Synthesis of the Isodityrosine Moiety of Seongsanamide A-D and Its Derivatives.

The concise and highly convergent synthesis of the isodityrosine unit of seongsanamide A-D and its derivatives bearing a diaryl ether moiety is described. In this work, the synthetic strategy features palladium-catalyzed C(sp3)-H functionalization and a Cu/ligand-catalyzed coupling reaction. We report a practical protocol for the palladium-catalyzed mono-arylation of ß-methyl C(sp3)-H of an alanine derivative bearing a 2-thiomethylaniline auxiliary. The reaction is compatible with a variety of functional groups, providing practical access to numerous ß-aryl-α-amino acids; these acids can be converted into various tyrosine and dihydroxyphenylalanine (DOPA) derivatives. Then, a CuI/N,N-dimethylglycine-catalyzed arylation of the already synthesized DOPA derivatives with aryl iodides is described for the synthesis of isodityrosine derivatives.

Induction of defense in cereals by 4-fluorophenoxyacetic acid suppresses insect pest populations and increases crop yields in the field.

Synthetic chemical elicitors, so called plant strengtheners, can protect plants from pests and pathogens. Most plant strengtheners act by modifying defense signaling pathways, and little is known about other mechanisms by which they may increase plant resistance. Moreover, whether plant strengtheners that enhance insect resistance actually enhance crop yields is often unclear. Here, we uncover how a mechanism by which 4-fluorophenoxyacetic acid (4-FPA) protects cereals from piercing-sucking insects and thereby increases rice yield in the field. Four-FPA does not stimulate hormonal signaling, but modulates the production of peroxidases, H2O2, and flavonoids and directly triggers the formation of flavonoid polymers. The increased deposition of phenolic polymers in rice parenchyma cells of 4-FPA-treated plants is associated with a decreased capacity of the white-backed planthopper (WBPH) Sogatella furcifera to reach the plant phloem. We demonstrate that application of 4-PFA in the field enhances rice yield by reducing the abundance of, and damage caused by, insect pests. We demonstrate that 4-FPA also increases the resistance of other major cereals such as wheat and barley to piercing-sucking insect pests. This study unravels a mode of action by which plant strengtheners can suppress herbivores and increase crop yield. We postulate that this represents a conserved defense mechanism of plants against piercing-sucking insect pests, at least in cereals.

Diversity-Oriented Synthesis of Natural-Product-like Libraries Containing a 3-Methylbenzofuran Moiety for the Discovery of New Chemical Elicitors.

Natural products are a major source of biological molecules. The 3-methylfuran scaffold is found in a variety of plant secondary metabolite chemical elicitors that confer host-plant resistance against insect pests. Herein, the diversity-oriented synthesis of a natural-product-like library is reported, in which the 3-methylfuran core is fused in an angular attachment to six common natural product scaffolds-coumarin, chalcone, flavone, flavonol, isoflavone and isoquinolinone. The structural diversity of this library is assessed computationally using cheminformatic analysis. Phenotypic high-throughput screening of ß-glucuronidase activity uncovers several hits. Further in vivo screening confirms that these hits can induce resistance in rice to nymphs of the brown planthopper Nilaparvata lugens. This work validates the combination of diversity-oriented synthesis and high-throughput screening of ß-glucuronidase activity as a strategy for discovering new chemical elicitors.

Finding new elicitors that induce resistance in rice to the white-backed planthopper Sogatella furcifera.

Herein we report a new way to identify chemical elicitors that induce resistance in rice to herbivores. Using this method, by quantifying the induction of chemicals for GUS activity in a specific screening system that we established previously, 5 candidate elicitors were selected from the 29 designed and synthesized phenoxyalkanoic acid derivatives. Bioassays confirmed that these candidate elicitors could induce plant defense and then repel feeding of white-backed planthopper Sogatella furcifera.

Molecular dynamics simulation of the interactions between EHD1 EH domain and multiple peptides.

OBJECTIVE: To provide essential information for peptide inhibitor design, the interactions of Eps15 homology domain of Eps15 homology domain-containing protein 1 (EHD1 EH domain) with three peptides containing NPF (asparagine-proline-phenylalanine), DPF (aspartic acid-proline-phenylalanine), and GPF (glycine-proline-phenylalanine) motifs were deciphered at the atomic level. The binding affinities and the underlying structure basis were investigated. METHODS: Molecular dynamics (MD) simulations were performed on EHD1 EH domain/peptide complexes for 60 ns using the GROMACS package. The binding free energies were calculated and decomposed by molecular mechanics/generalized Born surface area (MM/GBSA) method using the AMBER package. The alanine scanning was performed to evaluate the binding hot spot residues using FoldX software. RESULTS: The different binding affinities for the three peptides were affected dominantly by van der Waals interactions. Intermolecular hydrogen bonds provide the structural basis of contributions of van der Waals interactions of the flanking residues to the binding. CONCLUSIONS: van der Waals interactions should be the main consideration when we design peptide inhibitors of EHD1 EH domain with high affinities. The ability to form intermolecular hydrogen bonds with protein residues can be used as the factor for choosing the flanking residues.

Indirect readout in protein-peptide recognition: a different story from classical biomolecular recognition.

Protein-peptide interactions are prevalent and play essential roles in many living activities. Peptides recognize their protein partners by direct nonbonded interactions and indirect adjustment of conformations. Although processes of protein-peptide recognition have been comprehensively studied in both sequences and structures recently, flexibility of peptides and the configuration entropy penalty in recognition did not get enough attention. In this study, 20 protein-peptide complexes and their corresponding unbound peptides were investigated by molecular dynamics simulations. Energy analysis revealed that configurational entropy penalty introduced by restriction of the degrees of freedom of peptides in indirect readout process of protein-peptide recognition is significant. Configurational entropy penalty has become the main content of the indirect readout energy in protein-peptide recognition instead of deformation energy which is the main source of the indirect readout energy in classical biomolecular recognition phenomena, such as protein-DNA binding. These results provide us a better understanding of protein-peptide recognition and give us some implications in peptide ligand design.

A systematical comparison of DFT methods in reproducing the interaction energies of halide series with protein moieties.

A systematic theoretical investigation on the interaction energies of halogen-ionic bridges formed between halide ions and the polar H atoms bonded to N of protein moieties has been carried out by employing a variety of density functional methods. In this procedure, full geometry optimizations are performed at the Møller-Plesset second-order perturbation (MP2) level of theory in conjunction with the Dunning's augmented correlation-consistent basis set, aug-cc-pVDZ. Subsequently, two distinct basis sets, i.e. 6-311++G(df,pd) and aug-cc-pVTZ, are employed in the following single-point calculations so as to check the stability of the results obtained at the different levels of DFT. The performance of DFT methods has been evaluated by comparing the results with those obtained from the rigorous MP2 theory. It is shown that the B98, B97-1, and M05 give the lowest root-mean-square error (RMSE) for predicting fluoride-binding energies, M05-2X, MPW1B95, and MPW1PW91 have the best performance in reproducing chloride-binding energies, B97-1, PBEKCIS, and PBE1KCIS present the optimal result for bromide-binding energies, while B97-1, MPW1PW91, and TPSS perform most well on iodide-binding energies. The popular B3LYP functional seems to be quite modest for studying halide-protein moiety interactions. In addition, the PBE1KCIS functional provide accuracies close to the computationally expensive MP2 method for the calculation of interaction energies of all halide-binding systems.

Integrating statistical and experimental protocols to model and design novel Gemini surfactants with promising critical micelle concentration and low environmental risk.

A paradigmatic study of integrating statistical modeling and experimental analysis to investigate the critical micelle concentration (CMC) and environmental risk of 120 structurally diverse Gemini surfactants is performed. In this procedure, the structural profiles of studied compounds are characterized using hundreds of constitutional, topological, geometrical and electrostatic descriptors, and the resulting variables of the characterization are then calibrated on the basis of experimentally measured properties via a variety of regression techniques, including MLR, PLS, SVM, RF, and GP, in conjunction with two sophisticated variable selection methods, i.e. empirical heuristic strategy and nonnumerical genetic algorithm. Among all the built models the most predictable one is constructed based on the simplest combination of heuristic variable selection and MLR modeling, with its predictive coefficient of determination (r(pred)(2)) and root-mean-square error of prediction (RMSP) on external independent test set of 0.90 and 0.39, respectively. Subsequently, this model is used to explain the structural factors that fundamentally govern the self-assembly behavior of Gemini surfactant molecules in solution and to design several new Gemini surfactants with potentially high CMC activity and low environmental risk. Further, these designed compounds are synthesized by diquaternary ammonium reaction and characterized by elemental analysis, (1)H NMR, (13)C NMR and mass spectrum. Found a promising candidate that possesses particularly high CMC potency as 0.83 mmol L(-1) at 25°C. This experimentally measured value is in agreement with the model-predicted 0.89 mmol L(-1) fairly well.

Do halide motifs stabilize protein architecture?

Halide anions are traditionally recognized as the structure maker and breaker of bulk water to indirectly influence the physicochemical and biological properties of biomacromolecules immersed in electrolyte solution, but here we are more interested in whether they can be structured in the protein interior, forming that we named "halide motifs", to stabilize the protein architecture through direct noncovalent interactions with their context. In the current work, we present a systematical investigation on the energy components in 782 high-quality protein halide motifs retrieved from the Protein Data Bank (PDB), by means of the continuum electrostatic analysis coupled with nonelectrostatic considerations, as well as hybrid quantum mechanical/molecular mechanical (QM/MM) examination. We find that most halide motifs (91.6%) in our data set are substantially stabilizing, and their average stabilization energy is significantly larger than that previously obtained for sophisticated protein salt bridges (-15.16 vs -3.66 kcal/mol). Strikingly, nonelectrostatic factors, especially the dispersion potential, rather than the electrostatic aspect, dominate the energetic profile of the pronouncedly charged halide motifs, since the expensive cost for electrostatic desolvation penalty requires being paid off using the income receiving from the favorable Coulomb interactions during the motif formation. In addition, all the energy terms involved in halide motifs, regardless of their electrostatic or nonelectrostatic nature, highly depend on the degree of the motif's burial in the protein, and the buried halide motifs are generally associated with a high stability. The results presented herein should be of valuable use in establishing a knowledge framework toward understanding the functional implications underlying anion structured in a biological molecule.

Systematic classification and analysis of themes in protein-DNA recognition.

Protein-DNA recognition plays a central role in the regulation of gene expression. With the rapidly increasing number of protein-DNA complex structures available at atomic resolution in recent years, a systematic, complete, and intuitive framework to clarify the intrinsic relationship between the global binding modes of these complexes is needed. In this work, we modified, extended, and applied previously defined RNA-recognition themes to describe protein-DNA recognition and used a protocol that incorporates automatic methods into manual inspection to plant a comprehensive classification tree for currently available high-quality protein-DNA structures. Further, a nonredundant (representative) data set consisting of 200 thematically diverse complexes was extracted from the leaves of the classification tree by using a locally sensitive interface comparison algorithm. On the basis of the representative data set, various physical and chemical properties associated with protein-DNA interactions were analyzed using empirical or semiempirical methods. We also examined the individual energetic components involved in protein-DNA interactions and highlighted the importance of conformational entropy, which has been almost completely ignored in previous studies of protein-DNA binding energy.

Halogen-water-hydrogen bridges in biomolecules.

The importance of water in biological systems has long been recognized in chemistry and biology communities. In this article we describe a new manner by which water affects biomolecular behaviors, called halogen-water-hydrogen bridge (XWH bridge), that is, one hydrogen bonding (H-bonding) in water-mediated H-bond bridge is replaced by halogen bonding (X-bonding). Although behaving similarly to water-mediated H-bond motif, the XWH bridge usually stands in multifurcated forms and possesses stronger directionality. Quantum mechanical analysis on several model and real systems reveals that the XWH bridges are more thermodynamically stable than other water-involved interactions, and this stability is further enhanced by the cooperation of X-bonding and H-bonding. Crystal structure survey clearly demonstrates the significance of XWH bridges in stabilization of biomolecular conformations and in mediation of protein-protein, protein-nucleic acid, and receptor-ligand recognition and binding. These findings shed light into the potential value of XWH bridges in drug design and biological engineering.

Halogen-Ionic Bridges: Do They Exist in the Biomolecular World?

If considering that the pronouncedly charged halide anions are ubiquitous in the biological world, then it is interesting to ask whether the halogen-ionic bridges-this term is named by us to describe the interaction motif of a nonbonded halogen ion with two or more electrophiles simultaneously-commonly exist in biomolecules and how they contribute to the stability and specificity of biomolecular folding and binding? To address these problems, we herein present a particularly systematic investigation on the geometrical profile and the energy landscape of halogen ions interacting with and bridging between polar and charged molecular moieties in small model systems and real crystal structures, by means of ab initio calculation, database survey, continuum electrostatic analysis, and hybrid quantum mechanics/molecular mechanics examination. All of these unequivocally demonstrate that this putative halide motif is broadly distributed in biomolecular systems (>6000) and can confer a substantial stabilization for the architecture of proteins and their complexes with nucleic acids and small ligands. This stabilization energy is estimated to be generally more than 100 kcal·mol(-1) for gas-phase states or about 20 kcal·mol(-1) for solution conditions, which is much greater than that found in sophisticated water-mediated (<10 kcal·mol(-1)) and salt (∼ 3.66 kcal·mol(-1)) bridges. In this respect, we would expect that the proposed halogen-ionic bridge, which has long been unrecognized in the arena of biological repertoires, could be appreciated in chemistry and biology communities and might be exploited as a new and versatile tool for rational drug design and bioengineering.

Gaussian process: an alternative approach for QSAM modeling of peptides.

Different statistical modeling methods (SMMs) are used for nonlinear system classification and regression. On the basis of Bayesian probabilistic inference, Gaussian process (GP) is preliminarily used in the field of quantitative structure-activity relationship (QSAR) but has not yet been applied to quantitative sequence-activity model (QSAM) of biosystems. This paper proposes the application of GP as an alternative tool for the QSAM modeling of peptides. To investigate the modeling performance of GP, three classical peptide panels were used: Angiotensin-I converting enzyme inhibitory dipeptides, bradykinin-potentiating pentapeptides and cationic antimicrobial pentadecapeptides. On this basis, we made a comprehensive comparison between the GP and some widely used SMMs such as PLS, artificial neural network (ANN) and support vector machine (SVM), and gave the conclusions as follow: (1) for those of structurally complicated peptides, particularly the polypeptides, linear PLS was incapable of capturing all dependences hidden in the peptide systems, (2) even in assistance with the monitoring technique, ANN was inclined to be overtrained in the cases of insufficient number of peptide samples, (3) SVM and GP performed best for the three peptide panels. Moreover, since GP was able to correlate the linear and nonlinear-hybrid relationship, it was slightly superior to SVM at most peptide sets.

Fluorine bonding--how does it work in protein-ligand interactions?

Although fluorination of pharmacologically active compounds has long been a common strategy to increase their metabolic stability and membrane permeation, the functionality of protein-ligand interactions involving fluorine atoms (fluorine bonding) was only recently recognized in the chemistry and biology communities. In this study, the geometric characteristics and the energetic behaviors of fluorine bonding were systematically investigated by combining two quite disparate but complementary approaches: X-ray structural analysis and theoretical calculations. We found that the short contacts involving fluorine atoms (generalized fluorine bonding) between proteins and fluorinated ligands are very frequent, and these contacts, compared to those routine hydrogen/halogen bonding, are more similar to sulfur-involved hydrogen bonding observed in proteins. ONIOM-based quantum mechanics/molecular mechanics analysis further revealed that fluorine bonding does play an essential role in protein-ligand binding, albeit the strength of isolated fluorine bonding is quite modest. Furthermore, 14 quantum mechanics (QM) and molecular mechanics (MM) methods were performed to reproduce fluorine bonding energies obtained at the rigorous MP2/aug-cc-pVDZ level of theory, and the results showed that most QM and very few MM methods perform well in the reproducibility; the MPWLYP functional and MMFF94 force field are recommended to study moderate and large fluorine bonding systems, respectively.

2D molecular graphics: a flattened world of chemistry and biology.

Molecular graphics provides an intuitive way for representation, modeling and analysis of complex chemical and biological systems. It is now widely used in the theoretical chemistry, structural biology, molecular modeling and drug design communities. Traditional molecular graphics techniques mainly dedicate to showing molecular architectures at three-dimensional (3D) level. However, in some occasions the two-dimensional (2D) representation of molecular configurations, profiles, behaviors and interactions may be more readily acceptable for audiences, especially when we need to describe abstract information in a straightforward way or to present numerous data in schematic diagrams. In recent years, 2D representation methods/tools have been developed rapidly for various purposes, ranging from the aesthetic depiction of atomic arrangement for small organic molecules to schematic layout of complicated nonbonding network across the biomolecular binding interfaces, and have received considerable interest in the fields of chemistry, biology and medicine. In this article we first propose the term of 2D molecular graphics to cover the spectrum of 2D representing chemical and biological systems, we also give a comprehensive review on the methods, tools and applications of 2D molecular graphics.

Geometric similarity between protein-RNA interfaces.

A new method is described to measure the geometric similarity between protein-RNA interfaces quantitatively. The method is based on a procedure that dissects the interface geometry in terms of the spatial relationships between individual amino acid nucleotide pairs. Using this technique, we performed an all-on-all comparison of 586 protein-RNA interfaces deposited in the current Protein Data Bank, as the result, an interface-interface similarity score matrix was obtained. Based upon this matrix, hierarchical clustering was carried out which yielded a complete clustering tree for the 586 protein-RNA interfaces. By investigating the organizing behavior of the clustering tree and the SCOP classification of protein partners in complexes, a geometrically nonredundant, diverse data set (representative data set) consisting of 45 distinct protein-RNA interfaces was extracted for the purpose of studying protein-RNA interactions, RNA regulations, and drug design. We classified protein-RNA interfaces into three types. In type I, the families and interface structural classes of the protein partners, as well as the interface geometries are all similar. In type II, the interface geometries and the interface structural classes are similar, whereas the protein families are different. In type III, only the interface geometries are similar but the protein families and the interface structural classes are distinct. Furthermore, we also show two new RNA recognition themes derived from the representative data set.

Comprehensive comparison of eight statistical modelling methods used in quantitative structure-retention relationship studies for liquid chromatographic retention times of peptides generated by protease digestion of the Escherichia coli proteome.

In this study, we propose a new peptide characterization method that gives attention to both the amino acid composition and the residue local environment. Using this approach, structural characteristics of peptides derived from Escherichia coli proteome were parameterized and, based upon that, the performance profile of eight statistical modelling methods were validated rigorously and compared comprehensively by applying them to modelling relationship between the sequence structure and retention ability for 816 experimentally measured peptides and to predicting normalized retention times for 121,273 unmeasured peptides in liquid chromatography. Results show that the regression models constructed by nonlinear approaches are more robust and predictable but time-consuming than those by linear ones. In these modelling methods, Gaussian process and back-propagation neural network possess the best stability, unbiased ability and predictive power, thus they can be used to accurately model the peptide structure-retention relationships; multiple linear regression and partial least squares regression perform worse compared to nonlinear modelling techniques but they are computationally efficient, so they are promising candidates for solving the qualitative problems involved in massive data. In addition, by investigating the descriptor importance in different models we found that the amino acid composition presents a significantly linear correlation with the retention time of peptides, whereas the residue environment is mainly correlated nonlinearly with peptide retention. The polar Arg and strongly hydrophobic amino acids such as Leu, Ile, Phe, Trp and Val are the critical factors influencing peptide retention behavior.

Side-chain conformational space analysis (SCSA): a multi conformation-based QSAR approach for modeling and prediction of protein-peptide binding affinities.

In this article, the concept of multi conformation-based quantitative structure-activity relationship (MCB-QSAR) is proposed, and based upon that, we describe a new approach called the side-chain conformational space analysis (SCSA) to model and predict protein-peptide binding affinities. In SCSA, multi-conformations (rather than traditional single-conformation) have received much attention, and the statistical average information on multi-conformations of side chains is determined using self-consistent mean field theory based upon side chain rotamer library. Thereby, enthalpy contributions (including electrostatic, steric, hydrophobic interaction and hydrogen bond) and conformational entropy effects to the binding are investigated in terms of occurrence probability of residue rotamers. Then, SCSA was applied into the dataset of 419 HLA-A 0201 binding peptides, and nonbonding contributions of each position in peptide ligands are well determined. For the peptides, the hydrogen bond and electrostatic interactions of the two ends are essential to the binding specificity, van der Waals and hydrophobic interactions of all the positions ensure strong binding affinity, and the loss of conformational entropy at anchor positions partially counteracts other favorable nonbonding effects.

Geometric characteristics of hydrogen bonds involving sulfur atoms in proteins.

Sulfur atoms have been known to participate in hydrogen bonds (H-bonds) and these sulfur-containing H-bonds (SCHBs) are suggested to play important roles in certain biological processes. This study aims to comprehensively characterize all the SCHBs in 500 high-resolution protein structures (< or =1.8 A). We categorized SCHBs into six types according to donor/acceptor behaviors and used explicit hydrogen approach to distinguish SCHBs from those of nonhydrogen bonding interactions. It is revealed that sulfur atom is a very poor H-bond acceptor, but a moderately good H-bond donor. In alpha-helix, considerable SCHBs were found between the sulphydryl group of cysteine residue i and the carbonyl oxygen of residue i-4, and these SCHBs exert effects in stabilizing helices. Although for other SCHBs, they possess no specific secondary structural preference, their geometric characteristics in proteins and in free small compounds are significantly distinct, indicating the protein SCHBs are geometrically distorted. Interestingly, sulfur atom in the disulfide bond tends to form bifurcated H-bond whereas in cysteine-cysteine pairs prefer to form dual H-bond. These special H-bonds remarkably boost the interaction between H-bond donor and acceptor. By oxidation/reduction manner, the mutual transformation between the dual H-bonds and disulfide bonds for cysteine-cysteine pairs can accurately adjust the structural stability and biological function of proteins in different environments. Furthermore, few loose H-bonds were observed to form between the sulphydryl groups and aromatic rings, and in these cases the donor H is almost over against the rim rather than the center of the aromatic ring.

2D depiction of nonbonding interactions for protein complexes.

A program called the 2D-GraLab is described for automatically generating schematic representation of nonbonding interactions across the protein binding interfaces. The input file of this program takes the standard PDB format, and the outputs are two-dimensional PostScript diagrams giving intuitive and informative description of the protein-protein interactions and their energetics properties, including hydrogen bond, salt bridge, van der Waals interaction, hydrophobic contact, pi-pi stacking, disulfide bond, desolvation effect, and loss of conformational entropy. To ensure these interaction information are determined accurately and reliably, methods and standalone programs employed in the 2D-GraLab are all widely used in the chemistry and biology community. The generated diagrams allow intuitive visualization of the interaction mode and binding specificity between two subunits in protein complexes, and by providing information on nonbonding energetics and geometric characteristics, the program offers the possibility of comparing different protein binding profiles in a detailed, objective, and quantitative manner. We expect that this 2D molecular graphics tool could be useful for the experimentalists and theoreticians interested in protein structure and protein engineering.