Positioning of proteins in membranes: a computational approach

Explainable Machine Learning for ETR and Drug Chameleonicity

Explainable machine learning that identifies molecular "hot spots" for chameleonicity can guide rapid chemical design for oral absorption of beyond-rule-of-five (bRo5) drugs. Traditional in silico methods rely on computationally intensive 3D physics-based modeling or classical descriptors that do not fully explain bRo5 drug behavior. To address this, we introduced the EPSA-to-TPSA ratio (ETR) as a high-throughput measure of polarity reduction, generating data for thousands of macrocycles, PROTACs, and other bRo5s. Using this data set, we developed an explainable deep learning model to predict EPSA and locate polarity-reducing "hot spots" that influence chameleonicity. This first-of-its-kind interpretable model in the bRo5 3D domain guides chemical modifications before synthesis, helping chemists optimize physicochemical properties and design complex bRo5 drugs with improved oral bioavailability. Model insights validated by molecular dynamics enable robust, high-throughput predictions of bRo5 chameleonic behavior, building on Lipinski descriptors to establish new frameworks for complex drug design.

X-Ray Crystal and Cryo-Electron Microscopy Structure Analysis Unravels How the Unique Thylakoid Lipid Composition Is Utilized by Cytochrome b6f for Driving Reversible Proteins' Reorganization During State Transitions

The rapid regulatory mechanism of light-induced state transitions (STs) in oxygenic photosynthesis is particularly appealing for membrane-based applications. This interest stems from the unique ability of the thylakoid membrane protein cytochrome b6f (cytb6f) to increase or decrease its hydrophobic thickness (dP) in parallel with the reduction or oxidation of the PQ pool induced by changes in light quality. This property appears to be the long-sought biophysical driver behind the reorganizations of membrane proteins during STs. This study decisively advances the hydrophobic mismatch (HMM) model for cytb6f-driven STs by thoroughly analyzing thirteen X-ray crystal and eight cryo-electron microscopy cytb6f structures. It uncovers the lipid nanoenvironments that cytb6f, with different hydrophobic thicknesses, selectively attracts. Under optimal, stationary conditions for photosynthesis in low light, when there is hydrophobic matching between the hydrophobic thicknesses of cytb6f dP and that of the bulk thylakoid lipid phase dL, dP = dL, cytb6f predominantly binds to anionic lipids-several phosphatidylglycerol (PG) molecules and one sulfoquinovosyldiacylglycerol (SQDG) molecule. Upon the induction of the transition to State 2, when dP increases and induces a positive HMM (dP > dL), the neutral, non-bilayer-forming lipid monogalactosyldiacylglycerol (MGDG) replaces some of the bound PGs. Upon the induction of the transition to State 1, when dP decreases and induces a negative HMM (dP < dL), PGs and SQDG detach from their binding sites, and two neutral, bilayer-forming lipids such as digalactosyldiacylglycerol (DGDG) occupy two sites. Additionally, this research uncovers two lipid-mediated signaling pathways from Chla to the center of flexibility, the Phe/Tyr124fg-loop-suIV residue-one of which involves β-carotene. This study identifies two novel types of lipid raft-like nanodomains that are devoid of typical components, such as sphingomyelin and cholesterol. These findings firmly validate the HMM model and underscore the STs as the first recognized functional process that fully utilizes the unique and evolutionarily conserved composition of just four thylakoid lipid classes. This research contributes to our understanding of membrane dynamics in general and STs in particular. It introduces a novel and simple approach for reversible protein reorganization driven purely by biophysical mechanisms, with promising implications for various membrane-based applications.

Meta-Analysis of Permeability Literature Data Shows Possibilities and Limitations of Popular Methods

Permeability is an important molecular property in drug discovery, as it co-determines pharmacokinetics whenever a drug crosses the phospholipid bilayer, e.g., into the cell, in the gastrointestinal tract, or across the blood-brain barrier. Many methods for the determination of permeability have been developed, including cell line assays (CACO-2 and MDCK), cell-free model systems like parallel artificial membrane permeability assay (PAMPA) mimicking, e.g., gastrointestinal epithelia or the skin, as well as the black lipid membrane (BLM) and submicrometer liposomes. Furthermore, many in silico approaches have been developed for permeability prediction: meta-analysis of publicly available databases for permeability data (MolMeDB and ChEMBL) was performed to establish their usability. Four experimental and two computational methods were evaluated. It was shown that repeatability of the reported permeability measurement is not great even for the same method. For the PAMPA method, two different permeabilities are reported: intrinsic and apparent. They can vary in degrees of magnitude; thus, we suggest being extra cautious using literature data on permeability. When we compared data for the same molecules using different methods, the best agreement was between cell-based methods and between BLM and computational methods. Existence of unstirred water layer (UWL) permeability limits the data agreement between cell-based methods (and apparent PAMPA) with data that are not limited by UWL permeability (computational methods, BLM, intrinsic PAMPA). Therefore, different methods have different limitations. Cell-based methods provide results only in a small range of permeabilities (-8 to -4 in cm/s), and computational methods can predict a wider range of permeabilities beyond physical limitations, but their precision is therefore limited. BLM with liposomes can be used for both fast and slow permeating molecules, but its usage is more complicated than standard transwell techniques. To sum up, when working with in-house measured or published permeability data, we recommend caution in interpreting and combining them.

Flexibility-Induced Collective Behavior Drives Symmetry Breaking in Discrimination of Undesired Ions

Structure flexibility is essential for the biological function of proteins. At the same time, many proteins need to discriminate ligands with subtle differences, with one example being ion selectivity. Investigating the mechanisms by which flexible proteins achieve such precise discrimination is crucial for advancing our understanding of their functions. In this work, we study transporter KCC4, which undergoes continuous conformation changes during ion transport and can realize K+ over Na+ selectivity. Our findings reveal that the center of the binding site no longer represents a stable equilibrium for the undesired Na+, and its binding mode exhibits bifurcation. Interestingly, protein conformation fluctuation can induce collective behavior throughout the entire binding region, which contributes to this bifurcation. Thus, the symmetry of the binding mode decreases from the inherent T d symmetry to a C2v symmetry, and the binding stability of Na+ is largely reduced. A similar phenomenon is observed in a GPCR, β2-AR, where a less favored ligand forms a biased binding mode with reduced stability. The mechanism underlying the selectivity in such flexible regions could be interpreted as spontaneous symmetry breaking, which may represent a general mechanism by which flexible proteins achieve efficient ligand discrimination.

Computational Analysis of the Fully Activated Orexin Receptor 2 across Various Thermodynamic Ensembles with Surface Tension Monitoring and Markov State Modeling

In this study, we investigated the stability of the fully activated conformation of the orexin receptor 2 (OX2R) embedded in a pure POPC bilayer using MD simulations. Various thermodynamic ensembles (i.e., NPT, NVT, NVE, NPAT, μVT, and NPγT) were employed to explore the dynamical heterogeneity of the system in a comprehensive way. In addition, informational similarity metrics (e.g., Jensen-Shannon divergence) as well as Markov state modeling approaches were utilized to elucidate the receptor kinetics. Special attention was paid to assessing surface tension within the simulation box, particularly under NPγT conditions, where 21 nominal surface tension constants were evaluated. Our findings suggest that traditional thermodynamic ensembles such as NPT may not adequately control physical properties of the POPC membrane, impacting the plausibility of the OX2R model. In general, the performed study underscores the importance of employing the NPγT ensemble for computational investigations of membrane-embedded receptors, as it effectively maintains zero surface tension in the simulated system. These results offer valuable insights for future research aimed at understanding receptor dynamics and designing targeted therapeutics.

OPRLM: A Web Tool and a Database for Positioning and Simulations of Proteins in Realistic Lipid Membranes

Molecular dynamics (MD) simulations in explicit lipid bilayers enable modeling of protein-lipid interactions essential for membrane protein functions and regulation. The newly developed computational web tool, OPRLM (Orientations of Proteins in Realistic Lipid Membranes), automates the assembly of membrane protein structures with explicit lipids corresponding to 18 biological membrane types with symmetric or asymmetric lipid distributions, as well as 5 types of two-component lipid bilayers with varying cholesterol content. Built upon the CHARMM-GUI toolset and the PPM method, OPRLM simplifies the setup of complex simulation system involving integral and/or peripheral membrane proteins with explicit lipid mixtures and generates all necessary files for subsequent all-atom MD simulations. OPRLM has successfully generated protein-membrane systems for 286 tested protein structures in various biomembranes, including 138 structures containing ligands. The OPRLM database, an advanced successor of the OPM database, includes explicit protein-lipid systems for tested proteins in their native biomembranes. It provides coordinates of integral and peripheral membrane proteins from the Protein Data Bank embedded in planar or curved implicit lipid bilayers. Additionally, it includes the classification of proteins into types, superfamilies, and families, along with the information on intracellular localizations and membrane topology and visualization options. The OPRLM web tool and the database are publicly accessible at https://oprlm.org.

Activation of the Influenza B M2 Proton Channel (BM2)

Influenza B viruses have cocirculated during most seasonal flu epidemics and can cause significant human morbidity and mortality due to their rapid mutation, emerging drug resistance, and severe impact on vulnerable populations. The influenza B M2 proton channel (BM2) plays an essential role in viral replication, but the mechanisms behind its symmetric proton conductance and the involvement of a second histidine (His27) cluster remain unclear. Here we performed membrane-enabled continuous constant-pH molecular dynamics simulations on wildtype BM2 and a key H27A mutant channel to explore its pH-dependent conformational switch. Simulations captured the activation as the first histidine (His19) protonates and revealed the transition at lower pH values compared to AM2 is a result of electrostatic repulsions between His19 and preprotonated His27. Crucially, we provided an atomic-level understanding of the symmetric proton conduction by identifying preactivating channel hydration in the C-terminal portion. This research advances our understanding of the function of BM2 function and lays the groundwork for further chemically reactive modeling of the explicit proton transport process as well as possible antiflu drug design efforts.

Identification of interaction partners of outer inflammatory protein A: Computational and experimental insights into how Helicobacter pylori infects host cells

Outer membrane proteins (OMPs) play a key role in facilitating the survival of Helicobacter pylori within the gastric tissue by mediating adherence. Among these proteins, Outer inflammatory protein A (OipA) is a critical factor in H. pylori colonization of the host gastric epithelial cell surface. While the role of OipA in H. pylori attachment and its association with clinical outcomes have been established, the structural mechanisms underlying OipA's action in adherence to gastric epithelial cells remain limited. Our study employed experimental and computational approaches to investigate the interaction partners of OipA on the gastric epithelial cell surface. Initially, we conducted a proteomic analysis using a pull-down assay with recombinant OipA and gastric epithelial cell membrane proteins to identify the OipA interactome. This analysis revealed 704 unique proteins that interacted with OipA. We subsequently analyzed 16 of these OipA partners using molecular modeling tools. Among these 16 partners, we highlight three human proteins, namely Hepatocyte growth factor (HGF), Mesenchymal epithelial transition factor receptor (Met), and Adhesion G Protein-Coupled Receptor B1 (AGRB1) that could play a role in H. pylori adherence to the gastric epithelial cell surface with OipA. Collectively, these findings reveal novel host interactions mediated by OipA, suggesting their potential as therapeutic targets for combating H. pylori infection.

Plant protein-lipid interfaces studied by molecular dynamics simulations

The delineation of protein-lipid interfaces is essential for understanding the mechanisms of various membrane-associated processes crucial to plant development and growth, including signalling, trafficking, and membrane transport. Due to their highly dynamic nature, the precise characterization of lipid-protein interactions by experimental techniques is challenging. Molecular dynamics simulations provide a powerful computational alternative with a spatial-temporal resolution allowing the atomistic-level description. In this review, we aim to introduce plant scientists to molecular dynamics simulations. We describe different steps of performing molecular dynamics simulations and provide a broad survey of molecular dynamics studies investigating plant protein-lipid interfaces. Our aim is also to illustrate that combining molecular dynamics simulations with artificial intelligence-based protein structure determination opens up unprecedented possibilities for future investigations of dynamic plant protein-lipid interfaces.

Activation of the influenza B M2 proton channel (BM2)

Influenza B viruses have co-circulated during most seasonal flu epidemics and can cause significant human morbidity and mortality due to their rapid mutation, emerging drug resistance, and severe impact on vulnerable populations. The influenza B M2 proton channel (BM2) plays an essential role in viral replication, but the mechanisms behind its symmetric proton conductance and the involvement of a second histidine (His27) cluster remain unclear. Here we perform the membrane-enabled continuous constant-pH molecular dynamics simulations on wildtype BM2 and a key H27A mutant to explore its pH-dependent conformational switch. Simulations capture the activation as the first histidine (His19) protonates and reveal the transition at lower pH values compared to AM2 is a result of electrostatic repulsions between His19 and pre-protonated His27. Crucially, we provide an atomic-level understanding of the symmetric proton conduction by identifying pre-activating channel hydration in the C-terminal portion. This research advances our understanding of the function of BM2 function and lays the groundwork for further chemically reactive modeling of the explicit proton transport process as well as possible anti-flu drug design efforts.

In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy

Due to considerable global prevalence and high recurrence rate, the pursuit of effective new medication for epilepsy treatment remains an urgent and significant challenge. Drug repurposing emerges as a cost-effective and efficient strategy to combat this disorder. This study leverages the transformer-based deep learning methods coupled with molecular binding affinity calculation to develop a novel in-silico drug repurposing pipeline for epilepsy. The number of candidate inhibitors against 24 target proteins encoded by gain-of-function genes implicated in epileptogenesis ranged from zero to several hundreds. Our pipeline has repurposed the medications with most anti-epileptic drugs and nearly half psychiatric medications, highlighting the effectiveness of our pipeline. Furthermore, Lomitapide, a cholesterol-lowering drug, first emerged as particularly noteworthy, exhibiting high binding affinity for 10 targets and verified by molecular dynamics simulation and mechanism analysis. These findings provided a novel perspective on therapeutic strategies for other central nervous system disease.

The structure assessment web server: for proteins, complexes and more

The 'structure assessment' web server is a one-stop shop for interactive evaluation and benchmarking of structural models of macromolecular complexes including proteins and nucleic acids. A user-friendly web dashboard links sequence with structure information and results from a variety of state-of-the-art tools, which facilitates the visual exploration and evaluation of structure models. The dashboard integrates stereochemistry information, secondary structure information, global and local model quality assessment of the tertiary structure of comparative protein models, as well as prediction of membrane location. In addition, a benchmarking mode is available where a model can be compared to a reference structure, providing easy access to scores that have been used in recent CASP experiments and CAMEO. The structure assessment web server is available at https://swissmodel.expasy.org/assess.

Extracellular Kir2.1C122Y Mutant Upsets Kir2.1-PIP2 Bonds and Is Arrhythmogenic in Andersen-Tawil Syndrome

BACKGROUND

Andersen-Tawil syndrome type 1 is a rare heritable disease caused by mutations in the gene coding the strong inwardly rectifying K+ channel Kir2.1. The extracellular Cys (cysteine)122-to-Cys154 disulfide bond in the channel structure is crucial for proper folding but has not been associated with correct channel function at the membrane. We evaluated whether a human mutation at the Cys122-to-Cys154 disulfide bridge leads to Kir2.1 channel dysfunction and arrhythmias by reorganizing the overall Kir2.1 channel structure and destabilizing its open state.

METHODS

We identified a Kir2.1 loss-of-function mutation (c.366 A>T; p.Cys122Tyr) in an ATS1 family. To investigate its pathophysiological implications, we generated an AAV9-mediated cardiac-specific mouse model expressing the Kir2.1C122Y variant. We employed a multidisciplinary approach, integrating patch clamping and intracardiac stimulation, molecular biology techniques, molecular dynamics, and bioluminescence resonance energy transfer experiments.

RESULTS

Kir2.1C122Y mice recapitulated the ECG features of ATS1 independently of sex, including corrected QT prolongation, conduction defects, and increased arrhythmia susceptibility. Isolated Kir2.1C122Y cardiomyocytes showed significantly reduced inwardly rectifier K+ (IK1) and inward Na+ (INa) current densities independently of normal trafficking. Molecular dynamics predicted that the C122Y mutation provoked a conformational change over the 2000-ns simulation, characterized by a greater loss of hydrogen bonds between Kir2.1 and phosphatidylinositol 4,5-bisphosphate than wild type (WT). Therefore, the phosphatidylinositol 4,5-bisphosphate-binding pocket was destabilized, resulting in a lower conductance state compared with WT. Accordingly, on inside-out patch clamping, the C122Y mutation significantly blunted Kir2.1 sensitivity to increasing phosphatidylinositol 4,5-bisphosphate concentrations. In addition, the Kir2.1C122Y mutation resulted in channelosome degradation, demonstrating temporal instability of both Kir2.1 and NaV1.5 proteins.

CONCLUSIONS

The extracellular Cys122-to-Cys154 disulfide bond in the tridimensional Kir2.1 channel structure is essential for the channel function. We demonstrate that breaking disulfide bonds in the extracellular domain disrupts phosphatidylinositol 4,5-bisphosphate-dependent regulation, leading to channel dysfunction and defects in Kir2.1 energetic stability. The mutation also alters functional expression of the NaV1.5 channel and ultimately leads to conduction disturbances and life-threatening arrhythmia characteristic of Andersen-Tawil syndrome type 1.

Structure and mechanisms of transport of human Asc1/CD98hc amino acid transporter

Recent cryoEM studies elucidated details of the structural basis for the substrate selectivity and translocation of heteromeric amino acid transporters. However, Asc1/CD98hc is the only neutral heteromeric amino acid transporter that can function through facilitated diffusion, and the only one that efficiently transports glycine and D-serine, and thus has a regulatory role in the central nervous system. Here we use cryoEM, ligand-binding simulations, mutagenesis, transport assays, and molecular dynamics to define human Asc1/CD98hc determinants for substrate specificity and gain insights into the mechanisms that govern substrate translocation by exchange and facilitated diffusion. The cryoEM structure of Asc1/CD98hc is determined at 3.4-3.8 Å resolution, revealing an inward-facing semi-occluded conformation. We find that Ser 246 and Tyr 333 are essential for Asc1/CD98hc substrate selectivity and for the exchange and facilitated diffusion modes of transport. Taken together, these results reveal the structural bases for ligand binding and transport features specific to human Asc1.

EncoMPASS: An encyclopedia of membrane proteins analyzed by structure and symmetry

Protein structure determination and prediction, active site detection, and protein sequence alignment techniques all exploit information about protein structure and structural relationships. For membrane proteins, however, there is limited agreement among available online tools for highlighting and mapping such structural similarities. Moreover, no available resource provides a systematic overview of quaternary and internal symmetries, and their orientation relative to the membrane, despite the fact that these properties can provide key insights into membrane protein function and evolution. Here, we describe the Encyclopedia of Membrane Proteins Analyzed by Structure and Symmetry (EncoMPASS), a database for relating integral membrane proteins of known structure from the points of view of sequence, structure, and symmetry. EncoMPASS is accessible through a web interface, and its contents can be easily downloaded. This allows the user not only to focus on specific proteins, but also to study general properties of the structure and evolution of membrane proteins.

Viper Venom Phospholipase A2 Database: The Structural and Functional Anatomy of a Primary Toxin in Envenomation

Viper venom phospholipase A2 enzymes (vvPLA2s) and phospholipase A2-like (PLA2-like) proteins are two of the principal toxins in viper venom that are responsible for the severe myotoxic and neurotoxic effects caused by snakebite envenoming, among other pathologies. As snakebite envenoming is the deadliest neglected tropical disease, a complete understanding of these proteins' properties and their mechanisms of action is urgently needed. Therefore, we created a database comprising information on the holo-form, cofactor-bound 3D structure of 217 vvPLA2 and PLA2-like proteins in their physiologic environment, as well as 79 membrane-bound viper species from 24 genera, which we have made available to the scientific community to accelerate the development of new anti-snakebite drugs. In addition, the analysis of the sequenced, 3D structure of the database proteins reveals essential aspects of the anatomy of the proteins, their toxicity mechanisms, and the conserved binding site areas that may anchor universal interspecific inhibitors. Moreover, it pinpoints hypotheses for the molecular origin of the myotoxicity of the PLA2-like proteins. Altogether, this study provides an understanding of the diversity of these toxins and how they are conserved, and it indicates how to develop broad, interspecies, efficient small-molecule inhibitors to target the toxin's many mechanisms of action.

Automatic Rhodopsin Modeling with Multiple Protonation Microstates

Automatic Rhodopsin Modeling (ARM) is a simulation protocol providing QM/MM models of rhodopsins capable of reproducing experimental electronic absorption and emission trends. Currently, ARM is restricted to a single protonation microstate for each rhodopsin model. Herein, we incorporate an extension of the minimal electrostatic model (MEM) into the ARM protocol to account for all relevant protonation microstates at a given pH. The new ARM+MEM protocol determines the most important microstates contributing to the description of the absorption spectrum. As a test case, we have applied this methodology to simulate the pH-dependent absorption spectrum of a toy model, showing that the single-microstate picture breaks down at certain pH values. Subsequently, we applied ARM+MEM toAnabaenasensory rhodopsin, confirming an improved description of its absorption spectrum when the titration of several key residues is considered.

In silico design and cell-based evaluation of two dual anti breast cancer compounds targeting Bcl-2 and GPER

According to WHO statistics, breast cancer (BC) disease represents about 2.3 million diagnosed and 685,000 deaths globally. Regarding histological classification of BC, the Estrogen (ER) and Progesterone (PR) receptors negative-expression cancer, named Triple-Negative BC (TNBC), represents the most aggressive type of this disease, making it a challenge for drug discovery. In this context, our research group, applying a well-established Virtual Screening (VS) protocol, in addition to docking and molecular dynamics simulations studies, yielded two ligands identified as 6 and 37 which were chemically synthesized and evaluated on MCF-7 and MDA-MB-231 cancer cell lines. Strikingly, 37 assayed on MDA-MB-231 (a TNBC cell model) depicted an outstanding value of 18.66 μM much lower than 65.67 μM yielded by Gossypol Bcl-2 inhibitor whose main disadvantage is to produce multiple toxic effects. Highlighted above, enforce the premise of the computational tools to find new therapeutic options against the most aggressive forms of breast cancer, as the results herein showed.

Dynamic lipid interactions in the plasma membrane Na+,K+-ATPase

The function of ion-transporting Na+,K+-ATPases depends on the surrounding lipid environment in biological membranes. Two established lipid-interaction sites A and B within the transmembrane domain have been observed to induce protein activation and stabilization, respectively. In addition, lipid-mediated inhibition has been assigned to a site C, but with the exact location not experimentally confirmed. Also, possible effects on lipid interactions by disease mutants dwelling in the membrane-protein interface remain relatively uncharacterized. We simulated human Na+,K+-ATPase α1β1FXYD homology models in E1 and E2 states in an asymmetric, multicomponent plasma membrane to determine both wild-type and disease mutant lipid-protein interactions. The simulated wild-type lipid interactions at the established sites A and B were in agreement with experimental results thereby confirming the membrane-protein model system. The less well-characterized, proposed inhibitory site C was dominated by lipids lacking inhibitory properties. Instead, two sites hosting inhibitory lipids were identified at the extracellular side and also a cytoplasmic CHL-binding site that provide putative alternative locations of Na+,K+-ATPase inhibition. Three disease mutations, Leu302Arg, Glu840Arg and Met859Arg resided in the lipid-protein interface and caused drastic changes in the lipid interactions. The simulation results show that lipid interactions to the human Na+,K+-ATPase α1β1FXYD protein in the plasma membrane are highly state-dependent and can be disturbed by disease mutations located in the lipid interface, which can open up for new venues to understand genetic disorders.

Discovery of WLB-89462, a New Drug-like and Highly Selective σ2 Receptor Ligand with Neuroprotective Properties

The synthesis and pharmacological activity of a new series of isoxazolylpyrimidines as sigma-2 receptor (σ2R) ligands are reported. Modification of a new hit retrieved in an HTS campaign allowed the identification of the compound WLB-89462 (20c) with good σ2R affinity (Ki = 13 nM) and high selectivity vs both the σ1R (Ki = 1777 nM) and a general panel of 180 targets. It represents one of the first σ2R ligands with drug-like properties, linked to a good physicochemical and ADMET profile (good solubility, no CYP inhibition, good metabolic stability, high permeability, brain penetration, and high oral exposure in rodents). Compound 20c shows neuroprotective activity in vitro and improves short-term memory impairment induced by hippocampal injection of amyloid β peptide in rats. Together with the promising effects in the chronic models where 20c is currently being evaluated, these results pave the way toward its clinical development as a neuroprotective agent.

Atomic Models of All Major Trans-Envelope Complexes Involved in Lipid Trafficking in Escherichia Coli Constructed Using a Combination of AlphaFold2, AF2Complex, and Membrane Morphing Simulations

In Gram-negative bacteria, several trans-envelope complexes (TECs) have been identified that span the periplasmic space in order to facilitate lipid transport between the inner- and outer- membranes. While partial or near-complete structures of some of these TECs have been solved by conventional experimental techniques, most remain incomplete. Here we describe how a combination of computational approaches, constrained by experimental data, can be used to build complete atomic models for four TECs implicated in lipid transport in Escherichia coli . We use DeepMind's protein structure prediction algorithm, AlphaFold2, and a variant of it designed to predict protein complexes, AF2Complex, to predict the oligomeric states of key components of TECs and their likely interfaces with other components. After obtaining initial models of the complete TECs by superimposing predicted structures of subcomplexes, we use the membrane orientation prediction algorithm OPM to predict the likely orientations of the inner- and outer- membrane components in each TEC. Since, in all cases, the predicted membrane orientations in these initial models are tilted relative to each other, we devise a novel molecular mechanics-based strategy that we call "membrane morphing" that adjusts each TEC model until the two membranes are properly aligned with each other and separated by a distance consistent with estimates of the periplasmic width in E. coli . The study highlights the potential power of combining computational methods, operating within limits set by both experimental data and by cell physiology, for producing useable atomic structures of very large protein complexes.

The role of conformational change and key glutamic acid residues in the ClC-ec1 antiporter

The triple glutamine (Q) mutant (QQQ) structure of a Cl-/H+ antiporter from Escherichia coli (ClC-ec1) displaying a novel backbone arrangement has been used to challenge the long-held notion that Cl-/H+ antiporters do not operate through large conformational motions. The QQQ mutant substitutes the glutamine residue for an external glutamate E148, an internal glutamate E203, and a third glutamate E113 that hydrogen-bonds with E203. However, it is unknown if QQQ represents a physiologically relevant state, as well as how the protonation of the wild-type glutamates relates to the global dynamics. We herein apply continuous constant-pH molecular dynamics to investigate the H+-coupled dynamics of ClC-ec1. Although any large-scale conformational rearrangement upon acidification would be due to the accumulation of excess charge within the protein, protonation of the glutamates significantly impacts mainly the local structure and dynamics. Despite the fact that the extracellular pore enlarges at acidic pHs, an occluded ClC-ec1 within the active pH range of 3.5-7.5 requires a protonated E148 to facilitate extracellular Cl- release. E203 is also involved in the intracellular H+ transfer as an H+ acceptor. The water wire connection of E148 with the intracellular solution is regulated by the charge states of the E113/E203 dyad with coupled proton titration. However, the dynamics extracted from our simulations are not QQQ-like, indicating that the QQQ mutant does not represent the behavior of the wild-type ClC-ec1. These findings reinforce the necessity of having a protonatable residue at the E203 position in ClC-ec1 and suggest that a higher level of complexity exists for the intracellular H+ transfer in Cl-/H+ antiporters.

Structural Basis for Agonistic Activity and Selectivity toward Melatonin Receptors hMT1 and hMT2

Glaucoma, a major ocular neuropathy originating from a progressive degeneration of retinal ganglion cells, is often associated with increased intraocular pressure (IOP). Daily IOP fluctuations are physiologically influenced by the antioxidant and signaling activities of melatonin. This endogenous modulator has limited employment in treating altered IOP disorders due to its low stability and bioavailability. The search for low-toxic compounds as potential melatonin agonists with higher stability and bioavailability than melatonin itself could start only from knowing the molecular basis of melatonergic activity. Thus, using a computational approach, we studied the melatonin binding toward its natural macromolecular targets, namely melatonin receptors 1 (MT1) and 2 (MT2), both involved in IOP signaling regulation. Besides, agomelatine, a melatonin-derivative agonist and, at the same time, an atypical antidepressant, was also included in the study due to its powerful IOP-lowering effects. For both ligands, we evaluated both stability and ligand positioning inside the orthosteric site of MTs, mapping the main molecular interactions responsible for receptor activation. Affinity values in terms of free binding energy (ΔG_bind) were calculated for the selected poses of the chosen compounds after stabilization through a dynamic molecular docking protocol. The results were compared with experimental in vivo effects, showing a higher potency and more durable effect for agomelatine with respect to melatonin, which could be ascribed both to its higher affinity for hMT2 and to its additional activity as an antagonist for the serotonin receptor 5-HT2c, in agreement with the in silico results.

Human Diacylglycerol Kinase ε N-Terminal Segment Regulates the Phosphatidylinositol Cycle, Controlling the Rate but Not the Acyl Chain Composition of Its Lipid Intermediates

Diacylglycerol kinase ε (DGKε), an enzyme of the phosphatidylinositol (PI) cycle, bears a highly conserved hydrophobic N-terminal segment, which was proposed to anchor the enzyme into the membrane. However, the importance of this segment to the DGKε function remains to be determined. To address this question, it is here reported an in silico and in vitro combined research strategy. Capitalizing on the AlphaFold 2.0 predicted structure of human DGKε, it is shown that its hydrophobic N-terminal segment anchors it into the membrane via a transmembrane α-helix. Coarse-grained based elastic network model studies showed that a conformational change in the hydrophobic N-terminal segment determines the proximity between the active site of DGKε and the membrane-water interface, likely regulating its kinase activity. In vitro studies with a purified DGKε construct lacking the hydrophobic N-terminal segment (His-SUMO*-Δ⁵⁰-DGKε) corroborated the role of the N-terminus in regulating DGKε enzymatic properties. The comparison between the enzymatic properties of DGKε and His-SUMO*-Δ⁵⁰-DGKε showed that the conserved N-terminal segment markedly inhibits the enzyme activity and its sensitivity to membrane intrinsic negative curvature, while also playing a role in the modulation of the enzyme by phosphatidylserine. On the other hand, this segment did not strongly affect its diacylglycerol acyl chain specificity, the modulation of the enzyme by membrane morphological changes, or the activation by phosphatidic acid-rich lipid domains. Hence, these results suggest that the conservation of the hydrophobic N-terminal segment of DGKε throughout evolution guaranteed not only membrane anchorage but also an efficient and elegant manner to regulate the rate of the PI cycle.

Use of Solvent Mapping for Characterizing the Binding Site and for Predicting the Inhibition of the Human Ether-á-Go-Go-Related K+ Channel

Molecular dynamics was used to optimize the droperidol-hERG complex obtained from docking. To accommodate the inhibitor, residues T623, S624, V625, G648, Y652, and F656 did not move significantly during the simulation, while F627 moved significantly. Binding sites in cryo-EM structures and in structures obtained from molecular dynamics simulations were characterized using solvent mapping and Atlas ligands, which were negative images of the binding site, were generated. Atlas ligands were found to be useful for identifying human ether-á-go-go-related potassium channel (hERG) inhibitors by aligning compounds to them or by guiding the docking of compounds in the binding site. A molecular dynamics optimized structure of hERG led to improved predictions using either compound alignment to the Atlas ligand or docking. The structure was also found to be suitable to define a strategy for lowering inhibition based on the proposed binding mode of compounds in the channel.

TMbed: transmembrane proteins predicted through language model embeddings

BACKGROUND

Despite the immense importance of transmembrane proteins (TMP) for molecular biology and medicine, experimental 3D structures for TMPs remain about 4-5 times underrepresented compared to non-TMPs. Today's top methods such as AlphaFold2 accurately predict 3D structures for many TMPs, but annotating transmembrane regions remains a limiting step for proteome-wide predictions.

RESULTS

Here, we present TMbed, a novel method inputting embeddings from protein Language Models (pLMs, here ProtT5), to predict for each residue one of four classes: transmembrane helix (TMH), transmembrane strand (TMB), signal peptide, or other. TMbed completes predictions for entire proteomes within hours on a single consumer-grade desktop machine at performance levels similar or better than methods, which are using evolutionary information from multiple sequence alignments (MSAs) of protein families. On the per-protein level, TMbed correctly identified 94 ± 8% of the beta barrel TMPs (53 of 57) and 98 ± 1% of the alpha helical TMPs (557 of 571) in a non-redundant data set, at false positive rates well below 1% (erred on 30 of 5654 non-membrane proteins). On the per-segment level, TMbed correctly placed, on average, 9 of 10 transmembrane segments within five residues of the experimental observation. Our method can handle sequences of up to 4200 residues on standard graphics cards used in desktop PCs (e.g., NVIDIA GeForce RTX 3060).

CONCLUSIONS

Based on embeddings from pLMs and two novel filters (Gaussian and Viterbi), TMbed predicts alpha helical and beta barrel TMPs at least as accurately as any other method but at lower false positive rates. Given the few false positives and its outstanding speed, TMbed might be ideal to sieve through millions of 3D structures soon to be predicted, e.g., by AlphaFold2.

Polarization-Dependent Sum-Frequency Generation Spectroscopy for Ångstrom-Scale Depth Profiling of Molecules at Interfaces

The three-dimensional spatial distribution of molecules at soft matter interfaces is crucial for processes ranging from membrane biophysics to atmospheric chemistry. While several techniques can access surface composition, obtaining information on the depth distribution is challenging. We develop a noninvasive, polarization-resolved, surface-specific sum-frequency generation spectroscopy providing quantitative depth information. We demonstrate the technique on formic acid molecules at the air-water interface. With increasing molar fraction from 2.5% to 10%, the formic acid molecules shift, on average, ∼0.9  Å into the bulk. The consistency with the simulation data manifests that the technique allows for probing the Ångstrom-scale depth profile.

Predicting protein–membrane interfaces of peripheral membrane proteins using ensemble machine learning

Abnormal protein–membrane attachment is involved in deregulated cellular pathways and in disease. Therefore, the possibility to modulate protein–membrane interactions represents a new promising therapeutic strategy for peripheral membrane proteins that have been considered so far undruggable. A major obstacle in this drug design strategy is that the membrane-binding domains of peripheral membrane proteins are usually unknown. The development of fast and efficient algorithms predicting the protein–membrane interface would shed light into the accessibility of membrane–protein interfaces by drug-like molecules. Herein, we describe an ensemble machine learning methodology and algorithm for predicting membrane-penetrating amino acids. We utilize available experimental data from the literature for training 21 machine learning classifiers and meta-classifiers. Evaluation of the best ensemble classifier model accuracy yields a macro-averaged F1 score = 0.92 and a Matthews correlation coefficient = 0.84 for predicting correctly membrane-penetrating amino acids on unknown proteins of a validation set. The python code for predicting protein–membrane interfaces of peripheral membrane proteins is available at https://github.com/zoecournia/DREAMM.

The Inherent Coupling of Intrinsically Disordered Regions in the Multidomain Receptor Tyrosine Kinase KIT

RTK KIT regulates a variety of crucial cellular processes via its cytoplasmic domain (CD), which is composed of the tyrosine kinase domain, crowned by the highly flexible domains—the juxtamembrane region, kinase insertion domain, and C-tail, which are key recruitment regions for downstream signalling proteins. To prepare a structural basis for the characterization of the interactions of KIT with its signalling proteins (KIT INTERACTOME), we generated the 3D model of the full-length CD attached to the transmembrane helix. This generic model of KIT in inactive state was studied by molecular dynamics simulation under conditions mimicking the natural environment of KIT. With the accurate atomistic description of the multidomain KIT dynamics, we explained its intrinsic (intra-domain) and extrinsic (inter-domain) disorder and represented the conformational assemble of KIT through free energy landscapes. Strongly coupled movements within each domain and between distant domains of KIT prove the functional interdependence of these regions, described as allosteric regulation, a phenomenon widely observed in many proteins. We suggested that KIT, in its inactive state, encodes all properties of the active protein and its post-transduction events.

Ceramide-1-phosphate transfer protein promotes sphingolipid reorientation needed for binding during membrane interaction

Lipid transfer proteins acquire and release their lipid cargoes by interacting transiently with source and destination biomembranes. In the GlycoLipid Transfer Protein (GLTP) superfamily, the two-layer all-α-helical GLTP-fold defines proteins that specifically target sphingolipids (SLs) containing either sugar or phosphate headgroups via their conserved but evolutionarily-modified SL recognitions centers. Despite comprehensive structural insights provided by X-ray crystallography, the conformational dynamics associated with membrane interaction and SL uptake/release by GLTP superfamily members have remained unknown. Herein, we report insights gained from molecular dynamics (MD) simulations into the conformational dynamics that enable ceramide-1-phosphate transfer proteins (CPTPs) to acquire and deliver ceramide-1-phosphate (C1P) during interaction with 1-palmitoyl-2-oleoyl phosphatidylcholine bilayers. The focus on CPTP reflects this protein's involvement in regulating pro-inflammatory eicosanoid production and autophagy-dependent inflammasome assembly that drives interleukin (IL-1β and IL-18) production and release by surveillance cells. We found that membrane penetration by CPTP involved α-6 helix and the α-2 helix N-terminal region, was confined to one bilayer leaflet, and was relatively shallow. Large-scale dynamic conformational changes were minimal for CPTP during membrane interaction or C1P uptake except for the α-3/α-4 helices connecting loop, which is located near the membrane interface and interacts with certain phosphoinositide headgroups. Apart from functioning as a shallow membrane-docking element, α-6 helix was found to adeptly reorient membrane lipids to help guide C1P hydrocarbon chain insertion into the interior hydrophobic pocket of the SL binding site.These findings support a proposed 'hydrocarbon chain-first' mechanism for C1P uptake, in contrast to the 'lipid polar headgroup-first' uptake used by most lipid-transfer proteins.

Spatial arrangement of proteins in planar and curved membranes by PPM 3.0

Cellular protrusions, invaginations, and many intracellular organelles have strongly curved membrane regions. Transmembrane and peripheral membrane proteins that induce, sense, or stabilize such regions cannot be properly fitted into a single flat bilayer. To treat such proteins, we developed a new method and a web tool, PPM 3.0, for positioning proteins in curved or planar, single or multiple membranes. This method determines the energetically optimal spatial position, the hydrophobic thickness, and the radius of intrinsic curvature of a membrane-deforming protein structure by arranging it in a single or several sphere-shaped or planar membrane sections. In addition, it can define the lipid-embedded regions of a protein that simultaneously spans several membranes or determine the optimal position of a peptide in a spherical micelle. The PPM 3.0 web server operates with 17 types of biological membranes and 4 types of artificial bilayers. It is publicly available at https://opm.phar.umich.edu/ppm_server3. PPM 3.0 was applied to identify and characterize arrangements in membranes of 128 proteins with a significant intrinsic curvature, such as BAR domains, annexins, Piezo, and MscS mechanosensitive channels, cation-chloride cotransporters, as well as mitochondrial ATP synthases, calcium uniporters, and TOM complexes. These proteins form large complexes that are mainly localized in mitochondria, plasma membranes, and endosomes. Structures of bacterial drug efflux pumps, AcrAB-TolC, MexAB-OrpM, and MacAB-TolC, were positioned in both membranes of the bacterial cell envelop, while structures of multimeric gap-junction channels were arranged in two opposed cellular membranes.

Structural basis for substrate specificity of heteromeric transporters of neutral amino acids

Despite having similar structures, each member of the heteromeric amino acid transporter (HAT) family shows exquisite preference for the exchange of certain amino acids. Substrate specificity determines the physiological function of each HAT and their role in human diseases. However, HAT transport preference for some amino acids over others is not yet fully understood. Using cryo-electron microscopy of apo human LAT2/CD98hc and a multidisciplinary approach, we elucidate key molecular determinants governing neutral amino acid specificity in HATs. A few residues in the substrate-binding pocket determine substrate preference. Here, we describe mutations that interconvert the substrate profiles of LAT2/CD98hc, LAT1/CD98hc, and Asc1/CD98hc. In addition, a region far from the substrate-binding pocket critically influences the conformation of the substrate-binding site and substrate preference. This region accumulates mutations that alter substrate specificity and cause hearing loss and cataracts. Here, we uncover molecular mechanisms governing substrate specificity within the HAT family of neutral amino acid transporters and provide the structural bases for mutations in LAT2/CD98hc that alter substrate specificity and that are associated with several pathologies.

The tumor suppressor activity of DLC1 requires the interaction of its START domain with Phosphatidylserine, PLCD1, and Caveolin-1

BACKGROUND

DLC1, a tumor suppressor gene that is downregulated in many cancer types by genetic and nongenetic mechanisms, encodes a protein whose RhoGAP and scaffolding activities contribute to its tumor suppressor functions. The role of the DLC1 START (StAR-related lipid transfer; DLC1-START) domain, other than its binding to Caveolin-1, is poorly understood. In other START domains, a key function is that they bind lipids, but the putative lipid ligand for DLC1-START is unknown.

METHODS

Lipid overlay assays and Phosphatidylserine (PS)-pull down assays confirmed the binding of DLC1-START to PS. Co-immunoprecipitation studies demonstrated the interaction between DLC1-START and Phospholipase C delta 1 (PLCD1) or Caveolin-1, and the contribution of PS to those interactions. Rho-GTP, cell proliferation, cell migration, and/or anchorage-independent growth assays were used to investigate the contribution of PS and PLCD1, or the implications of TCGA cancer-associated DLC1-START mutants, to DLC1 functions. Co-immunoprecipitations and PS-pull down assays were used to investigate the molecular mechanisms underlying the impaired functions of DLC1-START mutants. A structural model of DLC1-START was also built to better understand the structural implications of the cancer-associated mutations in DLC1-START.

RESULTS

We identified PS as the lipid ligand for DLC1-START and determined that DLC1-START also binds PLCD1 protein in addition to Caveolin-1. PS binding contributes to the interaction of DLC1 with Caveolin-1 and with PLCD1. The importance of these activities for tumorigenesis is supported by our analysis of 7 cancer-associated DLC1-START mutants, each of which has reduced tumor suppressor function but retains wildtype RhoGAP activity. Our structural model of DLC1-START indicates the mutants perturb different elements within the structure, which is correlated with our experimental findings that the mutants are heterogenous with regard to the deficiency of their binding properties. Some have reduced PS binding, others reduced PLCD1 and Caveolin-1 binding, and others are deficient for all of these properties.

CONCLUSION

These observations highlight the importance of DLC1-START for the tumor suppressor function of DLC1 that is RhoGAP-independent. They also expand the versatility of START domains, as DLC1-START is the first found to bind PS, which promotes the binding to other proteins.

Diverse Scientific Benchmarks for Implicit Membrane Energy Functions

Energy functions are fundamental to biomolecular modeling. Their success depends on robust physical formalisms, efficient optimization, and high-resolution data for training and validation. Over the past 20 years, progress in each area has advanced soluble protein energy functions. Yet, energy functions for membrane proteins lag behind due to sparse and low-quality data, leading to overfit tools. To overcome this challenge, we assembled a suite of 12 tests on independent data sets varying in size, diversity, and resolution. The tests probe an energy function's ability to capture membrane protein orientation, stability, sequence, and structure. Here, we present the tests and use the franklin2019 energy function to demonstrate them. We then identify areas for energy function improvement and discuss potential future integration with machine-learning-based optimization methods. The tests are available through the Rosetta Benchmark Server (https://benchmark.graylab.jhu.edu/) and GitHub (https://github.com/rfalford12/Implicit-Membrane-Energy-Function-Benchmark).

Structural Modeling and in planta Complementation Studies Link Mutated Residues of the Medicago truncatula Nitrate Transporter NPF1.7 to Functionality in Root Nodules

Symbiotic nitrogen fixation is a complex and regulated process that takes place in root nodules of legumes and allows legumes to grow in soils that lack nitrogen. Nitrogen is mostly acquired from the soil as nitrate and its level in the soil affects nodulation and nitrogen fixation. The mechanism(s) by which legumes modulate nitrate uptake to regulate nodule symbiosis remain unclear. In Medicago truncatula, the MtNPF1.7 transporter has been shown to control nodulation, symbiosis, and root architecture. MtNPF1.7 belongs to the nitrate/peptide transporter family and is a symporter with nitrate transport driven by proton(s). In this study we combined in silico structural predictions with in planta complementation of the severely defective mtnip-1 mutant plants to understand the role of a series of distinct amino acids in the transporter's function. Our results support hypotheses about the functional importance of the ExxE(R/K) motif including an essential role for the first glutamic acid of the motif in proton(s) and possibly substrate transport. Results reveal that Motif A, a motif conserved among major facilitator transport (MFS) proteins, is essential for function. We hypothesize that it participates in intradomain packing of transmembrane helices and stabilizing one conformation during transport. Our results also question the existence of a putative TMH4-TMH10 salt bridge. These results are discussed in the context of potential nutrient transport functions for MtNPF1.7. Our findings add to the knowledge of the mechanism of alternative conformational changes as well as symport transport in NPFs and enhance our knowledge of the mechanisms for nitrate signaling.

Electrostatics and water occlusion regulate covalently-bound flavin mononucleotide cofactors of Vibrio cholerae respiratory complex NQR

Proteins like NADH:ubiquinone oxidoreductase (NQR), an essential enzyme and ion pump in the physiology of several pathogenic bacteria, tightly regulate the redox properties of their cofactors. Although flavin mononucleotide (FMN) is fully reduced in aqueous solution, FMN in subunits B and C of NQR exclusively undergo one-electron transitions during its catalytic cycle. Here, we perform ab initio calculations and molecular dynamics simulations to elucidate the mechanisms that regulate the redox state of FMN in NQR. QM/MM calculations show that binding site electrostatics disfavor anionic forms of FMNH₂ , but permit a neutral form of the fully reduced flavin. The potential energy surface is unaffected by covalent bonding between FMN and threonine. Molecular dynamics simulations show that the FMN binding sites are inaccessible by water, suggesting that further reductions of the cofactors are limited or prohibited by the availability of water and other proton donors. These findings provide a deeper understanding of the mechanisms used by NQR to regulate electron transfer through the cofactors and perform its physiologic role. They also provide the first, to our knowledge, evidence of the simple concept that proteins regulate flavin redox states via water occlusion.

Marker residue types at the structural regions of transmembrane alpha-helical and beta-barrel interfaces

Membrane proteins play a variety of biological functions to the survival of organisms and functionalities of these proteins are often due to their homo- or hetero-complexation. Encoded by ~30% of the genome in most organisms, they represent the target of over half of nowadays drugs. Spanning the entirety of the cell membrane, transmembrane proteins are the most common type of membrane proteins and can be classified by secondary structures: alpha-helical and beta-barrel structures. Protein-protein interaction (PPI) have been widely studied for globular proteins and many computational tools are available for predicting PPI sites and construct models of complexes. Here, the structural regions of a non-redundant set of 232 alpha-helical and 37 beta-barrel transmembrane complexes and their interfaces are analyzed. Using the residue composition, frequency and propensity, this study brings the light on the marker residue types located at the structural regions of alpha-helical and beta-barrel transmembrane homomeric protein complexes and of their interfaces. This study also shows the necessity to relate the frequency to the composition into a ratio for immediately figuring out residue types presenting high frequencies at the interface and/or at one of its structural regions despite being a minor contributor compared to other residue types to that location's residue composition.

Multilevel Density Functional Theory

Following recent developments in multilevel embedding methods, we introduce a novel density matrix-based multilevel approach within the framework of density functional theory (DFT). In this multilevel DFT, the system is partitioned in an active and an inactive fragment, and all interactions are retained between the two parts. The decomposition of the total system is performed upon the density matrix. The orthogonality between the two parts is maintained by solving the Kohn–Sham equations in the MO basis for the active part only, while keeping the inactive density matrix frozen. This results in the reduction of computational cost. We outline the theory and implementation and discuss the differences and similarities with state-of-the-art DFT embedding methods. We present applications to aqueous solutions of methyloxirane and glycidol.

Discovery of EST73502, a Dual μ-Opioid Receptor Agonist and σ1 Receptor Antagonist Clinical Candidate for the Treatment of Pain

The synthesis and pharmacological activity of a new series of 4-alkyl-1-oxa-4,9-diazaspiro[5.5]undecane derivatives as potent dual ligands for the σ1 receptor (σ1R) and the μ-opioid receptor (MOR) are reported. A lead optimization program over the initial 4-aryl analogues provided 4-alkyl derivatives with the desired functionality and good selectivity and ADME profiles. Compound 14u (EST73502) showed MOR agonism and σ1R antagonism and a potent analgesic activity, comparable to the MOR agonist oxycodone in animal models of acute and chronic pain after single and repeated administration. Contrary to oxycodone, 14u produces analgesic activity with reduced opioid-induced relevant adverse events, like intestinal transit inhibition and naloxone-precipitated behavioral signs of opiate withdrawal. These results provide evidence that dual MOR agonism and σ1R antagonism may be a useful strategy for obtaining potent and safer analgesics and were the basis for the selection of 14u as a clinical candidate for the treatment of pain.

Ligand with Two Modes of Interaction with the Dopamine D2 Receptor-An Induced-Fit Mechanism of Insurmountable Antagonism

A solid understanding of the mechanisms governing ligand binding is crucial for rational design of therapeutics targeting the dopamine D2 receptor (D2R). Here, we use G protein-coupled inward rectifier potassium (GIRK) channel activation in Xenopus oocytes to measure the kinetics of D2R antagonism by a series of aripiprazole analogues, as well as the recovery of dopamine (DA) responsivity upon washout. The aripiprazole analogues comprise an orthosteric and a secondary pharmacophore and differ by the length of the saturated carbon linker joining these two pharmacophores. Two compounds containing 3- and 5-carbon linkers allowed for a similar extent of recovery from antagonism in the presence of 1 or 100 μM DA (>25 and >90% of control, respectively), whereas recovery was less prominent (∼20%) upon washout of the 4-carbon linker compound, SV-III-130, both with 1 and 100 μM DA. Prolonging the coincubation time with SV-III-130 further diminished recovery. Curve-shift experiments were consistent with competition between SV-III-130 and DA. Two mutations in the secondary binding pocket (V91A and E95A) of D2R decreased antagonistic potency and increased recovery from SV-III-130 antagonism, whereas a third mutation (L94A) only increased recovery. Our results suggest that the secondary binding pocket influences recovery from inhibition by the studied aripiprazole analogues. We propose a mechanism, supported by in silico modeling, whereby SV-III-130 initially binds reversibly to the D2R, after which the drug-receptor complex undergoes a slow transition to a second ligand-bound state, which is dependent on secondary binding pocket integrity and irreversible during the time frame of our experiments.

Membrane dynamics of γ-secretase with the anterior pharynx-defective 1B subunit

The four-subunit protease complex γ-secretase cleaves many single-pass transmembrane (TM) substrates, including Notch and β-amyloid precursor protein to generate amyloid-β (Aβ), central to Alzheimer's disease. Two of the subunits anterior pharynx-defective 1 (APH-1) and presenilin (PS) exist in two homologous forms APH1-A and APH1-B, and PS1 and PS2. The consequences of these variations are poorly understood and could affect Aβ production and γ-secretase medicine. Here, we developed the first complete structural model of the APH-1B subunit using the published cryo-electron microscopy (cryo-EM) structures of APH1-A (Protein Data Bank: 5FN2, 5A63, and 6IYC). We then performed all-atom molecular dynamics simulations at 303 K in a realistic bilayer system to understand both APH-1B alone and in γ-secretase without and with substrate C83-bound. We show that APH-1B adopts a 7TM topology with a water channel topology similar to APH-1A. We demonstrate direct transport of water through this channel, mainly via Glu84, Arg87, His170, and His196. The apo and holo states closely resemble the experimental cryo-EM structures with APH-1A, however with subtle differences: The substrate-bound APH-1B γ-secretase was quite stable, but some TM helices of PS1 and APH-1B rearranged in the membrane consistent with the disorder seen in the cryo-EM data. This produces different accessibility of water molecules for the catalytic aspartates of PS1, critical for Aβ production. In particular, we find that the typical distance between the catalytic aspartates of PS1 and the C83 cleavage sites are shorter in APH-1B, that is, it represents a more closed state, due to interactions with the C-terminal fragment of PS1. Our structural-dynamic model of APH-1B alone and in γ-secretase suggests generally similar topology but some notable differences in water accessibility which may be relevant to the protein's existence in two forms and their specific function and location.

Interfacial Binding Sites for Cholesterol on Kir, Kv, K2P, and Related Potassium Channels

Inwardly rectifying, voltage-gated, two-pore domain, and related K+ channels are located in eukaryotic membranes rich in cholesterol. Here, molecular docking is used to detect specific binding sites ("hot spots") for cholesterol on K+ channels with characteristics that match those of known cholesterol binding sites. The transmembrane surfaces of all available high-resolution structures for K+ channels were swept for potential binding sites. Cholesterol poses were found to be located largely in hollows between protein ridges. A comparison between cholesterol poses and resolved phospholipids suggests that not all cholesterol molecules binding to the transmembrane surface of a K+ channel will result in displacement of a phospholipid molecule from the surface. Competition between cholesterol binding and binding of anionic phospholipids essential for activity could explain some of the effects of cholesterol on channel function.

Membrane interactions in drug delivery: Model cell membranes and orthogonal techniques

To generate the desired effect in the human body, the active pharmaceutical ingredient usually needs to interact with a receptor located on the cell membrane or inside the cell. Thus, understanding membrane interactions is of great importance when it comes to the development and testing of new drug molecules or new drug delivery systems. Nowadays, there is a tremendous selection of both model cell membranes and of techniques that can be used to characterize interactions between selected model cell membranes and a drug molecule, an excipient, or a drug delivery system. Having such a wide selection of model cell membranes and techniques available makes it sometimes challenging to select the optimal combination for a specific study. Furthermore, it is difficult to compare results obtained using different model cell membranes and techniques, and not all in vitro studies translate as well to an estimation of the in vivo biological activity or understanding of mode of action. This review provides an overview of the available lipid bilayer-based model cell membranes and of the most widely employed techniques for studying membrane interactions. Finally, the need for employing complimentary characterization techniques in order to acquire more reliable and in-depth information is highlighted.

Linking Biochemical and Structural States of SERCA: Achievements, Challenges, and New Opportunities

Sarcoendoplasmic reticulum calcium ATPase (SERCA), a member of the P-type ATPase family of ion and lipid pumps, is responsible for the active transport of Ca²⁺ from the cytoplasm into the sarcoplasmic reticulum lumen of muscle cells, into the endoplasmic reticulum (ER) of non-muscle cells. X-ray crystallography has proven to be an invaluable tool in understanding the structural changes of SERCA, and more than 70 SERCA crystal structures representing major biochemical states (defined by bound ligand) have been deposited in the Protein Data Bank. Consequently, SERCA is one of the best characterized components of the calcium transport machinery in the cell. Emerging approaches in the field, including spectroscopy and molecular simulation, now help integrate and interpret this rich structural information to understand the conformational transitions of SERCA that occur during activation, inhibition, and regulation. In this review, we provide an overview of the crystal structures of SERCA, focusing on identifying metrics that facilitate structure-based categorization of major steps along the catalytic cycle. We examine the integration of crystallographic data with different biophysical approaches and computational methods to link biochemical and structural states of SERCA that are populated in the cell. Finally, we discuss the challenges and new opportunities in the field, including structural elucidation of functionally important and novel regulatory complexes of SERCA, understanding the structural basis of functional divergence among homologous SERCA regulators, and bridging the gap between basic and translational research directed toward therapeutic modulation of SERCA.

Asc-1 Transporter (SLC7A10): Homology Models And Molecular Dynamics Insights Into The First Steps Of The Transport Mechanism

The alanine-serine-cysteine transporter Asc-1 regulates the synaptic availability of d-serine and glycine (the two co-agonists of the NMDA receptor) and is regarded as an important drug target. To shuttle the substrate from the extracellular space to the cytoplasm, this transporter undergoes multiple distinct conformational states. In this work, homology modeling, substrate docking and molecular dynamics simulations were carried out to learn more about the transition between the “outward-open” and “outward-open occluded” states. We identified a transition state involving the highly-conserved unwound TM6 region in which the Phe243 flips close to the d-serine substrate without major movements of TM6. This feature and those of other key residues are proposed to control the binding site and substrate translocation. Competitive inhibitors ACPP, LuAE00527 and SMLC were docked and their binding modes at the substrate binding site corroborated the key role played by Phe243 of TM6. For ACPP and LuAE00527, strong hydrophobic interactions with this residue hinder its mobility and prevent the uptake and the efflux of substrates. As for SMLC, the weaker interactions maintain the flexibility of Phe243 and the efflux process. Overall, we propose a molecular basis for the inhibition of substrate translocation of the Asc-1 transporter that should be valuable for rational drug design.

Replacing the eleven native tryptophans by directed evolution produces an active P-glycoprotein with site-specific, non-conservative substitutions

P-glycoprotein (Pgp) pumps an array of hydrophobic compounds out of cells, and has major roles in drug pharmacokinetics and cancer multidrug resistance. Yet, polyspecific drug binding and ATP hydrolysis-driven drug export in Pgp are poorly understood. Fluorescence spectroscopy using tryptophans (Trp) inserted at strategic positions is an important tool to study ligand binding. In Pgp, this method will require removal of 11 endogenous Trps, including highly conserved Trps that may be important for function, protein-lipid interactions, and/or protein stability. Here, we developed a directed evolutionary approach to first replace all eight transmembrane Trps and select for transport-active mutants in Saccharomyces cerevisiae. Surprisingly, many Trp positions contained non-conservative substitutions that supported in vivo activity, and were preferred over aromatic amino acids. The most active construct, W(3Cyto), served for directed evolution of the three cytoplasmic Trps, where two positions revealed strong functional bias towards tyrosine. W(3Cyto) and Trp-less Pgp retained wild-type-like protein expression, localization and transport function, and purified proteins retained drug stimulation of ATP hydrolysis and drug binding affinities. The data indicate preferred Trp substitutions specific to the local context, often dictated by protein structural requirements and/or membrane lipid interactions, and these new insights will offer guidance for membrane protein engineering.