Biology subjects

Grossfield, A.

Publications and source records attributed to Grossfield, A..

10 recordsLinked to original sources

bioRxiv2026

Physical Basis Of pKa Shift For Ionizable Lipids In An LNP-like Environment

Lipid nanoparticles (LNPs) are a leading drug delivery platform for mRNA or other nucleic acid-based therapeutics. LNP platforms are typically composed of ionizable aminolipids, phospholipids, sterols, and lipids tagged with polyethylene glycol. The ionizable aminolipids are typically cationic at low pH, allowing them to encapsulate negatively charged mRNA. The pH at which the ionizable head groups change charge states, the apparent pKa, is crucial to understand the characteristics and formulation of LNP. However, this is difficult to measure as the apparent pKa differs from the pKa of the aminolipids in bulk solution due to the complex chemical and charge environment. In this study, we use molecular dynamics (MD) simulations with alchemical free energy perturbation to calculate the pKa shift as a function of lipid composition, treating LNP-like and vesicle-like environments. Our results show that the pH-dependent structure of the systems affects the trends in pKa shifts in complex ways, driven by factors including surface electrostatics and lipid internalization. Our all-atom simulation protocol allows us to efficiently estimate the apparent pKa of LNP-like models formed with novel ionizable aminolipids and estimate how it will change with composition.

biophysics↗

bioRxiv2026

Ultrafast X-Rays Capture Retinal Traversing Conical Intersection in Rhodopsin

G-protein-coupled receptors of the Rhodopsin family are crucial medicinal targets, transmitting signals across biomembranes. While light absorption by visual rhodopsin is well studied, its activation via retinal cofactor dynamics remains unclear. Here we use a free-electron laser to show that time-resolved X-ray solution scattering captures the retinal cis-trans isomerization as it passes the conical intersection of excited and ground-state photoproduct energy surfaces. Femtosecond-scale nuclear changes occur due to resonant photon absorption, with all-atom simulations revealing ultrafast amino acid movements that initiate transmembrane helix shifts. Ligand-free opsin measurements confirm that light activation is unaffected by non-resonant processes, showing the photonic energy is directly transmitted within the protein. Our method unveils how cofactor dynamics activate rhodopsin, free of constraints from crystal lattice packing or cryotrapping photointermediates.

biophysics↗

bioRxiv2026

Reparameterization of the Amber RNA Force Field Non-Bonded Terms

All-atom simulations of RNA using molecular dynamics have the promise of modeling conformational preferences, folding thermodynamics, conformational change kinetics, and binding affinities of small molecule therapeutics. These simulations rely on a force field, a set of equations and parameters that model the potential energy as a function of conformation using classical mechanics. One popular force field for RNA is Amber OL3, with the most recent iteration derived in 1999 and with subsequent updates to backbone dihedral parameters. The Amber force field, while frequently used, is known to have limitations; for example, it does not properly stabilize native structures against alternative structures. Here, we provide a new approach to fitting the non-bonded parameters for the force field, specifically atom-centered point charges for electrostatics and the Lennard-Jones parameters. The parameters are fit to quantum mechanics (QM) interaction energies calculated with symmetry-adapted perturbation theory (SAPT), including embedded point charges to represent the electrostatic field from solvent and adjacent nucleotides. In this pilot study with a limited set of fitting data, we use the Amber ff99 equations and atom types unchanged. With the revised parameters, we observe improvement in the stability of native structures relative to alternative structures. Native tetraloop conformations, which unfold with the Amber OL3 force field, are stable on the microsecond timescale with our new force field parameters. We also see improvement in the conformational preferences of tetramers. Crucially, A-form helices are still well-modeled, but we observe additional flexibility in an internal loop that is not consistent with NMR data. Overall, we provide evidence that this new approach to fitting RNA force field parameters to SAPT interaction energies with native-structure context represented as embedded point charges is promising. It offers a flexible solution for revising the equations in future work or for extension to other molecules that interact with RNA, such as proteins and small molecules. We call this new set of force field parameters Amber RNA.ROC26.

biochemistry↗

bioRxiv2026

Theoretical estimate of the effective pKa of titratable lipids using continuum electrostatics

The apparent pKa of ionizable lipids in lipid nanoparticles (LNPs) is a key determinant of RNA encapsulation during formulation and endosomal release after cellular uptake. However, it is difficult to predict the effective pKa of a given ionizable lipid solely from its solution pKa, because it is sensitive to the membranes composition, as well as solution conditions such as the salt concentration. We developed a simple continuum electrostatics model, based on Gouy-Chapman theory, to predict the shift in effective pKa for ionizable lipids in lipid bilayers as a function of salt concentration and membrane composition. We derive equations for the surface potential and fraction of lipids charged, which are solved self-consistently as a function of solution pH to extract the titration curve and effective pKa. The model shows that the shift in effective pKa is largest when the concentration of titratable lipid is high, and the effect is diminished by increasing salt concentration. We provide a python implementation of the model and an interactive notebook that will allow users to further easily explore the predicted pKa shifts as a function of formulation variables.

biophysics↗

bioRxiv2025

A simple theory to explain super-additivity of highly similar drug combinations

Small-molecule drugs canonically act by binding to a specific site on a single protein, leading to a change in the proteins activity. In particular, allosteric agonists bind preferentially to the active form of the protein, increasing the population of the active state and increasing activity. Hence, it is not surprising that similar compounds often act in similar ways, because they naturally bind to the same sites. However, recent work has provided examples of closely related small molecules that act super-additively when co-administered, a phenomenon that is difficult to explain using this approach. Here, we derive a simple thermodynamic model that describes how a super-additive response can occur, even for two very similar ligands. We discuss its implications for the specific case of cysteine-derived compounds and the treatment of opioid withdrawal symptoms and suggest avenues by which it could be tested experimentally.

biochemistry↗

bioRxiv2024

Essential Considerations for Free Energy Calculations of RNA-Small Molecule Complexes: Lessons from Theophylline-Binding RNA Aptamer

Alchemical free energy calculations are widely used to predict the binding affinity of small molecule ligands to protein targets; however, the application of these methods to RNA targets has not been deeply explored. We systematically investigated how modeling decisions affect the performance of absolute binding free energy calculations for a relatively simple RNA model system: theophylline-binding RNA aptamer with theophylline and five analogs. The goal of this investigation was twofold: (1) understanding the performance levels we can expect from absolute free energy calculations for a simple RNA complex and (2) learning about practical modeling considerations that impact the success of RNA binding predictions, which may be different than the best practices established for protein targets. We learned that magnesium ion (Mg2+) placement is a critical decision that impacts affinity predictions. When information regarding Mg2+ positions is lacking, implementing RNA backbone restraints is an alternative way of stabilizing RNA structure that recapitulates prediction accuracy. Since mistakes in Mg2+ placement can be detrimental, omitting magnesium ions entirely and using RNA backbone restraints is attractive as a risk-mitigating approach. We found that predictions are sensitive to modeling experimental buffer conditions correctly, including salt type and ionic strength. We explored the effects of sampling in the alchemical protocol, choice of the ligand force field (GAFF2/OpenFF Sage), and water model (TIP3P/OPC) on predictions, which allowed us to give practical advice for the application of free energy methods to RNA targets. By capturing experimental buffer conditions and implementing RNA backbone restraints, we were able to compute binding affinities accurately (MAE = 2.2 kcal/mol, Pearsons correlation coefficient = 0.9, Kendalls tau = 0.7). We believe there is much to learn about how to apply free energy calculations for RNA targets and how to enhance their performance in prospective predictions. This study is an important first step for learning best practices and special considerations for RNA-ligand free energy calculations. Future studies will consider increasingly complicated ligands and diverse RNA systems and help the development of general protocols for therapeutically relevant RNA targets.

biophysics↗

bioRxiv2023

Understanding the Free Energy Landscape of Phase Separation in Lipid Bilayers using Molecular Dynamics

Liquid-liquid phase separation (LLPS) inside the cell often results in biological condensates that can critically impact cell homeostasis. Such phase separation events occur in multiple parts of cells, including the cell membranes, where the so-called "lipid raft" hypothesis posits the formation of ordered domains floating in a sea of disordered lipids. The resulting lipid domains often have functional roles. However, the thermodynamics of lipid phase separation and their resulting mechanistic effects on cell function and dysfunction are poorly understood. Understanding such complex phenomena in cell membranes, with their diverse lipid compositions, is exceptionally difficult. For this reasons, simple model systems that can recapitulate similar behavior are widely used to study this phenomenon. Despite these simplifications, the timescale and and length scales of domain formation pose a challenge for molecular dynamics (MD) simulations. Thus, most MD studies focus on spontaneous lipid phase separation -- essentially measuring the sign (but not the amplitude) of the free energy change upon separation -- rather than directly interrogating the thermodynamics. Here, we propose a proof-of-concept pipeline that can directly measure this free energy by combining coarse-grained MD with enhanced sampling protocols using a novel collective variable. This approach will be a useful tool to help connect the thermodynamics of phase separation with the mechanistic insights already available from molecular dynamics simulations. SIGNIFICANCEStandard molecular dynamics simulations can determine the sign the free energy change upon phase separation, but not the amplitude. We present a new method to determine the phase separation free energy for lipid membranes, based on a enhanced sampling using the weighted ensemble method combined with a novel collective variable, validated using coarse-grained simulations applied to several simple systems. The new method will be valuable as a way to develop models that connect molecular-level structural features to the thermodynamics of phase separation.

biophysics↗

bioRxiv2022

Surveying non-visual arrestins reveals allosteric interactions between functional sites

1.Arrestins are important scaffolding proteins that are expressed in all vertebrate animals. They regulate cell signaling events upon binding to active G-protein coupled receptors (GPCR) and trigger endocytosis of active GPCRs. While many of the functional sites on arrestins have been characterized, the question of how these sites interact is unanswered. We used anisotropic network modelling (ANM) together with our covariance compliment techniques to survey all of the available structures of the non-visual arrestins to map how structural changes and protein-binding affect their structural dynamics. We found that activation and clathrin binding have a marked effect on arrestin dynamics, and that these dynamics changes are localized to a small number of distant functional sites. These sites include -helix 1, the lariat loop, nuclear localization domain, and the C-domain {beta}-sheets on the C-loop side. Our techniques suggest that clathrin binding and/or GPCR activation of arrestin perturb the dynamics of these sites independent of structural changes.

biophysics↗

bioRxiv2021

Effects of Cholesterol on the mechanism of fengycin, a biofungicide

Fengycins are a class of antifungal lipopeptides synthesized by the bacteria Bacillus subtilis, commercially available as the primary component of the agricultural fungicide Serenade(R). They are toxic to fungi, but far less to mammalian cells. One key difference between mammalian and fungal cell membranes is the presence of cholesterol only in the former; recent experimental work showed that the presence of cholesterol reduces fengycin-induced membrane leakage. (1) Since our previous all-atom and coarse-grained simulations (2, 3) suggested that aggregation of membrane-bound fengycin is central to its ability to disrupt membranes, we hypothesized that cholesterol might reduce fengycin aggregation. Here, we test this hypothesis using coarse-grained molecular dynamics simulations, with sampling enhanced via the weighted ensemble method. The results indicate that cholesterol subtly alters the size distribution for fengycin aggregates, limits the lateral range of their membrane disordering, and reduces the ability of aggregates to bend the membrane. Taken together, these phenomena may account for cholesterols affects on fengycin activity.

biophysics↗

bioRxiv2018

Chemically Accurate Relative Folding Stability of RNA Hairpins from Molecular Simulations

This study describes a comparison between melts and simulated stabilities of the same RNAs that could be used to benchmark RNA force fields, and potentially to determine future melt-ing experiments. Using umbrella sampling molecular simulations of three 12-nucleotide RNA hairpin stem loops, for which there are experimentally determined free energies of unfold-ing, we projected unfolding onto the reaction coordinate of end to end (5' to 3' hydroxyl oxygen) distance. We estimate the free energy change of the transition from the native con-formation to a fully extended conformation--the stretched state--with no hydrogen bonds between non-neighboring bases. Each simulation was performed four times using the AM-BER FF99+bsc0+{chi}OL3 force field and each window, spaced at 1 [A] intervals, was sampled for 1 s, for a total of 552 s of simulation. We compared differences in the simulated free energy changes to analogous differences in free energies from optical melting experiments using ther-modynamic cycles where the free energy change between stretched and random coil sequences is assumed to be sequence independent. The differences between experimental and simulated {Delta}{Delta}G{degrees} are on average 1.00 {+/-} 0.66 kcal/mol, which is chemically accurate and suggests analo-gous simulations could be used predictively. We also report a novel method to identify where replica free energies diverge along the reaction coordinate, thus indicating where additional sampling would most improve convergence. We conclude by discussing methods to more economically perform such simulations.

biophysics↗