Conformational Changes in the Epidermal Growth Factor Receptor: Role of the Transmembrane Domain Investigated by Coarse-Grained MetaDynamics Free Energy Calculations

Machine Learning Derived Collective Variables for the Study of Protein Homodimerization in Membrane

The accurate calculation of equilibrium constants for protein-protein association is of fundamental importance to quantitative biology and remains an outstanding challenge for computational biophysics. Traditionally, equilibrium constants have been computed from one-dimensional free energy surfaces derived from sampling along a single collective variable. Importantly, recent advances in enhanced sampling methodology have facilitated the characterization of multidimensional free energy landscapes, often exposing multiple thermodynamically important minima missed by more restrictive sampling methods. A key to the effectiveness of this multidimensional sampling approach is the identification of collective variables that effectively define the configurational space of dissociated and associated states. Here we present the application of two machine learning methods for the unbiased determination of collective variables for enhanced sampling and analysis of protein-protein association. Our results both validate prior work, based on intuition derived collective variables, and demonstrate the effectiveness of the machine learning methods for the identification of collective variables for association reactions in complex biomolecular systems.

Drug-resistant EGFR mutations promote lung cancer by stabilizing interfaces in ligand-free kinase-active EGFR oligomers

The Epidermal Growth Factor Receptor (EGFR) is frequently found to be mutated in non-small cell lung cancer. Oncogenic EGFR has been successfully targeted by tyrosine kinase inhibitors, but acquired drug resistance eventually overcomes the efficacy of these treatments. Attempts to surmount this therapeutic challenge are hindered by a poor understanding of how and why cancer mutations specifically amplify ligand-independent EGFR auto-phosphorylation signals to enhance cell survival and how this amplification is related to ligand-dependent cell proliferation. Here we show that drug-resistant EGFR mutations manipulate the assembly of ligand-free, kinase-active oligomers to promote and stabilize the assembly of oligomer-obligate active dimer sub-units and circumvent the need for ligand binding. We reveal the structure and assembly mechanisms of these ligand-free, kinase-active oligomers, uncovering oncogenic functions for hitherto orphan transmembrane and kinase interfaces, and for the ectodomain tethered conformation of EGFR. Importantly, we find that the active dimer sub-units within ligand-free oligomers are the high affinity binding sites competent to bind physiological ligand concentrations and thus drive tumor growth, revealing a link with tumor proliferation. Our findings provide a framework for future drug discovery directed at tackling oncogenic EGFR mutations by disabling oligomer-assembling interactions.

T-cell virtuosity in ''knowing thyself"

Major Histocompatibility Complex (MHC) I and II and the αβ T-cell antigen receptor (TCRαβ) govern fundamental traits of adaptive immunity. They form a membrane-borne ligand-receptor system weighing host proteome integrity to detect contamination by nonself proteins. MHC-I and -II exhibit the "MHC-fold", which is able to bind a large assortment of short peptides as proxies for self and nonself proteins. The ensuing varying surfaces are mandatory ligands for Ig-like TCRαβ highly mutable binding sites. Conserved molecular signatures guide TCRαβ ligand binding sites to focus on the MHC-fold (MHC-restriction) while leaving many opportunities for its most hypervariable determinants to contact the peptide. This riveting molecular strategy affords many options for binding energy compatible with specific recognition and signalling aimed to eradicated microbial pathogens and cancer cells. While the molecular foundations of αβ T-cell adaptive immunity are largely understood, uncertainty persists on how peptide-MHC binding induces the TCRαβ signals that instruct cell-fate decisions. Solving this mystery is another milestone for understanding αβ T-cells' self/nonself discrimination. Recent developments revealing the innermost links between TCRαβ structural dynamics and signalling modality should help dissipate this long-sought-after enigma.

Standard Binding Free-Energy Calculations: How Far Are We from Automation?

Recent success stories suggest that in silico protein-ligand binding free-energy calculations are approaching chemical accuracy. However, their widespread application remains limited by the extensive human intervention required, posing challenges for the neophyte. As such, it is critical to develop automated workflows for estimating protein-ligand binding affinities with minimum personal involvement. Key human efforts include setting up and tuning enhanced-sampling or alchemical-transformation algorithms as a preamble to computational binding free-energy estimations. Additionally, preparing input files, bookkeeping, and postprocessing represent nontrivial tasks. In this Perspective, we discuss recent progress in automating standard binding free-energy calculations, featuring the development of adaptive or parameter-free algorithms, standardization of binding free-energy calculation workflows, and the implementation of user-friendly software. We also assess the current state of automated standard binding free-energy calculations and evaluate the limitations of existing methods. Last, we outline the requirements for future algorithms and workflows to facilitate automated free-energy calculations for diverse protein-ligand complexes.

Structural basis of dimerization of chemokine receptors CCR5 and CXCR4

G protein-coupled receptors (GPCRs) are prominent drug targets responsible for extracellular-to-intracellular signal transduction. GPCRs can form functional dimers that have been poorly characterized so far. Here, we show the dimerization mechanism of the chemokine receptors CCR5 and CXCR4 by means of an advanced free-energy technique named coarse-grained metadynamics. Our results reproduce binding events between the GPCRs occurring in the minute timescale, revealing a symmetric and an asymmetric dimeric structure for each of the three investigated systems, CCR5/CCR5, CXCR4/CXCR4, and CCR5/CXCR4. The transmembrane helices TM4-TM5 and TM6-TM7 are the preferred binding interfaces for CCR5 and CXCR4, respectively. The identified dimeric states differ in the access to the binding sites of the ligand and G protein, indicating that dimerization may represent a fine allosteric mechanism to regulate receptor activity. Our study offers structural basis for the design of ligands able to modulate the formation of CCR5 and CXCR4 dimers and in turn their activity, with therapeutic potential against HIV, cancer, and immune-inflammatory diseases.

The role of structural heterogeneity in the homodimerization of transmembrane proteins

The equilibrium association of transmembrane proteins plays a fundamental role in membrane protein function and cellular signaling. While the study of the equilibrium binding of single pass transmembrane proteins has received significant attention in experiment and simulation, the accurate assessment of equilibrium association constants remains a challenge to experiment and simulation. In experiment, there remain wide variations in association constants derived from experimental studies of the most widely studied transmembrane proteins. In simulation, state-of-the art methods have failed to adequately sample the thermodynamically relevant structures of the dimer state ensembles using coarse-grained models. In addition, all-atom force fields often fail to accurately assess the relative free energies of the dimer and monomer states. Given the importance of this fundamental biophysical process, it is essential to address these shortcomings. In this work, we establish an effective computational protocol for the calculation of equilibrium association constants for transmembrane homodimer formation. A set of transmembrane protein homodimers, used in the parameterization of the MARTINI v3 force field, are simulated using metadynamics, based on three collective variables. The method is found to be accurate and computationally efficient, providing a standard to be used in the future simulation studies using coarse-grained or all-atom models.

How Neuromembrane Lipids Modulate Membrane Proteins: Insights from G-Protein-Coupled Receptors (GPCRs) and Receptor Tyrosine Kinases (RTKs)

Lipids play a diverse and critical role in cellular processes in all tissues. The unique lipid composition of nerve membranes is particularly interesting because it contains, among other things, polyunsaturated lipids, such as docosahexaenoic acid, which the body only gets through the diet. The crucial role of lipids in neurological processes, especially in receptor-mediated cell signaling, is emphasized by the fact that in many neuropathological diseases there are significant deviations in the lipid composition of nerve membranes compared to healthy individuals. The lipid composition of neuromembranes can significantly affect the function of receptors by regulating the physical properties of the membrane or by affecting specific interactions between receptors and lipids. In addition, it is worth noting that the ligand-binding pocket of many receptors is located inside the cell membrane, due to which lipids can even modulate the binding of ligands to their receptors. These mechanisms highlight the importance of lipids in the regulation of membrane receptor activation and function. In this article, we focus on two major protein families: G-protein-coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs) and discuss how lipids affect their function in neuronal membranes, elucidating the basic mechanisms underlying neuronal function and dysfunction.

Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-Friendliness

Computational techniques applied to drug discovery have gained considerable popularity for their ability to filter potentially active drugs from inactive ones, reducing the time scale and costs of preclinical investigations. The main focus of these studies has historically been the search for compounds endowed with high affinity for a specific molecular target to ensure the formation of stable and long-lasting complexes. Recent evidence has also correlated the in vivo drug efficacy with its binding kinetics, thus opening new fascinating scenarios for ligand/protein binding kinetic simulations in drug discovery. The present article examines the state of the art in the field, providing a brief summary of the most popular and advanced ligand/protein binding kinetics techniques and evaluating their current limitations and the potential solutions to reach more accurate kinetic models. Particular emphasis is put on the need for a paradigm change in the present methodologies toward ligand and protein parametrization, the force field problem, characterization of the transition states, the sampling issue, and algorithms' performance, user-friendliness, and data openness.

Allosteric inhibition of the epidermal growth factor receptor through disruption of transmembrane interactions

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase (RTK) commonly targeted for inhibition by anticancer therapeutics. Current therapeutics target EGFR's kinase domain or extracellular region. However, these types of inhibitors are not specific for tumors over healthy tissue and therefore cause undesirable side effects. Our lab has recently developed a new strategy to regulate RTK activity by designing a peptide that specifically binds to the transmembrane (TM) region of the RTK to allosterically modify kinase activity. These peptides are acidity-responsive, allowing them to preferentially target acidic environments like tumors. We have applied this strategy to EGFR and created the PET1 peptide. We observed that PET1 behaves as a pH-responsive peptide that modulates the configuration of the EGFR TM through a direct interaction. Our data indicated that PET1 inhibits EGFR-mediated cell migration. Finally, we investigated the mechanism of inhibition through molecular dynamics simulations, which showed that PET1 sits between the two EGFR TM helices; this molecular mechanism was additionally supported by AlphaFold-Multimer predictions. We propose that the PET1-induced disruption of native TM interactions disturbs the conformation of the kinase domain in such a way that it inhibits EGFR's ability to send migratory cell signals. This study is a proof-of-concept that acidity-responsive membrane peptide ligands can be generally applied to RTKs. In addition, PET1 constitutes a viable approach to therapeutically target the TM of EGFR.

Into the dynamics of rotaxanes at atomistic resolution

Mechanically-interlocked molecules (MIMs) are at the basis of artificial molecular machines and are attracting increasing interest for various applications, from catalysis to drug delivery and nanoelectronics. MIMs are composed of mechanically-interconnected molecular sub-parts that can move with respect to each other, imparting these systems innately dynamical behaviors and interesting stimuli-responsive properties. The rational design of MIMs with desired functionalities requires studying their dynamics at sub-molecular resolution and on relevant timescales, which is challenging experimentally and computationally. Here, we combine molecular dynamics and metadynamics simulations to reconstruct the thermodynamics and kinetics of different types of MIMs at atomistic resolution under different conditions. As representative case studies, we use rotaxanes and molecular shuttles substantially differing in structure, architecture, and dynamical behavior. Our computational approach provides results in agreement with the available experimental evidence and a direct demonstration of the critical effect of the solvent on the dynamics of the MIMs. At the same time, our simulations unveil key factors controlling the dynamics of these systems, providing submolecular-level insights into the mechanisms and kinetics of shuttling. Reconstruction of the free-energy profiles from the simulations reveals details of the conformations of macrocycles on the binding site that are difficult to access via routine experiments and precious for understanding the MIMs' behavior, while their decomposition in enthalpic and entropic contributions unveils the mechanisms and key transitions ruling the intermolecular movements between metastable states within them. The computational framework presented herein is flexible and can be used, in principle, to study a variety of mechanically-interlocked systems.

Transmembrane dimers of type 1 receptors sample alternate configurations: MD simulations using coarse grain Martini 3 versus AlphaFold2 Multimer

Structures and dynamics of transmembrane (TM) receptor regions are key to understanding their signaling mechanism across membranes. Here we examine configurations of TM region dimers, assembled using the recent Martini 3 force field for coarse-grain (CG) molecular dynamics simulations. At first glance, our results show only a reasonable agreement with ab initio predictions using PREDDIMER and AlphaFold2 Multimer and with nuclear magnetic resonance (NMR)-derived structures. 5 of 11 CG TM structures are similar to the NMR structures (within <3.5 Å root-mean-square deviation [RMSD]) compared with 10 and 9 using PREDDIMER and AlphaFold2, respectively (with 8 structures of the later within 1.5 Å). Surprisingly, AlphaFold2 predictions are closer to NMR structures when the 2001 instead of 2020 database is used for training. The CG simulations reveal that alternative configurations of TM dimers readily interconvert with a predominant population. The implications for transmembrane signaling are discussed, including for the development of peptide-based pharmaceuticals.

Elucidating activation and deactivation dynamics of VEGFR-2 transmembrane domain with coarse-grained molecular dynamics simulations

The vascular endothelial growth factor receptor 2 (VEGFR-2) is a member of receptor tyrosine kinases (RTKs) and is a dimeric membrane protein that functions as a primary regulator of angiogenesis. As is usual with RTKs, spatial alignment of its transmembrane domain (TMD) is essential toward VEGFR-2 activation. Experimentally, the helix rotations within TMD around their own helical axes are known to participate importantly toward the activation process in VEGFR-2, but the detailed dynamics of the interconversion between the active and inactive TMD forms have not been clearly elucidated at the molecular level. Here, we attempt to elucidate the process by using coarse grained (CG) molecular dynamics (MD) simulations. We observe that inactive dimeric TMD in separation is structurally stable over tens of microseconds, suggesting that TMD itself is passive and does not allow spontaneous signaling of VEGFR-2. By starting from the active conformation, we reveal the mechanism of TMD inactivation through analyzing the CG MD trajectories. We observe that interconversions between a left-handed overlay and a right-handed one are essential for the process of going from an active TMD structure to the inactive form. In addition, our simulations find that the helices can rotate properly when the overlaying structure of the helices interconverts and when the crossing angle of the two helices changes by larger than ~40 degrees. As the activation right after the ligand attachment on VEGFR-2 will take place in the reverse manner of this inactivation process, these structural aspects will also appear importantly for the activation process. The rather large change in helix configuration for activation also explains why VEGFR-2 rarely self-activate and how the activating ligand structurally drive the whole VEGFR-2. This mechanism of TMD activation / inactivation within VEGFR-2 may help in further understanding the overall activation processes of other RTKs.

Transferring chemical and energetic knowledge between molecular systems with machine learning

Predicting structural and energetic properties of a molecular system is one of the fundamental tasks in molecular simulations, and it has applications in chemistry, biology, and medicine. In the past decade, the advent of machine learning algorithms had an impact on molecular simulations for various tasks, including property prediction of atomistic systems. In this paper, we propose a novel methodology for transferring knowledge obtained from simple molecular systems to a more complex one, endowed with a significantly larger number of atoms and degrees of freedom. In particular, we focus on the classification of high and low free-energy conformations. Our approach relies on utilizing (i) a novel hypergraph representation of molecules, encoding all relevant information for characterizing multi-atom interactions for a given conformation, and (ii) novel message passing and pooling layers for processing and making free-energy predictions on such hypergraph-structured data. Despite the complexity of the problem, our results show a remarkable Area Under the Curve of 0.92 for transfer learning from tri-alanine to the deca-alanine system. Moreover, we show that the same transfer learning approach can also be used in an unsupervised way to group chemically related secondary structures of deca-alanine in clusters having similar free-energy values. Our study represents a proof of concept that reliable transfer learning models for molecular systems can be designed, paving the way to unexplored routes in prediction of structural and energetic properties of biologically relevant systems.

The guidance and adhesion protein FLRT2 dimerizes in cis via dual small-X3-small transmembrane motifs

Fibronectin Leucine-rich Repeat Transmembrane (FLRT 1-3) proteins are a family of broadly expressed single-spanning transmembrane receptors that play key roles in development. Their extracellular domains mediate homotypic cell-cell adhesion and heterotypic protein interactions with other receptors to regulate cell adhesion and guidance. These in trans FLRT interactions determine the formation of signaling complexes of varying complexity and function. Whether FLRTs also interact at the surface of the same cell, in cis, remains unknown. Here, molecular dynamics simulations reveal two dimerization motifs in the FLRT2 transmembrane helix. Single particle tracking experiments show that these Small-X₃-Small motifs synergize with a third dimerization motif encoded in the extracellular domain to permit the cis association and co-diffusion patterns of FLRT2 receptors on cells. These results may point to a competitive switching mechanism between in cis and in trans interactions, which suggests that homotypic FLRT interaction mirrors the functionalities of classic adhesion molecules.

Threonine phosphorylation regulates the molecular assembly and signaling of EGFR in cooperation with membrane lipids

The cytoplasmic domain of the receptor tyrosine kinases (RTKs) plays roles as a phosphorylation enzyme and a protein scaffold but the allocation of these two functions is not fully understood. We here analyzed assembly of the transmembrane (TM)-juxtamembrane (JM) region of EGFR, one of the best studied species of RTKs, by combining single-pair FRET imaging and a nanodisc technique. The JM domain of EGFR contains a threonine residue (Thr654) that is phosphorylated after ligand association. We observed that the TM-JM peptides of EGFR form anionic lipid-induced dimers and cholesterol-induced oligomers. The two forms involve distinct molecular interactions, with a bias towards oligomer formation upon threonine phosphorylation. We further analyzed the functions and oligomerization of whole EGFR molecules, with or without a substitution of Thr654 to alanine, in living cells. The results suggested an autoregulatory mechanism in which Thr654 phosphorylation causes a switch of the major function of EGFR from kinase activation dimers to scaffolding oligomers.

Ligand-induced transmembrane conformational coupling in monomeric EGFR

Single pass cell surface receptors regulate cellular processes by transmitting ligand-encoded signals across the plasma membrane via changes to their extracellular and intracellular conformations. This transmembrane signaling is generally initiated by ligand binding to the receptors in their monomeric form. While subsequent receptor-receptor interactions are established as key aspects of transmembrane signaling, the contribution of monomeric receptors has been challenging to isolate due to the complexity and ligand-dependence of these interactions. By combining membrane nanodiscs produced with cell-free expression, single-molecule Förster Resonance Energy Transfer measurements, and molecular dynamics simulations, we report that ligand binding induces intracellular conformational changes within monomeric, full-length epidermal growth factor receptor (EGFR). Our observations establish the existence of extracellular/intracellular conformational coupling within a single receptor molecule. We implicate a series of electrostatic interactions in the conformational coupling and find the coupling is inhibited by targeted therapeutics and mutations that also inhibit phosphorylation in cells. Collectively, these results introduce a facile mechanism to link the extracellular and intracellular regions through the single transmembrane helix of monomeric EGFR, and raise the possibility that intramolecular transmembrane conformational changes upon ligand binding are common to single-pass membrane proteins.

Lipid-Mediated Association of the Slg1 Transmembrane Domains in Yeast Plasma Membranes

Clustering of transmembrane proteins underlies a multitude of fundamental biological processes at the plasma membrane (PM) such as receptor activation, lateral domain formation, and mechanotransduction. The self-association of the respective transmembrane domains (TMDs) has also been suggested to be responsible for the micron-scaled patterns seen for integral membrane proteins in the budding yeast PM. However, the underlying interplay between the local lipid composition and the TMD identity is still not mechanistically understood. In this work, we combined coarse-grained molecular dynamics simulations of simplified bilayer systems with high-resolution live-cell microscopy to analyze the distribution of a representative helical yeast TMD from the PM sensor Slg1 within different lipid environments. In our simulations, we specifically evaluated the effects of acyl chain saturation and anionic lipid head groups on the association of two TMDs. We found that weak lipid-protein interactions significantly affect the configuration of TMD dimers and the free energy of association. Increased amounts of unsaturated phospholipids (PLs) strongly reduced the helix-helix interaction, while the presence of anionic phosphatidylserine (PS) hardly affected the dimer formation. We could experimentally confirm this surprising lack of effect of PS using the network factor, a mesoscopic measure of PM pattern formation in yeast cells. Simulations also showed that the formation of TMD dimers in turn increased the order parameter of the surrounding lipids and induced long-range perturbations in lipid organization. In summary, our results shed new light on the mechanisms of lipid-mediated dimerization of TMDs in complex lipid mixtures.

SPICA Force Field for Proteins and Peptides

A coarse-grained (CG) model for peptides and proteins was developed as an extension of the Surface Property fItting Coarse grAined (SPICA) force field (FF). The model was designed to examine membrane proteins that are fully compatible with the lipid membranes of the SPICA FF. A preliminary version of this protein model was created using thermodynamic properties, including the surface tension and density in the SPICA (formerly called SDK) FF. In this study, we improved the CG protein model to facilitate molecular dynamics (MD) simulations with a reproduction of multiple properties from both experiments and all-atom (AA) simulations. An elastic network model was adopted to maintain the secondary structure within a single chain. The side-chain analogues reproduced the transfer free energy profiles across the lipid membrane and demonstrated reasonable association free energy (potential of mean force) in water compared to those from AA MD. A series of peptides/proteins adsorbed onto or penetrated into the membrane simulated by the CG MD correctly predicted the penetration depths and tilt angles of peripheral and transmembrane peptides/proteins as comparable to those in the orientations of proteins in membranes (OPM) database. In addition, the dimerization free energies of several transmembrane helices within a lipid bilayer were comparable to those from experimental estimation. Application studies on a series of membrane protein assemblies, scramblases, and poliovirus capsids demonstrated the good performance of the SPICA FF.

It Takes More than Two to Tango: Complex, Hierarchal, and Membrane-Modulated Interactions in the Regulation of Receptor Tyrosine Kinases

The search for an understanding of how cell fate and motility are regulated is not a purely scientific undertaking, but it can also lead to rationally designed therapies against cancer. The discovery of tyrosine kinases about half a century ago, the subsequent characterization of certain transmembrane receptors harboring tyrosine kinase activity, and their connection to the development of human cancer ushered in a new age with the hope of finding a treatment for malignant diseases in the foreseeable future. However, painstaking efforts were required to uncover the principles of how these receptors with intrinsic tyrosine kinase activity are regulated. Developments in molecular and structural biology and biophysical approaches paved the way towards better understanding of these pathways. Discoveries in the past twenty years first resulted in the formulation of textbook dogmas, such as dimerization-driven receptor association, which were followed by fine-tuning the model. In this review, the role of molecular interactions taking place during the activation of receptor tyrosine kinases, with special attention to the epidermal growth factor receptor family, will be discussed. The fact that these receptors are anchored in the membrane provides ample opportunities for modulatory lipid-protein interactions that will be considered in detail in the second part of the manuscript. Although qualitative and quantitative alterations in lipids in cancer are not sufficient in their own right to drive the malignant transformation, they both contribute to tumor formation and also provide ways to treat cancer. The review will be concluded with a summary of these medical aspects of lipid-protein interactions.

Structural Insight and Development of EGFR Tyrosine Kinase Inhibitors

Lung cancer has a high prevalence, with a growing number of new cases and mortality every year. Furthermore, the survival rate of patients with non-small-cell lung carcinoma (NSCLC) is still quite low in the majority of cases. Despite the use of conventional therapy such as tyrosine kinase inhibitor for Epidermal Growth Factor Receptor (EGFR), which is highly expressed in most NSCLC cases, there was still no substantial improvement in patient survival. This is due to the drug’s ineffectiveness and high rate of resistance among individuals with mutant EGFR. Therefore, the development of new inhibitors is urgently needed. Understanding the EGFR structure, including its kinase domain and other parts of the protein, and its activation mechanism can accelerate the discovery of novel compounds targeting this protein. This study described the structure of the extracellular, transmembrane, and intracellular domains of EGFR. This was carried out along with identifying the binding pose of commercially available inhibitors in the ATP-binding and allosteric sites, thereby clarifying the research gaps that can be filled. The binding mechanism of inhibitors that have been used clinically was also explained, thereby aiding the structure-based development of new drugs.

Tracking the Amide I and αCOO- Terminal ν(C=O) Raman Bands in a Family of l-Glutamic Acid-Containing Peptide Fragments: A Raman and DFT Study

The E-hook of β-tubulin plays instrumental roles in cytoskeletal regulation and function. The last six C-terminal residues of the βII isotype, a peptide of amino acid sequence EGEDEA, extend from the microtubule surface and have eluded characterization with classic X-ray crystallographic techniques. The band position of the characteristic amide I vibration of small peptide fragments is heavily dependent on the length of the peptide chain, the extent of intramolecular hydrogen bonding, and the overall polarity of the fragment. The dependence of the E residue's amide I ν(C=O) and the αCOO- terminal ν(C=O) bands on the neighboring side chain, the length of the peptide fragment, and the extent of intramolecular hydrogen bonding in the structure are investigated here via the EGEDEA peptide. The hexapeptide is broken down into fragments increasing in size from dipeptides to hexapeptides, including EG, ED, EA, EGE, EDE, DEA, EGED, EDEA, EGEDE, GEDEA, and, finally, EGEDEA, which are investigated with experimental Raman spectroscopy and density functional theory (DFT) computations to model the zwitterionic crystalline solids (in vacuo). The molecular geometries and Boltzmann sum of the simulated Raman spectra for a set of energetic minima corresponding to each peptide fragment are computed with full geometry optimizations and corresponding harmonic vibrational frequency computations at the B3LYP/6-311++G(2df,2pd) level of theory. In absence of the crystal structure, geometry sampling is performed to approximate solid phase behavior. Natural bond order (NBO) analyses are performed on each energetic minimum to quantify the magnitude of the intramolecular hydrogen bonds. The extent of the intramolecular charge transfer is dependent on the overall polarity of the fragment considered, with larger and more polar fragments exhibiting the greatest extent of intramolecular charge transfer. A steady blue shift arises when considering the amide I band position moving linearly from ED to EDE to EDEA to GEDEA and, finally, to EGEDEA. However, little variation is observed in the αCOO- ν(C=O) band position in this family of fragments.

Conformational plasticity and dynamic interactions of the N-terminal domain of the chemokine receptor CXCR1

The dynamic interactions between G protein-coupled receptors (GPCRs) and their cognate protein partners are central to several cell signaling pathways. For example, the association of CXC chemokine receptor 1 (CXCR1) with its cognate chemokine, interleukin-8 (IL8 or CXCL8) initiates pathways leading to neutrophil-mediated immune responses. The N-terminal domain of chemokine receptors confers ligand selectivity, but unfortunately the conformational dynamics of this intrinsically disordered region remains unresolved. In this work, we have explored the interaction of CXCR1 with IL8 by microsecond time scale coarse-grain simulations, complemented by atomistic models and NMR chemical shift predictions. We show that the conformational plasticity of the apo-receptor N-terminal domain is restricted upon ligand binding, driving it to an open C-shaped conformation. Importantly, we corroborated the dynamic complex sampled in our simulations against chemical shift perturbations reported by previous NMR studies and show that the trends are similar. Our results indicate that chemical shift perturbation is often not a reporter of residue contacts in such dynamic associations. We believe our results represent a step forward in devising a strategy to understand intrinsically disordered regions in GPCRs and how they acquire functionally important conformational ensembles in dynamic protein-protein interfaces.

Thermodynamics and Free Energy Landscape of BAR-Domain Dimerization from Molecular Simulations

Proteins with BAR domains function to bind to and remodel biological membranes, where the dimerization of BAR domains is a key step in this function. These domains can dimerize in solution or after localizing to the membrane surface. Here, we characterize the binding thermodynamics of homodimerization between the LSP1 BAR domain proteins in solution, using molecular dynamics (MD) simulations. By combining the MARTINI coarse-grained protein models with enhanced sampling through metadynamics, we construct a two-dimensional free energy surface quantifying the bound versus unbound ensembles as a function of two distance variables. With this methodology, our simulations can simultaneously characterize the structures and relative stabilities of a range of sampled dimers, portraying a heterogeneous and extraordinarily stable bound ensemble, where the proper crystal structure dimer is the most stable in a 100 mM NaCl solution. Nonspecific dimers that are sampled involve contacts that are consistent with experimental structures of higher-order oligomers formed by the LSP1 BAR domain. Because the BAR dimers and oligomers can assemble on membranes, we characterize the relative alignment of the known membrane binding patches, finding that only the specific dimer is aligned to form strong interactions with the membrane. Hence, we would predict a strong selection of the specific dimer in binding to or assembling when on the membrane. Establishing the pairwise stabilities of homodimer contacts is difficult experimentally when the proteins form stable oligomers, but through the method used here, we can isolate these contacts, providing a foundation to study the same interactions on the membrane.

Perspectives on High-Throughput Ligand/Protein Docking With Martini MD Simulations

Molecular docking is central to rational drug design. Current docking techniques suffer, however, from limitations in protein flexibility and solvation models and by the use of simplified scoring functions. All-atom molecular dynamics simulations, on the other hand, feature a realistic representation of protein flexibility and solvent, but require knowledge of the binding site. Recently we showed that coarse-grained molecular dynamics simulations, based on the most recent version of the Martini force field, can be used to predict protein/ligand binding sites and pathways, without requiring any a priori information, and offer a level of accuracy approaching all-atom simulations. Given the excellent computational efficiency of Martini, this opens the way to high-throughput drug screening based on dynamic docking pipelines. In this opinion article, we sketch the roadmap to achieve this goal.

Cholesterols Work as a Molecular Regulator of the Antimicrobial Peptide-Membrane Interactions

The existing cholesterols (Chols) in animal cell membranes play key roles in many fundamental cellular processes, which also promise the possibility to modulate the bioactivity of various membrane-active biomacromolecules. Here, combining dynamic giant unilamellar vesicle leakage experiments and molecular dynamics simulations, the inhibitory effect of Chols on the membrane poration activity of melittin (Mel), a typical natural antimicrobial peptide, is demonstrated. Molecular details of the Mel-Chol interactions in membrane show that, for a Chol-contained lipid membrane, Mel exposure would perturb the symmetric bilayer structure of the membrane and specifically influence the location and orientation distributions of Chol molecules to an asymmetric state between the two leaflets; moreover, the Mel-Chol interactions are significantly influenced by the membrane environment such as unsaturation degree of the lipid components. Such inhibitory effect is normally ascribed to an accumulation of Chol molecules around the membrane-bound peptide chains and formation of Chol-Mel complexes in the membrane, which hinder the further insertion of peptides into the membrane. This work clarifies the molecular interactions between membrane-active peptides and Chol-contained membranes, and suggest the possibility to develop targeted drugs due to the membrane component specificity between bacterial and animal cells.

Role of Cholesterol in Transmembrane Dimerization of the ErbB2 Growth Factor Receptor

The association of ErbB2 growth factor receptors is critical for cell growth and potentiates tumor proliferation in several cancer types. An important aspect in ErbB2 association is the role of lipids such as cholesterol, especially since their metabolism is often reprogrammed in cancer cells. Here, we have coupled metadynamics with coarse-grain simulations to identify cholesterol effects in the transmembrane dimerization of ErbB2 receptors. Overall, cholesterol interactions are observed with the receptor that directly tunes the association energetics. Several dimer conformations are identified both in the presence and absence of cholesterol, although the dimer regime appears to be more favorable in the presence of cholesterol. We observe an overall modulation of the underlying energy profile and the symmetric active and inactive conformational states are not distinguished in the presence of cholesterol. We show that cholesterol binds to the receptor transmembrane domain at a site (CRAC motif) that overlaps with the dimer interface (SmXXXSm motif). The competition between the transmembrane interactions and cholesterol interactions decides the final conformational landscape. Our work is an important step toward characterizing cholesterol effects in ErbB2 membrane receptor function.

Predicting the aptamer SYL3C-EpCAM complex's structure with the Martini-based simulation protocol

Aptamers (small single strand DNA/RNAs) such as SYL3C are considered as ideal alternatives to antibodies in cancer related research studies. However, 3D structure predictions for aptamers and aptamer-protein complexes are scarce due to the high cost of experimental measurements and unreliable computer-based methods. Thus aptamers' diagnostic and therapeutic applications are severely restricted. To meet the challenge, we proposed a Martini-based aptamer-protein complex prediction protocol. By combining the base-base contact map from simulation and secondary structure prediction from various tools, improved secondary structure predictions can be obtained. This method reduced the risk of providing incorrect or incomplete base pairs in secondary structure prediction. Thus 3D structure modeling based on the secondary structure can be more reliable. We introduced the soft elastic network to the hairpin folded regions of the Martini ssDNAs to preserve their canonical structure. Using our protocol, we predicted the first 3D structure of the aptamer SYL3C and the SYL3C-EpCAM complex. We believe that our work could contribute to the future aptamer-related research studies and medical implications.

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

Increasing the Sampling Efficiency of Protein Conformational Change by Combining a Modified Replica Exchange Molecular Dynamics and Normal Mode Analysis

Understanding conformational change at an atomic level is significant when determining a protein functional mechanism. Replica exchange molecular dynamics (REMD) is a widely used enhanced sampling method to explore protein conformational space. However, REMD with an explicit solvent model requires huge computational resources, immensely limiting its application. In this study, a variation of parallel tempering metadynamics (PTMetaD) with the omission of solvent-solvent interactions in exchange attempts and the use of low-frequency modes calculated by normal-mode analysis (NMA) as collective variables (CVs), namely ossPTMetaD, is proposed with the aim to accelerate MD simulations simultaneously in temperature and geometrical spaces. For testing the performance of ossPTMetaD, five protein systems with diverse biological functions and motion patterns were selected, including large-scale domain motion (AdK), flap movement (HIV-1 protease and BACE1), and DFG-motif flip in kinases (p38α and c-Abl). The simulation results showed that ossPTMetaD requires much fewer numbers of replicas than temperature REMD (T-REMD) with a reduction of ∼70% to achieve a similar exchange ratio. Although it does not obey the detailed balance condition, ossPTMetaD provides consistent results with T-REMD and experimental data. The high accessibility of the large conformational change of protein systems by ossPTMetaD, especially in simulating the very challenging DFG-motif flip of protein kinases, demonstrated its high efficiency and robustness in the characterization of the large-scale protein conformational change pathway and associated free energy profile.

Mechanisms of Action of EGFR Tyrosine Kinase Receptor Incorporated in Extracellular Vesicles

EGFR and some of the cognate ligands extensively traffic in extracellular vesicles (EVs) from different biogenesis pathways. EGFR belongs to a family of four homologous tyrosine kinase receptors (TKRs). This family are one of the major drivers of cancer and is involved in several of the most frequent malignancies such as non-small cell lung cancer, breast cancer, colorectal cancer and ovarian cancer. The carrier EVs exert crucial biological effects on recipient cells, impacting immunity, pre-metastatic niche preparation, angiogenesis, cancer cell stemness and horizontal oncogene transfer. While EV-mediated EGFR signalling is important to EGFR-driven cancers, little is known about the precise mechanisms by which TKRs incorporated in EVs play their biological role, their stoichiometry and associations to other proteins relevant to cancer pathology and EV biogenesis, and their means of incorporation in the target cell. In addition, it remains unclear whether different subtypes of EVs incorporate different complexes of TKRs with specific functions. A raft of high spatial and temporal resolution methods is emerging that could solve these and other questions regarding the activity of EGFR and its ligands in EVs. More importantly, methods are emerging to block or mitigate EV activity to suppress cancer progression and drug resistance. By highlighting key findings and areas that remain obscure at the intersection of EGFR signalling and EV action, we hope to cross-fertilise the two fields and speed up the application of novel techniques and paradigms to both.

Mcl-1 and Bok transmembrane domains: Unexpected players in the modulation of apoptosis

The Bcl-2 protein family comprises both pro- and antiapoptotic members that control the permeabilization of the mitochondrial outer membrane, a crucial step in the modulation of apoptosis. Recent research has demonstrated that the carboxyl-terminal transmembrane domain (TMD) of some Bcl-2 protein family members can modulate apoptosis; however, the transmembrane interactome of the antiapoptotic protein Mcl-1 remains largely unexplored. Here, we demonstrate that the Mcl-1 TMD forms homooligomers in the mitochondrial membrane, competes with full-length Mcl-1 protein with regards to its antiapoptotic function, and induces cell death in a Bok-dependent manner. While the Bok TMD oligomers locate preferentially to the endoplasmic reticulum (ER), heterooligomerization between the TMDs of Mcl-1 and Bok predominantly takes place at the mitochondrial membrane. Strikingly, the coexpression of Mcl-1 and Bok TMDs produces an increase in ER mitochondrial-associated membranes, suggesting an active role of Mcl-1 in the induced mitochondrial targeting of Bok. Finally, the introduction of Mcl-1 TMD somatic mutations detected in cancer patients alters the TMD interaction pattern to provide the Mcl-1 protein with enhanced antiapoptotic activity, thereby highlighting the clinical relevance of Mcl-1 TMD interactions.

Isolation of Common Light Chain Antibodies from Immunized Chickens Using Yeast Biopanning and Fluorescence-Activated Cell Sorting

The phylogenetic distance between chickens and humans accounts for a strong immune response and a broader epitope coverage compared to rodent immunization approaches. Here the authors report the isolation of common light chain (cLC)-based chicken monoclonal antibodies from an anti-epidermal growth factor receptor (EGFR) immune library utilizing yeast surface display in combination with yeast biopanning and fluorescence-activated cell sorting (FACS). For the selection of high-affinity antibodies, a yeast cell library presenting cLC-comprising fragment antigen binding (Fab) fragments is panned against hEGFR-overexpressing A431 cells. The resulting cell-cell-complexes are sorted by FACS resulting in gradual enrichment of EGFR-binding Fabs in three sorting rounds. The isolated antibodies share the same light chain and show high specificity for EGFR, resulting in selective binding to A431 cells with notable EC50 values. All identified antibodies show very good aggregation propensity profiles and thermostabilities. Additionally, epitope binning demonstrates that these cLC antibodies cover a broad epitope space. Isolation of antibodies from immunized chickens by yeast cell biopanning makes an addition to the repertoire of methods for antibody library screening, paving the way for the generation of cLC-based bispecific antibodies against native mammalian receptors.

Individual Roles of Peptides PGLa and Magainin 2 in Synergistic Membrane Poration

Synergy between antimicrobial peptides PGLa and Magainin 2 (MAG2) provides an efficient way to enhance their antimicrobial ability. However, the underlying molecular mechanism of such synergy, especially the individual roles of each peptide, remains poorly understood. We combined a giant unilamellar vesicle leakage assay, in situ interfacial photovoltage testing, and molecular dynamics to investigate membrane poration under the action of PGLa, MAG2, or a PGLa/MAG2 mixture. Our results clearly show the different membrane action modes of the three systems and demonstrate the importance of forming PGLa-MAG2 heterodimers in the membrane poration process. PGLa inserted into and extracted from a membrane rapidly and continually with minimal aggregation and produced only transient, small pores. In contrast, MAG2 peptides tended to aggregate together on the membrane surface or only shallowly embed in the membrane. Additionally, the PGLa and MAG2 residues were well integrated into the membrane via the formation of PGLa-MAG2 heterodimers. The membrane defect produced by the rapid insertion of PGLa was stabilized by MAG2, which further recruited other peptides for the formation of PGLa-MAG2 heterodimers and even heterodimer clusters. Growth in pore size then occurred in a step-by-step process involving the formation and assembly of heterodimer clusters within the membrane. Our results provide insight into the complicated synergy that occurs between PGLa and MAG2 during membrane poration and will assist in the design of new antimicrobial peptides.

Binding of the Anti-FIV Peptide C8 to Differently Charged Membrane Models: From First Docking to Membrane Tubulation

Gp36 is the virus envelope glycoproteins catalyzing the fusion of the feline immunodeficiency virus with the host cells. The peptide C8 is a tryptophan-rich peptide corresponding to the fragment ⁷⁷⁰W-I⁷⁷⁷ of gp36 exerting antiviral activity by binding the membrane cell and inhibiting the virus entry. Several factors, including the membrane surface charge, regulate the binding of C8 to the lipid membrane. Based on the evidence that imperceptible variation of membrane charge may induce a dramatic effect in several critical biological events, in the present work we investigate the effect induced by systematic variation of charge in phospholipid bilayers on the aptitude of C8 to interact with lipid membranes, the tendency of C8 to assume specific conformational states and the re-organization of the lipid bilayer upon the interaction with C8. Accordingly, employing a bottom-up multiscale protocol, including CD, NMR, ESR spectroscopy, atomistic molecular dynamics simulations, and confocal microscopy, we studied C8 in six membrane models composed of different ratios of zwitterionic/negatively charged phospholipids. Our data show that charge content modulates C8-membrane binding with significant effects on the peptide conformations. C8 in micelle solution or in SUV formed by DPC or DOPC zwitterionic phospholipids assumes regular β-turn structures that are progressively destabilized as the concentration of negatively charged SDS or DOPG phospholipids exceed 40%. Interaction of C8 with zwitterionic membrane surface is mediated by Trp1 and Trp4 that are deepened in the membrane, forming H-bonds and cation-π interactions with the DOPC polar heads. Additional stabilizing salt bridge interactions involve Glu2 and Asp3. MD and ESR data show that the C8-membrane affinity increases as the concentration of zwitterionic phospholipid increases. In the lipid membrane characterized by an excess of zwitterionic phospholipids, C8 is adsorbed at the membrane interface, inducing a stiffening of the outer region of the DOPC bilayer. However, the bound of C8 significantly perturbs the whole organization of lipid bilayer resulting in membrane remodeling. These events, measurable as a variation of the bilayer thickness, are the onset mechanism of the membrane fusion and vesicle tubulation observed in confocal microscopy by imaging zwitterionic MLVs in the presence of C8 peptide.

Recent Results on Computational Molecular Modeling of The Origins of Life

In the last decade of research in the origins of life, there has been an increase in the interest on theoretical molecular modeling methods aimed to improve the accuracy and speed of the algorithms that solve the molecular mechanics and chemical reactions of the matter. Research on the scenarios of prebiotic chemistry has also advanced. The presented work attempts to discuss the latest computational techniques and trends implemented so far. Although it is difficult to cover the full extent of the current publications, we tried to orient the reader into the modern tendencies and challenges faced by those who are in the origins of life field.

Order–disorder skewness in alpha-synuclein: a key mechanism to recognize membrane curvature

Currently, membrane curvature is understood as an active mechanism to control cells spatial organization and activity.

Large-Scale Conformational Changes and Protein Function: Breaking the in silico Barrier

Large-scale conformational changes are essential to link protein structures with their function at the cell and organism scale, but have been elusive both experimentally and computationally. Over the past few years developments in cryo-electron microscopy and crystallography techniques have started to reveal multiple snapshots of increasingly large and flexible systems, deemed impossible only short time ago. As structural information accumulates, theoretical methods become central to understand how different conformers interconvert to mediate biological function. Here we briefly survey current in silico methods to tackle large conformational changes, reviewing recent examples of cross-validation of experiments and computational predictions, which show how the integration of different scale simulations with biological information is already starting to break the barriers between the in silico, in vitro, and in vivo worlds, shedding new light onto complex biological problems inaccessible so far.

The In Silico Drug Discovery Toolbox: Applications in Lead Discovery and Optimization

BACKGROUND

Discovery and development of a new drug is a long lasting and expensive journey that takes around 20 years from starting idea to approval and marketing of new medication. Despite R&D expenditures have been constantly increasing in the last few years, the number of new drugs introduced into market has been steadily declining. This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. To cope with this issue, a number of in silico techniques are currently being used for an early stage evaluation/prediction of potential safety issues, allowing to increase the drug-discovery success rate and reduce costs associated with the development of a new drug.

METHODS

In the present review, we will analyse the early steps of the drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silico tools used to assess attrition risks and build a mitigation plan.

RESULTS

A comprehensive list of widely used in silico tools, databases, and public initiatives that can be effectively implemented and used in the drug discovery pipeline has been provided. A few examples of how these tools can be problem-solving and how they may increase the success rate of a drug discovery and development program have been also provided. Finally, selected examples where the application of in silico tools had effectively contributed to the development of marketed drugs or clinical candidates will be given.

CONCLUSION

The in silico toolbox finds great application in every step of early drug discovery: (i) target identification and validation; (ii) hit identification; (iii) hit-to-lead; and (iv) lead optimization. Each of these steps has been described in details, providing a useful overview on the role played by in silico tools in the decision-making process to speed-up the discovery of new drugs.

Molecular Modeling for Nanomaterial-Biology Interactions: Opportunities, Challenges, and Perspectives

Injection of nanoparticles (NP) into the bloodstream leads to the formation of a so-called "nano-bio" interface where dynamic interactions between nanoparticle surfaces and blood components take place. A common consequence is the formation of the protein corona, that is, a network of adsorbed proteins that can strongly alter the surface properties of the nanoparticle. The protein corona and the resulting structural changes experienced by adsorbed proteins can lead to substantial deviations from the expected cellular uptake as well as biological responses such as NP aggregation and NP-induced protein fibrillation, NP interference with enzymatic activity, or the exposure of new antigenic epitopes. Achieving a detailed understanding of the nano-bio interface is still challenging due to the synergistic effects of several influencing factors like pH, ionic strength, and hydrophobic effects, to name just a few. Because of the multiscale complexity of the system, modeling approaches at a molecular level represent the ideal choice for a detailed understanding of the driving forces and, in particular, the early events at the nano-bio interface. This review aims at exploring and discussing the opportunities and perspectives offered by molecular modeling in this field through selected examples from literature.

Ligand Binding, Unbinding, and Allosteric Effects: Deciphering Small-Molecule Modulation of HSP90

The molecular chaperone HSP90 oversees the functional activation of a large number of client proteins. Because of its role in multiple pathways linked to cancer and neurodegeneration, drug discovery targeting HSP90 has been actively pursued. Yet, a number of inhibitors failed to meet expectations due to induced toxicity problems. In this context, allosteric perturbation has emerged as an alternative strategy for the pharmacological modulation of HSP90 functions. Specifically, novel allosteric stimulators showed the interesting capability of accelerating HSP90 closure dynamics and ATPase activities while inducing tumor cell death. Here, we gain atomistic insight into the mechanisms of allosteric ligand recognition and their consequences on the functional dynamics of HSP90, starting from the fully unbound state. We integrate advanced computational sampling methods based on FunnelMetadynamics, with the analysis of internal dynamics of the structural ensembles visited during the simulations. We observe several binding/unbinding events, and from these, we derive an accurate estimation of the absolute binding free energy. Importantly, we show that different binding poses induce different dynamics states. Our work for the first time explicitly correlates HSP90 responses to binding/unbinding of an allosteric ligand to the modulation of functionally oriented protein motions.

Unique transmembrane domain interactions differentially modulate integrin αvβ3 and αIIbβ3 function

Lateral transmembrane (TM) helix-helix interactions between single-span membrane proteins play an important role in the assembly and signaling of many cell-surface receptors. Often, these helices contain two highly conserved yet distinct interaction motifs, arranged such that the motifs cannot be engaged simultaneously. However, there is sparse experimental evidence that dual-engagement mechanisms play a role in biological signaling. Here, we investigate the function of the two conserved interaction motifs in the TM domain of the integrin β3-subunit. The first motif uses reciprocating "large-large-small" amino acid packing to mediate the interaction of the β3 and αIIb TM domains and maintain the inactive resting conformation of the platelet integrin αIIbβ3. The second motif, S-x₃-A-x₃-I, is a variant of the classical "G-x₃-G" motif. Using site-directed mutagenesis, optical trap-based force spectroscopy, and molecular modeling, we show that S-x₃-A-x₃-I does not engage αIIb but rather mediates the interaction of the β3 TM domain with the TM domain of the αv-subunit of the integrin αvβ3. Like αIIbβ3, αvβ3 on circulating platelets is inactive, and in the absence of platelet stimulation is unable to interact with components of the subendothelial matrix. However, disrupting any residue in the β3 S-x₃-A-x₃-I motif by site-directed mutations is sufficient to induce αvβ3 binding to the αvβ3 ligand osteopontin and to the monoclonal antibody WOW-1. Thus, the β3-integrin TM domain is able to engage in two mutually exclusive interactions that produce alternate α-subunit pairing, creating two integrins with distinct biological functions.

Resolving the conformational dynamics of ErbB growth factor receptor dimers

The combinatorial dimerization of the ErbB growth factor receptors (ErbB¹- ErbB⁴) are critical for their function. Here, we have characterized the conformational dynamics of ErbB transmembrane homo-dimers and hetero-dimers by using a coarse-grain simulation framework. All dimers, except ErbB^4-4 and ErbB^1-4, exhibit at least two conformations. The reported NMR structures correspond to one of these conformations, representing the N-terminal active state in ErbB^1-1 (RH2), ErbB^2-2 (RH1) and ErbB^4-4 (RH) homo-dimers and the LH dimer in ErbB^3-3 homo-dimer, validating the computational approach. Further, we predict a right-handed ErbB^3-3 dimer conformer that warrants experimental testing. The five hetero-dimers that have not yet been experimentally resolved display prominent right-handed dimers associating by the SmXXXSm motif. Our results provide insights into the constitutive signaling of ErbB⁴ after cleavage of the extracellular region. The presence of the inactive-like dimer conformers leading to symmetric kinase domains gives clues on the autoinhibition of the receptor dimers. The dimer states characterized here represent an important step towards understanding the combinatorial cross associations in the ErbB family.

Structural Investigation of Human Prolactin Receptor Transmembrane Domain Homodimerization in a Membrane Environment through Multiscale Simulations

It is well established that prolactin (PRL) and its receptor (PRLR) are associated with hundreds of biological functions. They have been postulated to be linked to breast and prostate cancers, and PRLR signaling has attracted considerable medical and pharmaceutical interest in the development of compounds targeting PRLR. Dimerization of the receptor through its transmembrane (TM) domain is a key step for understanding its signaling and related issues. Our multiscale simulation results revealed that its TM domain can form dimers in a membrane environment with distinct states stabilized by different residue motifs. On the basis of the simulated data, an activation mechanism of PRL with the importance of two symmetrical tryptophan residues was proposed in detail to determine the conformational change of its receptor, which is essential for signal transduction. The better knowledge of PRLR structure and its protein-protein interaction can considerably contribute to a further understanding of PRLR signaling action and thereby help to develop some new PRLR signaling-based strategies for PRL-related diseases.

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead.

How Melittin Inserts into Cell Membrane: Conformational Changes, Inter-Peptide Cooperation, and Disturbance on the Membrane

Antimicrobial peptides (AMPs), as a key component of the immune defense systems of organisms, are a promising solution to the serious threat of drug-resistant bacteria to public health. As one of the most representative and extensively studied AMPs, melittin has exceptional broad-spectrum activities against microorganisms, including both Gram-positive and Gram-negative bacteria. Unfortunately, the action mechanism of melittin with bacterial membranes, especially the underlying physics of peptide-induced membrane poration behaviors, is still poorly understood, which hampers efforts to develop melittin-based drugs or agents for clinical applications. In this mini-review, we focus on recent advances with respect to the membrane insertion behavior of melittin mostly from a computational aspect. Membrane insertion is a prerequisite and key step for forming transmembrane pores and bacterial killing by melittin, whose occurrence is based on overcoming a high free-energy barrier during the transition of melittin molecules from a membrane surface-binding state to a transmembrane-inserting state. Here, intriguing simulation results on such transition are highlighted from both kinetic and thermodynamic aspects. The conformational changes and inter-peptide cooperation of melittin molecules, as well as melittin-induced disturbances to membrane structure, such as deformation and lipid extraction, are regarded as key factors influencing the insertion of peptides into membranes. The associated intermediate states in peptide conformations, lipid arrangements, membrane structure, and mechanical properties during this process are specifically discussed. Finally, potential strategies for enhancing the poration ability and improving the antimicrobial performance of AMPs are included as well.

Ligand binding effects on the activation of the EGFR extracellular domain

The epidermal growth factor receptor (EGFR) is one of the most common target proteins in anti-cancer therapy. The binding of the EGF ligand to the EGFR extracellular domain (EGFR-ECD) promotes its inactive-to-active conformational transition (activation) but the relevant detailed mechanism remains elusive still. Here, the structural characterization and energetics of the EGFR-ECD conformational transition with and without the binding of the EGF are quantitatively explored using an innovative enhanced sampling MD simulation method. Intriguingly, the EGF offers hydrophobic interactions (e.g., EGF residues of Tyr44 and Leu47) and electrostatic interactions (e.g., the EGF residues of Glu5, Asp11, Asp17, and Arg41) to play a dominant role in dragging domain III to close the ligand binding domain gap. Subsequently, the correlation between domains III and II is enhanced through salt-bridges among Glu376, Arg403, and Arg405 from domain III and Glu293, Glu295, and Arg300 from domain II. Finally, the structural bending of domain II is regulated to facilitate the disengagement of domain II from domain IV. In this regard, the functional conformational transition of EGFR-ECD is a consequence of the cooperative motion of protein domains driven by the EGF ligand binding. The present study shows a detailed scenario of the EGF induced activation of EGFR-ECD and provides valuable information for drug discovery targeting the EGFR.