Molecular Dynamics Simulations of Claudin-10a and -10b Ion Channels: With Similar Architecture, Different Pore Linings Determine the Opposite Charge Selectivity.

Claudin polymers constitute the tight junction (TJ) backbone that forms paracellular barriers, at least for bigger solutes. While some claudins also seal the barrier for small electrolytes, others form ion channels. For cation-selective claudin-15 and claudin-10b, structural models of channels embedded in homo-polymeric strands have been suggested. Here, we generated a model for the prototypic anion-selective claudin-10a channel. Based on previously established claudin-10b models, dodecamer homology models of claudin-10a embedded in two membranes were analyzed by molecular dynamics simulations. The results indicate that both claudin-10 isoforms share the same strand and channel architecture: Sidewise unsealed tetrameric pore scaffolds are interlocked with adjacent pores via the ß1ß2 loop of extracellular segment 1. This leads to TJ-like strands with claudin subunits arranged in four joined rows in two opposing membranes. Several but not all cis- and trans-interaction modes are indicated to be conserved among claudin-10a, -10b, and -15. However, pore-lining residues that differ between claudin-10a and -10b (i.e., R33/I35, A34/D36, K69/A71, N54/D56, H60/N62, R62/K64) result in opposite charge selectivity of channels. This was supported by electric field simulations for both claudins and is consistent with previous electrophysiological studies. In summary, for the first time, a structural and mechanistic model of complete and prototypic paracellular anion channels is provided. This improves understanding of epithelial paracellular transport.

Claudin-10b cation channels in tight junction strands: Octameric-interlocked pore barrels constitute paracellular channels with low water permeability.

Claudin proteins constitute the backbone of tight junctions (TJs) regulating paracellular permeability for solutes and water. The molecular mechanism of claudin polymerization and paracellular channel formation is unclear. However, a joined double-rows architecture of claudin strands has been supported by experimental and modeling data. Here, we compared two variants of this architectural model for the related but functionally distinct cation channel-forming claudin-10b and claudin-15: tetrameric-locked-barrel vs octameric-interlocked-barrels model. Homology modeling and molecular dynamics simulations of double-membrane embedded dodecamers indicate that claudin-10b and claudin-15 share the same joined double-rows architecture of TJ-strands. For both, the results indicate octameric-interlocked-barrels: Sidewise unsealed tetrameric pore scaffolds interlocked with adjacent pores via the ß1ß2 loop of the extracellular segment (ECS) 1. This loop mediates hydrophobic clustering and, together with ECS2, cis- and trans-interaction between claudins of the adjacent tetrameric pore scaffolds. In addition, the ß1ß2 loop contributes to lining of the ion conduction pathway. The charge-distribution along the pore differs between claudin-10b and claudin-15 and is suggested to be a key determinant for the cation- and water permeabilities that differ between the two claudins. In the claudin-10b simulations, similar as for claudin-15, the conserved D56 in the pore center is the main cation interaction site. In contrast to claudin-15 channels, the claudin-10b-specific D36, K64 and E153 are suggested to cause jamming of cations that prevents efficient water passage. In sum, we provide novel mechanistic information about polymerization of classic claudins, formation of embedded channels and thus regulation of paracellular transport across epithelia.

Identification of Potent and Selective JAK1 Lead Compounds Through Ligand-Based Drug Design Approaches.

JAK1 plays a significant role in the intracellular signaling by interacting with cytokine receptors in different types of cells and is linked to the pathogenesis of various cancers and in the pathology of the immune system. In this study, ligand-based pharmacophore modeling combined with virtual screening and molecular docking methods was incorporated to identify the potent and selective lead compounds for JAK1. Initially, the ligand-based pharmacophore models were generated using a set of 52 JAK1 inhibitors named C-2 methyl/hydroxyethyl imidazopyrrolopyridines derivatives. Twenty-seven pharmacophore models with five and six pharmacophore features were generated and validated using potency and selectivity validation methods. During potency validation, the Guner-Henry score was calculated to check the accuracy of the generated models, whereas in selectivity validation, the pharmacophore models that are capable of identifying selective JAK1 inhibitors were evaluated. Based on the validation results, the best pharmacophore models ADHRRR, DDHRRR, DDRRR, DPRRR, DHRRR, ADRRR, DDHRR, and ADPRR were selected and taken for virtual screening against the Maybridge, Asinex, Chemdiv, Enamine, Lifechemicals, and Zinc database to identify the new molecules with novel scaffold that can bind to JAK1. A total of 4,265 hits were identified from screening and checked for acceptable drug-like properties. A total of 2,856 hits were selected after ADME predictions and taken for Glide molecular docking to assess the accurate binding modes of the lead candidates. Ninety molecules were shortlisted based on binding energy and H-bond interactions with the important residues of JAK1. The docking results were authenticated by calculating binding free energy for protein-ligand complexes using the MM-GBSA calculation and induced fit docking methods. Subsequently, the cross-docking approach was carried out to recognize the selective JAK1 lead compounds. Finally, top five lead compounds that were potent and selective against JAK1 were selected and validated using molecular dynamics simulation. Besides, the density functional theory study was also carried out for the selected leads. Through various computational studies, we observed good potency and selectivity of these lead compounds when compared with the drug ruxolitinib. Compounds such as T5923555 and T5923531 were found to be the best and can be further validated using in vitro and in vivo methods.

Radio-protective efficacy of Gymnema sylvestre on Pangasius sutchi against gamma (60Co) irradiation.

PURPOSE: Freshwater fish Pangasius sutchi was used in this study as a vertebrate model. We evaluated the induction of certain antioxidant enzymes in various vital organs. The radioprotective efficacy of Gymnema sylvestre leaves extract (GS) [25 mg/kg Body Weight (B.W)] and its bioactive compound Gymnemagenin (GG) [0.3 mg/kg B.W] was compared with Amifostine (Ami), the only radioprotector clinically approved by the US-FDA [Ami- 83.3 mg/kg B.W] against different doses of gamma radiation - 60Co (Lethal Dose: LD30-9.2 Gy, LD50-10.2 Gy and LD70-11.4 Gy). MATERIALS AND METHODS: This study was done via stress marker enzymes, cell cycle analysis (CCA) and DNA damage assay prediction with molecular docking, which are reported here for the first time. The results indicate an elevated LPO level and decreased level of CAT, SOD and GSH due to oxidative stress initiation by 60Co Ionizing Radiation (IR) on 4th day and slightly reduced on 32nd day while the reverse observed when the fishes were pretreated with Ami, GS and GG. Similarly, CCA and dead/live cells counts were conducted with pretreatment of Ami, GS and GG against 60Co IR dose (LD50-10.2 Gy). RESULTS: In CCA, G0/G1 phase was observed to be the highest in Ami and lowest in GG, against 60Co IR doses 10.2 Gy which was 51.76 ± 7.55. The dead cells range observed in pretreated group of Ami, GS and GG was lowest in Ami and highest in GG and live cells (highest in Ami and lowest in GG) as compared to 60Co IR group (86.43 ± 3.42 and 8.77 ± 5.95). Thus, antioxidant profile improvement by oxidative stress reduction and gradual progression of different phases of cell cycle except the apoptotic phase along with the live cells counts indicates that the radio-protective efficacy of GS is similar to Ami. CONCLUSION: Predictive assessment was carried out by docking of Ami, various components of GS with p53, NF-κß cells and Rad51 proteins structures responsible for CCA, apoptosis and repair mechanism. These structural proteins were docked with other structural proteins like USP7, TNF-α and partner and localizer of BRCA2 associated (PALB2/BRCA2) complex which made us perform these systemic efforts to find the functional activity of these known radio-protectants.

Structure and dynamics of the somatostatin receptor 3-ligand binding in the presence of lipids examined using computational structural biology methods.

In the past two decades, the structural biology studies on G-protein coupled receptors (GPCRs) are on the rise. Understanding the relation between the structure and function of GPCRs is important as they play a huge role in various signaling mechanisms in a eukaryotic cell. Somatostatin receptor 3 (SSTR3), one of the GPCRs, is one such important receptor which oversees different cellular processes including cell-to-cell signaling. However, the information available regarding the structural features of SSTR3 responsible for their bioactivity is scarce. In this study, we report a structural understanding of SSTR3-ligand binding that could be helpful in demystifying the structural complexities related to functioning of the receptor. An integrated protocol consisting of different computational structural biology tools including protein structure prediction via comparative modeling, binding site characterization, three-dimensional quantitative structure-activity relationship based on comparative molecular field analysis and comparative molecular similarity indices analysis, density functional theory, and molecular dynamics simulations were performed. Different understandings from the simulation of SSTR3-ligand complexes, mainly the conditions that are favorable for the formation of lowest bioactive state of SSTR3 ligands are reported. In addition to that, we report the important physicochemical descriptors of SSTR3 ligands that could significantly influence their bioactivity. The results of the study could be helpful in developing novel SSTR3 ligands (both agonists and antagonists) with high potency and receptor selectivity.

Time-dependent conformational analysis of ALK5-lumican complex in presence of graphene and graphene oxide employing molecular dynamics and MMPBSA calculation.

Lumican, an extracellular matrix protein avails wound healing by binding to ALK5 membrane receptor (TGF-beta receptor I). Their interaction enables epithelialization and substantiates rejuvenation of injured tissue. To enrich permanence of ALK5-lumican interaction, we employed graphene and graphene oxide co-factors. Herein, this study explicates concomitancy of graphene and graphene oxide with ALK5-lumican. We performed an in silico approach involving molecular modelling, molecular docking, molecular dynamics for 200 ns, DSSP analysis and MMPBSA calculations. Results of molecular dynamics indicate cofactors influential in altering bioactive site of lumican than ALK5. Similarly, MMPBSA calculations unveiled binding energy of apoenzyme as -108.09 kcal/mol, holoenzyme (G) as -79.20 kcal/mol and holoenzyme (GO) as -114.33 kcal/mol. This concludes graphene oxide lucrative in enhancing binding energy of ALK5-lumican in holoenzyme (GO) via coil formation of Lum C13 domain. In contrast, graphene reduced binding energy of ALK5-lumican in holoenzyme (G) modifying Lum C13 into beta sheets. MMPBSA residual contribution analysis of Lum C13 residues revealed binding energy of -13.9 kcal/mol for apoenzyme, -6.8 kcal/mol for holoenzyme (G) and -19.5 kcal/mol for holoenzyme (GO). This supports coil formation propitious for better ALK5-Lum interaction. Highest SASA energy of -21.05 kcal/mol of holoenzyme (G) assures graphene reasonable for improved ALK5-lumican hydrophobicity. As per the motive of the study, graphene oxide enriches permanence of ALK5-lumican. This provides counsel for plausible exploitation of lumican and graphene oxide as targeted/nano drug delivery system to reinstate acute wounds, chronic wounds, corneal wounds, hypertrophic scars and keloids in near future. Communicated by Ramaswamy H. Sarma.

Understanding the influence of lipid bilayers and ligand molecules in determining the conformational dynamics of somatostatin receptor 2.

Somatostatin receptor 2 (SSTR2) is a G-protein coupled receptor (GPCR) that controls numerous cellular processes including cell-to-cell signaling. In this study, we report how the lipid and ligand molecules influence the conformational dynamics of the membrane-bound SSTR2. Molecular simulations of different holo and apoenzyme complexes of SSTR2 in the presence and absence of a lipid bilayer were performed, observed, and correlated with previously reported studies. We identified the important SSTR2 residues that take part in the formation of the SSTR2-ligand complex. On analyzing the molecular simulation trajectories, we identified that the residue D3.32 is crucial in determining the bioactive conformation of SSTR2 ligands in the binding site. Based on the results, we suggest that designing a novel SSTR2 ligand with an H-bond donor group at the R1 position, and hydrophobic groups at R2 and R3 might have higher activity and SSTR2-selectivity. We analyzed the simulated systems to identify other important structural features involved in SSTR2-ligand binding and to observe the different conformational changes that occur in the protein after the ligand binding. Additionally, we studied the conformational dynamics of N- and C-terminal regions of SSTR2 in the presence and absence of the lipid bilayer. Both the systems were compared to understand the influence of lipid molecules in the formation of secondary structural domains by these extracellular regions. The comparative study revealed that the secondary structural elements formed by C-terminal residues in presence of lipid molecules is crucial for the functioning of SSTR2. Our study results highlight the structural complexities involved in the functioning of SSTR upon binding with the ligands in the presence and absence of lipid bilayer, which is essential for designing novel drug targets.

Molecular-Level Understanding of the Somatostatin Receptor 1 (SSTR1)-Ligand Binding: A Structural Biology Study Based on Computational Methods.

Somatostatin receptor 1 (SSTR1), a subtype of somatostatin receptors, is involved in various signaling mechanisms in different parts of the human body. Like most of the G-protein-coupled receptors (GPCRs), the available information on the structural features of SSTR1 responsible for the biological activity is scarce. In this study, we report a molecular-level understanding of SSTR1-ligand binding, which could be helpful in solving the structural complexities involved in SSTR1 functioning. Based on a three-dimensional quantitative structure-activity relationship (3D-QSAR) study using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA), we have identified that an electronegative, less-bulkier, and hydrophobic atom substitution can substantially increase the biological activity of SSTR1 ligands. A density functional theory (DFT) study has been followed to study the electron-related properties of the SSTR1 ligands and to validate the results obtained via the 3D-QSAR study. 3D models of SSTR1-ligand systems have been embedded in lipid-lipid bilayer membranes to perform molecular dynamics (MD) simulations. Analysis of the MD trajectories reveals important information about the crucial residues involved in SSTR1-ligand binding and various conformational changes in the protein that occur after ligand binding. Additionally, we have identified the probable ligand-binding site of SSTR1 and validated it using MD. We have also studied the favorable conditions that are essential for forming the most stable and lowest-energy bioactive conformation of the ligands inside the binding site. The results of the study could be useful in constructing more potent and novel SSTR1 antagonists and agonists.

Computational evaluation of major components from plant essential oils as potent inhibitors of SARS-CoV-2 spike protein.

COVID-19, caused by SARS-CoV-2 has recently emerged as a global pandemic. Intense efforts are ongoing to find a vaccine or a drug to control the disease across the globe. Meanwhile, alternative therapies are also being explored to manage the disease. Phytochemicals present in essential oils are promising candidates which have been known to possess wide range of therapeutic activities. In this study, major components of several essential oils which are known for their antimicrobial properties have been docked against the S1 receptor binding domain of the spike (S) glycoprotein, which is the key target for novel antiviral drugs, to ascertain their inhibitory effects based on their binding affinities. It has been found that some monoterpenes, terpenoid phenols and phenyl propanoids such as anethole, cinnamaldehyde, carvacrol, geraniol, cinnamyl acetate, L-4-terpineol, thymol and pulegone from essential oils extracted from plants belonging to families such as Lamiaceae, Lauraceae, Myrtaceae, Apiaceae, Geraniaceae and Fabaceae are effective antiviral agents that have potential to inhibit the viral spikeprotein.

Understanding the structural features of JAK2 inhibitors: a combined 3D-QSAR, DFT and molecular dynamics study.

JAK2 plays a critical role in JAK/STAT signaling pathway and in patho-mechanism of myeloproliferative disorders and autoimmune diseases. Thus, effective JAK2 inhibitors provide a promising opportunity for the pharmaceutical intervention of many diseases. In this work, 3D-QSAR study was performed on a series of 1-amino-5H-pyrido-indole-4-carboxamide derivatives as JAK2 inhibitors to obtain reliable comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) models with three different alignment methods. Among the different alignment methods, ligand-based (CoMFA: q2 = 0.676, r2 = 0.979; CoMSIA: q2 = 0.700, r2 = 0.953) and pharmacophore-based alignment (CoMFA: q2 = 0.710, r2 = 0.982; CoMSIA: q2 = 0.686, r2 = 0.960) has produced better statistical results when compared to receptor-based alignment (CoMFA: q2 = 0.507, r2 = 0.979; CoMSIA: q2 = 0.544, r2 = 0.917). Statistical parameters indicated that data are well fitted and have high predictive ability. The presence of electrostatic and hydrophobic field is highly desirable for potent inhibitory activity, and the steric field plays a minor role in modulating the activity. The contour analysis indicates ARG980, ASN981, ASP939 and LEU937 have more possibility of interacting with bulky, hydrophobic groups in pyrido and positive and negative groups in pyrazole ring. Based on our findings, we have designed sixteen molecules and predicted its activity and drug-like properties. Subsequently, molecular docking, molecular dynamics and DFT calculations were performed to evaluate its potency.

Isolation, purification and characterization of proteinaceous fungal α-amylase inhibitor from rhizome of Cheilocostus speciosus (J.Koenig) C.D.Specht.

As the aim of this present study, a proteinaceous α-amylase inhibitor has been isolated from the rhizome of Cheilocostus specious (C. speciosus) and was purified using DEAE cellulose anion exchange chromatography followed by gel filtration using Sephacryl-S-200 column. The purity and molecular mass of the purified inhibitor was determined by SDS-PAGE and LC-MS respectively. The molecular mass of the purified inhibitor was determined to be 31.18kDa. Protein-protein docking was also carried out as molecular model. Model validation methods such as Ramachandran plot and Z-score plot were adopted to validate the structural description (sequence analysis) of proteins. The inhibitory activity was confirmed using spectrophotometric and reverse zymogram analyses. This 31.18kDa protein from C. speciosus inhibited the activity of fungal α-amylase by 71% at the level of ion exchange chromatography and 96% after gel filtration. The inhibition activity of the α-amylase inhibitor was stable and high at optimum pH6 (52.2%) and temperatures of 30-40°C (72.2%). Thus it was suggested that the main responsible for the versatile biological and pharmacological activities of C. speciosus is due to its primary metabolites (proteins) only.

3D-QSAR studies on indole and 7-azoindole derivatives as ROCK-2 inhibitors: An integrative computational approach.

Rho Kinases (ROCK) has been found to regulate a wide range of fundamental cell functions such as contraction, motility, proliferation, and apoptosis. Recent experiments have defined new functions of ROCKs in cells, including centrosome positioning and cell-size regulation, which might contribute to various physiological and pathological states. In this study, we have performed pharmacophore modeling and 3D QSAR studies on a series of 36 indoles and 7-azoindoles derivatives as ROCK2 inhibitors to elucidate the structural variations with their inhibitory activities. Ligand based CoMFA and CoMSIA models were generated based on three different alignment methods such as systematic search, simulated annealing and pharmacophore. A total of 15 CoMFA models and 27 CoMSIA were generated using different alignments. One model from each alignment is selected based on the statistical values. Contour maps of the selected models were compared, analysed and reported. The 3D QSAR study revealed that electro positive group linked to the methoxy-benzene ring position of the structure will enhance the biological activity and bulkier substitutions are preferred in the methyl dihydroindole region. Also, it is found that the hydrogen bond donor substituted at the R1 position enhances the inhibitory activity. In future, this study would give proper guidelines to further enhance the activity of novel inhibitors for ROCK2.

Theoretical analysis of somatostatin receptor 5 with antagonists and agonists for the treatment of neuroendocrine tumors.

We report on SSTR5 receptor modeling and its interaction with reported antagonist and agonist molecules. Modeling of the SSTR5 receptor was carried out using multiple templates with the aim of improving the precision of the generated models. The selective SSTR5 antagonists, agonists and native somatostatin SRIF-14 were employed to propose the binding site of SSTR5 and to identify the critical residues involved in the interaction of the receptor with other molecules. Residues Q2.63, D3.32, Q3.36, C186, Y7.34 and Y7.42 were found to be highly significant for their strong interaction with the receptor. SSTR5 antagonists were utilized to perform a 3D quantitative structure-activity relationship study. A comparative molecular field analysis (CoMFA) was conducted using two different alignment schemes, namely the ligand-based and receptor-based alignment methods. The best statistical results were obtained for ligand-based ([Formula: see text], [Formula: see text] = 0.988, noc = 4) and receptor-guided methods (docked mode 1:[Formula: see text], [Formula: see text], noc = 5), (docked mode 2:[Formula: see text] = 0.555, [Formula: see text], noc = 5). Based on CoMFA contour maps, an electropositive substitution at [Formula: see text], [Formula: see text] and [Formula: see text] position and bulky group at [Formula: see text] position are important in enhancing molecular activity.

Molecular Modeling Study on Diazine Indole Acetic Acid Derivatives for CRTH2 Inhibitory Activity.

In the present work, molecular modeling studies have been reported on a series of diazine indole acetic acid derivatives to analyze the structure-activity relationship studies of CRTH2 using fragment (Topomer CoMFA and HQSAR) and field (CoMFA and CoMSIA) based QSAR methods. Twenty-six compounds were used as a training set to establish the model, and six compounds were used as a test set to validate the model. The generated models exhibited good statistical results such as correlation coefficient (r2) and the cross-validated correlation coefficient (q2). Topomer CoMFA analysis yielded the q2 of 0.610 and r2 of 0.981. HQSAR model generated using bond and connectivity as fragment distinction and 3-6 as fragment size has the q2 value of 0.707 and conventional r2 value of 0.892 with five components. CoMFA model was assessed by cross-validated q2 value of 0.543 and r2 value of 0.901 with steric and electrostatic fields. CoMSIA model generated using steric, hydrophobic and donor fields with q2 value of 0.550 and r2 value of 0.888 was found to be the optimal model among the various models generated. The contour maps were generated to analyze the important structural features that regulate their inhibitory potency. From the result of contour maps we have suggested the critical sites for chemical modification which will be useful in designing potent compounds with improved activity.