by root-mean-square deviation clustering and subsequent quasi-harmonic analysis (QHA) of extracted sub-trajectories. Last, the entropy of the landscape is evaluated using the Gibbs formula. Because of the nature of QHA, this method is directly applicable to explicit-solvent simulations to access configurational entropies in solution. When compared with calorimetric data from NIST, QHMB is shown to predict absolute entropies in the gas phase for 23 small molecules with a root-mean-squared error of 0.36 kcal/mol from the experiments. In addition, the introduction of a QHMB correction in MM/GBSA calculations to account for the ligand configurational entropy loss on binding is shown to improve the correlation between calculated and experimental binding affinities with R² increasing from 0.67 to 0.78. Because this entropy correction penalizes large and flexible ligands more strongly, it might be useful to reduce the false-positive rate in virtual screening. The availability of an automatic procedure to compute QHMB entropies makes it a new available tool in the field of drug discovery.

Exploring the intrinsic dynamics of SARS-CoV-2, SARS-CoV and MERS-CoV spike glycoprotein through normal mode analysis using anisotropic network model

COVID-19 caused by SARS-CoV-2 have become a global pandemic with serious rate of fatalities. SARS-CoV and MERS-CoV have also caused serious outbreak previously but the intensity was much lower than the ongoing SARS-CoV-2. The main infectivity factor of all the three viruses is the spike glycoprotein. In this study we have examined the intrinsic dynamics of the prefusion, lying state of trimeric S protein of these viruses through Normal Mode Analysis using Anisotropic Network Model. The dynamic modes of the S proteins of the aforementioned viruses were compared by root mean square inner product (RMSIP), spectral overlap and cosine correlation matrix. S proteins show homogenous correlated or anticorrelated motions among their domains but direction of Cα atom among the spike proteins show less similarity. SARS-CoV-2 spike shows high vertically upward motion of the receptor binding motif implying its propensity for binding with the receptor even in the lying state. MERS-CoV spike shows unique dynamical motion compared to the other two S protein indicated by low RMSIP, spectral overlap and cosine correlation value. This study will guide in developing common potential inhibitor molecules against closed state of spike protein of these viruses to prevent conformational switching from lying to standing state.

Computational analysis of dynamic allostery and control in the SARS-CoV-2 main protease

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has no publicly available vaccine or antiviral drugs at the time of writing. An attractive coronavirus drug target is the main protease (Mpro, also known as 3CLpro) because of its vital role in the viral cycle. A significant body of work has been focused on finding inhibitors which bind and block the active site of the main protease, but little has been done to address potential non-competitive inhibition, targeting regions other than the active site, partly because the fundamental biophysics of such allosteric control is still poorly understood. In this work, we construct an elastic network model (ENM) of the SARS-CoV-2 Mpro homodimer protein and analyse its dynamics and thermodynamics. We found a rich and heterogeneous dynamical structure, including allosterically correlated motions between the homodimeric protease's active sites. Exhaustive 1-point and 2-point mutation scans of the ENM and their effect on fluctuation free energies confirm previously experimentally identified bioactive residues, but also suggest several new candidate regions that are distant from the active site, yet control the protease function. Our results suggest new dynamically driven control regions as possible candidates for non-competitive inhibiting binding sites in the protease, which may assist the development of current fragment-based binding screens. The results also provide new insights into the active biophysical research field of protein fluctuation allostery and its underpinning dynamical structure.

Using normal mode analysis on protein structural models. How far can we go on our predictions?

Normal mode analysis (NMA) is a fast and inexpensive approach that is largely used to gain insight into functional protein motions, and more recently to create conformations for further computational studies. However, when the protein structure is unknown, the use of computational models is necessary. Here, we analyze the capacity of NMA in internal coordinate space to predict protein motion, its intrinsic flexibility, and atomic displacements, using protein models instead of native structures, and the possibility to use it for model refinement. Our results show that NMA is quite insensitive to modeling errors, but that calculations are strictly reliable only for very accurate models. Our study also suggests that internal NMA is a more suitable tool for the improvement of structural models, and for integrating them with experimental data or in other computational techniques, such as protein docking or more refined molecular dynamics simulations.

Transient association between proteins elicits alteration of dynamics at sites far away from interfaces

Proteins are known to undergo structural changes upon binding to partner proteins. However, the prevalence, extent, location, and function of change in protein dynamics due to transient protein-protein interactions is not well documented. Here, we have analyzed a dataset of 58 protein-protein complexes of known three-dimensional structure and structures of their corresponding unbound forms to evaluate dynamics changes induced by binding. Fifty-five percent of cases showed significant dynamics change away from the interfaces. This change is not always accompanied by an observed structural change. Binding of protein partner is found to alter inter-residue communication within the tertiary structure in about 90% of cases. Also, residue motions accessible to proteins in unbound form were not always maintained in the bound form. Further analyses revealed functional roles for the distant site where dynamics change was observed. Overall, the results presented here strongly suggest that alteration of protein dynamics due to binding of a partner protein commonly occurs.

Virtual screening of phytoconstituents from miracle herb nigella sativa targeting nucleocapsid protein and papain-like protease of SARS-CoV-2 for COVID-19 treatment

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel etiological agent of coronavirus disease 2019 (COVID-19). Nigella sativa, commonly known as black seed or black cumin, has been a historical and traditional plant since thousands of years. Based on their therapeutic efficacy, the chief components of terpenoids and flavonoids were selected from N. sativa seeds and seed oil. This study was designed to check the antiviral efficacy of N. sativa main phytoconstituents against five potential targets of SARS-CoV-2 using in silico structure-based virtual screening approach. Out of twenty five phytocomponents, ten components showed best binding affinity against two viral proteins viz. N-terminal RNA binding domain (NRBD; PDB ID: 6M3M) of nucleocapsid protein and papain-like protease (PL-_PRO; PDB ID: 6W9C) of SARS-CoV-2 using AutoDock 4.2.6, AutoDock Vina and iGEMDOCK. PASS analyses of all ten phytocomponents using Lipinski's Rule of five showed promising results. Further, druglikeness and toxicity assessment using OSIRIS Data Warrior v5.2.1 software exhibited the feasibility of phytocomponents as drug candidates with no predicted toxicity. Molecular dynamics simulation study of NRBD of SARS-CoV-2 nucleocapsid protein-alpha-spinasterol complex and PL-_PRO-cycloeucalenol complex displayed strong stability at 300 K. Both these complexes exhibited constant root mean square deviation (RMSDs) of protein side chains and Cα atoms throughout the simulation run time. Interestingly, PL-_PRO and NRBD are key proteins in viral replication, host cell immune evasion and viral assembly. Thus, NRBD and PL-_PRO have the potential to serve as therapeutic targets for N. sativa phytoconstituents in drug discovery process against COVID-19.

Structure-based discovery and redesign of TGF-β1 Elbow epitope recognition by its type-II receptor in hypertrophic scarring biotherapy

Transforming growth factor-β1 (TGF-β1) signaling pathway has been implicated in the fibroblast activation of hypertrophic scarring (HS). Previously, we proposed a new biotherapeutic strategy to combat HS by disrupting the intermolecular interaction of TGF-β1 with its cognate type-II receptor (TβR-II). Here, we further demonstrate that the binding site of TGF-β1 to TβR-II is not overlapped with the conformational wrist epitope and linear knuckle epitope that are traditionally recognized as the functional binding sites of bone morphogenetic protein-2 (BMP-2) to its type-II receptor (BMPR-II), which can thus be regarded as a new functional site we called elbow epitope. Structural, energetic, and dynamic investigations reveal that the elbow epitope consists of two sequentially discontinuous, spatially vicinal segments Loop^30-34 and Turn^90-95 ; they cannot work effectively to independently interact with TβR-II. Rational redesign of the epitope is performed using an integrated in silio-in vitro method based on crystal and modeled structure data. In the procedure, the two epitope segments are split from the interface of TGF-β1-TβR-II complex and then connected with each other in a head-to-tail manner by adding a flexible poly-(Gly)n linker between them, thus resulting in a series of combined peptides. We found that the peptide affinity reaches maximum at n = 2, which shares a consistent binding mode with the elbow epitope at native complex interface. The linker of either too long (n > 2) or too short (n < 2) cannot properly place the gap space between the two segments, thus impairing the binding compatibility of designed peptides with TβR-II active site.

Insight to Functional Conformation and Noncovalent Interactions of Protein-Protein Assembly Using MALDI Mass Spectrometry

Noncovalent interactions are the keys to the structural organization of biomolecule e.g., proteins, glycans, lipids in the process of molecular recognition processes e.g., enzyme-substrate, antigen-antibody. Protein interactions lead to conformational changes, which dictate the functionality of that protein-protein complex. Besides biophysics techniques, noncovalent interaction and conformational dynamics, can be studied via mass spectrometry (MS), which represents a powerful tool, due to its low sample consumption, high sensitivity, and label-free sample. In this review, the focus will be placed on Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS) and its role in the analysis of protein-protein noncovalent assemblies exploring the relationship within noncovalent interaction, conformation, and biological function.

Structural role of essential light chains in the apicomplexan glideosome

Gliding, a type of motility based on an actin-myosin motor, is specific to apicomplexan parasites. Myosin A binds two light chains which further interact with glideosome associated proteins and assemble into the glideosome. The role of individual glideosome proteins is unclear due to the lack of structures of larger glideosome assemblies. Here, we investigate the role of essential light chains (ELCs) in Toxoplasma gondii and Plasmodium falciparum and present their crystal structures as part of trimeric sub-complexes. We show that although ELCs bind a conserved MyoA sequence, P. falciparum ELC adopts a distinct structure in the free and MyoA-bound state. We suggest that ELCs enhance MyoA performance by inducing secondary structure in MyoA and thus stiffen its lever arm. Structural and biophysical analysis reveals that calcium binding has no influence on the structure of ELCs. Our work represents a further step towards understanding the mechanism of gliding in Apicomplexa.

The allosteric activation mechanism of a phospholipase A2-like toxin from Bothrops jararacussu venom: a dynamic description

The activation process of phospholipase A₂-like (PLA₂-like) toxins is a key step in their molecular mechanism, which involves oligomeric changes leading to the exposure of specific sites. Few studies have focused on the characterization of allosteric activators and the features that distinguish them from inhibitors. Herein, a comprehensive study with the BthTX-I toxin from Bothrops jararacussu venom bound or unbound to α-tocopherol (αT) was carried out. The oligomerization state of BthTX-I bound or unbound to αT in solution was studied and indicated that the toxin is predominantly monomeric but tends to oligomerize when complexed with αT. In silico molecular simulations showed the toxin presents higher conformational changes in the absence of αT, which suggests that it is important to stabilize the structure of the toxin. The transition between the two states (active/inactive) was also studied, showing that only the unbound BthTX-I system could migrate to the inactive state. In contrast, the presence of αT induces the toxin to leave the inactive state, guiding it towards the active state, with more regions exposed to the solvent, particularly its active site. Finally, the structural determinants necessary for a molecule to be an inhibitor or activator were analyzed in light of the obtained results.

Physical Constraints on Epistasis

Living systems evolve one mutation at a time, but a single mutation can alter the effect of subsequent mutations. The underlying mechanistic determinants of such epistasis are unclear. Here, we demonstrate that the physical dynamics of a biological system can generically constrain epistasis. We analyze models and experimental data on proteins and regulatory networks. In each, we find that if the long-time physical dynamics is dominated by a slow, collective mode, then the dimensionality of mutational effects is reduced. Consequently, epistatic coefficients for different combinations of mutations are no longer independent, even if individually strong. Such epistasis can be summarized as resulting from a global nonlinearity applied to an underlying linear trait, that is, as global epistasis. This constraint, in turn, reduces the ruggedness of the sequence-to-function map. By providing a generic mechanistic origin for experimentally observed global epistasis, our work suggests that slow collective physical modes can make biological systems evolvable.

webPSN v2.0: a webserver to infer fingerprints of structural communication in biomacromolecules

A mixed Protein Structure Network (PSN) and Elastic Network Model-Normal Mode Analysis (ENM-NMA)-based strategy (i.e. PSN-ENM) was developed to investigate structural communication in bio-macromolecules. Protein Structure Graphs (PSGs) are computed on a single structure, whereas information on system dynamics is supplied by ENM-NMA. The approach was implemented in a webserver (webPSN), which was significantly updated herein. The webserver now handles both proteins and nucleic acids and relies on an internal upgradable database of network parameters for ions and small molecules in all PDB structures. Apart from the radical restyle of the server and some changes in the calculation setup, other major novelties concern the possibility to: a) compute the differences in nodes, links, and communication pathways between two structures (i.e. network difference) and b) infer links, hubs, communities, and metapaths from consensus networks computed on a number of structures. These new features are useful to identify commonalties and differences between two different functional states of the same system or structural-communication signatures in homologous or analogous systems. The output analysis relies on 3D-representations, interactive tables and graphs, also available for download. Speed and accuracy make this server suitable to comparatively investigate structural communication in large sets of bio-macromolecular systems. URL: http://webpsn.hpc.unimore.it.

Exploring the landscape of model representations

The success of any physical model critically depends upon adopting an appropriate representation for the phenomenon of interest. Unfortunately, it remains generally challenging to identify the essential degrees of freedom or, equivalently, the proper order parameters for describing complex phenomena. Here we develop a statistical physics framework for exploring and quantitatively characterizing the space of order parameters for representing physical systems. Specifically, we examine the space of low-resolution representations that correspond to particle-based coarse-grained (CG) models for a simple microscopic model of protein fluctuations. We employ Monte Carlo (MC) methods to sample this space and determine the density of states for CG representations as a function of their ability to preserve the configurational information, I, and large-scale fluctuations, Q, of the microscopic model. These two metrics are uncorrelated in high-resolution representations but become anticorrelated at lower resolutions. Moreover, our MC simulations suggest an emergent length scale for coarse-graining proteins, as well as a qualitative distinction between good and bad representations of proteins. Finally, we relate our work to recent approaches for clustering graphs and detecting communities in networks.

C-terminal Tail of β-Tubulin and its Role in the Alterations of Dynein Binding Mode

Dynein is a cytoskeletal molecular motor protein that moves along the microtubule (MT) and transports various cellular cargos during its movement. Using standard Molecular Dynamics (MD) simulation, Principle Component Analysis (PCA), and Normal Mode Analysis (NMA) methods, this investigation studied large-scale movements and local interactions of dynein's Microtubule Binding Domain (MTBD) when bound to tubulin heterodimer subunits. Examination of the interactions between the MTBD segments, and their adjustments in terms of intra- and intermolecular distances at the interfacial area with tubulin heterodimer, particularly at α-H16, β-H18, and β-tubulin C-terminal tail (CTT), was the main focus of this study. The specific intramolecular interactions, electrostatic forces, and the salt bridge residue pairs were shown to be the dominating factors in orchestrating movements of the MTBD and MT interfacial segments in the dynein's low-high-affinity binding modes. Important interactions included β-Glu447 and β-Glu449 (CTT) with Arg3469 (MTBD-H6), Lys3472 (MTBD-H6-H7 loop) and Lys3479 (MTBD-H7); β-Glu449 with Lys3384 (MTBD-H8), Lys3386 and His3387 (MTBD-H1). The structural and precise position, orientation, and functional effects of the CTTs on the MT-MTBD, within reasonable cut-off distance for non-bonding interactions and under physiological conditions, are unavailable from previous studies. The absence of the residues in the highly flexible MT-CTTs in the experimentally solved structures is perhaps in some cases due to insufficient data from density maps, but these segments are crucial in protein binding. The presented work contributes to the information useful for the MT-MTBD structure refinement.

Key role of quinone in the mechanism of respiratory complex I

Complex I is the first and the largest enzyme of respiratory chains in bacteria and mitochondria. The mechanism which couples spatially separated transfer of electrons to proton translocation in complex I is not known. Here we report five crystal structures of T. thermophilus enzyme in complex with NADH or quinone-like compounds. We also determined cryo-EM structures of major and minor native states of the complex, differing in the position of the peripheral arm. Crystal structures show that binding of quinone-like compounds (but not of NADH) leads to a related global conformational change, accompanied by local re-arrangements propagating from the quinone site to the nearest proton channel. Normal mode and molecular dynamics analyses indicate that these are likely to represent the first steps in the proton translocation mechanism. Our results suggest that quinone binding and chemistry play a key role in the coupling mechanism of complex I.

Complex I (NADH:ubiquinone oxidoreductase) is the first enzyme of the respiratory chain in bacteria and mitochondria. Here, the authors present cryo-EM and crystal structures of T. thermophilus complex I in different conformational states and further analyse them by Normal Mode Analysis and molecular dynamics simulations and conclude that quinone redox reactions are important for the coupling mechanism of complex I.