Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors.

The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (Mpro). The ligand-binding pathway sampling method based on parallel cascade selection molecular dynamics (LB-PaCS-MD) simulations was employed to elucidate plausible paths and conformations of ebselen, a synthetic organoselenium drug, within the Mpro catalytic site. Ebselen effectively engaged the active site, adopting proximity to H41 and interacting through the benzoisoselenazole ring in a π-π T-shaped arrangement, with an additional π-sulfur interaction with C145. In addition, the ligand-based drug design using the QSAR with GFA-MLR, RF, and ANN models were employed for biological activity prediction. The QSAR-ANN model showed robust statistical performance, with an r2training exceeding 0.98 and an RMSEtest of 0.21, indicating its suitability for predicting biological activities. Integration the ANN model with the LB-PaCS-MD insights enabled the rational design of novel compounds anchored in the ebselen core structure, identifying promising candidates with favorable predicted IC50 values. The designed compounds exhibited suitable drug-like characteristics and adopted an active conformation similar to ebselen, inhibiting Mpro function. These findings represent a synergistic approach merging ligand and structure-based drug design; with the potential to guide experimental synthesis and enzyme assay testing.

Identification of Promising Sulfonamide Chalcones as Inhibitors of SARS-CoV-2 3CLpro through Structure-Based Virtual Screening and Experimental Approaches.

3CLpro is a viable target for developing antiviral therapies against the coronavirus. With the urgent need to find new possible inhibitors, a structure-based virtual screening approach was developed. This study recognized 75 pharmacologically bioactive compounds from our in-house library of 1052 natural product-based compounds that satisfied drug-likeness criteria and exhibited good bioavailability and membrane permeability. Among these compounds, three promising sulfonamide chalcones were identified by combined theoretical and experimental approaches, with SWC423 being the most suitable representative compound due to its competitive inhibition and low cytotoxicity in Vero E6 cells (EC50 = 0.89 ± 0.32 µM; CC50 = 25.54 ± 1.38 µM; SI = 28.70). The binding and stability of SWC423 in the 3CLpro active site were investigated through all-atom molecular dynamics simulation and fragment molecular orbital calculation, indicating its potential as a 3CLpro inhibitor for further SARS-CoV-2 therapeutic research. These findings suggested that inhibiting 3CLpro with a sulfonamide chalcone such as SWC423 may pave the effective way for developing COVID-19 treatments.

Rational Design of a Low-Data Regime of Pyrrole Antioxidants for Radical Scavenging Activities Using Quantum Chemical Descriptors and QSAR with the GA-MLR and ANN Concepts.

A series of pyrrole derivatives and their antioxidant scavenging activities toward the superoxide anion (O2•-), hydroxyl radical (•OH), and 1,1-diphenyl-2-picryl-hydrazyl (DPPH•) served as the training data sets of a quantitative structure-activity relationship (QSAR) study. The steric and electronic descriptors obtained from quantum chemical calculations were related to the three O2•-, •OH, and DPPH• scavenging activities using the genetic algorithm combined with multiple linear regression (GA-MLR) and artificial neural networks (ANNs). The GA-MLR models resulted in good statistical values; the coefficient of determination (R2) of the training set was greater than 0.8, and the root mean square error (RMSE) of the test set was in the range of 0.3 to 0.6. The main molecular descriptors that play an important role in the three types of antioxidant activities are the bond length, HOMO energy, polarizability, and AlogP. In the QSAR-ANN models, a good R2 value above 0.9 was obtained, and the RMSE of the test set falls in a similar range to that of the GA-MLR models. Therefore, both the QSAR GA-MLR and QSAR-ANN models were used to predict the newly designed pyrrole derivatives, which were developed based on their starting reagents in the synthetic process.

Quantitative Structure-Electrochemistry Relationship (QSER) Studies on Metal-Amino-Porphyrins for the Rational Design of CO2 Reduction Catalysts.

The quantitative structure-electrochemistry relationship (QSER) method was applied to a series of transition-metal-coordinated porphyrins to relate their structural properties to their electrochemical CO2 reduction activity. Since the reactions mainly occur within the core of the metalloporphyrin catalysts, the cluster model was used to calculate their structural and electronic properties using density functional theory with the M06L exchange-correlation functional. Three dependent variables were employed in this work: the Gibbs free energies of H*, C*OOH, and O*CHO. QSER, with the genetic algorithm combined with multiple linear regression (GA-MLR), was used to manipulate the mathematical models of all three Gibbs free energies. The obtained statistical values resulted in a good predictive ability (R2 value) greater than 0.945. Based on our QSER models, both the electronic properties (charges of the metal and porphyrin) and the structural properties (bond lengths between the metal center and the nitrogen atoms of the porphyrin) play a significant role in the three Gibbs free energies. This finding was further applied to estimate the CO2 reduction activities of the metal-monoamino-porphyrins, which will prove beneficial in further experimental developments.

Multivariate Synthetic Strategy for Improving Crystallinity of Zwitterionic Squaraine-Linked Covalent Organic Frameworks with Enhanced Photothermal Performance.

Two-dimensional covalent organic frameworks (2D COFs) offer a designable platform to explore porous polyelectrolyte frameworks with periodic ionic skeletons and uniform pore channels. However, the crystallinity of ionized 2D COF is often far from satisfactory as the electrostatic assembly of structures impedes the ordered layered arrangement. Here, a multivariate synthetic strategy to synthesize a highly crystalline squaraine (SQ)-linked zwitterionic 2D COF is proved. A neutral aldehyde monomer copolymerizes with squaric acid (SA) and amines in a controlled manner, resulting in the ionized COF with linkage heterogeneity in one tetragonal framework. Thus, the zwitterions of SQ are spatially isolated to minimize the electrostatic interaction and maintain the highly ordered layered stacking. With the addition of 85%-90% SA (relative to a total of aldehydes and SA), a fully SQ-linked zwitterionic 2D COF is achieved by the in-situ conversion of imine to SQ linkages. Such a highly crystalline SQ-linked COF promotes absorptivity in a full spectrum and photothermal conversion performances, and in turn, it exhibits enhanced solar-to-vapor generation with an efficiency of as high as 92.19%. These results suggest that synthetically regulating charge distribution is desirable to constitute a family of new crystalline polyelectrolyte frameworks.

Computational Screening of Newly Designed Compounds against Coxsackievirus A16 and Enterovirus A71.

Outbreaks of hand, foot, and mouth disease (HFMD) that occur worldwide are mainly caused by the Coxsackievirus-A16 (CV-A16) and Enterovirus-A71 (EV-A71). Unfortunately, neither an anti-HFMD drug nor a vaccine is currently available. Rupintrivir in phase II clinical trial candidate for rhinovirus showed highly potent antiviral activities against enteroviruses as an inhibitor for 3C protease (3Cpro). In the present study, we focused on designing 50 novel rupintrivir analogs against CV-A16 and EV-A71 3Cpro using computational tools. From their predicted binding affinities, the five compounds with functional group modifications at P1', P2, P3, and P4 sites, namely P1'-1, P2-m3, P3-4, P4-5, and P4-19, could bind with both CV-A16 and EV-A71 3Cpro better than rupintrivir. Subsequently, these five analogs were studied by 500 ns molecular dynamics simulations. Among them, P2-m3, the derivative with meta-aminomethyl-benzyl group at the P2 site, showed the greatest potential to interact with the 3Cpro target by delivering the highest number of intermolecular hydrogen bonds and contact atoms. It formed the hydrogen bonds with L127 and K130 residues at the P2 site stronger than rupintrivir, supported by significantly lower MM/PB(GB)SA binding free energies. Elucidation of designed rupintrivir analogs in our study provides the basis for developing compounds that can be candidate compounds for further HFMD treatment.

Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease.

The emergence outbreak caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has received significant attention on the global risks. Due to itscrucial role in viral replication, the main protease 3CLpro is an important target for drug discovery and development to combat COVID-19. In this work, the structural and dynamic behaviors as well as binding efficiency of the four peptidomimetic inhibitors (N3, 11a, 13b, and 14b) recently co-crystalized with SARS-CoV-2 3CLpro were studied and compared using all-atom molecular dynamics (MD) simulations and solvated interaction energy-based binding free energy calculations. The per-residue decomposition free energy results suggested that the key residues involved in inhibitors binding were H41, M49, L141-C145, H163-E166, P168, and Q189-T190 in the domains I and II. The van der Waals interaction yielded the main energy contribution stabilizing all the focused inhibitors. Besides, their hydrogen bond formations with F140, G143, C145, H164, E166, and Q189 residues in the substrate-binding pocket were also essential for strengthening the molecular complexation. The predicted binding affinity of the four peptidomimetic inhibitors agreed with the reported experimental data, and the 13b showed the most efficient binding to SARS-CoV-2 3CLpro. From rational drug design strategies based on 13b, the polar moieties (e.g., benzamide) and the bulky N-terminal protecting groups (e.g., thiazole) should be introduced to P1' and P4 sites in order to enhance H-bonds and hydrophobic interactions, respectively. We hope that the obtained structural and energetic information could be beneficial for developing novel SARS-CoV-2 3CLpro inhibitors with higher inhibitory potency to combat COVID-19.

Alkali-Resistant NOx Reduction over SCR Catalysts via Boosting NH3 Adsorption Rates by In Situ Constructing the Sacrificed Sites.

Currently, improving the alkali resistance of vanadium-based catalysts still remains as an intractable issue for the selective catalytic reduction of NOx with NH3 (NH3-SCR). It is generally believed that the decrease in adsorbed NHx species deriving from the declined acidic sites is the chief culprit for the deactivation of alkali-poisoned catalysts. Herein, alkali-resistant NOx reduction over SCR catalysts via boosting NH3 adsorption rates was originally demonstrated by in situ constructing the sacrificed sites. It is interesting that the adsorbed NHx species largely decrease while the NH3 adsorption rate is well kept over the V2O5/CeO2 catalyst by in situ constructing the sacrificed sites. The SCR activity could be maintained after alkali poisoning because in situ constructed SO42- groups would prefer to be combined with K+ so that the specific V═O species can endow K-poisoned V2O5/CeO2 with high adsorption rate of NH3 and high reactivity of NHx species. This work provides a new viewpoint that NH3 adsorption rate plays more decisive roles in the performance of alkali-poisoned catalysts than the amount of NH3 adsorption and enlightens an alternative strategy to improve the alkali-resistance of catalysts, which is significant to both the academic and industrial fields.

Metal-porphyrin: a potential catalyst for direct decomposition of N(2)O by theoretical reaction mechanism investigation.

The adsorption of nitrous oxide (N2O) on metal-porphyrins (metal: Ti, Cr, Fe, Co, Ni, Cu, or Zn) has been theoretically investigated using density functional theory with the M06L functional to explore their use as potential catalysts for the direct decomposition of N2O. Among these metal-porphyrins, Ti-porphyrin is the most active for N2O adsorption in the triplet ground state with the strongest adsorption energy (-13.32 kcal/mol). Ti-porphyrin was then assessed for the direct decomposition of N2O. For the overall reaction mechanism of three N2O molecules on Ti-porphyrin, two plausible catalytic cycles are proposed. Cycle 1 involves the consecutive decomposition of the first two N2O molecules, while cycle 2 is the decomposition of the third N2O molecule. For cycle 1, the activation energies of the first and second N2O decompositions are computed to be 3.77 and 49.99 kcal/mol, respectively. The activation energy for the third N2O decomposition in cycle 2 is 47.79 kcal/mol, which is slightly lower than that of the second activation energy of the first cycle. O2 molecules are released in cycles 1 and 2 as the products of the reaction, which requires endothermic energies of 102.96 and 3.63 kcal/mol, respectively. Therefore, the O2 desorption is mainly released in catalytic cycle 2 of a TiO3-porphyrin intermediate catalyst. In conclusion, regarding the O2 desorption step for the direct decomposition of N2O, the findings would be very useful to guide the search for potential N2O decomposition catalysts in new directions.

Comparative Study of Machine Learning-Based QSAR Modeling of Anti-inflammatory Compounds from Durian Extraction.

Quantitative structure-activity relationship (QSAR) analysis, an in silico methodology, offers enhanced efficiency and cost effectiveness in investigating anti-inflammatory activity. In this study, a comprehensive comparative analysis employing four machine learning algorithms (random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and artificial neural networks (ANNs)) was conducted to elucidate the activities of naturally derived compounds from durian extraction. The analysis was grounded in the exploration of structural attributes encompassing steric and electrostatic properties. Notably, the nonlinear SVR model, utilizing five key features, exhibited superior performance compared to the other models. It demonstrated exceptional predictive accuracy for both the training and external test datasets, yielding R2 values of 0.907 and 0.812, respectively; in addition, their RMSE resulted in 0.123 and 0.097, respectively. The study outcomes underscore the significance of specific structural factors (denoted as shadow ratio, dipole z, methyl, ellipsoidal volume, and methoxy) in determining anti-inflammatory efficacy. Thus, the findings highlight the potential of molecular simulations and machine learning as alternative avenues for the rational design of novel anti-inflammatory agents.

Designing Potent α-Glucosidase Inhibitors: A Synthesis and QSAR Modeling Approach for Biscoumarin Derivatives.

Nineteen biscoumarins were synthesized, well-characterized, and evaluated against α-glucosidases in vitro. Of these, six compounds (10, 12, 16, and 17-19) were newly synthesized and not previously reported in the chemical literature. The majority of the synthesized derivatives demonstrated significant inhibitory activity. A quantitative structure-activity relationship (QSAR) model was developed, revealing a strong correlation between the anti-α-glucosidase activity and selected molecular descriptors. Based on this model, two new compounds (18 and 19) were designed, which exhibited the strongest inhibition with IC50 values of 0.62 and 1.21 µM, respectively, when compared to the positive control (acarbose) with an IC50 value of 93.63 µM. Enzyme kinetic studies of compounds 18 and 19 revealed their competitive inhibition with Ki values of 3.93 and 1.80 µM, respectively. Computational studies demonstrated that compound 18 could be inserted into the original binding site (OBS) of α-glucosidase MAL12 and form multiple hydrophobic interactions with nearby amino acids, with the bromo group playing an essential role in enhancing the binding strength and stability at the OBS of the enzyme based on the quantum mechanical calculations using the fragment molecular orbital method. These findings provide valuable insights into the design of potent α-glucosidase inhibitors, which may have potential therapeutic applications in the treatment of diabetes and related diseases.

Design of electron-donating group substituted 2-PAM analogs as antidotes for organophosphate insecticide poisoning.

The use of organophosphate (OPs) pesticides is widespread in agriculture and horticulture, but these chemicals can be lethal to humans, causing fatalities and deaths each year. The inhibition of acetylcholinesterase (AChE) by OPs leads to the overstimulation of cholinergic receptors, ultimately resulting in respiratory arrest, seizures, and death. Although 2-pralidoxime (2-PAM) is the FDA-approved drug for treating OP poisoning, there is difficulty in blood-brain barrier permeation. To address this issue, we designed and evaluated a series of 2-PAM analogs by substituting electron-donating groups on the para and/or ortho positions of the pyridinium core using in silico techniques. Our PCM-ONIOM2 (MP2/6-31G*:PM7//B3LYP/6-31G*:UFF) binding energy results demonstrated that 13 compounds exhibited higher binding energy than 2-PAM. The analog with phenyl and methyl groups substituted on the para and ortho positions, respectively, showed the most favorable binding characteristics, with aromatic residues in the active site (Y124, W286, F297, W338, and Y341) and the catalytic residue S203 covalently bonding with paraoxon. The results of DS-MD simulation revealed a highly favorable apical conformation of the potent analog, which has the potential to enhance reactivation of AChE. Importantly, newly designed compound demonstrated appropriate drug-likeness properties and blood-brain barrier penetration. These results provide a rational guide for developing new antidotes to treat organophosphate insecticide toxicity.

Prediction of the Glass Transition Temperature in Polyethylene Terephthalate/Polyethylene Vanillate (PET/PEV) Blends: A Molecular Dynamics Study.

Polyethylene terephthalate (PET) is one of the most common polymers used in industries. However, its accumulation in the environment is a health risk to humans and animals. Polyethylene vanillate (PEV) is a bio-based material with topological, mechanical, and thermal properties similar to PET, allowing it to be used as a PET replacement or blending material. This study aimed to investigate some structural and dynamical properties as well as the estimated glass transition temperature (Tg) of PET/PEV blended polymers by molecular dynamics (MD) simulations with an all-atom force field model. Four blended systems of PET/PEV with different composition ratios (4/1, 3/2, 2/3, and 1/4) were investigated and compared to the parent polymers, PET and PEV. The results show that the polymers with all blended ratios have Tg values around 344-347 K, which are not significantly different from each other and are close to the Tg of PET at 345 K. Among all the ratios, the 3/2 blended polymer showed the highest number of contacting atoms and possible hydrogen bonds between the two chain types. Moreover, the radial distribution results suggested the proper interactions in this system, which indicates that this is the most suitable ratio model for further experimental studies of the PET/PEV polymer blend.

Iodine-doped covalent organic frameworks with coaxially stacked cruciform anthracenes for high Hall mobility.

Cruciform anthracene building blocks are designed to construct an electroactive two-dimensional covalent organic framework (COF). Upon doping with iodine, cationic radicals are produced on the COF to exhibit structure-enhanced charge transfer properties with a low activation energy (0.13 eV) and a high Hall mobility (10.5 cm2 V-1 s-1).

Design, synthesis, in vitro, in silico, and SAR studies of flavone analogs towards anti-dengue activity.

Flavone has recently been proved as a promising scaffold for the development of a novel drug against dengue fever, one of the major health threats globally. However, the structure-activity relationship study of flavones on the anti-dengue activity remains mostly limited to the natural-occuring analogs. Herein, 27 flavone analogs were successfully synthesized, of which 5 analogs (5e, 5h, 5o, 5q, and 5r) were novel. In total, 33 analogs bearing a diverse range of substituents were evaluated for their efficacy against DENV2-infected LLC/MK2 cells. The introduction of electron-withdrawing groups on ring B such as Br (5m) or NO2 (5n and 5q) enhanced the activity significantly. In particular, the tri-ester 5d and di-ester 5e exhibited low toxicity against normal cell, and exceptional DENV2 inhibition with the EC50 as low as 70 and 68 nM, respectively, which is over 300-fold more active compared to the original baicalein reference. The viral targets for these potent flavone analogs were predicted to be NS5 MTase and NS5 RdRp, as suggested by the likelihood ratios from the molecular docking study. The great binding interaction energy of 8-bromobaicalein (5f) confirms the anti-dengue activity at atomistic level. The physicochemical property of all the synthetic flavone analogs in this study were predicted to be within the acceptable range. Moreover, the QSAR model showed the strong correlation between the anti-dengue activity and the selected molecular descriptors. This study emphasizes the great potential of flavone as a core structure for further development as a novel anti-dengue agent in the future.

Rational Design of Chrysene-Based Hybridized Local and Charge-Transfer Molecules as Efficient Non-Doped Deep-Blue Emitters for Simple-Structured Electroluminescent Devices.

Herein, we present a molecular design of chrysene-based deep-blue emissive materials (TC, TpPC, TpXC, and TmPC), in which chrysene as a core is functionalized with different triphenylamine moieties to realize a fine-tuning deep-blue fluorescence with superior electroluminescent (EL) performance. The photophysical analyses and density functional theory (DFT) calculations disclose that TC, TpPC, and TpXC possess HLCT characteristics with intense deep-blue emission in the solid-state, good hole-transporting ability, and high thermal and electrochemical stabilities. They are successfully employed as non-doped emitters in simple structured OLEDs (ITO/PEDOT : PSS : NF/emitter/TPBi/LiF : Al). In particular, TC-based device emits a deep-blue light with an emission peak at 446 nm and CIE color coordinates of (0.148, 0.096), a maximum external quantum efficiency (EQEmax ) of 4.31%, and a low turn-on voltage of 2.8 V.

Discovery of novel JAK2 and EGFR inhibitors from a series of thiazole-based chalcone derivatives.

The Janus kinase (JAK) and epidermal growth factor receptor (EGFR) have been considered as potential targets for cancer therapy due to their role in regulating proliferation and survival of cancer cells. In the present study, the aromatic alkyl-amino analogs of thiazole-based chalcone were selected to experimentally and theoretically investigate their inhibitory activity against JAK2 and EGFR proteins as well as their anti-cancer effects on human cancer cell lines expressing JAK2 (TF1 and HEL) and EGFR (A549 and A431). In vitro cytotoxicity screening results demonstrated that the HEL erythroleukemia cell line was susceptible to compounds 11 and 12, whereas the A431 lung cancer cell line was vulnerable to compound 25. However, TF1 and A549 cells were not sensitive to our thiazole derivatives. From kinase inhibition assay results, compound 25 was found to be a dual inhibitor against JAK2 and EGFR, whereas compounds 11 and 12 selectively inhibited the JAK2 protein. According to the molecular docking analysis, compounds 11, 12 and 25 formed hydrogen bonds with the hinge region residues Lys857, Leu932 and Glu930 and hydrophobically came into contact with Leu983 at the catalytic site of JAK2, while compound 25 formed a hydrogen bond with Met769 at the hinge region, Lys721 near a glycine loop, and Asp831 at the activation loop of EGFR. Altogether, these potent thiazole derivatives, following Lipinski's rule of five, could likely be developed as a promising JAK2/EGFR targeted drug(s) for cancer therapy.

Interactions between cycloguanil derivatives and wild type and resistance-associated mutant Plasmodium falciparum dihydrofolate reductases.

Comparative molecular field analysis (CoMFA) and quantum chemical calculations were performed on cycloguanil (Cyc) derivatives of the wild type and the quadruple mutant (Asn51Ile, Cys59Arg, Ser108Asn, Ile164Leu) of Plasmodium falciparum dihydrofolate reductase (PfDHFR). The represented CoMFA models of wild type (r(2) = 0.727 and r(2) = 0.985) and mutant type (r(2) = 0.786 and r(2) = 0.979) can describe the differences of the Cyc structural requirements for the two types of PfDHFR enzymes and can be useful to guide the design of new inhibitors. Moreover, the obtained particular interaction energies between the Cyc and the surrounding residues in the binding pocket indicated that Asn108 of mutant enzyme was the cause of Cyc resistance by producing steric clash with p-Cl of Cyc. Consequently, comparing the energy contributions with the potent flexible WR99210 inhibitor, it was found that the key mutant residue, Asn108, demonstrates attractive interaction with this inhibitor and some residues, Leu46, Ile112, Pro113, Phe116, and Leu119, seem to perform as second binding site with WR99210. Therefore, quantum chemical calculations can be useful for investigating residue interactions to clarify the cause of drug resistance.

Particular interaction between pyrimethamine derivatives and quadruple mutant type dihydrofolate reductase of Plasmodium falciparum: CoMFA and quantum chemical calculations studies.

Comparative molecular field analysis (CoMFA) was performed on twenty-three pyrimethamine (pyr) derivatives active against quadruple mutant type (Asn51Ile, Cys59Arg, Ser108Asn, Ile164Leu) dihydrofolate reductase of Plasmodium falcipaarum (PfDHFR). The represented CoMFA models were evaluated based on the various three different probe atoms, C(sp3) (+1), O(sp3) (-1) and H (+1), resulting in the best model with combined three types of probe atoms. The statistical results were r(2)(cv) = 0.702, S(press) = 0.608, r(2)(nv) = 0.980, s = 0.156, and r(2)(test-set) = 0.698 which can explain steric contribution of about 50%. In addition, an understanding of particular interaction energy between inhibitor and surrounding residues in the binding pocket was performed by using MP2/6-31G(d,p) quantum chemical calculations. The obtained results clearly demonstrate that Asn108 is the cause of pyr resistance with the highest repulsive interaction energy. Therefore, CoMFA and particular interaction energy analyses can be useful for identifying the structural features of potent pyr derivatives active against quadruple mutant type PfDHFR.

Silicon-coordinated nitrogen-doped graphene as a promising metal-free catalyst for N2O reduction by CO: a theoretical study.

Metal-free catalysts for the transformation of N2O and CO into green products under mild conditions have long been expected. The present work proposes using silicon-coordinated nitrogen-doped graphene (SiN4G) as a catalyst for N2O reduction and CO oxidation based on periodic DFT calculations. The reaction proceeds via two steps, which are N2O reduction at the Si reaction center, producing Si-O*, which subsequently oxidizes CO to CO2. The N2O reduction occurs with an activation energy barrier of 0.34 eV, while the CO oxidation step requires an energy of 0.66 eV. The overall reaction is highly exothermic, with a reaction energy of -3.41 eV, mostly due to the N2 generation step. Compared to other metal-free catalysts, SiN4G shows the higher selectivity because it not only strongly prefers to adsorb N2O over CO, but the produced N2 and CO2 are easily desorbed, which prevents the poisoning of the active catalytic sites. These results demonstrate that SiN4G is a promising metal-free catalyst for N2O reduction and CO oxidation under mild conditions, as the reaction is both thermodynamically and kinetically favorable.