Virtual Screening Research Articles

Artificial intelligence alphafold model for molecular biology and drug discovery: a machine-learning-driven informatics investigation.

AlphaFold model has reshaped biological research. However, vast unstructured data in the entire AlphaFold field requires further analysis to fully understand the current research landscape and guide future exploration. Thus, this scientometric analysis aimed to identify critical research clusters, track emerging trends, and highlight underexplored areas in this field by utilizing machine-learning-driven informatics methods. Quantitative statistical analysis reveals that the AlphaFold field is enjoying an astonishing development trend (Annual Growth Rate = 180.13%) and global collaboration (International Co-authorship = 33.33%). Unsupervised clustering algorithm, time series tracking, and global impact assessment point out that Cluster 3 (Artificial Intelligence-Powered Advancements in AlphaFold for Structural Biology) has the greatest influence (Average Citation = 48.36 ± 184.98). Additionally, regression curve and hotspot burst analysis highlight "structure prediction" (s = 12.40, R2 = 0.9480, p = 0.0051), "artificial intelligence" (s = 5.00, R2 = 0.8096, p = 0.0375), "drug discovery" (s = 1.90, R2 = 0.7987, p = 0.0409), and "molecular dynamics" (s = 2.40, R2 = 0.8000, p = 0.0405) as core hotspots driving the research frontier. More importantly, the Walktrap algorithm further reveals that "structure prediction, artificial intelligence, molecular dynamics" (Relevance Percentage[RP] = 100%, Development Percentage[DP] = 25.0%), "sars-cov-2, covid-19, vaccine design" (RP = 97.8%, DP = 37.5%), and "homology modeling, virtual screening, membrane protein" (RP = 89.9%, DP = 26.1%) are closely intertwined with the AlphaFold model but remain underexplored, which implies a broad exploration space. In conclusion, through the machine-learning-driven informatics methods, this scientometric analysis offers an objective and comprehensive overview of global AlphaFold research, identifying critical research clusters and hotspots while prospectively pointing out underexplored critical areas.

TFF3 and PVRL2 co-targeting identified by multi-omics approach as an effective cancer immunosuppression strategy

BackgroundThe immunosuppressive tumour microenvironment (TME) plays a critical role in cancer progression and relapse by significantly influencing cancer pathogenesis through autocrine and paracrine signalling. Trefoil factor 3 (TFF3), a secreted protein, has been implicated in modulating the TME to promote cancer advancement. Herein, we investigated the potential association between TFF3 and key immunosuppressive TME components to distinguish a co-targetable oncotherapeutic strategy. MethodsThe TFF3-PVRL2 association were identified and investigated by integrating multiple bioinformatic-tools. The virtual compound screening for PVRL2 inhibitors was done with EasyVS. The TFF3-PVRL2 protein-level correlation was validated by immunoblotting, and the effectiveness of co-inhibiting TFF3 and PVRL2 was assessed using siRNA and AMPC (a TFF3 inhibitor). ResultsAnalysis of the TISIDB database revealed a positive correlation between TFF3 and PVRL2 mRNA levels across multiple cancer types. This correlation was confirmed at the protein level through immunoblot analysis. Further evaluation using TCGA pan-cancer datasets demonstrated that TFF3 and PVRL2 interact to establish an immunosuppressive TME, promoting cancer progression in BRCA, LUAD, PAAD, PRAD, and STAD. Enrichment analyses of positively correlated genes, PPI network hub proteins, and ceRNA networks involving TFF3 and PVRL2, conducted using LinkedOmics, STRING, and Cytoscape, provided insights into their potential co-functions in cancer. A cell-based assay was performed to evaluate the combined therapeutic efficacy of targeting both, TFF3 and PVRL2 and virtual screening identified potential drugs for inhibiting PVRL2. ConclusionPVRL2 has emerged as a promising immunoinhibitory target with significant associations with TFF3 and represents a key co-targetable molecule for effective oncotherapeutic strategies.

An ANI-2 enabled open-source protocol to estimate ligand strain after docking.

In protein-ligand docking, the score assigned to a protein-ligand complex is approximate. Especially, the internal energy of the ligand is difficult to compute precisely using a molecular mechanics based force-field, introducing significant noise in the rank-ordering of ligands. We propose an open-source protocol (https://github.com/UnixJunkie/MMO), using two quantum mechanics (QM) single point energy calculations, plus a Monte Carlo (Monte Carlo) based ligand minimization procedure in-between, to estimate ligand strain after docking. The MC simulation uses the ANI-2x (QM approximating) force field and is performed in the dihedral space. On some protein targets, using strain filtering after docking allows to significantly improve hit rates. We performed a structure-based virtual screening campaign on nine protein targets from the Laboratoire d'Innovation Thérapeutique-PubChem assays dataset using Cambridge crystallographic data centre genetic optimization for ligand docking. Then, docked ligands were submitted to the strain estimation protocol and the impact on hit rate was analyzed. As for docking, the method does not always work. However, if sufficient active and inactive molecules are known for a given protein target, its efficiency can be evaluated.

Desmoplakin CSM models unravel mechanisms regulating the binding to intermediate filaments and putative therapeutics for cardiocutaneous diseases.

Arrhythmogenic cardiomyopathy (AC) is a common cause of sudden cardiac arrest and death in young adults. It can be induced by different types of mutations throughout the desmoplakin gene including the R2834H mutation in the extreme carboxyterminus tail of desmoplakin (DP CT) which remains structurally uncharacterized and poorly understood. Here, we have created 3D models of DP CT which show the structural effects of AC-inducing mutations as well as the implications of post-translational modifications (PTMs). Our results suggest that, in absence of PTMs, positively charged wildtype DP CT likely folds back onto negatively-charged plectin repeat 14 of nearby plakin repeat domain C (PRD C) contributing to the recruitment of intermediate filaments (IFs). When phosphorylated and methylated, negatively-charged wildtype DP CT would then fold back onto positively-charged plectin repeat 17 of PRD C, promoting the repulsion of intermediate filaments. However, by preventing PTMs, the R2834H mutation would lead to the formation of a cytoplasmic mutant desmoplakin with a constitutively positive DP CT tail that would be aberrantly recruited by cytoplasmic IFs instead of desmosomes, potentially weakening cell-cell contacts and promoting AC. Virtual screening of FDA-approved drug libraries identified several promising drug candidates for the treatment of cardiocutaneous diseases through drug repurposing.

Identification of novel brain penetrant GSK-3β inhibitors toward Alzheimer’s disease therapy by virtual screening, molecular docking, dynamic simulation, and MMPBSA analysis

One of the significant therapeutic targets for Alzheimer’s disease (AD) is Glycogen Synthase Kinase-3β (GSK-3β). Inhibition of GSK-3β can prevent hyperphosphorylation of tau, and thus prevent formation and accumulation of neurofibrillary tangles and neuropil threads that block intracellular transport, trigger unfolded protein response, and increase oxidative stress, cumulatively leading to neurodegeneration. In this study, we have performed structure-based virtual screening of two small-molecule libraries from ChemDiv CNS databases using AutoDock Vina to identify hit molecules based on their binding affinities compared to that of an established GSK-3β inhibitor, indirubin-3’-monoxime (IMO). Pharmacoinformatic screening on SwissADME and pkCSM servers enabled identification of lead molecules with favorable pharmacoinformatic properties for drug likeliness, including blood brain barrier (BBB) permeability. Further, molecular dynamic simulations identified six candidate lead molecules that show stable complex formation with GSK-3β in dynamic state under physiological conditions. Principal component analysis of the dynamic state was used to plot Free Energy Landscapes (FELs) of GSK-3β-ligand complexes. STRIDE secondary structure analysis of the lowest energy conformations identified from FEL plots, and binding free energy calculations by Molecular Mechanics Poisson-Boltzmann Surface Area ((ΔGbind )MM-PBSA) of the simulation trajectories led to the identification of two ligands as potential lead molecules having favorable free energy landscape profiles as well as significantly lower (ΔGbind )MM-PBSA in dynamic state compared to that of reference inhibitor IMO. Hence, this study identifies two novel brain penetrant GSK-3β inhibitors that are likely to have therapeutic potential against Alzheimer’s disease.

Identification of honokiol-based scaffold to design tankyrase 1/2 inhibitors by in silico and in vitro studies.

Recently, we identified magnolol bioinspired derivatives as new Tankyrase 1/2 (TNKS1/2) inhibitors by our Inverse Virtual Screening protocol. Based on these findings, in the present contribution, we enlarged our investigation of neolignans to the natural product honokiol (1) and a group of its analogues (2-8). By integrating in silico analysis and Surface Plasmon Resonance experiments, we demonstrated the binding of 1 (honokiol), 2, 6 and 7 towards TNKS2. Furthermore, we also proved the binding specificity of 1 and 7 against TNKS2, while 2 and 6 were found to be also TNSK1 binders, along with 4. Promising antiproliferative activity in A549 cancer cell line were observed for 1 and 6, with honokiol (1) presenting a higher potency than the well-known TNKS2 inhibitor XAV939. Collectively, these outcomes suggest that the honokiol-based scaffold can be employed to design novel anti-cancer therapeutic agents.

Comprehensive Computational Screening and Analysis of Natural Compounds Reveals Promising Estrogen Receptor Alpha Inhibitors for Breast Cancer Therapy.

Breast cancer remains a leading cause of death among women, with estrogen receptor alpha (ERα) overexpression playing a pivotal role in tumor growth and progression. This study aimed to identify novel ERα inhibitors from a library of 561 natural compounds using computational techniques, including virtual screening, molecular docking, and molecular dynamics simulations. Four promising candidates-Protopine, Sanguinarine, Pseudocoptisine, and Stylopine-were selected based on their high binding affinities and interactions with key ERα residues. Molecular dynamics simulations conducted over 500 nanoseconds revealed that Protopine and Sanguinarine exhibited more excellent stability with minimal fluctuations, suggesting strong and stable binding. In contrast, Pseudocoptisine and Stylopine showed higher flexibility, indicating less stable interactions. Binding free energy calculations further supported the potential of Protopine and Sanguinarine as ERα inhibitors, though their binding strength was slightly lower than that of the reference compound. These findings highlight Protopine and Sanguinarine as leading candidates for further investigation, and in vitro and in vivo studies are recommended to evaluate their therapeutic potential in breast cancer treatment.

Small Molecule Compound DHPA Screened by Computer-Aided Drug Design and Molecular Dynamics Simulation Inhibits Neuroblastoma Cell Proliferation by Targeting TrkB.

Neuroblastoma (NB) is a rare and malignant pediatric solid tumor. Due to its heterogeneity, it poses significant challenges for treatment, resulting in a high mortality rate. This study aimed to identify new therapeutic drugs by modeling the TrkB receptor from PDB 4AT5 and conducting virtual screening of compounds from the YaTCM database (containing 47,696 compounds derived from 6220 Traditional Chinese Medicines). The screening utilized the E-pharmacophore approach to select compounds with potential binding affinity to TrkB. The binding abilities of these compounds were tested through molecular dynamics simulations, stretch dynamics simulations, and US simulations. Among the top 11 optimized hit compounds, DHPA and 3″-demethylhexahydrocurcumin are prominent. Further simulations reveal that they form stable receptor-ligand binary complexes with TrkB. In subsequent in vitro cell experiments, 3″-demethylhexahydrocurcumin is eliminated due to its high IC50 for killing NB cells. Low concentrations of DHPA can significantly kill NB cells. Additionally, DHPA can inhibit the expression of TrkB, the activation of TrkB's downstream signaling pathways, and affect the thermal stability of TrkB protein and its response to streptase protease degradation. DHPA may be a potential TrkB inhibitor.

Widely-targeted in silico and in vitro evaluation of veratrum alkaloid analogs as FAK inhibitors and dual targeting of FAK and Hh/SMO pathways for cancer therapy: A critical analysis

Focal Adhesive Kinase (FAK), a key player in aggressive cancers, mediates signals crucial for progression, invasion, and metastasis. Despite advances in targeted therapies, drug resistance is still a challenge, and survival rates remain low, particularly for late-stage patients, emphasizing the need for innovative cancer therapeutics. Cyclopamine, a veratrum alkaloid, has shown promising anti-tumor properties, but the search for more potent analogs with enhanced affinity for the biological target continues.This study employs a hybrid virtual screening approach combining pharmacophore model-based virtual screening (PB-VS) and docking-based virtual screening (DB-VS) to identify potential inhibitors of the FAK catalytic domain. PB-VS on the PubChem database yielded a set of hits, which were then docked with the FAK catalytic domain in two stages (1st and 2nd DB-VS). Hits were ranked based on docking scores and interactions with the active site. The top three compounds underwent molecular dynamics simulations, alongside two control compounds (SMO inhibitor(s) and FAK inhibitor(s)), to assess stability through RMSD, RMSF, Rg, and SASA analyses. ADMET properties were evaluated, and compounds were filtered based on drug-likeness criteria.Molecular dynamics simulations demonstrated the stability of compounds when complexed with the FAK catalytic domain. Compounds 16 (−25 kcal/mol), 88 (−27.47 kcal/mol), and 87 (−18.94 kcal/mol) exhibited comparable docking scores, interaction profiles, stability, and binding energies, indicating their potential as lead candidates. However, further validation and optimization through quantitative structure-activity relationship (QSAR) studies are essential to refine their efficacy and therapeutic potential. The in vitro cell-based assay demonstrated that compound 101PF, a FAK inhibitor, significantly inhibited the proliferation and migration of A549 cells. However, the results regarding the combined effects of FAK and SMO inhibitors were inconclusive, highlighting the need for further investigation. This study contributes to developing more effective anti-cancer drugs by improving the understanding of potential cyclopamine-based veratrum alkaloid analogs with enhanced interactions with the FAK catalytic domain.

SMILES-based QSAR virtual screening to identify potential therapeutics for COVID-19 by targeting 3CLpro and RdRp viral proteins

The COVID-19 pandemic has prompted the medical systems of many countries to develop effective treatments to combat the high rate of infection and death caused by the disease. Within the array of proteins found in SARS-CoV-2, the 3 chymotrypsin-like protease (3CLpro) holds significance as it plays a crucial role in cleaving polyprotein peptides into distinct functional nonstructural proteins. Meanwhile, RNA-dependent RNA polymerase (RdRp) takes center stage as the key enzyme tasked with replicating the viral genomic RNA within host cells. These proteins, 3CLpro and RdRp, are deemed optimal subjects for QSAR modeling due to their pivotal functions in the viral lifecycle. In this study, SMILES-based QSAR classification models were developed for a dataset of 2377 compounds that were defined as either active or inactive against 3CLpro and RdRp. Pharmacophore (PH4) and QSAR modeling were used for the virtual screening on 60.2 million compounds including ZINC, ChEMBL, Molport, and MCULE databases to identify new potent inhibitors against 3CLpro and RdRp. Then, a filter was established based on typical molecular characteristics to identify drug-like molecules. The molecular docking was also performed to evaluate the binding affinity of 156 AND 51 potential inhibitors to 3CLpro and RdRp, respectively. Among the 15 hits identified based on molecular docking scores, M3, N2, and N4 were identified as promising inhibitors due to their good synthetic accessibility scores (3.07, 3.11, and 3.29 out of 10 for M3, N2, and N4 respectively). These compounds contain amine functional groups, which are known for their crucial role in the binding interactions between drugs and their targets. Consequently, these hits have been chosen for further biological assay studies to validate their activity. They may represent novel 3CLpro and RdRp inhibitors possessing drug-like properties suitable for COVID-19 therapy.

Integrated Exploration of Pyranocoumarin Derivatives as Synergistic Inhibitors of Dual-target for Mpro and PLpro Proteins of SARS-CoV-2 through Molecular Docking, ADMET Analysis, and Molecular Dynamics Simulation.

This study aimed to explore the potential of natural anticoagulant compounds as synergistic inhibitors of the main protease (Mpro) and papain-like protease (PLpro) of SARS-CoV-2 and find effective therapies against SARS-CoV-2 by investigating the inhibitory effects of natural anticoagulant compounds on key viral proteases. The objectives of this study were to conduct rigorous virtual screening and molecular docking analyses to evaluate the binding affinities and interactions of selected anticoagulant compounds with Mpro and PLpro, to assess the pharmacokinetic and pharmacodynamic profiles of the compounds to determine their viability for therapeutic use, and to employ molecular dynamics simulations to understand the stability of the identified compounds over time. In this study, a curated collection of natural anticoagulant compounds was conducted. Virtual screening and molecular docking analyses were performed to assess binding affinities and interactions with Mpro and PLpro. Furthermore, pharmacokinetic and pharmacodynamic analyses were carried out to evaluate absorption, distribution, metabolism, and excretion profiles. Molecular dynamics simulations were performed to elucidate compound stability. Natural compounds exhibiting significant inhibitory activity against Mpro and PLpro were identified. A dual-target approach was established as a promising strategy for attenuating viral replication and addressing coagulopathic complications associated with SARS-CoV-2 infection. The study lays a solid foundation for experimental validation and optimization of identified compounds, potentially leading to the development of precise treatments for SARS-CoV-2.

Xanthine oxidase inhibitors: Virtual screening and mechanism of inhibition studies

Xanthine oxidase (XO), which plays a key role in purine metabolism, is an important target enzyme for the prevention and treatment of hyperuricemia. Inhibitory activity against XO is a common criterion for the screening of compounds with potential anti-hyperuricemic activity. In this study, 22 XO inhibitors were used to construct a 3D-QSAR pharmacophore model. Subsequently, molecular docking and in vitro activity evaluations were used to identify strong XO inhibitors from a list of 2000 natural compounds. The interaction mechanisms of these compounds with XO were analyzed based on inhibition kinetics and multi-spectral analyses. The pharmacophore model was composed of three hydrogen bond receptors and a hydrophobic center. The screened compounds — Diosmetin, Fisetin, and Genistein — all showed good XO inhibitory activity, with IC50 values of 1.86 ± 0.11 μM, 5.83 ± 0.08 μM, and 7.56 ± 0.10 μM, respectively. Kinetic analysis, fluorescence quenching assays, and molecular docking experiments showed that Diosmetin, Fisetin, and Genistein docked near the same active site of XO, mainly affecting the microenvironment of tryptophan residues. These molecules showed static binding to XO via hydrogen bonds, hydrophobic interactions, and van der Waals forces. Diosmetin and Genistein were competitive inhibitors, whereas Fisetin was a mixed inhibitor. Infrared spectroscopy showed that Diosmetin, Fisetin, and Genistein increased the α-helix content of XO from 7.4 % to 16.6 %, 21.4 %, and 11.2 %, respectively, thereby enhancing its stability. In summary, the pharmacophore model constructed in this study was accurate. The flavonoids Diosmetin, Fisetin, and Genistein effectively inhibited the activity of XO, and the amino acid residues LEU257, ILE353, and VAL259 played a key role in the interaction between the flavonoids and XO. These findings are of great significance for the screening and development of new XO inhibitors.

Discovery of Potent Covalent CRM1 Inhibitors Via a Customized Structure-Based Virtual Screening Pipeline and Bioassays.

CRM1 (chromosomal region maintenance 1, also referred to as exportin 1 or XPO1) plays a crucial role in maintaining the appropriate nuclear levels of tumor suppressor proteins (TSPs), growth regulatory proteins (GRPs), and antiapoptotic proteins, thereby contributing significantly to their anticancer effects. Dysregulation of CRM1-mediated nuclear transport, observed in a range of cancers such as colon cancer as well as autoimmune diseases, highlights its significance in various disease processes. In this paper, we employed a customized structure-based virtual screening campaign to search for novel covalent CRM1 inhibitors and purchased 50 potentially active compounds for in vitro bioassays. Among these candidates, AN-988 displayed a notably higher binding affinity (KD = 615 nM) toward CRM1, as determined by the biolayer interferometry (BLI) assay. Furthermore, AN-988 exhibited a strong suppression of colorectal cancer cell proliferation and remarkable anti-inflammatory effects. Notably, AN-988 induced cell apoptosis and cell cycle arrest in a time- and dose-dependent manner by effectively inhibiting the translocation of FOXO3a from the nucleus to the cytosol, thereby preserving the activity of FOXO3a. Collectively, our study identified AN-988 as a promising CRM1 inhibitor, underscoring its potential as a preclinical colon cancer therapy candidate.

Identification of Novel Tyrosinase Inhibitors with Nanomolar Potency Using Virtual Screening Approaches.

Hyperpigmentation disorders are caused by excess production of the pigment melanin, catalyzed by the enzyme tyrosinase. Novel tyrosinase inhibitors are needed as therapeutic agents to treat these conditions. To discover new inhibitors, we performed a virtual screening of the ZINC20 library containing 1.4 billion compounds. An initial filter for drug-likeness, ADMET properties, and synthetic accessibility reduced the library to 10,217 hits. Quantitative structure-activity relationship (QSAR) modeling of this subset predicted nanomolar inhibitory potency for several chemical scaffolds. Comparative molecular docking studies and rigorous binding energy calculations further prioritized four cysteine-containing dipeptide compounds based on predicted strong binding affinity and mode to tyrosinase. Microsecond-long molecular dynamics simulations provided additional atomistic insights into the stability of inhibitor-enzyme binding interactions. This integrated computational workflow effectively sampled an extremely large chemical space to discover four novel tyrosinase inhibitors with half-maximal inhibitory concentration values below 10 nM. Overall, this demonstrates the power of virtual screening and multi-faceted computational techniques to accelerate the discovery of potent bioactive ligands from massive compound libraries by efficiently sampling chemical space.

Computational quest, synthesis and anticancer profiling of 3-methyl quinoxaline-2-one-based active hits against the tyrosine kinase

BackgroundCancer is the predominant cause of mortality and a remarkable obstacle to elevating life anticipation in every nation on globe. Hepatocellular carcinoma (HCC), a hyper-vascular tumour, develops and progresses due to angiogenesis, a key feature of malignancy. HCC exhibits high neoangiogenic activity because of the need to generate new blood vessels for tumour growth.MethodsThe present work includes the construction of virtual library of ligands, virtual screening using the Dockthor-VS server, ADMET study using the SwissADME and Osiris property explorer. All the synthesized compounds were characterized by UV, IR, NMR and mass spectroscopic techniques. MTT assay was done to find the IC50 of the synthesized compounds against HepG2 cell line. The more active compound found is subjected to the molecular dynamics simulation study.ResultsThe ligands exhibited good docking scores, ADMET profile compared to the reference drugs. The target compounds were obtained with the satisfactory yields of 66–82%. The best activity against the HepG2 cancer cell line is observed with the compound SA-4 with IUPAC name (2-(3-methyl-2-oxoquinoxalin-1(2H)-yl)-N-(5-(3-nitrophenyl)-5H-thiazolo[4,3-b] [1,3,4] thiadiazol-2-yl) acetamide). The experimental results obtained show correlation with the in silico results. MD simulation of the compound SA-4 indicates the moderate stability of the protein-ligand complex in real time environment.ConclusionThe results obtained suggest that the compound SA-4 has the potential to be a promising anticancer agent effective against the VEGFR-2 and FGFR-4.Graphical abstract

Exploring novel natural compound-based therapies for Duchenne muscular dystrophy management: insights from network pharmacology, QSAR modeling, molecular dynamics, and free energy calculations.

Muscular dystrophies encompass a heterogeneous group of rare neuromuscular diseases characterized by progressive muscle degeneration and weakness. Among these, Duchenne muscular dystrophy (DMD) stands out as one of the most severe forms. The present study employs an integrative approach combining network pharmacology, quantitative structure-activity relationship (QSAR) modeling, molecular dynamics (MD) simulations, and free energy calculations to identify potential therapeutic targets and natural compounds for DMD. Upon analyzing the GSE38417 dataset, it was found that individuals with DMD exhibited 290 upregulated differentially expressed genes (DEGs) compared to healthy controls. By utilizing gene ontology (GO) and protein-protein interaction (PPI) network analysis, this study provides insights into the functional roles of the identified DEGs, identifying ten hub genes that play a critical role in the pathology of DMD. These key genes include DMD, TTN, PLEC, DTNA, PKP2, SLC24A, FBXO32, SNTA1, SMAD3, and NOS1. Furthermore, through the use of ligand-based pharmacophore modeling and virtual screening, three natural compounds were identified as potential inhibitors. Among these, compounds 3874518 and 12314417 have demonstrated significant promise as an inhibitor of the SMAD3 protein, a crucial factor in the fibrotic and inflammatory mechanisms associated with DMD. The therapeutic potential of the compounds was further supported by molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analysis. These findings suggest that the compounds are viable candidates for experimental validation against DMD.

Identification of novel salt-enhancing peptides in soy protein and molecular docking studies with transmembrane channel-like 4 (TMC4)

The aim of this study was to rapidly screen novel salt-enhancing peptides from soy protein by virtual screening and molecular docking. Potential salt-enhancing peptides were screened by computerized virtual hydrolysis, bioactivity prediction, toxicity prediction, and water solubility prediction. Sensory evaluation and e-tongue analysis further indicated that the peptides DIF (Asp-Ile-Phe), QPR (Gln-Pro-Arg), MMR (Met-Met-Arg), and DPIY (Asp-Pro-Ile-Tyr) had significant salting enhancing effects. Among them, MMR had the most significant salting effect, replacing at least about 40.35% of NaCl. In addition, a transmembrane channel-like 4 (TMC4) salty receptor model was built, and molecular docking was performed using computational techniques. Glu286, His293, Glu319, and Ser585 were hypothesized to be key binding sites. Molecular dynamics simulations further confirmed the stability of the complex system. This study discovered new salt-enhancing peptides in soy protein and provided a rapid and effective approach for further research in this area.

Tanshinone IIA delays liver aging by modulating oxidative stress.

Organ-specific aging is increasingly recognized for its research significance, with liver aging demonstrating particular relevance due to its central role in metabolism. We have pioneered the discovery that the expression of ESRRG in the liver positively correlates with age and have established its association with clinical characteristics, including hepatic edema. Our findings link liver aging to a shift in oxidative stress states, where ESRRG, a crucial nuclear receptor responsive to oxidative stress, may be modulated by various small molecules. Through virtual screening of a natural medicinal molecule database followed by further validation, we confirmed that the natural compound Tanshinone IIA mitigates oxidative stress-induced damage in the liver via the ESRRG/Cyp2e1 pathway, thus decelerating liver aging. Importantly, our study also explores the dynamic impact of Tanshinone IIA on ESRRG conformation, providing a profound understanding of its molecular interactions with ESRRG and laying a foundation for the rational design of small molecules based on natural compounds.

Ligand-based pharmacophore modeling, virtual screening, and molecular dynamics simulations of Pfhsp90 fingerprints in Plasmodium malaria treatment

The World Health Organization (WHO) documents malaria as one of the leading causes of high morbidity and mortality worldwide. The disease affects millions and kills thousands of people annually. Efforts to reduce the global burden of malaria have prompted the WHO to recommend prevention strategies such as using antimalarial drugs. However, these strategies have been ineffective because of antimalarial drug resistance. The only efficacious malaria treatment is Artemisinin-based Combination Therapy (ACT). However, the extended ACT clearance times, linked to the emergence of artemisinin monotherapy resistance recorded most recently in Africa and the Great Mekong region, pose a danger to its efficacy. Therefore, better efficacious antimalarial drugs are required. Since P. falciparum heat shock protein 90 (PfHsp90) is a well-characterized malaria drug target, this study uses it to discover more efficacious antimalarial drugs. An in silico approach was used to discover PfHsp90 inhibitors with pharmacological properties against Plasmodium malaria using a molecular dynamics simulation (MDS) and hierarchical virtual screening. Geldanamycin (GDM), a well-known anti-PfHsp90 compound, was used to identify PfHsp90 inhibitors with pharmacological properties against Plasmodium malaria by screening it against the ZINC20 database via the ZINCPHARMER web server. This virtual screening process resulted in 17 hits. These ZINCPHARMER hits were subjected to drug-likeness and pharmacokinetics properties analysis in the SwissADME web server, and nine of them satisfied the requirements. The nine ZINC20 compounds were docked with PfHsp90 using the PyRx software version 0.8 to understand their interactions. From the molecular docking results, ZINC09060002 (−8.2 kcal/mol), ZINC72133064 (−7.8 kcal/mol), ZINC72163401 (−7.7 kcal/mol), ZINC72358537 (−8.1 kcal/mol), and ZINC72358557 (−7.6 kcal/mol) had better binding affinities to PfHsp90 than GDM (−7.5 kcal/mol). The stability of these molecularly docked protein–inhibitor complexes was assessed through MDS using GROMACS 2022. ZINC72163401, ZINC72358537, and ZINC72358557 formed stable complexes with PfHsp90. The lead compounds were subjected to in vitro validation for their inhibitory capability. They showed promising inhibition of parasite growth with IC50 values ranging between 200 and 400 ng/mL. In this regard, the three PfHsp90 inhibitors can be further developed as potential antimalarial drugs. However, further structural optimization studies and clinical (in vivo) tests are necessary to ascertain the antimalarial activity of these compounds in humans.

Virtual screening, molecular dynamics simulations, and in vitro validation of EGFR inhibitors as breast cancer therapeutics

A high abundance of Epidermal Growth Factor Receptor (EGFR) in malignant cells makes them a prospective therapeutic target for basal breast tumors. Although EGFR inhibitors are in development as anticancer therapeutics, there exists limitations due to the dose-limiting cytotoxicity that limits their clinical utilization, thereby necessitating the advancement of effective inhibitors. In the present study, we have developed common pharmacophore hypotheses using 30 known EGFR inhibitors. The best pharmacophore hypothesis DHRRR_1 was utilized for virtual screening (VS) of the Phase database containing 4.3 × 106 fully prepared compounds. The top 1000 hits were further subjected to ADME filtration followed by structure-based VS and Molecular Dynamics (MD) simulation investigations. Based on pharmacophore hypothesis matching, XP glide score, interactions between ligands and active site residues, ADME properties, and MD simulations, the five best hits (SN-01 through SN-05) were preferred for in-vitro cytotoxicity studies. All the molecules except SN-02 exhibited cytotoxicity in Triple Negative Breast Cancer (TNBC) cells. These potential EGFR inhibitors effectively downregulated the EGF-induced proliferation, migration, in-vitro tumorigenic capability, and EGFR activation (pEGFR) in the TNBCs. Additionally, in combination with doxorubicin, the identified EGFR inhibitors significantly decreased the EGF-induced proliferation. SN-04, and SN-05 in the presence of a lower concentration of doxorubicin markedly increased the apoptotic markers expression in the TNBCs, an effect which was comparable to a higher concentration of doxorubicin treatment, alone. These observations suggest that both SN-04 and/or SN-05 can improve the efficacy of chemotherapeutic drug, doxorubicin at a lower concentration to avert the higher dose of chemotherapeutic-induced side effects during breast cancer treatment.