PMFF: Development of a Physics-Based Molecular Force Field for Protein Simulation and Ligand Docking.

The physics-based molecular force field (PMFF) was developed by integrating a set of potential energy functions in which each term in an intermolecular potential energy function is derived based on experimental values, such as the dipole moments, lattice energy, proton transfer energy, and X-ray crystal structures. The term "physics-based" is used to emphasize the idea that the experimental observables that are considered to be the most relevant to each term are used for the parameterization rather than parameterizing all observables together against the target value. PMFF uses MM3 intramolecular potential energy terms to describe intramolecular interactions and includes an implicit solvation model specifically developed for the PMFF. We evaluated the PMFF in three ways. We concluded that the PMFF provides reliable information based on the structure in a biological system and interprets the biological phenomena accurately by providing more accurate evidence of the biological phenomena.

Chemical proteomic identification of T-plastin as a novel host cell response factor in HCV infection.

Hepatitis C virus (HCV) infection is the leading cause of chronic liver disease that currently affects at least 170 million people worldwide. Although significant efforts have been focused on discovering inhibitors of a viral polymerase (NS5B) or protease (NS3), strategies to cure HCV infection have been hampered by the limited therapeutic target proteins. Thus, discovery of a novel target remains a major challenge. Here, we report a method that combines transcriptome expression analysis with unbiased proteome reactivity profiling to identify novel host cell response factors in HCV infection. A chemical probe for non-directed proteomic profiling was selected based on genome-wide transcriptome expression analysis after HCV infection, which revealed noticeable alterations related to disulfide bond metabolism. On the basis of this result, we screened the proteome reactivity using chemical probes containing thiol-reactive functional groups and discovered a unique labeling profile in HCV-infected cells. A subsequent quantitative chemical proteomic mapping study led to the identification of a target protein, T-plastin (PLST), and its regulation of HCV replication. Our approach demonstrates both a straightforward strategy for selecting chemical probes to discriminate disease states using a model system and its application for proteome reactivity profiling for novel biomarker discovery.

Unbiased proteomic profiling strategy for discovery of bacterial effector proteins reveals that Salmonella protein PheA is a host cell cycle regulator.

Salmonella utilizes a type III secretion system to inject bacterial effector proteins into the host cell cytosol. Once in the cytosol, these effectors hijack various biochemical pathways to regulate virulence. Despite the importance of effector proteins, especially for understanding host-pathogen interactions, a potentially large number of effectors are yet to be identified. Here, we demonstrate that unbiased chemical proteomic profiling using off-the-shelf fluorescent probes leads to the discovery of a host cell cycle regulator encoded in the Salmonella genome. Our profiling combined with bioinformatic analysis implicates 29 Salmonella as potential effectors. We follow up on the top candidate, chorismate mutase-P/prehenate dehydratase, PheA, and present evidence that PheA is an effector that mimics E2F7 transcription factor of the host cell and promotes G1/S cell cycle arrest. This validates our strategy and opens opportunities for effector identification in the future.

Rational design of a photo-crosslinking BODIPY for in situ protein labeling.

Photo-crosslinking agents have emerged as critical tools to investigate protein-protein interactions in complex proteomes, but there are few photocrosslinkers available at the moment. Here, we report the first rational design of a photo-crosslinking BODIPY fluorophore (pcBD) and its biological application for biomolecule labeling. As a photosensitizing functional motif, an aryl ketone group was incorporated into the BODIPY fluorophore, and a series of proteins were labeled by pcBD compounds upon UV irradiation. In order to investigate protein-protein interactions in a protein mixture, amino-functionalized pcBD was prepared and covalently attached to a ubiquitin ligase binding peptide. Upon UV irradiation, we could successfully visualize the substrates in the total lysate. These results provided a proof of concept for spatially controllable tagging via photo-activation of the pcBD scaffold, and demonstrated its potential usage for in situ labeling applications.

Proteome reactivity profiling for the discrimination of pathogenic bacteria.

Diverse proteome reactivity profiles were obtained using small-molecule electrophiles. Based on the cross-reactivity profile, each protein generated a unique reactivity fingerprint. Here, we report the first proteome reactivity signature-based discrimination of 11 bacteria. Perfect differentiation of 11 bacteria can be achieved using 2 benzyl-halide probes.

Small-molecule probes elucidate global enzyme activity in a proteomic context.

The recent dramatic improvements in high-resolution mass spectrometry (MS) have revolutionized the speed and scope of proteomic studies. Conventional MS-based proteomics methodologies allow global protein profiling based on expression levels. Although these techniques are promising, there are numerous biological activities yet to be unveiled, such as the dynamic regulation of enzyme activity. Chemical proteomics is an emerging field that extends these types proteomic profiling. In particular, activity-based protein profiling (ABPP) utilizes small-molecule probes to monitor enzyme activity directly in living intact subjects. In this mini-review, we summarize the unique roles of small-molecule probes in proteomics studies and highlight some recent examples in which this principle has been applied.

Low stability and a conserved N-glycosylation site are associated with regulation of the discoidin domain receptor family by glucose via post-translational N-glycosylation.

Cell-surface expression of the discoidin domain receptor (DDR) tyrosine kinase family in high molecular mass form was controlled sensitively by the glucose concentration through a post-translational N-glycosylation process. Cycloheximide time-course experiments revealed that the high-molecular-mass forms of DDR1 and DDR2 were significantly less stable than control receptor tyrosine kinases. Site-directed mutational analysis of the consensus N-glycosylation sites of the DDRs revealed that mutations of asparagine 213 of DDR2 and asparagine 211 of DDR1, a conserved N-glycosylation site among vertebrate DDRs, inhibited the generation of the high-molecular-mass isoform. Taken together, these results suggest a mechanism to control the activity of the DDR family by regulating its cell-surface expression. Due to low stability, the steady-state population of functional DDR proteins in the cell surface depends sensitively on its maturation process via post-translational N-glycosylation, which is controlled by the glucose supply and the presence of a conserved N-glycosylation site.

The tyrosine kinase inhibitor nilotinib selectively inhibits CYP2C8 activities in human liver microsomes.

The tyrosine kinase inhibitor nilotinib was examined for its inhibition of cytochrome P450s (CYPs) in human liver microsomes and in human CYPs expressed in a baculovirus-insect cell system. Nilotinib demonstrated preferential inhibition of CYP2C8-mediated paclitaxel 6α-hydroxylation, rosiglitazone hydroxylation and amodiaquine N-deethylation in human liver microsomes, with IC50 values of 0.4, 7.5 and 0.7 µM, respectively. The IC50 value of nilotinib for paclitaxel 6α-hydroxylation was 20-fold lower than that of the other five tyrosine-kinase inhibitors tested. Nilotinib appears to display competitive inhibition against paclitaxel 6α-hydroxylation and amodiaquine N-deethylation, with estimated mean Ki values of 0.90 and 0.15 µM in human liver microsomes and 0.10 and 0.61 µM in recombinant human CYP2C8, respectively. These results are consistent with those of molecular docking simulations, where paclitaxel could not access the CYP2C8 catalytic site in the presence of nilotinib, but the binding of midazolam, a substrate of CYP3A4, to the catalytic site of CYP3A4 was not affected by nilotinib. The demonstrated inhibitory activity of nilotinib against CYP2C8 at concentrations less than those observed in patients who received nilotinib therapy is of potential clinical relevance and further in vivo exploration is warranted.

Identification of cancer cell-line origins using fluorescence image-based phenomic screening.

Universal phenotyping techniques that can discriminate among various states of biological systems have great potential. We applied 557 fluorescent library compounds to NCI's 60 human cancer cell-lines (NCI-60) to generate a systematic fluorescence phenotypic profiling data. By the kinetic fluorescence intensity analysis, we successfully discriminated the organ origin of all the 60 cell-lines.

Site-selective labeling at Cys302 of aldehyde dehydrogenase unveils a selective mitochondrial stain.

A mitochondria-trackable fluorophore, CDy2, selectively labels Cys302 in the active site of mitochondrial aldehyde dehydrogenase (ALDH2).

Inferring the physical connectivity of complex networks from their functional dynamics.

BACKGROUND: Biological networks, such as protein-protein interactions, metabolic, signalling, transcription-regulatory networks and neural synapses, are representations of large-scale dynamic systems. The relationship between the network structure and functions remains one of the central problems in current multidisciplinary research. Significant progress has been made toward understanding the implication of topological features for the network dynamics and functions, especially in biological networks. Given observations of a network system's behaviours or measurements of its functional dynamics, what can we conclude of the details of physical connectivity of the underlying structure? RESULTS: We modelled the network system by employing a scale-free network of coupled phase oscillators. Pairwise phase coherence (PPC) was calculated for all the pairs of oscillators to present functional dynamics induced by the system. At the regime of global incoherence, we observed a Significant pairwise synchronization only between two nodes that are physically connected. Right after the onset of global synchronization, disconnected nodes begin to oscillate in a correlated fashion and the PPC of two nodes, either connected or disconnected, depends on their degrees.Based on the observation of PPCs, we built a weighted network of synchronization (WNS), an all-to-all functionally connected network where each link is weighted by the PPC of two oscillators at the ends of the link. In the regime of strong coupling, we observed a Significant similarity in the organization of WNSs induced by systems sharing the same substrate network but different configurations of initial phases and intrinsic frequencies of oscillators.We reconstruct physical network from the WNS by choosing the links whose weights are higher than a given threshold. We observed an optimal reconstruction just before the onset of global synchronization.Finally, we correlated the topology of the background network to the observed change of the functional activities in the system. CONCLUSIONS: The results presented in this study indicate a strong relationship between the structure and dynamics of complex network systems. As coupling strength increases, synchronization emerges among hub nodes and recruits small-degree nodes. The results show that the onset of global synchronization in the system hinders the reconstruction of an underlying complex structure. Our analysis helps to clarify how the synchronization is achieved in systems of different network topologies.

Quantitative structural-activity relationship (QSAR) study for fungicidal activities of thiazoline derivatives against rice blast.

For the development of new fungicides against rice blast, the quantitative structural-activity relationship (QSAR) analyses for fungicidal activities of thiazoline derivatives were carried out using multiple linear regression (MLR) and neural network (NN). We have studied the substituent effects at para site of R(1) and at three sites (ortho, meta, or para) of R(2) aromatic rings in compounds. The results of MLR and NN analyses in the training set of Set-3 showed good correlations (r(2) values of 0.829 and 0.966, respectively) between the descriptors and the fungicidal activities. Five descriptors including the non-overlap steric volume SV(R2C2)), Connolly surface area SA(R1), hydrophobicity Sigma pi(R2), and Hammett substituent constants (sigma(pR1) and sigma(mR2)) were selected as important factors of fungicidal activities. Although the descriptors of optimum MLR model were used in NN, the results were improved by NN. This means that the descriptors used in MLR model include non-linear relationships.

Methodology of the thyroid gland disease decision-making using profiling in steroid hormone pathway.

To find out the genetic factors of outbreak of thyroid gland disease, we developed the thyroid gland decision-making system, which processes the metabolic profile in steroid hormone map using a statistical method. Metabolic profile is a measured data of lots of mixed materials that includes not only known metabolites, but also unknown ones, which is estimated to have an influence on the thyroid gland disease. Therefore, to develop thyroid gland disease decision-making system, analyzing metabolic profile containing multi-materials would be useful for diagnosing thyroid gland disease. Because experimental values used for system construction are area values for the retention time, the observations are preprocessed through variable transition and t-test to use the area values concurrently and the highly correlated materials are estimated by principal component analysis. The thyroid gland decision-making system developed through the logistic regression is an excellent system demonstrating 98.7% accuracy in the classification table.

Design and evolution of new catalytic activity with an existing protein scaffold.

The design of enzymes with new functions and properties has long been a goal in protein engineering. Here, we report a strategy to change the catalytic activity of an existing protein scaffold. This was achieved by simultaneous incorporation and adjustment of functional elements through insertion, deletion, and substitution of several active site loops, followed by point mutations to fine-tune the activity. Using this approach, we were able to introduce beta-lactamase activity into the alphabeta/betaalpha metallohydrolase scaffold of glyoxalase II. The resulting enzyme, evMBL8 (evolved metallo beta-lactamase 8), completely lost its original activity and, instead, catalyzed the hydrolysis of cefotaxime with a (kcat/Km)app of 1.8 x 10(2) (mole/liter)(-1) second(-1), thus increasing resistance to Escherichia coli growth on cefotaxime by a factor of about 100.

Identification and functional characterization of novel CYP2J2 variants: G312R variant causes loss of enzyme catalytic activity.

CYP2J2 plays important roles in the metabolism of therapeutic drugs, such as astemizole and ebastine, as well as endogenous fatty acids. This study aimed to identify CYP2J2 genetic variants in Koreans and to characterize their functional consequences. From direct sequencing of the CYP2J2 gene, 12 genetic variations, including the two novel nonsynonymous mutations G312R and P351L, were identified from 93 Korean subjects. The two novel CYP2J2 variants were co-expressed with NADPH-cytochrome P450 reductase in Sf9 cells and their catalytic activities were quantified. The recombinant CYP2J2 G312R variant showed almost complete loss of enzymatic activity, as determined by CYP2J2-catalysed astemizole O-demethylation and ebastine hydroxylation. The CYP2J2 P351L variant showed enzymatic activities that were comparable with the wild-type CYP2J2. The reduced CO spectra of the recombinant CYP2J2 proteins suggested no CO binding to the heme in CYP2J2 G312R. In addition, molecular modelling of the three-dimensional structure consistently predicted that there might be spatial hindrance between heme and the bulky side chain of the R312 residue in CYP2J2 G312R variant. The CYP2J2 G312R variant was not found in 192 Chinese, 99 African-Americans, 100 Caucasians and 159 Vietnamese subjects. Two of the 192 Chinese subjects (0.52%) were heterozygous for CYP2J2 P351L. Twelve CYP2J2 variants, including two novel nonsynonymous variants, were identified in a Korean population. The G312R variant is the first nonfunctional CYP2J2 allele to be identified, and is expected to influence the disposition of its substrate therapeutics, as well as endogenous compounds.

Two novel mutations of Wiskott-Aldrich syndrome: the molecular prediction of interaction between the mutated WASP L101P with WASP-interacting protein by molecular modeling.

Wiskott-Aldrich syndrome (WAS) is an X-linked disorder characterized by eczema, thrombocytopenia and increased susceptibility of infections, with mutations of the WAS gene being responsible for WAS and X-linked thrombocytopenia. Herein, two novel mutations of WAS at T336C on exon 3, and at 1326-1329, a G deletion on exon 10, resulting in L101P missense mutation and frameshift mutation 444 stop, respectively, are reported. The affected patients with either mutation showed severe suppression of WAS protein (WASP) levels, T cell proliferation, and CFSE-labeled T cells division. Because WASP L101 have not shown direct nuclear Overhauser effect (NOE) contact with the WASP-interacting protein (WIP) in NMR spectroscopy, molecular modeling was performed to evaluate the molecular effect of WASP P101 to WIP peptide. It is presumed that P101 induced a conformational change in the Q99 residue of WASP and made the side chain of Q99 move away from the WIP peptide, resulting in disruption of the hydrogen bond between Q99 WASP and Y475 WIP. A possible model for the molecular pathogenesis of WAS has been proposed by analyzing the interactions of WASP and WIP using a molecular modeling study.

Quantitative structure-polarization relationships (QSPR) study of BTEX tracers for the formation of antibody-BTEX-EDF complex.

The multiple linear regression (MLR) analysis and back propagation neural networks (NN) were performed to examine the quantitative structure-polarization relationships (QSPR) for the formation of antibody-BTEX-EDF complex. Five descriptors out of 18 ones were selected for both MLR and NN, respectively, and the selected descriptors in MLR were the same as those in NN. These descriptors were the number of atoms, which can form hydrogen bonds (HA), connolly surface area (Area), the highest occupied molecular orbital energy (HOMO), partial charge of C3 carbon atom (C3), and HOMO pi coefficient of C2 carbon atom (P2). The fact that the descriptors in MLR are identical to those in NN suggests that these descriptors have good linear relationships and play a significant role in the formation of antibody-tracer complex.

QSAR analysis of SH2-binding phosphopeptides: using interaction energies and cross-correlation coefficients.

Quantitative structure-activity relationships (QSAR) analyses were carried out on the SH2-phosphopeptide complexes using multiple linear regressions. The residue-residue interaction energies and cross-correlation coefficients were used as descriptors. Since the number of descriptors was very large (602 for interaction energies and 951 for cross-correlation coefficients), the stepwise addition method was applied for the multiple linear regressions. The residue-residue interaction energies were good descriptors for structure-activity relationships. The high r(2) regression models were achieved by using interaction energy. In addition, the concerted atomic motions, which show the dynamic properties during the SH2-phosphopeptide interaction, were used as descriptors. They were identified by the cross-correlation coefficients for atomic displacement. The best regression model, derived by using four cross-correlation coefficients, gave a high r(2) value of 0.925. This suggests that the dynamic properties showing concerted atomic motions can be used as good descriptors in QSAR study.

An investigation of phosphopeptide binding to SH2 domain.

A comparative molecular field analysis (CoMFA) was carried out to investigate quantitative structure-activity relationships for SH2-binding phosphopeptides. Two alignment rules were applied in our CoMFA model. The phosphopeptide backbone atoms were used for superposition in alignment I and the backbone atoms of peptide-binding residues of SH2-phosphopeptide complexes were used in alignment II to consider the position of phosphopeptides in SH2-binding sites. The higher correlation and predictivity in alignment II (r(2) value of 0.961 and cross-validated r(2) value of 0.682) suggest that the consideration of peptide-binding position at the binding sites gives rise to better results when the ligand-receptor complex structure is considered. In addition, CoMFA contour and electrostatic maps were well accorded with the experimental results in which the replacement of N-terminal residues with an acetyl group reduced the binding affinity. Therefore, the modification of molecular size and charge of phosphopeptides can be carried out based on these contour maps in order to increase binding affinities.

Attack vulnerability of complex networks.

We study the response of complex networks subject to attacks on vertices and edges. Several existing complex network models as well as real-world networks of scientific collaborations and Internet traffic are numerically investigated, and the network performance is quantitatively measured by the average inverse geodesic length and the size of the largest connected subgraph. For each case of attacks on vertices and edges, four different attacking strategies are used: removals by the descending order of the degree and the betweenness centrality, calculated for either the initial network or the current network during the removal procedure. It is found that the removals by the recalculated degrees and betweenness centralities are often more harmful than the attack strategies based on the initial network, suggesting that the network structure changes as important vertices or edges are removed. Furthermore, the correlation between the betweenness centrality and the degree in complex networks is studied.