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PubMed2005

Study of a ligand complexed with Cdk2/Cdk4 by computer simulation.

Cyclin-dependent kinases (Cdks) play important roles in the regulation of the cell cycle. Their inhibitors have entered clinical trials to treat cancer. Very recently, Davis et al. (Nat Struct Biol 9:745-749, 2002) have found a ligand NU6102, which has a high affinity with cyclin-dependent kinase 2 (K(i) = 6 nM) but a low affinity with cyclin-dependent kinase 4 (K(i) = 1,600 nM). To understand the selectivity, we use homology modeling, molecular docking, molecular dynamics and free-energy calculations to analyze the interactions. A rational 3D model of the Cdk4-NU6102 complex is built. Asp86 is a key residue that recognizes NU6102 more effectively with Cdk2 rather than Cdk4. Good binding free energies are obtained. Energetic analysis reveals that van der Waals interaction and nonpolar contributions to solvent are favorable in the formation of complexes and the sulfonamide group of the ligand plays a crucial role for binding selectivity between Cdk2 and Cdk4.

Amino Acid Sequence↗

PubMed2006

Computational studies of H5N1 hemagglutinin binding with SA-alpha-2, 3-Gal and SA-alpha-2, 6-Gal.

For influenza H5N1 hemagglutinin, a switch from SA-alpha-2, 3-Gal to SA-alpha-2, 6-Gal receptor specificity is a critical step leading to the conversion from avian-to-human to human-to-human infection. Therefore, the understanding of the binding modes of SA-alpha-2, 3-Gal and SA-alpha-2, 6-Gal to H5N1 hemagglutinin will be very important for the examination of possible mutations needed for going from an avian to a human flu virus. Based on the available H5N1 hemagglutinin crystal structure, the binding profiles between H5N1 hemagglutinin and two saccharide ligands, SA-alpha-2, 3-Gal and SA-alpha-2, 6-Gal, were investigated by ab initio quantum mechanics, molecular docking, molecular mechanics, and molecular dynamics simulations. It was found that SA-alpha-2, 3-Gal has strong multiple hydrophobic and hydrogen bond interactions in its trans conformation with H5N1 hemagglutinin, whereas the SA-alpha-2, 6-Gal only shows weak interactions in a different conformation (cis type).

Computational Biology↗

PubMed2002

Molecular pharmacology and modeling of vasopressin receptors.

AVP receptors represent a logical target for drug development. As a new class of therapeutic agents, orally active AVP analogs could be used to treat several human pathophysiological conditions including neurogenic diabetes insipidus, the syndrome of inappropriate secretion of AVP (SIADH), congestive heart failure, arterial hypertension, liver cirrhosis, nephrotic syndrome, dysmenorrhea, and ocular hypertension. By immunoprecipitation and immunoblotting, we elucidated the phosphorylation pattern of green fluorescent protein-tagged AVP receptors and showed interactions with the specific kinases PKC and GRK5 that are agonist-, time- and receptor subtype-dependent. The tyrosine residue of the NPWIY motif present in the 7th helix of AVP receptors is rapidly and transiently phosphorylated after agonist stimulation. This phosphorylation is instrumental in the genesis of the mitogenic cascade linked to the activation of this receptor, presumably by establishing key intramolecular contacts and by participating in the creation of a scaffold of proteins that produce the activation of downstream kinases. The random screening of chemical entities and optimization of lead compounds recently resulted in the development of orally active non-peptide AVP receptor agonists and antagonists. Furthermore, the identification of the molecular determinants of receptor-ligand interactions should facilitate the development of more potent and very selective orally active compounds via the approach of structure-based drug design. We developed three-dimensional molecular docking models of peptide and non-peptide ligands to the human V1 vascular, V2 renal and V3 pituitary AVP receptors. Docking of the peptide hormone AVP to the receptor ligand binding pockets reflects its dual polar and non-polar structure, but is receptor subtype-specific. The characteristics of non-peptide AVP analogs docking to the receptors are clearly distinct from those of peptide analogs docking. Molecular modeling of the results of site-directed mutagenesis experiments performed in CHO cells stably transfected with the human AVP receptor subtypes revealed that non-peptide antagonists establish key contacts with a few amino acid residues of the receptor subtypes that are different from those involved in agonist binding. Moreover, these interactions are species-specific. These findings provide further understanding of the signal transduction pathways of AVP receptors and new leads for elucidation of drug-receptor interactions and optimization of drug design. NOTE TO THE READER: The recent cloning and molecular characterization of AVP/OT receptor subtypes call for the revision of their nomenclature. For the sake of clarity and reference to their main site of expression, we call the V1a receptor the V1 vascular receptor, the V2 receptor the V2 renal receptor and the V1b or V3 receptor the V3 pituitary receptor in the present review.

Amino Acid Sequence↗

PubMed2006

How can (-)-epigallocatechin gallate from green tea prevent HIV-1 infection? Mechanistic insights from computational modeling and the implication for rational design of anti-HIV-1 entry inhibitors.

Possible inhibitors preventing human immunodeficiency virus type 1 (HIV-1) entry into the cells are recognized as hopeful next-generation anti-HIV-1 drugs. It is highly desirable to develop a potent inhibitor blocking binding of glycoprotein CD4 of the cell with glycoprotein gp120 of HIV-1, because the gp120-CD4 binding is the initial step of HIV-1 entry into the cells. It has been recently reported that (-)-epigallocatechin gallate (EGCG) from green tea is an inhibitor blocking gp120-CD4 binding. But the inhibitory mechanism remains unknown. For understanding the inhibitory mechanism, extensive molecular docking, molecular dynamics simulations, and binding free-energy calculations have been performed in this study to predict the most favorable structures of CD4-EGCG, gp120-CD4, and gp120-CD4-EGCG binding complexes in water. The results reveal that EGCG binds with CD4 in such a way that the calculated binding affinity of gp120 with the CD4-EGCG complex is negligible. So, the favorable binding of EGCG with CD4 can effectively block gp120-CD4 binding. The calculated CD4-EGCG binding affinity (DeltaG(bind) = -5.5 kcal/mol, K(d) = 94 microM) is in excellent agreement with available experimental data suggesting IC(50) approximately 100 microM for EGCG-blocking CD4-gp120 binding. These results and insights provide a rational basis for future design of novel, more potent inhibitors to block gp120-CD4 binding.

Anti-HIV Agents↗

PubMed2006

A model structure for the heterodimer apoA-IMilano-apoA-II supports its peculiar susceptibility to proteolysis.

In this study, we propose a structure for the heterodimer between apolipoprotein A-I(Milano) and apolipoprotein A-II (apoA-I(M)-apoA-II) in a synthetic high-density lipoprotein (HDL) containing L-alpha-palmitoyloleoyl phosphatidylcholine. We applied bioinformatics/computational tools and procedures, such as molecular docking, molecular and essential dynamics, starting from published crystal structures for apolipoprotein A-I and apolipoprotein A-II. Structural and energetic analyses onto the simulated system showed that the molecular dynamics produced a stabilized synthetic HDL. The essential dynamic analysis showed a deviation from the starting belt structure. Our structural results were validated by limited proteolysis experiments on HDL from apoA-I(M) carriers in comparison with control HDL. The high sensitivity of apoA-I(M)-apoA-II to proteases was in agreement with the high root mean-square fluctuation values and the reduction in secondary structure content from molecular dynamics data. Circular dichroism on synthetic HDL containing apoA-I(M)-apoA-II was consistent with the alpha-helix content computed on the proposed model.

Apolipoprotein A-I↗

PubMed2026

In silico screening of anti-atherosclerotic compounds from Morus alba leaves by machine learning and network pharmacology.

OBJECTIVE: This study integrates machine learning with network pharmacology, molecular docking, and molecular dynamics simulations to screen bioactive compounds from Mulberry leaves and elucidate their potential mechanisms against atherosclerosis (AS). METHODS: A training dataset of anti-AS active compounds was compiled and encoded as Morgan fingerprints. Three machine learning classifiers, specifically Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XG-Boost), were constructed and evaluated using multiple performance metrics. Potential active components from Mulberry leaves and AS-related targets were retrieved, followed by protein-protein interaction network construction and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was then performed to evaluate binding affinities between core targets and candidate compounds, and the most stable complex was subjected to molecular dynamics simulations using GROMACS (2025). RESULTS: The RF model achieved superior performance (accuracy= 0.8354, F1 = 0.8408, AUC = 0.9119) with 100% external validation accuracy. Thirteen anti-AS candidates were prioritized from mulberry leaves, four of which have been previously documented. Network pharmacology revealed AKT1 and IL6 as core targets, enriched in pathways such as endocrine resistance. Molecular docking and dynamics simulations confirmed strong binding between oxysanguinarine and AKT1, with the complex exhibiting high stability. CONCLUSION: The RF model provides a reliable computational tool for prioritizing anti-AS compounds from Mulberry leaves. The integrated analysis reveals that Mulberry leaves exert anti-atherosclerotic effects through multi-target (e.g., AKT1, IL6) and multi-pathway (e.g., PI3K-Akt) mechanisms, offering a framework for further experimental validation.

Morus↗

PubMed2003

Molecular recognition and docking algorithms.

Molecular docking is an invaluable tool in modern drug discovery. This review focuses on methodological developments relevant to the field of molecular docking. The forces important in molecular recognition are reviewed and followed by a discussion of how different scoring functions account for these forces. More recent applications of computational chemistry tools involve library design and database screening. Last, we summarize several critical methodological issues that must be addressed in future developments.

Algorithms↗

PubMed2026

Machine Learning in Hyperlipidaemia Research: Screening and Experimental Insights into Lipid Metabolism Modulators.

Hyperlipidemia, characterized by elevated blood lipid levels, represents a major global health concern due to its strong association with cardiovascular disease, diabetes, and metabolic syndrome. While current therapies - such as statins, fibrates, bile acid sequestrants, and PCSK9 inhibitors - are effective in controlling hyperlipidemia, they are often associated with adverse effects, potential drug resistance, and suboptimal efficacy in certain patient populations. All of the above underscore the urgent need for safer and more effective therapeutic alternatives. Among the major molecular targets involved in the regulation of lipid metabolism are HMG-CoA reductase, PCSK9, peroxisome proliferator-activated receptors (PPARs), cholesteryl ester transfer protein (CETP), and nuclear receptors, including the liver X receptor (LXR) and farnesoid X receptor (FXR), which are also targets for future antihyperlipidemic drug development. Recent advancements in artificial intelligence (AI) and machine learning (ML) have significantly transformed and accelerated drug discovery by enabling the processing of vast amounts of genomic, proteomic, and chemical data. Furthermore, ML tools such as quantitative structure-activity relationship (QSAR) modelling, deep learning, random forest, and support vector machines (SVM) have proven predictive and effective in identifying novel lipid metabolism modulators, thereby enhancing the efficacy and accuracy of virtual screening. Meanwhile, molecular docking has become an integral part of structure-based drug design (SBDD), and software such as AutoDock, Glide, and GOLD have proven effective in generating accurate ligand-target docking models. Molecular docking, together with ML-based approaches, enables the identification of potent and selective drug candidates. Overall, the combination of ML and molecular docking offers an efficient and accurate platform for antihyperlipidemic drug discovery, helping to overcome the limitations of currently available therapeutic strategies.

HMG-CoA reductase↗

PubMed1991

"Soft docking": matching of molecular surface cubes.

Molecular recognition is achieved through the complementarity of molecular surface structures and energetics with, most commonly, associated minor conformational changes. This complementarity can take many forms: charge-charge interaction, hydrogen bonding, van der Waals' interaction, and the size and shape of surfaces. We describe a method that exploits these features to predict the sites of interactions between two cognate molecules given their three-dimensional structures. We have developed a "cube representation" of molecular surface and volume which enables us not only to design a simple algorithm for a six-dimensional search but also to allow implicitly the effects of the conformational changes caused by complex formation. The present molecular docking procedure may be divided into two stages. The first is the selection of a population of complexes by geometric "soft docking", in which surface structures of two interacting molecules are matched with each other, allowing minor conformational changes implicitly, on the basis of complementarity in size and shape, close packing, and the absence of steric hindrance. The second is a screening process to identify a subpopulation with many favorable energetic interactions between the buried surface areas. Once the size of the subpopulation is small, one may further screen to find the correct complex based on other criteria or constraints obtained from biochemical, genetic, and theoretical studies, including visual inspection. We have tested the present method in two ways. First is a control test in which we docked the components of a molecular complex of known crystal structure available in the Protein Data Bank (PDB). Two molecular complexes were used: (1) a ternary complex of dihydrofolate reductase, NADPH and methotrexate (3DFR in PDB) and (2) a binary complex of trypsin and trypsin inhibitor (2PTC in PDB). The components of each complex were taken apart at an arbitrary relative orientation and then docked together again. The results show that the geometric docking alone is sufficient to determine the correct docking solutions in these ideal cases, and that the cube representation of the molecules does not degrade the docking process in the search for the correct solution. The second is the more realistic experiment in which we docked the crystal structures of uncomplexed molecules and then compared the structures of docked complexes with the crystal structures of the corresponding complexes. This is to test the capability of our method in accommodating the effects of the conformational changes in the binding sites of the molecules in docking.(ABSTRACT TRUNCATED AT 400 WORDS)

Antigen-Antibody Complex↗

PubMed2026

Exploring the Potential Molecular Targets of Cyanidin-3-O-glucoside for Type 2 Diabetes Mellitus Treatment.

INTRODUCTION: This study aims to elucidate the multi-target molecular mechanism of cyanidin-3-O-glucoside (C3G) in treating Type 2 Diabetes (T2DM) through network pharmacology methods. METHODS: The study was designed to predict the targets of C3G through public databases and to screen for T2DM-related targets. Protein-protein interaction (PPI) network analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the common targets. Core targets were further validated through molecular docking and molecular dynamics (MD) simulations. RESULTS: This research identified a total of 57 potential targets of C3G in the treatment of T2DM. Subsequent PPI analysis identified ALB (Degree=43), AKT1 (Degree=41), and TNF (Degree=41) as the top three hub proteins. Pathway analysis indicated significant involvement in the insulin signaling pathway (P = 4.205×10-9), AMPK signaling pathway (P = 9.582×10-7), and FoxO signaling pathway (P = 1.315×10-6). Molecular docking revealed strong binding affinities between C3G and NOS3 (-9.5 kcal/mol), PPARG (-9.0 kcal/mol), TNF (-8.5 kcal/mol), and INSR (-8.4 kcal/mol). MD simulations further confirmed that the C3G-target complex has excellent binding stability. DISCUSSION: C3G may intervene in the pathological progression of T2DM by regulating key pathways such as insulin sensitivity, inflammatory responses, and oxidative stress. Further studies suggest that INSR and NOS3 may be new targets through which C3G exerts its effects, but their specific mechanisms and in vivo biological functions still need to be elucidated by subsequent experiments. CONCLUSION: C3G may intervene in the progression of T2DM in a multi-pathway synergistic manner by targeting key molecules such as INSR and NOS3.

Anthocyanins↗

PubMed2026

Integrative computational analysis combining network pharmacology, regulatory network modeling, and molecular dynamics reveals the mechanisms of Quanshen compound in ITP.

UNLABELLED: Immune thrombocytopenia (ITP) is a hemorrhagic disorder caused by immune dysfunction. Quanshen Compound (QSC) is an in-house preparation developed by the Uyghur Hospital in Hotan Prefecture. This study primarily investigates and validates the potential pharmacological basis and mechanism of action of QSC in modulating immune thrombopoiesis. Based on the multi-database screening of the QSC and the related targets of ITP, the intersection was obtained to construct a protein-protein interaction (PPI) network and screen the core targets; the intersection targets were analyzed for gene ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using R packages; a component-target-pathway network was constructed to screen the key active components and their mechanisms of action. At the same time, the TF-mRNA-miRNA regulatory network of the core targets was constructed, and chromosome localization and subcellular localization analysis were performed; further, the binding stability of key components and core targets was verified through molecular docking and molecular dynamics simulation. A total of 227 potential target sites were screened out, among which TNF, IL6, AKT1, TP53 and IL1B were the core targets. The enrichment results indicated that these intersecting target sites mainly participated in inflammatory responses, immune regulation and hemostasis-related biological processes, and were significantly enriched in the PI3K-Akt signaling pathway, Toll-like receptor signaling pathway, Th17 cell differentiation and PD-1/PD-L1 signaling pathway. The core target TF-mRNA-miRNA regulatory network contained 184 nodes and 200 edges, suggesting that the core targets were subject to multi-level regulation. Molecular docking results showed that the main active components had good binding activity with the core targets, and molecular dynamics simulation further verified the stability of the complex. QSC may improve ITP through a multi-component, multi-target, and multi-pathway synergistic mechanism involving key targets such as TNF, IL6, AKT1, TP53, and IL1B, as well as the PI3K-Akt signaling pathway. These findings provide new insights into the potential therapeutic mechanisms of QSC against ITP and warrant further experimental validation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s40203-026-00718-0.

Immune thrombocytopenia↗

PubMed2026

Integrated dual transcriptome sequencing and experimental validation reveal potential mechanisms of baicalin against pneumocystis pneumonia in immunosuppressed rats.

BACKGROUND: Pneumocystis pneumonia (PCP) remains a major cause of morbidity and mortality in immunocompromised individuals. Although baicalin (Ba), a natural bioactive flavonoid, has demonstrated protective and therapeutic effects against PCP, its molecular mechanisms remain undefined. We employed dual RNA sequencing (dual RNA-seq) to characterize host and pathogen transcriptional responses to Ba treatment in an immunosuppressed rat model of PCP. METHODS: Comparative transcriptomic analyses identified differentially expressed genes in both the host and Pneumocystis, followed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses. Candidate targets were further investigated using network pharmacology, protein-protein interaction analysis, molecular docking, and molecular dynamics simulations. Key findings were validated by immunohistochemistry, enzyme-linked immunosorbent assay, and quantitative PCR. RESULTS: Ba markedly remodeled host and pathogen transcriptomes. Host transcriptomic analyses showed that Ba attenuated inflammatory and oxidative stress responses by modulating immune-related pathways, including Toll-like receptor, NF-κB, cytokine-cytokine receptor interaction, chemokine signaling, Th17 cell differentiation, and antigen processing and presentation. Experimental validation demonstrated that Ba reduced pulmonary expression of indoleamine 2,3-dioxygenase 1 (IDO1), Toll-like receptor 2 (TLR2), and TLR4 while increasing nuclear factor erythroid 2-related factor 2 (Nrf2) and its downstream antioxidant enzyme heme oxygenase-1 (HO-1). Pathogen transcriptomic analysis identified Pneumocystis Rtt109 (PcRtt109), a fungal histone acetyltransferase, as a potential pathogen-specific target that was significantly downregulated after Ba treatment. Molecular docking and molecular dynamics simulations supported stable interactions between Ba and IDO1, Nrf2, TLR2, TLR4, and PcRtt109, with the strongest predicted binding observed for PcRtt109. CONCLUSION: Dual RNA-seq revealed that Ba exerts anti-PCP activity through coordinated modulation of host and pathogen molecular networks. Its therapeutic effects are associated with suppression of inflammatory signaling, enhancement of antioxidant defenses, and inhibition of a fungal virulence-associated target. These findings provide mechanistic insights into host-pathogen interactions during PCP and support Ba as a potential therapeutic candidate for PCP.

Nrf2↗

PubMed2026

Exploring the mechanism of Shengmai San in treating lung adenocarcinoma based on bioinformatics and molecular dynamics simulation.

To investigate the mechanism of Shengmai San (SMS) in the treatment of lung adenocarcinoma (LUAD) based on an integrated strategy combining "network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulation," aiming to provide a precise combination therapy strategy and identify potential bioactive compounds. Differentially expressed genes in LUAD were identified from the Gene Expression Omnibus database using R (originally developed at Bell Laboratories and currently managed by Lucent Technologies). SMS components (ginseng, Ophiopogon japonicus, and Schisandra chinensis) were retrieved from encyclopaedia of traditional Chinese medicine, with Lipinski-compliant compounds selected. Compound targets were predicted via SwissTargetPrediction and Similarity Ensemble Approach. Intersecting targets between differentially expressed genes and compound targets were identified for "herbs-compounds-targets-disease" network construction. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Hub targets were identified by analyzing the protein-protein interaction network. High-prognostic relevance targets were screened from The Cancer Genome Atlas. Compounds targeting these were identified through the herbs-compounds-targets-disease network, and absorption, distribution, metabolism, excretion, and toxicity-compliant compounds were selected using SwissADME (a web-based tool provided by the Molecular Modeling Group of the Swiss Institute of Bioinformatics). Core regulatory targets were identified through molecular docking, with complex stability assessed by molecular dynamics simulations. The key bioactive compounds of SMS for treating LUAD were identified as 7-hydroxy-2,5-dimethyl-4H-1-benzopyran-4-one, N-trans-feruloyltyramine, paprazine, and (E)-N-[(2S)-2-hydroxy-2-(4-hydroxyphenyl)ethyl]-3-(4-hydroxyphenyl)prop-2-enamide. Hub targets included AURKA, CCNA2, CCNB1, CDK1, CHEK1, KIF11, NEK2, PLK1, TTK, and TYMS. Among these, CDK1, CHEK1, and PLK1 demonstrated both high-prognostic relevance and strong binding affinity with SMS, emerging as core regulatory targets for SMS in LUAD treatment. Mechanistically, SMS exerts its anticancer effects primarily by modulating the tumor necrosis factor, interleukin-17, cell cycle, and Lipid and atherosclerosis signaling pathways. The active components of SMS, such as paprazine, may exert antitumor effects partly through downregulating CDK1, CHEK1, and PLK1 expression. Although the present study did not examine drug-resistance models or combination regimens, our findings raise the possibility that, in patients with high expression of these genes, combining SMS with standard chemotherapy or targeted therapy could potentially enhance chemosensitivity and mitigate the development of resistance. This hypothesis, however, requires formal testing in appropriate preclinical models and functional validation studies.

Molecular Dynamics Simulation↗

PubMed2026

LARS promotes hepatocellular carcinoma progression via the PI3K/AKT/mTOR pathway and interaction with RPS5, and serves as a prognostic biomarker.

BACKGROUND: Hepatocellular carcinoma (HCC) caused many cancer deaths around the world. Its progression involves complex mechanisms, creating an urgent need to identify new therapeutic targets. Leucine-tRNA synthetase (LARS) is a key enzyme for protein synthesis, but its specific role and mechanism in HCC are not well understood. PURPOSE: This research aims to investigate the biological function, molecular mechanism, and clinical relevance of the LARS gene in HCC progression, to assess its potential as a treatment target. METHODS: LARS expression was assessed in HCC cell lines (PLC-PRF-5, HCC-LM3) and in mouse subcutaneous tumor models using siRNA and adeno-associated virus (AAV). Techniques including Cell Counting Kit-8(CCK-8), colony formation, EdU, Transwell, wound healing, and flow cytometry were used to measure cell proliferation, migration, invasion, and apoptosis. RNA-seq, proteomics (TMT), western blot, co-immunoprecipitation (Co-IP) with mass spectrometry, molecular docking, and molecular dynamics simulation were employed to study the affected signaling pathway (PI3K/AKT/mTOR) and interacting protein (RPS5). The TCGA (The Cancer Genome Atlas) database and UALCAN platform were used to analyze links between LARS expression and clinicopathological features or prognosis in HCC patients. RESULTS: Reducing LARS expression significantly inhibited the proliferation, colony formation, migration, and invasion of HCC cells, while promoting apoptosis. In mice, LARS knockdown markedly slowed tumor growth. Mechanistic studies showed that reducing LARS expression levels affected the PI3K/AKT/mTOR signaling pathway and led to decreased levels of the key interacting protein RPS5. Overexpressing RPS5 partly reversed the proliferation inhibition caused by LARS depletion. Molecular docking and dynamics simulations suggested that the environmental contaminant triphenyl phosphate (TPP) might bind to the LARS protein. Clinical data analysis revealed that LARS expression is higher in HCC tissues. High LARS expression was significantly associated with shorter overall survival (OS) in patients and correlated positively with various clinical features like tumor stage, grade, and TP53 mutation status. CONCLUSION: LARS helped HCC become worse by affecting the PI3K/AKT/mTOR pathway and working with RPS5. High LARS meant a worse outcome for patients. This suggested LARS could be used to predict disease or as a treatment target in HCC.

Carcinoma, Hepatocellular↗

PubMed1999

Exhaustive docking of molecular fragments with electrostatic solvation.

A new method is presented for docking molecular fragments to a rigid protein with evaluation of the binding energy. Polar fragments are docked with at least one hydrogen bond with the protein while apolar fragments are positioned in the hydrophobic pockets. The electrostatic contribution to the binding energy, which consists of screened intermolecular energy and protein and fragment desolvation terms, is evaluated efficiently by a numerical approach based on the continuum dielectric approximation. The latter is also used to predetermine the hydrophobic pockets of the protein by rolling a low dielectric sphere over the protein surface and calculating the electrostatic desolvation of the protein and van der Waals interaction energy. The method was implemented in the program SEED (solvation energy for exhaustive docking). The SEED continuum electrostatic approach has been successfully validated by a comparison with finite difference solutions of the Poisson equation for more than 2,500 complexes of small molecules with thrombin and the monomer of HIV-1 aspartic proteinase. The fragments docked by SEED in the active site of thrombin reproduce the structural features of the interaction patterns between known inhibitors and thrombin. Moreover, the combinatorial connection of these fragments yields a number of compounds that are very similar to potent inhibitors of thrombin. Proteins 1999;37:88-105.

Computer Simulation↗

PubMedDate not supplied

Molecular modeling studies of human A3 adenosine antagonists: structural homology and receptor docking.

Molecular modeling studies were conducted on various chemically diverse classes of human A3 adenosine receptor antagonists (hA3ANTs), such as adenines, xanthines, triazoloquinazolines, flavonoids, thiazolopyridines, 6-phenyl-1, 4-dihydropyridines, and 6-phenylpyridines. Using a combination of ab initio quantum mechanical calculations, electrostatic potential map comparison, and the steric and electrostatic alignment (SEAL) method, a general pharmacophore map for hA3ANTs has been derived. Based on the proposed pharmacophore map, we hypothesize that the receptor binding properties of different A3 antagonist derivatives are due to recognition at a common region inside the receptor binding site and, consequently, a common electrostatic potential profile. A model of the human A3 receptor, docked with the triazoloquinazoline reference ligand CGS 15953 (9-chloro-2-(2-furyl)[1,2,4]triazolo[1,5-c]quinazolin-5-amine), was built and analyzed to help interpret these results. All other antagonist structures were docked inside the receptor according to the results obtained through the steric and electrostatic alignment (SEAL) approach using the structure of CGS 15953 as a template. The receptor model was derived from primary sequence comparison, secondary structure predictions, and three-dimensional homology building, using rhodopsin as a template. An energetically refined 3D structure of the ligand-receptor complex was obtained using our recently introduced cross-docking procedure (J. Med. Chem. 1998, 41, 1456-1466), which simulates the ligand-induced reorganization of the native receptor structure.

Animals↗

PubMed2026

Discovery of NAT-6-321056 as a novel modulator of VEGFR2 signaling to suppress tumor angiogenesis.

Vascular endothelial growth factor receptor 2 (VEGFR2) is a master regulator of angiogenesis and cancer progression. However, current VEGFR2 modulators face significant challenges, including off-target toxicity and acquired resistance, underscoring the urgent need for novel therapeutic agents with improved efficacy and safety profiles. Here, we reported that virtual screening of 39,442 natural products from the ZINC natural products-derived library, coupled with molecular docking and molecular dynamics (MD) simulations to evaluate the binding stability of candidate compounds, identified NAT-6-321056 as a highly promising modulator of VEGFR2 signaling. Biological evaluations demonstrated that NAT-6-321056 exerted potent inhibition on the growth of a broad spectrum of cancer cells, including both solid tumors and hematological malignancies. In EA.hy 926 endothelial cells and SK-N-DZ neuroblast cells, the compound significantly suppressed proliferation, migration, and invasion. Microscale thermophoresis (MST) confirmed direct binding of NAT-6-321056 to VEGFR2 with favorable affinity. Kinase profiling against a panel of 33 kinases indicated that NAT-6-321056 exhibited a multi-kinase modulation profile. Mechanistic studies revealed that NAT-6-321056 suppressed the expression of hypoxia-inducible factor 1-alpha (HIF-1α) and was associated with reduced VEGFR2 phosphorylation and attenuation of the downstream ERK/JNK/AKT signaling pathways. Moreover, NAT-6-321056 exhibited robust in vivo anti-angiogenic effects in both the chick chorioallantoic membrane (CAM) assay and transgenic zebrafish vascular fluorescence imaging models. Computational absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction suggested acceptable drug-like properties. Collectively, these findings demonstrated that NAT-6-321056 is a promising modulator of VEGFR2 signaling with potent anti-angiogenic activity and represents a viable candidate for cancer therapy.

Vascular Endothelial Growth Factor Receptor-2↗

PubMed2026

Toxicological effects of propyl 4-hydroxybenzoate on gallstone pathogenesis: An integrated mendelian randomization, network toxicology, and experimental study.

BACKGROUND: Gallstone disease is a prevalent digestive disorder with substantial global socioeconomic burden. Propyl 4-hydroxybenzoate (PP), a widely used paraben preservative, exhibits potential metabolic and hepatic toxicity, yet its role in gallstone pathogenesis remains unclear. This study aimed to explore the causal association between PP exposure and gallstone formation and the underlying mechanism. METHODS: Two-sample Mendelian randomization (MR) was performed using genome-wide association study (GWAS) data. Network toxicology, molecular docking, and molecular dynamics simulation were applied to screen for core targets. In vivo experiments, transcriptome sequencing, Western blot (WB), and ELISA were conducted for mechanistic validation. RESULTS: MR confirmed a causal link between circulating PP levels and an elevated risk of gallstones (P < 0.05), with AKT1 identified as the key target. In mice, PP aggravated gallstone formation by activating the AKT1-NF-κB-CXCL1 pathway, enhancing hepatic inflammation and neutrophil extracellular traps (NETs) formation; these effects were reversed by AKT inhibition. CONCLUSION: PP promotes gallstone formation via the AKT1-NF-κB-CXCL1-NETs axis. Our findings highlight PP as an environmental risk factor for gallstones, providing novel insights into their prevention and targeted therapy.

Animals↗