Free Energy Calculations for the Peripheral Binding of Proteins/Peptides to an Anionic Membrane. 1. Implicit Membrane Models

The binding of peptides and proteins to the surface of complex lipid membranes is important in many biological processes such as cell signaling and membrane remodeling. Computational studies can aid experiments by identifying physical interactions and structural motifs that determine the binding affinity and specificity. However, previous studies focused on either qualitative behaviors of protein/membrane interactions or the binding affinity of small peptides. Motivated by this observation, we set out to develop computational protocols for bimolecular binding to charged membranes that are applicable to both peptides and large proteins. In this work, we explore a method based on an implicit membrane/solvent model (generalized Born with a simple switching in combination with the Gouy–Chapman–Stern model for a charged interface), which we expect to lead to useful results when the binding does not implicate significant membrane deformation and local demixing of lipids. We show that the binding free energy can be efficiently computed following a thermodynamic cycle similar to protein–ligand binding calculations, especially when a Bennett acceptance ratio based protocol is used to consider both the membrane bound and solution conformational ensembles. Test calculations on a series of peptides show that our computational approach leads to binding affinities in encouraging agreement with experimental data, including for the challenging example of the bringing of flexible MARCKS-ED peptides to membranes. The calculations highlight that for a membrane with a significant fraction of anionic lipids, it is essential to include the effect of ion adsorption using the Stern model, which significantly modifies the effective surface charge. This implicit membrane model based computational protocol helps lay the groundwork for more systematic analysis of protein/peptide binding to membranes of complex shape and composition

Molecular Mechanism of Stabilizing the Helical Structure of Huntingtin N17 in a Micellar Environment

Huntington’s disease is a deadly neurodegenerative disease caused by the fibrilization of huntingtin (HTT) exon-1 protein mutants. Despite extensive efforts over the past decade, much remains unknown about the structures of (mutant) HTT exon-1 and their enigmatic roles in aggregation. Particularly, whether the first 17 residues in the N-terminal (HTT-N17) adopt a helical or a coiled structure remains unclear. Here, with the rigorous study of molecular dynamics simulations, we explored the most possible structures of HTT-N17 in both dodecylphosphocholine (DPC) micelles and aqueous solution, using three commonly applied force fields (OPLS-AA/L, CHARMM36, and AMBER99sb*-ILDNP) to examine the underlying molecular mechanisms and rule out potential artifacts. We show that local environments are essential for determining the secondary structure of HTT-N17. This is evidenced by the insertion of five hydrophobic residues of HTT-N17 into the DPC micelle, which promotes the formation of an amphipathic helix, whereas such amphipathic helices unfold quickly in aqueous solution. A relatively low free-energy barrier (∼3 kcal/mol) for the secondary structure transformation was also observed for all three force fields from their respective folding-free-energy landscapes, which accounts for possible HTT-N17 conformational changes upon environmental shifts such as membrane binding and protein complex aggregation

Binding Specificity Determines the Cytochrome P450 3A4 Mediated Enantioselective Metabolism of Metconazole

Cytochrome P450 3A4 (CYP3A4) is a promiscuous enzyme, mediating the biotransformations of ∼50% of clinically used drugs, many of which are chiral molecules. Probing the interactions between CYP3A4 and chiral chemicals is thus essential for the elucidation of molecular mechanisms of enantioselective metabolism. We developed a stepwise-restrained-molecular-dynamics (MD) method to model human CYP3A4 in a complex with <i>cis</i>-metconazole (MEZ) isomers and performed conventional MD simulations with a total simulation time of 2.2 μs to probe the molecular interactions. Our current study, which employs a combined experimental and theoretical approach, reports for the first time on the distinct conformational changes of CYP3A4 that are induced by the enantioselective binding of <i>cis</i>-MEZ enantiomers. CYP3A4 preferably metabolizes <i>cis</i>-<i>RS</i> MEZ over the <i>cis</i>-<i>SR</i> isomer, with the resultant enantiomer fraction for <i>cis</i>-MEZ increasing rapidly from 0.5 to 0.82. <i>cis</i>-<i>RS</i> MEZ adopts a more extended structure in the active pocket with its Cl atom exposed to the solvent, whereas <i>cis</i>-<i>SR</i> MEZ sits within the hydrophobic core of the active pocket. Free-energy-perturbation calculations indicate that unfavorable van der Waals interactions between the <i>cis</i>-MEZ isomers and the CYP3A4 binding pocket predominantly contribute to their binding-affinity differences. These results demonstrate that binding specificity determines the cytochrome P450 3A4 mediated enantioselective metabolism of <i>cis</i>-MEZ

Lipid Corona Formation from Nanoparticle Interactions with Bilayers and Membrane-Specific Biological Outcomes

<a></a><a>While mixing nanoparticles with certain biological molecules can result in coronas that afford some control over how engineered nanomaterials interact with living systems, corona formation mechanisms remain enigmatic. Here, we report spontaneous lipid corona formation, i.e. without active mixing, upon attachment to stationary lipid bilayer model membranes and bacterial cell envelopes, and present ribosome-specific outcomes for multi-cellular organisms. Experiments show that polycation-wrapped particles disrupt the tails of zwitterionic lipids, increase bilayer fluidity, and leave the membrane with reduced ζ-potentials. Computer simulations show contact ion pairing between the lipid headgroups and the polycations’ ammonium groups leads to the formation of stable, albeit fragmented, lipid bilayer coronas, while microscopy shows fragmented bilayers around nanoparticles after interacting with <i>Shewanella oneidensis</i>. Our mechanistic insight can be used to improve control over nano-bio interactions and to help understand why some nanomaterial/ligand combinations are detrimental to organisms, like <i>Daphnia magna</i>, while others are not. </a