Biology subjects

Sherman, W.

Publications and source records attributed to Sherman, W..

6 recordsLinked to original sources

bioRxiv2025

Interactions with lipid membrane modulate the conformational dynamics and energy landscape of Tumor Necrosis Factor

Tumor Necrosis Factor (TNF) is a trimeric cytokine that exists in soluble (sTNF) and membrane-bound (mTNF) forms, both of which regulate immune responses through interactions with their cognate receptors. sTNF has been the subject of extensive biophysical investigations, leading to a mechanistic model in which a symmetric arrangement of the trimer promotes receptor signaling, whereas asymmetric conformations inhibit this function. In contrast, the structural and energetic landscape of mTNF remains largely under-explored. Here, we combined multi-microsecond unbiased molecular dynamics and Metadynamics-Adaptive Biasing Force simulations to characterize mTNF embedded in a physiologically relevant lipid bilayer. We show that in the absence of membrane engagement, the extracellular domain (ECD) dynamically samples multiple asymmetric conformations similar to those observed in sTNF. The association of the ECD with the membrane, mediated primarily by the basic residues R78-R82, R107, R108, R120, and R207, restricts conformational heterogeneity and stabilizes the symmetric state. By quantifying the energetic effects of ECD-membrane association, we demonstrate that the symmetric state in the membrane-bound ECD is stabilized over asymmetric conformations to a greater extent than in sTNF. This energetic effect, together with the spatial confinement imposed by the lipid bilayer, may explain the previously reported reduction in affinity of certain biologics for mTNF. In conclusion, our work elucidates how the membrane influences the structure, dynamics, and energetics of TNF. These mechanistic insights could guide future efforts to design mTNF-selective inhibitors that account for both membrane constraints and the energetic modulation of the ECD conformational landscape.

biophysics↗

bioRxiv2025

Spatial Analysis of Placentae During Congenital Cytomegalovirus Infection Reveals Distinct Cellular Profiles in Immune Cells and Trophoblasts

Withdrawal StatementThe authors have withdrawn the manuscript because the data it contained has been updated. Consequently, they request that this work should not be cited as a reference for any projects to ensure the use of the most current information. For any questions or further clarifications, readers are encouraged to contact the corresponding author directly

immunology↗

bioRxiv2024

STORMM: Structure and TOpology Replica Molecular Mechanics for chemical simulations

The Structure and TOpology Replica Molecular Mechanics (STORMM) code is a next-generation molecular simulation engine and associated libraries optimized for performance on fast, multicore central processor units (CPUs) and graphics processing units (GPUs) with independent memory and tens of thousands of threads. STORMM is built to run thousands of independent molecular mechanical calculations on a single GPU with novel implementations that optimize numerical precision, mathematical operations, throughput, and resource management. The libraries are built around accessible classes with detailed documentation, supporting fine-grained parallelism and algorithm development as well as macroscopic manipulations of groups of systems on and off of the GPU. A primary intention of the STORMM libraries is to provide developers of atomic simulation methods with access to a high-performance molecular mechanics engine with extensive facilities to prototype and develop bespoke tools aimed toward drug discovery applications. In its present state, STORMM delivers molecular dynamics simulations of small molecules and small proteins in implicit solvent with tens to hundreds of times the throughput of conventional codes. The engineering paradigm also transforms two of the most memory bandwidth-intensive aspects of condensed-phase dynamics, particle-mesh mapping and valence interactions, into compute-bound problems for several times the scalability of existing programs. Numerical methods for getting the most out of each bit of information present in stored coordinates and lookup tables are also presented, delivering improved accuracy over methods implemented in other molecular dynamics engines. The open-source code is released under the MIT license.

biophysics↗

bioRxiv2023

Comprehensive Approach to Simulating Large Scale Conformational Changes in Biological Systems Utilizing a Path Collective Variable and New Barrier Restraint

Conformational sampling of complex biomolecules is an emerging frontier in drug discovery. Advances in lab-based structural biology and related computational approaches like AlphaFold have made great strides in obtaining static protein structures for biologically relevant targets. However, biology is in constant motion and many important biological processes rely on conformationally-driven events. Conventional molecular dynamics (MD) simulations run on standard hardware, are impractical for many drug design projects, where conformationally-driven biological events can take microseconds to milliseconds or longer. An alternative approach is to focus the search on a limited region of conformational space defined by a putative reaction coordinate (i.e. path collective variable). The search space is typically limited by applying restraints, which can be guided by insights about the underlying biological process of interest. The challenge is striking a balance between the degree to which the system is constrained while still allowing for natural motions along the path. A plethora of restraints exist to limit the size of conformational search space, although each has drawbacks when simulating complex biological motions. In this work, we present a three-stage procedure to construct realistic path collective variables (PCV), and introduce a new kind of barrier restraint that is particularly well suited for complex conformationally-driven biological events, such as allosteric modulations and conformational signalling. The PCV presented here is all-atom (as opposed to C-alpha or backbone only) and is derived from all-atom MD trajectory frames. The new restraint relies on a barrier function (specifically, the scaled reciprocal function), which we show is particularly beneficial in the context of molecular dynamics, where near-hard-wall restraints are needed with zero tolerance to restraint violation. We have implemented our PCV and barrier restraint within a hybrid sampling framework that combines well-tempered meta-dynamics and extended-Lagrangian adaptive biasing force (meta-eABF). We use three particular examples of high pharmaceutical interest to demonstrate the value of this approach: (1) sampling the distance from ubiquitin to a protein of interest within the supramolecular Cullin-RING ligase complex, (2) stabilizing the wild-type conformation of the oncogenic mutant JAK2-V617F pseudokinase domain, and (3) inducing an activated state of the stimulator of interferon genes (STING) protein observed upon ligand binding. For (2) and (3), we present statistical analysis of meta-eABF free energy estimates and for each case, code for reproducing this work.

biophysics↗

bioRxiv2022

Design of a systemic small molecule clinical STING agonist using physics-based simulations and artificial intelligence

The protein STING (stimulator of interferon genes) is a central regulator of the innate immune system and plays an important role in antitumor immunity by inducing the production of cytokines such as type I interferon (IFN). Activation of STING stems from the selective recognition of endogenous cyclic dinucleotides (CDNs) by the large, polar, and flexible binding site, thus posing challenges to the design of small molecule agonists with drug-like physicochemical properties. In this work we present the design of SNX281, a small molecule STING agonist that functions through a unique self-dimerizing mechanism in the STING binding site, where the ligand dimer approximates the size and shape of a cyclic dinucleotide while maintaining drug-like small molecule properties. SNX281 exhibits systemic exposure, STING-mediated cytokine release, strong induction of type I IFN, potent in vivo antitumor activity, durable immune memory, and single-dose tumor elimination in mouse models via a Cmax-driven pharmacologic response. Bespoke computational methods - a combination of quantum mechanics, molecular dynamics, binding free energy simulations, and artificial intelligence - were developed during the course of the project to design SNX281 by explicitly accounting for the unique self-dimerization mechanism and the large-scale conformational change of the STING protein upon activation. Over the course of the project, we explored millions of virtual molecules while synthesizing and testing only 208 molecules in the lab. This work highlights the value of a multifaceted computationally-driven approach anchored by methods tailored to address target-specific problems encountered along the project progression from initial hit to the clinic.

cancer biology↗

bioRxiv2021

Atomic-Resolution Prediction of Degrader-mediated Ternary Complex Structures by Combining Molecular Simulations with Hydrogen Deuterium Exchange

Targeted protein degradation (TPD) has emerged as a powerful approach in drug discovery for removing (rather than inhibiting) proteins implicated in diseases. A key step in this approach is the formation of an induced proximity complex, where a degrader molecule recruits an E3 ligase to the protein of interest (POI), facilitating the transfer of ubiquitin to the POI and initiating the proteasomal degradation process. Here, we address three critical aspects of the TPD process: 1) formation of the ternary complex induced by a degrader molecule, 2) conformational heterogeneity of the ternary complex, and 3) assessment of ubiquitination propensity via the full Cullin Ring Ligase (CRL) macromolecular assembly. The novel approach presented here combines experimental biophysical data--in this case hydrogen-deuterium exchange mass spectrometry (HDX-MS, which measures the solvent exposure of protein residues)--with all-atom explicit solvent molecular dynamics (MD) simulations aided by enhanced sampling techniques to predict structural ensembles of ternary complexes at atomic resolution. We present results demonstrating the efficiency, accuracy, and reliability of our approach to predict ternary structure ensembles using the bromodomain of SMARCA2 (SMARCA2BD) with the E3 ligase VHL as the system of interest. The simulations reproduce X-ray crystal structures - including prospective simulations validated on a new structure that we determined in this work (PDB ID: 7S4E) - with root mean square deviations (RMSD) of 1.1 to 1.6 [A]. The simulations also reveal a structural ensemble of low-energy conformations of the ternary complex within a broad energy basin. To further characterize the structural ensemble, we used snapshots from the aforementioned simulations as seeds for Hamiltonian replica exchange molecular dynamics (HREMD) simulations, and then perform 7.1 milliseconds of aggregate simulation time using Folding@home. The resulting free energy surface identifies the crystal structure conformation within a broad low-energy basin and the dynamic ensemble is consistent with solution-phase biophysical experimental data (HDX-MS and small-angle x-ray scattering, SAXS). Finally, we graft structures from the ternary complexes onto the full CRL and perform enhanced sampling simulations, where we find that differences in degradation efficiency can be explained by the proximity distribution of lysine residues on the POI relative to the E2-loaded ubiquitin. Several of the top predicted ubiquitinated lysine residues are validated prospectively through a ubiquitin mapping proteomics experiment.

biophysics↗