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Kinesin-mediated transport along microtubules is critical for axon development and health. Mutations in the kinesin Kif21a, or the microtubule subunit β-tubulin, inhibit axon growth and/or maintenance resulting in the eye-movement disorder congenital fibrosis of the extraocular muscles (CFEOM). While most examined CFEOM-causing β-tubulin mutations inhibit kinesin-microtubule interactions, Kif21a mutations activate the motor protein. These contrasting observations have led to opposed models of inhibited or hyperactive Kif21a in CFEOM. We show that, contrary to other CFEOM-causing β-tubulin mutations, R380C enhances kinesin activity. Expression of β-tubulin-R380C increases kinesin-mediated peroxisome transport in S2 cells. The binding frequency, percent motile engagements, run length and plus-end dwell time of Kif21a are also elevated on β-tubulin-R380C compared to wildtype microtubules in vitro. This conserved effect persists across tubulins from multiple species and kinesins from different families. The enhanced activity is independent of tail-mediated kinesin auto-inhibition and thus utilizes a mechanism distinct from CFEOM-causing Kif21a mutations. Using molecular dynamics, we visualize how β-tubulin-R380C allosterically alters critical structural elements within the kinesin motor domain, suggesting a basis for the enhanced motility. These findings resolve the disparate models and confirm that inhibited or increased kinesin activity can both contribute to CFEOM. They also demonstrate the microtubule's role in regulating kinesin and highlight the importance of balanced transport for cellular and organismal health.Movie S1Movie S1Longitudinal ‘rocking’ of kinesin represented by the first normal mode of non‐rigid body motion. The kinesin motor domain is shown in grey, α‐tubulin subunit in tan, and β‐tubulin in gold. The amplitude of movement is arbitrarily set to clearly depict the direction of kinesin movement relative to the underlying microtubule.Movie S2Movie S2Lateral ‘tilting’ of kinesin represented by the second normal mode of non‐rigid body motion. The kinesin motor domain is shown in grey, α‐tubulin subunit in tan, and β‐tubulin in gold. The amplitude of movement is arbitrarily set to clearly depict the direction of kinesin movement relative to the underlying microtubule.Movie S3Movie S3Rotational ‘twisting’ of kinesin represented by the third normal mode of non‐rigid body motion. The kinesin motor domain is shown in grey, α‐tubulin subunit in tan, and β‐tubulin in gold. The amplitude of movement is arbitrarily set to clearly depict the direction of kinesin movement relative to the underlying microtubule.Movie S4Movie S4Lateral ‘tilting’ of the core kinesin motor domain and helix α4 relative to the underlying tubulin. View is longitudinal along microtubule protofilament. Kinesin motor domain is shown in grey, helix α4 residues 246‐270 highlighted in red, α‐tubulin subunit in tan, and β‐tubulin in gold. The amplitude of movement is arbitrarily set to clearly depict the direction of kinesin movement relative to the underlying microtubule.

Protein functional mechanisms usually require conformational changes, and often there are known structures for the different conformational states. However, usually neither the origin of the driving force nor the underlying pathways for these conformational transitions is known. Exothermic chemical reactions may be an important source of forces that drive conformational changes. Here we investigate this type of force originating from ATP hydrolysis in the chaperonin GroEL, by applying forces originating from the chemical reaction. Specifically, we apply directed forces to drive the GroEL conformational changes and learn that there is a highly specific direction for applied forces to drive the closed form to the open form. For this purpose, we utilize coarse-grained elastic network models. Principal component analysis on 38 GroEL experimental structures yields the most important motions, and these are used in structural interpolation for the construction of a coarse-grained free energy landscape. In addition, we investigate a more random application of forces with a Monte Carlo method and demonstrate pathways for the closed-open conformational transition in both directions by computing trajectories that are shown upon the free energy landscape. Initial root mean square deviation (RMSD) between the open and closed forms of the subunit is 14.7 Å and final forms from our simulations reach an average RMSD of 3.6 Å from the target forms, closely matching the level of resolution of the coarse-grained model.

The sequence correlations within a protein multiple sequence alignment are routinely being used to predict contacts within its structure, but here we point out that these data can also be used to predict a protein’s dynamics directly. The elastic network protein dynamics models rely directly upon the contacts, and the normal modes of motion are obtained from the decomposition of the inverse of the contact map. To make the direct connection between sequence and dynamics, it is necessary to apply coarse-graining to the structure at the level of one point per amino acid, which has often been done, and protein coarse-grained dynamics from elastic network models has been highly successful, particularly in representing the large-scale motions of proteins that usually relate closely to their functions. The interesting implication of this is that it is not necessary to know the structure itself to obtain its dynamics and instead to use the sequence information directly to obtain the dynamics.

Cadherin intermolecular interactions are critical for cell-cell adhesion and play essential roles in tissue formation and the maintenance of tissue structures. In this study, we focus on E-cadherin, a classical cadherin that connects epithelial cells, to understand how they interact in cisand transconformations when attached to the same cell or opposing cells. We employ coevolutionary sequence analysis and molecular dynamics simulations to confirm previously known interaction sites as well as to identify new interaction sites. The sequence coevolutionary results yield a surprising result indicating that there are no strongly favored intermolecular interaction sites, which is unusual and suggests that many interaction sites may be possible, with none being strongly preferred over others. By using molecular dynamics, we test the persistence of these interactions and how they facilitate adhesion. We build several types of cadherin assemblages, with different numbers and combinations of cisand transinterfaces to understand how these conformations act to facilitate adhesion. Our results suggest that, in addition to the established interaction sites on the EC1 and EC2 domains, an additional plausible cisinterface at the EC3-EC5 domain exists. Furthermore, we identify specific mutations at cis/transbinding sites that impair adhesion within E-cadherin assemblages.

ABSTRACTAvian pathogenic Escherichia coli(APEC) strains cause one of the three most significant infectious diseases in the poultry industry and are also potential food-borne pathogens threating human health. In this study, we showed that ArcA (aerobic respiratory control), a global regulator important for E. coli's adaptation from anaerobic to aerobic conditions and control of that bacterium's enzymatic defenses against reactive oxygen species (ROS), is involved in the virulence of APEC. Deletion of arcAsignificantly attenuates the virulence of APEC in the duck model. Transcriptome sequencing (RNA-Seq) analyses comparing the APEC wild type and the arcAmutant indicate that ArcA regulates the expression of 129 genes, including genes involved in citrate transport and metabolism, flagellum synthesis, and chemotaxis. Further investigations revealed that citCEFXGcontributed to APEC's microaerobic growth at the lag and log phases when cultured in duck serum and that ArcA played a dual role in the control of citrate metabolism and transportation. In addition, deletion of flagellar genes motAand motBand chemotaxis gene cheAsignificantly attenuated the virulence of APEC, and ArcA was shown to directly regulate the expression of motA, motB, and cheA. The combined results indicate that ArcA controls metabolism, chemotaxis, and motility contributing to the pathogenicity of APEC.

The apparent motions of experimentally determined RNA structures point to a relatively limited set of motions that are captured by a small set of principal components (PCs). These limited motions closely resemble the motions computed with a small number of low frequency normal modes from elastic network models (ENMs), either at atomic or coarse-grained resolution. The loss of dynamical information upon coarse-graining is somewhat larger for RNAs than for globular proteins, but RNA structures show less sensitivity to the elastic network model parameters than do proteins.

Flexibility and dynamics of protein structures are reflected in the B-factors and order parameters obtained experimentally with X-ray crystallography and Nuclear Magnetic Resonance (NMR). Methods such as Normal Mode Analysis (NMA) and Elastic Network Models (ENM) can be used to predict the fluctuations of protein structures for either atomic level or coarse-grained structures. Here, we introduce the Local-Distance Matrix Error (DME), an efficient and simple analytic method to study the fluctuations of protein structures, especially for the ensembles of NMR-determined protein structures. Comparisons with the fluctuations obtained by experiments and other by computations show strong correlations.

We approximate the loop motions of various proteins by using a coarse-grained model and the theory of rubberlike elasticity of polymer chains. The loops are considered as chains where only the first and the last residues thereof are tethered by their connections to the main structure, while, within the loop, the loop residues are connected only to their sequence neighbors. We applied these approximate models to five proteins. Our approximation shows that the loop motions can usually be computed locally which shows these motions are robust and not random. But most interestingly, the new method presented here can be used to compute the likely motions of loops that are missing in the structures.

The mixed-resolution elastic network model was introduced previously for computing the motions of a structure, which is described at different levels of detail in different parts, for example, with atomistic and residue-level regions. This method has proved to be an efficient tool to explore the collective dynamics of proteins with some atomistic details, which would be difficult to obtain with either conventional full-atom approaches or fully coarse-grained models. Understanding function often requires atomic detail, but not necessarily for the entire structure. In this study, the calculation of the interaction forces between different resolution regions for the hierarchical levels of coarse-graining is further elaborated on in the new approach by considering explicitly the atomic contacts in the crystal structure. The collective dynamics of the enzyme triosephosphate isomerase and its active site together with loop 6 motions are considered in detail. The supramolecular assemblage ribosome and local atomic motions in its “interesting” functional part—the decoding center—are investigated for the low frequency range of the spectrum with high computational efficiency. This new atom-based mixed coarse-graining approach can be effectively used to generate realistic high-resolution conformations of extremely large protein-DNA or RNA complexes by performing energy minimization on structures deformed along the normal modes of the elastic network model. The new model permits focusing on specific functional parts that move in coordination and response to the remainder of the entire structure.

Due to insufficient experimental restraints, a biologically critical loop region in PrPc (residues 167-171), which is a potential binding site for Protein X, is under-determined in most mammalian species. Here, we show that by adding information about distance constraints derived from a database of high-resolution protein structures, this under-determined loop as well as other secondary structural elements of the E200K variant of Human Prion Protein (hPrPc), a disease-related isoform, can be refined into more realistic structures in the structural ensemble with improved quality and increased accuracy. In particular, the ensemble becomes more compact after the refinement and the percentage of residues in the most favourable region of the Ramachandran diagram is increased to about 90% in the refined structures from the 80% to 85% range in the previously reported structures.

Escherichia colirequires an efficient transport and signaling system to successfully sequester iron from its environment. FecA, a TonB-dependent protein, serves a critical role in this process: first, it binds and transports iron in the form of ferric citrate, and second, it initiates a signaling cascade that results in the transcription of several iron transporter genes in interaction with inner membrane proteins. The structure of the plug and barrel domains and the periplasmic N-terminal domain (NTD) are separately available. However, the linker connecting the plug and barrel and the NTD domains is highly mobile, which may prevent the determination of the FecA structure as a whole assembly. Here, we reduce the conformation space of this linker into most probable structural models using the modeling tool CABS, then apply normal-mode analysis to investigate the motions of the whole structure of FecA by using elastic network models. We relate the FecA domain motions to the outer-inner membrane communication, which initiates transcription. We observe that the global motions of FecA assign flexibility to the TonB box and the NTD, and control the exposure of the TonB box for binding to the TonB inner membrane protein, suggesting how these motions relate to FecA function. Our simulations suggest the presence of a communication between the loops on both ends of the protein, a signaling mechanism by which a signal could be transmitted by conformational transitions in response to the binding of ferric citrate.

In this article, we apply a coarse-grained elastic network model (ENM) to study conformational transitions to address the following questions: How well can a conformational change be predicted by the mode motions? Is there a way to improve the model to gain better results? To answer these questions, we use a dataset of 170 pairs having “open” and “closed” structures from Gerstein's protein motion database. Our results show that the conformational transitions fall into three categories: 1), the transitions of these proteins that can be explained well by ENM; 2), the transitions that are not explained well by ENM, but the results are significantly improved after considering the rigidity of some residue clusters and modeling them accordingly; and 3), the intrinsic nature of these transitions, specifically the low degree of collectivity, prevents their conformational changes from being represented well with the low frequency modes of any elastic network models. Our results thus indicate that the applicability of ENM for explaining conformational changes is not limited by the size of the studied protein or even the scale of the conformational change. Instead, it depends strongly on how collective the transition is.

RNA-protein interactions are vitally important in a wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses. We have developed a computational tool for predicting which amino acids of an RNA binding protein participate in RNA-protein interactions, using only the protein sequence as input. RNABindR was developed using machine learning on a validated nonredundant data set of interfaces from known RNA-protein complexes in the Protein Data Bank. It generates a classifier that captures primary sequence signals sufficient for predicting which amino acids in a given protein are located in the RNA-protein interface. In leave-one-out cross-validation experiments, RNABindR identifies interface residues with >85% overall accuracy. It can be calibrated by the user to obtain either high specificity or high sensitivity for interface residues. RNABindR, implementing a Naive Bayes classifier, performs as well as a more complex neural network classifier (to our knowledge, the only previously published sequence-based method for RNA binding site prediction) and offers the advantages of speed, simplicity and interpretability of results. RNABindR predictions on the human telomerase protein hTERT are in good agreement with experimental data. The availability of computational tools for predicting which residues in an RNA binding protein are likely to contact RNA should facilitate design of experiments to directly test RNA binding function and contribute to our understanding of the diversity, mechanisms, and regulation of RNA-protein complexes in biological systems. (RNABindR is available as a Web tool from http://bindr.gdcb.iastate.edu.).

A general method is presented that allows the separation of the rigid body motions from the nonrigid body motions of structural subunits when bound in a complex. The application presented considers the motions of the tRNAs: free, bound to the ribosome and to a synthase. We observe that both the rigid body and nonrigid body motions of the structural subunits are highly controlled by the large ribosomal assembly and are important for the functional motions of the assembly. For the intact ribosome, its major parts, the 30S and the 50S subunits, are found to have counterrotational motions in the first few slowest modes, which are consistent with the experimentally observed ratchet motion. The tRNAs are found to have on average ∼72–75% rigid body motions and principally translational motions within the first 100 slow modes of the complex. Although the three tRNAs exhibit different apparent total motions, after the rigid body motions are removed, the remaining internal motions of all three tRNAs are essentially the same. The direction of the translational motions of the tRNAs are in the same direction as the requisite translocation step, especially in the first slowest mode. Surprisingly the small intrinsically flexible mRNA has all of its internal motions completely inhibited and shows mainly a rigid-body translation in the slow modes of the ribosome complex. On the other hand, the required nonrigid body motions of the tRNA during translocation reveal that the anticodon-stem-loop, as well as the acceptor arm, of the tRNA enjoy a large mobility but act as rigid structural units. In summary, the ribosome exerts its control by enforcing rigidity in the functional parts of the tRNAs as well as in the mRNA.

We present a rigid-body-based technique (called rigid-cluster elastic network interpolation) to generate feasible transition pathways between two distinct conformations of a macromolecular assembly. Many biological molecules and assemblies consist of domains which act more or less as rigid bodies during large conformational changes. These collective motions are thought to be strongly related with the functions of a system. This fact encourages us to simply model a macromolecule or assembly as a set of rigid bodies which are interconnected with distance constraints. In previous articles, we developed coarse-grained elastic network interpolation (ENI) in which, for example, only Cα atoms are selected as representatives in each residue of a protein. We interpolate distance differences of two conformations in ENI by using a simple quadratic cost function, and the feasible conformations are generated without steric conflicts. Rigid-cluster interpolation is an extension of the ENI method with rigid-clusters replacing point masses. Now the intermediate conformations in an anharmonic pathway can be determined by the translational and rotational displacements of large clusters in such a way that distance constraints are observed. We present the derivation of the rigid-cluster model and apply it to a variety of macromolecular assemblies. Rigid-cluster ENI is then modified for a hybrid model represented by a mixture of rigid clusters and point masses. Simulation results show that both rigid-cluster and hybrid ENI methods generate sterically feasible pathways of large systems in a very short time. For example, the HK97 virus capsid is an icosahedral symmetric assembly composed of 60 identical asymmetric units. Its original Hessian matrix size for a Cα coarse-grained model is >(300,000)2. However, it reduces to (84)2 when we apply the rigid-cluster model with icosahedral symmetry constraints. The computational cost of the interpolation no longer scales heavily with the size of structures; instead, it depends strongly on the minimal number of rigid clusters into which the system can be decomposed.

Domain swapping is a structural phenomenon that plays an important role in the mechanism of oligomerization of some proteins. The monomer units in the oligomeric structure become entangled with each other. Here we investigate the mechanism of domain swapping in diphtheria toxin and the structural criteria required for it to occur by analyzing the slower modes of motion with elastic network models, Gaussian network model and anisotropic network model. We take diphtheria toxin as a representative of this class of domain-swapped proteins and show that the domain, which is being swapped in the dimeric state, rotates and twists, in going from the “open” to the “closed” state, about a hinge axis that passes through the middle of the loop extending between two domains. A combination of the intra- and intermolecular contacts of the dimer is almost equivalent to that of the monomer, which shows that the relative orientations of the residues in both forms are almost identical. This is also reflected in the calculated B-factors when compared with the experimentally determined B-factors in x-ray crystal structures. The slowest modes of both the monomer and dimer show a common hinge centered on residue 387. The differences in distances between the monomer and the dimer also shows the hinge at nearly the same location (residue 381). Finally, the first three dominant modes of anisotropic network model together shows a twisting motion about the hinge centered on residue 387. We further identify the location of hinges for a set of another 12 domain swapped proteins and give the quantitative measures of the motions of the swapped domains toward their “closed” state, i.e., the overlap and correlation between vectors.

We show that long- and short-range interactions in almost all protein native structures are actually consistent with each other for coarse-grained energy scales; specifically we mean the long-range inter-residue contact energies and the short-range secondary structure energies based on peptide dihedral angles, which are potentials of mean force evaluated from residue distributions observed in protein native structures. This consistency is observed at equilibrium in sequence space rather than in conformational space. Statistical ensembles of sequences are generated by exchanging residues for each of 797 protein native structures with the Metropolis method. It is shown that adding the other category of interaction to either the short- or long-range interactions decreases the means and variances of those energies for essentially all protein native structures, indicating that both interactions consistently work by more-or-less restricting sequence spaces available to one of the interactions. In addition to this consistency, independence by these interaction classes is also indicated by the fact that there are almost no correlations between them when equilibrated using both interactions and significant but small, positive correlations at equilibrium using only one of the interactions. Evidence is provided that protein native sequences can be regarded approximately as samples from the statistical ensembles of sequences with these energy scales and that all proteins have the same effective conformational temperature. Designing protein structures and sequences to be consistent and minimally frustrated among the various interactions is a most effective way to increase protein stability and foldability. Proteins 2003;50:35–43. © 2002 Wiley-Liss, Inc.

We develop a computationally efficient method to simulate the transition of a protein between two conformations. Our method is based on a coarse-grained elastic network model in which distances between spatially proximal amino acids are interpolated between the values specified by the two end conformations. The computational speed of this method depends strongly on the choice of cutoff distance used to define interactions as measured by the density of entries of the constant linking/contact matrix. To circumvent this problem we introduce the concept of using a cutoff based on a maximum number of nearest neighbors. This generates linking matrices that are both sparse and uniform, hence allowing for efficient computations that are independent of the arbitrariness of cutoff distance choices. Simulation results demonstrate that the method developed here reliably generates feasible intermediate conformations, because our method observes steric constraints and produces monotonic changes in virtual bond and torsion angles. Applications are readily made to large proteins, and we demonstrate our method on lactate dehydrogenase, citrate synthase, and lactoferrin. We also illustrate how this framework can be used to complement experimental techniques that partially observe protein motions.

Microtubules (MT), along with a variety of associated motor proteins, are involved in a range of cellular functions including vesicle movement, chromosome segregation, and cell motility. MTs are assemblies of heterodimeric proteins, αβ-tubulins, the structure of which has been determined by electron crystallography of zinc-induced, pacilitaxel-stabilized tubulin sheets. These data provide a basis for examining relationships between structural features and protein function. Here, we study the fluctuation dynamics of the tubulin dimer with the aim of elucidating its functional motions relevant to substrate binding, polymerization/depolymerization and MT assembly. A coarse-grained model, harmonically constrained according to the crystal structure, is used to explore the global dynamics of the dimer. Our results identify six regions of collective motion, comprised of structurally close but discontinuous sequence fragments, observed only in the dimeric form, dimerization being a prerequisite for domain identification. Boundaries between regions of collective motions appear to act as linkages, found primarily within secondary-structure elements that lack sequence conservation, but are located at minima in the fluctuation curve, at positions of hydrophobic residues. Residue fluctuations within these domains identify the most mobile regions as loops involved in recognition of the adjacent regions. The least mobile regions are associated with nucleotide binding sites where lethal mutations occur. The functional coupling of motions between and within regions identifies three global motions: torsional and wobbling movements, en bloc, between the α- and β-tubulin monomers, and stretching longitudinally. Further analysis finds the antitumor drug pacilitaxel (TaxotereR) to reduce flexibility in the M loop of the β-tubulin monomer; an effect that may contribute to tightening lateral interactions between protofilaments assembled into MTs. Our analysis provides insights into relationships between intramolecular tubulin movements of MT organization and function.

Elastic network models have been successful in elucidating the largest scale collective motions of proteins. These models are based on a set of highly coupled springs, where only the close neighboring amino acids interact, without any residue specificity. Our objective here is to determine whether the equivalent cooperative motions can be obtained upon further coarse‐graining of the protein structure along the backbone. The influenza virus hemagglutinin A (HA), composed of N=1509 residues, is utilized for this analysis. Elastic network model calculations are performed for coarse‐grained HA structures containing only N/2, N/10, N/20, and N/40 residues along the backbone. High correlations (>0.95) between residue fluctuations are obtained for the first dominant (slowest) mode of motion between the original model and the coarse‐grained models. In the case of coarse‐graining by a factor of 1/40, the slowest mode shape for HA is reconstructed for all residues by successively selecting different subsets of residues, shifting one residue at a time. The correlation for this reconstructed first mode shape with the original all‐residue case is 0.73, while the computational time is reduced by about three orders of magnitude. The reduction in computational time will be much more significant for larger targeted structures. Thus, the dominant motions of protein structures are robust enough to be captured at extremely high levels of coarse‐graining. And more importantly, the dynamics of extremely large complexes are now accessible with this new methodology. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 119–127, 2002

Coarse-grained protein structures have the unusual property of manifesting a greater regularity than is evident when all atoms are considered. Here, we follow proteins at the level of one point per residue. We confirm that lattices with large coordination numbers provide better fits to protein structures. But, underlying these protein structures, there is an intrinsic geometry that closely resembles the face-centered-cubic (fcc) lattice, in so far as the coordination angles observed in clusters of near neighboring residues are concerned. While the fcc lattice has 12 neighbors, the coordination number about any given residue in a protein is usually smaller; however, the neighbors are not distributed in a uniform, less dense way, but rather in a clustered dense way, occupying positions closely approximating those of a distorted fcc packing. This packing geometry is a direct manifestation of the hydrophobic effect. Surprisingly, specific residues are clustered with similar angular geometry, whether on the interior or on the exterior of a protein.

The fluctuations and important motions of three large proteins—hemaglutinin, xanthine dehydrogenase, and β-galactosidase—have been considered with a range of models having various levels of detail to represent the structures. Because the slowest modes of motion are the largest contributors to the total motions, and because these motions depend mainly on the shapes of the structures rather than their details, it is possible to replace the real structures with significantly fewer points and still retain the essential features of the structure for these modes of motion. We obtain excellent results, both for the magnitudes of the individual motions as well as for the molecular changes occurring during these motions. Similar results are obtained with another completely different approach where the coarse graining is based on invariant regions of structure found by comparing two structures of the same protein, given as an example here for myosin. Results confirm the important coupling of local functional motions with the large-scale motions, implying important functional roles for the entire protein structure. © 2002 Wiley Periodicals, Inc. Int J Quantum Chem, 2002

We examine how effectively simple potential functions previously developed can identify compatibilities between sequences and structures of proteins for database searches. The potential function consists of pairwise contact energies, repulsive packing potentials of residues for overly dense arrangement and short-range potentials for secondary structures, all of which were estimated from statistical preferences observed in known protein structures. Each potential energy term was modified to represent compatibilities between sequences and structures for globular proteins. Pairwise contact interactions in a sequence–structure alignment are evaluated in a mean field approximation on the basis of probabilities of site pairs to be aligned. Gap penalties are assumed to be proportional to the number of contacts at each residue position, and as a result gaps will be more frequently placed on protein surfaces than in cores. In addition to minimum energy alignments, we use probability alignments made by successively aligning site pairs in order by pairwise alignment probabilities. The results show that the present energy function and alignment method can detect well both folds compatible with a given sequence and, inversely, sequences compatible with a given fold, and yield mostly similar alignments for these two types of sequence and structure pairs. Probability alignments consisting of most reliable site pairs only can yield extremely small root mean square deviations, and including less reliable pairs increases the deviations. Also, it is observed that secondary structure potentials are usefully complementary to yield improved alignments with this method. Remarkably, by this method some individual sequence–structure pairs are detected having only 5–20% sequence identity.

Pairwise contact energies for 20 types of residues are estimated self‐consistently from the actual observed frequencies of contacts with regression coefficients that are obtained by comparing “input” and predicted values with the Bethe approximation for the equilibrium mixtures of residues interacting. This is premised on the fact that correlations between the “input” and the predicted values are sufficiently high although the regression coefficients themselves can depend to some extent on protein structures as well as interaction strengths. Residue coordination numbers are optimized to obtain the best correlation between “input” and predicted values for the partition energies. The contact energies self‐consistently estimated this way indicate that the partition energies predicted with the Bethe approximation should be reduced by a factor of about 0.3 and the intrinsic pairwise energies by a factor of about 0.6. The observed distribution of contacts can be approximated with a small relative error of only about 0.08 as an equilibrium mixture of residues, if many proteins were employed to collect more than 20,000 contacts. Including repulsive packing interactions and secondary structure interactions further reduces the relative errors. These new contact energies are demonstrated by threading to have improved their ability to discriminate native structures from other non‐native folds. Proteins 1999;34:49–68. © 1999 Wiley‐Liss, Inc.

In order to study the inferences of structure for mechanism, the collective motions of the retroviral reverse transcriptase HIV-1 RT (RT) are examined using the Gaussian network model (GNM) of proteins. This model is particularly suitable for elucidating the global dynamic characteristics of large proteins such as the presently investigated heterodimeric RT comprising a total of 982 residues. Local packing density and coordination order of amino acid residues is inspected by the GNM to determine the type and range of motions, both at the residue level and on a global scale, such as the correlated movements of entire subdomains. Of the two subunits, p66 and p51, forming the RT, only p66 has a DNA-binding cleft and a functional polymerase active site. This difference in the structure of the two subunits is shown here to be reflected in their dynamic characteristics: only p66 has the potential to undergo large-scale cooperative motions in the heterodimer, while p51 is essentially rigid. Taken together, the global motion of the RT heterodimer is comprised of movements of the p66 thumb subdomain perpendicular to those of the p66 fingers, accompanied by anticorrelated fluctuations of the RNase H domain and p51 thumb, thus providing information about the details of one processivity mechanism. A few clusters of residues, generally distant in sequence but close in space, are identified in the p66 palm and connection subdomains, which form the hinge-bending regions that control the highly concerted motion of the subdomains. These regions include the catalytically active site and the non-nucleoside inhibitor binding pocket of p66 polymerase, as well as sites whose mutations have been shown to impair enzyme activity. It is easily conceivable that this hinge region, indicated by GNM analysis to play a critical role in modulating the global motion, is locked into an inactive conformation upon binding of an inhibitor. Comparative analysis of the dynamic characteristics of the unliganded and liganded dimers indicates severe repression of the mobility of the p66 thumb in RT's global mode, upon binding of non-nucleoside inhibitors.

Short‐range interactions for secondary structures of proteins are evaluated as potentials of mean force from the observed frequencies of secondary structures in known protein structures which are assumed to have an equilibrium distribution with the Boltzmann factor of secondary structure energies. A secondary conformation at each residue position in a protein is described by a tripeptide, including one nearest neighbor on each side. The secondary structure potentials are approximated as additive contributions from neighboring residues along the sequence. These are part of an empirical potential to provide a crude estimate of protein conformational energy at a residue level. Unlike previous works, interactions are decoupled into intrinsic potentials of residues, potentials of backbone‐backbone interactions, and of side chain‐backbone interactions. Also interactions are decoupled into one‐body, two‐body, and higher order interactions between peptide backbone and side chain and between backbones. These decouplings are essential to correctly evaluate the total secondary structure energy of a protein structure without overcounting interactions. Each interaction potential is evaluated separately by taking account of the correlation in the amino acid order of protein sequences. Interactions among side chains are neglected, because of the relatively limited number of protein structures. Proteins 1999;36:347–356. Published 1999 Wiley‐Liss, Inc.

We consider modifications of an empirical energy potential for fold and sequence recognition to represent approximately the stabilities of proteins in various environments. A potential used here includes a secondary structure potential representing short‐range interactions for secondary structures of proteins, and a tertiary structure potential consisting of a long‐range, pairwise contact potential and a repulsive packing potential. This potential is devised to evaluate together the total conformational energy of a protein at the coarse grained residue level. It was previously estimated from the observed frequencies of secondary structures, from contact frequencies between residues, and from the distributions of the number of residues in contact in known protein structures by regarding those distributions as the equilibrium distributions with the Boltzmann factor of these interaction energies. The stability of native structures is assumed as a primary requirement for proteins to fold into their native structures. A collapse energy is subtracted from the contact energies to remove the protein size dependence and to represent protein stabilities for monomeric and multimeric states. The free energy of the whole ensemble of protein conformations that is subtracted from the conformational energy to represent protein stability is approximated as the average energy expected for a typical native structure with the same amino acid composition. This term may be constant in fold recognition but essentially varies in sequence recognition. A simple test of threading sequences into structures without gaps is employed to demonstrate the importance of the present modifications that permit the same potential to be utilized for both fold and sequence recognition. Proteins 1999;36:357–369. Published 1999 Wiley‐Liss, Inc.

Knowledge of amino acid composition, alone, is verified here to be sufficient for recognizing the structural class, α, β, α+β, or α/β of a given protein with an accuracy of 81%. This is supported by results from exhaustive enumerations of all conformations for all sequences of simple, compact lattice models consisting of two types (hydrophobic and polar) of residues. Different compositions exhibit strong affinities for certain folds. Within the limits of validity of the lattice models, two factors appear to determine the choice of particular folds: 1) the coordination numbers of individual sites and 2) the size and geometry of non-bonded clusters. These two properties, collectively termed the distribution of non-bonded contacts, are quantitatively assessed by an eigenvalue analysis of the so-called Kirchhoff or adjacency matrices obtained by considering the non-bonded interactions on a lattice. The analysis permits the identification of conformations that possess the same distribution of non-bonded contacts. Furthermore, some distributions of non-bonded contacts are favored entropically, due to their high degeneracies. Thus, a competition between enthalpic and entropic effects is effective in determining the choice of a distribution for a given composition. Based on these findings, an analysis of non-bonded contacts in protein structures was made. The analysis shows that proteins belonging to the four distinct folding classes exhibit significant differences in their distributions of non-bonded contacts, which more directly explains the success in predicting structural class from amino acid composition. Proteins 29:172–185, 1997. Published 1997 Wiley-Liss, Inc.This article is a US Goverment work and, as such, is in the public domain in the United States of America.

The concept of CH…O hydrogen bonds has recently gained much interest, with a number of reports indicating the significance of these non-classical hydrogen bonds in stabilizing nucleic acid and protein structures. Here, we analyze the CH…O interactions in the protein-DNA interface, based on 43 crystal structures of protein-DNA complexes. Surprisingly, we find that the number of close intermolecular CH…O contacts involving the thymine methyl group and position C5 of cytosine is comparable to the number of protein-DNA hydrogen bonds involving nitrogen and oxygen atoms as donors and acceptors. A comprehensive analysis of the geometries of these close contacts shows that they are similar to other CH…O interactions found in proteins and small molecules, as well as to classical NH…O hydrogen bonds. Thus, we suggest that C5 of cytosine and C5-Met of thymine form relatively weak CH…O hydrogen bonds with Asp, Asn, Glu, Gln, Ser, and Thr, contributing to the specificity of recognition. Including these interactions, in addition to the classical protein-DNA hydrogen bonds, enables the extraction of simple structural principles for amino acid-base recognition consistent with electrostatic considerations.

Matrix-generator and Monte Carlo methods have been employed to study the influence of thermal fluctuations on the overall sizes and shapes of curved pieces of DNA. The DNA model involves the independent angular parameters relating successive base-pair steps: the sequence-dependent equilibrium values and fluctuations of the twist, tilt, and roll angles. The curved sequence under study is the (A₅X₅)_n repeating polymer, the AA and XX steps having different equilibrium roll and twist values. Both planar circles and superhelices are analysed. Detailed comparison is made between the rigorous statistical mechanical representation of the DNA and simplified static models currently used in the literature. That is, a more realistic "flexible wedge" model is contrasted with the existing "static wedge" model of DNA curvature, which is demonstrated to be inadequate. The size of the coils is described by the unperturbed root-mean-square end-to-end distance and the shape by a ratio of the principal moments of the radius of gyration. The moment ratios indicate that when DNA is relatively short (e.g. its length is shorter than half a turn of the static superhelix), the flexible chains are more "short and thick" than the static structure. The end-to-end distances, however, are practically the same in the two models. For longer DNA fragments, the flexible chain is more extended in terms of the end-to-end distance and more globular in terms of the moment ratio. Thus, fluctuations "blur" the curvature of longer DNA fragments compared with static models. Furthermore, the overall average shape of slightly curved DNA subject to natural bending and twisting fluctuations is essentially indistinguishable from that of the corresponding "straight" DNA. Such configurational similarities are apparently responsible for the relative insensitivity of the polyacrylamide gel matrix to small degrees of DNA curvature. These findings raise serious questions regarding the quantitative estimation of wedge angles in DNA from electrophoretic experiments, based on static models. Comparison between planar circles and superhelices shows that when fluctuations are considered, the flexible circles are more spherical than the superhelices. The results imply that when DNA bending is exactly "in phase" with the helical repeat (i.e. when the DNA loop is exactly planar at 0 K), the DNA coil is packed more tightly than when bending and twisting are "out of phase" (and a superhelix is formed at 0 K). This finding is consistent with polyacrylamide gel electrophoresis data testifying to an increase in DNA retardation when twisting is more precisely "tuned". Finally, it is found that asymmetry of bending in the roll co-ordinate can produce significant macroscopic curvature of DNA. "Skewed" bending of AA steps in the A₅X₅ polymer is indistinguishable from symmetric bending with the same mean value and fluctuation of roll. Asymmetric rolling in the AA dimer thus can introduce substantial curvature in DNAs containing A_n · T_n blocks, even if the lowest energy stacked arrangement of AA base-pair steps is nearly flat, thereby resolving apparent contradictions between the crystallographic and solution structures of chains containing A_n · T_n tracts. Copyright 1993, 1999 Academic Press

A three-stranded DNA that is a putative intermediate of homologous recombination is a novel DNA triplex,R-form DNA. InR- form DNA the third strand includes both purines and pyrimidines and is parallel to the identical strand of the duplex. To text and refine our previously proposedR-form base triplets we have used two approaches: (1) dimethyl sulfate protection ofR-form DNA; and (2) thermal dissociation ofR-form DNAs in which the duplex strands were substituted in a strand-specific manner with either 7-deaza-guanine or 7-deaza-adenine. Together, the footprinting and isosteric substitution results demonstrate that the third strand inR-form DNA is in contact with the purines in the N7position in the major groove of the Watson–Crick duplex in three ((GC):G, (AT):A and (TA):T out of the four possile triplets. Furthermore, these reults suggest that the N7positions of the duplex play a significant role in stabilizing the DNA–DNA contacts during the homology recognition process.

Here we study the pattern of amino acid pair interchanges at spatially, locally conserved regions in globally dissimilar and unrelated proteins. By using a method which completely separates the amino acid sequence from its respective structure, this work addresses the question of which properties of the amino acids are the most crucial for the stability of conserved structural motifs. The proteins are taken from a structurally non-redundant dataset. The spatially conserved substructural motifs are defined as consisting of a "large enough" number ofC^αatoms found to provide a geometric match between two proteins, regardless of the order of theC^αatoms in the sequence, or of the sequence composition of the substructures. This approach can apply to proteins with little or no sequence similarity but with sufficient structural similarity, and is unique in its ability to handle local, non-topological matches between pairs of dissimilar proteins. The method uses a computer-vision based algorithm, the Geometric Hashing. Since the Geometric Hashing ignores sequence information it lends itself to answer the question posed above. The interchanges at geometrically similar positions that have been obtained with our method demonstrate the expected behaviour. Yet, a closer inspection reveals some distinct characteristics, as compared with interchanges based upon sequence-order based techniques, or from energy-contact-based considerations. First, a pronounced division of the amino acids into two classes is displayed: Lys, Glu, Arg, Gln, Asp, Asn, Pro, Gly, Thr, Ser and His on the one hand, and Ile, Val, Leu, Phe, Met, Tyr, Trp, Cys and Ala on the other. These groups further cluster into subgroups: Lys, Glu, Arg, Gln; Asp Asn; Pro, Gly; Ile, Val, Leu, Phe. The other amino acids stand alone. Analysis of the conservation among amino acids indicates proline to be consistently, by far, the most conserved. Next are Asp, Glu, Lys and Gly. Cys is also highly conserved. Interestingly, oppositely charged amino acids are interchanged roughly as frequently as those of the same charge. These observations can be explained in terms of the three- dimensional structures of the proteins. Most of all, there is a clear distinction between residues which prefer to be on the protein surfaces, compared to those frequently buried in the interiors. Analysis of the interchanges indicates their low information content. This, together with the separation into two groups, suggests that the predictive value of the spatial positions of theC^αatoms is not much greater than the sequence alone, aside from their hydrophobicity/hydrophillicity classification.

The vibrational dynamics of transfer RNAs, both free, and complexed with the cognate synthetase, are analyzed using a model (Gaussian network model) which recently proved to satisfactorily describe the collective motions of folded proteins. The approach is similar to a normal mode analysis, with the major simplification that no residue specificity is taken into consideration, which permits us (i) to cast the problem into an analytical form applicable to biomolecular systems including about 103residues, and (ii) to acquire information on the essential dynamics of such large systems within computational times at least two orders of magnitude shorter than conventional simulations. On a local scale, the fluctuations calculated for yeast tRNAPheand tRNAAspin the free state, and for tRNAGlncomplexed with glutaminyl-tRNA synthetase (GlnRS) are in good agreement with the corresponding crystallographic Bfactors. On a global scale, a hinge-bending region comprising nucleotides U8 to C12 in the D arm, G20 to G22 in the D loop, and m7G46 to C48 in the variable loop (for tRNAPhe), is identified in the free tRNA, conforming with previous observations. The two regions subject to the largest amplitude anticorrelated fluctuations in the free form, i.e. the anticodon region and the acceptor arm are, at the same time, the regions that experience the most severe suppression in their flexibilities upon binding to synthetase, suggesting that their sampling of the conformational space facilitates their recognition by the synthetase. Likewise, examination of the global mode of motion of GlnRS in the complex indicates that residues 40 to 45, 260 to 270, 306 to 314, 320 to 327 and 478 to 485, all of which cluster near the ATP binding site, form a hinge-bending region controlling the cooperative motion, and thereby the catalytic function, of the enzyme. The distal β-barrel and the tRNA acceptor binding domain, on the other hand, are distinguished by their high mobilities in the global modes of motion, a feature typical of recognition sites, also observed for other proteins. Most of the conserved bases and residues of tRNA and GlnRS are severely constrained in the global motions of the molecules, suggesting their having a role in stabilizing and modulating the global motion.

Protein conformations have been generated with both a Monte Carlo scheme and a simpler two-state noninteracting globule-coil model. Conformational energies are taken to consist of intraresidue and interresidue terms. Interresidue energies are taken to be proportional to the number of nativelike contacts. To describe probable folding pathways, either energy or the number of native residues are employed as simple one-dimensional folding-unfolding coordinates. By considering only conformations at each point on these coordinates, it is possible to obtain detailed conformational descriptions of relatively rare intermediates on the folding pathway. This technique of “trapping” intermediates and statistically characterizing them is useful for studying conformational transitions. Equilibrium folding-unfolding pathways have been constructed by connecting most probable conformations in order along the folding coordinate. Calculations with the noninteracting globule-coil model have been performed with details chosen to correspond to those in the Monte Carlo calculation for pancreatic trypsin inhibitor. Both pathways are similar. Thea helix appears prior to formation of the central beta sheet; beta sheet formation coincides with a large maximum in the free energy because of the attendant loss of conformational entropy. Subsequently the Monte Carlo method indicates two alternative pathways for growth toward either the amino or the carboxyl terminus, followed by completion of the native form. For the globule-coil model, the growth pattern differs somewhat, with the appearance of the single pathway for folding up to the carboxyl terminus prior to completion of folding. This difference may originate in the Monte Carlo sampling procedures or in the simplifications of the globule-coil model.

Attractive inter-residue contact energies for proteins have been re-evaluated with the same assumptions and approximations used originally by us in 1985, but with a significantly larger set of protein crystal structures. An additional repulsive packing energy term, operative at higher densities to prevent overpacking, has also been estimated for all 20 amino acids as a function of the number of contacting residues, based on their observed distributions. The two terms of opposite sign are intended to be used together to provide an estimate of the overall energies of inter-residue interactions in simplified proteins without atomic details. To overcome the problem of how to utilize the many homologous proteins in the Protein Data Bank, a new scheme has been devised to assign different weights to each protein, based on similarities among amino acid sequences. A total of 1168 protein structures containing 1661 subunit sequences are actually used here. After the sequence weights have been applied, these correspond to an effective number of residue – residue contacts of 113,914, or about six times more than were used in the old analysis. Remarkably, the new attractive contact energies are nearly identical to the old ones, except for those with Leu and the rarer amino acids Trp and Met. The largest change found for Leu is surprising. The estimates of hydrophobicity from the contact energies for non-polar side-chains agree well with the experimental values. In an application of these contact energies, the sequences of 88 structurally distinct proteins in the Protein Data Bank are threaded at all possible positions without gaps into 189 different folds of proteins whose sequences differ from each other by at least 35% sequence identity. The native structures for 73 of 88 proteins, excluding 15 exceptional proteins such as membrane proteins, are all demonstrated to have the lowest alignment energies.

Drug extrusion through molecular efflux pumps is an important mechanism for the survival of many pathogenic bacteria by removing drugs, providing multidrug resistance (MDR). Understanding molecular mechanisms for drug extrusion in multidrug efflux pumps is important for the development of new antiresistance drugs. The AbgT family of transporters involved in the folic acid biosynthesis pathway represents one such important efflux pump system. In addition to the transport of the folic acid precursor p-amino benzoic acid (PABA), members of this family are involved in the efflux of several sulfa drugs, conferring drug resistance to the bacteria. With the availability of structures for two members of this family (YdaH and MtrF), we investigate molecular pathways for transport of PABA and a sulfa drug (sulfamethazine) particularly for the YdaH transporter using steered molecular dynamics. Our analyses reveal the probable ligand migration pathways through the transporter, which also identifies key residues along the transport pathway. In addition, simulations using both PABA and sulfamethazine show how the protein is able to transport ligands of different shapes and sizes out of the pathogen. Our observations confirm previously reported functional residues for transport along the pathways by which YdaH transporters achieve antibiotic resistance to shuttle drugs out of the cells.

Hinge motions are essential for many protein functions, and their dynamics are important to understand underlying biological mechanisms. The ways that these motions are represented by various computational methods differ significantly. By focusing on a specific class of motion, we have developed a new hinge-domain anisotropic network model (hdANM) that is based on the prior identification of flexible hinges and rigid domains in the protein structure and the subsequent generation of global hinge motions. This yields a set of motions in which the relative translations and rotations of the rigid domains are modulated and controlled by the deformation of the flexible hinges, leading to a more restricted, specific view of these motions. hdANM is the first model, to our knowledge, that combines information about protein hinges and domains to model the characteristic hinge motions of a protein. The motions predicted with this new elastic network model provide important conceptual advantages for understanding the underlying biological mechanisms. As a matter of fact, the generated hinge movements are found to resemble the expected mechanisms required for the biological functions of diverse proteins. Another advantage of this model is that the domain-level coarse graining makes it significantly more computationally efficient, enabling the generation of hinge motions within even the largest molecular assemblies, such as those from cryo-electron microscopy. hdANM is also comprehensive as it can perform in the same way as the well-known protein dynamics models (anisotropic network model, rotational-translation block, and nonlinear rigid block normal mode analysis), depending on the definition of flexible and rigid parts in the protein structure and on whether the motions are extrapolated in a linear or nonlinear fashion. Furthermore, our results indicate that hdANM produces more realistic motions as compared to the anisotropic network model. hdANM is an open-source software, freely available, and hosted on a user-friendly website (https://hdanm.bb.iastate.edu/).