The switch states of the GDP-bound HRAS affected by point mutations: a study from Gaussian accelerated molecular dynamics simulations and free energy landscapes

Point mutations play a vital role in the conformational transformation of HRAS. In this work, Gaussian accelerated molecular dynamics (GaMD) simulations followed by constructions of free energy landscapes (FELs) were adopted to explore the effect of mutations D33K, A59T and L120A on conformation states of the GDP-bound HRAS. The results from the post-processing analyses on GaMD trajectories suggest that mutations alter the flexibility and motion modes of the switch domains from HRAS. The analyses from FELs show that mutations induce more disordered states of the switch domains and affect interactions of GDP with HRAS, implying that mutations yield a vital effect on the binding of HRAS to effectors. The GDP-residue interaction network revealed by our current work indicates that salt bridges and hydrogen bonding interactions (HBIs) play key roles in the binding of GDP to HRAS. Furthermore, instability in the interactions of magnesium ions and GDP with the switch SI leads to the extreme disorder of the switch domains. This study is expected to provide the energetic basis and molecular mechanism for further understanding the function of HRAS.Communicated by Ramaswamy H. Sarma.

Deciphering the molecular choreography of Janus kinase 2 inhibition via Gaussian accelerated molecular dynamics simulations: a dynamic odyssey

The Janus kinases (JAK) are crucial targets in drug development for several diseases. However, accounting for the impact of possible structural rearrangements on the binding of different kinase inhibitors is complicated by the extensive conformational variability of their catalytic kinase domain (KD). The dynamic KD contains mainly four prominent mobile structural motifs: the phosphate-binding loop (P-loop), the αC-helix within the N-lobe, the Asp-Phe-Gly (DFG) motif, and the activation loop (A-loop) within the C-lobe. These distinct structural orientations imply a complex signal transmission path for regulating the A-loop's flexibility and conformational preference for optimal JAK function. Nevertheless, the precise dynamical features of the JAK induced by different types of inhibitors still remain elusive. We performed comparative, microsecond-long, Gaussian accelerated molecular dynamics simulations in triplicate of three phosphorylated JAK2 systems: the KD alone, type-I ATP-competitive inhibitor (CI) bound KD in the catalytically active DFG-in conformation, and the type-II inhibitor (AI) bound KD in the catalytically inactive DFG-out conformation. Our results indicate significant conformational variations observed in the A-loop and αC helix motions upon inhibitor binding. Our studies also reveal that the DFG-out inactive conformation is characterized by the closed A-loop rearrangement, open catalytic cleft of N and C-lobe, the outward movement of the αC helix, and open P-loop states. Moreover, the outward positioning of the αC helix impacts the hallmark salt bridge formation between Lys882 and Glu898 in an inactive conformation. Finally, we compared their ligand binding poses and free energy by the MM/PBSA approach. The free energy calculations suggested that the AI's binding affinity is higher than CI against JAK2 due to an increased favorable contribution from the total non-polar interactions and the involvement of the αC helix. Overall, our study provides the structural and energetic insights crucial for developing more promising type I/II JAK2 inhibitors for treating JAK-related diseases.

Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters

Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.

Characterization of Posttranslationally Modified PHF-1 Tau Peptides Using Gaussian Accelerated Molecular Dynamics Simulation

The microtubule-associated protein, Tau, is an intrinsically disordered protein that plays a crucial role in neurodegenerative diseases like Alzheimer's disease. The posttranslational modifications across the Tau protein domains are involved in regulating Tau protein's function and disease onset. Of the various posttranslational modifications at Ser, Thr, and Tyr sites, O-GlcNAcylation and phosphorylation are the most critical ones, playing a vital role in Tau aggregation and tauopathies. To understand the function, it is essential to characterize the structural changes associated with Tau modification. Previous experimental studies have focused on high-resolution nuclear magnetic resonance techniques to structurally characterize the effect of phosphorylation, O-GlcNAcylation, and combination of both PTMs on Tau conformation in small peptides centered on the PHF-1 epitope from amino acid 392 to 411. The structural characterization using atomistic molecular dynamics simulation of such disordered peptides requires long simulation time, proper sampling method, and utilization of appropriate force fields for accurate determination of conformational ensembles, resembling the experimental data. This chapter details the protocol for the structural characterization of modified Tau peptides using the CHARMM36m force field and enhanced sampling methods like Gaussian accelerated molecular dynamics (GaMD) simulation. We have focused on a detailed explanation of the GaMD method and analyses of molecular dynamics trajectories to explain the relationship between two modifications, phospho- and glyco-, at C-terminus of Tau protein and its stable conformation over the longer simulation timeframes. The analyses involve energetics reweighting, clustering of simulation trajectories, and characterization of secondary structure using circular dichroism data from the simulation. The reader can utilize this protocol to investigate the structures of complex proteins, especially the disordered ones.

Molecular Dynamics Activation of γ-Secretase for Cleavage of the Notch1 Substrate

γ-Secretase is an intramembrane aspartyl protease complex that cleaves the transmembrane domain of over 150 peptide substrates, including amyloid precursor protein (APP) and the Notch family of receptors, via two conserved aspartates D257 and D385 in the presenilin-1 (PS1) catalytic subunit. However, while the activation of γ-secretase for cleavage of APP has been widely studied, the cleavage of Notch by γ-secretase remains poorly explored. Here, we combined Gaussian accelerated molecular dynamics (GaMD) simulations and mass spectrometry (MS) analysis of proteolytic products to present the first dynamic models for cleavage of Notch by γ-secretase. MS showed that γ-secretase cleaved the WT Notch at Notch residue G34, while cleavage of the L36F mutant Notch occurred at Notch residue C33. Initially, we prepared our simulation systems starting from the cryoEM structure of Notch-bound γ-secretase (PDB: 6IDF) and failed to capture the proper cleavages of WT and L36F Notch by γ-secretase. We then discovered an incorrect registry of the Notch substrate in the PS1 active site through alignment of the experimental structure of Notch-bound (PDB: 6IDF) and APP-bound γ-secretase (PDB: 6IYC). Every residue of the APP substrate was systematically mutated to the corresponding Notch residue to prepare a resolved model of Notch-bound γ-secretase complexes. GaMD simulations of the resolved model successfully captured γ-secretase activation for proper cleavages of both WT and L36F mutant Notch. Our findings presented here provided mechanistic insights into the structural dynamics and enzyme-substrate interactions required for γ-secretase activation for cleavage of Notch and other substrates.

The role of glycerol-water mixtures in the stability of FKBP12-rapalog-FRB complexes

The thermodynamic and biophysical implications of the introduction of a co-solvent during protein-ligand binding remain elusive. Using ternary complexes of 12-kDa FK506 binding protein (FKBP12), FKBP-rapamycin binding (FRB) domain of the mammalian/mechanistic target of rapamycin (mTOR) kinase, and rapamycin analogs (rapalogs) in glycerol-water mixtures, the influence of solvent composition on ligand binding dynamics was explored. The pharmaceutical potential of rapalogs and the utility of glycerol as a co-solvent in drug delivery applications were critical in deciding the system to be studied. Consolidation of existing studies on rapamycin modification was first performed to strategically design a new rapalog called T1. The results from 100-ns dual-boost Gaussian accelerated molecular dynamics simulations showed that protein stability was induced in the presence of glycerol. Reweighting of the trajectories revealed that the glycerol-rich solvent system lowers the energy barrier in the conformational space of the protein while also preserving native contacts between the ligand and the residues in the binding site. Calculated binding free energies using MM/GBSA also showed that electrostatic energy and polar contribution of solvation energy are heavily influenced by the changes in solvation. Glycerol molecules are preferentially excluded through electrostatic interactions from the solvation shell which induce complex stability as seen in existing experiments. Hence, using glycerol as a co-solvent in rapamycin delivery has a significant role in maintaining stability. In addition, compound T1 is a potential mTORC1-selective inhibitor with strong affinity for the FKBP12-FRB complex. This study aims to provide insights on the design of new rapalogs, and the applicability of glycerol as co-solvent for FKBP12-rapalog-FRB complexes.

Conformational and mechanical stability of the isolated large subunit of membrane-bound [NiFe]-hydrogenase from Cupriavidus necator

Comprising at least a bipartite architecture, the large subunit of [NiFe]-hydrogenase harbors the catalytic nickel-iron site while the small subunit houses an array of electron-transferring Fe-S clusters. Recently, some [NiFe]-hydrogenase large subunits have been isolated showing an intact and redox active catalytic cofactor. In this computational study we have investigated one of these metalloproteins, namely the large subunit HoxG of the membrane-bound hydrogenase from Cupriavidus necator (CnMBH), targeting its conformational and mechanical stability using molecular modelling and long all-atom Gaussian accelerated molecular dynamics (GaMD). Our simulations predict that isolated HoxG is stable in aqueous solution and preserves a large portion of its mechanical properties, but loses rigidity in regions around the active site, in contrast to the MBH heterodimer. Inspired by biochemical data showing dimerization of the HoxG protein and IR measurements revealing an increased stability of the [NiFe] cofactor in protein preparations with higher dimer content, corresponding simulations of homodimeric forms were also undertaken. While the monomeric subunit contains several flexible regions, our data predicts a regained rigidity in homodimer models. Furthermore, we computed the electrostatic properties of models obtained by enhanced sampling with GaMD, which displays a significant amount of positive charge at the protein surface, especially in solvent-exposed former dimer interfaces. These data offer novel insights on the way the [NiFe] core is protected from de-assembly and provide hints for enzyme anchoring to surfaces, which is essential information for further investigations on these minimal enzymes.

Binding modes of GDP, GTP and GNP to NRAS deciphered by using Gaussian accelerated molecular dynamics simulations

Probing binding modes of GDP, GTP and GNP to NRAS are of significance for understanding the regulation mechanism on the activity of RAS proteins. Four separate Gaussian accelerated molecular dynamics (GaMD) simulations were performed on the apo, GDP-, GTP- and GNP-bound NRAS. Dynamics analyses suggest that binding of three ligands highly affects conformational states of the switch domains from NRAS, which disturbs binding of NRAS to its effectors. The analyses of free energy landscapes (FELs) indicate that binding of GDP, GTP and GNP induces more energetic states of NRAS compared to the apo NRAS but the presence of GNP makes the switch domains more ordered than binding of GDP and GNP. The information of interaction networks of ligands with NRAS reveals that the π-π interaction of residue F28 and the salt bridge interactions of K16 and D119 with ligands stabilize binding of GDP, GTP and GNP to NRAS. Meanwhile magnesium ion plays a bridge role in interactions of ligands with NRAS, which is favourable for associations of GDP, GTP and GNP with NRAS. This work is expected to provide useful information for deeply understanding the function and activity of NRAS.

Mechanism of tethered agonist-mediated signaling by polycystin-1

Mutations of polycystin-1 (PC1) are the major cause (85% of cases) of autosomal dominant polycystic kidney disease (ADPKD), which is the fourth leading cause of kidney failure. PC1 is thought to function as an atypical G protein-coupled receptor, yet the mechanism by which PC1 regulates G-protein signaling remains poorly understood. A significant portion of ADPKD mutations of PC1 encode a protein with defects in maturation or reduced function that may be amenable to functional rescue. In this work, we have combined complementary biochemical and cellular assay experiments and accelerated molecular simulations, which revealed an allosteric transduction pathway in activation of the PC1 C-terminal fragment. Our findings will facilitate future rational drug design efforts targeting the PC1 signaling function.

Polycystin-1 (PC1) is an important unusual G protein-coupled receptor (GPCR) with 11 transmembrane domains, and its mutations account for 85% of cases of autosomal dominant polycystic kidney disease (ADPKD). PC1 shares multiple characteristics with Adhesion GPCRs. These include a GPCR proteolysis site that autocatalytically divides these proteins into extracellular, N-terminal, and membrane-embedded, C-terminal fragments (CTF), and a tethered agonist (TA) within the N-terminal stalk of the CTF that is suggested to activate signaling. However, the mechanism by which a TA can activate PC1 is not known. Here, we have combined functional cellular signaling experiments of PC1 CTF expression constructs encoding wild type, stalkless, and three different ADPKD stalk variants with all-atom Gaussian accelerated molecular dynamics (GaMD) simulations to investigate TA-mediated signaling activation. Correlations of residue motions and free-energy profiles calculated from the GaMD simulations correlated with the differential signaling abilities of wild type and stalk variants of PC1 CTF. They suggested an allosteric mechanism involving residue interactions connecting the stalk, Tetragonal Opening for Polycystins (TOP) domain, and putative pore loop in TA-mediated activation of PC1 CTF. Key interacting residues such as N3074–S3585 and R3848–E4078 predicted from the GaMD simulations were validated by mutagenesis experiments. Together, these complementary analyses have provided insights into a TA-mediated activation mechanism of PC1 CTF signaling, which will be important for future rational drug design targeting PC1.

Most Probable Druggable Pockets in Mutant p53-Arg175His Clusters Extracted from Gaussian Accelerated Molecular Dynamics Simulations

p53, a tumor suppressor protein, is essential for preventing cancer development. Enhancing our understanding of the human p53 function and its modifications in carcinogenesis will aid in developing more highly effective strategies for cancer prevention and treatment. In this study, we have modeled five human p53 forms, namely, inactive, distal-active, proximal-active, distal-Arg175His mutant, and proximal-Arg175His mutant forms. These forms have been investigated using Gaussian accelerated molecular dynamics (GaMD) simulations in OPC water model at physiological temperature and pH. Our observations, obtained throughout [Formula: see text] of production run, are in good agreement with the relevant results in the classical molecular dynamics (MD) studies. Therefore, GaMD method is more economic and efficient method than the classical MD method for studying biomolecular systems. The featured dynamics of the five human p53-DBD forms include noticeable conformational changes of L1 and [Formula: see text]-[Formula: see text] loops as well as [Formula: see text]-[Formula: see text] and [Formula: see text]-[Formula: see text] turns. We have identified two clusters that represent two distinct conformational states in each p53-DBD form. The free-energy profiles of these clusters demonstrate the flexibility of the protein to undergo a conformational transition between the two clusters. We have predicted two out of seven possible druggability pockets on the clusters of the Arg175His forms. These two druggability pockets are near the mutation site and are expected to be actual pockets, which will be helpful for the compound clinical progression studies.

Mechanism of RNA recognition by a Musashi RNA-binding protein

The Musashi RNA-binding proteins (RBPs) regulate translation of target mRNAs and maintenance of cell stemness and tumorigenesis. Musashi-1 (MSI1), long considered as an intestinal and neural stem cell marker, has been more recently found to be over expressed in many cancers. It has served as an important drug target for treating acute myeloid leukemia and solid tumors such as ovarian, colorectal and bladder cancer. One of the reported binding targets of MSI1 is Numb, a negative regulator of the Notch signaling. However, the dynamic mechanism of Numb RNA binding to MSI1 remains unknown, largely hindering effective drug design targeting this critical interaction. Here, we have performed extensive all-atom microsecond-timescale simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method, which successfully captured multiple times of spontaneous and highly accurate binding of the Numb RNA from bulk solvent to the MSI1 protein target site. GaMD simulations revealed that Numb RNA binding to MSI1 involved largely induced fit in both the RNA and protein. The simulations also identified important low-energy intermediate conformational states during RNA binding, in which Numb interacted mainly with the β2-β3 loop and C terminus of MSI1. The mechanistic understanding of RNA binding obtained from our GaMD simulations is expected to facilitate rational structure-based drug design targeting MSI1 and other RBPs.

Conformational transformation of switch domains in GDP/K-Ras induced by G13 mutants: An investigation through Gaussian accelerated molecular dynamics simulations and principal component analysis

Mutations in K-Ras are involved in a large number of all human cancers, thus, K-Ras is regarded as a promising target for anticancer drug design. Understanding the target roles of K-Ras is important for providing insights on the molecular mechanism underlying the conformational transformation of the switch domains in K-Ras due to mutations. In this study, multiple replica Gaussian accelerated molecular (MR-GaMD) simulations and principal component analysis (PCA) were applied to probe the effect of G13A, G13D and G13I mutations on conformational transformations of the switch domains in GDP-associated K-Ras. The results suggest that G13A, G13D and G13I enhance the structural flexibility of the switch domains, change the correlated motion modes of the switch domains and strengthen the total motion strength of K-Ras compared with the wild-type (WT) K-Ras. Free energy landscape analyses not only show that the switch domains of the GDP-bound inactive K-Ras mainly exist as a closed state but also indicate that mutations evidently alter the free energy profile of K-Ras and affect the conformational transformation of the switch domains between the closed and open states. Analyses of hydrophobic interaction contacts and hydrogen bonding interactions show that the mutations scarcely change the interaction network of GDP with K-Ras and only disturb the interaction of GDP with the switch (SW1). In summary, two newly introduced mutations, G13A and G13I, play similar adjustment roles in the conformational transformations of two switch domains to G13D and are possibly utilized to tune the activity of K-Ras and the binding of guanine nucleotide exchange factors.

Conformation and dynamics of the kinase domain drive subcellular location and activation of LRRK2

To explore how pathogenic mutations of the multidomain leucine-rich repeat kinase 2 (LRRK2) hijack its finely tuned activation process and drive Parkinson's disease (PD), we used a multitiered approach. Most mutations mimic Rab-mediated activation by "unleashing" kinase activity, and many, like the kinase inhibitor MLi-2, trap LRRK2 onto microtubules. Here we mimic activation by simply deleting the inhibitory N-terminal domains and then characterize conformational changes induced by MLi-2 and PD mutations. After confirming that LRRK2_RCKW retains full kinase activity, we used hydrogen-deuterium exchange mass spectrometry to capture breathing dynamics in the presence and absence of MLi-2. Solvent-accessible regions throughout the entire protein are reduced by MLi-2 binding. With molecular dynamics simulations, we created a dynamic portrait of LRRK2_RCKW and demonstrate the consequences of kinase domain mutations. Although all domains contribute to regulating kinase activity, the kinase domain, driven by the DYGψ motif, is the allosteric hub that drives LRRK2 regulation.

Pathways and Mechanism of Caffeine Binding to Human Adenosine A2A Receptor

Caffeine (CFF) is a common antagonist to the four subtypes of adenosine G-protein-coupled receptors (GPCRs), which are critical drug targets for treating heart failure, cancer, and neurological diseases. However, the pathways and mechanism of CFF binding to the target receptors remain unclear. In this study, we have performed all-atom-enhanced sampling simulations using a robust Gaussian-accelerated molecular dynamics (GaMD) method to elucidate the binding mechanism of CFF to human adenosine A_2A receptor (A_2AAR). Multiple 500–1,000 ns GaMD simulations captured both binding and dissociation of CFF in the A_2AAR. The GaMD-predicted binding poses of CFF were highly consistent with the x-ray crystal conformations with a characteristic hydrogen bond formed between CFF and residue N6.55 in the receptor. In addition, a low-energy intermediate binding conformation was revealed for CFF at the receptor extracellular mouth between ECL2 and TM1. While the ligand-binding pathways of the A_2AAR were found similar to those of other class A GPCRs identified from previous studies, the ECL2 with high sequence divergence serves as an attractive target site for designing allosteric modulators as selective drugs of the A_2AAR.

Anti-TNF Alpha Antibody Humira with pH-dependent Binding Characteristics: A constant-pH Molecular Dynamics, Gaussian Accelerated Molecular Dynamics, and In Vitro Study

Humira is a monoclonal antibody that binds to TNF alpha, inactivates TNF alpha receptors, and inhibits inflammation. Neonatal Fc receptors can mediate the transcytosis of Humira-TNF alpha complex structures and process them toward degradation pathways, which reduces the therapeutic effect of Humira. Allowing the Humira-TNF alpha complex structures to dissociate to Humira and soluble TNF alpha in the early endosome to enable Humira recycling is crucial. We used the cytoplasmic pH (7.4), the early endosomal pH (6.0), and pKa of histidine side chains (6.0-6.4) to mutate the residues of complementarity-determining regions with histidine. Our engineered Humira (W1-Humira) can bind to TNF alpha in plasma at neutral pH and dissociate from the TNF alpha in the endosome at acidic pH. We used the constant-pH molecular dynamics, Gaussian accelerated molecular dynamics, two-dimensional potential mean force profiles, and in vitro methods to investigate the characteristics of W1-Humira. Our results revealed that the proposed Humira can bind TNF alpha with pH-dependent affinity in vitro. The W1-Humira was weaker than wild-type Humira at neutral pH in vitro, and our prediction results were close to the in vitro results. Furthermore, our approach displayed a high accuracy in antibody pH-dependent binding characteristics prediction, which may facilitate antibody drug design. Advancements in computational methods and computing power may further aid in addressing the challenges in antibody drug design.

Structure of the Human Respiratory Syncytial Virus M2-1 Protein in Complex with a Short Positive-Sense Gene-End RNA

The M2-1 protein of human respiratory syncytial virus (HRSV) is a transcription anti-terminator that regulates the processivity of the HRSV RNA-dependent RNA polymerase (RdRP). Here, we report a crystal structure of HRSV M2-1 bound to a short positive-sense gene-end RNA (SH7) at 2.7 Å resolution. We identified multiple critical residues of M2-1 involved in RNA interaction and examined their roles using mutagenesis and MicroScale Thermophoresis (MST) assay. We found that hydrophobic residue Phe23 is indispensable for M2-1 to recognize the base of RNA. We also captured spontaneous binding of RNA (SH7) to M2-1 in all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method. Both experiments and simulations revealed that the interactions of RNA with two separate domains of M2-1, the zinc-binding domain (ZBD) and the core domain (CD), are independent of each other. Collectively, our results provided a structural basis for RNA recognition by HRSV M2-1.

Pathway and mechanism of drug binding to chemokine receptors revealed by accelerated molecular simulations

Background: Chemokine GPCRs play key roles in biology and medicine. Particularly, CXCR4 promotes cancer metastasis and facilitate HIV entry into host cells. Plerixafor (PLX) is a CXCR4 drug, but the pathway and binding site of PLX in CXCR4 remain unknown. Results & methodology: We have performed molecular docking and all-atom simulations using Gaussian accelerated molecular dynamics (GaMD), which are consistent with previous mutation experiments, suggesting that PLX binds to the orthosteric site of CXCR4 as an antagonist. The GaMD simulations further revealed an intermediate allosteric binding site at the extracellular mouth of CXCR4. Conclusion: The newly identified allosteric site can be targeted for novel drug design targeting CXCR4 and other chemokine receptors.

Retrospective ensemble docking of allosteric modulators in an adenosine G-protein-coupled receptor

BACKGROUND

Ensemble docking has proven useful in drug discovery and development. It increases the hit rate by incorporating receptor flexibility into molecular docking as demonstrated on important drug targets including G-protein-coupled receptors (GPCRs). Adenosine A₁ receptor (A₁AR) is a key GPCR that has been targeted for treating cardiac ischemia-reperfusion injuries, neuropathic pain and renal diseases. Development of allosteric modulators, compounds binding to distinct and less conserved GPCR target sites compared with agonists and antagonists, has attracted increasing interest for designing selective drugs of the A₁AR. Despite significant advances, more effective approaches are needed to discover potent and selective allosteric modulators of the A₁AR.

METHODS

Ensemble docking that integrates Gaussian accelerated molecular dynamic (GaMD) simulations and molecular docking using Autodock has been implemented for retrospective docking of known positive allosteric modulators (PAMs) in the A₁AR.

RESULTS

Ensemble docking outperforms docking of the receptor cryo-EM structure. The calculated docking enrichment factors (EFs) and the area under the receiver operating characteristic curves (AUC) are significantly increased.

CONCLUSIONS

Receptor ensembles generated from GaMD simulations are able to increase the success rate of discovering PAMs of A₁AR. It is important to account for receptor flexibility through GaMD simulations and flexible docking.

GENERAL SIGNIFICANCE

Ensemble docking is a promising approach for drug discovery targeting flexible receptors.

G-Protein-Coupled Receptor-Membrane Interactions Depend on the Receptor Activation State

G-protein-coupled receptors (GPCRs) are the largest family of human membrane proteins and serve as primary targets of approximately one-third of currently marketed drugs. In particular, adenosine A1 receptor (A1 AR) is an important therapeutic target for treating cardiac ischemia-reperfusion injuries, neuropathic pain, and renal diseases. As a prototypical GPCR, the A1 AR is located within a phospholipid membrane bilayer and transmits cellular signals by changing between different conformational states. It is important to elucidate the lipid-protein interactions in order to understand the functional mechanism of GPCRs. Here, all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method were performed on both the inactive (antagonist bound) and active (agonist and G-protein bound) A1 AR, which was embedded in a 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) lipid bilayer. In the GaMD simulations, the membrane lipids played a key role in stabilizing different conformational states of the A1 AR. Our simulations further identified important regions of the receptor that interacted distinctly with the lipids in highly correlated manner. Activation of the A1 AR led to differential dynamics in the upper and lower leaflets of the lipid bilayer. In summary, GaMD enhanced simulations have revealed strongly coupled dynamics of the GPCR and lipids that depend on the receptor activation state. © 2019 Wiley Periodicals, Inc.

The mechanism of high affinity pentasaccharide binding to antithrombin, insights from Gaussian accelerated molecular dynamics simulations

The activity of antithrombin (AT), a serpin protease inhibitor, is enhanced by heparin and heparin analogs against its target proteases, mainly thrombin, factors Xa and IXa. Considerable amount of information is available on the multistep mechanism of the heparin pentasaccharide binding and conformational activation. However, much of the details were inferred from 'static' structures obtained by X-ray diffraction. Moreover, limited information is available for the early steps of binding mechanism other than kinetic studies with various ligands. To gain insights into these processes, we performed enhanced sampling molecular dynamics (MD) simulations using the Gaussian Accelerated Molecular Dynamics (GAMD) method, applied previously in drug binding studies. We were able to observe the binding of the pentasaccharide idraparinux to a 'non-activated' AT conformation in two separate trajectories with low root mean square deviation (RMSD) values compared to X-ray structures of the bound state. These trajectories along with further simulations of the AT-pentasaccharide complex provided insights into the mechanisms of multiple conformational transitions, including the expulsion of the hinge region, the extension of helix D and the conformational behavior of the reactive center loop (RCL). We could also confirm the high stability of helix P in non-activated AT conformations, such states might play an important role in heparin binding. 'Generalized correlation' matrices revealed possible paths of allosteric signal propagation to the binding sites for the target proteases, factors Xa and IXa. Enhanced MD simulations of ligand binding to AT may assist the design of new anticoagulant drugs.Communicated by Ramaswamy H. Sarma.

Gaussian accelerated molecular dynamics for elucidation of drug pathways

INTRODUCTION

Understanding pathways and mechanisms of drug binding to receptors is important for rational drug design. Remarkable advances in supercomputing and methodological developments have opened a new era for application of computer simulations in predicting drug-receptor interactions at an atomistic level. Gaussian accelerated molecular dynamics (GaMD) is a computational enhanced sampling technique that works by adding a harmonic boost potential to reduce energy barriers. GaMD enables free energy calculations without the requirement of predefined collective variables. GaMD has proven useful in biomolecular simulations, in particular, the prediction of drug-receptor interactions. Areas covered: Herein, the authors review recent GaMD simulation studies that elucidated pathways of drug binding to proteins including the G-protein-coupled receptors and HIV protease. Expert opinion: GaMD is advantageous for enhanced simulations of, amongst many biological processes, drug binding to target receptors. Compared with conventional molecular dynamics, GaMD speeds up biomolecular simulations by orders of magnitude. GaMD enables routine drug binding simulations using personal computers with GPUs or common computing clusters. GaMD and, more broadly, enhanced sampling simulations are expected to dramatically increase our capabilities to determine the mechanisms of drug binding to a wide range of receptors in the near future. This will greatly facilitate computer-aided drug design.