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[…] Twenty compounds were prepared for a Monte Carlo docking simulation. Force field CHARMm was employed to start minimization. A receptor-rigid docking algorithm (LigandFit) was employed to calculate ligand binding affinity, in which minimized docking poses were then clustered with 1.5 RMS Threshold for Diversity. Scoring functions such as the potential of mean force (PMF), Jain and Piecewise Linear Potential 1/2 (PLP1/2) were used to validate the major determinate-Dock Score (Dock Score = - ligand/receptor interaction energy + ligand internal energy). A mutation study was employed to evaluate the role of key residues by generating seven mutation models that were used for further re-docking. Results were further used to produce a scaffold for molecular dynamics simulation. [...] Activity was predicted using QSAR models. This study establishes activity prediction models for Ligand prediction using compounds with UT-B inhibitory activity screened by the erythrocyte osmotic lysis assay. The chemical properties for the compounds were calculated through DS 2.5, and more than 200 descriptors were produced. Then, genetic function approximation (GFA) was used to filter out and select descriptors with higher relevance, and the square correlation coefficient (r2) was used for ordering and selection. Training sets and test sets were obtained by random allocation of the descriptors selected through GFA () along with the IC50s of the sixteen analogues of PU21 [Ren et al., under review]. Support Vector Machine (SVM) and Multiple Linear Regression (MLR), respectively, used LibSVM and MATLAB (MATrix LABoratory, Natick, MA, US: The MathWorks Inc.) to establish linear and non-linear models. 3D-QSAR models were established to understand the structural characteristics of the compounds. Comparative force field analysis (CoMFA) was used to study steric and electrostatic properties. Comparative similarity indices analysis (CoMSIA) was used to study steric, electrostatic, hydrophobic, hydrogen donor and acceptor properties. The training set and test set used the atom-fit module of SYBYL-X 1.1 (St Louis, M. USA: Tripos.) to conduct scaffold alignment. Then, CoMFA and CoMSIA models were established. Coulombic potential and Lennard-Jones potential (LJP) were used to calculate electrostatic fields and steric fields, respectively. Gaussian functions were used to calculate steric, hydrogen bond acceptor and donor, hydrophobic and electrostatic fields in the CoMSIA model. From the results of the partial least squares (PLS) analysis, the conventional correlation coefficient (r2) and cross-validated coefficient (q2) were produced, which were used to evaluate the accuracy of non-cross validation and cross validation models, respectively. All tested SVM, MLR, and 3D-QSAR models were used to predict the activity of the predicted sets. [...] The experiment was divided into three portions that simulated the structural and dynamic differences of UT-B under normal conditions when inhibitors exist. Unbound UT-B (eUT-B), UT-B bound with single urea (uUT-B and UT-Bu, in which uUT-B represents urea binding in the extracellular binding site close to the inhibitor binding site), and UT-B bound with double urea (uUT-Bu) were used to simulate UT-B states under normal functionality. Four systems were used to simulate the effects of inhibitors in UT-B (PU21, PU168, PU468 and PU474). In addition, four systems were used to simulate the situation in which urea and inhibitors both exist in UT-B (PU21UT-Bu, PU168UT-Bu, PU468UT-Bu, PU474UT-Bu). Force field CHARMm27 and parameters were added to each ligand by using SwissParam and the pdb2gmx protocol of Gromacs version 4.5. Coupled ligand-UT-B complex and uUT-Bu complex, ligand-UT-B-urea complex were used to generate a cubic box and to immerse into a buffer solution (solvated with TIP3P water model). Mean square of displacement (MSD) was used to demonstrate the diffusion of molecules in the system (). The distance between the edge of the cubic box and complex was set to 1.2 nm. 0.145 M NaCl ions were added to neutralize the system. A steepest descent algorithm was calculated for minimization, and minimization would stop when max(|Fn|) < ε or defined minimization steps had been approached. Maximum steepest descents minimization was set to 5,000 time steps. For the equilibration, the last configuration of energy-minimization was used to generate restrained dynamics production. NVT equilibration, Particle-Mesh Ewald (PME) and Berendsen weak thermal coupling methods were used in dynamics production, whereas PME was also used in the calculation of electrostatic interactions. The time step was set at 2 fs under the PME option, where the cut-off for PME was 1.0 nm. Simulation trajectories analysis was conducted by plug-in open source methods. […]

Pipeline specifications

Software tools CHARMM, PHENIX, LIBSVM, Sybyl-X, SwissParam, GROMACS
Organisms Mus musculus, Rattus norvegicus, Homo sapiens
Diseases Deficiency Diseases, Wiskott-Aldrich Syndrome, Genetic Diseases, Inborn
Chemicals Urea