Computational design of highly efficient thermostable MHET hydrolases and dual enzyme system for PET recycling.

Recently developed enzymes for the depolymerization of polyethylene terephthalate (PET) such as FAST-PETase and LCC-ICCG are inhibited by the intermediate PET product mono(2-hydroxyethyl) terephthalate (MHET). Consequently, the conversion of PET enzymatically into its constituent monomers terephthalic acid (TPA) and ethylene glycol (EG) is inefficient. In this study, a protein scaffold (1TQH) corresponding to a thermophilic carboxylesterase (Est30) was selected from the structural database and redesigned in silico. Among designs, a double variant KL-MHETase (I171K/G130L) with a similar protein melting temperature (67.58 °C) to that of the PET hydrolase FAST-PETase (67.80 °C) exhibited a 67-fold higher activity for MHET hydrolysis than FAST-PETase. A fused dual enzyme system comprising KL-MHETase and FAST-PETase exhibited a 2.6-fold faster PET depolymerization rate than FAST-PETase alone. Synergy increased the yield of TPA by 1.64 fold, and its purity in the released aromatic products reached 99.5%. In large reaction systems with 100 g/L substrate concentrations, the dual enzyme system KL36F achieved over 90% PET depolymerization into monomers, demonstrating its potential applicability in the industrial recycling of PET plastics. Therefore, a dual enzyme system can greatly reduce the reaction and separation cost for sustainable enzymatic PET recycling.

DeepTM: A deep learning algorithm for prediction of melting temperature of thermophilic proteins directly from sequences.

Thermally stable proteins find extensive applications in industrial production, pharmaceutical development, and serve as a highly evolved starting point in protein engineering. The thermal stability of proteins is commonly characterized by their melting temperature (Tm). However, due to the limited availability of experimentally determined Tm data and the insufficient accuracy of existing computational methods in predicting Tm, there is an urgent need for a computational approach to accurately forecast the Tm values of thermophilic proteins. Here, we present a deep learning-based model, called DeepTM, which exclusively utilizes protein sequences as input and accurately predicts the Tm values of target thermophilic proteins on a dataset consisting of 7790 thermophilic protein entries. On a test set of 1550 samples, DeepTM demonstrates excellent performance with a coefficient of determination (R2) of 0.75, Pearson correlation coefficient (P) of 0.87, and root mean square error (RMSE) of 6.24 ℃. We further analyzed the sequence features that determine the thermal stability of thermophilic proteins and found that dipeptide frequency, optimal growth temperature (OGT) of the host organisms, and the evolutionary information of the protein significantly affect its melting temperature. We compared the performance of DeepTM with recently reported methods, ProTstab2 and DeepSTABp, in predicting the Tm values on two blind test datasets. One dataset comprised 22 PET plastic-degrading enzymes, while the other included 29 thermally stable proteins of broader classification. In the PET plastic-degrading enzyme dataset, DeepTM achieved RMSE of 8.25 ℃. Compared to ProTstab2 (20.05 ℃) and DeepSTABp (20.97 ℃), DeepTM demonstrated a reduction in RMSE of 58.85% and 60.66%, respectively. In the dataset of thermally stable proteins, DeepTM (RMSE=7.66 ℃) demonstrated a 51.73% reduction in RMSE compared to ProTstab2 (RMSE=15.87 ℃). DeepTM, with the sole requirement of protein sequence information, accurately predicts the melting temperature and achieves a fully end-to-end prediction process, thus providing enhanced convenience and expediency for further protein engineering.

Prediction of bioactivities of microsomal prostaglandin E2 synthase-1 inhibitors by machine learning algorithms.

There is a strong interest in the development of microsomal prostaglandin E2 synthase-1 (mPGES-1) inhibitors of their potential to safely and effectively treat inflammation. Herein, 70 QSAR models were built on the dataset (735 mPGES-1 inhibitors) characterized with RDKit descriptors by multiple linear regression (MLR), support vector machine (SVM), random forest (RF), deep neural networks (DNN), and eXtreme Gradient Boosting (XGBoost). The other three regression models on the dataset are represented by SMILES using self-attention recurrent neural networks (RNN) and Graph Convolutional Networks (GCN). For the best model (Model C2), which was developed by SVM with RDKit descriptors, the coefficient of determination (R2 ) of 0.861 and root mean squared error (RMSE) of 0.235 were achieved for the test set. Additionally, R2 of 0.692 and RMSE of 0.383 were obtained on the external test set. We investigated the applicability domain (AD) of Model C2 with the rivality index (RI), the prediction of Model C2 on 78.92% of molecules in the test set, and 78.33% of molecules in the external test set were reliable. After dissecting the RDKit descriptors of Model C2, we found important physicochemical properties of highly active mPGES-1 inhibitors. Besides, by analyzing the attention weight of each atom of each inhibitor from the attention layer, we found that the benzamide group and the trifluoromethyl cyclohexane group are favorable substructures for mPGES-1 inhibitors.

Construction of a chiral zinc-camphorate framework for enantioselective separation.

A chiral metal-organic framework (CMOF) with open chiral channels and multiple recognition sites is constructed from camphoric acid and a dipyridyl ligand. It can act as an efficient chiral solid adsorbent, capable of separating a variety of racemic alcohols and epoxides with excellent enantioselectivities.

Enantioseparation in Hierarchically Porous Assemblies of Homochiral Cages.

Efficient enantioselective separation using porous materials requires tailored and diverse pore environments to interact with chiral substrates; yet, current cage materials usually feature uniform pores. Herein, we report two porous assemblies, PCC-60 and PCC-67, using isostructural octahedral cages with intrinsic microporous cavities of 1.5 nm. The PCC-67 adopts a densely packed mode, while the PCC-60 is a hierarchically porous assembly featuring interconnected 2.4 nm mesopores. Compared with PCC-67, the PCC-60 demonstrates excellent enantioselectivity and recyclability in separating racemic diols and amides. This solid adsorbent PCC-60 is further utilized as a chiral stationary phase for high-performance liquid chromatography (HPLC), enabling the complete separation of six valuable pharmaceutical intermediates. According to quantitative dynamic experiments, the hierarchical pores facilitate the mass transfer within the superstructure, shortening the equilibrium time for adsorbing chiral substrates. Notably, this hierarchically porous material PCC-60 indicates remarkably higher enantiomeric excess (ee) values in separating racemates than PCC-67 with uniform microporous cavities. Control experiments confirm that the presence of mesopores enables the PCC-60 to separate bulky substrates. These results uncover the traditionally underestimated role of hierarchical porosity in porous-superstructure-based enantioseparation.

Solar-driven aromatic aldehydes: green production from mandelic acid derivatives by a Co(ii)/C3N4 combined catalyst in aqueous media.

According to the requirements for sustainable development, reclaiming fine chemicals from wastewater under mild conditions is an extremely significant line of research. A low-cost and high-efficiency polydentate chelate- and polymeric Co(ii)-based complex (Co-L)-loaded C3N4 photocatalyst (Co-L/C3N4) was constructed and used to convert aromatic mandelic acids in wastewater at room temperature. The BET specific surface area increased from 28 m2 g-1 to 68 m2 g-1, indicating its excellent absorptive character. The light absorption range of Co-L/C3N4 reached 650 nm, while the band energy reduced to 2.30 eV, which caused a significant enhancement in photocatalytic activity. The conversion of substituted mandelic acids was more than 90% due to the photoactivity of Co-L/C3N4. Time-resolved PL spectra indicated the remarkable separation of the photogenerated electron-hole pairs in Co-L/C3N4. Furthermore, the UV-vis and in situ FTIR spectra indicated the formation of aldehyde groups in the selective oxidation process, which provided support for the plausible catalytic mechanism.

Building 2D classification models and 3D CoMSIA models on small-molecule inhibitors of both wild-type and T790M/L858R double-mutant EGFR.

Epidermal growth factor receptor (EGFR) has received widespread attention because it is an important target for anticancer drug design. Mutations in the EGFR, especially the T790M/L858R double mutation, have made cancer treatment more difficult. We herein built the structure-activity relationship models of small-molecule inhibitors on wild-type and T790M/L858R double-mutant EGFR with a whole dataset of 379 compounds. For 2D classification models, we used ECFP4 fingerprints to build support vector machine and random forest models and used SMILES to build self-attention recurrent neural network models. Each of all six models resulted in an accuracy of above 0.87 and the Matthews correlation coefficient value of above 0.76 on the test set, respectively. We concluded that inhibitors containing anilinoquinoline and methoxy or fluoro phenyl are highly active against wild EGFR. Substructures such as anilinopyrimidine, acrylamide, amino phenyl, methoxy phenyl, and thienopyrimidinyl amide appeared more in highly active inhibitors against double-mutant EGFR. We also used self-organizing map to cluster the inhibitors into six subsets based on ECFP4 fingerprints and analyzed the activity characteristics of different scaffolds in each subset. Among them, three datasets, which are based on pteridin, anilinopyrimidine, and anilinoquinoline scaffold, were selected to build 3D comparative molecular similarity analysis models individually. Models with the leave-one-out coefficient of determination (q2) above 0.65 were selected, and five descriptor types (steric, electrostatic, hydrophobic, donor, and acceptor) were used to study the effects of side chains of inhibitors on the activity against wild-type and mutant-type EGFR.

Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithms.

Cysteinyl leukotrienes 1 (CysLT1) receptor is a promising drug target for rhinitis or other allergic diseases. In our study, we built classification models to predict bioactivities of CysLT1 receptor antagonists. We built a dataset with 503 CysLT1 receptor antagonists which were divided into two groups: highly active molecules (IC50 < 1000 nM) and weakly active molecules (IC50 ≥ 1000 nM). The molecules were characterized by several descriptors including CORINA descriptors, MACCS fingerprints, Morgan fingerprint and molecular SMILES. For CORINA descriptors and two types of fingerprints, we used the random forests (RF) and deep neural networks (DNN) to build models. For molecular SMILES, we used recurrent neural networks (RNN) with the self-attention to build models. The accuracies of test sets for all models reached 85%, and the accuracy of the best model (Model 2C) was 93%. In addition, we made structure-activity relationship (SAR) analyses on CysLT1 receptor antagonists, which were based on the output from the random forest models and RNN model. It was found that highly active antagonists usually contained the common substructures such as tetrazoles, indoles and quinolines. These substructures may improve the bioactivity of the CysLT1 receptor antagonists.

Effect and Mechanism of Aluminum(III) for Guaiacol-Glyoxylic Acid Condensation Reaction in Vanillin Production.

3-methoxy-4-hydroxymandelic acid (VMA) was the critical intermediate for the synthesis of vanillin by the glyoxylic acid method. Meanwhile, a valuable byproduct (2-hydroxy-3-methoxy-mandelic acid, o-VMA) was obtained during the reaction. Al3+ was found to be a helpful catalyst in increasing the selectivity for VMA and o-VMA. In the presence of Al3+, the selectivity for VMA and o-VMA increased from 83 to 88% and from 3 to 8%, respectively, while that of the helpless byproduct 2-hydroxy-3-methoxy-1,5-mandelic acid (di-VMA) decreased from 14% to less than 4%. The kinetics based on the kinetic equation of the condensation reaction was studied by the initial concentration method. The results indicated that the involvement of Al3+ could reduce the activation energy of the reaction on the basis of the Arrhenius equation. Combined with thermogravimetric analysis, in situ Fourier transform-infrared spectroscopy, and 1H NMR research, Al3+ was found to interact with guaiacol through Al-O and Al···H, which further improved the selectivity of the VMA and o-VMA and reduced the selectivity of di-VMA by adding the electronegativity of the ortho- and para-positions of hydroxyl groups of guaiacol.

One-Pot Efficient Catalytic Oxidation for Bio-Vanillin Preparation and Carbon Isotope Analysis.

Vanillin (4-hydroxy-3-methoxybenzaldehyde) is one of the most widely used food spices. Aimed at bio-vanillin green production, the natural materials were directly catalytically oxidized efficiently in one pot under low O2 pressure (0.035 MPa) in the presence of a non-noble metal oxidation combined catalyst (NiCo2O4/SiO2 nanoparticles), which showed remarkable advantages of a short synthetic route and less industrial waste. The catalytic system showed good universality to many natural substrates with nearly 100% conversion and 86.3% bio-vanillin yield. More importantly, carbon isotope ratio investigations were employed to verify the origin of the organic matter. One hundred percent 14C content of the obtained vanillin was detected, which indicated that it was an efficient method to distinguish the vanillin from biomass or fossil materials. Furthermore, the 13C isotope examination showed effective distinguishing ability for the vanillin from a particular biomass source. The C isotope detection provides an effective method for commercial vanillin identification.

Reliability of lower leg proximal end and forefoot kinematics during different paces of barefoot racewalking on a treadmill using a motion recorder (MVP-RF8-BC).

[Purpose] This study was performed to investigate the changes in lower leg proximal end and forefoot kinematics, and reliability of measurement during different paces of barefoot racewalking on treadmill. [Subjects] Eleven junior racewalking men participated in this study. [Methods] To identify changes in lower leg proximal end and forefoot kinematics, during different paces of barefoot racewalking on a treadmill, a wireless motion recorder (MVP-RF8-BC) was used. Interclass correlation coefficients (ICC 1, 2) were used to estimate reliability. [Results] There were significant differences in the lower leg proximal end and forefoot maximum medial/lateral rotations at a pace of 9 km/h compared with those at a pace of 5 km/h pace. The intra-examiner reliability estimates ranged from 0.82 and 0.89 to 0.87 and 0.93 for lower leg proximal end inversion/eversion rotation and medial/lateral rotation, and from 0.92 and 0.84 to 0.93 and 0.91 for forefoot inversion/eversion rotation and medial/lateral rotation. [Conclusion] We conclude that the lower leg proximal end and forefoot kinematics of barefoot racewalking on a treadmill are influenced by different paces and that assessment of lower leg proximal end and forefoot kinematics by means of the wireless motion recorder (MVP-RF8-BC) is adequately reliable. This information may be useful for determining exercise prescriptions.

Kinematics of the forefoot in the horizontal plane during progressive pace barefoot racewalking on a treadmill after aerobic exercise load.

[Purpose] The aim of this study was to measure the changes in forefoot maximum medial/lateral rotation in the horizontal plane during progressive pace barefoot racewalking on a treadmill after a physically demanding aerobic exercise load (a fatigue protocol). [Subjects] Eleven junior racewalking men participated in this study. [Methods] To identify changes in forefoot maximum medial/lateral rotation in the horizontal plane after physically demanding aerobic exercise load, an 8 ch wireless Motion Recorder (MVP-RF8-BC) was utilized. [Results] Forefoot maximum medial/lateral rotation in the horizontal plane was significantly associated with increased paces during progressive pace treadmill racewalking. Significant increases in forefoot maximum medial/lateral rotation were observed during progressive pace barefoot racewalking on the instrumented treadmill at 8 km/h and 10 km/h after a physically demanding aerobic exercise load. [Conclusion] The findings of this study indicated that forefoot maximum medial/lateral rotation increased during progressive pace barefoot racewalking in the fatigue state after a physically demanding aerobic exercise load, which implies that the kinematic features of the forefoot are changed in the fatigue state.

Effect of progressive resistance exercise with neuromuscular joint facilitation on the dynamic balance performance of junior soccer players.

[Purpose] The aim of this study was to investigate the change in dynamic balance performance of junior soccer players after progressive resistance treatment with neuromuscular joint facilitation (NJF). [Subjects] The subjects were 14 healthy males who were divided into two groups, namely the NJF and control groups. The NJF group consisted of 8 subjects, and the control group consisted of 6 subjects. [Methods] The participants in the NJF group received NJF progressive resistance treatment. Dynamic balance performance was measured before and after 3 weeks of exercise. [Results] Significant improvement in dynamic balance performance was observed both in the NJF and control groups. In the NJF group, dynamic balance performance was significantly increased compared with that in the control group. [Conclusion] The NJF intervention shortened movement time, which implies that NJF is effective for dynamic balance performance.

Effects on ROM and joint position sense of the neck of two different interventions.

[Purpose] The purpose of this study was to evaluate whether neuromuscular joint facilitation (NJF) training is superior to NJF distal resistance training at improving the ROM and proprioceptive acuity of the neck. [Subjects] 10 healthy subjects (8 males, 2 females) participated in this study. [Methods] The participants were allocated to three groups: 10 in the control group, 10 in the NJF distal resistance training group, and 10 in the NJF training group. A miniature wireless motion recorder was used to record the maximum cervical range of motion and joint position error (JPE) before and after the interventions. The three interventions were tested on different days. [Results] No difference of ROM was observed among the three groups. A significant pre- to post-intervention decrease in JPE in extension was identified in the NJF group. No other significant differences were observed among the three groups. [Conclusion] The NJF training conferred remarkable benefits on the cervical JPE of healthy people. This result suggests that the best way to improve proprioceptive acuity is intervention together with proximal resistance training, such as NJF training.

The Immediate Effect of Neuromuscular Joint Facilitation (NJF) Treatment on Electromechanical Reaction Times of Hip Flexion.

[Purpose] The aim of this study was to investigate the change in electromechanical reaction times (EMG-RT) of hip flexion of younger persons after neuromuscular joint facilitation (NJF) treatment. [Subjects] The subjects were 39 healthy young people, who were divided into two groups: a NJF group and a proprioceptive neuromuscular facilitation (PNF) group. The NJF group consisted of 16 subjects (7 males, 9 females), and the PNF group consisted of 23 subjects (10 males, 13 females). [Methods] Participants in the NJF group received NJF treatment. We measured the EMG-RT, the premotor time (PMT) and the motor time (MT) during hip flexion movement before and after the intervention in both groups. [Results] There were no significant differences among the results of the PNF group. For the NJF group, there were significant differences in PMT and EMG-RT after NJF treatment. [Conclusion] These results suggest that there is an immediate effect of NJF intervention on electromechanical reaction times of hip flexion.