Hydrolysis Mechanism of Water-Soluble Ammonium Polyphosphate Affected by Zinc Ions.

Ammonium polyphosphate (APP) as a chelated and controlled-release fertilizer has been widely used in agriculture, and its hydrolysis process is of significance for its storage and application. In this study, the hydrolysis regularity of APP affected by Zn2+ was explored systematically. The hydrolysis rate of APP with different polymerization degrees was calculated in detail, and the hydrolysis route of APP deduced from the proposed hydrolysis model was combined with the conformation analysis of APP to reveal the mechanism of APP hydrolysis. The results show that Zn2+ decreased the stability of the P-O-P bond by causing a conformational change in the polyphosphate due to chelation, which in turn promoted APP hydrolysis. Meanwhile, Zn2+ caused the hydrolysis of polyphosphates with a high polymerization degree in APP to be switched from a terminal chain scission to an intermediate chain scission or various coexisting routes, affecting orthophosphate release. This work provides a theoretical basis and guiding significance for the production, storage, and application of APP.

Treatment of distiller grain with wet-process phosphoric acid leads to biochar for the sustained release of nutrients and adsorption of Cr(VI).

Soil amendment products, such as biochar, with both sustained nutrient release and heavy metal retention properties are of great need in agricultural and environmental industries. Herein, we successfully prepared a new biochar material with multinutrient sustained-release characteristics and chromium removal potential derived from distiller grain by wet-process phosphoric acid (WPPA) modification without washing. SEM, TEM TG-IR, in situ DRIFTS and XRD characterization indicated that biochar and polyphosphate formed simultaneously and were tightly intertwined by one-step pyrolysis. The optimal product (PKBC-400) had the most stable carbon structure and an adequate P-O-P structure with less P loss. Batch experiments illustrated that 92.83% P (ortho-P), 85.94% K, 41.49% Fe, 78.42% Al and 65.60% Mg were continuously released in water from PKBC-400 within 63 days, and the maximum Cr removal rate reached 83.57% (50 mg/L K2Cr2O7, pH=3.0) with an increased BET surface area (304.0557 m2/g) after nutrient release. SEM, IC and 31P NMR analyses revealed that the dissolution and hydrolysis of polyphosphates not only realized the sustained release of multiple nutrients but also significantly improved the sustained release performance. The proposed resource utilization strategy provided new ideas for Cr hazard control, biomass waste utilization and fertilizer development.

Fulvic-polyphosphate composite embedded in ZnO nanorods (FA-APP@ZnO) for efficient P/Zn nutrition for peas (Pisum sativum L.).

A nano-fertilizer (FA-APP@ZnO) was designed and prepared based on the copolymer of fulvic acid (FA) and ammonium polyphosphate (APP) with ZnO nanorods embedded, to tackle the antagonism between phosphorus (P) and zinc (Zn) in fertilization. FA-APP@ZnO was confirmed to revert the precipitability of H2PO4 - and Zn2+ into a synergistic performance, where FA and APP can disperse ZnO nanorods, and in return, ZnO catalyzes the hydrolysis of the absorbed APP. The hydrolysis rate constant of pyrophosphates consequently increased 8 times. The dry biomass of pea (Pisum sativum L.) under the FA-APP@ZnO hydroponics for 7 days increased by 119%, as compared with the situation employing the conventional NH4H2PO4 and ZnSO4 compound fertilizer. Moreover, the uptake of seedlings for P and Zn was enhanced by 54% and 400%, respectively. The accelerated orthophosphate release due to ZnO catalysis and the well-dispersed ZnO nanorods enabled by APP met the urgent demand for P and Zn nutrients for peas, especially at their vigorous seedling stage. This work would provide a new idea for constructing nano-platforms to coordinate the incompatible P and Zn nutrients for the improvement of agronomic efficiency.

NIPS, a 3D network-integrated predictor of deleterious protein SAPs, and its application in cancer prognosis.

Identifying deleterious mutations remains a challenge in cancer genome sequencing projects, reflecting the vast number of candidate mutations per tumour and the existence of interpatient heterogeneity. Based on a 3D protein interaction network profiled via large-scale cross-linking mass spectrometry, we propose a weighted average formula involving the combination of three types of information into a 'meta-score'. We assume that a single amino acid polymorphism (SAP) may have a deleterious effect if the mutation rarely occurs naturally during evolution, if it inhibits binding between a pair of interacting proteins when located at their interface, or if it plays an important role in a protein interaction (PPI) network. Cross-validation indicated that this new method presents an AUC value of 0.93 and outperforms other widely used tools. The application of this method to the CPTAC colorectal cancer dataset enabled the accurate identification of validated deleterious mutations and yielded insights into their potential pathogenesis. Survival analysis showed that the accumulation of deleterious SAPs is significantly associated with a poor prognosis. The new method provides an alternative method to identifying and ranking deleterious cancer SAPs based on a 3D PPI network and will contribute to the understanding of pathogenesis and the discovery of prognostic biomarkers.

Synergistic Allosteric Mechanism of Fructose-1,6-bisphosphate and Serine for Pyruvate Kinase M2 via Dynamics Fluctuation Network Analysis.

Pyruvate kinase M2 (PKM2) plays a key role in tumor metabolism and regulates the rate-limiting final step of glycolysis. In tumor cells, there are two allosteric effectors for PKM2: fructose-1,6-bisphosphate (FBP) and serine. However, the relationship between FBP and serine for allosteric regulation of PKM2 is unknown. Here we constructed residue/residue fluctuation correlation network based on all-atom molecular dynamics simulations to reveal the regulation mechanism. The results suggest that the correlation network in bound PKM2 is distinctly different from that in the free state, FBP/PKM2, or Ser/PKM2. The community network analysis indicates that the information can freely transfer from the allosteric sites of FBP and serine to the substrate site in bound PKM2, while there exists a bottleneck for information transfer in the network of the free state. Furthermore, the binding free energy between the substrate and PKM2 for bound PKM2 is significantly lower than either of FBP/PKM2 or Ser/PKM2. Thus, a hypothesis of "synergistic allosteric mechanism" is proposed for the allosteric regulation of FBP and serine. This hypothesis was further confirmed by the perturbational and mutational analyses of community networks and binding free energies. Finally, two possible synergistic allosteric pathways of FBP-K433-T459-R461-A109-V71-R73-MG2-OXL and Ser-I47-C49-R73-MG2-OXL were identified based on the shortest path algorithm and were confirmed by the network perturbation analysis. Interestingly, no similar pathways could be found in the free state. The process targeting on the allosteric pathways can better regulate the glycolysis of PKM2 and significantly inhibit the progression of tumor.

Conformational selection and induced fit for RNA polymerase and RNA/DNA hybrid backtracked recognition.

RNA polymerase catalyzes transcription with a high fidelity. If DNA/RNA mismatch or DNA damage occurs downstream, a backtracked RNA polymerase can proofread this situation. However, the backtracked mechanism is still poorly understood. Here we have performed multiple explicit-solvent molecular dynamics (MD) simulations on bound and apo DNA/RNA hybrid to study backtracked recognition. MD simulations at room temperature suggest that specific electrostatic interactions play key roles in the backtracked recognition between the polymerase and DNA/RNA hybrid. Kinetics analysis at high temperature shows that bound and apo DNA/RNA hybrid unfold via a two-state process. Both kinetics and free energy landscape analyses indicate that bound DNA/RNA hybrid folds in the order of DNA/RNA contracting, the tertiary folding and polymerase binding. The predicted Φ-values suggest that C7, G9, dC12, dC15, and dT16 are key bases for the backtracked recognition of DNA/RNA hybrid. The average RMSD values between the bound structures and the corresponding apo ones and Kolmogorov-Smirnov (KS) P-test analyses indicate that the recognition between DNA/RNA hybrid and polymerase might follow an induced fit mechanism for DNA/RNA hybrid and conformation selection for polymerase. Furthermore, this method could be used to relative studies of specific recognition between nucleic acid and protein.

Recognition mechanism between Lac repressor and DNA with correlation network analysis.

Lac repressor is a DNA-binding protein which inhibits the expression of a series of genes involved in lactose metabolism. Lac repressor can bind at a random DNA site via nonspecific interactions; then, it rapidly translocates through the double chain of DNA until it finds the specific binding site. Therefore, the site transform between these two modes is essential for the specific recognition between Lac repressor and DNA. Here, the recognition mechanism between Lac repressor and DNA was illustrated with molecular dynamics simulations and correlation network analyses. We have found that the correlation network of the specific system (2KEI) is more centralized and denser than that of the nonspecific system (1OSL). The significant difference in the networks between the nonspecific and specific systems is apparently due to the different binding modes. Then, different interaction modes were found where electrostatic and hydrogen bonding interactions in the nonspecific system are stronger than those in the specific system. Hydrophobic interactions were found only in specific complexes and mostly focused on the hinge helices. Furthermore, the hinge helix will induce the bending of DNA for the specific system. At the same time, a common specific sequence of DNA was revealed for three specific systems. Then, two design systems (positive and control) were used to evaluate the specific recognition between DNA and Lac repressor. These combined methods can be used to reveal the recognition mechanism between other transcription factors and DNA.

Kink turn sRNA folding upon L7Ae binding using molecular dynamics simulations.

The kink-turn sRNA motif in archaea, whose combination with protein L7Ae initializes the assembly of small ribonucleoprotein particles (sRNPs), plays a key role in ribosome maturation and the translation process. Although many studies have been reported on this motif, the mechanism of sRNA folding coupled with protein binding is still poorly understood. Here, room and high temperature molecular dynamics (MD) simulations were performed on the complex of 25-nt kink-turn sRNA and L7Ae. The average RMSD values between the bound and corresponding apo structures and Kolmogorov-Smirnov P test analysis indicate that sRNA may follow an induced fit mechanism upon binding with L7Ae, both locally and globally. These conclusions are further supported by high-temperature unfolding kinetic analysis. Principal component analysis (PCA) found both closing and opening motions of the kink-turn sRNA. This might play a key role in the sRNP assembly and methylation catalysis. These combined computational methods can be used to study the specific recognition of other sRNAs and proteins.