Kathryn A. Thomasson

Brownian Dynamics Simulations of Interactions between Aldolase and G- or F-Actin

Compartmentation of proteins in cells is important to proper cell function. Interactions of F-actin and glycolytic enzymes is one mechanism by which glycolytic enzymes can compartment. Brownian dynamics (BD) simulations of the binding of the muscle form of the glycolytic enzyme fructose-1,6-bisphosphate aldolase (aldolase) to F- or G-actin provide first-encounter snapshots of these interactions. Using x-ray structures of aldolase, G-actin, and three-dimensional models of F-actin, the electrostatic potential about each protein was predicted by solving the linearized Poisson-Boltzmann equation for use in BD simulations. The BD simulations provided solution complexes of aldolase with F- or G-actin. All complexes demonstrate the close contacts between oppositely charged regions of the protein surfaces. Positively charged surface regions of aldolase (residues Lys 13, 27, 288, 293, and 341 and Arg 257) are attracted to the negatively charged amino terminus (Asp 1 and Glu 2 and 4) and other patches (Asp 24, 25, and 363 and Glu 361, 364, 99, and 100) of actin subunits. According to BD results, the most important factor for aldolase binding to actin is the quaternary structure of aldolase and actin. Two pairs of adjacent aldolase subunits greatly add to the positive electrostatic potential of each other creating a region of attraction for the negatively charged subdomain 1 of the actin subunit that is exposed to solvent in the quaternary F-actin structure.

Identification of specific calcitonin-like receptor residues important for calcitonin gene-related peptide high affinity binding.

BackgroundCalcitonin gene-related peptide (CGRP) is a vasoactive neuropeptide whose biological activity has potential therapeutic value for many vascular related diseases. CGRP is a 37 amino acid neuropeptide that signals through a G protein-coupled receptor belonging to the secretin receptor family. Previous studies on the calcitonin-like receptor (CLR), which requires co-expression of the receptor-activity-modifying protein-1 (RAMP1) to function as a CGRP receptor, have shown an 18 amino acid N-terminus sequence important for binding CGRP. Moreover, several investigations have recognized the C-terminal amidated phenylalanine (F37) of CGRP as essential for docking to the mature receptor. Therefore, we hypothesize that hydrophobic amino acids within the previously characterized 18 amino acid CLR N-terminus domain are important binding contacts for the C-terminal phenylalaninamide of CGRP.ResultsTwo leucine residues within this previously characterized CLR N-terminus domain, when mutated to alanine and expressed on HEK293T cells stably transfected with RAMP1, demonstrated a significantly decreased binding affinity for CGRP compared to wild type receptor. Additional decreases in binding affinity for CGRP were not found when both leucine mutations were expressed in the same CLR construct. Decreased binding characteristic of these leucine mutant receptors was observed for all CGRP ligands tested that contained the necessary amidated phenylalanine at their C-terminus. However, there was no difference in the potency of CGRP to increase cAMP production by these leucine mutant receptors when compared to wild type CLR, consistent with the notion that the neuropeptide C-terminal F37 is important for docking but not activation of the receptor. This observation was conserved when modified CGRP ligands lacking the amidated F37 demonstrated similar potencies to generate cAMP at both wild type and mutant CLRs. Furthermore, these modified CGRP ligands displayed a significant but similar loss of binding for all leucine mutant and wild type CLR because the important receptor contact on the neuropeptide was missing in all experimental situations.ConclusionThese results are consistent with previous structure-function investigations of the neuropeptide and are the first to propose specific CLR binding contacts for the amidated F37 of CGRP that are important for docking but not activation of the mature CGRP receptor.

Interactions of glyceraldehyde-3-phosphate dehydrogenase with G- and F-actin predicted by Brownian dynamics.

Brownian dynamics (BD) was used to simulate the binding of glyceraldehyde‐3‐phosphate dehydrogenase (GAPDH) to G‐ and F‐actin. High‐resolution three‐dimensional models (X‐ray and homology built) of the proteins were used in the simulations. The electrostatic potential about each protein was predicted by solving the linearized Poisson–Boltzmann equation for use in BD simulations. The BD simulations resulted in complexes of GAPDH with G‐ or F‐actin involving positively charged surface patches on GAPDH (Lyses 24, 69, 110 and 114) and negatively charged residues of the N‐ and C‐termini (Asps 1, 25 and 363 and Glus 2, 4, 224 and 364) of actin. The actin residues all belong to subdomain 1. Although the positively charged surface patches of GAPDH are not close enough to each other to enhance their electrostatic potential, occasionally two subunits of the GAPDH tetramer may simultaneously interact with two neighboring monomers of F‐actin. These results are different from those of fructose‐1,6‐bisphosphate aldolase, where quaternary structure directly influenced binding by two subunits combining their electrostatic potentials (see previous study, Ouporov et al., 1999 , Biophys. J. 76: 17–27). Instead, GAPDH uses its quaternary structure to span the distance between two different actin subunits so that it can interact with two different actin subunits simultaneously. Copyright

Brownian Dynamics Simulations of Aldolase Binding Glyceraldehyde 3- Phosphate Dehydrogenase and the Possibility of Substrate Channeling

Brownian dynamics (BD) simulations test for channeling of the substrate, glyceraldehyde 3-phosphate (GAP), as it passes between the enzymes fructose-1,6-bisphosphate aldolase (aldolase) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH). First, BD simulations determined the favorable complexes between aldolase and GAPDH; two adjacent subunits of GAPDH form salt bridges with two subunits of aldolase. These intermolecular contacts provide a strong electrostatic interaction between the enzymes. Second, BD simulates GAP moving out of the active site of the A or D aldolase subunit and entering any of the four active sites of GAPDH. The efficiency of transfer is determined as the relative number of BD trajectories that reached any active site of GAPDH. The distribution functions of the transfer time were calculated based on the duration of successful trajectories. BD simulations of the GAP binding from solution to aldolase/GAPDH complex were compared to the channeling simulations. The efficiency of transfer of GAP within an aldolase/GAPDH complex was 2 to 3% compared to 1.3% when GAP was binding to GAPDH from solution. There is a preference for GAP channeling between aldolase and GAPDH when compared to binding from solution. However, this preference is not large enough to be considered as a theoretical proof of channeling between these proteins.

Ionic strength dependence of F-actin and glycolytic enzyme associations: a Brownian dynamics simulations approach.

The association of glycolytic enzymes with F‐actin is proposed to be one mechanism by which these enzymes are compartmentalized, and, as a result, may possibly play important roles for: regulation of the glycolytic pathway, potential substrate channeling, and increasing glycolytic flux. Historically, in vitro experiments have shown that many enzyme/actin interactions are dependent on ionic strength. Herein, Brownian dynamics (BD) examines how ionic strength impacts the energetics of the association of F‐actin with the glycolytic enzymes: lactate dehydrogenase (LDH), glyceraldehyde‐3‐phosphate dehydrogenase (GAPDH), fructose‐1,6‐bisphosphate aldolase (aldolase), and triose phosphate isomerase (TPI). The BD simulations are steered by electrostatics calculated by Poisson‐Boltzmann theory. The BD results confirm experimental observations that the degree of association diminishes as ionic strength increases but also suggest that these interactions are significant, at physiological ionic strengths. Furthermore, BD agrees with experiments that muscle LDH, aldolase, and GAPDH interact significantly with F‐actin whereas TPI does not. BD indicates similarities in binding regions for aldolase and LDH among the different species investigated. Furthermore, the residues responsible for salt bridge formation in stable complexes persist as ionic strength increases. This suggests the importance of the residues determined for these binary complexes and specificity of the interactions. That these interactions are conserved across species, and there appears to be a general trend among the enzymes, support the importance of these enzyme‐F‐actin interactions in creating initial complexes critical for compartmentation. Proteins 2011;

Computer simulations of glycolytic enzyme interactions with F-actin.

Abstract Muscle actin and fructose-1, 6-bisphosphate aldolase (aldolase) were chemically crosslinked to produce an 80 kDa product representing one subunit of aldolase linked to one subunit of actin. Hydroxylamine digestion of the crosslinked product resulted in two 40.5 kDa fragments, one that was aldolase linked to the 12 N-terminal residues of actin. Brownian dynamics simulations of muscle aldolase and GAPDH with F-actin (muscle, yeast, and various mutants) estimated the association free energy. Mutations of residues 1–4 of muscle actin to Ala individually or two in combination of the first four residues reduced the estimated binding free energy. Simulations showed that muscle aldolase binds with the same affinity to the yeast actin as to the double mutated muscle actin; these mutations make the N-terminal of muscle actin identical to yeast, supporting the conclusion that the actin N-terminus participates in binding. Because the depth of free energy wells for yeast and the double mutants is less than for native rabbit actin, the simulations support experimental findings that muscle aldolase and GAPDH have a higher affinity for muscle actin than for yeast actin. Furthermore, Brownian dynamics revealed that the lower affinity of yeast actin for aldolase and GAPDH compared to muscle actin, was directly related to the acidic residues at the N-terminus of actin.

Molecular recognition of a tris(histidine) ligand

Design and synthesis of a tri-Hg2+ complex to selectivity recognize a tris(histidine) ligand is presented.