Exploring the Light-Emitting Agents in Renilla Luciferases by an Effective QM/MM Approach.

Bioluminescence is a fascinating natural phenomenon, wherein organisms produce light through specific biochemical reactions. Among these organisms, Renilla luciferase (RLuc) derived from the sea pansy Renilla reniformis is notable for its blue light emission and has potential applications in bioluminescent tagging. Our study focuses on RLuc8, a variant of RLuc with eight amino acid substitutions. Recent studies have shown that the luminescent emitter coelenteramide can adopt multiple protonation states, which may be influenced by nearby residues at the enzyme's active site, demonstrating a complex interplay between protein structure and bioluminescence. Herein, using the quantum mechanical consistent force field method and the semimacroscopic protein dipole-Langevin dipole method with linear response approximation, we show that the phenolate state of coelenteramide in RLuc8 is the primary light-emitting species in agreement with experimental results. Our calculations also suggest that the proton transfer (PT) from neutral coelenteramide to Asp162 plays a crucial role in the bioluminescence process. Additionally, we reproduced the observed emission maximum for the amide anion in RLuc8-D120A and the pyrazine anion in the presence of a Na+ counterion in RLuc8-D162A, suggesting that these are the primary emitters. Furthermore, our calculations on the neutral emitter in the engineered AncFT-D160A enzyme, structurally akin to RLuc8-D162A but with a considerably blue-shifted emission peak, aligned with the observed data, possibly explaining the variance in emission peaks. Overall, this study demonstrates an effective approach to investigate chromophores' bimolecular states while incorporating the PT process in emission spectra calculations, contributing valuable insights for future studies of PT in photoproteins.

Electrochemical E-Selective Semireductive Dicarboxylation of Aryl Alkynes with CO2.

Herein, we report an electrochemical protocol for the dicarboxylation of aryl alkynes using CO2. With a graphite rod as the cathode and Al as the sacrificial anode, a series of valuable butenedioic acids are obtained in moderate to excellent yields with an E/Z ratio up to 50:1. This method features high E-selectivity, high step and atom economy, easy scalability, and a nice substrate scope, which renders it appealing for promising applications in organic synthesis and materials chemistry.

Molecular basis of Gabija anti-phage supramolecular assemblies.

As one of the most prevalent anti-phage defense systems in prokaryotes, Gabija consists of a Gabija protein A (GajA) and a Gabija protein B (GajB). The assembly and function of the Gabija system remain unclear. Here we present cryo-EM structures of Bacillus cereus GajA and GajAB complex, revealing tetrameric and octameric assemblies, respectively. In the center of the complex, GajA assembles into a tetramer, which recruits two sets of GajB dimer at opposite sides of the complex, resulting in a 4:4 GajAB supramolecular complex for anti-phage defense. Further biochemical analysis showed that GajA alone is sufficient to cut double-stranded DNA and plasmid DNA, which can be inhibited by ATP. Unexpectedly, the GajAB displays enhanced activity for plasmid DNA, suggesting a role of substrate selection by GajB. Together, our study defines a framework for understanding anti-phage immune defense by the GajAB complex.

Mononuclear Iron Pyridinethiolate Complex Promoted CO2 Photoreduction via Rapid Intramolecular Electron Transfer.

Designing earth-abundant metal complexes as efficient molecular photocatalysts for visible light-driven CO2 reduction is a key challenge in artificial photosynthesis. Here, we demonstrated the first example of a mononuclear iron pyridine-thiolate complex that functions both as a photosensitizer and catalyst for CO2 reduction. This single-component bifunctional molecular photocatalyst efficiently reduced CO2 to formate and CO with a total turnover number (TON) of 46 and turnover frequency (TOF) of 11.5 h-1 in 4 h under visible light irradiation. Notably, the quantum yield was determined to be 8.4 % for the generation of formate and CO at 400 nm. Quenching experiments indicate that high photocatalytic activity is mainly attributed to the rapid intramolecular quenching protocol. The mechanism investigation by DFT calculation and electrochemical studies revealed that the protonation of Febpy(pyS)2 is indispensable step for photocatalytic CO2 reduction.

Molecular Engineering of Copper Phthalocyanine for CO2 Electroreduction to Methane.

Efficient electrochemical CO2 reduction reaction (ECO2RR) to multi-electron reductive products remains a great challenge. Herein, molecular engineering of copper phthalocyanines (CuPc) was explored by modifying electron-withdrawing groups (EWGs) (cyano, sulfonate anion) and electron-donating groups (EDGs) (methoxy, amino) to CuPc, then supporting onto carbon paper or carbon cloth by means of droplet coating, loading with carbon nanotubes and coating in polypyrrole (PPy). The results showed that the PPy-coated CuPc effectively catalysed ECO2RR to CH4. Interestingly, experimental results and DFT calculations indicated EWGs markedly improved the selectivity of methane for the reason that the introduction of EWGs reduces electron density of catalytic active center, resulting in a positive move to initial reduction potential. Otherwise, the modification of EDGs significantly reduces the selectivity towards methane. This electronic effect and heterogenization of CuPc are facile and effective molecular engineering, benefitting the preparation of electrocatalysts for further reduction of CO2.

[The role of mitochondria-associated endoplasmic reticulum membranes in age-related cardiovascular diseases].

Mitochondria-associated endoplasmic reticulum membranes (MAMs) are the physical connection sites between mitochondria and endoplasmic reticulum (ER). As the compartments controlling substance and information communications between ER and mitochondria, MAMs were involved in the regulation of various pathophysiological processes, such as calcium homeostasis, mitochondrial morphology and function, lipid metabolism and autophagy. In the past decades, accumulating lines of evidence have revealed the pivotal role of MAMs in diverse cardiovascular diseases (CVD). Aging is one of the major independent risk factors for CVD, which causes progressive degeneration of the cardiovascular system, leading to increased morbidity and mortality of CVD. This review aims to summarize the research progress of MAMs in age-related CVD, and explore new targets for its prevention and treatment.

Enhancing luciferase activity and stability through generative modeling of natural enzyme sequences.

The availability of natural protein sequences synergized with generative AI provides new paradigms to engineer enzymes. Although active enzyme variants with numerous mutations have been designed using generative models, their performance often falls short of their wild type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze Renilla luciferase (RLuc) homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate to improve either luciferase activity or stability of designed single mutants is ~50%. This finding highlights nature's ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in RLuc toward emitting blue light that holds advantages in terms of water penetration compared to other light spectra. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.

Harnessing Generative AI to Decode Enzyme Catalysis and Evolution for Enhanced Engineering.

Enzymes, as paramount protein catalysts, occupy a central role in fostering remarkable progress across numerous fields. However, the intricacy of sequence-function relationships continues to obscure our grasp of enzyme behaviors and curtails our capabilities in rational enzyme engineering. Generative artificial intelligence (AI), known for its proficiency in handling intricate data distributions, holds the potential to offer novel perspectives in enzyme research. By applying generative models, we could discern elusive patterns within the vast sequence space and uncover new functional enzyme sequences. This review highlights the recent advancements in employing generative AI for enzyme sequence analysis. We delve into the impact of generative AI in predicting mutation effects on enzyme fitness, activity, and stability, rationalizing the laboratory evolution of de novo enzymes, decoding protein sequence semantics, and its applications in enzyme engineering. Notably, the prediction of enzyme activity and stability using natural enzyme sequences serves as a vital link, indicating how enzyme catalysis shapes enzyme evolution. Overall, we foresee that the integration of generative AI into enzyme studies will remarkably enhance our knowledge of enzymes and expedite the creation of superior biocatalysts.

Enhancing Luciferase Activity and Stability through Generative Modeling of Natural Enzyme Sequences.

The availability of natural protein sequences synergized with generative artificial intelligence (AI) provides new paradigms to create enzymes. Although active enzyme variants with numerous mutations have been produced using generative models, their performance often falls short compared to their wild-type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze Renilla luciferase homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate of designed single mutants is ~50% to improve either luciferase activity or stability. These finding highlights nature's ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in Renilla luciferase towards emitting blue light that holds advantages in terms of water penetration compared to other light spectrum. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.

Relationships among body weight, lipids and bone mass in elderly individuals with fractures: A case-control study.

BACKGROUND: The prevalence of osteoporosis and low bone mass is steadily rising each year. Low body weight is commonly linked to diminished bone mass and serves as a robust predictor of osteoporosis. Nonetheless, the connection between body mass index (BMI), bone mineral density, and lipid profiles among the elderly remains elusive. AIM: To examine the association between BMI and bone mass, explore the correlation between lipid profiles and bone mass, and delve into the interplay between lipid metabolism and bone health. METHODS: The study included 520 patients aged ≥ 65 years (178 men and 342 women). Age, sex, weight, and height were recorded. Femoral neck bone mineral density and T scores were determined using a dual-energy X-ray absorptiometry scanner. Blood calcium (Ca), phosphorus (P), albumin (ALB), alkaline phosphatase (ALP), aspartate aminotransferase, alanine aminotransferase, triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL) and low-density lipoprotein (LDL) levels were measured. Patients were classified by sex (male and female), age (65-79 years and ≥ 80 years), and T score (normal bone mineral density, osteopenia and osteoporosis). RESULTS: Age, sex, BMI, and ALP and TG levels were independent risk factors for osteoporosis. For the 65-79- and ≥ 80-year-old groups, females presented lower T scores than males. Ca, P, ALB, ALP, TC, HDL and LDL levels were significantly different between men and women in the 65-79-year-old group. In addition, BMI and TG levels were significantly decreased in osteoporotic patients compared with patients with normal bone mass. TC levels declined in 65- to 79-year-old male and female osteoporosis patients. In the group of women aged ≥ 80 years, osteoporotic patients showed significantly increased ALP levels. Furthermore, we found positive correlations between BMI and TG levels in the male and female patient groups. However, we found no significant differences in ALB, Ca, P, HDL and LDL levels in osteoporotic patients compared to patients with normal bone mass. CONCLUSION: Osteoporotic patients showed significantly decreased BMI and TG levels compared with those with normal bone mass. BMI showed positive correlations with TG levels in male and female patients. These results indicate correlations between BMI and bone mass and between lipid profiles and bone mass.

[Comparison of curative effect between percutaneous compression plate and cannulated compression screw in the treatment of displaced femoral neck fractures in young and middle-aged patients].

OBJECTIVE: To compare the efficacy of percutaneous compression plate and cannulated compression screw in the treatment of displaced femoral neck fractures in young and middle-aged patients. METHODS: From January 2015 to July 2020, 68 young and middle-aged patients with displaced femoral neck fracture were retrospectively analyzed. Among them, 31 cases were fixed by percutaneous compression plate (PCCP), and 37 cases were fixed by cannulated compression screw (CCS). General data such as gender, age, cause of injury, comorbidities, fracture classification and cause of injury of two groups were collected. The operation time, intraoperative blood loss, hospital stay, full weight bearing time, fracture healing time, visual analogue scale(VAS), Harris hip score and complications were compared between two groups. RESULTS: Patients in both groups were followed up for more than 2 years. There were no significant differences in operation time, intraoperative blood loss, fracture reduction quality, hospital stay and VAS between two groups. The fracture healing time in PCCP group was significantly shorter than that in CCS group (t=-4.404, P=0.000). The complete weight bearing time of PCCP group was significantly shorter than that of CCS group (t=-9.011, P=0.000). Harris score of hip joint in PCCP group was better than that in CCS group 2 years after operation (P=0.002). Complications occurred in 3 cases (9.68%) in PCCP group, while 11 cases (29.72%) in CCS group, with a statistically significant difference (P=0.042). CONCLUSION: Both PCCP and CCS can be used for the treatment of displaced femoral neck fractures in young and middle-aged people. Compared with CCS, PCCP fixation can achieve shorter fracture healing time and create conditions for early full weight bearing. PCCP results in higher hip score and lower complications.

Harnessing generative AI to decode enzyme catalysis and evolution for enhanced engineering.

Enzymes, as paramount protein catalysts, occupy a central role in fostering remarkable progress across numerous fields. However, the intricacy of sequence-function relationships continues to obscure our grasp of enzyme behaviors and curtails our capabilities in rational enzyme engineering. Generative artificial intelligence (AI), known for its proficiency in handling intricate data distributions, holds the potential to offer novel perspectives in enzyme research. Generative models could discern elusive patterns within the vast sequence space and uncover new functional enzyme sequences. This review highlights the recent advancements in employing generative AI for enzyme sequence analysis. We delve into the impact of generative AI in predicting mutation effects on enzyme fitness, catalytic activity and stability, rationalizing the laboratory evolution of de novo enzymes, and decoding protein sequence semantics and their application in enzyme engineering. Notably, the prediction of catalytic activity and stability of enzymes using natural protein sequences serves as a vital link, indicating how enzyme catalysis shapes enzyme evolution. Overall, we foresee that the integration of generative AI into enzyme studies will remarkably enhance our knowledge of enzymes and expedite the creation of superior biocatalysts.

Thyroidectomy using a single-port cervico-mental angle approach.

Background: Over the last two decades, several endoscopic thyroidectomy methods have been developed. However, there are some limitations in these procedures. To date, the optimal surgical approach for thyroid cancer has not yet been developed. This study reported the surgical operation steps, clinical outcomes, and experience of 30 patients who underwent trans-cervico-mental angle single-port endoscopic thyroidectomy (TCMASPET) at our centre. Patients and Methods: A total of 30 patients were enrolled in the present study. Patients underwent unilateral or bilateral thyroidectomy through a cervico-mental angle incision of 2.48 ± 0.31 cm, after which the lymphoid adipose tissues in the central region were dissected. Results: All surgeries were successfully completed. Two patients underwent bilateral thyroid carcinoma resection with bilateral central region lymph node dissection, 23 patients received unilateral thyroid cancer resection with unilateral central region lymph node dissection, four patients underwent unilateral thyroid resection, and one patient received bilateral thyroid resection with unilateral central region lymph node dissection. No permanent post-operative complications were observed. Conclusions: TCMASPET was a safe and feasible approach that was relatively easy to perform. This approach may expand the indications for endoscopic thyroidectomy while maintaining excellent cosmetic outcomes.

Cobalt Phthalocyanine Cross-Linked Polypyrrole for Efficient Electroreduction of Low Concentration CO2 To CO.

Immobilizing cobalt phthalocyanine (CoPc) onto the electrode surface is a significant approach to performing efficient electrochemical CO2 reduction reaction (ECO2 RR). Herein, sulfylphenoxy decorated CoPc cross-linked polypyrrole is prepared by in situ polymerization on the surface of carbon cloth. The synthesized N-rich catalyst exhibits above 95 % Faradaic efficiency toward CO (FECO ) at -0.9 V versus reversible hydrogen electrode (RHE) at least for 10 h in aqueous solution and even enables direct electrolysis at low CO2 concentrations, being potential for coupling ECO2 RR with CO2 capture. This facile in situ polymerization strategy would pave the way for developing efficient and practical electrocatalysis for ECO2 RR.

Exploring the Role of Chemical Reactions in the Selectivity of Tyrosine Kinase Inhibitors.

A variety of diseases are associated with tyrosine kinase enzymes that activate many proteins via signal transduction cascades. The similar ATP-binding pockets of these tyrosine kinases make it extremely difficult to design selective covalent inhibitors. The present study explores the contribution of the chemical reaction steps to the selectivity of the commercialized inhibitor acalabrutinib over the Bruton's tyrosine kinase (BTK) and the interleukin-2-inducible T-cell kinase (ITK). Ab initio and empirical valence bond (EVB) simulations of the two kinases indicate that the most favorable reaction path involves a water-assisted mechanism of the 2-butynamide reactive group of acalabrutinib. BTK reacts with acalabrutinib with a substantially lower barrier than ITK, according to our calculated free-energy profile and kinetic simulations. Such a difference is due to the microenvironment of the active site, as further supported by a sequence-based analysis of specificity determinants for several commercialized inhibitors. Our study involves a new approach of simulating directly the IC50 and inactivation efficiency keff, instead of using the standard formulas. This new strategy is particularly important in studies of covalent inhibitors with a very exothermic bonding step. Overall, our results demonstrate the importance of understanding the chemical reaction steps in designing selective covalent inhibitors for tyrosine kinases.

Molecular Engineering of Metal Complexes for Electrocatalytic Carbon Dioxide Reduction: From Adjustment of Intrinsic Activity to Molecular Immobilization.

The electrocatalytic CO2 reduction reaction (ECO2 RR) is one promising method for storing intermittent clean energy in chemical bonds and producing fuels. Among various kinds of catalysts for ECO2 RR, molecular metal complexes with well-defined structures are convenient for studies of their rational design, structure-reactivity relationships, and mechanisms. In this Review, we summarize the molecular engineering of several N-based metal complexes including Re/Mn bipyridine compounds and metal macrocycles, concluding with general modification strategies to devise novel molecular catalysts with high intrinsic activity. Through physical adsorption, covalent linking, and formation of a periodic backbone, these active molecules can be heterogenized into immobilized catalysts with more practical prospects. Finally, significant challenges and opportunities based on molecular catalysts are discussed.

Natural Evolution Provides Strong Hints about Laboratory Evolution of Designer Enzymes.

Laboratory evolution combined with computational enzyme design provides the opportunity to generate novel biocatalysts. Nevertheless, it has been challenging to understand how laboratory evolution optimizes designer enzymes by introducing seemingly random mutations. A typical enzyme optimized with laboratory evolution is the abiological Kemp eliminase, initially designed by grafting active site residues into a natural protein scaffold. Here, we relate the catalytic power of laboratory-evolved Kemp eliminases to the statistical energy ([Formula: see text]) inferred from their natural homologous sequences using the maximum entropy model. The [Formula: see text] of designs generated by directed evolution is correlated with enhanced activity and reduced stability, thus displaying a stability-activity trade-off. In contrast, the [Formula: see text] for mutants in catalytic-active remote regions (in which remote residues are important for catalysis) is strongly anticorrelated with the activity. These findings provide an insight into the role of protein scaffolds in the adaption to new enzymatic functions. It also indicates that the valley in the [Formula: see text] landscape can guide enzyme design for abiological catalysis. Overall, the connection between laboratory and natural evolution contributes to understanding what is optimized in the laboratory and how new enzymatic function emerges in nature, and provides guidance for computational enzyme design.

pH regulates potassium conductance and drives a constitutive proton current in human TMEM175.

Human TMEM175, a noncanonical potassium (K+) channel in endolysosomes, contributes to their pH stability and is implicated in the pathogenesis of Parkinson's disease (PD). Structurally, the TMEM175 family exhibits an architecture distinct from canonical potassium channels, as it lacks the typical TVGYG selectivity filter. Here, we show that human TMEM175 not only exhibits pH-dependent structural changes that reduce K+ permeation at acidic pH but also displays proton permeation. TMEM175 constitutively conducts K+ at pH 7.4 but displays reduced K+ permeation at lower pH. In contrast, proton current through TMEM175 increases with decreasing pH because of the increased proton gradient. Molecular dynamics simulation, structure-based mutagenesis, and electrophysiological analysis suggest that K+ ions and protons share the same permeation pathway. The M393T variant of human TMEM175 associated with PD shows reduced function in both K+ and proton permeation. Together, our structural and electrophysiological analysis reveals a mechanism of TMEM175 regulation by pH.

Enhancing computational enzyme design by a maximum entropy strategy.

Although computational enzyme design is of great importance, the advances utilizing physics-based approaches have been slow, and further progress is urgently needed. One promising direction is using machine learning, but such strategies have not been established as effective tools for predicting the catalytic power of enzymes. Here, we show that the statistical energy inferred from homologous sequences with the maximum entropy (MaxEnt) principle significantly correlates with enzyme catalysis and stability at the active site region and the more distant region, respectively. This finding decodes enzyme architecture and offers a connection between enzyme evolution and the physical chemistry of enzyme catalysis, and it deepens our understanding of the stability-activity trade-off hypothesis for enzymes. Overall, the strong correlations found here provide a powerful way of guiding enzyme design.

Electrostatic influence on IL-1 transport through the GSDMD pore.

A variety of signals, including inflammasome activation, trigger the formation of large transmembrane pores by gasdermin D (GSDMD). There are primarily two functions of the GSDMD pore, to drive lytic cell death, known as pyroptosis, and to permit the release of leaderless interleukin-1 (IL-1) family cytokines, a process that does not require pyroptosis. We are interested in the mechanism by which the GSDMD pore channels IL-1 release from living cells. Recent studies revealed that electrostatic interaction, in addition to cargo size, plays a critical role in GSDMD-dependent protein release. Here, we determined computationally that to enable electrostatic filtering against pro-IL-1ß, acidic lipids in the membrane need to effectively neutralize positive charges in the membrane-facing patches of the GSDMD pore. In addition, we predicted that salt has an attenuating effect on electrostatic filtering and then validated this prediction using a liposome leakage assay. A calibrated electrostatic screening factor is necessary to account for the experimental observations, suggesting that ion distribution within the pore may be different from the bulk solution. Our findings corroborate the electrostatic influence of IL-1 transport exerted by the GSDMD pore and reveal extrinsic factors, including lipid and salt, that affect the electrostatic environment.