Three-dimensional computation of atom depth in complex molecular structures

Solution Structure Ensembles of the Open and Closed Forms of the ∼130 kDa Enzyme I via AlphaFold Modeling, Coarse Grained Simulations, and NMR

Large-scale interdomain rearrangements are essential to protein function, governing the activity of large enzymes and molecular machineries. Yet, obtaining an atomic-resolution understanding of how the relative domain positioning is affected by external stimuli is a hard task in modern structural biology. Here, we show that combining structural modeling by AlphaFold2 with coarse-grained molecular dynamics simulations and NMR residual dipolar coupling data is sufficient to characterize the spatial domain organization of bacterial enzyme I (EI), a ∼130 kDa multidomain oligomeric protein that undergoes large-scale conformational changes during its catalytic cycle. In particular, we solve conformational ensembles for EI at two different experimental temperatures and demonstrate that a lower temperature favors sampling of the catalytically competent closed state of the enzyme. These results suggest a role for conformational entropy in the activation of EI and demonstrate the ability of our protocol to detect and characterize the effect of external stimuli (such as mutations, ligand binding, and post-translational modifications) on the interdomain organization of multidomain proteins. We expect the ensemble refinement protocol described here to be easily transferrable to the investigation of the structure and dynamics of other uncharted multidomain systems and have assembled a Google Colab page (https://potoyangroup.github.io/Seq2Ensemble/) to facilitate implementation of the presented methodology elsewhere.

Structure-Function Relationship of Homogentisate 1,2-dioxygenase: Understanding the Genotype-Phenotype Correlations in the Rare Genetic Disease Alkaptonuria

Alkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in organs, which occurs because the homogentisate 1,2-dioxygenase (HGD) enzyme is not functional due to gene variants. Over time, HGA oxidation and accumulation cause the formation of the ochronotic pigment, a deposit that provokes tissue degeneration and organ malfunction. Here, we report a comprehensive review of the variants so far reported, the structural studies on the molecular consequences of protein stability and interaction, and molecular simulations for pharmacological chaperones as protein rescuers. Moreover, evidence accumulated so far in alkaptonuria research will be re-proposed as the bases for a precision medicine approach in a rare disease.

Dynamic allostery in substrate binding by human thymidylate synthase

Human thymidylate synthase (hTS) is essential for DNA replication and therefore a therapeutic target for cancer. Effective targeting requires knowledge of the mechanism(s) of regulation of this 72 kDa homodimeric enzyme. Here, we investigate the mechanism of binding cooperativity of the nucleotide substrate. We have employed exquisitely sensitive methyl-based CPMG and CEST NMR experiments enabling us to identify residues undergoing bifurcated linear 3-state exchange, including concerted switching between active and inactive conformations in the apo enzyme. The inactive state is populated to only ~1.3%, indicating that conformational selection contributes negligibly to the cooperativity. Instead, methyl rotation axis order parameters, determined by ²H transverse relaxation rates, suggest that rigidification of the enzyme upon substrate binding is responsible for the entropically-driven cooperativity. Lack of the rigidification in product binding and substrate binding to an N-terminally truncated enzyme, both non-cooperative, support this idea. In addition, the lack of this rigidification in the N-terminal truncation indicates that interactions between the flexible N-terminus and the rest of the protein, which are perturbed by substrate binding, play a significant role in the cooperativity—a novel mechanism of dynamic allostery. Together, these findings yield a rare depth of insight into the substrate binding cooperativity of an essential enzyme.

Structural Bioinformatic Survey of Protein-Small Molecule Interfaces Delineates the Role of Glycine in Surface Pocket Formation

With a structural bioinformatic approach, we have explored amino acid compositions at PISA defined interfaces between small molecules and proteins that are contained in an optimized subset of 11,351 PDB files. The use of a series of restrictions, to prevent redundancy and biases from interactions between amino acids with charged side chains and ions, yielded a final data set of 45,230 protein-small molecule interfaces. We have compared occurrences of natural amino acids in surface exposed regions and binding sites for all the proteins of our data set. From our structural bioinformatic survey, the most relevant signal arose from the unexpected Gly abundance at enzyme catalytic sites. This finding suggested that Gly must have a fundamental role in stabilizing concave protein surface moieties. Subsequently, we have tried to predict the effect of in silico Gly mutations in hen egg white lysozyme to optimize those conditions that can reshape the protein surface with the appearance of new pockets. Replacing amino acids having bulky side chains with Gly in specific protein regions seems a feasible way for designing proteins with additional surface pockets, which can alter protein surface dynamics, therefore, representing controllable switches for protein activity.

The anatomy of unfolding of Yfh1 is revealed by site-specific fold stability analysis measured by 2D NMR spectroscopy

Most techniques allow detection of protein unfolding either by following the behaviour of single reporters or as an averaged all-or-none process. We recently added 2D NMR spectroscopy to the well-established techniques able to obtain information on the process of unfolding using resonances of residues in the hydrophobic core of a protein. Here, we questioned whether an analysis of the individual stability curves from each resonance could provide additional site-specific information. We used the Yfh1 protein that has the unique feature to undergo both cold and heat denaturation at temperatures above water freezing at low ionic strength. We show that stability curves inconsistent with the average NMR curve from hydrophobic core residues mainly comprise exposed outliers that do nevertheless provide precious information. By monitoring both cold and heat denaturation of individual residues we gain knowledge on the process of cold denaturation and convincingly demonstrate that the two unfolding processes are intrinsically different.

Quantifying the thermodynamics of protein unfolding using 2D NMR spectroscopy

A topic that has attracted considerable interest in recent years is the possibility to perform thermodynamic studies of proteins directly in-cell or in complex environments which mimic the cellular interior. Nuclear magnetic resonance (NMR) could be an attractive technique for these studies but its applicability has so far been limited by technical issues. Here, we demonstrate that 2D NMR methods can be successfully applied to measure thermodynamic parameters provided that a suitable choice of the residues used for the calculation is made. We propose a new parameter, named RAD, which reflects the level of protection of a specific amide proton in the protein core and can guide through the selection of the resonances. We also suggest a way to calibrate the volumes to become independent of technical limitations. The methodology we propose leads to stability curves comparable to that calculated from CD data and provides a new tool for thermodynamic measurements in complex environments.

A possible strategy to fight COVID-19: Interfering with spike glycoprotein trimerization

The recent release of COVID-19 spike glycoprotein allows detailed analysis of the structural features that are required for stabilizing the infective form of its quaternary assembly. Trying to disassemble the trimeric structure of COVID-19 spike glycoprotein, we analyzed single protomer surfaces searching for concave moieties that are located at the three protomer-protomer interfaces. The presence of some druggable pockets at these interfaces suggested that some of the available drugs in Drug Bank could destabilize the quaternary spike glycoprotein formation by binding to these pockets, therefore interfering with COVID-19 life cycle. The approach we propose here can be an additional strategy to fight against the deadly virus. Ligands of COVID-19 spike glycoprotein that we have predicted in the present computational investigation, might be the basis for new experimental studies in vitro and in vivo.

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Search for ligand binding sites in COVID-19 S glycoprotein protomeric interfaces.

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Structure based ligand selection for interfering to COVID-19 S glycoprotein assembly.

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Ligand-protomer docking simulation to find the best candidates for therapeutic use.

NMR Methods for Structural Characterization of Protein-Protein Complexes

Protein-protein interactions and the complexes thus formed are critical elements in a wide variety of cellular events that require an atomic-level description to understand them in detail. Such complexes typically constitute challenging systems to characterize and drive the development of innovative biophysical methods. NMR spectroscopy techniques can be applied to extract atomic resolution information on the binding interfaces, intermolecular affinity, and binding-induced conformational changes in protein-protein complexes formed in solution, in the cell membrane, and in large macromolecular assemblies. Here we discuss experimental techniques for the characterization of protein-protein complexes in both solution NMR and solid-state NMR spectroscopy. The approaches include solvent paramagnetic relaxation enhancement and chemical shift perturbations (CSPs) for the identification of binding interfaces, and the application of intermolecular nuclear Overhauser effect spectroscopy and residual dipolar couplings to obtain structural constraints of protein-protein complexes in solution. Complementary methods in solid-state NMR are described, with emphasis on the versatility provided by heteronuclear dipolar recoupling to extract intermolecular constraints in differentially labeled protein complexes. The methods described are of particular relevance to the analysis of membrane proteins, such as those involved in signal transduction pathways, since they can potentially be characterized by both solution and solid-state NMR techniques, and thus outline key developments in this frontier of structural biology.

Glycine-induced formation and druggability score prediction of protein surface pockets

Nowadays, it is well established that most of the human diseases which are not related to pathogen infections have their origin from DNA disorders. Thus, DNA mutations, waiting for the availability of CRISPR-like remedies, will propagate into proteomics, offering the possibility to select natural or synthetic molecules to fight against the effects of malfunctioning proteins. Drug discovery, indeed, is a flourishing field of biotechnological research to improve human health, even though the development of a new drug is increasingly more expensive in spite of the massive use of informatics in Medicinal Chemistry. CRISPR technology adds new alternatives to cure diseases by removing DNA defects responsible of genome-related pathologies. In principle, the same technology, however, could also be exploited to induce protein mutations whose effects are controlled by the presence of suitable ligands. In this paper, a new idea is proposed for the realization of mutated proteins, on the surface of which more spacious transient pockets are formed and, therefore, are more suitable for hosting drugs. In particular, new allosteric sites are obtained by replacing amino-acids with bulky side chains with glycine, Gly, the smallest natural amino-acid. We also present a machine learning approach to evaluate the druggability score of new (or enlarged) pockets. Preliminary experimental results are very promising, showing that 10% of the sites created by the Gly-pipe software are druggable.

On Nature's Strategy for Assigning Genetic Code Multiplicity

Genetic code redundancy would yield, on the average, the assignment of three codons for each of the natural amino acids. The fact that this number is observed only for incorporating Ile and to stop RNA translation still waits for an overall explanation. Through a Structural Bioinformatics approach, the wealth of information stored in the Protein Data Bank has been used here to look for unambiguous clues to decipher the rationale of standard genetic code (SGC) in assigning from one to six different codons for amino acid translation. Leu and Arg, both protected from translational errors by six codons, offer the clearest clue by appearing as the most abundant amino acids in protein-protein and protein-nucleic acid interfaces. Other SGC hidden messages have been sought by analyzing, in a protein structure framework, the roles of over- and under-protected amino acids.

Studying the structure and dynamics of biomolecules by using soluble paramagnetic probes

Characterisation of the structure and dynamics of large biomolecules and biomolecular complexes by NMR spectroscopy is hampered by increasing overlap and severe broadening of NMR signals. As a consequence, the number of available NMR spectroscopy data is often sparse and new approaches to provide complementary NMR spectroscopy data are needed. Paramagnetic relaxation enhancements (PREs) obtained from inert and soluble paramagnetic probes (solvent PREs) provide detailed quantitative information about the solvent accessibility of NMR-active nuclei. Solvent PREs can be easily measured without modification of the biomolecule; are sensitive to molecular structure and dynamics; and are therefore becoming increasingly powerful for the study of biomolecules, such as proteins, nucleic acids, ligands and their complexes in solution. In this Minireview, we give an overview of the available solvent PRE probes and discuss their applications for structural and dynamic characterisation of biomolecules and biomolecular complexes.

Atom depth analysis delineates mechanisms of protein intermolecular interactions

The systematic analysis of amino acid distribution, performed inside a large set of resolved protein structures, sheds light on possible mechanisms driving non random protein-protein approaches. Protein Data Bank entries have been selected using as filters a series of restrictions ensuring that the shape of protein surface is not modified by interactions with large or small ligands. 3D atom depth has been evaluated for all the atoms of the 2,410 selected structures. The amino acid relative population in each of the structural layers formed by grouping atoms on the basis of their calculated depths, has been evaluated. We have identified seven structural layers, the inner ones reproducing the core of proteins and the outer one incorporating their most protruding moieties. Quantitative analysis of amino acid contents of structural layers identified, as expected, different behaviors. Atoms of Q, R, K, N, D residues are increasingly more abundant in going from core to surfaces. An opposite trend is observed for V, I, L, A, C, and G. An intermediate behavior is exhibited by P, S, T, M, W, H, F and Y. The outer structural layer hosts predominantly E and K residues whose charged moieties, protruding from outer regions of the protein surface, reorient free from steric hindrances, determining specific electrodynamics maps. This feature may represent a protein signature for long distance effects, driving the formation of encounter complexes and the eventual short distance approaches that are required for protein-protein functional interactions.

Adepth: New Representation and its implications for atomic depths of macromolecules

We applied the signed distance function (SDF) for representing the depths of atoms in a macromolecule. The calculations of SDF values were performed on grid points in a rectangular box that accommodates the macromolecule. The depth for an atom inside the molecule was then obtained as a result of tri-linear interpolation of SDF values at the nearest grid points surrounding the atom. For testing the performance of present program Adepth, we have constructed an artificial molecule whose atomic depths are known as the gold standard for accuracy assessments. On average, our results showed that Adepth reached an accuracy of 1.6% at 0.5 Å of grid spacing, whereas the current reference server DEPTH reached 7.5%. The Adepth program provides both depth and height representations; it is capable of computing iso-surfaces for atomic depths and presenting graphical view of macromolecular shape at some distance away from the surface. Web interface is available at http://biodev.cea.fr/adepth.

Enzymatic excision of uracil residues in nucleosomes depends on the local DNA structure and dynamics

The excision of uracil bases from DNA is accomplished by the enzyme uracil DNA glycosylase (UNG). Recognition of uracil bases in free DNA is facilitated by uracil base pair dynamics, but it is not known whether this same mechanistic feature is relevant for detection and excision of uracil residues embedded in nucleosomes. Here we investigate this question using nucleosome core particles (NCPs) generated from Xenopus laevis histones and the high-affinity "Widom 601" positioning sequence. The reactivity of uracil residues in NCPs under steady-state multiple-turnover conditions was generally decreased compared to that of free 601 DNA, mostly because of anticipated steric effects of histones. However, some sites in NCPs had equal or even greater reactivity than free DNA, and the observed reactivities were not readily explained by simple steric considerations or by global DNA unwrapping models for nucleosome invasion. In particular, some reactive uracils were found in occluded positions, while some unreactive uracils were found in exposed positions. One feature of many exposed reactive sites is a wide DNA minor groove, which allows penetration of a key active site loop of the enzyme. In single-turnover kinetic measurements, multiphasic reaction kinetics were observed for several uracil sites, where each kinetic transient was independent of the UNG concentration. These kinetic measurements, and supporting structural analyses, support a mechanism in which some uracils are transiently exposed to UNG by local, rate-limiting nucleosome conformational dynamics, followed by rapid trapping of the exposed state by the enzyme. We present structural models and plausible reaction mechanisms for the reaction of UNG at three distinct uracil sites in the NCP.

NMR studies on structure and dynamics of the monomeric derivative of BS-RNase: new insights for 3D domain swapping

Three-dimensional domain swapping is a common phenomenon in pancreatic-like ribonucleases. In the aggregated state, these proteins acquire new biological functions, including selective cytotoxicity against tumour cells. RNase A is able to dislocate both N- and C-termini, but usually this process requires denaturing conditions. In contrast, bovine seminal ribonuclease (BS-RNase), which is a homo-dimeric protein sharing 80% of sequence identity with RNase A, occurs natively as a mixture of swapped and unswapped isoforms. The presence of two disulfides bridging the subunits, indeed, ensures a dimeric structure also to the unswapped molecule. In vitro, the two BS-RNase isoforms interconvert under physiological conditions. Since the tendency to swap is often related to the instability of the monomeric proteins, in these paper we have analysed in detail the stability in solution of the monomeric derivative of BS-RNase (mBS) by a combination of NMR studies and Molecular Dynamics Simulations. The refinement of NMR structure and relaxation data indicate a close similarity with RNase A, without any evidence of aggregation or partial opening. The high compactness of mBS structure is confirmed also by H/D exchange, urea denaturation, and TEMPOL mapping of the protein surface. The present extensive structural and dynamic investigation of (monomeric) mBS did not show any experimental evidence that could explain the known differences in swapping between BS-RNase and RNase A. Hence, we conclude that the swapping in BS-RNase must be influenced by the distinct features of the dimers, suggesting a prominent role for the interchain disulfide bridges.

Cosolute paramagnetic relaxation enhancements detect transient conformations of human uracil DNA glycosylase (hUNG)

The human DNA repair enzyme uracil DNA glycosylase (hUNG) locates and excises rare uracil bases that arise in DNA from cytosine deamination or through dUTP incorporation by DNA polymerases. Previous NMR studies of hUNG have revealed millisecond time scale dynamic transitions in the enzyme-nonspecific DNA complex, but not the free enzyme, that were ascribed to a reversible clamping motion of the enzyme as it scans along short regions of duplex DNA in its search for uracil. Here we further probe the properties of the nonspecific DNA binding surface of {(2)H(12)C}{(15)N}-labeled hUNG using a neutral chelate of a paramagnetic Gd(3+) cosolute (Gd(HP-DO3A)). Overall, the measured paramagnetic relaxation enhancements (PREs) on R(2) of the backbone amide protons for free hUNG and its DNA complex were in good agreement with those calculated based on their relative exposure observed in the crystal structures of both enzyme forms. However, the calculated PREs systematically underestimated the experimental PREs by large amounts in discrete regions implicated in DNA recognition and catalysis: active site loops involved in DNA recognition (268-274, 246-250), the uracil binding pocket (143-148, 169-170), a transient extrahelical base binding site (214-216), and a remote hinge region (129-132) implicated in dynamic clamping. These reactive hot spots were not correlated with structural, hydrophobic, or solvent exchange properties that might be common to these regions, leaving the possibility that the effects arise from dynamic sampling of exposed conformations that are distinct from the static structures. Consistent with this suggestion, the above regions have been previously shown to be flexible based on relaxation dispersion measurements and course-grained normal-mode analysis. A model is suggested where the intrinsic dynamic properties of these regions allows sampling of transient conformations where the backbone amide groups have greater average exposure to the cosolute as compared to the static structures. We conclude that PREs derived from the paramagnetic cosolute reveal dynamic hot spots in hUNG and that these regions are highly correlated with substrate binding and recognition.

Improved sequence-based prediction of strand residues

Accurate identification of strand residues aids prediction and analysis of numerous structural and functional aspects of proteins. We propose a sequence-based predictor, BETArPRED, which improves prediction of strand residues and β-strand segments. BETArPRED uses a novel design that accepts strand residues predicted by SSpro and predicts the remaining positions utilizing a logistic regression classifier with nine custom-designed features. These are derived from the primary sequence, the secondary structure (SS) predicted by SSpro, PSIPRED and SPINE, and residue depth as predicted by RDpred. Our features utilize certain local (window-based) patterns in the predicted SS and combine information about the predicted SS and residue depth. BETArPRED is evaluated on 432 sequences that share low identity with the training chains, and on the CASP8 dataset. We compare BETArPRED with seven modern SS predictors, and the top-performing automated structure predictor in CASP8, the ZHANG-server. BETArPRED provides statistically significant improvements over each of the SS predictors; it improves prediction of strand residues and β-strands, and it finds β-strands that were missed by the other methods. When compared with the ZHANG-server, we improve predictions of strand segments and predict more actual strand residues, while the other predictor achieves higher rate of correct strand residue predictions when under-predicting them.

A structurally driven analysis of thiol reactivity in mammalian albumins

Understanding the structural basis of protein redox activity is still an open question. Hence, by using a structural genomics approach, different albumins have been chosen to correlate protein structural features with the corresponding reaction rates of thiol exchange between albumin and disulfide DTNB. Predicted structures of rat, porcine, and bovine albumins have been compared with the experimentally derived human albumin. High structural similarity among these four albumins can be observed, in spite of their markedly different reactivity with DTNB. Sequence alignments offered preliminary hints on the contributions of sequence-specific local environments modulating albumin reactivity. Molecular dynamics simulations performed on experimental and predicted albumin structures reveal that thiolation rates are influenced by hydrogen bonding pattern and stability of the acceptor C34 sulphur atom with donor groups of nearby residues. Atom depth evolution of albumin C34 thiol groups has been monitored during Molecular Dynamic trajectories. The most reactive albumins appeared also the ones presenting the C34 sulphur atom on the protein surface with the highest accessibility. High C34 sulphur atom reactivity in rat and porcine albumins seems to be determined by the presence of additional positively charged amino acid residues favoring both the C34 S⁻ form and the approach of DTNB.

Concentration of specific amino acids at the catalytic/active centers of highly-conserved "housekeeping" enzymes of central metabolism in archaea, bacteria and Eukaryota: is there a widely conserved chemical signal of prebiotic assembly?

In alignments of 1969 protein sequences the amino acid glycine and others were found concentrated at most-conserved sites within approximately 15 A of catalytic/active centers (C/AC) of highly conserved kinases, dehydrogenases or lyases of Archaea, Bacteria and Eukaryota. Lysine and glutamic acid were concentrated at least-conserved sites furthest from their C/ACs. Logistic-regression analyses corroborated the "movement" of glycine towards and lysine away from their C/ACs: the odds of a glycine occupying a site were decreased by 19%, while the odds for a lysine were increased by 53%, for every 10 A moving away from the C/AC. Average conservation of MSA consensus sites was highest surrounding the C/AC and directly decreased in transition toward model's peripheries. Findings held with statistical confidence using sequences restricted to individual Domains or enzyme classes or to both. Our data describe variability in the rate of mutation and likelihoods for phylogenetic trees based on protein sequence data and endorse the extension of substitution models by incorporating data on conservation and distance to C/ACs rather than only using cumulative levels. The data support the view that in the most-conserved environment immediately surrounding the C/AC of taxonomically distant and highly conserved essential enzymes of central metabolism there are amino acids whose identity and degree of occupancy is similar to a proposed amino acid set and frequency associated with prebiotic evolution.

Shape and evolution of thermostable protein structure

Organisms evolved at high temperatures must maintain their proteins' structures in the face of increased thermal disorder. This challenge results in differences in residue utilization and overall structure. Focusing on thermostable/mesostable pairs of homologous structures, we have examined these differences using novel geometric measures: specifically burial depth (distance from the molecular surface to each atom) and travel depth (distance from the convex hull to the molecular surface that avoids the protein interior). These along with common metrics like packing and Wadell Sphericity are used to gain insight into the constraints experienced by thermophiles. Mean travel depth of hyperthermostable proteins is significantly less than that of their mesostable counterparts, indicating smaller, less numerous and less deep pockets. The mean burial depth of hyperthermostable proteins is significantly higher than that of mesostable proteins indicating that they bury more atoms further from the surface. The burial depth can also be tracked on the individual residue level, adding a finer level of detail to the standard exposed surface area analysis. Hyperthermostable proteins for the first time are shown to be more spherical than their mesostable homologues, regardless of when and how they adapted to extreme temperature. Additionally, residue specific burial depth examinations reveal that charged residues stay unburied, most other residues are slightly more buried and Alanine is more significantly buried in hyperthermostable proteins.

Prodepth: predict residue depth by support vector regression approach from protein sequences only

Residue depth (RD) is a solvent exposure measure that complements the information provided by conventional accessible surface area (ASA) and describes to what extent a residue is buried in the protein structure space. Previous studies have established that RD is correlated with several protein properties, such as protein stability, residue conservation and amino acid types. Accurate prediction of RD has many potentially important applications in the field of structural bioinformatics, for example, facilitating the identification of functionally important residues, or residues in the folding nucleus, or enzyme active sites from sequence information. In this work, we introduce an efficient approach that uses support vector regression to quantify the relationship between RD and protein sequence. We systematically investigated eight different sequence encoding schemes including both local and global sequence characteristics and examined their respective prediction performances. For the objective evaluation of our approach, we used 5-fold cross-validation to assess the prediction accuracies and showed that the overall best performance could be achieved with a correlation coefficient (CC) of 0.71 between the observed and predicted RD values and a root mean square error (RMSE) of 1.74, after incorporating the relevant multiple sequence features. The results suggest that residue depth could be reliably predicted solely from protein primary sequences: local sequence environments are the major determinants, while global sequence features could influence the prediction performance marginally. We highlight two examples as a comparison in order to illustrate the applicability of this approach. We also discuss the potential implications of this new structural parameter in the field of protein structure prediction and homology modeling. This method might prove to be a powerful tool for sequence analysis.

Protein-thiol substitution or protein dethiolation by thiol/disulfide exchange reactions: the albumin model

Dethiolation experiments of thiolated albumin with thionitrobenzoic acid and thiols (glutathione, cysteine, homocysteine) were carried out to understand the role of albumin in plasma distribution of thiols and disulfide species by thiol/disulfide (SH/SS) exchange reactions. During these experiments we observed that thiolated albumin underwent thiol substitution (Alb-SS-X+RSH<-->Alb-SS-R+XSH) or dethiolation (Alb-SS-X+XSH<-->Alb-SH+XSSX), depending on the different pK(a) values of thiols involved in protein-thiol mixed disulfides (Alb-SS-X). It appeared in these reactions that the compound with lower pK(a) in mixed disulfide was a good leaving group and that the pK(a) differences dictated the kind of reaction (substitution or dethiolation). Thionitrobenzoic acid, bound to albumin by mixed disulfide (Alb-TNB), underwent rapid substitution after thiol addition, forming the corresponding Alb-SS-X (peaks at 0.25-1 min). In turn, Alb-SS-X were dethiolated by the excess nonprotein SH groups because of the lower pK(a) value in mixed disulfide with respect to that of other thiols. Dethiolation of Alb-SS-X was accompanied by formation of XSSX and Alb-SH up to equilibrium levels at 35 min, which were different for each thiol. Structures by molecular simulation of thiolated albumin, carried out for understanding the role of sulfur exposure in mixed disulfides in dethiolation process, evidenced that the sulfur exposure is important for the rate but not for determining the kind of reaction (substitution or dethiolation). Our data underline the contribution of SH/SS exchanges to determine levels of various thiols as reduced and oxidized species in human plasma.

The importance of discerning shape in molecular pharmacology

Shape is a fundamentally important molecular feature that often determines the fate of a compound in terms of molecular interactions with preferred and non-preferred biological targets. Complementarity of binding in small-molecule-protein, peptide-receptor, antigen-antibody and protein-protein interactions is the key to life and survival and also to targeting molecules with bioactivity. We review the application of shape in various biological systems such as substrate recognition, ligand specificity or selectivity and antibody recognition in the context of computational methods such as docking, quantitative structure-activity relationships, classification models and similarity-search algorithms. These in silico pharmacology methods have recently demonstrated the importance and applicability of determining molecular shape in drug discovery, virtual screening and predictive toxicology. The results from recently published studies show that shape and shape-based descriptors are at least as useful as other traditional molecular descriptors.

Sequence based residue depth prediction using evolutionary information and predicted secondary structure

Background

Residue depth allows determining how deeply a given residue is buried, in contrast to the solvent accessibility that differentiates between buried and solvent-exposed residues. When compared with the solvent accessibility, the depth allows studying deep-level structures and functional sites, and formation of the protein folding nucleus. Accurate prediction of residue depth would provide valuable information for fold recognition, prediction of functional sites, and protein design.

Results

A new method, RDPred, for the real-value depth prediction from protein sequence is proposed. RDPred combines information extracted from the sequence, PSI-BLAST scoring matrices, and secondary structure predicted with PSIPRED. Three-fold/ten-fold cross validation based tests performed on three independent, low-identity datasets show that the distance based depth (computed using MSMS) predicted by RDPred is characterized by 0.67/0.67, 0.66/0.67, and 0.64/0.65 correlation with the actual depth, by the mean absolute errors equal 0.56/0.56, 0.61/0.60, and 0.58/0.57, and by the mean relative errors equal 17.0%/16.9%, 18.2%/18.1%, and 17.7%/17.6%, respectively. The mean absolute and the mean relative errors are shown to be statistically significantly better when compared with a method recently proposed by Yuan and Wang [Proteins 2008; 70:509–516]. The results show that three-fold cross validation underestimates the variability of the prediction quality when compared with the results based on the ten-fold cross validation. We also show that the hydrophilic and flexible residues are predicted more accurately than hydrophobic and rigid residues. Similarly, the charged residues that include Lys, Glu, Asp, and Arg are the most accurately predicted. Our analysis reveals that evolutionary information encoded using PSSM is characterized by stronger correlation with the depth for hydrophilic amino acids (AAs) and aliphatic AAs when compared with hydrophobic AAs and aromatic AAs. Finally, we show that the secondary structure of coils and strands is useful in depth prediction, in contrast to helices that have relatively uniform distribution over the protein depth. Application of the predicted residue depth to prediction of buried/exposed residues shows consistent improvements in detection rates of both buried and exposed residues when compared with the competing method. Finally, we contrasted the prediction performance among distance based (MSMS and DPX) and volume based (SADIC) depth definitions. We found that the distance based indices are harder to predict due to the more complex nature of the corresponding depth profiles.

Conclusion

The proposed method, RDPred, provides statistically significantly better predictions of residue depth when compared with the competing method. The predicted depth can be used to provide improved prediction of both buried and exposed residues. The prediction of exposed residues has implications in characterization/prediction of interactions with ligands and other proteins, while the prediction of buried residues could be used in the context of folding predictions and simulations.

Guanidinoneomycin B recognition of an HIV-1 RNA helix

Aminoglycoside antibiotics are small-molecule drugs that bind RNA. The affinity and specificity of aminoglycoside binding to RNA can be increased through chemical modification, such as guanidinylation. Here, we report the binding of guanidinoneomycin B (GNB) to an RNA helix from the HIV-1 frameshift site. The binding of GNB increases the melting temperature (T(m)) of the frameshift-site RNA by at least 10 degrees C, to a point at which a melting transition is not even observed in 2 M urea. A structure of the complex was obtained by using multidimensional heteronuclear NMR spectroscopic methods. We also used a novel paramagnetic-probe assay to identify the site of GNB binding to the surface of the RNA. GNB makes major-groove contacts to two sets of Watson-Crick bases and is in van der Waals contact with a highly structured ACAA tetraloop. Rings I and II of GNB fit into the major groove and form the binding interface with the RNA, whereas rings III and IV are exposed to the solvent and disordered. The binding of GNB causes a broadening of the major groove across the binding site.

Measuring the dynamic surface accessibility of RNA with the small paramagnetic molecule TEMPOL

The surface accessibility of macromolecules plays a key role in modulating molecular recognition events. RNA is a complex and dynamic molecule involved in many aspects of gene expression. However, there are few experimental methods available to measure the accessible surface of RNA. Here, we investigate the accessible surface of RNA using NMR and the small paramagnetic molecule TEMPOL. We investigated two RNAs with known structures, one that is extremely stable and one that is dynamic. For helical regions, the TEMPOL probing data correlate well with the predicted RNA surface, and the method is able to distinguish subtle variations in atom depths, such as the relative accessibility of pyrimidine versus purine aromatic carbon atoms. Dynamic motions are also detected by TEMPOL probing, and the method accurately reports a previously characterized pH-dependent conformational transition involving formation of a protonated C-A pair and base flipping. Some loop regions are observed to exhibit anomalously high accessibility, reflective of motions that are not evident within the ensemble of NMR structures. We conclude that TEMPOL probing can provide valuable insights into the surface accessibility and dynamics of RNA, and can also be used as an independent means of validating RNA structure and dynamics in solution.

Quantifying the relationship of protein burying depth and sequence

Protein burying depth (BD) is a structural descriptor that is exploited not only to find whether a residue is exposed or buried, but also to determine how deep a residue is buried. The widely used solvent accessible surface area is mainly focusing on the study of protein surface residues, while protein BD can provide more detailed information about the arrangement of buried residues, which may be used to study protein deep level structure and the formation of protein folding nucleus. In this work, we analyse the relationship of protein BD and sequences, and describe it by nonlinear functions estimated by support vector machines. We examine the functions by crossvalidation tests and find strong correlation between residue BD and local sequence environment. By further taking account the size of the molecule where a residue is located, we find that the correlation coefficient between predicted and observed depths improves from 0.60 to 0.65. Moreover, nearly half of the deepest 10% residues in a protein sequence can be correctly predicted. Our study suggests that a residue's burying extent is able to be predicted, to some degree, by itself and its local neighbouring residues. The methods used to estimate the sequence-depth functions are expected to become more useful in the investigation of protein structures and folding mechanism.

NMR studies of lysozyme surface accessibility by using different paramagnetic relaxation probes

Paramagnetic probes, whose approach to proteins can be monitored by nuclear magnetic resonance (NMR) studies, have been found to be of primary relevance for investigating protein surfaces' accessibility. Here, a Gd(III) neutral complex which contains two metal ions, [Gd2(L7)(H2O)2], is suggested as a paramagnetic probe particularly suited for systematic NMR investigation of protein surface accessibility, due to an expected high relaxivity and to the lack of electric charge which could favor specific interactions. Hen egg white lysozyme has been used as a model system to verify the absence of preferential approaches of this paramagnetic probe to specific protein moieties by comparing paramagnetic perturbation profiles of 1H-13C HSQC signals obtained in the presence of TEMPOL and [Gd2(L7)(H2O)2]. From the similarity of the measured paramagnetic perturbation profiles induced by the two different probes, specific interactions of [Gd2(L7)(H2O)2] with the enzyme could be ruled out. The large size of the latter probe is suggested to be responsible for the strong paramagnetic perturbations observed for CalphaH groups which are located in convex surface-exposed regions. The combined use of the two probes reveals fine details of the dynamics controlling their approach toward the protein surface.

MD and NMR studies of alpha-bungarotoxin surface accessibility

Protein surface accessibility represents a dimension of structural biology which has not been discussed in details so far, in spite of its fundamental role in controlling the molecular recognition process. In the present report the surface accessibility of alpha-bungarotoxin, a small and well characterized protein, has been investigated by analyzing its interaction with solvent and paramagnetic molecules in an integrated way. The presence of strong hydration sites, identified by a combined analysis of MD simulation and NMR results, seems to prevent the access of Gd(III)DTPA-BMA to the protein surface. On the contrary, the limited hydration of the alpha-bungarotoxin active site favors frequent encounters between the paramagnetic probe and the protein in the latter region. All the data obtained here for alpha-bungarotoxin suggest that shape and stability of the solvation shell control its surface accessibility and, hence, intermolecular interactions in a way which could be common to many other proteins.