In silico insight into voltage-gated sodium channel 1.7 inhibition for anti-pain drug discovery

Carbenoid-involved reactions integrated with scaffold-based screening generates a Nav1.7 inhibitor

The discovery of selective Nav1.7 inhibitors is a promising approach for developing anti-nociceptive drugs. In this study, we present a novel oxindole-based readily accessible library (OREAL), which is characterized by readily accessibility, unique chemical space, ideal drug-like properties, and structural diversity. We used a scaffold-based approach to screen the OREAL and discovered compound C4 as a potent Nav1.7 inhibitor. The bioactivity characterization of C4 reveals that it is a selective Nav1.7 inhibitor and effectively reverses Paclitaxel-induced neuropathic pain (PINP) in rodent models. Preliminary toxicology study shows C4 is negative to hERG. The consistent results of molecular docking and molecular simulations further support the reasonability of the in-silico screening and show the insight of the binding mode of C4. Our discovery of C4 paves the way for pushing the Nav1.7-based anti-nociceptive drugs forward to the clinic.

Finding new analgesics: Computational pharmacology faces drug discovery challenges

Despite the worldwide prevalence and huge burden of pain, pain is an undertreated phenomenon. Currently used analgesics have several limitations regarding their efficacy and safety. The discovery of analgesics possessing a novel mechanism of action has faced multiple challenges, including a limited understanding of biological processes underpinning pain and analgesia and poor animal-to-human translation. Computational pharmacology is currently employed to face these challenges. In this review, we discuss the theory, methods, and applications of computational pharmacology in pain research. Computational pharmacology encompasses a wide variety of theoretical concepts and practical methodological approaches, with the overall aim of gaining biological insight through data acquisition and analysis. Data are acquired from patients or animal models with pain or analgesic treatment, at different levels of biological organization (molecular, cellular, physiological, and behavioral). Distinct methodological algorithms can then be used to analyze and integrate data. This helps to facilitate the identification of biological molecules and processes associated with pain phenotype, build quantitative models of pain signaling, and extract translatable features between humans and animals. However, computational pharmacology has several limitations, and its predictions can provide false positive and negative findings. Therefore, computational predictions are required to be validated experimentally before drawing solid conclusions. In this review, we discuss several case study examples of combining and integrating computational tools with experimental pain research tools to meet drug discovery challenges.

Leveraging a meta-learning approach to advance the accuracy of Nav blocking peptides prediction

The voltage-gated sodium (Nav) channel is a crucial molecular component responsible for initiating and propagating action potentials. While the α subunit, forming the channel pore, plays a central role in this function, the complete physiological function of Nav channels relies on crucial interactions between the α subunit and auxiliary proteins, known as protein-protein interactions (PPI). Nav blocking peptides (NaBPs) have been recognized as a promising and alternative therapeutic agent for pain and itch. Although traditional experimental methods can precisely determine the effect and activity of NaBPs, they remain time-consuming and costly. Hence, machine learning (ML)-based methods that are capable of accurately contributing in silico prediction of NaBPs are highly desirable. In this study, we develop an innovative meta-learning-based NaBP prediction method (MetaNaBP). MetaNaBP generates new feature representations by employing a wide range of sequence-based feature descriptors that cover multiple perspectives, in combination with powerful ML algorithms. Then, these feature representations were optimized to identify informative features using a two-step feature selection method. Finally, the selected informative features were applied to develop the final meta-predictor. To the best of our knowledge, MetaNaBP is the first meta-predictor for NaBP prediction. Experimental results demonstrated that MetaNaBP achieved an accuracy of 0.948 and a Matthews correlation coefficient of 0.898 over the independent test dataset, which were 5.79% and 11.76% higher than the existing method. In addition, the discriminative power of our feature representations surpassed that of conventional feature descriptors over both the training and independent test datasets. We anticipate that MetaNaBP will be exploited for the large-scale prediction and analysis of NaBPs to narrow down the potential NaBPs.

Structure-based virtual screening of natural compounds against wild and mutant (R1155K, A1156T and D1168A) NS3-4A protease of Hepatitis C virus

NS3-4A, a serine protease, is a primary target for drug development against Hepatitis C Virus (HCV). However, the effectiveness of potent next-generation protease inhibitors is limited by the emergence of mutations and resulting drug resistance. To address this, in this study a structure-based drug design approach is employed to screen a large library of 7320 natural compounds against both wild-type and mutant variants of NS3-4A protease. Telaprevir, a widely used protease inhibitor, was recruited as the control drug. The top 10 compounds with favorable binding affinities underwent drug-likeness evaluation. Based on ADMET studies, complexes of NP_024762 and NP_006776 were selected for molecular dynamic simulations. Principal component analysis (PCA) was employed to explore the conformational space and protein dynamics of the protein-ligand complex using a Free Energy Landscape (FEL) approach. The cosine values obtained from FEL analysis ranged from 0 to 1, and eigenvectors with cosine values below 0.2 were chosen for further analysis. To forecast binding free energies and evaluate energy contributions per residue, the MM-PBSA method was employed. The results highlighted the crucial role of amino acids in the catalytic domain for the binding of the protease with phytochemicals. Stable associations between the top compounds and the target protease were confirmed by the formation of hydrogen bonds in the binding pocket involving residues: His1057, Gly1137, Ser1139, and Ala1157. These findings suggest the potential of these compounds for further validation through biological evaluation.Communicated by Ramaswamy H. Sarma.

Design, synthesis, and biological evaluation of low-toxic lappaconitine derivatives as potential analgesics

The C₁₈-diterpenoid alkaloid lappaconitine (LA) is a non-addictive analgesic used in China. The toxicity (LD₅₀ = 11.7 mg/kg) limits its application. Two series of LA derivatives, including amides and sulfonamides (1-93), were designed and synthesized by modification on their C4 acetamidobenzoate side chains in this work. In vivo analgesic activity and toxicity of all derivatives were evaluated, and the structure-activity relationship was summarized. Six lead compounds (35, 36, 39, 49, 70, and 89) exhibited approximate analgesic activity to LA but with significantly reduced toxicity. The therapeutic index of these compounds is 14-30 times that of LA. In vivo metabolism study of the lead compounds 39, 49, 70, and 89 were conducted by UPLC-MS^E, indicating the reason for the low toxicity of the potential derivatives might be they are difficult to metabolize to toxic metabolite N-deacetyllappaconitine compared to LA. The effects of lead compounds on sodium channels and hERG channels were also studied by ion channel reader (ICR) which further revealed their analgesic and toxicity-attenuating mechanisms. Sodium channel assay revealed that the analgesic mechanism of these lead compounds was inhibiting the Na_v 1.7 channels. Taken together, compound 39 was provided as a new analgesic lead compound with significantly low toxicity and comparable activity to LA.

Identification of natural compounds targeting SARS-CoV-2 Mpro by virtual screening and molecular dynamics simulations

The SARS-CoV-2 main protease (Mpro) has been chosen as a conserved molecular target to develop broad-spectrum antiviral drugs. Using molecular docking and molecular dynamics (MD) simulations, a total of 5600 natural compounds available for virtual screening were tested to identify potential inhibitors of SARS-CoV-2 Mpro. As a result, three natural compounds (pentagalloylglucose, malonylawobanin and gnetin E dihydride) were found to be potential inhibitors of SARS-CoV-2, which confirms the theoretical and practical significance of this approach for the design of SARS-CoV-2 inhibitors.

CK-3, A Novel Methsulfonyl Pyridine Derivative, Suppresses Hepatocellular Carcinoma Proliferation and Invasion by Blocking the PI3K/AKT/mTOR and MAPK/ERK Pathways

Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis that highly expresses phosphatidylinositol 3-kinase (PI3K) and mitogen-activated protein kinase (ERK). The PI3K/AKT/mTOR and MAPK/ERK signaling pathways play a crucial role in HCC tumor formation, cell cycle, apoptosis and survival. However, no effective targeted therapies against these pathways is available, mainly due to the extensive and complex negative feedback loops between them. Here we used CK-3, a dual blocker of the PI3K/AKT/mTOR and MAPK/ERK pathways, against HCC cell lines to verify its anti-tumor activity in vitro. CK-3 exhibited cytotoxic activity against HCC, as demonstrated with MTT and colony formation assays. The anti-metastatic potential of CK-3 was demonstrated with wound healing and cell invasion assays. The ability of CK-3 to block both the PI3K/AKT/mTOR and MAPK/ERK pathways was also confirmed. CK-3 induced the apoptosis of Hep3B cells, while Bel7402 cells died via mitotic catastrophe (MC). Oral administration of CK-3 also inhibited the subcutaneous growth of BEL7402 cells in nude mice. Simultaneous PI3K/AKT/mTOR and MAPK/ERK pathway inhibition with CK-3 may be superior to single pathway monotherapies by inhibiting their feedback-regulation, and represents a potential treatment for HCC.

Repurposing of cefpodoxime proxetil as potent neuroprotective agent through computational prediction and in vitro validation

In recent reports, NR2B-NMDA receptor antagonists showed more research value because of its strong targeting ability and less side effects potential. In 2016, EVT-101 was reported to bind in an almost entirely new binding region of this target. Whether strikingly different binding modes can improve targeting and reduce side effects is worth studying. In our preliminary work, we explored the binding patterns of ifenprodil and EVT-101, found the key amino acids and summarized the pharmacophores, hoping to find such antagonists that target the two binding modes simultaneously. In this study, we developed a scalable virtual screening workflow in the FDA-approved drugs library to identify novel NR2B-NMDAR antagonists based on the combination of two pharmacophores. Cefpodoxime proxetil (5) was identified as the hit compound, and it was found for the first time that 5 might have neuroprotective activity as a NR2B-NMDAR antagonist. This result interested us to make further study, the ligand-receptor interactions modeled by molecular docking studies showed that the compound could perfectly merge both the pharmacophore characteristics of ifenprodil and EVT-101 at the binding cavity between the ATDs of GluN1 and GluN2B. The accuracy of molecular docking results and binding stability of ligand-receptor complexes were validated through 100 ns molecular dynamics simulation and binding free energy calculation. Afterwards, MTT assay (49.8%±0.1%, 5 μM) on NMDA injured SH-SY5Y cells and evidence of the effect on attenuating Ca2+ influx induced by NMDA were applied to validate the computational results, further investigation showed that 5 could suppress the NR2B upregulation induced by NMDA. [Formula: see text] Communicated by Ramaswamy H. Sarma.

The structure-based virtual screening of non-benzofuran inhibitors against M. tuberculosis Pks13-TE for anti-tuberculosis phenotypic discovery

Structure-based virtual screening against M. tuberculosis Pks13-TE was performed for anti-tuberculosis phenotypic discovery.

In silico identification of angiotensin-1 converting enzyme inhibitors using text mining and virtual screening

Cardiovascular diseases are the world's leading cause of death. Hypertension is an important risk factor for cardiovascular and renal diseases. Angiotensin-converting enzyme (ACE) can be a possible therapeutic target for managing angiotensin I conversion to angiotensin II and ultimately controlling hypertension. Indole is an significant fragment used in many medicines approved by FDA. For this reason, the molecules in their fragments containing" indol" keywords were taken from the Specs-SC (small compound) database. The predicted therapeutc activity values (TAV) of these compounds against hypertension were evaluated using binary models of QSAR by MetaCore/MetaDrug. For the 26 separate QSAR models of toxicity, molecules with measured TAV greater than 0.5 were used. 3792 non-toxic compounds were investigated by molecular docking study and molecular dynamics simulations for their ACE inhibitory activity. Glide standard precision (SP) of Maestro Molecular Modeling pocket was used to perform molecular docking. Short molecular dynamics (MD) simulations (5-ns) were carried out by initiating the top docking poses of selected 40 molecules. To quantitatively evaluate the predicted binding affinity of a screened compound, average MM/GBSA scores of screened ligands were calculated and based on their binding free energy values, hit compounds were identified for the long (100-ns) MD simulations. Root mean square deviation and root mean square fluctuations were also calculated to assess the structural characteristics and observe fluctuations of the 100-ns time scale. Thus, with the application of text mining and integrated molecular modeling we reported novel indole-based hit inhibitors for ACE-1.Communicated by Ramaswamy H. Sarma.

Homology modeling, molecular dynamics and virtual screening of endothelin-A receptor for the treatment of pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a progressive disease of pulmonary arteries, causing serious shortness of breath and right ventricular failure with high mortality. Numerous studies have verified that the symptoms of PAH could be attenuated effectively with endothelin-A receptor (ETAR) antagonists. Unfortunately, the 3D structure of ETAR has not been released, making it difficult to understand the interactions between ETAR and its antagonists. In this study, computational methods including homology modeling, molecular docking and molecular dynamics simulations were performed to build the structure of ETAR and predict the binding patterns of ETAR with its two antagonists. Based on these results, virtual screening study was implemented against Traditional Chinese Medicine (TCM) database to identify novel natural ETAR antagonists. Six compounds with best binding energies were screened out and two of them were found to bind steadily with ETAR validated through molecular dynamics simulations and MM-GBSA calculation, indicating that they were potential antagonists of ETAR. In a word, our research provided a deep exploration into the interaction between ETAR and its antagonists, which could promote the development of novel therapy against PAH.[Formula: see text]Communicated by Ramaswamy H. Sarma.

Synthesis, biological activity, molecular docking studies of a novel series of 3-Aryl-7H-thiazolo[3,2-b]-1,2,4-triazin-7-one derivatives as the acetylcholinesterase inhibitors

The acetylcholinesterase inhibitors play a critical role in the drug therapy for Alzheimer's disease. In this study, twenty-nine novel 3-aryl-7H-thiazolo[3,2-b]-1,2,4-triazin-7-one derivatives were synthesized and assayed for their human acetylcholinesterase (hAChE) inhibitory activities. Inhibitory ratio values of seventeen compounds were above 55% with 4c having the highest value as 77.19%. The compounds with the halogen atoms in the aromatic ring, and N,N-diethylamino or N,N-dimethylamino groups in the side chains at C-3 positions exhibited good inhibitory activity. SAR study was carried out by means of molecular docking technique. According to molecular docking results, the common interacting site for all compounds were found to be peripheral anionic site whereas highly active compounds were interacting with the catalytic active site too. HIGHLIGHTSA novel series of 3-aryl-7H-thiazolo[3,2-b]-1,2,4-triazin-7-one derivatives were synthesized and assayed for their human acetylcholinesterase (hAChE) inhibitory activities.The SAR study of the target 3-aryl-7H-thiazolo[3,2-b]-1,2,4-triazin-7-one derivatives was summarized.The active sites in the acetylcholinesterase were analyzed by molecular docking technique.Communicated by Ramaswamy H. Sarma.

Discovery of specific HDAC6 inhibitor with anti-metastatic effects in pancreatic cancer cells through virtual screening and biological evaluation

Histone deacetylase 6 (HDAC6) has been demonstrated to play a major role in cell motility and aggresome formation, and HDAC6 inhibition is therefore considered as a promising epigenetic strategy for cancer treatment. At present, only a minority of compounds have been reported as HDAC6 inhibitors, so specific HDAC6 inhibitors with safety profile need to be discovered urgently. In this paper, HDAC6 inhibitors with diverse structures were used to generate the pharmacophore model by ligand-based method, which contained two hydrogen bond acceptors and two hydrophobic groups. A combined virtual screening based on pharmacophore model and molecular docking was adopted to screen potential HDAC6 inhibitors. Subsequently, the HDAC6 inhibitory activity of the hit compounds were evaluated using an in vitro enzyme binding inhibition assay. The experimental results illustrated that cefoperazone sodium had the strongest inhibitory effect on HDAC6 among the six screened compounds, and its IC₅₀ value was 8.59 ± 1.06 μM. Cefoperazone sodium significantly catalyzed the hyperacetylation of α-tubulin but not histone H3, proving that cefoperazone sodium was a selective inhibitor of HDAC6. Since the expression of HDAC6 plays an important role in cancer metastasis, the effects of cefoperazone sodium on migration and invasion of human pancreatic cancer PANC-1 cells were further investigated by wound healing and transwell chamber assays. It was found that cefoperazone sodium could evidently inhibit the migration and invasion of PANC-1 cells. Furthermore, the binding pattern of inhibitor at the active site of the crystal structure was revealed by molecular docking, providing a reference value for the structural design and optimization of HDAC6 inhibitors. This study provides a systematic virtual screening approach for discovering HDAC6 active inhibitors, and by which the specific effect of cefoperazone sodium against HDAC6 was found, suggesting its potential application on cancer therapy.

Dipeptidyl Peptidase-4 Is a Target Protein of Epigallocatechin-3-Gallate

Epigallocatechin-3-gallate (EGCG), a major active ingredient in green tea, has various health benefits. It affects glucose metabolism, but the mechanism is not well understood. This study aimed to identify targets of EGCG related to glucose metabolism. The core fragment of EGCG is a flavonoid. The flavonoid scaffold was used as a substructure to find proteins cocrystallized with flavonoids in the Protein Data Bank. The proteins identified were screened in PubMed for known relationships with diabetes. Dipeptidyl peptidase-4 (DPP4; PDB 5J3J) was identified following this approach. By molecular docking, the interactions of EGCG and DPP4 were assessed. To test the stability of the interactions between EGCG and DPP4, molecular dynamics simulation for 100 ns was performed using Desmond software. In vitro, the concentration of EGCG required to inhibit DPP4 activity by 50% (the IC50 value) was 28.42 μM. These data provide a theoretical basis for intervention in glucose metabolism with EGCG.

Molecular determinants for ligand binding at Nav1.4 and Nav1.7 channels: Experimental affinity results analyzed by molecular modeling

Here, we focused on exploring the selectivity mechanism against Nav1.7 over Nav1.4 due to different binding modes of two selected inhibitors. By the superposition of Nav1.7 and Nav1.4 proteins, we selected the most homologous chain of Nav1.7 with Nav1.4, defining the active site of Nav1.4-VSD4 based on the aryl sulfonamide binding site of Nav1.7-VSD4. Comparison of the conformations exhibited by Tyr1386 (Nav1.4) and Tyr1537 (Nav1.7) suggested that the steric hindrance caused by Tyr1386 owned primary influence on inhibition selectivity, which was further verified through molecular docking and MD simulation of two representative inhibitors. Our finding would be helpful for discovery of selective Nav1.7 inhibitors over Nav1.4.

Design, Synthesis and Molecular Docking Analysis of Flavonoid Derivatives as Potential Telomerase Inhibitors

Based on the structural scaffolds of natural products, two series of flavonoid derivatives, for a total of twelve compounds, were designed and synthesized as potential human telomerase inhibitors. Using a modified TRAP-PCR assay, compound 5c exhibited the most potent inhibitory activity against human telomerase with an IC₅₀ value of less than 50 μM. In vitro, the results demonstrated that compound 5c had potent anticancer activity against five classes of tumor cell lines. The molecular docking and molecular dynamics analyses binding to the human telomerase holoenzyme were performed to elucidate the binding mode of active compound 5c. This finding helps the rational design of more potent telomerase inhibitors based on the structural scaffolds of natural products.

Quinone-thioether metabolites of hydroquinone play a dual role in promoting a vicious cycle of ROS generation: in vitro and in silico insights

Humans are exposed to hydroquinone (HQ) via diet, smoking, occupation, and even via inhalation of polluted air. Given its preferential distribution in kidney and liver, the impact of biotransformation on the nephrotoxicity and hepatotoxicity of HQ was evaluated. Indeed, HQ and its metabolites, benzoquinone, and quinone-thioethers (50, 100, 200, and 400 μM) all induced ROS-dependent cell death in both HK-2, a human kidney proximal epithelial cell line, and THLE-2, a human liver epithelial cell line, in a concentration-dependent manner. For a deeper insight into the biological mechanism of ROS stimulation, the bioinformatics database was reviewed. Intriguingly, 163 proteins were currently reported to form co-crystal complex with benzoquinone analogs, a large proportion of which are closely related to ROS generation. After a thorough assessment of the interaction affinity and binding energy, three key mitochondrial proteins that are particularly involved in electric transport, namely, cytochrome BC1, succinate dehydrogenase, and sulfide:quinone oxidoreductase, were highlighted for further verification. Their binding affinity and the action pattern were explored and validated by molecular docking and molecular dynamics simulations. Remarkably, quinone-thioether metabolites of HQ afforded high affinity to the above proteins that purportedly cause a surge in the generation of ROS. Therefore, HQ can be further converted into quinone-thioethers, which on one hand can function as substrates for redox cycling, and on the other hand may afford high affinity with key proteins evolved in mitochondrial electron transport system, leading to a vicious cycle of ROS generation. The combined data provide a prospective insight into the mechanisms of ROS motivation, expanding HQ-mediated toxicology profiles.

Discovery of a natural PI3Kδ inhibitor through virtual screening and biological assay study

Phosphoinositide-3-kinase-δ (PI3Kδ) is a key regulator in the process of IgE mediated mast cell degranulation, which directly induces allergic diseases, such as asthma. This study is aimed at discovery of natural PI3Kδ inhibitors from Chinese medicine and evaluating their anti-mast cell degranulation activity. A combined virtual screening based on 3D pharmacophore model and molecular docking was used to screen for bioactive ingredients directly targeting PI3Kδ. Then, an in vitro kinase inhibition assay was conducted to evaluate the PI3Kδ inhibitory activity of the virtual screening hits. Subsequently, a β-hexosaminidase release assay was performed to verify the anti-mast cell degranulation activity of the active compounds. Finally, ginkgoneolic acid was identified as a PI3Kδ inhibitor (IC₅₀ = 2.49 μM) and exhibited anti-mast cell degranulation activity in vitro (IC₅₀ = 2.40 μM). Docking studies showed that Glu826, Val827 and Val828 were key amino acid residues for PI3Kδ inhibitory activity. Ginkgoneolic acid may be a potential lead compound for developing effective and safe PI3Kδ-inhibiting drugs.

In silico exploration of aryl sulfonamide analogs as voltage-gated sodium channel 1.7 inhibitors by using 3D-QSAR, molecular docking study, and molecular dynamics simulations

It has been demonstrated by human genetics that the voltage-gated sodium channel Nav1.7 is currently a promising target for the treatment of pain. In this research, we performed molecular simulation works on a series of classic aryl sulfonamide Nav1.7 inhibitors using three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking and molecular dynamics (MD) simulations for the first time to explore the correlation between their structures and activities. The results of the relevant statistical parameters of comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analyses (CoMSIA) had been verified to be reasonable, and the deep relationship between the structures and activities of these inhibitors was obtained by analyzing the contour maps. The generated 3D-QSAR model showed a good predictive ability and provided valuable clues for the rational modification of molecules. The interactions between compounds and proteins were modeled by molecular docking studies. Finally, accuracy of the docking results and stability of the complexes were verified by 100 ns MD simulations. Detailed information on the key residues at the binding site and the types of interactions they participate in involved was obtained. The van der Waals energy contributed the most in the molecular binding process according to the calculation of binding free energy. All research results provided a good basis for further research on novel and effective Nav1.7 inhibitors.