Towards the Design of Metamorphic Proteins using Ensemble-Based Energetic Information

Miralles, Enric; Tagliabue, BenedettaPrimer pla d'una part del Parc de Diagonal-Mar. Es pot veure el paisatge del parc, realitzat amb estructures d'acer i elements de trencadís ceràmic. Al fons, es veuen uns edificis de gran alçada

Predicting the Energetics of Conformational Fluctuations in Proteins from Sequence: A Strategy for Profiling the Proteome

SUMMARY The abundance of dynamic and disordered regions in proteins suggests that structural determinants alone may not be sufficient to describe function. Instead, descriptors that account for the dynamic features of the energy landscape populated by the protein ensemble may be required. Here, we show that the thermodynamics of the dynamical complexity that imparts biological function can be largely reconstructed using sequence information alone, allowing thermodynamic characterization of entire proteomes without the need for structural analysis. We show that this tool can be used to analyze conserved energetic signatures within classes of proteins, as well as to compare the thermodynamic character of different proteomes

Exploring allosteric coupling in the α-subunit of Heterotrimeric G proteins using evolutionary and ensemble-based approaches

<p>Abstract</p> <p>Background</p> <p>Allosteric coupling, which can be defined as propagation of a perturbation at one region of the protein molecule (such as ligand binding) to distant sites in the same molecule, constitutes the most general mechanism of regulation of protein function. However, unlike molecular details of ligand binding, structural elements involved in allosteric effects are difficult to diagnose. Here, we identified allosteric linkages in the α-subunits of heterotrimeric G proteins, which were evolved to transmit membrane receptor signals by allosteric mechanisms, by using two different approaches that utilize fundamentally different and independent information.</p> <p>Results</p> <p>We analyzed: 1) correlated mutations in the family of G protein α-subunits, and 2) cooperativity of the native state ensemble of the Gαi1 or transducin. The combination of these approaches not only recovered already-known details such as the switch regions that change conformation upon nucleotide exchange, and those regions that are involved in receptor, effector or Gβγ interactions (indicating that the predictions of the analyses can be viewed with a measure of confidence), but also predicted new sites that are potentially involved in allosteric communication in the Gα protein. A summary of the new sites found in the present analysis, which were not apparent in crystallographic data, is given along with known functional and structural information. Implications of the results are discussed.</p> <p>Conclusion</p> <p>A set of residues and/or structural elements that are potentially involved in allosteric communication in Gα is presented. This information can be used as a guide to structural, spectroscopic, mutational, and theoretical studies on the allosteric network in Gα proteins, which will provide a better understanding of G protein-mediated signal transduction.</p

Investigating Homology between Proteins using Energetic Profiles

Accumulated experimental observations demonstrate that protein stability is often preserved upon conservative point mutation. In contrast, less is known about the effects of large sequence or structure changes on the stability of a particular fold. Almost completely unknown is the degree to which stability of different regions of a protein is generally preserved throughout evolution. In this work, these questions are addressed through thermodynamic analysis of a large representative sample of protein fold space based on remote, yet accepted, homology. More than 3,000 proteins were computationally analyzed using the structural-thermodynamic algorithm COREX/BEST. Estimated position-specific stability (i.e., local Gibbs free energy of folding) and its component enthalpy and entropy were quantitatively compared between all proteins in the sample according to all-vs.-all pairwise structural alignment. It was discovered that the local stabilities of homologous pairs were significantly more correlated than those of non-homologous pairs, indicating that local stability was indeed generally conserved throughout evolution. However, the position-specific enthalpy and entropy underlying stability were less correlated, suggesting that the overall regional stability of a protein was more important than the thermodynamic mechanism utilized to achieve that stability. Finally, two different types of statistically exceptional evolutionary structure-thermodynamic relationships were noted. First, many homologous proteins contained regions of similar thermodynamics despite localized structure change, suggesting a thermodynamic mechanism enabling evolutionary fold change. Second, some homologous proteins with extremely similar structures nonetheless exhibited different local stabilities, a phenomenon previously observed experimentally in this laboratory. These two observations, in conjunction with the principal conclusion that homologous proteins generally conserved local stability, may provide guidance for a future thermodynamically informed classification of protein homology

A horizontal alignment tool for numerical trend discovery in sequence data: application to protein hydropathy.

PMC3794901An algorithm is presented that returns the optimal pairwise gapped alignment of two sets of signed numerical sequence values. One distinguishing feature of this algorithm is a flexible comparison engine (based on both relative shape and absolute similarity measures) that does not rely on explicit gap penalties. Additionally, an empirical probability model is developed to estimate the significance of the returned alignment with respect to randomized data. The algorithm's utility for biological hypothesis formulation is demonstrated with test cases including database search and pairwise alignment of protein hydropathy. However, the algorithm and probability model could possibly be extended to accommodate other diverse types of protein or nucleic acid data, including positional thermodynamic stability and mRNA translation efficiency. The algorithm requires only numerical values as input and will readily compare data other than protein hydropathy. The tool is therefore expected to complement, rather than replace, existing sequence and structure based tools and may inform medical discovery, as exemplified by proposed similarity between a chlamydial ORFan protein and bacterial colicin pore-forming domain. The source code, documentation, and a basic web-server application are available.JH Libraries Open Access Fun