All-atom structural models of insulin binding to the insulin receptor in the presence of a tandem hormone-binding element

Spontaneous Dimerization and Distinct Packing Modes of Transmembrane Domains in Receptor Tyrosine Kinases

The insulin receptor (IR) and the insulin-like growth factor-1 receptor (IGF1R) are homodimeric transmembrane glycoproteins that transduce signals across the membrane on binding of extracellular peptide ligands. The structures of IR/IGF1R fragments in apo and liganded states have revealed that the extracellular subunits of these receptors adopt Λ-shaped configurations to which are connected the intracellular tyrosine kinase (TK) domains. The binding of peptide ligands induces structural transitions in the extracellular subunits leading to potential dimerization of transmembrane domains (TMDs) and autophosphorylation in TKs. However, the activation mechanisms of IR/IGF1R, especially the role of TMDs in coordinating signal-inducing structural transitions, remain poorly understood, in part due to the lack of structures of full-length receptors in apo or liganded states. While atomistic simulations of IR/IGF1R TMDs showed that these domains can dimerize in single component membranes, spontaneous unbiased dimerization in a plasma membrane having physiologically representative lipid composition has not been observed. We address this limitation by employing coarse-grained (CG) molecular dynamics simulations to probe the dimerization propensity of IR/IGF1R TMDs. We observed that TMDs in both receptors spontaneously dimerized independent of their initial orientations in their dissociated states, signifying their natural propensity for dimerization. In the dimeric state, IR TMDs predominantly adopted X-shaped configurations with asymmetric helical packing and significant tilt relative to the membrane normal, while IGF1R TMDs adopted symmetric V-shaped or parallel configurations with either no tilt or a small tilt relative to the membrane normal. Our results suggest that IR/IGF1R TMDs spontaneously dimerize and adopt distinct dimerized configurations.

Peptide Inhibitors of Insulin Fibrillation: Current and Future Challenges

Amyloidoses include a large variety of local and systemic diseases that share the common feature of protein unfolding or refolding into amyloid fibrils. The most studied amyloids are those directly involved in neurodegenerative diseases, while others, such as those formed by insulin, are surprisingly far less studied. Insulin is a very important polypeptide that plays a variety of biological roles and, first and foremost, is at the basis of the therapy of diabetic patients. It is well-known that it can form fibrils at the site of injection, leading to inflammation and immune response, in addition to other side effects. In this concise review, we analyze the current knowledge on insulin fibrillation, with a focus on the development of peptide-based inhibitors, which are promising candidates for their biocompatibility but still pose challenges to their effective use in therapy.

Structural models of viral insulin-like peptides and their analogs

The insulin receptor (IR), the insulin-like growth factor-1 receptor (IGF1R), and the insulin/IGF1 hybrid receptors (hybR) are homologous transmembrane receptors. The peptide ligands, insulin and IGF1, exhibit significant structural homology and can bind to each receptor via site-1 and site-2 residues with distinct affinities. The variants of the Iridoviridae virus family show capability in expressing single-chain insulin/IGF1 like proteins, termed viral insulin-like peptides (VILPs), which can stimulate receptors from the insulin family. The sequences of VILPs lacking the central C-domain (dcVILPs) are known, but their structures in unbound and receptor-bound states have not been resolved to date. We report all-atom structural models of three dcVILPs (dcGIV, dcSGIV, and dcLCDV1) and their complexes with the receptors (μIR, μIGF1R, and μhybR), and probed the peptide/receptor interactions in each system using all-atom molecular dynamics (MD) simulations. Based on the nonbonded interaction energies computed between each residue of peptides (insulin and dcVILPs) and the receptors, we provide details on residues establishing significant interactions. The observed site-1 insulin/μIR interactions are consistent with previous experimental studies, and a residue-level comparison of interactions of peptides (insulin and dcVILPs) with the receptors revealed that, due to sequence differences, dcVILPs also establish some interactions distinct from those between insulin and IR. We also designed insulin analogs and report enhanced interactions between some analogs and the receptors.

A Companion Guide to the String Method with Swarms of Trajectories: Characterization, Performance, and Pitfalls

The string method with swarms of trajectories (SMwST) is an algorithm that identifies a physically meaningful transition pathway─a one-dimensional curve, embedded within a high-dimensional space of selected collective variables. The SMwST algorithm leans on a series of short, unbiased molecular dynamics simulations spawned at different locations of the discretized path, from whence an average dynamic drift is determined to evolve the string toward an optimal pathway. However conceptually simple in both its theoretical formulation and practical implementation, the SMwST algorithm is computationally intensive and requires a careful choice of parameters for optimal cost-effectiveness in applications to challenging problems in chemistry and biology. In this contribution, the SMwST algorithm is presented in a self-contained manner, discussing with a critical eye its theoretical underpinnings, applicability, inherent limitations, and use in the context of path-following free-energy calculations and their possible extension to kinetics modeling. Through multiple simulations of a prototypical polypeptide, combining the search of the transition pathway and the computation of the potential of mean force along it, several practical aspects of the methodology are examined with the objective of optimizing the computational effort, yet without sacrificing accuracy. In light of the results reported here, we propose some general guidelines aimed at improving the efficiency and reliability of the computed pathways and free-energy profiles underlying the conformational transitions at hand.

Structures and interactions of insulin-like peptides from cone snail venom

The venomous insulin-like peptides released by certain cone snails stimulate hypoglycemic shock to immobilize fish and catch the prey. Compared to human insulin (hIns), the cone snail insulins (Con-Ins) are typically monomeric and shorter in sequence, yet they exhibit moderate hIns-like biological activity. We have modeled six variants of Con-Ins (G3, K1, K2, T1A, T1B, and T2) and carried out explicit-solvent molecular dynamics (MD) simulations of eight types of insulins, two with known structures (hIns and Con-Ins-G1) and six Con-Ins with modeled structures, to characterize key residues of each insulin that interact with the truncated human insulin receptor (μIR). We show that each insulin/μIR complex is stable during explicit-solvent MD simulations and hIns interactions indicate the highest affinity for the "site 1" of IR. The residue contact maps reveal that each insulin preferably interacts with the αCT peptide than the L1 domain of IR. Through analysis of the average nonbonded interaction energy contribution of every residue of each insulin for the μIR, we probe the residues establishing favorable interactions with the receptor. We compared the interaction energy of each residue of every Con-Ins to the μIR and observed that γ-carboxylated glutamate (Gla), His, Thr, Tyr, Tyr/His, and Asn in Con-Ins are favorable substitutions for GluA4, AsnA21, ValB12, LeuB15, GlyB20, and ArgB22 in hIns, respectively. The identified insulin analogs, although lacking the last eight residues of the B-chain of hIns, bind strongly to μIR. Our findings are potentially useful in designing potent fast-acting therapeutic insulin.

Progress in Simulation Studies of Insulin Structure and Function

Insulin is a peptide hormone known for chiefly regulating glucose level in blood among several other metabolic processes. Insulin remains the most effective drug for treating diabetes mellitus. Insulin is synthesized in the pancreatic β-cells where it exists in a compact hexameric architecture although its biologically active form is monomeric. Insulin exhibits a sequence of conformational variations during the transition from the hexamer state to its biologically-active monomer state. The structural transitions and the mechanism of action of insulin have been investigated using several experimental and computational methods. This review primarily highlights the contributions of molecular dynamics (MD) simulations in elucidating the atomic-level details of conformational dynamics in insulin, where the structure of the hormone has been probed as a monomer, dimer, and hexamer. The effect of solvent, pH, temperature, and pressure have been probed at the microscopic scale. Given the focus of this review on the structure of the hormone, simulation studies involving interactions between the hormone and its receptor are only briefly highlighted, and studies on other related peptides (e.g., insulin-like growth factors) are not discussed. However, the review highlights conformational dynamics underlying the activities of reported insulin analogs and mimetics. The future prospects for computational methods in developing promising synthetic insulin analogs are also briefly highlighted.

String Method with Swarms-of-Trajectories, Mean Drifts, Lag Time, and Committor

The kinetics of a dynamical system comprising two metastable states is formulated in terms of a finite-time propagator in phase space (position and velocity) adapted to the underdamped Langevin equation. Dimensionality reduction to a subspace of collective variables yields familiar expressions for the propagator, committor, and steady-state flux. A quadratic expression for the steady-state flux between the two metastable states can serve as a robust variational principle to determine an optimal approximate committor expressed in terms of a set of collective variables. The theoretical formulation is exploited to clarify the foundation of the string method with swarms-of-trajectories, which relies on the mean drift of short trajectories to determine the optimal transition pathway. It is argued that the conditions for Markovity within a subspace of collective variables may not be satisfied with an arbitrary short time-step and that proper kinetic behaviors appear only when considering the effective propagator for longer lag times. The effective propagator with finite lag time is amenable to an eigenvalue-eigenvector spectral analysis, as elaborated previously in the context of position-based Markov models. The time-correlation functions calculated by swarms-of-trajectories along the string pathway constitutes a natural extension of these developments. The present formulation provides a powerful theoretical framework to characterize the optimal pathway between two metastable states of a system.

Role of surface-exposed charged basic amino acids (Lys, Arg) and guanidination in insulin on the interaction and stability of insulin-insulin receptor complex

Naturally occurring proteins are emerging as novel therapeutics in the protein-based biopharmaceutical industry for the treatment of diabetes and obesity. However, proteins are not suitable for oral delivery due to short half-life, reduced physical and chemical stability and low permeability across the membrane. Chemical modification has been identified as a formulation strategy to enhance the stability and bioavailability of protein drugs. The present study aims to study the effect of charge-specific modification of basic amino acids (Lys, Arg) and guanidination on the interaction of insulin with its receptor using molecular modelling. Our investigation revealed that the guanidination of insulin (Lys-NHC = NHNH₂) enhanced and exerted stronger binding of the protein to its receptor through electrostatic interaction than native insulin (Lys-NH₃⁺). Point mutations of Lys and Arg (R22, K29; R22K, K29; R22, K29R; R22K, K29R) were attempted and the effects on the interaction and stability between insulin/modified insulins and insulin receptor were also analyzed in this study. The findings from the study are expected to provide a better understanding of the possible mechanism of action of the modified protein at a molecular level before advancing to real experiments.

Insulin Dissociates by Diverse Mechanisms of Coupled Unfolding and Unbinding

The protein hormone insulin exists in various oligomeric forms, and a key step in binding its cellular receptor is dissociation of the dimer. This dissociation process and its corresponding association process have come to serve as paradigms of coupled (un)folding and (un)binding more generally. Despite its fundamental and practical importance, the mechanism of insulin dimer dissociation remains poorly understood. Here, we use molecular dynamics simulations, leveraging recent developments in umbrella sampling, to characterize the energetic and structural features of dissociation in unprecedented detail. We find that the dissociation is inherently multipathway with limiting behaviors corresponding to conformational selection and induced fit, the two prototypical mechanisms of coupled folding and binding. Along one limiting path, the dissociation leads to detachment of the C-terminal segment of the insulin B chain from the protein core, a feature believed to be essential for receptor binding. We simulate IR spectroscopy experiments to aid in interpreting current experiments and identify sites where isotopic labeling can be most effective for distinguishing the contributions of the limiting mechanisms.

Probing the Differential Dynamics of the Monomeric and Dimeric Insulin from Amide-I IR Spectroscopy

The monomer-dimer equilibrium for insulin is one of the essential steps in forming the receptor-binding competent monomeric form of the hormone. Despite this importance, the thermodynamic stability, in particular for modified insulins, is quite poorly understood, in part, due to experimental difficulties. This work explores one- and two-dimensional infrared spectroscopy in the range of the amide-I band for the hydrated monomeric and dimeric wild-type hormone. It is found that for the monomer the frequency fluctuation correlation function (FFCF) and the one-dimensional infrared spectra are position sensitive. The spectra of the -CO probes at the dimerization interface (residues Phe24, Phe25, and Tyr26) split and indicate an asymmetry despite the overall (formal) point symmetry of the dimer structure. Also, the decay times of the FFCF for the same -CO probe in the monomer and the dimer can differ by up to 1 order of magnitude, for example, for residue PheB24, which is solvent exposed for the monomer but at the interface for the dimer. The spectroscopic shifts correlate approximately with the average number of hydration waters and the magnitude of the FFCF at time zero. However, this correlation is only qualitative due to the heterogeneous and highly dynamical environment. Based on density functional theory calculations, the dominant contribution for solvent-exposed -CO is found to arise from the surrounding water (∼75%), whereas the protein environment contributes considerably less. The results suggest that infrared spectroscopy is a positionally sensitive probe of insulin dimerization, in particular in conjunction with isotopic labeling of the probe.

Diffusion network of CO in FeFe-Hydrogenase

FeFe-hydrogenase is an efficient enzyme to produce H₂ under optimal conditions. However, the activity of this enzyme is highly sensitive to the presence of inhibitory gases CO and O₂ that cause irreversible damage to the active site. Therefore, a detailed knowledge of the diffusion pathways of these inhibitory gases is necessary to develop strategies for designing novel enzymes that are tolerant to these gases. In this work, we studied the diffusion pathways of CO in the CpI FeFe-hydrogenase from Clostridium pasteurianum. Specifically, we used several enhanced sampling and free-energy simulation methods to reconstruct a three-dimensional free-energy surface for CO diffusion which revealed 45 free-energy minima forming an interconnected network of pathways. We discovered multiple pathways of minimal free-energy as diffusion portals for CO and found that previously suggested hydrophobic pathways are not thermodynamically favorable for CO diffusion. We also observed that the global minimum in the free-energy surface is located in the vicinity of the active-site metal cluster, the H-cluster, which suggests a high-affinity for CO near the active site. Among 19 potential residues that we propose as candidates for future mutagenesis studies, 11 residues are shared with residues that have been previously proposed to increase the tolerance of this enzyme for O₂. We hypothesize that these shared candidate residues are potentially useful for designing new variants of this enzyme that are tolerant to both inhibitory gases.

Building Graphs To Describe Dynamics, Kinetics, and Energetics in the d-ALa:d-Lac Ligase VanA

The d-Ala:d-Lac ligase, VanA, plays a critical role in the resistance of vancomycin. Indeed, it is involved in the synthesis of a peptidoglycan precursor, to which vancomycin cannot bind. The reaction catalyzed by VanA requires the opening of the so-called “ω-loop”, so that the substrates can enter the active site. Here, the conformational landscape of VanA is explored by an enhanced sampling approach: the temperature-accelerated molecular dynamics (TAMD). Analysis of the molecular dynamics (MD) and TAMD trajectories recorded on VanA permits a graphical description of the structural and kinetics aspects of the conformational space of VanA, where the internal mobility and various opening modes of the ω-loop play a major role. The other important feature is the correlation of the ω-loop motion with the movements of the opposite domain, defined as containing the residues A149–Q208. Conformational and kinetic clusters have been determined and a path describing the ω-loop opening was extracted from these clusters. The determination of this opening path, as well as the relative importance of hydrogen bonds along the path, permit one to propose some key residue interactions for the kinetics of the ω-loop opening.

All-Atom Structural Models of the Transmembrane Domains of Insulin and Type 1 Insulin-Like Growth Factor Receptors

The receptor tyrosine kinase superfamily comprises many cell-surface receptors including the insulin receptor (IR) and type 1 insulin-like growth factor receptor (IGF1R) that are constitutively homodimeric transmembrane glycoproteins. Therefore, these receptors require ligand-triggered domain rearrangements rather than receptor dimerization for activation. Specifically, binding of peptide ligands to receptor ectodomains transduces signals across the transmembrane domains for trans-autophosphorylation in cytoplasmic kinase domains. The molecular details of these processes are poorly understood in part due to the absence of structures of full-length receptors. Using MD simulations and enhanced conformational sampling algorithms, we present all-atom structural models of peptides containing 51 residues from the transmembrane and juxtamembrane regions of IR and IGF1R. In our models, the transmembrane regions of both receptors adopt helical conformations with kinks at Pro961 (IR) and Pro941 (IGF1R), but the C-terminal residues corresponding to the juxtamembrane region of each receptor adopt unfolded and flexible conformations in IR as opposed to a helix in IGF1R. We also observe that the N-terminal residues in IR form a kinked-helix sitting at the membrane-solvent interface, while homologous residues in IGF1R are unfolded and flexible. These conformational differences result in a larger tilt-angle of the membrane-embedded helix in IGF1R in comparison to IR to compensate for interactions with water molecules at the membrane-solvent interfaces. Our metastable/stable states for the transmembrane domain of IR, observed in a lipid bilayer, are consistent with a known NMR structure of this domain determined in detergent micelles, and similar states in IGF1R are consistent with a previously reported model of the dimerized transmembrane domains of IGF1R. Our all-atom structural models suggest potentially unique structural organization of kinase domains in each receptor.

Molecular Dynamics Simulations of Insulin: Elucidating the Conformational Changes that Enable Its Binding

A sequence of complex conformational changes is required for insulin to bind to the insulin receptor. Recent experimental evidence points to the B chain C-terminal (BC-CT) as the location of these changes in insulin. Here, we present molecular dynamics simulations of insulin that reveal new insights into the structural changes occurring in the BC-CT. We find three key results: 1) The opening of the BC-CT is inherently stochastic and progresses through an open and then a “wide-open” conformation—the wide-open conformation is essential for receptor binding, but occurs only rarely. 2) The BC-CT opens with a zipper-like mechanism, with a hinge at the Phe24 residue, and is maintained in the dominant closed/inactive state by hydrophobic interactions of the neighboring Tyr26, the critical residue where opening of the BC-CT (activation of insulin) is initiated. 3) The mutation Y26N is a potential candidate as a therapeutic insulin analogue. Overall, our results suggest that the binding of insulin to its receptor is a highly dynamic and stochastic process, where initial docking occurs in an open conformation and full binding is facilitated through interactions of insulin receptor residues with insulin in its wide-open conformation.

Free energy and hidden barriers of the β-sheet structure of prion protein

On-the-fly free-energy parametrization is a new collective variable biasing approach akin to metadynamics with one important distinction: rather than acquiring an accelerated distribution via a history-dependent bias potential, sampling on this distribution is achieved from the beginning of the simulation using temperature-accelerated molecular dynamics. In the present work, we compare the performance of both approaches to compute the free-energy profile along a scalar collective variable measuring the H-bond registry of the β-sheet structure of the mouse Prion protein. Both methods agree on the location of the free-energy minimum, but free-energy profiles from well-tempered metadynamics are subject to a much higher degree of statistical noise due to hidden barriers. The sensitivity of metadynamics to hidden barriers is shown to be a consequence of the history dependence of the bias potential, and we detail the nature of these barriers for the prion β-sheet. In contrast, on-the-fly parametrization is much less sensitive to these barriers and thus displays improved convergence behavior relative to that of metadynamics. While hidden barriers are a frequent and central issue in free-energy methods, on-the-fly free-energy parametrization appears to be a robust and preferable method to confront this issue.

Temperature Accelerated Molecular Dynamics with Soft-Ratcheting Criterion Orients Enhanced Sampling by Low-Resolution Information

Many proteins exhibit an equilibrium between multiple conformations, some of them being characterized only by low-resolution information. Visiting all conformations is a demanding task for computational techniques performing enhanced but unfocused exploration of collective variable (CV) space. Otherwise, pulling a structure toward a target condition biases the exploration in a way difficult to assess. To address this problem, we introduce here the soft-ratcheting temperature-accelerated molecular dynamics (sr-TAMD), where the exploration of CV space by TAMD is coupled to a soft-ratcheting algorithm that filters the evolving CV values according to a predefined criterion. Any low resolution or even qualitative information can be used to orient the exploration. We validate this technique by exploring the conformational space of the inactive state of the catalytic domain of the adenyl cyclase AC from Bordetella pertussis. The domain AC gets activated by association with calmodulin (CaM), and the available crystal structure shows that in the complex the protein has an elongated shape. High-resolution data are not available for the inactive, CaM-free protein state, but hydrodynamic measurements have shown that the inactive AC displays a more globular conformation. Here, using as CVs several geometric centers, we use sr-TAMD to enhance CV space sampling while filtering for CV values that correspond to centers moving close to each other, and we thus rapidly visit regions of conformational space that correspond to globular structures. The set of conformations sampled using sr-TAMD provides the most extensive description of the inactive state of AC up to now, consistent with available experimental information.

Theoretical and computational studies of peptides and receptors of the insulin family

Synergistic interactions among peptides and receptors of the insulin family are required for glucose homeostasis, normal cellular growth and development, proliferation, differentiation and other metabolic processes. The peptides of the insulin family are disulfide-linked single or dual-chain proteins, while receptors are ligand-activated transmembrane glycoproteins of the receptor tyrosine kinase (RTK) superfamily. Binding of ligands to the extracellular domains of receptors is known to initiate signaling via activation of intracellular kinase domains. While the structure of insulin has been known since 1969, recent decades have seen remarkable progress on the structural biology of apo and liganded receptor fragments. Here, we review how this useful structural information (on ligands and receptors) has enabled large-scale atomically-resolved simulations to elucidate the conformational dynamics of these biomolecules. Particularly, applications of molecular dynamics (MD) and Monte Carlo (MC) simulation methods are discussed in various contexts, including studies of isolated ligands, apo-receptors, ligand/receptor complexes and intracellular kinase domains. The review concludes with a brief overview and future outlook for modeling and computational studies in this family of proteins.

Flexibility in the insulin receptor ectodomain enables docking of insulin in crystallographic conformation observed in a hormone-bound microreceptor

Insulin binding to the insulin receptor (IR) is the first key step in initiating downstream signaling cascades for glucose homeostasis in higher organisms. The molecular details of insulin recognition by IR are not yet completely understood, but a picture of hormone/receptor interactions at one of the epitopes (Site 1) is beginning to emerge from recent structural evidence. However, insulin-bound structures of truncated IR suggest that crystallographic conformation of insulin cannot be accommodated in the full IR ectodomain due to steric overlap of insulin with the first two type III fibronectin domains (F1 and F2), which are contributed to the insulin binding-pocket by the second subunit in the IR homodimer. A conformational change in the F1-F2 pair has thus been suggested. In this work, we present an all-atom structural model of complex of insulin and the IR ectodomain, where no structural overlap of insulin with the receptor domains (F1 and F2) is observed. This structural model was arrived at by flexibly fitting parts of our earlier insulin/IR all-atom model into the simulated density maps of crystallized constructs combined with conformational sampling from apo-IR solution conformations. Importantly, our experimentally-consistent model helps rationalize yet unresolved Site.

Temperature-accelerated molecular dynamics gives insights into globular conformations sampled in the free state of the AC catalytic domain

The catalytic domain of the adenyl cyclase (AC) toxin from Bordetella pertussis is activated by interaction with calmodulin (CaM), resulting in cAMP overproduction in the infected cell. In the X-ray crystallographic structure of the complex between AC and the C terminal lobe of CaM, the toxin displays a markedly elongated shape. As for the structure of the isolated protein, experimental results support the hypothesis that more globular conformations are sampled, but information at atomic resolution is still lacking. Here, we use temperature-accelerated molecular dynamics (TAMD) simulations to generate putative all-atom models of globular conformations sampled by CaM-free AC. As collective variables, we use centers of mass coordinates of groups of residues selected from the analysis of standard molecular dynamics (MD) simulations. Results show that TAMD allows extended conformational sampling and generates AC conformations that are more globular than in the complexed state. These structures are then refined via energy minimization and further unrestrained MD simulations to optimize inter-domain packing interactions, thus resulting in the identification of a set of hydrogen bonds present in the globular conformations.

Exploring the conformational transitions of biomolecular systems using a simple two-state anisotropic network model

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results.

Many biomolecules are like tiny molecular machines that need to change their shapes and visit many states to perform their biological functions. For a complete molecular understanding of a biological process, one needs to have information on the relevant stable states of the system in question, as well as the pathways by which the system travels from one state to another. We report here an efficient computational method that uses the knowledge of experimental structures of a pair of stable states in order to construct an energetically favoravle pathway between them. We adopt a simple representation of the molecular system by replacing the atoms with beads connected by springs and constructing an energy function with two minima around the end-states. We searched for the structure with highest energy that the system is most likely to visit during the transition and created two paths starting from this structure and proceeding toward the end-states. The combined result of these two paths is the minimum energy pathway between the two stable states. We apply this method to study important structural changes in one enzyme and three large proteins that transport small molecules and ions across the cell membrane.

Comparison between Mean Forces and Swarms-of-Trajectories String Methods

The original formulation of the string method in collective variable space is compared with a recent variant called string method with swarms-of-trajectories. The assumptions made in the original method are revisited and the significance of the minimum free energy path (MFEP) is discussed in the context of reactive events. These assumptions are compared to those made in the string method with swarms-of-trajectories, and shown to be equivalent in a certain regime: in particular an expression for the path identified by the swarms-of-trajectories method is given and shown to be closely related to the MFEP. Finally, the algorithmic aspects of both methods are compared.

Conformational dynamics of a regulator of G-protein signaling protein reveals a mechanism of allosteric inhibition by a small molecule

Regulators of G protein signaling (RGS) proteins are key players in regulating signaling via G protein-coupled receptors. RGS proteins directly bind to the Gα-subunits of activated heterotrimeric G-proteins, and accelerate the rate of GTP hydrolysis, thereby rapidly deactivating G-proteins. Using atomistic simulations and NMR spectroscopy, we have studied in molecular detail the mechanism of action of CCG-50014, a potent small molecule inhibitor of RGS4 that covalently binds to cysteine residues on RGS4. We apply temperature-accelerated molecular dynamics (TAMD) to carry out enhanced conformational sampling of apo RGS4 structures, and consistently find that the α5-α6 helix pair of RGS4 can spontaneously span open-like conformations, allowing binding of CCG-50014 to the buried side-chain of Cys95. Both NMR experiments and MD simulations reveal chemical shift perturbations in residues in the vicinity of inhibitor binding site as well as in the RGS4-Gα binding interface. Consistent with a loss of G-protein binding, GAP activity, and allosteric mechanism of action of CCG-50014, our simulations of the RGS4-Gα complex in the presence of inhibitor suggest a relatively unstable protein-protein interaction. These results have potential implications for understanding how the conformational dynamics among RGS proteins may play a key role in the sensitivity of inhibitors.