The role of the molecular footprint of EGFR in tailoring treatment decisions in NSCLC

The majority of patients with non-small-cell lung cancer (NSCLC) present with advanced disease, with targeted therapies providing some improvement in clinical outcomes. The epidermal growth factor receptor (EGFR) tyrosine kinase (TK) plays an important role in the pathogenesis of NSCLC. Tyrosine kinase inhibitors (TKIs), which target the EGFR TK domain, have proven to be an effective treatment strategy; however, patient responses to treatment vary considerably. Therefore, the identification of patients most likely to respond to treatment is essential to optimise the benefit of TKIs. Tumour-associated activating mutations in EGFR can identify patients with NSCLC who are likely to have a good response to TKIs. Nonetheless, the majority of patients relapse within a year of starting treatment. Studies of tumours at relapse have demonstrated expression of a T790M mutation in exon 20 of the EGFR TK domain in approximately 50% of cases. Although conferring resistance to reversible TKIs, these patients may remain sensitive to new-generation irreversible/panerb inhibitors. A number of techniques have been employed for genotypic assessment of tumourassociated DNA to identify EGFR mutations, each of which has advantages and disadvantages. This review presents an overview of the current methodologies used to identify such molecular markers. Recent developments in technology may make the monitoring of changes in patients' tumour genotypes easier in clinical practice, which may enable patients' treatment regimens to be tailored during the course of their disease, potentially leading to improved patient outcomes.

Atomistic simulation of surface functionalization on the interfacial properties of graphene-polymer nanocomposites

Graphene has been increasingly used as nano sized fillers to create a broad range of nanocomposites with exceptional properties. The interfaces between fillers and matrix play a critical role in dictating the overall performance of a composite. However, the load transfer mechanism along graphene-polymer interface has not been well understood. In this study, we conducted molecular dynamics simulations to investigate the influence of surface functionalization and layer length on the interfacial load transfer in graphene polymer nanocomposites. The simulation results show that oxygen-functionalized graphene leads to larger interfacial shear force than hydrogen-functionalized and pristine ones during pull-out process. The increase of oxygen coverage and layer length enhances interfacial shear force. Further increase of oxygen coverage to about 7% leads to a saturated interfacial shear force. A model was also established to demonstrate that the mechanism of interfacial load transfer consists of two contributing parts, including the formation of new surface and relative sliding along the interface. These results are believed to be useful in development of new graphene-based nanocomposites with better interfacial properties.

Modeling nitrous oxide emissions from irrigated agriculture : testing DayCent with high-frequency measurements

A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N2O fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management system (i.e. frequent irrigation, avoidance of excessive fertiliser application), while sustaining maximum yield potentials.

Nanostructured hydroxyapatite surfaces-mediated adsorption alters recognition of BMP receptor IA and bioactivity of bone morphogenetic protein-2

Highly efficient loading of bone morphogenetic protein-2 (BMP-2) onto carriers with desirable performance is still a major challenge in the field of bone regeneration. Till now, the nanoscaled surface-induced changes of the structure and bioactivity of BMP-2 remains poorly understood. Here, the effect of nanoscaled surface on the adsorption and bioactivity of BMP-2 was investigated with a series of hydroxyapatite surfaces (HAPs): HAP crystal-coated surface (HAP), HAP crystal-coated polished surface (HAP-Pol), and sintered HAP crystal-coated surface (HAP-Sin). The adsorption dynamics of recombinant human BMP-2 (rhBMP-2) and the accessibility of the binding epitopes of adsorbed rhBMP-2 for BMP receptors (BMPRs) were examined by a quartz crystal microbalance with dissipation. Moreover, the bioactivity of adsorbed rhBMP-2 and the BMP-induced Smad signaling were investigated with C2C12 model cells. A noticeably high mass-uptake of rhBMP-2 and enhanced recognition of BMPR-IA to adsorbed rhBMP-2 were found on the HAP-Pol surface. For the rhBMP-2-adsorbed HAPs, both ALP activity and Smad signaling increased in the order of HAP-Sin < HAP < HAP-Pol. Furthermore, hybrid molecular dynamics and steered molecular dynamics simulations validated that BMP-2 tightly anchored on the HAP-Pol surface with a relative loosened conformation, but the HAP-Sin surface induced a compact conformation of BMP-2. In conclusion, the nanostructured HAPs can modulate the way of adsorption of rhBMP-2, and thus the recognition of BMPR-IA and the bioactivity of rhBMP-2. These findings can provide insightful suggestions for the future design and fabrication of rhBMP-2-based scaffolds/implants.

A simulation study of the mixing, atomic flow and velocity profiles of crystalline materials during sliding

Self-contained Non-Equilibrium Molecular Dynamics (NEMD) simulations using Lennard-Jones potentials were performed to identify the origin and mechanisms of atomic scale interfacial behavior between sliding metals. The mixing sequence and velocity profiles were compared via MD simulations for three cases, viz.: sell-mated, similar and hard-softvcrystal pairs. The results showed shear instability, atomic scale mixing, and generation of eddies at the sliding interface. Vorticity at the interface suggests that atomic flow during sliding is similar to fluid flow under Kelvin-Helmholtz instability and this is supported by velocity profiles from the simulations. The initial step-function velocity profile spreads during sliding. However the velocity profile does not change much at later stages of the simulation and it eventually stops spreading. The steady state friction coefficient during simulation was monitored as a function of sliding velocity. Frictional behavior can be explained on the basis of plastic deformation and adiabatic effects. The mixing layer growth kinetics was also investigated.

Molecular Modelling of Estrogen-Producing Enzymes CYP450 Aromatase and 17beta-Hydroxysteroid Dehydrogenase Type 1

Breast cancer is the most common cancer in women in the western countries. Approximately two-thirds of breast cancer tumours are hormone dependent, requiring estrogens to grow. Estrogens are formed in the human body via a multistep route starting from cholesterol. The final steps in the biosynthesis include the CYP450 aromatase enzyme, converting the male hormones androgens (preferred substrate androstenedione ASD) into estrogens(estrone E1), and the 17beta-HSD1 enzyme, converting the biologically less active E1 into the active hormone 17beta-hydroxyestradiol E2. E2 is bound to the nuclear estrogen receptors causing a cascade of biochemical reactions leading to cell proliferation in normal tissue, and to tumour growth in cancer tissue. Aromatase and 17beta-HSD1 are expressed in or near the breast tumour, locally providing the tissue with estrogens. One approach in treating hormone dependent breast tumours is to block the local estrogen production by inhibiting these two enzymes. Aromatase inhibitors are already on the market in treating breast cancer, despite the lack of an experimentally solved structure. The structure of 17beta-HSD1, on the other hand, has been solved, but no commercial drugs have emerged from the drug discovery projects reported in the literature. Computer-assisted molecular modelling is an invaluable tool in modern drug design projects. Modelling techniques can be used to generate a model of the target protein and to design novel inhibitors for them even if the target protein structure is unknown. Molecular modelling has applications in predicting the activities of theoretical inhibitors and in finding possible active inhibitors from a compound database. Inhibitor binding at atomic level can also be studied with molecular modelling. To clarify the interactions between the aromatase enzyme and its substrate and inhibitors, we generated a homology model based on a mammalian CYP450 enzyme, rabbit progesterone 21-hydroxylase CYP2C5. The model was carefully validated using molecular dynamics simulations (MDS) with and without the natural substrate ASD. Binding orientation of the inhibitors was based on the hypothesis that the inhibitors coordinate to the heme iron, and were studied using MDS. The inhibitors were dietary phytoestrogens, which have been shown to reduce the risk for breast cancer. To further validate the model, the interactions of a commercial breast cancer drug were studied with MDS and ligand–protein docking. In the case of 17beta-HSD1, a 3D QSAR model was generated on the basis of MDS of an enzyme complex with active inhibitor and ligand–protein docking, employing a compound library synthesised in our laboratory. Furthermore, four pharmacophore hypotheses with and without a bound substrate or an inhibitor were developed and used in screening a commercial database of drug-like compounds. The homology model of aromatase showed stable behaviour in MDS and was capable of explaining most of the results from mutagenesis studies. We were able to identify the active site residues contributing to the inhibitor binding, and explain differences in coordination geometry corresponding to the inhibitory activity. Interactions between the inhibitors and aromatase were in agreement with the mutagenesis studies reported for aromatase. Simulations of 17beta-HSD1 with inhibitors revealed an inhibitor binding mode with hydrogen bond interactions previously not reported, and a hydrophobic pocket capable of accommodating a bulky side chain. Pharmacophore hypothesis generation, followed by virtual screening, was able to identify several compounds that can be used in lead compound generation. The visualisation of the interaction fields from the QSAR model and the pharmacophores provided us with novel ideas for inhibitor development in our drug discovery project.

A phosphorylation-induced turn defines the Alzheimer's disease AT8 antibody epitope on the tau protein

Post mortem biochemical staging of Alzheimer’s disease is currently based on immunochemical analysis of brain slices with the AT8 antibody. The epitope of AT8 is described around the pSer202/pThr205 region of the hyperphosphorylated form of the neuronal protein tau. In this study, NMR spectroscopy was used to precisely map the AT8 epitope on phosphorylated tau, and derive its defining structural features by a combination of NMR analyses and molecular dynamics. A particular turn conformation is stabilized by a hydrogen bond of the phosphorylated Thr205 residue to the amide proton of Gly207, and is further stabilized by the two Arg residues opposing the pSer202/pThr205.

Free energy calculations of glycosaminoglycan - Protein interactions

Glycosaminoglycans (GAGs) are complex highly charged linear polysaccharides that have a variety of roles in biological processes. We report the first use of molecular dynamics (MD) free energy calculations using the MM/PBSA method to investigate the binding of GAGs to protein molecules, namely the platelet endothelial cell adhesion molecule 1 (PECAM-1) and annexin A2. Calculations of the free energy of the binding of heparin fragments of different sizes reveal the existence of a region of low GAG-binding affinity in domains 5-6 of PECAM-1 and a region of high affinity in domains 2-3, consistent with experimental data and ligand-protein docking studies. A conformational hinge movement between domains 2 and 3 was observed, which allows the binding of heparin fragments of increasing size (pentasaccharides to octasaccharides) with an increasingly higher binding affinity. Similar simulations of the binding of a heparin fragment to annexin A2 reveal the optimization of electrostatic and hydrogen bonding interactions with the protein and protein-bound calcium ions. In general, these free energy calculations reveal that the binding of heparin to protein surfaces is dominated by strong electrostatic interactions for longer fragments, with equally important contributions from van der Waals interactions and vibrational entropy changes, against a large unfavorable desolvation penalty due to the high charge density of these molecules.

Free energy calculations of the interactions of c-Jun-based synthetic peptides with the c-Fos protein

The c-Fos–c-Jun complex forms the activator protein 1 transcription factor, a therapeutic target in the treatment of cancer. Various synthetic peptides have been designed to try to selectively disrupt the interaction between c-Fos and c-Jun at its leucine zipper domain. To evaluate the binding affinity between these synthetic peptides and c-Fos, polarizable and nonpolarizable molecular dynamics (MD) simulations were conducted, and the resulting conformations were analyzed using the molecular mechanics generalized Born surface area (MM/GBSA) method to compute free energies of binding. In contrast to empirical and semiempirical approaches, the estimation of free energies of binding using a combination of MD simulations and the MM/GBSA approach takes into account dynamical properties such as conformational changes, as well as solvation effects and hydrophobic and hydrophilic interactions. The predicted binding affinities of the series of c-Jun-based peptides targeting the c-Fos peptide show good correlation with experimental melting temperatures. This provides the basis for the rational design of peptides based on internal, van der Waals, and electrostatic interactions.

Ligand dependent intra and inter subunit communication in human tryptophanyl tRNA synthetase as deduced from the dynamics of structure networks

Homodimeric protein tryptophanyl tRNA synthetase (TrpRS) has a Rossmann fold domain and belongs to the 1c subclass of aminoacyl tRNA synthetases. This enzyme performs the function of acylating the cognate tRNA. This process involves a number of molecules (2 protein subunits, 2 tRNAs and 2 activated Trps) and thus it is difficult to follow the complex steps in this process. Structures of human TrpRS complexed with certain ligands are available. Based on structural and biochemical data, mechanism of activation of Trp has been speculated. However, no structure has yet been solved in the presence of both the tRNA(Trp) and the activated Trp (TrpAMP). In this study, we have modeled the structure of human TrpRS bound to the activated ligand and the cognate tRNA. In addition, we have performed molecular dynamics (MD) simulations on these models as well as other complexes to capture the dynamical process of ligand induced conformational changes. We have analyzed both the local and global changes in the protein conformation from the protein structure network (PSN) of MD snapshots, by a method which was recently developed in our laboratory in the context of the functionally monomeric protein, methionyl tRNA synthetase. From these investigations, we obtain important information such as the ligand induced correlation between different residues of this protein, asymmetric binding of the ligands to the two subunits of the protein as seen in the crystal structure analysis, and the path of communication between the anticodon region and the aminoacylation site. Here we are able to elucidate the role of dimer interface at a level of detail, which has not been captured so far.

Structure and Dynamics of Coil-like Molecules by Residual Dipolar Couplings

Nuclear magnetic resonance (NMR) spectroscopy provides us with many means to study biological macromolecules in solution. Proteins in particular are the most intriguing targets for NMR studies. Protein functions are usually ascribed to specific three-dimensional structures but more recently tails, long loops and non-structural polypeptides have also been shown to be biologically active. Examples include prions, -synuclein, amylin and the NEF HIV-protein. However, conformational preferences in coil-like molecules are difficult to study by traditional methods. Residual dipolar couplings (RDCs) have opened up new opportunities; however their analysis is not trivial. Here we show how to interpret RDCs from these weakly structured molecules. The most notable residual dipolar couplings arise from steric obstruction effects. In dilute liquid crystalline media as well as in anisotropic gels polypeptides encounter nematogens. The shape of a polypeptide conformation limits the encounter with the nematogen. The most elongated conformations may come closest whereas the most compact remain furthest away. As a result there is slightly more room in the solution for the extended than for the compact conformations. This conformation-dependent concentration effect leads to a bias in the measured data. The measured values are not arithmetic averages but essentially weighted averages over conformations. The overall effect can be calculated for random flight chains and simulated for more realistic molecular models. Earlier there was an implicit thought that weakly structured or non-structural molecules would not yield to any observable residual dipolar couplings. However, in the pioneering study by Shortle and Ackerman RDCs were clearly observed. We repeated the study for urea-denatured protein at high temperature and also observed indisputably RDCs. This was very convincing to us but we could not possibly accept the proposed reason for the non-zero RDCs, namely that there would be some residual structure left in the protein that to our understanding was fully denatured. We proceeded to gain understanding via simulations and elementary experiments. In measurements we used simple homopolymers with only two labelled residues and we simulated the data to learn more about the origin of RDCs. We realized that RDCs depend on the position of the residue as well as on the length of the polypeptide. Investigations resulted in a theoretical model for RDCs from coil-like molecules. Later we extended the studies by molecular dynamics. Somewhat surprisingly the effects are small for non-structured molecules whereas the bias may be large for a small compact protein. All in all the work gave clear and unambiguous results on how to interpret RDCs as structural and dynamic parameters of weakly structured proteins.

Allostery and conformational free energy changes in human tryptophanyl-tRNA synthetase from essential dynamics and structure networks

The interdependence of the concept of allostery and enzymatic catalysis, and they being guided by conformational mobility is gaining increased prominence. However, to gain a molecular level understanding of llostery and hence of enzymatic catalysis, it is of utter importance that the networks of amino acids participating in allostery be deciphered. Our lab has been exploring the methods of network analysis combined with molecular dynamics simulations to understand allostery at molecular level. Earlier we had outlined methods to obtain communication paths and then to map the rigid/flexible regions of proteins through network parameters like the shortest correlated paths, cliques, and communities. In this article, we advance the methodology to estimate the conformational populations in terms of cliques/communities formed by interactions including the side-chains and then to compute the ligand-induced population shift. Finally, we obtain the free-energy landscape of the protein in equilibrium, characterizing the free-energy minima accessed by the protein complexes. We have chosen human tryptophanyl-tRNA synthetase (hTrpRS), a protein esponsible for charging tryptophan to its cognate tRNA during protein biosynthesis for this investigation. This is a multidomain protein exhibiting excellent allosteric communication. Our approach has provided valuable structural as well as functional insights into the protein. The methodology adopted here is highly generalized to illuminate the linkage between protein structure networks and conformational mobility involved in the allosteric mechanism in any protein with known structure.

Structures of apo and GTP-bound molybdenum cofactor biosynthesis protein MoaC from Thermus thermophilus HB8

The first step in the molybdenum cofactor (Moco) biosynthesis pathway involves the conversion of guanosine triphosphate (GTP) to precursor Z by two proteins (MoaA and MoaC). MoaA belongs to the S-adenosylmethioninedependent radical enzyme superfamily and is believed to generate protein and/or substrate radicals by reductive cleavage of S-adenosylmethionine using an Fe-S cluster. MoaC has been suggested to catalyze the release of pyrophosphate and the formation of the cyclic phosphate of precursor Z. However, structural evidence showing the binding of a substrate-like molecule to MoaC is not available. Here, apo and GTP-bound crystal structures of MoaC from Thermus thermophilus HB8 are reported. Furthermore, isothermal titration calorimetry experiments have been carried out in order to obtain thermodynamic parameters for the protein-ligand interactions. In addition, molecular-dynamics (MD) simulations have been carried out on the protein-ligand complex of known structure and on models of relevant complexes for which X-ray structures are not available. The biophysical, structural and MD results reveal the residues that are involved in substrate binding and help in speculating upon a possible mechanism.

Elucidation of the conformational free energy landscape in H.pylori LuxS and its implications to catalysis

Background: One of the major challenges in understanding enzyme catalysis is to identify the different conformations and their populations at detailed molecular level in response to ligand binding/environment. A detail description of the ligand induced conformational changes provides meaningful insights into the mechanism of action of enzymes and thus its function. Results: In this study, we have explored the ligand induced conformational changes in H. pylori LuxS and the associated mechanistic features. LuxS, a dimeric protein, produces the precursor (4,5-dihydroxy-2,3-pentanedione) for autoinducer-2 production which is a signalling molecule for bacterial quorum sensing. We have performed molecular dynamics simulations on H. pylori LuxS in its various ligand bound forms and analyzed the simulation trajectories using various techniques including the structure network analysis, free energy evaluation and water dynamics at the active site. The results bring out the mechanistic details such as co operativity and asymmetry between the two subunits, subtle changes in the conformation as a response to the binding of active and inactive forms of ligands and the population distribution of different conformations in equilibrium. These investigations have enabled us to probe the free energy landscape and identify the corresponding conformations in terms of network parameters. In addition, we have also elucidated the variations in the dynamics of water co-ordination to the Zn2+ ion in LuxS and its relation to the rigidity at the active sites. Conclusions: In this article, we provide details of a novel method for the identification of conformational changes in the different ligand bound states of the protein, evaluation of ligand-induced free energy changes and the biological relevance of our results in the context of LuxS structure-function. The methodology outlined here is highly generalized to illuminate the linkage between structure and function in any protein of known structure.