Multiscale Simulations Suggest a Mechanism for the Association of the Dok7 PH Domain with PIP-Containing Membranes

The Influence of Phosphoinositide Lipids in the Molecular Biology of Membrane Proteins: Recent Insights from Simulations

The phosphoinositide family of membrane lipids play diverse and critical roles in eukaryotic molecular biology. Much of this biological activity derives from interactions of phosphoinositide lipids with integral and peripheral membrane proteins, leading to modulation of protein structure, function, and cellular distribution. Since the discovery of phosphoinositides in the 1940s, combined molecular biology, biophysical, and structural approaches have made enormous progress in untangling this vast and diverse cellular network of interactions. More recently, in silico approaches such as molecular dynamics simulations have proven to be an asset in prospectively identifying, characterising, explaining the structural basis of these interactions, and in the best cases providing atomic level testable hypotheses on how such interactions control the function of a given membrane protein. This review details a number of recent seminal discoveries in phosphoinositide biology, enabled by advanced biomolecular simulation, and its integration with molecular biology, biophysical, and structural biology approaches. The results of the simulation studies agree well with experimental work, and in a number of notable cases have arrived at the key conclusion several years in advance of the experimental structures. SUMMARY: Hedger and Yen review developments in simulations of phosphoinositides and membrane proteins.

mosGraphGPT: a foundation model for multi-omic signaling graphs using generative AI

Generative pretrained models represent a significant advancement in natural language processing and computer vision, which can generate coherent and contextually relevant content based on the pre-training on large general datasets and fine-tune for specific tasks. Building foundation models using large scale omic data is promising to decode and understand the complex signaling language patterns within cells. Different from existing foundation models of omic data, we build a foundation model, mosGraphGPT, for multi-omic signaling (mos) graphs, in which the multi-omic data was integrated and interpreted using a multi-level signaling graph. The model was pretrained using multi-omic data of cancers in The Cancer Genome Atlas (TCGA), and fine-turned for multi-omic data of Alzheimer's Disease (AD). The experimental evaluation results showed that the model can not only improve the disease classification accuracy, but also is interpretable by uncovering disease targets and signaling interactions. And the model code are uploaded via GitHub with link: https://github.com/mosGraph/mosGraphGPT.

Intrinsically disordered region of talin's FERM domain functions as an initial PIP2 recognition site

Focal adhesions (FAs) mediate the interaction of the cytoskeleton with the extracellular matrix in a highly dynamic fashion. Talin is a central regulator, adaptor protein, and mechano-sensor of FA complexes. For recruitment and firm attachment at FAs, talin's N-terminal FERM domain binds to phosphatidylinositol 4,5-bisphosphate (PIP2)-enriched membranes. A newly published autoinhibitory structure of talin-1, where the known PIP2 interaction sites are covered up, lead us to hypothesize that a hitherto less examined loop insertion of the FERM domain acts as an additional and initial site of contact. We evaluated direct interactions of talin-1 with a PIP2 membrane by means of atomistic molecular dynamics simulations. We show that this unstructured, 33-residue-long loop strongly interacts with PIP2 and can facilitate further membrane contacts, including the canonical PIP2 interactions, by serving as a flexible membrane anchor. Under force as present at FAs, the extensible FERM loop ensures talin maintains membrane contacts when pulled away from the membrane by up to 7 nm. We identify key basic residues of the anchor mediating the highly dynamic talin-membrane interaction. Our results put forward an intrinsically disordered loop as a key and highly adaptable PIP2 recognition site of talin and potentially other PIP2-binding mechano-proteins.

Specific interactions of peripheral membrane proteins with lipids: what can molecular simulations show us?

Peripheral membrane proteins (PMPs) can reversibly and specifically bind to biological membranes to carry out functions such as cell signalling, enzymatic activity, or membrane remodelling. Structures of these proteins and of their lipid-binding domains are typically solved in a soluble form, sometimes with a lipid or lipid headgroup at the binding site. To provide a detailed molecular view of PMP interactions with the membrane, computational methods such as molecular dynamics (MD) simulations can be applied. Here, we outline recent attempts to characterise these binding interactions, focusing on both intracellular proteins, such as phosphatidylinositol phosphate (PIP)-binding domains, and extracellular proteins such as glycolipid-binding bacterial exotoxins. We compare methods used to identify and analyse lipid-binding sites from simulation data and highlight recent work characterising the energetics of these interactions using free energy calculations. We describe how improvements in methodologies and computing power will help MD simulations to continue to contribute to this field in the future.

PIP2-induced membrane binding of the vinculin tail competes with its other binding partners

Vinculin plays a key role during the first phase of focal adhesion formation and interacts with the plasma membrane through specific binding of its tail domain to the lipid phosphatidylinositol 4,5-bisphosphate (PIP₂). Our understanding of the PIP₂-vinculin interaction has been hampered by contradictory biochemical and structural data. Here, we used a multiscale molecular dynamics simulation approach, in which unbiased coarse-grained molecular dynamics were used to generate starting structures for subsequent microsecond-long all-atom simulations. This allowed us to map the interaction of the vinculin tail with PIP₂-enriched membranes in atomistic detail. In agreement with experimental data, we have shown that membrane binding is sterically incompatible with the intramolecular interaction between vinculin's head and tail domain. Our simulations further confirmed biochemical and structural results, which identified two positively charged surfaces, the basic collar and the basic ladder, as the main PIP₂ interaction sites. By introducing a valency-disaggregated binding network analysis, we were able to map the protein-lipid interactions in unprecedented detail. In contrast to the basic collar, in which PIP₂ is specifically recognized by an up to hexavalent binding pocket, the basic ladder forms a series of low-valency binding sites. Importantly, many of these PIP₂ binding residues are also involved in maintaining vinculin in a closed, autoinhibited conformation. These findings led us to propose a molecular mechanism for the coupling between vinculin activation and membrane binding. Finally, our refined binding site suggests an allosteric relationship between PIP₂ and F-actin binding that disfavors simultaneous interaction with both ligands, despite nonoverlapping binding sites.

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

Estimating the accuracy of the MARTINI model towards the investigation of peripheral protein–membrane interactions

In this article, we investigate the ability of the MARTINI CG force field, specifically the 3 open-beta version, to reproduce known experimental observations regarding the membrane binding behavior of 12 peripheral membrane proteins and peptides.

Advances in understanding and in multi-disciplinary methodology used to assess lipid regulation of signalling cascades from the cancer cell plasma membrane

The lipid bilayer is a functional component of cells, forming a stable platform for the initiation of key biological processes, including cell signalling. There are distinct changes in the lipid composition of cell membranes during oncogenic transformation resulting in aberrant activation and inactivation of signalling transduction pathways. Studying the role of the cell membrane in cell signalling is challenging, since techniques are often limited to by timescale, resolution, sensitivity, and averaging. To overcome these limitations, combining 'computational', 'wet-lab' and 'semi-dry' approaches offers the best opportunity to resolving complex biological processes involved in membrane organisation. In this review, we highlight analytical tools that have been applied for the study of cell signalling initiation from the cancer cell membranes through computational microscopy, biological assays, and membrane biophysics. The cancer therapeutic potential of extracellular membrane-modulating agents, such as cholesterol-reducing agents is also discussed, as is the need for future collaborative inter-disciplinary research for studying the role of the cell membrane and its components in cancer therapy.

Capturing Choline-Aromatics Cation-π Interactions in the MARTINI Force Field

Cation−π interactions play an important role in biomolecular recognition, including interactions between membrane phosphatidylcholine lipids and aromatic amino acids of peripheral proteins. While molecular mechanics coarse grain (CG) force fields are particularly well suited to simulate membrane proteins in general, they are not parameterized to explicitly reproduce cation−π interactions. We here propose a modification of the polarizable MARTINI coarse grain (CG) model enabling it to model membrane binding events of peripheral proteins whose aromatic amino acid interactions with choline headgroups are crucial for their membrane binding. For this purpose, we first collected and curated a dataset of eight peripheral proteins from different families. We find that the MARTINI CG model expectedly underestimates aromatics–choline interactions and is unable to reproduce membrane binding of the peripheral proteins in our dataset. Adjustments of the relevant interactions in the polarizable MARTINI force field yield significant improvements in the observed binding events. The orientation of each membrane-bound protein is comparable to reference data from all-atom simulations and experimental binding data. We also use negative controls to ensure that choline–aromatics interactions are not overestimated. We finally check that membrane properties, transmembrane proteins, and membrane translocation potential of mean force (PMF) of aromatic amino acid side-chain analogues are not affected by the new parameter set. This new version “MARTINI 2.3P” is a significant improvement over its predecessors and is suitable for modeling membrane proteins including peripheral membrane binding of peptides and proteins.

Molecular Dynamics of the Association of L-Selectin and FERM Regulated by PIP2

Phosphatidylinositol 4,5-bisphosphate (PIP2) acts as a signaling lipid, mediating membrane trafficking and recruitment of proteins to membranes. A key example is the PIP2-dependent regulation of the adhesion of L-selectin to the cytoskeleton adaptors of the N-terminal subdomain of ezrin-radixin-moesin (FERM). The molecular details of the mediating behavior of multivalent anionic PIP2 lipids in this process, however, remain unclear. Here, we use coarse-grained molecular dynamics simulation to explore the mechanistic details of PIP2 in the transformation, translocation, and association of the FERM/L-selectin complex. We compare membranes of different compositions and find that anionic phospholipids are necessary for both FERM and the cytoplasmic domain of L-selectin to absorb on the membrane surface. The subsequent formation of the FERM/L-selectin complex is strongly favored by the presence of PIP2, which clusters around both proteins and triggers a conformational transition in the cytoplasmic domain of L-selectin. We are able to quantify the effect of PIP2 on the association free energy of the complex by means of a potential of mean force. We conclude that PIP2 behaves as an adhesive agent to enhance the stability of the FERM/L-selectin complex and identify key residues involved. The molecular information revealed in this study highlights the specific role of membrane lipids such as PIP2 in protein translocation and potential signaling.

Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation

The cellular membrane constitutes one of the most fundamental compartments of a living cell, where key processes such as selective transport of material and exchange of information between the cell and its environment are mediated by proteins that are closely associated with the membrane. The heterogeneity of lipid composition of biological membranes and the effect of lipid molecules on the structure, dynamics, and function of membrane proteins are now widely recognized. Characterization of these functionally important lipid-protein interactions with experimental techniques is however still prohibitively challenging. Molecular dynamics (MD) simulations offer a powerful complementary approach with sufficient temporal and spatial resolutions to gain atomic-level structural information and energetics on lipid-protein interactions. In this review, we aim to provide a broad survey of MD simulations focusing on exploring lipid-protein interactions and characterizing lipid-modulated protein structure and dynamics that have been successful in providing novel insight into the mechanism of membrane protein function.

Structural mechanism for Bruton's tyrosine kinase activation at the cell membrane

Bruton’s tyrosine kinase (Btk) activation on the cell membrane is critical for B cell proliferation and development, and Btk inhibition is a promising treatment for several hematologic cancers and autoimmune diseases. Here, we examine Btk activation using the results of long-timescale molecular dynamics simulations. In our simulations, Btk lipid-binding modules dimerized on the membrane in a single predominant conformation. We observed that the phospholipid PIP₃—in addition to its expected role of recruiting Btk to the membrane—allosterically mediated dimer formation and stability by binding at two novel sites. Our results provide strong evidence that PIP₃-mediated dimerization of Btk at the cell membrane is a critical step in Btk activation and suggest a potential approach to allosteric Btk inhibitor development.

Bruton’s tyrosine kinase (Btk) is critical for B cell proliferation and activation, and the development of Btk inhibitors is a vigorously pursued strategy for the treatment of various B cell malignancies. A detailed mechanistic understanding of Btk activation has, however, been lacking. Here, inspired by a previous suggestion that Btk activation might depend on dimerization of its lipid-binding PH–TH module on the cell membrane, we performed long-timescale molecular dynamics simulations of membrane-bound PH–TH modules and observed that they dimerized into a single predominant conformation. We found that the phospholipid PIP₃ stabilized the dimer allosterically by binding at multiple sites, and that the effects of PH–TH mutations on dimer stability were consistent with their known effects on Btk activity. Taken together, our simulation results strongly suggest that PIP₃-mediated dimerization of Btk at the cell membrane is a critical step in Btk activation.

DOK7V1 influences the malignant phenotype of lung cancer cells through PI3K/AKT/mTOR and FAK/paxillin signaling pathways

Downstream of tyrosine kinase 7 transcript variant 1 (DOK7V1) is a docking protein mediating signal transduction between receptors and intracellular downstream molecules. Our previous study indicated that DOK7V1 was decreased in lung cancer and its lower expression was associated with a decreased survival rate. The 5‑year overall survival rate for patients with lung cancer was 20.2 and 18.6% for high and low DOK7 expression, respectively; the 5‑year disease‑free survival rate for patients with lung cancer was 14.3 and 16.9% for high and low DOK7 expression, respectively. DOK7V1 inhibited proliferation and migration, but enhanced adhesion, of lung cancer cells. In the present study, the effect of DOK7V1 and its domains [pleckstrin homology (PH) and phosphotyrosine‑binding (PTB) domain] on the malignant phenotype and associated signaling pathway in lung cancer cells was investigated. The results indicated that truncation of DOK7V1 domains (DOK7V1Δ‑PH and DOK7V1Δ‑PTB) inhibited the proliferation and migration of lung cancer cells which exhibited the same trend as DOK7V1, whereas DOK7V1Δ‑PH and DOK7V1Δ‑PTB exhibited different functions from those of DOK7V1 in cell matrix adhesion. Consistently, DOK7V1 overexpression in lung cancer cells suppressed the phosphoinositide 3‑kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathways, but activated the focal adhesion kinase (FAK)/paxillin signaling pathway. Taken together, these results indicate that DOK7V1 may inhibit proliferation and migration via negatively regulating the PI3K/AKT/mTOR signaling pathway, and increase adhesion by upregulating the FAK/paxillin signaling pathway in lung cancer cells.

Membrane Lipid Nanodomains

Lipid membranes can spontaneously organize their components into domains of different sizes and properties. The organization of membrane lipids into nanodomains might potentially play a role in vital functions of cells and organisms. Model membranes represent attractive systems to study lipid nanodomains, which cannot be directly addressed in living cells with the currently available methods. This review summarizes the knowledge on lipid nanodomains in model membranes and exposes how their specific character contrasts with large-scale phase separation. The overview on lipid nanodomains in membranes composed of diverse lipids (e.g., zwitterionic and anionic glycerophospholipids, ceramides, glycosphingolipids) and cholesterol aims to evidence the impact of chemical, electrostatic, and geometric properties of lipids on nanodomain formation. Furthermore, the effects of curvature, asymmetry, and ions on membrane nanodomains are shown to be highly relevant aspects that may also modulate lipid nanodomains in cellular membranes. Potential mechanisms responsible for the formation and dynamics of nanodomains are discussed with support from available theories and computational studies. A brief description of current fluorescence techniques and analytical tools that enabled progress in lipid nanodomain studies is also included. Further directions are proposed to successfully extend this research to cells.

Molecular Dynamics Simulations of Membrane Proteins: An Overview

Simulations of membrane proteins have been rising in popularity in the past decade. Advancements in technology and force fields made it possible to simulate behavior of membrane proteins. Membrane protein simulations can now be used as supporting evidence for experimental findings, for elucidating protein mechanisms, and validating protein crystal structures. Unrelated to experimental data, these simulations can also serve to investigate larger scale processes like protein sorting, protein-membrane interactions, and more. In this review, the history as well as the state-of-the-art methodologies in membrane protein simulations will be summarized. An emphasis will be put on how to set up the system and on the current models for the different components of the simulation system. An overview of the available tools for membrane protein simulation will be given, and current limitations and prospects will also be discussed.

Multiscale molecular dynamics simulations of lipid interactions with P-glycoprotein in a complex membrane

P-glycoprotein (P-gp) can transport a wide range of very different hydrophobic organic molecules across the membrane. Its ability to extrude molecules from the cell creates delivery problems for drugs that target proteins in the central nervous system (CNS) and also causes drug-resistance in many forms of cancer. Whether a drug will be susceptible to export by P-gp is difficult to predict and currently this is usually assessed with empirical and/or animal models. Thus, there is a need to better understand how P-gp works at the molecular level in order to fulfil the 3Rs: Refinement, reduction and replacement of animals in research. As structural information increasingly becomes available, our understanding at the molecular level improves. Proteins like P-gp are however very dynamic entities and thus one of the most appropriate ways to study them is with molecular dynamics simulations, especially as this can capture the influence of the surrounding environment. Recent parameterization developments have meant that it is now possible to simulate lipid bilayers that more closely resemble in vivo membranes in terms of their composition. In this report we construct a complex lipid bilayer that mimics the composition of brain epithelial cells and examine the interactions of it with P-gp. We find that the negatively charged phosphatidylserine lipids in the inner leaflet of the membrane tend to form an annulus around P-gp. We also observed the interaction of cholesterol with three distinct areas of the P-gp. Potential of mean force (PMF) calculations suggest that a crevice between transmembrane helices 10 and 12 has particularly favourable interaction energy for cholesterol.

Computational and theoretical approaches for studies of a lipid recognition protein on biological membranes

Many cellular functions, including cell signaling and related events, are regulated by the association of peripheral membrane proteins (PMPs) with biological membranes containing anionic lipids, e.g., phosphatidylinositol phosphate (PIP). This association is often mediated by lipid recognition modules present in many PMPs. Here, I summarize computational and theoretical approaches to investigate the molecular details of the interactions and dynamics of a lipid recognition module, the pleckstrin homology (PH) domain, on biological membranes. Multiscale molecular dynamics simulations using combinations of atomistic and coarse-grained models yielded results comparable to those of actual experiments and could be used to elucidate the molecular mechanisms of the formation of protein/lipid complexes on membrane surfaces, which are often difficult to obtain using experimental techniques. Simulations revealed some modes of membrane localization and interactions of PH domains with membranes in addition to the canonical binding mode. In the last part of this review, I address the dynamics of PH domains on the membrane surface. Local PIP clusters formed around the proteins exhibit anomalous fluctuations. This dynamic change in protein-lipid interactions cause temporally fluctuating diffusivity of proteins, i.e., the short-term diffusivity of the bound protein changes substantially with time, and may in turn contribute to the formation/dissolution of protein complexes in membranes.

Multiscale molecular dynamics simulations of lipid interactions with P-glycoprotein in a complex membrane

P-glycoprotein (P-gp) can transport a wide range of very different hydrophobic organic molecules across the membrane. Its ability to extrude molecules from the cell creates delivery problems for drugs that target proteins in the central nervous system (CNS) and also causes drug-resistance in many forms of cancer. Whether a drug will be susceptible to export by P-gp is difficult to predict and currently this is usually assessed with empirical and/or animal models. Thus, there is a need to better understand how P-gp works at the molecular level in order to fulfil the 3Rs: Refinement, reduction and replacement of animals in research. As structural information increasingly becomes available, our understanding at the molecular level improves. Proteins like P-gp are however very dynamic entities and thus one of the most appropriate ways to study them is with molecular dynamics simulations, especially as this can capture the influence of the surrounding environment. Recent parameterization developments have meant that it is now possible to simulate lipid bilayers that more closely resemble in vivo membranes in terms of their composition. In this report we construct a complex lipid bilayer that mimics the composition of brain epithelial cells and examine the interactions of it with P-gp. We find that the negatively charged phosphatidylserine lipids in the inner leaflet of the membrane tend to form an annulus around P-gp. We also observed the interaction of cholesterol with three distinct areas of the P-gp. Potential of mean force (PMF) calculations suggest that a crevice between transmembrane helices 10 and 12 has particularly favourable interaction energy for cholesterol.