Finding small chemical modulators capable of blocking 1 membrane-embedded CXCR4, a critical therapeutic target for renal fibrosis: a computational approach

Despite essential experimental efforts focused on studying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), computational chemistry methods are promising complementary tools in combating coronavirus disease 2019 (COVID-19). The present review aims to provide readers with the recent progress and advances in computational approaches currently used to streamline drug discovery and development in the context of COVID-19. Our review is dual purpose. It is intended (a) to familiarize the readership with the general concept of QSAR, in silico screening, molecular docking and molecular dynamics (MD) simulations and (b) to provide key examples of the recent applications of these computational tools in discovering novel therapeutic agents against COVID-19. We outline how structure- and ligand-based drug design can accelerate the structural elucidation of pharmacological drug targeting and the discovery of preclinical drug candidate molecules. Several examples of MD computational studies demonstrate how atomistic MD simulations can facilitate our understanding of the molecular basis of drug actions and biological mechanisms of virus inhibition in atomic detail. Finally, the short- and long-term perspectives in computational drug discovery are discussed. The aim of this study is to summarize the last three years' progress and advances in computational approaches currently used to streamline the drug discovery and development process in the context of COVID-19. Materials and methods. The literature overview of QSAR, in silico screening, machine learning, molecular docking and molecular dynamics (MD) simulations is given in the context of COVID-19. The literature search was performed using online databases, such as Scopus, Web of Science, PDB-protein databank, and PubMed, focusing on the following keywords - human coronavirus, QSAR, molecular docking, virtual screening, machine learning, molecular dynamics, Mpro and PLpro proteases, SARS-CоV-2, respectively. Results. The review familiarizes the readership with the general concept of QSAR, in silico screening, machine learning, molecular docking and MD simulations and provides key examples of the recent applications of these computational tools in discovering novel therapeutic agents against COVID-19. Conclusions. New insight into the recent progress and achievements in computer-guided drug discovery for therapeutic agents against SARS-CoV-2 is provided

Integrated network analysis and experimental verification of the mechanisms employed by Compound Jixuecao Decoction to improve endoplasmic reticulum stress and apoptosis in chronic renal failure

CD248+ stromal cells are associated with progressive chronic kidney disease

IntroductionThe CXCR4 chemokine receptor is a G protein-coupled receptor that plays a role in many physiological processes and diseases, such as cancer metastasis, HIV infection, and immune response. Because of this, it may be possible to target it therapeutically. In addition, the active ingredient of Phaseolus vulgaris L (PVL) has been reported to have anti-inflammatory, antioxidant, and anticancer properties. Novel CXCR4 antagonists from natural resources can be a promising drug development product using a computational approach. This study aims to explore the active compound in PVL that has the responsibility to inhibit CXCR4 using molecular docking and dynamics simulation.Materials and methodsPharmacokinetic analysis were performed using the pkCSM, OSIRIS for toxicity risk analysis, and the PerMM for membrane permeability assessment. Molecular docking was performed using PyRx software to determine the interaction between the CXCR4 target protein from the PDB database and the active component of PVL from the PubChem database. A molecular dynamics (MD) simulation was performed to determine the stability of the interaction using the WEBGRO Macromolecular Simulations online server. The analysis were performed by comparing the results with plerixafor as a control ligand.Results and discussionThe pharmacokinetic analysis of quercetin, kaempferol, myricetin, catechin, 3,4-dihydroxybenzoic acid, and daidzin in PVL showed that they met the drug-like criteria. These chemicals were expected to have medium-risk effects on mutagenesis and tumorigenesis, with the exception of catechin, which has no risk of toxicity, and daidzin, which has high-risk effects on mutagenesis and reproduction. Molecular docking identified that quercetin (− 6.6 kcal/mol), myricetin (− 6.6 kcal/mol), catechin (− 6.5 kcal/mol), and 3,4-dihydroxybenzoic acid (− 5.4 kcal/mol) bind to CXCR4 with the highest affinity compared to plerixafor (− 5.0 kcal/mol) and can bind to the same binding pocket with key residues Asp187, Asp97, and Glu288. The MD simulation analysis showed that quercetin has a similar stability interaction compared to the control.ConclusionsConsidering the pharmacokinetic analysis, molecular docking, and MD simulations, quercetin, myricetin, and 3,4-dihydroxybenzoic acid have the potential to become CXCR4 agonists with their good oral bioavailability and safety properties for the novel drug candidates. Future studies are needed to consider the molecular docking result.

Molecular docking, molecular dynamics simulations and QSAR studies on some of 2-arylethenylquinoline derivatives for inhibition of Alzheimer's amyloid-beta aggregation: Insight into mechanism of interactions and parameters for design of new inhibitors

Xiaoqinglong Decoction (XQLD) is a traditional Chinese medicinal formula commonly used to treat chronic urticaria (CU). However, its underlying therapeutic mechanisms remain incompletely characterized. This study employed an integrated approach combining network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulations to identify the active components, potential targets, and related signaling pathways involved in XQLD's therapeutic action against CU, thereby providing a mechanistic foundation for its clinical application. The active components of XQLD and their corresponding targets were identified using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CU-related targets were retrieved from the OMIM and GeneCards databases. Subsequently, core components and targets were determined via protein-protein interaction (PPI) network analysis and component-target-pathway network construction. Topological analyses were performed using Cytoscape software to prioritize core nodes within these networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted via the DAVID database to identify enriched biological processes and signaling pathways. Molecular docking was performed to evaluate binding interactions between key components and core targets, while molecular dynamics (MD) simulations were employed to assess the stability of the component-target complexes with the lowest binding energy. Finally, CU-related targets of XQLD were validated using datasets from the Gene Expression Omnibus (GEO) database. A total of 135 active components and 249 potential targets of XQLD were identified, alongside 1,711 CU-related targets. Core components, such as quercetin, kaempferol, beta-sitosterol, naringenin, stigmasterol, and luteolin, exhibited high degree values in the constructed networks. The core targets identified included AKT1, TNF, IL6, TP53, PTGS2, CASP3, BCL2, ESR1, PPARG, and MAPK3. GO and KEGG pathway enrichment analyses revealed the PI3K-Akt signaling pathway as a central regulatory mechanism. Molecular docking studies demonstrated strong binding affinities between active components and core targets, with the stigmasterol-AKT1 complex exhibiting the lowest binding energy (-11.4 kcal/mol) and high stability in MD simulations. Validation using GEO datasets identified 12 core genes shared between CU-related targets and XQLD-associated targets, including PTGS2 and IL6, which were also prioritized as core targets in the network pharmacology analyses. This study comprehensively integrates multidisciplinary approaches to clarify the potential molecular mechanisms of XQLD in treating CU, highlighting its multitarget and multipathway synergistic effects. Molecular docking and dynamics simulations confirm the stable interaction between stigmasterol and the core target AKT1. Additionally, GEO dataset analysis verifies the pathogenic relevance of targets such as PTGS2 and IL6, significantly enhancing the credibility of our findings. These results provide a modern scientific basis for the traditional therapeutic effects of XQLD on CU and have important implications for developing multitarget treatments for this condition. However, this study mainly relies on database mining and computational simulations. Further in vitro and in vivo experimental validations are needed to confirm the predicted component-target-pathway interactions. This study identifies the active components, potential targets, and pathways through which XQLD exerts therapeutic effects on CU. These findings provide a theoretical foundation for further mechanistic studies and support their clinical application in the treatment of CU.

Monoamine oxidase B (MAO-B) serves as a critical target in the management of neurodegenerative diseases (NDDs) such as Alzheimer’s and Parkinson’s due to its role in regulating oxidative stress and dopamine metabolism. In this context, phytochemicals from Oxalis species, known for their neuroprotective properties, were explored for their potential MAO-B inhibitory activity using computational approach. Plant-derived compounds, offering a better safety profile than synthetic drugs and greater cost-effectiveness, present a promising avenue for developing alternative therapeutic strategies. Molecular docking (MD), molecular dynamics simulations (MDS), and binding free energy calculations were employed to evaluate the inhibitory potential of Oxalis phytochemicals against MAO-B (PDB ID: 4A79). Stable ligand-protein complexes with optimal docking scores were selected, and key parameters from molecular dynamics trajectories, including binding stability and interactions, were analyzed to identify high potential inhibitors of MAO-B for therapeutic development. Results showed beta-sitosterol (−11.92 kcal/mol), squalene (−11.89 kcal/mol), etretinate (−11.46 kcal/mol), rhoifolin (−11.44 kcal/mol), and swertisin (−11.13 kcal/mol) demonstrated superior binding affinities compared to the native ligand (−11.12 kcal/mol). Three additional compounds; phloridzin (−11.10 kcal/mol), rhapontin (−11.02 kcal/mol), and diosmetin 7-O-beta-D-glucopyranoside (−10.96 kcal/mol) exhibited better binding than reference drugs. The predominant interactions between protein and ligand were hydrophobic, with hydrogen bonds and Pi-stacking enhancing the complexes’ stability. The evaluation based on geometrical and thermodynamic metrics derived from 200 ns MDS, identified rhoifolin, beta-sitosterol, and swertisin as promising MAO-B inhibitors. Minimal translational and rotational movements of these ligands within the catalytic site of MAO-B under quasi-physiological conditions suggested effective inhibition. Preserved thermodynamic feasibility reinforced these findings. ADMET analysis identified squalene and beta-sitosterol as CNS active candidates with favorable pharmacokinetics, while etretinate, rhoifolin, and swertisin may act as peripheral modulators, requiring optimization for improved CNS delivery. Further experimental validation of efficacy, pharmacokinetics, and safety is recommended to advance the therapeutic potential of these hit candidates.

Monoamine oxidase B (MAO-B) serves as a critical target in the management of neurodegenerative diseases (NDDs) such as Alzheimer’s and Parkinson’s due to its role in regulating oxidative stress and dopamine metabolism. In this context, phytochemicals from Oxalis species, known for their neuroprotective properties, were explored for their potential MAO-B inhibitory activity using computational approach. Plant-derived compounds, offering a better safety profile than synthetic drugs and greater cost-effectiveness, present a promising avenue for developing alternative therapeutic strategies. Molecular docking (MD), molecular dynamics simulations (MDS), and binding free energy calculations were employed to evaluate the inhibitory potential of Oxalis phytochemicals against MAO-B (PDB ID: 4A79). Stable ligand-protein complexes with optimal docking scores were selected, and key parameters from molecular dynamics trajectories, including binding stability and interactions, were analyzed to identify high potential inhibitors of MAO-B for therapeutic development. Results showed beta-sitosterol (−11.92 kcal/mol), squalene (−11.89 kcal/mol), etretinate (−11.46 kcal/mol), rhoifolin (−11.44 kcal/mol), and swertisin (−11.13 kcal/mol) demonstrated superior binding affinities compared to the native ligand (−11.12 kcal/mol). Three additional compounds; phloridzin (−11.10 kcal/mol), rhapontin (−11.02 kcal/mol), and diosmetin 7-O-beta-D-glucopyranoside (−10.96 kcal/mol) exhibited better binding than reference drugs. The predominant interactions between protein and ligand were hydrophobic, with hydrogen bonds and Pi-stacking enhancing the complexes’ stability. The evaluation based on geometrical and thermodynamic metrics derived from 200 ns MDS, identified rhoifolin, beta-sitosterol, and swertisin as promising MAO-B inhibitors. Minimal translational and rotational movements of these ligands within the catalytic site of MAO-B under quasi-physiological conditions suggested effective inhibition. Preserved thermodynamic feasibility reinforced these findings. ADMET analysis identified squalene and beta-sitosterol as CNS active candidates with favorable pharmacokinetics, while etretinate, rhoifolin, and swertisin may act as peripheral modulators, requiring optimization for improved CNS delivery. Further experimental validation of efficacy, pharmacokinetics, and safety is recommended to advance the therapeutic potential of these hit candidates.

Nonalcoholic fatty liver disease (NAFLD) is a metabolic disease, the incidence of which increases annually. Shugan Xiaozhi (SGXZ) decoction, a composite traditional Chinese medicinal prescription, has been demonstrated to exert a therapeutic effect on NAFLD. In this study, the potential bioactive ingredients and mechanism of SGXZ decoction against NAFLD were explored via network pharmacology, molecular docking, and molecular dynamics simulation. Compounds in SGXZ decoction were identified and collected from the literature, and the corresponding targets were predicted through the Similarity Ensemble Approach database. Potential targets related to NAFLD were searched on DisGeNET and GeneCards databases. The compound-target-disease and protein-protein interaction (PPI) networks were constructed to recognize key compounds and targets. Functional enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed on the targets. Molecular docking was used to further screen the potent active compounds in SGXZ. Finally, molecular dynamics (MD) simulation was applied to verify and validate the binding between the most potent compound and targets. A total of 31 active compounds and 220 corresponding targets in SGXZ decoction were collected. Moreover, 1,544 targets of NAFLD were obtained, of which 78 targets intersected with the targets of SGXZ decoction. Key compounds and targets were recognized through the compound-target-disease and PPI network. Multiple biological pathways were annotated, including PI3K-Akt, MAPK, insulin resistance, HIF-1, and tryptophan metabolism. Molecular docking showed that gallic acid, chlorogenic acid and isochlorogenic acid A could combine with the key targets. Molecular dynamics simulations suggested that isochlorogenic acid A might potentially bind directly with RELA, IL-6, VEGFA, and MMP9 in the regulation of PI3K-Akt signaling pathway. This study investigated the active substances and key targets of SGXZ decoction in the regulation of multiple-pathways based on network pharmacology and computational approaches, providing a theoretical basis for further pharmacological research into the potential mechanism of SGXZ in NAFLD.

Background:Alpinia officinarum, a member of the Zingiberaceae family, is native to East Asia. It possesses various properties, including antineoplastic effects, but the molecular mechanism underlying its inhibition of acute myeloid leukemia (AML) remains unclear. This study explored the biological mechanisms and pharmacological effects of Alpinia officinarum in AML through network pharmacology, molecular docking and molecular dynamics (MD) simulation. Methods: Active compounds were identified through a literature review and Dr. Duke’s database. Compounds were screened based on solubility, oral bioavailability (OB) and drug-likeness (DL) using SwissADME and Molsoft tools. Targets related to the identified compounds were acquired using SwissTargetPrediction, and AML targets were extracted from DisGeNET, OMIM and GeneCards. Common targets of the active compounds and AML were further analyzed via gene ontology (GO) and pathway enrichment using ShinyGO, followed by the protein–protein interaction (PPI) through STRING and Cytoscape to elucidate key targets. Molecular docking and dynamics simulation were employed to find a lead compound. Results: Eleven potential active compounds and six key targets were identified. The targets were enriched in pathways such as central carbon metabolism in cancer and the PI3K-Akt signaling pathway. Molecular docking revealed that Alpinin A had a high affinity for the six key targets (BCL2, AKT1, PIK3CA, ABL1, TERT and FLT3). Furthermore, MD simulation demonstrated the stability of the AKT1-Alpinin A complex which showed the best docking score among other active compounds. Conclusion: Our study indicates that Alpinin A may serve as a promising agent against AML, highlighting its potential for further pharmacological investigation.

Spinocerebellar ataxia (SCA) is a rare neurological illness inherited dominantly that causes severe impairment and premature mortality. While each rare disease may affect individuals infrequently, collectively they pose a significant healthcare challenge. It is mainly carried out due to the expansion of RNA triplet (CAG) repeats, although missense or point mutations can also be induced. Unfortunately, there is no cure; only symptomatic treatments are available. To date, SCA has about 48 subtypes, the most common of these being SCA 1, 2, 3, 6, 7, 12, and 17 having CAG repeats. Using molecular docking and molecular dynamics (MD) simulation, this study seeks to investigate effective natural herbal neuroprotective compounds against CAG repeats, which are therapeutically significant in treating SCA. Initially, virtual screening followed by molecular docking was used to estimate the binding affinity of neuroprotective natural compounds toward CAG repeats. The compound with the highest binding affinity, somniferine, was then chosen for MD simulation. The structural stability, interaction mechanism, and conformational dynamics of CAG repeats and somniferine were investigated via MD simulation. The MD study revealed that during the simulation period, the interaction between CAG repeats and somniferine stabilizes and results in fewer conformational variations. This in silico study suggests that Somniferine can be used as a therapeutic medication against RNA CAG repeats in SCA.

Acetylcholinesterase (AChE) is a critical enzyme involved in neurotransmission by hydrolyzing acetylcholine at the synaptic cleft, making it a key target for drug discovery, particularly in the treatment of neurodegenerative disorders such as Alzheimer's disease. Computational approaches, particularly molecular docking and molecular dynamics (MD) simulations, have become indispensable tools for identifying and optimizing AChE inhibitors by predicting ligand-binding affinities, interaction mechanisms, and conformational dynamics. This review serves as a comprehensive guide for future research on AChE using molecular docking and MD simulations. It compiles and analyzes studies conducted over the past five years, providing a critical evaluation of the most widely used computational tools, including AutoDock, AutoDock Vina, and GROMACS, which have significantly contributed to the advancement of AChE inhibitor screening. Furthermore, we identify PDB ID: 4EY7, the most frequently used AChE crystal structure in docking studies, and highlight Donepezil, a well-established reference molecule widely employed as a control in computational screening for novel inhibitors. By examining these key aspects, this review aims to enhance the accuracy and reliability of virtual screening approaches and guide researchers in selecting the most appropriate computational methodologies. The integration of docking and MD simulations not only improves hit identification and lead optimization but also provides deeper mechanistic insights into AChE-ligand interactions, contributing to the rational design of more effective AChE inhibitors.

Benign prostatic hyperplasia (BPH) is caused by augmented levels of androgen dihydrotestosterone (DHT) which is involved in the growth of the prostate in humans. 5α-Reductase type II (5αR2) is an intracellular enzyme that catalyses the formation of DHT from testosterone; hence, the inhibition of 5αR2 has emerged as one of the most promising strategies for the treatment of BPH. In this study, a computational approach that integrates ligand-based pharmacophore modelling, virtual screening, molecular docking and molecular dynamics (MD) simulations was adopted to discover novel 5αR2 inhibitors with less side effects. After validating by Fischer's randomisation and Güner–Henry test, the best quantitative pharmacophore model (Hypo1), consisting of two hydrogen-bond acceptors and three hydrophobic features, was subsequently used as a three-dimensional-query in virtual screening to identify potential hits from Maybridge and National Cancer Institute databases. These hits were further filtered by ADMET (absorption, distribution, metabolism, elimination and toxicology) and molecular docking experiments, and their binding stabilities were validated by 10-ns MD simulations. Finally, only one hit was identified as a potential lead based on higher predicted inhibitory activity to 5αR2 compared with the most active inhibitor (finasteride). Our results further suggest that this potential lead could easily be synthesised and has structural novelty, making it a promising candidate for treating BPH.

Heat shock protein 90(Hsp90), as a molecular chaperone, play a crucial role in folding and proper function of many proteins. Hsp90 inhibitors containing isoxazole scaffold are currently being used in the treatment of cancer as tumor suppressers. Here in the present studies, new compounds based on isoxazole scaffold were predicted using a combination of molecular modeling techniques including three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking and molecular dynamic (MD) simulations. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were also done. The steric and electrostatic contour map of CoMFA and CoMSIA were created. Hydrophobic, hydrogen bond donor and acceptor of CoMSIA model also were generated, and new compounds were predicted by CoMFA and CoMSIA contour maps. To investigate the binding modes of the predicted compounds in the active site of Hsp90, a molecular docking simulation was carried out. MD simulations were also conducted to evaluate the obtained results on the best predicted compound and the best reported Hsp90 inhibitors in the 3D-QSAR model. Findings indicate that the predicted ligands were stable in the active site of Hsp90.

Fufang Honghua Buji (FHB) granules, have proven efficacy against vitiligo in long-term clinical practice. However, its major active chemical components and molecular mechanisms of action remain unknown. The purpose of this study was to confirm the molecular mechanism of FHB's therapeutic effect on vitiligo utilizing network pharmacology, molecular docking, and molecular dynamics simulation prediction, as well as experimental verification. Traditional Chinese Medicine Systems Pharmacology (TCMSP) and HERB databases were used to obtain the chemical composition and action targets of FHB. Online Mendelian Inheritance in Man (OMIM), DrugBank, DisGeNET, GeneCards, and Therapeutic Target Database (TTD) databases were applied to screen for vitiligo-related targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed through the Matascape database. Molecular docking and dynamics simulation methods were for the analysis of the binding sites and binding energies between the FHB's active components and the targets. Finally, a vitiligo mouse model was created, and the therapeutic effect and molecular mechanism of action of FHB were validated using enzyme linked immunosorbent assay (ELISA), western blot (WB), and quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Additionally, hematoxylin-eosin staining (HE) and blood biochemical assays were conducted to assess the biosafety of FHB. The screening of chemical composition and targets suggested that 94 genetic targets of FHB were associated with vitiligo. The bioinformatics analysis suggested that luteolin, quercetin, and wogonin may be major active components, and nuclear factor-kappa B p65 subunit (RELA), signal transducer, and activator of transcription (STAT) 3 and RAC-alpha serine/threonine-protein kinase (AKT) 1 may be potential targets of FHB-vitiligo therapy. Molecular docking and dynamics simulation further demonstrated that luteolin, quercetin, and wogonin all bound best to STAT3. Through experimental verification, FHB has been demonstrated to alleviate the pathogenic characteristics of vitiligo mice, suppress the JAK-STAT signaling pathway, reduce inflammation, and increase melanogenesis. The in vivo safety evaluation experiments also demonstrated the non-toxicity of FHB. FHB exerts anti-inflammatory and melanogenesis-promoting effects via the effect of multi-component on multi-target, among which the JAK-STAT pathway is a validated FHB-vitiligo target, providing new ideas and clues for the development of vitiligo therapy.