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.

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.

Cholesterol occupies the lipid translocation pathway to block phospholipid scrambling by a G protein-coupled receptor.

Class A (rhodopsin-like) G protein-coupled receptors (GPCRs) are constitutive phospholipid scramblases as evinced after their reconstitution into liposomes. Yet phospholipid scrambling is not detectable in the resting plasma membrane of mammalian cells that is replete with GPCRs. We considered whether cholesterol, a prominent component of the plasma membrane, limits the ability of GPCRs to scramble lipids.

A highly accurate metadynamics-based Dissociation Free Energy method to calculate protein-protein and protein-ligand binding potencies.

Although seeking to develop a general and accurate binding free energy calculation method for protein-protein and protein-ligand interactions has been a continuous effort for decades, only limited successes have been obtained so far. Here, we report the development of a metadynamics-based procedure that calculates Dissociation Free Energy (DFE) and its application to 19 non-congeneric protein-protein complexes and hundreds of protein-ligand complexes covering eight targets. We achieved very high correlations in comparison to experimental binding free energies for these diverse sets of systems, demonstrating the generality and accuracy of the method.

Use of paramagnetic F NMR to monitor domain movement in a glutamate transporter homolog.

In proteins where conformational changes are functionally important, the number of accessible states and their dynamics are often difficult to establish. Here we describe a novel F-NMR spectroscopy approach to probe dynamics of large membrane proteins. We labeled a glutamate transporter homolog with a F probe via cysteine chemistry and with a Ni ion via chelation by a di-histidine motif.

Reconciling Simulated Ensembles of Apomyoglobin with Experimental Hydrogen/Deuterium Exchange Data Using Bayesian Inference and Multiensemble Markov State Models.

Hydrogen/deuterium exchange (HDX) is a powerful technique to investigate protein conformational dynamics at amino acid resolution. Because HDX provides a measurement of solvent exposure of backbone hydrogens, ensemble-averaged over potentially slow kinetic processes, it has been challenging to use HDX protection factors to refine structural ensembles obtained from molecular dynamics simulations. This entails dual challenges: (1) identifying structural observables that best correlate with backbone amide protection from exchange and (2) restraining these observables in molecular simulations to model ensembles consistent with experimental measurements.

A Graphic Encoding Method for Quantitative Classification of Protein Structure and Representation of Conformational Changes.

In order to successfully predict a proteins function throughout its trajectory, in addition to uncovering changes in its conformational state, it is necessary to employ techniques that maintain its 3D information while performing at scale. We extend a protein representation that encodes secondary and tertiary structure into fix-sized, color images, and a neural network architecture (called GEM-net) that leverages our encoded representation. We show the applicability of our method in two ways: (1) performing protein function prediction, hitting accuracy between 78 and 83 percent, and (2) visualizing and detecting conformational changes in protein trajectories during molecular dynamics simulations.

How structural elements evolving from bacterial to human SLC6 transporters enabled new functional properties.

Background: Much of the structure-based mechanistic understandings of the function of SLC6A neurotransmitter transporters emerged from the study of their bacterial LeuT-fold homologs. It has become evident, however, that structural differences such as the long N- and C-termini of the eukaryotic neurotransmitter transporters are involved in an expanded set of functional properties to the eukaryotic transporters. These functional properties are not shared by the bacterial homologs, which lack the structural elements that appeared later in evolution.

Mechanisms of Lipid Scrambling by the G Protein-Coupled Receptor Opsin.

Several class-A G protein-coupled receptor (GPCR) proteins act as constitutive phospholipid scramblases catalyzing the transbilayer translocation of >10,000 phospholipids per second when reconstituted into synthetic vesicles. To address the molecular mechanism by which these proteins facilitate rapid lipid scrambling, we carried out large-scale ensemble atomistic molecular dynamics simulations of the opsin GPCR. We report that, in the process of scrambling, lipid head groups traverse a dynamically revealed hydrophilic pathway in the region between transmembrane helices 6 and 7 of the protein while their hydrophobic tails remain in the bilayer environment.

Thermodynamic Coupling Function Analysis of Allosteric Mechanisms in the Human Dopamine Transporter.

Allostery plays a crucial role in the mechanism of neurotransmitter-sodium symporters, such as the human dopamine transporter. To investigate the molecular mechanism that couples the transport-associated inward release of the Na ion from the Na2 site to intracellular gating, we applied a combination of the thermodynamic coupling function (TCF) formalism and Markov state model analysis to a 50-μs data set of molecular dynamics trajectories of the human dopamine transporter, in which multiple spontaneous Na release events were observed. Our TCF approach reveals a complex landscape of thermodynamic coupling between Na release and inward-opening, and identifies diverse, yet well-defined roles for different Na-coordinating residues.

Molecular simulations and free-energy calculations suggest conformation-dependent anion binding to a cytoplasmic site as a mechanism for Na/K-ATPase ion selectivity.

Na/K-ATPase transports Na and K ions across the cell membrane via an ion-binding site becoming alternatively accessible to the intra- and extracellular milieu by conformational transitions that confer marked changes in ion-binding stoichiometry and selectivity. To probe the mechanism of these changes, we used molecular simulation and free-energy perturbation approaches to identify probable protonation states of Na- and K-coordinating residues in E1P and E2P conformations of Na/K-ATPase. Analysis of these simulations revealed a molecular mechanism responsible for the change in protonation state: the conformation-dependent binding of an anion (a chloride ion in our simulations) to a previously unrecognized cytoplasmic site in the loop between transmembrane helices 8 and 9, which influences the electrostatic potential of the crucial Na-coordinating residue Asp This mechanistic model is consistent with experimental observations and provides a molecular-level picture of how E1P to E2P enzyme conformational transitions are coupled to changes in ion-binding stoichiometry and selectivity.

A Markov State-based Quantitative Kinetic Model of Sodium Release from the Dopamine Transporter.

The dopamine transporter (DAT) belongs to the neurotransmitter:sodium symporter (NSS) family of membrane proteins that are responsible for reuptake of neurotransmitters from the synaptic cleft to terminate a neuronal signal and enable subsequent neurotransmitter release from the presynaptic neuron. The release of one sodium ion from the crystallographically determined sodium binding site Na2 had been identified as an initial step in the transport cycle which prepares the transporter for substrate translocation by stabilizing an inward-open conformation. We have constructed Markov State Models (MSMs) from extensive molecular dynamics simulations of human DAT (hDAT) to explore the mechanism of this sodium release.

Surprisal Metrics for Quantifying Perturbed Conformational Dynamics in Markov State Models.

Markov state models (MSMs), which model conformational dynamics as a network of transitions between metastable states, have been increasingly used to model the thermodynamics and kinetics of biomolecules. In considering perturbations to molecular dynamics induced by sequence mutations, chemical modifications, or changes in external conditions, it is important to assess how transition rates change, independent of changes in metastable state definitions. Here, we present a surprisal metric to quantify the difference in metastable state transitions for two closely related MSMs, taking into account the statistical uncertainty in observed transition counts.

Kinetic network models of tryptophan mutations in β-hairpins reveal the importance of non-native interactions.

We present an analysis of the most extensive explicit-solvent simulations of β-hairpins to date (9.4 ms in aggregate), with the aim of probing the effects of tryptophan mutations on folding. From molecular simulations of GB1 hairpin, trpzip4, trpzip5, and trpzip6 performed on Folding@home, Markov State Models (MSMs) were constructed using a unified set of metastable states, enabling objective comparison of folding mechanisms.

Computational screening and selection of cyclic peptide hairpin mimetics by molecular simulation and kinetic network models.

Designing peptidomimetic compounds to have a preorganized structure in solution is highly nontrivial. To show how simulation-based approaches can help speed this process, we performed an extensive simulation study of designed cyclic peptide mimics of a β-hairpin from bacterial protein LapD involved in a protein-protein interaction (PPI) pertinent to bacterial biofilm formation. We used replica exchange molecular dynamics (REMD) simulation to screen 20 covalently cross-linked designs with varying stereochemistry and selected the most favorable of these for massively parallel simulation on Folding@home in explicit solvent.