A machine learning potential construction based on radial distribution function sampling.

Sampling reference data is crucial in machine learning potential (MLP) construction. Inadequate coverage of local configurations in reference data may lead to unphysical behaviors in MLP-based molecular dynamics (MLP-MD) simulations. To address this problem, this study proposes a new on-the-fly reference data sampling method called radial distribution function (RDF)-based data sampling for MLP construction. This method detects and extracts anomalous structures from the trajectories of MLP-MD simulations by focusing on the shapes of RDFs. The detected structures are added to the reference data to improve the accuracy of the MLP. This method allows us to realize a reasonable MLP construction for liquid water with minimal additional data. We prepare data from an H2O molecular cluster system and verify whether the constructed MLPs are practical for bulk water systems. MLP-MD simulations without RDF-based data sampling show unphysical behaviors, such as atomic collisions. In contrast, after applying this method, we obtain MLP-MD trajectories with features, such as RDF shapes and angle distributions, that are comparable to those of ab initio MD simulations. Our simulation results demonstrate that the RDF-based data sampling approach is useful for constructing MLPs that are robust to extrapolations from molecular cluster systems to bulk systems without any specialized know-how.

Why is Dimeric 3D Domain Swapping in Antibody Light Chains Missing from the Solution? Atomistic Insights Mechanisms.

Misfolding of antibody light chains can lead to systemic light chain amyloidosis, which is associated with misfolding and aggregation. The antibody light chain may engage in 3D domain swapping within the variable region (#4VL) through hydrogen bonding (HB) interactions, potentially forming the tetramer, as revealed in solution and crystal structures. However, the 3D-domain swapping (3D-DS) dimers could not be detected experimentally. This study investigates the absence of 3D-DS using computational approaches, focusing on structural dynamics, solvation effects, and stability relevant to the loss of 3D-DS. Microscale molecular dynamics simulations of #4VL and 3D-DS confirm that native HB interactions are essential to maintain ß-sheet structures in both #4VL and 3D-DS. A flickering native HB interaction in the 3D-DS system, caused by repulsive interaction with water molecules in the hydrophobic region, leads to intramolecular breathing motions and oligomerization in another 3D-DS. Structural dynamics of the 3D-DS dimer in long-run simulations were analyzed using the newly developed integrated solvation-based principal component analysis (3D-RISM/PCA) and density-based spatial clustering of applications with noise, confirm that if the 3D-DS cannot form the tetramer within the breathing motion process, the 3D-DS will collapse. This finding provides insights into why the 3D-DS dimer is missing from the solution and can be used to design and develop 3D-DS in other antibodies.

Ribosome Tunnel Environment Drives the Formation of α-Helix during Cotranslational Folding.

Protein conformations in cells are not solely determined by amino acid sequences; they also depend on cellular environments. For instance, the ribosome tunnel induces its specific α-helix formation during cotranslational folding. Owing to the link between these temporally α-helix and biological functions, the mechanism of α-helix formation inside the ribosome tunnel has been previously explored. Consequently, the conformational restrictions of the tunnel were considered one of the driving forces of α-helix formation. Conversely, the ribosomal tunnel environment, including its chemical properties, appears to influence the α-helix formation. However, a comprehensive analysis of the ribosome tunnel environment's impact on the α-helix formation has not been conducted yet due to challenges in experimentally controlling it. Therefore, as a new computational approach, we proposed a ribosome environment-mimicking model (REMM) based on the radius and components of the experimentally determined ribosome tunnel structures. Using REMM, we assessed the impact of the ribosome tunnel environment on α-helix formation. Herein, we employed carbon nanotubes (CNT) as a reference model alongside REMM because CNT reproduce conformational restrictions rather than the ribosome tunnel environment. Quantitatively, the ability to reproduce the α-helix of nascent peptides in the experimental structure was compared between the CNT and REMM using enhanced all-atom molecular dynamics simulations. Consequently, the REMM more accurately reproduced the α-helix of the nascent peptides than the CNT, highlighting the significance of the ribosome tunnel environment in α-helix formation. Additionally, we analyzed the properties of the peptide inside each model to reveal the mechanism of ribosome tunnel-specific α-helix formation. Consequently, we revealed that the chemical diversities of the tunnel are essential for the formation of backbone-to-backbone hydrogen bonds in the peptides. In conclusion, the ribosome tunnel environment, with the diverse chemical properties, drives its specific α-helix formation. By proposing REMM, we newly provide the technical basis for investigating the protein conformations in various cellular environments.

Rational Design of Cyclopentadiene-Based Super- and Hyperacids Based on Aromaticity.

The design and synthesis of neutral organic superacids have been of interest recently due to their vast applications in chemistry and material sciences, for example, olefinic polymerization, isolation of highly reactive short-lived cations, etc. Cyclopentadiene behaves as a mild organic acid, producing a stable conjugate base by gaining aromaticity and conjugation after deprotonation. To stabilize conjugate bases of organic acids to show superacidities and hyperacidities, we considered aromatic phenyl substituents with cyclopentadiene (mono-, di-, and triphenyl-substituted cyclopentadiene and their cyano derivatives). The MP2, DFT (B3LYP, M06-2X), and CBS-QB3 methods were used to calculate the gas-phase proton affinities of the parent cyclopentadiene, and the DFT methods were chosen for the substituted cyclopentadiene as they yield an experimental proton affinity of cyclopentadiene of 253.66 kcal/mol (Expt. 253.6 ± 1.3 kcal/mol). The stable trisubstituted cyclopentadiene derivative shows gas-phase enthalpies of deprotonation (ΔHacid) of 245 and 239 kcal/mol with DFT B3LYP and M06-2X methods, respectively, with values in the range of hyperacidity. Some of the tautomers of cyclopentadiene derivatives show hyperacidity, with proton affinity values of 205-240 kcal/mol. Triphenyl-substituted cyclopentadiene behaves as a moderate acid but transforms into a superacid after replacing the phenyl group with nitrobenzene, which is a stronger acid than H2SO4 (ΔHacid = 298 kcal/mol). The nucleus-independent chemical shift (NICS) shows the extent of conjugation in the derivatives of cyclopentadienyl anions after deprotonation, which affects the stabilities of conjugate bases, i.e., the acidities of the protonated species. The calculated harmonic oscillator model of aromaticity and NICS indices reveal that the stability of conjugate bases as well as their acidities increase with increasing aromaticity of cyclopentadiene rings after deprotonation in all molecules.

Calcium Binding Mechanism in TAT Rhodopsin.

TAT rhodopsin binds Ca2+ near the Schiff base region, which accompanies deprotonation of the Schiff base. This paper reports the Ca2+-free and Ca2+-bound structures of TAT rhodopsin by molecular dynamics (MD) simulation launched from AlphaFold structures. In the Ca2+-bound TAT rhodopsin, Ca2+ is directly coordinated by eight oxygen atoms, four oxygens of the side chains of E54 and D227, and four oxygens of water molecules. E54 is not involved in the hydrogen-bonding network of the Ca2+-free TAT rhodopsin, while flipping motion of E54 allows Ca2+ binding to TAT rhodopsin with deformation of helices observed by FTIR spectroscopy. The hydrogen-bonding network plays a crucial role in maintaining the Ca2+ binding, as mutations of E54, Y55, R79, Y200, E220, and D227 abolished the binding. Only T82V exhibited the Ca2+ binding like the wild type among the mutants in this study. The molecular mechanism of Ca2+ binding is discussed based on the present computational and experimental analysis.

Real-time observation of a metal complex-driven reaction intermediate using a porous protein crystal and serial femtosecond crystallography.

Determining short-lived intermediate structures in chemical reactions is challenging. Although ultrafast spectroscopic methods can detect the formation of transient intermediates, real-space structures cannot be determined directly from such studies. Time-resolved serial femtosecond crystallography (TR-SFX) has recently proven to be a powerful method for capturing molecular changes in proteins on femtosecond timescales. However, the methodology has been mostly applied to natural proteins/enzymes and limited to reactions promoted by synthetic molecules due to structure determination challenges. This work demonstrates the applicability of TR-SFX for investigations of chemical reaction mechanisms of synthetic metal complexes. We fix a light-induced CO-releasing Mn(CO)3 reaction center in porous hen egg white lysozyme (HEWL) microcrystals. By controlling light exposure and time, we capture the real-time formation of Mn-carbonyl intermediates during the CO release reaction. The asymmetric protein environment is found to influence the order of CO release. The experimentally-observed reaction path agrees with quantum mechanical calculations. Therefore, our demonstration offers a new approach to visualize atomic-level reactions of small molecules using TR-SFX with real-space structure determination. This advance holds the potential to facilitate design of artificial metalloenzymes with precise mechanisms, empowering design, control and development of innovative reactions.

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.

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.

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.

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.

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.

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.

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.

[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.

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.

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.