PubMed Health⌕ Search

Biomedical subjects

Michael E Wall

Publications and source records attributed to Michael E Wall.

7 recordsLinked to original sources
PubMed2006

Interactions in native binding sites cause a large change in protein dynamics.

Cellular functions are regulated by molecules that interact with proteins and alter their activities. To enable such control, protein activity, and therefore protein conformational distributions, must be susceptible to alteration by molecular interactions at functional sites. Here we investigate whether interactions at functional sites cause a large change in the protein conformational distribution. We apply a computational method, called dynamics perturbation analysis (DPA), to identify sites at which interactions have a large allosteric potential D(x), which is the Kullback-Leibler divergence between protein conformational distributions with and without an interaction. In DPA, a protein is decorated with surface points that interact with neighboring protein atoms, and D(x) is calculated for each of the points in a coarse-grained model of protein vibrations. We use DPA to examine hundreds of protein structures from a standard small-molecule docking test set, and find that ligand-binding sites have elevated values of D(x): for 95% of proteins, the probability of randomly obtaining values as high as those in the binding site is 10(-3) or smaller. We then use DPA to develop a computational method to predict functional sites in proteins, and find that the method accurately predicts ligand-binding-site residues for proteins in the test set. The performance of this method compares favorably with that of a cleft analysis method. The results confirm that interactions at small-molecule binding sites cause a large change in the protein conformational distribution, and motivate using DPA for large-scale prediction of functional sites in proteins. They also suggest that natural selection favors proteins whose activities are capable of being regulated by molecular interactions.

Algorithms↗
PubMed2005

Allostery in a coarse-grained model of protein dynamics.

We propose a criterion for optimal parameter selection in coarse-grained models of proteins and develop a refined elastic network model (ENM) of bovine trypsinogen. The unimodal density-of-states distribution of the trypsinogen ENM disagrees with the bimodal distribution obtained from an all-atom model; however, the bimodal distribution is recovered by strengthening interactions between atoms that are backbone neighbors. We use the backbone-enhanced model to analyze allosteric mechanisms of trypsinogen and find relatively strong communication between the regulatory and active sites.

Algorithms↗
PubMed2005

Quantifying allosteric effects in proteins.

In allosteric regulation, protein activity is altered when ligand binding causes changes in the protein conformational distribution. Little is known about which aspects of protein design lead to effective allosteric regulation, however. To increase understanding of the relation between protein structure and allosteric effects, we have developed theoretical tools to quantify the influence of protein-ligand interactions on probability distributions of reaction rates and protein conformations. We define the rate divergence, Dk, and the allosteric potential, Dx, as the Kullback-Leibler divergence between either the reaction-rate distributions or protein conformational distributions with and without the ligand bound. We then define Dx as the change in the conformational distribution of the combined protein/ligand system, derive Dx in the harmonic approximation, and identify contributions from 3 separate terms: the first term, D[stackxomega], results from changes in the eigenvalue spectrum; the second term, D[stackxDeltax], results from changes in the mean conformation; and the third term, Dxv, corresponds to changes in the eigenvectors. Using normal modes analysis, we have calculated these terms for a natural interaction between lysozyme and the ligand tri-N-acetyl-D-glucosamine, and compared them with calculations for a large number of simulated random interactions. The comparison shows that interactions in the known binding-site are associated with large values of Dxv. The results motivate using allosteric potential calculations to predict functional binding sites on proteins, and suggest the possibility that, in Nature, effective ligand interactions occur at intrinsic control points at which binding induces a relatively large change in the protein conformational distribution.

Allosteric Regulation↗
PubMed2005

Multiple functions of a feed-forward-loop gene circuit.

The feed-forward-loop (FFL), a network motif in genetic regulatory networks, involves two transcription factors (TFs): one regulates the expression of the second, and both TFs regulate the expression of an effector gene. Analysis of FFL design principles has been initiated, but the functional significance of the FFL is still unclear. In theoretical studies so far, the TFs are assumed to interact with different signals, which is common. However, we have found examples of FFLs in Escherichia coli in which both TFs interact with the same signal. These examples belong to the type 2 incoherent class of FFLs, in which each TF acts exclusively as a repressor of transcription. Here, we analyze mathematical models of this class of circuits, examining a comprehensive array of subclasses that differ in the way a signal modulates the activities of the TFs. Through parameter variation, we characterize statistically how input/output (I/O) behavior and temporal responsiveness are predicted to depend on the wiring of signal interactions in a circuit. We find that circuits can exhibit any of 13 qualitatively distinct steady-state I/O patterns, including inducible and repressible patterns. Some subclasses exhibit as many as six patterns. Transient pulses are also possible, and the response of a circuit to a signal may be either faster or slower than that of a gene circuit in which there is only one TF. Our results provide a catalog of functions for a class of FFL circuits, whose subclasses have different breadths of possible behaviors and different typical behaviors.

Escherichia coli↗
PubMed2003

Design principles for regulator gene expression in a repressible gene circuit.

We consider the design of a type of repressible gene circuit that is common in bacteria. In this type of circuit, a regulator protein acts to coordinately repress the expression of effector genes when a signal molecule with which it interacts is present. The regulator protein can also independently influence the expression of its own gene, such that regulator gene expression is repressible (like effector genes), constitutive, or inducible. Thus, a signal-directed change in the activity of the regulator protein can result in one of three patterns of coupled regulator and effector gene expression: direct coupling, in which regulator and effector gene expression change in the same direction; uncoupling, in which regulator gene expression remains constant while effector gene expression changes; or inverse coupling, in which regulator and effector gene expression change in opposite directions. We have investigated the functional consequences of each form of coupling using a mathematical model to compare alternative circuits on the basis of engineering-inspired criteria for functional effectiveness. The results depend on whether the regulator protein acts as a repressor or activator of transcription at the promoters of effector genes. In the case of repressor control of effector gene expression, direct coupling is optimal among the three forms of coupling, whereas in the case of activator control, inverse coupling is optimal. Results also depend on the sensitivity of effector gene expression to changes in the level of a signal molecule; the optimal form of coupling can be physically realized only for circuits with sufficiently small sensitivity. These theoretical results provide a rationale for autoregulation of regulator genes in repressible gene circuits and lead to testable predictions, which we have compared with data available in the literature and electronic databases.

Gene Expression Regulation, Bacterial↗
PubMed2003

Mechanisms associated with cGMP binding and activation of cGMP-dependent protein kinase.

Using small-angle x-ray scattering, we have observed the cGMP-induced elongation of an active, cGMP-dependent, monomeric deletion mutant of cGMP-dependent protein kinase (Delta(1-52)PKG-I beta). On saturation with cGMP, the radius of gyration of Delta(1-52)PKG-I beta increases from 29.4 +/- 0.1 A to 40.1 +/- 0.7 A, and the maximum linear dimension increases from 90 A +/- 10% to 130 A +/- 10%. The elongation is due to a change in the interaction between structured regulatory (R) and catalytic (C) domains. A model of cGMP binding to Delta(1-52)PKG-I beta indicates that elongation of Delta(1-52)PKG-I beta requires binding of cGMP to the low-affinity binding site of the R domain. A comparison with cAMP-dependent protein kinase suggests that both elongation and activation require cGMP binding to both sites; cGMP binding to the low-affinity site therefore seems to be a necessary, but not sufficient, condition for both elongation and activation of Delta(1-52)PKG-I beta. We also predict that there is little or no cooperativity in cGMP binding to the two sites of Delta(1-52)PKG-I beta under the conditions used here. Results obtained by using the Delta(1-52)PKG-I beta monomer indicate that a previously observed elongation of PKG-I alpha is consistent with a pure change in the interaction between the R domain and the C domain, without alteration of the dimerization interaction. This study has revealed important features of molecular mechanisms in the biochemical network describing PKG-I beta activation by cGMP, yielding new insight into ligand activation of cyclic nucleotide-dependent protein kinases, a class of regulatory proteins that is key to many cellular processes.

Binding Sites↗