Accessibility to internal cavities and ligand binding sites monitored by protein crystallographic thermal factors

RNAfcg: RNA Flexibility Prediction Based on Topological Centrality and Global Features

The dynamics of RNAs are related intimately to their functions. Molecular flexibility, as a starting point for understanding their dynamics, has been utilized to predict many characteristics associated with their functions. Since the experimental measurement methods are time-consuming and labor-intensive, it is urgently needed to develop reliable theoretical methods to predict RNA flexibility. In this work, we develop an effective machine learning method, RNAfcg, to predict RNA flexibility, where the Random Forest (RF) is trained by features including the topological centralities, flexibility-rigidity index, and global characteristics first introduced by us, as well as some traditional sequence and structural features. The analyses show that the three types of features introduced first have significant contributions to RNA flexibility prediction, among which the topological type contributes the most, which indicates the importance of structural topology in determining RNA flexibility. The performance comparison indicates that RNAfcg outperforms the state-of-the-art machine learning methods and the commonly used Gaussian Network Model (GNM) models, achieving a much higher Pearson correlation coefficient (PCC) of 0.6619 on the test data set. This work is helpful for understanding RNA dynamics and can be used to predict RNA function information. The source code is available at https://github.com/ChunhuaLab/RNAfcg/.

Improving the Thermostability of Thermomyces lanuginosus Lipase by Restricting the Flexibility of N-Terminus and C-Terminus Simultaneously via the 25-Loop Substitutions

(1) Lipases are catalysts widely applied in industrial fields. To sustain the harsh treatments in industries, optimizing lipase activities and thermal stability is necessary to reduce production loss. (2) The thermostability of Thermomyces lanuginosus lipase (TLL) was evaluated via B-factor analysis and consensus-sequence substitutions. Five single-point variants (K24S, D27N, D27R, P29S, and A30P) with improved thermostability were constructed via site-directed mutagenesis. (3) The optimal reaction temperatures of all the five variants displayed 5 °C improvement compared with TLL. Four variants, except D27N, showed enhanced residual activities at 80 °C. The melting temperatures of three variants (D27R, P29S, and A30P) were significantly increased. The molecular dynamics simulations indicated that the 25-loop (residues 24-30) in the N-terminus of the five variants generated more hydrogen bonds with surrounding amino acids; hydrogen bond pair D254-I255 preserved in the C-terminus of the variants also contributes to the improved thermostability. Furthermore, the newly formed salt-bridge interaction (R27…E56) in D27R was identified as a crucial determinant for thermostability. (4) Our study discovered that substituting residues from the 25-loop will enhance the stability of the N-terminus and C-terminus simultaneously, restrict the most flexible regions of TLL, and result in improved thermostability.

Are Protein Cavities and Pockets Commonly Used by Redox Active Signalling Molecules?

It has been well known for a long time that inert gases, such as xenon (Xe), have significant biological effects. As these atoms are extremely unlikely to partake in direct chemical reactions with biomolecules such as proteins, lipids, and nucleic acids, there must be some other mode of action to account for the effects reported. It has been shown that the topology of proteins allows for cavities and hydrophobic pockets, and it is via an interaction with such protein structures that inert gases are thought to have their action. Recently, it has been mooted that the relatively inert gas molecular hydrogen (H₂) may also have its effects via such a mechanism, influencing protein structures and actions. H₂ is thought to also act via interaction with redox active compounds, particularly the hydroxyl radical (^·OH) and peroxynitrite (ONOO^-), but not nitric oxide (NO^·), superoxide anions (O₂^·-) or hydrogen peroxide (H₂O₂). However, instead of having a direct interaction with H₂, is there any evidence that these redox compounds can also interact with Xe pockets and cavities in proteins, either having an independent effect on proteins or interfering with the action of inert gases? This suggestion will be explored here.

Uses and Abuses of the Atomic Displacement Parameters in Structural Biology

B-factors determined with X-ray crystallographic analyses are commonly used to estimate the flexibility degree of atoms, residues, and molecular moieties in biological macromolecules. In this chapter, the most recent studies and applications of B-factors in protein engineering and structural biology are briefly summarized. Particular emphasis is given to the limitations in using B-factors, in order to prevent inappropriate applications. It is eventually predicted that future applications will involve anisotropically refined B-factors, deep learning, and data produced by cryo-EM.

Random sampling of the Protein Data Bank: RaSPDB

A novel and simple procedure (RaSPDB) for Protein Data Bank mining is described. 10 PDB subsets, each containing 7000 randomly selected protein chains, are built and used to make 10 estimations of the average value of a generic feature F—the length of the protein chain, the amino acid composition, the crystallographic resolution, and the secondary structure composition. These 10 estimations are then used to compute an average estimation of F together with its standard error. It is heuristically verified that the dimension of these 10 subsets—7000 protein chains—is sufficiently small to avoid redundancy within each subset and sufficiently large to guarantee stable estimations amongst different subsets. RaSPDB has two major advantages over classical procedures aimed to build a single, non-redundant PDB subset: a larger fraction of the information stored in the PDB is used and an estimation of the standard error of F is possible.

RNA Flexibility Prediction With Sequence Profile and Predicted Solvent Accessibility

Structural flexibility plays an essential role in many biological processes. B-factor is an important indicator to measure the flexibility of protein or RNA structures. Many methods were developed to predict protein B-factors, but few studies have been done for RNA B-factor prediction. In this paper, we proposed a new method RNAbval to predict RNA B-factors using random forest. The method was developed using a comprehensive set of features, including the sequence profile and predicted solvent accessibility. RNAbval achieved an improvement of 9.2-20.5 percent over the state-of-the-art method on two benchmark test datasets. The proposed method is available at http://yanglab.nankai.edu.cn/RNAbval/.

Correlated Motions in Structural Biology

Correlated motions in proteins arising from the collective movements of residues have long been proposed to be fundamentally important to key properties of proteins, from allostery and catalysis to evolvability. Recent breakthroughs in structural biology have made it possible to capture proteins undergoing complex conformational changes, yet intrinsic correlated motions within a conformation remain one of the least understood facets of protein structure. For many decades, the analysis of total X-ray scattering held the promise of animating crystal structures with correlated motions. With recent advances in both X-ray detectors and data interpretation methods, this long-held promise can now be met. In this Perspective, we will introduce how correlated motions are captured in total scattering and provide guidelines for the collection, interpretation, and validation of data. As structural biology continues to push the boundaries, we see an opportunity to gain atomistic insight into correlated motions using total scattering as a bridge between theory and experiment.

Reversibly Sampling Conformations and Binding Modes Using Molecular Darting

Sampling multiple binding modes of a ligand in a single molecular dynamics simulation is difficult. A given ligand may have many internal degrees of freedom, along with many different ways it might orient itself in a binding site or across several binding sites, all of which might be separated by large energy barriers. We have developed a novel Monte Carlo move called molecular darting (MolDarting) to reversibly sample between predefined binding modes of a ligand. Here, we couple this with nonequilibrium candidate Monte Carlo (NCMC) to improve acceptance of moves. We apply this technique to a simple dipeptide system, a ligand binding to T4 lysozyme L99A, and ligand binding to HIV integrase to test this new method. We observe significant increases in acceptance compared to uniformly sampling the internal and rotational/translational degrees of freedom in these systems.

SCOT: Rethinking the classification of secondary structure elements

MOTIVATION

Secondary structure classification is one of the most important issues in structure-based analyses due to its impact on secondary structure prediction, structural alignment and protein visualization. There are still open challenges concerning helix and sheet assignments which are currently not addressed by a single multi-purpose software.

RESULTS

We introduce SCOT (Secondary structure Classification On Turns) as a novel secondary structure element assignment software which supports the assignment of turns, right-handed α-, 310- and π-helices, left-handed α- and 310-helices, 2.27- and polyproline II helices, β-sheets and kinks. We demonstrate that the introduction of helix Purity values enables a clear differentiation between helix classes. SCOT's unique strengths are highlighted by comparing it to six state-of-the-art methods (DSSP, STRIDE, ASSP, SEGNO, DISICL and SHAFT). The assignment approaches were compared concerning geometric consistency, protein structure quality and flexibility dependency and their impact on secondary structure element-based structural alignments. We show that only SCOT's combination of hydrogen bonds, geometric criteria and dihedral angles enables robust assignments independent of the structure quality and flexibility. We demonstrate that this combination and the elaborate kink detection lead to SCOT's clear superiority for protein alignments. As the resulting helices and strands are provided in a PDB conform output format, they can immediately be used for structure alignment algorithms. Taken together, the application of our new method and the straight-forward visualization using the accompanying PyMOL scripts enable the comprehensive analysis of regular backbone geometries in proteins.

AVAILABILITY AND IMPLEMENTATION

https://this-group.rocks.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Local and global analysis of macromolecular atomic displacement parameters

This paper describes the global and local analysis of atomic displacement parameters (ADPs) of macromolecules in X-ray crystallography. The distribution of ADPs is shown to follow the shifted inverse-gamma distribution or a mixture of these distributions. The mixture parameters are estimated using the expectation-maximization algorithm. In addition, a method for the resolution- and individual ADP-dependent local analysis of neighbouring atoms has been designed. This method facilitates the detection of mismodelled atoms, heavy-metal atoms and disordered and/or incorrectly modelled ligands. Both global and local analyses can be used to detect errors in atomic models, thus helping in the (re)building, refinement and validation of macromolecular structures. This method can also serve as an additional validation tool during PDB deposition.

Structural Basis for the Regulation of PPARγ Activity by Imatinib

Imatinib is an effective anticancer drug for the treatment of leukemia. Interestingly, when an FDA-approved drug library was tested for agents that block peroxisome proliferator-activated receptor γ (PPARγ) phosphorylation at Ser245 to evaluate possibilities of antidiabetic drug repositioning, imatinib was determined as a PPARγ antagonist ligand. However, it is not well understood how imatinib binds to PPARγ or would improve insulin sensitivity without classical agonism. Here, we report the crystal structure of the PPARγ R288A mutant in complex with imatinib. Imatinib bound to Arm2 and Arm3 regions in the ligand-binding domain (LBD) of PPARγ, of which the Arm3 region is closely related to the inhibition of PPARγ phosphorylation at Ser245. The binding of imatinib in LBD induced a stable conformation of helix H2′ and the Ω loop compared with the ligand-free state. In contrast, imatinib does not interact with Tyr473 on PPARγ helix H12, which is important for the classical agonism associated with side effects. Our study provides new structural insights into the PPARγ regulation by imatinib and may contribute to the development of new antidiabetic drugs targeting PPARγ while minimizing known side effects.

Reviving B-Factors: Retrospective Normalized B-Factor Analysis of c-ros Oncogene 1 Receptor Tyrosine Kinase and Anaplastic Lymphoma Kinase L1196M with Crizotinib and Lorlatinib

Structure-based drug design (SBDD) is commonly leveraged in rational drug design. Usually, ligand and binding site atomic coordinates from crystallographic data are exploited to optimize potency and selectivity. In addition to traditional, static views of proteins and ligands, we propose using normalized B-factors to study protein dynamics as a part of the drug optimization process. A retrospective case study of crizotinib and lorlatinib bound to both c-ros oncogene 1 kinase (ROS1) and anaplastic lymphoma kinase (ALK) L1196M related normalized B-factors to differences in binding affinity. This analysis showed that ligand binding can have protein-stabilizing effects that start near the ligand but propagate through nearby residues and structural waters to more distal motifs. The potential opportunities for analyzing normalized B-factors in SBDD are also discussed.

How large B-factors can be in protein crystal structures

BACKGROUND

Protein crystal structures are potentially over-interpreted since they are routinely refined without any restraint on the upper limit of atomic B-factors. Consequently, some of their atoms, undetected in the electron density maps, are allowed to reach extremely large B-factors, even above 100 square Angstroms, and their final positions are purely speculative and not based on any experimental evidence.

RESULTS

A strategy to define B-factors upper limits is described here, based on the analysis of protein crystal structures deposited in the Protein Data Bank prior 2008, when the tendency to allow B-factor to arbitrary inflate was limited. This B-factor upper limit (B_max) is determined by extrapolating the relationship between crystal structure average B-factor and percentage of crystal volume occupied by solvent (pcVol) to pcVol =100%, when, ab absurdo, the crystal contains only liquid solvent, the structure of which is, by definition, undetectable in electron density maps.

CONCLUSIONS

It is thus possible to highlight structures with average B-factors larger than B_max, which should be considered with caution by the users of the information deposited in the Protein Data Bank, in order to avoid scientifically deleterious over-interpretations.

Gaussian network model can be enhanced by combining solvent accessibility in proteins

Gaussian network model (GNM), regarded as the simplest and most representative coarse-grained model, has been widely adopted to analyze and reveal protein dynamics and functions. Designing a variation of the classical GNM, by defining a new Kirchhoff matrix, is the way to improve the residue flexibility modeling. We combined information arising from local relative solvent accessibility (RSA) between two residues into the Kirchhoff matrix of the parameter-free GNM. The undetermined parameters in the new Kirchhoff matrix were estimated by using particle swarm optimization. The usage of RSA was motivated by the fact that our previous work using RSA based linear regression model resulted out higher prediction quality of the residue flexibility when compared with the classical GNM and the parameter free GNM. Computational experiments, conducted based on one training dataset, two independent datasets and one additional small set derived by molecular dynamics simulations, demonstrated that the average correlation coefficients of the proposed RSA based parameter-free GNM, called RpfGNM, were significantly increased when compared with the parameter-free GNM. Our empirical results indicated that a variation of the classical GNMs by combining other protein structural properties is an attractive way to improve the quality of flexibility modeling.

Improving the thermostability of a fungal GH11 xylanase via site-directed mutagenesis guided by sequence and structural analysis

BACKGROUND

Xylanases have been widely employed in many industrial processes, and thermophilic xylanases are in great demand for meeting the high-temperature requirements of biotechnological treatments. In this work, we aim to improve the thermostability of XynCDBFV, a glycoside hydrolase (GH) family 11 xylanase from the ruminal fungus Neocallimastix patriciarum, by site-directed mutagenesis. We report favorable mutations at the C-terminus from B-factor comparison and multiple sequence alignment.

RESULTS

C-terminal residues 207-NGGA-210 in XynCDBFV were discovered to exhibit pronounced flexibility based on comparison of normalized B-factors. Multiple sequence alignment revealed that beneficial residues 207-SSGS-210 are highly conserved in GH11 xylanases. Thus, a recombinant xylanase, Xyn-MUT, was constructed by substituting three residues (N207S, G208S, A210S) at the C-terminus of XynCDBFV. Xyn-MUT exhibited higher thermostability than XynCDBFV at ≥70 °C. Xyn-MUT showed promising improvement in residual activity with a thermal retention of 14% compared to that of XynCDBFV after 1 h incubation at 80 °C; Xyn-MUT maintained around 50% of the maximal activity after incubation at 95 °C for 1 h. Kinetic measurements showed that the recombinant Xyn-MUT had greater kinetic efficiency than XynCDBFV (K_m, 0.22 and 0.59 µM, respectively). Catalytic efficiency values (k_cat/K_m) of Xyn-MUT also increased (1.64-fold) compared to that of XynCDBFV. Molecular dynamics simulations were performed to explore the improved catalytic efficiency and thermostability: (1) the substrate-binding cleft of Xyn-MUT prefers to open to a larger extent to allow substrate access to the active site residues, and (2) hydrogen bond pairs S208-N205 and S210-A55 in Xyn-MUT contribute significantly to the improved thermostability. In addition, three xylanases with single point mutations were tested, and temperature assays verified that the substituted residues S208 and S210 give rise to the improved thermostability.

CONCLUSIONS

This is the first report for GH11 recombinant with improved thermostability based on C-terminus replacement. The resulting Xyn-MUT will be an attractive candidate for industrial applications.

Waters in room temperature and cryo protein crystal structures

Since it has been observed that low temperature protein crystal structures may differ from room temperature structures, it is necessary to compare systematically the protein hydration structure in low and room protein crystal structures. High quality data sets of protein structures were built in an extremely rigorous manner and crystal symmetry was included in the identification of four types of water molecules (buried in the protein core, deeply inserted into crevices at the protein surface, first and second hydration layers). More water molecules are observed at low temperature only if the resolution is better than 2.1–2.3 Å. At worse resolution, temperature does not play any role. The numerous water molecules that become detectable at low temperature and at higher resolution are more mobile, relative to the protein average flexibility. Despite that, the occupancy does not depend on temperature. It can be hypothesized that water structure and around proteins and hydrogen bond network do not depend on the temperature, at least in the temperature range examined here. At low temperature more water molecules are detected because the average flexibility of all the atoms decreases, so that also water molecules that are considerably more mobile than the average atoms become observable in the electron density maps.

Criteria to Extract High-Quality Protein Data Bank Subsets for Structure Users

It is often necessary to build subsets of the Protein Data Bank to extract structural trends and average values. For this purpose it is mandatory that the subsets are non-redundant and of high quality. The first problem can be solved relatively easily at the sequence level or at the structural level. The second, on the contrary, needs special attention. It is not sufficient, in fact, to consider the crystallographic resolution and other feature must be taken into account: the absence of strings of residues from the electron density maps and from the files deposited in the Protein Data Bank; the B-factor values; the appropriate validation of the structural models; the quality of the electron density maps, which is not uniform; and the temperature of the diffraction experiments. More stringent criteria produce smaller subsets, which can be enlarged with more tolerant selection criteria. The incessant growth of the Protein Data Bank and especially of the number of high-resolution structures is allowing the use of more stringent selection criteria, with a consequent improvement of the quality of the subsets of the Protein Data Bank.

Statistical survey of the buried waters in the Protein Data Bank

The structures of buried water molecules were studied in an ensemble of high-quality and non-redundant protein crystal structures. Buried water molecules were clustered and classified in lake-like clusters, which are completely isolated from the bulk solvent, and bay-like clusters, which are in contact with the bulk solvent through a surface water molecule. Buried water molecules are extremely common: lake-like clusters are found in 89 % of the protein crystal structures and bay-like clusters in 93 %. Clusters with only one water molecule are much more common than larger clusters. Both cluster types incline to be surrounded by loop residues, and to a minor extent by residues in extended secondary structure. Helical residues on the contrary do not tend to surround clusters of buried water molecules. One buried water molecule is found every 30-50 amino acid residues, depending on the secondary structures that are more abundant in the protein. Both main- and side-chain atoms are in contact with buried waters; they form four hydrogen bonds with the first water and 1-1.5 additional hydrogen bond for each additional water in the cluster. Consequently, buried water molecules appear to be firmly packed and rigid like the protein atoms. In this regard, it is remarkable to observe that prolines often surround water molecules buried in the protein interior. Interestingly, clusters of buried water molecules tend to be just beneath the protein surface. Moreover, water molecules tend to form a one-dimensional wire rather than more compact arrangements. This agrees with recent evidence of the mechanisms of solvent exchange between internal cavities and bulk solvent.

Buried chloride stereochemistry in the Protein Data Bank

Background

Despite the chloride anion is involved in fundamental biological processes, its interactions with proteins are little known. In particular, we lack a systematic survey of its coordination spheres.

Results

The analysis of a non-redundant set (pairwise sequence identity?<?30%) of 1739 high resolution (<2 Å) crystal structures that contain at least one chloride anion shows that the first coordination spheres of the chlorides are essentially constituted by hydrogen bond donors. Amongst the side-chains positively charged, arginine interacts with chlorides much more frequently than lysine. Although the most common coordination number is 4, the coordination stereochemistry is closer to the expected geometry when the coordination number is 5, suggesting that this is the coordination number towards which the chlorides tend when they interact with proteins.

Conclusions

The results of these analyses are useful in interpreting, describing, and validating new protein crystal structures that contain chloride anions.

Functional relevance of the internal hydrophobic cavity of urate oxidase

Urate oxidase from Aspergillus flavus is a 135 kDa homo-tetramer which has a hydrophobic cavity buried within each monomer and located close to its active site. Crystallographic studies under moderate gas pressure and high hydrostatic pressure have shown that both gas presence and high pressure would rigidify the cavity leading to an inhibition of the catalytic activity. Analysis of the cavity volume variations and functional modifications suggest that the flexibility of the cavity would be an essential parameter for the active site efficiency. This cavity would act as a connecting vessel to give flexibility to the neighboring active site, and its expansion under pure oxygen pressure reveals that it might serve as a transient reservoir on its pathway to the active site.

Dynamic void distribution in myoglobin and five mutants

Globular proteins contain cavities/voids that play specific roles in controlling protein function. Elongated cavities provide migration channels for the transport of ions and small molecules to the active center of a protein or enzyme. Using Monte Carlo and Molecular Dynamics on fully atomistic protein/water models, a new computational methodology is introduced that takes into account the protein's dynamic structure and maps all the cavities in and on the surface. To demonstrate its utility, the methodology is applied to study cavity structure in myoglobin and five of its mutants. Computed cavity and channel size distributions reveal significant differences relative to the wild type myoglobin. Computer visualization of the channels leading to the heme center indicates restricted ligand access for the mutants consistent with the existing interpretations. The new methodology provides a quantitative measure of cavity structure and distributions and can become a valuable tool for the structural characterization of proteins.

Stochastic model for protein flexibility analysis

Protein flexibility is an intrinsic property and plays a fundamental role in protein functions. Computational analysis of protein flexibility is crucial to protein function prediction, macromolecular flexible docking, and rational drug design. Most current approaches for protein flexibility analysis are based on Hamiltonian mechanics. We introduce a stochastic model to study protein flexibility. The essential idea is to analyze the free induction decay of a perturbed protein structural probability, which satisfies the master equation. The transition probability matrix is constructed by using probability density estimators including monotonically decreasing radial basis functions. We show that the proposed stochastic model gives rise to some of the best predictions of Debye-Waller factors or B factors for three sets of protein data introduced in the literature.

Conformational barrier of CheY3 and inability of CheY4 to bind FliM control the flagellar motor action in Vibrio cholerae

Vibrio cholerae contains multiple copies of chemotaxis response regulator (VcCheY1-VcCheY4) whose functions are elusive yet. Although previous studies suggested that only VcCheY3 directly switches the flagellar rotation, the involvement of VcCheY4 in chemotaxis could not be ruled out. None of these studies, however, focused on the structure, mechanism of activation or molecular basis of FliM binding of the VcCheYs. From the crystal structures of Ca(2+) and Mg(2+) bound VcCheY3 we proposed the presence of a conformational barrier composed of the hydrophobic packing of W61, M88 and V106 and a unique hydrogen bond between T90 and Q97 in VcCheY3. Lesser fluorescence quenching and higher Km value of VcCheY3, compared to its mutants VcCheY3-Q97A and VcCheY3-Q97A/E100A supported our proposition. Furthermore, aforesaid biochemical data, in conjunction with the structure of VcCheY3-Q97A, indicated that the coupling of T90 and Q97 restricts the movement of T90 toward the active site reducing the stabilization of the bound phosphate and effectively promoting autodephosphorylation of VcCheY3. The structure of BeF3(-) activated VcCheY3 insisted us to argue that elevated temperature and/or adequacy of phosphate pool might break the barrier of the free-state VcCheY3 and the conformational changes, required for FliM binding, occur upon phosphorylation. Structure of VcCheY4 has been solved in the free and sulfated states. VcCheY4(sulf), containing a bound sulfate at the active site, appears to be more compact and stable with a longer α4 helix, shorter β4α4 loop and hydrogen bond between T82 and the sulfate compared to VcCheY4(free). While pull down assay of VcCheYs with VcFliMNM showed that only activated VcCheY3 can interact with VcFliMNM and VcCheY4 cannot, a knowledge based docking explained the molecular mechanism of the interactions between VcCheY3 and VcFliM and identified the limitations of VcCheY4 to interact with VcFliM even in its phosphorylated state.

Toward an understanding of the sequence and structural basis of allosteric proteins

Allostery is the most efficient means of regulating protein functions, ranging from the control of metabolic mechanisms to signal transduction pathways. Although allosteric regulation has been recognized for half a century, our knowledge is limited to the characteristics of allosteric proteins and the structural coupling of allosteric sites and modulators. In this paper, we present a comprehensive analysis of allosteric proteins that provides insight into the foundation of allosteric interactions by revealing a series of common features in the allosteric proteins. Allosteric proteins mainly appear in transferases, and phosphorylation is the most common type of modification found in allosteric proteins. Disorders related to allosteric proteins primarily comprise metabolic diseases and cancers. In general, allosteric proteins prefer to exist as monomers or even-numbered multimers. Greater stability and hydrophobicity are observed in allosteric proteins than in general proteins. Further analysis of the allosteric sites reveals a series of buried and compact pockets composed of significantly greater hydrophobic surface area than the corresponding orthosteric sites. The hydrophobicity of the allosteric sites plays a dominant role in the binding of allosteric modulators as observed in the analysis of 106 diverse allosteric protein-modulator pairs. These results may be of great significance in predicting which proteins are allosteric and in designing novel triggers to inhibit or activate proteins of interest.

Role of remote scaffolding residues in the inhibitory loop pre-organization, flexibility, rigidification and enzyme inhibition of serine protease inhibitors

Canonical serine protease inhibitors interact with cognate enzymes through the P3-P2' region of the inhibitory loop while its scaffold hardly makes any contact. Neighboring scaffolding residues like Arginines or Asparagine shape-up the inhibitory loop and favor the resynthesis of cleaved scissile bond. However, role of remote scaffolding residues, which are not involved in religation, was not properly explored. Crystal structures of two engineered winged bean chymotrypsin inhibitor (WCI) complexed with Bovine trypsin (BPT) namely L65R-WCI:BPT and F64Y/L65R-WCI:BPT show that the inhibitory loop of these engineered inhibitors are recognized and rigidified properly at the enzyme active site like other strong trypsin inhibitors. Chimeric protein ETI(L)-WCI(S), having a loop of Erythrina caffra Trypsin Inhibitor, ETI on the scaffold of WCI, was previously shown to behave like substrate. Non-canonical structure of the inhibitory loop and its flexibility are attributed to the presence of smaller scaffolding residues which cannot act as barrier to the inhibitory loop like in ETI. Double mutant A76R/L115Y-(ETI(L)-WCI(S)), where the barrier is reintroduced on ETI(L)-WCI(S), shows regaining of inhibitory activity. The structure of A76R/L115Y-(ETI(L)-WCI(S)) along with L65R-WCI:BPT and F64Y/L65R-WCI:BPT demonstrate here that the lost canonical conformation of the inhibitory loop is fully restored and loop flexibility is dramatically reduced. Therefore, residues at the inhibitory loop interact with the enzyme playing the primary role in recognition and binding but scaffolding residues having no direct interaction with the enzyme are crucial for rigidification event and the inhibitory potency. B-factor analysis indicates that the amount of inhibitory loop rigidification varies between different inhibitor families.

Hydration sites of unpaired RNA bases: a statistical analysis of the PDB structures

BACKGROUND

Hydration is crucial for RNA structure and function. X-ray crystallography is the most commonly used method to determine RNA structures and hydration and, therefore, statistical surveys are based on crystallographic results, the number of which is quickly increasing.

RESULTS

A statistical analysis of the water molecule distribution in high-resolution X-ray structures of unpaired RNA nucleotides showed that: different bases have the same penchant to be surrounded by water molecules; clusters of water molecules indicate possible hydration sites, which, in some cases, match those of the major and minor grooves of RNA and DNA double helices; complex hydrogen bond networks characterize the solvation of the nucleotides, resulting in a significant rigidity of the base and its surrounding water molecules. Interestingly, the hydration sites around unpaired RNA bases do not match, in general, the positions that are occupied by the second nucleotide when the base-pair is formed.

CONCLUSIONS

The hydration sites around unpaired RNA bases were found. They do not replicate the atom positions of complementary bases in the Watson-Crick pairs.

Predicting the Flexibility Profile of Ribosomal RNAs

Flexibility in biomolecules is an important determinant of biological functionality, which can be measured quantitatively by atomic Debye-Waller factor or B-factor. Although numerous works have been addressed on theoretical and computational studies of the B-factor profiles of proteins, the methods used for predicting B-factor values of nucleic acids, especially the complicated ribosomal RNAs (rRNAs), which are very functionally similar to proteins in providing matrix structures and in catalyzing biochemical reactions, still remain unexploited. In this article, we present a quantitative structure-flexibility relationship (QSFR) study with the aim at the quantitative prediction of rRNA B-factor based on primary sequences (sequence-based) and advanced structures (structure-based) by using both linear and nonlinear machine learning approaches, including partial least squares regression (PLS), least squares support vector machine (LSSVM), and Gaussian process (GP). By rigorously examining the performance and reliability of constructed statistical models and by comparing our models in detail to those developed previously for protein B-factors, we demonstrate that (i) rRNA B-factors could be predicted at a similar level of accuracy with that of protein, (ii) a structure-based approach performed much better as compared to sequence-based methods in modeling of rRNA B-factors, and (iii) rRNA flexibility is primarily governed by the local features of nonbonding potential landscapes, such as electrostatic and van der Waals forces.

Determination of ensemble-average pairwise root mean-square deviation from experimental B-factors

Root mean-square deviation (RMSD) after roto-translational least-squares fitting is a measure of global structural similarity of macromolecules used commonly. On the other hand, experimental x-ray B-factors are used frequently to study local structural heterogeneity and dynamics in macromolecules by providing direct information about root mean-square fluctuations (RMSF) that can also be calculated from molecular dynamics simulations. We provide a mathematical derivation showing that, given a set of conservative assumptions, a root mean-square ensemble-average of an all-against-all distribution of pairwise RMSD for a single molecular species, <RMSD(2)>(1/2), is directly related to average B-factors (<B>) and <RMSF(2)>(1/2). We show this relationship and explore its limits of validity on a heterogeneous ensemble of structures taken from molecular dynamics simulations of villin headpiece generated using distributed-computing techniques and the Folding@Home cluster. Our results provide a basis for quantifying global structural diversity of macromolecules in crystals directly from x-ray experiments, and we show this on a large set of structures taken from the Protein Data Bank. In particular, we show that the ensemble-average pairwise backbone RMSD for a microscopic ensemble underlying a typical protein x-ray structure is approximately 1.1 A, under the assumption that the principal contribution to experimental B-factors is conformational variability.

Discrimination between closely related cellular metabolites by the SAM-I riboswitch

The SAM-I riboswitch is a cis-acting element of genetic control found in bacterial mRNAs that specifically binds S-adenosylmethionine (SAM). We previously determined the 2.9-A X-ray crystal structure of the effector-binding domain of this RNA element, revealing details of RNA-ligand recognition. To improve this structure, variations were made to the RNA sequence to alter lattice contacts, resulting in a 0.5-A improvement in crystallographic resolution and allowing for a more accurate refinement of the crystallographic model. The basis for SAM specificity was addressed by a structural analysis of the RNA complexed to S-adenosylhomocysteine (SAH) and sinefungin and by measuring the affinity of SAM and SAH for a series of mutants using isothermal titration calorimetry. These data illustrate the importance of two universally conserved base pairs in the RNA that form electrostatic interactions with the positively charged sulfonium group of SAM, thereby providing a basis for discrimination between SAM and SAH.

Pathways and mechanisms for product release in the engineered haloalkane dehalogenases explored using classical and random acceleration molecular dynamics simulations

Eight mutants of the DhaA haloalkane dehalogenase carrying mutations at the residues lining two tunnels, previously observed by protein X-ray crystallography, were constructed and biochemically characterized. The mutants showed distinct catalytic efficiencies with the halogenated substrate 1,2,3-trichloropropane. Release pathways for the two dehalogenation products, 2,3-dichloropropane-1-ol and the chloride ion, and exchange pathways for water molecules, were studied using classical and random acceleration molecular dynamics simulations. Five different pathways, denoted p1, p2a, p2b, p2c, and p3, were identified. The individual pathways showed differing selectivity for the products: the chloride ion releases solely through p1, whereas the alcohol releases through all five pathways. Water molecules play a crucial role for release of both products by breakage of their hydrogen-bonding interactions with the active-site residues and shielding the charged chloride ion during its passage through a hydrophobic tunnel. Exchange of the chloride ions, the alcohol product, and the waters between the buried active site and the bulk solvent can be realized by three different mechanisms: (i) passage through a permanent tunnel, (ii) passage through a transient tunnel, and (iii) migration through a protein matrix. We demonstrate that the accessibility of the pathways and the mechanisms of ligand exchange were modified by mutations. Insertion of bulky aromatic residues in the tunnel corresponding to pathway p1 leads to reduced accessibility to the ligands and a change in mechanism of opening from permanent to transient. We propose that engineering the accessibility of tunnels and the mechanisms of ligand exchange is a powerful strategy for modification of the functional properties of enzymes with buried active sites.

Ligand-protein docking with water molecules

The presence of water molecules plays an important role in the accuracy of ligand-protein docking predictions. Comprehensive docking simulations have been performed on a large set of ligand-protein complexes whose crystal structures contain water molecules in their binding sites. Only those water molecules found in the immediate vicinity of both the ligand and the protein were considered. We have investigated whether prior optimization of the orientation of water molecules in either the presence or absence of the bound ligand has any effect on the accuracy of docking predictions. We have observed a statistically significant overall increase in accuracy when water molecules are included during docking simulations and have found this to be independent of the method of optimization of the orientation of water molecules. These results confirm the importance of including water molecules whenever possible in a ligand-protein docking simulation. Our findings also reveal that prior optimization of the orientation of water molecules, in the absence of any bound ligand, does not have a detrimental effect on the improved accuracy of ligand-protein docking. This is important, given the use of docking simulations to predict the binding modes of new ligands or drug molecules.

Statistical and conformational analysis of the electron density of protein side chains

Protein side chains make most of the specific contacts between proteins and other molecules, and their conformational properties have been studied for many years. These properties have been analyzed primarily in the form of rotamer libraries, which cluster the observed conformations into groups and provide frequencies and average dihedral angles for these groups. In recent years, these libraries have improved with higher resolution structures and using various criteria such as high thermal factors to eliminate side chains that may be misplaced within the crystallographic model coordinates. Many of these side chains have highly non-rotameric dihedral angles. The origin of side chains with high B-factors and/or with non-rotameric dihedral angles is of interest in the determination of protein structures and in assessing the prediction of side chain conformations. In this paper, using a statistical analysis of the electron density of a large set of proteins, it is shown that: (1) most non-rotameric side chains have low electron density compared to rotameric side chains; (2) up to 15% of chi1 non-rotameric side chains in PDB models can clearly be fit to density at a single rotameric conformation and in some cases multiple rotameric conformations; (3) a further 47% of non-rotameric side chains have highly dispersed electron density, indicating potentially interconverting rotameric conformations; (4) the entropy of these side chains is close to that of side chains annotated as having more than one chi(1) rotamer in the crystallographic model; (5) many rotameric side chains with high entropy clearly show multiple conformations that are not annotated in the crystallographic model. These results indicate that modeling of side chains alternating between rotamers in the electron density is important and needs further improvement, both in structure determination and in structure prediction.

Protein crystallography under xenon and nitrous oxide pressure: comparison with in vivo pharmacology studies and implications for the mechanism of inhaled anesthetic action

In contrast with most inhalational anesthetics, the anesthetic gases xenon (Xe) and nitrous oxide (N(2)O) act by blocking the N-methyl-d-aspartate (NMDA) receptor. Using x-ray crystallography, we examined the binding characteristics of these two gases on two soluble proteins as structural models: urate oxidase, which is a prototype of a variety of intracellular globular proteins, and annexin V, which has structural and functional characteristics that allow it to be considered as a prototype for the NMDA receptor. The structure of these proteins complexed with Xe and N(2)O were determined. One N(2)O molecule or one Xe atom binds to the same main site in both proteins. A second subsite is observed for N(2)O in each case. The gas-binding sites are always hydrophobic flexible cavities buried within the monomer. Comparison of the effects of Xe and N(2)O on urate oxidase and annexin V reveals an interesting relationship with the in vivo pharmacological effects of these gases, the ratio of the gas-binding sites' volume expansion and the ratio of the narcotic potency being similar. Given these data, we propose that alterations of cytosolic globular protein functions by general anesthetics would be responsible for the early stages of anesthesia such as amnesia and hypnosis and that additional alterations of ion-channel membrane receptor functions are required for deeper effects that progress to "surgical" anesthesia.

Cofactor assisted gating mechanism in the active site of NADH oxidase from Thermus thermophilus

NADH oxidase (NOX) from Thermus thermophilus is a member of a structurally homologous flavoprotein family of nitroreductases and flavin reductases. The importance of local conformational dynamics in the active site of NOX has been recently demonstrated. The enzyme activity was increased by 250% in the presence of 1 M urea with no apparent perturbation of the native structure of the protein. The present in silico results correlate with the in vitro data and suggest the possible explanation about the effect of urea on NOX activity at the molecular level. Both, X-ray structure and molecular dynamics (MD) simulations, show open conformation of the active site represented by approximately 0.9 nm distance between the indole ring of Trp47 and the isoalloxazine ring of FMN412. In this conformation, the substrate molecule can bind in the active site without sterical restraints. MD simulations also indicate more stable conformation of the active site called "closed" conformation. In this conformation, Trp47 and the isoalloxazine ring of FMN412 are so close to each other (approximately 0.5 nm) that the substrate molecule is unable to bind between them without perturbing this conformation. The open/close transition of the active site between Trp47 and the flavin ring is accompanied by release of the "tightly" bound water molecule from the active site--cofactor assisted gating mechanism. The presence of urea in aqueous solutions of NOX prohibits closing of the active site and even unlocks the closed active site because of the concomitant binding of a urea molecule in the active site cavity. The binding of urea in the active site is stabilized by formation of one/two persistent hydrogen bonds involving the carbonyl group of the urea molecule. Our report represents the first MD study of an enzyme from the novel flavoprotein family of nitroreductases and flavin reductases. The common occurrence of aromatic residues covering the active sites in homologous enzymes suggests the possibility of a general gating mechanism and the importance of local dynamics within this flavoprotein family.

The ins and outs of cytochrome P450s

The active site of cytochromes P450 is situated deep inside the protein next to the heme cofactor. Consequently, enzyme specificity and kinetics can be influenced by how substrates pass through the protein to access the active site and how products egress from the active site. We previously analysed the channels between the active site and the protein surface in P450 crystal structures available in October 2003 [R.C. Wade, P.J. Winn, I. Schlichting, Sudarko, A survey of active site access channels in cytochromes P450, J. Inorg. Biochem. 98 (2004) 1175-1182]. Since then, 52 new P450 structures have been made available, including entries for ten isozymes for which structures were not previously available. We present an updated survey covering all P450 crystal structures available in March 2006. This survey shows channels not observed earlier in crystal structures, some of which were identified in previous molecular dynamics simulations. The crystal structures demonstrate how some of the channels can merge when the protein structure opens up resulting in a wide cleft to the active site, caused largely by movements of the F-G helix-loop-helix and the B-C loop. Significant differences were observed between the channels in the crystal structures of the mammalian and bacterial enzymes. The multiplicity of channels suggests possibilities for substrate channelling to and from the P450s.

Prediction of protein B-factor profiles

The polypeptide backbones and side chains of proteins are constantly moving due to thermal motion and the kinetic energy of the atoms. The B-factors of protein crystal structures reflect the fluctuation of atoms about their average positions and provide important information about protein dynamics. Computational approaches to predict thermal motion are useful for analyzing the dynamic properties of proteins with unknown structures. In this article, we utilize a novel support vector regression (SVR) approach to predict the B-factor distribution (B-factor profile) of a protein from its sequence. We explore schemes for encoding sequences and various settings for the parameters used in SVR. Based on a large dataset of high-resolution proteins, our method predicts the B-factor distribution with a Pearson correlation coefficient (CC) of 0.53. In addition, our method predicts the B-factor profile with a CC of at least 0.56 for more than half of the proteins. Our method also performs well for classifying residues (rigid vs. flexible). For almost all predicted B-factor thresholds, prediction accuracies (percent of correctly predicted residues) are greater than 70%. These results exceed the best results of other sequence-based prediction methods.

Protein flexibility and rigidity predicted from sequence

Structural flexibility has been associated with various biological processes such as molecular recognition and catalytic activity. In silico studies of protein flexibility have attempted to characterize and predict flexible regions based on simple principles. B-values derived from experimental data are widely used to measure residue flexibility. Here, we present the most comprehensive large-scale analysis of B-values. We used this analysis to develop a neural network-based method that predicts flexible-rigid residues from amino acid sequence. The system uses both global and local information (i.e., features from the entire protein such as secondary structure composition, protein length, and fraction of surface residues, and features from a local window of sequence-consecutive residues). The most important local feature was the evolutionary exchange profile reflecting sequence conservation in a family of related proteins. To illustrate its potential, we applied our method to 4 different case studies, each of which related our predictions to aspects of function. The first 2 were the prediction of regions that undergo conformational switches upon environmental changes (switch II region in Ras) and the prediction of surface regions, the rigidity of which is crucial for their function (tunnel in propeller folds). Both were correctly captured by our method. The third study established that residues in active sites of enzymes are predicted by our method to have unexpectedly low B-values. The final study demonstrated how well our predictions correlated with NMR order parameters to reflect motion. Our method had not been set up to address any of the tasks in those 4 case studies. Therefore, we expect that this method will assist in many attempts at inferring aspects of function.

Local flexibility in molecular function paradigm

It is generally accepted that the functional activity of biological macromolecules requires tightly packed three-dimensional structures. Recent theoretical and experimental evidence indicates, however, the importance of molecular flexibility for the proper functioning of some proteins. We examined high resolution structures of proteins in various functional categories with respect to the secondary structure assessment. The latter was considered as a characteristic of the inherent flexibility of a polypeptide chain. We found that the proteins in functionally competent conformational states might be comprised of 20-70% flexible residues. For instance, proteins involved in gene regulation, e.g. transcription factors, are on average largely disordered molecules with over 60% of amino acids residing in "coiled" configurations. In contrast, oxygen transporters constitute a class of relatively rigid molecules with only 30% of residues being locally flexible. Phylogenic comparison of a large number of protein families with respect to the propagation of secondary structure illuminates the growing role of the local flexibility in organisms of greater complexity. Furthermore the local flexibility in protein molecules appears to be dependent on the molecular confinement and is essentially larger in extracellular proteins.