Ambient hydrogenation of solid aromatics enabled by a high entropy alloy nanocatalyst.

Hydrogenation is a versatile chemical process with significant applications in various industries, including food production, petrochemical refining, pharmaceuticals, and hydrogen carriers/safety. Traditional hydrogenation of aromatics, hindered by the stable π-conjugated phenyl ring structures, typically requires high temperatures and pressures, making ambient hydrogenation a grand challenge. Herein, we introduce a PdPtRuCuNi high entropy alloy (HEA) nanocatalyst, achieving an exceptional 100% hydrogenation of carbon-carbon unsaturated bonds, including alkynyl and phenyl groups, in solid 1,4-bis(phenylethynyl)benzene (DEB) at 25 °C under ≤1 bar H2 and solventless condition. This results in a threefold higher hydrogen uptake for DEB-contained composites compared to conventional Pd catalysts, which can only hydrogenate the alkynyl groups with a ~ 27% conversion of DEB. Our experimental results, complemented by theoretical calculations, reveal that PdPtRu alloy is highly active and crucial in enabling the hydrogenation of phenyl groups, while all five elements work synergistically to regulate the reaction rate. Remarkably, this newly developed catalyst also achieves nearly 100% reactivity for ambient hydrogenation of a broad range of aromatics, suggesting its universal effectiveness. Our research uncovers a novel material platform and catalyst design principle for efficient and general hydrogenation. The multi-element synergy in HEA also promises unique catalytic behaviors beyond hydrogenation applications.

Theoretical insights into enantioselective [2 + 1] cyclopropanation reactions of diazo compounds with electron-deficient olefins.

CONTEXT: The cyclopropane skeleton plays a significant role in bioactive  molecules due to its distinctive structural properties. This has sparked keen interest and in-depth exploration in the field of stereoselective synthesis of cyclopropane derivatives. In the present study, the mechanism and the origin of stereoselectivity of diastereodivergent synthesis of cyclopropane derivatives via the catalyst-free [2 + 1]-cyclopropanation reactions of 3-diazo-N-methylindole (R1) with two types of electron-deficient olefins (R2 and R3) in both aqueous and toluene media have been studied using the DFT calculations. The findings indicate that these [2 + 1] cycloaddition reactions proceed in two stages, where the first step is not only the rate-determining step but also critically dictates the stereoselectivity of the product. The calculated diastereomeric ratios are in agreement with the experimental results. Furthermore, by utilizing non-covalent interaction (NCI) analysis and energy decomposition analysis based on molecular force fields (EDA-FF), we elucidated that the electrostatic interactions between reactant fragments in the transition state TS1s for the first step are the predominant factors determining the stereoselectivity, as opposed to the experimentally hypothesized steric hindrance and π-π stacking interactions. METHODS: The geometrical structures of all minima and transition states on the potential energy surface (PES) in solvents water and toluene were fully optimized using the DFT method at the M06-2X(D3)/SMD/6-31 + G(d,p) level of theory. Single-point energy calculations were carried out based on the optimized geometries in the solution at the M06-2X(D3)/6-311 + G(d,p) level. All the DFT calculations were performed using the Gaussian 09 software. The optimized molecular structures were visualized using CYLview software. NCI analysis was performed using the Multiwfn and VMD softwares. The Multiwfn program was also used for CDFT and EDA-FF analyses.

A Three-Dimensional Open-Framework Tin(II) Sulfate with Near-Unity Photoluminescence Quantum Yield.

A new open-framework tin(II) sulfate, formulated as C4H12N2·Sn(SO4)2·H2O, was prepared under the structure-directing effect of piperazine. This compound features a 3D structure with 16-ring channels. Under ultraviolet light irradiation, it emits bright yellow luminescence with a near-unity photoluminescence quantum yield. Theoretical calculations were carried out to understand the luminescence mechanism.

Decarboxylation Mechanism of iso-Orotate Decarboxylase Revisited.

iso-Orotate decarboxylase (IDCase), which is involved in the thymidine salvage pathway, has attracted considerable interest owing to its chemical similarity to a hypothetical DNA decarboxylase in mammals. Although valuable insights into the active DNA demethylation of 5-methyl-cytosine can be obtained from the decarboxylation mechanism of 5-carboxyl-uracil (5caU) catalyzed by IDCase, this mechanism remains under debate. In this study, the catalytic mechanism of 5caU decarboxylation by IDCase was studied using hybrid quantum mechanics/molecular mechanics (QM/MM) methodologies and density functional theory (DFT) calculations with a truncated model. The calculations supported a mechanism involving three sequential stages: activation of the 5caU substrate via proton transfer from an arginine (R262') to the carboxyl group of 5caU, formation of a tetrahedral intermediate, and decarboxylation of the tetrahedral intermediate to generate uracil as the product. The reaction pathways and structures obtained using the QM/MM and DFT methods coincided with each other. These simulations provided detailed insights into the unique mechanism of IDCase, clarifying various unresolved issues, such as the critical role of R262'. In addition, aspartate D323 was found to act as a general base in the tetrahedral intermediate formation step and a general acid in the later C-C bond cleavage step.

A theoretical study of the mechanism of cationic polymerization of isobutylene catalysed by EtAlCl2/t-BuCl with bis(2-chloroethyl)ether in hexanes.

The mechanism of cationic polymerization of isobutylene catalyzed by t-BuCl/ethylaluminum dichloride (EADC) combined with bis(2-chloroethyl)ether (CEE) in n-hexane solvent has been investigated using ab initio molecular dynamics (AIMD) and metadynamics (MTD) simulations. The results indicated that the polyisobutylene (PIB) initiation stage involves a clear two-step mechanism. Calculation of the free energy landscapes of the other two ether reactions reveals that the energy barriers of diisopropyl ether (i-Pr2O) and 2-chloroethyl ethyl ether (CEEE) are much higher than those of CEE, which is consistent with the experimental results. During the chain propagation phase, the required free energy barrier gradually decreases and tends to reach equilibrium as the chain length increases. Finally, the oxonium mechanism during the chain initiation stage was investigated by calculating the 1H NMR spectra and MTD simulation. Our calculations can confirm that the existence of tert-butyloxonium ions during the reaction is possible. Their contribution to the whole reaction is further discussed.

Self-assembly of rigid amphiphilic graft cyclic-brush copolymers to nanochannels using dissipative particle dynamics simulation.

The synthesis of specific artificial nanochannels remains a formidable challenge in the field of nanomaterials and synthetic chemistry. In particular, the preparation of artificial nanochannels using amphiphilic graft cyclic-brush copolymers (AGCCs) as monomers has garnered substantial attention. Nevertheless, because of the constrained time and length scales inherent in traditional molecular dynamics simulations, a comprehensive theoretical understanding of the morphological regulation mechanism governing the self-assembly of AGCCs into nanochannels remains elusive. In this study, we employed the dissipative particle dynamics (DPD) method to explore the self-assembly mechanism considering factors such as the DPD interaction parameters, concentrations, and sizes of AGCCs. By calculating the phase diagrams, we predicted the emergence of four distinct nanochannel types: short independent, long independent, parallel, and disordered channels. Importantly, the formation of these nanochannels is highly contingent on specific environmental conditions. Furthermore, we extensively discussed self-assembly processes that lead to different types of nanochannels. The self-assembly of AGCCs is revealed as a multistep process primarily influenced by the interaction parameters. However, while the monomer size and concentration do not introduce novel self-assembly morphologies, they do influence the final aggregation state. The elucidation of the self-assembly mechanism presented in this study deepens our understanding of AGCC nanochannel formation. Consequently, this is a valuable guide for the preparation of copolymer materials with specific functionalities, offering insights into targeted copolymer material design.

Effects of void defects on the mechanical properties of biphasic calcium phosphate nanoparticles: A molecular dynamics investigation.

Porous biphasic calcium phosphate (BCP) ceramics are widely used in bone tissue engineering, and the mechanical properties of BCP implants must be reliable. However, the effects of pore structure (e.g., shape and size) on the mechanical properties are not well understood. In this study, we used molecular dynamics simulations to investigate the influence of pore shape and size on the mechanical behavior of BCP nanoparticles. BCP void models with cylindrical and cuboid pores ranging from 2 to 16 nm in diameter were constructed, and the elastic moduli were calculated. In addition, uniaxial tensile and compressive tests were performed on the models. We found that the pore size had a more significant impact on the mechanical properties of BCP than pore shape. Further, the elastic moduli decreased nonlinearly with increasing pore size. In addition, the tensile and compressive strength also decreased with the increase in pore size, but the ductility improved. Furthermore, deformation and fracture were more likely to occur near the pores and at the phase interfaces as a result of high atomic local strain in the calcium-deficient hydroxyapatite area. The results of this work reveal the effects of pore parameters on the mechanical properties of porous BCP at the nanometer level, which may aid the design of improved porous and multiphase CaP-based biomaterials for bone regeneration.

Quantum Mechanical/Molecular Mechanical Elucidation of the Catalytic Mechanism of Leukotriene A4 Hydrolase as an Epoxidase.

Leukotriene A4 hydrolase (LTA4H) functions as a mono-zinc bifunctional enzyme with aminopeptidase and epoxidase activities. While the aminopeptidase mechanism is well understood, the epoxidase mechanism remains less clear. In continuation of our prior research, we undertook an in-depth exploration of the LTA4H catalytic role as an epoxidase, employing a combined SCC-DFTB/CHARMM method. In the current work, we found that the conversion of LTA4 to leukotriene B4 (LTB4) involves three successive steps: epoxy ring opening (RO), nucleophilic attack (NA), and proton transfer (PT) reactions at the epoxy oxygen atom. Among these steps, the RO and NA stages constitute the potential rate-limiting step within the entire epoxidase mechanism. Notably, the NA step implicates D375 as the general base catalyst, while the PT step engages protonated E271 as the general acid catalyst. Additionally, we delved into the mechanism behind the formation of the isomer product, Δ6-trans-Δ8-cis-LTB4. Our findings debunked the feasibility of a direct LTB4 to iso-LTB4 conversion. Instead, we highlight the possibility of isomerization from LTA4 to its isomeric conjugate (iso-LTA4), showing comparable energy barriers of 5.1 and 5.5 kcal/mol in aqueous and enzymatic environments, respectively. The ensuing dynamics of iso-LTA4 hydrolysis subsequently yield iso-LTB4 via a mechanism akin to LTA4 hydrolysis, albeit with a heightened barrier. Our computations firmly support the notion that substrate isomerization exclusively takes place prior to or during the initial substrate-binding phase, while LTA4 remains the dominant conformer. Notably, our simulations suggest that irrespective of the active site's constrained L-shape, isomerization from LTA4 to its isomeric conjugate remains plausible. The mechanistic insights garnered from our simulations furnish a valuable understanding of LTA4H's role as an epoxidase, thereby facilitating potential advancements in inhibitor design.

Discovery and Evaluation of 3-Quinoxalin Urea Derivatives as Potent, Selective, and Orally Available ATM Inhibitors Combined with Chemotherapy for the Treatment of Cancer via Goal-Oriented Molecule Generation and Virtual Screening.

ATM plays an important role in DNA damage response and is considered a potential target in cancer therapies. In this study, a goal-directed molecular generation approach based on ligand similarity and target specificity was applied to sample active molecules, and they were screened virtually to identify the theoretical lead compound 7a, which was later shown to inhibit ATM adequately. However, there is a main concern about its poor metabolic stability in vitro. Subsequent optimization was performed to improve the potency and selectivity toward ATM and attenuate the hepatic clearance in vitro, culminating in the identification of 10r with nanomolar ATM inhibition, excellent cellular sensitivity to radiation and chemotherapy drugs, and impressive pharmacokinetic profiles. Furthermore, 10r combined with irinotecan demonstrated a synergistic antitumor efficacy in SW620 xenograft models, suggesting that it could be a promising candidate drug combined with chemotherapy for the treatment of cancer.

Interactions between curcumin and human salt-induced kinase 3 elucidated from computational tools and experimental methods.

Natural products are widely used for treating mitochondrial dysfunction-related diseases and cancers. Curcumin, a well-known natural product, can be potentially used to treat cancer. Human salt-induced kinase 3 (SIK3) is one of the target proteins for curcumin. However, the interactions between curcumin and human SIK3 have not yet been investigated in detail. In this study, we studied the binding models for the interactions between curcumin and human SIK3 using computational tools such as homology modeling, molecular docking, molecular dynamics simulations, and binding free energy calculations. The open activity loop conformation of SIK3 with the ketoenol form of curcumin was the optimal binding model. The I72, V80, A93, Y144, A145, and L195 residues played a key role for curcumin binding with human SIK3. The interactions between curcumin and human SIK3 were also investigated using the kinase assay. Moreover, curcumin exhibited an IC50 (half-maximal inhibitory concentration) value of 131 nM, and it showed significant antiproliferative activities of 9.62 ± 0.33 µM and 72.37 ± 0.37 µM against the MCF-7 and MDA-MB-23 cell lines, respectively. This study provides detailed information on the binding of curcumin with human SIK3 and may facilitate the design of novel salt-inducible kinases inhibitors.

General Charge Transfer Dipole Model for AMOEBA-Like Force Fields.

The development of highly accurate force fields is always an importance aspect in molecular modeling. In this work, we introduce a general damping-based charge transfer dipole (D-CTD) model to describe the charge transfer energy and the corresponding charge flow for H, C, N, O, P, S, F, Cl, and Br elements in common bio-organic systems. Then, two effective schemes to evaluate the charge flow from the corresponding induced dipole moment between the interacting molecules were also proposed and discussed. The potential applicability of the D-CTD model in ion-containing systems was also demonstrated in a series of ion-water complexes including Li+, Na+, K+, Mg2+, Ca2+, Fe2+, Zn2+, Pt2+, F-, Cl-, Br-, and I- ions. In general, the D-CTD model demonstrated good accuracy and good transferability in both charge transfer energy and the corresponding charge flow for a wide range of model systems. By distinguishing the intermolecular charge redistribution (charge transfer) under the influence of an external electric field from the accompanying intramolecular charge redistribution (polarization), the D-CTD model is theoretically consistent with current induced dipole-based polarizable dipole models and hence can be easily implemented and parameterized. Along with our previous work in charge penetration-corrected electrostatics, a bottom-up approach constructed water model was also proposed and demonstrated. The structure-maker and structure-breaker roles of cations and anions were also correctly reproduced using Na+, K+, Cl-, and I- ions in the new water model, respectively. This work demonstrates a cost-effective approach to describe the charge transfer phenomena. The water and ion models also show the feasibility of a modulated development approach for future force fields.

Insights into the effect of protein glycosylation on carbohydrate substrate binding.

The role of glycosylation in the binding of glycoproteins to carbohydrate substrates has not been well understood. The present study addresses this knowledge gap by elucidating the links between the glycosylation patterns of a model glycoprotein, a Family 1 carbohydrate-binding module (TrCBM1), and the thermodynamic and structural properties of its binding to different carbohydrate substrates using isothermal titration calorimetry and computational simulation. The variations in glycosylation patterns cause a gradual transition of the binding to soluble cellohexaose from an entropy-driven process to an enthalpy-driven one, a trend closely correlated with the glycan-induced shift of the predominant binding force from hydrophobic interactions to hydrogen bonding. However, when binding to a large surface of solid cellulose, glycans on TrCBM1 have a more dispersed distribution and thus have less adverse impact on the hydrophobic interaction forces, leading to overall improved binding. Unexpectedly, our simulation results also suggest an evolutionary role of O-mannosylation in transforming the substrate binding features of TrCBM1 from those of type A CBMs to those of type B CBMs. Taken together, these findings provide new fundamental insights into the molecular basis of the role of glycosylation in protein-carbohydrate interactions and are expected to better facilitate further studies in this area.

Data Mining and Graph Network Deep Learning for Band Gap Prediction in Crystalline Borate Materials.

Crystalline borates are an important class of functional materials with wide applications in photocatalysis and laser technologies. Obtaining their band gap values in a timely and precise manner is a great challenge in material design due to the issues of computational accuracy and cost of first-principles methods. Although machine learning (ML) techniques have shown great successes in predicting the versatile properties of materials, their practicality is often limited by the data set quality. Here, by using a combination of natural language processing searches and domain knowledge, we built an experimental database of inorganic borates, including their chemical compositions, band gaps, and crystal structures. We performed graph network deep learning to predict the band gaps of borates with accuracy, and the results agreed favorably with experimental measurements from the visible-light to the deep-ultraviolet (DUV) region. For a realistic screening problem, our ML model could correctly identify most of the investigated DUV borates. Furthermore, the extrapolative ability of the model was validated against our newly synthesized borate crystal Ag3B6O10NO3, supplemented by the discussion of an ML-based material design for structural analogues. The applications and interpretability of the ML model were also evaluated extensively. Finally, we implemented a web-based application, which could be utilized conveniently in material engineering for the desired band gap. The philosophy behind this study is to use cost-effective data mining techniques to build high-quality ML models, which can provide useful clues for further material design.

Identifying Protein-Ligand Interactions via a Novel Distance Self-Feedback Biomolecular Interaction Network.

Efficient and accurate characterizations of protein-ligand interactions are key to understanding biology at the molecular level. They are particularly useful in pharmaceutical industry applications. They are usually computationally demanding for those widely applied dynamics-based methods in identifying important residues or calculating ligand binding free energy. In this work, we proposed a graph deep learning (DL) framework, namely, the distance self-feedback biomolecular interaction network (DSBIN), in which the relationship between the complex structure and binding affinity can be established by means of a carefully designed distance self-feedback module and interaction layer. Our model can directly provide a quantitative evaluation of inhibitor binding affinities (pKd). More importantly, the DSBIN model efficiently identifies key interactions for inhibitor binding and thus intrinsically bears the interpretability. Its generalization performance was further verified using 1405 unseen structures. The predicted binding free energies' deviations were calculated to be less than 1.37 kcal/mol for more than 55% structures. Moreover, we also compared the DSBIN model with a commonly used theoretical method in calculating the substrate binding free energy, MM/GBSA. Our results show that the current DL model has generally better performance in predicting the binding free energy. For a specific complex system, mannopentaose/TmCBM27, the DSBIN predicted binding free energy is -8.21 kcal/mol, which is very close to experimentally measured -7.76 kcal/mol and MM/GBSA calculated -7.16 kcal/mol. Meanwhile, all important aromatic residues around the binding pocket can be identified by our DL model. Considering the accuracy and efficiency of the newly developed DL model, it may be very helpful in the field of drug design and molecular recognition.

Design, synthesis and biological evaluation of purine-based derivatives as novel JAK2/BRD4(BD2) dual target inhibitors.

Based on the pharmacological synergy of JAK2 and BRD4 in the NF-κB pathway and positive therapeutic effect of combination of JAK2 and BRD4 inhibitors in treating MPN and inflammation. A series of unique 9H-purine-2,6-diamine derivatives that selectively inhibited Janus kinase 2 (JAK2) and BRD4(BD2) were designed, prepared, and evaluated for their in vitro and in vivo potency. Among them, compound 9j exhibited acceptable inhibitory activity with IC50 values of 13 and 22 nM for BD2 of BRD4 and JAK2, respectively. The western blot assay demonstrated that 9j performed good functional potency in the NF-κB pathway and the phosphorylation of p65, IκB-α, and IKKα/ß signal intensities were suppressed on RAW264.7 cell lines. Furthermore, 9j significantly improved the disease symptoms in a Ba/F3-JAK2V617F allograft model. Meanwhile, 9j was also effective in relieving symptoms in an acute ulcerative colitis model. Taken together, 9j was a potent JAK2/BRD4(BD2) dual target inhibitor and could be a potential lead compound in treating myeloproliferative neoplasms and inflammatory diseases.

Corrigendum to "Mussel-inspired nanozyme catalyzed conductive and self-setting hydrogel for adhesive and antibacterial bioelectronics" [Bioact. Mater. 6 (2021) 2676-2687 / 452].

[This corrects the article DOI: 10.1016/j.bioactmat.2021.01.033.].

Processive binding mechanism of Cel9G from Clostridium cellulovorans: molecular dynamics and free energy landscape investigations.

The degradation of recalcitrant polysaccharides such as cellulose and chitin requires the synergistic functionality of processive glycosidase (GH) cocktails. Understanding the fundamental phenomenon of processivity is of biological and economic importance for the conversion of biomass into biofuel. In this work, cellulase family 9 from Clostridium cellulovorans (Cel9G), which is a processive endoglucanase, was used to elucidate the processive binding mechanism with respect to polysaccharides, since it exhibits a multimodular crystallographic structure. Metadynamics and molecular dynamics simulations were performed to explore the dynamics of cellulose chain binding to Cel9G via processive motion. The processive movement of the cellulose chain towards the catalytic domain may exhibit several local minima, which are related to strong CH/π interactions between the sugar rings and the aromatic residues distributed at the active site. For the binding of the G6 and G12 molecules, the energy barriers were determined to be 4.8 and 7.4 kcal mol-1, respectively. Based on the site-directed mutagenesis simulations of Y520A, it was found that the existence of Y520 is critical for processive binding. It is likely that Y520 and H125/Y416 form two anchor points to facilitate processive binding to polysaccharides. More importantly, the straight-line morphology of the substrate could be observed after the formation of the so-called slide mode, which is different from the V-shaped Michaelis complex structure revealed by quantum mechanics/molecular mechanics simulations. This indicates that an additional step, namely, catalytic activation, probably exists between processive binding and the hydrolysis reaction. Finally, a four-step catalytic cycle was proposed for Cel9G. Our work provides novel molecular-level insights into the structure-function relationship for the processive enzyme Cel9G and should aid the development of improved GH cocktails for the efficient cleavage of glycosidic linkages.

Molecular Dynamics Simulation of Biomimetic Biphasic Calcium Phosphate Nanoparticles.

Biphasic calcium phosphate (BCP) is used as a bone substitute and bone tissue repair material due to its better control over bioactivity and biodegradability. It is crucial to stabilize the implanted biomaterial while promoting bone ingrowth. However, a lack of standard experimental and theoretical protocols to characterize the physicochemical properties of BCP limits the optimization of its composition and properties. Computational simulations can help us better to learn BCP at a nanoscale level. Here, the Voronoi tessellation method was combined with simulated annealing molecular dynamics to construct BCP nanoparticle models of different sizes, which were used to understand the physicochemical properties of BCP (e.g., melting point, infrared spectrum, and mechanical properties). We observed a ∼20 to 30 Å layer of calcium-deficient hydroxyapatite at the HAP/ß-TCP interface due to particle migration, which may contribute to BCP stability. The BCP model may stimulate further research into BCP ceramics and multiphasic ceramics. Moreover, our study may facilitate the optimization of compositions of BCP-based biomaterials.

Molecular investigations of the prenucleation mechanism of bone-like apatite assisted by type I collagen nanofibrils: insights into intrafibrillar mineralization.

Bone is a typical inorganic-organic composite material with a multilevel hierarchical organization. In the lowest level of bone tissue, inorganic minerals, which are mainly composed of hydroxyapatite, are mineralized within the type I collagen fibril scaffold. Understanding the crystal prenucleation mechanism and growth of the inorganic phase is particularly important in the design and development of materials with biomimetic nanostructures. In this study, we built an all-atom human type I collagen fibrillar model with a 67 nm overlap/gap D-periodicity. Arginine residues were shown to serve as the dominant cross-linker to stabilize the fibril scaffold. Subsequently, the prenucleation mechanism of collagen intrafibrillar mineralization was investigated using a molecular dynamics approach. Considering the physiological pH of the human body (i.e., ∼7.4), HPO42- was initially used to simulate the protonation state of the phosphate ions. Due to the spatially constrained effects resulting from the overlap/gap structure of the collagen fibrils, calcium phosphate clusters formed mainly inside the hole zone but with different spatial distributions along the long axis direction; this indicated that the nucleation of calcium phosphate may be highly site-selective. Furthermore, the model containing both HPO42- and PO43- in the solution phase formed significantly larger clusters without any change in the nucleation sites. This phenomenon suggests that the existence of PO43- is beneficial for the mineralization process, and so the conversion of HPO42- to PO43- was considered a critical step during mineralization. Finally, we summarize the nucleation mechanism for collagen intrafibrillar mineralization, which could contribute to the fabrication of mineralized collagen biomimetic materials.

Small Molecules Promote Selective Denaturation and Degradation of Tubulin Heterodimers through a Low-Barrier Hydrogen Bond.

Here, we report a novel mechanism to selectively degrade target proteins. 3-(3-Phenoxybenzyl)amino-ß-carboline (PAC), a tubulin inhibitor, promotes selective degradation of αß-tubulin heterodimers. Biochemical studies have revealed that PAC specifically denatures tubulin, making it prone to aggregation that predisposes it to ubiquitinylation and then degradation. The degradation is mediated by a single hydrogen bond formed between the pyridine nitrogen of PAC and ßGlu198, which is identified as a low-barrier hydrogen bond (LBHB). In contrast, another two tubulin inhibitors that only form normal hydrogen bonds with ßGlu198 exhibit no degradation effect. Thus, the LBHB accounts for the degradation. We then screened for compounds capable of forming an LBHB with ßGlu198 and demonstrated that BML284, a Wnt signaling activator, also promotes tubulin heterodimer degradation through the LBHB. Our study provided a unique example of LBHB function and identified a novel approach to obtain tubulin degraders.