Current computer-aided drug design最新文献

Background: Pancreatic ductal adenocarcinoma (PDAC) has a 5-year relative survival rate of less than 10% making it one of the most fatal cancers. A lack of early measures of prognosis, challenges in molecular targeted therapy, ineffective adjuvant chemotherapy, and strong resistance to chemotherapy cumulatively make pancreatic cancer challenging to manage.

Objective: The present study aims to enhance understanding of the disease mechanism and its progression by identifying prognostic biomarkers, potential drug targets, and candidate drugs that can be used for therapy in pancreatic cancer.

Methods: Gene expression profiles from the GEO database were analyzed to identify reliable prognostic markers and potential drug targets. The disease's molecular mechanism and biological pathways were studied by investigating gene ontologies, KEGG pathways, and survival analysis to understand the strong prognostic power of key DEGs. FDA-approved anti-cancer drugs were screened through cell line databases, and docking studies were performed to identify drugs with high affinity for ARNTL2 and PIK3C2A. Molecular dynamic simulations of drug targets ARNTL2 and PIK3C2A in their native state and complex with nilotinib were carried out for 100 ns to validate their therapeutic potential in PDAC.

Results: Differentially expressed genes that are crucial regulators, including SUN1, PSMG3, PIK3C2A, SCRN1, and TRIAP1, were identified. Nilotinib as a candidate drug was screened using sensitivity analysis on CCLE and GDSC pancreatic cancer cell lines. Molecular dynamics simulations revealed the underlying mechanism of the binding of nilotinib with ARNTL2 and PIK3C2A and the dynamic perturbations. It validated nilotinib as a promising drug for pancreatic cancer.

Conclusion: This study accounts for prognostic markers, drug targets, and repurposed anti-cancer drugs to highlight their usefulness for translational research on developing novel therapies. Our results revealed potential and prospective clinical applications in drug targets ARNTL2, EGFR, and PI3KC2A for pancreatic cancer therapy.

Background: Plasmodium vivax (P. vivax) is one of the highly prevalent human malaria parasites. Due to the presence of extravascular reservoirs, P. vivax is extremely challenging to manage and eradicate. Traditionally, flavonoids have been widely used to combat various diseases. Recently, biflavonoids were discovered to be effective against Plasmodium falciparum.

Methods: In this study, in silico approaches were utilized to inhibit Duffy binding protein (DBP), responsible for Plasmodium invasion into red blood cells (RBC). The interaction of flavonoid molecules with the Duffy antigen receptor for chemokines (DARC) binding site of DBP was investigated using a molecular docking approach. Furthermore, molecular dynamic simulation studies were carried out to study the stability of top-docked complexes.

Results: The results showed the effectiveness of flavonoids, such as daidzein, genistein, kaempferol, and quercetin, in the DBP binding site. These flavonoids were found to bind in the active region of DBP. Furthermore, the stability of these four ligands was maintained throughout the 50 ns simulation, maintaining stable hydrogen bond formation with the active site residues of DBP.

Conclusion: The present study suggests that flavonoids might be good candidates and novel agents against DBP-mediated RBC invasion of P. vivax and can be further analyzed in in vitro studies.

Background: The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a worldwide public health crisis. At present, the development of effective drugs and/or related therapeutics is still the most urgent and important task for combating the virus. The viral entry and associated infectivity mainly rely on its envelope spike protein to recognize and bind to the host cell receptor angiotensin-converting enzyme 2 (ACE2) through a conformational switch of the spike receptor binding domain (RBD) from inactive to active state. Thus, it is of great significance to design an allosteric inhibitor targeting spike to lock it in the inactive and ACE2-inaccessible state.

Objective: This study aims to discover the potential broad-spectrum allosteric inhibitors capable of binding and stabilizing the diverse spike variants, including the wild type, Delta, and Omicron, in the inactive RBD down state.

Methods: In this work, we first detected a potential allosteric pocket within the SARS-CoV-2 spike protein. Then, we performed large-scale structure-based virtual screening by targeting the putative allosteric pocket to identify allosteric inhibitors that could stabilize the spike inactive state. Molecular dynamics simulations were further carried out to evaluate the effects of compound binding on the stability of spike RBD.

Results: Finally, we identified three potential allosteric inhibitors, CPD3, CPD5, and CPD6, against diverse SARS-CoV-2 variants, including Wild-type, Delta, and Omicron variants. Our simulation results showed that the three compounds could stably bind the predicted allosteric site and effectively stabilize the spike in the inactive state.

Conclusion: The three compounds provide novel chemical structures for rational drug design targeting spike protein, which is expected to greatly assist in the development of new drugs against SARS-CoV-2.

Background: Type 2 diabetes-associated cognitive dysfunction (DCD) is a chronic complication of diabetes that has gained international attention. The medicinal compound Banxia Xiexin Decoction (BXXXD) from traditional Chinese medicine (TCM) has shown potential in improving insulin resistance, regulating endoplasmic reticulum stress (ERS), and inhibiting cell apoptosis through various pathways. However, the specific mechanism of action and medical value of BXXXD remain unclear.

Methods: We utilized TCMSP databases to screen the chemical constituents of BXXXD and identified DCD disease targets through relevant databases. By using Stitch and String databases, we imported the data into Cytoscape 3.8.0 software to construct a protein-protein interaction (PPI) network and subsequently identified core targets through network topology analysis. The core targets were subjected to Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The results were further validated through in vitro experiments.

Results: Network pharmacology analysis revealed the screening of 1490 DCD-related targets and 190 agents present in BXXXD. The topological analysis and enrichment analysis conducted using Cytoscape software identified 34 core targets. Additionally, GO and KEGG pathway analyses yielded 104 biological targets and 97 pathways, respectively. BXXXD exhibited its potential in treating DCD by controlling synaptic plasticity and conduction, suppressing apoptosis, reducing inflammation, and acting as an antioxidant. In a high glucose (HG) environment, the expression of JNK, Foxo3a, SIRT1, ATG7, Lamp2, and LC3 was downregulated. BXXXD intervention on HT22 cells potentially involved inhibiting excessive oxidative stress, promoting neuronal autophagy, and increasing the expression levels of JNK, SIRT1, Foxo3a, ATG7, Lamp2, and LC3. Furthermore, the neuroprotective effect of BXXXD was partially blocked by SP600125, while quercetin enhanced the favorable role of BXXXD in the HG environment.

Conclusion: BXXXD exerts its effects on DCD through multiple components, targets, levels, and pathways. It modulates the JNK/SIRT1/Foxo3a signaling pathway to mitigate autophagy inhibition and apoptotic damage in HT22 cells induced by HG. These findings provide valuable perspectives and concepts for future clinical trials and fundamental research.

Background: Shugan Jieyu Capsule (SJC) is a pure Chinese medicine compound prepared with Hypericum perforatum and Acanthopanacis senticosi. SJC has been approved for the clinical treatment of depression, but the mechanism of action is still unclear.

Objectives: Network pharmacology, molecular docking, and molecular dynamics simulation (MDS) were applied in the present study to explore the potential mechanism of SJC in the treatment of depression.

Methods: TCMSP, BATMAN-TCM, and HERB databases were used, and related literature was reviewed to screen the effective active ingredients of Hypericum perforatum and Acanthopanacis senticosi. TCMSP, BATMAN-TCM, HERB, and STITCH databases were used to predict the potential targets of effective active ingredients. GeneCards database, DisGeNET database, and GEO data set were used to obtain depression targets and clarify the intersection targets of SJC and depression. STRING database and Cytoscape software were used to build a protein-protein interaction (PPI) network of intersection targets and screen the core targets. The enrichment analysis on the intersection targets was conducted. Then the receiver operator characteristic (ROC) curve was constructed to verify the core targets. The pharmacokinetic characteristics of core active ingredients were predicted by SwissADME and pkCSM. Molecular docking was performed to verify the docking activity of the core active ingredients and core targets, and molecular dynamics simulations were performed to evaluate the accuracy of the docking complex.

Results: We obtained 15 active ingredients and 308 potential drug targets with quercetin, kaempferol, luteolin, and hyperforin as the core active ingredients. We obtained 3598 targets of depression and 193 intersection targets of SJC and depression. A total of 9 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2) were screened with Cytoscape 3.8.2 software. A total of 442 GO entries and 165 KEGG pathways (p <0.01) were obtained from the enrichment analysis of the intersection targets, mainly enriched in IL-17, TNF, and MAPK signaling pathways. The pharmacokinetic characteristics of the 4 core active ingredients indicated that they could play a role in SJC antidepressants with fewer side effects. Molecular docking showed that the 4 core active components could effectively bind to the 8 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2), which were related to depression by the ROC curve. MDS showed that the docking complex was stable.

Conclusion: SJC may treat depression by using active ingredients such as quercetin, kaempferol, luteolin, and hyperforin to regulate targets such as PTGS2 and CASP3 and signaling pathways such as IL-17, TNF, and MAPK, and participate in immune inflammation, oxidative stress, apoptosis, neurogenesis, etc.

Background: Based on the anti-inflammatory and analgesic activity of hydrazone and phthalimide, a new series of hybrid hydrazone and phthalimide pharmacophores was prepared and evaluated as analgesic agents.

Methods: The designed ligands were synthesized by reaction of the appropriate aldehydes and 2- aminophthalimide. Analgesic, cyclooxygenase inhibitory, and cytostatic activity of prepared compounds were measured.

Results: All the tested ligands demonstrated significant analgesic activity. Moreover, compounds 3i and 3h were the most potent ligands in the formalin and writhing tests, respectively. Compounds 3g, 3j, and 3l were the most COX-2 selective ligands and ligand 3e was the most potent COX inhibitor with a 0.79 of COX-2 selectivity ratio. The presence of electron-withdrawing moieties with hydrogen bonding ability at the meta position was found to affect the selectivity efficiently, in which compounds 3g, 3l, and 3k showed high COX-2 selectivity, and compound 3k was the most potent one. The cytostatic activity of selected ligands demonstrated that compounds 3e, 3f, 3h, 3k, and 3m showed good analgesic and COX inhibitory activity and were less toxic than the reference drug.

Conclusion: High therapeutic index of these ligands is one of the valuable advantages of these compounds.

Aims: The aim of this study is to develop a novel antiviral strategy capable of efficiently targeting a broad set of SARS-CoV-2 variants.

Background: Since the first emergence of SARS-CoV-2, it has rapidly transformed into a global pandemic, posing an unprecedented threat to public health. SARS-CoV-2 is prone to mutation and continues to evolve, leading to the emergence of new variants capable of escaping immune protection achieved due to previous SARS-CoV-2 infections or by vaccination.

Objective: RNA interference (RNAi) is a remarkable biological mechanism that can induce gene silencing by targeting complementary mRNA and inhibiting its translation.

Methods: In this study, using the computational approach, we predicted the most efficient siRNA capable of inhibiting SARS-CoV-2 variants of concern (VoCs).

Results: The presented siRNA was characterized and evaluated for its thermodynamic properties, offsite-target hits, and in silico validation by molecular docking and molecular dynamics simulations (MD) with Human AGO2 protein.

Conclusion: The study contributes to the possibility of designing and developing an effective response strategy against existing variants of concerns and preventing further.

Introduction: JAK3 kinase inhibitor has become an effective means to treat tumors and autoimmune diseases.

Methods: In this study, molecular docking and molecular dynamics simulation were used to study the theoretical interaction mechanism between 1-phenylimidazolidine-2-one molecules and JAK3 protein.

Results: The results of molecular docking showed that the six 1-phenylimidazolidine-2-one derivatives obtained by virtual screening were bound to the ATP pocket of JAK3 kinase, which were competitive inhibitors of ATP, and were mainly bound to the pocket through hydrogen bonding and hydrophobic interaction. Further, MM/GBSA based on molecular dynamics simulation sampling was used to calculate the binding energy between six molecules and the JAK3 kinase protein. Subsequently, the binding energy was decomposed into the contribution of each amino acid residue, of which Leu905, Lys855, Asp967, Leu956, Tyr904, and Val836 were the main energycontributing residues. Among them, the molecule numbered LCM01415405 can interact with the specific amino acid Arg911 of JAK3 kinase, suggesting that the molecule may be a selective JAK3 kinase inhibitor. The root-mean-square fluctuation (RMSF) of JAK3 kinase pocket residues during molecular dynamics simulation showed that the combination of six new potential small molecule inhibitors with JAK3 kinase could reduce the flexibility of JAK3 kinase pocket residues.

Conclusion: These findings reveal the mechanism of 1-phenylimidazolidine-2-one derivatives on JAK3 protein and provide a relatively solid theoretical basis for the development and structural optimization of JAK3 protein inhibitors.

Background: Drug-resistant Staphylococcus aureus (S. aureus) has spread from nosocomial to community-acquired infections. Novel antimicrobial drugs that are effective against resistant strains should be developed. S. aureus tyrosyl-tRNA synthetase (saTyrRS) is considered essential for bacterial survival and is an attractive target for drug screening.

Objectives: The purpose of this study was to identify potential new inhibitors of saTyrRS by screening compounds in silico and evaluating them using molecular dynamics (MD) simulations.

Methods: A 3D structural library of 154,118 compounds was screened using the DOCK and GOLD docking simulations and short-time MD simulations. The selected compounds were subjected to MD simulations of a 75-ns time frame using GROMACS.

Results: Thirty compounds were selected by hierarchical docking simulations. The binding of these compounds to saTyrRS was assessed by short-time MD simulations. Two compounds with an average value of less than 0.15 nm for the ligand RMSD were ultimately selected. The longtime (75 ns) MD simulation results demonstrated that two novel compounds bound stably to saTyrRS in silico.

Conclusion: Two novel potential saTyrRS inhibitors with different skeletons were identified by in silico drug screening using MD simulations. The in vitro validation of the inhibitory effect of these compounds on enzyme activity and their antibacterial effect on drug-resistant S. aureus would be useful for developing novel antibiotics.

Background: Medicinal plants play an essential role in everyday life; plants highly contain therapeutic phytoconstituents commonly used to treat various diseases. This paper discusses the Chemical composition, In vitro antiproliferative activity and In silico study of essential oil extracted from Ocimum tenuiflorum (family Lamiaceae) and Coriandrum sativum (family Apiaceae).

Objective: In present study GC-MS was used to identify the chemical constituents from O. tenuiflorum and C. sativum. In vitro antiproliferative activity was performed on A549 cancer cell lines. In silico study was performed by Schrodinger's maestro software to identify chemical constituents in both plants as potential EGFR inhibitors for the treatment of lung cancer.

Methods: The essential oil was extracted by hydro distillation from aerial parts of O. tenuiflorum and C. sativum. The volatile oil sample was analyzed by (GC-MS) Gas Chromatography- Mass Spectrometry. Different chemical constituents were identified based on the retention index and compared with the NIST library. The oil samples from O. tenuiflorum and C. sativum was also evaluated for antiproliferative activity against human lung cancer A549 cell lines. In silico study was performed by Schrodinger maestro software against EGFR (PDB ID 5HG8).

Results: O. tenuiflorum essential oil contains Eugenol (42.90%), 2-β-Elemene (25.98%), β- Caryophyllene (19.12%) are the major constituents. On the other side, C. sativum contains nnonadecanol- 1 (16.37%), decanal (12.37%), dodecanal (12.27%), 2-Dodecanal (9.67%), Phytol (8.81%) as the major constituents. Both the oils have shown in vitro antiproliferative activity against human lung cancer cell lines A549 having IC₅₀ values of 38.281 μg/ml (O. tenuiflorum) and 74.536 μg/ml (C. sativum). Molecular interactions of constituents hydro distilled from two oils was analysed by schrodinger maestro software against EGFR (PDB ID 5HG8).

Conclusion: The oil sample extracted from O. tenuiflorum showed more antiproliferative activity than C. sativum. In silico study showed that two chemical constituents, namely di-isobutyl phthalate (-7.542 kcal/mol) and dibutyl phthalate (-7.181 kcal/mol) from O. tenuiflorum and one diethyl phthalate (-7.224 kcal/mol) from C. sativum having more docking score than standard Osimertinib which indicates the effectiveness of oils for lung cancer.