Journal of Biomolecular Structure & Dynamics最新文献

Lung adenocarcinoma is highly heterogeneous at the molecular level between different stages; therefore, understanding molecular mechanisms contributing to such heterogeneity is needed. In addition, multiple stages of progression are critical factors for lung adenocarcinoma treatment. However, previous studies showed that cancer progression is associated with altered lncRNA expression, highlighting the tissue-specific and developmental stage-specific nature of lncRNAs in various diseases. Therefore, a study using an integrated network approach to explore the role of lncRNA in carcinogenesis was done using expression profiles revealing stage-specific and conserved lncRNA biomarkers in lung adenocarcinoma. We constructed ceRNA networks for each stage of lung adenocarcinoma and analysed them using network topology, differential co-expression network, protein-protein interaction network, functional enrichment, survival analysis, genomic analysis and deep learning to identify potential lncRNA biomarkers. The co-expression networks of healthy and three successive stages of lung adenocarcinoma have shown different network properties. One conserved and four stage-specific lncRNAs are identified as genome regulatory biomarkers. These lncRNAs can successfully identify lung adenocarcinoma and different stages of progression using deep learning. In addition, we identified five mRNAs, four miRNAs and twelve novel carcinogenic interactions associated with the progression of lung adenocarcinoma. These lncRNA biomarkers will provide a novel perspective into the underlying mechanism of adenocarcinoma progression and may be further helpful in early diagnosis, treatment and prognosis of this deadly disease.

Glycyrrhizic acid (GLA) is the most important bioactive constituent of licorize root and exhibits antiviral, antimicrobial, anti-oxidant, anti-inflammatory, anti-allergic, and antitumor activities. GLA has an amphiphilic nature consisting of two hydrophilic and one hydrophobic part, and its mechanism of action could be mediated by its incorporation into the membrane. Furthermore, GLA presents two different forms, protonated (GLA) and deprotonated (GLAD), and has been suggested that their location inside the membrane could be different. Since GLA could be a source against many types of diseases, we have localized the GLA molecule in the presence of a complex membrane and established the detailed interactions of GLA with lipids using all-atom molecular dynamics. Our outcomes sustain that GLA/GLAD tend to locate amid the CHOL oxygen atom and the phospholipid phosphates, preferably perpendicular to the membrane surface, increasing membrane fluidity. Interestingly, GLA and GLAD tend to be surrounded by specific phospholipids, different for each type of molecule. Outstandingly, both GLA and GLAD tend to spontaneously associate in solution forming aggregates, precluding them from inserting into the membrane and, therefore, interacting with it. Consequently, some of the biological properties of GLA/GLAD could be credited to the alteration of the membrane biophysical properties by interacting with specific lipids. However, the formation of an aggregate in solution could hinder its bioactive properties and should be considered a suited vehicle when prepared to be used in biological or clinical assays.

HDAC8 and HDAC2 are recently reported to be overexpressed in cervical cancer. To date, studies related to the use of dual targeted HDAC inhibitor to treat cervical cancer are not well explored. Again, majority of the selective HDAC inhibitors discovered so far are hydroxamic acids, which have multiple adverse side-effects due to their strong zinc chelating ability. In this study, we repurposed DrugBank molecules to identify novel non hydroxamate compounds as potential HDAC8/2 dual inhibitors that can be effective for cervical cancer management. Therefore, a comprehensive integrated in silico approach, involving two-tier virtual screening, has been adopted. An initial e-pharmacophore model generation based on the co-ligands associated with HDAC8 and HDAC2 and subsequent PBVS of 12223 drug molecules were performed which eventually yielded 658 hits having fitness scores ≥ 1.0 for both the proteins. Then, SBVS for these hits was done using Glide XP method into the HDAC8 and HDAC2 crystal structures which resulted in 52 hits having XPGS ≤ -9.0 kcal/mol against both the proteins. Following this, they were re-docked into other HDAC isoforms to confirm isoform selectivity. DB11747, DB03973, DB03812, DB07890, and DB03448 were identified as top hits and were finally subjected to molecular dynamics simulation for stability of the complexes and MM-GBSA studies to calculate binding free energies. These hits have stable interactions with both HDAC8 and HDAC2 protein binding sites. In silico ADMET studies brought to limelight the promising pharmacokinetics and safety profiles of the hits. In silico cytotoxicity prediction studies also revealed potent anticancer activity.

Breast cancer (BC) is the most dominant kind of cancer, which grows continuously and serves as the second highest cause of death for women worldwide. Early BC prediction helps decrease the BC mortality rate and improve treatment plans. Ultrasound is a popular and widely used imaging technique to detect BC at an earlier stage. Segmenting and classifying the tumors from ultrasound images is difficult. This paper proposes an optimal deep learning (DL)-based BC detection system with effective pre-trained transfer learning models-based segmentation and feature learning mechanisms. The proposed system comprises five phases: preprocessing, segmentation, feature learning, selection, and classification. Initially, the ultrasound images are collected from the breast ultrasound images (BUSI) dataset, and the preprocessing operations, such as noise removal using the Wiener filter and contrast enhancement using histogram equalization, are performed on the collected data to improve the dataset quality. Then, the segmentation of cancer-affected regions from the preprocessed data is done using a dilated convolution-based U-shaped network (DCUNet). The features are extracted or learned from the segmented images using spatial and channel attention including densely connected convolutional network-121 (SCADN-121). Afterwards, the system applies an enhanced cuckoo search optimization (ECSO) algorithm to select the features from the extracted feature set optimally. Finally, the ECSO-tuned long short-term memory (ECSO-LSTM) was utilized to classify BC into '3' classes, such as normal, benign, and malignant. The experimental outcomes proved that the proposed system attains 99.86% accuracy for BC classification, which is superior to the existing state-of-the-art methods.

Transcription is a fundamental process involving the interaction of RNA polymerase II and related transcription factors. TFIIB is a transcription factor that plays a significant role in the formation and stability of the preinitiation complex in a precise orientation, as well as in the control of initiation and pre-elongation steps. At the initiation step, TFIIB interacts with three structures: the end of the TATA-binding protein, a GC-rich DNA sequence followed by the TATA box, and the C-terminal domain of RNA polymerase II. It is known that RNA polymerase II is a glycoprotein and contains O-GlcNAc sugar at the C-terminal domain during the initiation stage of transcription. However, it is unclear whether the transcription factors interacting with RNA polymerase II are glycoproteins or not. The study aims to determine the glycosylation (N- and/or O-linked glycosylations) of TFIIB by using bioinformatics in one invertebrate and seven vertebrate species and experimental methods in the sea urchin Paracentrotus lividus oocyte. Both bioinformatics and experimental analysis have shown that TFIIB is a glycoprotein. In addition, PNGase-F enzyme treatment, lectin blotting, and colloidal-gold conjugated lectin labeling results revealed that TFIIB contains O-linked GalNAc, mannose, GlcNAc, and α-2,3-linked sialic acid. Based on our results, we suggest that glycosylation modification may be involved in the transcription mechanism of the TFIIB protein.

The lysosomal cysteine peptidase Cathepsin B is identified as a pivotal contributor to cancer development. In the pursuit of discovering less toxic inhibitors for Cathepsin B, various organic compounds have undergone thorough investigation and are being studied at the moment in clinical studies for cancer treatment. Notably, curcumin and resveratrol emerge as prominent candidates. However, the precise molecular mechanism underlying the inhibition of Cathepsin B by these compounds remains elusive. To address this gap, we conducted molecular docking and dynamics studies to unravel the interaction dynamics between Cathepsin B and phytochemicals such as curcumin and resveratrol. Remarkably, Molecular docking studies revealed that curcumin and resveratrol exhibit high binding affinities 7.599 and 6.103 kcal/mol, respectively, positioning them as promising inhibitors for Cathepsin B. Further insights from 150 ns of molecular dynamics simulations, incorporating structural analyses encompassing RMSF, RMSD, Rg, SASA, and H-bond analysis, indicate the superior stability of curcumin compared to resveratrol. Additionally, we assessed their drug-likeness properties using the PreADMET web server, and the MM/BPSA method facilitated the calculation of binding energies for the complexes. On targeting Cathepsin B, this research promises to contribute to the development of drugs that inhibit the progression of cancer.

The potential health risks associated with radionuclides, particularly actinides, have prompted investigations into their interactions with body fluids in living organisms. Human serum albumin (HSA), a plenteous plasma protein with extraordinary binding capacities, is a key player in these interactions. The present study is intended at understanding the interplay between metal ions, namely, zinc and uranyl ions and fatty acids binding with HSA, using all atom equilibrium and non-equilibrium molecular dynamics simulations. Results highlight distinct behaviours of zinc and uranyl ions, elucidating how their interactions with HSA are influenced by the presence of fatty acids. Hydrogen bonding dynamics analysis reveals the disruption of existing bonds due to fatty acid binding, contrasting with the weakening effect caused by metal binding. The resulting conformational changes have significant implications for HSA's structure and dynamics. The potential of mean force (PMF) plots reveals binding and unbinding routes for zinc and uranyl ions, both in fatty acid's presence and absence. Short-range interactions reveal distinct binding behaviours of zinc and uranyl ions, altered by fatty acids, providing insights into unbinding pathways and correlating with the PMF plots.

Phosphodiesterase-5 (PDE5) is a homodimeric enzyme that specifically targets cyclic guanosine monophosphate (cGMP), that mediates many downstream effects such as vasodilation, neurotransmission, and calcium homeostasis. Considering the functions of cGMP, inhibition of PDE5 has been established to have several therapeutic effects in disease conditions such as cancer, cardiovascular diseases and Alzheimer's disease. Consequently, many PDE5 inhibitors were developed but with severe adverse effects such as non-arteritic anterior ischemic optic neuropathy (NAION), priapism, etc. Hence, in our study for the identification of new PDE5 inhibitors from alternative sources, Cassia auriculata L. was identified as a potential PDE5 inhibitors with 56.23% inhibition at 100 μg/mL in vitro. In addition, the respective phytoconstituents were evaluated through molecular docking, interaction studies and MM/GBSA binding free energy calculations, identifying two potential flavone C-glycosides, lucenin-II (-15.977, dG bind = -38.8), stellarin-II (-15.099, dG bind = -34.59), and a flavan derivative (2S)-7,4-dihydroxyflavan(4β-8)-catechin, in comparison to sildenafil (-10.890, dG bind = -75.4) and having frequent contacts with Phe 786, Phe 820, Ser 663, Tyr 664, and other crucial residues at the catalytic site of PDE5. Molecular dynamics simulations performed for 100 ns showed structural stability and compactness of the candidates through RMSD, RMSF which showed less fluctuations. The ADMET analysis revealed favorable pharmacokinetics, and pharmacodynamic properties with no subsequent toxicity in normal cells. The biological target class prediction identified enzymes with similar properties and icariin, which is a well-established natural PDE5 inhibitor was identified as a structurally similar analogue. These findings could lead to the development of novel natural product based PDE5 inhibitors.

Thestructure and function of a protein are closely connected. Changes in a protein structure can impact on its function. Nephrotic syndrome type 4 (NPHS4) is an uncommon genetic condition caused by mutations in the WT1 gene, which codes for the wilms tumor-1 protein. Several studies have discovered that patients with nephrotic syndromes are resistant to steroid therapy and are likely to develop end-stage renal failure. The use of phytochemicals-based therapeutics is in demand due to their high potential and low toxicity. Based on this context, we employed the Autodock raccoon to screen 67 distinct potent phytochemicals from the Boerhavia diffusa (B.diffusa) plant against the wild type and mutant model at position C388R (cysteine is replaced with arginine at position 388) of the C-terminal DNA binding domain of the wilms tumor-1 protein. Out of 67 active compounds, only 10 compounds (lunamarine, kaempferol, boeravinone B, boeravinone E, boeravinone A, boeravinone F, boeravinone J, boeravinone P, boerhaavic acid and 4',7-dihydroxy-3'-methylflavone) were screened based on drug-likeness properties and binding energy for explicit water ligand docking against wild and mutant model of C-terminal DNA binding domain of wilms tumor-1 protein. Consequently, the hydrated form of boeravinone F and boeravinone A demonstrated the highest binding energy against the protein mutant model described above, the binding energies were -9.56 and -8.96 Kcal/mol, respectively. Followed by explicit water ligand docking the microscopic properties of wild type, mutant, mutant-boeravinone F complex, and mutant-boeravinone A complex systems were evaluated using molecular dynamics simulation steps with 100 ns of trajectory. The findings indicate that, due to mutation the mutant model system had decreasing stability and decreasing compactness nature. However, boeravinone A effectively monitored the mutant system's stability and improved compactness nature after binding with the mutant model. Boeravinone A with the mutant model complex system was determined to have the lowest energy point as compared to other studied systems. The study revealed minimal structural alterations and reduced conformational mobility.

The Tobacco Mosaic Virus (TMV) is a critical plant virus that can cause a significant drop in crop yield. To understand how recombinant coat-protein impacts the affinity and assembly of TMV's subunits, research is being conducted to assess the effect of recombinant protein on virus resistance. To develop a recombinant coat-protein that can lower TMV infection rates in plants, a design strategy was employed that involves creating defective viral subunits leading to incorrect assembly. This method is similar to using defective puzzle pieces that form incorrect connections resulting in disrupted viral assembly, ultimately affecting the production of mature virus particles. The study investigated the effect of mutations on one side of the Tobacco mosaic virus coat-protein using molecular modeling and dynamics simulation techniques. The simulation showed that the recombinant subunit had lower flexibility (between 0.15 to 0.20 nm) compared to the other subunits (between 0.45 to 0.75 nm), which was attributed to the smaller loop area. The study suggests an effective recombinant coat-protein with the potential to prevent virus infection by disrupting the coat-protein assembly process. This approach can be used to design a plant vaccine against viruses. Developing a recombinant protein can also provide benefits to plants such as protection from pests and enhancement of growth and productivity.