Effects of Distal Mutations on Ligand-Binding Affinity in E. coli Dihydrofolate Reductase.

Mutations far from the center of chemical activity in dihydrofolate reductase (DHFR) can affect several steps in the catalytic cycle. Mutations at highly conserved positions and the distal distance of the catalytic center (Met-42, Thr-113, and Gly-121) were designed, including single-point and double-point mutations. Upon ligand binding, the fluorescence of the intrinsic optical probe, tryptophan, decreases due to either fluorescence quenching or energy transfer. We demonstrated an optical approach in measuring the equilibrium dissociation constant for enzyme-cofactor, enzyme-substrate, and enzyme-product complexes in wildtype ecDHFR and each mutant. We propose that the effects of these distal mutations on ligand-binding affinity stem from the spatial steric hindrance, the disturbance on the hydrogen network, or the modification of the protein flexibility. The modified N-terminus tag in DHFR acts as a cap on the entrance of the substrate-binding cavity, squeezes the adenosine binding subdomain, and influences the binding of NADPH in some mutants. If the mutation positions are away from the N-terminus tag and the adenosine binding subdomain, the additive effects due to the N-terminus tag were not observed. In the double-mutant-cycle analysis, double mutations show nonadditive properties upon either cofactor or substrate binding. Also, in general, the first point mutation strongly affects the ligand binding compared to the second one.

On the relationship between residue structural environment and sequence conservation in proteins.

Residues that are crucial to protein function or structure are usually evolutionarily conserved. To identify the important residues in protein, sequence conservation is estimated, and current methods rely upon the unbiased collection of homologous sequences. Surprisingly, our previous studies have shown that the sequence conservation is closely correlated with the weighted contact number (WCN), a measure of packing density for residue's structural environment, calculated only based on the Cα positions of a protein structure. Moreover, studies have shown that sequence conservation is correlated with environment-related structural properties calculated based on different protein substructures, such as a protein's all atoms, backbone atoms, side-chain atoms, or side-chain centroid. To know whether the Cα atomic positions are adequate to show the relationship between residue environment and sequence conservation or not, here we compared Cα atoms with other substructures in their contributions to the sequence conservation. Our results show that Cα positions are substantially equivalent to the other substructures in calculations of various measures of residue environment. As a result, the overlapping contributions between Cα atoms and the other substructures are high, yielding similar structure-conservation relationship. Take the WCN as an example, the average overlapping contribution to sequence conservation is 87% between Cα and all-atom substructures. These results indicate that only Cα atoms of a protein structure could reflect sequence conservation at the residue level.

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

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.

(PS)2: protein structure prediction server version 3.0.

Protein complexes are involved in many biological processes. Examining coupling between subunits of a complex would be useful to understand the molecular basis of protein function. Here, our updated (PS)(2) web server predicts the three-dimensional structures of protein complexes based on comparative modeling; furthermore, this server examines the coupling between subunits of the predicted complex by combining structural and evolutionary considerations. The predicted complex structure could be indicated and visualized by Java-based 3D graphics viewers and the structural and evolutionary profiles are shown and compared chain-by-chain. For each subunit, considerations with or without the packing contribution of other subunits cause the differences in similarities between structural and evolutionary profiles, and these differences imply which form, complex or monomeric, is preferred in the biological condition for the subunit. We believe that the (PS)(2) server would be a useful tool for biologists who are interested not only in the structures of protein complexes but also in the coupling between subunits of the complexes. The (PS)(2) is freely available at http://ps2v3.life.nctu.edu.tw/.

On the packing density of the unbound protein-protein interaction interface and its implications in dynamics.

BACKGROUND: Characterizing the interface residues will help shed light on protein-protein interactions, which are involved in many important biological processes. Many studies focus on characterizing sequence or structure features of protein interfaces, but there are few studies characterizing the dynamics of interfaces. Therefore, we would like to know whether there is any specific dynamics pattern in the protein-protein interaction interfaces. Thermal fluctuation is an important dynamical property for a residue, and could be quickly estimated by local packing density without large computation since studies have showen closely relationship between these two properties. Therefore, we divided surface of an unbound subunit (free protein subunits before they are involved in forming the protein complexes) into several separate regions, and compared their average thermal fluctuations of different regions in order to characterize the dynamics pattern in unbound protein-protein interaction interfaces. RESULTS: We used weighted contact numbers (WCN), a parameter-free method to quantify packing density, to estimate the thermal fluctuations of residues in the interfaces. By analyzing the WCN distributions of interfaces in unbound subunits from 1394 non-homologous protein complexes, we show that the residues in the central regions of interfaces have higher packing density (i.e. more rigid); on the other hand, residues surrounding the central regions have smaller packing density (i.e. more flexible). The distinct distributions of packing density, suggesting distinct thermal fluctuation, reveals specific dynamics pattern in the interface of unbound protein subunits. CONCLUSIONS: We found general trend that the unbound protein-protein interaction interfaces consist of rigid residues in the central regions, which are surrounded by flexible residues. This finding suggests that the dynamics might be one of the important features for the formation of protein complexes.

Local packing density is the main structural determinant of the rate of protein sequence evolution at site level.

Functional and biophysical constraints result in site-dependent patterns of protein sequence variability. It is commonly assumed that the key structural determinant of site-specific rates of evolution is the Relative Solvent Accessibility (RSA). However, a recent study found that amino acid substitution rates correlate better with two Local Packing Density (LPD) measures, the Weighted Contact Number (WCN) and the Contact Number (CN), than with RSA. This work aims at a more thorough assessment. To this end, in addition to substitution rates, we considered four other sequence variability scores, four measures of solvent accessibility (SA), and other CN measures. We compared all properties for each protein of a structurally and functionally diverse representative dataset of monomeric enzymes. We show that the best sequence variability measures take into account phylogenetic tree topology. More importantly, we show that both LPD measures (WCN and CN) correlate better than all of the SA measures, regardless of the sequence variability score used. Moreover, the independent contribution of the best LPD measure is approximately four times larger than that of the best SA measure. This study strongly supports the conclusion that a site's packing density rather than its solvent accessibility is the main structural determinant of its rate of evolution.

A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility.

BACKGROUND: Protein sites evolve at different rates due to functional and biophysical constraints. It is usually considered that the main structural determinant of a site's rate of evolution is its Relative Solvent Accessibility (RSA). However, a recent comparative study has shown that the main structural determinant is the site's Local Packing Density (LPD). LPD is related with dynamical flexibility, which has also been shown to correlate with sequence variability. Our purpose is to investigate the mechanism that connects a site's LPD with its rate of evolution. RESULTS: We consider two models: an empirical Flexibility Model and a mechanistic Stress Model. The Flexibility Model postulates a linear increase of site-specific rate of evolution with dynamical flexibility. The Stress Model, introduced here, models mutations as random perturbations of the protein's potential energy landscape, for which we use simple Elastic Network Models (ENMs). To account for natural selection we assume a single active conformation and use basic statistical physics to derive a linear relationship between site-specific evolutionary rates and the local stress of the mutant's active conformation.We compare both models on a large and diverse dataset of enzymes. In a protein-by-protein study we found that the Stress Model outperforms the Flexibility Model for most proteins. Pooling all proteins together we show that the Stress Model is strongly supported by the total weight of evidence. Moreover, it accounts for the observed nonlinear dependence of sequence variability on flexibility. Finally, when mutational stress is controlled for, there is very little remaining correlation between sequence variability and dynamical flexibility. CONCLUSIONS: We developed a mechanistic Stress Model of evolution according to which the rate of evolution of a site is predicted to depend linearly on the local mutational stress of the active conformation. Such local stress is proportional to LPD, so that this model explains the relationship between LPD and evolutionary rate. Moreover, the model also accounts for the nonlinear dependence between evolutionary rate and dynamical flexibility.

On the relationship between catalytic residues and their protein contact number.

Due to advances in structural biology, an increasing number of protein structures of unknown function have been deposited in Protein Data Bank (PDB). These proteins are usually characterized by novel structures and sequences. Conventional comparative methodology (such as sequence alignment, structure comparison, or template search) is unable to determine their function. Thus, it is important to identify protein's function directly from its structure, but this is not an easy task. One of the strategies used is to analyze whether there are distinctive structure-derived features associated with functional residues. If so, one may be able to identify the functional residues directly from a single structure. Recently, we have shown that protein weighted contact number is related to atomic thermal fluctuations and can be used to derive motional correlations in proteins. In this report, we analyze the weighted contact-number profiles of both catalytic residues and non-catalytic residues for a dataset of 760 structures. We found that catalytic residues have distinct distributions of weighted contact numbers from those of non-catalytic residues. Using this feature, we are able to effectively differentiate catalytic residues from other residues with a single optimized threshold value. Our method is simple to implement and compares favourably with other more sophisticated methods. In addition, we discuss the physics behind the relationship between catalytic residues and their contact numbers as well as other features (such as residue centrality or B-factors) associated with catalytic residues.

Proteinase-activated receptor-1 mediates elastase-induced apoptosis of human lung epithelial cells.

Apoptosis of distal lung epithelial cells plays a pivotal role in the pathogenesis of acute lung injury. In this context, proteinases, either circulating or leukocyte-derived, may contribute to epithelial apoptosis and lung injury. We hypothesized that apoptosis of lung epithelial cells induced by leukocyte elastase is mediated via the proteinase activated receptor (PAR)-1. Leukocyte elastase, thrombin, and PAR-1-activating peptide, but not the control peptide, induced apoptosis in human airway and alveolar epithelial cells as assessed by increases in cytoplasmic histone-associated DNA fragments and TUNEL staining. These effects were largely prevented by a specific PAR-1 antagonist and by short interfering RNA directed against PAR-1. To ascertain the mechanism of epithelial apoptosis, we determined that PAR-1AP, thrombin, and leukocyte elastase dissipated mitochondrial membrane potential, induced translocation of cytochrome c to the cytosol, enhanced cleavage of caspase-9 and caspase-3, and led to JNK activation and Akt inhibition. In concert, these observations provide strong evidence that leukocyte elastase mediates apoptosis of human lung epithelial cells through PAR-1-dependent modulation of the intrinsic apoptotic pathway via alterations in mitochondrial permeability and by modulation of JNK and Akt.