Improving ligand-ranking of AutoDock Vina by changing the empirical parameters

The secoiridoid glycoside Gentiopicroside is a USP22 inhibitor with potent antitumor immunotherapeutic activity

Over the past decade, immunotherapies have brought about significant changes in how we approach the treatment of various solid tumors and blood-related cancers. However, the effectiveness of checkpoint blockade therapy has been constrained to a rate of under 30 %. A significant challenge in the realm of tumor immunotherapy revolves around comprehending the mechanisms through which regulatory T (Treg) cells induce immunosuppression. We have recently discovered that USP22 (ubiquitin-specific peptidase 22) a deubiquitinating enzyme that is increased in various tumors, is an oncogene and controls Treg immune suppressive activity for tumor evasion, providing a rationale for USP22 targeting to achieve both onco- and immuno-therapeutic efficacies. Herein, we identified the traditional Chinese secoiridoid compound gentiopicroside as a USP22 inhibitor. Gentiopicroside treatment decreased the forkhead box P3 (Foxp3) expression, which subsequently reduced Treg immune suppressive activity. Treatment of cancer cells by gentiopicroside resulted in an increase in histone 2B monoubiquitination (H2Bub) in a USP22-dependent manner and a decrease in programmed cell death ligand 1 (PD-L1) expression, both of which are known as USP22-specific substrates. Docking and molecular dynamic simulation revealed that gentiopicroside stably binds to USP22 catalytic pocket, supporting that gentiopicroside is a USP22 inhibitor. Importantly, administration of gentiopicroside to mice significantly inhibited the growth of syngenetic lung adenocarcinoma. Further analysis of intratumoral immune cells revealed a dramatic increase CD8+ T cell production of IFN-γ and granzyme B (GZMB), confirming that gentiopicroside enhances antitumor immunity. Our study revealed that gentiopicroside is a USP22-specific inhibitor with potent antitumor therapeutic potentials.

Organophosphate esters uptake, translocation and accumulation in rice (Oryza sativa L.): impacts of lipid transporters and chemical properties

To explore key factors involved in the uptake, translocation and accumulation of organophosphate esters (OPEs), computer simulation analysis and hydroponic experiments were executed. Lipid transporters with stocky-like active (SAC) cavities usually showed stronger binding affinities with the OPEs, especially when the SAC cavities belong to the Fish Trap model according to molecular docking. In our hydroponic trial, the binding affinity and gene expression of the lipid transporters and log Kow of the OPEs could be charged to the uptake, translocation and accumulation of the OPEs; however, these three factors played various important roles in roots and shoots. In detail, the effect of gene expression and binding affinity were stronger than log Kow in roots uptake and accumulation, but the result was the opposite in the shoots translocation. Transporters OsTIL and OsLTPL1 among all investigated transporters could play key roles in transporter-mediated OPE uptake, translocation and accumulation in the roots and shoots. OsMLP could be involved in the bidirected vertical translocation of the OPEs. OsLTP2 and OsLTP4 mainly acted as transporters of the OPEs in roots.

CBD Versus CBDP: Comparing In Vitro Receptor-Binding Activities

Phytocannabinoids with seven-carbon alkyl chains (phorols) have gained a lot of attention, as they are commonly believed to be more potent versions of typical cannabinoids with shorter alkyl chains. At the time of this article, cannabidiphorol (CBDP) and tetrahydrocannabiphorol (THCP) can both be purchased in the North American market, even though their biological activities are nearly unknown. To investigate their relative potency, we conducted in vitro receptor-binding experiments with CBDP (cannabinoid CB1/CB2 receptor antagonism, serotonin 5HT-1A agonism, dopamine D2S (short form) agonism, and mu-opioid negative allosteric modulation) and compared the observed activity with that of CBD. To our knowledge, this is the first publication to investigate CBDP's receptor activity in vitro. A similar activity profile was observed for both CBD and CBDP, with the only notable difference at the CB2 receptor. Contrary to common expectations, CBD was found to be a slightly more potent CB2 antagonist than CBDP (p < 0.05). At the highest tested concentration, CBD demonstrated antagonist activity with a 33% maximum response of SR144528 (selective CB2 antagonist/inverse agonist). CBDP at the same concentration produced a weaker antagonist activity. A radioligand binding assay revealed that among cannabinoid and serotonin receptors, CB2 is likely the main biological target of CBDP. However, both CBD and CBDP were found to be significantly less potent than SR144528. The interaction of CBDP with the mu-opioid receptor (MOR) produced unexpected results. Although the cannabidiol family is considered to be a set of negative allosteric modulators (NAMs) of opioid receptors, we observed a significant increase in met-enkephalin-induced mu-opioid internalization when cells were incubated with 3 µM of CBDP and 1 µM met-enkephalin, a type of activity expected from positive allosteric modulators (PAMs). To provide a structural explanation for the observed PAM effect, we conducted molecular docking simulations. These simulations revealed the co-binding potential of CBDP (or CBD) and met-enkephalin to the MOR.

MedChemExpress compounds prevent neuraminidase N1 via physics- and knowledge-based methods

Influenza A viruses spread out worldwide, causing several global concerns. Hence, discovering neuraminidase inhibitors to prevent the influenza A virus is of great interest. In this work, a machine learning model was employed to evaluate the ligand-binding affinity of ca. 10 000 compounds from the MedChemExpress (MCE) database for inhibiting neuraminidase. Atomistic simulations, including molecular docking and molecular dynamics simulations, then confirmed the ligand-binding affinity. Furthermore, we clarified the physical insights into the binding process of ligands to neuraminidase. It was found that five compounds, including micronomicin, didesmethyl cariprazine, argatroban, Kgp-IN-1, and AY 9944, are able to inhibit neuraminidase N1 of the influenza A virus. Ten residues, including Glu119, Asp151, Arg152, Trp179, Gln228, Glu277, Glu278, Arg293, Asn295, and Tyr402, may be very important in controlling the ligand-binding process to N1.

Using In Silico Molecular Docking to Explain Differences in Receptor Binding Behavior of HHC and THCV Isomers: Revealing New Binding Modes

Even slight structural differences between phytocannabinoid isomers are usually enough to cause a change in their biological properties. In this study, we used in vitro CB1 agonism/antagonism assays to compare the receptor binding functionality of THCV (tetrahydrocannabivarin) and HHC (hexahydrocannabinol) isomers and applied molecular docking to provide an explanation for the difference in the activities. No CB1 agonism was observed for ∆9- and ∆8-THCV. Instead, both isomers antagonized CP 55940, with ∆9-THCV being approximately two times more potent than the ∆8 counterpart (IC50 = 52.4 nM and 119.6 nM for ∆9- and ∆8-THCV, respectively). Docking simulations found two binding poses for THCV isomers, one very similar to ∆9-THC and one newly discovered pose involving the occupation of side pocket 1 of the CB1 receptor by the alkyl chain of the ligand. We suggested the latter as a potential antagonist pose. In addition, our results established 9R-HHC and 9S-HHC among partial agonists of the CB1 receptor. The 9R-HHC (EC50 = 53.4 nM) isomer was a significantly more potent agonist than 9S (EC50 = 624.3 nM). ∆9-THC and 9R-HHC showed comparable binding poses inside the receptor pocket, whereas 9S-HHC adopted a new and different binding posture that can explain its weak agonist activity.

Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds

To date, the COVID-19 pandemic has still been infectious around the world, continuously causing social and economic damage on a global scale. One of the most important therapeutic targets for the treatment of COVID-19 is the main protease (Mpro) of SARS-CoV-2. In this study, we combined machine-learning (ML) model with atomistic simulations to computationally search for highly promising SARS-CoV-2 Mpro inhibitors from the representative natural compounds of the National Cancer Institute (NCI) Database. First, the trained ML model was used to scan the library quickly and reliably for possible Mpro inhibitors. The ML output was then confirmed using atomistic simulations integrating molecular docking and molecular dynamic simulations with the linear interaction energy scheme. The results turned out to show that there was evidently good agreement between ML and atomistic simulations. Ten substances were proposed to be able to inhibit SARS-CoV-2 Mpro. Seven of them have high-nanomolar affinity and are very potential inhibitors. The strategy has been proven to be reliable and appropriate for fast prediction of SARS-CoV-2 Mpro inhibitors, benefiting for new emerging SARS-CoV-2 variants in the future accordingly.

Natural compounds inhibit Monkeypox virus methyltransferase VP39 in silico studies

VP39, an essential 2'-O-RNA methyltransferase enzyme discovered in Monkeypox virus (MPXV), plays a vital role in viral RNA replication and transcription. Inhibition of the enzyme may prevent viral replication. In this context, using a combination of molecular docking and molecular dynamics (MDs) simulations, the inhibitory ability of NCI Diversity Set VII natural compounds to VP39 protein was investigated. It should be noted that the computed binding free energy of ligand via molecular docking and linear interaction energy (LIE) approaches are in good agreement with the corresponding experiments with coefficients of R = 0.72 and 0.75, respectively. NSC 319990, NSC 196515 and NSC 376254 compounds were demonstrated that can inhibit MPVX methyltransferase VP39 protein with the similar affinity compared to available inhibitor sinefungin. Moreover, nine residues involving Gln39, Gly68, Gly72, Asp95, Arg97, Val116, Asp138, Arg140 and Asn156 may be argued that they play an important role in binding process of inhibitors to VP39.Communicated by Ramaswamy H. Sarma.

Tinctoric acid A-B, two new hopan-type triterpenoids from the Vietnamese lichen, Parmotrema tinctorum (Despr. ex Nyl.) hale with α-glucosidase inhibitory activity

Two new hopan-type triterpenoids, namely tinctoric acid A-B (1-2), were isolated from the lichen Parmotrema tinctorum (Despr. ex Nyl.) Hale. Their structures were elucidated by extensive spectroscopic analyses (1D and 2D NMR). The absolute configuration at C-22 of 1 was established through DP4 probability. Compounds 1-2 were evaluated for their inhibitory activity against α-glucosidase and found to be more potent than those of positive control (acarbose, IC50 168 µM) with values IC50 74.7 and 98.2 µM, respectively. Both of these compounds interacted well with enzyme α-glucosidase MAL32 through H-bonds and hydrophobic interaction.

Adsorption of Diclofenac and PFBS on a Hair Keratin Dimer

Environmental pollution by man-made toxic and persistent organic compounds, found throughout the world in surface and groundwater, has various negative effects on aquatic life systems and even humans. Therefore, it is important to develop and improve water treatment technologies capable of removing such substances from wastewater and purifying drinking water. The two substances investigated are the widely used painkiller diclofenac and a member of the class of "forever chemicals", perfluorobutanesulfonate. Both are known to have serious negative effects on living organisms, especially under long-term exposure, and are detectable in human hair, suggesting adsorption to a part of the hair fiber complex. In this study, a human hair keratin dimer is investigated for its ability to absorb diclofenac and perfluorobutanesulfonate. Initial predictions for binding sites are obtained via molecular docking and subjected to molecular dynamics simulations for more than 1 μs. The binding affinities obtained by the linear interaction energy method are high enough to motivate further research on human hair keratins as a sustainable, low-cost, and easily allocatable filtration material.

In Vitro and in Silico Analysis of α -Amylase Inhibitory Activity of Ethanolic Extract of Adhatoda vasica Leaves

Objective

Diabetic individuals have a higher probability of suffering from illness and death due to small blood vessel-related problems such as retinopathy, neuropathy, nephropathy, and stroke than other complications. There are many synthetic anti-diabetic agents available, but these can be expensive and have undesirable pathological effects. The enzyme α-amylase (hydrolase), catalyzes the hydrolysis of starch to maltose and glucose via the cleavage of α-1,4-glucosidic linkages. Diabetes mellitus patients may benefit from a therapeutic strategy that involves slowing the hydrolysis of starch by inhibiting the activity of α-amylase. Thus, looking for cost-effective, natural, and safe antidiabetic agents is essential. This study aims to screen phytoconstituents and evaluate the in-vitro and in-silico α-amylase inhibitory activity of the ethanolic extract of Adhatoda vasica leaves.

Methods

The extraction of Adhatoda vasica leaves was performed using ethanol via the Soxhlet extraction process. Different concentrations (100 μg/mL to 1000 μg/mL) of ethanolic extract, Acarbose, and Sitagliptin, were prepared and evaluated for α-amylase inhibitory activity using the spectrophotometric method. Molecular docking (AutodockVina 1.2.0) and toxicity profiling (SToPToX web server) studies were performed.

Results

The ethanolic extract of Adhatoda vasica leaves showed the highest percentage inhibition against α-amylase (56.763 ± 0.0035) at a concentration of 1000 μg/mL. The in-silico study supported this inhibitory activity. Vasicoline (C5) and Quercetin (C9), the active constitute of Adhatoda vasica, showed the best binding energies of -8.3 and -8.0 Kcal/mol, respectively against α-amylase enzyme (PDBID: 4W93). A toxicity study revealed the safety profile of the plant extract.

Conclusion

It was concluded that Adhatoda vasica leaves possess some bioactive compounds that are responsible for controlling blood glucose levels, and their identification, purification, and isolation may lead to the development of new therapeutic agents with fewer side effects than the available drugs.

Calculation of binding affinity of JAK1 inhibitors via accurately computational estimation

Janus kinase 1 (JAK1) is a tyrosine kinase that is involved in the initiation of responses to a number of different cytokine receptor families. The JAK1-dependent pathway is a therapeutic target, and several JAK inhibitors have been developed thanks to intensive research. However, since the ATP binding sites of JAK family members are quite alike, JAK1 inhibitors can thus be less selective, resulting in unanticipated adverse effects. Despite this, minor variations in the ATP-binding site have been extensively used to find a variety of small compounds with different inhibitory properties. Stronger binding affinity of JAK1 inhibitors is believed to be able to reduce the negative effects, leading to better treatment results. Therefore, a thorough computational search that can effectively identify ligands with extremely high binding affinity for JAK1 to serve as promising inhibitors is required. Here, a method combining steered-molecular dynamic (SMD) simulations with a modified linear interaction energy (LIE) model has been developed to evaluate the binding affinities of known JAK1 inhibitors. The correlation coefficient between the estimated and experimental values was 0.72 and a root-mean-square error was 0.97 kcal•mol-1, revealing that the SMD/LIE method can precisely and quickly predict the binding free energies of JAK1 inhibitors. Furthermore, three marine fungus-derived compounds, namely hansforesters E, hansforesters G and tetroazolemycins B, were identified to be particularly promising JAK1 inhibitors, accordingly. These findings show that the SMD/LIE method has a lot of promise for in silico screening of possible JAK1 inhibitors from a vast number of compounds that are now accessible.Communicated by Ramaswamy H. Sarma.

Computational insight into stability-enhanced systems of anthocyanin with protein/peptide

Anthocyanins, which belong to the flavonoid group, are commonly found in the organs of plants native to South and Central America. However, these pigments are unstable under conditions of varying pH, heat, etc., which limits their potential applications. One method for preserving the stability of anthocyanins is through encapsulation using proteins or peptides. Nevertheless, the complex and diverse structure of these molecules, as well as the limitation of experimental technologies, have hindered a comprehensive understanding of the encapsulation processes and the mechanisms by which stability is enhanced. To address these challenges, computational methods, such as molecular docking and molecular dynamics simulation have been used to study the binding affinity and dynamics of interactions between proteins/peptides and anthocyanins. This review summarizes the mechanisms of interaction between these systems, based on computational approaches, and highlights the role of proteins and peptides in the stability enhancement of anthocyanins. It also discusses the current limitations of these methods and suggests possible solutions.

Identification of potential novel inhibitors against glutamine synthetase enzyme of Leishmania major by using computational tools

Glutamine Synthetase (GS) is functionally important in many pathogens, so its viability as a drug target has been widely investigated. We identified Leishmania major glutamine synthetase (Lm-GS) as an appealing target for developing potential leishmaniasis inhibitors. Comparative modeling, virtual screening, MD simulations along with MM-PBSA analyses were performed and two FDA approved compounds namely Chlortalidone (id ZINC00020253) and Ciprofloxacin (id ZINC00020220) were identified as potential inhibitor among the screened library. These compounds may be used as a lead molecule, although additional in vitro and in vivo testing is required to establish its anti-leishmanial effect. Hence, the goal of this study was to locate and identify certain medications that were previously FDA-approved for definite disorders and that might show anti-leishmanial effect. Due to GS's presence in additional Leishmania species, a novel medication docked with Lm-GS may have broad anti-leishmania efficacy.Communicated by Ramaswamy H. Sarma.

Approaching the Dimerization Mechanism of Small Molecule Inhibitors Targeting PD-L1 with Molecular Simulation

Inhibitors blocking the PD-1/PD-L1 immune checkpoint demonstrate impressive anti-tumor immunity, and small molecule inhibitors disclosed by the Bristol-Myers Squibb (BMS) company have become a hot topic. In this work, by modifying the carbonyl group of BMS-202 into a hydroxyl group to achieve two enantiomers (MS and MR) with a chiral center, we found that this is an effective way to regulate its hydrophobicity and thus to reduce the negative effect of polar solvation free energy, which enhances the stability of PD-L1 dimer/inhibitor complexes. Moreover, we studied the binding modes of BMS-200 and BMS-202-related small molecule inhibitors by molecular dynamics simulation to explore their inhibitory mechanism targeting PD-L1 dimerization. The results showed that the size exclusion effect of the inhibitors triggered the rearrangement of the residue _ATyr56, leading to the formation of an axisymmetric tunnel-shaped pocket, which is an important structural basis for improving the binding affinity of symmetric inhibitors with PD-L1. Furthermore, after inhibitor dissociation, the conformation of _ATyr123 and _BMet115 rearranged, which blocked the entrance of the binding pocket, while the reverse rearrangements of the same residues occurred when the PD-L1 monomer was complexed with the inhibitors, preparing PD-L1 for dimerization. Overall, this study casts a new light on the inhibitory mechanism of BMS inhibitors targeting PD-L1 dimerization and provides an idea for designing novel small molecule inhibitors for future cancer immunotherapy.

Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches

Computational approaches, including physics- and knowledge-based methods, have commonly been used to determine the ligand-binding affinity toward SARS-CoV-2 main protease (Mpro or 3CLpro). Strong binding ligands can thus be suggested as potential inhibitors for blocking the biological activity of the protease. In this context, this paper aims to provide a short review of computational approaches that have recently been applied in the search for inhibitor candidates of Mpro. In particular, molecular docking and molecular dynamics (MD) simulations are usually combined to predict the binding affinity of thousands of compounds. Quantitative structure-activity relationship (QSAR) is the least computationally demanding and therefore can be used for large chemical collections of ligands. However, its accuracy may not be high. Moreover, the quantum mechanics/molecular mechanics (QM/MM) method is most commonly used for covalently binding inhibitors, which also play an important role in inhibiting the activity of SARS-CoV-2. Furthermore, machine learning (ML) models can significantly increase the searching space of ligands with high accuracy for binding affinity prediction. Physical insights into the binding process can then be confirmed via physics-based calculations. Integration of ML models into computational chemistry provides many more benefits and can lead to new therapies sooner.

Integrated plasma pharmacochemistry and network pharmacology to explore the mechanism of Gerberae Piloselloidis Herba in treatment of allergic asthma

ETHNOPHARMACOLOGICAL RELEVANCE

Gerberae Piloselloidis Herba (GPH), a commonly used traditional medicine in China, is derived from Gerbera piloselloides (Linn.) Cass. It is featured by its special bioactivities as antitussive, expectorant, anti-asthma, anti-bacterial, anti-tumor, uterine analgesia, and immunity-enhancing. With a long history of medication in ethnic minority areas in China, it is often used as an effective treatment for cough and sore throat as well as allergic asthma. Although our previous investigation also has discovered GPH performed effective treatment on allergic asthma, its underlying mechanism remains unclear.

AIM OF THE STUDY

This research aims to reveal the pharmacological mechanism of GPH in the treatment for allergic asthma through combination of plasma pharmacology and network pharmacology.

MATERIALS AND METHODS

Firstly, the components of GPH in blood samples were identified using UHPLC- Q-Orbitrap HRMS. An interaction network of "compound-target-disease" was constructed based on the compounds confirmed in blood and on their corresponding targets of allergic asthma acquired from disease gene databases, predicting the possible biological targets and potential signal pathways of GPH with the network pharmacology analysis. Then, a molecular docking between the blood ingredients and the core targets was carried out using the Autodock Vina software. Subsequently, after establishing a mouse model with allergic asthma induced by ovalbumin (OVA), the effect of GPH on allergic asthma was evaluated by analyzing a series of indicators including behavior, lung pathological changes, inflammatory factors in serum and bronchoalveolar lavage fluid (BALF). Finally, the key pathway and targets predicted by network pharmacology and molecular docking were further verified using Western blot analysis.

RESULTS

Eleven chemical constituents (such as arbutin, neochlorogenic acid, chlorogenic acid, etc.) were identified through the analysis of plasma samples, on which basis a total of 142 genes intersecting GPH and allergic asthma were collected by network pharmacology. After performing enrichment analysis of these genes in gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG), it was found that arbutin-related targets mainly focused on phosphatidylinositol 3 kinase (PI3K)/protein kinase B (Akt) signal pathway, while luteolin and marmesin -related targets tended to locate at Interleukin-17 (IL-17) signal pathway. Meanwhile, the findings of molecular docking suggested that such components as arbutin, luteolin and marmesin entering into blood had good binding with the core targets related to PI3K/Akt and IL-17 pathways. In addition, GPH improved the OVA-induced asthma symptoms, the alveolar septa thickening and the infiltration of inflammatory cell around bronchi and bronchioles as well as reduced the levels of IgE, IL-8 and TNF-α in serum or BALF. Furthermore, GPH could inhibit the phosphorylation level of Akt and the expression of PI3K, an efficacy supported by the findings by way of Western blot which suggests that GPH in the treatment of allergic asthma was linked to PI3K/Akt signal pathway.

CONCLUSION

In this study, a comprehensive strategy to combine the UPLC-Q-Orbitrap HRMS with network pharmacology was employed to clarify the mechanism of GPH against allergic asthma, a finding where GPH may inhibit PI3K/Akt signal pathway to protect mice from OVA-induced allergic asthma. This study provides a deeper understanding of the pharmacological mechanism of GPH in treatment of asthma, offering a scientific reference for further research and clinical application of GPH in terms of allergic asthma.

Multitargeted Molecular Docking and Dynamic Simulation Studies of Bioactive Compounds from Rosmarinus officinalis against Alzheimer’s Disease

Alzheimer’s disease (AD) has been associated with the hallmark features of cholinergic dysfunction, amyloid beta (Aβ) aggregation and impaired synaptic transmission, which makes the associated proteins, such as β-site amyloid precursor protein cleaving enzyme 1 (BACE I), acetylcholine esterase (AChE) and synapsin I, II and III, major targets for therapeutic intervention. The present study investigated the therapeutic potential of three major phytochemicals of Rosmarinus officinalis, ursolic acid (UA), rosmarinic acid (RA) and carnosic acid (CA), based on their binding affinity with AD-associated proteins. Detailed docking studies were conducted using AutoDock vina followed by molecular dynamic (MD) simulations using Amber 20. The docking analysis of the selected molecules showed the binding energies of their interaction with the target proteins, while MD simulations comprising root mean square deviation (RMSD), root mean square fluctuation (RMSF) and molecular mechanics/generalized born surface area (MM/GBSA) binding free energy calculations were carried out to check the stability of bound complexes. The drug likeness and the pharmacokinetic properties of the selected molecules were also checked through the Lipinski filter and ADMETSAR analysis. All these bioactive compounds demonstrated strong binding affinity with AChE, BACE1 and synapsin I, II and III. The results showed UA and RA to be potential inhibitors of AChE and BACE1, exhibiting binding energies comparable to those of donepezil, used as a positive control. The drug likeness and pharmacokinetic properties of these compounds also demonstrated drug-like characteristics, indicating the need for further in vitro and in vivo investigations to ascertain their therapeutic potential for AD.

Novel Efficient Multistage Lead Optimization Pipeline Experimentally Validated for DYRK1B Selective Inhibitors

In addition to general challenges in drug discovery such as the identification of lead compounds in time- and cost-effective ways, specific challenges also exist. Particularly, it is necessary to develop pharmacological inhibitors that effectively discriminate between closely related molecular targets. DYRK1B kinase is considered a valuable target for cancer-specific mono- or combination chemotherapy; however, the inhibition of its closely related DYRK1A kinase is not beneficial. Existing inhibitors target both kinases with essentially the same efficiency, and the unavailability of the DYRK1B crystal structure makes the discovery of DYRK1B-specific inhibitors even more challenging. Here, we propose a novel multi-stage compound discovery pipeline aimed at in silico identification of both potent and selective small molecules from a large set of initial candidates. The method uses structure-based docking and ligand-based quantitative structure–activity relationship modeling. This approach allowed us to identify lead and runner-up small-molecule compounds targeting DYRK1B with high efficiency and specificity.

The mechanism of dioscin preventing lung cancer based on network pharmacology and experimental validation

ETHNOPHARMACOLOGICAL RELEVANCE

Dioscorea nipponica Makino as a Chinese folk medicine has been used for the treatment of chronic bronchitis, cough, and asthma. Several studies have established the antimetastatic potential of Dioscorea nipponica Makino extract. Dioscin is a major bioactive compound in Dioscorea nipponica Makino and has anti-tumor property in lung cancer cell lines. However, the preventive effect of dioscin against lung cancer and its key mechanism haven't been identified yet.

AIM OF STUDY

To identify the prevention effect of dioscin on lung cancer and explore its key mechanism based on network pharmacology and experimental validation.

METHODS

The potential targets of dioscin were obtained from the HERB database. The therapeutic targets of lung cancer were acquired from the GeneCards database. Protein-protein interaction network (PPI) was constructed in the STRING 11.0 database. The David database was used for enrichment analysis. Molecular Docking was finished by the AutoDock Vina. NSCLC cell lines and mouse lung cancer model were used to confirm the prevention effect of dioscin on lung cancer and its key mechanism.

RESULTS

76 potential targets of dioscin were identified to be involved in lung cancer treatment, which refer to 512 biological processes, 47 molecular functions, 77 cellular components and 107 signal pathways. The molecular docking suggested that dioscin might bind to AKT1, Caspase3, TP53, C-JUN and IL-6. The DARTS indicated that dioscin could bind to AKT1. In vitro, dioscin could decrease proliferation, invasion and migration in A549 and PC-9 cells with the significant reduction in the expression of p-AKT, MMP2, and PCNA. In vivo, dioscin could reduce lung nodules, lung injury, and mortality in mouse lung cancer model with reducing the expression of p-AKT, MMP2, PCNA and increasing the expression of active-caspase3.

CONCLUSION

Dioscin could prevent lung cancer and its key target is AKT1 kinase, a center protein of PI3K/AKT signaling pathway.

Identifying Possible AChE Inhibitors from Drug-like Molecules via Machine Learning and Experimental Studies

Acetylcholinesterase (AChE) is one of the most important drug targets for Alzheimer's disease (AD) treatment. In this work, a machine learning model was trained to rapidly and accurately screen large chemical databases for the potential inhibitors of AChE. The obtained results were then validated via in vitro enzyme assay. Moreover, atomistic simulations including molecular docking and molecular dynamics simulations were then used to understand molecular insights into the binding process of ligands to AChE. In particular, two compounds including benzyl trifluoromethyl ketone and trifluoromethylstyryl ketone were indicated as highly potent inhibitors of AChE because they established IC₅₀ values of 0.51 and 0.33 μM, respectively. The obtained IC₅₀ of two compounds is significantly lower than that of galantamine (2.10 μM). The predicted log(BB) suggests that the compounds may be able to traverse the blood-brain barrier. A good agreement between computational and experimental studies was observed, indicating that the hybrid approach can enhance AD therapy.

Evaluation of the binding performance of flavonoids to estrogen receptor alpha by Autodock, Autodock Vina and Surflex-Dock

Molecular docking is a widely used method to predict the binding modes of small-molecule ligands to the target binding site. However, it remains a challenge to identify the correct binding conformation and the corresponding binding affinity for a series of structurally similar ligands, especially those with weak binding. An understanding of the various relative attributes of popular docking programs is required to ensure a successful docking outcome. In this study, we systematically compared the performance of three popular docking programs, Autodock, Autodock Vina, and Surflex-Dock for a series of structurally similar weekly binding flavonoids (22) binding to the estrogen receptor alpha (ERα). For these flavonoids-ERα interactions, Surflex-Dock showed higher accuracy than Autodock and Autodock Vina. The hydrogen bond overweighting by Autodock and Autodock Vina led to incorrect binding results, while Surflex-Dock effectively balanced both hydrogen bond and hydrophobic interactions. Moreover, the selection of initial receptor structure is critical as it influences the docking conformations of flavonoids-ERα complexes. The flexible docking method failed to further improve the docking accuracy of the semi-flexible docking method for such chemicals. In addition, binding interaction analysis revealed that 8 residues, including Ala350, Glu353, Leu387, Arg394, Phe404, Gly521, His524, and Leu525, are the key residues in ERα-flavonoids complexes. This work provides reference for assessing molecular interactions between ERα and flavonoid-like chemicals and provides instructive information for other environmental chemicals.