Structural mechanisms for domain movements in proteins

CryoEM-sampling of metastable conformations appearing in cofactor-ligand association and catalysis of glutamate dehydrogenase

Kinetic aspects of enzymatic reactions are described by equations based on the Michaelis-Menten theory for the initial stage. However, the kinetic parameters provide little information on the atomic mechanism of the reaction. In this study, we analyzed structures of glutamate dehydrogenase in the initial and steady stages of the reaction using cryoEM at near-atomic resolution. In the initial stage, four metastable conformations displayed different domain motions and cofactor/ligand association modes. The most striking finding was that the enzyme-cofactor-substrate complex, treated as a single state in the enzyme kinetic theory, comprised at least three different metastable conformations. In the steady stage, seven conformations, including derivatives from the four conformations in the initial stage, made the reaction pathway complicated. Based on the visualized conformations, we discussed stage-dependent pathways to illustrate the dynamics of the enzyme in action.

Coenzyme-binding pathway on glutamate dehydrogenase suggested from multiple-binding sites visualized by cryo-electron microscopy

The structure of hexameric glutamate dehydrogenase (GDH) in the presence of the coenzyme nicotinamide adenine dinucleotide phosphate (NADP) was visualized using cryogenic transmission electron microscopy to investigate the ligand-binding pathways to the active site of the enzyme. Each subunit of GDH comprises one hexamer-forming core domain and one nucleotide-binding domain (NAD domain), which spontaneously opens and closes the active-site cleft situated between the two domains. In the presence of NADP, the potential map of GDH hexamer, assuming D3 symmetry, was determined at a resolution of 2.4 Å, but the NAD domain was blurred due to the conformational variety. After focused classification with respect to the NAD domain, the potential maps interpreted as NADP molecules appeared at five different sites in the active-site cleft. The subunits associated with NADP molecules were close to one of the four metastable conformations in the unliganded state. Three of the five binding sites suggested a pathway of NADP molecules to approach the active-site cleft for initiating the enzymatic reaction. The other two binding modes may rarely appear in the presence of glutamate, as demonstrated by the reaction kinetics. Based on the visualized structures and the results from the enzymatic kinetics, we discussed the binding modes of NADP to GDH in the absence and presence of glutamate.

Revealing Allosteric Mechanism of Amino Acid Binding Proteins from Open to Closed State

Amino acid binding proteins (AABPs) undergo significant conformational closure in the periplasmic space of Gram-negative bacteria, tightly binding specific amino acid substrates and then initiating transmembrane transport of nutrients. Nevertheless, the possible closure mechanisms after substrate binding, especially long-range signaling, remain unknown. Taking three typical AABPs-glutamine binding protein (GlnBP), histidine binding protein (HisJ) and lysine/arginine/ornithine binding protein (LAOBP) in Escherichia coli (E. coli)-as research subjects, a series of theoretical studies including sequence alignment, Gaussian network model (GNM), anisotropic network model (ANM), conventional molecular dynamics (cMD) and neural relational inference molecular dynamics (NRI-MD) simulations were carried out. Sequence alignment showed that GlnBP, HisJ and LAOBP have high structural similarity. According to the results of the GNM and ANM, AABPs' Index Finger and Thumb domains exhibit closed motion tendencies that contribute to substrate capture and stable binding. Based on cMD trajectories, the Index Finger domain, especially the I-Loop region, exhibits high molecular flexibility, with residues 11 and 117 both being potentially key residues for receptor-ligand recognition and initiation of receptor allostery. Finally, the signaling pathway of AABPs' conformational closure was revealed by NRI-MD training and trajectory reconstruction. This work not only provides a complete picture of AABPs' recognition mechanism and possible conformational closure, but also aids subsequent structure-based design of small-molecule oncology drugs.

Specifying conformational heterogeneity of multi-domain proteins at atomic resolution

The conformational landscape of multi-domain proteins is inherently linked to their specific functions. This also holds for polyubiquitin chains that are assembled by two or more ubiquitin domains connected by a flexible linker thus showing a large interdomain mobility. However, molecular recognition and signal transduction are associated with particular conformational substates that are populated in solution. Here, we apply high-resolution NMR spectroscopy in combination with dual-scale MD simulations to explore the conformational space of K6-, K29-, and K33-linked diubiquitin molecules. The conformational ensembles are evaluated utilizing a paramagnetic cosolute reporting on solvent exposure plus a set of complementary NMR parameters. This approach unravels a conformational heterogeneity of diubiquitins and explains the diversity of structural models that have been determined for K6-, K29-, and K33-linked diubiquitins in free and ligand-bound states so far. We propose a general application of the approach developed here to demystify multi-domain proteins occurring in nature.

Dissecting the Structural Dynamics of Authentic Cholesteryl Ester Transfer Protein for the Discovery of Potential Lead Compounds: A Theoretical Study

Current structural and functional investigations of cholesteryl ester transfer protein (CETP) inhibitor design are nearly entirely based on a fully active mutation (CETPMutant) constructed for protein crystallization, limiting the study of the dynamic structural features of authentic CETP involved in lipid transport under physiological conditions. In this study, we conducted comprehensive molecular dynamics (MD) simulations of both authentic CETP (CETPAuthentic) and CETPMutant. Considering the structural differences between the N- and C-terminal domains of CETPAuthentic and CETPMutant, and their crucial roles in lipid transfer, we identified the two domains as binding pockets of the ligands for virtual screening to discover potential lead compounds targeting CETP. Our results revealed that CETPAuthentic displays greater flexibility and pronounced curvature compared to CETPMutant. Employing virtual screening and MD simulation strategies, we found that ZINC000006242926 has a higher binding affinity for the N- and C-termini, leading to reduced N- and C-opening sizes, disruption of the continuous tunnel, and increased curvature of CETP. In conclusion, CETPAuthentic facilitates the formation of a continuous tunnel in the "neck" region, while CETPMutant does not exhibit such characteristics. The ligand ZINC000006242926 screened for binding to the N- and C-termini induces structural changes in the CETP unfavorable to lipid transport. This study sheds new light on the relationship between the structural and functional mechanisms of CETP. Furthermore, it provides novel ideas for the precise regulation of CETP functions.

Combining Protein Conformational Diversity and Phylogenetic Information Using CoDNaS and CoDNaS-Q

CoDNaS (http://ufq.unq.edu.ar/codnas/) and CoDNaS-Q (http://ufq.unq.edu.ar/codnasq) are repositories of proteins with different degrees of conformational diversity. Following the ensemble nature of the native state, conformational diversity represents the structural differences between the conformers in the ensemble. Each entry in CoDNaS and CoDNaS-Q contains a redundant collection of experimentally determined conformers obtained under different conditions. These conformers represent snapshots of the protein dynamism. While CoDNaS contains examples of conformational diversity at the tertiary level, a recent development, CoDNaS-Q, contains examples at the quaternary level. In the emerging age of accurate protein structure prediction by machine learning approaches, many questions remain open regarding the characterization of protein dynamism. In this context, most bioinformatics resources take advantage of distinct features derived from protein alignments, however, the complexity and heterogeneity of information makes it difficult to recover reliable biological signatures. Here we present five protocols to explore tertiary and quaternary conformational diversity at the individual protein level as well as for the characterization of the distribution of conformational diversity at the protein family level in a phylogenetic context. These protocols can provide curated protein families with experimentally known conformational diversity, facilitating the exploration of sequence determinants of protein dynamism. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Assessing conformational diversity with CoDNaS Alternate Protocol 1: Assessing conformational diversity at the quaternary level with CoDNaS-Q Basic Protocol 2: Exploring conformational diversity in a protein family Alternate Protocol 2: Exploring quaternary conformational diversity in a protein family Basic Protocol 3: Representing conformational diversity in a phylogenetic context.

Comparing the Effect of HPP on the Structure and Stability of Soluble and Membrane-Bound Polyphenol Oxidase from 'Lijiang Snow' Peach: Multispectroscopic and Molecular Dynamics Simulation

Polyphenol oxidase (PPO) easily causes fruits and vegetables to lose their color and nutritional value. As a non-thermal process, high-pressure processing (HPP) showed different inactivation effects on endogenous enzymes. In this work, soluble PPO (sPPO) and membrane-bound PPO (mPPO) from 'Lijiang snow' peaches were purified, and then the effect of high pressure on the conformation of sPPO and mPPO was investigated and compared at the molecular level. The maximum activation of sPPO and mPPO by 11.2% and 4.8% was observed after HPP at 200 MPa, while their activities both gradually decreased at 400 MPa and 600 MPa; in particular, the residual activities of sPPO and mPPO at 600 MPa for 50 min were 41.42% and 72.95%, respectively. The spectroscopic results indicated that the secondary structure of PPOs was little affected by HPP, but HPP led to obvious changes in their tertiary structure. The simulations showed that the decreasing distance between the copper ion and His residue in the copper-binding region of two PPOs at 200 MPa was favorable to catalytic activity, while the increasing distance between copper ions and His residues and the disordered movement of the loop region above 400 MPa were unfavorable. In addition, the structure of sPPO was relatively looser than that of mPPO, and high pressure showed a more significant effect on the conformation of sPPO than that of mPPO. This study clarified the effect of HPP on PPO's structure and the relationship between its structure and activity and provided a basis for the prevention of enzymatic browning.

Sequence and structure alignments in post-AlphaFold era

Sequence alignment is fundamental for analyzing protein structure and function. For all but closely-related proteins, alignments based on structures are more accurate than alignments based purely on amino-acid sequences. However, the disparity between the large amount of sequence data and the relative paucity of experimentally-determined structures has precluded the general applicability of structure alignment. Based on the success of AlphaFold (and its likes) in producing high-quality structure predictions, we suggest that when aligning homologous proteins, lacking experimental structures, better results can be obtained by a structural alignment of predicted structures than by an alignment based only on amino-acid sequences. We present a quantitative evaluation, based on pairwise alignments of sequences and structures (both predicted and experimental) to support this hypothesis.

Ligands-induced open-close conformational change during DapE catalysis: Insights from molecular dynamics simulations

The microbial enzyme DapE plays a critical role in the lysine biosynthetic pathway and is considered as a potentially safe antibiotic target. In this study, atomistic simulations are employed to identify the modes of essential dynamics that define the conformational response of the enzyme to ligand binding and unbinding. The binding modes and the binding affinities of the products to the DapE enzyme are estimated from the MM-PBSA method, and the residues contributing to the ligand binding are identified. Various structural analyses and the principal component analysis of the molecular dynamics trajectories reveal that the removal of products from the active site causes a significant change in the overall enzyme structure. Both Cartesian and dihedral principal component analyses are used to characterize the structural changes in terms of domain unfolding and domain twisting motions. In the most dominant mode, that is, the domain unfolding motion, the two catalytic domains move away from the two dimerization domains of the dimeric enzyme, representing a closed-to-open conformational change. The conformational changes are initiated by the coordinated movement of three loops (Asp75-Pro82, Gly240-Asn244, and Thr347-Glu353) that trigger a domain-level movement. From multiple short trajectories, the time constant associated with the domain opening motion is estimated as 43.6 ns. Physiologically, this close-to-open conformational change is essential for the regeneration of the initial state of the enzyme for the subsequent cycle of catalytic action and provides the apo enzyme enough flexibility for efficient substrate binding.

Probing Conformational Dynamics of Antibodies with Geometric Simulations

This chapter describes the application of constrained geometric simulations for prediction of antibody structural dynamics. We utilize constrained geometric simulations method FRODAN, which is a low computational complexity alternative to molecular dynamics (MD) simulations that can rapidly explore flexible motions in protein structures. FRODAN is highly suited for conformational dynamics analysis of large proteins, complexes, intrinsically disordered proteins, and dynamics that occurs on longer biologically relevant time scales that are normally inaccessible to classical MD simulations. This approach predicts protein dynamics at an all-atom scale while retaining realistic covalent bonding, maintaining dihedral angles in energetically good conformations while avoiding steric clashes in addition to performing other geometric and stereochemical criteria checks. In this chapter, we apply FRODAN to showcase its applicability for probing functionally relevant dynamics of IgG2a, including large-amplitude domain-domain motions and motions of complementarity determining region (CDR) loops. As was suggested in previous experimental studies, our simulations show that antibodies can explore a large range of conformational space.

Finite temperature string method with umbrella sampling using path collective variables: application to secondary structure change in a protein

The transition of an α-helix to a β-sheet in proteins is among the most complex conformational changes seen in biomolecular systems. Due to long time scales involved in the transition, it is challenging to study such protein conformational changes using direct molecular dynamics simulations. This limitation is typically overcome using an indirect approach wherein one computes the free energy landscape associated with the transition. Computation of free energy landscapes, however, requires a suitable set of collective variables that describe the transition. In this work, we demonstrate the use of path collective variables [D. Branduardi, F. L. Gervasio and M. Parrinello, J. Chem. Phys., 2007, 126, 054103] and combine it with the finite temperature string (FTS) method [E. Weinan, W. Ren and E. Vanden-Eijnden, J. Phys. Chem. B, 2005, 109, 6688-6693] to determine the molecular mechanisms involved during the structural transition of the mini G-protein from an α-helix to a β-hairpin. The transition from the α-helix proceeds via unfolding of the terminal residues, giving rise to a β-turn unfolded intermediate to eventually form the β-hairpin. Our proposed algorithm uses umbrella sampling simulations to simulate images along the string and the weighted histogram analysis to compute the free energy along the computed transition path. This work demonstrates that the string method in combination with path collective variables can be exploited to study complex protein conformational changes such as a complete change in the secondary structure.

Impact of protein conformational diversity on AlphaFold predictions

MOTIVATION

After the outstanding breakthrough of AlphaFold in predicting protein 3D models, new questions appeared and remain unanswered. The ensemble nature of proteins, for example, challenges the structural prediction methods because the models should represent a set of conformers instead of single structures. The evolutionary and structural features captured by effective deep learning techniques may unveil the information to generate several diverse conformations from a single sequence. Here, we address the performance of AlphaFold2 predictions obtained through ColabFold under this ensemble paradigm.

RESULTS

Using a curated collection of apo-holo pairs of conformers, we found that AlphaFold2 predicts the holo form of a protein in ∼70% of the cases, being unable to reproduce the observed conformational diversity with the same error for both conformers. More importantly, we found that AlphaFold2's performance worsens with the increasing conformational diversity of the studied protein. This impairment is related to the heterogeneity in the degree of conformational diversity found between different members of the homologous family of the protein under study. Finally, we found that main-chain flexibility associated with apo-holo pairs of conformers negatively correlates with the predicted local model quality score plDDT, indicating that plDDT values in a single 3D model could be used to infer local conformational changes linked to ligand binding transitions.

AVAILABILITY AND IMPLEMENTATION

Data and code used in this manuscript are publicly available at https://gitlab.com/sbgunq/publications/af2confdiv-oct2021.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Positive selection during niche adaptation results in large-scale and irreversible rearrangement of chromosomal gene order in bacteria

Analysis of bacterial genomes shows that, whereas diverse species share many genes in common, their linear order on the chromosome is often not conserved. Whereas rearrangements in gene order could occur by genetic drift, an alternative hypothesis is rearrangement driven by positive selection during niche adaptation (SNAP). Here, we provide the first experimental support for the SNAP hypothesis. We evolved Salmonella to adapt to growth on malate as the sole carbon source and followed the evolutionary trajectories. The initial adaptation to growth in the new environment involved the duplication of 1.66 Mb, corresponding to one-third of the Salmonella chromosome. This duplication is selected to increase the copy number of a single gene, dctA, involved in the uptake of malate. Continuing selection led to the rapid loss or mutation of duplicate genes from either copy of the duplicated region. After 2000 generations, only 31% of the originally duplicated genes remained intact and the gene order within the Salmonella chromosome has been significantly and irreversibly altered. These results experientially validate predictions made by the SNAP hypothesis and show that SNAP can be a strong driving force for rearrangements in chromosomal gene order.

Structure determination of high-energy states in a dynamic protein ensemble

Macromolecular function frequently requires that proteins change conformation into high-energy states^1-4. However, methods for solving the structures of these functionally essential, lowly populated states are lacking. Here we develop a method for high-resolution structure determination of minorly populated states by coupling NMR spectroscopy-derived pseudocontact shifts⁵ (PCSs) with Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion⁶ (PCS-CPMG). Our approach additionally defines the corresponding kinetics and thermodynamics of high-energy excursions, thereby characterizing the entire free-energy landscape. Using a large set of simulated data for adenylate kinase (Adk), calmodulin and Src kinase, we find that high-energy PCSs accurately determine high-energy structures (with a root mean squared deviation of less than 3.5 angström). Applying our methodology to Adk during catalysis, we find that the high-energy excursion involves surprisingly small openings of the AMP and ATP lids. This previously unresolved high-energy structure solves a longstanding controversy about conformational interconversions that are rate-limiting for catalysis. Primed for either substrate binding or product release, the high-energy structure of Adk suggests a two-step mechanism combining conformational selection to this state, followed by an induced-fit step into a fully closed state for catalysis of the phosphoryl-transfer reaction. Unlike other methods for resolving high-energy states, such as cryo-electron microscopy and X-ray crystallography, our solution PCS-CPMG approach excels in cases involving domain rearrangements of smaller systems (less than 60 kDa) and populations as low as 0.5%, and enables the simultaneous determination of protein structure, kinetics and thermodynamics while proteins perform their function.

D3PM: a comprehensive database for protein motions ranging from residue to domain

Background

Knowledge of protein motions is significant to understand its functions. While currently available databases for protein motions are mostly focused on overall domain motions, little attention is paid on local residue motions. Albeit with relatively small scale, the local residue motions, especially those residues in binding pockets, may play crucial roles in protein functioning and ligands binding.

Results

A comprehensive protein motion database, namely D3PM, was constructed in this study to facilitate the analysis of protein motions. The protein motions in the D3PM range from overall structural changes of macromolecule to local flip motions of binding pocket residues. Currently, the D3PM has collected 7679 proteins with overall motions and 3513 proteins with pocket residue motions. The motion patterns are classified into 4 types of overall structural changes and 5 types of pocket residue motions. Impressively, we found that less than 15% of protein pairs have obvious overall conformational adaptations induced by ligand binding, while more than 50% of protein pairs have significant structural changes in ligand binding sites, indicating that ligand-induced conformational changes are drastic and mainly confined around ligand binding sites. Based on the residue preference in binding pocket, we classified amino acids into “pocketphilic” and “pocketphobic” residues, which should be helpful for pocket prediction and drug design.

Conclusion

D3PM is a comprehensive database about protein motions ranging from residue to domain, which should be useful for exploring diverse protein motions and for understanding protein function and drug design. The D3PM is available on www.d3pharma.com/D3PM/index.php.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04595-0.

Structural and dynamic studies of the peptidase domain from Clostridium thermocellum PCAT1

The export of antimicrobial peptides is mediated by diverse mechanisms in bacterial quorum sensing pathways. One such binary system employed by gram-positive bacteria is the PCAT1 ABC transporter coupled to a cysteine protease. The focus of this study is the N-terminal C39 peptidase (PEP) domain from Clostridium thermocellum PCAT1 that processes its natural substrate CtA by cleaving a conserved -GG- motif to separate the cargo from the leader peptide prior to secretion. In this study, we are primarily interested in elucidating the dynamic and structural determinants of CtA binding and how it is coupled to cleavage efficiency in the PCAT1 PEP domain. To this end, we have characterized CtA interactions with PEP domain and PCAT1 transporter in detergent micelles using solution nuclear magnetic resonance spectroscopy. The bound CtA structure revealed the disordered C-terminal cargo peptide is linked by a sterically hindered cleavage site to a helix docked within a hydrophobic cavity in the PEP domain. The wide range of internal motions detected by amide nitrogen (N¹⁵ ) relaxation measurements in the free enzyme and substrate-bound complex suggests the binding site is relatively floppy. This flexibility plays a key role in the structural rearrangement necessary to relax steric inhibition in the bound substrate. In conjunction with previously reported PCAT1 structures, we offer fresh insight into the ATP-mediated association between PEP and transmembrane domains as a putative mechanism to optimize peptide cleavage by regulating the width and flexibility of the enzyme active site.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

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.

Time-resolved X-ray scattering studies of proteins

Time-resolved small- and wide-angle X-ray scattering studies of proteins in solution based on the pump-probe approach unveil structural information from intermediates over a broad range of length and time scales. In spite of the promise of this methodology, only a fraction of the wealth of information encoded in scattering data has been extracted in studies performed thus far. Here, we discuss the methodology, summarize results from recent time-resolved X-ray scattering studies, and examine the potential to extract additional information from these scattering curves.

Decline of protein structure rigidity with interatomic distance

BACKGROUND

Protein structural rigidity was analyzed in a non-redundant ensemble of high-resolution protein crystal structures by means of the Hirshfeld test, according to which the components (uX and uY) of the B-factors of two atoms (X and Y) along the interatomic direction is related to their degree of rigidity: the atoms may move as a rigid body if uX = uY and they cannot if uX ≠ uY.

RESULTS

It was observed that the rigidity degree diminishes if the number of covalent bonds intercalated between the two atoms (d_seq) increases, while it is rather independent on the Euclidean distance between the two atoms (d): for a given value of d_seq, the difference between uX and uY does not depend on d. No additional rigidity decline is observed when d_seq ≥  ~ 30 and this upper limit is very modest, close to 0.015 Å.

CONCLUSIONS

This suggests that protein flexibility is not fully described by B-factors that capture only partially the wide range of distortions that proteins can afford.

The hairpin extension controls solvent access to the chromophore binding pocket in a bacterial phytochrome: a UV-vis absorption spectroscopy study

Solvent access to the protein interior plays an important role in the function of many proteins. Phytochromes contain a specific structural feature, a hairpin extension that appears to relay structural information from the chromophore to the rest of the protein. The extension interacts with amino acids near the chromophore, and hence shields the chromophore from the surrounding solvent. We envision that the detachment of the extension from the protein surface allows solvent exchange reactions in the vicinity of the chromophore. This can facilitate for example, proton transfer processes between solvent and the protein interior. To test this hypothesis, the kinetics of the protonation state of the biliverdin chromophore from Deinococcus radiodurans bacteriophytchrome, and thus, the pH of the surrounding solution, is determined. The observed absorbance changes are related to the solvent access of the chromophore binding pocket, gated by the hairpin extension. We therefore propose a model with an "open" (solvent-exposed, deprotonation-active on a (sub)second time-scale) state and a "closed" (solvent-gated, deprotonation inactive) state, where the hairpin fluctuates slowly between these conformations thereby controlling the deprotonation process of the chromophore on a minute time scale. When the connection between the hairpin and the biliverdin surroundings is destabilized by a point mutation, the amplitude of the deprotonation phase increases considerably. In the absence of the extension, the chromophore deprotonates essentially without any "gating". Hence, we introduce a straightforward method to study the stability and fluctuation of the phytochrome hairpin in its photostationary state. This approach can be extended to other chromophore-protein systems where absorption changes reflect dynamic processes of the protein.

Dimensional reduction in complex living systems: Where, why, and how

The unprecedented prowess of measurement techniques provides a detailed, multi-scale look into the depths of living systems. Understanding these avalanches of high-dimensional data-by distilling underlying principles and mechanisms-necessitates dimensional reduction. We propose that living systems achieve exquisite dimensional reduction, originating from their capacity to learn, through evolution and phenotypic plasticity, the relevant aspects of a non-random, smooth physical reality. We explain how geometric insights by mathematicians allow one to identify these genuine hallmarks of life and distinguish them from universal properties of generic data sets. We illustrate these principles in a concrete example of protein evolution, suggesting a simple general recipe that can be applied to understand other biological systems.

"Protein" no longer means what it used to

Every biologist knows that the word protein describes a group of macromolecules essential to sustain life on Earth. As biologists, we are invariably trained under a protein paradigm established since the early twentieth century. However, in recent years, the term protein unveiled itself as an euphemism to describe the overwhelming heterogeneity of these compounds. Most of our current studies are targeted on carefully selected subsets of proteins, but we tend to think and write about these as representative of the whole population. Here we discuss how seeking for universal definitions and general rules in any arbitrarily segmented study would be misleading about the conclusions. Of course, it is not our purpose to discourage the use of the word protein. Instead, we suggest to embrace the extended universe of proteins to reach a deeper understanding of their full potential, realizing that the term encompasses a group of molecules very heterogeneous in terms of size, shape, chemistry and functions, i.e. the term protein no longer means what it used to.

Structural Analysis of a Genetically Encoded FRET Biosensor by SAXS and MD Simulations

Inspired by the modular architecture of natural signaling proteins, ligand binding proteins are equipped with two fluorescent proteins (FPs) in order to obtain Förster resonance energy transfer (FRET)-based biosensors. Here, we investigated a glucose sensor where the donor and acceptor FPs were attached to a glucose binding protein using a variety of different linker sequences. For three resulting sensor constructs the corresponding glucose induced conformational changes were measured by small angle X-ray scattering (SAXS) and compared to recently published single molecule FRET results (Höfig et al., ACS Sensors, 2018). For one construct which exhibits a high change in energy transfer and a large change of the radius of gyration upon ligand binding, we performed coarse-grained molecular dynamics simulations for the ligand-free and the ligand-bound state. Our analysis indicates that a carefully designed attachment of the donor FP is crucial for the proper transfer of the glucose induced conformational change of the glucose binding protein into a well pronounced FRET signal change as measured in this sensor construct. Since the other FP (acceptor) does not experience such a glucose induced alteration, it becomes apparent that only one of the FPs needs to have a well-adjusted attachment to the glucose binding protein.

Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins

Large-scale conformational transitions in multi-domain proteins are often essential for their functions. To investigate the transitions, it is necessary to explore multiple potential pathways, which involve different intermediate structures. Here, we present a multi-basin (MB) coarse-grained (CG) structure-based Go̅ model for describing transitions in proteins with more than two moving domains. This model is an extension of our dual-basin Go̅ model in which system-dependent parameters are determined systematically using the multistate Bennett acceptance ratio method. In the MB Go̅ model for multi-domain proteins, we assume that intermediate structures may have partial inter-domain native contacts. This approach allows us to search multiple transition pathways that involve distinct intermediate structures using the CG molecular dynamics (MD) simulations. We apply this scheme to an enzyme, adenylate kinase (AdK), which has three major domains and can move along two different pathways. Using the optimized mixing parameters for each pathway, AdK shows frequent transitions between the Open, Closed, and the intermediate basins and samples a wide variety of conformations within each basin. The explored multiple transition pathways could be compared with experimental data and examined in more detail by atomistic MD simulations.

Transient kinetic studies of the antiviral Drosophila Dicer-2 reveal roles of ATP in self-nonself discrimination

Some RIG-I-like receptors (RLRs) discriminate viral and cellular dsRNA by their termini, and Drosophila melanogaster Dicer-2 (dmDcr-2) differentially processes dsRNA with blunt or 2 nucleotide 3’-overhanging termini. We investigated the transient kinetic mechanism of the dmDcr-2 reaction using a rapid reaction stopped-flow technique and time-resolved fluorescence spectroscopy. Indeed, we found that ATP binding to dmDcr-2’s helicase domain impacts association and dissociation kinetics of dsRNA in a termini-dependent manner, revealing termini-dependent discrimination of dsRNA on a biologically relevant time scale (seconds). ATP hydrolysis promotes transient unwinding of dsRNA termini followed by slow rewinding, and directional translocation of the enzyme to the cleavage site. Time-resolved fluorescence anisotropy reveals a nucleotide-dependent modulation in conformational fluctuations (nanoseconds) of the helicase and Platform–PAZ domains that is correlated with termini-dependent dsRNA cleavage. Our study offers a kinetic framework for comparison to other Dicers, as well as all members of the RLRs involved in innate immunity.

A graph-based algorithm for detecting rigid domains in protein structures

Background

Conformational transitions are implicated in the biological function of many proteins. Structural changes in proteins can be described approximately as the relative movement of rigid domains against each other. Despite previous efforts, there is a need to develop new domain segmentation algorithms that are capable of analysing the entire structure database efficiently and do not require the choice of protein-dependent tuning parameters such as the number of rigid domains.

Results

We develop a graph-based method for detecting rigid domains in proteins. Structural information from multiple conformational states is represented by a graph whose nodes correspond to amino acids. Graph clustering algorithms allow us to reduce the graph and run the Viterbi algorithm on the associated line graph to obtain a segmentation of the input structures into rigid domains. In contrast to many alternative methods, our approach does not require knowledge about the number of rigid domains. Moreover, we identified default values for the algorithmic parameters that are suitable for a large number of conformational ensembles. We test our algorithm on examples from the DynDom database and illustrate our method on various challenging systems whose structural transitions have been studied extensively.

Conclusions

The results strongly suggest that our graph-based algorithm forms a novel framework to characterize structural transitions in proteins via detecting their rigid domains. The web server is available at http://azifi.tz.agrar.uni-goettingen.de/webservice/.

Edge expansion parallel cascade selection molecular dynamics simulation for investigating large-amplitude collective motions of proteins

We propose edge expansion parallel cascade selection molecular dynamics (eePaCS-MD) as an efficient adaptive conformational sampling method to investigate the large-amplitude motions of proteins without prior knowledge of the conformational transitions. In this method, multiple independent MD simulations are iteratively conducted from initial structures randomly selected from the vertices of a multi-dimensional principal component subspace. This subspace is defined by an ensemble of protein conformations sampled during previous cycles of eePaCS-MD. The edges and vertices of the conformational subspace are determined by solving the "convex hull problem." The sampling efficiency of eePaCS-MD is achieved by intensively repeating MD simulations from the vertex structures, which increases the probability of rare event occurrence to explore new large-amplitude collective motions. The conformational sampling efficiency of eePaCS-MD was assessed by investigating the open-close transitions of glutamine binding protein, maltose/maltodextrin binding protein, and adenylate kinase and comparing the results to those obtained using related methods. In all cases, the open-close transitions were simulated in ∼10 ns of simulation time or less, offering 1-3 orders of magnitude shorter simulation time compared to conventional MD. Furthermore, we show that the combination of eePaCS-MD and accelerated MD can further enhance conformational sampling efficiency, which reduced the total computational cost of observing the open-close transitions by at most 36%.

Ligand-induced structural changes analysis of ribose-binding protein as studied by molecular dynamics simulations

BACKGROUND

The ribose-binding protein (RBP) from Escherichia coli is one of the representative structures of periplasmic binding proteins. Binding of ribose at the cleft between two domains causes a conformational change corresponding to a closure of two domains around the ligand. The RBP has been crystallized in the open and closed conformations.

OBJECTIVE

With the complex trajectory as a control, our goal was to study the conformation changes induced by the detachment of the ligand, and the results have been revealed from two computational tools, MD simulations and elastic network models.

METHODS

Molecular dynamics (MD) simulations were performed to study the conformation changes of RBP starting from the open-apo, closed-holo and closed-apo conformations.

RESULTS

The evolution of the domain opening angle θ clearly indicates large structural changes. The simulations indicate that the closed states in the absence of ribose are inclined to transition to the open states and that ribose-free RBP exists in a wide range of conformations. The first three dominant principal motions derived from the closed-apo trajectories, consisting of rotating, bending and twisting motions, account for the major rearrangement of the domains from the closed to the open conformation.

CONCLUSIONS

The motions showed a strong one-to-one correspondence with the slowest modes from our previous study of RBP with the anisotropic network model (ANM). The results obtained for RBP contribute to the generalization of robustness for protein domain motion studies using either the ANM or PCA for trajectories obtained from MD.

Exploring Large Domain Motions in Proteins Using Atomistic Molecular Dynamics with Enhanced Conformational Sampling

Conformational transitions in multidomain proteins are essential for biological functions. The Apo conformations are typically open and flexible, while the Holo states form more compact conformations stabilized by protein-ligand interactions. Unfortunately, the atomically detailed mechanisms for such open-closed conformational changes are difficult to be accessed experimentally as well as computationally. To simulate the transitions using atomistic molecular dynamics (MD) simulations, efficient conformational sampling algorithms are required. In this work, we propose a new approach based on generalized replica-exchange with solute tempering (gREST) for exploring the open-closed conformational changes in multidomain proteins. Wherein, selected surface charged residues in a target protein are defined as the solute region in gREST simulation and the solute temperatures are different in replicas and exchanged between them to enhance the domain motions. This approach is called gREST selected surface charged residues (gREST_SSCR) and is applied to the Apo and Holo states of ribose binding protein (RBP) in solution. The conformational spaces sampled with gREST_SSCR are much wider than those with the conventional MD, sampling open-closed conformational changes while maintaining RBP domains’ stability. The free-energy landscapes of RBP in the Apo and Holo states are drawn along with twist and hinge angles of the two moving domains. The inter-domain salt-bridges that are not observed in the experimental structures are also important in the intermediate states during the conformational changes.

Evolution of Protein Structure and Stability in Global Warming

This review focuses on the molecular signatures of protein structures in relation to evolution and survival in global warming. It is based on the premise that the power of evolutionary selection may lead to thermotolerant organisms that will repopulate the planet and continue life in general, but perhaps with different kinds of flora and fauna. Our focus is on molecular mechanisms, whereby known examples of thermoresistance and their physicochemical characteristics were noted. A comparison of interactions of diverse residues in proteins from thermophilic and mesophilic organisms, as well as reverse genetic studies, revealed a set of imprecise molecular signatures that pointed to major roles of hydrophobicity, solvent accessibility, disulfide bonds, hydrogen bonds, ionic and π-electron interactions, and an overall condensed packing of the higher-order structure, especially in the hydrophobic regions. Regardless of mutations, specialized protein chaperones may play a cardinal role. In evolutionary terms, thermoresistance to global warming will likely occur in stepwise mutational changes, conforming to the molecular signatures, such that each "intermediate" fits a temporary niche through punctuated equilibrium, while maintaining protein functionality. Finally, the population response of different species to global warming may vary substantially, and, as such, some may evolve while others will undergo catastrophic mass extinction.

Sequence-Based Prediction of Metamorphic Behavior in Proteins

An increasing number of proteins have been demonstrated in recent years to adopt multiple three-dimensional folds with different functions. These metamorphic proteins are characterized by having two or more folds with significant differences in their secondary structure, in which each fold is stabilized by a distinct local environment. So far, ∼90 metamorphic proteins have been identified in the Protein Databank, but we and others hypothesize that a far greater number of metamorphic proteins remain undiscovered. In this work, we introduce a computational model to predict metamorphic behavior in proteins using only knowledge of the sequence. In this model, secondary structure prediction programs are used to calculate diversity indices, which are measures of uncertainty in predicted secondary structure at each position in the sequence; these are then used to assign protein sequences as likely to be metamorphic versus monomorphic (i.e., having just one fold). We constructed a reference data set to train our classification method, which includes a novel compilation of 136 likely monomorphic proteins and a set of 201 metamorphic protein structures taken from the literature. Our model is able to classify proteins as metamorphic versus monomorphic with a Matthews correlation coefficient of ∼0.36 and true positive/true negative rates of ∼65%/80%, suggesting that it is possible to predict metamorphic behavior in proteins using only sequence information.

Molecular modeling and simulation study of homoserine kinase as an effective leishmanial drug target

Leishmaniasis is a tropical neglected disease that imposes major health concerns in many endemic countries worldwide and requires urgent attention to the identification of new drug targets as well as drug candidates. In the current study, we propose homoserine kinase (HSK) inhibition as a strategy to induce pathogen mortality via generating threonine deficiency. We introduce a homology-based molecular model of leishmanial HSK that appears to possess all conserved structural as well as functional features in the GHMP kinase family. Furthermore, 200 ns molecular dynamics data of the enzyme in open and closed state attempts to provide the mechanistic details involved in the substrate as well as phosphate binding to this enzyme. We discuss the structural and functional significance of movements involved in various loops (motif 1, 2, 3) and lips (upper and lower) in the transition of leishmanial HSK from closed to open state. Virtual screening data of more than 40,000 compounds from the present investigation tries to identify a few potential HSK inhibitors that possess important features to act as efficient HSK inhibitors. These compounds can be considered an effective starting point for the identification of novel drug-like scaffolds. We hope the structural wealth that is offered in this report will be utilized in designing competent experimental and therapeutic interventions for leishmaniasis management. Graphical abstract.

Evidence of combined effect of amino acid substitutions within G-H and B-C loops of VP1 conferring serological heterogeneity in foot-and-mouth disease virus serotype A

Foot-and-mouth disease virus (FMDV) serotype A exhibits a higher degree of genetic and antigenic diversity resulting in frequent vaccine failure due to serological mismatch between the vaccine and heterologous strains. Currently, knowledge on the molecular basis of antigenic relationships among the FMDVs is limited; nevertheless, intratype antigenic variation due to mutation(s) is widely considered as the main hurdle to appropriate FMD vaccine development. Here, we studied genetic and antigenic variations of four FMDV serotype A isolates, BAN/GA/Sa-197/2013 (BAN-197), BAN/CH/Sa-304/2016 (BAN-304), BAN/DH/Sa-307/2016 (BAN-307) and BAN/DH/Sa-310/2017 (BAN-310) circulating in Bangladesh during 2013-2017. Initially, antigenic relationships (r₁ -values) of the field isolates were evaluated by the two-dimensional microneutralization test (2D-MNT) using the hyperimmune antisera raised in cattle against the vaccine strain, BAN-304. Interesingly, the results showed protective serological cross-reactivity (r₁ -values > 0.4) between the vaccine strain and the field isolates, BAN-307 and BAN-310, except BAN-197 that substantially mismatched (r₁  = 0.129 ± 0.043) with the BAN-304. Although VP1-based phylogeny grouped all the isolates within the same sublineage C (a subgroup of VP3^Δ59 variant) under the lineage A/ASIA/G-VII, strikingly, computational analyses of the viral capsid proteins demonstrated significant deviation at the VP1 G-H loop of BAN-197 from the vaccine strain, while VP(2-4) of both isolates were structurally conserved. To bridge the gap of how the distortion of the G-H loop and consequent antigenic hetergeneity occurred in BAN-197, we performed in silico combinatorial substitutions of the VP1 mutant amino acids (aa) of BAN-197 with the respective residues in BAN-304. Remarkably, our analyses revealed that two substitutions of distantly located aa at B-C (T48I:threonine → isoleucine) and G-H (A143V:alanine → valine) loops, in combination, distorted the VP1 G-H loop. Overall, this work contributes to understanding the molecular basis of antigenic relationships operating in serotype A FMDVs and the selection of suitable vaccine strain(s) for effective prophylaxis of FMD based on VP1-based analyses.

Cytoskeletal Drugs Modulate Off-Target Protein Folding Landscapes Inside Cells

The dynamic cytoskeletal network of microtubules and actin filaments can be disassembled by drugs. Cytoskeletal drugs work by perturbing the monomer-polymer equilibrium, thus changing the size and number of macromolecular crowders inside cells. Changes in both crowding and nonspecific surface interactions ("sticking") following cytoskeleton disassembly can affect the protein stability, structure, and function directly or indirectly by changing the fluidity of the cytoplasm and altering the crowding and sticking of other macromolecules in the cytoplasm. The effect of cytoskeleton disassembly on protein energy landscapes inside cells has yet to be observed. Here we have measured the effect of several cytoskeletal drugs on the folding energy landscape of two FRET-labeled proteins with different in vitro sensitivities to macromolecular crowding. Phosphoglycerate kinase (PGK) was previously shown to be more sensitive to crowding, whereas variable major protein-like sequence expressed (VlsE) was previously shown to be more sensitive to sticking. The in-cell effects of drugs that depolymerize either actin filaments (cytochalasin D and latrunculin B) or microtubules (nocodazole and vinblastine) were compared. The crowding sensor protein CrH2-FRET verified that cytoskeletal drugs decrease the extent of crowding inside cells despite also reducing the overall cell volume. The decreased compactness and folding stability of PGK could be explained by the decreased extent of crowding induced by these drugs. VlsE's opposite response to the drugs shows that depolymerization of the cytoskeleton also changes sticking in the cellular milieu. Our results demonstrate that perturbation of the monomer-polymer cytoskeletal equilibrium, for example, during natural cell migration or stresses from drug treatment, has off-target effects on the energy landscapes of proteins in the cell.

The crystal structures of Thermus thermophilus CMP kinase complexed with a phosphoryl group acceptor and donor

Nucleoside monophosphate kinases play crucial roles in biosynthesis and regeneration of nucleotides. These are bi-substrate enzymes that catalyze reversible transfers of a phosphoryl group between ATP and nucleoside monophosphate. These enzymes are comprised of the CORE domain, the NMP-binding domain, and the LID domain. Large conformational rearrangement of the three domains occurs during the catalytic cycle. Although many structures of CMP kinase have been determined, only limited structural information has been available on the conformational changes along the reaction pathway. We determined five crystal structures of CMP kinase of Thermus thermophilus HB8 in ligand-free form and the CMP "open", CMP "closed", ADP-CDP-Gd3+-, and CDP-bound forms at resolutions of 1.7, 2.2, 1.5, 1.6, and 1.7 Å, respectively. The ligand-free form was in an open conformation, whereas the structures of the CMP "closed", ADP-CDP-Gd3+-, and CDP-bound forms were in a closed conformation, in which the shift of the NMP-binding domain and LID domain caused closure of the substrate-binding cleft. Interestingly, the CMP "open" form was in an open conformation even with CMP bound, implying intrinsic conformational fluctuation. The structure of the ADP-CDP complex is the first structure of CMP kinase with a phosphoryl group donor and an acceptor. Upon simultaneous binding of ADP and CDP, the side chains of several residues in the LID domain moved toward the nucleotides without global open-closed conformational changes compared to those in the CMP "closed" and CDP complexes. These global and local conformational changes may be crucial for the substrate recognition and catalysis. The terminal phosphate groups of ADP and CDP had similar geometry to those of two ADP in AMP kinase, suggesting common catalytic mechanisms to other nucleoside monophosphate kinases. Our findings are expected to contribute to detailed understanding of the reaction mechanism of CMP kinase.

Investigation of sequence features of hinge-bending regions in proteins with domain movements using kernel logistic regression

Background

Hinge-bending movements in proteins comprising two or more domains form a large class of functional movements. Hinge-bending regions demarcate protein domains and collectively control the domain movement. Consequently, the ability to recognise sequence features of hinge-bending regions and to be able to predict them from sequence alone would benefit various areas of protein research. For example, an understanding of how the sequence features of these regions relate to dynamic properties in multi-domain proteins would aid in the rational design of linkers in therapeutic fusion proteins.

Results

The DynDom database of protein domain movements comprises sequences annotated to indicate whether the amino acid residue is located within a hinge-bending region or within an intradomain region. Using statistical methods and Kernel Logistic Regression (KLR) models, this data was used to determine sequence features that favour or disfavour hinge-bending regions. This is a difficult classification problem as the number of negative cases (intradomain residues) is much larger than the number of positive cases (hinge residues). The statistical methods and the KLR models both show that cysteine has the lowest propensity for hinge-bending regions and proline has the highest, even though it is the most rigid amino acid. As hinge-bending regions have been previously shown to occur frequently at the terminal regions of the secondary structures, the propensity for proline at these regions is likely due to its tendency to break secondary structures. The KLR models also indicate that isoleucine may act as a domain-capping residue. We have found that a quadratic KLR model outperforms a linear KLR model and that improvement in performance occurs up to very long window lengths (eighty residues) indicating long-range correlations.

Conclusion

In contrast to the only other approach that focused solely on interdomain hinge-bending regions, the method provides a modest and statistically significant improvement over a random classifier. An explanation of the KLR results is that in the prediction of hinge-bending regions a long-range correlation is at play between a small number amino acids that either favour or disfavour hinge-bending regions. The resulting sequence-based prediction tool, HingeSeek, is available to run through a webserver at hingeseek.cmp.uea.ac.uk.

Shear viscosity of two-state enzyme solutions

We discuss the shear viscosity of a Newtonian solution of catalytic enzymes and substrate molecules. The enzyme is modeled as a two-state dimer consisting of two spherical domains connected with an elastic spring. The enzymatic conformational dynamics is induced by the substrate binding and such a process is represented by an additional elastic spring. Employing the Boltzmann distribution weighted by the waiting times of enzymatic species in each catalytic cycle, we obtain the shear viscosity of dilute enzyme solutions as a function of substrate concentration and its physical properties. The substrate affinity distinguishes between fast and slow enzymes, and the corresponding viscosity expressions are obtained. Furthermore, we connect the obtained viscosity with the diffusion coefficient of a tracer particle in enzyme solutions.

Energy landscape of domain motion in glutamate dehydrogenase deduced from cryo-electron microscopy

Analysis of the conformational changes of protein is important to elucidate the mechanisms of protein motions correlating with their function. Here, we studied the spontaneous domain motion of unliganded glutamate dehydrogenase from Thermococcus profundus using cryo-electron microscopy and proposed a novel method to construct free-energy landscape of protein conformations. Each subunit of the homo-hexameric enzyme comprises nucleotide-binding domain (NAD domain) and hexamer-forming core domain. A large active-site cleft is situated between the two domains and varies from open to close according to the motion of a NAD domain. A three-dimensional map reconstructed from all cryo-electron microscopy images displayed disordered volumes of NAD domains, suggesting that NAD domains in the collected images adopted various conformations in domain motion. Focused classifications on NAD domain of subunits provided several maps of possible conformations in domain motion. To deduce what kinds of conformations appeared in EM images, we developed a novel analysis method that describe the EM maps as a linear combination of representative conformations appearing in a 200-ns molecular dynamics simulation as reference. The analysis enabled us to estimate the appearance frequencies of the representative conformations, which illustrated a free-energy landscape in domain motion. In the open/close domain motion, two free-energy basins hindered the direct transformation from open to closed state. Structure models constructed for representative EM maps in classifications demonstrated the correlation between the energy landscape and conformations in domain motion. Based on the results, the domain motion in glutamate dehydrogenase and the analysis method to visualize conformational changes and free-energy landscape were discussed. DATABASE: The EM maps of the four conformations were deposited to Electron Microscopy Data Bank (EMDB) as accession codes EMD-9845 (open), EMD-9846 (half-open1), EMD-9847 (half-open2), and EMD-9848 (closed), respectively. In addition, the structural models built for the four conformations were deposited to the Protein Data Bank (PDB) as accession codes 6JN9 (open), 6JNA (half-open1), 6JNC (half-open2), and 6JND (closed), respectively.

Mechanics of Allostery: Contrasting the Induced Fit and Population Shift Scenarios

In allosteric proteins, binding a ligand can affect function at a distant location, for example, by changing the binding affinity of a substrate at the active site. The induced fit and population shift models, which differ by the assumed number of stable configurations, explain such cooperative binding from a thermodynamic viewpoint. Yet, understanding what mechanical principles constrain these models remains a challenge. Here, we provide an empirical study on 34 proteins supporting the idea that allosteric conformational change generally occurs along a soft elastic mode presenting extended regions of high shear. We argue, based on a detailed analysis of how the energy profile along such a mode depends on binding, that in the induced fit scenario, there is an optimal stiffness ka∗ ∼ 1/N for cooperative binding, where N is the number of residues. We find that the population shift scenario is more robust to mutations affecting stiffness because binding becomes more and more cooperative with stiffness up to the same characteristic value ka∗, beyond which cooperativity saturates instead of decaying. We numerically confirm these findings in a nonlinear mechanical model. Dynamical considerations suggest that a stiffness of order ka∗ is favorable in that scenario as well, supporting that for proper function, proteins must evolve a functional elastic mode that is softer as their size increases. In consistency with this view, we find a fair anticorrelation between the stiffness of the allosteric response and protein size in our data set.

Patch-DCA: improved protein interface prediction by utilizing structural information and clustering DCA scores

Motivation

Over the past decade, there have been impressive advances in determining the 3D structures of protein complexes. However, there are still many complexes with unknown structures, even when the structures of the individual proteins are known. The advent of protein sequence information provides an opportunity to leverage evolutionary information to enhance the accuracy of protein–protein interface prediction. To this end, several statistical and machine learning methods have been proposed. In particular, direct coupling analysis has recently emerged as a promising approach for identification of protein contact maps from sequential information. However, the ability of these methods to detect protein–protein inter-residue contacts remains relatively limited.

Results

In this work, we propose a method to integrate sequential and co-evolution information with structural and functional information to increase the performance of protein–protein interface prediction. Further, we present a post-processing clustering method that improves the average relative F1 score by 70% and 24% and the average relative precision by 80% and 36% in comparison with two state-of-the-art methods, PSICOV and GREMLIN.

Availability and implementation

https://github.com/BioMLBoston/PatchDCA

Supplementary information

Supplementary data are available at Bioinformatics online.

NMR Analysis of Apo Glutamine-Binding Protein Exposes Challenges in the Study of Interdomain Dynamics

Glutamine-binding protein (GlnBP) displays an apo, "open" and a holo, "closed" crystal form, mutually related by a rigid-body reorientation of its domains. A fundamental question about such large-scale conformational transitions, whether the closed state exists in the absence of ligand, is controversial in the case of GlnBP. NMR observations have indicated no evidence of the closed form, whereas experimentally validated computations have suggested a remarkable ca. 40 % population. Herein, a paramagnetic NMR strategy designed to detect the putative apo-closed species shows that a major population of the latter is highly improbable. Further, NMR residual dipolar couplings collected under three anisotropic conditions do not reveal differential domain alignment and establish that the average solution conformation is satisfied by the apo-open crystal structure. Our results indicate that the computational prediction of large-scale interdomain motions is not trivial and may lead to erroneous conclusions without proper experimental validation.

Crystal structure of the Fab region of a neutralizing antibody against granulocyte-macrophage colony-stimulating factor

An increased level of granulocyte-macrophage colony-stimulating factor has a potential role in the development of autoimmune diseases, and the neutralization of its activity by monoclonal antibodies is a promising therapy for some diseases. Here, the crystal structure of the Fab region of EV1007, a fully human antibody expressed in Chinese hamster ovary cells that was developed from human peripheral blood mononuclear cells, is described. The structure closely resembles that of MB007, which is the Fab region of the same antibody expressed in Escherichia coli [Blech et al. (2012), Biochem. J. 447, 205-215], except at the hinge regions between the immunoglobulin domains and the H3 loop region. This paper presents evidence for the flexibility of the hinge and H3 loop regions of the antibody based on the comparison of two independently solved crystal structures.

Structural variations within proteins can be as large as variations observed across their homologues

Understanding the structural plasticity of proteins is key to understanding the intricacies of their functions and mechanistic basis. In the current study, we analyzed the available multiple crystal structures of the same protein for the structural differences. For this purpose we used an abstraction of protein structures referred as Protein Blocks (PBs) that was previously established. We also characterized the nature of the structural variations for a few proteins using molecular dynamics simulations. In both the cases, the structural variations were summarized in the form of substitution matrices of PBs. We show that certain conformational states are preferably replaced by other specific conformational states. Interestingly, these structural variations are highly similar to those previously observed across structures of homologous proteins (r² = 0.923) or across the ensemble of conformations from NMR data (r² = 0.919). Thus our study quantitatively shows that overall trends of structural changes in a given protein are nearly identical to the trends of structural differences that occur in the topologically equivalent positions in homologous proteins. Specific case studies are used to illustrate the nature of these structural variations.

Principles for Optimal Cooperativity in Allosteric Materials

Allosteric proteins transmit a mechanical signal induced by binding a ligand. However, understanding the nature of the information transmitted and the architectures optimizing such transmission remains a challenge. Here we show, using an in silico evolution scheme and theoretical arguments, that architectures optimized to be cooperative, which efficiently propagate energy, qualitatively differ from previously investigated materials optimized to propagate strain. Although we observe a large diversity of functioning cooperative architectures (including shear, hinge, and twist designs), they all obey the same principle of displaying a mechanism, i.e., an extended soft mode. We show that its optimal frequency decreases with the spatial extension L of the system as L^-d/2, where d is the spatial dimension. For these optimal designs, cooperativity decays logarithmically with L for d = 2 and does not decay for d = 3. Overall, our approach leads to a natural explanation for several observations in allosteric proteins and indicates an experimental path to test if allosteric proteins lie close to optimality.

Comparative dynamics of tropomyosin in vertebrates and invertebrates

Tropomyosin (Tpm) is an extended α-helical coiled-coil homodimer that regulates actinomyosin interactions in muscle. Molecular simulations of four Tpms, two from the vertebrate class Mammalia (rat and pig), and two from the invertebrate class Malacostraca (shrimp and lobster), showed that despite extensive sequence and structural homology across metazoans, dynamic behavior-particularly long-range structural fluctuations-were clearly distinct. Vertebrate Tpms were more flexible and sampled complex, multi-state conformational landscapes. Invertebrate Tpms were more rigid, sampling a highly constrained harmonic landscape. Filtering of trajectories by principle component analysis into essential subspaces showed significant overlap within but not between phyla. In vertebrate Tpms, hinge-regions decoupled long-range interhelical motions and suggested distinct domains. In contrast, crustacean Tpms did not exhibit long-range dynamic correlations-behaving more like a single rigid rod on the nanosecond time scale. These observations suggest there may be divergent mechanisms for Tpm binding to actin filaments, where conformational flexibility in mammalian Tpm allows a preorganized shape complementary to the filament surface, and where rigidity in the crustacean Tpm requires concerted bending and binding.

Structure, interactions and self-assembly of ASC-dependent inflammasomes

The inflammasome is a multi-protein platform that assembles upon the presence of cues derived from infection or tissue damage, and triggers the inflammatory response. Inflammasome components include sensor proteins that detect danger signals, procaspase 1 and the adapter ASC (apoptosis-associated speck-like protein containing a CARD) tethering these molecules together. Upon inflammasome assembly, procaspase 1 self-activates and renders functional cytokines to arbitrate in the defense mechanism. This assembly is mediated by self-association and protein interactions via Death Domains. The inflammasome plays a critical role in innate immunity and its dysregulation is the culprit of many autoimmune disorders. An in-depth understanding of the factors involved in inflammasome assembly could help fight these conditions. This review describes our current knowledge on the biophysical aspects of inflammasome formation from the perspective of ASC. The specific characteristics of the three-dimensional solution structure and interdomain dynamics of ASC are explained in relation to its function in inflammasome assembly. Additionally, the review elaborates on the identification of ASC interacting surfaces at the amino acid level using NMR techniques. Finally, the macrostructures formed by full-length ASC and its two Death Domains studied with Transmission Electron Microscopy are compared in the context of a directional model for inflammasome assembly.