Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods.

The therapeutic approach of targeted protein degradation (TPD) is gaining momentum due to its potentially superior effects compared with protein inhibition. Recent advancements in the biotech and pharmaceutical sectors have led to the development of compounds that are currently in human trials, with some showing promising clinical results. However, the use of computational tools in TPD is still limited, as it has distinct characteristics compared with traditional computational drug design methods. TPD involves creating a ternary structure (protein-degrader-ligase) responsible for the biological function, such as ubiquitination and subsequent proteasomal degradation, which depends on the spatial orientation of the protein of interest (POI) relative to E2-loaded ubiquitin. Modeling this structure necessitates a unique blend of tools initially developed for small molecules (e.g., docking) and biologics (e.g., protein-protein interaction modeling). Additionally, degrader molecules, particularly heterobifunctional degraders, are generally larger than conventional small molecule drugs, leading to challenges in determining drug-like properties like solubility and permeability. Furthermore, the catalytic nature of TPD makes occupancy-based modeling insufficient. TPD consists of multiple interconnected yet distinct steps, such as POI binding, E3 ligase binding, ternary structure interactions, ubiquitination, and degradation, along with traditional small molecule properties. A comprehensive set of tools is needed to address the dynamic nature of the induced proximity ternary complex and its implications for ubiquitination. In this Perspective, we discuss the current state of computational tools for TPD. We start by describing the series of steps involved in the degradation process and the experimental methods used to characterize them. Then, we delve into a detailed analysis of the computational tools employed in TPD. We also present an integrative approach that has proven successful for degrader design and its impact on project decisions. Finally, we examine the future prospects of computational methods in TPD and the areas with the greatest potential for impact.

A Suite of Tutorials for the WESTPA 2.0 Rare-Events Sampling Software [Article v2.0].

The weighted ensemble (WE) strategy has been demonstrated to be highly efficient in generating pathways and rate constants for rare events such as protein folding and protein binding using atomistic molecular dynamics simulations. Here we present two sets of tutorials instructing users in the best practices for preparing, carrying out, and analyzing WE simulations for various applications using the WESTPA software. The first set of more basic tutorials describes a range of simulation types, from a molecular association process in explicit solvent to more complex processes such as host-guest association, peptide conformational sampling, and protein folding. The second set ecompasses six advanced tutorials instructing users in the best practices of using key new features and plugins/extensions of the WESTPA 2.0 software package, which consists of major upgrades for larger systems and/or slower processes. The advanced tutorials demonstrate the use of the following key features: (i) a generalized resampler module for the creation of "binless" schemes, (ii) a minimal adaptive binning scheme for more efficient surmounting of free energy barriers, (iii) streamlined handling of large simulation datasets using an HDF5 framework, (iv) two different schemes for more efficient rate-constant estimation, (v) a Python API for simplified analysis of WE simulations, and (vi) plugins/extensions for Markovian Weighted Ensemble Milestoning and WE rule-based modeling for systems biology models. Applications of the advanced tutorials include atomistic and non-spatial models, and consist of complex processes such as protein folding and the membrane permeability of a drug-like molecule. Users are expected to already have significant experience with running conventional molecular dynamics or systems biology simulations.

Predicting the structural basis of targeted protein degradation by integrating molecular dynamics simulations with structural mass spectrometry.

Targeted protein degradation (TPD) is a promising approach in drug discovery for degrading proteins implicated in diseases. A key step in this process is the formation of a ternary complex where a heterobifunctional molecule induces proximity of an E3 ligase to a protein of interest (POI), thus facilitating ubiquitin transfer to the POI. In this work, we characterize 3 steps in the TPD process. (1) We simulate the ternary complex formation of SMARCA2 bromodomain and VHL E3 ligase by combining hydrogen-deuterium exchange mass spectrometry with weighted ensemble molecular dynamics (MD). (2) We characterize the conformational heterogeneity of the ternary complex using Hamiltonian replica exchange simulations and small-angle X-ray scattering. (3) We assess the ubiquitination of the POI in the context of the full Cullin-RING Ligase, confirming experimental ubiquitinomics results. Differences in degradation efficiency can be explained by the proximity of lysine residues on the POI relative to ubiquitin.

Ligand-mediated Structural Dynamics of a Mammalian Pancreatic KATP Channel.

Regulation of pancreatic KATP channels involves orchestrated interactions of their subunits, Kir6.2 and SUR1, and ligands. Previously we reported KATP channel cryo-EM structures in the presence and absence of pharmacological inhibitors and ATP, focusing on the mechanisms by which inhibitors act as pharmacological chaperones of KATP channels (Martin et al., 2019). Here we analyzed the same cryo-EM datasets with a focus on channel conformational dynamics to elucidate structural correlates pertinent to ligand interactions and channel gating. We found pharmacological inhibitors and ATP enrich a channel conformation in which the Kir6.2 cytoplasmic domain is closely associated with the transmembrane domain, while depleting one where the Kir6.2 cytoplasmic domain is extended away into the cytoplasm. This conformational change remodels a network of intra- and inter-subunit interactions as well as the ATP and PIP2 binding pockets. The structures resolved key contacts between the distal N-terminus of Kir6.2 and SUR1's ABC module involving residues implicated in channel function and showed a SUR1 residue, K134, participates in PIP2 binding. Molecular dynamics simulations revealed two Kir6.2 residues, K39 and R54, that mediate both ATP and PIP2 binding, suggesting a mechanism for competitive gating by ATP and PIP2.

Continuum dynamics and statistical correction of compositional heterogeneity in multivalent IDP oligomers resolved by single-particle EM.

Multivalent intrinsically disordered protein (IDP) complexes are prevalent in biology and act in regulation of diverse processes, including transcription, signaling events, and the assembly and disassembly of complex macromolecular architectures. These systems pose significant challenges to structural investigation, due to continuum dynamics imparted by the IDP and compositional heterogeneity resulting from characteristic low-affinity interactions. Here, we developed a modular pipeline for automated single-particle electron microscopy (EM) distribution analysis of common but relatively understudied semi-ordered systems: 'beads-on-a-string' assemblies, composed of IDPs bound at multivalent sites to the ubiquitous ∼20 kDa cross-linking hub protein LC8. This approach quantifies conformational geometries and compositional heterogeneity on a single-particle basis, and statistically corrects spurious observations arising from random proximity of bound and unbound LC8. The statistical correction is generically applicable to oligomer characterization and not specific to our pipeline. Following validation, the approach was applied to the nuclear pore IDP Nup159 and the transcription factor ASCIZ. This analysis unveiled significant compositional and conformational diversity in both systems that could not be obtained from ensemble single particle EM class-averaging strategies, and new insights for exploring how these architectural properties might contribute to their physiological roles in supramolecular assembly and transcriptional regulation. We expect that this approach may be adopted to many other intrinsically disordered systems that have evaded traditional methods of structural characterization.

Vascular KATP channel structural dynamics reveal regulatory mechanism by Mg-nucleotides.

Vascular tone is dependent on smooth muscle KATP channels comprising pore-forming Kir6.1 and regulatory SUR2B subunits, in which mutations cause Cantú syndrome. Unique among KATP isoforms, they lack spontaneous activity and require Mg-nucleotides for activation. Structural mechanisms underlying these properties are unknown. Here, we determined cryogenic electron microscopy structures of vascular KATP channels bound to inhibitory ATP and glibenclamide, which differ informatively from similarly determined pancreatic KATP channel isoform (Kir6.2/SUR1). Unlike SUR1, SUR2B subunits adopt distinct rotational "propeller" and "quatrefoil" geometries surrounding their Kir6.1 core. The glutamate/aspartate-rich linker connecting the two halves of the SUR-ABC core is observed in a quatrefoil-like conformation. Molecular dynamics simulations reveal MgADP-dependent dynamic tripartite interactions between this linker, SUR2B, and Kir6.1. The structures captured implicate a progression of intermediate states between MgADP-free inactivated, and MgADP-bound activated conformations wherein the glutamate/aspartate-rich linker participates as mobile autoinhibitory domain, suggesting a conformational pathway toward KATP channel activation.

Carotenoids promote lateral packing and condensation of lipid membranes.

Carotenoids are pigment molecules that protect biomembranes against degradation and may be involved in the formation of functional bacterial membrane microdomains. Little is known on whether different types of carotenoids have different effects on the membrane or if there is any concentration dependence of these effects. In this work, we present results from molecular dynamics simulations of phospholipid bilayers containing different amounts of either ß-carotene or zeaxanthin. Both ß-carotene and zeaxanthin show the ability to laterally condense the membrane lipids and reduce their inter-leaflet interactions. With increasing concentrations, both carotenoids increase the bilayer thickness and rigidity. The results reveal that carotenoids have similar effects to cholesterol on regulating the behavior of fluid-phase membranes, suggesting that they could function as sterol substitutes and confirming their potential role in the formation of functional membrane domains.

High-throughput, single-particle tracking reveals nested membrane domains that dictate KRasG12D diffusion and trafficking.

Membrane nanodomains have been implicated in Ras signaling, but what these domains are and how they interact with Ras remain obscure. Here, using single particle tracking with photoactivated localization microscopy (spt-PALM) and detailed trajectory analysis, we show that distinct membrane domains dictate KRasG12D (an active KRas mutant) diffusion and trafficking in U2OS cells. KRasG12D exhibits an immobile state in ~70 nm domains, each embedded in a larger domain (~200 nm) that confers intermediate mobility, while the rest of the membrane supports fast diffusion. Moreover, KRasG12D is continuously removed from the membrane via the immobile state and replenished to the fast state, reminiscent of Ras internalization and recycling. Importantly, both the diffusion and trafficking properties of KRasG12D remain invariant over a broad range of protein expression levels. Our results reveal how membrane organization dictates membrane diffusion and trafficking of Ras and offer new insight into the spatial regulation of Ras signaling.

The Ras family of proteins play an important role in relaying signals from the outside to the inside of the cell. Ras proteins are attached by a fatty tail to the inner surface of the cell membrane. When activated they transmit a burst of signal that controls critical behaviors like growth, survival and movement. It has been suggested that to prevent these signals from being accidently activated, Ras molecules must group together at specialized sites within the membrane before passing on their message. However, visualizing how Ras molecules cluster together at these domains has thus far been challenging. As a result, little is known about where these sites are located and how Ras molecules come to a stop at these domains. Now, Lee et al. have combined two microscopy techniques called 'single-particle tracking' and 'photoactivated localization microscopy' to track how individual molecules of activated Ras move in human cells grown in the lab. This revealed that Ras molecules quickly diffuse along the inside of the membrane until they arrive at certain locations that cause them to halt. However, computer models consisting of just the 'fast' and 'immobile' state could not correctly re-capture the way Ras molecules moved along the membrane. Lee et al. found that for these models to mimic the movement of Ras, a third 'intermediate' state of Ras mobility needed to be included. To investigate this further, Lee et al. created a fluorescent map that overlaid all the individual paths taken by each Ras molecule. The map showed regions in the membrane where the Ras molecules had stopped and possibly clustered together. Each of these 'immobilization domains' were then surrounded by an 'intermediate domain' where Ras molecules had begun to slow down their movement. Although the intermediate domains did not last long, they seemed to guide Ras molecules into the immobilization domains where they could cluster together with other molecules. From there, the cell constantly removed Ras molecules from these membrane domains and returned them back to their 'fast' diffusing state. Mutations in Ras proteins occur in around a third of all cancers, so a better understanding of their dynamics could help with future drug discovery. The methods used here could also be used to investigate the movement of other signaling molecules.

A Multifunctional Cosolvent Pair Reveals Molecular Principles of Biomass Deconstruction.

The complex structure of plant cell walls resists chemical or biological degradation, challenging the breakdown of lignocellulosic biomass into renewable chemical precursors that could form the basis of future production of green chemicals and transportation fuels. Here, experimental and computational results reveal that the effect of the tetrahydrofuran (THF)-water cosolvents on the structure of lignin and on its interactions with cellulose in the cell wall drives multiple synergistic mechanisms leading to the efficient breakdown and fractionation of biomass into valuable chemical precursors. Molecular simulations show that THF-water is an excellent "theta" solvent, such that lignin dissociates from itself and from cellulose and expands to form a random coil. The expansion of the lignin molecules exposes interunit linkages, rendering them more susceptible to depolymerization by acid-catalyzed cleavage of aryl-ether bonds. Nanoscale infrared sensors confirm cosolvent-mediated molecular rearrangement of lignin in the cell wall of micrometer-thick hardwood slices and track the disappearance of lignin. At bulk scale, adding dilute acid to the cosolvent mixture liberates the majority of the hemicellulose and lignin from biomass, allowing unfettered access of cellulolytic enzymes to the remaining cellulose-rich material, allowing them to sustain high rates of hydrolysis to glucose without enzyme deactivation. Through this multiscale analysis, synergistic mechanisms for biomass deconstruction are identified, portending a paradigm shift toward first-principles design and evaluation of other cosolvent methods to realize low cost fuels and bioproducts.

Branched-Chain Fatty Acid Content Modulates Structure, Fluidity, and Phase in Model Microbial Cell Membranes.

Recent progress in understanding the importance and origins of lipid rafts in microbial cell membranes has focused attention on membranes containing branched-chain fatty acids. The working hypothesis is that branched fatty acids increase the fluidity of the bilayer, analogous to unsaturated fatty acids in membranes of higher organisms. Here, we perform a series of 7 µs long atomistic simulations on biomimetic, branched-chain lipid containing bilayer patches, systematically varying the amount of the straight-chain fatty acid component, n16:0, from 7.0 to 47.3 mol %. The simulations reveal thickening and ordering of the bilayer as well as higher bilayer viscosity and bending modulus with increasing n16:0 content, thus providing quantitative support that branched fatty acids increase the bilayer fluidity. A sharp transition in these properties is observed at ∼20% n16:0 content, resembling a phase change. The simulations provide the first access to ordered and disordered phases in a bacterial cell membrane mimic containing branched-chain lipids. Granted several assumptions, a comparison of these phases provides estimates of physical properties such as hydrophobic mismatch (∼1.2 Å), difference in bending moduli (∼15.7 kBT), and the line tension (∼0.6 pN) for a putative lipid raft in the cell membrane of an organism such as Bacillus subtilis or Staphylococcus aureus.

Statistical Uncertainty Analysis for Small-Sample, High Log-Variance Data: Cautions for Bootstrapping and Bayesian Bootstrapping.

Recent advances in molecular simulations allow the evaluation of previously unattainable observables, such as rate constants for protein folding. However, these calculations are usually computationally expensive, and even significant computing resources may result in a small number of independent estimates spread over many orders of magnitude. Such small-sample, high "log-variance" data are not readily amenable to analysis using the standard uncertainty (i.e., "standard error of the mean") because unphysical negative limits of confidence intervals result. Bootstrapping, a natural alternative guaranteed to yield a confidence interval within the minimum and maximum values, also exhibits a striking systematic bias of the lower confidence limit in log space. As we show, bootstrapping artifactually assigns high probability to improbably low mean values. A second alternative, the Bayesian bootstrap strategy, does not suffer from the same deficit and is more logically consistent with the type of confidence interval desired. The Bayesian bootstrap provides uncertainty intervals that are more reliable than those from the standard bootstrap method but must be used with caution nevertheless. Neither standard nor Bayesian bootstrapping can overcome the intrinsic challenge of underestimating the mean from small-size, high log-variance samples. Our conclusions are based on extensive analysis of model distributions and reanalysis of multiple independent atomistic simulations. Although we only analyze rate constants, similar considerations will apply to related calculations, potentially including highly nonlinear averages like the Jarzynski relation.

Computational Estimation of Microsecond to Second Atomistic Folding Times.

Despite the development of massively parallel computing hardware including inexpensive graphics processing units (GPUs), it has remained infeasible to simulate the folding of atomistic proteins at room temperature using conventional molecular dynamics (MD) beyond the microsecond scale. Here, we report the folding of atomistic, implicitly solvated protein systems with folding times τ ranging from ∼10 µs to ∼100 ms using the weighted ensemble (WE) strategy in combination with GPU computing. Starting from an initial structure or set of structures, WE organizes an ensemble of GPU-accelerated MD trajectory segments via intermittent pruning and replication events to generate statistically unbiased estimates of rate constants for rare events such as folding; no biasing forces are used. Although the variance among atomistic WE folding runs is significant, multiple independent runs are used to reduce and quantify statistical uncertainty. Folding times are estimated directly from WE probability flux and from history-augmented Markov analysis of the WE data. Three systems were examined: NTL9 at low solvent viscosity (yielding τf = 0.8-9 µs), NTL9 at water-like viscosity (τf = 0.2-2 ms), and Protein G at low viscosity (τf = 3-200 ms). In all cases, the folding time, uncertainty, and ensemble properties could be estimated from WE simulation; for Protein G, this characterization required significantly less overall computing than would be required to observe a single folding event with conventional MD simulations. Our results suggest that the use and calibration of force fields and solvent models for precise estimation of kinetic quantities is becoming feasible.

A Suite of Tutorials for the WESTPA Rare-Events Sampling Software [Article v1.0].

The weighted ensemble (WE) strategy has been demonstrated to be highly efficient in generating pathways and rate constants for rare events such as protein folding and protein binding using atomistic molecular dynamics simulations. Here we present five tutorials instructing users in the best practices for preparing, carrying out, and analyzing WE simulations for various applications using the WESTPA software. Users are expected to already have significant experience with running standard molecular dynamics simulations using the underlying dynamics engine of interest (e.g. Amber, Gromacs, OpenMM). The tutorials range from a molecular association process in explicit solvent to more complex processes such as host-guest association, peptide conformational sampling, and protein folding.

Supramolecular self assembly of nanodrill-like structures for intracellular delivery.

Despite recent advances in the supramolecular assembly of cell-penetrating peptide (CPP) nanostructures, the tuning of size, shape, morphology and packaging of drugs in these materials still remain unexplored. Herein, through sequential ligation of peptide building blocks, we create cell-penetrating self-assembling peptide nanomaterials (CSPNs) with the capability to translocate inside cells. We devised a triblock array of Tat48-59 [HIV-1 derived transactivator of transcription48-59] based CPPs, conjugated to up to four Phenylalanine (Phe) residues through an amphiphilic linker, (RADA)2. We observed that the sequential addition of Phe leads to the transition of CSPN secondary structures from a random coil, to a distorted α-helix, a ß-sheet, or a pure α-helix. This transition occurs due to formation of a heptad by virtue of even number of Phe. Atomic force microscopy revealed that CSPNs form distinct shapes reminiscent of a "drill-bit". CSPNs containing two, three or four Phe, self-assemble into "nanodrill-like structures" with a coarse-twisted, non-twisted or fine-twisted morphology, respectively. These nanodrills had a high capacity to encapsulate hydrophobic guest molecules. In particular, the coarse-twisted nanodrills demonstrate higher internalization and are able to deliver rapamycin, a hydrophobic small molecule that induced autophagy and are capable of in vivo delivery. Molecular dynamics studies provide microscopic insights into the structure of the nanodrills that can contribute to its morphology and ability to interact with cellular membrane. CSPNs represent a new modular drug delivery platform that can be programmed into exquisite structures through sequence-specific fine tuning of amino acids.

Effects of carotenoids on lipid bilayers.

Carotenoids have been found to be important in improving the integrity of biomembranes in eukaryotes. However, the molecular details of how carotenoids modulate the physical properties of biomembranes are unknown. To this end, we have conducted a series of molecular dynamics simulations of different biologically-relevant membranes in the presence of carotenoids. The carotenoid effect on the membrane was found to be specific to the identity of the carotenoid and the composition of the membrane itself. Therefore, different classes of carotenoids produce a different effect on the membrane, and different membrane phases are affected differently by carotenoids. It is apparent from our data that carotenoids do trigger the bilayer to become thinner. The mechanism by which this occurs depends on two competing factors, the ability of the lipid tails of opposing monolayers to either (1) compress or (2) interdigitate as the bilayer condenses. Indeed, carotenoids directly influence the physical properties via these two mechanisms, thus compacting the bilayer. However, the degree to which these competing mechanisms are utilized depends on the bilayer phase and the carotenoid identity.

Organosolv-Water Cosolvent Phase Separation on Cellulose and its Influence on the Physical Deconstruction of Cellulose: A Molecular Dynamics Analysis.

Deconstruction of cellulose is crucial for the chemical conversion of lignocellulose into fuel/bioproduct precursors. Recently, a water-organosolv cosolvent system (THF-water) has been shown to both phase-separate on cellulose surfaces and partially deconstruct Avicel  (cellulose) in the absence of acid. Here we employ molecular dynamics simulations to determine whether other common water-organosolv cosolvent systems (acetone, ethanol, and γ-valerolactone) exhibit phase separation at cellulose surface and whether this alters a purely physical cellulose dissociation pathway. Despite finding varied degrees of phase-separation of organosolv on cellulose surfaces, physical dissociation is not enhanced. Interestingly, however, the total amount the median water-cellulose contact lifetimes increases for the cosolvent systems in the order of THF > acetone > ethanol > γ-valerolactone. Together our results indicate two points: a purely physical process for deconstruction of cellulose is unlikely for these cosolvents, and in THF-water, unlike γ-valerolactone- (and some concentrations of acetone and ethanol) water cosolvents, a significant fraction of surface water is slowed. This slowing may be of importance in enhancing chemical deconstruction of cellulose, as it permits an increase in potential THF-water-cellulose reactions, even while the amount of water near cellulose is decreased.

Bacillus subtilis Lipid Extract, A Branched-Chain Fatty Acid Model Membrane.

Lipid extracts are an excellent choice of model biomembrane; however at present, there are no commercially available lipid extracts or computational models that mimic microbial membranes containing the branched-chain fatty acids found in many pathogenic and industrially relevant bacteria. We advance the extract of Bacillus subtilis as a standard model for these diverse systems, providing a detailed experimental description and equilibrated atomistic bilayer model included as Supporting Information to this Letter and at ( http://cmb.ornl.gov/members/cheng ). The development and validation of this model represents an advance that enables more realistic simulations and experiments on bacterial membranes and reconstituted bacterial membrane proteins.

Structural relaxation, viscosity, and network connectivity in a hydrogen bonding liquid.

In liquids, the ability of neighboring molecules to rearrange and jostle past each other is directly related to viscosity, the property which describes the propensity to flow. The presence of hydrogen bonds (H-bonds) complicates the molecular scale picture of viscosity. H-Bonds are attractive, directional interactions between molecules which, in some cases, result in transient network structures. In this work, we use experimental and computational methods to demonstrate that the timescale of H-bond network reorganization is the dominant dynamical timescale associated with viscosity for the case of the model H-bonding liquid n-methylacetamide (NMA). This molecule is a peptide analog which forms a transient linear H-bond network. Individual H-bond lifetimes and dynamical fluctuations were observed on the timescale of 1.5 ps, while collective motions and the longest lived population of H-bond partner lifetimes were observed on the order of 20 ps, in agreement with the Maxwell relaxation time. This identifies a mechanism which may aid in understanding the emergence of various complex phenomena arising from transient molecular structures, with implications ranging from the internal dynamics of proteins, to the glass transition, to better understanding the origins of the unique properties of H-bonding liquids.

Local Phase Separation of Co-solvents Enhances Pretreatment of Biomass for Bioenergy Applications.

Pretreatment facilitates more complete deconstruction of plant biomass to enable more economic production of lignocellulosic biofuels and byproducts. Various co-solvent pretreatments have demonstrated advantages relative to aqueous-only methods by enhancing lignin removal to allow unfettered access to cellulose. However, there is a limited mechanistic understanding of the interactions between the co-solvents and cellulose that impedes further improvement of such pretreatment methods. Recently, tetrahydrofuran (THF) has been identified as a highly effective co-solvent for the pretreatment and fractionation of biomass. To elucidate the mechanism of the THF-water interactions with cellulose, we pair simulation and experimental data demonstrating that enhanced solubilization of cellulose can be achieved by the THF-water co-solvent system at equivolume mixtures and moderate temperatures (≤445 K). The simulations show that THF and water spontaneously phase separate on the local surface of a cellulose fiber, owing to hydrogen bonding of water molecules with the hydrophilic cellulose faces and stacking of THF molecules on the hydrophobic faces. Furthermore, a single fully solvated cellulose chain is shown to be preferentially bound by water molecules in the THF-water mixture. In light of these findings, co-solvent reactions were performed on microcrystalline cellulose and maple wood to show that THF significantly enhanced cellulose deconstruction and lignocellulose solubilization at simulation conditions, enabling a highly versatile and efficient biomass pretreatment and fractionation method.