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Diagnosis and treatment of hepatocellular carcinoma or metastases rely heavily on accurate segmentation and classification of liver tumours. However, due to the liver tumor's hazy borders and wide range of possible shapes, sizes, and positions, accurate and automatic tumour segmentation and classification remains a difficult challenge. With the advancement of computing, new models in artificial intelligence have evolved. Following its success in Natural language processing (NLP), the transformer paradigm has been adopted by the computer vision (CV) community of the NLP. While there are already accepted approaches to classifying the liver, especially in clinical settings, there is room for advancement in terms of their precision. This paper makes an effort to apply a novel model for segmenting and classifying liver tumours built on deep learning. In order to accomplish this, the created model follows a three-stage procedure consisting of (a) pre-processing, (b) liver segmentation, and (c) classification. In the first phase, the collected Computed Tomography (CT) images undergo three stages of pre-processing, including contrast improvement via histogram equalization and noise reduction via the median filter. Next, an enhanced mask region-based convolutional neural networks (Mask R-CNN) model is used to separate the liver from the CT abdominal image. To prevent overfitting, the segmented picture is fed onto an Enhanced Swin Transformer Network with Adversarial Propagation (APESTNet). The experimental results prove the superior performance of the proposed perfect on a wide variety of CT images, as well as its efficiency and low sensitivity to noise.

Isorhamnetin is a flavonoid that is abundant in the fruit of Hippophae rhamnoides L. It is widely studied for its ability to modulate inflammatory responses. In this study, we evaluated the potential of isorhamnetin to prevent gram-negative sepsis. We investigated its efficacy using an Escherichia coli -induced sepsis model. Our study reveals that isorhamnetin treatment significantly enhances survival and reduces proinflammatory cytokine levels in the serum and lung tissue of E. coli -infected mice. Further, isorhamnetin treatment also significantly reduces the levels of aspartate aminotransferase, alanine amino transferase and blood urea nitrogen, suggesting that it can improve liver and kidney function in infected mice. Docking studies reveal that isorhamnetin binds deep in the hydrophobic binding pocket of MD-2 via extensive hydrophobic interactions and hydrogen bonding with Tyr102, preventing TLR4/MD-2 dimerization. Notably, binding and secreted alkaline phosphatase reporter gene assays show that isorhamnetin can interact directly with the TLR4/MD-2 complex, thus inhibiting the TLR4 cascade, which eventually causes systemic inflammation, resulting in death due to cytokine storms. We therefore presume that isorhamnetin could be a suitable therapeutic candidate to treat bacterial sepsis.

Mesenchymal-epithelial transition factor (c-Met) is a member of receptor tyrosine kinase. It involves in various cellular signaling pathways which includes proliferation, motility, migration, and invasion. Over-expression of c-Met has been reported in various cancers. Hence, it is an ideal therapeutic target for cancer. The main objective of the study is to identify crucial residues involved in the inhibition of c-Met kinase and to design a series of potent imidazo [4,5-b] pyrazine derivatives as c-Met inhibitors. Docking was used to identify important active site residues involved in the inhibition of c-Met kinase which was further validated by 100 ns of molecular dynamics simulation and free energy calculation using molecular mechanics generalized born surface area. Furthermore, binding energy decomposition identified that residues Tyr1230, Met1211, Asp1222, Tyr1159, Met1160, Val1092, Ala1108, and Leu1157 contributed favorably to the binding stability of compound 32. Receptor-guided Comparative Molecular Field Analysis (CoMFA) (q 2 = 0.751, NOC = 6, r 2 = 0.933) and Comparative Molecular Similarity Indices Analysis (COMSIA) (q 2 = 0.744, NOC = 6, r 2 = 0.950) models were generated based on the docked conformation of the most active compound 32. The robustness of these models was tested using various validation techniques and found to be predictive. The results of CoMFA and CoMSIA contour maps exposed the regions favorable to enhance the activity. Based on this information, 27 novel c-Met inhibitors were designed. These designed compounds exhibited potent activity than the most active compound of the existing dataset. Communicated by Ramaswamy H. Sarma.

Bacterial fatty acid synthesis (FAS) has been extensively studied as a potential target of antimicrobials. In FAS, FabD mediates transacylation of the malonyl group from malonyl-CoA to acyl-carrier protein (ACP). The mounting threat of nosocomial infection by multidrug-resistant Acinetobacter baumannii warrants a deeper understanding of its essential cellular mechanisms, which could lead to effective control of this highly competent pathogen. The molecular mechanisms involved in A. baumannii FAS are poorly understood, and recent research has suggested that Pseudomonas aeruginosa, a closely related nosocomial pathogen of A. baumannii, utilizes FAS to produce virulence factors. In this study, we solved the crystal structure of A. baumannii FabD (AbFabD) to provide a platform for the development of new antibacterial agents. Analysis of the structure of AbFabD confirmed the presence of highly conserved active site residues among bacterial homologs. Binding constants between AbFabD variants and A. baumannii ACP (AbACP) revealed critical conserved residues Lys195 and Lys200 involved in AbACP binding. Computational docking of a potential inhibitor, trifluoperazine, revealed a unique inhibitor-binding pocket near the substrate-binding site. The structural study presented herein will be useful for the structure-based design of potent AbFabD inhibitors., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The Bcl-2 family proteins are the central regulators of apoptosis. Due to its predominant role in cancer progression, the Bcl-2 family proteins act as attractive therapeutic targets. Recently, molecular series of Benzothiazole Hydrazone (BH) inhibitors that exhibits drug-likeness characteristics, which selectively targets Bcl-xL have been reported. In the present study, docking was used to explore the plausible binding mode of the highly active BH inhibitor with Bcl-xL; and Molecular Dynamics (MD) simulation was applied to investigate the stability of predicted conformation over time. Furthermore, the molecular properties of the series of BH inhibitors were extensively investigated by pharmacophore based 3D-QSAR model. The docking correctly predicted the binding mode of the inhibitor inside the Bcl-xL hydrophobic groove, whereas the MD-based free energy calculation exhibited the binding strength of the complex over the time period. Furthermore, the residue decomposition analysis revealed the major energy contributing residues - F105, L108, L130, N136, and R139 - involved in complex stability. Additionally, a six-featured pharmacophore model - AAADHR.89 - was developed using the series of BH inhibitors that exhibited high survival score. The statistically significant 3D-QSAR model exhibited high correlation co-efficient (R 2  = .9666) and cross validation co-efficient (Q 2  = .9015) values obtained from PLS regression analysis. The results obtained from the current investigation might provide valuable insights for rational drug design of Bcl-xL inhibitor synthesis.

Background: Bruton tyrosine kinase (Btk) plays an important role in B-cell development, differentiation, and signaling. It is also found be in involved in male immunodeficiency disease such as X-linked agammaglobulinemia (XLA). Btk is considered as a potential therapeutic target for treating autoimmune diseases and hematological malignancies., Results: In this work, a combined molecular modeling study was performed on a series of thieno [3,2-c] pyridine-4-amine derivatives as Btk inhibitors. Receptor-guided COMFA (q 2  = 0.574, NOC = 3, r 2  = 0.924) and COMSIA (q 2  = 0.646, NOC = 6, r 2  = 0.971) models were generated based on the docked conformation of the most active compound 26. All the developed models were tested for robustness using various validation techniques. Furthermore, a 5-ns molecular dynamics (MD) simulation and binding free energy calculations were carried out to determine the binding modes of the inhibitors and to identify crucial interacting residues. The rationality and stability of molecular docking and 3D-QSAR results were validated by MD simulation. The binding free energies calculated by the MM/PBSA method showed the importance of the van der Waals interaction., Conclusions: A good correlation between the MD results, docking studies, and the contour map analysis were observed. The study has identified the key amino acid residues in Btk binding pocket. The results from this study can provide some insights into the development of potent, novel Btk inhibitors.

Bruton tyrosine kinase (Btk) is a non-receptor tyrosine kinase. It is a crucial component in BCR pathway and expressed only in hematopoietic cells except T cells and Natural killer cells. BTK is a promising target because of its involvement in signaling pathways and B cell diseases such as autoimmune disorders and lymphoma. In this work, a combined molecular modeling study of molecular docking, 3D-QSAR and molecular dynamic (MD) simulation were performed on a series of 2,5-diaminopyrimidine compounds as inhibitors targeting Btk kinase to understand the interaction and key residues involved in the inhibition. A structure based CoMFA (q (2) = 0.675, NOC = 5, r (2) = 0.961) and COMSIA (q (2) = 0.704, NOC = 6, r (2) = 0.962) models were developed from the conformation obtained by docking. The developed models were subjected to various validation techniques such as leave-five-out, external test set, bootstrapping, progressive sampling and rm (2) metrics and found to have a good predictive ability in both internal and external validation. Our docking results showed the important residues that interacts in the active site residues in inhibition of Btk kinase. Furthermore, molecular dynamics simulation was employed to study the stability of the docked conformation and to investigate the binding interactions in detail. The MD simulation analyses identified several important hydrogen bonds with Btk, including the gatekeeper residue Thr474 and Met477 at the hinge region. Hydrogen bond with active site residues Leu408 and Arg525 were also recognized. A good correlation between the MD results, docking studies and the contour map analysis are observed. This indicates that the developed models are reliable. Our results from this study can provide insights in the designing and development of more potent Btk kinase inhibitors.

Background: Checkpoint kinase 1 (Chk1) has emerged as a potential therapeutic target for design and development of novel anticancer drugs., Objective: Herein, we have performed three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking analyses on a series of diazacarbazoles to design potent Chk1 inhibitors., Methods: 3D-QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Docking studies were performed using AutoDock., Results: The best CoMFA and CoMSIA models exhibited cross-validated correlation coefficient (q2) values of 0.631 and 0.585, and non-cross-validated correlation coefficient (r2) values of 0.933 and 0.900, respectively. CoMFA and CoMSIA models showed reasonable external predictabilities (r2 pred) of 0.672 and 0.513, respectively., Conclusion: A satisfactory performance in the various internal and external validation techniques indicated the reliability and robustness of the best model. Docking studies were performed to explore the binding mode of inhibitors inside the active site of Chk1. Molecular docking revealed that hydrogen bond interactions with Lys38, Glu85 and Cys87 are essential for Chk1 inhibitory activity. The binding interaction patterns observed during docking studies were complementary to 3D-QSAR results. Information obtained from the contour map analysis was utilized to design novel potent Chk1 inhibitors. Their activities and binding affinities were predicted using the derived model and docking studies. Designed inhibitors were proposed as potential candidates for experimental synthesis.

Vascular endothelial growth factor-2 receptor (VEGFR-2) kinase is a promising target for the development of novel anticancer drugs. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed on a series of tetrahydro-3H-imidazo[4,5-c]pyridine derivatives to understand the structural basis for VEGFR-2 inhibitory activity. Several 3D-QSAR models were developed using various partial atomic charge schemes. Comparative molecular field analysis (CoMFA) and Comparative molecular similarity indices analysis (CoMSIA) methods were employed to derive these models. The CoMFA models performed better than the CoMSIA models. The reliable CoMFA model was obtained with the Gasteiger-Marsili charge scheme. The model produced statistically significant results with a cross-validated correlation coefficient (q(2)) of 0.635 and a coefficient of determination (r(2)) of 0.930. The model showed reasonable predictive power with predictive correlation coefficient ([Formula: see text]) of 0.582. Robustness of the model was further checked by leave-five-out cross-validation, bootstrapping and progressive scrambling analysis. The model was found to be statistically robust and expected to assist in the design of novel compounds with enhanced VEGFR-2 inhibitory activity.

The HIV-1 envelope glycoprotein gp120 plays a vital role in the entry of virus into the host cells and is a potential antiviral drug target. Recently, indole derivatives have been reported to inhibit HIV-1 through binding to gp120, and this prevents gp120 and CD4 interaction to inhibit the infectivity of HIV-1. In this work, molecular docking, molecular dynamics (MD) and three-dimensional quantitative structure-activity relationship studies were carried out. Molecular docking studies of the most active and the least active compounds were performed to identify important residues in the binding pocket. We refined the docked poses by MD simulations which resulted in conformational changes. After equilibration, the structure of the ligand and receptor complex was stable. Therefore, we just took the last snapshot as the representative binding pose for this study. This pose for the most active inhibitor was used as a template for receptor-based alignment which was subsequently used for comparative molecular field analysis. Resultant 3D contour maps suggested smaller substituents are desirable at the 7-position of indole ring to avoid steric interactions with Ser375, Phe382 and Tyr384 residues in the active site. These results can be exploited to develop potential leads and for structure-based drug design of novel HIV-1 inhibitors.

C-C chemokine receptor type 1 (CCR1) is a chemokine receptor with seven transmembrane helices and it belongs to the G-Protein Coupled receptor (GPCR) family. It plays an important role in rheumatoid arthritis, organ transplant rejection, Alzheimer's disease and also causes inflammation. Because of its role in disease processes, CCR1 is considered to be an important drug target. In the present study, we have performed three dimensional Quantitative Structure activity relationship (3D-QSAR) studies on a series of 1-(4-Phenylpiperazin-1-yl)-2-(1H-pyrazol-1-yl) ethanone derivatives targeting CCR1. Homology modeling of CCR1 was performed based on a template structure (4EA3) which has a high sequence identity and resolution. The highest active molecule was docked into this model. Ligand-based and Receptor-based quantitative structure-activity relationship (QSAR) study was performed and CoMFA models with reasonable statistics was developed for both ligand-based (q(2)=0.606; r(2)=0.968) and receptor-guided (q(2)=0.640; r(2)=0.932) alignment methods. Contour map analyses identified favorable regions for high affinity binding. The docking results highlighted the important active site residues. Tyr113 was found to interact with the ligand through hydrogen bonding. This residue has been considered responsible for anchoring ligands inside the active site. Our results could also be helpful to understand the inhibitory mechanism of 1-(4-Phenylpiperazin-1-yl)-2-(1H-pyrazol-1-yl) ethanone derivatives thereby to design more effective ligands in the future., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Multidrug resistance (MDR) is a phenomenon whereby cancer cells experience intrinsic or acquired resistance to a broad spectrum of structurally and functionally distinct chemotherapeutic agents. Permeability glycoprotein (P-gp) is the key protein responsible for the development of MDR in cancer cells, as it exports chemotherapeutic agents from cells. In the present study, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram quantitative structure activity relationship (HQSAR) techniques were used to derive predictive models for phenylsulfonylfuroxan derivatives as P-gp inhibitors. Cross-validated correlation coefficients (q(2)) of 0.811, 0.855, and 0.907 and non-cross-validated correlation coefficients (r(2)) of 0.87, 0.985, and 0.973 were obtained for CoMFA, CoMSIA, and HQSAR derived models, respectively. The predictive power of the models were assessed using an external test set of five compounds and showed reasonable external predictabilities (r(2) pred) of 0.704, 0.517, and 0.713, respectively. Contour and atomic contribution maps were generated to investigate physicochemical requirements of ligands for better receptor binding affinity. 3D Contour maps suggested molecular interactions such as steric and electrostatic effects and hydrogen bond formation. However, atomic contribution maps indicated that ortho and para positions of the R(1) phenylsulfonyl ring are the most desirable regions to modulate P-gp antagonism. The 3(rd) and 4(th) positions of the central five-membered ring were also found to be important. Our results are in line with previous reports. Information obtained from the contour and atomic contribution maps were utilized to design more potent compounds containing different R(1) fragments. In addition, the activities of these more potent compounds were predicted using derived models.

Checkpoint kinase 1 (Chk1) is a promising target for the design of novel anticancer agents. In the present work, molecular docking simulations and three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on pyridyl aminothiazole derivatives as Chk1 inhibitors. AutoDock was used to determine the probable binding conformations of all the compounds inside the active site of Chk1. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed based on the docking conformations and alignments. The CoMFA model produced statistically significant results with a cross-validated correlation coefficient (q2) of 0.608 and a coefficient of determination (r2) of 0.972. The reliable CoMSIA model with q2 of 0.662 and r2 of 0.970 was obtained from the combination of steric, electrostatic and hydrogen bond acceptor fields. The predictive power of the models were assessed using an external test set of 14 compounds and showed reasonable external predictabilities (r(2)pred) of 0.668 and 0.641 for CoMFA and CoMSIA models, respectively. The models were further evaluated by leave-ten-out cross-validation, bootstrapping and progressive scrambling analyses. The study provides valuable information about the key structural elements that are required in the rational design of potential drug candidates of this class of Chk1 inhibitors.

Theranostic nanoparticles with multifunctional ability have been emerging as a new platform for biomedical applications such as imaging, sensing and drug delivery. Despite gold nanorods (Au NRs) being an excellent nanosource with multifunctional versatility, they have certain limitations in biomedical applications, which include surfactant toxicity, biological stability and controlled drug release kinetics. Herein, we have developed Au NR-doxorubicin conjugates (DOX@PSS-Au NR) with improved drug loading efficiency (55 ± 6%) and minimum CTAB toxicity, by employing Au NRs (4.4 ± 0.5 aspect ratio) coated with poly(sodium 4-styrenesulfonate) (PSS). DOX@PSS-Au NR conjugates exhibited higher biological stability with sustained drug release kinetics at pH 5. The binding events of DOX molecules onto the PSS coated gold nanorods (PSS-Au NRs) were monitored through fluorescence quenching and the longitudinal surface plasmon resonance signals. Furthermore the anti-cancer potential and apoptosis inducing efficiency of DOX@PSS-Au NR conjugates in MCF-7 cells revealed higher therapeutic efficiency than free DOX, as corroborated through morphological assessment and in vitro cytotoxicity assay. In addition, DOX@PSS-Au NR conjugates showed efficient cellular entry and uniform intracellular distribution, suggesting the augmenting effect of chemotherapeutic drugs by Au NRs. Thus DOX@PSS-Au NR conjugates demonstrate significant therapeutic potential, suggesting their potential in anticancer therapy.