The fungal natural product azaphilone-9 binds to HuR and inhibits HuR-RNA interaction in vitro.
PLoS One. 2017;12(4):e0175471
Authors: Kaur K, Wu X, Fields JK, Johnson DK, Lan L, Pratt M, Somoza AD, Wang CCC, Karanicolas J, Oakley BR, Xu L, De Guzman RN
The RNA-binding protein Hu antigen R (HuR) binds to AU-rich elements (ARE) in the 3'-untranslated region (UTR) of target mRNAs. The HuR-ARE interactions stabilize many oncogenic mRNAs that play important roles in tumorigenesis. Thus, small molecules that interfere with the HuR-ARE interaction could potentially inhibit cancer cell growth and progression. Using a fluorescence polarization (FP) competition assay, we identified the compound azaphilone-9 (AZA-9) derived from the fungal natural product asperbenzaldehyde, binds to HuR and inhibits HuR-ARE interaction (IC50 ~1.2 μM). Results from surface plasmon resonance (SPR) verified the direct binding of AZA-9 to HuR. NMR methods mapped the RNA-binding interface of HuR and identified the involvement of critical RNA-binding residues in binding of AZA-9. Computational docking was then used to propose a likely binding site for AZA-9 in the RNA-binding cleft of HuR. Our results show that AZA-9 blocks key RNA-binding residues of HuR and disrupts HuR-RNA interactions in vitro. This knowledge is needed in developing more potent AZA-9 derivatives that could lead to new cancer therapy.
PMID: 28414767 [PubMed - in process]
Gramicidin A Channel Formation Induces Local Lipid Redistribution II: A 3D Continuum Elastic Model.
Biophys J. 2017 Mar 28;112(6):1198-1213
Authors: Sodt AJ, Beaven AH, Andersen OS, Im W, Pastor RW
To change conformation, a protein must deform the surrounding bilayer. In this work, a three-dimensional continuum elastic model for gramicidin A in a lipid bilayer is shown to describe the sensitivity to thickness, curvature stress, and the mechanical properties of the lipid bilayer. A method is demonstrated to extract the gramicidin-lipid boundary condition from all-atom simulations that can be used in the three-dimensional continuum model. The boundary condition affects the deformation dramatically, potentially much more than typical variations in the material stiffness do as lipid composition is changed. Moreover, it directly controls the sensitivity to curvature stress. The curvature stress and hydrophobic surfaces of the all-atom and continuum models are found to be in excellent agreement. The continuum model is applied to estimate the enrichment of hydrophobically matched lipids near the channel in a mixture, and the results agree with single-channel experiments and extended molecular dynamics simulations from the companion article by Beaven et al. in this issue of Biophysical Journal.
PMID: 28355547 [PubMed - in process]
Gramicidin A Channel Formation Induces Local Lipid Redistribution I: Experiment and Simulation.
Biophys J. 2017 Mar 28;112(6):1185-1197
Authors: Beaven AH, Maer AM, Sodt AJ, Rui H, Pastor RW, Andersen OS, Im W
Integral membrane protein function can be modulated by the host bilayer. Because biological membranes are diverse and nonuniform, we explore the consequences of lipid diversity using gramicidin A channels embedded in phosphatidylcholine (PC) bilayers composed of equimolar mixtures of di-oleoyl-PC and di-erucoyl-PC (dC18:1+dC22:1, respectively), di-palmitoleoyl-PC and di-nervonoyl-PC (dC16:1+dC24:1, respectively), and di-eicosenoyl-PC (pure dC20:1), all of which have the same average bilayer chain length. Single-channel lifetime experiments, molecular dynamics simulations, and a simple lipid compression model are used in tandem to gain insight into lipid redistribution around the channel, which partially alleviates the bilayer deformation energy associated with channel formation. The average single-channel lifetimes in the two-component bilayers (95 ± 10 ms for dC18:1+dC22:1 and 195 ± 20 ms for dC16:1+dC24:1) were increased relative to the single-component dC20:1 control bilayer (65 ± 10 ms), implying lipid redistribution. Using a theoretical treatment of thickness-dependent changes in channel lifetimes, the effective local enrichment of lipids around the channel was estimated to be 58 ± 4% dC18:1 and 66 ± 2% dC16:1 in the dC18:1+dC22:1 and dC16:1+dC24:1 bilayers, respectively. 3.5-μs molecular dynamics simulations show 66 ± 2% dC16:1 in the first lipid shell around the channel in the dC16:1+dC24:1 bilayer, but no significant redistribution (50 ± 4% dC18:1) in the dC18:1+dC22:1 bilayer; these simulated values are within the 95% confidence intervals of the experimental averages. The strong preference for the better matching lipid (dC16:1) near the channel in the dC16:1+dC24:1 mixture and lesser redistribution in the dC18:1+dC22:1 mixture can be explained by the energetic cost associated with compressing the lipids to match the channel's hydrophobic length.
PMID: 28355546 [PubMed - in process]
"Solvent hydrogen-bond occlusion": A new model of polar desolvation for biomolecular energetics.
J Comput Chem. 2017 Mar 20;:
Authors: Bazzoli A, Karanicolas J
Water engages in two important types of interactions near biomolecules: it forms ordered "cages" around exposed hydrophobic regions, and it participates in hydrogen bonds with surface polar groups. Both types of interaction are critical to biomolecular structure and function, but explicitly including an appropriate number of solvent molecules makes many applications computationally intractable. A number of implicit solvent models have been developed to address this problem, many of which treat these two solvation effects separately. Here, we describe a new model to capture polar solvation effects, called SHO ("solvent hydrogen-bond occlusion"); our model aims to directly evaluate the energetic penalty associated with displacing discrete first-shell water molecules near each solute polar group. We have incorporated SHO into the Rosetta energy function, and find that scoring protein structures with SHO provides superior performance in loop modeling, virtual screening, and protein structure prediction benchmarks. These improvements stem from the fact that SHO accurately identifies and penalizes polar groups that do not participate in hydrogen bonds, either with solvent or with other solute atoms ("unsatisfied" polar groups). We expect that in future, SHO will enable higher-resolution predictions for a variety of molecular modeling applications. © 2017 Wiley Periodicals, Inc.
PMID: 28318014 [PubMed - as supplied by publisher]
Survival of Phenotypic Information during Cellular Growth Transitions.
ACS Synth Biol. 2016 08 19;5(8):810-6
Authors: Ray JC
Phenotypic memory can predispose cells to physiological outcomes, contribute to heterogeneity in cellular populations, and allow computation of environmental features, such as nutrient gradients. In bacteria and synthetic circuits in general, memory can often be set by protein concentrations: because of the relative stability of proteins, the degradation rate is often dominated by the growth rate, and inheritance is a significant factor. Cells can then be primed to respond to events that recur with frequencies faster than the time to eliminate proteins. Protein memory can be extended if cells reach extremely low growth rates or no growth. Here we characterize the necessary time scales for different quantities of protein memory, measured as relative entropy (Kullback-Leibler divergence), for a variety of cellular growth arrest transition dynamics. We identify a critical manifold in relative protein degradation/growth arrest time scales where information is, in principle, preserved indefinitely because proteins are trapped at a concentration determined by the competing time scales as long as nongrowth-mediated protein degradation is negligible. We next asked what characteristics of growth arrest dynamics and initial protein distributions best preserve or eliminate information about previous environments. We identified that sharp growth arrest transitions with skewed initial protein distributions optimize flexibility, with information preservation and minimal cost of residual protein. As a result, a nearly memoryless regime, corresponding to a form of bet-hedging, may be an optimal strategy for storage of information by protein concentrations in growth-arrested cells.
PMID: 26910476 [PubMed - indexed for MEDLINE]
Computing the Dynamic Supramolecular Structural Proteome.
PLoS Comput Biol. 2017 Jan;13(1):e1005290
Authors: Nussinov R, Papin JA, Vakser I
PMID: 28103234 [PubMed - in process]