Trimeric structure of (+)-pinoresinol-forming dirigent protein at 1.95 Å resolution with three isolated active sites.

Control over phenoxy radical-radical coupling reactions in vivo in vascular plants was enigmatic until our discovery of dirigent proteins (DPs, from the Latin dirigere, to guide or align). The first three-dimensional structure of a DP ((+)-pinoresinol-forming DP, 1.95 Å resolution, rhombohedral space group H32)) is reported herein. It has a tightly packed trimeric structure with an eight-stranded ß-barrel topology for each DP monomer. Each putative substrate binding and orientation coupling site is located on the trimer surface but too far apart for intermolecular coupling between sites. It is proposed that each site enables stereoselective coupling (using either two coniferyl alcohol radicals or a radical and a monolignol). Interestingly, there are six differentially conserved residues in DPs affording either the (+)- or (-)-antipodes in the vicinity of the putative binding site and region known to control stereoselectivity. DPs are involved in lignan biosynthesis, whereas dirigent domains/sites have been implicated in lignin deposition.

Triazine-Based Sequence-Defined Polymers with Side-Chain Diversity and Backbone-Backbone Interaction Motifs.

Sequence control in polymers, well-known in nature, encodes structure and functionality. Here we introduce a new architecture, based on the nucleophilic aromatic substitution chemistry of cyanuric chloride, that creates a new class of sequence-defined polymers dubbed TZPs. Proof of concept is demonstrated with two synthesized hexamers, having neutral and ionizable side chains. Molecular dynamics simulations show backbone-backbone interactions, including H-bonding motifs and pi-pi interactions. This architecture is arguably biomimetic while differing from sequence-defined polymers having peptide bonds. The synthetic methodology supports the structural diversity of side chains known in peptides, as well as backbone-backbone hydrogen-bonding motifs, and will thus enable new macromolecules and materials with useful functions.

The structural basis of cholesterol accessibility in membranes.

Although the majority of free cellular cholesterol is present in the plasma membrane, cholesterol homeostasis is principally regulated through sterol-sensing proteins that reside in the cholesterol-poor endoplasmic reticulum (ER). In response to acute cholesterol loading or depletion, there is rapid equilibration between the ER and plasma membrane cholesterol pools, suggesting a biophysical model in which the availability of plasma membrane cholesterol for trafficking to internal membranes modulates ER membrane behavior. Previous studies have predominantly examined cholesterol availability in terms of binding to extramembrane acceptors, but have provided limited insight into the structural changes underlying cholesterol activation. In this study, we use both molecular dynamics simulations and experimental membrane systems to examine the behavior of cholesterol in membrane bilayers. We find that cholesterol depth within the bilayer provides a reasonable structural metric for cholesterol availability and that this is correlated with cholesterol-acceptor binding. Further, the distribution of cholesterol availability in our simulations is continuous rather than divided into distinct available and unavailable pools. This data provide support for a revised cholesterol activation model in which activation is driven not by saturation of membrane-cholesterol interactions but rather by bulk membrane remodeling that reduces membrane-cholesterol affinity.

Allosteric activation transitions in enzymes and biomolecular motors: insights from atomistic and coarse-grained simulations.

The chemical step in enzymes is usually preceded by a kinetically distinct activation step that involves large-scale conformational transitions. In "simple" enzymes this step corresponds to the closure of the active site; in more complex enzymes, such as biomolecular motors, the activation step is more complex and may involve interactions with other biomolecules. These activation transitions are essential to the function of enzymes and perturbations in the scale and/or rate of these transitions are implicated in various serious human diseases; incorporating key flexibilities into engineered enzymes is also considered a major remaining challenge in rational enzyme design. Therefore it is important to understand the underlying mechanism of these transitions. This is a significant challenge to both experimental and computational studies because of the allosteric and multi-scale nature of such transitions. Using our recent studies of two enzyme systems, myosin and adenylate kinase (AK), we discuss how atomistic and coarse-grained simulations can be used to provide insights into the mechanism of activation transitions in realistic systems. Collectively, the results suggest that although many allosteric transitions can be viewed as domain displacements mediated by flexible hinges, there are additional complexities and various deviations. For example, although our studies do not find any evidence for "cracking" in AK, our results do underline the contribution of intra-domain properties (e.g., dihedral flexibility) to the rate of the transition. The study of mechanochemical coupling in myosin highlights that local changes important to chemistry require stabilization from more extensive structural changes; in this sense, more global structural transitions are needed to activate the chemistry in the active site. These discussions further emphasize the importance of better understanding factors that control the degree of co-operativity for allosteric transitions, again hinting at the intimate connection between protein stability and functional flexibility. Finally, a number of topics of considerable future interest are briefly discussed.

Origin of parameter degeneracy and molecular shape relationships in geometric-flow calculations of solvation free energies.

Implicit solvent models are important tools for calculating solvation free energies for chemical and biophysical studies since they require fewer computational resources but can achieve accuracy comparable to that of explicit-solvent models. In past papers, geometric flow-based solvation models have been established for solvation analysis of small and large compounds. In the present work, the use of realistic experiment-based parameter choices for the geometric flow models is studied. We find that the experimental parameters of solvent internal pressure p = 172 MPa and surface tension γ = 72 mN/m produce solvation free energies within 1 RT of the global minimum root-mean-squared deviation from experimental data over the expanded set. Our results demonstrate that experimental values can be used for geometric flow solvent model parameters, thus eliminating the need for additional parameterization. We also examine the correlations between optimal values of p and γ which are strongly anti-correlated. Geometric analysis of the small molecule test set shows that these results are inter-connected with an approximately linear relationship between area and volume in the range of molecular sizes spanned by the data set. In spite of this considerable degeneracy between the surface tension and pressure terms in the model, both terms are important for the broader applicability of the model.

Interconversion of functional motions between mesophilic and thermophilic adenylate kinases.

Dynamic properties are functionally important in many proteins, including the enzyme adenylate kinase (AK), for which the open/closed transition limits the rate of catalytic turnover. Here, we compare our previously published coarse-grained (double-well Go) simulation of mesophilic AK from E. coli (AKmeso) to simulations of thermophilic AK from Aquifex aeolicus (AKthermo). In AKthermo, as with AKmeso, the LID domain prefers to close before the NMP domain in the presence of ligand, but LID rigid-body flexibility in the open (O) ensemble decreases significantly. Backbone foldedness in O and/or transition state (TS) ensembles increases significantly relative to AKmeso in some interdomain backbone hinges and within LID. In contact space, the TS of AKthermo has fewer contacts at the CORE-LID interface but a stronger contact network surrounding the CORE-NMP interface than the TS of AKmeso. A "heated" simulation of AKthermo at 375K slightly increases LID rigid-body flexibility in accordance with the "corresponding states" hypothesis. Furthermore, while computational mutation of 7 prolines in AKthermo to their AKmeso counterparts produces similar small perturbations, mutation of these sites, especially positions 8 and 155, to glycine is required to achieve LID rigid-body flexibility and hinge flexibilities comparable to AKmeso. Mutating the 7 sites to proline in AKmeso reduces some hinges' flexibilities, especially hinge 2, but does not reduce LID rigid-body flexibility, suggesting that these two types of motion are decoupled in AKmeso. In conclusion, our results suggest that hinge flexibility and global functional motions alike are correlated with but not exclusively determined by the hinge residues. This mutational framework can inform the rational design of functionally important flexibility and allostery in other proteins toward engineering novel biochemical pathways.

Large-scale motions in the adenylate kinase solution ensemble: coarse-grained simulations and comparison with solution X-ray scattering.

While coarse-grained (CG) simulations provide an efficient approach to identify small- and large-scale motions important to protein conformational transitions, coupling with appropriate experimental validation is essential. Here, by comparing small-angle X-ray scattering (SAXS) predictions from CG simulation ensembles of adenylate kinase (AK) with a range of energetic parameters, we demonstrate that AK is flexible in solution in the absence of ligand and that a small population of the closed form exists without ligand. In addition, by analyzing variation of scattering patterns within CG simulation ensembles, we reveal that rigid-body motion of the LID domain corresponds to a dominant scattering feature. Thus, we have developed a novel approach for three-dimensional structural interpretation of SAXS data. Finally, we demonstrate that the agreement between predicted and experimental SAXS can be improved by increasing the simulation temperature or by computationally mutating selected residues to glycine, both of which perturb LID rigid-body flexibility.

Allosteric communication occurs via networks of tertiary and quaternary motions in proteins.

Allosteric proteins bind an effector molecule at one site resulting in a functional change at a second site. We hypothesize that allosteric communication in proteins relies upon networks of quaternary (collective, rigid-body) and tertiary (residue-residue contact) motions. We argue that cyclic topology of these networks is necessary for allosteric communication. An automated algorithm identifies rigid bodies from the displacement between the inactive and the active structures and constructs "quaternary networks" from these rigid bodies and the substrate and effector ligands. We then integrate quaternary networks with a coarse-grained representation of contact rearrangements to form "global communication networks" (GCNs). The GCN reveals allosteric communication among all substrate and effector sites in 15 of 18 multidomain and multimeric proteins, while tertiary and quaternary networks exhibit such communication in only 4 and 3 of these proteins, respectively. Furthermore, in 7 of the 15 proteins connected by the GCN, 50% or more of the substrate-effector paths via the GCN are "interdependent" paths that do not exist via either the tertiary or the quaternary network. Substrate-effector "pathways" typically are not linear but rather consist of polycyclic networks of rigid bodies and clusters of rearranging residue contacts. These results argue for broad applicability of allosteric communication based on structural changes and demonstrate the utility of the GCN. Global communication networks may inform a variety of experiments on allosteric proteins as well as the design of allostery into non-allosteric proteins.

Structure-based predictive models for allosteric hot spots.

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68-81% of known hotspots, and among total hotspot predictions, 58-67% were actual hotspots. Hence, these models have precision P = 58-67% and recall R = 68-81%. The corresponding models for Feature Set 2 had P = 55-59% and R = 81-92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73-81% and P = 64-71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues.

Contact rearrangements form coupled networks from local motions in allosteric proteins.

Allosteric proteins bind an effector molecule at one site resulting in a functional change at a second site. We hypothesize that networks of contacts altered, formed, or broken are a significant contributor to allosteric communication in proteins. In this work, we identify which interactions change significantly between the residue-residue contact networks of two allosteric structures, and then organize these changes into graphs. We perform the analysis on 15 pairs of allosteric structures with effector and substrate each present in at least one of the two structures. Most proteins exhibit large, dense regions of contact rearrangement, and the graphs form connected paths between allosteric effector and substrate sites in five of these proteins. In the remaining 10 proteins, large-scale conformational changes such as rigid-body motions are likely required in addition to contact rearrangement networks to account for substrate-effector communication. On average, clusters which contain at least one substrate or effector molecule comprise 20% of the protein. These allosteric graphs are small worlds; that is, they typically have mean shortest path lengths comparable to those of corresponding random graphs and average clustering coefficients enhanced relative to those of random graphs. The networks capture 60-80% of known allostery-perturbing mutants in three proteins, and the metrics degree and closeness are statistically good discriminators of mutant residues from nonmutant residues within the networks in two of these three proteins. For two proteins, coevolving clusters of residues which have been hypothesized to be allosterically important differ from the regions with the most contact rearrangement. Residues and contacts which modulate normal mode fluctuations also often participate in the contact rearrangement networks. In summary, residue-residue contact rearrangement networks provide useful representations of the portions of allosteric pathways resulting from coupled local motions.

Local motions in a benchmark of allosteric proteins.

Allosteric proteins have been studied extensively in the last 40 years, but so far, no systematic analysis of conformational changes between allosteric structures has been carried out. Here, we compile a set of 51 pairs of known inactive and active allosteric protein structures from the Protein Data Bank. We calculate local conformational differences between the two structures of each protein using simple metrics, such as backbone and side-chain Cartesian displacement, and torsion angle change and rearrangement in residue-residue contacts. Thresholds for each metric arise from distributions of motions in two control sets of pairs of protein structures in the same biochemical state. Statistical analysis of motions in allosteric proteins quantifies the magnitude of allosteric effects and reveals simple structural principles about allostery. For example, allosteric proteins exhibit substantial conformational changes comprising about 20% of the residues. In addition, motions in allosteric proteins show strong bias toward weakly constrained regions such as loops and the protein surface. Correlation functions show that motions communicate through protein structures over distances averaging 10-20 residues in sequence space and 10-20 A in Cartesian space. Comparison of motions in the allosteric set and a set of 21 nonallosteric ligand-binding proteins shows that nonallosteric proteins also exhibit bias of motion toward weakly constrained regions and local correlation of motion. However, allosteric proteins exhibit twice as much percent motion on average as nonallosteric proteins with ligand-induced motion. These observations may guide efforts to design flexibility and allostery into proteins.

Divalent Ion Parameterization Strongly Affects Conformation and Interactions of an Anionic Biomimetic Polymer.

The description of peptides and the use of molecular dynamics simulations to refine structures and investigate the dynamics on an atomistic scale are well developed. Through a consensus in this community over multiple decades, parameters were developed for molecular interactions that only require the sequence of amino-acids and an initial guess for the three-dimensional structure. The recent discovery of peptoids will require a retooling of the currently available interaction potentials in order to have the same level of confidence in the predicted structures and pathways as there is presently in the peptide counterparts. Here we present modeling of peptoids using a combination of ab initio molecular dynamics (AIMD) and atomistic resolution classical force field (FF) to span the relevant time and length scales. To properly account for the dominant forces that stabilize ordered structures of peptoids, namely steric-, electrostatic, and hydrophobic interactions mediated through side chain-side chain interactions in the FF model, those have to be first mapped out using high fidelity atomistic representations. A key feature here is not only to use gas phase quantum chemistry tools, but also account for solvation effects in the condensed phase through AIMD. One major challenge is to elucidate ion binding to charged or polar regions of the peptoid and its concomitant role in the creation of local order. Here, similar to proteins, a specific ion effect is observed suggesting that both the net charge and the precise chemical nature of the ion will need to be described.

Highly stable and self-repairing membrane-mimetic 2D nanomaterials assembled from lipid-like peptoids.

An ability to develop sequence-defined synthetic polymers that both mimic lipid amphiphilicity for self-assembly of highly stable membrane-mimetic 2D nanomaterials and exhibit protein-like functionality would revolutionize the development of biomimetic membranes. Here we report the assembly of lipid-like peptoids into highly stable, crystalline, free-standing and self-repairing membrane-mimetic 2D nanomaterials through a facile crystallization process. Both experimental and molecular dynamics simulation results show that peptoids assemble into membranes through an anisotropic formation process. We further demonstrated the use of peptoid membranes as a robust platform to incorporate and pattern functional objects through large side-chain diversity and/or co-crystallization approaches. Similar to lipid membranes, peptoid membranes exhibit changes in thickness upon exposure to external stimuli; they can coat surfaces in single layers and self-repair. We anticipate that this new class of membrane-mimetic 2D nanomaterials will provide a robust matrix for development of biomimetic membranes tailored to specific applications.

CAPRI rounds 3-5 reveal promising successes and future challenges for RosettaDock.

CAPRI Rounds 3, 4, and 5 are the first public test of the published RosettaDock algorithm. The targets cover a wide range of sizes and shapes. For most targets, published biological information indicated the region of the binding site on at least one docking partner. The RosettaDock algorithm produced high accuracy predictions for three targets, medium-accuracy predictions for two targets, and an acceptable prediction for one target. RosettaDock predicted all five targets with less than 450 residues to high or medium accuracy, but it predicted only one of seven targets with above 450 residues to acceptable accuracy. RosettaDock's high-accuracy predictions for small to moderately large targets reveal the predictive power and fidelity of the algorithm, especially the high-resolution refinement and scoring protocol. In addition, RosettaDock can predict complexes from at least one homology-modeled docking partner with comparable accuracy to unbound cases of similar size. Larger targets present a more intensive sampling problem, and some large targets present repulsive barriers to entering the binding site. Ongoing improvements to RosettaDock's low-resolution search may alleviate this problem. This first public test suggests that RosettaDock can be useful in a significant range of applications in biochemistry and cell biology.

pK values of histidine residues in ribonuclease Sa: effect of salt and net charge.

The primary goal of this study was to gain a better understanding of the effect of environment and ionic strength on the pK values of histidine residues in proteins. The salt-dependence of pK values for two histidine residues in ribonuclease Sa (RNase Sa) (pI=3.5) and a variant in which five acidic amino acids have been changed to lysine (5K) (pI=10.2) was measured and compared to pK values of model histidine-containing peptides. The pK of His53 is elevated by two pH units (pK=8.61) in RNase Sa and by nearly one pH unit (pK=7.39) in 5K at low salt relative to the pK of histidine in the model peptides (pK=6.6). The pK for His53 remains elevated in 1.5M NaCl (pK=7.89). The elevated pK for His53 is a result of screenable electrostatic interactions, particularly with Glu74, and a non-screenable hydrogen bond interaction with water. The pK of His85 in RNase Sa and 5K is slightly below the model pK at low salt and merges with this value at 1.5M NaCl. The pK of His85 reflects mainly effects of long-range Coulombic interactions that are screenable by salt. The tautomeric states of the neutral histidine residues are changed by charge reversal. The histidine pK values in RNase Sa are always higher than the pK values in the 5K variant. These results emphasize that the net charge of the protein influences the pK values of the histidine residues. Structure-based pK calculations capture the salt-dependence relatively well but are unable to predict absolute histidine pK values.

Improved Coarse-Grained Modeling of Cholesterol-Containing Lipid Bilayers.

Cholesterol trafficking, which is an essential function in mammalian cells, is intimately connected to molecular-scale interactions through cholesterol modulation of membrane structure and dynamics and interaction with membrane receptors. Since these effects of cholesterol occur on micro- to millisecond timescales, it is essential to develop accurate coarse-grained simulation models that can reach these timescales. Cholesterol has been shown experimentally to thicken the membrane and increase phospholipid tail order between 0-40% cholesterol, above which these effects plateau or slightly decrease. Here, we showed that the published MARTINI coarse-grained force-field for phospholipid (POPC) and cholesterol fails to capture these effects. Using reference atomistic simulations, we systematically modified POPC and cholesterol bonded parameters in MARTINI to improve its performance. We showed that the corrections to pseudo-bond angles between glycerol and the lipid tails and around the oleoyl double bond particle (the "angle-corrected model") slightly improves the agreement of MARTINI with experimentally measured thermal, elastic, and dynamic properties of POPC membranes. The angle-corrected model improves prediction of the thickening and ordering effects up to 40% cholesterol but overestimates these effects at higher cholesterol concentration. In accordance with prior work that showed the cholesterol rough face methyl groups are important for limiting cholesterol self-association, we revised the coarse-grained representation of these methyl groups to better match cholesterol-cholesterol radial distribution functions from atomistic simulations. In addition, by using a finer-grained representation of the branched cholesterol tail than MARTINI, we improved predictions of lipid tail order and bilayer thickness across a wide range of concentrations. Finally, transferability testing shows that a model incorporating our revised parameters into DOPC outperforms other CG models in a DOPC/cholesterol simulation series, which further argues for its efficacy and generalizability. These results argue for the importance of systematic optimization for coarse-graining biologically important molecules like cholesterol with complicated molecular structure.

Structural and functional characterization of DUF1471 domains of Salmonella proteins SrfN, YdgH/SssB, and YahO.

Bacterial species in the Enterobacteriaceae typically contain multiple paralogues of a small domain of unknown function (DUF1471) from a family of conserved proteins also known as YhcN or BhsA/McbA. Proteins containing DUF1471 may have a single or three copies of this domain. Representatives of this family have been demonstrated to play roles in several cellular processes including stress response, biofilm formation, and pathogenesis. We have conducted NMR and X-ray crystallographic studies of four DUF1471 domains from Salmonella representing three different paralogous DUF1471 subfamilies: SrfN, YahO, and SssB/YdgH (two of its three DUF1471 domains: the N-terminal domain I (residues 21-91), and the C-terminal domain III (residues 244-314)). Notably, SrfN has been shown to have a role in intracellular infection by Salmonella Typhimurium. These domains share less than 35% pairwise sequence identity. Structures of all four domains show a mixed α+ß fold that is most similar to that of bacterial lipoprotein RcsF. However, all four DUF1471 sequences lack the redox sensitive cysteine residues essential for RcsF activity in a phospho-relay pathway, suggesting that DUF1471 domains perform a different function(s). SrfN forms a dimer in contrast to YahO and SssB domains I and III, which are monomers in solution. A putative binding site for oxyanions such as phosphate and sulfate was identified in SrfN, and an interaction between the SrfN dimer and sulfated polysaccharides was demonstrated, suggesting a direct role for this DUF1471 domain at the host-pathogen interface.

Many local motions cooperate to produce the adenylate kinase conformational transition.

Conformational transitions are functionally important in many proteins. In the enzyme adenylate kinase (AK), two small domains (LID and NMP) close over the larger CORE domain; the reverse (opening) motion limits the rate of catalytic turnover. Here, using double-well Go simulations of Escherichia coli AK, we elaborate on previous investigations of the AK transition mechanism by characterizing the contributions of rigid-body (Cartesian), backbone dihedral, and contact motions to transition-state (TS) properties. In addition, we compare an apo simulation to a pseudo-ligand-bound simulation to reveal insights into allostery. In Cartesian space, LID closure precedes NMP closure in the bound simulation, consistent with prior coarse-grained models of the AK transition. However, NMP-first closure is preferred in the apo simulation. In backbone dihedral space, we find that, as expected, backbone fluctuations are reduced in the O/C transition in parts of all three domains. Among these "quenching" residues, most in the CORE, especially residues 11-13, are rigidified in the TS of the bound simulation, while residues 42-44 in the NMP are flexible in the TS. In contact space, in both apo and bound simulations, one nucleus of closed-state contacts includes parts of the NMP and CORE; CORE-LID contacts are absent in the TS of the apo simulation but formed in the TS of the bound simulation. From these results, we predict mutations that will perturb the opening and/or closing transition rates by changing the entropy of dihedrals and/or the enthalpy of contacts. Furthermore, regarding allostery, the fully closed structure is populated in the apo simulation, but our contact results imply that ligand binding shifts the preferred O/C transition pathway, thus precluding a simple conformational selection mechanism. Finally, the analytical approach and the insights derived from this work may inform the rational design of flexibility and allostery in proteins.