Flowchart of salt-bridge design in this study.

<p>Identification of potential positions and mutation types for a given protein structure are demonstrated.</p

Protein Thermal Stability Enhancement by Designing Salt Bridges: A Combined Computational and Experimental Study

<div><p>Protein thermal stability is an important factor considered in medical and industrial applications. Many structural characteristics related to protein thermal stability have been elucidated, and increasing salt bridges is considered as one of the most efficient strategies to increase protein thermal stability. However, the accurate simulation of salt bridges remains difficult. In this study, a novel method for salt-bridge design was proposed based on the statistical analysis of 10,556 surface salt bridges on 6,493 X-ray protein structures. These salt bridges were first categorized based on pairing residues, secondary structure locations, and Cα–Cα distances. Pairing preferences generalized from statistical analysis were used to construct a salt-bridge pair index and utilized in a weighted electrostatic attraction model to find the effective pairings for designing salt bridges. The model was also coupled with B-factor, weighted contact number, relative solvent accessibility, and conservation prescreening to determine the residues appropriate for the thermal adaptive design of salt bridges. According to our method, eight putative salt-bridges were designed on a mesophilic β-glucosidase and 24 variants were constructed to verify the predictions. Six putative salt-bridges leaded to the increase of the enzyme thermal stability. A significant increase in melting temperature of 8.8, 4.8, 3.7, 1.3, 1.2, and 0.7°C of the putative salt-bridges N437K–D49, E96R–D28, E96K–D28, S440K–E70, T231K–D388, and Q277E–D282 was detected, respectively. Reversing the polarity of T231K–D388 to T231D–D388K resulted in a further increase in melting temperatures by 3.6°C, which may be caused by the transformation of an intra-subunit electrostatic interaction into an inter-subunit one depending on the local environment. The combination of the thermostable variants (N437K, E96R, T231D and D388K) generated a melting temperature increase of 15.7°C. Thus, this study demonstrated a novel method for the thermal adaptive design of salt bridges through inference of suitable positions and substitutions.</p></div

Frequency distributions of surface salt bridges at different pairs of secondary structures.

<p>Four types of salt-bridge pairings, Arg/Asp (R/D), Arg/Glu (R/E), Lys/Asp (K/D), and Lys/Glu (K/E), were considered in the statistical analysis.</p

Relative solvent accessibility of salt bridges in 6,493 X-ray protein structures.

<p>Abbreviation: K, Lysine; R, Arginine; D, Asparagine; E, Glutamine; and RSA: Relative solvent accessibility.</p>a<p>RSA of both residues of a salt bridge are indicated.</p>b<p>RSA of one residue of a salt bridge is >25% and the other is >35%.</p><p>Relative solvent accessibility of salt bridges in 6,493 X-ray protein structures.</p

Locations of eight predicted pairs and one control pair in the octameric structure (PDB: 1BGA).

<p>A, D, E subunits are represented in green, yellow, and purple, respectively. The N437–D49 pair is between subunits A and D; the T231–D388 pair is between subunits A and E; whereas E96–D28, Q141–E148, Q277–R137, S440–E70 and control pair Q216-D289 are intra-subunit pairs. The predictive pairs as well as T231D–D388K and Q216R–D289 pairs were simulated by Pymol program. Each pair is magnified in an independent window showing secondary structure elements and the paired residues (red for negatively charged residues and blue for positively charged residues). The neighboring charge residue of each position (E96, Q141, T231, Q277, N437, S440, and Q216) suggested the oppositely charged substitutions for forming salt bridges.</p

Characteristics of positions in BglA for mutations.

<p>Secondary structure (SS: H, helix; E, beta-sheet; C, coil), relative solvent accessibility (RSA), Z-scores of B-factor (z_B-factor) and reciprocal of weighted contact number (z_rWCN), conservation score, and inter- or intra- subunit location are indicated.</p><p>Characteristics of positions in BglA for mutations.</p

Spatial orientation and Cα–Cα distances of salt bridges on protein surfaces.

<p>(A) Statitical analysis of angles (θ₁, θ₂) of 10,556 salt bridges on the surfaces of 6,493 X-ray protein structures. Two angles of a salt bridge (<i>i</i>–<i>j</i>), ∠Cβ₁Cα₁Cα₂ (θ₁) and ∠Cβ₂Cα₂Cα₁ (θ₂), were used to describe the charge group interaction based on the relative orientation of the two residues’ Cα–Cβ vectors as indicated. All of the angles are in the range of 0° to 180° (θ₁ and θ₂ color in black and gray). The length of radius are corresponding to Cα–Cα distance (Å). (B) The scatter plot shows the angles (θ₁, θ₂) of the salt bridges at a backbone distance >7 Å, which are restrained within 0° to 110°.</p

CP Viability Prediction Performance of Various Procedures.

a<p>Random forest was applied in this experiment to the assess the prediction power of closeness and farness.</p>b<p>A combination of the four machine learning methods (HI, ANN, RF and SVM) by averaging their probability scores into a single score. See the main text for details.</p>c<p>These results were obtained with 10-fold cross-validation.</p

Sequence Conservation, Radial Distance and Packing Density in Spherical Viral Capsids

<div><p>The conservation level of a residue is a useful measure about the importance of that residue in protein structure and function. Much information about sequence conservation comes from aligning homologous sequences. Profiles showing the variation of the conservation level along the sequence are usually interpreted in evolutionary terms and dictated by site similarities of a proper set of homologous sequences. Here, we report that, of the viral icosahedral capsids, the sequence conservation profile can be determined by variations in the distances between residues and the centroid of the capsid – with a direct inverse proportionality between the conservation level and the centroid distance – as well as by the spatial variations in local packing density. Examining both the centroid and the packing density models against a dataset of 51 crystal structures of nonhomologous icosahedral capsids, we found that many global patterns and minor features derived from the viral structures are consistent with those present in the sequence conservation profiles. The quantitative link between the level of conservation and structural features like centroid-distance or packing density allows us to look at residue conservation from a structural viewpoint as well as from an evolutionary viewpoint.</p></div

Probability Scores of DHFR.

<p>The structure of the dihydrofolate reductase from <i>Escherichia coli</i> (PDB entry: 1RX4) is shown as a cross-eye stereo image, in which the thickness of backbone of a residue is in proportion to the probability score computed by our prediction system for that residue. In addition, probability scores are color-coded — a color closer to red represents a higher score. Gray- to black-colored residues have scores increasingly lower than 0.5. Among the 67 residues with probability scores ≥0.5, only 6 are inviable CP sites (shown in blue). The other 61 residues are experimentally-verified viable CP sites <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031791#pone.0031791-Iwakura1" target="_blank">[29]</a>. Thus, at a probability score threshold of 0.5, the precision of the developed prediction system for this independent evaluation dataset is 90% (61/67).</p