Elucidating the complex membrane binding of a protein with multiple anchoring domains using extHMMM.

Membrane binding is a crucial mechanism for many proteins, but understanding the specific interactions between proteins and membranes remains a challenging endeavor. Coagulation factor Va (FVa) is a large protein whose membrane interactions are complicated due to the presence of multiple anchoring domains that individually can bind to lipid membranes. Using molecular dynamics simulations, we investigate the membrane binding of FVa and identify the key mechanisms that govern its interaction with membranes. Our results reveal that FVa can either adopt an upright or a tilted molecular orientation upon membrane binding. We further find that the domain organization of FVa deviates (sometimes significantly) from its crystallographic reference structure, and that the molecular orientation of the protein matches with domain reorganization to align the C2 domain toward its favored membrane-normal orientation. We identify specific amino acid residues that exhibit contact preference with phosphatidylserine lipids over phosphatidylcholine lipids, and we observe that mostly electrostatic effects contribute to this preference. The observed lipid-binding process and characteristics, specific to FVa or common among other membrane proteins, in concert with domain reorganization and molecular tilt, elucidate the complex membrane binding dynamics of FVa and provide important insights into the molecular mechanisms of protein-membrane interactions. An updated version of the HMMM model, termed extHMMM, is successfully employed for efficiently observing membrane bindings of systems containing the whole FVa molecule.

Membrane binding and lipid-protein interaction of the C2 domain from coagulation factor V.

Anchoring of coagulation factors to anionic regions of the membrane involves the C2 domain as a key player. The rate of enzymatic reactions of the coagulation factors is increased by several orders of magnitude upon membrane binding. However, the precise mechanisms behind the rate acceleration remain unclear, primarily because of a lack of understanding of the conformational dynamics of the C2-containing factors and corresponding complexes. We elucidate the membrane-bound form of the C2 domain from human coagulation factor V (FV-C2) by characterizing its membrane binding the specific lipid-protein interactions. Employing all-atom molecular dynamics simulations and leveraging the highly mobile membrane-mimetic (HMMM) model, we observed spontaneous binding of FV-C2 to a phosphatidylserine (PS)-containing membrane within 2-25 ns across twelve independent simulations. FV-C2 interacted with the membrane through three loops (spikes 1-3), achieving a converged, stable orientation. Multiple HMMM trajectories of the spontaneous membrane binding provided extensive sampling and ample data to examine the membrane-induced effects on the conformational dynamics of C2 as well as specific lipid-protein interactions. Despite existing crystal structures representing presumed "open" and "closed" states of FV-C2, our results revealed a continuous distribution of structures between these states, with the most populated structures differing from both "open" and "closed" states observed in crystal environments. Lastly, we characterized a putative PS-specific binding site formed by K23, Q48, and S78 located in the groove enclosed by spikes 1-3 (PS-specificity pocket), suggesting a different orientation of a bound headgroup moiety compared to previous proposals based upon analysis of static crystal structures.

Evaluating Polarizable Biomembrane Simulations against Experiments.

Owing to the increase of available computational capabilities and the potential for providing a more accurate description, polarizable molecular dynamics force fields are gaining popularity in modeling biomolecular systems. It is, however, crucial to evaluate how much precision is truly gained with increasing cost and complexity of the simulation. Here, we leverage the NMRlipids open collaboration and Databank to assess the performance of available polarizable lipid models─the CHARMM-Drude and the AMOEBA-based parameters─against high-fidelity experimental data and compare them to the top-performing nonpolarizable models. While some improvement in the description of ion binding to membranes is observed in the most recent CHARMM-Drude parameters, and the conformational dynamics of AMOEBA-based parameters are excellent, the best nonpolarizable models tend to outperform their polarizable counterparts for each property we explored. The identified shortcomings range from inaccuracies in describing the conformational space of lipids to excessively slow conformational dynamics. Our results provide valuable insights for the further refinement of polarizable lipid force fields and for selecting the best simulation parameters for specific applications.

Optimizing Coarse-Grained Models for Large-Scale Membrane Protein Simulation.

Coarse-grained (CG) models have been developed for studying membrane proteins at physiologically relevant scales. Such methods, including popular CG lipid models, exhibit stability and efficiency at moderate scales, but they can become impractical or even unusable beyond a critical size due to various technical issues. Here, we report that these scale-dependent issues can arise from progressively slower relaxation dynamics and become confounded by unforeseen instabilities observed only at larger scales. To address these issues, we systemically optimized a 4-site solvent-free CG lipid model that is suitable for conducting micron-scale molecular dynamics simulations of membrane proteins under various membrane properties. We applied this lipid model to explore the long-range membrane deformation induced by a large mechanosensitive ion channel, PIEZO. We show that the optimized CG models are powerful in elucidating the structural and dynamic interplay between PIEZO and the membrane. Furthermore, we anticipate that our methodological insights can prove useful for resolving issues stemming from scale-dependent limitations of similar CG methodologies.

Distal Protein-Protein Interactions Contribute to SARS-CoV-2 Main Protease Substrate Binding and Nirmatrelvir Resistance.

SARS-CoV-2 main protease, M pro , is responsible for the processing of the viral polyproteins into individual proteins, including the protease itself. M pro is a key target of anti-COVID-19 therapeutics such as nirmatrelvir (the active component of Paxlovid). Resistance mutants identified clinically and in viral passage assays contain a combination of active site mutations (e.g. E166V, E166A, L167F), which reduce inhibitor binding and enzymatic activity, and non-active site mutations (e.g. P252L, T21I, L50F), which restore the fitness of viral replication. Although the mechanism of resistance for the active site mutations is apparent, the role of the non-active site mutations in fitness rescue remains elusive. In this study, we use the model system of a M pro triple mutant (L50F/E166A/L167F) that confers not only nirmatrelvir drug resistance but also a similar fitness of replication compared to the wild-type both in vitro and in vivo. By comparing peptide and full-length M pro protein as substrates, we demonstrate that the binding of M pro substrate involves more than residues in the active site. In particular, L50F and other non-active site mutations can enhance the M pro dimer-dimer interactions and help place the nsp5-6 substrate at the enzyme catalytic center. The structural and enzymatic activity data of M pro L50F, L50F/E166A/L167F, and others underscore the importance of considering the whole substrate protein in studying M pro and substrate interactions, and offers important insights into M pro function, resistance development, and inhibitor design.

Staphylococcus aureus FtsZ and PBP4 bind to the conformationally dynamic N-terminal domain of GpsB.

In the Firmicutes phylum, GpsB is a membrane associated protein that coordinates peptidoglycan synthesis with cell growth and division. Although GpsB has been studied in several bacteria, the structure, function, and interactome of Staphylococcus aureus GpsB is largely uncharacterized. To address this knowledge gap, we solved the crystal structure of the N-terminal domain of S. aureus GpsB, which adopts an atypical, asymmetric dimer, and demonstrates major conformational flexibility that can be mapped to a hinge region formed by a three-residue insertion exclusive to Staphylococci. When this three-residue insertion is excised, its thermal stability increases, and the mutant no longer produces a previously reported lethal phenotype when overexpressed in Bacillus subtilis. In S. aureus, we show that these hinge mutants are less functional and speculate that the conformational flexibility imparted by the hinge region may serve as a dynamic switch to fine-tune the function of the GpsB complex and/or to promote interaction with its various partners. Furthermore, we provide the first biochemical, biophysical, and crystallographic evidence that the N-terminal domain of GpsB binds not only PBP4, but also FtsZ, through a conserved recognition motif located on their C-termini, thus coupling peptidoglycan synthesis to cell division. Taken together, the unique structure of S. aureus GpsB and its direct interaction with FtsZ/PBP4 provide deeper insight into the central role of GpsB in S. aureus cell division.

Dynamic Nature of Staphylococcus aureus Type I Signal Peptidases.

Molecular dynamics simulations are used to interrogate the dynamic nature of Staphylococcus aureus Type I signal peptidases, SpsA and SpsB, including the impact of the P29S mutation of SpsB. Fluctuations and plasticity- rigidity characteristics vary among the proteins, particularly in the extracellular domain. Intriguingly, the P29S mutation, which influences susceptibility to arylomycin antibiotics, affect the mechanically coupled motions in SpsB. The integrity of the active site is crucial for catalytic competency, and variations in sampled structural conformations among the proteins are consistent with diverse peptidase capabilities. We also explored the intricate interactions between the proteins and the model S. aureus membrane. It was observed that certain membrane-inserted residues in the loop around residue 50 (50s) and C-terminal loops, beyond the transmembrane domain, give rise to direct interactions with lipids in the bilayer membrane. Our findings are discussed in the context of functional knowledge about these signal peptidases, offering additional understanding of dynamic aspects relevant to some cellular processes with potential implications for drug targeting strategies.

Overlay databank unlocks data-driven analyses of biomolecules for all.

Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitable training data in programmatically accessible format. Here we propose an effective solution to make data scattered in various locations and formats accessible for data-driven and machine learning applications using the overlay databank format. To demonstrate the practical relevance of such approach, we present the NMRlipids Databank-a community-driven, open-for-all database featuring programmatic access to quality-evaluated atom-resolution molecular dynamics simulations of cellular membranes. Cellular membrane lipid composition is implicated in diseases and controls major biological functions, but membranes are difficult to study experimentally due to their intrinsic disorder and complex phase behaviour. While MD simulations have been useful in understanding membrane systems, they require significant computational resources and often suffer from inaccuracies in model parameters. Here, we demonstrate how programmable interface for flexible implementation of data-driven and machine learning applications, and rapid access to simulation data through a graphical user interface, unlock possibilities beyond current MD simulation and experimental studies to understand cellular membranes. The proposed overlay databank concept can be further applied to other biomolecules, as well as in other fields where similar barriers hinder the AI revolution.

Cholesterol and M2 Rendezvous in Budding and Scission of Influenza A Virus.

The cholesterol of the host cell plasma membrane and viral M2 protein plays a crucial role in multiple stages of infection and replication of the influenza A virus. Cholesterol is required for the formation of heterogeneous membrane microdomains (or rafts) in the budozone of the host cell that serves as assembly sites for the viral components. The raft microstructures act as scaffolds for several proteins. Cholesterol may further contribute to the mechanical forces necessary for membrane scission in the last stage of budding and help to maintain the stability of the virus envelope. The M2 protein has been shown to cause membrane scission in model systems by promoting the formation of curved lipid bilayer structures that, in turn, can lead to membrane vesicles budding off or scission intermediates. Membrane remodeling by M2 is intimately linked with cholesterol as it affects local lipid composition, fluidity, and stability of the membrane. Thus, both cholesterol and M2 protein contribute to the efficient and proper release of newly formed influenza viruses from the virus-infected cells.

Deciphering specificity and cross-reactivity in tachykinin NK1 and NK2 receptors.

The tachykinin receptors neurokinin 1 (NK1R) and neurokinin 2 (NK2R) are G protein-coupled receptors that bind preferentially to the natural peptide ligands substance P and neurokinin A, respectively, and have been targets for drug development. Despite sharing a common C-terminal sequence of Phe-X-Gly-Leu-Met-NH2 that helps direct biological function, the peptide ligands exhibit some degree of cross-reactivity toward each other's non-natural receptor. Here, we investigate the detailed structure-activity relationships of the ligand-bound receptor complexes that underlie both potent activation by the natural ligand and cross-reactivity. We find that the specificity and cross-reactivity of the peptide ligands can be explained by the interactions between the amino acids preceding the FxGLM consensus motif of the bound peptide ligand and two regions of the receptor: the ß-hairpin of the extracellular loop 2 (ECL2) and a N-terminal segment leading into transmembrane helix 1. Positively charged sidechains of the ECL2 (R177 of NK1R and K180 of NK2R) are seen to play a vital role in the interaction. The N-terminal positions 1 to 3 of the peptide ligand are entirely dispensable. Mutated and chimeric receptor and ligand constructs neatly swap around ligand specificity as expected, validating the structure-activity hypotheses presented. These findings will help in developing improved agonists or antagonists for NK1R and NK2R.

A 19F-qNMR-Guided Mathematical Model for G Protein-Coupled Receptor Signaling.

G protein-coupled receptors (GPCRs) exhibit a wide range of pharmacological efficacies, yet the molecular mechanisms responsible for the differential efficacies in response to various ligands remain poorly understood. This lack of understanding has hindered the development of a solid foundation for establishing a mathematical model for signaling efficacy. However, recent progress has been made in delineating and quantifying receptor conformational states and associating function with these conformations. This progress has allowed us to construct a mathematical model for GPCR signaling efficacy that goes beyond the traditional ON/OFF binary switch model. In this study, we present a quantitative conformation-based mathematical model for GPCR signaling efficacy using the adenosine A2A receptor (A2AR) as a model system, under the guide of 19F quantitative nuclear magnetic resonance experiments. This model encompasses two signaling states, a fully activated state and a partially activated state, defined as being able to regulate the cognate Gα s nucleotide exchange with respective G protein recognition capacity. By quantifying the population distribution of each state, we can now in turn examine GPCR signaling efficacy. This advance provides a foundation for assessing GPCR signaling efficacy using a conformation-based mathematical model in response to ligand binding. SIGNIFICANCE STATEMENT: Mathematical models to describe signaling efficacy of GPCRs mostly suffer from considering only two states (ON/OFF). However, research indicates that a GPCR possesses multiple active-(like) states that can interact with Gαßγ independently, regulating varied nucleotide exchanges. With the guide of 19F-qNMR, the transitions among these states are quantified as a function of ligand and Gαßγ, serving as a foundation for a novel conformation-based mathematical signaling model.

Quantitative Comparison against Experiments Reveals Imperfections in Force Fields' Descriptions of POPC-Cholesterol Interactions.

Cholesterol is a central building block in biomembranes, where it induces orientational order, slows diffusion, renders the membrane stiffer, and drives domain formation. Molecular dynamics (MD) simulations have played a crucial role in resolving these effects at the molecular level; yet, it has recently become evident that different MD force fields predict quantitatively different behavior. Although easily neglected, identifying such limitations is increasingly important as the field rapidly progresses toward simulations of complex membranes mimicking the in vivo conditions: pertinent multicomponent simulations must capture accurately the interactions between their fundamental building blocks, such as phospholipids and cholesterol. Here, we define quantitative quality measures for simulations of binary lipid mixtures in membranes against the C-H bond order parameters and lateral diffusion coefficients from NMR spectroscopy as well as the form factors from X-ray scattering. Based on these measures, we perform a systematic evaluation of the ability of commonly used force fields to describe the structure and dynamics of binary mixtures of palmitoyloleoylphosphatidylcholine (POPC) and cholesterol. None of the tested force fields clearly outperforms the others across the tested properties and conditions. Still, the Slipids parameters provide the best overall performance in our tests, especially when dynamic properties are included in the evaluation. The quality evaluation metrics introduced in this work will, particularly, foster future force field development and refinement for multicomponent membranes using automated approaches.

Mechanistic basis of GPCR activation explored by ensemble refinement of crystallographic structures.

G protein-coupled receptors (GPCRs) are important drug targets characterized by a canonical seven transmembrane (TM) helix architecture. Recent advances in X-ray crystallography and cryo-EM have resulted in a wealth of GPCR structures that have been used in drug design and formed the basis for mechanistic activation hypotheses. Here, ensemble refinement (ER) of crystallographic structures is applied to explore the impact of binding of agonists and antagonist/inverse agonists to selected structures of cannabinoid receptor 1 (CB1R), ß2 adrenergic receptor (ß2 AR), and A2A adenosine receptor (A2A AR). To assess the conformational flexibility and its role in GPCR activation, hydrogen bond (H-bond) networks are analyzed by calculating and comparing H-bond propensities. Mapping pairwise propensity differences between agonist- and inverse agonist/antagonist-bound structures for CB1R and ß2 AR shows that agonist binding destabilizes H-bonds in the intracellular parts of TM 5-7, forming the G protein binding cavity, while H-bonds of the extracellular segment of TMs surrounding the orthosteric site are conversely stabilized. Certain class A GPCRs, for example, A2A AR, bind an allosteric sodium ion that negatively modulates agonist binding. The impact of sodium-excluding mutants (D522.50 N, S913.39 A) of A2A AR on agonist binding is examined by applying ER analysis to structures of wildtype and the two mutants in complex with a full agonist. While S913.39 A exhibits normal activity, D522.50 N quenches the downstream signaling. The mainchain H-bond pattern of the latter is stabilized in the intracellular part of TM 7 containing the NPxxY motif, indicating that an induced rigidity of the mutation prevents conformational selection of G proteins resulting in receptor inactivation.

19F NMR: A promising tool for dynamic conformational studies of G protein-coupled receptors.

Advances in X-ray crystallography and cryoelectron microscopy enabled unprecedented insights into the activation processes of G protein-coupled receptors (GPCRs). However, these static receptor structures provide limited information about dynamics and conformational transitions that play pivotal roles in mediating signaling diversity through the multifaceted interactions between ligands, receptors, and transducers. Developing NMR approaches to probe the dynamics of conformational transitions will push the frontier of receptor science toward a more comprehensive understanding of these signaling processes. Although much progress has been made during the last decades, it remains challenging to delineate receptor conformational states and interrogate the functions of the individual states at a quantitative level. Here we cover the progress of 19F NMR applications in GPCR conformational and dynamic studies during the past 20 years. Current challenges and limitations of 19F NMR for studying GPCR dynamics are also discussed, along with experimental strategies that will drive this field forward.

A systematic approach for evaluating the role of surface-exposed loops in trypsin-like serine proteases applied to the 170 loop in coagulation factor VIIa.

Proteases play a major role in many vital physiological processes. Trypsin-like serine proteases (TLPs), in particular, are paramount in proteolytic cascade systems such as blood coagulation and complement activation. The structural topology of TLPs is highly conserved, with the trypsin fold comprising two ß-barrels connected by a number of variable surface-exposed loops that provide a surprising capacity for functional diversity and substrate specificity. To expand our understanding of the roles these loops play in substrate and co-factor interactions, we employ a systematic methodology akin to the natural truncations and insertions observed through evolution of TLPs. The approach explores a larger deletion space than classical random or directed mutagenesis. Using FVIIa as a model system, deletions of 1-7 amino acids through the surface exposed 170 loop, a vital allosteric regulator, was introduced. All variants were extensively evaluated by established functional assays and computational loop modelling with Rosetta. The approach revealed detailed structural and functional insights recapitulation and expanding on the main findings in relation to 170 loop functions elucidated over several decades using more cumbersome crystallization and single deletion/mutation methodologies. The larger deletion space was key in capturing the most active variant, which unexpectedly had a six-amino acid truncation. This variant would have remained undiscovered if only 2-3 deletions were considered, supporting the usefulness of the methodology in general protease engineering approaches. Our findings shed further light on the complex role that surface-exposed loops play in TLP function and supports the important role of loop length in the regulation and fine-tunning of enzymatic function throughout evolution.

An in-membrane NMR spectroscopic approach probing native ligand-GPCR interaction.

Conventional approaches to study ligand-receptor interactions using solution-state NMR often involve laborious sample preparation, isotopic labeling, and receptor reconstitution. Each of these steps remains challenging for membrane proteins such as G protein-coupled receptors (GPCRs). Here we introduce a combinational approach integrating NMR and homogenized membrane nano-discs preparation to characterize the ligand-GPCR interactions. The approach will have a great potential for drug screening as it benefits from minimal receptor preparation, minimizing non-specific binding. In addition, the approach maintains receptor structural heterogeneity essential for functional diversity, making it feasible for probing a more reliable ligand-GPCR interaction that is vital for faithful ligand discovery.

Inverse Conformational Selection in Lipid-Protein Binding.

Interest in lipid interactions with proteins and other biomolecules is emerging not only in fundamental biochemistry but also in the field of nanobiotechnology where lipids are commonly used, for example, in carriers of mRNA vaccines. The outward-facing components of cellular membranes and lipid nanoparticles, the lipid headgroups, regulate membrane interactions with approaching substances, such as proteins, drugs, RNA, or viruses. Because lipid headgroup conformational ensembles have not been experimentally determined in physiologically relevant conditions, an essential question about their interactions with other biomolecules remains unanswered: Do headgroups exchange between a few rigid structures, or fluctuate freely across a practically continuous spectrum of conformations? Here, we combine solid-state NMR experiments and molecular dynamics simulations from the NMRlipids Project to resolve the conformational ensembles of headgroups of four key lipid types in various biologically relevant conditions. We find that lipid headgroups sample a wide range of overlapping conformations in both neutral and charged cellular membranes, and that differences in the headgroup chemistry manifest only in probability distributions of conformations. Furthermore, the analysis of 894 protein-bound lipid structures from the Protein Data Bank suggests that lipids can bind to proteins in a wide range of conformations, which are not limited by the headgroup chemistry. We propose that lipids can select a suitable headgroup conformation from the wide range available to them to fit the various binding sites in proteins. The proposed inverse conformational selection model will extend also to lipid binding to targets other than proteins, such as drugs, RNA, and viruses.

Uncovering Membrane-Bound Models of Coagulation Factors by Combined Experimental and Computational Approaches.

In the life sciences, including hemostasis and thrombosis, methods of structural biology have become indispensable tools for shedding light on underlying mechanisms that govern complex biological processes. Advancements of the relatively young field of computational biology have matured to a point where it is increasingly recognized as trustworthy and useful, in part due to their high space-time resolution that is unparalleled by most experimental techniques to date. In concert with biochemical and biophysical approaches, computational studies have therefore proven time and again in recent years to be key assets in building or suggesting structural models for membrane-bound forms of coagulation factors and their supramolecular complexes on membrane surfaces where they are activated. Such endeavors and the proposed models arising from them are of fundamental importance in describing and understanding the molecular basis of hemostasis under both health and disease conditions. We summarize the body of work done in this important area of research to drive forward both experimental and computational studies toward new discoveries and potential future therapeutic strategies.

Conformational Plasticity-Rigidity Axis of the Coagulation Factor VII Zymogen Elucidated by Atomistic Simulations of the N-Terminally Truncated Factor VIIa Protease Domain.

The vast majority of coagulation factor VII (FVII), a trypsin-like protease, circulates as the inactive zymogen. Activated FVII (FVIIa) is formed upon proteolytic activation of FVII, where it remains in a zymogen-like state and it is fully activated only when bound to tissue factor (TF). The catalytic domains of trypsin-like proteases adopt strikingly similar structures in their fully active forms. However, the dynamics and structures of the available corresponding zymogens reveal remarkable conformational plasticity of the protease domain prior to activation in many cases. Exactly how ligands and cofactors modulate the conformational dynamics and function of these proteases is not entirely understood. Here, we employ atomistic simulations of FVIIa (and variants hereof, including a TF-independent variant and N-terminally truncated variants) to provide fundamental insights with atomistic resolution into the plasticity-rigidity interplay of the protease domain conformations that appears to govern the functional response to proteolytic and allosteric activation. We argue that these findings are relevant to the FVII zymogen, whose structure has remained elusive despite substantial efforts. Our results shed light on the nature of FVII and demonstrate how conformational dynamics has played a crucial role in the evolutionary adaptation of regulatory mechanisms that were not present in the ancestral trypsin. Exploiting this knowledge could lead to engineering of protease variants for use as next-generation hemostatic therapeutics.

Trifluorinated Keto-Enol Tautomeric Switch in Probing Domain Rotation of a G Protein-Coupled Receptor.

Conformational dynamics and transitions of biologically active molecules are pivotal for understanding the physiological responses they elicit. In the case of receptor activation, there are major implications elucidating disease mechanisms and drug discovery innovation. Yet, incorporation of these factors into drug screening systems remains challenging in part due to the lack of suitable approaches to include them. Here, we present a novel strategy to probe the GPCR domain rotation by utilizing the 19fluorine signal variability of a trifluorinated keto-enol (TFKE) chemical equilibrium. The method takes advantage of the high sensitivity of the TFKE tautomerism toward microenvironmental changes resulting from receptor conformational transitions upon ligand binding. We validated the method using the adenosine A2AR receptor as a model system in which the TFKE was attached to two sites exhibiting opposing motions upon ligand binding, namely, V229C6.31 on transmembrane domain VI (TM6) and A289C7.54 on TM7. Our results demonstrated that the TFKE switch was an excellent reporter for the domain rotation and could be used to study the conformational transition and dynamics of relative domain motions. Although further studies are needed in order to establish a quantitative relationship between the rotational angle and the population distribution of different components in a particular system, the research presented here provides a foundation for its application in studying receptor domain rotation and dynamics, which could be useful in drug screening efforts.