Investigating energy‐based pool structure selection in the structure ensemble modeling with experimental distance constraints: The example from a multidomain protein Pub1

The structural variations of multidomain proteins with flexible parts mediate many biological processes, and a structure ensemble can be determined by selecting a weighted combination of representative structures from a simulated structure pool, producing the best fit to experimental constraints such as interatomic distance. In this study, a hybrid structure‐based and physics‐based atomistic force field with an efficient sampling strategy is adopted to simulate a model di‐domain protein against experimental paramagnetic relaxation enhancement (PRE) data that correspond to distance constraints. The molecular dynamics simulations produce a wide range of conformations depicted on a protein energy landscape. Subsequently, a conformational ensemble recovered with low‐energy structures and the minimum‐size restraint is identified in good agreement with experimental PRE rates, and the result is also supported by chemical shift perturbations and small‐angle X‐ray scattering data. It is illustrated that the regularizations of energy and ensemble‐size prevent an arbitrary interpretation of protein conformations. Moreover, energy is found to serve as a critical control to refine the structure pool and prevent data overfitting, because the absence of energy regularization exposes ensemble construction to the noise from high‐energy structures and causes a more ambiguous representation of protein conformations. Finally, we perform structure‐ensemble optimizations with a topology‐based structure pool, to enhance the understanding on the ensemble results from different sources of pool candidates.     

Monte Carlo replica‐exchange based ensemble docking of protein conformations

A replica‐exchange Monte Carlo (REMC) ensemble docking approach has been developed that allows efficient exploration of protein–protein docking geometries. In addition to Monte Carlo steps in translation and orientation of binding partners, possible conformational changes upon binding are included based on Monte Carlo selection of protein conformations stored as ordered pregenerated conformational ensembles. The conformational ensembles of each binding partner protein were generated by three different approaches starting from the unbound partner protein structure with a range spanning a root mean square deviation of 1–2.5 Å with respect to the unbound structure. Because MC sampling is performed to select appropriate partner conformations on the fly the approach is not limited by the number of conformations in the ensemble compared to ensemble docking of each conformer pair in ensemble cross docking. Although only a fraction of generated conformers was in closer agreement with the bound structure the REMC ensemble docking approach achieved improved docking results compared to REMC docking with only the unbound partner structures or using docking energy minimization methods. The approach has significant potential for further improvement in combination with more realistic structural ensembles and better docking scoring functions. Proteins 2017; 85:924–937. © 2016 Wiley Periodicals, Inc.     

Fast de novo discovery of low‐energy protein loop conformations

In the prediction of protein structure from amino acid sequence, loops are challenging regions for computational methods. Since loops are often located on the protein surface, they can have significant roles in determining protein functions and binding properties. Loop prediction without the aid of a structural template requires extensive conformational sampling and energy minimization, which are computationally difficult. In this article we present a new de novo loop sampling method, the Parallely filtered Energy Targeted All‐atom Loop Sampler (PETALS) to rapidly locate low energy conformations. PETALS explores both backbone and side‐chain positions of the loop region simultaneously according to the energy function selected by the user, and constructs a nonredundant ensemble of low energy loop conformations using filtering criteria. The method is illustrated with the DFIRE potential and DiSGro energy function for loops, and shown to be highly effective at discovering conformations with near‐native (or better) energy. Using the same energy function as the DiSGro algorithm, PETALS samples conformations with both lower RMSDs and lower energies. PETALS is also useful for assessing the accuracy of different energy functions. PETALS runs rapidly, requiring an average time cost of 10 minutes for a length 12 loop on a single 3.2 GHz processor core, comparable to the fastest existing de novo methods for generating an ensemble of conformations. Proteins 2017; 85:1402–1412. © 2017 Wiley Periodicals, Inc.     

Frustration‐guided motion planning reveals conformational transitions in proteins

Proteins exist as conformational ensembles, exchanging between substates to perform their function. Advances in experimental techniques yield unprecedented access to structural snapshots of their conformational landscape. However, computationally modeling how proteins use collective motions to transition between substates is challenging owing to a rugged landscape and large energy barriers. Here, we present a new, robotics‐inspired motion planning procedure called dCC‐RRT that navigates the rugged landscape between substates by introducing dynamic, interatomic constraints to modulate frustration. The constraints balance non‐native contacts and flexibility, and instantaneously redirect the motion towards sterically favorable conformations. On a test set of eight proteins determined in two conformations separated by, on average, 7.5 Å root mean square deviation (RMSD), our pathways reduced the Cα atom RMSD to the goal conformation by 78%, outperforming peer methods. We then applied dCC‐RRT to examine how collective, small‐scale motions of four side‐chains in the active site of cyclophilin A propagate through the protein. dCC‐RRT uncovered a spatially contiguous network of residues linked by steric interactions and collective motion connecting the active site to a recently proposed, non‐canonical capsid binding site 25 Å away, rationalizing NMR and multi‐temperature crystallography experiments. In all, dCC‐RRT can reveal detailed, all‐atom molecular mechanisms for small and large amplitude motions. Source code and binaries are freely available at https://github.com/ExcitedStates/KGS/ .     

Conformational ensemble of an intrinsically flexible loop in mitochondrial import protein Tim21 studied by modeling and molecular dynamics simulations

BackgroundTim21, a subunit of a highly dynamic translocase of the inner mitochondrial membrane (TIM23) complex, translocates proteins by interacting with subunits in the translocase of the outer membrane (TOM) complex and Tim23 channel in the TIM23 complex. A loop segment in Tim21, which is in close proximity of the binding site of Tim23, has different conformations in X-ray, NMR and new crystal contact-free space (CCFS) structures. MD simulations can provide information on the structure and dynamics of the loop in solution.MethodsThe conformational ensemble of the loop was characterized using loop modeling and molecular dynamics (MD) simulations.ResultsMD simulations confirmed mobility of the loop. Multidimensional scaling and clustering were used to characterize the dynamic conformational ensemble of the loop. Free energy landscape showed that the CCFS crystal structure occupied a low energy region as compared to the conventional X-ray crystal structure. Analysis of crystal packing indicates that the CCFS provides larger conformational space for the motions of the loop.ConclusionsOur work reported the conformational ensemble of the loop in solution, which is in agreement with the structure obtained from CCFS approach. The combination of the experimental techniques and computational methods is beneficial for studying highly flexible regions of proteins.General significanceComputational methods, such as loop modeling and MD simulations, have proved to be useful for studying conformational flexibility of proteins. These methods in integration with experimental techniques such as CCFS has the potential to transform the studies on flexible regions of proteins.     

Exploring the dynamic information content of a protein NMR structure: Comparison of a molecular dynamics simulation with the NMR and X‐ray structures of Escherichia coli ribonuclease HI

The multiconformer nature of solution nuclear magnetic resonance (NMR) structures of proteins results from the effects of intramolecular dynamics, spin diffusion and an uneven distribution of structural restraints throughout the molecule. A delineation of the former from the latter two contributions is attempted in this work for an ensemble of 15 NMR structures of the protein Escherichia coli ribonuclease HI (RNase HI). Exploration of the dynamic information content of the NMR ensemble is carried out through correlation with data from two crystal structures and a 1.7‐ns molecular dynamics (MD) trajectory of RNase HI in explicit solvent. Assessment of the consistency of the crystal and mean MD structures with nuclear Overhauser effect (NOE) data showed that the NMR ensemble is overall more compatible with the high‐resolution (1.48 Å) crystal structure than with either the lower‐resolution (2.05 Å) crystal structure or the MD simulation. Furthermore, the NMR ensemble is found to span more conformational space than the MD simulation for both the backbone and the sidechains of RNase HI. Nonetheless, the backbone conformational variability of both the NMR ensemble and the simulation is especially consistent with NMR relaxation measurements of two loop regions that are putative sites of substrate recognition. Plausible side‐chain dynamic information is extracted from the NMR ensemble on the basis of (i) rotamericity and syn‐pentane character of variable torsion angles, (ii) comparison of the magnitude of atomic mean‐square fluctuations (msf) with those deduced from crystallographic thermal factors, and (iii) comparison of torsion angle conformational behavior in the NMR ensemble and the simulation. Several heterogeneous torsion angles, while adopting non‐rotameric/syn‐pentane conformations in the NMR ensemble, exist in a unique conformation in the simulation and display low X‐ray thermal factors. These torsions are identified as sites whose variability is likely to be an artifact of the NMR structure determination procedure. A number of other torsions show a close correspondence between the conformations sampled in the NMR and MD ensembles, as well as significant correlations among crystallographic thermal factors and atomic msf calculated from the NMR ensemble and the simulation. These results indicate that a significant amount of dynamic information is contained in the NMR ensemble. The relevance of the present findings for the biological function of RNase HI, protein recognition studies, and previous investigations of the motional content of protein NMR structures are discussed. Proteins 1999;36:87–110. © 1999 Wiley‐Liss, Inc.     

The relationship between the flexibility of proteins and their conformational states on forming protein-protein complexes with an application to protein-protein docking

We investigate the extent to which the conformational fluctuations of proteins in solution reflect the conformational changes that they undergo when they form binary protein-protein complexes. To do this, we study a set of 41 proteins that form such complexes and whose three-dimensional structures are known, both bound in the complex and unbound. We carry out molecular dynamics simulations of each protein, starting from the unbound structure, and analyze the resulting conformational fluctuations in trajectories of 5 ns in length, comparing with the structure in the complex. It is found that fluctuations take some parts of the molecules into regions of conformational space close to the bound state (or give information about it), but at no point in the simulation does each protein as whole sample the complete bound state. Subsequent use of conformations from a clustered MD ensemble in rigid-body docking is nevertheless partially successful when compared to docking the unbound conformations, as long as the unbound conformations are themselves included with the MD conformations and the whole globally rescored. For one key example where sub-domain motion is present, a ribonuclease inhibitor, principal components analysis of the MD was applied and was also able to produce conformations for docking that gave enhanced results compared to the unbound. The most significant finding is that core interface residues show a tendency to be less mobile (by size of fluctuation or entropy) than the rest of the surface even when the other binding partner is absent, and conversely the peripheral interface residues are more mobile. This surprising result, consistent across up to 40 of the 41 proteins, suggests different roles for these regions in protein recognition and binding, and suggests ways that docking algorithms could be improved by treating these regions differently in the docking process.     

Exploring the conformational and binding properties of unphosphorylated/phosphorylated monomeric and trimeric Bcl‐2 through docking and molecular dynamics simulations

B‐cell lymphoma (Bcl‐2) is commonly associated with the progression and preservation of cancer and certain lymphomas; therefore, it is considered as a biological target against cancer. Nevertheless, evidence of all its structural binding sites has been hidden because of the lack of a complete Bcl‐2 model, given the presence of a flexible loop domain (FLD), which is responsible for its complex behavior. FLD region has been implicated in phosphorylation, homotrimerization, and heterodimerization associated with Bcl‐2 antiapoptotic function. In this contribution, homology modeling, molecular dynamics (MD) simulations in the microsecond (µs) time‐scale and docking calculations were combined to explore the conformational complexity of unphosphorylated/phosphorylated monomeric and trimeric Bcl‐2 systems. Conformational ensembles generated through MD simulations allowed for identifying the most populated unphosphorylated/phosphorylated monomeric conformations, which were used as starting models to obtain trimeric complexes through protein–protein docking calculations, also submitted to µs MD simulations. Principal component analysis showed that FLD represents the main contributor to total Bcl‐2 mobility, and is affected by phosphorylation and oligomerization. Subsequently, based on the most representative unphosphorylated/phosphorylated monomeric and trimeric Bcl‐2 conformations, docking studies were initiated to identify the ligand binding site of several known Bcl‐2 inhibitors to explain their influence in homo‐complex formation and phosphorylation. Docking studies showed that the different conformational states experienced by FLD, such as phosphorylation and oligomerization, play an essential role in the ability to make homo and hetero‐complexes. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 393–413, 2016.     

qFit 3: Protein and ligand multiconformer modeling for X‐ray crystallographic and single‐particle cryo‐EM density maps

New X‐ray crystallography and cryo‐electron microscopy (cryo‐EM) approaches yield vast amounts of structural data from dynamic proteins and their complexes. Modeling the full conformational ensemble can provide important biological insights, but identifying and modeling an internally consistent set of alternate conformations remains a formidable challenge. qFit efficiently automates this process by generating a parsimonious multiconformer model. We refactored qFit from a distributed application into software that runs efficiently on a small server, desktop, or laptop. We describe the new qFit 3 software and provide some examples. qFit 3 is open‐source under the MIT license, and is available at https://github.com/ExcitedStates/qfit-3.0 .     

Ligand binding to a high‐energy partially unfolded protein

The conformational energy landscape of a protein determines populations of all possible conformations of the protein and also determines the kinetics of the conversion between the conformations. Interaction with ligands influences the conformational energy landscapes of proteins and shifts populations of proteins in different conformational states. To investigate the effect of ligand binding on partial unfolding of a protein, we use Escherichia coli dihydrofolate reductase (DHFR) and its functional ligand NADP⁺ as a model system. We previously identified a partially unfolded form of DHFR that is populated under native conditions. In this report, we determined the free energy for partial unfolding of DHFR at varying concentrations of NADP⁺ and found that NADP⁺ binds to the partially unfolded form as well as the native form. DHFR unfolds partially without releasing the ligand, though the binding affinity for NADP⁺ is diminished upon partial unfolding. Based on known crystallographic structures of NADP⁺‐bound DHFR and the model of the partially unfolded protein we previously determined, we propose that the adenosine‐binding domain of DHFR remains folded in the partially unfolded form and interacts with the adenosine moiety of NADP⁺. Our result demonstrates that ligand binding may affect the conformational free energy of not only native forms but also high‐energy non‐native forms.     

A flexible docking scheme to explore the binding selectivity of PDZ domains

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTA LIGAND , we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density‐95/Dlg/ZO‐1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.     

Applying conformational selection theory to improve crossdocking efficiency in 3‐phosphoinositide dependent protein kinase‐1

The emerging picture of biomolecular recognition is that of conformational selection followed by induced‐fit. Conformational selection theory states that binding partners exist in various conformations in solution, with binding involving a “selection” between complementary conformers. In this study, we devise a docking protocol that mimics conformational selection in protein–ligand binding and demonstrate that it significantly enhances crossdocking accuracy over Glide's flexible docking protocol, which is widely used in the pharmaceutical industry. Our protocol uses a pregenerated conformational ensemble to simulate ligand flexibility. The ensemble was generated by thorough conformational sampling coupled with conformer minimization. The generated conformers were then rigidly docked in the active site of the protein along with a postdocking minimization step that allows limited induced fit effects to be modeled for the ligand. We illustrate the improved performance of our protocol through crossdocking of 31 ligands to cocomplexed proteins of the kinase 3‐phosphoinositide dependent protein kinase‐1 extracted from the crystal structures 1H1W (ATP bound), 1OKY (staurosporine bound) and 3QD0 (bound to a potent inhibitor). Consistent with conformational selection theory, the performance of our protocol was the best for crossdocking to the cognate protein bound to the natural ligand, ATP. Proteins 2014; 82:436–451. © 2013 Wiley Periodicals, Inc.     

Temperature‐accelerated molecular dynamics gives insights into globular conformations sampled in the free state of the AC catalytic domain

The catalytic domain of the adenyl cyclase (AC) toxin from Bordetella pertussis is activated by interaction with calmodulin (CaM), resulting in cAMP overproduction in the infected cell. In the X‐ray crystallographic structure of the complex between AC and the C terminal lobe of CaM, the toxin displays a markedly elongated shape. As for the structure of the isolated protein, experimental results support the hypothesis that more globular conformations are sampled, but information at atomic resolution is still lacking. Here, we use temperature‐accelerated molecular dynamics (TAMD) simulations to generate putative all‐atom models of globular conformations sampled by CaM‐free AC. As collective variables, we use centers of mass coordinates of groups of residues selected from the analysis of standard molecular dynamics (MD) simulations. Results show that TAMD allows extended conformational sampling and generates AC conformations that are more globular than in the complexed state. These structures are then refined via energy minimization and further unrestrained MD simulations to optimize inter‐domain packing interactions, thus resulting in the identification of a set of hydrogen bonds present in the globular conformations. Proteins 2014; 82:2483–2496. © 2014 Wiley Periodicals, Inc.     

The flexible C‐terminal arm of the Lassa arenavirus Z‐protein mediates interactions with multiple binding partners

The arenavirus genome encodes for a Z‐protein, which contains a RING domain that coordinates two zinc ions, and has been identified as having several functional roles at various stages of the virus life cycle. Z‐protein binds to multiple host proteins and has been directly implicated in the promotion of viral budding, repression of mRNA translation, and apoptosis of infected cells. Using homology models of the Z‐protein from Lassa strain arenavirus, replica exchange molecular dynamics (MD) was used to refine the structures, which were then subsequently clustered. Population‐weighted ensembles of low‐energy cluster representatives were predicted based upon optimal agreement of the chemical shifts computed with the SPARTA program with the experimental NMR chemical shifts. A member of the refined ensemble was indentified to be a potential binder of budding factor Tsg101 based on its correspondence to the structure of the HIV‐1 Gag late domain when bound to Tsg101. Members of these ensembles were docked against the crystal structure of human eIF4E translation initiation factor. Two plausible binding modes emerged based upon their agreement with experimental observation, favorable interaction energies and stability during MD trajectories. Mutations to Z are proposed that would either inhibit both binding mechanisms or selectively inhibit only one mode. The C‐terminal domain conformation of the most populated member of the representative ensemble shielded protein‐binding recognition motifs for Tsg101 and eIF4E and represents the most populated state free in solution. We propose that C‐terminal flexibility is key for mediating the different functional states of the Z‐protein. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Energetics-based protein profiling on a proteomic scale: identification of proteins resistant to proteolysis

Native states of proteins are flexible, populating more than just the unique native conformation. The energetics and dynamics resulting from this conformational ensemble are inherently linked to protein function and regulation. Proteolytic susceptibility is one feature determined by this conformational energy landscape. As an attempt to investigate energetics of proteins on a proteomic scale, we challenged the Escherichia coli proteome with extensive proteolysis and determined which proteins, if any, have optimized their energy landscape for resistance to proteolysis. To our surprise, multiple soluble proteins survived the challenge. Maltose binding protein, a survivor from thermolysin digestion, was characterized by in vitro biophysical studies to identify the physical origin of proteolytic resistance. This experimental characterization shows that kinetic stability is responsible for the unusual resistance in maltose binding protein. The biochemical functions of the identified survivors suggest that many of these proteins may have evolved extreme proteolytic resistance because of their critical roles under stressed conditions. Our results suggest that under functional selection proteins can evolve extreme proteolysis resistance by modulating their conformational energy landscapes without the need to invent new folds, and that proteins can be profiled on a proteomic scale according to their energetic properties by using proteolysis as a structural probe.     

Identification of putative unfolding intermediates of the mutant His‐107‐tyr of human carbonic anhydrase II in a multidimensional property space

In this article, we develop an extensive search procedure of the multi‐dimensional folding energy landscape of a protein. Our aim is to identify different classes of structures that have different aggregation propensities and catalytic activity. Following earlier studies by Daggett et al. [Jong, D. D.; Riley, R.: Alonso, D.O.: Dagett, V. J. Mol. Biol. 2002, 319, 229], a series of high temperature all‐atom classical molecular simulation studies has been carried out to derive a multi‐dimensional property space. Dynamical changes in these properties are then monitored by projecting them along a one‐dimensional reaction coordinate, d_mean. We have focused on the application of this method to partition a wide array of conformations of wild type human carbonic anhydrase II (HCA II) and its unstable mutant His‐107‐Tyr along d_mean by sampling a 35‐dimensional property space. The resultant partitioning not only reveals the distribution of conformations corresponding to stable structures of HCA II and its mutant, but also allows the monitoring of several partially unfolded and less stable conformations of the mutant. We have investigated the population of these conformations at different stages of unfolding and collected separate sets of structures that are widely separated in the property space. The dynamical diversity of these sets are examined in terms of the loading of their respective first principal component. The partially unfolded structures thus collected are qualitatively mapped on to the experimentally postulated light molten globule (MGL) and molten globule (MG) intermediates with distinct aggregation propensities and catalytic activities. Proteins 2016; 84:726–743. © 2016 Wiley Periodicals, Inc.