Dynamics of allosteric transitions in GroEL

The chaperonin GroEL-GroES, a machine which helps some proteins to fold, cycles through a number of allosteric states, the $T$ state, with high affinity for substrate proteins (SPs), the ATP-bound $R$ state, and the $R^{\prime\prime}$ ($GroEL-ADP-GroES$) complex. Structures are known for each of these states. Here, we use a self-organized polymer (SOP) model for the GroEL allosteric states and a general structure-based technique to simulate the dynamics of allosteric transitions in two subunits of GroEL and the heptamer. The $T \to R$ transition, in which the apical domains undergo counter-clockwise motion, is mediated by a multiple salt-bridge switch mechanism, in which a series of salt-bridges break and form. The initial event in the $R \to R^{\prime\prime}$ transition, during which GroEL rotates clockwise, involves a spectacular outside-in movement of helices K and L that results in K80-D359 salt-bridge formation. In both the transitions there is considerable heterogeneity in the transition pathways. The transition state ensembles (TSEs) connecting the $T$, $R$, and $R^{\prime\prime}$ states are broad with the the TSE for the $T \to R$ transition being more plastic than the $R\to R^{\prime\prime}$ TSE. The results suggest that GroEL functions as a force-transmitting device in which forces of about (5-30) pN may act on the SP during the reaction cycle.Comment: 32 pages, 10 figures (Longer version than the one published

SCHEMA Recombination of a Fungal Cellulase Uncovers a Single Mutation That Contributes Markedly to Stability

A quantitative linear model accurately (R^2 = 0.88) describes the thermostabilities of 54 characterized members of a family of fungal cellobiohydrolase class II (CBH II) cellulase chimeras made by SCHEMA recombination of three fungal enzymes, demonstrating that the contributions of SCHEMA sequence blocks to stability are predominantly additive. Thirty-one of 31 predicted thermostable CBH II chimeras have thermal inactivation temperatures higher than the most thermostable parent CBH II, from Humicola insolens, and the model predicts that hundreds more CBH II chimeras share this superior thermostability. Eight of eight thermostable chimeras assayed hydrolyze the solid cellulosic substrate Avicel at temperatures at least 5 °C above the most stable parent, and seven of these showed superior activity in 16-h Avicel hydrolysis assays. The sequence-stability model identified a single block of sequence that adds 8.5 °C to chimera thermostability. Mutating individual residues in this block identified the C313S substitution as responsible for the entire thermostabilizing effect. Introducing this mutation into the two recombination parent CBH IIs not featuring it (Hypocrea jecorina and H. insolens) decreased inactivation, increased maximum Avicel hydrolysis temperature, and improved long time hydrolysis performance. This mutation also stabilized and improved Avicel hydrolysis by Phanerochaete chrysosporium CBH II, which is only 55–56% identical to recombination parent CBH IIs. Furthermore, the C313S mutation increased total H. jecorina CBH II activity secreted by the Saccharomyces cerevisiae expression host more than 10-fold. Our results show that SCHEMA structure-guided recombination enables quantitative prediction of cellulase chimera thermostability and efficient identification of stabilizing mutations

Identification of direct residue contacts in protein-protein interaction by message passing

Understanding the molecular determinants of specificity in protein-protein interaction is an outstanding challenge of postgenome biology. The availability of large protein databases generated from sequences of hundreds of bacterial genomes enables various statistical approaches to this problem. In this context covariance-based methods have been used to identify correlation between amino acid positions in interacting proteins. However, these methods have an important shortcoming, in that they cannot distinguish between directly and indirectly correlated residues. We developed a method that combines covariance analysis with global inference analysis, adopted from use in statistical physics. Applied to a set of >2,500 representatives of the bacterial two-component signal transduction system, the combination of covariance with global inference successfully and robustly identified residue pairs that are proximal in space without resorting to ad hoc tuning parameters, both for heterointeractions between sensor kinase (SK) and response regulator (RR) proteins and for homointeractions between RR proteins. The spectacular success of this approach illustrates the effectiveness of the global inference approach in identifying direct interaction based on sequence information alone. We expect this method to be applicable soon to interaction surfaces between proteins present in only 1 copy per genome as the number of sequenced genomes continues to expand. Use of this method could significantly increase the potential targets for therapeutic intervention, shed light on the mechanism of protein-protein interaction, and establish the foundation for the accurate prediction of interacting protein partners.Comment: Supplementary information available on http://www.pnas.org/content/106/1/67.abstrac

Thermal and chemical unfolding and refolding of a eukaryotic sodium channel

Voltage-gated sodium channels are dynamic membrane proteins essential for signaling in nervous and muscular systems. They undergo substantial conformational changes associated with the closed, open and inactivated states. However, little information is available regarding their conformational stability. In this study circular dichroism spectroscopy was used to investigate the changes in secondary structure accompanying chemical and thermal denaturation of detergent-solubilised sodium channels isolated from Electrophorus electricus electroplax. The proteins appear to be remarkably resistant to either type of treatment, with "denatured" channels, retaining significant helical secondary structure even at 77 degrees C or in 10% SDS. Further retention of helical secondary structure at high temperature was observed in the presence of the channel-blocking tetrodotoxin. It was possible to refold the thermally-denatured (but not chemically-denatured) channels in vitro. The correctly refolded channels were capable of undergoing the toxin-induced conformational change indicative of ligand binding. In addition, flux measurements in liposomes showed that the thermally-denatured (but not chemically-denatured) proteins were able to re-adopt native, active conformations. These studies suggest that whilst sodium channels must be sufficiently flexible to undergo major conformational changes during their functional cycle, the proteins are highly resistant to unfolding, a feature that is important for maintaining structural integrity during dynamic processes. (c) 2009 Elsevier B.V. All rights reserved

In the light of directed evolution: Pathways of adaptive protein evolution

Directed evolution is a widely-used engineering strategy for improving the stabilities or biochemical functions of proteins by repeated rounds of mutation and selection. These experiments offer empirical lessons about how proteins evolve in the face of clearly-defined laboratory selection pressures. Directed evolution has revealed that single amino acid mutations can enhance properties such as catalytic activity or stability and that adaptation can often occur through pathways consisting of sequential beneficial mutations. When there are no single mutations that improve a particular protein property experiments always find a wealth of mutations that are neutral with respect to the laboratory-defined measure of fitness. These neutral mutations can open new adaptive pathways by at least 2 different mechanisms. Functionally-neutral mutations can enhance a protein's stability, thereby increasing its tolerance for subsequent functionally beneficial but destabilizing mutations. They can also lead to changes in “promiscuous” functions that are not currently under selective pressure, but can subsequently become the starting points for the adaptive evolution of new functions. These lessons about the coupling between adaptive and neutral protein evolution in the laboratory offer insight into the evolution of proteins in nature

Foreword

The postsynaptic density protein-95/disks large/zonula occludens-1 (PDZ) protein domain family is one of the most common proteinprotein interaction modules in mammalian cells, with paralogs present in several hundred human proteins. PDZ domains are found in most cell types, but neuronal proteins, for example, are particularly rich in these domains. The general function of PDZ domains is to bring proteins together within the appropriate cellular compartment, thereby facilitating scaffolding, signaling, and trafficking events. The many functions of PDZ domains under normal physiological as well as pathological conditions have been reviewed recently. In this review, we focus on the molecular details of how PDZ domains bind their protein ligands and their potential as drug targets in this context

Ion-binding properties of a K+ channel selectivity filter in different conformations

K(+) channels are membrane proteins that selectively conduct K(+) ions across lipid bilayers. Many voltage-gated K(+) (K(V)) channels contain two gates, one at the bundle crossing on the intracellular side of the membrane and another in the selectivity filter. The gate at the bundle crossing is responsible for channel opening in response to a voltage stimulus, whereas the gate at the selectivity filter is responsible for C-type inactivation. Together, these regions determine when the channel conducts ions. The K(+) channel from Streptomyces lividians (KcsA) undergoes an inactivation process that is functionally similar to K(V) channels, which has led to its use as a practical system to study inactivation. Crystal structures of KcsA channels with an open intracellular gate revealed a selectivity filter in a constricted conformation similar to the structure observed in closed KcsA containing only Na(+) or low [K(+)]. However, recent work using a semisynthetic channel that is unable to adopt a constricted filter but inactivates like WT channels challenges this idea. In this study, we measured the equilibrium ion-binding properties of channels with conductive, inactivated, and constricted filters using isothermal titration calorimetry (ITC). EPR spectroscopy was used to determine the state of the intracellular gate of the channel, which we found can depend on the presence or absence of a lipid bilayer. Overall, we discovered that K(+) ion binding to channels with an inactivated or conductive selectivity filter is different from K(+) ion binding to channels with a constricted filter, suggesting that the structures of these channels are different

Structure of a Membrane-Embedded Prenyltransferase Homologous to UBIAD1

Membrane-embedded prenyltransferases from the UbiA family catalyze the Mg2+-dependent transfer of a hydrophobic polyprenyl chain onto a variety of acceptor molecules and are involved in the synthesis of molecules that mediate electron transport, including Vitamin K and Coenzyme Q. In humans, missense mutations to the protein UbiA prenyltransferase domain-containing 1 (UBIAD1) are responsible for Schnyder crystalline corneal dystrophy, which is a genetic disease that causes blindness. Mechanistic understanding of this family of enzymes has been hampered by a lack of three-dimensional structures. We have solved structures of a UBIAD1 homolog from Archaeoglobus fulgidus, AfUbiA, in an unliganded form and bound to Mg2+ and two different isoprenyl diphosphates. Functional assays on MenA, a UbiA family member from E. coli, verified the importance of residues involved in Mg2+ and substrate binding. The structural and functional studies led us to propose a mechanism for the prenyl transfer reaction. Disease-causing mutations in UBIAD1 are clustered around the active site in AfUbiA, suggesting the mechanism of catalysis is conserved between the two homologs

A Random Forest model for predicting allosteric and functional sites on proteins

We thank the Scottish Universities Life Sciences Alliance (SULSA) for funding to JBOM and for PB’s PhD studentship under NJW’s supervision.We created a computational method to identify allosteric sites using a machine learning method trained and tested on protein structures containing bound ligand molecules. The Random Forest machine learning approach was adopted to build our three-way predictive model. Based on descriptors collated for each ligand and binding site, the classification model allows us to assign protein cavities as allosteric, regular or orthosteric, and hence to identify allosteric sites. 43 structural descriptors per complex were derived and were used to characterize individual protein-ligand binding sites belonging to the three classes, allosteric, regular and orthosteric. We carried out a separate validation on a further unseen set of protein structures containing the ligand 2-(N-cyclohexylamino) ethane sulfonic acid (CHES).PostprintPeer reviewe