Current Computer - Aided Drug Design - Current Issue

This study aimed to investigate the medicinal properties of SZS before and after processing and provide novel insights into its potential for treating insomnia.

This study employed the network pharmacology platform to gather information on the chemical composition of SZS, human targets, genes, molecular networks, and pathways associated with insomnia treatment using SZS. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was utilized to analyze the chemical profiles of crude SZS, parched SZS, and their combined decoction. The effects of different SZS products on p-chlorophenylalanine-induced insomnia mice were evaluated through pentobarbital-induced sleep tests, behavioral analyses, examination of brain tissue-related mRNA levels, and measurement of plasma neurotransmitters, aiming to explore the sedative and hypnotic effects of various SZS products.

SZS was found to contain a total of 47 genes, including 22 target genes associated with insomnia. These genes may contribute to the sedative and hypnotic effects through 9 related pathways and 69 biological processes. The active components of SZS remained consistent before and after processing. Jujuboside B was found in higher concentrations in crude SZS, while jujuboside A was more abundant in parched SZS. Additionally, SZS exhibited reduced locomotor activity in mice, enhanced the hypnotic effect of pentobarbital sodium, and decreased the levels of acetylcholinesterase, α-1B adrenergic receptor, and solute carrier family 6 member 4 mRNA in the cortex and hippocampus of mice. The levels of acetylcholine, choline acetyltransferase, 5-hydroxyindoleacetic acid, and glutamate in plasma increased, with the hypnotic effect being proportional to the dosage of the drug.

SZS demonstrates sedative and hypnotic effects, potentially mediated by its influence on neurotransmitter levels and related receptors within the central nervous system. There was a slight variation in regulatory capabilities before and after SZS processing, with the combined decoction of crude and parched SZS exhibiting a more pronounced effect, particularly at higher dosages.

This study aimed to evaluate the pharmacological mechanism of Hederagenin (HD) combined with oxaliplatin (L-OHP) in treating gastric cancer (GC) through network pharmacology combined with experimental verification.

Network pharmacology methods were used to screen potential targets for HD, L-OHP, and GC-related targets from public databases, and the intersection of the three gene sets was taken. Cross genes were analyzed through protein-protein interaction (PPI) networks to predict core targets, and related pathways were predicted through GO and KEGG enrichment analysis. The experimental results were verified by the in vitro experiments. HD was applied on AGS/L-OHP cells, and then cellular chemosensitivity and the expressions of P-gp, Survivin, Bcl-2, p-Akt, and p-PI3K genes were detected. Wound assay and Transwell Chamber assay were employed to detect the effect of HD on AGS/L-OHP cells. Nude mice xenograft models transfected using AGS/L-OHP cells were also treated with HD in order to verify the results. The size and weight of the tumor, as well as the expressions of P-gp, Survivin, Bcl-2, p-Akt and p-PI3K genes, were also measured.

KEGG analysis showed that the anti-gastric cancer effect of HD was mediated mainly by PI3K-Akt signaling pathways. The PI3K-Akt signaling pathway containing more enriched genes may play a greater role in anti-gastric cancer. It was observed that for AGS/L-OHP cells jointly treated with HD and L-OHP, their activity, migration and invasion were significantly lower than those treated only using HD or L-OHP group. Moreover, expressions of p-Akt, p-PI3K, Bcl-2, P-gp, and Survivin for the HD+L-OHP group decreased significantly. Results of the in vivo experiments showed that the sizes and weights of tumors in the HD+L-OHP group were the lowest compared to the HD group and L-OHP group.

Our findings suggest that HD may reduce the resistance of AGS/L-OHP cells to L-OHP by regulating the PI3K/Akt signaling pathway.

Transcription factors are vital biological components that control gene expression, and their primary biological function is to recognize DNA sequences. As related research continues, it was found that the specificity of DNA-protein binding has a significant role in gene expression, regulation, and especially gene therapy. Convolutional Neural Networks (CNNs) have become increasingly popular for predicting DNa-protein-specific binding sites, but their accuracy in prediction needs to be improved.

We proposed a framework for combining Multi-Instance Learning (MIL) and a hybrid neural network named WSHNN. First, we utilized sliding windows to split the DNA sequences into multiple overlapping instances, each instance containing multiple bags. Then, the instances were encoded using a K-mer encoding. Afterward, the scores of all instances in the same bag were calculated separately by a hybrid neural network.

Finally, a fully connected network was utilized as the final prediction for that bag. The framework could achieve the performances of 90.73% in Pre, 82.77% in Recall, 87.17% in Acc, 0.8657 in F1-score, and 0.7462 in MCC, respectively. In addition, we discussed the performance of K-mer encoding. Compared with other art-of-the-state efforts, the model has better performance with sequence information.

From the experimental results, it can be concluded that Bi-directional Long-Short-Term Memory (Bi-LSTM) can better capture the long-sequence relationships between DNA sequences (the code and data can be visited at https://github.com/baowz12345/Weak_Super_Network).

The study aimed to explore the crucial genes involved in cancer-related biological processes, including EMT, autophagy, apoptosis, anoikis, and metastasis. It also sought to identify common genes among the pathways linked to these biological processes, determine the level of Bcl-2 expression in various types of cancers, and find a potent inhibitor of Bcl-2 among natural compounds.

Common genes involved in the pathways related to EMT, autophagy, apoptosis, anoikis, and metastasis were explored, and the level of the most frequently overexpressed gene that was Bcl-2, in various types of cancers was analyzed by gene expression analysis. A set of 102 natural compounds was sorted according to their docking scores using molecular docking and filtering. The top-ranked molecule was chosen for additional molecular dynamics (MD) simulation for 100 ns. Differential gene expression analysis was performed for Dioscin using GEO2R.

The study identified four common genes, Bcl-2, Bax, BIRC3, and CHUK, among the pathways linked to EMT, autophagy, apoptosis, anoikis, and metastasis. Bcl-2 was highly overexpressed in many cancers, including Acute Myeloid Leukemia, Diffuse large B cell lymphoma, and Thymoma. The Dioscin structure in the Bcl-2 binding site received the highest docking score and the most relevant interactions. Dioscin's determined binding free energy by MM/GBSA was -52.21 kcal/mol, while the same calculated by MM/PBSA was -9.18 kcal/mol. A p-value of less than 0.05 was used to determine the statistical significance of the analysis performed using GEO2R. It was observed that Dioscin downregulates Bcl-2, BIRC3, and CHUK and upregulates the pro-apoptotic protein Bax.

The study concluded that Dioscin has the potential to act as a protein inhibitor, with a noteworthy value of binding free energy and relevant interactions with the Bcl-2 binding site. Dioscin might be a good alternative for targeting multiple cancer pathways through a single target.

Acinetobacter baumannii is one of the main causes of nosocomial infections. No vaccine has yet been licensed for use in humans, and efforts are still ongoing.

In the present study, we have predicted the B-cell epitopes of A. baumannii’s outer membrane protein K (OMPK) by using epitope prediction algorithms as possible vaccine candidates for future studies.

The linear B-cell epitopes were predicted by seven different prediction tools. The 3D structure of OMPK was modeled and used for discontinuous epitope prediction by ElliPro and DiscoTope 2.0 tools. The final linear epitopes and the discontinuous epitope segments were checked for potential allergenicity, toxicity, human similarity, and experimental records. The structure and physicochemical features of the final epitopic peptide were assessed by numerous bioinformatics tools.

Many B-cell epitopes were detected that could be assessed for possible antigenicity and immunogenicity. Also, an epitopic 22-mer region (peptide) of OMPK was found that contained both linear and discontinuous B-cell epitopes. This epitopic peptide has been found to possess appropriate physicochemical and structural properties to be an A. baumannii vaccine candidate.

Altogether, here, the high immunogenic B-cell epitopes of OMPK have been identified, and a high immunogenic 22-mer peptide as an A. baumannii vaccine candidate has been introduced. The in vitro/in vivo studies of this peptide are recommended to decide its real efficacy and efficiency.

Cancer poses a great threat to human health, and effective drugs to treat it are always needed. Several compounds containing a 2-aminopyrazine framework have been identified as antitumor agents with SHP2 inhibition activities. This current work aimed to search for more potent novel compounds possessing a 2-aminopyrazine moiety with antitumor activities.

A series of 12 novel 2-aminopyrazine derivatives was synthesized, and their structures were confirmed by spectroscopic techniques. The inhibitory activities of all the synthesized compounds against MDA-MB-231 and H1975 cancer cell lines were evaluated by an MTT assay. The most potent compound 3e was analyzed by flow cytometry. Subsequently, computational studies were performed to investigate the possible antitumor mechanisms of compound 3e.

The results indicated that compound 3e exhibited potent antitumor activities with IC50 values of 11.84 ± 0.83 μM against H1975 cells and 5.66 ± 2.39 μM against MDA-MB-231 cells, which were more potent than the SHP2 inhibitor GS493 (IC50 = 19.08 ± 1.01 μM against H1975 cells and IC50 = 25.02 ± 1.47 μM against MDA-MB-231 cells). Further analysis by flow cytometry demonstrated that compound 3e induced cell apoptosis in H1975 cells. The results of the molecular docking and MD simulations, including RMSD, RMSF, PCA, DCCM and binding energy and decomposition analyses, revealed that compound 3e probably selectively inhibited SHP2.

A new compound having a 2-aminopyrazine substructure with potent inhibitory activities against the H1975 and MDA-MB-231 cancer cells was obtained, meriting further investigation as an antitumor drug.

Methicillin-resistant Staphylococcus aureus (MRSA) is a causative agent for multiple drug-resistant diseases and is a prime health concern. Currently, antibiotics like vancomycin, daptomycin, fluoroquinolones, linezolid, fifth-generation cephalosporin and others are available in the market for the treatment of MRSA infection.

With the increasing prevalence of drug-resistant cases, researchers are actively investigating alternative strategies to combat MRSA, including the exploration of peptide therapeutics. This study employed computational methods to prospect for potential Antimicrobial Peptides (AMPs).

A total of One hundred and fifty antimicrobial peptides were explored based on physicochemical properties. The results showed that Clavanin B was the most appropriate candidate. Molecular Docking and Molecular Dynamics Simulation results showed the protein-peptide interaction of the MRSA target proteins, Penicillin Binding Protein 2a and Panton-Valentine Leukocidin Toxin, with the Antimicrobial Peptide Clavanin B.

Currently, the antimicrobial peptide database highlights Clavanin B's role as an anti-HIV peptide. Moreover, this investigation proposes Clavanin B as a viable repurposed drug for treating MRSA, underscoring its potential deployment in the management of MRSA infections.

Cinnamic acid (Cinn) is a phenolic acid of Cinnamomum cassia (L.) J. Presl. that can ameliorate diabetic nephropathy (DN). However, comprehensive therapeutic targets and underlying mechanisms for Cinn against DN are limited.

In this study, a network pharmacology approach and in vivo experiments were adopted to predict the pharmacological effects and mechanisms of Cinn in DN therapy.

The nephroprotective effect of Cinn on DN was investigated by a streptozotocin-induced diabetes mellitus (DM) mouse model. The protein-protein interaction network of Cinn against DN was established by a network pharmacology approach. The core targets were then identified and subjected to molecular docking with Cinn.

Cinn treatment effectively restored body weight, ameliorated hyperglycemia, and reduced kidney dysfunction markers in DM mice, also demonstrating a reduction in tissue injury. Network pharmacology analysis identified 298 DN-Cinn co-target genes involved in various biological processes and pathways. Seventeen core targets were identified, eight of which showed significant differential expression in the DN and healthy control groups. Molecular docking analysis revealed a strong interaction between Cinn and PTEN. Cinn treatment downregulated the PTEN protein expression in DM mice.

This study revealed the multi-target and multi-pathway characteristics of Cinn against DN. Cinn improved renal pathological damage of DN, which was related to the downregulation of PTEN.

The purpose of this research is to develop an analytical method and validate it according to ICH guidelines for the estimation of Toremifene by RP-HPLC-PDA with molecular docking and ADMET analysis. From molecular docking, it came to know the receptor affinity specifically to estrogen receptors (ERα and ERβ), which are responsible for cancer therapy. ADMET analyses secure its therapeutic potential as well safety of the drug.

An isocratic method has developed by RP-HPLC-PDA (AGILENT 1100) with symmetry of 100 mm x 4.6 mm x 5 µm particle size C18 column and optimise mobile phase is methanol: 0.1% OPA (orthophosphoric acid) water ratio of 43:57% v/v. Under different conditions like acidic, alkaline, oxidative, and neutral environments, toremifene was tested for degradation.

The developed method is validated in accordance with ICH guidelines. A calibration curve with an r2 value of 0.9987 has been prepared across the range of 10 to 50 µg/ml with five standard dilutions. The retention time of the drug is 5.575 minutes. The validation results are system suitability (%RSD-0.76), inter-day precision (%RSD 0.14-0.29), intraday precision (%RSD 0.08-0.34), accuracy (%RSD 0.16-0.96), and robustness (%RSD 0.16-0.35). In different intended conditions, four peaks are in 1 N HCl, two peaks in 1 N NaOH, three peaks in 10% H2O2 (1hr), and one peak in neutral.

Toremifene, a Selective Estrogen Receptor Modulator (SERM), Drug pharmacokinetic properties and receptor binding affinity results are helpful in designing the analytical method. Developing the RP-HPLC-PDA method is found to be novel, simple and precise. It could be used for testing toremifene in bulk and pharmaceutical tablet dosage forms in quality control, as well as stability tests.

Hyperlipidemia is characterized by an abnormally elevated serum cholesterol, triglycerides, or both. The relationship between an elevated level of LDL and cardiovascular diseases is well-established. Cholesteryl ester transfer protein (CETP) is an enzyme that moves cholesterol esters and triglycerides between LDL, VLDL, and HDL. CETP inhibition leads to a reduction in cardiovascular disease by raising HDL and minimizing LDL.

This study synthesized ten meta-chlorinated benzene sulfonamides 6a-6j and explored their structure-activity relationship.

The synthesized molecules were characterized using ¹H-NMR, ¹³C-NMR, IR, and HR-MS. Moreover, cheminformatics analyses included pharmacophore mapping, LibDock studies, and cheminformatics characterization using 2-dimensional (2D) molecular descriptors and principal component analysis.

Based on in vitro functional CETP assays, compounds 6e, 6i, and 6j demonstrated the strongest inhibitory activities against CETP, reaching 100% inhibition. The inhibitory activity of compounds 6a-6d and 6f-6h ranged from 47.5% to 96.5% at 10 µM concentration. Pharmacophore mapping results suggested CETP inhibitory action, while the docking scores and calculated binding energies predicted favoring binding at the CETP active site. Best-scoring docking poses predicted critical hydrophobic features corresponding to key interactions with His232 and Cys13. Cheminformatics analysis using 2D molecular descriptors indicated that the synthesized compounds span various physicochemical properties and drug-likeness.

It was found that a chloro moiety at the ortho-position, or a nitro group at the meta and para-positions, improves the CETP inhibitory activity of synthesized analogs. Computational studies suggest the formation of stable ligand-protein complexes between compounds 6a-6j and CETP.

Drug-resistant Staphylococcus aureus represents a substantial healthcare challenge worldwide, and its range of available therapeutic options continues to diminish progressively. Thus, this study aimed to identify potential inhibitors against FemA, a crucial protein involved in the cell wall biosynthesis of S. aureus.

The screening process involved a comprehensive structure-based virtual screening on the StreptomDB database to identify ligands with potential inhibitory effects on FemA using AutoDock Vina. The most desirable ligands with the highest binding affinity and pharmacokinetic properties were selected. Two ligands with the highest number of hydrogen bonds and hydrophobic interactions were further analyzed by molecular dynamics (MD) using the GROMACS version 2018 simulation package.

Six H-donor conserved residues were selected as protein active sites, including Arg-220, Tyr-38, Gln-154, Asn-73, Arg-74, and Thr-24. Through virtual screening, a total of nine compounds with the highest binding affinity to the FemA protein were identified. Frigocyclinone and C21H21N3O4 exhibited the highest binding affinity and demonstrated favorable pharmacokinetic properties. Molecular dynamics analysis of the FemA-ligand complexes further indicated desirable stability and reliability of complexes, reinforcing the potential efficacy of these ligands as inhibitors of FemA protein.

Our findings suggest that Frigocyclinone and C21H21N3O4 are promising inhibitors of FemA in S. aureus. To further validate these computational results, experimental studies are planned to confirm the inhibitory effects of these compounds on various S. aureus strains. Combining computational screening with experimental validation contributes valuable insights to the field of drug discovery in comparison to the classical drug discovery approaches.

Non-alcoholic Fatty Liver Disease (NAFLD) has become a significant health and economic burden globally. Yinchenhao decoction (YCHD) is a traditional Chinese medicine formula that has been validated to exert therapeutic effects on NAFLD.

The current study aimed to explore the pharmacological mechanisms of YCHD on NAFLD and further identify the potential active compounds acting on the main targets.

Compounds in YCHD were screened and collected from TCMSP and published studies, and their corresponding targets were obtained from the Swisstargetprediction and SEA databases. NAFLD-related targets were searched in the GeneCards and DisGeNet databases. The “compound-intersection target” network was constructed to recognize the key compounds. Moreover, a PPI network was constructed to identify potential targets. GO and KEGG analyses were performed to enrich the functional information of the intersection targets. Then, molecular docking was used to identify the most promising compounds and targets. Finally, molecular dynamics (MD) simulations were performed to verify the binding affinity of the most potential compounds with the key targets.

A total of 53 compounds and 556 corresponding drug targets were collected. Moreover, 2684 NAFLD-related targets were obtained, and 201 intersection targets were identified. Biological processes, including the apoptotic process, inflammatory response, xenobiotic metabolic process, and regulation of MAP kinase activity, were closely related to the treatment of NAFLD. Metabolic pathways, non-alcoholic fatty liver disease, the MAPK signaling pathway, and the PI3K-Akt signaling pathway were found to be the key pathways. Molecular docking showed that quercetin and isorhamnetin were the potential active compounds, while AKT1, IL1B, and PPARG were the most promising targets. MD simulations further verified that the binding of PPARG-isorhamnetin (-35.96 ± 1.64 kcal/mol) and AKT1-quercetin (-31.47 ± 1.49 kcal/mol) was due to their lowest binding free energy.

This study demonstrated that YCHD exerts therapeutic effects for the treatment of NAFLD through multiple targets and pathways, providing a theoretical basis for further pharmacological research on the potential mechanisms of YCHD in NAFLD.