A conserved tryptophan in the acylated segment of RTX toxins controls their ß2 integrin-independent cell penetration.

The acylated Repeats in ToXins (RTX) leukotoxins, the adenylate cyclase toxin (CyaA) or α-hemolysin (HlyA), bind ß2 integrins of leukocytes but also penetrate cells lacking these receptors. We show that the indoles of conserved tryptophans in the acylated segments, W876 of CyaA and W579 of HlyA, are crucial for ß2 integrin-independent membrane penetration. Substitutions of W876 by aliphatic or aromatic residues did not affect acylation, folding, or the activities of CyaA W876L/F/Y variants on cells expressing high amounts of the ß2 integrin CR3. However, toxin activity of CyaA W876L/F/Y on cells lacking CR3 was strongly impaired. Similarly, a W579L substitution selectively reduced HlyA W579L cytotoxicity towards cells lacking ß2 integrins. Intriguingly, the W876L/F/Y substitutions increased the thermal stability (Tm) of CyaA by 4 to 8 °C but locally enhanced the accessibility to deuteration of the hydrophobic segment and of the interface of the two acylated loops. W876Q substitution (showing no increase in Tm), or combination of W876F with a cavity-filling V822M substitution (this combination decreasing the Tm closer to that of CyaA), yielded a milder defect of toxin activity on erythrocytes lacking CR3. Furthermore, the activity of CyaA on erythrocytes was also selectively impaired when the interaction of the pyrrolidine of P848 with the indole of W876 was ablated. Hence, the bulky indoles of residues W876 of CyaA, or W579 of HlyA, rule the local positioning of the acylated loops and enable a membrane-penetrating conformation in the absence of RTX toxin docking onto the cell membrane by ß2 integrins.

Knowledge-based prediction of DNA hydration using hydrated dinucleotides as building blocks.

Water plays an important role in stabilizing the structure of DNA and mediating its interactions. Here, the hydration of DNA was analyzed in terms of dinucleotide fragments from an ensemble of 2727 nonredundant DNA chains containing 41 853 dinucleotides and 316 265 associated first-shell water molecules. The dinucleotides were classified into categories based on their 16 sequences and the previously determined structural classes known as nucleotide conformers (NtCs). The construction of hydrated dinucleotide building blocks allowed dinucleotide hydration to be calculated as the probability of water density distributions. Peaks in the water densities, known as hydration sites (HSs), uncovered the interplay between base and sugar-phosphate hydration in the context of sequence and structure. To demonstrate the predictive power of hydrated DNA building blocks, they were then used to predict hydration in an independent set of crystal and NMR structures. In ten tested crystal structures, the positions of predicted HSs and experimental waters were in good agreement (more than 40% were within 0.5 Å) and correctly reproduced the known features of DNA hydration, for example the `spine of hydration' in B-DNA. Therefore, it is proposed that hydrated building blocks can be used to predict DNA hydration in structures solved by NMR and cryo-EM, thus providing a guide to the interpretation of experimental data and computer models. The data for the hydrated building blocks and the predictions are available for browsing and visualization at the website https://watlas.datmos.org/watna/.

Protein Binder (ProBi) as a New Class of Structurally Robust Non-Antibody Protein Scaffold for Directed Evolution.

Engineered small non-antibody protein scaffolds are a promising alternative to antibodies and are especially attractive for use in protein therapeutics and diagnostics. The advantages include smaller size and a more robust, single-domain structural framework with a defined binding surface amenable to mutation. This calls for a more systematic approach in designing new scaffolds suitable for use in one or more methods of directed evolution. We hereby describe a process based on an analysis of protein structures from the Protein Data Bank and their experimental examination. The candidate protein scaffolds were subjected to a thorough screening including computational evaluation of the mutability, and experimental determination of their expression yield in E. coli, solubility, and thermostability. In the next step, we examined several variants of the candidate scaffolds including their wild types and alanine mutants. We proved the applicability of this systematic procedure by selecting a monomeric single-domain human protein with a fold different from previously known scaffolds. The newly developed scaffold, called ProBi (Protein Binder), contains two independently mutable surface patches. We demonstrated its functionality by training it as a binder against human interleukin-10, a medically important cytokine. The procedure yielded scaffold-related variants with nanomolar affinity.

Structural alphabets for conformational analysis of nucleic acids available at dnatco.datmos.org.

A detailed description of the dnatco.datmos.org web server implementing the universal structural alphabet of nucleic acids is presented. It is capable of processing any mmCIF- or PDB-formatted files containing DNA or RNA molecules; these can either be uploaded by the user or supplied as the wwPDB or PDB-REDO structural database access code. The web server performs an assignment of the nucleic acid conformations and presents the results for the intuitive annotation, validation, modeling and refinement of nucleic acids.

Rutinosidase from Aspergillus niger: crystal structure and insight into the enzymatic activity.

Rutinosidases (α-l-rhamnosyl-ß-d-glucosidases) catalyze the cleavage of the glycosidic bond between the aglycone and the disaccharide rutinose (α-l-rhamnopyranosyl-(1→6)-ß-d-glucopyranose) of specific flavonoid glycosides such as rutin (quercetin 3-O-rutinoside). Microbial rutinosidases are part of the rutin catabolic pathway, enabling the microorganism to utilize rutin and related plant phenolic glycosides. Here, we report the first three-dimensional structure of a rutinosidase determined at 1.27-Å resolution. The rutinosidase from Aspergillus niger K2 (AnRut), a member of glycoside hydrolase family GH-5, subfamily 23, was heterologously produced in Pichia pastoris. The X-ray structure of AnRut is represented by a distorted (ß/α)8 barrel fold with its closest structural homologue being an exo-ß-(1,3)-glucanase from Candida albicans (CaExg). The catalytic site is located in a deep pocket with a striking structural similarity to CaExg. However, the entrance to the active site of AnRut has been found to be different from that of CaExg - a mostly unstructured section of ~ 40 residues present in CaExg is missing in AnRut, whereas an additional loop of 13 amino acids partially covers the active site of AnRut. NMR analysis of reaction products provided clear evidence for a retaining reaction mechanism of AnRut. Unexpectedly, quercetin 3-O-glucoside was found to be a better substrate than rutin, and thus, AnRut cannot be considered a typical diglycosidase. Mutational analysis of conserved active site residues in combination with in silico modeling allowed identification of essential interactions for enzyme activity and helped to reveal further details of substrate binding. The protein sequence of AnRut has been revised. DATABASES: The nucleotide sequence of the rutinosidase-encoding gene is available in the GenBank database under the accession number MN393234. Structural data are available in the PDB database under the accession number 6I1A. ENZYME: α-l-Rhamnosyl-ß-d-glucosidase (EC 3.2.1.168).

WatAA: Atlas of Protein Hydration. Exploring synergies between data mining and ab initio calculations.

Water molecules represent an integral part of proteins and a key determinant of protein structure, dynamics and function. WatAA is a newly developed, web-based atlas of amino-acid hydration in proteins. The atlas provides information about the ordered first hydration shell of the most populated amino-acid conformers in proteins. The data presented in the atlas are drawn from two sources: experimental data and ab initio quantum-mechanics calculations. The experimental part is based on a data-mining study of a large set of high-resolution protein crystal structures. The crystal-derived data include 3D maps of water distribution around amino-acids and probability of occurrence of each of the identified hydration sites. The quantum mechanics calculations validate and extend this primary description by optimizing the water position for each hydration site, by providing hydrogen atom positions and by quantifying the interaction energy that stabilizes the water molecule at the particular hydration site position. The calculations show that the majority of experimentally derived hydration sites are positioned near local energy minima for water, and the calculated interaction energies help to assess the preference of water for the individual hydration sites. We propose that the atlas can be used to validate water placement in electron density maps in crystallographic refinement, to locate water molecules mediating protein-ligand interactions in drug design, and to prepare and evaluate molecular dynamics simulations. WatAA: Atlas of Protein Hydration is freely available without login at .

Hydration of proteins and nucleic acids: Advances in experiment and theory. A review.

BACKGROUND: Most biological processes involve water, and the interactions of biomolecules with water affect their structure, function and dynamics. SCOPE OF REVIEW: This review summarizes the current knowledge of protein and nucleic acid interactions with water, with a special focus on the biomolecular hydration layer. Recent developments in both experimental and computational methods that can be applied to the study of hydration structure and dynamics are reviewed, including software tools for the prediction and characterization of hydration layer properties. MAJOR CONCLUSIONS: In the last decade, important advances have been made in our understanding of the factors that determine how biomolecules and their aqueous environment influence each other. Both experimental and computational methods contributed to the gradually emerging consensus picture of biomolecular hydration. GENERAL SIGNIFICANCE: An improved knowledge of the structural and thermodynamic properties of the hydration layer will enable a detailed understanding of the various biological processes in which it is involved, with implications for a wide range of applications, including protein-structure prediction and structure-based drug design.

Structure of the ordered hydration of amino acids in proteins: analysis of crystal structures.

Crystallography provides unique information about the arrangement of water molecules near protein surfaces. Using a nonredundant set of 2818 protein crystal structures with a resolution of better than 1.8 Å, the extent and structure of the hydration shell of all 20 standard amino-acid residues were analyzed as function of the residue conformation, secondary structure and solvent accessibility. The results show how hydration depends on the amino-acid conformation and the environment in which it occurs. After conformational clustering of individual residues, the density distribution of water molecules was compiled and the preferred hydration sites were determined as maxima in the pseudo-electron-density representation of water distributions. Many hydration sites interact with both main-chain and side-chain amino-acid atoms, and several occurrences of hydration sites with less canonical contacts, such as carbon-donor hydrogen bonds, OH-π interactions and off-plane interactions with aromatic heteroatoms, are also reported. Information about the location and relative importance of the empirically determined preferred hydration sites in proteins has applications in improving the current methods of hydration-site prediction in molecular replacement, ab initio protein structure prediction and the set-up of molecular-dynamics simulations.

Redesigning protein cavities as a strategy for increasing affinity in protein-protein interaction: interferon- γ receptor 1 as a model.

Combining computational and experimental tools, we present a new strategy for designing high affinity variants of a binding protein. The affinity is increased by mutating residues not at the interface, but at positions lining internal cavities of one of the interacting molecules. Filling the cavities lowers flexibility of the binding protein, possibly reducing entropic penalty of binding. The approach was tested using the interferon-γ receptor 1 (IFNγR1) complex with IFNγ as a model. Mutations were selected from 52 amino acid positions lining the IFNγR1 internal cavities by using a protocol based on FoldX prediction of free energy changes. The final four mutations filling the IFNγR1 cavities and potentially improving the affinity to IFNγ were expressed, purified, and refolded, and their affinity towards IFNγ was measured by SPR. While individual cavity mutations yielded receptor constructs exhibiting only slight increase of affinity compared to WT, combinations of these mutations with previously characterized variant N96W led to a significant sevenfold increase. The affinity increase in the high affinity receptor variant N96W+V35L is linked to the restriction of its molecular fluctuations in the unbound state. The results demonstrate that mutating cavity residues is a viable strategy for designing protein variants with increased affinity.

Increasing affinity of interferon-γ receptor 1 to interferon-γ by computer-aided design.

We describe a computer-based protocol to design protein mutations increasing binding affinity between ligand and its receptor. The method was applied to mutate interferon-γ receptor 1 (IFN-γ-Rx) to increase its affinity to natural ligand IFN-γ, protein important for innate immunity. We analyzed all four available crystal structures of the IFN-γ-Rx/IFN-γ complex to identify 40 receptor residues forming the interface with IFN-γ. For these 40 residues, we performed computational mutation analysis by substituting each of the interface receptor residues by the remaining standard amino acids. The corresponding changes of the free energy were calculated by a protocol consisting of FoldX and molecular dynamics calculations. Based on the computed changes of the free energy and on sequence conservation criteria obtained by the analysis of 32 receptor sequences from 19 different species, we selected 14 receptor variants predicted to increase the receptor affinity to IFN-γ. These variants were expressed as recombinant proteins in Escherichia coli, and their affinities to IFN-γ were determined experimentally by surface plasmon resonance (SPR). The SPR measurements showed that the simple computational protocol succeeded in finding two receptor variants with affinity to IFN-γ increased about fivefold compared to the wild-type receptor.

Mechanistic dichotomy in the asymmetric allylation of aldehydes with allyltrichlorosilanes catalyzed by chiral pyridine N-oxides.

Detailed kinetic and computational investigation of the enantio- and diastereoselective allylation of aldehydes 1 with allyltrichlorosilanes 5, employing the pyridine N-oxides METHOX (9) and QUINOX (10) as chiral organocatalysts, indicate that the reaction can proceed through a dissociative (cationic) or associative (neutral) mechanism: METHOX apparently favors a pentacoordinate cationic transition state, while the less sterically demanding QUINOX is likely to operate via a hexacoordinate neutral complex. In both pathways, only one molecule of the catalyst is involved in the rate- and selectivity-determining step, which is supported by both experimental and computational data.

Software tools for identification, visualization and analysis of protein tunnels and channels.

Protein structures contain highly complex systems of voids, making up specific features such as surface clefts or grooves, pockets, protrusions, cavities, pores or channels, and tunnels. Many of them are essential for the migration of solvents, ions and small molecules through proteins, and their binding to the functional sites. Analysis of these structural features is very important for understanding of structure-function relationships, for the design of potential inhibitors or proteins with improved functional properties. Here we critically review existing software tools specialized in rapid identification, visualization, analysis and design of protein tunnels and channels. The strengths and weaknesses of individual tools are reported together with examples of their applications for the analysis and engineering of various biological systems. This review can assist users with selecting a proper software tool for study of their biological problem as well as highlighting possible avenues for further development of existing tools. Development of novel descriptors representing not only geometry, but also electrostatics, hydrophobicity or dynamics, is needed for reliable identification of biologically relevant tunnels and channels.

CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures.

Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.

A single mutation in a tunnel to the active site changes the mechanism and kinetics of product release in haloalkane dehalogenase LinB.

Many enzymes have buried active sites. The properties of the tunnels connecting the active site with bulk solvent affect ligand binding and unbinding and also the catalytic properties. Here, we investigate ligand passage in the haloalkane dehalogenase enzyme LinB and the effect of replacing leucine by a bulky tryptophan at a tunnel-lining position. Transient kinetic experiments show that the mutation significantly slows down the rate of product release. Moreover, the mechanism of bromide ion release is changed from a one-step process in the wild type enzyme to a two-step process in the mutant. The rate constant of bromide ion release corresponds to the overall steady-state turnover rate constant, suggesting that product release became the rate-limiting step of catalysis in the mutant. We explain the experimental findings by investigating the molecular details of the process computationally. Analysis of trajectories from molecular dynamics simulations with a tunnel detection software reveals differences in the tunnels available for ligand egress. Corresponding differences are seen in simulations of product egress using a specialized enhanced sampling technique. The differences in the free energy barriers for egress of a bromide ion obtained using potential of mean force calculations are in good agreement with the differences in rates obtained from the transient kinetic experiments. Interactions of the bromide ion with the introduced tryptophan are shown to affect the free energy barrier for its passage. The study demonstrates how the mechanism of an enzymatic catalytic cycle and reaction kinetics can be engineered by modification of protein tunnels.

Novel high-affinity binders of human interferon gamma derived from albumin-binding domain of protein G.

Recombinant ligands derived from small protein scaffolds show promise as robust research and diagnostic reagents and next generation protein therapeutics. Here, we derived high-affinity binders of human interferon gamma (hIFNγ) from the three helix bundle scaffold of the albumin-binding domain (ABD) of protein G from Streptococcus G148. Computational interaction energy mapping, solvent accessibility assessment, and in silico alanine scanning identified 11 residues from the albumin-binding surface of ABD as suitable for randomization. A corresponding combinatorial ABD scaffold library was synthesized and screened for hIFNγ binders using in vitro ribosome display selection, to yield recombinant ligands that exhibited K(d) values for hIFNγ from 0.2 to 10 nM. Molecular modeling, computational docking onto hIFNγ, and in vitro competition for hIFNγ binding revealed that four of the best ABD-derived ligands shared a common binding surface on hIFNγ, which differed from the site of human IFNγ receptor 1 binding. Thus, these hIFNγ ligands provide a proof of concept for design of novel recombinant binding proteins derived from the ABD scaffold.

Another role of proline: stabilization interactions in proteins and protein complexes concerning proline and tryptophane.

Proline-tryptophan complexes derived from experimental structures are investigated by quantum chemical procedures known to properly describe the London dispersion energy. We study two geometrical arrangements: the "L-shaped", stabilized by an H-bond, and the "stacked-like", where the two residues are in parallel orientation without any H-bond. Interestingly, the interaction energies in both cases are comparable and very large ( approximately 7 kcal mol(-1)). The strength of stabilization in the stacked arrangement is rather surprising considering the fact that only one partner has an aromatic character. The interaction energy decomposition using the SAPT method further demonstrates the very important role of dispersion energy in such arrangement. To elucidate the structural features responsible for this unexpectedly large stabilization we examined the role of the nitrogen heteroatom and the importance of the cyclicity of the proline residue. We show that the electrostatic interaction due to the presence of the dipole, caused by the nitrogen heteroatom, contributes largely to the strength of the interaction. Nevertheless, the cyclic arrangement of proline, which allows for the largest amount of dispersive contact with the aromatic partner, also has a notable-effect. Geometry optimizations carried out for the "stacked-like" complexes show that the arrangements derived from protein structure are close to their gas phase optimum geometry, suggesting that the environment has only a minor effect on the geometry of the interaction. We conclude that the strength of proline non-covalent interactions, combined with this residue's rigidity, might be the explanation for its prominent role in protein stabilization and recognition processes.

MedusaScore: an accurate force field-based scoring function for virtual drug screening.

Virtual screening is becoming an important tool for drug discovery. However, the application of virtual screening has been limited by the lack of accurate scoring functions. Here, we present a novel scoring function, MedusaScore, for evaluating protein-ligand binding. MedusaScore is based on models of physical interactions that include van der Waals, solvation, and hydrogen bonding energies. To ensure the best transferability of the scoring function, we do not use any protein-ligand experimental data for parameter training. We then test the MedusaScore for docking decoy recognition and binding affinity prediction and find superior performance compared to other widely used scoring functions. Statistical analysis indicates that one source of inaccuracy of MedusaScore may arise from the unaccounted entropic loss upon ligand binding, which suggests avenues of approach for further MedusaScore improvement.

On the mechanism of asymmetric allylation of aldehydes with allyltrichlorosilanes catalyzed by QUINOX, a chiral isoquinoline N-oxide.

Allylation of aromatic aldehydes 1a-m with allyl- and crotyl-trichlorosilanes 2- 4, catalyzed by the chiral N-oxide QUINOX (9), has been found to exhibit a significant dependence on the electronics of the aldehyde, with p-(trifluoromethyl)benzaldehyde 1g and its p-methoxy counterpart 1h affording the corresponding homoallylic alcohols 6g, h in 96 and 16% ee, respectively, at -40 degrees C. The kinetic and computational data indicate that the reaction is likely to proceed via an associative pathway involving neutral, octahedral silicon complex 22 with only one molecule of the catalyst involved in the rate- and selectivity-determining step. The crotylation with (E) and (Z)-crotyltrichlorosilanes 3 and 4 is highly diastereoselective, suggesting the chairlike transition state 5, which is supported by computational data. High-level quantum chemical calculations further suggest that attractive aromatic interactions between the catalyst 9 and the aldehyde 1 contribute to the enantiodifferentiation and that the dramatic drop in enantioselectivity, observed with the electron-rich aldehyde 1h, originates from narrowing the energy gap between the (R)- and (S)-reaction channels in the associative mechanism (22). Overall, a good agreement between the theoretically predicted enantioselectivities for 1a and 1h and the experimental data allowed to understand the specific aspects of the reaction mechanism.

Identifying stabilizing key residues in proteins using interresidue interaction energy matrix.

We are proposing an interresidue interaction energy map (IEM)--a new tool for protein structure analysis and protein bioinformatics. This approach employs the sum of pair-wise interaction energies of a particular residue as a measure of its structural importance. We will show that the IEM can serve as a means for identifying key residues responsible for the stability of a protein. Our method can be compared with the interresidue contact map but has the advantage of weighting the contacts by the stabilization energy content which they bring to the protein structure. For the theoretical adjustment of the proposed method, we chose the Trp-cage mini protein as a model system to compare a spectrum of computational methods ranging from the ab initio MP2 level through the DFT method to empirical force-field methods. The IEM method correctly identifies Tryptophane 6 as the key residue in the Trp-cage. The other residues with the highest stabilizing contributions correspond to the structurally important positions in the protein. We have further tested our method on the Trp2Cage miniprotein--a P12W mutant of the Trp-cage and on two proteins from the rubredoxin family that differ in their thermostability. Our method correctly identified the thermodynamically more stable variants in both cases and therefore can also be used as a tool for the relative measurement of protein stability. Finally, we will point out the important role played by dispersion energy, which contributes significantly to the total stabilization energy and whose role in aromatic pairs is clearly dominant. Surprisingly, the dispersion energy plays an even more important role in the interaction of prolines with aromatic systems.