Maximum Flux Transition Paths of Conformational Change

Given two metastable states A and B of a biomolecular system, the problem is to calculate the likely paths of the transition from A to B. Such a calculation is more informative and more manageable if done for a reduced set of collective variables chosen so that paths cluster in collective variable space. The computational task becomes that of computing the "center" of such a cluster. A good way to define the center employs the concept of a committor, whose value at a point in collective variable space is the probability that a trajectory at that point will reach B before A. The committor "foliates" the transition region into a set of isocommittors. The maximum flux transition path is defined as a path that crosses each isocommittor at a point which (locally) has the highest crossing rate of distinct reactive trajectories. (This path is different from that of the MaxFlux method of Huo and Straub.) It is argued that such a path is nearer to an ideal path than others that have been proposed with the possible exception of the finite-temperature string method path. To make the calculation tractable, three approximations are introduced, yielding a path that is the solution of a nonsingular two-point boundary-value problem. For such a problem, one can construct a simple and robust algorithm. One such algorithm and its performance is discussed.Comment: 7 figure

Charge environments around phosphorylation sites in proteins

Background: Phosphorylation is a central feature in many biological processes. Structural analyses have identified the importance of charge-charge interactions, for example mediating phosphorylation-driven allosteric change and protein binding to phosphopeptides. Here, we examine computationally the prevalence of charge stabilisation around phosphorylated sites in the structural database, through comparison with locations that are not phosphorylated in the same structures. Results: A significant fraction of phosphorylated sites appear to be electrostatically stabilised, largely through interaction with sidechains. Some examples of stabilisation across a subunit interface are evident from calculations with biological units. When considering the immediately surrounding environment, in many cases favourable interactions are only apparent after conformational change that accompanies phosphorylation. A simple calculation of potential interactions at longer-range, applied to non-phosphorylated structures, recovers the separation exhibited by phosphorylated structures. In a study of sites in the Phospho.ELM dataset, for which structural annotation is provided by non-phosphorylated proteins, there is little separation of the known phospho-acceptor sites relative to background, even using the wider interaction radius. However, there are differences in the distributions of patch polarity for acceptor and background sites in the Phospho.ELM dataset. Conclusion: In this study, an easy to implement procedure is developed that could contribute to the identification of phospho-acceptor sites associated with charge-charge interactions and conformational change. Since the method gives information about potential anchoring interactions subsequent to phosphorylation, it could be combined with simulations that probe conformational change. Our analysis of the Phospho.ELM dataset also shows evidence for mediation of phosphorylation effects through (i) conformational change associated with making a solvent inaccessible phospho-acceptor site accessible, and (ii) modulation of protein-protein interactions

Anion transport inhibitor binding to band 3 in red blood cell membranes.

The inhibitor of anion exchange 4,4'-dibenzoamido-2,2'-disulfonic stilbene (DBDS) binds to band 3, the anion transport protein in human red cell ghost membranes, and undergoes a large increase in fluorescence intensity when bound to band 3. Equilibrium binding studies performed in the absence of transportable anions show that DBDS binds to both a class of high-affinity (65 nM) and low-affinity (820 nM) sites with stoichiometry equivalent to 1.6 nmol/mg ghost protein for each site, which is consistent with one DBDS site on each band 3 monomer. The kinetics of DBDS binding were studied both by stopped-flow and temperature-jump experiments. The stopped-flow data indicate that DBDS binding to the apparent high-affinity site involves association with a low-affinity site (3 microM) followed by a slow (4 s-1) conformational change that locks the DBDS molecule in place. A detailed, quantitative fit of the temperature-jump data to several binding mechanisms supports a sequential-binding model, in which a first DBDS molecule binds to one monomer and induces a conformational change. A second DBDS molecule then binds to the second monomer. If the two monomers are assumed to be initially identical, thermodynamic characterization of the binding sites shows that the conformational change induces an interaction between the two monomers that modifies the characteristics of the second DBDS binding site

Molecular recognition mechanisms of calmodulin examined by perturbation-response scanning

We analyze the apo and holo calmodulin (CaM) structures by sequentially inserting a perturbation on every residue of the protein, and monitoring the linear response. Residue crosscorrelation matrices obtained from 20 ns long molecular dynamics simulation of the apo-form are used as the kernel in the linear response. We determine two residues whose perturbation equivalently yields the experimentally determined displacement profiles of CaM, relevant to the binding of the trifluoperazine (TFP) ligand. They reside on structurally equivalent positions on the N- and C-terminus lobes of CaM, and are not in direct contact with the binding region. The direction of the perturbation that must be inserted on these residues is an important factor in recovering the conformational change, implying that highly selective binding must occur near these sites to invoke the necessary conformational change

A network model to investigate structural and electrical properties of proteins

One of the main trend in to date research and development is the miniaturization of electronic devices. In this perspective, integrated nanodevices based on proteins or biomolecules are attracting a major interest. In fact, it has been shown that proteins like bacteriorhodopsin and azurin, manifest electrical properties which are promising for the development of active components in the field of molecular electronics. Here we focus on two relevant kinds of proteins: The bovine rhodopsin, prototype of GPCR protein, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer disease. Both these proteins exert their functioning starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different electrical response associated with the different configurations. The model resolution of the electrical response is found able to monitor the structure and the conformational change of the given protein. In this respect, rhodopsin exhibits a better differential response than AChE. This result gives room to different interpretations of the degree of conformational change and in particular supports a recent hypothesis on the existence of a mixed state already in the native configuration of the protein.Comment: 25 pages, 12 figure

Structure of protease-cleaved escherichia coliα-2-macroglobulin reveals a putative mechanism of conformational activation for protease entrapment

Bacterial -2-macroglobulins have been suggested to function in defence as broad-spectrum inhibitors of host proteases that breach the outer membrane. Here, the X-ray structure of protease-cleaved Escherichia coli -2-macroglobulin is described, which reveals a putative mechanism of activation and conformational change essential for protease inhibition. In this competitive mechanism, protease cleavage of the bait-region domain results in the untethering of an intrinsically disordered region of this domain which disrupts native interdomain interactions that maintain E. coli -2-macroglobulin in the inactivated form. The resulting global conformational change results in entrapment of the protease and activation of the thioester bond that covalently links to the attacking protease. Owing to the similarity in structure and domain architecture of Escherichia coli -2-macroglobulin and human -2-macro­globulin, this protease-activation mechanism is likely to operate across the diverse members of this group