Effects of carboxylated multi-walled carbon nanotubes on bioconcentration of pentachlorophenol and hepatic damages in goldfish.

Carboxylated multi-walled carbon nanotubes (MWCNT-COOH) exerts strong adsorption capacity for pentachlorophenol (PCP) and they inevitably co-occur in the environment, but few studies have characterized the effects of MWCNT-COOH on the bioavailability of PCP and its oxidative and tissue damages to fish. In this work, we assessed the PCP accumulation in different organs and the induced oxidative and tissue damages of goldfish following 50-d in vivo exposure to PCP alone or co-exposure with MWCNT-COOH. Our results indicated that PCP bioaccumulation in goldfish liver, gill, muscle, intestine and gut contents was inhibited after co-exposure with MWCNT-COOH in uptake phase. PCP exposure alone and co-exposure with MWCNT-COOH evoked severe oxidative and tissue damages in goldfish bodies, as indicated by significant inhibition of activities of antioxidant enzymes, remarkable decrease in glutathione level, simultaneous elevation of malondialdehyde content, and obvious histological damages to liver and gill. The decreased accumulation of PCP in the presence of MWCNT-COOH led to the reduction of PCP-induced toxicity to liver tissues, as confirmed by the alleviation of hepatic oxidative damages. However, co-exposure groups had higher concentrations of PCP in the tissues than PCP treatment alone (p < 0.05 each) in the depuration phase, revealing that MWCNT-COOH-bound pollutants might pose higher risk once desorbed from the nanoparticles. These results provided substantial information regarding the combined effects of PCP and MWCNT-COOH on aquatic species, which helps to deeply understand the potential ecological risks of the emerging pollutants.

Additive-Induced Supramolecular Isomerism and Enhancement of Robustness in Co(II)-Based MOFs for Efficiently Trapping Acetylene from Acetylene-Containing Mixtures.

Although supramolecular isomerism in metal-organic frameworks (MOFs) would offer a favorable platform for in-depth exploring their structure-property relationship, the design and synthesis of the isomers are still rather a challenging aspect of crystal engineering. Here, a pair of supramolecular isomers of Co(II)-based MOFs (FJU-88 and FJU-89) can be directionally fabricated by rational tuning the additives. In spite of the fact that the isomers have the similar Co3 secondary building units and organic linkers, they adopt distinct networks with acs and snw topologies, respectively, which derive from the conformational flexibility of the organic ligands. It is noteworthy that the porous structure of FJU-88 would be collapsed after removal of the solvent from the pores. But FJU-89a shows permanent porosity accompanied with unusual hierarchical micro- and mesopores and superior gas selective adsorption performance. In addition, FJU-89a can efficiently trap C2H2 from C2H2/CO2 and C2H2/CH4 mixture gases through fixed-bed dynamic breakthrough experiments.

Synthesis and antitumor activity of novel substituted uracil-1'(N)-acetic acid ester derivatives of 20(S)-camptothecins.

A series of novel substituted uracil-1'(N)-acetic acid esters (6-20) of camptothecins (CPTs) were synthesized by the acylation method. These new compounds were evaluated for in vitro antitumor activity against tumor cell lines, A549, Bel7402, BGC-823, HCT-8 and A2780. In vitro results showed that most of the derivatives exhibited comparable or superior cytotoxicity compare to CPT (1) and topotecan (TPT, 2), with 12 and 13 possessing the best efficacy. Four compounds, 9, 12, 13 and 16, were selected to be evaluated for in vivo antitumor activity against H22, BGC-823 and Bel-7402 in mice. In vivo testing results indicated that 12 and 13 had antitumor activity against mouse liver carcinoma H22 close to Paclitaxel and cyclophosphamide. 12 had similar antitumor activity against human gastric carcinoma BGC-823 in nude mice compared to irinotecan (3) and possessed better antitumor activity against human hepatocarcinoma Bel-7402 in nude mice than 2. It is also discovered that 12 showed a similar mechanism but better inhibitory activity on topoisomerase I (Topo I) compared to 2. These findings indicate that 20(S)-O-fluorouracil-1'(N)-acetic acid ester derivative of CPTs, 12, could be developed as an antitumor drug candidate for clinical trial.

Prediction of protein folding rates from simplified secondary structure alphabet.

Protein folding is a very complicated and highly cooperative dynamic process. However, the folding kinetics is likely to depend more on a few key structural features. Here we find that secondary structures can determine folding rates of only large, multi-state folding proteins and fails to predict those for small, two-state proteins. The importance of secondary structures for protein folding is ordered as: extended ß strand > α helix > bend > turn > undefined secondary structure>310 helix > isolated ß strand > π helix. Only the first three secondary structures, extended ß strand, α helix and bend, can achieve a good correlation with folding rates. This suggests that the rate-limiting step of protein folding would depend upon the formation of regular secondary structures and the buckling of chain. The reduced secondary structure alphabet provides a simplified description for the machine learning applications in protein design.

Reduced alphabet for protein folding prediction.

What are the key building blocks that would have been needed to construct complex protein folds? This is an important issue for understanding protein folding mechanism and guiding de novo protein design. Twenty naturally occurring amino acids and eight secondary structures consist of a 28-letter alphabet to determine folding kinetics and mechanism. Here we predict folding kinetic rates of proteins from many reduced alphabets. We find that a reduced alphabet of 10 letters achieves good correlation with folding rates, close to the one achieved by full 28-letter alphabet. Many other reduced alphabets are not significantly correlated to folding rates. The finding suggests that not all amino acids and secondary structures are equally important for protein folding. The foldable sequence of a protein could be designed using at least 10 folding units, which can either promote or inhibit protein folding. Reducing alphabet cardinality without losing key folding kinetic information opens the door to potentially faster machine learning and data mining applications in protein structure prediction, sequence alignment and protein design.

How the folding rates of two- and multistate proteins depend on the amino acid properties.

Proteins fold by either two-state or multistate kinetic mechanism. We observe that amino acids play different roles in different mechanism. Many residues that are easy to form regular secondary structures (α helices, ß sheets and turns) can promote the two-state folding reactions of small proteins. Most of hydrophilic residues can speed up the multistate folding reactions of large proteins. Folding rates of large proteins are equally responsive to the flexibility of partial amino acids. Other properties of amino acids (including volume, polarity, accessible surface, exposure degree, isoelectric point, and phase transfer energy) have contributed little to folding kinetics of the proteins. Cysteine is a special residue, it triggers two-state folding reaction and but inhibits multistate folding reaction. These findings not only provide a new insight into protein structure prediction, but also could be used to direct the point mutations that can change folding rate.

Inter-residue interaction is a determinant of protein folding kinetics.

In recent years, there have been many breakthroughs in the prediction of protein folding kinetics using empirical and theoretical methods. These predictions focus primarily on the structural parameters in concert with contacting residues. The non-covalent contacts are a simplified model of the interactions found in proteins. Here we investigate the physico-chemical origin and derive the approximate formula ln k(f)=a+b×Σ1/d(6), where d is the distance between different residues of the protein structure. It achieves -0.83 correlation with experimental over 57 two- and multi-state folding proteins, indicating that protein folding kinetics is determined by the interactions between all pairs of residues. The interaction is a short-range coupling that is effective only when two residues are in close proximity, consistent with the dominant role of the contacts in determining folding rates.

Catalytic and inhibitory kinetic behavior of horseradish peroxidase on the electrode surface.

Enzymatic biosensors are often used to detect trace levels of some specific substance. An alternative methodology is applied for enzymatic assays, in which the electrocatalytic kinetic behavior of enzymes is monitored by measuring the faradaic current for a variety of substrate and inhibitor concentrations. Here we examine a steady-state and pre-steady-state reduction of H(2)O(2) on the horseradish peroxidase electrode. The results indicate the substrate-concentration dependence of the steady-state current strictly obeys Michaelis-Menten kinetics rules; in other cases there is ambiguity, whereby he inhibitor-concentration dependence of the steady-state current has a discontinuity under moderate concentration conditions. For pre-steady-state phases, both catalysis and inhibition show an abrupt change of the output current. These anomalous phenomena are universal and there might be an underlying biochemical or electrochemical rationale.

Choice of synonymous codons associated with protein folding.

Bioinformatical studies suggest that additional information provided by nucleic acids is necessary to construct protein three-dimensional structures. We find underlying correlations between the contents of bases. All correlations occur at the third codon position of a gene sequence. Four inverse relationships are observed between u(3) and c(3), between a(3) and g(3), between u(3) and g(3), and between c(3) and a(3); and two positive relationships are apparent between u(3) and a(3), and between c(3) and g(3). Their correlation coefficients reach -0.92, -0.89, -0.83, -0.85, 0.83, and 0.66, respectively, for large proteins with multistate folding kinetics. The interconnection of bases can be ascribed to choice of synonymous codons associated with protein folding in vivo. In this study, the refolding rate constants of large proteins correlate with the contents of the third base, suggesting that there is underlying biochemical rationale of guiding protein folding in choosing synonymous codons.

Relationship between protein folding kinetics and amino acid properties.

The successful prediction of protein-folding rates based on the sequence-predicted secondary structure suggests that the folding rates might be predicted from sequence alone. To pursue this question, we directly predict the folding rates from amino acid sequences, which do not require any information on secondary or tertiary structure. Our work achieves 88% correlation with folding rates determined experimentally for proteins of all folding types and peptide, suggesting that almost all of the information needed to specify a protein's folding kinetics and mechanism is comprised within its amino acid sequence. The influence of residue on folding rate is related to amino acid properties. Hydrophobic character of amino acids may be an important determinant of folding kinetics, whereas other properties, size, flexibility, polarity and isoelectric point, of amino acids have contributed little to the folding rate constant.

Differentiation between two-state and multi-state folding proteins based on sequence.

Prediction of protein-folding rates follows different rules in two-state and multi-state kinetics. The prerequisite for the prediction is to recognize the folding kinetic pathway of proteins. Here, we use the logistic regression and support vector machine to discriminate between two-state and multi-state folding proteins. We find that chain length is sufficient to accurately recognize multi-state proteins. There is a transition boundary between two kinetic models. Protein folds with multi-state kinetics, if its length is larger than 112 residues. The logistic prediction from amino acid composition shows that the kinetic pathway of folding is closely related to amino acid volume. Small amino acids make two-state folding easier, and vice versa. However, cysteine, alanine, arginine, lysine, histidine, and methionine do not conform to this rule.

Prediction of folding transition-state position (betaT) of small, two-state proteins from local secondary structure content.

Folding kinetics of proteins is governed by the free energy and position of transition states. But attempts to predict the position of folding transition state on reaction pathway from protein structure have been met with only limited success, unlike the folding-rate prediction. Here, we find that the folding transition-state position is related to the secondary structure content of native two-state proteins. We present a simple method for predicting the transition-state position from their alpha-helix, turn and polyproline secondary structures. The method achieves 81% correlation with experiment over 24 small, two-state proteins, suggesting that the local secondary structure content, especially for content of alpha-helix, is a determinant of the solvent accessibility of the transition state ensemble and size of folding nucleus.

Secondary structure length as a determinant of folding rate of proteins with two- and three-state kinetics.

We present a simple method for determining the folding rates of two- and three-state proteins from the number of residues in their secondary structures (secondary structure length). The method is based on the hypothesis that two- and three-state foldings share a common pattern. Three-state proteins first condense into metastable intermediates, subsequent forming of alpha-helices, turns, and beta-sheets at slow rate-limiting step. The folding rate of such proteins anticorrelate with the length of these beta-secondary structures. It is also assumed that in two-state folding, rapidly folded alpha-helices and turns may facilitate formation of fleeting unobservable intermediates and thus show two-state behavior. There is an inverse relationship between the folding rate and the length of beta-sheets and loops. Our study achieves 94.0 and 88.1% correlations with folding rates determined experimentally for 21 three- and 38 two-state proteins, respectively, suggesting that protein-folding rates are determined by the secondary structure length. The kinetic kinds are selected on the basis of a competitive formation of hydrophobic collapse and alpha-structure in early intermediates.

Amino acid sequence predicts folding rate for middle-size two-state proteins.

The significant correlation between protein folding rates and the sequence-predicted secondary structure suggests that folding rates are largely determined by the amino acid sequence. Here, we present a method for predicting the folding rates of proteins from sequences using the intrinsic properties of amino acids, which does not require any information on secondary structure prediction and structural topology. The contribution of residue to the folding rate is expressed by the residue's Omega value. For a given residue, its Omega depends on the amino acid properties (amino acid rigidity and dislike of amino acid for secondary structures). Our investigation achieves 82% correlation with folding rates determined experimentally for simple, two-state proteins studied until the present, suggesting that the amino acid sequence of a protein is an important determinant of the protein-folding rate and mechanism.

Secondary structural wobble: the limits of protein prediction accuracy.

At present, accuracies of secondary structural prediction scarcely go beyond 70-75%. Secondary structural comparison is carried out among sequence-identified proteins. The results show natural wobble between different secondary structural types is possible in homologous families, and the best prediction accuracy will rarely be 100%. Besides shortcoming of the prediction approaches, secondary structural wobble is found to be responsible for nearly all secondary structural prediction limits. Only average 73.2% of amino acid residue is conserved in secondary structural types. The wobble allows alpha-class/coil and beta-class/coil transitions but not direct alpha-class/beta-class transition. Propensity values representing the statistical occurrence of 20 amino acid residues in secondary structural wobbles are given.