Pharmacophore modeling for COX-1 and -2 inhibitors with LigandScout in comparison to Discovery Studio

Eight structurally diverse components with anti-acetylcholinesterase activity from Daphne bholua

Eight structurally diverse components, including six undescribed ones, (±)-daphuarin A (1a/1b), daphuarin B (2), daphuarin D-E (4-6), together with a pair of new natural products (±)-daphuarin C (3a/3b) were isolated from the herb of Daphne bholua Buch.-Ham. ex D. Don. Their planar structures were elucidated by extensive spectroscopic analyses. The configurations were established with the assistance of quantum chemical calculations, together with the Custom DP4+ method. The inhibitory potentials of all isolates against acetylcholinesterase were evaluated.

Identification of Novel β-Tubulin Inhibitors Using a Combined In Silico/In Vitro Approach

Due to their potential as leads for various therapeutic applications, including as antimitotic and antiparasitic agents, the development of tubulin inhibitors offers promise for drug discovery. In this study, an in silico pharmacophore-based virtual screening approach targeting the colchicine binding site of β-tubulin was employed. Several structure- and ligand-based models for known tubulin inhibitors were generated. Compound databases were virtually screened against the models, and prioritized hits from the SPECS compound library were tested in an in vitro tubulin polymerization inhibition assay for their experimental validation. Out of the 41 SPECS compounds tested, 11 were active tubulin polymerization inhibitors, leading to a prospective true positive hit rate of 26.8%. Two novel inhibitors displayed IC50 values in the range of colchicine. The most potent of which was a novel acetamide-bridged benzodiazepine/benzimidazole derivative with an IC50 = 2.9 μM. The screening workflow led to the identification of diverse inhibitors active at the tubulin colchicine binding site. Thus, the pharmacophore models show promise as valuable tools for the discovery of compounds and as potential leads for the development of cancer therapeutic agents.

Uncovering the interactions between PME and PMEI at the gene and protein levels: Implications for the design of specific PMEI

CONTEXT

Pectin methylesterase inhibitor (PMEI) can specifically bind and inhibit the activity of pectin methylesterase (PME), which has been widely used in fruit and vegetable juice processing. However, the limited three-dimensional structure, unclear action mechanism, low thermal stability and biological activity of PMEI severely limited its application. In this work, molecular recognition and conformational changes of PME and PMEI were analyzed by various molecular simulation methods. Then suggestions were proposed for improving thermal stability and affinity maturation of PMEI through semi-rational design.

METHODS

Phylogenetic trees of PME and PMEI were established using the Maximum likelihood (ML) method. The results show that PME and PMEI have good sequence and structure conservation in various plants, and the simulated data can be widely adopted. In this work, MD simulations were performed using AMBER20 package and ff14SB force field. Protein interaction analysis indicates that H-bonds, van der Waals forces, and the salt bridge formed of K224 with ID116 are the main driving forces for mutual molecular recognition of PME and PMEI. According to the analyses of free energy landscape (FEL), conformational cluster, and motion, the association with PMEI greatly disrupts PME's dispersed functional motion mode and biological function. By monitoring the changes of residue contact number and binding free energy, IG35M/ IG35R: IT93F and IT113W/ IT113W: ID116W mutations contribute to thermal stability and affinity maturation of the PME-PMEI complex system, respectively. This work reveals the interaction between PME and PMEI at the gene and protein levels and provides options for modifying specific PMEI.

Multiomics Study of a Novel Naturally Derived Small Molecule, NSC772864, as a Potential Inhibitor of Proto-Oncogenes Regulating Cell Cycle Progression in Colorectal Cancer

Colorectal cancer (CRC) is one of the most prevalent malignant tumors, and it contributes to high numbers of deaths globally. Although advances in understanding CRC molecular mechanisms have shed significant light on its pathogenicity, current treatment options, including combined chemotherapy and molecular-targeted agents, are still limited due to resistance, with almost 25% of patients developing distant metastasis. Therefore, identifying novel biomarkers for early diagnosis is crucial, as they will also influence strategies for new targeted therapies. The proto-oncogene, c-Met, a tyrosine kinase that promotes cell proliferation, motility, and invasion; c-MYC, a transcription factor associated with the modulation of the cell cycle, proliferation, apoptosis; and cyclin D1 (CCND1), an essential regulatory protein in the cell cycle, all play crucial roles in cancer progression. In the present study, we explored computational simulations through bioinformatics analysis and identified the overexpression of c-Met/GSK3β/MYC/CCND1 oncogenic signatures that were associated with cancer progression, drug resistance, metastasis, and poor clinical outcomes in CRC. We further demonstrated the anticancer activities of our newly synthesized quinoline-derived compound, NSC772864, against panels of the National Cancer Institute's human CRC cell lines. The compound exhibited cytotoxic activities against various CRC cell lines. Using target prediction tools, we found that c-Met/GSK3β/MYC/CCND1 were target genes for the NSC772864 compound. Subsequently, we performed in silico molecular docking to investigate protein-ligand interactions and discovered that NSC772864 exhibited higher binding affinities with these oncogenes compared to FDA-approved drugs. These findings strongly suggest that NSC772864 is a novel and potential antiCRC agent.

Investigation of Pharmacological Mechanisms of Yinhua Pinggan Granule on the Treatment of Pneumonia through Network Pharmacology and In Vitro

Yinhua pinggan granule (YHPGKL), a traditional Chinese medical compound, could treat pneumonia. Although previous studies demonstrated the protective and therapeutic effects of YHPGKL on pneumonia, its potential molecular mechanisms and its effective components are still elusive. Herein, we performed a network pharmacology analysis to determine the possible signaling pathways involved in the protective effects of components of YHPGKL. A total of 119 components and 257 target proteins of YHPGKL were identified, among which 117 effective components interacted with 113 proteins related to pneumonia. Then, a compound-effective component-target protein network was established to screen the effective hub components. The top three effective components, namely luteolin, kaempferol, and quercetin, were selected. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of 113 proteins revealed a significant enrichment term associated with host immune and anti-infectious responses. Furthermore, by constructing a protein-protein interaction network between common proteins, ten hub proteins were identified, among which three hub components hit eight proteins. A further molecular docking analysis confirmed that the three effective hub components had a good affinity with six hub proteins. Eventually, the interactions were further visualized and screened on account of an infectious macrophage model in vitro. The results noted that three components could inhibit proinflammatory related hub genes but had no effect on survival-related hub genes. Thus, the three effective hub components and corresponding hub genes may play essential roles in the treatment of YHPGKL on pneumonia.

Natural Xylooligosaccharides Exert Antitumor Activity via Modulation of Cellular Antioxidant State and TLR4

It has been recently proven that xylooligosaccharides (XOS) with prebiotic properties have diverse beneficial biological effects including immunomodulatory and antitumor activities. The present article focused on the chemical and biological evaluation of corn-derived commercially available XOS and aimed to elucidate their cytotoxicity and inhibitory potential against tumor cells. Spectrophotometric chemical analyses, Fourier transform infrared spectroscopy, and high-performance liquid chromatography analyses were performed. Antioxidant activity was determined by measuring the oxygen radical absorbance capacity and hydroxyl radical averting capacity. In vitro cytotoxicity assays with human cell lines derived from normal and tumor tissues, assessments of ATP production, mitochondrial membrane potential specific staining, cytokine assays, and molecular docking were used to evaluate the biological activity of XOS. The sample showed significant antioxidant activity, and it was determined that most xylose oligomers in it are composed of six units. XOS exhibited antitumor activity with pronounced inhibitory effect on lysosomes, but mitochondrial functionality was also affected. The production of proinflammatory cytokines by lipopolysaccharide-stimulated U-937 cells was reduced by XOS treatment, which suggested the involvement of Toll-like receptor 4 (TLR4)-mediated signaling in the mechanism of XOS action. Molecular docking analyses confirmed the potential inhibitory interaction between the sample and TLR4. In addition, XOS treatment had significant tumor-cell-specific influence on the glutathione antioxidant system, affecting its balance and thus contributing to the inhibition of cellular viability. The present study elucidated the tumor-inhibitory potential of commercially available XOS that could be utilized in pharmaceutical and food industry providing disease-preventive and therapeutic benefits.

Molecular Mimicry of the Rheumatoid Arthritis-Related Immunodominant T-Cell Epitope within Type II Collagen (CII260-270) by the Bacterial L-Asparaginase

The etiology of most autoimmune diseases, including rheumatoid arthritis (RA), remains unclear. Both genetic and environmental factors are believed to be involved in pathogenesis. Molecular mimicry is considered one of the mechanisms for the occurrence of autoimmune diseases. The aim of the study was to determine whether the bacterial peptide L-ASNase67-81, which mimics the immunodominant T-cell epitope CII259-273, can induce T-cell reactivity in blood samples from RA patients and healthy subjects through molecular mimicry. Using bioinformatic molecular modeling methods, we first determined whether the L-ASNase67-81 peptide binds to the HLA-DRB1*04:01 molecule and whether the formed MHCII–peptide complex interacts with the corresponding T-cell receptor. To validate the obtained results, leukocytes isolated from early RA patients and healthy individuals were stimulated in vitro with L-ASNase67-81 and CII259-273 peptides as well as with bacterial L-asparaginase or human type II collagen (huCII). The activated T cells (CD4+CD154+) were analyzed by flow cytometry (FACS), and the levels of cytokines produced (IL-2, IL-17A/F, and IFN-γ) were measured by ELISA. Our in silico analyses showed that the bacterial peptide L-ASNase67-81 binds better to HLA-DRB1*04:01 compared to the immunodominant T-cell epitope CII259-273, mimicking its structure and localization in the binding groove of MHCII. Six contact points were involved in the molecular interaction of the peptide with the TCR. FACS data showed that after in vitro stimulation with the L-ASNase67-81 peptide, the percentage of activated T cells (CD154⁺CD4⁺) was significantly increased in both cell cultures isolated from ERA patients and those isolated from healthy individuals, as higher values were observed for the ERA group (9.92 ± 0.23 vs. 4.82 ± 0.22). Furthermore, the ELISA assays revealed that after stimulation with L-ASNase67-81, a significant increase in the production of the cytokines IL-2, IL-17A/F, and IFN-γ was detected in the group of ERA patients. Our data showed that the bacterial L-ASNase67-81 peptide can mimic the immunodominant T-cell epitope CII259-273 and activate HLA-DRB1*04:01-restricted T cells as well as induce cytokine production in cells isolated from ERA patients. These results are the first to demonstrate that a specific bacterial antigen could play a role in the pathogenesis of RA, mimicking the immunodominant T-cell epitope from type II collagen.

Identification of Novel Dopamine D2 Receptor Ligands—A Combined In Silico/In Vitro Approach

Diseases of the central nervous system are an alarming global problem showing an increasing prevalence. Dopamine receptor D2 (D2R) has been shown to be involved in central nervous system diseases. While different D2R-targeting drugs have been approved by the FDA, they all suffer from major drawbacks due to promiscuous receptor activity leading to adverse effects. Increasing the number of potential D2R-targeting drug candidates bears the possibility of discovering molecules with less severe side-effect profiles. In dire need of novel D2R ligands for drug development, combined in silico/in vitro approaches have been shown to be efficient strategies. In this study, in silico pharmacophore models were generated utilizing both ligand- and structure-based approaches. Subsequently, different databases were screened for novel D2R ligands. Selected virtual hits were investigated in vitro, quantifying their binding affinity towards D2R. This workflow successfully identified six novel D2R ligands exerting micro- to nanomolar (most active compound KI = 4.1 nM) activities. Thus, the four pharmacophore models showed prospective true-positive hit rates in between 4.5% and 12%. The developed workflow and identified ligands could aid in developing novel drug candidates for D2R-associated pathologies.

Molecular Detection of Colistin Resistance mcr-1 Gene in Multidrug-Resistant Escherichia coli Isolated from Chicken

Zoonotic and antimicrobial-resistant Escherichia coli (hereafter, E. coli) is a global public health threat which can lead to detrimental effects on human health. Here, we aim to investigate the antimicrobial resistance and the presence of mcr-1 gene in E. coli isolated from chicken feces. Ninety-four E. coli isolates were obtained from samples collected from different locations in Bangladesh, and the isolates were identified using conventional microbiological tests. Phenotypic disk diffusion tests using 20 antimicrobial agents were performed according to CLSI-EUCAST guidelines, and minimum inhibitory concentrations (MICs) were determined for a subset of samples. E. coli isolates showed high resistance to colistin (88.30%), ciprofloxacin (77.66%), trimethoprim/sulfamethoxazole (76.60%), tigecycline (75.53%), and enrofloxacin (71.28%). Additionally, the pathotype eaeA gene was confirmed in ten randomly selected E. coli isolates using primer-specific polymerase chain reaction (PCR). The presence of mcr-1 gene was confirmed using PCR and sequencing analysis in six out of ten E. coli isolates. Furthermore, sequencing and phylogenetic analyses revealed a similarity between the catalytic domain of Neisseria meningitidis lipooligosaccharide phosphoethanolamine transferase A (LptA) and MCR proteins, indicating that the six tested isolates were colistin resistant. Finally, the findings of the present study showed that E. coli isolated from chicken harbored mcr-1 gene, and multidrug and colistin resistance. These findings accentuate the need to implement strict measures to limit the imprudent use of antibiotics, particularly colistin, in agriculture and poultry farms.

Anticancer Activities of 9-chloro-6-(piperazin-1-yl)-11H-indeno[1,2-c] quinolin-11-one (SJ10) in Glioblastoma Multiforme (GBM) Chemoradioresistant Cell Cycle-Related Oncogenic Signatures

Simple Summary

Glioblastoma multiforme (GBM) remains to be the most frequent malignant tumor of the central nervous system (CNS), which accounts for approximately 54% of all primary brain gliomas. Current treatment modalities for GBM include surgical resection, followed by radiotherapy and chemotherapy with temozolomide (TMZ). However, due to its genetic heterogeneity, GBM tumors always recur, due to treatment reasistance. The aim of this study was to identify molecular gene signatures, responsible for cancer initiation, progression, resistances and to treatment, metastasis, and also evaluate the potency of our novel compounds SJ10 as potential target for CCNB1/CDC42/MAPK7/CD44 oncogenic signatures. Accordingly, we used computational simulation and identify these signatures as regulators of the cell cycle in GBM, which leads to cancer development and metastasis. We also showed the antiproliferative and cytotoxic effects of SJ10 compound against a panel of NCI-60 cancer cell lines. This suggests the potential of the compounds to inhibit CCNB1/CDC42/MAPK7/CD44 in GBM.

Abstract

Current anticancer treatments are inefficient against glioblastoma multiforme (GBM), which remains one of the most aggressive and lethal cancers. Evidence has shown the presence of glioblastoma stem cells (GSCs), which are chemoradioresistant and associated with high invasive capabilities in normal brain tissues. Moreover, accumulating studies have indicated that radiotherapy contributes to abnormalities in cell cycle checkpoints, including the G₁/S and S phases, which may potentially lead to resistance to radiation. Through computational simulations using bioinformatics, we identified several GBM oncogenes that are involved in regulating the cell cycle. Cyclin B1 (CCNB1) is one of the cell cycle-related genes that was found to be upregulated in GBM. Overexpression of CCNB1 was demonstrated to be associated with higher grades, proliferation, and metastasis of GBM. Additionally, increased expression levels of CCNB1 were reported to regulate activation of mitogen-activated protein kinase 7 (MAPK7) in the G₂/M phase, which consequently modulates mitosis; additionally, in clinical settings, MAPK7 was demonstrated to promote resistance to temozolomide (TMZ) and poor patient survival. Therefore, MAPK7 is a potential novel drug target due to its dysregulation and association with TMZ resistance in GBM. Herein, we identified MAPK7/extracellular regulated kinase 5 (ERK5) genes as being overexpressed in GBM tumors compared to normal tissues. Moreover, our analysis revealed increased levels of the cell division control protein homolog (CDC42), a protein which is also involved in regulating the cell cycle through the G₁ phase in GBM tissues. This therefore suggests crosstalk among CCNB1/CDC42/MAPK7/cluster of differentiation 44 (CD44) oncogenic signatures in GBM through the cell cycle. We further evaluated a newly synthesized small molecule, SJ10, as a potential target agent of the CCNB1/CDC42/MAPK7/CD44 genes through target prediction tools and found that SJ10 was indeed a target compound for the above-mentioned genes; in addition, it displayed inhibitory activities against these oncogenes as observed from molecular docking analysis.

Structural and functional study on cysteine 495, coordinating ligand to T1Cu site in multicopper oxidase CopA

Excessive intake of manganese seriously affects human health. Manganese oxidizing bacteria can efficiently remove manganese, among which manganese oxidase plays a decisive role. Multicopper oxidase, one of the manganese oxidases, has 4 copper binding sites, among them, T1Cu coordinates with two histidine, one cysteine and one axial residue, mainly transferring electrons from the substrate to T2Cu and T3Cu. Here, we conducted site-directed mutagenesis on T1Cu coordinating 495 amino acid site from cysteine to aspartic acid, histidine and methionine in multicopper oxidase CopA from Brevibacillus panacihumi MK-8, through the enzyme kinetics and structure models, finding that the enzyme catalytic efficiency (k_cat/K_m) of the mutated C495H with Mn²⁺ and ABTS reached 9.03 min^-1 mM^-1 and 8863 s^-1 mM^-1, 1.47 times and 1.67 times that of CopA. And it was found strain Rosetta-pET-copA^C495H could remove 91.67% manganese after 7-day culture, which was 11.65% higher than the original strain. To sum up, these results provide a vision for the future application of protein engineering in biological manganese removal.

Comprehensive Omics Analysis of a Novel Small-Molecule Inhibitor of Chemoresistant Oncogenic Signatures in Colorectal Cancer Cell with Antitumor Effects

Tumor recurrence from cancer stem cells (CSCs) and metastasis often occur post-treatment in colorectal cancer (CRC), leading to chemoresistance and resistance to targeted therapy. MYC is a transcription factor in the nuclei that modulates cell growth and development, and regulates immune response in an antitumor direction by mediating programmed death ligand 1 (PD-L1) and promoting CRC tumor recurrence after adjuvant chemotherapy. However, the molecular mechanism through which c-MYC maintains stemness and confers treatment resistance still remains elusive in CRC. In addition, recent reports demonstrated that CRC solid colon tumors expresses C-X-C motif chemokine ligand 8 (CXCL8). Expression of CXCL8 in CRC was reported to activate the expression of PD-L1 immune checkpoint through c-MYC, this ultimately induces chemoresistance in CRC. Accumulating studies have also demonstrated increased expression of CXCL8, matrix metalloproteinase 7 (MMP7), tissue inhibitor of metalloproteinase 1 (TIMP1), and epithelial-to-mesenchymal transition (EMT) components, in CRC tumors suggesting their potential collaboration to promote EMT and CSCs. TIMP1 is MMP-independent and regulates cell development and apoptosis in various cancer cell types, including CRC. Recent studies showed that TIMP1 cleaves CXCL8 on its chemoattractant, thereby influencing its mechanistic response to therapy. This therefore suggests crosstalk among the c-MYC/CXCL8/TIMP1 oncogenic signatures. In this study, we explored computer simulations through bioinformatics to identify and validate that the MYC/CXCL8/TIMP1 oncogenic signatures are overexpressed in CRC, Moreover, our docking results exhibited putative binding affinities of the above-mentioned oncogenes, with our novel small molecule, RV59, Finally, we demonstrated the anticancer activities of RV59 against NCI human CRC cancer cell lines both as single-dose and dose-dependent treatments, and also demonstrated the MYC/CXCL8/TIMP1 signaling pathway as a potential RV59 drug target.

Structure-based molecular modeling in SAR analysis and lead optimization

In silico methods like molecular docking and pharmacophore modeling are established strategies in lead identification. Their successful application for finding new active molecules for a target is reported by a plethora of studies. However, once a potential lead is identified, lead optimization, with the focus on improving potency, selectivity, or pharmacokinetic parameters of a parent compound, is a much more complex task. Even though in silico molecular modeling methods could contribute a lot of time and cost-saving by rationally filtering synthetic optimization options, they are employed less widely in this stage of research. In this review, we highlight studies that have successfully used computer-aided SAR analysis in lead optimization and want to showcase sound methodology and easily accessible in silico tools for this purpose.

Multidrug Antimicrobial Resistance and Molecular Detection of mcr-1 Gene in Salmonella Species Isolated from Chicken

Colistin (polymyxin E) is widely used in animal and human medicine and is increasingly used as one of the last-resort antibiotics against Gram-negative bacilli. Due to the increased use of colistin in treating infections caused by multidrug-resistant Gram-negative bacteria, resistance to this antibiotic ought to be monitored. The study was undertaken to elucidate the molecular mechanisms, genetic relationships and phenotype correlations of colistin-resistant isolates. Here, we report the detection of the mcr-1 gene in chicken-associated Salmonella isolates in Bangladesh and its in-silico functional analysis. Out of 100 samples, 82 Salmonella spp. were isolated from chicken specimens (liver, intestine). Phenotypic disc diffusion and minimum inhibitory concentration (MIC) assay using different antimicrobial agents were performed. Salmonella isolates were characterized using PCR methods targeting genus-specific invA and mcr-1 genes with validation for the functional analysis. The majority of the tested Salmonella isolates were found resistant to colistin (92.68%), ciprofloxacin (73.17%), tigecycline (62.20%) and trimethoprim/sulfamethoxazole (60.98%). When screened using PCR, five out of ten Salmonella isolates were found to carry the mcr-1 gene. One isolate was confirmed for Salmonella enterica subsp. enterica serovar Enteritidis, and other four isolates were confirmed for Salmonella enterica subsp. enterica serovar Typhimurium. Sequencing and phylogenetic analysis revealed a divergent evolutionary relationship between the catalytic domain of Neisseria meningitidis lipooligosaccharide phosphoethanolamine transferase A (LptA) and MCR proteins, rendering them resistant to colistin. Three-dimensional homology structural analysis of MCR-1 proteins and molecular docking interactions suggested that MCR-1 and LptA share a similar substrate binding cavity, which could be validated for the functional analysis. The comprehensive molecular and in-silico analyses of the colistin resistance mcr-1 gene of Salmonella spp. of chicken origin in the present study highlight the importance of continued monitoring and surveillance for antimicrobial resistance among pathogens in food chain animals.

Unravelling high-affinity binding compounds towards transmembrane protease serine 2 enzyme in treating SARS-CoV-2 infection using molecular modelling and docking studies

The coronavirus disease-19 (COVID-19) outbreak that is caused by a highly contagious severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a zoonotic pandemic, with approximately 24.5 million positive cases and 8.3 lakhs deaths globally. The lack of effective drugs or vaccine provoked the research for drug candidates that can disrupt the spread and progression of the virus. The identification of drug molecules through experimental studies is time-consuming and expensive, so there is a need for developing alternative strategies like in silico approaches which can yield better outcomes in less time. Herein, we selected transmembrane protease serine 2 (TMPRSS2) enzyme, a potential pharmacological target against SARS-CoV-2, involved in the spread and pathogenesis of the virus. Since 3D structure is not available for this protein, the present study aims at homology modelling and validation of TMPRSS2 using Swiss-model server. Validation of the modelled TMPRSS2 using various online tools confirmed model accuracy, topology and stereochemical plausibility. The catalytic triad consisting of Serine-441, Histidine-296 and Aspartic acid-345 was identified as active binding site of TMPRSS2 using existing ligands. Molecular docking studies of various drugs and phytochemicals against the modelled TMPRSS2 were performed using camostat as a standard drug. The results revealed eight potential drug candidates, namely nafamostat, meloxicam, ganodermanontriol, columbin, myricetin, proanthocyanidin A2, jatrorrhizine and baicalein, which were further studied for ADME/T properties. In conclusion, the study unravelled eight high affinity binding compounds, which may serve as potent antagonists against TMPRSS2 to impact COVID-19 drug therapy.

Molecular modeling and in vitro study on pyrocatechol as potential pharmacophore of CD151 inhibitor

CD151 has been recognized as a prognostic marker, the therapeutic target of breast cancers, but less explored for small molecule inhibitors due to lack of a validated model. The 3-D structure of CD151 large extracellular loop (LEL) was modeled using the LOMETS server and validated by the Ramachandran plot. The validated structure was employed for molecular docking and structure-based pharmacophore analysis. Druglikeness was evaluated by the ADMET description protocol. Antiproliferative activity was evaluated by MTT, BrdU incorporation, flow cytometry, and cell death ELISA^PLUS assay. This study predicted the best model for CD151-LEL with 94.1% residues in favored regions and Z score -2.79 kcal/mol using the threading method. The web-based receptor cavity method identified one functional target site, which was suitable for the binding of aromatic and heterocyclic compounds. Molecular docking study identified pyrocatechol (PCL) and 5-fluorouracil (FU) as potential leads of CD151-LEL. The pharmacophore model identified interaction points of modeled CD151-LEL with PCL and FU. Also, the analysis of ADMET properties revealed the drug-likeness of PCL and FU. The viability of MDA-MB 231 cells was significantly reduced with PCL and FU but less affected MCF-12A, normal healthy breast epithelial cell line. With 50% toxic concentration, both PCL and FU significantly inhibited 82.46 and 87.12% proliferation, respectively, of MDA-MB 231 cells by altering morphology and inducing G1 cell cycle arrest and apoptosis. In addition, PCL and FU inhibited the CD151 expression by 4.5-and 4.8-folds, respectively. This study suggests the further assessment of pyrocatechol as a potential lead of CD151 in breast cancer at the molecular level.

Probabilistic Approach for Virtual Screening Based on Multiple Pharmacophores

Pharmacophore modeling is usually considered as a special type of virtual screening without probabilistic nature. Correspondence of at least one conformation of a molecule to pharmacophore is considered as evidence of its bioactivity. We show that pharmacophores can be treated as one-class machine learning models, and the probability the reflecting model’s confidence can be assigned to a pharmacophore on the basis of their precision of active compounds identification on a calibration set. Two schemes (Max and Mean) of probability calculation for consensus prediction based on individual pharmacophore models were proposed. Both approaches to some extent correspond to commonly used consensus approaches like the common hit approach or the one based on a logical OR operation uniting hit lists of individual models. Unlike some known approaches, the proposed ones can rank compounds retrieved by multiple models. These approaches were benchmarked on multiple ChEMBL datasets used for ligand-based pharmacophore modeling and externally validated on corresponding DUD-E datasets. The influence of complexity of pharmacophores and their performance on a calibration set on results of virtual screening was analyzed. It was shown that Max and Mean approaches have superior early enrichment to the commonly used approaches. Thus, a well-performing, easy-to-implement, and probabilistic alternative to existing approaches for pharmacophore-based virtual screening was proposed.

Exploring the effect of aplidin on low molecular weight protein tyrosine phosphatase by molecular docking and molecular dynamic simulation study

The low molecular weight protein tyrosine phosphatase (LMW-PTP) could regulate many signaling pathways, and it had drawn attention as a potential target for cancer. As previous report has indicated that the aplidin could inhibit the LMW-PTP, and thus, the relevant cancer caused by the abnormal regulation of the LMW-PTP could be remission. However, the molecular mechanism of inhibition of the LMW-PTP by the aplidin had not been fully understood. In this study, various computational approaches, namely molecular docking, MDs and post-dynamic analyses were utilized to explore the effect of the aplidin on the LMW-PTP. The results suggested that the intramolecular interactions of the residues in the two sides of the active site (Ser43-Ala55 and Pro121-Asn134) and the P-loop region (Leu13-Ser19) in the LMW-PTP was disturbed owing to the aplidin, meanwhile, the π-π interaction between Tyr131 and Tyr132 might be broken. The Asn15 might be the key residue to break the residues interactions. In a word, this study may provide more information for understanding the effect of inhibition of the aplidin on the LMW-PTP.

Novel inhibitors of leukocyte transendothelial migration

Leukocyte transendothelial migration is one of the most important step in launching an inflammatory immune response and chronic inflammation can lead to devastating diseases. Leukocyte migration inhibitors are considered as promising and potentially effective therapeutic agents to treat inflammatory and auto-immune disorders. In this study, based on previous trioxotetrahydropyrimidin based integrin inhibitors that suboptimally blocked leukocyte adhesion, twelve molecules with a modified scaffold were designed, synthesized, and tested in vitro for their capacity to block the transendothelial migration of immune cells. One of the molecules, namely, methyl 4-((2-(tert-butyl)-6-((2,4,6-trioxotetrahydropyrimidin-5(2H)-ylidene) methyl) phenoxy) methyl) benzoate, (compound 12), completely blocked leukocyte transendothelial migration, without any toxic effects on immune or endothelial cells (IC₅₀ = 2.4 µM). In vivo, compound 12 exhibited significant therapeutic effects in inflammatory bowel disease (IBD)/Crohn's disease, multiple sclerosis, fatty liver disease, and rheumatoid arthritis models. A detailed acute and chronic toxicity profile of the lead compound in vivo did not reveal any toxic effects. Such a type of molecule might therefore provide a unique starting point for designing a novel class of leukocyte transmigration blocking agents with broad therapeutic applications in inflammatory and auto-immune pathologies.

Computational Approaches for the Design of Mosquito Repellent Chemicals

BACKGROUND

In view of many current mosquito-borne diseases there is a need for the design of novel repellents.

OBJECTIVE

The objective of this article is to review the results of the researches carried out by the authors in the computer-assisted design of novel mosquito repellents.

METHODS

Two methods in the computational design of repellents have been discussed: a) Quantitative Structure Activity Relationship (QSAR) studies from a set of repellents structurally related to DEET using computed mathematical descriptors, and b) Pharmacophore based modeling for design and discovery of novel repellent compounds including virtual screening of compound databases and synthesis of novel analogues.

RESULTS

Effective QSARs could be developed using mathematical structural descriptors. The pharmacophore based method is an effective tool for the discovery of new repellent molecules.

CONCLUSION

Results reviewed in this article show that both QSAR and pharmacophore based methods can be used to design novel repellent molecules.

Identification of hepatotoxic and nephrotoxic potential markers of triptolide in mice with delayed-type hypersensitivity

Triptolide (TP) is the crucial active ingredient of Tripterygium glycoside tablets and has been shown to have a significant therapeutic effect on delayed-type hypersensitivity (DTH)-related diseases. However, due to its potential hepatotoxicity and nephrotoxicity, adverse reactions have often been observed in long-term treatment regimens. Therefore, it is meaningful to find metabolic markers for toxicity for early diagnosis. In this study, a feasible strategy using HPLC-HRMS method combined with multivariate statistical analysis to discover toxic potential markers of TP was developed. TP was used to treat a DTH mouse model at a therapeutic dose (45μg/kg) and toxic dose (900 μg/kg). The metabolic profiles of the liver, kidney and plasma were characterized by HPLC-Q/TOF MS. Significant differences in the metabolite profiles of the liver, kidney and plasma existed between the toxic and therapeutically dosed mice. Forty-six metabolites were identified and 27 of them may be related to toxicity based on a structure-toxicity prediction model. Using OPLS-DA analysis, the metabolite profiles between the two dose groups could be well distinguished. It was found that 18, 4 and 4 metabolic markers were altered in the liver, kidney and plasma, respectively; 15, 4 and 3 of these metabolic markers were predicted to be toxic. Two toxic markers detected both in mouse plasma and human liver microsomes following incubation with TP showed great potential as early diagnosis markers for TP hepatotoxicity and nephrotoxicity.

Discriminating agonist and antagonist ligands of the nuclear receptors using 3D-pharmacophores

Nuclear receptors (NRs) constitute an important class of therapeutic targets. We evaluated the performance of 3D structure-based and ligand-based pharmacophore models in predicting the pharmacological profile of NRs ligands using the NRLiSt BDB database. We could generate selective pharmacophores for agonist and antagonist ligands and we found that the best performances were obtained by combining the structure-based and the ligand-based approaches. The combination of pharmacophores that were generated allowed to cover most of the chemical space of the NRLiSt BDB datasets. By screening the whole NRLiSt BDB on our 3D pharmacophores, we demonstrated their selectivity towards their dedicated NRs ligands. The 3D pharmacophores herein presented can thus be used as a predictor of the pharmacological activity of NRs ligands.Graphical AbstractUsing a combination of structure-based and ligand-based pharmacophores, agonist and antagonist ligands of the Nuclear Receptors included in the NRLiSt BDB database could be separated.

Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases

Computational methods are well-established tools in the drug discovery process and can be employed for a variety of tasks. Common applications include lead identification and scaffold hopping, as well as lead optimization by structure-activity relationship analysis and selectivity profiling. In addition, compound-target interactions associated with potentially harmful effects can be identified and investigated. This review focuses on pharmacophore-based virtual screening campaigns specifically addressing the target class of hydroxysteroid dehydrogenases. Many members of this enzyme family are associated with specific pathological conditions, and pharmacological modulation of their activity may represent promising therapeutic strategies. On the other hand, unintended interference with their biological functions, e.g., upon inhibition by xenobiotics, can disrupt steroid hormone-mediated effects, thereby contributing to the development and progression of major diseases. Besides a general introduction to pharmacophore modeling and pharmacophore-based virtual screening, exemplary case studies from the field of short-chain dehydrogenase/reductase (SDR) research are presented. These success stories highlight the suitability of pharmacophore modeling for the various application fields and suggest its application also in futures studies.

Prospective performance evaluation of selected common virtual screening tools. Case study: Cyclooxygenase (COX) 1 and 2

Computational methods can be applied in drug development for the identification of novel lead candidates, but also for the prediction of pharmacokinetic properties and potential adverse effects, thereby aiding to prioritize and identify the most promising compounds. In principle, several techniques are available for this purpose, however, which one is the most suitable for a specific research objective still requires further investigation. Within this study, the performance of several programs, representing common virtual screening methods, was compared in a prospective manner. First, we selected top-ranked virtual screening hits from the three methods pharmacophore modeling, shape-based modeling, and docking. For comparison, these hits were then additionally predicted by external pharmacophore- and 2D similarity-based bioactivity profiling tools. Subsequently, the biological activities of the selected hits were assessed in vitro, which allowed for evaluating and comparing the prospective performance of the applied tools. Although all methods performed well, considerable differences were observed concerning hit rates, true positive and true negative hits, and hitlist composition. Our results suggest that a rational selection of the applied method represents a powerful strategy to maximize the success of a research project, tightly linked to its aims. We employed cyclooxygenase as application example, however, the focus of this study lied on highlighting the differences in the virtual screening tool performances and not in the identification of novel COX-inhibitors.