The AutoDock suite at 30

Metal-ion-chelating phenylalanine nanostructures reverse immune dysfunction and sensitize breast tumour to immune checkpoint blockade

An immunosuppressive tumour microenvironment strongly influences response rates in patients receiving immune checkpoint blockade-based cancer immunotherapies, such as programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1). Here we demonstrate that metal-ion-chelating L-phenylalanine nanostructures synergize with short-term starvation (STS) to remodel the immunosuppressive microenvironment of breast and colorectal tumours. These nanostructures modulate the electrophysiological behaviour of dendritic cells and activate them through the NLRP3 inflammasome and calcium-mediated nuclear factor-κB pathway. STS promotes the cellular uptake of nanostructures through amino acid transporters and plays a key role in dendritic cell maturation and tumour-specific cytotoxic T lymphocyte responses. This study demonstrates the potential role of metal-ion-chelating L-phenylalanine nanostructures in activating immune responses and the effect of STS treatment in improving nanomaterial-mediated cancer immunotherapy.

Tolerance enhancement of Dendrobium officinale by salicylic acid family-related metabolic pathways under unfavorable temperature

BACKGROUND

Unfavorable temperatures significantly constrain the quality formation of Dendrobium officinale, severely limiting its food demand. Salicylic acid (SA) enhances the resistance of D. officinale to stress and possesses various analogs. The impact and mechanism of the SA family on improving the quality of D. officinale under adverse temperature conditions remains unclear.

RESULTS

Combined with molecular docking analysis, chlorophyll fluorescence and metabolic analysis after treatments with SA analogues or extreme temperatures are performed in this study. The results demonstrate that both heat and cold treatments impede several main parameters of chlorophyll fluorescence of D. officinale, including the ΦPSII parameter, a sensitive growth indicator. However, this inhibition is mitigated by SA or its chemically similar compounds. Comprehensive branch imaging of ΦPSII values revealed position-dependent improvement of tolerance. Molecular docking analysis using a crystal structure model of NPR4 protein reveals that the therapeutic effects of SA analogs are determined by their binding energy and the contact of certain residues. Metabolome analysis identifies 17 compounds are considered participating in the temperature-related SA signaling pathway. Moreover, several natural SA analogs such as 2-hydroxycinnamic acid, benzamide, 2-(formylamino) benzoic acid and 3-o-methylgallic acid, are further found to have high binding ability to NPR4 protein and probably enhance the tolerance of D. officinale against unfavorable temperatures through flavone and guanosine monophosphate degradation pathways.

CONCLUSIONS

These results reveal that the SA family with a high binding capability of NPR4 could improve the tolerance of D. officinale upon extreme temperature challenges. This study also highlights the collaborative role of SA-related natural compounds present in D. officinale in the mechanism of temperature resistance and offers a potential way to develop protective agents for the cultivation of D. officinale.

Unlocking a Sustainable Future for Plastics: A Chemical-Enzymatic Pathway for Efficient Conversion of Mixed Waste to MHET and Energy-Saving PET Recycling

The heterogeneous monomers obtained from plastic waste degradation are unfavorable for PET recondensation and high-value derivative synthesis. Herein, we developed an efficient chemical-enzymatic approach to convert mixed plastic wastes into homogeneous mono-2-hydroxyethyl terephthalate (MHET) without downstream purification, benefiting from three discovered BHETases (KbEst, KbHyd, and BrevEst) in nature. Towards the mixed plastic waste, integrating the chemical K2CO3-driven glycolysis process with the BHETase depolymerization technique resulted in an MHET yield of up to 98.26 % in 40 h. Remarkably, BrevEst accomplished the highest BHET hydrolysis (~87 % efficiency in 12 h) for yielding analytical-grade MHET compared to seven state-of-the-art PET hydrolases (18 %-40 %). In an investigation combining quantum theoretical computations and experimental validations, we established a MHET-initiated PET repolymerization pathway. This shortcut approach with MHET promises to strengthen the valorization of mixed plastics, offering a substantially more efficient and energy-saving route for PET recycling.

The mechanism of Gejie Zhilao Pill in treating tuberculosis based on network pharmacology and molecular docking verification

Introduction

Gejie Zhilao Pill (GJZLP), a traditional Chinese medicine formula is known for its unique therapeutic effects in treating pulmonary tuberculosis. The aim of this study is to further investigate its underlying mechanisms by utilizing network pharmacology and molecular docking techniques.

Methods

Using TCMSP database the components, potential targets of GJZLP were identified. Animal-derived components were supplemented through the TCMID and BATMAN-TCM databases. Tuberculosis-related targets were collected from the TTD, OMIM, and GeneCards databases. The intersection target was imported into the String database to build the PPI network. The Metascape platform was employed to carry out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Heatmaps were generated through an online platform (https://www.bioinformatics.com.cn). Molecular docking was conducted between the core targets and core compounds to explore their binding strengths and patterns at the molecular level.

Results

61 active ingredients and 118 therapeutic targets were identified. Quercetin, Luteolin, epigallocatechin gallate, and beta-sitosterol showed relatively high degrees in the network. IL6, TNF, JUN, TP53, IL1B, STAT3, AKT1, RELA, IFNG, and MAPK3 are important core targets. GO and KEGG revealed that the effects of GJZLP on tuberculosis mainly involve reactions to bacterial molecules, lipopolysaccharides, and cytokine stimulation. Key signaling pathways include TNF, IL-17, Toll-like receptor and C-type lectin receptor signaling. Molecular docking analysis demonstrated a robust binding affinity between the core compounds and the core proteins. Stigmasterol exhibited the lowest binding energy with AKT1, indicating the most stable binding interaction.

Discussion

This study has delved into the efficacious components and molecular mechanisms of GJZLP in treating tuberculosis, thereby highlighting its potential as a promising therapeutic candidate for the treatment of tuberculosis.

Pharmacognostic Evaluation, Chemical Characterization, and Antibacterial Activity of Bassia indica (Wight) A.J. Scott

Bassia indica (Wight) A.J. Scott is an Indian origin plant with documented medicinal and nutritional value, but has not been fully characterized yet. The present study was designed to establish pharmacognostic standards for the proper identification of the B. indica plant and its chemical characterization. The plant was standardized with World Health Organization (WHO) standardization tools and chemically characterized by Fourier transform infrared spectroscopy (FTIR) and gas chromatography-mass spectroscopy (GC-MS) analysis. Antibacterial potential was assessed by the zone of inhibition and minimum inhibitory concentration (MIC), and molecular docking studies were also performed. Pharmacognostic evaluation established the macroscopic and microscopic parameters for the identification of whole plant and its powder. Physicochemical parameters were also set forth while quantitative phytochemical analysis showed that the ethyl acetate fraction had the highest quantity of phenols, flavonoids, and tannins. FTIR analysis showed several functional groups such as phenols, alkanes, and alcohols while 55 phytochemicals were identified in the GC-MS analysis of the crude fraction. The crude extract and other fractions showed marked antibacterial activity, while the ethyl acetate fraction showed the least MIC (1.95-31.25 mg/mL). Phytochemicals identified in the GC-MS showed good molecular docking interactions against the DNA gyrase subunit B of bacteria with binding energies ranging from -4.2 to -9.4 kcal/mol. The current study describes the pharmacognostic characterization and phytochemical profiling of B. indica and provides scientific evidence to support its use in infections.

Recent advances in computational and experimental protein-ligand affinity determination techniques

INTRODUCTION

Modern drug discovery revolves around designing ligands that target the chosen biomolecule, typically proteins. For this, the evaluation of affinities of putative ligands is crucial. This has given rise to a multitude of dedicated computational and experimental methods that are constantly being developed and improved.

AREAS COVERED

In this review, the authors reassess both the industry mainstays and the newest trends among the methods for protein - small-molecule affinity determination. They discuss both computational affinity predictions and experimental techniques, describing their basic principles, main limitations, and advantages. Together, this serves as initial guide to the currently most popular and cutting-edge ligand-binding assays employed in rational drug design.

EXPERT OPINION

The affinity determination methods continue to develop toward miniaturization, high-throughput, and in-cell application. Moreover, the availability of data analysis tools has been constantly increasing. Nevertheless, cross-verification of data using at least two different techniques and careful result interpretation remain of utmost importance.

Identification of lead compound screened from the natural products atlas to treat renal inflammasomes using molecular docking and dynamics simulation

One of the most prevalent ailments is kidney disease. Effective therapies for chronic renal disease are hard to come by. As a result, there is significant clinical and social interest to predict and develop novel compounds to treat renal disorders. So, specific natural products have been employed in this study because they have protective effects against kidney diseases. When taken orally, natural products can help protect against or lessen the severity of the kidney damage caused by high fructose intake, a high-fat diet, and both Type I and Type 2 diabetes. Reduced podocyte injury, a contributor to albuminuria in diabetic nephropathy, reduces renal endothelial barrier function disruption due to hyperglycemia, as well as urinary microalbumin excretion and glomerular hyperfiltration. Multiple natural products have been shown to protect the kidneys from nephrotoxic chemicals such as LPS, gentamycin, alcohol, nicotine, lead, and cadmium, all of which can persuade acute kidney injury (AKI) or chronic kidney disease (CKD). Natural compounds inhibit regulatory enzymes for controlling inflammation-related diseases. For this, use computational methods such as drug design to identify novel flavonoid compounds against kidney diseases. Drug design via computational methods gaining admiration as a swift and effective technique to identify lead compounds in a shorter time at a low cost. In this in-silico study, we screened The Natural Product Atlas based on a structure-based pharmacophore query. Top hits were analyzed for ADMET analysis followed by molecular docking and docking validation. Finally, the lead compound was simulated for a period of 200 ns and trajectories were studied for stability. We found that NPA024823 showed promising binding and stability with the AIM2. This research work aims to predict novel anti-inflammatory compounds against kidney diseases to inhibit kidney inflammasome by targeting the AIM2 protein. So, in initial preclinical research, there will be lower failure rates that demonstrate safety profiles against predicted compounds.Communicated by Ramaswamy H. Sarma.

A deep learning based multi-model approach for predicting drug-like chemical compound's toxicity

Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate prediction of compound toxicity using deep learning models offers a promising solution to mitigate these risks during drug discovery. In this study, we present the development of several deep-learning models aimed at evaluating different types of compound toxicity, including acute toxicity, carcinogenicity, hERG_cardiotoxicity (the human ether-a-go-go related gene caused cardiotoxicity), hepatotoxicity, and mutagenicity. To address the inherent variations in data size, label type, and distribution across different types of toxicity, we employed diverse training strategies. Our first approach involved utilizing a graph convolutional network (GCN) regression model to predict acute toxicity, which achieved notable performance with Pearson R 0.76, 0.74, and 0.65 for intraperitoneal, intravenous, and oral administration routes, respectively. Furthermore, we trained multiple GCN binary classification models, each tailored to a specific type of toxicity. These models exhibited high area under the curve (AUC) scores, with an impressive AUC of 0.69, 0.77, 0.88, and 0.79 for predicting carcinogenicity, hERG_cardiotoxicity, mutagenicity, and hepatotoxicity, respectively. Additionally, we have used the approved drug dataset to determine the appropriate threshold value for the prediction score in model usage. We integrated these models into a virtual screening pipeline to assess their effectiveness in identifying potential low-toxicity drug candidates. Our findings indicate that this deep learning approach has the potential to significantly reduce the cost and risk associated with drug development by expediting the selection of compounds with low toxicity profiles. Therefore, the models developed in this study hold promise as critical tools for early drug candidate screening and selection.

Spectroscopic characterization, DFT, antimicrobial activity and molecular docking studies on 4,5-bis[(E)-2-phenylethenyl]-1H,1'H-2,2'-biimidazole

The newly synthesized imidazole derivative namely, 4,5-bis[(E)-2-phenylethenyl]-1H,1'H-2,2'-biimidazole (KA1), was studied for its molecular geometry, docking studies, spectral analysis and density functional theory (DFT) studies. Experimental vibrational frequencies were compared with scaled ones. The reactivity sites were determined using average localized ionization analysis (ALIE), electron localized function (ELF), localized orbital locator (LOL), reduced density gradient (RDG), Fukui functions and frontier molecular orbital (FMO). Due to the solvent effect, a lower gas phase energy gap was observed. Through utilization of the noncovalent interaction (NCI) method, the hydrogen bond interaction, steric effect and Vander Walls interaction were investigated. Molecular docking simulations were employed to determine the specific atom inside the molecules that exhibits a preference for binding with protein. The parameters for the molecular electrostatic potential (MESP) and global reactivity descriptors were also determined. The thermodynamic characteristics were determined through calculations employing the B3LYP/cc-pVDZ basis set. Antimicrobial activity was carried out using the five different microorganisms like Escherichia coli, Streptococcus pneumoniae, Staphylococcus aureus, Klebsiella pneumoniae and Candida albicans.

Bioinformatics Study of Flavonoids From Genus Erythrina As Ace2 inhibitor Candidates For Covid-19 Treatment

Purpose

This study aimed to screen potential drug candidates from the flavonoids of the genus Erythrina for the Corona Virus Disease 2019 (COVID-19) treatment.

Patients and Methods

A comprehensive screening was conducted on the structures of 473 flavonoids derived from the genus Erythrina, focusing on their potential toxicity and pharmacokinetic profiles. Subsequently, flavonoids that were non-toxic and possessed favorable pharmacokinetic properties underwent further analysis to explore their interactions with the angiotensin-converting enzyme 2 (ACE2) receptor, employing molecular docking and molecular dynamics simulations.

Results

Among 473 flavonoids, 104 were predicted to be safe from being mutagenic, hepatotoxic, and inhibitors of the human ether-a-go-go-related gene (hERG). Among these 104 flavonoids, 18 compounds were predicted not to be substrates of P-glycoprotein (P-gp). Among these 18 flavonoids, gangetinin (471) and erybraedin D (310) exhibit low binding affinities and root mean square deviation (RMSD) values, indicating stable binding to the ACE2 receptor. The physicochemical attributes of compounds 310 and 471 suggest that they possess drug-like properties.

Conclusion

Gangetinin (471) and erybraedin D (310) may serve as promising candidates for COVID-19 treatment due to their potential to inhibit the ACE2-RBD interaction. This warrants further investigation into their inhibitory effects on ACE2-RBD binding through in vitro experiments.

AutoDock-SS: AutoDock for Multiconformational Ligand-Based Virtual Screening

Ligand-based virtual screening (LBVS) can be pivotal for identifying potential drug leads, especially when the target protein's structure is unknown. However, current LBVS methods are limited in their ability to consider the ligand conformational flexibility. This study presents AutoDock-SS (Similarity Searching), which adapts protein-ligand docking for use in LBVS. AutoDock-SS integrates novel ligand-based grid maps and AutoDock-GPU into a novel three-dimensional LBVS workflow. Unlike other approaches based on pregenerated conformer libraries, AutoDock-SS's built-in conformational search optimizes conformations dynamically based on the reference ligand, thus providing a more accurate representation of relevant ligand conformations. AutoDock-SS supports two modes: single and multiple ligand queries, allowing for the seamless consideration of multiple reference ligands. When tested on the Directory of Useful Decoys─Enhanced (DUD-E) data set, AutoDock-SS surpassed alternative 3D LBVS methods, achieving a mean AUROC of 0.775 and an EF1% of 25.72 in single-reference mode. The multireference mode, evaluated on the augmented DUD-E+ data set, demonstrated superior accuracy with a mean AUROC of 0.843 and an EF1% of 34.59. This enhanced performance underscores AutoDock-SS's ability to treat compounds as conformationally flexible while considering the ligand's shape, pharmacophore, and electrostatic potential, expanding the potential of LBVS methods.

Characterization of two novel hydrolases from Sphingopyxis sp. DBS4 for enantioselective degradation of chiral herbicide diclofop-methyl

Diclofop-methyl, an aryloxyphenoxypropionate (AOPP) herbicide, is a chiral compound with two enantiomers. Microbial detoxification and degradation of various enantiomers is garnering immense research attention. However, enantioselective catabolism of diclofop-methyl has been rarely explored, especially at the molecular level. This study cloned two novel hydrolase genes (dcmA and dcmH) in Sphingopyxis sp. DBS4, and characterized them for diclofop-methyl degradation. DcmA, a member of the amidase superfamily, exhibits 26.1-45.9% identity with functional amidases. Conversely, DcmH corresponded to the DUF3089 domain-containing protein family (a family with unknown function), sharing no significant similarity with other biochemically characterized proteins. DcmA exhibited a broad spectrum of substrates, with preferential hydrolyzation of (R)-(+)-diclofop-methyl, (R)-(+)-quizalofop-ethyl, and (R)-(+)-haloxyfop-methyl. DcmH also preferred (R)-(+)-quizalofop-ethyl and (R)-(+)-haloxyfop-methyl degradation while displaying no apparent enantioselective activity towards diclofop-methyl. Using site-directed mutagenesis and molecular docking, it was determined that Ser175 was the fundamental residue influencing DcmA's activity against the two enantiomers of diclofop-methyl. For the degradation of AOPP herbicides, DcmA is an enantioselective amidase that has never been reported in research. This study provided novel hydrolyzing enzyme resources for the remediation of diclofop-methyl in the environment and deepened the understanding of enantioselective degradation of chiral AOPP herbicides mediated by microbes.

Synthesis, topology, molecular docking and dynamics studies of o-phenylenediamine derivative

The N, N'-(1,2-phenylene) bis (1- (4- chlorophenyl) methanimine) (CS4) was synthesized and characterized by infrared (IR), absorption (UV-vis) and NMR (1H and 13C) spectral analyses. The structural parameters, vibrational frequencies, potential energy and the distribution analysis (PED) were calculated by using DFT with the basis set of B3LYP/cc-pVDZ and these spectral values were compared to the experimental values. HOMO and LUMO studied were performed in order to understand the stability and biological activity of the compound. The most reactive sites on the compound were investigated by utilizing MEP energy surface and Fukui function descriptor with the natural population analysis (NPA) of the charges. The study of the natural bond orbitals (NBO) reveals the delocalization of the intramolecular interaction of the charges in the compound. Additionally, topological investigations (ELF, LOL), determination of thermodynamic parameters and noncovalent interaction (NCI) study by using topology (RDG) analysis were also carried out. Finally, the molecular docking and molecular dynamics simulations was carried out by examining against glycosylphosphatidylinositol phospholipase D inhibitor receptor for distinct protein targets (3MZG).Communicated by Ramaswamy H. Sarma.

Contrastive pre-training and 3D convolution neural network for RNA and small molecule binding affinity prediction

MOTIVATION

The diverse structures and functions inherent in RNAs present a wealth of potential drug targets. Some small molecules are anticipated to serve as leading compounds, providing guidance for the development of novel RNA-targeted therapeutics. Consequently, the determination of RNA-small molecule binding affinity is a critical undertaking in the landscape of RNA-targeted drug discovery and development. Nevertheless, to date, only one computational method for RNA-small molecule binding affinity prediction has been proposed. The prediction of RNA-small molecule binding affinity remains a significant challenge. The development of a computational model is deemed essential to effectively extract relevant features and predict RNA-small molecule binding affinity accurately.

RESULTS

In this study, we introduced RLaffinity, a novel deep learning model designed for the prediction of RNA-small molecule binding affinity based on 3D structures. RLaffinity integrated information from RNA pockets and small molecules, utilizing a 3D convolutional neural network (3D-CNN) coupled with a contrastive learning-based self-supervised pre-training model. To the best of our knowledge, RLaffinity was the first deep learning based method for the prediction of RNA-small molecule binding affinity. Our experimental results exhibited RLaffinity's superior performance compared to baseline methods, revealed by all metrics. The efficacy of RLaffinity underscores the capability of 3D-CNN to accurately extract both global pocket information and local neighbor nucleotide information within RNAs. Notably, the integration of a self-supervised pre-training model significantly enhanced predictive performance. Ultimately, RLaffinity was also proved as a potential tool for RNA-targeted drugs virtual screening.

AVAILABILITY AND IMPLEMENTATION

https://github.com/SaisaiSun/RLaffinity.

Medicine for chronic atrophic gastritis: a systematic review, meta- and network pharmacology analysis

PURPOSE

The aim of this study is to determine the effectiveness and reliability of adding traditional Chinese medicine (TCM) in the clinical intervention and explore mechanisms of action for chronic atrophic gastritis (CAG) through meta- and network pharmacology analysis (NPAs).

METHODS

A predefined search strategy was used to retrieve literature from PubMed, Embase database, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese BioMedical Literature Database (CBM), Wan Fang Data and China Science and Technology Journal Database (VIP). After applying inclusion and exclusion criteria, a total of 12 randomized controlled trials (RCTs) were included for meta-analysis to provide clinical evidence of the intervention effects. A network meta-analysis using Bayesian networks was conducted to observe the relative effects of different intervention measures and possible ranking of effects. The composition of the TCM formulation in the experimental group was analysed, and association rule mining was performed to identify hub herbal medicines. Target genes for CAG were searched in GeneCards, Online Mendelian Inheritance in Man, PharmGKB, Therapeutic Target Database and DrugBank. A regulatory network was constructed to connect the target genes with active ingredients of the hub herbal medicines. Enrichment analyses were performed using the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to examine the central targets from a comprehensive viewpoint. Protein-protein interaction networks (PPINs) were constructed to identify hub genes and conduct molecular docking with differentially expressed genes (DEGs) and corresponding active molecules.

RESULTS

A total of 1140 participants from 12 RCTs were included in the statistical analysis, confirming that the experimental group receiving the addition of TCM intervention had better clinical efficacy. Seven hub TCMs (Paeonia lactiflora, Atractylodes macrocephala, Pinellia ternata, Citrus reticulata, Codonopsis pilosula, Salvia miltiorrhiza and Coptis chinensis) were identified through association rule analysis of all included TCMs. Thirteen hub genes (CDKN1A, CASP3, STAT1, TP53, JUN, MAPK1, STAT3, MAPK3, MYC, HIF1A, FOS, MAPK14 and AKT1) were obtained from 90 gene PPINs. Differential gene expression analysis between the disease and normal gastric tissue identified MAPK1 and MAPK3 as the significant genes. Molecular docking analysis revealed that naringenin, luteolin and quercetin were the main active compounds with good binding activities to the two hub targets. GO analysis demonstrated the function of the targets in protein binding, while KEGG analysis indicated their involvement in important pathways related to cancer.

CONCLUSIONS

The results of a meta-analysis of 12 RCTs indicate that TCM intervention can improve the clinical treatment efficacy of CAG. NPAs identified seven hub TCM and 13 target genes associated with their actions, while bioinformatics analysis identified two DEGs between normal and CAG gastric tissues. Finally, molecular docking was employed to reveal the mechanism of action of the active molecules in TCM on the DEGs. These findings not only reveal the mechanisms of action of the active components of the TCMs, but also provide support for the development of new drugs, ultimately blocking the progression from chronic gastritis to gastric cancer.

Naturally Occurring Isorhamnetin Glycosides as Potential Agents Against Influenza Viruses: Antiviral and Molecular Docking Studies

Influenza remains one of the most widespread infections, causing an annual illness in adults and children. Therefore, the search for new antiviral drugs is one of the priorities of practical health care. Eight isorhamnetin glycosides were purified from Persicaria species, characterized by nuclear magnetic resonance spectroscopy and mass spectrometry and then evaluated as potential agents against influenza virus. A comprehensive in vitro and in vivo assessment of the compounds revealed that compound 5 displayed the most potent inhibitory activity with an EC50 value of 1.2-1.3 μM, better than standard drugs (isorhamnetin 28.0-56.0 μM and oseltamivir 1.3-9.1 μM). Molecular docking results also revealed that compound 5 has the lowest binding energy (-10.7 kcal/mol) among the tested compounds and isorhamnetin (-8.1 kcal/mol). The ability of the isorhamnetin glycosides to suppress the reproduction of the influenza virus was studied on a model of a cell culture and chicken embryos. The ability of active compounds to influence the structure of the virion, as well as the activity of hemagglutinin and neuraminidase, has been demonstrated. Compound 1, 5, and 6 demonstrated the most effective inhibition of virus replication for all tested viruses. Molecular dynamics simulation techniques were run for 100 ns for compound 5 with two protein receptors Hem (1RUY) and Neu (3BEQ). These results revealed that the Hem-complex system acquired a relatively more stable conformation and even better descriptors than the other Neu-complex studied systems, suggesting that it can be an effective inhibiting drug toward hemagglutinin than neuraminidase inhibition. Based on the reported results, compound 5 can be a good candidate to be evaluated for effectiveness in preclinical testing.

Virtual screening combined with experimental verification reveals the potential mechanism of Fuzitang decoction against Gouty Arthritis

Background

and Purpose: Fuzitang decoction (FZT), a classic prescription of traditional Chinese medicine (TCM), has excellent efficacy in treating gouty arthritis (GA). However, the underlying molecular mechanism remains obscure. In the present study, we aimed to explore the underlying mechanisms of FZT in treating GA by virtual screening combined with experimental verification.

Methods

In this study, the active components of FZT and their corresponding targets were screened from the TCMSP database and TargetNet database. Then, the potential targets of FZT against GA were retrieved from multiple databases to generate a network. Protein-protein interaction, herbal-component-target, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were applied to identify potential targets and related signaling pathways. Furthermore, molecular docking simulation was applied to identify the interactions between the drug and targets. Finally, in vitro experiments were conducted to validate the potential targets and signaling pathways.

Results

In the present study, several crucial components, including kaempferol, luteolin, catechin, deoxyandrographolide, and perlolyrine in FZT, were obtained through network pharmacology, and several potential targets to treat GA were developed, such as PPARG, CYP3A4, PTGS2 (known as COX2), VEGFA, and CYP1A1. Experimental validation suggested that deoxyandrographolide significantly suppressed the expression of IL-1β, COX2, NLRP3 and IL-6 in inflammatory monocyte cells.

Conclusions

Our results identified a novel anti-inflammatory compound, deoxyandrographolide, which helps to explain the potential mechanism of FZT in treating GA and provides evidence to support FZT's clinical use.

Antimicrobial activity prediction, inter- and intramolecular charge transfer investigation, reactivity analysis and molecular docking studies of adenine derivatives

The utilization of the density functional theory (DFT) methodology has developed as a highly efficient method for investigating molecular structure and vibrational spectra, and it is increasingly being employed in various applications relating to biological systems. This study focuses on conducting investigations, both experimental and computed, to analyze the molecular structure, electronic properties and features of (E)-4-(((9H-purin-6-yl)imino)methyl)-2-methoxyphenol (ANVA). The expression ANVA should be rewritten as follows: the compound is a derivative of adenine (primary amine), specifically a vanillin (aldehyde). The present study reports the synthesis, characterization, DFT, docking and antimicrobial activity of ANVA. The optimization of the molecular structure was conducted, and the determination of its structural features was performed using DFT with the B3LYP/cc-pVDZ method. The vibrational assignments were determined in detail by analyzing the potential energy distribution. A strong correlation was observed between the spectra that were observed and the spectra that were calculated. The calculation of intramolecular charge transfer was performed using natural bond orbital analysis. In addition, several computational methods were employed, including highest occupied molecular orbital-least unoccupied molecular orbital analysis, molecular electrostatic potential calculations, non-linear optical, reduced density gradient, localization orbital locator and electron localization function analysis. This paper examines the present use of adenine derivatives in combatting bacterial and fungal infections, as well as the inclusion of spectral and quantum chemical calculations in the discussion.Communicated by Ramaswamy H. Sarma.

Synthesis, biological evaluation and in silico investigations of benzotriazole derivatives as potential inhibitors of NIMA related kinase

In the current study, a novel compound, bis(3-(2H-benzo[d][1,2,3]triazol-2-yl)-2-(prop-2-yn-1-yloxy)-5-(2,4,4-trimethylpentan-2-yl)phenyl)methane (TAJ1), has been synthesized by the reaction of 6,6'-methylenebis(2-(2H-benzo[d][1,2,3]triazol-2-yl)-4-(2,4,4-trimethylpentan-2-yl)phenol) (1), propargyl bromide (2) and potassium carbonate. Spectroscopic (FTIR, 1H-NMR, 13C-NMR) and single-crystal assays proved the structure of the synthesized sample. XRD analysis confirmed the structure of the synthesized compound, showing that it possesses two aromatic parts linked via a -CH2 carbon with a bond angle of 108.40°. The cell line activity reported a percent growth reduction for different cell types (HeLa cells, MCF-7 cells, and Vero cells) under various treatment conditions (TAJ1, cisplatin, and doxorubicin) after 24 hours and 48 hours. The percent growth reduction represents a decrease in cell growth compared to a control condition. Furthermore, density functional theory (DFT) calculations were utilized to examine the frontier molecular orbitals (FMOs) and overall chemical reactivity descriptors of TAJ1. The molecule's chemical reactivity and stability were assessed by determining the HOMO-LUMO energy gap. TAJ1 displayed a HOMO energy level of -0.224 eV, a LUMO energy level of -0.065 eV, and a HOMO-LUMO gap of 0.159 eV. Additionally, molecular docking analysis was performed to assess the binding affinities of TAJ1 with various proteins. The compound TAJ1 showed potent interactions with NEK2, exhibiting -10.5 kcal mol-1 binding energy. Although TAJ1 has demonstrated interactions with NEK7, NEK9, TP53, NF-KAPPA-B, and caspase-3 proteins, suggesting its potential as a therapeutic agent, it is important to evaluate the conformational stability of the protein-ligand complex. Hence, molecular dynamics simulations were conducted to assess this stability. To analyze the complex, root mean square deviation (RMSD) and root mean square fluctuation analyses were performed. The results of these analyses indicate that the top hits obtained from the virtual screening possess the ability to act as effective NEK2 inhibitors. Therefore, further investigation of the inhibitory potential of these identified compounds using in vitro and in vivo approaches is recommended.

Unveiling the Anti-Cancer Potential of Onoceranoid Triterpenes from Lansium domesticum Corr. cv. kokosan: An In Silico Study against Estrogen Receptor Alpha

Breast cancer is a significant global concern, with tamoxifen, the standard treatment, raising long-term safety issues due to side effects. In this study, we evaluated the potential of five onoceranoid triterpenes from Lansium domesticum Corr. cv. kokosan against estrogen receptor alpha (ERα) using in silico techniques. Utilizing molecular docking, Lipinski's rule of five, in silico ADMET, and molecular dynamics simulations, we assessed the potency of five onoceranoid triterpenes against ERα. Molecular docking indicated competitive binding energies for these triterpenes relative to the active form of tamoxifen (4OHT) and estradiol, an ERα native ligand. Three triterpenes met drug-likeness criteria with favorable ADMET profiles. Notably, 2 demonstrated superior binding affinity in molecular dynamics simulations, outperforming estradiol, closely followed by 3 and 4. Hierarchical clustering on principal components (HCPC) and the spatial distribution of contact surface area (CSA) analyses suggest that these triterpenes, especially 2, may act as antagonist ligands akin to 4OHT. These findings highlight the potential of onoceranoid triterpenes in treating ERα-related breast cancer.

Computational and theoretical chemistry of newly synthesized and characterized 2,2'-(5,5'-(1,4-phenylene)bis(1H-tetrazole-5,1-diyl))bis-N-acetamides

Energetic heterocycles, including pyridines, triazoles, and tetrazoles, exhibit greater density, heats of formation, and oxygen balance compared to their carbocyclic counterparts, making them a promising approach for synthesizing novel bis-tetrazole acetamides. Synthesized compounds A-F, some of which feature a chlorine atom attached to the phenyl ring, serve as valuable synthons for aryl coupling reactions. Analysis via 1H-NMR and 13C-NMR spectroscopy, as well as density functional considerations through B3LYP functional correlation with 6-311 +  + G(d) and 6-31G(d) basis set, revealed the observed LUMO/HOMO energies and charge transfer within the molecule. Additionally, the dipole moment, chemical hardness, softness, ionization potential, local reactivity potential via Fukui indices and thermodynamic properties (entropy, enthalpy, and Gibbs free energy) of the molecule were calculated through density functional theory studies. In addition, Molecular Docking studies were conducted to investigate the anti-cancer potential of synthesized heterocyclic compounds against caspase 3, NF-KAPPA-B and P53 protein. Molecular docking analysis demonstrated a potent interaction between 2,2'-(5,5'-(1,4-phenylene)bis(1H-tetrazole-5,1-diyl))bis-N-(2,4-dinitrophenyl) acetamides (6d) and TP53 and NF-KAPPA-B with binding energies of - 11.8 kJ/mol and - 10.9 kJ/mol for TP53 and NF-KAPPA-B, respectively. Similarly, 2,2'-(5,5'-(1,4-phenylene)bis(1H-tetrazole-5,1-diyl))bis-N-(2-chlorophenyl) acetamides (6f) exhibited a strong interaction with caspase-3 with binding energy of -10.0 kJ/mol, indicating their potential as therapeutic agents against these proteins. Furthermore, the findings of current study was further strengthen by 100 ns molecular dynamics (MD) simulations. Finally, theoretical studies of oxygen balance and nitrogen percentage suggest that these molecules can be utilized as energetic materials.

Unraveling the mechanism of tetrandrine combined with Buyang Huanwu Decoction against silicosis using network pharmacology and molecular docking analyses

Silicosis is an incurable chronic disease characterized by lung fibrosis and inflammation. The combination of tetrandrine and Buyang Huanwu Decoction (BYHWD) has a curative effect on silicosis. However, the mechanism of action and the key active constituent in BYHWD are still unclear. The present study employed network pharmacology and molecular docking to determine the mechanism of action and the key active components of BYHWD of Tetrandrine in combination with BYHWD for silicosis. The primary elements and targets of BYHWD were obtained from the Traditional Chinese Medicine Systems Pharmacology and analysis platform. The targets associated with tetrandrine and silicosis were identified and extracted from the Comparative Toxicogenomics Database and GeneCards database. The potential targets for the treatment of silicosis using a combination of Tetrandrine and BYHWD were identified by considering the overlapping targets between compound drugs and silicosis. These targets were then utilized to construct protein-protein interaction networks, compound drug-ingredient-target networks, and perform enrichment analyses. The top 5 active ingredients present in the compound drug-ingredient-target network are tetrandrine, quercetin, luteolin, kaempferol, and beta-carotene. Similarly, the top 6 hub genes in the protein-protein interaction network are FGF2, MMP-9, MMP-1, IL-10, IL-17A, and IL-6. The molecular docking suggested that the active components may easily access the active pocket of the hub gene. The in-silico investigation suggested that quercetin might be the active component in BYHWD responsible for therapeutic effectiveness against silicosis. This study identified the active compound and potential molecular mechanism underlying the therapeutic effects of BYHWD in combination with tetrandrine for treating silicosis. Notably, we found that quercetin may serve as the key compound in BYHWD for the treatment of silicosis.

A Non-G-Quadruplex DNA Aptamer Targeting NCL for Diagnosis and Therapy in Bladder Cancer

Bladder cancer (BC) is a highly aggressive malignant tumor affecting the urinary system, characterized by metastasis and a poor prognosis that often leads to limited therapeutic success. This study aims to develop a novel DNA aptamer for the diagnosis and treatment of BC using a tissue-based systematic evolution of ligands by an exponential enrichment (SELEX) process. By using SELEX, this work successfully generates a new aptamer named TB-5, which demonstrates a remarkable and specific affinity for nucleolin (NCL) in BC tissues and displays marked biocompatibility both in vitro and in vivo. Additionally, this work shows that NCL is a reliable tissue-specific biomarker in BC. Moreover, according to circular dichroism spectroscopy, TB-5 forms a non-G-quadruplex structure, distinguishing it from the current NCL-targeting aptamer AS1411, and exhibits a distinct binding region on NCL compared to AS1411. Notably, this study further reveals that TB-5 activates NCL function by promoting autophagy and suppressing the migration and invasion of BC cells, which occurs by disrupting mRNA transcription processes. These findings highlight the critical role of NCL in the pathological examination of BC and warrant more comprehensive investigations on anti-NCL aptamers in BC imaging and treatment.

Benzenesulfonamide Analogs: Synthesis, Anti-GBM Activity and Pharmacoprofiling

The tropomyosin receptor kinase A (TrkA) family of receptor tyrosine kinases (RTKs) emerge as a potential target for glioblastoma (GBM) treatment. Benzenesulfonamide analogs were identified as kinase inhibitors possessing promising anticancer properties. In the present work, four known and two novel benzenesulfonamide derivatives were synthesized, and their inhibitory activities in TrkA overexpressing cells, U87 and MEF cells were investigated. The cytotoxic effect of benzenesulfonamide derivatives and cisplatin was determined using trypan blue exclusion assays. The mode of interaction of benzenesulfonamides with TrkA was predicted by docking and structural analysis. ADMET profiling was also performed for all compounds to calculate the drug likeness property. Appropriate QSAR models were developed for studying structure-activity relationships. Compound 4-[2-(4,4-dimethyl-2,6-dioxocyclohexylidene)hydrazinyl]-N-(5-methyl-1,3,4-thiadiazol-2-yl)benzenesulfon-amide (AL106) and 4-[2-(1,3-dioxo-1,3-dihydro-2H-inden-2-ylidene)hydrazinyl]-N-(5-methyl-1,3,4-thiadiazol-2-yl)benzenesulfonamide (AL107) showed acceptable binding energies with the active sites for human nerve growth factor receptor, TrkA. Here, AL106 was identified as a potential anti-GBM compound, with an IC50 value of 58.6 µM with a less toxic effect in non-cancerous cells than the known chemotherapeutic agent, cisplatin. In silico analysis indicated that AL106 formed prominent stabilizing hydrophobic interactions with Tyr359, Ser371, Ile374 and charged interactions with Gln369 of TrkA. Furthermore, in silico analysis of all benzenesulfonamide derivatives revealed that AL106 has good pharmacokinetics properties, drug likeness and toxicity profiles, suggesting the compound may be suitable for clinical trial. Thus, benzenesulfonamide analog, AL106 could potentially induce GBM cell death through its interaction with TrkA and might be an attractive strategy for developing a drug targeted therapy to treat glioblastoma.

Study on the mechanism of action of colchicine in the treatment of coronary artery disease based on network pharmacology and molecular docking technology

Objective: This is the first study to explore the mechanism of colchicine in treating coronary artery disease using network pharmacology and molecular docking technology, aiming to predict the key targets and main approaches of colchicine in treating coronary artery disease. It is expected to provide new ideas for research on disease mechanism and drug development. Methods: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Swiss Target Prediction and PharmMapper databases were used to obtain drug targets. GeneCards, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), DrugBank and DisGeNET databases were utilized to gain disease targets. The intersection of the two was taken to access the intersection targets of colchicine for the treatment of coronary artery disease. The Sting database was employed to analyze the protein-protein interaction network. Gene Ontology (GO) functional enrichment analysis was performed using Webgestalt database. Reactom database was applied for Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Molecular docking was simulated using AutoDock 4.2.6 and PyMOL2.4 software. Results: A total of 70 intersecting targets of colchicine for the treatment of coronary artery disease were obtained, and there were interactions among 50 targets. GO functional enrichment analysis yielded 13 biological processes, 18 cellular components and 16 molecular functions. 549 signaling pathways were obtained by KEGG enrichment analysis. The molecular docking results of key targets were generally good. Conclusion: Colchicine may treat coronary artery disease through targets such as Cytochrome c (CYCS), Myeloperoxidase (MPO) and Histone deacetylase 1 (HDAC1). The mechanism of action may be related to the cellular response to chemical stimulus and p75NTR-mediated negative regulation of cell cycle by SC1, which is valuable for further research exploration. However, this research still needs to be verified by experiments. Future research will explore new drugs for treating coronary artery disease from these targets.

Mechanism of ligusticum cycloprolactam against neuroinflammation based on network pharmacology and experimental verification

Ligustilide, a natural phthalide mainly derived from chuanxiong rhizomes and Angelica Sinensis roots, possesses anti-inflammatory activity, particularly in the context of the nervous system. However, its application is limited because of its unstable chemical properties. To overcome this limitation, ligusticum cycloprolactam (LIGc) was synthesized through structural modification of ligustilide. In this study, we combined network pharmacological methods with experimental verification to investigate the anti-neuroinflammatory effects and mechanisms of ligustilide and LIGc. Based on our network pharmacology analysis, we identified four key targets of ligustilide involved in exerting an anti-inflammatory effect, with the nuclear factor (NF)-κB signal pathway suggested as the main signalling pathway. To verify these results, we examined the expression of inflammatory cytokines and inflammation-related proteins, analysed the phosphorylation level of NF-κB, inhibitor of κBα (IκBα) and inhibitor of κB kinase α and β (IKKα+β), and evaluated the effect of BV2 cell-conditioned medium on HT22 cells in vitro. Our results, demonstrate for the first time that LIGc can downregulate the activation of the NF-κB signal pathway in BV2 cells induced by lipopolysaccharide, suppress the production of inflammatory cytokines and reduce nerve injury in HT22 cells mediated by BV2 cells. These findings suggest that LIGc inhibits the neuroinflammatory response mediated by BV2 cells, providing strong scientific support for the development of anti-inflammatory drugs based on natural ligustilide or its derivatives. However, there are some limitations to our current study. In the future, further experiments using in vivo models may provide additional evidence to support our findings.

Exploring the pharmacological mechanisms of Tripterygium wilfordii against diabetic kidney disease using network pharmacology and molecular docking

Background

Tripterygium wilfordii (TW), when formulated in traditional Chinese medicine (TCM), can effectively treat diabetic kidney disease (DKD). However, the pharmacological mechanism associated with its success has not yet been elucidated. The current work adopted network pharmacology and molecular docking for exploring TW-related mechanisms in treating DKD. Methods: In the present work, the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was employed to obtain the effective components and candidate targets of TW. Additionally, this work utilized the UniProt protein database for screening and standardizing human-derived targets for effective components. The Cytoscape software was utilized to construct an effective component-target network for TW. Targets for DKD were acquired in the GEO, DisGeNET, GeneCards, and OMIM databases. Additionally, a Venn diagram was also plotted to select the possible targets of TW for treating DKD. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted to explore the TW-related mechanism underlying DKD treatment. This work also built a protein-protein interaction (PPI) network based on the Cytoscape and String platform. Then, molecular docking was conducted in order to assess the affinity of key proteins for related compounds. Results: In total, 29 active components and 134 targets of TW were acquired, including 63 shared targets, which were identified as candidate therapeutic targets. Some key targets and important pathways were included in the effect of TW in treating DKD. Genes with higher degrees, including TNF and AKT1, were identified as hub genes of TW against DKD. Molecular docking showed that TNF and AKT1 bind well to the main components in TW (kaempferol, beta-sitosterol, triptolide, nobiletin, and stigmasterol).

Conclusions

TW primarily treats DKD by acting on two targets (AKT1 and TNF) via the five active ingredients kaempferol, beta-sitosterol, triptolide, nobiletin, and stigmasterol.

Computer Analysis of the Inhibition of ACE2 by Flavonoids and Identification of Their Potential Antiviral Pharmacophore Site

In the present study, we investigated the antiviral activities of 17 flavonoids as natural products. These derivatives were evaluated for their in vitro antiviral activities against HIV and SARS-CoV-2. Their antiviral activity was evaluated for the first time based on POM (Petra/Osiris/Molispiration) theory and docking analysis. POM calculation was used to analyze the atomic charge and geometric characteristics. The side effects, drug similarities, and drug scores were also assumed for the stable structure of each compound. These results correlated with the experimental values. The bioinformatics POM analyses of the relative antiviral activities of these derivatives are reported for the first time.

Developments in molecular docking technologies for application of polysaccharide-based materials: A review

With the increasing pollution of the planet, the search for natural multifunctional alternatives to petroleum-based plastics has assumed to be a great important proposition. Polysaccharides, an inexhaustible natural resource with good biocompatibility as well as mechanical properties, are considered as an ideal alternative to petroleum-based materials. However, blind experimentation and development will inevitably lead to waste of raw materials and contamination of reagents. Therefore, researchers desire a technology which can assist in predicting and screening experimental materials at the higher level. Molecular docking simulations, an emerging computer technology that can effectively predict the structure of interactions between molecules and analyze the optimal conformation, are a common aid for materials and drug design. In this review, we describe the origins and development of molecular docking techniques, mainly performed an overview of various molecular docking software on their applications in the field of different polysaccharide materials.

A Single Active-Site Mutagenesis Confers Enhanced Activity and/or Changed Product Distribution to a Pentalenene Synthase from Streptomyces sp. PSKA01

Pentalenene is a ternary cyclic sesquiterpene formed via the ionization and cyclization of farnesyl pyrophosphate (FPP), which is catalyzed by pentalenene synthase (PentS). To better understand the cyclization reactions, it is necessary to identify more key sites and elucidate their roles in terms of catalytic activity and product specificity control. Previous studies primarily relied on the crystal structure of PentS to analyze and verify critical active sites in the active cavity, while this study started with the function of PentS and screened a novel key site through random mutagenesis. In this study, we constructed a pentalenene synthetic pathway in E. coli BL21(DE3) and generated PentS variants with random mutations to construct a mutant library. A mutant, PentS-13, with a varied product diversity, was obtained through shake-flask fermentation and product identification. After sequencing and the functional verification of the mutation sites, it was found that T182A, located in the G2 helix, was responsible for the phenotype of PentS-13. The site-saturation mutagenesis of T182 demonstrated that mutations at this site not only affected the solubility and activity of the enzyme but also affected the specificity of the product. The other products were generated through different routes and via different carbocation intermediates, indicating that the 182 active site is crucial for PentS to stabilize and guide the regioselectivity of carbocations. Molecular docking and molecular dynamics simulations suggested that these mutations may induce changes in the shape and volume of the active cavity and disturb hydrophobic/polar interactions that were sufficient to reposition reactive intermediates for alternative reaction pathways. This article provides rational explanations for these findings, which may generally allow for the protein engineering of other terpene synthases to improve their catalytic efficiency or modify their specificities.

Network pharmacology, molecular docking, and experimental validation to explore the potential mechanism of Long Mu Qing Xin mixture for the treatment of attention deficit hyperactivity disorder

Background: Long Mu Qing Xin Mixture (LMQXM) has shown potentially positive effects in alleviating attention deficit hyperactivity disorder (ADHD); however, the action mechanism is still not fully understood. This study aimed to predict the potential mechanism of LMQXM for ADHD using network pharmacology and molecular docking, which were then validated using animal experiments.

Methods: Network pharmacology and molecular docking techniques were used to predict the core targets and potential pathways of LMQXMQ for ADHD, and KEGG pathway enrichment analysis revealed the potential significance of dopamine (DA) and cyclic adenosine monophosphate (cAMP) signaling pathways. To verify the hypothesis, we conducted an animal experiment. In the animal experiment, the young spontaneously hypertensive rats (SHRs) were randomly divided into the model group (SHR), the methylphenidate hydrochloride group (MPH, 4.22 mg/kg), and 3 LMQXM groups (low-dose (LD) group, 5.28 ml/kg; medium-dose (MD) group, 10.56 ml/kg; and high-dose (HD) group, 21.12 ml/kg), and administered by gavage for 4 weeks; the WKY rats were set as the control group. The open field test and Morris water maze test were used to evaluate the behavioral performance of rats, high performance liquid chromatography mass spectrometry (LC-MS) was used to analyze DA levels in the prefrontal cortex (PFC) and striatum of rats, ELISA was used to detect cAMP concentrations in the PFC and striatum, and immunohistochemistry and qPCR were used to analyze positive cell expression and mRNA expression for indicators related to DA and cAMP pathways.

Results: The results showed that beta-sitosterol, stigmasterol, rhynchophylline, baicalein, and formononetin might be key components of LMQXM for ADHD and that these components bind well to the core targets, DA receptors (DRD1 and DRD2). Furthermore, LMQXM might act through the DA and cAMP signaling pathways. In the animal experiment, we found that MPH and LMQXM-MD controlled hyperactivity and improved learning and memory in SHRs, while LMQXM-HD only controlled hyperactivity in SHRs; meanwhile, MPH and LMQXM-MD upregulated DA and cAMP levels, mean optical density (MOD) of cAMP, and MOD and mRNA expression of DRD1 and PKA in the prefrontal cortex (PFC) and striatum of SHRs, while LMQXM-LD and LMQXM-HD upregulated DA and cAMP levels in the striatum, MOD of cAMP in the PFC, and mRNA expression of PKA in the PFC. However, we did not find a significant regulatory effect of LMQXM on DRD2.

Conclusion: To sum up, this study demonstrated that LMQXM may increase DA levels mainly by activating the cAMP/PKA signaling pathway through DRD1, thereby controlling the behavioral disorders of SHRs, which is most effective at moderate doses, and this may be a key mechanism for LMQXM in the treatment of ADHD.

AlphaFold2 protein structure prediction: Implications for drug discovery

The drug discovery process involves designing compounds to selectively interact with their targets. The majority of therapeutic targets for low molecular weight (small molecule) drugs are proteins. The outstanding accuracy with which recent artificial intelligence methods compile the three-dimensional structure of proteins has made protein targets more accessible to the drug design process. Here, we present our perspective of the significance of accurate protein structure prediction on various stages of the small molecule drug discovery life cycle focusing on current capabilities and assessing how further evolution of such predictive procedures can have a more decisive impact in the discovery of new medicines.

In Silico Study on the Interactions, Molecular Docking, Dynamics and Simulation of Potential Compounds from Withania somnifera (L.) Dunal Root against Cancer by Targeting KAT6A

Cancer is characterized by the abnormal development of cells that divide in an uncontrolled manner and further take over the body and destroy the normal cells of the body. Although several therapies are practiced, the demand and need for new therapeutic agents are ever-increasing because of issues with the safety, efficacy and efficiency of old drugs. Several plant-based therapeutics are being used for treatment, either as conjugates with existing drugs or as standalone formulations. Withania somnifera (L.) Dunal is a highly studied medicinal plant which is known to possess immunomodulatory activity as well as anticancer properties. The pivotal role of KAT6A in major cellular pathways and its oncogenic nature make it an important target in cancer treatment. Based on the literature and curated datasets, twenty-six compounds from the root of W. somnifera and a standard inhibitor were docked with the target KAT6A using Autodock vina. The compounds and the inhibitor complexes were subjected to molecular dynamics simulation (50 ns) using Desmond to understand the stability and interactions. The top compounds (based on the docking score of less than -8.5 kcal/mol) were evaluated in comparison to the inhibitor. Based on interactions at ARG655, LEU686, GLN760, ARG660, LEU689 and LYS763 amino acids with the inhibitor WM-8014, the compounds from W. somnifera were evaluated. Withanolide D, Withasomniferol C, Withanolide E, 27-Hydroxywithanone, Withanolide G, Withasomniferol B and Sitoindoside IX showed high stability with the residues of interest. The cell viability of human breast cancer MCF-7 cells was evaluated by treating them with W. Somnifera root extract using an MTT assay, which showed inhibitory activity with an IC50 value of 45 µg/mL. The data from the study support the traditional practice of W. somnifera as an anticancer herb.

New Fructokinase, OsFRK3, Regulates Starch Accumulation and Grain Filling in Rice

Plant fructokinase (FRK) guarantees the growth and development of higher plants by participating in carbohydrate metabolism. In this study, a new fructokinase, OsFRK3, was identified using bioinformatics analysis, enzyme assay, bacterial growth assay, and yeast complementation test. Then, we created OsFRK3 knockout transgenic lines (osfrk3-1 and osfrk3-2) by the CRISPR/Cas9 technology. We found that the 1000-grain weight decreased notably (approximately -3.6% and -6.1%, respectively) in osfrk3-1 and osfrk3-2. Evidently decreased grain width, grain thickness, and endosperm filling rate were detected in the osfrk3 mutants (osfrk3-1 and osfrk3-2) compared with those of the WT. In addition, the content of seed total starch was significantly decreased by 3.42 and 4.80% in osfrk3 lines, compared with that in the WT. The level of maltose was significantly reduced in the mutants, while that of sucrose and fructose was obviously increased in the mutants. The transcript levels of OsGBSS1, OsBEIIb, OsPFP1β, and OsAGPL1 were significantly decreased in the osfrk3 mutants. These results suggest that OsFRK3 may positively regulate the accumulation of starch through influencing the sugar metabolism.

Potential molecular mechanisms of Erlongjiaonang action in idiopathic sudden hearing loss: A network pharmacology and molecular docking analyses

Background

Idiopathic sudden hearing loss (ISHL) is characterized by sudden unexplainable and unilateral hearing loss as a clinically emergent symptom. The use of the herb Erlongjiaonang (ELJN) in traditional Chinese medicine is known to effectively control and cure ISHL. This study explored the underlying molecular mechanisms using network pharmacology and molecular docking analyses.

Method

The Traditional Chinese Medicine System Pharmacological database and the Swiss Target Prediction database were searched for the identification of ELJN constituents and potential gene targets, respectively, while ISHL-related gene abnormality was assessed using the Online Mendelian Inheritance in Man and Gene Card databases. The interaction of ELJN gene targets with ISHL genes was obtained after these databases were cross-screened, and a drug component-intersecting target network was constructed, and the gene ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction networks were analyzed. Cytoscape software tools were used to map the active components-crossover target-signaling pathway network and screened targets were then validated by establishing molecular docking with the corresponding components.

Result

Erlongjiaonang contains 85 components and 250 corresponding gene targets, while ISHL has 714 disease-related targets, resulting in 66 cross-targets. The bioinformatical analyses revealed these 66 cross-targets, including isorhamnetin and formononetin on NOS3 expression, baicalein on AKT1 activity, and kaempferol and quercetin on NOS3 and AKT1 activity, as potential ELJN-induced anti-ISHL targets.

Conclusion

This study uncovered potential ELJN gene targets and molecular signaling pathways in the control of ISHL, providing a molecular basis for further investigation of the anti-ISHL activity of ELJN.

Silico analysis of the target and possible mechanism of lomustine in the treatment of primary glioblastoma

OBJECTIVE

The targets and mechanism of lomustine in the treatment of primary glioblastoma (PGBM) were investigated by molecular docking and molecular dynamics simulation, which provided theoretical guidance for its clinical application.

METHODS

We used the PharmMapper database to identify all of the targets of lomustine, and then examined the effect of lomustine on PGBM using molecular docking, molecular mechanics generalized born surface area (MMGB/SA), gene difference analysis, molecular dynamics simulation, survival analysis, and protein subcellular localization prediction.

RESULTS

A total of 243 lomustine targets and 3197 PGBM-related targets were screened. The intersection of the two was 59 active targets. Protein interaction (PPI), gene enrichment analysis, gene difference analysis, molecular docking, and molecular dynamics simulation finally screened out three effective targets of lomustine, namely HMOX1, AKT1, and EGFR, which exist mainly in the cytoplasm, nucleus, and vesicles, respectively. These three targets mainly inhibit JAK-STAT, PD-1/PD-L1, PI3K-Akt, Rap1, HIF-1, MAPK, and Fc-εRI involved in protein metabolism, the regulation of cell differentiation, the regulation of the Notch signaling pathway and glial cell activation, and other biological processes and could play a role in the treatment of PGBM.

CONCLUSIONS

HMOX1, AKT1, and EGFR may represent novel therapeutic targets for lomustine in the clinical treatment of PGBM.

Cryo-EM structure-based selection of computed ligand poses enables design of MTA-synergic PRMT5 inhibitors of better potency

Projected potential of 2.5-4.0 Å cryo-EM structures for structure-based drug design is not well realized yet. Here we show that a 3.1 Å structure of PRMT5 is suitable for selecting computed poses of a chemical inhibitor and its analogs for enhanced potency. PRMT5, an oncogenic target for various cancer types, has many inhibitors manifesting little cooperativity with MTA, a co-factor analog accumulated in MTAP-/- cells. To achieve MTA-synergic inhibition, a pharmacophore from virtual screen leads to a specific inhibitor (11-2 F). Cryo-EM structures of 11-2 F / MTA-bound human PRMT5/MEP50 complex and its apo form resolved at 3.1 and 3.2 Å respectively show that 11-2 F in the catalytic pocket shifts the cofactor-binding pocket away by ~2.0 Å, contributing to positive cooperativity. Computational analysis predicts subtype specificity of 11-2 F among PRMTs. Structural analysis of ligands in the binding pockets is performed to compare poses of 11-2 F and its redesigned analogs and identifies three new analogs predicted to have significantly better potency. One of them, after synthesis, is ~4 fold more efficient in inhibiting PRMT5 catalysis than 11-2 F, with strong MTA-synergy. These data suggest the feasibility of employing near-atomic resolution cryo-EM structures and computational analysis of ligand poses for small molecule therapeutics.

Sodium danshensu attenuates cerebral ischemia–reperfusion injury by targeting AKT1

The beneficial properties of Sodium Danshensu (SDSS) for controlling cerebral ischemia and reperfusion injury (CIRI) are elucidated here both in vivo and in vitro. SDSS administration significantly improved the viability of P12 cells, reduced lactate dehydrogenase (LDH) leakage, and decreased the apoptosis rate following exposure to an oxygen-glucose deprivation/reoxygenation (OGD) environment. In addition, the results of a Huprot^TM human protein microarray and network pharmacology indicated that AKT1 is one of the main targets of SDSS. Moreover, functional experiments showed that SDSS intervention markedly increased the phosphorylation level of AKT1 and its downstream regulator, mTOR. The binding sites of SDSS to AKT1 protein were confirmed by Autodock software and a surface plasmon resonance experiment, the result of which imply that SDSS targets to the PH domain of AKT1 at ASN-53, ARG-86, and LYS-14 residues. Furthermore, knockdown of AKT1 significantly abolished the role of SDSS in protecting cells from apoptosis and necrosis. Finally, we investigated the curative effect of SDSS in a rat model of CIRI. The results suggest that administration of SDSS significantly reduces CIRI-induced necrosis and apoptosis in brain samples by activating AKT1 protein. In conclusion, SDSS exerts its positive role in alleviating CIRI by binding to the PH domain of AKT1 protein, further resulting in AKT1 activation.

Identification of new aptamer BC-3 targeting RPS7 from rapid screening for bladder carcinoma

Aptamers, short single DNA or RNA oligonucleotides, have shown immense application potential as molecular probes for the early diagnosis and therapy of cancer. However, conventional cell-SELEX technologies for aptamer discovery are time-consuming and laborious. Here we discovered a new aptamer BC-3 by using an improved rapid X-Aptamer selection process for human bladder carcinoma, for which there is no specific molecular probe yet. We show that BC-3 exhibited excellent affinity in bladder cancer cells but not normal cells. We demonstrate that BC-3 displayed high selectivity for tumor cells over their normal counterparts in vitro, in mice, and in patient tumor tissue specimens. Further endocytosis pathway analysis revealed that BC-3 internalized into bladder cancer cells via clathrin-mediated endocytosis. Importantly, we identified ribosomal protein S7 (RPS7) as the binding target of BC-3 via an integrated methodology (mass spectrometry, colocalization assay, and immunoblotting). Together, we report that a novel aptamer BC-3 is discovered for bladder cancer and its properties in the disease are unearthed. Our findings will facilitate the discovery of novel diagnostic and therapeutic strategies for bladder cancer.

Characterization and Identification of a New Daidzein Reductase Involved in (S)-Equol Biosynthesis in Clostridium sp. ZJ6

(S)-equol (EQ) is an isoflavone with high estrogen-like activity in the human body, and is only produced by some gut bacteria in vivo. It plays an important role in maintaining individual health, however, the dearth of resources associated with (S)-EQ-producing bacteria has seriously restricted the production and application of (S)-EQ. We report here a new functional gene KEC48-07020 (K-07020) that was identified from a chick (S)-EQ-producing bacterium (Clostridium sp. ZJ6, ZJ6). We found that recombinant protein of K-07020 possessed similar function to daidzein reductase (DZNR), which can convert daidzein (DZN) into R/S-dihydrodaidzein (R/S-DHD). Interestingly, K-07020 can reversely convert (R/S)-DHD (DHD oxidase) into DZN even without cofactors under aerobic conditions. Additionally, high concentrations of (S)-EQ can directly promote DHD oxidase but inhibit DZNR activity. Molecular docking and site-directed mutagenesis revealed that the amino acid > Arg75 was the active site of DHD oxidase. Subsequently, an engineered E. coli strain based on K-07020 was constructed and showed higher yield of (S)-EQ than the engineered bacteria from our previous work. Metagenomics analysis and PCR detection surprisingly revealed that K-07020 and related bacteria may be prevalent in the gut of humans and animals. Overall, a new DZNR from ZJ6 was found and identified in this study, and its bidirectional enzyme activities and wide distribution in the gut of humans and animals provide alternative strategies for revealing the individual regulatory mechanisms of (S)-EQ-producing bacteria.

Purification of menthone and menthol from Mentha haplocalyx by suspension particle assisted solvent sublation, neuroprotective effect in vitro and molecular docking of menthol on amyloid-β

Suspension particle assisted solvent sublation was designed for the first time. The volatile monoterpenes in Mentha haplocalyx Briq were extracted using this method from a solution containing plant solid particles as the lower phase of solvent sublation. Under the optimum conditions of the solvent sublation (n-hexane/plant solid particles 20% ethanol-water solution system, pH 4, flotation time 30 min and air flow rate 30 mL/min), the extraction yields were 2.0 × 10² mg/kg, 9.5 × 10¹ mg/kg and 1.2 × 10³ mg/kg for menthone, isomenthone and menthol, respectively. Compared with the traditional methods, the established suspension particle assisted solvent sublation might be an economical and efficient extraction method in some aspects. Through a cellular antioxidant activity experiment, menthol could alleviate H₂O₂-induced oxidative stress. Molecular docking was applied to simulate the molecular recognition process between amyloid-β and menthol. The affinity energy of menthol was -12.59 kJ/mol, indicating that menthol might have neuroprotective activity and the potential to be an amyloid-β inhibitor.

Hybrid drug-screening strategy identifies potential SARS-CoV-2 cell-entry inhibitors targeting human transmembrane serine protease

The spread of coronavirus infectious disease (COVID-19) is associated with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has risked public health more than any other infectious disease. Researchers around the globe use multiple approaches to identify an effective approved drug (drug repurposing) that treats viral infections. Most of the drug repurposing approaches target spike protein or main protease. Here we use transmembrane serine protease 2 (TMPRSS2) as a target that can prevent the virus entry into the cell by interacting with the surface receptors. By hypothesizing that the TMPRSS2 binders may help prevent the virus entry into the cell, we performed a systematic drug screening over the current approved drug database. Furthermore, we screened the Enamine REAL fragments dataset against the TMPRSS2 and presented nine potential drug-like compounds that give us clues about which kinds of groups the pocket prefers to bind, aiding future structure-based drug design for COVID-19. Also, we employ molecular dynamics simulations, binding free energy calculations, and well-tempered metadynamics to validate the obtained candidate drug and fragment list. Our results suggested three potential FDA-approved drugs against human TMPRSS2 as a target. These findings may pave the way for more drugs to be exposed to TMPRSS2, and testing the efficacy of these drugs with biochemical experiments will help improve COVID-19 treatment.

Supplementary information

The online version contains supplementary material available at 10.1007/s11224-022-01960-w.

Accelerating AutoDock Vina with GPUs

AutoDock Vina is one of the most popular molecular docking tools. In the latest benchmark CASF-2016 for comparative assessment of scoring functions, AutoDock Vina won the best docking power among all the docking tools. Modern drug discovery is facing a common scenario of large virtual screening of drug hits from huge compound databases. Due to the seriality characteristic of the AutoDock Vina algorithm, there is no successful report on its parallel acceleration with GPUs. Current acceleration of AutoDock Vina typically relies on the stack of computing power as well as the allocation of resource and tasks, such as the VirtualFlow platform. The vast resource expenditure and the high access threshold of users will greatly limit the popularity of AutoDock Vina and the flexibility of its usage in modern drug discovery. In this work, we proposed a new method, Vina-GPU, for accelerating AutoDock Vina with GPUs, which is greatly needed for reducing the investment for large virtual screens and also for wider application in large-scale virtual screening on personal computers, station servers or cloud computing, etc. Our proposed method is based on a modified Monte Carlo using simulating annealing AI algorithm. It greatly raises the number of initial random conformations and reduces the search depth of each thread. Moreover, a classic optimizer named BFGS is adopted to optimize the ligand conformations during the docking progress, before a heterogeneous OpenCL implementation was developed to realize its parallel acceleration leveraging thousands of GPU cores. Large benchmark tests show that Vina-GPU reaches an average of 21-fold and a maximum of 50-fold docking acceleration against the original AutoDock Vina while ensuring their comparable docking accuracy, indicating its potential for pushing the popularization of AutoDock Vina in large virtual screens.

Application of molecular dynamics simulation in biomedicine

Molecular dynamics (MD) simulation has been widely used in the field of biomedicine to study the conformational transition of proteins caused by mutation or ligand binding/unbinding. It provides some perspectives those are difficult to find in traditional biochemical or pathological experiments, for example, detailed effects of mutations on protein structure and protein-protein/ligand interaction at the atomic level. In this review, a broad overview on conformation changes and drug discovery by MD simulation is given. We first discuss the preparation of protein structure for MD simulation, which is a key step that determines the accuracy of the simulation. Then, we summarize the applications of commonly used force fields and MD simulations in scientific research. Finally, enhanced sampling methods and common applications of these methods are introduced. In brief, MD simulation is a powerful tool and it can be used to guide experimental study. The combination of MD simulation and experimental techniques is an a priori means to solve the biomedical problems and give a deep understanding on the relationship between protein structure and function.

NeuralDock: Rapid and Conformation-Agnostic Docking of Small Molecules

Virtual screening is a cost- and time-effective alternative to traditional high-throughput screening in the drug discovery process. Both virtual screening approaches, structure-based molecular docking and ligand-based cheminformatics, suffer from computational cost, low accuracy, and/or reliance on prior knowledge of a ligand that binds to a given target. Here, we propose a neural network framework, NeuralDock, which accelerates the process of high-quality computational docking by a factor of 106, and does not require prior knowledge of a ligand that binds to a given target. By approximating both protein-small molecule conformational sampling and energy-based scoring, NeuralDock accurately predicts the binding energy, and affinity of a protein-small molecule pair, based on protein pocket 3D structure and small molecule topology. We use NeuralDock and 25 GPUs to dock 937 million molecules from the ZINC database against superoxide dismutase-1 in 21 h, which we validate with physical docking using MedusaDock. Due to its speed and accuracy, NeuralDock may be useful in brute-force virtual screening of massive chemical libraries and training of generative drug models.