Computational targeting of allosteric site of MEK1 by quinoline-based molecules

An in silico analysis of the interaction of marine sponge-derived bioactive compounds with type 2 diabetes mellitus targets DPP-4 and PTP1B

Type 2 diabetes is a medical condition involving elevated blood glucose levels resulting from impaired or improper insulin utilization. As the number of type 2 diabetes cases increases each year, there is an urgent need to develop novel drugs having new targets and/or complementing existing therapeutic protocols. In this regard, marine sponge-derived compounds hold great potential due to their potent biological activity and structural diversity. In this study, a small library of 50 marine sponge-derived compounds were examined for their activity towards type 2 diabetes targets, namely dipeptidyl peptidase-4 (DPP-4) and protein tyrosine phosphatase 1B (PTP1B). The compounds were first subjected to molecular docking on protein models based on their respective co-crystal structures to assess binding free energies (BFE) and conformations. Clustering analysis yielded BFE that ranged from 24.54 kcal/mol to -9.97 kcal/mol for DPP-4, and from -4.98 kcal/mol to -8.67 kcal/mol for PTP1B. Interaction analysis on the top ten compounds with the most negative BFE towards each protein target showed similar intermolecular interactions and key interacting residues as in the previously solved co-crystal structure. These compounds were subjected to absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling to characterize drug-likeness and combining the results from these analyses, (S)-6'-debromohamacanthin B was identified as a potential multi-target inhibitor of DPP-4 and PTP1B, having favorable protein interaction, no Lipinski violations, good gastrointestinal (GI) tract absorption, blood-brain barrier (BBB) penetration, and no predicted toxicity. Finally, the interaction of (S)-6'-debromohamacanthin B with the two proteins was validated using molecular dynamics simulations over 100 ns through RMSD, radius of gyration, PCA, and molecular mechanics Poisson-Boltzmann surface area (MMPBSA) confirming favorable interactions with the respective proteins.

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.

Effects of F53 hotspot mutations on the molecular dynamics of MEK1 protein and the binding of its FDA-approved inhibitors

MEK1 (MAP2K1) could emerge as an oncogenic protein in the presence of certain mutations, and could be inhibited by FDA-approved drugs (trametinib, cobimetinib, binimetinib and selumetinib). However, how the mutations on MEK1's hotspot residue F53 affect the bindings of these therapeutic molecules remained largely unexplored. We performed molecular dynamics (MD) simulations with wild-type and mutated (F53L/V/C/I/Y) MEK1 structures in the presence and absence of these drugs and observed changes on the motion of MEK1. A longer duration in the lowest energy state conformation was observed during the simulations in the presence of F53 mutations. This was complemented by cross-correlated motions of amino acids of MEK1. More importantly, the binding affinities of inhibitors were affected. There was a marked reduction in the calculated binding affinity of trametinib in the presence of F53C mutation. On the other hand, the binding affinities of cobimetinib and selumetinib could overcome F53 mutations on MEK1. Binimetinib interestingly exhibited an increased binding affinity when F53C/I mutations were present. Taken together, our results provide a comprehensive perspective on the structural and drug-binding effects of observed mutations on the hotspot residue F53 within MEK1; warranting further research in stratifying F53 hotspot mutations for effective drug binding.

Exosomes derived from human umbilical cord mesenchymal stem cells decrease neuroinflammation and facilitate the restoration of nerve function in rats suffering from intracerebral hemorrhage

Exosomes derived from human umbilical cord mesenchymal stem cells (hUCMSC-ex) have become a hopeful substitute for whole-cell therapy due to their minimal immunogenicity and tumorigenicity. The present study aimed to investigate the hypothesis that hUCMSC-ex can alleviate excessive inflammation resulting from intracerebral hemorrhage (ICH) and facilitate the rehabilitation of the nervous system in rats. In vivo, hemorrhagic stroke was induced by injecting collagenase IV into the striatum of rats using stereotactic techniques. hUCMSC-ex were injected via the tail vein at 6 h after ICH model establishment at a dosage of 200 µg. In vitro, astrocytes were pretreated with hUCMSC-ex and then stimulated with hemin (20 μmol/mL) to establish an ICH cell model. The expression of TLR4/NF-κB signaling pathway proteins and inflammatory factors, including TNF-α, IL-1β, and IL-10, was assessed both in vivo and in vitro to investigate the impact of hUCMSC-ex on inflammation. The neurological function of the ICH rats was evaluated using the corner turn test, forelimb placement test, Longa score, and Bederson score on the 1st, 3rd, and 5th day. Additionally, RT-PCR was employed to examine the mRNA expression of TLR4 following hUCMSC-ex treatment. The findings demonstrated that hUCMSC-ex downregulated the protein expression of TLR4, NF-κB/P65, and p-P65, reduced the levels of pro-inflammatory cytokines TNF-α and IL-1β, and increased the expression of the anti-inflammatory cytokine IL-10. Ultimately, the administration of hUCMSC-ex improved the behavioral performance of the ICH rats. However, the results of PT-PCR indicated that hUCMSC-ex did not affect the expression of TLR4 mRNA induced by ICH, suggesting that hUCMSCs-ex may inhibit TLR4 translation rather than transcription, thereby suppressing the TLR4/NF-κB signaling pathway. We can conclude that hUCMSC-ex mitigates hyperinflammation following ICH by inhibiting the TLR4/NF-κB signaling pathway. This study provides preclinical evidence for the potential future application of hUCMSC-ex in the treatment of cerebral injury.

Integrated computational biophysics approach for drug discovery against Nipah virus

The Nipah virus (NiV) poses a pressing global threat to public health due to its high mortality rate, multiple modes of transmission, and lack of effective treatments. NiV glycoprotein G (NiV-G) emerges as a promising target for the discovery of NiV drugs because of its essential role in viral entry and membrane fusion. Therefore, in this study, we applied an integrated computational and biophysics approach to identify potential inhibitors of NiV-G within a curated dataset of Peruvian phytochemicals. The virtual screening results indicated that these compounds could represent a natural source of potential NiV-G inhibitors with ΔG values ranging from -8 to -11 kcal/mol. Among them, procyanidin B2, B3, B7, and C1 exhibited the highest binding affinities and formed the most molecular interactions with NiV-G. Molecular dynamics simulations revealed the induced-fit mechanism of NiV-G pocket interaction with these procyanidins, primarily driven by its hydrophobic nature. Non-equilibrium free energy calculations were used to determine binding affinities, highlighting Procyanidin B3 and B2 as the ligands with the most substantial interactions. In general, this work underscores the potential of Peruvian phytochemicals, particularly procyanidins B2, B3, B7, and C1, as lead compounds for developing anti-NiV drugs through an integrated computational biophysics approach.

Discovery of Palbociclib as a potent c-Myc G4 stabilizer for lung cancer treatment using molecular docking, molecular dynamics simulation, and in vitro activity evaluation

Despite significant progress in lung cancer treatment, this disease remains a prevalent and serious global malignancy, leading to high rates of illness and death. Urgent research is needed to discover new or alternative therapies that can improve clinical outcomes for lung cancer patients. In our study, we successfully demonstrated the effectiveness of Palbociclib, a CDK4/6 inhibitor, in suppressing the growth of lung cancer cells. The IC50 values obtained were 11.00 μM and 11.74 μM for H1299 and A549 cells, respectively. Furthermore, our findings indicate that Palbociclib may possess strong c-Myc G4 stabilizing properties by significantly reducing both protein and mRNA expression levels of c-Myc. Additionally, Palbociclib induces apoptosis and causes cell cycle arrest at the G2/M phase in two cells. Through circular dichroism (CD), molecular docking, and molecular dynamics (MD) simulation, we have provided evidence that Palbociclib enhances the structural stability of c-Myc G4 while exhibiting a high binding affinity to its ligand's binding site on c-Myc G4. These results suggest that Palbociclib holds promise as a novel c-Myc G4 stabilizer for treating cancers associated with abnormal c-Myc activity; further optimization and development are warranted.

Molecular targets and mechanisms of Sijunzi decoction in the treatment of Parkinson's disease: evidence from network pharmacology, molecular docking, molecular dynamics simulation, and experimental validation

Aim

To explore the molecular mechanism of Sijunzi Decoction (SJZD) in the treatment of Parkinson's disease (PD) through the application of network pharmacology, molecular docking, and molecular dynamics simulations, complemented by experimental verification.

Methods

The BATMAN-TCM, GeneCards, and DisGeNet databases were searched to screen the active components and therapeutic targets of SJZD. Cytoscape (3.7.1) was used to create a network diagram of the components and targets. The STRING platform was used to construct a protein-protein interaction (PPI) network. The Bioconductor database and RX64 (4.0.0) software were used to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the core target genes. The binding sites and binding energies between SJZD active components and the target were analyzed by molecular docking and dynamic simulation. Finally, the therapeutic effect and mechanism of SJZD were verified by Cell Counting Kit-8 (CCK-8) and Western blotting (WB).

Results

This research identified 188 active compounds in SJZD, 1568 drug targets, 2069 PD targets, and 451 intersection targets related to PD. According to network analysis, Adenosine Triphosphate, Tridecanoic Acid, Hexadecanoic Acid, Pentadecanoic Acid, and Adenosine were identified as the core components of SJZD in the treatment of PD. The five targets with the highest Degree values in the PPI network were AKT1, INS, TNF, IL-6, and TP53. The GO and KEGG enrichment analyses, in turn, determined that the administration of SJZD for the treatment of PD may engage processes such as xenobiotic stimulation and biological stimulus response. Furthermore, AGE-RAGE and cAMP signaling pathways related to diabetic complications may be involved. Molecular docking and kinetic simulations showed that IL-6 and AKT1 bind best to Adenosine. Experimental results showed that SJZD significantly reduced 6-OHDA-induced apoptosis of SH⁃SY5Y cells by activating the PI3K/AKT signaling pathway and regulating the expression of apoptosis factors such as Bcl⁃2 and Bax.

Conclusion

SJZD is essential in the processes of apoptosis and neuronal protection, acting through various components that target multiple pathways. Notably, the PI3K/AKT pathway is a verified SJZD-PD target, providing a reference for clinical precision drug use for PD.

High-throughput virtual screening of potential inhibitors of GPR52 using docking and biased sampling method for Huntington's disease therapy

Huntington's disease (HD) is a rare and progressive neurodegenerative disorder caused by polyglutamine (poly-Q) mutations of the huntingtin (HTT) gene resulting in chorea, cognitive, and psychiatric dysfunctions. Being a monogenic condition, reducing the levels of the mutated huntingtin protein (mHTT) holds promise as an effective therapeutic approach. GPR52, an orphan G-protein coupled receptor (GPCR), enriched in the striatum, is a novel target for slowing down the progression of HD by lowering the mHTT levels. Therefore, the study focuses on identifying potent small-molecule inhibitors for GPR52 using a combination of robust high-throughput virtual screening (HTVS) and pharmacokinetics profiling followed by fast pulling of ligand (FPL) and umbrella sampling (US) simulations. Initially, screening a library of 2,36,545 compounds was done against the binding pocket of GPR52. Based on binding affinity, stereochemical and non-bonded interactions, and pharmacokinetic profiling, 50 compounds were shortlisted. Selected hit compounds 1, 2, and 3 were subjected to FPL simulations with applied external bias potential to investigate their unique dissociation pathways and intermolecular interactions over time. Subsequently, the US simulations were performed on the selected hit compounds to estimate their binding free energy (ΔG). The analysis of the trajectories obtained from simulations revealed that the residues TYR34, TYR185, GLY187, ASP188, ILE189, SER299, PHE300, and THR303 within the active site of GPR52 were significant for efficient ligand binding through the formation of various hydrogen bond interactions and hydrophobic contacts. Out of the three hit compounds, compound 3 had the lowest ΔG of - 20.82 ± 0.44 kcal/mol. The study identified compounds 1, 2, and 3 as potential molecules that can be developed as GPR52 inhibitors holding promise for lowering mHTT levels.

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.

A discovery of potent kaempferol derivatives as multi-target medicines against diabetes as well as bacterial infections: an in silico approach

Flavonoids demonstrate beneficial effects on human health because flavonoids contain important biological properties. Kaempferol is a flavonol, type of flavonoid found in eatable plants and in plants usually employed in ancient drugs (Moringa oleifera, Tilia spp., fern genus spp. and gingko etc.). Some medicinal studies have shown that the use of foods full of kaempferol decreases the risk of many (cancer, vascular) diseases. All the data of 50 kaempferol derivatives were collected from PubChem database. Through Schrödinger software, 3D-QSAR study was performed for 50 compounds by using method of field base. Conformer of kaempferol derivatives was docked against anti-diabetic, anti-microbial co-crystal structures and protein. To monitor the best anti-diabetic and antibacterial agent, particular kaempferol derivatives were downloaded from PubChem database. Virtual screening by molecular docking provided four lead compounds with four different proteins. These hit compounds were found to be potent inhibitor for diabetic enzymes alpha-amylase and DPP IV and had the potential to suppress DNA gyrase and dihydrofolate reductase synthesis. Molecular dynamic simulation of docked complexes evaluates the value of root mean square fluctuation by iMOD server. Kaempferol 3-O-alpha-L-(2, 3-di-Z-p-coumaroyl) rhamnoside (42) compound used as anti-diabetic and kaempferol 3-O-gentiobioside (3) as antibacterial with good results can be used for drug discovery.

Identification of selective dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) inhibitors and their effects on tau and microtubule

The overexpression of dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), commonly observed in neurodegenerative diseases like Alzheimer's disease (AD) and Down syndrome (DS), can induce the formation of neurofibrillary tangles (NFTs) and amyloid plaques. Hence, designing a selective DYRK1A inhibitor would result in a promising small molecule for treating neurodegenerative diseases. Developing selective inhibitors for DYRK1A has been a difficult challenge due to the highly preserved ATP-binding site of protein kinases. In this study, we employed a structure-based virtual screening (SBVS) campaign targeting DYRK1A from a database containing 1.6 million compounds. Enzymatic assays were utilized to verify inhibitory properties, confirming that Y020-3945 and Y020-3957 showed inhibitory activity towards DYRK1A. In particular, the compounds exhibited high selectivity for DYRK1A over a panel of 120 kinases, reduced the phosphorylation of tau, and reversed the tubulin polymerization for microtubule stability. Additionally, treatment with the compounds significantly reduced the secretion of inflammatory cytokines IL-6 and TNF-α activated by DYRK1A-assisted NFTs and Aβ oligomers. These identified inhibitors possess promising therapeutic potential for conditions associated with DYRK1A in neurodegenerative diseases. The results showed that Y020-3945 and Y020-3957 demonstrated structural novelty compared to known DYRK1A inhibitors, making them a valuable addition to developing potential treatments for neurodegenerative diseases.

Cuproptosis gene-related, neural network-based prognosis prediction and drug-target prediction for KIRC

BACKGROUND

Kidney renal clear cell carcinoma (KIRC), as a common case in renal cell carcinoma (RCC), has the risk of postoperative recurrence, thus its prognosis is poor and its prognostic markers are usually based on imaging methods, which have the problem of low specificity. In addition, cuproptosis, as a novel mode of cell death, has been used as a biomarker to predict disease in many cancers in recent years, which also provides an important basis for prognostic prediction in KIRC. For postoperative patients with KIRC, an important means of preventing disease recurrence is pharmacological treatment, and thus matching the appropriate drug to the specific patient's target is also particularly important. With the development of neural networks, their predictive performance in the field of medical big data has surpassed that of traditional methods, and this also applies to the field of prognosis prediction and drug-target prediction.

OBJECTIVE

The purpose of this study is to screen for cuproptosis genes related to the prognosis of KIRC and to establish a deep neural network (DNN) model for patient risk prediction, while also developing a personalized nomogram model for predicting patient survival. In addition, sensitivity drugs for KIRC were screened, and a graph neural network (GNN) model was established to predict the targets of the drugs, in order to discover potential drug action sites and provide new treatment ideas for KIRC.

METHODS

We used the Cancer Genome Atlas (TCGA) database, International Cancer Genome Consortium (ICGC) database, and DrugBank database for our study. Differentially expressed genes (DEGs) were screened using TCGA data, and then a DNN-based risk prediction model was built and validated using ICGC data. Subsequently, the differences between high- and low-risk groups were analyzed and KIRC-sensitive drugs were screened, and finally a GNN model was trained using DrugBank data to predict the relevant targets of these drugs.

RESULTS

A prognostic model was built by screening 10 significantly different cuproptosis-related genes, the model had an AUC of 0.739 on the training set (TCGA data) and an AUC of 0.707 on the validation set (ICGC data), which demonstrated a good predictive performance. Based on the prognostic model in this paper, patients were also classified into high- and low-risk groups, and functional analyses were performed. In addition, 251 drugs were screened for sensitivity, and four drugs were ultimately found to have high sensitivity, with 5-Fluorouracil having the best inhibitory effect, and subsequently their corresponding targets were also predicted by GraphSAGE, with the most prominent targets including Cytochrome P450 2D6, UDP-glucuronosyltransferase 1A, and Proto-oncogene tyrosine-protein kinase receptor Ret. Notably, the average accuracy of GraphSAGE was 0.817 ± 0.013, which was higher than that of GAT and GTN.

CONCLUSION

Our KIRC risk prediction model, constructed using 10 cuproptosis-related genes, had good independent prognostic ability. In addition, we screened four highly sensitive drugs and predicted relevant targets for these four drugs that might treat KIRC. Finally, literature research revealed that four drug-target interactions have been demonstrated in previous studies and the remaining targets are potential sites of drug action for future research.

In Vitro Antioxidant and In Vivo Hepatoprotective Properties of Wissadula periplocifolia Extract

Wissadula periplocifolia (L.) Thwaites is a traditional medicinal plant belonging to the family Malvaceae, used in folk medicine for inflamed snake bites and bee stings. The current study was designed to investigate the in vitro antioxidant and in vivo anti-inflammatory and hepatoprotective activities of 80% ethanol extract of W. periplocifolia and its different fractions. The crude ethanolic extract (CEE) was then serially fractionated with petroleum ether fraction (PEF), chloroform fraction (CHF), and aqueous fraction (AQF). The antioxidant activity was assessed using 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical assay, anti-inflammatory activity was determined in the xylene-induced ear edema model, and hepatoprotective activity was measured in the paracetamol-induced hepatic injury model. PEF showed a significant scavenging effect with an IC50 value of 33.5 μg/mL, followed by CEE (IC50 = 42.2 μg/mL), CHF (IC50 = 77 μg/mL), and AQF (IC50 = 80 μg/mL), compared to standard butylated hydroxytoluene (IC50 = 14.8 μg/mL). Both doses of CEE (250 and 500 mg/kg) could reduce ear edema by 41.3 and 50%, respectively, compared to standard diclofenac sodium (76.09%). Moreover, CEE significantly reduces the elevated liver enzymes (ALT, AST, and ALP), compared to control. Nevertheless, it elevated blood protein and reduced the blood bilirubin level (p < 0.01), compared to control. Histopathological studies also indicated significant protection of the liver from paracetamol-induced liver damage. In conclusion, W. periplocifolia could be a good source of antioxidant and hepatoprotective phytochemicals; meanwhile, toxicological and pharmacokinetic studies are recommended.

FormulationAI: a novel web-based platform for drug formulation design driven by artificial intelligence

Today, pharmaceutical industry faces great pressure to employ more efficient and systematic ways in drug discovery and development process. However, conventional formulation studies still strongly rely on personal experiences by trial-and-error experiments, resulting in a labor-consuming, tedious and costly pipeline. Thus, it is highly required to develop intelligent and efficient methods for formulation development to keep pace with the progress of the pharmaceutical industry. Here, we developed a comprehensive web-based platform (FormulationAI) for in silico formulation design. First, the most comprehensive datasets of six widely used drug formulation systems in the pharmaceutical industry were collected over 10 years, including cyclodextrin formulation, solid dispersion, phospholipid complex, nanocrystals, self-emulsifying and liposome systems. Then, intelligent prediction and evaluation of 16 important properties from the six systems were investigated and implemented by systematic study and comparison of different AI algorithms and molecular representations. Finally, an efficient prediction platform was established and validated, which enables the formulation design just by inputting basic information of drugs and excipients. FormulationAI is the first freely available comprehensive web-based platform, which provides a powerful solution to assist the formulation design in pharmaceutical industry. It is available at https://formulationai.computpharm.org/.

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.

Molecular Dynamics Simulation Study of the Selective Inhibition of Coagulation Factor IXa over Factor Xa

Thromboembolic disorders, arising from abnormal coagulation, pose a significant risk to human life in the modern world. The FDA has recently approved several anticoagulant drugs targeting factor Xa (FXa) to manage these disorders. However, these drugs have potential side effects, leading to bleeding complications in patients. To mitigate these risks, coagulation factor IXa (FIXa) has emerged as a promising target due to its selective regulation of the intrinsic pathway. Due to the high structural and functional similarities of these coagulation factors and their inhibitor binding modes, designing a selective inhibitor specifically targeting FIXa remains a challenging task. The dynamic behavior of protein-ligand interactions and their impact on selectivity were analyzed using molecular dynamics simulation, considering the availability of potent and selective compounds for both coagulation factors and the co-crystal structures of protein-ligand complexes. Throughout the simulations, we examined ligand movements in the binding site, as well as the contact frequencies and interaction fingerprints, to gain insights into selectivity. Interaction fingerprint (IFP) analysis clearly highlights the crucial role of strong H-bond formation between the ligand and D189 and A190 in the S1 subsite for FIXa selectivity, consistent with our previous study. This dynamic analysis also reveals additional FIXa-specific interactions. Additionally, the absence of polar interactions contributes to the selectivity for FXa, as observed from the dynamic profile of interactions. A contact frequency analysis of the protein-ligand complexes provides further confirmation of the selectivity criteria for FIXa and FXa, as well as criteria for binding and activity. Moreover, a ligand movement analysis reveals key interaction dynamics that highlight the tighter binding of selective ligands to the proteins compared to non-selective and inactive ligands.

Active site determination of novel plant versatile peroxidase extracted from Citrus sinensis and bioconversion of β-naphthol

A ligninolytic peroxidase called versatile peroxidase, VP, (EC 1.11.1.16) is an iron-containing metalloenzyme. The most distinctive feature of this enzyme is its composite molecular framework, which combines lignin peroxidase's capacity to oxidize compounds with high-redox potential with manganese peroxidase's capacity to oxidize Mn2+ to Mn3+. In this study, we have extracted amino acid sequences from the Citrus sinensis source and subjected them to various computation tools to visualize the insight secondary and 3D structure, physicochemical properties, and validation of the structure which have not been studied so far to further investigate the catalytic efficiency and effectiveness of VP. The binding energies of HEME and HEME C (HEC) ligands with produced PDB (6rqf.1. A) have been also assessed, analyzed, and confirmed utilizing AutoDock. Binding energies were calculated using the AutoDock and validated by MD simulation using SCHRODINGER DESMOND. Most stable confirmation was achieved through a protein-ligand interaction study. Bio-technological use of VP in the biotransformation of β-naphthol has also been studied. The findings in the current study will have a substantial impact on proteomics, biochemistry, biotechnology, and possible uses of versatile peroxidase in the bio-remediation of different toxic organic compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03758-x.

Identification of potential mutational hotspots in serratiopeptidase to address its poor pH tolerance issue

Serratiopeptidase is the multifunctionality metalloendopeptidase extensively employed in biopharmaceutical and industrial biotechnology. Despite its poor pH tolerance, serratiopeptidase must withstand the highly acidic environment of the gastrointestinal tract to be used as a potent anti-inflammatory and analgesic medication. In earlier studies, post-translational deamination related mutations showed alteration in the net charge of protein's surface. Therefore, the current study aimed to enhance the acid resistance of serratiopeptidase via implementing computational interventions to screen out the most stable mutational hotspot. The methodology used in this study is as follows: (a) Higher accessibility to surface (b) 4 Å away from active site region to avoid interference with its proteolytic activity, and (c) By converting non-conserved amide residues to acidic residues. A docking study has been conducted to establish the substrate specificity and binding affinity to native and mutant proteins. The docking outcomes were then validated using molecular dynamic simulations to clarify each mutant's molecular stability and conformation while preserving their activity. The results showed that N412D is the best-screened mutant with negative electrostatic potential that can alter the overall charge on the protein's surface with increased H+ ions. Alteration in overall charge leads to protein surface more acidic that causes a common ion effect in stomach pH and act as a buffer which could stabilize the serratiopeptidase amid extreme pH.Communicated by Ramaswamy H. Sarma.

Elucidating the mutational impact in causing Niemann-Pick disease type C: an in silico approach

Niemann-Pick disease type C is a rare autosomal recessive of lysosomal storage disorder characterized by impaired intracellular lipid transport and has a tendency to accumulate the fatty acids and glycosphingolipids in a variety of neurovisceral tissues. This work includes computational tools to deciphere the mutational effect in NPC protein. The study initiated with the collection of 471 missense mutations from various databases, which were then analyzed using computational tools. The mutations (G549V, F703S, Q775P and L1244P) were said to be disease associated, altering the biophysical properties, in highly conserved regions and reduces the stability using several in silico methods and were subjected to molecular docking analysis. To analyze the ligand (Itraconazole: a small molecule of antifungal drug class, which is known to inhibit cholesterol export from lysosomes) activity Molecular docking study was performed for all the complex proteins. The average binding affinity was taken and found to be -10.76 kcal/mol (native) and -11.06 kcal/mol (Q775P was located in transmembrane region IV which impacts the sterol-sensing domain of the NPC1 protein and associated with a severe infantile neurological form). Finally, molecular dynamic simulation was performed in duplicate and trajectories were built for the backbone of the RMSD, RMSF, the number of intramolecular hydrogen bonds, the radius of gyration and the SSE percent for both the complex proteins. This work contributes to understand the effectiveness and may provide an insight on the stability of the drug with the complex variant structures.Communicated by Ramaswamy H. Sarma.

Comprehensive analysis and validation reveal potential MYCN regulatory biomarkers associated with neuroblastoma prognosis

Neuroblastoma (NB) is an embryonic malignant tumor that occurs in the sympathetic nervous system. The treatment results of patients in the high-risk group are poor, and relapse and treatment failure can occur even with multiple combination treatments. The proto-oncogene MYCN is a BHLH Transcription Factor used as an independent prognostic factor for NB. The proportion of MYCN amplification in tumor tissues of high-risk patients reaches 40-50%. Hence, exploring new MYCN target genes is a meaningful approach in developing treatment for high-risk NB patients. The microarray datasets were obtained from Gene Expression Omnibus (GEO), and differentially expressed genes (DEGs) were identified. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and miRPathDB were used for enrichment analysis. STRING and Cytoscape were used to construct a protein-protein interaction (PPI) network and for modular analysis. The miRNet and NetworkAnalyst databases were used to predict and construct gene-miRNA and gene-TFs networks. The R2 database was used for expression, correlation, and prognostic analyses. The diagnostic value of the biomarkers was predicted by ROC analysis, and RT-qPCR was used to validate the identified hub genes. Finally, using specific MYCN siRNA and overexpressing plasmids, the correlation between the identified hub genes and MYCN was investigated. Our results showed that FBXO9, HECW2, MIB2, RNF19B, RNF213, TRIM36, and ZBTB16 are novel biomarkers that affect the prognosis of the NB patients. In addition, FBXO9, RNF19B, and TRIM36 were preliminarily confirmed as potential target genes of MYCN. Overall, FBXO9, HECW2, MIB2, RNF19B, RNF213, TRIM36, and ZBTB16 are expected to become novel biomarkers for the treatment of high-risk NB patients.Communicated by Ramaswamy H. Sarma.

Phylogenetic investigation of Gammaproteobacteria proteins involved in exogenous long-chain fatty acid acquisition and assimilation

Background

The incorporation of exogenous fatty acids into the cell membrane yields structural modifications that directly influence membrane phospholipid composition and indirectly contribute to virulence. FadL and FadD are responsible for importing and activating exogenous fatty acids, while acyltransferases (PlsB, PlsC, PlsX, PlsY) incorporate fatty acids into the cell membrane. Many Gammaproteobacteria species possess multiple homologs of these proteins involved in exogenous fatty acid metabolism, suggesting the evolutionary acquisition and maintenance of this transport pathway.

Methods

This study developed phylogenetic trees based on amino acid and nucleotide sequences of homologs of FadL, FadD, PlsB, PlsC, PlsX, and PlsY via Mr. Bayes and RAxML algorithms. We also explored the operon arrangement of genes encoding for FadL. Additionally, FadL homologs were modeled via SWISS-MODEL, validated and refined by SAVES, Galaxy Refine, and GROMACS, and docked with fatty acids via AutoDock Vina. Resulting affinities were analyzed by 2-way ANOVA test and Tukey's post-hoc test.

Results

Our phylogenetic trees revealed grouping based on operon structure, original homolog blasted from, and order of the homolog, suggesting a more ancestral origin of the multiple homolog phenomena. Our molecular docking simulations indicated a similar binding pattern for the fatty acids between the different FadL homologs.

General significance

Our study is the first to illustrate the phylogeny of these proteins and to investigate the binding of various FadL homologs across orders with fatty acids. This study helps unravel the mystery surrounding these proteins and presents topics for future research.

Identification of potential inhibitors against Alzheimer-related proteins in Cordyceps militaris ethanol extract: experimental evidence and computational analyses

Laboratory experiments were carried out to identify the chemical composition of Cordyceps militaris and reveal the first evidence of their Alzheimer-related potential. Liquid chromatography-mass spectrometry analysis identified 21 bioactive compounds in the ethanol extract (1-21). High-performance liquid chromatography quantified the content of cordycepin (0.32%). Bioassays revealed the overall anti-Alzheimer potential of the extract against acetylcholinesterase (IC50 = 115.9 ± 11.16 µg mL-1). Multi-platform computations were utilized to predict the biological inhibitory effects of its phytochemical components against Alzheimer-related protein structures: acetylcholinesterase (PDB-4EY7) and β-amyloid protein (PDB-2LMN). In particular, 7 is considered as a most effective inhibitor predicted by its chemical stability in dipole-based environments (ground state - 467.26302 a.u.; dipole moment 11.598 Debye), inhibitory effectiveness (DS ¯ - 13.6 kcal mol-1), polarized compatibility (polarizability 25.8 Å3; logP - 1.01), and brain penetrability (logBB - 0.244; logPS - 3.047). Besides, 3 is promising as a brain-penetrating agent (logBB - 0.257; logPS - 2.400). The results preliminarily suggest further experimental attempts to verify the pro-cognitive effects of l(-)-carnitine (7).

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03714-9.

Target validation and structure-based virtual screening to Discover potential lead molecules against the oncogenic NSD1 histone methyltransferase

The aim of the study was to validate Nuclear receptor-binding SET Domain NSD1 as a cancer drug target followed by the design of lead molecules against NSD1. TCGA clinical data, molecular expression techniques were used to validate the target and structure-based virtual screening was performed to design hits against NSD1. Clinical data analysis suggests the role of NSD1 in metastasis, prognosis and influence on overall survival in various malignancies. Furthermore, the mRNA and protein expression profile of NSD1 was evaluated in various cell lines. NSD1 was exploited as a target protein for in silico design of inhibitors using two major databases including ZINC15 and ChemDiv by structure-based virtual screening approach. Virtual screening was performed using the pharmacophore hypothesis designed with a protein complex S-adenosyl-l-methionine (SAM) as an endogenous ligand. Subsequently, a combined score was used to distinguish the top 10 compounds from the docking screened compounds having high performance in all four scores (docking score, XP, Gscore, PhaseScreenScore, and MMGBSA delta G Bind). Finally, the top three Zinc compounds were subjected to molecular dynamic simulation. The binding MMGBSA data suggests that ZINC000257261703 and ZINC000012405780 can be taken for in vitro and in vivo studies as they have lesser MMGBSA energy towards the cofactor binding site of NSD1 than the sinefungin. Our data validates NSD1 as a cancer drug target and provides promising structures that can be utilized for further lead optimization and rational drug design to open new gateways in the field of cancer therapeutics.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00158-0.

Network pharmacology and molecular docking analysis on potential molecular targets and mechanism of action of BRAF inhibitors for application in wound healing

Topical application of BRAF inhibitors has been shown to accelerate wound healing in murine models, which can be extrapolated into clinical applications. The aim of the study was to identify suitable pharmacological targets of BRAF inhibitors and elucidate their mechanisms of action for therapeutic applicability in wound healing, by employing bioinformatics tools including network pharmacology and molecular docking. The potential targets for BRAF inhibitors were obtained from SwissTargetPrediction, DrugBank, CTD, Therapeutic Target Database, and Binding Database. Targets of wound healing were obtained using online databases DisGeNET and OMIM (Online Mendelian Inheritance in Man). Common targets were found by using the online GeneVenn tool. Common targets were then imported to STRING to construct interaction networks. Topological parameters were assessed using Cytoscape and core targets were identified. FunRich was employed to uncover the signaling pathways, cellular components, molecular functions, and biological processes in which the core targets participate. Finally, molecular docking was performed using MOE software. Key targets for the therapeutic application of BRAF inhibitors for wound healing are peroxisome proliferator-activated receptor γ, matrix metalloproteinase 9, AKT serine/threonine kinase 1, mammalian target of rapamycin, and Ki-ras2 Kirsten rat sarcoma viral oncogene homolog. The most potent BRAF inhibitors that can be exploited for their paradoxical activity for wound healing applications are Encorafenib and Dabrafenib. By using network pharmacology and molecular docking, it can be predicted that the paradoxical activity of BRAF inhibitors can be used for their potential application in wound healing.

A comparative study on inclusion complex formation between formononetin and β-cyclodextrin derivatives through multiscale classical and umbrella sampling simulations

Formononetin, a naturally occurring isoflavone exhibits a wide range of therapeutic applications including antioxidant, anti-tumor, antiviral, anti-diabetic and neuroprotective activities. However, the low hydro-solubility of formononetin has limited its prospective use in cosmetic, neutraceutical and pharmaceutical industries. Cyclodextrins (CDs), especially β-CD and its derivatives have emerged as promising agents to improve the water solubility of poorly hydrosoluble compounds by the formation of inclusion complexes. We employed multiscale (1000 ns) explicit solvent and umbrella sampling molecular dynamics (MD) simulations to study the interactions and thermodynamic parameters of inclusion complex formation between formononetin and five most commonly used β-CD derivatives. Classical MD simulations revealed two possible binding conformations of formononetin inside the central cavity of hydroxypropyl-β-CD (HP-β-CD), randomly methylated-β-CD (ME-β-CD), and sulfobutylether-β-CD (SBE-β-CD). The binding conformation with the benzopyrone ring of formononetin inside the central cavity of β-CD derivatives was more frequent than the phenyl group occupying the hydrophobic cavity. These interactions were supported by a variety of non-bonded contacts including hydrogen bonds, pi-lone pair, pi-sigma, and pi-alkyl interactions. Formononetin showed favorable end-state MD-driven thermodynamic binding free energies with all the selected β-CD derivatives, except succinyl-β-CD (S-β-CD). Furthermore, umbrella sampling simulations were used to investigate the interactions and thermodynamic parameters of the host-guest inclusion complexes. The SBE-β-CD/formononetin inclusion complex showed the lowest binding energy signifying the highest affinity among all the selected host-guest inclusion complexes. Our study could be used as a standard for analyzing and comparing the ability of different β-CD derivatives to enhance the hydro-solubility of poorly soluble molecules.

New insights on the catalytic center of proteins from peptidylprolyl isomerase group based on the FOD-M model

Generating the structure of the hydrophobic core is based on the orientation of hydrophobic residues towards the central part of the protein molecule with the simultaneous exposure of polar residues. Such a course of the protein folding process takes place with the active participation of the polar water environment. While the self-assembly process leading to the formation of micelles concerns freely moving bi-polar molecules, bipolar amino acids in polypeptide chain have limited mobility due to the covalent bonds. Therefore, proteins form a more or less perfect micelle-like structure. The criterion is the hydrophobicity distribution, which to a greater or lesser extent reproduces the distribution expressed by the 3D Gaussian function on the protein body. The vast majority of proteins must ensure solubility, so a certain part of it-as it is expected-should reproduce the structuring of micelles. The biological activity of proteins is encoded in the part that does not reproduce the micelle-like system. The location and quantitative assessment of the contribution of orderliness to disorder is of critical importance for the determination of biological activity. The form of maladjustment to the 3D Gauss function may be varied-hence the obtained high diversity of specific interactions with strictly defined molecules: ligands or substrates. The correctness of this interpretation was verified on the basis of the group of enzymes Peptidylprolyl isomerase-E.C.5.2.1.8. In proteins representing this class of enzymes, zones responsible for solubility-micelle-like hydrophobicity system-the location and specificity of the incompatible part in which the specific activity of the enzyme is located and coded were identified. The present study showed that the enzymes of the discussed group show two different schemes of the structure of catalytic center (taking into account the status as defined by the fuzzy oil drop model).

Molecular mechanisms augmenting resistance to current therapies in clinics among cervical cancer patients

Cervical cancer (CC) is the fourth leading cause of cancer death (~ 324,000 deaths annually) among women internationally, with 85% of these deaths reported in developing regions, particularly sub-Saharan Africa and Southeast Asia. Human papillomavirus (HPV) is considered the major driver of CC, and with the availability of the prophylactic vaccine, HPV-associated CC is expected to be eliminated soon. However, female patients with advanced-stage cervical cancer demonstrated a high recurrence rate (50-70%) within two years of completing radiochemotherapy. Currently, 90% of failures in chemotherapy are during the invasion and metastasis of cancers related to drug resistance. Although molecular target therapies have shown promising results in the lab, they have had little success in patients due to the tumor heterogeneity fueling resistance to these therapies and bypass the targeted signaling pathway. The last two decades have seen the emergence of immunotherapy, especially immune checkpoint blockade (ICB) therapies, as an effective treatment against metastatic tumors. Unfortunately, only a small subgroup of patients (< 20%) have benefited from this approach, reflecting disease heterogeneity and manifestation with primary or acquired resistance over time. Thus, understanding the mechanisms driving drug resistance in CC could significantly improve the quality of medical care for cancer patients and steer them to accurate, individualized treatment. The rise of artificial intelligence and machine learning has also been a pivotal factor in cancer drug discovery. With the advancement in such technology, cervical cancer screening and diagnosis are expected to become easier. This review will systematically discuss the different tumor-intrinsic and extrinsic mechanisms CC cells to adapt to resist current treatments and scheme novel strategies to overcome cancer drug resistance.

Research Progress on the Pharmacodynamic Mechanisms of Sini Powder against Depression from the Perspective of the Central Nervous System

Depression is a highly prevalent emotional disorder characterized by persistent low mood, diminished interest, and loss of pleasure. The pathological causes of depression are associated with neuronal atrophy, synaptic loss, and neurotransmitter activity decline in the central nervous system (CNS) resulting from injuries, such as inflammatory responses. In Traditional Chinese Medicine (TCM) theory, patients with depression often exhibit the liver qi stagnation syndrome type. Sini Powder (SNP) is a classic prescription for treating such depression-related syndrome types in China. This study systematically summarized clinical applications and experimental studies of SNP for treatments of depression. We scrutinized the active components of SNP with blood-brain barrier (BBB) permeability and speculated about the corresponding pharmacodynamic pathways relevant to depression treatment through intervening in the CNS. Therefore, this article can enhance our understanding of SNP's pharmacological mechanisms and formula construction for depression treatment. Moreover, a re-demonstration of this classic TCM prescription in the modern-science language is of great significance for future drug development and research.

Molecular dynamics of the ERRγ ligand-binding domain bound with agonist and inverse agonist

Estrogen-related receptor gamma (ERRγ), the latest member of the ERR family, does not have any known reported natural ligands. Although the crystal structures of the apo, agonist-bound, and inverse agonist-bound ligand-binding domain (LBD) of ERRγ have been solved previously, their dynamic behavior has not been studied. Hence, to explore the intrinsic dynamics of the apo and ligand-bound forms of ERRγ, we applied long-range molecular dynamics (MD) simulations to the crystal structures of the apo and ligand-bound forms of the LBD of ERRγ. Using the MD trajectories, we performed hydrogen bond and binding free energy analysis, which suggested that the agonist displayed more hydrogen bonds with ERRγ than the inverse agonist 4-OHT. However, the binding energy of 4-OHT was higher than that of the agonist GSK4716, indicating that hydrophobic interactions are crucial for the binding of the inverse agonist. From principal component analysis, we observed that the AF-2 helix conformation at the C-terminal domain was similar to the initial structures during simulations, indicating that the AF-2 helix conformation is crucial with respect to the agonist or inverse agonist for further functional activity of ERRγ. In addition, we performed residue network analysis to understand intramolecular signal transduction within the protein. The betweenness centrality suggested that few of the amino acids are important for residue signal transduction in apo and ligand-bound forms. The results from this study may assist in designing better therapeutic compounds against ERRγ associated diseases.

Computational analysis of protein-ligand interaction by targeting a cell cycle restrainer

BACKGROUND AND OBJECTIVE

The cyclin-dependent kinases 4/6 (CDK4/6) are among the most crucial controllers of the cell cycle, and their abnormal activity may induce uncontrolled cell multiplication, leading to cancers. The FDA currently approved three CDK4/6 inhibitors, however, they are associated with a variety of side effects. Thus it is required to design/develop novel potent and safe CDK4/6 inhibitors.

METHODS

In the present work, we furnished an integrated in-silico approach followed by steered molecular dynamics (SMD) simulations to identify molecules that can be developed into novel CDK4/6 inhibitors.

RESULTS

Out of thirty-two 3-methyleneisoindolin-1-one molecules we selected top three M18, M24, and M32 molecules as potential drug candidates based on their respective interaction energies. According to the robust 250 ns MD simulations and thermodynamic free energy, M24 was the best molecule in comparison to palbociclib. In SMD, M24 required ∼205.587 kJ/mol/nm external pulling force, while palbociclib needed ∼160.97 kJ/mol/nm to dissociate from the binding pocket of the CDK4.

CONCLUSIONS

The high pulling force required for M24 dissociation from the binding site denotes stronger binding with CDK4. Therefore, M24 offers the possibility of a critical starting structure in developing effective CDK4 inhibitors.

Leaf Extract of Perilla frutescens (L.) Britt Promotes Adipocyte Browning via the p38 MAPK Pathway and PI3K-AKT Pathway

The leaf of Perilla frutescens (L.) Britt (PF) has been reported to negatively affect adipocyte formation, inhibit body-fat formation, and lower body weight. However, its effect on adipocyte browning remains unknown. Thus, the mechanism of PF in promoting adipocyte browning was investigated. The ingredients of PF were acquired from the online database and filtered with oral bioavailability and drug-likeness criteria. The browning-related target genes were obtained from the Gene Card database. A Venn diagram was employed to obtain the overlapped genes that may play a part in PF promoting adipocyte browning, and an enrichment was analysis conducted based on these overlapped genes. A total of 17 active ingredients of PF were filtered, which may regulate intracellular receptor-signaling pathways, the activation of protein kinase activity, and other pathways through 56 targets. In vitro validation showed that PF promotes mitochondrial biogenesis and upregulates brite adipocyte-related gene expression. The browning effect of PF can be mediated by the p38 MAPK pathway as well as PI3K-AKT pathway. The study revealed that PF could promote adipocyte browning through multitargets and multipathways. An in vitro study validated that the browning effect of PF can be mediated by both the P38 MAPK pathway and the PI3K-AKT pathway.

Structure restoration and aggregate inhibition of V30M mutant transthyretin protein by potential quinoline molecules

Transthyretin (TTR) is a tetrameric protein found in human plasma and cerebrospinal fluid that functions as a transporter of thyroxine (T4) and retinol. A mutation resulting in the substitution of valine to methionine at position 30 (V30M) is the most common mutation that destabilizes the tetramer structure of TTR protein resulting in a fatal neuropathy known as TTR amyloidosis. The V30M TTR-induced neuropathy can be inhibited through stabilization of the TTR tetramer by the binding of small molecules. We accessed the potential of in-house synthesized quinoline molecules to stabilize the V30M TTR structure and analyzed the impact of protein-ligand interactions through molecular docking, molecular dynamics (MD) simulations, steered MD, and umbrella sampling simulations. This study revealed that the binding of quinoline molecules reverted back the structural changes including the residual flexibility, changes in secondary structural elements, and also restored the alterations in the electrostatic surface potential induced by the V30M mutation. Further, the top-most 4G and 4R molecules were compared with an FDA-approved drug (Tafamidis) and a reference quinoline molecule 14C. Here, we intend to suggest that the quinoline molecules could revert the structural changes, cease tetramer dissociation, prevent abnormal oligomerization and therefore could be developed as an effective therapeutics against TTR amyloidosis.

Exploring the Potential of Phytocompounds for Targeting Epigenetic Mechanisms in Rheumatoid Arthritis: An In Silico Study Using Similarity Indexing

Finding structurally similar compounds in compound databases is highly efficient and is widely used in present-day drug discovery methodology. The most-trusted and -followed similarity indexing method is Tanimoto similarity indexing. Epigenetic proteins like histone deacetylases (HDACs) inhibitors are traditionally used to target cancer, but have only been investigated very recently for their possible effectiveness against rheumatoid arthritis (RA). The synthetic drugs that have been identified and used for the inhibition of HDACs include SAHA, which is being used to inhibit the activity of HDACs of different classes. SAHA was chosen as a compound of high importance as it is reported to inhibit the activity of many HDAC types. Similarity searching using the UNPD database as a reference identified aglaithioduline from the Aglaia leptantha compound as having a ~70% similarity of molecular fingerprints with SAHA, based on the Tanimoto indexing method using ChemmineR. Aglaithioduline is abundantly present in the shell and fruits of A. leptantha. In silico studies with aglaithioduline were carried out against the HDAC8 protein target and showed a binding affinity of -8.5 kcal mol. The complex was further subjected to molecular dynamics simulation using Gromacs. The RMSD, RMSF, compactness and SASA plots of the target with aglaithioduline, in comparison with the co-crystallized ligand (SAHA) system, showed a very stable configuration. The results of the study are supportive of the usage of A. leptantha and A. edulis in Indian traditional medicine for the treatment of pain-related ailments similar to RA. Our study therefore calls for further investigation of A. leptantha and A. edulis for their potential use against RA by targeting epigenetic changes, using in vivo and in vitro studies.

In silico analysis of peroxidase from Luffa acutangula

Peroxidases are oxidoreductase enzymes that widely gained attention as biocatalysts for their robust catalytic activity, specificity, and regioselective functionality for phenolic compounds. The study of molecular aspects of peroxidases is as crucial as that of the physicochemical aspects. A bioinformatics approach is utilized in this study to investigate the structural aspects and functions of luffa peroxidase (LPrx) from Luffa acutangula. The evolutionary relationship of LPrx with other class III peroxidases was studied by constructing a neighbour-joining phylogenetic tree. An analysis of the phylogenetic tree revealed that plant peroxidases share a common ancestor. The gene ontology term showed that LPrx had a molecular functionality of the oxidation-reduction process, heme binding and peroxidase-like activity, and the biological function of hydrogen peroxide scavenging activity. The enzyme-ligand interactions were studied from a catalytic point of view using the molecular docking technique. The molecular docking was carried out with LPrx as a receptor and guaiacol, m-cresol, p-cresol, catechol, quinol, pyrogallol, 2,4-dimethoxyphenol, gallic acid, aniline, and o-phenylenediamine as ligands. The results presented in the current communication will have a significant implication in proteomics, biochemistry, biotechnology, and the potential applications of peroxidases in the biotransformations of organic compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03432-8.

Andrographolide-based potential anti-inflammatory transcription inhibitors against nuclear factor NF-kappa-B p50 subunit (NF-κB p50): an integrated molecular and quantum mechanical approach

The unregulated activation of nuclear factor-κB (NF-κB) is a critical event in the progression of various inflammatory diseases such as ulcerative colitis, asthma, rheumatoid arthritis, bacterial induced gastritis, etc. Hence, blocking the transcriptional activity of NF-κB is a promising strategy towards the development of an anti-inflammatory agent. In this study, an integrated molecular and quantum mechanical approach was carried out to find a new potent andrographolide (AGP)-based analog that can inhibit DNA binding to NF-κB p50 and manifest anti-inflammatory activity. Our approach includes multiple sequence alignment, virtual screening, molecular docking (protein-ligand and protein-DNA), in silico site-directed mutagenesis, ADMET prediction, DFT (HOMO, LUMO, HLG, and EPM energy) analysis, MD simulation, and MM/GBSA rescoring. The virtual screening analysis of 237 AGP analogs yielded the five lead compounds based on the binding affinity. Further, molecular interactive docking and ADMET prediction of hit analogs revealed that Ana2 ((3Z,4S)-3-[2-[(4aR,6aS,7R,10aS,10bR)-3,3,6a,10b-tetramethyl-8-methylidene-1,4a,5,6,7,9,10,10a-octahydronaphtho[2,1-d][1,3]dioxin-7-yl]ethylidene]-4-hydroxyoxolan-2-one) is the most potent moiety as it displays the strongest binding affinity and better molecular/pharmacokinetic features. Moreover, DFT, MD simulation, and MM/GBSA studies corroborated the docking results and demonstrated better chemical and dynamic stability with the least binding free energy (- 29.99 kcal/mol) for the Ana2. Site-directed mutagenesis investigation (Cys62Ala) establishes the importance of the Cys62 amino acid residue towards the binding interaction and stability of Ana2 with NF-κB p50. Overall, the identified NF-κB p50 inhibitor opens up a new research horizon towards the development of plant-based anti-inflammatory drugs to combat progressive inflammatory diseases.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03431-9.

Predicting and Validating the Mechanism of Qingyi II Granules in the Treatment of Acute Pancreatitis by Network Pharmacology

Network pharmacology, reverse molecular docking, and rat acute pancreatitis (AP) models were used to analyze the mechanism of protection by Qingyi II granules. The chemical components of 7 Chinese herbal medicines in Qingyi II granules were searched through the TCMSP (traditional Chinese medicine systems pharmacology database and analysis platform) database. The active ingredients were screened out in the OB (oral bioavailability) and DL (drug likeness) filters as a condition for inclusion. Then, the prediction analysis of potential targets was performed through databases. A GO (gene ontology) enrichment analysis of target proteins related to AP and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway annotation was performed using the DAVID (The Database for Annotation, Visualization, and Integrated Discovery) database. Finally, the “Herbal-Compound-Target” network was constructed using Cytoscape software. The active component structure and target name were uploaded to the Systems Dock database for reverse molecular docking. With octreotide as a positive control, Qingyi II decoction and Qingyi II granules were administered to AP rats at low, medium, and high doses. The pathological changes in the pancreas were observed using HE staining. The levels of Bcl-2, AMS, BAX, IL-2, and CASP3 in plasma were determined by an ELISA kit. Real-time PCR detected the expression of AKT1 and PIK3CA mRNA in the pancreas. The database predicted 94 active components of Qingyi II granules, 76 potential targets, and 64 signaling pathways. Twenty pathways were directly or indirectly associated with acute pancreatitis, including the TNF signaling pathway and the PI3K-AKT signaling pathway. In the reverse molecular docking experiment, the matching scores of the active components and the target were mainly between 6.0 and 7.0, with strong binding activity. Compared to the normal group, the plasma concentrations of BAX, IL-2, Bcl-2, AMS, and CASP3 in the model group were significantly increased ( $P<0.05$ ). Compared with the model group, the low-dose group of Qingyi II granules only significantly reduced IL-2 levels and had no effect on other indicators. The other groups could significantly reduce the levels of AMS, BAX, and CASP3 ( $P<0.05$ ). Compared with the model group, the octreotide group and Qingyi II granules high-dose group significantly increased the Bcl-2 level ( $P<0.05$ ), and there was no statistical difference in other drug-administered groups. Compared with the normal group, the expression of AKT1 and PIK3CA in the pancreas of the model group was significantly higher. Compared to the model group, the expression of PIK3CA was low in all drug-administered groups. In addition to the low-dose group, the other drug-administered groups significantly reduced the expression of AKT1. Qingyi can reduce the levels of AMS, BAX, IL-2, and CASP3 and increase the levels of Bcl-2. This mechanism may be related to the PI3K- AKT signaling pathway.

PHF8 promotes osteogenic differentiation of BMSCs in old rat with osteoporosis by regulating Wnt/β-catenin pathway

Osteoporosis is a progressive bone disorder with a higher incidence in the elderly and has become a major public health concern all over the world. Therefore, it is urgent to investigate the mechanisms underlying the pathogenesis of osteoporosis. In this study, the osteoporosis animal model was established, and then rat bone marrow mesenchymal stem cells (rBMSCs) were cultured. The results showed that PHF8 expression was decreased in osteoporosis rats compared to controls. Overexpression of PHF8 promoted BMSC osteogenic differentiation and the expression of osteogenesis-related genes. In addition, the Wnt/β-catenin signaling pathway in BMSCs was inhibited in osteoporosis rats, which was rescued by overexpression of PHF8. After treatment with the Wnt pathway antagonist, the improved osteogenic differentiation of BMSCs induced by overexpression of PHF8 was blocked. Collectively, our data revealed that the decreased expression of PHF8 in osteoporosis rats suppressed the osteogenic differentiation of BMSCs, which was then restored by PHF8 overexpression. Furthermore, the inhibition of the Wnt/β-catenin signaling pathway in BMSCs suppressed osteogenic differentiation. Thus, these findings indicated that PHF8 plays a role in osteogenic differentiation through the Wnt/β-catenin signaling pathway.

Uncovering the Key Targets and Therapeutic Mechanisms of Qizhen Capsule in Gastric Cancer through Network Pharmacology and Bioinformatic Analyses

Objective. This study is aimed at screening out effective active compounds of Qizhen capsule (QZC) and exploring the underlying mechanisms against gastric cancer (GACA) by combining both bioinformatic analysis and experimental approaches. Weighted gene coexpression network analysis (WGCNA), network pharmacology, molecular docking simulation, survival analysis, and data-based differential gene and protein expression analysis were employed to predict QZC’s potential targets and explore the underlying mechanisms. Subsequently, multiple experiments, including cell viability, apoptosis, and protein expression analyses, were conducted to validate the bioinformatics-predicted therapeutic targets. The results indicated that luteolin, rutin, quercetin, and kaempferol were vital active compounds, and TP53, MAPK1, and AKT1 were key targets. Molecular docking simulation showed that the four abovementioned active compounds had high binding affinities to the three main targets. Enrichment analysis showed that vital active compounds exerted therapeutic effects on GACA through regulating the TP53 pathway, MAPK pathway, and PI3K/AKT pathway. Furthermore, data-based gene expression analysis revealed that TP53 and JUN genes were not only differentially expressed between normal and GACA tissues but also correlated with clinical stages. In parallel, in vitro experimental results suggested that QZC exerted therapeutic effects on GACA by decreasing IC50 values, downregulating AKT expression, upregulating TP53 and MAPK expression, and increasing apoptosis of SGC-7901 cells. This study highlights the potential candidate biomarkers, therapeutic targets, and basic mechanisms of QZC in treating GACA, providing a foundation for new drug development, target mining, and related animal studies in GACA.

Decoding the Key Functional Combined Components Group and Uncovering the Molecular Mechanism of Longdan Xiegan Decoction in Treating Uveitis

Objective

Longdan Xiegan Decoction (LXD) is a famous herbal formula in China. It has been proved that LXD has been shown to have a significant inhibitory effect on suppresses the inflammatory cells associated with uveitis. However, the key functional combination of component groups and their possible mechanisms remain unclear.

Methods

The community detecting model of the network, the functional response space, and reverse prediction model were utilized to decode the key components group (KCG) and possible mechanism of LXD in treating uveitis. Finally, MTT assay, NO assay and ELISA assay were applied to verify the effectiveness of KCG and the accuracy of our strategy.

Results

In the components-targets-pathogenic genes-disease (CTP) network, a combination of Huffman coding and random walk algorithm was used and eight foundational acting communities (FACs) were discovered with important functional significance. Verification has shown that FACs can represent the corresponding C-T network for treating uveitis. A novel node importance calculation method was designed to construct the functional response space and pick out 349 effective proteins. A total of 54 components were screened and defined as KCG. The pathway enrichment results showed that KCG and their targets enriched signal pathways of IL-17, Toll-like receptor, and T cell receptor played an important role in the pathogenesis of uveitis. Furthermore, experimental verification results showed that important KCG quercetin and sitosterol markedly inhibited the production of nitric oxide and significantly regulated the level of TNF-α and IFN-γ in Lipopolysaccharide-induced RAW264.7 cells.

Discussion

In this research, we decoded the potential mechanism of the multi-components-genes-pathways of LXD’s pharmacological action mode against uveitis based on an integrated pharmacology approach. The results provided a new perspective for the future studies of the anti-uveitis mechanism of traditional Chinese medicine.

Potential of paracetamol for reproductive disruption: Molecular interaction, dynamics and MM-PBSA based In-silico assessment

Paracetamol is generally recommended for pain and fever. However, as per experimental and epidemiological data, widespread and irrational or long-term use of paracetamol may be harmful to human endocrine homeostasis, especially during pregnancy. Some researchers suggest that prenatal exposure to paracetamol might alter foetal development and also enhance the risk of reproductive disorders. An imbalance in the levels of these hormones may play a significant role in the emergence of various diseases, including infertility. Therefore, in this study, the interaction mechanism of paracetamol with reproductive hormone receptors was investigated by molecular docking, molecular dynamics (MD) simulations, and poisson-Boltzmann surface area (MM-PBSA) for assessing paracetamol's potency to disrupt reproductive hormones. The results indicate that paracetamol has the ability to interact with reproductive hormone receptors (estrogen 1XP9; 1QKM with binding energy of -5.61 kcal/mol; -5.77 kcal/mol; androgen 5CJ6 -5.63 kcal/mol; and progesterone 4OAR-5.60 kcal/mol) by hydrogen bonds as well as hydrophobic and van der Waals interactions to maintain its stability. In addition, the results of the MD simulations and MM-PBSA confirm that paracetamol and reproductive receptor complexes are stable. This research provides a molecular and atomic level understanding of how paracetamols disrupt reproductive hormone synthesis. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), Radius of Gyration and hydrogen bonding exhibited that paracetamol mimic at various attribute to bisphenol and native ligand.

Novel benzylidene benzofuranone analogues as potential anticancer agents: design, synthesis and in vitro evaluation based on CDK2 inhibition assays

The classical anticancer agents do not have their efficacy on inhibiting the G2 phase of the cell cycle. There are a very few reports available on drugs that work at G2 phase. Flavopiridol is one such drug candidate. In the current study, we sought to make analogues of flavopiridol. Still, the conditions used during their synthesis were unfavourable for the formation of flavopiridol and led to the generation of benzofuranones. In the present work, a new series of benzylidene benzofuranones were designed, synthesized and evaluated for their antioxidant, anti-colorectal cancer activity. Molecular docking, MMGBSA and molecular dynamics studies were conducted to assess their binding affinity at the active site of CDK2. Based on the cytotoxicity exhibited by test compounds, the compound NISOA4 (from isopropyl series) was further selected for mechanistic anticancer studies on HCT 116 cell lines. The compound selected was evaluated by comet assay, DNA fragmentation assay, cell cycle analysis, apoptosis detection by annexin FITC, semi-quantitative RTPCR based gene expression studies and FRET assay on the target CDK2/Cyclin A. Compound NISOA4 exhibited marked olive moments in comet assay studies. The apoptotic DNA fragmentation for compound NISOA4 demonstrated a marked change in the DNA fragmentation. The compound exhibited cell cycle arrest at G2/M phase at both the test concentrations. Apoptosis induction was observed at both the test concentrations and the compound was found to be a potent proapoptotic agent. It exhibited marked inhibition for the CDK2 gene expression and did not show any effect on CyclinA gene expression. However, the compound NISOA4 along with other analogues showed appreciable inhibition for the CDK2/Cyclin A target enzyme.

Network Toxicology Guided Mechanism Study on the Association between Thyroid Function and Exposures to Polychlorinated Biphenyls Mixture

Polychlorinated biphenyls (PCBs) are persistent and highly toxic pollutants, which can accumulate in organisms and produce toxic effects, especially damaging the function of thyroid hormones. So far, the molecular mechanism of PCBs mixture and their metabolites interfering with thyroid hormones has not been studied thoroughly except for individual compounds. In this study, PubMed, Web of Science, and STITCH databases were used to search PCBs and their corresponding target proteins. The intersection of PCBs and thyroid hormone dysfunction target proteins was obtained from GeneCards. The “compounds-targets-pathways” network was constructed by Cytoscape software. And KEGG and Go analyses were performed for key targets. Finally, molecular docking was used to verify the binding effect. Four major active components, five key targets, and 10 kernel pathways were successfully screened by constructing the network. Functional enrichment analysis showed that the interference was mediated by cancer, proteoglycans, PI3K-Akt, thyroid hormone, and FoxO signaling pathways. The molecular docking results showed that the binding energies were less than -5 kcal·mol-1. PCBs and their metabolites may act on the key targets of MAPK3, MAPK1, RXRA, PIK3R1, and TP53. The toxic effect of sulfated and methyl sulfone PCBs is greater. The method of screening targets based on the simultaneous action of multiple PCBs can provide a reference for other research. The targets were not found in previous metabolite toxicity studies. It also provides a bridge for the toxic effects and experimental research of PCBs and their metabolites in the future.

Screening of Sepsis Biomarkers Based on Bioinformatics Data Analysis

Methods

Gene expression profiles of GSE13904, GSE26378, GSE26440, GSE65682, and GSE69528 were obtained from the National Center for Biotechnology Information (NCBI). The differentially expressed genes (DEGs) were searched using limma software package. Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs and screen hub genes.

Results

A total of 108 DEGs were identified in the study, of which 67 were upregulated and 41 were downregulated. 15 superlative diagnostic biomarkers (CCL5, CCR7, CD2, CD27, CD274, CD3D, GNLY, GZMA, GZMH, GZMK, IL2RB, IL7R, ITK, KLRB1, and PRF1) for sepsis were identified by bioinformatics analysis.

Conclusion

15 hub genes (CCL5, CCR7, CD2, CD27, CD274, CD3D, GNLY, GZMA, GZMH, GZMK, IL2RB, IL7R, ITK, KLRB1, and PRF1) have been elucidated in this study, and these biomarkers may be helpful in the diagnosis and therapy of patients with sepsis.

Network Pharmacology and Molecular Docking Analyses Unveil the Mechanisms of Yiguanjian Decoction against Parkinson’s Disease from Inner/Outer Brain Perspective

Objective

This study aims to explore the pharmacodynamic mechanism of Yiguanjian (YGJ) decoction against Parkinson's disease (PD) through integrating the central nervous (inner brain) and peripheral system (outer brain) relationship spectrum.

Methods

The active components of YGJ were achieved from the TCMSP, TCMID, and TCM@Taiwan databases. The blood-brain barrier (BBB) permeability of the active components along with their corresponding targets was evaluated utilizing the existing website, namely, SwissADME and SwissTargetPrediction. The targets of PD were determined through database retrieval. The interaction network was constructed upon the STRING database, followed by the visualization using Cytoscape software. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on potential targets. Finally, the molecular docking approach was employed to assess the binding affinity between key components and key targets.

Results

Overall, we identified 79 active components, 128 potential targets of YGJ, and 97 potential targets of YGJ-BBB potentially suitable for the treatment of PD. GO and KEGG analyses showed that the YGJ treatment of PD mainly relied on PI3K-Akt pathway while the YGJ-BBB was mostly involved in endocrine resistance. The molecular docking results displayed high affinity between multiple compounds and targets in accordance with previous observations.

Conclusions

Our study unveiled the potential mechanisms of YGJ against PD from a systemic perspective: (1) for the YGJ, they have potential exerting effects on the peripheral system and inhibiting neuronal apoptosis through regulating the PI3K-Akt pathway; (2) for the YGJ-BBB, they can directly modulate endocrine resistance of the central nervous and holistically enhance body resistance to PD along with YGJ on PI3K-Akt pathway.

Enhancement of Vitamin K2 Efflux in Bacillus subtilis Natto via a Potential Protein Receptor for Increased Yield

Bacillus subtilis is one of the few strains that can secrete synthetic menaquinone-7 (MK-7) to the outside of the cell, and its purpose and mechanism have not been clearly studied. As an amphiphilic protein naturally synthesized by Bacillus subtilis, the BslA protein may be involved in the inversion of extracellular vitamin K2 solubility. The protein structure in UniProt was used to search for the possible binding sites of MK-7, and the analysis of the higher ranking results of the genetic algorithm showed that the ASP166 residue was likely to be the binding site. They could form a stable hydrogen bond connection through ASP166, and approximately 7 proteins formed the conformation of a fixed naphthoquinone ring. We isolated and obtained the BslA protein by Ni-NTA affinity chromatography. Then, MK-7 was modified by BslA in vitro. A series of experiments, such as SEM, XPS, and WCA, showed that MK-7 and BslA proteins can realize self-assembly and transform from fat-soluble to water-soluble complexes. When the bslA protein in Bacillus subtilis natto was overexpressed, its MK-7 synthesis ability was further improved, especially the extracellular MK-7 content, which increased by 16%. This finding suggests that the BslA protein in Bacillus subtilis is likely to be involved in the extracellular secretion of MK-7 as a receptor.

Synthesis, Biological Evaluation, and In Silico Studies of Novel Coumarin-Based 4H,5H-pyrano[3,2-c]chromenes as Potent β-Glucuronidase and Carbonic Anhydrase Inhibitors

The search for novel heterocyclic compounds with a natural product skeleton as potent enzyme inhibitors against clinical hits is our prime concern in this study. Here, a simple and facile two-step strategy has been designed to synthesize a series of novel coumarin-based dihydropyranochromenes (12a-12m) in a basic moiety. The synthesized compounds were thus characterized through spectroscopic techniques and screened for inhibition potency against the cytosolic hCA II isoform and β-glucuronidase. Few of these compounds were potent inhibitors of hCA II and β-glucuronidase with varying IC₅₀ values ranging from 4.55 ± 0.22 to 21.77 ± 3.32 μM and 440.1 ± 1.17 to 971.3 ± 0.05 μM, respectively. Among the stream of synthesized compounds, 12e and 12i were the most potent inhibitors of β-glucuronidase, while 12h, 12i, and 12j showed greater potency against hCA II. In silico docking studies illustrated the significance of substituted groups on the pyranochromene skeleton and binding pattern of these highly potent compounds inside enzyme pockets.

Identification of potential inhibitors, conformational dynamics, and mechanistic insights into mutant Kirsten rat sarcoma virus (G13D) driven cancers

The mutations at the hotspot region of K-Ras result in the progression of cancer types. Our study aimed to explore the small molecule inhibitors against the G13D mutant K-Ras model with anti-cancerous activity from food and drug administration (FDA)-approved drug compounds. We implemented several computational strategies such as pharmacophore-based virtual screening, molecular docking, absorption, distribution, metabolism and excretion features, and molecular simulation to ensure the identified hit compounds have potential efficacy against G13D K-Ras. We found that the FDA-approved compounds, namely, azelastine, dihydrocodeine, paroxetine, and tramadol, are potential candidates to inhibit the action of G13D mutant K-Ras. All four compounds exhibited similar binding patterns of sotorasib, and a structural binding mechanism with significant hydrophobic contacts. The descriptor features from the QikProp of all four compounds are within allowable limits compared to sotorasib drug. Consequently, a molecular simulation result emphasized that the dihydrocodeine and tramadol exhibited less fluctuation, minimal basin, significant h-bonds, and potent inhibition against G13D K-Ras. As a result, the current research identifies prospective K-Ras inhibitors that could be further improved with biochemical analysis for precision medicine against K-Ras-driven cancers.