The unfolded features on the synchronized fashion of gut microbiota and Drynaria rhizome against obesity via integrated pharmacology

Drynaria rhizome (DR) is used as a natural remedy to ameliorate obesity (OB) in East Asia; in parallel, the gut microbiota (GM) might exert a positive impact on OB through their metabolites. This study elucidates the orchestrated effects of DR and GM on OB. DR-GM, - a key signaling pathway-target-metabolite (DGSTM) networks were used to unveil the relationship between DR and GM, and Molecular Docking Test (MDT) and Density Functional Theory (DFT) were adopted to underpin the uppermost molecules. The NR1H3 (target) - 3-Epicycloeucalenol (ligand), and PPARG (target) - Clionasterol (ligand) conjugates from DR, FABP3 (target) - Ursodeoxycholic acid, FABP4 (target) - Lithocholic acid (ligand) or Deoxycholic acid (ligand), PPARA (target) - Equol (ligand), and PPARD (target) - 2,3-Bis(3,4-dihydroxybenzyl)butyrolactone (ligand) conjugates from GM formed the most stable conformers via MDT and DFT. Overall, these findings suggest that DR-GM might be a promising ameliorator on PPAR signaling pathway against OB.

Enhancing colloidal stability of nanodiamond via surface modification with dendritic molecules for optical sensing in physiological environments

Pre-treatment of diamond surface in low-temperature plasma for oxygenation and in acids for carboxylation was hypothesized to promote the branching density of the hyperbranched glycidol polymer. This was expected to increase the homogeneity of the branching level and suppress interactions with proteins. As a result, composite nanodiamonds with reduced hydrodynamic diameters that are maintained in physiological environments were anticipated. Surfaces of 140-nm-sized nanodiamonds were functionalized with oxygen and carboxyl groups for grafting of hyperbranched dendritic polyglycerol via anionic ring-opening polymerization of glycidol. The modification was verified with Fourier-transform infrared spectroscopy and X-ray photoelectron spectroscopy. Dynamic light scattering investigated colloidal stability in pH-diverse (2-12) solutions, concentrated phosphate-buffered saline, and cell culture media. Thermogravimetric analysis of nanodiamonds-protein incubations examined non-specific binding. Fluorescence emission was tested across pH conditions. Molecular dynamics simulations modeled interparticle interactions in ionic solutions. The hyperbranched polyglycerol grafting increased colloidal stability of nanodiamonds across diverse pH, high ionic media like 10 × concentrated phosphate-buffered saline, and physiological media like serum and cell culture medium. The hyperbranched polyglycerol suppressed non-specific protein adsorption while maintaining intensive fluorescence of nanodiamonds regardless of pH. Molecular modelling indicated reduced interparticle interactions in ionic solutions correlating with the improved colloidal stability.

Cysteine hyperoxidation rewires communication pathways in the nucleosome and destabilizes the dyad

Gene activity is tightly controlled by reversible chemical modifications called epigenetic marks, which are of various types and modulate gene accessibility without affecting the DNA sequence. Despite an increasing body of evidence demonstrating the role of oxidative-type modifications of histones in gene expression regulation, there remains a complete absence of structural data at the atomistic level to understand the molecular mechanisms behind their regulatory action. Owing to μs time-scale MD simulations and protein communication networks analysis, we describe the impact of histone H3 hyperoxidation (i.e., S-sulfonylation) on the nucleosome core particle dynamics. Our results reveal the atomic-scale details of the intrinsic structural networks within the canonical histone core and their perturbation by hyperoxidation of the histone H3 C110. We show that this modification involves local rearrangements of the communication networks and destabilizes the dyad, and that one modification is enough to induce a maximal structural signature. Our results suggest that cysteine hyperoxidation in the nucleosome core particle might favor its disassembly.

AlloViz: A tool for the calculation and visualisation of protein allosteric communication networks

Allostery, the presence of functional interactions between distant parts of proteins, is a critical concept in the field of biochemistry and molecular biology, particularly in the context of protein function and regulation. Understanding the principles of allosteric regulation is essential for advancing our knowledge of biology and developing new therapeutic strategies. This paper presents AlloViz, an open-source Python package designed to quantitatively determine, analyse, and visually represent allosteric communication networks on the basis of molecular dynamics (MD) simulation data. The software integrates well-known techniques for understanding allosteric properties simplifying the process of accessing, rationalising, and representing protein allostery and communication routes. It overcomes the inefficiency of having multiple methods with heterogeneous implementations and showcases the advantages of using MD simulations and multiple replicas to obtain statistically sound information on protein dynamics; it also enables the calculation of "consensus-like" scores aggregating methods that consider multiple structural aspects of allosteric networks. We demonstrate the features of AlloViz on two proteins: β-arrestin 1, a key player for regulating G protein-coupled receptor (GPCR) signalling, and the protein tyrosine phosphatase 1B, an important pharmaceutical target for allosteric inhibitors. The software includes comprehensive documentation and examples, tutorials, and a user-friendly graphical interface.

Elucidating the role of Rhodiola rosea L. in sepsis-induced acute lung injury via network pharmacology: emphasis on inflammatory response, oxidative stress, and the PI3K-AKT pathway

CONTEXT

Sepsis-induced acute lung injury (ALI) is associated with high morbidity and mortality. Rhodiola rosea L. (Crassulaceae) (RR) and its extracts have shown anti-inflammatory, antioxidant, immunomodulatory, and lung-protective effects.

OBJECTIVE

This study elucidates the molecular mechanisms of RR against sepsis-induced ALI.

MATERIALS AND METHODS

The pivotal targets of RR against sepsis-induced ALI and underlying mechanisms were revealed by network pharmacology and molecular docking. Human umbilical vein endothelial cells (HUVECs) were stimulated by 1 μg/mL lipopolysaccharide for 0.5 h and treated with 6.3, 12.5, 25, 50, 100, and 200 μg/mL RR for 24 h. Then, the lipopolysaccharide-stimulated HUVECs were subjected to cell counting kit-8 (CCK-8), enzyme-linked immunosorbent, apoptosis, and Western blot analyses. C57BL/6 mice were divided into sham, model, low-dose (40 mg/kg), mid-dose (80 mg/kg), and high-dose (160 mg/kg) RR groups. The mouse model was constructed through caecal ligation and puncture, and histological, apoptosis, and Western blot analyses were performed for further validation.

RESULTS

We identified six hub targets (MPO, HRAS, PPARG, FGF2, JUN, and IL6), and the PI3K-AKT pathway was the core pathway. CCK-8 assays showed that RR promoted the viability of the lipopolysaccharide-stimulated HUVECs [median effective dose (ED50) = 18.98 μg/mL]. Furthermore, RR inhibited inflammation, oxidative stress, cell apoptosis, and PI3K-AKT activation in lipopolysaccharide-stimulated HUVECs and ALI mice, which was consistent with the network pharmacology results.

DISCUSSION AND CONCLUSION

This study provides foundational knowledge of the effective components, potential targets, and molecular mechanisms of RR against ALI, which could be critical for developing targeted therapeutic strategies for sepsis-induced ALI.

Ionotropic purinergic receptor 7 (P2X7) channel structure and pharmacology provides insight regarding non-nucleotide agonism

P2X7 is a member of the Ionotropic Purinergic Receptor (P2X) family. The P2X family of receptors is composed of seven (P2X1-7), ligand-gated, nonselective cation channels. Changes in P2X expression have been reported in multiple disease models. P2Xs have large complex extracellular domains that function as receptors for a variety of ligands, including endogenous and synthetic agonists and antagonists. ATP is the canonical agonist. ATP affinity ranges from nanomolar to micromolar for most P2XRs, but P2X7 has uniquely poor ATP affinity. In many physiological settings, it may be difficult to achieve the millimolar extracellular ATP concentrations needed for P2X7 channel activation; however, channel function is implicated in pain sensation, immune cell function, cardiovascular disease, cancer, and osteoporosis. Multiple high-resolution P2X7 structures have been solved in apo-, ATP-, and antagonist-bound states. P2X7 structural data reveal distinct allosteric and orthosteric antagonist-binding sites. Both allosteric and orthosteric P2X7 antagonists are well documented to inhibit ATP-evoked channel current. However, a growing body of evidence supports P2X7 activation by non-nucleotide agonists, including extracellular histone proteins and human cathelicidin-derived peptides (LL-37). Interestingly, P2X7 non-nucleotide agonism is not inhibited by allosteric antagonists, but is inhibited by orthosteric antagonists. Herein, we review P2X7 function with a focus on the efficacy of available pharmacology on P2X7 channel current activation by non-nucleotide agonists in effort to understand agonist/antagonist efficacy, and consider the impact of these data on the current understanding of P2X7 in physiology and disease given these limitations of P2X7-selective antagonists and incomplete knockout mouse models.

Development of novel ALOX15 inhibitors combining dual machine learning filtering and fragment substitution optimisation approaches, molecular docking and dynamic simulation methods

The oxidation of unsaturated lipids, facilitated by the enzyme Arachidonic acid 15-lipoxygenase (ALOX15), is an essential element in the development of ferroptosis. This study combined a dual-score exclusion strategy with high-throughput virtual screening, naive Bayesian and recursive partitioning machine learning models, the already established ALOX15 inhibitor i472, and a docking-based fragment substitution optimisation approach to identify potential ALOX15 inhibitors, ultimately leading to the discovery of three FDA-approved drugs that demonstrate optimal inhibitory potential against ALOX15. Through fragment substitution-based optimisation, seven new inhibitor structures have been developed. To evaluate their practicality, ADMET predictions and molecular dynamics simulations were performed. In conclusion, the compounds found in this study provide a novel approach to combat conditions related to ferroptosis-related injury by inhibiting ALOX15.

Putative mechanism of a multivitamin treatment against insulin resistance

Insulin resistance is caused by the abnormal secretion of proinflammatory cytokines in adipose tissue, which is induced by an increase in lipid accumulation in adipocytes, hepatocytes, and myocytes. The inflammatory pathway involves multiple targets such as nuclear factor kappa B, inhibitor of nuclear factor κ-B kinase, and mitogen-activated protein kinase. Vitamins are micronutrients with anti-inflammatory activities that have unclear mechanisms. The present study aimed to describe the putative mechanisms of vitamins involved in the inflammatory pathway of insulin resistance. The strategy to achieve this goal was to integrate data mining and analysis, target prediction, and molecular docking simulation calculations to support our hypotheses. Our results suggest that the multitarget activity of vitamins A, B1, B2, B3, B5, B6, B7, B12, C, D3, and E inhibits nuclear factor kappa B and mitogen-activated protein kinase, in addition to vitamins A and B12 against inhibitor of nuclear factor κ-B kinase. The findings of this study highlight the pharmacological potential of using an anti-inflammatory and multitarget treatment based on vitamins and open new perspectives to evaluate the inhibitory activity of vitamins against nuclear factor kappa B, mitogen-activated protein kinase, and inhibitor of nuclear factor κ-B kinase in an insulin-resistant context.

Do selectivity filter carbonyls in K+ channels flip away from the pore? Two-dimensional infrared spectroscopy study

Molecular dynamics simulations revealed that the carbonyls of the Val residue in the conserved selectivity filter sequence TVGTG of potassium ion channels can flip away from the pore to form hydrogen bonds with the network of water molecules residing behind the selectivity filter. Such a configuration has been proposed to be relevant for C-type inactivation. Experimentally, X-ray crystallography of the KcsA channel admits the possibility that the Val carbonyls can flip, but it cannot decisively confirm the existence of such a configuration. In this study, we combined molecular dynamics simulations and line shape theory to design two-dimensional infrared spectroscopy experiments that can corroborate the existence of the selectivity filter configuration with flipped Val carbonyls. This ability to distinguish between flipped and unflipped carbonyls is based on the varying strength of the electric field inside and outside the pore, which is directly linked to carbonyl stretching frequencies that can be resolved using infrared spectroscopy.

Wheat gliadin/xanthan gum intermolecular complexes: Interaction mechanism and structural characterization

In this study, the interactions between wheat gliadin (GL) and xanthan gum (XG) were investigated to design new systems with potential applications as a gluten-free substitute product. Combining spectral with morphological and molecular docking methods allowed the establishment of the complexation mechanism between globular hydrophobic GL and the hydrophilic XG with an extended and partially disordered backbone. GL maintains intact its hydrophobic core even at high GL/XG ratios and organizes into small aggregate-type assemblies. The stable and uniform complexes have a low GL content, based on intermolecular hydrogen bonds and hydrophobic interactions. The GL/XG combining ratio influences the size, structure and interaction mechanism of the microparticles. The preferred sites of interaction and the binding affinities were determined by molecular docking on GL libraries and XG models. This research may provide significant knowledge for the development of low-GL wheat food products using a dietary fiber polysaccharide as a functional compound.

Design of NiCoP nanorod loaded on cocoon carbon substrate and its non-metal doping for efficient hydrogen evolution

The quest for effective and sustainable electrocatalysts for hydrogen evolution is crucial in advancing the widespread use of H2. In this study, we utilized silkworm cocoons as the source material to produce porous N-doped carbon (PNCC) substrates through a process involving degumming and annealing. Subsequently, NiCoP nanorod (NiCoP@PNCC) is deposited onto the substrates via a simple impregnation and calcination method to enhance the catalytic performance for the hydrogen evolution reaction (HER). The optimal spacing between the silk fibers of PNCC facilitates longitudinal growth, increases the active surface area, and balances the adsorption and desorption of reaction intermediates, thereby accelerating HER kinetics. Consequently, NiCoP@PNCC demonstrates impressive performance, with 44 mV overpotential to achieve a current density of 10 mA cm-2. Additionally, density functional theory (DFT) calculations reveal that the electronic structure and energy band of NiCoP@PNCC can be modified through the doping of elements such as B, C, N, O, F, and S. In addition, with the electronegativity enhancement of the doping elements, the interaction between Co atoms in NiCoP@PNCC and O atoms in adsorbed H2O molecules gradually enhanced, which is conducive to the dissociation of water in alkaline solution. This research introduces a novel approach for fine-tuning the catalytic activity of transition metal phosphides.

Novel alloxazine analogues: design, synthesis, and antitumour efficacy enhanced by kinase screening, molecular docking, and ADME studies

This study describes the development of novel alloxazine analogues as potent antitumor agents with enhanced selectivity for tumour cells. Twenty-nine out of 45 newly compounds were investigated in vitro for their growth inhibitory activities, against two human tumour cell lines, namely, the human T-cell acute lymphoblastoid leukaemia cell line (CCRF-HSB-2) and human oral epidermoid carcinoma cell line (KB), and the antitumor agent "Ara-C" was used as a positive reference in this investigation. Compounds 9e and 10J were the highest among their analogues, against both tumour cell lines (CCRF-HSB-2 and KB). Correlation analyses demonstrated a strong relationship between the IC50 values and AutoDock binding free energy or calculated inhibition (Ki). The study delves into structure-activity relationships (SARs) through advanced modelling tools integrated with structure-based drug design (SBDD) using GOLD 5.2.2, AutoDock 4.2, and Accelrys Discovery Studio 3.5. Physicochemical properties, pharmacokinetics, drug-likeness, and toxicity predictions of the most potent alloxazine derivatives were conducted using ProTox-II and Swiss ADME for effective antitumor agents with improved selectivity.

Development of potent and effective SARS-CoV-2 main protease inhibitors based on maleimide analogs for the potential treatment of COVID-19

In the present work, we report a new series of potent SARS-CoV-2 Main Protease (Mpro) inhibitors based on maleimide derivatives. The inhibitory activities were tested in an enzymatic assay using recombinant Mpro (3CL Protease from coronavirus SARS-CoV-2). Within the set of new Mpro inhibitors, 6e demonstrated the highest activity in the enzymatic assay with an IC50 value of 8.52 ± 0.44 µM. The IC50 value for Nirmatrelvir (PF-07321332, used as a reference) was 0.84 ± 0.37 µM. The cytotoxic properties were determined in the MTT assay using MRC-5 and HEK-293 cell lines. In the course of the investigation, we found that the newly obtained maleimide derivatives are not substantially cytotoxic (IC50 values for most compounds were above 200 µM).

Novel hybrids of 1,2,3-triazole-benzoxazole: design, synthesis, and assessment of DprE1 enzyme inhibitors using fluorometric assay and computational analysis

Decaprenylphosphoryl-β-D-ribose-oxidase (DprE1), a subunit of the essential decaprenylphosphoribose-2'-epimerase, plays a crucial role in the synthesis of cell wall arabinan components in mycobacteria, including the pathogen responsible for tuberculosis, Mycobacterium tuberculosis. In this study, we designed, synthesised, and evaluated 15 (BOK-1-BOK-10 and BOP-1-BOP-5) potential inhibitors of DprE1 from a series of 1,2,3-triazole ligands using a validated DprE1 inhibition assay. Two compounds, BOK-2 and BOK-3, demonstrated significant inhibition with IC50 values of 2.2 ± 0.1 and 3.0 ± 0.6 μM, respectively, whereas the standard drug (TCA-1) showed inhibition at 3.0 ± 0.2 μM. Through molecular modelling and dynamic simulations, we explored the structural relationships between selected 1,2,3-triazole compounds and DprE1, revealing key features for effective drug-target interactions. This study introduces a novel approach for designing ligands against DprE1, offering a potential therapeutic strategy for tuberculosis treatment.

Computational fragment-based drug design of potential Glo-I inhibitors

In this study, a fragment-based drug design approach, particularly de novo drug design, was implemented utilising three different crystal structures in order to discover new privileged scaffolds against glyoxalase-I enzyme as anticancer agents. The fragments were evoluted to indicate potential inhibitors with high receptor affinities. The resulting compounds were served as a benchmark for choosing similar compounds from the ASINEX® database by applying different computational ligand-based drug design techniques. Afterwards, the selection of potential hits was further aided by various structure-based approaches. Then, 14 compounds were purchased, and tested in vitro against Glo-I enzyme. Of the tested 14 hits, the biological screening results showed humble activities where the percentage of Glo-I inhibition ranged from 0-18.70 %. Compound 19 and compound 28, whose percentage of inhibitions are 18.70 and 15.80%, respectively, can be considered as hits that need further optimisation in order to be converted into lead-like compounds.

Synthesis, carbonic anhydrase inhibition studies and modelling investigations of phthalimide-hydantoin hybrids

A novel series of hydantoins incorporating phthalimides has been synthesised by condensation of activated phthalimides with 1-aminohydantoin and investigated for their inhibitory activity against a panel of human (h) carbonic anhydrase (CA, EC 4.2.1.1): the cytosolic isoforms hCA I, hCA II, and hCA VII, secreted isoform hCA VI, and the transmembrane hCA IX, by a stopped-flow CO2 hydrase assay. Although all newly developed compounds were totally inactive on hCA I and mainly ineffective towards hCA II, they generally exhibited moderate repressing effects on hCA VI, VII, and IX with KIs values in the submicromolar to micromolar ranges. The salts 3a and 3b, followed by derivative 5, displayed the best inhibitory activity of all the evaluated compounds and their binding mode was proposed in silico. These compounds can also be considered interesting starting points for the development of novel pharmacophores for this class of enzyme inhibitors.

Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities

Molecular docking is a widely used technique in drug discovery to predict the binding mode of a given ligand to its target. However, the identification of the near-native binding pose in docking experiments still represents a challenging task as the scoring functions currently employed by docking programs are parametrized to predict the binding affinity, and, therefore, they often fail to correctly identify the ligand native binding conformation. Selecting the correct binding mode is crucial to obtaining meaningful results and to conveniently optimizing new hit compounds. Deep learning (DL) algorithms have been an area of a growing interest in this sense for their capability to extract the relevant information directly from the protein-ligand structure. Our review aims to present the recent advances regarding the development of DL-based pose selection approaches, discussing limitations and possible future directions. Moreover, a comparison between the performances of some classical scoring functions and DL-based methods concerning their ability to select the correct binding mode is reported. In this regard, two novel DL-based pose selectors developed by us are presented.

Elucidating molecular mechanism and chemical space of chalcones through biological networks and machine learning approaches

We developed a bio-cheminformatics method, exploring disease inhibition mechanisms using machine learning-enhanced quantitative structure-activity relationship (ML-QSAR) models and knowledge-driven neural networks. ML-QSAR models were developed using molecular fingerprint descriptors and the Random Forest algorithm to explore the chemical spaces of Chalcones inhibitors against diverse disease properties, including antifungal, anti-inflammatory, anticancer, antimicrobial, and antiviral effects. We generated and validated robust machine learning-based bioactivity prediction models (https://github.com/RatulChemoinformatics/QSAR) for the top genes. These models underwent ROC and applicability domain analysis, followed by molecular docking studies to elucidate the molecular mechanisms of the molecules. Through comprehensive neural network analysis, crucial genes such as AKT1, HSP90AA1, SRC, and STAT3 were identified. The PubChem fingerprint-based model revealed key descriptors: PubchemFP521 for AKT1, PubchemFP180 for SRC, PubchemFP633 for HSP90AA1, and PubchemFP145 and PubchemFP338 for STAT3, consistently contributing to bioactivity across targets. Notably, chalcone derivatives demonstrated significant bioactivity against target genes, with compound RA1 displaying a predictive pIC50 value of 5.76 against HSP90AA1 and strong binding affinities across other targets. Compounds RA5 to RA7 also exhibited high binding affinity scores comparable to or exceeding existing drugs. These findings emphasize the importance of knowledge-based neural network-based research for developing effective drugs against diverse disease properties. These interactions warrant further in vitro and in vivo investigations to elucidate their potential in rational drug design. The presented models provide valuable insights for inhibitor design and hold promise for drug development. Future research will prioritize investigating these molecules for mycobacterium tuberculosis, enhancing the comprehension of effectiveness in addressing infectious diseases.

In silico and in vivo analysis reveal impact of c-Myc tag in FMC63 scFv-CD19 protein interface and CAR-T cell efficacy

Anti-CD19 CAR-T cell therapy represents a breakthrough in the treatment of B-cell malignancies, and it is expected that this therapy modality will soon cover a range of solid tumors as well. Therefore, a universal cheap and sensitive method to detect CAR expression is of foremost importance. One possibility is the use of epitope tags such as c-Myc, HA or FLAG tags attached to the CAR extracellular domain, however, it is important to determine whether these tags can influence binding of the CAR with its target molecule. Here, we conducted in-silico structural modelling of an FMC63-based anti-CD19 single-chain variable fragment (scFv) with and without a c-Myc peptide tag added to the N-terminus portion and performed molecular dynamics simulation of the scFv with the CD19 target. We show that the c-Myc tag presence in the N-terminus portion does not affect the scFv's structural equilibrium and grants more stability to the scFv. However, intermolecular interaction potential (IIP) analysis reveals that the tag can approximate the complementarity-determining regions (CDRs) present in the scFv and cause steric impediment, potentially disturbing interaction with the CD19 protein. We then tested this possibility with CAR-T cells generated from human donors in a Nalm-6 leukemia model, showing that CAR-T cells with the c-Myc tag have overall worse antitumor activity, which was also observed when the tag was added to the C-terminus position. Ultimately, our results suggest that tag addition is an important aspect of CAR design and can influence CAR-T cell function, therefore its use should be carefully considered.

Databases of ligand-binding pockets and protein-ligand interactions

Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket-finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.

A novel ACE inhibitory peptide from Douchi hydrolysate: Stability, inhibition mechanism, and antihypertensive potential in spontaneously hypertensive rats

Angiotensin I-converting enzyme (ACE) regulates blood pressure through the renin-angiotensin system. Douchi, a traditional fermented soybean condiment, may have antihypertensive effects, but research on ACE inhibitory peptides from Douchi hydrolysates is limited. We hypothesized that enzymatic treatment could enhance ACE inhibitory peptide diversity and efficacy. We tested ten single enzymes and four combinations, finding pepsin-trypsin-chymotrypsin most effective. Hydrolysates were purified using Sephadex G-15 and reversed-phase HPLC, and peptides were identified via LC-MS/MS. Five peptides (LF, VVF, VGAW, GLFG, NGK) were identified, with VGAW as the most potent ACE inhibitor (IC50 46.6 ± 5.2 μM) showing excellent thermal and pH stability. Lineweaver-Burk plots confirmed competitive inhibition, and molecular docking revealed eight hydrogen bonds between VGAW and ACE. In hypertensive rats, VGAW significantly reduced blood pressure at 12.5, 25, and 50 mg/kg. These findings highlight Douchi as a source of ACE inhibitory peptides and suggest VGAW as a promising functional food ingredient.

Panicum maximum Jacq. mediated green synthesis of silver nanoparticles: synthesis, characterization, and biological activities supported by molecular docking

This study uses the aerial parts of Panicum maximum total extract (PMTE) to synthesize silver nanoparticles (AgNPs) in an environmentally friendly manner. TEM, SEM, FTIR, X-ray powder diffraction (XRD), Zeta potential, UV, and FTIR were used to characterize the green silver nanoparticles (PM-AgNPs). PM-AgNPs were evaluated as anticancer agents compared to (PMTE) against breast (MCF-7), lung (A549), and ovary adenocarcinoma (SKOV3) human tumour cells. The antibacterial activity of AgNPs was assessed against Staphylococcus aureus isolates. The PM-AgNPs had an absorbance of 418 nm, particle size of 15.18 nm, and zeta potential of -22.4 mV, ensuring the nanosilver's stability. XRD evaluated the crystallography nature of the formed PM-AgNPs. The cytotoxic properties of PM-AgNPs on MCF-7 and SKOV 3 were the strongest, with IC50s of 0.13 ± 0.015 and 3.5 ± 0.5 g/ml, respectively, as compared to A549 (13 ± 3.2 µg/mL). The increase in the apoptotic cells was 97.79 ± 1.61 and 96.6 ± 1.91% for MCF-7 and SKOV3 cell lines, respectively. PM-AgNPs were found to affect the membrane integrity and membrane permeability of 50 and 43.75% of the tested isolates, respectively. Also, PM-AgNPs have recorded a reduction in the biofilm formation of S. aurues. These results suggest using PM-AgNPs to treat breast and ovarian cancers.

Rapid detection of perfluorooctanoic acid by surface enhanced Raman spectroscopy and deep learning

Perfluorooctanoic acid (PFOA) has received increasing concerns in recent years due to its wide distribution and potential toxicity. Existing detection techniques of PFOA require complex pre-treatment, therefore often taking several hours. Here, we developed a rapid PFOA detection mode to detect approximate concentrations of PFOA (ranging from 10-15 to 10-3 mol/L) in deionized water, and detecting one sample takes only 20 min. The detection mode was achieved using a deep learning model trained by a large surface enhanced Raman spectra dataset, based on the agglomeration of PFOA with crystal violet. In addition, transfer learning approach was used to fine tune the model, the fine-tuned model was generalizable across water samples with different impurities and environments to determine whether meet the safety standards of PFOA, the accuracy was 96.25 % and 94.67 % for tap water and lake water samples, respectively. The mechanism and specificity of the detection mode were further confirmed by molecular dynamics simulation. Our work provides a promising solution for PFOA detection, especially in the context of the increasingly widespread application of PFOA.

Avian cryptochrome 4 binds superoxide

Flavin-binding cryptochromes are blue-light sensitive photoreceptors that have been implicated with magnetoreception in some species. The photocycle involves an intra-protein photo-reduction of the flavin cofactor, generating a magnetosensitive radical pair, and its subsequent re-oxidation. Superoxide (O2 • - ) is generated in the re-oxidation with molecular oxygen. The resulting O2 • - -containing radical pairs have also been hypothesised to underpin various magnetosensitive traits, but due to fast spin relaxation when tumbling in solution would require immobilisation. We here describe our insights in the binding of superoxide to cryptochrome 4 from C. livia based on extensive all-atom molecular dynamics studies and density-functional theory calculations. The positively charged "crypt" region that leads to the flavin binding pocket transiently binds O2 • - at 5 flexible binding sites centred on arginine residues. Typical binding times amounted to tens of nanoseconds, but exceptional binding events extended to several hundreds of nanoseconds and slowed the rotational diffusion, thereby realising rotational correlation times as large as 1 ns. The binding sites are particularly efficient in scavenging superoxide escaping from a putative generation site close to the flavin-cofactor, possibly implying a functional relevance. We discuss our findings in view of a potential magnetosensitivity of biological flavin semiquinone/superoxide radical pairs.

HA N193D substitution in the HPAI H5N1 virus alters receptor binding affinity and enhances virulence in mammalian hosts

During the 2021/2022 winter season, we isolated highly pathogenic avian influenza (HPAI) H5N1 viruses harbouring an amino acid substitution from Asparagine(N) to Aspartic acid (D) at residue 193 of the hemagglutinin (HA) receptor binding domain (RBD) from migratory birds in South Korea. Herein, we investigated the characteristics of the N193D HA-RBD substitution in the A/CommonTeal/Korea/W811/2021[CT/W811] virus by using recombinant viruses engineered via reverse genetics (RG). A receptor affinity assay revealed that the N193D HA-RBD substitution in CT/W811 increases α2,6 sialic acid receptor binding affinity. The rCT/W811-HA193N virus caused rapid lethality with high virus titres in chickens compared with the rCT/W811-HA193D virus, while the rCT/W811-HA193D virus exhibited enhanced virulence in mammalian hosts with multiple tissue tropism. Surprisingly, a ferret-to-ferret transmission assay revealed that rCT/W811-HA193D virus replicates well in the respiratory tract, at a rate about 10 times higher than that of rCT/W811-HA193N, and all rCT/W811-HA193D direct contact ferrets were seroconverted at 10 days post-contact. Further, competition transmission assay of the two viruses revealed that rCT/W811-HA193D has enhanced growth kinetics compared with the rCT/W811-HA193N, eventually becoming the dominant strain in nasal turbinates. Further, rCT/W811-HA193D exhibits high infectivity in primary human bronchial epithelial (HBE) cells, suggesting the potential for human infection. Taken together, the HA-193D containing HPAI H5N1 virus from migratory birds showed enhanced virulence in mammalian hosts, but not in avian hosts, with multi-organ replication and ferret-to-ferret transmission. Thus, this suggests that HA-193D change increases the probability of HPAI H5N1 infection and transmission in humans.

A consortium of Hordeum vulgare and gut microbiota against non-alcoholic fatty liver disease via data-driven analysis

Despite many recent studies on non-alcoholic fatty liver disease (NAFLD) therapeutics, the optimal treatment has yet to be determined. In this unfinished project, we combined secondary metabolites (SMs) from the gut microbiota (GM) and Hordeum vulgare (HV) to investigate their combinatorial effects via network pharmacology (NP). Additionally, we analyzed GM or barley - signalling pathways - targets - metabolites (GBSTMs) in combinatorial perspectives (HV, and GM). A total of 31 key targets were analysed via a protein-protein interaction (PPI) network, and JUN was identified as the uppermost target in NAFLD. On a bubble plot, we revealed that apelin signalling pathway, which had the lowest enrichment factor antagonize NAFLD. Holistically, we scrutinized GBSTM to identify key components (GM, signalling pathways, targets, and metabolites) associated with the Apelin signalling pathway. Consequently, we found that the primary GMs (Eubacterium limosum, Eggerthella sp. SDG-2, Alistipes indistinctus YIT 12060, Odoribacter laneus YIT 12061, Paraprevotella clara YIT 11840, Paraprevotella xylaniphila YIT 11841) to ameliorate NAFLD. The molecular docking test (MDT) suggested that tryptanthrin-JUN is an agonist, conversely, dihydroglycitein-HDAC5, 1,3-diphenylpropan-2-ol-NOS1, and (10[(Acetyloxy)methyl]-9-anthryl)methyl acetate-NOS2, which are antagonistic conformers in the apelin signalling pathway. Overall, these results suggest that combination therapy could be an effective strategy for treating NAFLD.

Unravelling the physicochemical and antimicrobial mechanisms of human serum albumin/tannic acid coatings for medical-grade polycaprolactone scaffolds

Biofilm-related biomaterial infections are notoriously challenging to treat and can lead to chronic infection and persisting inflammation. To date, a large body of research can be reviewed for coatings which potentially prevent bacterial infection while promoting implant integration. Yet only a very small number has been translated from bench to bedside. This study provides an in-depth analysis of the stability, antibacterial mechanism, and biocompatibility of medical grade polycaprolactone (mPCL), coated with human serum albumin (HSA), the most abundant protein in blood plasma, and tannic acid (TA), a natural polyphenol with antibacterial properties. Molecular docking studies demonstrated that HSA and TA interact mainly through hydrogen-bonding, ionic and hydrophobic interactions, leading to smooth and regular assemblies. In vitro bacteria adhesion testing showed that coated scaffolds maintained their antimicrobial properties over 3 days by significantly reducing S. aureus colonization and biofilm formation. Notably, amplitude modulation-frequency modulation (AMFM) based viscoelasticity mapping and transmission electron microscopy (TEM) data suggested that HSA/TA-coatings cause morphological and mechanical changes on the outer cell membrane of S. aureus leading to membrane disruption and cell death while proving non-toxic to human primary cells. These results support this antibiotic-free approach as an effective and biocompatible strategy to prevent biofilm-related biomaterial infections.

The C-terminal amino acid motifs of NS1 protein affect the replication and virulence of naturally NS-truncated H1N1 canine influenza virus

The vast majority of data obtained from sequence analysis of influenza A viruses (IAVs) have revealed that nonstructural 1 (NS1) proteins from H1N1 swine, H3N8 equine, H3N2 avian and the correspondent subtypes from dogs have a conserved four C-terminal amino acid motif when independent cross-species transmission occurs between these species. To test the influence of the C-terminal amino acid motifs of NS1 protein on the replication and virulence of IAVs, we systematically generated 7 recombinants, which carried naturally truncated NS1 proteins, and their last four C-terminal residues were replaced with PEQK and SEQK (for H1N1), EPEV and KPEI (for H3N8) and ESEV and ESEI (for H3N2) IAVs. Another recombinant was generated by removing the C-terminal residues by reverse genetics. Remarkably, the ESEI and KPEI motifs circulating in canines largely contributed efficient replication in cultured cells and these had enhanced virulence. In contrast, the avian ESEV motif was only responsible for high pathogenicity in mice. We examined the effects of these motifs upon interferon (IFN) induction. The 7 mutant viruses replicated in vitro in an IFN-independent manner, and the canine SEQK motif was able to induced higher levels of IFN-β in human cell lines. These findings shed further new light on the role of the four C-terminal residues in replication and virulence of IAVs and suggest that these motifs can modulate viral replication in a species-specific manner.

Expression, potential biological behaviour and clinical significance of MCM3 in pancreatic adenocarcinoma: a comprehensive study integrating high throughput sequencing, CRISPR screening and in-house immunohistochemistry

BACKGROUND

Minichromosome maintenance complex component 3 (MCM3) plays a key role in various tumours. However, it remains largely unknown what the specific role and clinical significance of MCM3 in pancreatic adenocarcinoma (PAAD) are.

MATERIALS AND METHODS

We integrated high-throughput data from PAAD worldwide to analyse the expression level of MCM3 mRNA. We used immunohistochemistry to analyse MCM3 protein expression levels in 145 cases in the PAAD group and 29 cases in the non-PAAD group. We also mainly analysed the necessity of MCM3 for PAAD growth based on CRISPR screen data. In addition, we used enrichment analysis and protein-protein interaction networks to explore the molecular mechanism of MCM3 in PAAD. We also analysed the correlation between MCM3 expression, components of the immune microenvironment in PAAD tissue and clinical prognosis.

RESULTS

In PAAD, we observed for the first time that MCM3 was significantly highly expressed at both the mRNA (SMD = 0.67, 95% CI: 0.38 ∼ 0.96) and the protein level (p < 0.05). The mRNA (AUC = 0.78, 95% CI: 0.74 ∼ 0.81; sensitivity = 0.66, 95% CI: 0.55 ∼ 0.76; specificity = 0.76, 95% CI: 0.67 ∼ 0.84) and protein (AUC = 0.929) expression levels of MCM3 had a good ability to distinguish between PAAD and non-PAAD tissue. There was heterogeneity reflected by the differential expression of MCM3 protein in PAAD cells. MCM3 played an essential role in PAAD growth, through abnormal DNA replication, p53 signalling and cell cycle checkpoints. PAAD with high MCM3 expression was sensitive to c-75, brivanib, flavopiridol and VNLG/124 drugs, with stable molecular docking models.

CONCLUSION

MCM3 is likely to be a critical element in promoting the initiation and growth of PAAD. Flavopiridol may exert its anti-PAAD effect through the interaction between MCM3, classic CDK1 targets in the cell cycle checkpoint and p53 pathway as well as related molecules in other pathways.

Isomer-sourced structure iteration methods for in silico development of inhibitors: Inducing GTP-bound NRAS-Q61 oncogenic mutations to an "off-like" state

The NRAS-mutant subset of melanoma represent some of the most aggressive and deadliest types associated with poor overall survival. Unfortunately, for more than 40 years, no therapeutic agent directly targeting NRAS mutations has been clinically approved. In this work, based on microsecond scale molecular dynamics simulations, the effect of Q61 mutations on NRAS conformational characteristics is revealed at the atomic level. The GTP-bound NRAS-Q61R and Q61K mutations show a specific targetable pocket between Switch-II and α-helix 3 whereas the NRAS-Q61L non-polar mutation category shows a different targetable pocket. Moreover, a new isomer-sourced structure iteration method has been developed for the in silico design of potential inhibitor prototypes for oncogenes. We show the possibility of a designed prototype HM-387 to target activated NRAS-Q61R and that it can gradually induce the transition from the activated NRAS-Q61R to an "off-like" state.

Anilino-1,4-naphthoquinones as potent mushroom tyrosinase inhibitors: in vitro and in silico studies

Tyrosinase, a pivotal enzyme in melanin synthesis, is a primary target for the development of depigmenting agents. In this work, in vitro and in silico techniques were employed to identify novel tyrosinase inhibitors from a set of 12 anilino-1,4-naphthoquinone derivatives. Results from the mushroom tyrosinase activity assay indicated that, among the 12 derivatives, three compounds (1, 5, and 10) demonstrated the most significant inhibitory activity against mushroom tyrosinase, surpassing the effectiveness of the kojic acid. Molecular docking revealed that all studied derivatives interacted with copper ions and amino acid residues at the enzyme active site. Molecular dynamics simulations provided insights into the stability of enzyme-inhibitor complexes, in which compounds 1, 5, and particularly 10 displayed greater stability, atomic contacts, and structural compactness than kojic acid. Drug likeness prediction further strengthens the potential of anilino-1,4-naphthoquinones as promising candidates for the development of novel tyrosinase inhibitors for the treatment of hyperpigmentation disorders.

SERT-StructNet: Protein secondary structure prediction method based on multi-factor hybrid deep model

Protein secondary structure prediction (PSSP) is a pivotal research endeavour that plays a crucial role in the comprehensive elucidation of protein functions and properties. Current prediction methodologies are focused on deep-learning techniques, particularly focusing on multi-factor features. Diverging from existing approaches, in this study, we placed special emphasis on the effects of amino acid properties and protein secondary structure propensity scores (SSPs) on secondary structure during the meticulous selection of multi-factor features. This differential feature-selection strategy results in a distinctive and effective amalgamation of the sequence and property features. To harness these multi-factor features optimally, we introduced a hybrid deep feature extraction model. The model initially employs mechanisms such as dilated convolution (D-Conv) and a channel attention network (SENet) for local feature extraction and targeted channel enhancement. Subsequently, a combination of recurrent neural network variants (BiGRU and BiLSTM), along with a transformer module, was employed to achieve global bidirectional information consideration and feature enhancement. This approach to multi-factor feature input and multi-level feature processing enabled a comprehensive exploration of intricate associations among amino acid residues in protein sequences, yielding a Q 3 accuracy of 84.9% and an Sov score of 85.1%. The overall performance surpasses that of the comparable methods. This study introduces a novel and efficient method for determining the PSSP domain, which is poised to deepen our understanding of the practical applications of protein molecular structures.

Multiscale calculations reveal new insights into the reaction mechanism between KRASG12C and α, β-unsaturated carbonyl of covalent inhibitors

Utilizing α,β-unsaturated carbonyl group as Michael acceptors to react with thiols represents a successful strategy for developing KRASG12C inhibitors. Despite this, the precise reaction mechanism between KRASG12C and covalent inhibitors remains a subject of debate, primarily due to the absence of an appropriate residue capable of deprotonating the cysteine thiol as a base. To uncover this reaction mechanism, we first discussed the chemical reaction mechanism in solvent conditions via density functional theory (DFT) calculation. Based on this, we then proposed and validated the enzymatic reaction mechanism by employing quantum mechanics/molecular mechanics (QM/MM) calculation. Our QM/MM analysis suggests that, in biological conditions, proton transfer and nucleophilic addition may proceed through a concerted process to form an enolate intermediate, bypassing the need for a base catalyst. This proposed mechanism differs from previous findings. Following the formation of the enolate intermediate, solvent-assisted tautomerization results in the final product. Our calculations indicate that solvent-assisted tautomerization is the rate-limiting step in the catalytic cycle under biological conditions. On the basis of this reaction mechanism, the calculated kinact/ki for two inhibitors is consistent well with the experimental results. Our findings provide new insights into the reaction mechanism between the cysteine of KRASG12C and the covalent inhibitors and may provide valuable information for designing effective covalent inhibitors targeting KRASG12C and other similar targets.

Computation-guided transcription factor biosensor specificity engineering for adipic acid detection

Transcription factor (TF)-based biosensors that connect small-molecule sensing with readouts such as fluorescence have proven to be useful synthetic biology tools for applications in biotechnology. However, the development of specific TF-based biosensors is hindered by the limited repertoire of TFs specific for molecules of interest since current construction methods rely on a limited set of characterized TFs. In this study, we present an approach for engineering the specificity of TFs through a computation-based workflow using molecular docking that enables targeted alteration of TF ligand specificity. Using this method, we engineer the LysR family BenM TF to alter its specificity from its cognate ligand cis,cis-muconic acid to adipic acid through a single amino acid substitution identified by our computational workflow. When implemented in a cell-free system, the engineered biosensor shows higher ligand sensitivity, expanding the potential applications of this circuit. We further investigate ligand binding through molecular dynamics to analyze the substitution, elucidating the impact of modulating a single amino acid position on the mechanism of BenM ligand binding. This study represents the first application of biomolecular modeling methods for altering BenM specificity and for gaining insights into how mutations influence the structural dynamics of BenM. Such methods can potentially be applied to other TFs to alter specificity and analyze the dynamics responsible for these changes, highlighting the applicability of computational tools for informing experiments. In addition, our developed adipic acid biosensor can be applied for the identification and engineering of enzymes to produce adipic acid.

Language models can identify enzymatic binding sites in protein sequences

Recent advances in language modeling have had a tremendous impact on how we handle sequential data in science. Language architectures have emerged as a hotbed of innovation and creativity in natural language processing over the last decade, and have since gained prominence in modeling proteins and chemical processes, elucidating structural relationships from textual/sequential data. Surprisingly, some of these relationships refer to three-dimensional structural features, raising important questions on the dimensionality of the information encoded within sequential data. Here, we demonstrate that the unsupervised use of a language model architecture to a language representation of bio-catalyzed chemical reactions can capture the signal at the base of the substrate-binding site atomic interactions. This allows us to identify the three-dimensional binding site position in unknown protein sequences. The language representation comprises a reaction-simplified molecular-input line-entry system (SMILES) for substrate and products, and amino acid sequence information for the enzyme. This approach can recover, with no supervision, 52.13% of the binding site when considering co-crystallized substrate-enzyme structures as ground truth, vastly outperforming other attention-based models.

A structural atlas of druggable sites on Nav channels

Voltage-gated sodium (Nav) channels govern membrane excitability by initiating and propagating action potentials. Consistent with their physiological significance, dysfunction, or mutations in these channels are associated with various channelopathies. Nav channels are thereby major targets for various clinical and investigational drugs. In addition, a large number of natural toxins, both small molecules and peptides, can bind to Nav channels and modulate their functions. Technological breakthrough in cryo-electron microscopy (cryo-EM) has enabled the determination of high-resolution structures of eukaryotic and eventually human Nav channels, alone or in complex with auxiliary subunits, toxins, and drugs. These studies have not only advanced our comprehension of channel architecture and working mechanisms but also afforded unprecedented clarity to the molecular basis for the binding and mechanism of action (MOA) of prototypical drugs and toxins. In this review, we will provide an overview of the recent advances in structural pharmacology of Nav channels, encompassing the structural map for ligand binding on Nav channels. These findings have established a vital groundwork for future drug development.

Truncations and in silico docking to enhance the analytical response of aptamer-based biosensors

Aptamers are short oligonucleotides capable of binding specifically to various targets (i.e., small molecules, proteins, and whole cells) which have been introduced in biosensors such as in the electrochemical aptamer-based (E-AB) sensing platform. E-AB sensors are comprised of a redox-reporter-modified aptamer attached to an electrode that undergoes, upon target addition, a binding-induced change in electron transfer rates. To date, E-AB sensors have faced a limitation in the translatability of aptamers into the sensing platform presumably because sequences obtained from Systematic Evolution of Ligands by Exponential Enrichment (SELEX) are typically long (>80 nucleotides) and that obtaining structural information remains time and resource consuming. In response, we explore the utility of aptamer base truncations and in silico docking to improve their translatability into E-AB sensors. Here, we first apply this to the glucose aptamer, which we characterize in solution using NMR methods to guide design and translate truncated variants in E-AB biosensors. We further investigated the applicability of the truncation and computational approaches to four other aptamer systems (vancomycin, cocaine, methotrexate and theophylline) from which we derived functional E-AB sensors. We foresee that our strategy will increase the success rate of translating aptamers into sensing platforms to afford low-cost measurements of molecules directly in undiluted complex matrices.

Major specialized natural products from the endangered plant Heptacodium miconioides, potential medicinal uses and insights into its longstanding unresolved systematic classification

A comprehensive phytochemical investigation of the flower buds and leaves/twigs of Heptacodium miconioides, a cultivated ornamental plant native to China and categorized as 'vulnerable', has led to the isolation of 45 structurally diverse compounds, which comprise 18 phenylpropanoids (1-4, 7-20), 11 pentacyclic triterpenoids (5, 6, 21-29), eight secoiridoid glycosides (30-37), three quinic acid derivatives (38-40), and a few miscellaneous components (41-45). Among them, (+)-α-intermedianol (1), (+)-holophyllol A (2), and (-)-pseudolarkaemin A (3) represent previously unreported enantiomeric lignans, while (+)-7'(R)-hydroxymatairesinol (4) is an undescribed naturally occurring lignan. Heptacoacids A (5) and B (6) are undescribed 24-nor-urs-28-oic acid derivatives. Their chemical structures were determined by 2D-NMR, supplemented by evidence from specific rotations and circular dichroism spectra. Given the uncertainty surrounding the systematic position of Heptacodium, integrative taxonomy (ITA), a method utilized to define contentious species, is applied. Chemotaxonomy, a vital aspect of ITA, becomes significant. By employing hierarchical clustering analysis (HCA) and syntenic pattern analysis methods, a taxonomic examination based on the major specialized natural products from the flower buds of H. miconioides and two other Caprifoliaceae plants (i.e., Lonicera japonica and Abelia × grandiflora) could offer enhanced understanding of the systematic placement of Heptacodium. Additionally, compounds 39 and 40 displayed remarkable inhibitory activities against ATP-citrate lyase (ACL), with IC50 values of 0.11 and 1.10 μM, respectively. In summary, the discovery of medical properties and refining systematic classification can establish a sturdy groundwork for conservation efforts aimed at mitigating species diversity loss while addressing human diseases.

Preparation of monoclonal antibodies recognizing pharmacologically active metabolites of metamizole based on rational hapten design and their application in the detection of animal-derived food

Metamizole (MET) is an antipyretic and analgesic drug, the illegal use of which can result in residues of MET metabolites in edible tissues of animals. In this study, a computational chemistry-assisted hapten screening strategy was used to screen for the optimal immunogenic hapten-A and the optimal coating antigen hapten-G-OVA. A monoclonal antibody capable of recognizing two pharmacologically active metabolites of MET, 4-methylamidinoantipyrine (MAA) and 4-aminoantipyrine (AA), was prepared from the hapten-A. The antibody showed excellent specificity for MAA and AA and almost no cross-reactivity with the pharmacologically inactive metabolites 4-formamidinoantipyrine (FAA) and 4-acetamidinoantipyrine (AAA). An ic-ELISA was developed for the simultaneous detection of MAA and AA in animal-derived food, the limits of detection for MAA ranged from 0.93 to 1.18 μg/kg, while those for AA ranged from 1.74 to 4.61 μg/kg. The recovery rate fell within the range of 82 %-110 %, with a coefficient of variation less than 16.39 %.

Discovery of selective ACAT2 antagonist via a combination strategy based on deep docking, pharmacophore modelling, and molecular dynamics simulation

Acyl-CoA: cholesterol acyltransferase (ACAT), a pivotal enzyme in the absorption and metabolism of cholesterol, is primarily responsible for intracellular esterification. ACAT inhibition is expected to diminish plasma lipid levels by impeding intestinal cholesterol absorption, thereby preventing the progression of atherosclerotic lesions. A previous study shows that selective inhibition of ACAT2 significantly mitigated hypercholesterolaemia and atherosclerosis in mouse models. Therefore, the need for ACAT2 selective inhibitors becomes particularly urgent. In this study, we established a multilayer virtual screening workflow and subjected biologically evaluated representative compounds to enzyme inhibitory assays. The experimental results indicated that the two compounds, STL565001 (inhibition rate at 25 μM: 75.7 ± 27.8%, selectivity = 6) and STL528213 (inhibition rate at 25 μM: 87.8 ± 12.4%, selectivity = 13), demonstrated robust activity against ACAT2, displaying greater selectivity for ACAT2 than for ACAT1. The molecular mechanisms governing the inhibitory activities of the selected compounds were systematically elucidated using computational approaches. In addition, hotspot residues in ACAT2 that are crucial for ligand binding were successfully identified. In summary, we devised a multilayer screening scheme to expeditiously and efficiently identify compounds with enzyme inhibitory activity, offering novel scaffolds for subsequent drug design centred on ACAT2 targets.

Inhibitory effect of truncated isoforms on GPCR dimerization predicted by combinatorial computational strategy

G protein-coupled receptors (GPCRs) play a pivotal role in fundamental biological processes and disease development. GPCR isoforms, derived from alternative splicing, can exhibit distinct signaling patterns. Some highly-truncated isoforms can impact functional performance of full-length receptors, suggesting their intriguing regulatory roles. However, how these truncated isoforms interact with full-length counterparts remains largely unexplored. Here, we computationally investigated the interaction patterns of three human GPCRs from three different classes, ADORA1 (Class A), mGlu2 (Class C) and SMO (Class F) with their respective truncated isoforms because their homodimer structures have been experimentally determined, and they have truncated isoforms deposited and identified at protein level in Uniprot database. Combining the neural network-based AlphaFold2 and two physics-based protein-protein docking tools, we generated multiple complex structures and assessed the binding affinity in the context of atomistic molecular dynamics simulations. Our computational results suggested all the four studied truncated isoforms showed potent binding to their counterparts and overlapping interfaces with homodimers, indicating their strong potential to block homodimerization of their counterparts. Our study offers insights into functional significance of GPCR truncated isoforms and supports the ubiquity of their regulatory roles.

Impact of an irreversible β-galactosylceramidase inhibitor on the lipid profile of zebrafish embryos

Krabbe disease is a sphingolipidosis characterized by the genetic deficiency of the acid hydrolase β-galactosylceramidase (GALC). Most of the studies concerning the biological role of GALC performed on Krabbe patients and Galc-deficient twitcher mice (an authentic animal model of the disease) indicate that the pathogenesis of this disorder is the consequence of the accumulation of the neurotoxic GALC substrate β-galactosylsphingosine (psychosine), ignoring the possibility that this enzyme may exert a wider biological impact. Indeed, limited information is available about the effect of GALC downregulation on the cell lipidome in adult and developing organisms. The teleost zebrafish (Danio rerio) has emerged as a useful platform to model human genetic diseases, including sphingolipidoses, and two GALC co-orthologs have been identified in zebrafish (galca and galcb). Here, we investigated the effect of the competitive and irreversible GALC inhibitor β-galactose-cyclophellitol (GCP) on the lipid profile of zebrafish embryos. Molecular modelling indicates that GCP can be sequestered in the catalytic site of the enzyme and covalently binds human GALC, and the zebrafish Galca and Galcb proteins in a similar manner. Accordingly, GCP inhibits the β-galactosylceramide hydrolase activity of zebrafish in vitro and in vivo, leading to significant alterations of the lipidome of zebrafish embryos. These results indicate that the lack of GALC activity deeply affects the lipidome during the early stages of embryonic development, and thereby provide insights into the pathogenesis of Krabbe disease.

Discovering novel Cathepsin L inhibitors from natural products using artificial intelligence

Cathepsin L (CTSL) is a promising therapeutic target for metabolic disorders. Current pharmacological interventions targeting CTSL have demonstrated potential in reducing body weight gain, serum insulin levels, and improving glucose tolerance. However, the clinical application of CTSL inhibitors remains limited. In this study, we used a combination of artificial intelligence and experimental methods to identify new CTSL inhibitors from natural products. Through a robust deep learning model and molecular docking, we screened 150 molecules from natural products for experimental validation. At a concentration of 100 µM, we found that 36 of them exhibited more than 50 % inhibition of CTSL. Notably, 13 molecules displayed over 90 % inhibition and exhibiting concentration-dependent effects. The molecular dynamics simulation on the two most potent inhibitors, Plumbagin and Beta-Lapachone, demonstrated stable interaction at the CTSL active site. Enzyme kinetics studies have shown that these inhibitors exert an uncompetitive inhibitory effect on CTSL. In conclusion, our research identifies Plumbagin and Beta-Lapachone as potential CTSL inhibitors, offering promising candidates for the treatment of metabolic disorders and illustrating the effectiveness of artificial intelligence in drug discovery.

Structure-guided identification and characterization of potent inhibitors targeting PhoP and MtrA to combat mycobacteria

Mycobacteria are causative agents of tuberculosis (TB), which is a global health concern. Drug-resistant TB strains are rapidly emerging, thereby necessitating the urgent development of new drugs. Two-component signal transduction systems (TCSs) are signaling pathways involved in the regulation of various bacterial behaviors and responses to environmental stimuli. Applying specific inhibitors of TCSs can disrupt bacterial signaling, growth, and virulence, and can help combat drug-resistant TB. We conducted a comprehensive pharmacophore-based inhibitor screening and biochemical and biophysical examinations to identify, characterize, and validate potential inhibitors targeting the response regulators PhoP and MtrA of mycobacteria. The constructed pharmacophore model Phar-PR-n4 identified effective inhibitors of formation of the PhoP-DNA complex: ST132 (IC50 = 29 ± 1.6 µM) and ST166 (IC50 = 18 ± 1.3 µM). ST166 (KD = 18.4 ± 4.3 μM) and ST132 (KD = 14.5 ± 0.1 μM) strongly targeted PhoP in a slow-on, slow-off manner. The inhibitory potency and binding affinity of ST166 and ST132 for MtrAC were comparable to those of PhoP. Structural analyses and molecular dynamics simulations revealed that ST166 and ST132 mainly interact with the α8-helix and C-terminal β-hairpin of PhoP, with functionally essential residue hotspots for structure-based inhibitor optimization. Moreover, ST166 has in vitro antibacterial activity against Macrobacterium marinum. Thus, ST166, with its characteristic 1,2,5,6-tetrathiocane and terminal sulphonic groups, has excellent potential as a candidate for the development of novel antimicrobial agents to combat pathogenic mycobacteria.

Identification of novel PD-1/PD-L1 small molecule inhibitors: virtual screening, synthesis and in vitro characterisation

The PD-1/PD-L1 pathway is considered as one of the most promising immune checkpoints in tumour immunotherapy. However, researchers are faced with the inherent limitations of antibodies, driving them to pursue PD-L1 small molecule inhibitors. Virtual screening followed by experimental validation is a proven approach to discover active compounds. In this study, we employed multistage virtual screening methods to screen multiple compound databases to predict new PD-1/PD-L1 ligands. 35 compounds were proposed by combined analysis of fitness scores, interaction pattern and MM-GBSA binding affinities. Enzymatic assay confirmed that 10 out of 35 ligands were potential PD-L1 inhibitors, with inhibitory rate higher than 50% at the concentration of 30 µM. Among them, ZDS20 was identified as the most effective inhibitor with low micromolar activity (IC50 = 3.27 μM). Altogether, ZDS20 carrying novel scaffold was identified and could serve as a lead for the development of new classes of PD-L1 inhibitors.

Mechanistic insights into P-glycoprotein ligand transport and inhibition revealed by enhanced molecular dynamics simulations

P-glycoprotein (P-gp) plays a crucial role in cellular detoxification and drug efflux processes, transitioning between inward-facing (IF) open, occluded, and outward-facing (OF) states to facilitate substrate transport. Its role is critical in cancer therapy, where P-gp contributes to the multidrug resistance phenotype. In our study, classical and enhanced molecular dynamics (MD) simulations were conducted to dissect the structural and functional features of the P-gp conformational states. Our advanced MD simulations, including kinetically excited targeted MD (ketMD) and adiabatic biasing MD (ABMD), provided deeper insights into state transition and translocation mechanisms. Our findings suggest that the unkinking of TM4 and TM10 helices is a prerequisite for correctly achieving the outward conformation. Simulations of the IF-occluded conformations, characterized by kinked TM4 and TM10 helices, consistently demonstrated altered communication between the transmembrane domains (TMDs) and nucleotide binding domain 2 (NBD2), suggesting the implication of this interface in inhibiting P-gp's efflux function. A particular emphasis was placed on the unstructured linker segment connecting the NBD1 to TMD2 and its role in the transporter's dynamics. With the linker present, we specifically noticed a potential entrance of cholesterol (CHOL) through the TM4-TM6 portal, shedding light on crucial residues involved in accommodating CHOL. We therefore suggest that this entry mechanism could be employed for some P-gp substrates or inhibitors. Our results provide critical data for understanding P-gp functioning and developing new P-gp inhibitors for establishing more effective strategies against multidrug resistance.

Crystal structure of dihydroneopterin aldolase from Mycobacterium tuberculosis associated with 8-mercaptoguanine, and development of novel S8-functionalized analogues as inhibitors: Synthesis, enzyme inhibition, in vitro toxicity and antitubercular activity

The crystallographic structure of the FolB enzyme from Mycobacterium tuberculosis (MtFolB), complexed with its inhibitor 8-mercaptoguanine (8-MG), was elucidated at a resolution of 1.95 Å. A novel series of S8-functionalized 8-MG derivatives were synthesised and evaluated as in vitro inhibitors of dihydroneopterin aldolase (DHNA, EC 4.1.2.25) activity of MtFolB. These compounds exhibited IC50 values in the submicromolar range. Evaluation of the activity for five compounds indicated their inhibition mode and inhibition constants. Molecular docking analyses were performed to determine the enzyme-inhibitor intermolecular interactions and ligand conformations upon complex formation. The inhibitory activities of all compounds against the M. tuberculosis H37Rv strain were evaluated. Compound 3e exhibited a minimum inhibitory concentration in the micromolar range. Finally, Compound 3e showed no apparent toxicity in both HepG2 and Vero cells. The findings presented herein will advance the quest for novel, specific inhibitors targeting MtFolB, an attractive molecular target for TB drug development.

Rational design of glycosaminoglycan binding cyclic peptides using cPEPmatch

Cyclic peptides present a robust platform for drug design, offering high specificity and stability due to their conformationally constrained structures. In this study, we introduce an updated version of the Cyclic Peptide Matching program (cPEPmatch) tailored for the identification of cyclic peptides capable of mimicking protein-glycosaminoglycan (GAG) binding sites. We focused on engineering cyclic peptides to replicate the GAG-binding affinity of antithrombin III (ATIII), a protein that plays a crucial role in modulating anticoagulation through interaction with the GAG heparin. By integrating computational and experimental methods, we successfully identified a cyclic peptide binder with promising potential for future optimization. MD simulations and MM-GBSA calculations were used to assess binding efficacy, supplemented by umbrella sampling to approximate free energy landscapes. The binding specificity was further validated through NMR and ITC experiments. Our findings demonstrate that the computationally designed cyclic peptides effectively target GAGs, suggesting their potential as novel therapeutic agents. This study advances our understanding of peptide-GAG interactions and lays the groundwork for future development of cyclic peptide-based therapeutics.

Generation and characterization of two acid-resistant macrocin O-methyltransferase variants with a higher enzyme activity at 30 °C from Streptomyces fradiae

Tylosin is an important macrolide antibiotic produced by Streptomyces fradiae. In the biosynthesis of tylosin, macrocin O-methyltransferase TylF catalyzes the conversion of the side-product tylosin C (macrocin) to the primary component tylosin A (C/A conversion). This conversion is the rate-limiting step in the biosynthesis of tylosin, and affects the quality of the end product. To find a high activity and environment-adapted TylF enzyme, a TylF variant pool has been constructed via protein evolution approach in our previous study (Fan et al., 2023 [41]). In this study, the TylF variants with higher C/A conversion rates were expressed in E. coli and purified. The variants TylFY139F, TylFQ138H, F232Y and TylFT36S, V54A were shown to have a higher C/A conversion rate at 30 °C than that of TylF at 38 °C. Moreover, they had a greater acid resistance and showed more adaptable to the pH change during fermentation. Further protein structural and substrate-binding affinity analyses revealed that the T36S, V54A, Q138H, Y139F, and F232Y mutations enlarged the volume of the substrate-binding pocket, thereby increasing the affinity of enzyme variants for their substrates of SAM and macrocin, and decreasing the inhibition of SAH. Three of the TylF variants were overexpressed in the industrial tylosin-producing S. fradiae strain, and the recombinant strains showed the highest C/A conversion at 30 °C without heating up to 38 °C during the last 24 h of fermentation. This is of great energy-saving significance for tylosin industrial production.

Hydrogen-bonded micelle assembly directed conjugated microporous polymers for nanospherical carbon frameworks towards dual-ion capacitors

Well-orchestrated carbon nanostructure with superb stable framework and high surface accessibility is crucial for zinc-ion hybrid capacitors (ZIHCs). Herein, a hydrogen-bonded micelle self-assembly strategy is proposed for morphology-controllable synthesis of conjugated microporous polymers (CMPs) derived carbon to boost zinc ion storage capability. In the strategy, F127 micellar assembly through intermolecular hydrogen bonds serves as structure-directed agents, directing CMPs' oligomers grow into nanospherical assembly. The nanospherical carbon frameworks derived from CMPs (CNS-2) have shown maximized surface accessibility due to their plentiful tunable porosity and hierarchical porous structure with abundant mesoporous interconnected channels, and superb stability originating from CMPs' robust framework, thus the CNS-2-based ZIHCs exhibit ultrahigh energy density of 163 Wh kg-1 and ultralong lifespan with 93 % capacity retention after 200, 000 cycles at 20 A g-1. Charged ion storage efficiency also lies in dual-ion alternate uptake of Zn2+ and CF3SO3- as well as chemical redox of Zn2+ with carbonyl/pyridine motifs forming O-Zn-N bonds. Maximized surface accessibility and dual-ion storage mechanism ensure excellent electrochemical performance. Thus, the hydrogen-bond-guide micelle self-assembly strategy has provided a facile way to design nanoarchitectures of CMPs derived carbon for advanced cathodes of ZIHCs.