Study of the insulin dimerization: binding free energy calculations and per-residue free energy decomposition

Analysis of the Dynamics of a Complex, Multipathway Reaction: Insulin Dimer Dissociation

The protein hormone insulin forms a homodimer that must dissociate to bind to its receptor. Understanding the kinetics and mechanism of dissociation is essential for the rational design of therapeutic analogs. In addition to its physiological importance, this dissociation process serves as a paradigm for coupled (un)folding and (un)binding. Based on previous free energy simulations, insulin dissociation is thought to involve multiple pathways with comparable free energy barriers. Here, we analyze the mechanism of insulin dimer dissociation using a recently developed computational framework for estimating kinetic statistics from short-trajectory data. These statistics indicate that the likelihood of dissociation (the committor) closely tracks the decrease in the number of (native and nonnative) intermonomer contacts and the increase in the number of water contacts at the dimer interface; the transition state with equal likelihood of association and dissociation corresponds to an encounter complex with relatively few native contacts and many nonnative contacts. We identify four pathways out of the dimer state and quantify their contributions to the rate as well as their exchange by computing reactive fluxes. We show that both the pathways and their extents of exchange can be understood in terms of rotations around three axes of the dimer structure. Our results provide insights into the kinetics of insulin analogs and, more generally, how to characterize complex, multipathway processes.

Study on SHP2 Conformational Transition and Structural Characterization of Its High-Potency Allosteric Inhibitors by Molecular Dynamics Simulations Combined with Machine Learning

The src-homology 2 domain-containing phosphatase 2 (SHP2) is a human cytoplasmic protein tyrosine phosphatase that plays a crucial role in cellular signal transduction. Aberrant activation and mutations of SHP2 are associated with tumor growth and immune suppression, thus making it a potential target for cancer therapy. Initially, researchers sought to develop inhibitors targeting SHP2's catalytic site (protein tyrosine phosphatase domain, PTP). Due to limitations such as conservativeness and poor membrane permeability, SHP2 was once considered a challenging drug target. Nevertheless, with the in-depth investigations into the conformational switch mechanism from SHP2's inactive to active state and the emergence of various SHP2 allosteric inhibitors, new hope has been brought to this target. In this study, we investigated the interaction models of various allosteric inhibitors with SHP2 using molecular dynamics simulations. Meanwhile, we explored the free energy landscape of SHP2 activation using enhanced sampling technique (meta-dynamics simulations), which provides insights into its conformational changes and activation mechanism. Furthermore, to biophysically interpret high-dimensional simulation trajectories, we employed interpretable machine learning methods, specifically extreme gradient boosting (XGBoost) with Shapley additive explanations (SHAP), to comprehensively analyze the simulation data. This approach allowed us to identify and highlight key structural features driving SHP2 conformational dynamics and regulating the activity of the allosteric inhibitor. These studies not only enhance our understanding of SHP2's conformational switch mechanism but also offer crucial insights for designing potent allosteric SHP2 inhibitors and addressing drug resistance issues.

Analysis of the dynamics of a complex, multipathway reaction: Insulin dimer dissociation

The protein hormone insulin forms a homodimer that must dissociate to bind to its receptor. Understanding the kinetics and mechanism of dissociation is essential for rational design of therapeutic analogs. In addition to its physiological importance, this dissociation process serves as a paradigm for coupled (un)folding and (un)binding. Based on previous free energy simulations, insulin dissociation is thought to involve multiple pathways with comparable free energy barriers. Here, we analyze the mechanism of insulin dimer dissociation using a recently developed computational framework for estimating kinetic statistics from short-trajectory data. These statistics indicate that the likelihood of dissociation (the committor) closely tracks the decrease in the number of (native and nonnative) intermonomer contacts and the increase in the number of water contacts at the dimer interface; the transition state with equal likelihood of association and dissociation corresponds to an encounter complex with relatively few native contacts and many nonnative contacts. We identify four pathways out of the dimer state and quantify their contributions to the rate, as well as their exchange, by computing reactive fluxes. We show that both the pathways and their extents of exchange can be understood in terms of rotations around three axes of the dimer structure. Our results provide insights into the kinetics of insulin analogues and, more generally, how to characterize complex, multipathway processes.

Conformational Properties of Poly(A)-Binding Protein Complexed with Poly(A) RNA

Microscopic understanding of protein-RNA interactions is important for different biological activities, such as RNA transport, translation, splicing, silencing, etc. Polyadenine (Poly(A)) binding proteins (PABPs) make up a class of regulatory proteins that play critical roles in protecting the poly(A) tails of cellular mRNAs from nuclease degradation. In this work, we performed molecular dynamics simulations to investigate the conformational modifications of human PABP protein and poly(A) RNA that occur during complexation. It is demonstrated that the intermediate linker domain of the protein transforms from a disordered coil-like structure to a helical form during the recognition process, leading to the formation of the complex. On the other hand, disordered collapsed coil-like RNA on complexation has been found to transform into a rigid extended conformation. Importantly, the binding free energy calculation showed that the thermodynamic stability of the complex is primarily guided by favorable hydrophobic interactions between the protein and the RNA.

A theoretical study on the activity and selectivity of IDO/TDO inhibitors

Indoleamine 2,3-dioxygenase 1 (IDO) is a tryptophan (Trp) metabolic enzyme along the kynurenine (NFK) pathway. Under pathological conditions, IDO overexpressed by tumor cells causes depletion of tryptophan and the accumulation of metabolic products, which inhibit the local immune response and form immune escape. Therefore, the suppression of IDO activity is one of the strategies for tumor immunotherapy, and drug design for this target has been the focus of research for more than two decades. Apart from IDO, tryptophan dioxygenase (TDO) of the same family can also catalyze the same biochemical reaction in the human body, but it has different tissue distribution and substrate selectivity from IDO. Based on the principle of drug design with high potency and low cross-reactivity to specific targets, in this subject, the activity and selectivity of IDO and TDO toward small molecular inhibitors were studied from the perspective of thermodynamics and kinetics. The aim was to elucidate the structural requirements for achieving favorable biological activity and selectivity of IDO and TDO inhibitors. Specifically, the interactions of inhibitors from eight families with IDO and TDO were initially investigated through molecular docking and molecular dynamics simulations, and the thermodynamic data for binding of inhibitors were predicted by the molecular mechanics/generalized Born surface area (MM/GBSA) method. Secondly, we explored the free energy landscape of JKloops, the kinetic control element of IDO/TDO, using temperature replica exchange molecular dynamics (T-REMD) simulations and elucidated the connection between the rules of IDO/TDO conformational changes and the inhibitor selectivity mechanism. Furthermore, the binding and dissociation processes of the C1 inhibitor (NLG919) were simulated by the adaptive steering molecular dynamics (ASMD) method, which not only addressed the possible stable, metastable, and transition states for C1 inhibitor-IDO/TDO interactions, but also accurately predicted kinetic data for C1 inhibitor binding and dissociation. In conclusion, we have constructed a complete process from enzyme (IDO/TDO) conformational activation to inhibitor binding/dissociation and used the thermodynamic and kinetic data of each link as clues to verify the control mechanism of IDO/TDO on inhibitor selectivity. This is of great significance for us to understand the design principles of tumor immunotherapy drugs and to avoid drug resistance of immunotherapy drugs.

Understanding the Reversible Binding of a Multichain Protein-Protein Complex through Free-Energy Calculations

We demonstrate that the binding affinity of a multichain protein-protein complex, insulin dimer, can be accurately predicted using a streamlined route of standard binding free-energy calculations. We find that chains A and C, which do not interact directly during binding, stabilize the insulin monomer structures and reduce the binding affinity of the two monomers, therefore enabling their reversible association. Notably, we confirm that although classical methods can estimate the binding affinity of the insulin dimer, conventional molecular dynamics, enhanced sampling algorithms, and classical geometrical routes of binding free-energy calculations may not fully capture certain aspects of the role played by the noninteracting chains in the binding dynamics. Therefore, this study not only elucidates the role of noninteracting chains in the reversible binding of the insulin dimer but also offers a methodological guide for investigating the reversible binding of multichain protein-protein complexes utilizing streamlined free-energy calculations.

Exploring the conformational changes of the Munc18-1/syntaxin 1a complex

Neurotransmitters are released from synaptic vesicles, the membrane of which fuses with the plasma membrane upon calcium influx. This membrane fusion reaction is driven by the formation of a tight complex comprising the plasma membrane N-ethylmaleimide-sensitive factor attachment receptor (SNARE) proteins syntaxin-1a and SNAP-25 with the vesicle SNARE protein synaptobrevin. The neuronal protein Munc18-1 forms a stable complex with syntaxin-1a. Biochemically, syntaxin-1a cannot escape the tight grip of Munc18-1, so formation of the SNARE complex is inhibited. However, Munc18-1 is essential for the release of neurotransmitters in vivo. It has therefore been assumed that Munc18-1 makes the bound syntaxin-1a available for SNARE complex formation. Exactly how this occurs is still unclear, but it is assumed that structural rearrangements occur. Here, we used a series of mutations to specifically weaken the complex at different positions in order to induce these rearrangements biochemically. Our approach was guided through sequence and structural analysis and supported by molecular dynamics simulations. Subsequently, we created a homology model showing the complex in an altered conformation. This conformation presumably represents a more open arrangement of syntaxin-1a that permits the formation of a SNARE complex to be initiated while still bound to Munc18-1. In the future, research should investigate how this central reaction for neuronal communication is controlled by other proteins.

SurfPB: A GPU-Accelerated Electrostatic Calculation and Visualization Tool for Biomolecules

In this work, we present SurfPB as a useful tool for the study of biomolecules. It can do many typical calculations, including the molecular surface, electrostatic potential, solvation free energy, entropy, and binding free energy. Among all of the calculations, the entropy calculation is the most time-consuming one. In SurfPB, the calculation can be performed in a vacuum or implicit solvent and accelerated on GPU. The Poisson-Boltzmann equation solver is accelerated on GPU as well. Moreover, we developed a graphical user interface for SurfPB. It allows users to input the parameters and complete the whole calculation in a visual way. The calculated electrostatic potentials are shown on the molecular surface in a three-dimensional scene.

Heterogeneous and Allosteric Role of Surface Hydration for Protein-Ligand Binding

Atomistic-level understanding of surface hydration mediating protein-protein interactions and ligand binding has been a challenge due to the dynamic nature of water molecules near the surface. We develop a computational method to evaluate the solvation free energy based on the density map of the first hydration shell constructed from all-atom molecular dynamics simulation and use it to examine the binding of two intrinsically disordered ligands to their target protein domain. One ligand is from the human protein, and the other is from the 1918 Spanish flu virus. We find that the viral ligand incurs a 6.9 kcal/mol lower desolvation penalty upon binding to the target, which is consistent with its stronger binding affinity. The difference arises from the spatially fragmented and nonuniform water density profiles of the first hydration shell. In particular, residues that are distal from the ligand-binding site contribute to a varying extent to the desolvation penalty, among which the "entropy hotspot" residues contribute significantly. Thus, ligand binding alters hydration on remote sites in addition to affecting the binding interface. The nonlocal effect disappears when the conformational motion of the protein is suppressed. The present results elucidate the interplay between protein conformational dynamics and surface hydration. Our approach of measuring the solvation free energy based on the water density of the first hydration shell is tolerant of the conformational fluctuation of protein, and we expect it to be applicable to investigating a broad range of biomolecular interfaces.

Microscopic Understanding of the Conformational Stability of the Aggregated Nonamyloid β Components of α-Synuclein

Self-association of α-synuclein peptides into oligomeric species and ordered amyloid fibrils is associated with Parkinson's disease, a progressive neurodegenerative disorder. In particular, the peptide domain formed between the residues Glu-61 (or E61) and Val-95 (or V95) of α-synuclein, typically termed the "nonamyloid β component" (NAC), is known to play critical roles in forming aggregated structures. In this work, we have employed molecular dynamics simulations to explore the conformational properties and relative stabilities of aggregated protofilaments of different orders, namely, tetramer (P(4)), hexamer (P(6)), octamer (P(8)), decamer (P(10)), dodecamer (P(12)), and tetradecamer (P(14)), formed by the NAC domains of α-synuclein. Besides, center-of-mass pulling and umbrella sampling simulation methods have also been employed to characterize the mechanistic pathway of peptide association/dissociation and the corresponding free energy profiles. Structural analysis showed that the disordered C-terminal loop and the central core regions of the peptide units lead to more flexible and distorted structures of the lower order protofilaments (P(4) and P(6)) as compared to the higher order ones. Interestingly, our calculation shows the presence of multiple distinctly populated conformational states for the lower order protofilament P(4), which may drive the oligomerization process along multiple pathways to form different polymorphic α-synuclein fibrillar structures. It is further observed that the nonpolar interaction between the peptides and the corresponding nonpolar solvation free energy play a dominant role in stabilizing the aggregated protofilaments. Importantly, our result showed that reduced cooperativity during the binding of a peptide unit beyond a critical size of the protofilament (P(12)) leads to less favorable binding free energy of a peptide.

CD19 CAR antigen engagement mechanisms and affinity tuning

Chimeric antigen receptor (CAR) T cell therapy relies on T cells that are guided by synthetic receptors to target and lyse cancer cells. CARs bind to cell surface antigens through an scFv (binder), the affinity of which is central to determining CAR T cell function and therapeutic success. CAR T cells targeting CD19 were the first to achieve marked clinical responses in patients with relapsed/refractory B cell malignancies and to be approved by the U.S. Food and Drug Administration (FDA). We report cryo-EM structures of CD19 antigen with the binder FMC63, which is used in four FDA-approved CAR T cell therapies (Kymriah, Yescarta, Tecartus, and Breyanzi), and the binder SJ25C1, which has also been used extensively in multiple clinical trials. We used these structures for molecular dynamics simulations, which guided creation of lower- or higher-affinity binders, and ultimately produced CAR T cells endowed with distinct tumor recognition sensitivities. The CAR T cells exhibited different antigen density requirements to trigger cytolysis and differed in their propensity to prompt trogocytosis upon contacting tumor cells. Our work shows how structural information can be applied to tune CAR T cell performance to specific target antigen densities.

Solvation free energy arithmetic for small organic molecules

Solvent-mediated interactions contribute to ligand binding affinities in computational drug design and provide a challenge for theoretical predictions. In this study, we analyze the solvation free energy of benzene derivatives in water to guide the development of predictive models for solvation free energies and solvent-mediated interactions. We use a spatially resolved analysis of local solvation free energy contributions and define solvation free energy arithmetic, which enable us to construct additive models to describe the solvation of complex compounds. The substituents analyzed in this study are carboxyl and nitro-groups due to their similar sterical requirements but distinct interactions with water. We find that nonadditive solvation free energy contributions are primarily attributed to electrostatics, which are qualitatively reproduced with computationally efficient continuum models. This suggests a promising route for the development of efficient and accurate models for the solvation of complex molecules with varying substitution patterns using solvation arithmetic.

Dual-Reporter System for Real-Time Monitoring of SARS-CoV-2 Main Protease Activity in Live Cells Enables Identification of an Allosteric Inhibition Path

The SARS-CoV-2 pandemic is an ongoing threat to global health, and the continuing emergence of contagious variants highlights the urgent need for additional antiviral therapy to attenuate COVID-19 disease. The SARS-CoV-2 main protease (3CL^pro) presents an attractive target for such therapy due to its high sequence conservation and key role in the viral life cycle. In this study, we designed a fluorescent-luminescent cell-based reporter for the detection and quantification of 3CL^pro intracellular activity. Employing this platform, we examined the efficiency of known protease inhibitors against 3CL^pro and further identified potent inhibitors through high-throughput chemical screening. Computational analysis confirmed a direct interaction of the lead compounds with the protease catalytic site and identified a prototype for efficient allosteric inhibition. These developments address a pressing need for a convenient sensor and specific targets for both virus detection and rapid discovery of potential inhibitors.

Multi-Level High-Throughput Screening for Discovery of Ligands That Inhibit Insulin Aggregation

We have developed a multi-level virtual screening protocol to identify lead molecules from the FDA inactives database that can inhibit insulin aggregation. The method is based on the presence of structural and interaction specificity in non-native aggregation pathway protein-protein interactions. Some key challenges specific to the present problem, when compared with native protein association, include structural heterogeneity of the protein species involved, multiple association pathways, and relatively higher probability of conformational rearrangement of the association complex. In this multi-step method, the inactives database was first screened using the dominant pharmacophore features of previously identified molecules shown to significantly inhibit insulin aggregation nucleation by binding to its aggregation-prone conformers. We then performed ensemble docking of several low-energy ligand conformations on these aggregation-prone conformers followed by molecular dynamics simulations and binding affinity calculations on a subset of docked complexes to identify a final set of five potential lead molecules to inhibit insulin aggregation nucleation. Their effect on aggregation inhibition was extensively investigated by incubating insulin under aggregation-prone aqueous buffer conditions (low pH, high temperature). Aggregation kinetics were characterized using size exclusion chromatography and Thioflavin T fluorescence assay, and the secondary structure was determined using circular dichroism spectroscopy. Riboflavin provided the best aggregation inhibition, with 85% native monomer retention after 48 h incubation under aggregation-prone conditions, whereas the no-ligand formulation showed complete monomer loss after 36 h. Further, insulin incubated with two of the screened inactives (aspartame, riboflavin) had the characteristic α-helical dip in CD spectra, while the no-ligand formulation showed a change to β-sheet rich conformations.

Counteractive Effects of Choline Geranate (CAGE) ILs and Ethanol on Insulin's Stability-A Leap Forward towards Oral Insulin Formulation

Choline geranate (CAGE) ionic liquids (ILs) stabilize insulin, thereby aiding its oral delivery, whereas ethanol (EtOH) affects its stability by disrupting the hydrophobic interactions. In this study, cognizance of the stabilization mechanism of insulin dimer in the presence of both CAGE ILs and EtOH mixtures is achieved through biased and unbiased molecular dynamics (MD) simulations. Here, two order parameters are employed to study the insulin dimer dissociation using well-tempered metadynamics (WT-MetaD). The stability of insulin is found to be strongly maintained until a 0.20 mole fraction of EtOH. Besides, higher concentrations of EtOH marginally affect the insulin stability. Moreover, geranate anions form a higher number of H-bonding interactions with water molecules, which aids insulin stabilization. Conversely, the addition of EtOH minimizes the water-mediated H-bonding interactions of geranate. Additionally, geranate traps the EtOH molecules, thereby preventing the interactions between insulin and EtOH. Furthermore, the free energy landscape (FEL) reveals the absence of dimer dissociation along with noticeable deviations in the distances R and the number of contacts Q. The dimerization free energy of insulin was calculated to be −16.1 kcal/mol at a 0.20 mole fraction of EtOH. Moreover, increments in mole fractions of EtOH effectuate a decrease in the insulin stability. Thus, the present study represents CAGE ILs as efficient insulin dimer stabilizes at low concentrations of EtOH.

Hazardous Shortcuts in Standard Binding Free Energy Calculations

Calculating the standard binding free energies of protein-protein and protein-ligand complexes from atomistic molecular dynamics simulations in explicit solvent is a problem of central importance in computational biophysics. A rigorous strategy for carrying out such calculations is the so-called "geometrical route". In this method, two molecular objects are progressively separated from one another in the presence of orientational and conformational restraints serving to control the change in configurational entropy that accompanies the dissociation process, thereby allowing the computations to converge within simulations of affordable length. Although the geometrical route provides a rigorous theoretical framework, a tantalizing computational shortcut consists of simply leaving out such orientational and conformational degrees of freedom during the separation process. Here the accuracy and convergence of the two approaches are critically compared in the case of two protein-ligand complexes (Abl kinase-SH3:p41 and MDM2-p53:NVP-CGM097) and three protein-protein complexes (pig insulin dimer, SARS-CoV-2 spike RBD:ACE2, and CheA kinase-P2:CheY). The results of the simulations that strictly follow the geometrical route match the experimental standard binding free energies within chemical accuracy. In contrast, simulations bereft of geometrical restraints converge more poorly, yielding inconsistent results that are at variance with the experimental measurements. Furthermore, the orientational and positional time correlation functions of the protein in the unrestrained simulations decay over several microseconds, a time scale that is far longer than the typical simulation times of the geometrical route, which explains why those simulations fail to sample the relevant degrees of freedom during the separation process of the complexes.

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.

Fragment hopping protocol for the design of small-molecule protein-protein interaction inhibitors

Fragment-based ligand discovery (FBLD) is one of the most successful approaches to designing small-molecule protein-protein interaction (PPI) inhibitors. The incorporation of computational tools to FBLD allows the exploration of chemical space in a time- and cost-efficient manner. Herein, a computational protocol for the development of small-molecule PPI inhibitors using fragment hopping, a fragment-based de novo design approach, is described and a case study is presented to illustrate the efficiency of this protocol. Fragment hopping facilitates the design of PPI inhibitors from scratch solely based on key binding features in the PPI complex structure. This approach is an open system that enables the inclusion of different state-of-the-art programs and softwares to improve its performances.

Quantitative molecular simulations

All-atom simulations can provide molecular-level insights into the dynamics of gas-phase, condensed-phase and surface processes. One important requirement is a sufficiently realistic and detailed description of the underlying intermolecular interactions. The present perspective provides an overview of the present status of quantitative atomistic simulations from colleagues' and our own efforts for gas- and solution-phase processes and for the dynamics on surfaces. Particular attention is paid to direct comparison with experiment. An outlook discusses present challenges and future extensions to bring such dynamics simulations even closer to reality.

Computation of the Protein Conformational Transition Pathway on Ligand Binding by Linear Response-Driven Molecular Dynamics

While extremely important for relating the protein structure to its biological function, determination of the protein conformational transition pathway upon ligand binding is made difficult due to the transient nature of intermediates, a large and rugged conformational space, and coupling between protein dynamics and ligand-protein interactions. Existing methods that rely on prior knowledge of the bound (holo) state structure are restrictive. A second concern relates to the correspondence of intermediates obtained to the metastable states on the apo → holo transition pathway. Here, we have taken the protein apo structure and ligand-binding site as only inputs and combined an elastic network model (ENM) representation of the protein Hamiltonian with linear response theory (LRT) for protein-ligand interactions to identify the set of slow normal modes of protein vibrations that have a high overlap with the direction of the protein conformational change. The structural displacement along the chosen direction was performed using excited normal modes molecular dynamics (MDeNM) simulations rather than by the direct use of LRT. Herein, the MDeNM excitation velocity was optimized on-the-fly on the basis of its coupling to protein dynamics and ligand-protein interactions. Thus, a determined set of structures was validated against crystallographic and simulation data on four protein-ligand systems, namely, adenylate kinase-di(adenosine-5')pentaphosphate, ribose binding protein-β-d-ribopyranose, DNA β-glucosyltransferase-uridine-5'-diphosphate, and G-protein α subunit-guanosine-5'-triphosphate, which present important differences in protein conformational heterogeneity, ligand binding mechanism, viz. induced-fit or conformational selection, extent, and nonlinearity in protein conformational changes upon ligand binding, and presence of allosteric effects. The obtained set of intermediates was used as an input to path metadynamics simulations to obtain the free energy profile for the apo → holo transition.

Atomistic Simulations for Reactions and Vibrational Spectroscopy in the Era of Machine Learning─Quo Vadis?

Atomistic simulations using accurate energy functions can provide molecular-level insight into functional motions of molecules in the gas and in the condensed phase. This Perspective delineates the present status of the field from the efforts of others and some of our own work and discusses open questions and future prospects. The combination of physics-based long-range representations using multipolar charge distributions and kernel representations for the bonded interactions is shown to provide realistic models for the exploration of the infrared spectroscopy of molecules in solution. For reactions, empirical models connecting dedicated energy functions for the reactant and product states allow statistically meaningful sampling of conformational space whereas machine-learned energy functions are superior in accuracy. The future combination of physics-based models with machine-learning techniques and integration into all-purpose molecular simulation software provides a unique opportunity to bring such dynamics simulations closer to reality.

Tug-of-War between Internal and External Frictions and Viscosity Dependence of Rate in Biological Reactions

The role of water in biological processes is studied in three reactions, namely, the Fe-CO bond rupture in myoglobin, GB1 unfolding, and insulin dimer dissociation. We compute both internal and external components of friction on relevant reaction coordinates. In all of the three cases, the cross-correlation between forces from protein and water is found to be large and negative that serves to reduce the total friction significantly, increase the calculated reaction rate, and weaken solvent viscosity dependence. The computed force spectrum reveals bimodal 1/f noise, suggesting the use of a non-Markovian rate theory.

Proteomic Changes to the Updated Discovery of Engineered Insulin and Its Analogs: Pros and Cons

The destruction of β-cells of the pancreas leads to either insulin shortage or the complete absence of insulin, which in turn causes diabetes Mellitus. For treating diabetes, many trials have been conducted since the 19th century until now. In ancient times, insulin from an animal's extract was taken to treat human beings. However, this resulted in some serious allergic reactions. Therefore, scientists and researchers have tried their best to find alternative ways for managing diabetes with progressive advancements in biotechnology. However, a lot of research trials have been conducted, and they discovered more progressed strategies and approaches to treat type I and II diabetes with satisfaction. Still, investigators are finding more appropriate ways to treat diabetes accurately. They formulated insulin analogs that mimic the naturally produced human insulin through recombinant DNA technology and devised many methods for appropriate delivery of insulin. This review will address the following questions: What is insulin preparation? How were these devised and what are the impacts (both positive and negative) of such insulin analogs against TIDM (type-I diabetes mellitus) and TIIDM (type-II diabetes mellitus)? This review article will also demonstrate approaches for the delivery of insulin analogs into the human body and some future directions for further improvement of insulin treatment.

Tracking Confined Reaction Based on Host-Guest Interaction Using Single-Molecule Conductance Measurement

The host-guest interaction acts as an essential part of supramolecular chemistry, which can be applied in confined reaction. However, it is challenging to obtain the dynamic process during confined reactions below micromolar concentrations. In this work, a new method is provided to characterize the dimerization process of the guest 1,2-bis(4-pyridinyl) ethylene in host cucurbit[8]curil using scanning tunneling microscope-break junction (STM-BJ) technique. The guest reaction kinetics is quantitatively by nuclear magnetic resonance (NMR) and in situ single-molecule junctions. It is found that in the single-molecule conductance measurements, the electrical signals of the reactants with a concentration as low as 5 × 10^-6  m are clearly detected, and the reaction kinetics at micromolar concentrations are further obtained. However, in NMR measurements, the characteristic peak signal of the reactants is undetectable when the concentration of the reactants is lower than 0.5 × 10^-3  m and it cannot be quantified. In addition, the strong electric field from the nanogap accelerates the reaction. This work reveals that single-molecule STM-BJ techniques are more sensitive for tracking confined reactions than that by NMR techniques and can be used to study effect of extremely strong electric field on kinetics.

The molecular mechanism behind the stabilization of insulin by choline and geranate (CAGE) ionic liquids - computational insights into oral insulin drug formulation

Insulin is a principal hormone that is involved in the regulation of glucose levels in the blood. Oral insulin formulation is a recent development in drug delivery systems. Biocompatible choline-based ionic liquids (ILs) show promising antibacterial activity and are useful for oral and transdermal drug delivery applications. Choline and geranate (CAGE) ILs enhance the stability and oral efficacy of insulin delivery. The molecular mechanism behind insulin formulation in the oral form is at issue. In the present work, the molecular-level understanding of CAGE ILs in insulin is scrutinized by employing atomistic molecular dynamics (MD) simulations. To identify the stability of insulin in an IL medium, we have studied a series of concentration (mole fraction 0.05-1.00) of CAGE ILs with an insulin dimer. It can be well evidenced from the experimental reports that in an aqueous medium, there is a refashioning of CAGE nanostructures at 0.50 mole fraction. It is found from our calculations that the first solvation shell of insulin is readily occupied by choline and geranate ions in the presence of water. Moreover, the geranate ions strongly interacted with the water molecules and thereby, eliminating the intermolecular hydrogen bonding (H-bonding) interactions towards the insulin at 0.30-0.50 mole fraction of CAGE ILs. The most desirable 0.30-0.50 mole fraction of CAGE invigorates water-mediated H-bonding interactions with geranate ions, which also enhances the electrostatic behavior around the vicinity of the insulin dimer. These important findings can help in the development of oral insulin drug delivery and related applications.

Structural Stability of Insulin Oligomers and Protein Association-Dissociation Processes: Free Energy Landscape and Universal Role of Water

Association and dissociation of proteins are important biochemical events. In this Feature Article, we analyze the available studies of these processes for insulin oligomers in aqueous solution. We focus on the solvation of the insulin monomer in water, stability and dissociation of its dimer, and structural integrity of the hexamer. The intricate role of water in solvation of the dimer- and hexamer-forming surfaces, in long-range interactions between the monomers and the stability of the oligomers, is discussed. Ten water molecules inside the central cavity stabilize the structure of the insulin hexamer. We discuss how different order parameters can be used to understand the dissociation of the insulin dimer. The calculation of the rate using a recently computed multidimensional free energy provides considerable insight into the interplay between protein and water dynamics.

Calculation of CYP450 protein-ligand binding and dissociation free energy paths

The function of an enzyme depends on its dynamic structure, and the catalytic mechanism has long been an active focus of research. The principle for interpreting protein selectivity and fidelity stems from optimization of the active site upon protein-substrate complexation, i.e., a lock-and-key configuration, on which most protein-substrate molecule binding recognition, and hence drug discovery, relies. Yet another thought has been to incorporate the protein folding interior tunnels for stereo- and regio-selectivity along the protein-substrate or protein-ligand/inhibitor binding process. Free energy calculations provide valuable information for molecular recognition and protein-ligand binding dynamics and kinetics. In this study, we focused on the kinetics of cytochrome P450 proteins (CYP450s) and the protein interior tunnel structure-dynamics relationship in terms of the substrate binding and leaving mechanism. A case in point is given by the prostaglandin H₂ (PGH₂) homologous isomerase of prostacyclin synthase. To calculate the reactant and product traversing the tunnels to and from the heme site, the free energy paths and tunnel potentials of mean force are constructed from steered molecular dynamics simulations and adaptive basing force umbrella sampling simulations. We explore the binding tunnels and critical residue lining characteristics for the ligand traverse and the underlying mechanism of CYP450 activity. Our theoretical analysis provides insights into the decisive role of the substrate tunnel binding process of the CYP450 mechanism and may be useful in drug design and protein engineering contexts.

Unusual mode of dimerization of retinitis pigmentosa-associated F220C rhodopsin

Mutations in the G protein-coupled receptor (GPCR) rhodopsin are a common cause of autosomal dominant retinitis pigmentosa, a blinding disease. Rhodopsin self-associates in the membrane, and the purified monomeric apo-protein opsin dimerizes in vitro as it transitions from detergent micelles to reconstitute into a lipid bilayer. We previously reported that the retinitis pigmentosa-linked F220C opsin mutant fails to dimerize in vitro, reconstituting as a monomer. Using fluorescence-based assays and molecular dynamics simulations we now report that whereas wild-type and F220C opsin display distinct dimerization propensities in vitro as previously shown, they both dimerize in the plasma membrane of HEK293 cells. Unexpectedly, molecular dynamics simulations show that F220C opsin forms an energetically favored dimer in the membrane when compared with the wild-type protein. The conformation of the F220C dimer is unique, with transmembrane helices 5 and 6 splayed apart, promoting widening of the intracellular vestibule of each protomer and influx of water into the protein interior. FRET experiments with SNAP-tagged wild-type and F220C opsin expressed in HEK293 cells are consistent with this conformational difference. We speculate that the unusual mode of dimerization of F220C opsin in the membrane may have physiological consequences.

Computational IR Spectroscopy of Insulin Dimer Structure and Conformational Heterogeneity

We have investigated the structure and conformational dynamics of insulin dimer using a Markov state model (MSM) built from extensive unbiased atomistic molecular dynamics simulations and performed infrared spectral simulations of the insulin MSM to describe how structural variation within the dimer can be experimentally resolved. Our model reveals two significant conformations to the dimer: a dominant native state consistent with other experimental structures of the dimer and a twisted state with a structure that appears to reflect a ∼55° clockwise rotation of the native dimer interface. The twisted state primarily influences the contacts involving the C-terminus of insulin's B chain, shifting the registry of its intermolecular hydrogen bonds and reorganizing its side-chain packing. The MSM kinetics predict that these configurations exchange on a 14 μs time scale, largely passing through two Markov states with a solvated dimer interface. Computational amide I spectroscopy of site-specifically ¹³C¹⁸O labeled amides indicates that the native and twisted conformation can be distinguished through a series of single and dual labels involving the B24F, B25F, and B26Y residues. Additional structural heterogeneity and disorder is observed within the native and twisted states, and amide I spectroscopy can also be used to gain insight into this variation. This study will provide important interpretive tools for IR spectroscopic investigations of insulin structure and transient IR kinetics experiments studying the conformational dynamics of insulin dimer.

Evaluating the Efficiency of the Martini Force Field to Study Protein Dimerization in Aqueous and Membrane Environments

Protein-protein complex assembly is one of the major drivers of biological response. Understanding the mechanisms of protein oligomerization/dimerization would allow one to elucidate how these complexes participate in biological activities and could ultimately lead to new approaches in designing novel therapeutic agents. However, determining the exact association pathways and structures of such complexes remains a challenge. Here, we use parallel tempering metadynamics simulations in the well-tempered ensemble to evaluate the performance of Martini 2.2P and Martini open-beta 3 (Martini 3) force fields in reproducing the structure and energetics of the dimerization process of membrane proteins and proteins in an aqueous solution in reasonable accuracy and throughput. We find that Martini 2.2P systematically overestimates the free energy of association by estimating large barriers in distinct areas, which likely leads to overaggregation when multiple monomers are present. In comparison, the less viscous Martini 3 results in a systematic underestimation of the free energy of association for proteins in solution, while it performs well in describing the association of membrane proteins. In all cases, the near-native dimer complexes are identified as minima in the free energy surface albeit not always as the lowest minima. In the case of Martini 3, we find that the spurious supramolecular protein aggregation present in Martini 2.2P multimer simulations is alleviated and thus this force field may be more suitable for the study of protein oligomerization. We propose that the use of enhanced sampling simulations with a refined coarse-grained force field and appropriately defined collective variables is a robust approach for studying the protein dimerization process, although one should be cautious of the ranking of energy minima.

Spectroscopy, Dynamics, and Hydration of S-Nitrosylated Myoglobin

S-Nitrosylation, the covalent addition of NO to the thiol side chain of cysteine, is an important post-transitional modification that can alter the function of various proteins. The structural dynamics and vibrational spectroscopy of S-nitrosylation in the condensed phase are investigated for the methyl-capped cysteine model system and for myoglobin. Using conventional point charge and physically more realistic multipolar force fields for the -SNO group, it is found that the SN- and NO-stretch and the SNO-bend vibrations can be located and distinguished from the other protein modes for simulations of MbSNO at 50 K. The finding of stable cis- and trans-MbSNO agrees with experimental findings on other proteins as is the observation of buried -SNO. For MbSNO the observed relocation of the EF loop in the simulations by ∼3 Å is consistent with the available X-ray structure, and the conformations adopted by the -SNO label are in good overall agreement with the X-ray structure. Despite the larger size of the -SNO group compared with -SH, MbSNO recruits more water molecules in the first two hydration shells due to stronger electrostatic interactions. Similarly, when comparing the hydration between the A- and H-helices, they differ by up to 30% between WT and MbSNO. This suggests that local hydration can also be significantly modulated through nitrosylation.

On the vibrational free energy of hydrated proteins

When the hydration shell of a protein is filled with at least 0.6 gram of water per gram of protein, a significant anti-correlation between the vibrational free energy and the potential energy of energy-minimized conformers is observed. This means that low potential energy, well-hydrated, protein conformers tend to be more rigid than high-energy ones. On the other hand, in the case of CASP target 624, when its hydration shell is filled, a significant energy gap is observed between the crystal structure and the best conformers proposed during the prediction experiment, strongly suggesting that including explicit water molecules may help identifying unlikely conformers among good-looking ones.

Dynamics and Infrared Spectrocopy of Monomeric and Dimeric Wild Type and Mutant Insulin

The infrared spectroscopy and dynamics of -CO labels in wild type and mutant insulin monomer and dimer are characterized from molecular dynamics simulations using validated force fields. It is found that the spectroscopy of monomeric and dimeric forms in the region of the amide-I vibration differs for residues B24-B26 and D24-D26, which are involved in dimerization of the hormone. Also, the spectroscopic signatures change for mutations at position B24 from phenylalanine, which is conserved in many organisms and is known to play a central role in insulin aggregation, to alanine or glycine. Using three different methods to determine the frequency trajectories (solving the nuclear Schrödinger equation on an effective 1-dimensional potential energy curve, using instantaneous normal modes, and using parametrized frequency maps) leads to the same overall conclusions. The spectroscopic response of monomeric WT and mutant insulin differs from that of their respective dimers, and the spectroscopy of the two monomers in the dimer is also not identical. For the WT and F24A and F24G monomers, spectroscopic shifts are found to be ∼20 cm^-1 for residues (B24-B26) located at the dimerization interface. Although the crystal structure of the dimer is that of a symmetric homodimer, dynamically the two monomers are not equivalent on the nanosecond time scale. Together with earlier work on the thermodynamic stability of the WT and the same mutants, it is concluded that combining computational and experimental infrared spectroscopy provides a potentially powerful way to characterize the aggregation state and dimerization energy of modified insulins.

Amyloid-Like Peptide Aggregates

Self-assembly of proteins and peptides into the amyloid fold is a widespread phenomenon in the natural world. The structural hallmark of self-assembly into amyloid fibrillar assemblies is the cross-beta motif, which conveys distinct morphological and mechanical properties. The amyloid fibril formation has contrasting results depending on the organism, in the sense that it can bestow an organism with the advantages of mechanical strength and improved functionality or, on the contrary, could give rise to pathological states. In this chapter we review the existing information on amyloid-like peptide aggregates, which could either be derived from protein sequences, but also could be rationally or de novo designed in order to self-assemble into amyloid fibrils under physiological conditions. Moreover, the development of self-assembled fibrillar biomaterials that are tailored for the desired properties towards applications in biomedical or environmental areas is extensively analyzed. We also review computational studies predicting the amyloid propensity of the natural amino acid sequences and the structure of amyloids, as well as designing novel functional amyloid materials.

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.

Residue-Residue Mutual Work Analysis of Retinal-Opsin Interaction in Rhodopsin: Implications for Protein-Ligand Binding

Energetic contributions at the single-residue level for retinal-opsin interactions in rhodopsin were studied by combining molecular dynamics simulations, transition path sampling, and a newly developed energy decomposition approach. The virtual work at an infinitesimal time interval was decomposed into the work components on one residue due to its interaction with another residue, which were then averaged over the transition path ensemble along a proposed reaction coordinate. Such residue-residue mutual work analysis on 62 residues within the active center of rhodopsin resulted in a very sparse interaction matrix, which is generally not symmetric but antisymmetric to some extent. Fourteen residues were identified to be major players in retinal relaxation along a plausible pathway from bathorhodopsin to the blue-shifted intermediate, which is in good agreement with an existing NMR study. Based on the matrix of mutual work, a comprehensive network was constructed to provide detailed insights into the chromophore-protein interaction from a viewpoint of energy flow.

Calculating the absolute binding free energy of the insulin dimer in an explicit solvent

Insulin is a significant hormone in the regulation of glucose level in the blood. Its monomers bind to each other to form dimers or hexamers through a complex process. To study the binding of the insulin dimer, we first calculate its absolute binding free energy by the steered molecular dynamics method and the confinement method based on a fictitious thermodynamic cycle. After considering some special correction terms, the final calculated binding free energy at 298 K is −8.97 ± 1.41 kcal mol⁻¹, which is close to the experimental value of −7.2 ± 0.8 kcal mol⁻¹. Furthermore, we discuss the important residue–residue interactions between the insulin monomers, including hydrophobic interactions, π–π interactions and hydrogen bond interactions. The analysis reveals five key residues, Vla^B12, Tyr^B16, Phe^B24, Phe^B25, and Tyr^B26, for the dimerization of the insulin. We also perform MM-PBSA calculations for the wild-type dimer and some mutants and study the roles of the key residues by the change of the binding energy of the insulin dimer.

In this paper, we calculate the absolute binding free energy of an insulin dimer by steered MD method. The result of −8.97 kcal mol⁻¹ is close to the experimental value −7.2 kcal mol⁻¹. We also analyze the residue–residue interactions.

Inhibitor discovery for the E. coli meningitis virulence factor IbeA from homology modeling and virtual screening

Escherichia coli (E. coli) K1 is the most common Gram-negative bacteria cause of neonatal meningitis. The penetration of E. coli through the blood-brain barrier is a key step of the meningitis pathogenesis. A host receptor protein, Caspr1, interacts with the E. coli virulence factor IbeA and thus facilitates bacterial penetration through the blood-brain barrier. Based on this result, we have now predicted the binding pattern between Caspr1 and IbeA by an integrated computational protocol. Based on the predicted model, we have identified a putative molecular binding pocket in IbeA, that directly bind with Caspr1. This evidence indicates that the IbeA (229-343aa) region might play a key role in mediating the bacteria invasion. Virtual screening with the molecular model was conducted to search for potential inhibitors from 213,279 commercially available chemical compounds. From the top 50 identified compounds, 9 demonstrated a direct binding ability to the residues within the Caspr1 binding site on IbeA. By using human brain microvascular endothelial cells (hBMEC) with E. coli strain RS218, four molecules were characterized that significantly attenuated the bacteria invasions at concentrations devoid of cell toxicity. Our study provides useful structural information for understanding the pathogenesis of neonatal meningitis, and have identified drug-like compounds that could be used to develop effective anti-meningitis agents.

Molecular dynamics investigations of oligosaccharides recognized by family 16 and 22 carbohydrate binding modules

As a non-catalytic domain, carbohydrate binding modules (CBMs) are often considered to play some key roles in the degradation and recognition of polysaccharides catalyzed by cellulases. In this work, we investigated the recognition dynamics of cello- or xylo-saccharides by two typical CBMs (CBM16-1 and CBM22-2), which are grouped into Type B CBMs. By combining extensive molecular dynamics, principle component analysis, and binding free energy calculations, we constructed several complex models of the two CBMs in both complex cello- and xylo-oligosaccharides. The corresponding substrate recognition affinity and critical residues having significant contributions were systematically investigated. The residues containing aromatic side chain groups were shown to contribute significantly to substrate binding. The calculated binding free energies were in fairly good agreement with the experimental measurements with the absolute mean error of 0.69 kcal mol^-1. The overall electrostatic interactions were shown to have negative effects on substrate recognition. Further metadynamics simulations revealed the substrate dissociation process.

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.

Configurational Entropy Components and Their Contribution to Biomolecular Complex Formation

Configurational entropy change is a central constituent of the free energy change in noncovalent interactions between biomolecules. Due to both experimental and computational limitations, however, the impact of individual contributions to configurational entropy change remains underexplored. Here, we develop a novel, fully analytical framework to dissect the configurational entropy change of binding into contributions coming from molecular internal and external degrees of freedom. Importantly, this framework accounts for all coupled and uncoupled contributions in the absence of an external field. We employ our parallel implementation of the maximum information spanning tree algorithm to provide a comprehensive numerical analysis of the importance of the individual contributions to configurational entropy change on an extensive set of molecular dynamics simulations of protein binding processes. Contrary to commonly accepted assumptions, we show that different coupling terms contribute significantly to the overall configurational entropy change. Finally, while the magnitude of individual terms may be largely unpredictable a priori, the total configurational entropy change can be well approximated by rescaling the sum of uncoupled contributions from internal degrees of freedom only, providing support for NMR-based approaches for configurational entropy change estimation.

Effect of ethanol on insulin dimer dissociation

Insulin-dimer dissociation is an essential biochemical process required for the activity of the hormone. We investigate this dissociation process at the molecular level in water and at the same time, in 5% and 10% water-ethanol mixtures. We compute the free energy surface of the protein dissociation processes by employing biased molecular dynamics simulation. In the presence of ethanol (EtOH), we observe a marked lowering in the free energy barrier of activation of dimer dissociation from that in the neat water, by as much as ∼50%, even in the 5% water-ethanol solution. In addition, ethanol is found to induce significant changes in the dissociation pathway. We extract the most probable conformations of the intermediate states along the minimum energy pathway in the case of all the three concentrations (EtOH mole fractions 0, 5, and 10). We explore the change in microscopic structures that occur in the presence of ethanol. Interestingly, we discover a stable intermediate state in the water-ethanol binary mixture where the centers of the monomers are separated by about 3 nm and the contact order parameter is close to zero. This intermediate is stabilized by the wetting of the interface between the two monomers by the preferential distribution of ethanol and water molecules. This wetting serves to reduce the free energy barrier significantly and thus results in an increase in the rate of dimer dissociation. We also analyze the solvation of the two monomers during the dissociation and both the proteins' departure from the native state configuration to obtain valuable insights into the dimer dissociation processes.

Molecular dynamics and free energy studies on the Drosophila melanogaster and Leptinotarsa decemlineata ecdysone receptor complexed with agonists: Mechanism for binding and selectivity

The ecdysone receptor is a nuclear hormone receptor that plays a pivotal role in the insect metamorphosis and development. To address the molecular mechanisms of binding and selectivity, the interactions of two typical agonists Ponasterone A and 20-Hydroxyecdysone with Drosophila melanogaster (DME) and Leptinotarsa decemlineata ecdysone (LDE) receptors were investigated by homology modeling, molecular docking, molecular dynamic simulation, and thermodynamic analysis. We discover that 1) the L5-loop, L11-loop, and H12 helix for DME, L7-loop, and L11-loop for LDE are more flexible, which affect the global dynamics of the ligand-binding pocket, thus facilitating the ligand recognition of ecdysone receptor; 2) several key residues (Thr55/Thr37, Phe109/Phe91, Arg95/Arg77, Arg99/Arg81, Phe108/Leu90, and Ala110/Val92) are responsible for the binding of the proteins; 3) the binding-free energy is mainly contributed by the van der Waals forces as well as the electrostatic interactions of ligand and receptor; 4) the computed binding-free energy difference between DME-C1 and LDE-C1 is -4.65 kcal/mol, explains that C1 can form many more interactions with the DME; 5) residues Phe108/Leu90 and Ala110/Val92 have relatively position and orientation difference in the two receptors, accounting most likely for the ligand selectivity of ecdysone receptor from different orders of insects. This study underscores the expectation that different insect pests should be able to discriminate among compounds from different as yet undiscovered compounds, and the results firstly show a structural and functional relay between the agonists and receptors (DME and LDE), which can provide an avenue for the development of target-specific insecticides. Communicated by Ramaswamy H. Sarma.