Nanoparticles-based viral treatment has expressed an outstanding potency against most viral streams such as SARS-CoV-2, and influenza. Metallic nanoparticles, especially gold and silver, have gained considerable interest and have been extensively manipulated and tested as proposed antiviral agents, owing to their outstanding characteristics, such as their interesting biocompatibility. In our study, we focus on using uncapped ultra-small Gold (AuNP) and Silver (AgNP) nanoparticles of 1.5 nm radius to test their potency against receptor-binding domain (RBD) of the spike protein binding to the angiotensin converting enzyme-2 (ACE2). To explore protein dynamics and the effect of AuNP and AgNP on the RBD-ACE2 binding, a molecular dynamics (MD) simulation was employed. It was found that AuNP has been able to destabilize the bonding between RBD and ACE2, and has caused conformational changes in the RBD domain, while maintaining the ACE2 conformation and structure, compared to the NP-free system. This indicates that AuNP is safe to be used for targeting the omicron variant and hindering it from invading the host cell. While, even if AgNP was able to denature the viral RBD, it affected the host cell receptor ACE2 structure and conformation and helped in increasing their binding compared to the NP-free system. This was confirmed through the free energy of binding calculation including the interaction entropy contribution of the three systems.

Previous research has shown that there is an interaction between Influenza A viral surface neuraminidase (NA) and the host endoplasmic reticulum chaperone GRP78 in the early phases of NA production in the endoplasmic reticulum. In this study, we predict the binding sites of neuraminidase for H1N1, H3N2, and H5N1 strains. We select 13 conserved, cysteine-cyclized regions, one of which is hypothesized to be a possible binding site for GRP78. Using the grand average hydrophobicity index (GRAVY), we focus only on specific highlighted hydrophobic regions, which match the profile of the cyclic peptide, Pep42. Protein-protein docking analysis using HADDOCK suggests that region VIII (C278:C291) is the best possible binding site with the substrate-binding domain β (SBDβ) of GRP78. Subsequently, MDS runs for 150 ns are conducted, and MM-GBSA calculations are done for the three complexes (-7.10, -22.22, and -11.26 kcal/mol for H1N1, H3N2, and H5N1, respectively). The results indicate that GRP78 remains associated with the NA of H3N2, whereas the NAs of H1N1 and H5N1 dissociate from GRP78 during the simulation. Our findings show that region VIII is a potential therapeutic target for neutralizing the viral neuraminidase of seasonal H3N2 flu.

Iron oxide nanoparticles (IONPs) have proven to be of therapeutic potential against cancer. The feature of the surface coating can affect important properties of IONPs; it is therefore critical for further understanding how these materials react to physiological conditions, which is still needed to fully exploit the potential of IONPs for their theranostic applications. In this study, we explored the therapeutic potential of rutin and nisin conjugated IONPs as anticancer agents. One important hallmark of many cancers is the overexpression of the endoplasmic reticulum-resident chaperone, GRP78, and its translocation to many cellular compartments, including the cell membrane. We explored the potential binding affinity of rutin and nisin against the substrate-binding domain β (SBDβ) of GRP78. The results show promising results for both nisin and rutin, with more enhanced binding capability of the former due to its extended structure (peptide in nature), forming more non-bonded interactions with the GRP78 surface. Our findings pave the way for the use of these coating agents against the cell-exposed chaperone, GRP78, to alleviate its chemoresistance characteristics in cancer.

Cytochalasans are a structurally diverse class of fungal-derived natural products with remarkable cytotoxic and anticancer properties. However, the rarity of experimental data and the complexity of their molecular scaffolds hinder systematic pharmacological evaluation. In this study, we introduce a deep learning-based artificial neural network (ANN) framework to predict the cytotoxic activity of cytochalasans using an experimental dataset of 291 compounds. Molecular descriptors, including physicochemical properties (SwissADME, pkCSM) and structural fingerprints (RDKit, Morgan, and pharmacophore-based), were extracted and processed via dimensionality reduction (PCA, retaining 95% variance). A six-layer ANN architecture was trained and evaluated across training (70%), testing (15%), and validation (15%) sets, achieving robust predictive performance (training: accuracy = 0.97, AUC = 0.998; test: accuracy = 0.84, AUC = 0.883; validation: accuracy = 0.90, AUC = 0.893). This ANN model enables classification of compounds into active or inactive categories, further subclassifying actives based on predicted potency (strong, moderate, or weak). The effective virtual screening of 127 previously untested cytochalasan derivatives using the trained ANN illustrates the model's practical applicability. The compounds prioritized by the ANN during virtual screening. High-confidence predictions were further validated through molecular docking studies, and molecular dynamics (MD) simulations against 15-lipoxygenase-2 (15-LOX-2). Furthermore, three derivatives were prioritized based on strong predicted activity by the deep learning model: cytochalasin Z6 (11), chaetoglobosin W (64), and hydroxy-10-phenyl-[11]-cytochalasa-13, 19-diene-1,21-dione (102). These cytochalasans emerged as the most promising candidates for cancer treatment due to their capacity to inhibit the 15-LOX-2 enzyme, as demonstrated by molecular docking and MD analyses.

Cardiovascular diseases remain the leading cause of mortality worldwide, and endoplasmic reticulum (ER) stress has emerged as an important molecular mechanism underlying myocardial injury and heart failure. This study investigated the expression of the ER stress-related genes GRP78, PERK, and CHOP in peripheral whole blood obtained from patients with acute cardiovascular diseases. A total of 300 participants were enrolled, including 200 patients with ST-segment elevation myocardial infarction (STEMI, n = 55), non-ST-segment elevation myocardial infarction (NSTEMI, n = 88), decompensated heart failure (DHF, n = 40), or unstable angina pectoris (USAP, n = 17), and 100 healthy controls. Relative mRNA expression levels were quantified using quantitative real-time PCR. Intergroup comparisons were performed using the Kruskal-Wallis test followed by Dunn's post hoc test with Bonferroni adjustment. Significant differences in GRP78, PERK, and CHOP expression were observed among the study groups (all p < 0.001). GRP78 and PERK expression levels were highest in the STEMI and DHF groups, whereas CHOP expression was highest in the STEMI group. Significant positive correlations were identified between troponin and CHOP (r = 0.48), GRP78 (r = 0.42), and PERK (r = 0.39) (all p < 0.001), while weaker but significant associations were observed between inflammatory markers (CRP and NLR) and ER stress-related gene expression. Exploratory receiver operating characteristic (ROC) analysis showed that CHOP demonstrated the highest discriminatory performance for distinguishing patients with acute cardiovascular disease from healthy controls. These findings indicate that peripheral whole-blood ER stress-related gene expression is associated with acute cardiovascular disease and correlates with established biomarkers of myocardial injury and inflammation. Further prospective studies are required to determine the clinical significance of these findings.

Here, we present a comprehensive computational evaluation of three FDA (Food and Drug Administration) approved drug leads, ZINC150338755, ZINC6716957, and ZINC203686879, as potential inhibitors targeting the Cripto/FRL-1/Cryptic (CFC) domain of the CRIPTO (Teratocarcinoma-derived growth factor1) protein. CRIPTO is a key oncogenic protein implicated in tumor progression, metastasis, and therapy resistance across multiple cancer types. Its overexpression promotes cancer stemness and survival in various tumors, such as liver cancer and glioblastoma, while its restricted expression in normal tissues makes it an attractive therapeutic target. Through an integrated approach merging molecular docking (with results -8.6 to -9.1 kcal/mol affinities), molecular dynamics (MD) simulations, molecular mechanics-generalized Born surface area (MM-GBSA) binding free energy calculations, and free energy landscape (FEL) analysis, we delineate distinct binding modes and thermodynamic fingerprints of the inhibitor complexes. Virtual screening determined the lead compounds, which were subjected to 250 ns MD simulations to check the stability and dynamics of interactions. Binding free energy calculation revealed striking disparities in binding energies (Delta G(bind) from -26.83 to -57.37 kcal/mol), where Complex1 exhibited increased stability through hydrophobic superiority, Complex2 showed similar polar/nonpolar interactions, and Complex3 exhibited unique electrostatic-driven recognition. These findings shed atomic-level insight into CRIPTO-inhibitor interactions and offer a solid foundation for structure-based optimization of CRIPTO inhibitors.

About 20% of breast cancer cases are triple-negative breast cancer (TNBC), a highly aggressive subtype with limited therapeutic options. Emerging evidence suggests that ferroptosis — a form of regulated cell death — and stress-response pathways play critical roles in TNBC progression. We investigated the interaction between glucose-regulated protein 78 (GRP78), a central stress-response chaperone, and mitochondrial glutathione peroxidase 4 (mGPX4), a key regulator of ferroptosis resistance. Using a combined computational approach — including protein–protein docking, molecular dynamics (MD) simulations, and MM/GBSA free-energy calculations — we identified stable complexes between GRP78’s SBDβ domain and several regions of mGPX4. Docking with PRODIGY revealed binding affinities ranging from − 7.7 ± 0.5 to − 10.5 ± 0.6 kcal/mol, surpassing that of Pep42 (–6.9 ± 0.1 kcal/mol), with region III (the mitochondrial import sequence) showing the strongest binding (–10.5 ± 0.6 kcal/mol). HADDOCK scoring further highlighted region II as particularly favorable (–72.0 ± 5.4). After 100 ns of MD, MM/GBSA analysis estimated binding free energies from − 45.20 to − 86.39 kcal/mol, with the region-II complex exhibiting the highest affinity (–86.4 kcal/mol), driven predominantly by electrostatic and van der Waals interactions. This interaction could serve as a promising therapeutic target to undermine cancer cell survival by sensitizing TNBC cells to ferroptosis-inducing strategies.

Cancer cells can adapt to their surrounding microenvironment by upregulating glucose-regulated protein 78 kDa (GRP78) and vacuolar-type ATPase (V-ATPase) proteins to increase their proliferation and resilience to anticancer therapy. Therefore, targeting these proteins can obstruct cancer progression. A comprehensive computational study was conducted to investigate the inhibitory potential of four proton pump inhibitors (PPIs), dexlasnoprazole (DEX), esomeprazole (ESO), pantoprazole (PAN), and rabeprazole (RAB), against GRP78 and V-ATPase. Molecular docking revealed high-affinity scores for PPIs against both proteins. Moreover, molecular dynamics showed favorable root mean square deviation values for GRP78 and V-ATPase complexes, whereas root mean square fluctuations were high at the substrate-binding subdomains of GRP78 complexes and the α-helices of V-ATPase. Meanwhile, the radius of gyration and the surface-accessible surface area of the complexes were not significantly affected by ligand binding. Trajectory projections of the first two principal components showed similar motions of GRP78 structures and the fluctuating nature of V-ATPase structures, while the free-energy landscape revealed the thermodynamically favored GRP78-RAB and V-ATPase-DEX conformations. Furthermore, the binding free energy was −16.59 and −18.97 kcal/mol for GRP78-RAB and V-ATPase-DEX, respectively, indicating their stability. According to our findings, RAB and DEX are promising candidates for GRP78 and V-ATPase inhibition experiments, respectively.

Cell surface glucose-regulated protein 78 (cs-GRP78) was previously reported as a receptor of many infectious agents including viruses, bacteria, and fungi. The association of GRP78 inside the cell and at the cell surface is important to be studied to understand how the cell recognizes pathogens. Combined bioinformatics tools, molecular docking, and dynamics simulation were utilized to study the homodimeric form of GRP78 at both aqueous and impeded inside the lipid bilayer membrane. The results revealed that both systems are stable during the simulation period of 100 ns but the substrate binding domains α and β of one monomer of GRP78 have less fluctuations in the membrane system compared to the dimer at aqueous solution. This may explain the stability of the protein dimer inside the membrane. Additionally, we found that the GRP78 dimer in the membrane forms a stable pore of 12 Å diameter that remained open throughout the simulation period, indicating increased membrane permeability. This may explain the ability of cs-GRP78 to facilitate hydrophobic molecule internalization.

Recent studies have shown that ferroptosis and cellular stress are related to triple-negative breast cancer (TNBC). This study used molecular dynamics simulations (MDS) and protein-peptide docking to pinpoint the glutathione peroxidase 4 (GPX4) protein and glucose-regulated protein 78 (GRP78) interaction site. The cyclic peptide Pep42 had previously been identified as a selective target for GRP78 on cancer cell membranes. Sequence alignments reveal that the GPX4 cyclic regions: R1 (C7-C16), R2 (C16-C29), R3 (C7-C29), and R7 (C93-C102) share sequence identity of 30.00 %, 30.77 %, 38.46 %, and 42.86 % against Pep42 peptide, respectively. Moreover, these four GPX4 regions have a grand average hydrophobicity index (GRAVY) of 1.2, 1.3, 1.2, and 1.5, respectively, similar to Pep42's GRAVY of 1.1. Additionally, they show strong binding affinities for GRP78 substrate binding domain β (SBDβ) (-6.81, -7.85, -8.77, and -7.25 kcal/mol, for R1, R2, R3, and R7, respectively). This study attempts to predict the binding site which needs further extensive experimental validation aimed at exploring potential disruptors of the GRP78 -GPX4 association. This would block ferroptosis resistance and chemoresistance in TNBC.

Human Immuno-deficiency virus (HIV) is still spreading all over the world. There are many routes through which the virus recognizes host cells by its envelope protein. One of these routes is through binding to glucose-regulated protein 78 (GRP78), which is overexpressed in stressed cells. In this study, we investigate the association between GRP78 and HIV envelope protein at four different binding sites (R1: C130-C162), (R2: C223-C252), (R3: C301-C335), and (R4: C388-C418) using a comprehensive in silico approach. Protein-protein docking and molecular dynamics simulations (MDS) are conducted to evaluate the binding. Results indicate that the R4 region (C388-C418) is the potential binding site of the envelope protein to GRP78 on the cell surface with an average binding energy of -12.20 ± 2.0 kcal/mol. The predicted findings open the gate towards further studies that could lead to the development of effective inhibitors that can alleviate viral recognition of the host cell and eradicate the viral infection.

Glioblastoma multiforme (GBM) is one of the most malignant tumors in central nervous system (CNS) tumors. The glucose-regulated protein 78 (GRP78) and CRIPTO (Cripto-1), a protein that belongs to the EGF-CFC (epidermal growth factor cripto-1 FRL-1 cryptic) family, are overexpressed in GBM. A complex between GRP78 SBDβ (substrate binding domain beta) and CRIPTO CFC domain was reported in previous studies. This complex activates MAPK/AKT signaling, Src/PI3K/AKT, and Smad2/3 pathways which is a reason for tumor proliferation. In this work, we study how the two proteins form the complex figuring out binding sites between GRP78 and CRIPTO utilizing computational biophysics and bioinformatics tools, such as protein-protein docking, molecular dynamics simulation and MMGBSA calculations. Haddock web server results of 4 regions from the CFC domain (region1 (- 70.4), region2 (- 78.7), region3 (- 74.2), region4 (- 86.8)) with selected residues of the SBDβ are then simulated for 100 ns MDS then MMGBSA were calculated for the four complexes. The results reveal the stability of the complexes with binding free energy (complex1 (- 15.07 kcal/mol), complex2 (- 59.78 kcal/mol), complex3 (- 81.92 kcal/mol), complex4 (- 126.26 kcal/mol). All these findings ensure that GRP78 SBDβ associates with the CRIPTO CFC domain, and the binding sites suggested make stable interactions between the proteins.

INTRODUCTION:Lysozyme is a globular hydrolytic enzyme whose tissue level is imperative for various clinical diagnostics. High levels of lysozyme are related to several inflammatory disorders, that breakdown cartilaginous tissues. Recently nanostructures have become widely used as modulators for enzyme activity. AREAS COVERED:This study delves into the influential role played by surface-modified iron oxide nanoparticles (IONPs) as novel lysozyme nano-inhibitors. Stern-Volmer plots results for lysozyme interaction with Cit-IONPs and Thy-IONPs reveal dynamic quenching constant (KSV) of 40.075 and 65.714 ml/mg, binding constant (Kb) of 1.539 × 103 and 4.418 × 103 ml/mg, and binding free energy (∆G°binding) of -43.563 KJ. mol-1 and -49.821 KJ. mol-1, respectively. Upon interaction with IONPs, the catalytic activity of lysozyme decreases due to conjugation with Thy-IONPs and Cit-IONPs compared to the free form of the enzyme. Computational approaches show that the citrate and thymoquinone molecules have binding affinities with lysozyme active residues of about -4.3 and -4.7 kcal/mol, respectively. EXPERT OPINION/COMMENTARY:Both formulations of IONPs demonstrate high affinity toward lysozyme proteins. This work shows a higher binding affinity between lysozyme and Thy-IONPs than with Cit-IONPs. These findings suggest that Thy-IONPs represent a promising class of nano-inhibitors for lysozyme, opening new avenues for treating disorders associated with lysozyme overexpression.

Angiotensin-converting enzyme 2 (ACE2) has been reported to be the primary host cell receptor for recognizing SARS-CoV and SARS-CoV-2 spike proteins. This host-cell element, despite having a crucial role in normal cells, may be hijacked by viruses to invade human cells. It has been reported that ACE2 trafficking to the cell membrane is mediated by other cellular factors, such as the endoplasmic reticulum resident chaperone, named glucose-regulated protein 78 (GRP78). GRP78 is the master of the unfolded protein response during cellular stress. This study uses sequence alignment, protein-protein docking, and molecular dynamics simulation (MDS) to predict the potential binding sites between the two proteins for the first time aiming to understand its role in viral recognition and infection. Results revealed three critical regions in ACE2 (C133-C141, C344-C361, and C530-C542), that could be the recognition site for GRP78 from which, the second region (C344-C361) is the suggested best region based on protein-protein docking, MDS, and MM-GBSA calculations. These cyclic regions show similarity (<38% identity) with the cyclic peptide Pep42, which is previously reported to target GRP78 over cancer cells. This approach paves the way toward suggesting potential inhibitors based on the prevention of the association between ACE2 and GRP78.

INTRODUCTION:In recent months, monkeypox (mpox) virus (MPXV) infections has grown to be a major worldwide concern. Cynomolgus monkeys, rhesus macaques, marmosets, and baboons are the nonhuman primate (NHP) models that provide the much needed means for developing new therapies against MPXV due to their genetic proximity to humans. AREA COVERED:In this review, the authors discuss epidemiology, transmission, clinical presentation, and the use of NHP in studying the treatment of MPXV over the past two decades on Google Scholar. NHP models have been widely used to evaluate the efficacy of antiviral drugs and antibodies, providing important information regarding immune responses and disease. NHPs continue to be an important mainstay in preclinical testing, enabling the optimization of the efficacy and safety of drugs, antibodies, and vaccines to accelerate the development of effective MPXV treatments for humans. EXPERT OPINION:The intravenous forms of medications like cidofovir, brincidofovir, and Vaccinia Immune Globulin (VIG) constitute the basis of MPXV therapy. Additionally, antibodies such as HAI, PN, and CF assess the efficacy of smallpox vaccination against MPXV in primates. This would help both the development of diagnostic tools and the optimization of vaccine strategies. Moreover, the similarities between MPXV and vaccinia or variola can play a role in developing targeted antiviral treatment methods.

The glucose-regulated protein 78 (GRP78) is pivotal in endoplasmic reticulum protein homeostasis and the unfolded protein response during cellular stress. Experimental validation has shown its role in SARS-CoV-2 attachment and entry. Here, the full GRP78 sequence, adding carbohydrate sugars to nucleotide-binding domain sites, and conduct molecular dynamics simulations is modeled. Utilizing DeepPurpose virtual screening on the COCONUT database, followed by blind structure-based screening with AutoDock Vina, top interacting binders is identified. Molecular dynamic simulations with MM/GBSA reveal stable binding of CNP0339053 and CNP0400762 to GRP78 (free energies of -43.5 +/- 6.7 and -34.8 +/- 3.9 kcal mol-1, respectively). These compounds hold promise as safe antiviral treatments for COVID-19. It is focused on the CS-GRP78, which is suggested as one of the SARS-CoV-2 recognition routes. Two compounds (CNP0339053 and CNP0400762) are predicted to bind to SBD and NBD of the GRP78 protein, respectively. These compounds to be novel antivirals that will be added to the arsenal of drugs against COVID-19 is expected. image

HIF-1α is a primary regulator in the adaptation of cancer cells to hypoxia. The aim was to find out new inhibitors of the HIF-1α. A molecular dynamic (MD) simulation performed on HIF-1α showed stable dynamic features. Virtual screening of 217 anticancer drugs was performed along with a positive control (2-Methoxyestradiolm, 2-ME2) on an optimized HIF-1α and dynamically simulated structure. Docking results produced two compounds namely pycnidione and nilotinib of high binding affinity -9.34 kcal/mol and -9.04 kcal/mol respectively, whereas 2-ME2 displayed a relatively lower affinity (-6.68 kcal/mol). For the three complexes, MD of 200 ns simulation was run. Data analysis showed that the three medications behaved similarly in the MD simulation. Nilotinib had a lower RMSD and higher SASA than the other complexes. In addition, the Nilotinib-HIF-1α combination had a lower RMSF value, a flatter Rg, and a number of hydrogen bonds similar to other complexes. MM-GBSA analysis revealed that nilotinib, pycnidione and 2-ME2 compounds had free binding energy of -23.77 ± 5.29, -21.85 ± 4.24 and -7.53 ± 6.62 kcal/mol respectively. Nilotinib and pycnidione bind competitively to HIF-1α, with nilotinib showing consistent molecular-dynamic properties. They relatively pass the blood-brain barrier, non-carcinogenic, and have IV-category acute oral toxicity. They have low CYP inhibitory characteristics. Further investigations are therefore warranted to elucidate their implications in hypoxia pathways, cell proliferation, apoptosis, survival, and metastatic potential.

Researchers worldwide are looking for molecules that might disrupt the COVID-19 life cycle. Endoribonuclease, which is responsible for processing viral RNA to avoid detection by the host defense system, and helicase, which is responsible for unwinding the RNA helices for replication, are two key non-structural proteins. This study performs a hierarchical structure-based virtual screening approach for NSP15 and helicase to reach compounds with high binding probabilities. In this investigation, we incorporated a variety of filtering strategies for predicting compound interactions. First, we evaluated 756,275 chemicals from four databases using a deep learning method (NCI, Drug Bank, Maybridge, and COCONUT). Following that, two docking techniques (extra precision and induced fit) were utilized to evaluate the compounds' binding affinity, followed by molecular dynamic simulation supported by the MM-GBSA free binding energy calculation. Remarkably, two compounds (90616 and CNP0111740) exhibited high binding affinity values of -66.03 and -12.34 kcal/mol for helicase and NSP15, respectively. The VERO-E6 cell line was employed to test their in vitro therapeutic impact. The CC50 for CNP0111740 and 90616 were determined to be 102.767 mu g/ml and 379.526 mu g/ml, while the IC50 values were 140.176 mu g/ml and 5.147 mu g/ml, respectively. As a result, the selectivity index for CNP0111740 and 90616 is 0.73 and 73.73, respectively. Finally, these compounds were found to be novel, effective inhibitors for the virus; however, further in vivo validation is needed.

The global prevalence of dengue virus (DENV), a widespread flavivirus, has led to varied epidemiological impacts, economic burdens, and health consequences. The alarming increase in infections is exacerbated by the absence of approved antiviral agents against the DENV. Within flaviviruses, the NS3/NS2B serine protease plays a pivotal role in processing the viral polyprotein into distinct components, making it an attractive target for antiviral drug development. In this study, machine-learning (ML) techniques were employed to build predictive models for the screening of a library containing 32,000 protease inhibitors. Utilizing GNINA for structure-based virtual screening, the top potential candidates underwent a subsequent evaluation of their absorption, distribution, metabolism, excretion, and toxicity properties. Selected compounds were subjected to molecular dynamics simulations and binding free energy calculations via MM/GBSA. The results suggest that comp530 possesses binding potential to DENV protease as a noncovalent inhibitor with multiple positions for chemical substitutions, presenting opportunities for optimizing their selectivity and specificity. However, other compounds predicted via ML models may still provide a promising start for covalent inhibitors.

BACKGROUND:Human immunodeficiency virus (HIV) infection continues to pose a major global health challenge. HIV entry into host cells via membrane fusion mediated by the viral envelope glycoprotein gp120/gp41 is a key step in the HIV life cycle. CCR5, expressed on CD4+ T cells and macrophages, acts as a coreceptor facilitating HIV-1 entry. The CCR5 antagonist maraviroc is used to treat HIV infection. However, it can cause adverse effects and has limitations such as only inhibiting CCR5-tropic viruses. There remains a need to develop alternative CCR5 inhibitors with improved safety profiles. PROBLEM STATEMENT:Natural products may offer advantages over synthetic inhibitors including higher bioavailability, binding affinity, effectiveness, lower toxicity, and molecular diversity. However, screening the vast chemical space of natural compounds to identify novel CCR5 inhibitors presents challenges. This study aimed to address this gap through a hybrid ligand-based pharmacophore modeling and molecular docking approach to virtually screen large natural product databases. METHODS:A reliable pharmacophore model was developed based on 311 known CCR5 antagonists and validated against an external data set. Five natural product databases containing over 306,000 compounds were filtered based on drug-likeness rules. The validated pharmacophore model screened the databases to identify 611 hits. Key residues of the CCR5 receptor crystal structure were identified for docking. The top hits were docked, and interactions were analyzed. Molecular dynamics simulations were conducted to examine complex stability. Computational prediction evaluated pharmacokinetic properties. RESULTS:Three compounds exhibited similar interactions and binding energies to maraviroc. MD simulations demonstrated complex stability comparable to maraviroc. One compound showed optimal predicted absorption, minimal metabolism, and a lower likelihood of interactions than maraviroc. CONCLUSION:This computational screening workflow identified three natural compounds with promising CCR5 inhibition and favorable pharmacokinetic profiles. One compound emerged as a lead based on bioavailability potential and minimal interaction risk. These findings present opportunities for developing alternative CCR5 antagonists and warrant further experimental investigation. Overall, the hybrid virtual screening approach proved effective for mining large natural product spaces to discover novel molecular entities with drug-like properties.