Alpha and gamma mangostins inhibit wild-type B SARS-CoV-2 more effectively than the SARS-CoV-2 variants and the major target is unlikely the 3C-like protease.

Background: Anti-SARS-CoV-2 and immunomodulatory drugs are important for treating clinically severe patients with respiratory distress symptoms. Alpha- and gamma-mangostins (AM and GM) were previously reported as potential 3C-like protease (3CLpro) and Angiotensin-converting enzyme receptor 2 (ACE2)-binding inhibitors in silico. Objective: We aimed to evaluate two active compounds, AM and GM, from Garcinia mangostana for their antivirals against SARS-CoV-2 in live virus culture systems and their cytotoxicities using standard methods. Also, we aimed to prove whether 3CLpro and ACE2 neutralization were major targets and explored whether any additional targets existed. Methods: We tested the translation and replication efficiencies of SARS-CoV-2 in the presence of AM and GM. Initial and subgenomic translations were evaluated by immunofluorescence of SARS-CoV-2 3CLpro and N expressions at 16 h after infection. The viral genome was quantified and compared with the untreated group. We also evaluated the efficacies and cytotoxicities of AM and GM against four strains of SARS-CoV-2 (wild-type B, B.1.167.2, B.1.36.16, and B.1.1.529) in Vero E6 cells. The potential targets were evaluated using cell-based anti-attachment, time-of-drug addition, in vitro 3CLpro activities, and ACE2-binding using a surrogated viral neutralization test (sVNT). Moreover, additional targets were explored using combinatorial network-based interactions and Chemical Similarity Ensemble Approach (SEA). Results: AM and GM reduced SARS-CoV-2 3CLpro and N expressions, suggesting that initial and subgenomic translations were globally inhibited. AM and GM inhibited all strains of SARS-CoV-2 at EC50 of 0.70-3.05 µM, in which wild-type B was the most susceptible strain (EC50 0.70-0.79 µM). AM was slightly more efficient in the variants (EC50 0.88-2.41 µM), resulting in higher selectivity indices (SI 3.65-10.05), compared to the GM (EC50 0.94-3.05 µM, SI 1.66-5.40). GM appeared to be more toxic than AM in both Vero E6 and Calu-3 cells. Cell-based anti-attachment and time-of-addition suggested that the potential molecular target could be at the post-infection. 3CLpro activity and ACE2 binding were interfered with in a dose-dependent manner but were insufficient to be a major target. Combinatorial network-based interaction and chemical similarity ensemble approach (SEA) suggested that fatty acid synthase (FASN), which was critical for SARS-CoV-2 replication, could be a target of AM and GM. Conclusion: AM and GM inhibited SARS-CoV-2 with the highest potency at the wild-type B and the lowest at the B.1.1.529. Multiple targets were expected to integratively inhibit viral replication in cell-based system.

Evaluating solubility, stability, and inclusion complexation of oxyresveratrol with various ß-cyclodextrin derivatives using advanced computational techniques and experimental validation.

Oxyresveratrol (OXY), a natural stilbenoid in mulberry fruits, is known for its diverse pharmacological properties. However, its clinical use is hindered by low water solubility and limited bioavailability. In the present study, the inclusion complexes of OXY with ß-cyclodextrin (ßCD) and its three analogs, dimethyl-ß-cyclodextrin (DMßCD), hydroxypropyl-ß-cyclodextrin (HPßCD) and sulfobutylether-ß-cyclodextrin (SBEßCD), were investigated using in silico and in vitro studies. Molecular docking revealed two binding orientations of OXY, namely, 4',6'-dihydroxyphenyl (A-form) and 5,7-benzenediol ring (B-form). Molecular Dynamics simulations suggested the formation of inclusion complexes with ßCDs through two distinct orientations, with OXY/SBEßCD exhibiting maximum atom contacts and the lowest solvent-exposed area in the hydrophobic cavity. These results corresponded well with the highest binding affinity observed in OXY/SBEßCD when assessed using the MM/GBSA method. Beyond traditional simulation methods, Ligand-binding Parallel Cascade Selection Molecular Dynamics method was employed to investigate how the drug enters and accommodates within the hydrophobic cavity. The in silico results aligned with stability constants: SBEßCD (2060 M-1), HPßCD (1860 M-1), DMßCD (1700 M-1), and ßCD (1420 M-1). All complexes exhibited a 1:1 binding mode (AL type), with SBEßCD enhancing OXY solubility (25-fold). SEM micrographs, DSC thermograms, FT-IR and 1H NMR spectra confirm the inclusion complex formation, revealing novel surface morphologies, distinctive thermal behaviors, and new peaks. Notably, the inhibitory impact on the proliferation of breast cancer cell lines, MCF-7, exhibited by inclusion complexes particularly OXY/DMßCD, OXY/HPßCD, and OXY/SBEßCD were markedly superior compared to that of OXY alone.

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.

Aggregation of Apo/Glycated Human Serum Albumins and Aptamer-Saturated Graphene Quantum Dot: A Simulation Study.

Human serum albumin (HSA) is a protein carrier that transports a wide range of drugs and nutrients. The amount of glycated HSA (GHSA) is used as a diabetes biomarker. To quantify the GHSA amount, the fluorescent graphene-based aptasensor has been a successful method. In aptasensors, the key mechanism is the adsorption/desorption of albumin from the aptamer-graphene complex. Recently, the graphene quantum dot (GQD) has been reported to be an aptamer sorbent. Due to its comparable size to aptamers, it is attractive enough to explore the possibility of GQD as a part of an albumin aptasensor. Therefore, molecular dynamics (MD) simulations were performed here to reveal the binding mechanism of albumin to an aptamer-GQD complex in molecular detail. GQD saturated by albumin-selective aptamers (GQDA) is studied, and GHSA and HSA are studied in comparison to understand the effect of glycation. Fast and spontaneous albumin-GQDA binding was observed. While no specific GQDA-binding site on both albumins was found, the residues used for binding were confined to domains I and III for HSA and domains II and III for GHSA. Albumins were found to bind preferably to aptamers rather than to GQD. Lysines and arginines were the main contributors to binding. We also found the dissociation of GLC from all GHSA trajectories, which highlights the role of GQDA in interfering with the ligand binding affinity in Sudlow site I. The binding of GQDA appears to impair albumin structure and function. The insights obtained here will be useful for the future design of diabetes aptasensors.

Prediction of the binding mechanism of a selective DNA methyltransferase 3A inhibitor by molecular simulation.

DNA methylation is an epigenetic mechanism that introduces a methyl group at the C5 position of cytosine. This reaction is catalyzed by DNA methyltransferases (DNMTs) and is essential for the regulation of gene transcription. The DNMT1 and DNMT3A or -3B family proteins are known targets for the inhibition of DNA hypermethylation in cancer cells. A selective non-nucleoside DNMT3A inhibitor was developed that mimics S-adenosyl-l-methionine and deoxycytidine; however, the mechanism of selectivity is unclear because the inhibitor-protein complex structure determination is absent. Therefore, we performed docking and molecular dynamics simulations to predict the structure of the complex formed by the association between DNMT3A and the selective inhibitor. Our simulations, binding free energy decomposition analysis, structural isoform comparison, and residue scanning showed that Arg688 of DNMT3A is involved in the interaction with this inhibitor, as evidenced by its significant contribution to the binding free energy. The presence of Asn1192 at the corresponding residues in DNMT1 results in a loss of affinity for the inhibitor, suggesting that the interactions mediated by Arg688 in DNMT3A are essential for selectivity. Our findings can be applied in the design of DNMT-selective inhibitors and methylation-specific drug optimization procedures.

Site Identification and Next Choice Protocol for Hit-to-Lead Optimization.

Time efficiency and cost savings are major challenges in drug discovery and development. In this process, the hit-to-lead stage is expected to improve efficiency because it primarily exploits the trial-and-error approach of medicinal chemists. This study proposes a site identification and next choice (SINCHO) protocol to improve the hit-to-lead efficiency. This protocol selects an anchor atom and growth site pair, which is desirable for a hit-to-lead strategy starting from a 3D complex structure. We developed and fine-tuned the protocol using a training data set and assessed it using a test data set of the preceding hit-to-lead strategy. The protocol was tested for experimentally determined structures and molecular dynamics (MD) ensembles. The protocol had a high prediction accuracy for applying MD ensembles, owing to the consideration of protein flexibility. The SINCHO protocol enables medicinal chemists to visualize and modify functional groups in a hit-to-lead manner.

Cocrystalline Matrices for Hyperpolarization at Room Temperature Using Photoexcited Electrons.

We propose using cocrystals as effective polarization matrices for triplet dynamic nuclear polarization (DNP) at room temperature. The polarization source can be uniformly doped into cocrystals formed through acid-acid, amide-amide, and acid-amide synthons. The dense-packing crystal structures, facilitated by multiple hydrogen bonding and π-π interactions, result in extended T1 relaxation times, enabling efficient polarization diffusion within the crystals. Our study demonstrates the successful polarization of a DNP-magnetic resonance imaging molecular probe, such as urea, within a cocrystal matrix at room temperature using triplet-DNP.

[Development of Integrated Database for Experiments and Simulations].

Researchers collect data and use various methods to organize it. Ensuring the reliability and reproducibility of data is crucial, and collaboration across different research fields is on the rise. However, when there is geographical distance, sharing data becomes a challenging task. Therefore, there is a need for the development of a mechanism for sharing data on the web. We have developed an integrated database to facilitate the sharing and management of research data, particularly focusing on small molecules. The integrated database serves as a platform for centralizing data related to small molecules, including their chemical structures, wet lab experimental data, simulation data, and more. It has been constructed as a web application, offering features such as library management for small molecules, registration and viewing of wet lab experiment results, generation of initial conformations for simulations, and data visualization. This enables researchers to efficiently share their research data and collaborate seamlessly, whether within their research group or via cloud-based access that allows project and team members to connect from anywhere. This integrated database plays a critical role in connecting wet lab experiments and simulations, enabling researchers to cross-reference and analyze experimental data comprehensively. It serves as an essential tool to advance research and foster idea generation.

[Development of Membrane Permeability Coefficient by Means of Novel Molecular Dynamics Methods].

The membrane permeability, and its evaluation, is crucial factor in the process of uptake of compounds from outside to inside the cell and in the inhibition of the activity of disease-causing target proteins. Although molecular dynamics (MD) simulations have been shown to be able to reproduce the conformational changes of compounds occurring during membrane permeation, it is still challenging to extract the membrane permeability at an affordable computational workload solely by conventional MD. Indeed, the time scale accessible by MD is far below the one characterizing the actual permeation process. Phenomena occurring in living organisms escaping the reach of standard MD are generally referred to as biological rare events, and the membrane permeation process is one of them. To overcome this time-scale problem, several enhanced sampling methods have been proposed over the years to improve conformational sampling. In this review, a hybrid sampling method that combines the parallel cascade selection MD (PaCS-MD) and the outlier flooding method (OFLOOD), introduced and developed by our group, is proposed as a tool to study the membrane permeation from structural sampling (rare-event sampling). The obtained trajectories are used to estimate the free energy profiles for the membrane permeation and to compute the membrane permeation coefficients. Moreover, we present an example of application of the free energy reaction network method as a versatile way for incorporating explicitly into reaction coordinates the degrees of freedom related to internal motion.

Preferential Door for Ligand Binding and Unbinding Pathways in Inhibited Human Acetylcholinesterase.

Rising global population and increased food demands have resulted in the increased use of organophosphate pesticides (OPs), leading to toxin accumulation and transmission to humans. Pralidoxime (2-PAM), an FDA-approved drug, serves as an antidote for OP therapy. However, the atomic-level detoxification mechanisms regarding the design of novel antidotes remain unclear. This is the first study to examine the binding and unbinding pathways of 2-PAM to human acetylcholinesterase (HuAChE) through three identified doors using an enhanced sampling method called ligand-binding parallel cascade selection molecular dynamics (LB-PaCS-MD). Remarkably, LB-PaCS-MD could identify a predominant in-line binding mechanism through the acyl door at 63.79% ± 6.83%, also implicating it in a potential unbinding route (90.14% ± 4.22%). Interestingly, crucial conformational shifts in key residues, W86, Y341, and Y449, and the Ω loop significantly affect door dynamics and ligand binding modes. The LB-PaCS-MD technique can study ligand-binding pathways, thereby contributing to the design of antidotes and covalent drugs.

Network topology diversification of porous organic salts.

Hydrogen-bonded organic frameworks (HOFs) are porous organic materials constructed via hydrogen bonds. HOFs have solubility in specific high-polar organic solvents. Therefore, HOFs can be returned to their components and can be reconstructed, which indicates their high recyclability. Network topologies, which are the frameworks of porous structures, control the pore sizes and shapes of HOFs. Therefore, they strongly affect the functions of porous materials. However, hydrogen bonds are usually weak interactions, and the design of the intended network topology in HOFs from their components has been challenging. Porous organic salts (POSs) are an important class of HOFs, are hierarchically constructed via strong charge-assisted hydrogen bonds between sulfonic acids and amines, and therefore are expected to have high designability of the porous structure. However, the network topology of POSs has been limited to only dia-topology. Here, we combined tetrasulfonic acid with the adamantane core (4,4',4'',4'''-(adamantane-1,3,5,7-tetrayl)tetrabenzenesulfonic acid; AdPS) and triphenylmethylamines with modified substituents in para-positions of benzene rings (TPMA-X, X = F, methyl (Me), Cl, Br, I). We changed the steric hindrance between the adamantane and substituents (X) in TPMA-X and obtained not only the common dia-topology for POSs but also rare sod-topology, and lon- and uni-topologies that are formed for the first time in HOFs. Changing template molecules under preparation helped in successfully isolating the porous structures of AdPS/TPMA-Me with dia-, lon-, and sod-topologies which exhibited different gas adsorption properties. Therefore, for the first time, we demonstrated that the steric design of HOF components facilitated the formation, diversification, and control of the network topologies and functions of HOFs.

Development of an FeII Complex Exhibiting Intermolecular Proton Shifting Coupled Spin Transition.

In this study, we investigated reversible intermolecular proton shifting (IPS) coupled with spin transition (ST) in a novel FeII complex. The host FeII complex and the guest carboxylic acid anion were connected by intermolecular hydrogen bonds (IHBs). We extended the intramolecular proton transfer coupled ST phenomenon to the intermolecular system. The dynamic phenomenon was confirmed by variable-temperature single-crystal X-ray diffraction, neutron crystallography, and infrared spectroscopy. The mechanism of IPS was further validated using density functional theory calculations. The discovery of IPS-coupled ST in crystalline molecular materials provides good insights into fundamental processes and promotes the design of novel multifunctional materials with tunable properties for various applications, such as optoelectronics, information storage, and molecular devices.

Grinding-Induced Water Solubility Exhibited by Mechanochromic Luminescent Supramolecular Fibers.

Most mechanochromic luminescent compounds are crystalline and highly hydrophobic; however, mechanochromic luminescent molecular assemblies comprising amphiphilic molecules have rarely been explored. This study investigated mechanochromic luminescent supramolecular fibers composed of dumbbell-shaped 9,10-bis(phenylethynyl)anthracene-based amphiphiles without any tetraethylene glycol (TEG) substituents or with two TEG substituents. Both amphiphiles formed water-insoluble supramolecular fibers via linear hydrogen bond formation. Both compounds acquired water solubility when solid samples composed of supramolecular fibers are ground. Grinding induces the conversion of 1D supramolecular fibers into micellar assemblies where fluorophores can form excimers, thereby resulting in a large redshift in the fluorescence spectra. Excimer emission from the ground amphiphile without TEG chains is retained after dissolution in water. The micelles are stable in water because hydrophilic dendrons surround the hydrophobic luminophores. By contrast, when water is added to a ground amphiphile having TEG substituents, fragmented supramolecular fibers with the same molecular arrangement as the initial supramolecular fibers are observed, because fragmented fibers are thermodynamically preferable to micelles as the hydrophobic arrays of fluorophores are covered with hydrophilic TEG chains. This leads to the recovery of the initial fluorescent properties for the latter amphiphile. These supramolecular fibers can be used as practical mechanosensors to detect forces at the mesoscale.

FMO-guided design of darunavir analogs as HIV-1 protease inhibitors.

The prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment molecular orbital (FMO) method and structure-based drug design to create DRV analogs. Using combinatorial programming, we generated novel analogs freely accessible via an on-the-cloud mode implemented in Google Colab, Combined Analog generator Tool (CAT). The designed analogs underwent cascade screening through molecular docking with HIV-1 PR wild-type and major mutations at the active site. Molecular dynamics (MD) simulations confirmed the assess ligand binding and susceptibility of screened designed analogs. Our findings indicate that the three designed analogs guided by FMO, 19-0-14-3, 19-8-10-0, and 19-8-14-3, are superior to DRV and have the potential to serve as efficient PR inhibitors. These findings demonstrate the effectiveness of our approach and its potential to be used in further studies for developing new antiretroviral drugs.

Machine learning-guided design of potent darunavir analogs targeting HIV-1 proteases: A computational approach for antiretroviral drug discovery.

In the pursuit of novel antiretroviral therapies for human immunodeficiency virus type-1 (HIV-1) proteases (PRs), recent improvements in drug discovery have embraced machine learning (ML) techniques to guide the design process. This study employs ensemble learning models to identify crucial substructures as significant features for drug development. Using molecular docking techniques, a collection of 160 darunavir (DRV) analogs was designed based on these key substructures and subsequently screened using molecular docking techniques. Chemical structures with high fitness scores were selected, combined, and one-dimensional (1D) screening based on beyond Lipinski's rule of five (bRo5) and ADME (absorption, distribution, metabolism, and excretion) prediction implemented in the Combined Analog generator Tool (CAT) program. A total of 473 screened analogs were subjected to docking analysis through convolutional neural networks scoring function against both the wild-type (WT) and 12 major mutated PRs. DRV analogs with negative changes in binding free energy ( ΔΔ G bind ) compared to DRV could be categorized into four attractive groups based on their interactions with the majority of vital PRs. The analysis of interaction profiles revealed that potent designed analogs, targeting both WT and mutant PRs, exhibited interactions with common key amino acid residues. This observation further confirms that the ML model-guided approach effectively identified the substructures that play a crucial role in potent analogs. It is expected to function as a powerful computational tool, offering valuable guidance in the identification of chemical substructures for synthesis and subsequent experimental testing.

Manipulation of photosynthetic energy transfer by vibrational strong coupling.

Uncovering the mystery of efficient and directional energy transfer in photosynthetic organisms remains a critical challenge in quantum biology. Recent experimental evidence and quantum theory developments indicate the significance of quantum features of molecular vibrations in assisting photosynthetic energy transfer, which provides the possibility of manipulating the process by controlling molecular vibrations. Here, we propose and theoretically demonstrate efficient manipulation of photosynthetic energy transfer by using vibrational strong coupling between the vibrational state of a Fenna-Matthews-Olson (FMO) complex and the vacuum state of an optical cavity. Specifically, based on a full-quantum analytical model to describe the strong coupling effect between the optical cavity and molecular vibration, we realize efficient manipulation of energy transfer efficiency (from 58% to 92%) and energy transfer time (from 20 to 500 ps) in one branch of FMO complex by actively controlling the coupling strength and the quality factor of the optical cavity under both near-resonant and off-resonant conditions, respectively. Our work provides a practical scenario to manipulate photosynthetic energy transfer by externally interfering molecular vibrations via an optical cavity and a comprehensible conceptual framework for researching other similar systems.

Latrunculin resistance mechanism of non-conventional actin NAP1 uncovered by molecular dynamics simulations.

Monomeric G-actin polymerizes into F-actin to perform various cellular functions. Actin depolymerization drugs, such as latrunculin-A (Lat-A), inhibit filament formation and disrupt the cytoskeleton. Interestingly, the green algae Chlamydomonas alternatively produces a non-conventional actin, NAP1, that responds to inhibition by latrunculin. However, the molecular mechanism underlying latrunculin resistance of NAP1 remains unclear because of the difficulty due to its low in vitro polymerizability. Instead of biochemical experiments, we performed molecular dynamics (MD) simulations to investigate whether NAP1 has a lower affinity for Lat-A than the conventional actins. Our phylogenetic comparison of the binding free energies shows that Lat-A is evolutionarily optimized for skeletal muscles. By decomposing the binding free energy into each amino acid residue, we found that some residues in NAP1 play an important role in latrunculin resistance, suggesting that the primary mechanism of latrunculin resistance is the loss of affinity for Lat-A due to substitutions. In conclusion, our binding-free-energy calculations using MD simulations provide the critical insight that loss of affinity is the direct mechanism of latrunculin resistance.

Pathological mutations promote proteolysis of mitochondrial tRNA-specific 2-thiouridylase 1 (MTU1) via mitochondrial caseinolytic peptidase (CLPP).

MTU1 controls intramitochondrial protein synthesis by catalyzing the 2-thiouridine modification of mitochondrial transfer RNAs (mt-tRNAs). Missense mutations in the MTU1 gene are associated with life-threatening reversible infantile hepatic failure. However, the molecular pathogenesis is not well understood. Here, we investigated 17 mutations associated with this disease, and our results showed that most disease-related mutations are partial loss-of-function mutations, with three mutations being particularly severe. Mutant MTU1 is rapidly degraded by mitochondrial caseinolytic peptidase (CLPP) through a direct interaction with its chaperone protein CLPX. Notably, knockdown of CLPP significantly increased mutant MTU1 protein expression and mt-tRNA 2-thiolation, suggesting that accelerated proteolysis of mutant MTU1 plays a role in disease pathogenesis. In addition, molecular dynamics simulations demonstrated that disease-associated mutations may lead to abnormal intermolecular interactions, thereby impairing MTU1 enzyme activity. Finally, clinical data analysis underscores a significant correlation between patient prognosis and residual 2-thiolation levels, which is partially consistent with the AlphaMissense predictions. These findings provide a comprehensive understanding of MTU1-related diseases, offering prospects for modification-based diagnostics and novel therapeutic strategies centered on targeting CLPP.

Synthesis and biological evaluation of 2'-hydroxychalcone derivatives as AMPK activators.

A series of 2'-hydroxychalcone derivatives with various substituents on B-ring were synthesized and evaluated for AMP-activated protein kinase (AMPK) activation activity in podocyte cells. The results displayed that hydroxy, methoxy and methylenedioxy groups on B-ring could enhance the activitiy better than O-saturated alkyl, O-unsaturated alkyl or other alkoxy groups. Compounds 27 and 29 possess the highest fold change of 2.48 and 2.73, respectively, which were higher than those of reference compound (8) (1.28) and metformin (1.88). Compounds 27 and 29 were then subjected to a concentration-response study to obtain the EC50 values of 2.0 and 4.8 µM, respectively and MTT assays also showed that cell viability was not influenced by the exposure of podocytes to compounds 27 and 29 at concentrations up to 50 µM. In addition, compound 27 was proved to activate AMPK via calcium/calmodulin-dependent protein kinase kinase ß (CaMKKß)-dependent pathway without affecting intracellular calcium levels. The computational study showed that the potent compounds exhibited stronger ligand-binding strength to CaMKKß, particularly compounds 27 (-8.4 kcal/mol) and 29 (-8.0 kcal/mol), compared to compound 8 (-7.5 kcal/mol). Fragment molecular orbital (FMO) calculation demonstrated that compound 27 was superior to compound 29 due to the presence of methyl group, which amplified the binding by hydrophobic interactions. Therefore, compound 27 would represent a promising AMPK activator for further investigation of the treatment of diabetes and diabetic nephropathy.

Structural and thermodynamic insights into antibody light chain tetramer formation through 3D domain swapping.

Overexpression of antibody light chains in small plasma cell clones can lead to misfolding and aggregation. On the other hand, the formation of amyloid fibrils from antibody light chains is related to amyloidosis. Although aggregation of antibody light chain is an important issue, atomic-level structural examinations of antibody light chain aggregates are sparse. In this study, we present an antibody light chain that maintains an equilibrium between its monomeric and tetrameric states. According to data from X-ray crystallography, thermodynamic and kinetic measurements, as well as theoretical studies, this antibody light chain engages in 3D domain swapping within its variable region. Here, a pair of domain-swapped dimers creates a tetramer through hydrophobic interactions, facilitating the revelation of the domain-swapped structure. The negative cotton effect linked to the ß-sheet structure, observed around 215 nm in the circular dichroism (CD) spectrum of the tetrameric variable region, is more pronounced than that of the monomer. This suggests that the monomer contains less ß-sheet structures and exhibits greater flexibility than the tetramer in solution. These findings not only clarify the domain-swapped structure of the antibody light chain but also contribute to controlling antibody quality and advancing the development of future molecular recognition agents and drugs.