Identification of selective cyclin-dependent kinase 2 inhibitor from the library of pyrrolone-fused benzosuberene compounds: an in silico exploration

BCOR-rearranged sarcomas: In silico insights into altered domains and BCOR interactions

BCOR (BCL-6 corepressor) rearranged small round cell sarcoma (BRS) represents an uncommon soft tissue malignancy, frequently characterized by the BCOR::CCNB3 fusion. Other noteworthy fusions include BCOR::MAML3, BCOR::CLGN, BCOR::MAML1, ZC3H7B::BCOR, KMT2D::BCOR, CIITA::BCOR, RTL9::BCOR, and AHR::BCOR. The BCOR gene plays a pivotal role in the Polycomb Repressive Complex 1 (PRC1), essential for histone modification and gene silencing. It interfaces with the Polycomb group RING finger homolog (PCGF1). This study employed comprehensive in silico methodologies to investigate the structural and functional effects of BCOR fusion events in BRS. The analysis revealed significant alterations in the domain architecture of BCOR, which resulted in the loss of BCL6-regulated transcriptional repression. Furthermore, IUPred3 prediction indicated a significant increase in disorder in the C-terminal regions of the BCOR in the fusion proteins. A detailed analysis of the physicochemical properties by ProtParam revealed a decrease in isoelectric point, stability, and hydrophobicity. The analysis of protein structures predicted by AlphaFold3 using the PRODIGY algorithm revealed statistically significant deviations in binding affinities for BCOR-PCGF1 dimers and a non-canonical PRC1 variant tetramer compared to the wild-type BCOR. The findings provide a comprehensive summary and elucidation of the fusion proteome associated with BRS, suggesting a substantial impact on the stability and functionality of the fusion proteins, thereby contributing to the oncogenic mechanisms underlying BRS. In this study, we provide the first compilation and comparative analysis of the known BCOR fusions of BRS and introduce a new in silico approach to enhance a better understanding of the molecular basis of BRS.

Discovery of novel inhibitors of dengue viral RNA-dependent RNA polymerase by molecular docking, in vitro assay, DFT, and MD simulations

Dengue virus (DENV) is a significant significant mosquito-borne pathogen. Its RNA-dependent RNA polymerase (RdRp) plays a crucial role in viral replication, making it a critical target for antiviral drug development. The goal of this study was to identify potential inhibitors of the DENV RdRp through virtual screening and experimental assays. In this study, based on Topscience and TargetMol database. 47 compounds were stand out from 1.1 million compounds with high binding energies between -77.24 kcal/mol and-44.08 kcal/mol by initial virtual screening. Their inhibition activity against dengue virus was evaluated by cell-based antiviral and RdRp enzyme assays, and 4 compounds (R2, R29, R37, and R39) identified in our study demonstrated promising in vitro activity, with IC₅₀ values of less than 10 μM, indicating their strong potential as antiviral agents against DENV. The RdRp enzyme inhibition assay revealed that R37 demonstrated significant activity against the DENV RdRp enzyme, with an IC₅₀ of 10.86 ± 2.06 μM, which was lower than that of 3'-dATP (IC₅₀ = 30.09 ± 8.26 μM). These 4 compounds were further subjected to DFT calculations and MD simulation, which not only provided valuable structural insights but also enhanced the reliability of our findings by offering a detailed understanding of the stability and binding interactions of the top compounds with the DENV RdRp enzyme. These results suggest that the identified compounds are promising candidates for novel DENV RdRp inhibitors and provide both theoretical and experimental groundwork for further optimization and validation.

Assessment of in vitro assays and quantitative determination of selectivity and modality of inhibitors targeting the cell cycle regulating, oncogenic cyclin-dependent kinases

At the heart of cancer pathology lies the dysregulated cell cycle, which is often driven by aberrant activities of the cell cycle regulating, cyclin-dependent kinases (CDKs). Efforts to harness the therapeutic potential of modulating CDK activities have led to the development of inhibitors with tailored CDK selectivity. However, uniformity in the methods used to evaluate CDK inhibitor selectivity has been lacking and consequently, direct comparison and interpretation of selectivity profiles determined under different assay conditions is difficult. Determination of the inhibition modalities crucial to profiling selectivity of a CDK inhibitor requires thorough kinetic analysis carried out under comparable assay conditions. In this study, we employed a streamlined series of in vitro assays for profiling CDK inhibitors wherein intrinsic inhibition constants and cellular binding parameters were measured by using strategically designed enzymatic inhibition and complementary biophysical assays. Our findings demonstrate the effectiveness of this strategy in determining and quantitatively analyzing the selectivity and inhibition modality of a set of representative CDK inhibitors towards the major oncogenic, cell cycle CDKs. In addition, the assay results provide insights into the inhibitor-target interactions that extend beyond potency and selectivity.

PRMT1-Mediated SWI/SNF Complex Recruitment via SMARCC1 Drives IGF2BP2 Transcription to Enhance Carboplatin Resistance in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a malignancy with poor prognosis and chemotherapy resistance. Here, protein arginine methyltransferase 1 (PRMT1) is identified as a key driver of carboplatin (CBP) resistance in HNSCC. Analyses of clinical samples, cell lines, patient-derived organoids, and xenograft models reveal that PRMT1 promotes tumor growth and CBP resistance through a novel, methyltransferase-independent mechanism. Conditional PRMT1 knockout suppresses tumorigenesis and enhances CBP sensitivity in vivo, highlighting its essential role in HNSCC progression. Mechanistically, PRMT1 recruits the SWI/SNF chromatin remodeling complex via direct interaction with SMARCC1, leading to the transcriptional activation of insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), which enhances CBP resistance and tumor growth. Notably, this function is independent of PRMT1's enzymatic activity, distinguishing it from its well-established roles in arginine methylation. Furthermore, pre-B-cell leukemia homeobox 2 (PBX2) is identified as an upstream transcriptional activator that binds the PRMT1 promoter, driving its overexpression and reinforcing this oncogenic network. Clinically, high PBX2, PRMT1, SMARCC1, and IGF2BP2 expression correlates with malignant progression and poor prognosis in HNSCC patients. This study uncovers a previously unrecognized non-catalytic function of PRMT1 and highlights the PBX2-PRMT1-SWI/SNF-IGF2BP2 axis as a potential therapeutic target for overcoming CBP resistance in HNSCC.

In Silico and In Vivo Investigation of the Anti-Hyperglycemic Effects of Caffeic Acid

Hyperglycemia, characterized by elevated blood glucose levels, is a major risk factor for diabetes mellitus and its complications. While conventional therapies are effective, they are often associated with side effects and high costs, necessitating alternative strategies. This study evaluates the potential of caffeic acid (CA), a phenolic compound with reported antihyperglycemic properties, using both in silico and in vivo approaches. Molecular docking simulations revealed that CA demonstrates a strong binding affinity to protein tyrosine phosphatase 1B (PTP1B), a critical enzyme in glucose metabolism, with superior interaction profiles compared to the reference drug, ertiprotafib. In the in vivo studies, a Drosophila melanogaster model was used to investigate the effects of CA under hyperglycemic conditions induced by a high-sugar diet. Treatment with CA, particularly at a concentration of 500 μM, significantly reduced hemolymph glucose levels and improved several physiological and behavioral parameters, including survival rates, body size, body weight, and larval movement. Furthermore, gene expression analysis demonstrated that CA modulates key metabolic and stress-related pathways, enhancing glucose homeostasis and reducing metabolic stress. These findings highlight the dual utility of in silico and in vivo methodologies in elucidating the antihyperglycemic potential of CA. The results support the development of CA as a cost-effective and ethically viable therapeutic candidate with implications for diabetes management in resource-limited settings.

Traditional Chinese medicine-based therapeutics for Pediatric pneumonia-related acute lung injury and acute respiratory distress syndrome

Pediatric pneumonia remains a leading cause of morbidity and mortality among children worldwide, necessitating the exploration of novel therapeutic interventions. Traditional Chinese Medicine (TCM) offers a rich repository of natural compounds with potential therapeutic benefits. In this study, we explore the role of the TCM-derived compound ADHPE ([(1S,3S)-3-acetoxy-5-(3,4-dihydroxyphenyl)-1-[2-(3,4-dihydroxyphenyl)ethyl]pentyl]) as a stabilizer of 14-3-3σ and p65 complex in pediatric pneumonia through a comprehensive in silico approach. Using virtual screening and molecular docking, we screen the TCM drug library and assess the binding affinity of ADHPE to key protein targets implicated in the pathogenesis of pediatric pneumonia-associated acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). The stability and dynamics of the drug-target complexes are further evaluated through molecular dynamics (MD) simulations, providing insights into the interaction mechanisms at an atomic level. Additionally, we perform ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis to predict the pharmacokinetic and safety profiles of ADHPE. Further, MM\GBSA, WaterMap, and Piper analyses were conducted to confirm the results. The findings from this study may pave the way for the development of effective TCM-based therapies for pediatric pneumonia, offering a promising alternative to current treatment modalities.

Embracing the changes and challenges with modern early drug discovery

INTRODUCTION

The landscape of early drug discovery is rapidly evolving, fueled by significant advancements in artificial intelligence (AI) and machine learning (ML), which are transforming the way drugs are discovered. As traditional drug discovery faces growing challenges in terms of time, cost, and efficacy, there is a pressing need to integrate these emerging technologies to enhance the discovery process.

AREAS COVERED

In this perspective, the authors explore the role of AI and ML in modern early drug discovery and discuss their application in drug target identification, compound screening, and biomarker discovery. This article is based on a thorough literature search using the PubMed database to identify relevant studies that highlight the use of AI/ML models in computational chemistry, systems biology, and data-driven approaches to drug development. Emphasis is placed on how these technologies address key challenges such as data integration, predictive performance, and cost-efficiency in the drug discovery pipeline.

EXPERT OPINION

AI and ML have the potential to revolutionize early drug discovery by improving the accuracy and speed of identifying viable drug candidates. However, successful integration of these technologies requires overcoming challenges related to data quality, model interpretability, and the need for interdisciplinary collaboration.

Evaluation of Pyrrolone-Fused Benzosuberene MK2 Inhibitors as Promising Therapeutic Agents for HNSCC: In Vitro Efficacy, In-Vivo Safety, and Pharmacokinetic Profiling

MAPKAPK2/MK2 is well implicated in the progression of Head and Neck Squamous Cell Carcinoma (HNSCC), and potent MK2-inhibitors are required to suppress its activity. Several MK2-inhibitors have been developed in recent years to combat its effects on cancer. However, inadequate solubility, insufficient cellular permeability, systemic toxicity-mediated side effects, and low bioavailability have severely impeded the advancement of MK2-inhibitors to clinical trials. This void necessitates research to develop less toxic and more bioavailable potent MK2-inhibitors in HNSCC. In the present article, we have evaluated the in-vitro efficacy, in-vivo single-dose acute toxicity, and in-vivo pharmacokinetic profiling of recently developed PfBS (pyrrolone-fused benzosuberene) MK2-inhibitor analogues against HNSCC. The PfBS MK2 inhibitor analogues impeded HPV+ and HPV- HNSCC cell proliferation and two-dimensional migration. Moreover, MK2-inhibitors lowered HNSCC cell clonogenic survival in a dose-dependent manner, significantly enhancing radiation-induced cell death via exerting radio-sensitization effects. Furthermore, γ-H2AX immunostaining revealed that PfBS analogues impaired DNA damage repair in HNSCC cells exposed to gamma radiation. In mice, PfBS MK2 inhibitors at 300 mg/kg were well-tolerated without any lethal effects. Pharmacokinetic studies showed that PfBS analogues exhibited rapid absorption (Tmax), adequate plasma concentration above the micromolar level (C0 or Cmax), limited tissue distribution (Vd), and faster elimination from the body (Cl). Overall, this study summarizes in-vitro efficacy, safety, and pharmacokinetics of developed MK2-inhibitors and opens doors for pharmacodynamics and mechanism of action study of most effective leads in HNSCC.

Identification of novel inhibitors for epidermal growth factor receptor tyrosine kinase using absolute binding free-energy simulations

Mutations in the kinase domain of the epidermal growth factor receptor (EGFR), a critical biological macromolecule involved in cell growth and division, can lead to drug resistance in patients undergoing chemotherapy with kinase inhibitors. Notably, the emergence of the C797S mutation poses new challenges for targeted EGFR therapy, highlighting the urgent need for agents effective against this triple mutation (L858R/T790M/C797S, EGFR™). Building on our previous finding that sulfonyl and piperidinyl groups significantly contribute to the EGFR™-inhibitor interactions, we have identified the best-in-class inhibitors containing these groups through functional-group-based screening and formally exact absolute binding free-energy calculations. Our new strategy offers greater flexibility than traditional workflows leaning on relative binding free-energy calculations and accommodates ligands with substantial structural variations. The result shows that the top candidate exhibits a binding affinity of -15.8 kcal/mol towards the EGFR™ mutant, surpassing BLU-945, a state-of-the-art fourth-generation inhibitor with a binding free energy of -12.6 kcal/mol. Subsequent free-energy decomposition indicates that the presented top candidate primarily enhances interactions with the K745, D800 and R841 residues, suggesting its potential to overcome resistance from the C797S mutation. Notably, K745 forms highly favorable hydrogen bonds and cation-π interactions with C6. Targeting lysine has emerged as a promising strategy, especially in cases where the C797S mutation renders traditional covalent inhibitors ineffective. We propose that these novel inhibitors represent promising drug candidates for non-small cell lung cancer treatment and offer new strategies to overcome drug resistance caused by EGFR mutation.

Repurposing of FDA-approved drugs against oligomerization domain of dengue virus NS1 protein: a computational approach

Dengue fever is a serious health hazard on a global scale and its primary causative agent is the dengue virus (DENV). The non-structural protein 1 (NS1) of DENV plays a pivotal role in pathogenesis. It is associated with several autoimmune events, endothelial cell apoptosis, and vascular leakage, which increase mainly during the critical phase of infection. In this study, important residues of the oligomerization domain of NS1 protein were identified by literature searches. Virtual screening has been conducted using the entire dataset of the DrugBank database and the potential small-molecule inhibitors against the NS1 protein have been chosen on the basis of binding energy values. This is succeeded by molecular dynamics (MD) simulations of the shortlisted compounds, ultimately giving rise to five compounds. These five compounds were further subjected to RAMD simulations by applying a random direction force of specific magnitude on the ligand center of mass in order to push the ligand out of the protein-binding pocket, for the quantitative estimation of their binding energy values to determine the interaction strength between protein and ligand which prevents ligand unbinding from its binding site, ultimately leading to the selection of three major compounds, DB00826 (Natamycin), DB11274 (Dihydro-alphaergocryptine), and DB11275 (Epicriptine), with the DB11274 having a role against idiopathic Parkinson's disease, and thus may have possible important roles in the prevention of dengue-associated Parkinsonism. These compounds may act as prospective drugs against dengue, by preventing the oligomerization of the NS1 protein, thereby preventing disease progression and pathogenesis.

Computational discovery of natural inhibitors targeting enterovirus D68 3C protease using molecular docking pharmacokinetics and dynamics simulations

Enterovirus D68 (EV-D68) is a significant global health threat, responsible for severe respiratory and neurological complications, with no FDA-approved antiviral treatments currently available. The 3C protease of EV-D68, an essential enzyme involved in viral replication, represents a key target for therapeutic development. In this study, we employed a comprehensive computational approach, including molecular docking, pharmacokinetic predictions, and molecular dynamics simulations, to identify potential natural inhibitors of the EV-D68 3C protease. Screening a library of natural compounds, Withaferin-A (CID: 265,237) and Baicalin (CID: 64,982) emerged as top candidates due to their favorable pharmacokinetic profiles, high binding affinities (-10.7 kcal/mol for Withaferin-A and -9.5 kcal/mol for Baicalin), and interactions with key residues in the protease's active site. The molecular dynamics simulations demonstrated the stability of the protein-ligand complexes, with low root mean square deviation (RMSD) and fluctuation (RMSF) values over a 100-ns trajectory. Free energy calculations further supported the superior binding efficiency of Withaferin-A. These findings suggest that Withaferin-A and Baicalin have significant potential as natural inhibitors of EV-D68 3C protease, offering a promising foundation for future experimental validation and the development of targeted antiviral therapies against EV-D68.

Computational drug design for neurosyphilis disease by targeting Phosphoglycerate Kinase in Treponema pallidum with enhanced binding affinity and reduced toxicity

Neurosyphilis, a severe neurological complication of syphilitic infection caused by the gram-negative spirochete Treponema pallidum poses significant challenges in treatment due to its irregular physiology and lack of efficacy in present therapeutic strategies. Here, we report a new approach to developing drug treatment that targets the enzyme phosphoglycerate kinase (PGK), an essential component of the T. pallidum glycolytic pathway. Therefore, a ligand was designed involving common neuroprotectant elements reported from literature by a computational drug design method, to increase their binding energy with lower toxicity. The calculated binding affinity of the designed ligand with PGK was analyzed by molecular docking to be - 116.68 kcal/mol. Also, interaction analysis predicted that there are 5 hydrophobic bonds and 3 hydrogen bonds present between the docked complex. Afterward, in-silico ADMET studies were conducted for the designed ligand that determined a strong pharmacological profile with good absorption, zero violation of Lipinski's rule, and non-toxic properties. DFT analysis further optimized the ligand with a HOMO/LOMO gap value of 0.01421 kcal/mol indicating higher reactivity and enhanced electronic interactions, improving ligand efficiency. Moreover, pharmacophore modeling confirmed the reactive nature of the ligand. Furthermore, MD simulations showed stability in the overall structure. The output shows that our optimized ligand has statistically better binding affinity than the currently used drug penicillin, with improved pharmacokinetic profiles. This work demonstrates the importance of ligand design for the discovery of new drugs to treat neurosyphilis.

Interactions of flavonoid and coumarin derivative compounds with transforming growth factor-beta receptor 1 (TGF-βR1): integrating virtual screening, molecular dynamics, maximum common substructure, and ADMET approaches in the treatment of idiopathic pulmonary fibrosis

CONTEXT

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung disease characterized by very limited treatment options and significant side effects from existing therapies, highlighting the urgent need for more effective drug-like molecules. Transforming growth factor-beta receptor 1 (TGF-βR1) is a key player in the pathogenesis of IPF and represents a critical target for therapeutic intervention. In this study, the potential of plant-derived flavonoid and coumarin compounds as novel TGF-βR1 inhibitors was explored. A total of 1206 flavonoid and coumarin derivatives were investigated through a series of computational approaches, including drug-like filtering, virtual screening, molecular docking, 200-ns molecular dynamics (MD) simulations in triplicate, maximum common substructure (MCS) analysis, and absorption-distribution-metabolism-excretion-toxicity (ADMET) profiling. 2',3',4'-trihydroxyflavone and dicoumarol emerged as promising plant-based hit candidates, exhibiting comparable docking scores, MD-based structural stability, and more negative MM/PBSA binding free energy relative to the co-crystallized inhibitor, while surpassing pirfenidone in these parameters and demonstrating superior pharmacological properties. In light of the findings from this study, 2',3',4'-trihydroxyflavone and dicoumarol could be considered novel TGF-βR1 inhibitors for IPF treatment, and it is recommended that their structural optimization be pursued through in vitro binding assays and in vivo animal studies.

METHODS

The initial dataset of 1206 flavonoid and coumarin derivatives was filtered for drug-likeness using Lipinski's Rule of Five in the ChemMaster-Pro 1.2 program, resulting in 161 potential candidates. These compounds were then subjected to virtual screening against the TGF-βR1 kinase domain (PDB ID: 6B8Y) using AutoDock Vina 1.2.5, identifying the top three hit compounds-dicoumarol, 2',3',4'-trihydroxyflavone, and 2',3'-dihydroxyflavone. These hits underwent further exhaustive molecular docking for refinement of docking poses, followed by 200-ns MD simulations in triplicate using the AMBER03 force field in GROMACS. Subsequently, the binding free energies were calculated using the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method. MCS analysis was conducted to determine shared structural features among the top three hits, while ADMET properties were predicted using Deep-PK, a deep learning-based platform. Finally, the ligand-protein interactions were further visualized, analyzed, and rendered using ChimeraX, Discovery Studio Visualizer, and Visual Molecular Dynamics (VMD) program.

Structural insights into molecular and cellular level FXR binding potentials of GW4064 and LY2562175 hybrids by multi in silico modelling analyses

CONTEXT

Non-alcoholic fatty liver disease (NAFLD) has become a significant health concern. Existing farnesoid X receptor (FXR) agonists like GW4064 and LYS2562175 show poor pharmacokinetics, prompting researchers to develop alternative molecules. This study aims to pinpoint the structural features responsible for exhibiting FXR agonism of a series of hybrid structures of GW4064 and LYS2562175 with improved pharmacokinetic properties which supersede the existing parent ligands. Electronegative components were found to critically influence biological activity on the molecular level, supported by 2D- and 3D-Quantitative Structure Activity Relationship (2D- and 3D-QSAR) analyses. Quantitative Activity-Activity Relationship (QAAR) highlighted key descriptors impacting cellular level FXR binding potential. Molecular dynamics (MD) simulations identified pivotal interactions, such as π-π and H-bond interactions with key residues. Furthermore, binding free energy calculated with Molecular Mechanics with Generalised Born and Surface Area solvation (MM-GBSA) analyses with selected compounds reflected the variations in their binding potential towards FXR protein.

METHODS

The study began by curating ligand SMILES and preparing a dataset with molecular and cellular activity as dependent variables. AlvaDesc descriptors and interpretable descriptors were calculated using the OCHEM webserver. QSAR analyses were performed using Sequential Forward Selection (SFS) and Genetic Algorithm (GA) methods, while QAAR analysis used 50% effective concentration at the molecular level as an independent variable with the same algorithms. 3D QSAR analysis was performed with the Open3DQSAR tool. Docking studies in AutoDock 4.2 with FXR protein identified optimal ligand poses, and 500 ns MD simulations were performed with Amber 20. The use of open-access tools ensures reproducibility and accessibility for future research.

Computational analysis of antimicrobial peptides targeting key receptors in infection-related cardiovascular diseases: molecular docking and dynamics insights

Infection-related cardiovascular diseases (CVDs) pose a significant health challenge, driving the need for novel therapeutic strategies to target key receptors involved in inflammation and infection. Antimicrobial peptides (AMPs) show the potential to disrupt pathogenic processes and offer a promising approach to CVD treatment. This study investigates the binding potential of selected AMPs with critical receptors implicated in CVDs, aiming to explore their therapeutic potential. A comprehensive computational approach was employed to assess AMP interactions with CVD-related receptors, including ACE2, CRP, MMP9, NLRP3, and TLR4. Molecular docking studies identified AMPs with high binding affinities to these targets, notably Tachystatin, Pleurocidin, and Subtilisin A, which showed strong interactions with ACE2, CRP, and MMP9. Following docking, 100 ns molecular dynamics (MD) simulations confirmed the stability of AMP-receptor complexes, and MM/PBSA calculations provided quantitative insights into binding energies, underscoring the potential of these AMPs to modulate receptor activity in infection and inflammation contexts. The study highlights the therapeutic potential of Tachystatin, Pleurocidin, and Subtilisin A in targeting infection-related pathways in CVDs. These AMPs demonstrate promising receptor binding properties and stability in computational models. Future research should focus on in vitro and in vivo studies to confirm their efficacy and safety, paving the way for potential clinical applications in managing infection-related cardiovascular conditions.

Identification biomarkers and therapeutic targets of disulfidptosis-related in rheumatoid arthritis via bioinformatics, molecular dynamics simulation, and experimental validation

The relationship between disulfidptosis and rheumatoid arthritis (RA) remains unclear. We aimed to identified biomarkers disulfidptosis-related in RA and revealed potential targeted drugs. Two microarray datasets (GSE93272, GSE45291) related to RA were downloaded from the Gene Expression Omnibus (GEO) database. Disulfidptosis-related genes(DRGs) were extracted from FerrDb database. GSE93272 was used to identify DRGs, and GSE45291 was used to verify results. Multivariate Cox regression analysis was used to identify candidate disulfidptosis-associated hub genes. The differentiated values of DRGs were determined by receiver operator characteristic (ROC) monofactor analysis to judge their potential quality as biomarkers. RT-qPCR were used to validate the expression of hub genes. Additionally, we analyzed the connection between the hub genes and the filtration of immune cells in RA. We made predictions about the miRNAs, TFs and possible drugs that regulate the hub genes. Subsequently, molecular docking was carried out to predict the combination of drugs with hub targets. Finally, molecular dynamics simulation was conducted to further verify the findings. Oxoacyl-ACP Synthase Mitochondrial(OXSM) was identified as a biomarker with high diagnostic value, and an RA diagnostic model based on OXSM for a single gene was constructed. The model showed high accuracy in distinguishing RA and healthy controls (AUC = 0.802) and was validated by external datasets, showing excellent diagnostic power (AUC = 0.982). Twelve potential drugs against RA were recognized by comparative toxicogenomics database (CTD). Molecular docking results showed that ICG 001 had the highest binding affinity to OXSM, and molecular dynamics simulations confirmed the stability of this complexes. Furthermore, CIBERSORT analysis showed a significant correlation between immune cell infiltration and OXSM, and a regulatory network of TFs-gene-miRNAs comprising 8 miRNAs and 34 TFs was identified. Finally, the RT-qPCR results showed that OXSM was significantly increased in the peripheral blood of RA patients compared with healthy controls, consistent with the bioinformatics analysis. These studies suggest that OXSM may be a potential biomarker and therapeutic target for diagnosing RA, and ICG 001 may be a potential drug for RA. These findings may provide new avenues for the effective diagnosis and treatment of RA.

Computational study on the mechanism of small molecules inhibiting NLRP3 with ensemble docking and molecular dynamic simulations

NLRP3 (Nucleotide-binding oligomerization domain, LRR and pyrin domain-containing protein 3) is a pivotal regulator of inflammation, with strong implications in gout, neurodegenerative diseases, and various inflammatory conditions. Consequently, the exploration of NLRP3 inhibitors is of great significance for the treatment of diseases. MCC950, NP3-146, compound (3), and YQ128 are four highly bioactive NLRP3 inhibitors that show great potential; however, their mechanism of action is currently limited to targeting the ATP binding region (NACHT site) of the NLRP3 protein. To gain deeper insights into the defining features of NLRP3 inhibitors and to develop more potent inhibitors, it is imperative to elucidate the interaction mechanism between NLRP3 and these inhibitors. In this study, we employ a comprehensive computational approach to investigate the binding mechanism between NLRP3 and representative inhibitors. Utilizing the molecular mechanics/generalized Born surface area (MM/GBSA) method, we calculate the binding free energy and pinpoint the key residues involved in the binding of the four inhibitors to NLRP3. The decomposition of binding free energy by the MM/GBSA method reveals that the residues Val71, Arg195, Ile255, Phe419, Arg422, and Met505, situated around the binding pocket, play a crucial role in conferring the high bioactivity of NLRP3 inhibitors. Furthermore, pharmacophore analysis of the four NLRP3 complexes indicates that the primary interaction between the inhibitors and NLRP3 was mainly hydrophobic interaction. Our study provides a profound understanding of the interaction mechanism between NLRP3 and its inhibitors, identifies the key residues involved, and provides theoretical guidance for the design of more efficient NLRP3 inhibitors.

IAMPDB: A Knowledgebase of Manually Curated Insects-Derived Antimicrobial Peptides

Insects, a majority of animal species, rely on innate immunity and antimicrobial peptides (AMPs), which are a part of their innate immunity, to combat diverse parasites and pathogens. These peptides have applications ranging from agriculture to antimicrobial resistance (AMR). However, there is a lack of a specialized database, prompting the development of the Insect Antimicrobial Peptide Database (IAMPDB) as a pioneering comprehensive Knowledgebase dedicated to insect-derived antimicrobial peptides (IAMPs), serving as a resource for researchers and industry professionals. Curated from UniProt and associated literature(s), IAMPDB currently houses 438 curated entries of IAMPs from various insect species, spanning 10 taxonomical orders of insects. Each entry is meticulously annotated with details on peptide sequence, source organism, activities, physicochemical properties, and more. IAMPDB offers a user-friendly interface with diverse search options, interactive visualizations, and links to external databases; advanced tools, including a peptide sequence alignment toolbox and a peptide feature calculation toolbox, facilitating sequence alignment, physicochemical property calculation, and in-depth analysis. The knowledgebase is accessible online (at URL https://bblserver.org.in/iampdb/).

Multi-group structure analysis and molecular docking of aptamers and small molecules: A case study of chloramphenicol

Aptamers, a kind of short nucleotide sequences with high specificity and affinity with targets, have attracted extensive attention in recent years. Molecular docking method (MDM) is the most common method to explore the binding mode and recognition mechanism of aptamers and small molecules, which generally use the target to dock with the highest scoring tertiary structural model of the aptamer, and the highest scoring result is used as the predicted model. However, this prediction results may miss out the true interaction pattern due to the fact that aptamers are not completely rigid and the natural aptamers conformations are not in a single state. Thus, evaluation of the binding pattern from two or more tertiary structural modes might be more accurate. The use of chloramphenicol (CAP) has been banned because it causes myelosuppression and aplastic anemia in humans. However, CAP is still abused and is often studied as a target for detection. Two CAP aptamers (Apt-11 and Apt-16) were used as cases in this study. All secondary structures of these two aptamers were predicted using the UNAFold Web Server tool, and then the corresponding tertiary structure models were built using the RNA Composer tool and Discovery Studio 4.5 Client software. The resulted six tertiary structure models were docked with CAP respectively. By optimizing the docking conditions, multiple groups of docking outcomes were obtained, including the tertiary structure, its binding free energy, and the binding site. The results suggested that there may be multiple binding sites in the same tertiary structure, and the binding energy of the same tertiary structure as well as the proportion of multiple binding sites vary greatly. In addition, it was found that Autodock4 works well in analyzing the binding mode between screened aptamers with its defined target, but cannot be used to identify that whether an aptamer could bind well with other molecule with big structural difference from the target. The CAP aptamer was tailored according to the molecular docking results, and the potential binding sites with CAP were verified by a colloidal gold colorimetry assay. In conclusion, we propose a method to explore the binding patterns between aptamer and its targets by using multiple optimized docking data from different tertiary structures of the aptamer, which provides a theoretical basis for the study of the binding mode of aptamers and targets, as well as the optimization and modification of aptamers.

In silico discovery of a novel potential allosteric PI3Kα inhibitor incorporating 2-oxopropyl urea targeting head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the most common head and neck cancer and highly aggressive and heterogeneous. Targeted therapy is still the main treatment method used in clinic due to lower side effect and personalized medication. In order to discover novel and effective drugs with low side effect against HNSCC, we analyzed the genes related to HNSCC, and found that PIK3CA was highly expressed in tumor tissues and often experienced mutations, leading to excessive activation of phosphoinositide 3-kinase alpha (PI3Kα), promoting the development of HNSCC. The allosteric PI3Kα inhibitor STX-478 inhibits the growth of tumor with hotspot mutations in PI3Kα and shows prominent efficacy on the treatment of human HNSCC xenografts without displaying the metabolic dysfunction observed in Alpelisib. These mutations open the allosteric site more readily, increasing the selectivity of STX-478 for mutant PI3Kα. STX-478 cleverly avoids the side effect of ATP competitive PI3Kα inhibitors. So, the structure of STX-478 was optimized based on the interaction mechanism between STX-478 and PI3Kα. Then, virtual screening, binding mode research, target verification, physical and chemical properties, pharmacokinetic properties and stabilities of ligand-PI3Kα complexes were evaluated by computer technologies (scaffold hopping, cdocker, SuperPred, SwissTarget prediction, Lipinski's rule of five, ADMET and MD simulation). Finally, J-53 (2-oxopropyl urea compound) with excellent properties was selected. J-53 not only formed H-bonds with key amino acids, but its unique -C(O)CH3 could also form H-bonds with ILE1019, making it more stably bound to PI3Kα and contributing to its activity. After the SciFinder verification, J-53 with novel structure had the value of further study. This study suggested that J-53 could be used as potential inhibitors of PI3Kα, and provides valuable information for the subsequent drug discovery of allosteric PI3Kα inhibitors.

Computer-aided drug repurposing & discovery for Hepatitis B capsid protein

The primary objective of this study is to harness computer-aided drug repurposing (CADR) techniques to identify existing FDA-approved drugs that can potentially disrupt the assembly of the Hepatitis B Virus (HBV) core protein (HBcAg), an essential process in the virus's life cycle. By targeting this critical step, our study aims to expand the repertoire of therapeutic options for managing chronic Hepatitis B infection, a major global health challenge. Utilizing a combination of computational methods, including the CavityPlus server for ability to analyze druggable protein cavities and extract pharmacophore features and LigandScout for pharmacophore-based virtual screening of a vast library of FDA-approved drugs was conducted. Molecular dynamic simulation (MDS) was employed to evaluate the stability of HBcAg, complexed with Heteroaryldihydropyrimidine (HAP) and statins exhibiting particularly strong binding energies and conformational compatibility. Our approach focused on identifying pharmacophore features that align with known HBcAg inhibitors. The study identified several promising candidates, including Ciclopirox olamine, Voriconazole, Enasidenib, and statins, demonstrating potential interactions with HBc protein residues. Molecular docking further validated these interactions. The significance of these findings lies in their potential to offer new, effective therapeutic strategies for HBV treatment, particularly as alternatives to current therapies that often suffer from issues of viral resistance and adverse side effects. MDS analysis verified the robustness of HAP and statins by showing a high level of binding energies and compatibility with HBcAg. Our results provide a foundation for further experimental validation and underscore the utility of computer-aided drug repurposing as a rapid, cost-effective approach to drug discovery in antiviral research. This study contributes to our understanding of HBV biology and opens avenues for developing novel anti-HBV therapies based on repurposed drugs. The highlighted compound may also enhance the challenges of drug resistance when used as a combination therapy.

Therapeutic Role of Quercetin in Prostate Cancer: A Study of Network Pharmacology, Molecular Docking, and Dynamics Simulation

Prostate cancer (PCa) is a major cause of cancer-related mortality in men. This study explores the anticancer potential of Quercetin, a polyphenolic compound with antioxidant and anti-inflammatory properties, by network pharmacology, molecular docking, and molecular dynamics simulation approaches. Target genes for Quercetin and PCa were identified from the bioinformatics databases MalaCards, Comparative Toxicogenomics Databases, SwissTargetPrediction, and Traditional Chinese Medicine Systems Pharmacology, and the obtained genes were matched using the Venny platform to find out the common genes. We obtained 11 preliminary genes and analyzed them in ShinyGO-0.77 databases to obtain genetic otology data. Then, we constructed a protein-protein interaction network in STRING, which enabled us to identify six hub genes AKT1, EGFR, MMP2, MMP9, PARP1, and ABCG2. Hub genes were analyzed in the TISIDB database for immune cell infiltration. Furthermore, a molecular docking study between the target proteins and Quercetin was performed in the SwissDock databases. Subsequently, we corroborated the docking with molecular dynamics studies using GROMACS software. Gene Ontology and KEGG pathway analyses revealed that Quercetin influences oxidative stress, mitochondrial function, and metalloproteinase activity. Immune cell infiltration analysis highlighted correlations between key genes and specific immune responses, suggesting a modulatory role of Quercetin in the tumor microenvironment. Finally, docking and molecular dynamics analysis showed that Quercetin has a stable interaction with the hub genes. In conclusion, these findings underline the potential of Quercetin to induce apoptosis, inhibit angiogenesis, and suppress metastasis, proposing it as a promising therapeutic tool for the treatment of PCa. However, additional experimental studies are required to translate these findings into clinical practice.

In silico pentapeptide design for the inhibition between S100 calcium-binding A9 (S100A9) proteins

CONTEXT

S100 calcium-binding protein A9 (S100A9) is easily assembled into amyloid aggregates in solution. These amyloid aggregates cause retinal toxicity and act as an attachment core for Aβ fibrillar plaques that contribute to Alzheimer's disease progression. The overexpression of S100A9 is also noticed in various malignancies. Therefore, the S100A9 amyloid formation inhibition is of significant interest. In comparison with small-molecule drugs, short peptides demonstrate higher specificity, potency, and biosafety. Hence, it could be beneficial to identify potential peptides to inhibit or disrupt S100A9 amyloid aggregation. Typical peptide design and identification via experimental means requires extensive preparation procedures and is limited to random selection of peptides. Virtual screening therefore offers an unbiased, higher throughput, and economically efficient approach in peptide drug development. Here, we reported in silico pentapeptide design against S100A9 and studied the interaction of pentapeptide with S100A9 that leads to the binding of the peptide with S100A9.

METHOD

Docking simulation resulted in three top binding free energy tripeptides (WWF, WPW, and YWF) with comparable affinity towards a known S100A9 inhibitor (polyphenol oleuropein aglycone; OleA). Subsequently, pentapeptides that consist of the three core tripeptides were selected from a pre-constructed pentapeptide library for further evaluation with docking simulation. Based on best docked binding free energy, two pentapeptides (WWPWH and WPWYW) were selected and subjected to 500 ns molecular dynamics (MD) simulation to study the important features that lead to the binding with S100A9. MMGBSA binding free energy calculation estimated - 30.38, - 24.58, and - 30.31 kcal/mol for WWPWH, WPWYW, and OleA, respectively. The main driving force for pentapeptide-S100A9 recognition was contributed by the electrostatic interaction. The results demonstrate that at in silico level, this workflow is able to design potential pentapeptides that are comparable with OleA and might be the lead molecule for future use to disaggregate S100A9 fibrils.

Elucidating the potential of EGFR mutated NSCLC and identifying its multitargeted inhibitors

Lung cancer is the leading cause of cancer-related fatalities globally, accounting for the highest mortality rate among both men and women. Mutations in the epidermal growth factor receptor (EGFR) gene are frequently found in non-small cell lung cancer (NSCLC). Since curcumin and CB[2]UN support various medicinal applications in drug delivery and design, we investigated the effect of curcumin and CB[2]UN-based drugs in controlling EGFR-mutant NSCLC through a dodecagonal computational approach. Molecular docking studies revealed that the ligands curcumin (-6.9 kcal/mol) and CB[2]UN (-8.1 kcal/mol) bound more strongly to the EGFR-mutant NSCLC proteins with 2ITX and 2ITV, respectively. Molecular dynamics simulation (50 ns) investigation of protein-ligand complexes using RMSD, RMSF, Rg, and SASA indicated that curcumin and CB[2]UN with EGFR-mutant proteins are kinetically stable. In addition, MMPBSA/MMGBSA analysis confirmed the thermodynamic stability of each curcumin and CB[2]UN protein-ligand complex. Finally, KDeep absolute binding affinity calculations show energies of -6.13 kcal/mol and - 5.26 kcal/mol for 2ITX-CUR and 2ITV-CB[2]UN protein-ligand complexes, respectively. Thus, our dodecagonal strategy reveals that 2ITX-CUR and 2ITV-CB[2]UN are more likely to form protein-ligand complexes with more significant binding affinities and excellent stability throughout the 50 ns simulation time.

Curcumin as a potential inhibitor of TGFβ3 computational insights for breast cancer therapy

Previous research indicates that Transforming growth factor beta-3 (TGFβ3) expression levels correlate with breast cancer metastasis, and elevated TGFβ3 levels have been linked with poor overall survival in breast cancer patients. The study used computational methods to examine curcumin's effects on TGFβ3, a chemical with antiviral and anticancer characteristics. The curcumin has low Molecular Weight 368.130 (MW) and follows Lipinski Rule, Pfizer Rule, GSK Rule, Golden Triangle, BMS Rule, zero PAINS alert and Acute Toxicity Rule with zero alert. Any drug-like contender must follow these qualities. Through molecular docking analyses, curcumin displayed favourable binding affinities at the TGFβ3 binding pocket, forming key interactions such as hydrogen bonds with residues like ASP323, ARG325, VAL333, HIS334, PRO336, LYS337, GLY393, and ARG394. 500 ns molecular dynamic simulations examined docking interactions. Molecular dynamics (MD) simulations trajectories analysis, by calculating lower structural deviation, minimal residual fluctuations, structural compactness assessment by calculating radius of gyration, surface area calculation which interact with solvent, role of hydrogen bonding, and secondary structural analyses. Furthermore, principal component, Gibbs free energy landscape and MMPBSA analysis, signifying system stability. These data suggest curcumin may inhibit TGFβ3, providing a framework for developing new compounds targeting this protein.

In-silico screening and analysis of missense SNPs in human CYP3A4/5 affecting drug-enzyme interactions of FDA-approved COVID-19 antiviral drugs

Single nucleotide polymorphisms (SNPs) represent the prevailing form of genetic variations observed in the human population. Such variations could alter the encoded enzymes' activities. CYP3A4/5 enzymes are involved in metabolizing drugs, notably antivirals against SARS-CoV-2. In this work, we computationally investigated antiviral-enzyme interactions of CYP3A4/5 genetic variants. We also examined the deleterious impact of 751 missense single nucleotide polymorphisms (SNPs) within the CYP3A4/5 genes. An ensemble of bioinformatics tools, [SIFT, PolyPhen-2, cadd, revel, metaLr, mutation assessor, Panther, SNP&GO, PhD-SNP, SNAP, Meta-SNP, FATHMM, I-Mutant, MuPro, INPS, CONSURF, GPS 5.0, MusiteDeep and NetPhos], identified a total of 94 variants (47 SNPs in CYP3A4, 47 SNPs in CYP3A5) to potentially impact the structural integrity as well as the activity of the CYP3A4/5 enzymes. Molecular docking was done to recognize the structural stability and binding properties of the CYP3A4/5 protein isoforms with 3 FDA-approved antiviral drugs. Our findings indicated that the CYP3A4 gene variants; R418T, I335T and R130P and the CYP3A5 gene variants; I335T, L133P and R130Q are considered the most deleterious missense SNPs. These mutants potentially affect drug-enzyme binding and hence may alter therapeutic response. Cataloguing deleterious SNPs is essential for personalized gene-based pharmacotherapy.

Computational screening and molecular dynamics of natural compounds targeting the SH2 domain of STAT3: a multitarget approach using network pharmacology

SH2 (Src Homology 2) domains play a crucial role in phosphotyrosine-mediated signaling and have emerged as promising drug targets, particularly in cancer therapy. STAT3 (Signal Transducer and Activator of Transcription 3), which contains an SH2 domain, plays a pivotal role in cancer progression and immune evasion because it facilitates the dimerization of STAT3, which is essential for their activation and subsequent nuclear translocation. SH2 domain-mediated STAT3 inhibition disrupts this binding, reduces phosphorylation of STAT3, and impairs dimerization. This study employed an in silico approach to screen potential natural compounds that could target the SH2 domain of STAT3 and inhibit its function. The phytomolecules (182455) were retrieved from the ZINC 15 database and were docked using various modes like HTVS, SP, and XP. The phytomolecules exhibiting higher binding affinity were selected. MM-GBSA was performed to determine binding free energy, and the QikProp tool was utilized to assess the pharmacokinetic properties of potential hit compounds, narrowing down the list of candidates. Molecular dynamics simulations, thermal MM-GBSA, and WaterMap analysis were performed on compounds that exhibited favorable binding affinities and pharmacokinetic characteristics. Based on docking scores and binding interactions, ZINC255200449, ZINC299817570, ZINC31167114, and ZINC67910988 were identified as potential STAT3 inhibitors. ZINC67910988 demonstrated superior stability in molecular dynamics simulation and WaterMap analysis. Furthermore, DFT was performed to determine energetic and electronic properties, and HOMO and LUMO sites were predicted for electronic structure calculation. Additionally, network pharmacology was performed to map the compounds' interactions within biological networks, highlighting their multitarget potential. Compound-target networks elucidate the relationships between compounds and multiple targets, along with their associated pathways and help to minimize off-target effects. The identified lead compound showed strong potential as a STAT3 inhibitor, warranting further validation through in vitro and in vivo studies.

Exploring Chemical Space to Identify Partial Binders Against hMPV Nucleocapsid Protein

Human metapneumovirus (hMPV) has gained prominence in recent times as the predominant etiological agent of acute respiratory tract infections. This virus targets children, the elderly, and individuals with compromised immune systems. Given the protracted duration of hMPV transmission, it is probable that the majority of children will have acquired the virus by the age of 5. In individuals with compromised immune systems, recurrence of hMPV infection is possible. As hMPV matures, it remains latent from the time of acquisition. The genome of hMPV encompasses a pivotal protein referred to as the nucleocapsid protein (N). This protein assumes the form of a left-handed helical nucleocapsid, enveloping the viral RNA genome. The primary function of this structure is to protect nucleases, rendering it a potentially promising target for therapeutic advancements. The present study employs a methodology that involves structure-based virtual screening, followed by molecular dynamics simulation at a 250-ns time scale, to identify potential natural molecules or their derivatives from the ZINC Database. These molecules are investigated for their binding properties against the hMPV nucleoprotein. Based on an evaluation of the docking score, binding site interaction, and molecular dynamics studies, it has been found that two naturally occurring molecules, namely M1 (ZINC85629735) and M3 (ZINC85569125), have shown notable docking scores of -9.6 and -10.7 kcal/mol, acceptable RMSD, RMSF, Rg, and so on calculated from molecular dynamics trajectory associated with MMGBSA binding energy of -81.94 and -99.63 kcal/mol, respectively. These molecules have shown the highest binding affinity toward nucleocapsid protein and demonstrated promising attributes as potential binders against hMPV.

Identification of phytomolecules as isoform and mutation specific PI3K-α inhibitor for protection against breast cancer using e-pharmacophore modeling and molecular dynamics simulations

PI3K-α mutation plays a critical role in cancer development, notably in breast cancer, particularly within HR + /HER2- subtypes. These mutations drive tumor growth and survival by activating the PI3K/AKT/mTOR pathway, which is essential for cell proliferation and survival. Our research aimed to identify natural compounds that can inhibit mutant and specific isoforms of PI3K-α to prevent tumor progression. e-Pharmacophore model was generated using Receptor-Ligand complex using the Inavolisib drug (PDB:8EXV) and phase screening was performed using the Molport database of natural compounds. Through molecular docking studies we identified seven promising compounds for further molecular dynamics simulations. Among these, three compounds-STOCK1N-85097, STOCK1N-85998, and STOCK1N-86060-showed significant stability and interaction with PI3K-α. These compounds demonstrated favorable results in several parameters, including RMSD, RMSF, Rg, SASA, PCA, FEL, and total energy evaluations. Therefore, these compounds are projected to function as PI3K-α inhibitors and because of its natural origin it can possess fewer side effects than the conventional medicine, which should be validated by proper in vivo and in vitro models.

Inhibition of IRF3-STING axis interaction in silicosis using natural compounds: an in-silico study using molecular docking, ADMET, molecular dynamics and MMPBSA approach

Silicosis is a chronic occupational lung disease characterized by persistent inflammation driven by the activation of the cGAS-STING pathway, leading to the downstream activation of IRF3. To develop a natural compound library of COCONUT database for this investigation, Lipinski's rule of five was used and we explored the potential of these compounds to disrupt the IRF3-STING interaction, thereby mitigating the inflammatory response. Molecular docking and molecular dynamics (MD) simulations were employed to assess the binding stability and interaction dynamics of these compounds with IRF3. The stable RMSD values indicate that the protein-ligand complexes maintained structural integrity throughout the simulation period. The compounds also demonstrated drug-like characteristics, a promising safety profile, and formed stable complexes with the target protein. Further, decomposition of binding free energy highlighted the key contributions of IRF3 residues VAL295, ASP308, PRO324, and ARG338 interacting with the selected compounds, potentially inhibiting the IRF3-STING interaction. The origin of the selected compounds was determined using ClassyFire, classifying compound CNP0310627 as a burfenolide and compound CNP0200121 as a psoralen. Both classes are recognized for their anti-inflammatory properties, reinforcing the therapeutic potential of these compounds in reducing inflammation associated with silicosis. Our findings suggest that these compounds could serve as promising candidates for further investigation in the development of anti-inflammatory therapeutic molecules in the cGAS-STING-IRF3 signaling pathway. However, to fully assess the therapeutic potential of these compounds, further in vitro and in vivo studies are required to validate their efficacy and safety in modulating the STING-IRF3 pathway.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00290-5.

Molecular dynamics-based computational investigations on the influence of tumor suppressor p53 binding protein against other proteins/peptides

The tumor-suppressing p-53 binding protein is a crucial protein that is involved in the prevention of cancer via its regulatory effect on a number of cellular processes. Recent evidence indicates that it interacts with a number of other proteins involved in cancer in ways that are not fully understood. An understanding of such interactions could provide insights into novel ways p53 further exerts its tumour prevention role via its interactions with diverse proteins. Thus, this study aimed to examine the interactions of the p53 protein with other proteins (peptides and histones) using molecular simulation dynamics. We opted for a total of seven proteins, namely 2LVM, 2MWO, 2MWP, 4CRI, 4 × 34, 5Z78, and 6MYO (control), and had their PBD files retrieved from the protein database. These proteins were then docked against the p-53 protein and the resulting interactions were examined using molecular docking simulations run at 500 ns. The result of the interactions revealed the utilisation of various amino acids in the process. The peptide that interacted with the highest number of amino acids was 5Z78 and these were Lys10, Gly21, Trp24, Pro105, His106, and Arg107, indicating a stronger interaction. The RMSD and RMSF values indicate that the complexes formed were stable, with 4CRI, 6MYO, and 2G3R giving the most stable values (less than 2.5 Å). Other parameters, including the SASA, Rg, and number of hydrogen bonds, all indicated the formation of fairly stable complexes. Our study indicates that overall, the interactions of 53BP1 with p53K370me2, p53K382me2, methylated K810 Rb, p53K381acK382me2, and tudor-interacting repair regulator protein indicated interactions that were not as strong as those with the histone protein. Thus, it could be that P53 may mediate its tumour suppressing effect via interactions with amino acids and histone.

Molecular Regulator Driving Endometriosis Towards Endometrial Cancer: A Multi-Scale Computational Investigation to Repurpose Anti-Cancer drugs

Endometriosis is a gynecological disorder among reproductive-aged women. Recent epidemiological investigations suggest endometriosis increases the risk of endometrial cancer. However, the molecular entity leading to endometriosis-to-endometrial cancer is largely unknown. This study aimed to combine a variety of computational approaches to identify the key therapeutic target promoting endometriosis-to-endometrial cancer and screen potential inhibitors against target to prevent cancer development. Our systematic investigations, includes transcriptomic profiling, protein network, pharmacophore modeling, docking, binding free energy calculation, dynamics simulation, and quantum mechanics. The gene expression analysis on endometriosis and endometrial cancer was performed and showed 108 shared upregulated genes in both conditions. Further construction of interaction network with 108 genes showed intercellular adhesion molecule 1 (ICAM1) to be a crucial molecule with a high degree of connectivity that influences vital mechanisms related to cancer pathways. We then generated ligand-based pharmacophore models using established ICAM1 inhibitors. Among the models, the ADRRR_8 pharmacophore exhibited a robust area under curve (AUC = 0.83), was employed to screen 1739 anti-cancer drugs. On screening, 421 anti-cancer drugs displayed ICAM1-inhibiting pharmacophore features. Further, the docking of 421 drugs with ICAM1 showed lanreotide (-7.80 kcal/mol) with better affinity than the reference ICAM1 inhibitor (-3.59 kcal/mol). Further validation though binding free energy and dynamics simulation of the lanreotide-ICAM1 complex showed a high binding affinity of -55.90 kcal/mol and contributed stable confirmation. According to quantum chemical calculations, lanreotide's electronic properties favour ICAM1 binding with highest occupied molecular orbital was -6.91 eV and lowest unoccupied molecular orbital was -3.93 eV. Our study supports using lanreotide to treat endometriosis, which could delay or prevent endometrial cancer. These predictions need to be confirmed and examined to determine the use of lanreotide in endometriosis treatment.

Cutting-edge Bioinformatics strategies for synthesizing Cyclotriazadisulfonamide (CADA) analogs in next-Generation HIV therapies

Cyclotriazadisulfonamide (CADA) is a macrocyclic compound known for its unique mechanism in inhibiting HIV infection by downregulating the CD4 T-cell receptor, a crucial entry point for the virus. Unlike other antiretrovirals, CADA exhibits activity against a wide range of HIV strains, as all HIV variants require CD4 binding for infection. Furthermore, CADA has shown a synergistic effect with clinically approved anti-HIV drugs, offering potential for enhanced therapeutic strategies (Vermeire & Schols, [65]). One proposed mechanism for CADA's inhibition of the CD4 receptor involves blocking the gates of the Sec61 channel, thereby preventing its translocation. However, CADA suffers from poor solubility and bioavailability. To address this, the study aimed to design CADA analogs with improved binding to the Sec61 channel, enhanced bioavailability, and reduced toxicity. The analogs were designed using SeeSAR, with Avogadro and Meeko used for 3D configuration and pseudoatom placement, respectively. AutoDock Vina version 1.2.4 was employed to predict the binding energies of these analogs. Of the 113 analogs designed, 93 demonstrated a more negative binding energy to the Sec61 channel compared to CADA. Structure-binding energy analyses were done to the top-binding analogs to show favorable structural modifications. Enzyme-ligand interactions were analyzed to elucidate the forces contributing to these binding energies. Additionally, 33 of the 113 analogs were deemed bioavailable using a bioavailability criteria specific for macrocycles. Toxicity predictions using PASS Online and StopTox identified analogs JGL023, JGL024, JGL032, and JGL047 as potential drug candidates. Molecular dynamics simulations using Gromacs-2020.4 revealed that JGL023 and JGL032 exhibited the most favorable binding to the Sec61 channel, as determined by evaluating ligand and residue flexibility, compactness, contact frequency, motion pathways, free energy, and other relevant parameters. Synthetic routes for these four analogs were proposed for future studies. The results of this study offer a new perspective on developing drugs to inhibit HIV entry.

Drug repositioning for rosacea disease: Biological TARGET identification, molecular docking, pharmacophore mapping, and molecular dynamics analysis

Rosacea is a chronic dermatological condition that currently lacks a clear treatment approach due to an uncomprehensive knowledge of its pathogenesis. The main obstacle lies in understanding its etiology and the mode of action of the different drugs used. This study aims to clarify these aspects by employing drug repositioning. Using an in silico approach, we performed a transcriptomic analysis comparing samples from individuals with diverse types of rosacea to those from healthy controls to identify genes deregulated in this disease. Subsequently, we realized molecular docking and molecular dynamics studies to assess the binding affinity of drugs currently used to treat rosacea and drugs that target proteins interacting with, and thus affecting, proteins deregulated in rosacea. Our findings revealed that the downregulation of SKAP2 and upregulation of S100A7A in rosacea, could be involved in the pathogenesis of the disease. Furthermore, considering the drugs currently used for rosacea management, we demonstrated stable interactions between isotretinoin and BFH772 with SKAP2, and permethrin and PAC-14028 with S100A7A. Similarly, considering drugs targeting SKAP2 and S100A7A interactome proteins, we found that pitavastatin and dasatinib exert stable interactions with SKAP2, and lovastatin and tirbanibulin with S100A7A. In addition, we determine that the types of bonds involved in the interactions were different in SKAP2 from S100A7A. The drug-SKAP2 interactions are hydrogen bonds, whereas the drug-S100A7A interactions are of the hydrophobic type. In conclusion, our study provides evidence for the possible contribution of SKAP2 and S100A7A to rosacea pathology. Furthermore, it provides significant information on the molecular interactions between drugs and these proteins, highlighting the importance of considering structural features and binding interactions in the design of targeted therapies for skin disorders such as rosacea.

Discovering novel targets of abscisic acid using computational approaches

Abscisic acid (ABA) is a crucial plant hormone that is naturally produced in various mammalian tissues and holds significant potential as a therapeutic molecule in humans. ABA is selected for this study due to its known roles in essential human metabolic processes, such as glucose homeostasis, immune responses, cardiovascular system, and inflammation regulation. Despite its known importance, the molecular mechanism underlying ABA's action remain largely unexplored. This study employed computational techniques to identify potential human ABA receptors. We screened 64 candidate molecules using online servers and performed molecular docking to assess binding affinity and interaction types with ABA. The stability and dynamics of the best complexes were investigated using molecular dynamics simulation over a 100 ns time period. Root mean square fluctuations (RMSF), root mean square deviation (RMSD), solvent-accessible surface area (SASA), radius of gyration (Rg), free energy landscape (FEL), and principal component analysis (PCA) were analyzed. Next, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method was employed to calculate the binding energies of the complexes based on the simulated data. Our study successfully pinpointed four key receptors responsible for ABA signaling (androgen receptor, glucocorticoid receptor, mineralocorticoid receptor, and retinoic acid receptor beta) that have a strong affinity for binding with ABA and remained structurally stable throughout the simulations. The simulations with Hydralazine as an unrelated ligand were conducted to validate the specificity of the identified receptors for ABA. The findings of this study can contribute to further experimental validation and a better understanding of how ABA functions in humans.

Deciphering the pH-dependent oligomerization of aspartate semialdehyde dehydrogenase from Wolbachia endosymbiont of Brugia malayi: An in vitro and in silico approaches

The enzyme aspartate semialdehyde dehydrogenase (ASDH) plays a pivotal role in the amino acid biosynthesis pathway, making it an attractive target for the development of new antimicrobial drugs due to its absence in humans. This study aims to investigate the presence of ASDH in the filarial parasite Wolbachia endosymbiont of Brugia malayi (WBm) using both in vitro and in silico approaches. The size exclusion chromatography (SEC) and Native-PAGE analysis demonstrate that WBm-ASDH undergoes pH-dependent oligomerization and dimerization. To gain a deeper understanding of this phenomenon, the modelled monomer and dimer structures were subjected to pH-dependent dynamics simulations in various conditions. The results reveal that residues Val240, Gln161, Thr159, Tyr160, and Trp316 form strong hydrogen bond contacts in the intersurface area to maintain the structure in the dimeric form. Furthermore, the binding of NADP+ induces conformational changes, leading to an open or closed conformation in the structure. Importantly, the binding of NADP+ does not disturb either the dimerization or oligomerization of the protein, a finding confirmed through both in vitro and in silico analysis. These findings shed light on the structural characteristics of WBm-ASDH and offer valuable insights for the development of new inhibitors specific to WBm, thereby contributing to the development of potential therapies for filarial parasitic infections.

Structural modifications and kinetic effects of KRAS interactions with HRAS and NRAS: an in silico comparative analysis of KRAS mutants

The RAS genes which code for KRAS, HRAS, and NRAS are three of the most frequently mutated oncogenes responsible for cancer deaths. Tumorigenesis is one of the most significant outcomes of deregulation of RAS GTPases. Although the structures have been extensively studied, there is still more to be discovered about the actual binding conformations of the three isoforms, especially when mutated, to design an inhibitory drug. Recent studies have identified important interactions between the three isoforms that affect the oncogenic strength of the others when they are mutated. In this study, we utilize molecular dynamics simulations to examine the modifications of the structural property, mechanism, and kinetic energy of KRAS when interacting individually and with HRAS and NRAS. Notably, we found that WT-KRAS' orientation when bound to WT-HRAS vs. WT-NRAS is rotated 180°, with mutants demonstrating a similar binding pattern. The binding sites of the isoforms with KRAS share similarities with those involved in the GDP/GTP active site and site of KRAS dimerization. Thus, the isoform interaction can serve as an inhibitory method of KRAS actions. This study advances the understanding of inhibiting RAS-driven cancers through a novel isoform interaction approach only recently discovered, which has been proven to be an effective alternate therapeutic approach. We developed a blueprint of the interaction which would be beneficial in the development of KRAS mutant-specific and pan-KRAS mutant inhibitory drugs that mimic the isoform interactions. Our results support the direct interaction inhibition mechanism of mutant KRAS when bound to WT-HRAS and WT-NRAS by the isoforms' hypervariable region binding to the G-domain of KRAS. Furthermore, our results support the approach of reducing the effects of oncogenic KRAS by altering the concentration of the isoforms or a drug alternative based on the overall structural and kinetic stability, as well as the binding strength of the mutant-isoform complexes.

Integrated metabolomics and serum-feces pharmacochemistry-based network pharmacology to reveal the mechanisms of an herbal prescription against ulcerative colitis

BACKGROUND

CDD-2103 is an herbal prescription used to treat ulcerative colitis (UC). This study aimed to uncover its mechanism by integrating metabolomics and serum-feces pharmacochemistry-based network pharmacology.

METHODS

A DSS-induced chronic colitis mice model was used to evaluate the anti-colitis effect of CDD-2103. Serum and feces metabolomics were conducted to identify differential metabolites and pathways. In the serum-feces pharmacochemistry study, biological samples were collected from rats treated with CDD-2103. Then, network pharmacology was utilized to predict the targets of the identified compounds. Critical genes were extracted through the above-integrated analysis. The interactions between targets, CDD-2103, and its compounds were validated through molecular docking, immunoblotting, and enzyme activity assays.

RESULTS

CDD-2103 alleviated ulcerous symptoms and colonic injuries in colitis mice. Metabolomics study identified differential metabolites associated with tryptophan, glycerophospholipid, and linoleic acid metabolisms. The serum-feces pharmacochemistry study revealed twenty-three compounds, which were subjected to network pharmacology analysis. Integration of these results identified three key targets (AHR, PLA2, and PTGS2). Molecular docking showed strong affinities between the compounds and targets. PTGS2 was identified as a hub gene targeted by most CDD-2103 compounds. Immunoblotting and enzyme activity assays provided further evidence that CDD-2103 alleviates UC, potentially through its inhibitory effect on cyclooxygenase-2 (COX-2, encoded by PTGS2), with alkaloids and curcuminoids speculated as crucial anti-inflammatory compounds.

CONCLUSION

This integrated strategy reveals the mechanism of CDD-2103 and provides insights for developing herbal medicine-based therapies for UC.

Marine fungal diversity unlocks potent antivirals against monkeypox through methyltransferase inhibition revealed by molecular dynamics and free energy landscape

The escalating threat posed by the Monkeypox virus (MPXV) to global health necessitates the urgent discovery of effective antiviral agents, as there are currently no specific drugs available for its treatment, and existing inhibitors are hindered by toxicity and poor pharmacokinetic profiles. This study aimed to identify potent MPXV inhibitors by screening a diverse library of small molecule compounds derived from marine fungi, focusing on the viral protein VP39, a key methyltransferase involved in viral replication. An extensive virtual screening process identified four promising compounds-CMNPD15724, CMNPD28811, CMNPD30883, and CMNPD18569-alongside a control molecule. Rigorous evaluations, including re-docking, molecular dynamics (MD) simulations, and hydrogen bond analysis, were conducted to assess their inhibitory potential against MPXV VP39. CMNPD15724 and CMNPD30883, in particular, demonstrated a superior binding affinity and stable interactions within the target protein's active site throughout the MD simulations, suggesting a capacity to overcome the limitations associated with sinefungin. The stability of these VP39-compound complexes, corroborated by MD simulations, provided crucial insights into the dynamic behavior of these interactions. Furthermore, Principal Component Analysis (PCA) based free energy landscape assessments offered a detailed understanding of the dynamic conformational changes and energetic profiles underlying these compounds' functional disruption of VP39. These findings establish CMNPD15724, CMNPD28811, CMNPD30883, and CMNPD18569 as promising MPXV inhibitors and highlight marine fungi as a valuable source of novel antiviral agents. These compounds represent potential candidates for further experimental validation, advancing the development of safer and more effective therapeutic options to combat this emerging viral infection.

Molecular insights into the interactions between PEG carriers and drug molecules from Celastrus hindsii: a multi-scale simulation study

Efficient drug delivery is crucial for the creation of effective pharmaceutical treatments, and polyethylene glycol (PEG) carriers have been emerged as promising candidates for this purpose due to their bio-compatibility, enhancement of drug solubility, and stability. In this study, we utilized molecular simulations to examine the interactions between PEG carriers and selected drug molecules extracted from Celastrus hindsii: Hindsiilactone A, Hindsiiquinoflavan B, Maytenfolone A, and Celasdin B. The simulations provided detailed insights into the binding affinity, stability, and structural properties of these drug molecules when complexed with PEG carriers. A multi-scale approach combining density functional theory (DFT), extended tight-binding (xTB), and molecular dynamics (MD) simulations was conducted to investigate both unbound and bound states of PEG/drug systems. The results from DFT and xTB calculations revealed that the unbound complex has an unfavorable binding free energy, primarily due to negative contributions of delta solvation free energy and entropy. The MD simulations provided more detailed insights into the interactions between PEG and drug molecules in water solutions. By integrating the findings from the multi-scale simulations, a comprehensive picture of the unbound and bound states of PEG and drug systems were obtained. This information is valuable for understanding the molecular mechanisms governing the binding of drugs in PEG-based delivery platforms, and it contributes to the rational design and optimization of these systems.

Integrating pan-genome and reverse vaccinology to design multi-epitope vaccine against Herpes simplex virus type-1

Herpes simplex virus type-1 (HSV-1), the etiological agent of sporadic encephalitis and recurring oral (sometimes genital) infections in humans, affects millions each year. The evolving viral genome reduces susceptibility to existing antivirals and, thus, necessitates new therapeutic strategies. Immunoinformatics strategies have shown promise in designing novel vaccine candidates in the absence of a clinically licensed vaccine to prevent HSV-1. However, to encourage clinical translation, the HSV-1 pan-genome was integrated with the reverse-vaccinology pipeline for rigorous screening of universal vaccine candidates. Viral targets were screened from 104 available complete genomes. Among 364 proteins, envelope glycoprotein D being an outer membrane protein with a high antigenicity score (> 0.4) and solubility (> 0.6) was selected for epitope screening. A total of 17 T-cell and 4 B-cell epitopes with highly antigenic, immunogenic, non-toxic properties and high global population coverage were identified. Furthermore, 8 vaccine constructs were designed using different combinations of epitopes and suitable linkers. VC-8 was identified as the most potential vaccine candidate regarding chemical and structural stability. Molecular docking revealed high interactive affinity (low binding energy: - 56.25 kcal/mol) of VC-8 with the target elicited by firm intermolecular H-bonds, salt-bridges, and hydrophobic interactions, which was validated with simulations. Compatibility of the vaccine candidate to be expressed in pET-29(a) + plasmid was established by in silico cloning studies. Immune simulations confirmed the potential of VC-8 to trigger robust B-cell, T-cell, cytokine, and antibody-mediated responses, thereby suggesting a promising candidate for the future of HSV-1 prevention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04022-6.

Transcriptomic and proteomic investigations identify PI3K-akt pathway targets for hyperthyroidism management in rats via polar iridoids from radix Scrophularia

High-polarity iridoids from Radix Scrophulariae (R. Scrophulariae) offer a range of benefits, including anti-inflammatory, antioxidant, antitumour, antibacterial, antiviral, and antiallergic effects. Although previous studies have indicated the potential of R. Scrophulariae for hyperthyroidism prevention and treatment, the specific active compounds involved and their mechanisms of action are not fully understood. This study explored the effects of high-polarity iridoid glycosides from R. Scrophulariae on hyperthyroidism induced in rats by levothyroxine sodium. The experimental design included a control group, a hyperthyroidism model group, and a group treated with iridoid glycosides. Serum triiodothyronine (T3) and thyroxine (T4) levels were quantified using an enzyme-linked immunosorbent assay (ELISA). Transcriptomic and proteomic analyses were applied to liver samples to identify differentially expressed genes and proteins. These analyses were complemented by trend analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The effectiveness of key factors was further examined through molecular biology techniques. ELISA results indicated a notable increase in T3 and T4 in the hyperthyroid rats, which was significantly mitigated by treatment with iridoid glycosides. Transcriptomic analysis revealed 6 upregulated and 6 downregulated genes in the model group, showing marked improvement following treatment. Proteomic analysis revealed changes in 30 upregulated and 50 downregulated proteins, with improvements observed upon treatment. The PI3K-Akt signalling pathway was investigated through KEGG enrichment analysis. Molecular biology methods verified the upregulation of Spp1, Thbs1, PI3K, and Akt in the model group, which was reversed in the treatment group. This study revealed that highly polar iridoids from R. Scrophulariae can modulate the Spp1 gene and Thbs1 protein via the PI3K-Akt signalling pathway, suggesting a therapeutic benefit for hyperthyroidism and providing a basis for drug development targeting this condition.

Investigating the potential of mono-chalcone compounds in targeting breast cancer receptors through network pharmacology, molecular docking, molecular dynamics simulation, antiproliferative effects, and gene expressions

The study aims to investigate various aspects of synthesized mono-chalcone compounds 5 and 8 concerning breast cancer, including network pharmacology, molecular docking, molecular dynamics (MD) simulations, antiproliferative effects, and gene expressions. Initially, the compounds underwent a network pharmacology analysis targeting breast cancer-related targets, with MalaCards, SwissTargetPrediction, and PharmMapper identifying 70 breast cancer target receptors. Subsequently, protein-protein interaction (PPI) network analysis revealed two distinct target gene clusters. Survival analysis identified seven significant target genes following Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and Gene Ontology (GO) evaluation. Molecular docking and MD simulations were conducted on these seven target genes (AKT2, BRAF, ESR1, FGFR1, IGF1, IGF1R, and KIT), revealing that compound 8 exhibited the highest binding affinities, as well as better stability and compactness when interacting with the targeted proteins. Next, the compounds underwent cell viability assay and gene expression analysis to validate the in silico findings. Both compounds demonstrated the ability to suppress breast cancer proliferation, with compound 8 showing increased selectivity in targeting breast cancer cells while causing minimal harm to normal breast cells. The suppression of breast cancer cell proliferation was attributed to decreased expression levels of AKT2, BRAF, FGFR1, IGF1, IGF1R, KIT, and ESR1. Hence, the results provide insights into the molecular interaction responsible for the anti-breast cancer capabilities of mono-chalcone compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-03991-y.

Molecular Mechanism of Yangshen Maidong Decoction in the Treatment of Chronic Heart Failure based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulations

Chronic heart failure (CHF) is a complex multifactorial clinical syndrome leading to abnormal cardiac structure and function. The severe form of this ailment is characterized by high disability, high mortality, and morbidity. Worldwide, 2-17% of patients die at first admission, of which 17-45% die within 1 year of admission and >50% within 5 years. Yangshen Maidong Decoction (YSMDD) is frequently used to treat the deficiency and pain of the heart. The specific mechanism of action of YSMDD in treating CHF, however, remains unclear. Therefore, a network pharmacology-based strategy combined with molecular docking and molecular dynamics simulations was employed to investigate the potential molecular mechanism of YSMDD against CHF. The effective components and their targets of YSMDD and related targets of CHF were predicted and screened based on the public database. The network pharmacology was used to explore the potential targets and possible pathways that involved in YSMDD treated CHF. Molecular docking and molecular dynamics simulations were performed to elucidate the binding affinity between the YSMDD and CHF targets. Screen results, 10 main active ingredients, and 6 key targets were acquired through network pharmacology analysis. Pathway enrichment analysis showed that intersectional targets associated pathways were enriched in the Prostate cancer pathway, Hepatitis B pathway, and C-type lectin receptor signaling pathways. Molecular docking and molecular dynamics simulations analysis suggested 5 critical active ingredients have high binding affinity to the 5 key targets. This research shows the multiple active components and molecular mechanisms of YSMDD in the treatment of CHF and offers resources and suggestions for future studies.

Role of CSF1R 550th-tryptophan in kusunokinin and CSF1R inhibitor binding and ligand-induced structural effect

Binding affinity is an important factor in drug design to improve drug-target selectivity and specificity. In this study, in silico techniques based on molecular docking followed by molecular dynamics (MD) simulations were utilized to identify the key residue(s) for CSF1R binding affinity among 14 pan-tyrosine kinase inhibitors and 15 CSF1R-specific inhibitors. We found tryptophan at position 550 (W550) on the CSF1R binding site interacted with the inhibitors' aromatic ring in a π-π way that made the ligands better at binding. Upon W550-Alanine substitution (W550A), the binding affinity of trans-(-)-kusunokinin and imatinib to CSF1R was significantly decreased. However, in terms of structural features, W550 did not significantly affect overall CSF1R structure, but provided destabilizing effect upon mutation. The W550A also did not either cause ligand to change its binding site or conformational changes due to ligand binding. As a result of our findings, the π-π interaction with W550's aromatic ring could be still the choice for increasing binding affinity to CSF1R. Nevertheless, our study showed that the increasing binding to W550 of the design ligand may not ensure CSF1R specificity and inhibition since W550-ligand bound state did not induce significantly conformational change into inactive state.

Molecular docking and molecular dynamics simulation decoding molecular mechanism of EDCs binding to hERRγ

CONTEXT

Human estrogen-related receptor γ (hERRγ) is a key protein involved in various endocrines and metabolic signaling. Numerous environmental endocrine-disrupting chemicals (EDCs) can impact related physiological activities through receptor signaling pathways. Focused on hERRγ with 4-isopropylphenol, bisphenol-F (BPF), and BP(2,2)(Un) complexes, we executed molecular docking and multiple molecular dynamics (MD) simulations along with molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) and solvation interaction energy (SIE) calculation to study the detailed dynamical structural characteristics and interactions between them. Molecular docking showed that hydrogen bonds and hydrophobic interactions were the prime interactions to keep the stability of BPF-hERRγ and hERRγ-BP(2,2)(Un) complexes. Through MD simulations, we observed that all complexes reach equilibrium during the initial 50 ns of simulation, but these three EDCs lead to local structure changes in hERRγ. Energy results further identified key residues L268, V313, L345, and F435 around the binding pockets through CH-π, π-π, and hydrogen bonds interactions play an important stabilizing role in the recognition with EDCs. And most noticeable of all, hydrophobic methoxide groups in BP(2,2)(Un) is useful for decreasing the binding ability between EDCs and hERRγ. These results may contribute to evaluate latent diseases associated with EDCs exposure at the micro level and find potential substitutes.

METHOD

Autodock4.2 was used to conduct the molecular docking, sietraj program was performed to calculate the energy, and VMD software was used to visualize the structure. Amber18 was conducted to perform the MD simulation and other analyses.

PIM Kinases as Potential Biomarkers and Therapeutic Targets in Inflammatory Arthritides

The Proviral Integration site for the Moloney murine leukemia virus (PIM)-1 kinase and its family members (PIM-2 and PIM-3) regulate several cellular functions including survival, proliferation, and apoptosis. Recent studies showed their involvement in the pathogenesis of rheumatoid arthritis RA, while no studies are available on psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA). The main objective of this study is to assess the expression of PIM kinases in inflammatory arthritides, their correlation with proinflammatory cytokines, and their variation after treatment with biologic disease-modifying anti-rheumatic drugs or JAK inhibitors. We evaluated PIM-1, -2, and -3 expression at the gene and protein level, respectively, in the peripheral blood mononuclear cells and serum of patients with RA, PsA, axSpA, and healthy individuals (CTR). All the samples showed expression of PIM-1, -2, and -3 kinases both at the gene and protein level. PIM-1 was the most expressed protein, PIM-3 the least. PIM kinase levels differed between controls and disease groups, with reduced PIM-1 protein and increased PIM-3 protein in all disease samples compared to controls. No difference was found in the expression of these molecules between the three different pathologies. PIM levels were not modified after 6 months of therapy. In conclusion, our preliminary data suggest a deregulation of the PIM pathway in inflammatory arthritides. In-depth studies on the role of PIM kinases in this field are warranted.

Resistance gene-guided genome mining reveals the roseopurpurins as inhibitors of cyclin-dependent kinases

With the significant increase in the availability of microbial genome sequences in recent years, resistance gene-guided genome mining has emerged as a powerful approach for identifying natural products with specific bioactivities. Here, we present the use of this approach to reveal the roseopurpurins as potent inhibitors of cyclin-dependent kinases (CDKs), a class of cell cycle regulators implicated in multiple cancers. We identified a biosynthetic gene cluster (BGC) with a putative resistance gene with homology to human CDK2. Using targeted gene disruption and transcription factor overexpression in Aspergillus uvarum, and heterologous expression of the BGC in Aspergillus nidulans, we demonstrated that roseopurpurin C (1) is produced by this cluster and characterized its biosynthesis. We determined the potency, specificity, and mechanism of action of 1 as well as multiple intermediates and shunt products produced from the BGC. We show that 1 inhibits human CDK2 with a Kiapp of 44 nM, demonstrates selectivity for clinically relevant members of the CDK family, and induces G1 cell cycle arrest in HCT116 cells. Structural analysis of 1 complexed with CDK2 revealed the molecular basis of ATP-competitive inhibition.

Unlocking potential inhibitors for Bruton's tyrosine kinase through in-silico drug repurposing strategies

Bruton's tyrosine kinase (BTK) is a non-receptor protein kinase that plays a crucial role in various biological processes, including immune system function and cancer development. Therefore, inhibition of BTK has been proposed as a therapeutic strategy for various complex diseases. In this study, we aimed to identify potential inhibitors of BTK by using a drug repurposing approach. To identify potential inhibitors, we performed a molecular docking-based virtual screening using a library of repurposed drugs from DrugBank. We then used various filtrations followed by molecular dynamics (MD) simulations, principal component analysis (PCA), and Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA) analysis to further evaluate the binding interactions and stability of the top-ranking compounds. Molecular docking-based virtual screening approach identified several repurposed drugs as potential BTK inhibitors, including Eltrombopag and Alectinib, which have already been approved for human use. All-atom MD simulations provided insights into the binding interactions and stability of the identified compounds, which will be helpful for further experimental validation and optimization. Overall, our study demonstrates that drug repurposing is a promising approach to identify potential inhibitors of BTK and highlights the importance of computational methods in drug discovery.

Novel pyrrolone-fused benzosuberene MK2 inhibitors: synthesis, pharmacophore modelling, molecular docking, and anti-cancer efficacy evaluation in HNSCC cells

Head and neck Squamous Cell Carcinoma (HNSCC) is a growing concern worldwide and MAPKAPK2/MK2 (Mitogen-Activated Protein Kinase Activated Protein Kinase 2) is crucially involved in HNSCC progression. Increased disease burden and lacuna of targeted therapies require novel and safe pharmacological inhibitors to suppress the well-explored molecular targets in HNSCC. Here, we used dibromo-substituted benzosuberene synthesized from the mixture of α, β, γ-himachalenes and utilized as a precursor for the synthesis of Pyrrolone-fused benzosuberenes (PfBS) as MK2 inhibitors through aminocarbonylation approach in a single-pot reaction. The devised protocol provides a broad substrate scope, facile recovery, recyclability of Polystyrene-supported palladium (Pd@PS) nanoparticle catalyst, and fewer synthesis steps. In-silico molecular docking, pharmacophore modeling, and ADMET revealed MK2-inhibitory potential and drug-likeliness of PfBS analogues. Surface plasmon resonance (SPR) analysis revealed effective high binding affinity (KD) and kinetics of PfBS analogues with MK2. Additionally, the SPR-mediated in-solution inhibition assay established the MK2-inhibition properties of PfBS analogues through abrogation of MK2-Hsp27 interaction. Further, in-vitro studies validate the findings in HNSCC cells. PfBS analogues exhibited significant anti-proliferative effects on CAL 27 tongue squamous carcinoma cells and were found safe on IEC-6 intestinal epithelial cells. Moreover, immunofluorescence analysis and western-blot assays potentiated, that selected analogues inhibited the inflammatory cytokine TNF-α induced activation of MK2 on cellular and molecular levels in HNSCC cells. In conclusion, this study presents novel MK2-inhibitors and opens the avenue for further pre-clinical and clinical efficacy evaluation of developed PfBS analogues in the treatment of HNSCC.Communicated by Ramaswamy H. Sarma.