Current Issue : April - June Volume : 2015 Issue Number : 2 Articles : 5 Articles
Predicting FRET pathways in proteins using computer\nsimulation techniques is very important for reliable interpretation\nof experimental data. A novel and relatively simple\nmethodology has been developed and applied to purine\nnucleoside phosphorylase (PNP) complexed with a fluorescent\nligand ââ?¬â? formycin A (FA). FRET occurs between an\nexcited Tyr residue (D*) and FA (A). This study aims to interpret\nexperimental data that, among others, suggests the absence\nof FRET for the PNPF159A mutant in complex with\nFA, based on novel theoretical methodology. MD simulations\nfor the protein molecule containing D*, and complexed with\nA, are carried out. Interactions of D* with its molecular environment\nare accounted by including changes of the ESP\ncharges in S1, compared to S0, and computed at the SCF-CI\nlevel. FRET probability WF depends on the inverse six-power\nof the D*-A distance, Rda. The orientational factor 0 Read More
The mitochondrial cytochrome P450 enzymes inhibitor steroid 11-hydroxylase\n(CYP11B1) can decrease the production of cortisol. Therefore, these inhibitors have an\neffect in the treatment of Cushing�s syndrome. A pharmacophore model generated by\nGenetic Algorithm with Linear Assignment for Hypermolecular Alignment of Datasets\n(GALAHAD) was used to align the compounds and perform comparative molecular field\nanalysis (CoMFA) with Q2 = 0.658, R2 = 0.959. The pharmacophore model contained six\nhydrophobic regions and one acceptor atom, and electropositive and bulky substituents\nwould be tolerated at the A and B sites, respectively. A three-dimensional quantitative\nstructure-activity relationship (3D-QSAR) study based on the alignment with the atom root\nmean square (RMS) was applied using comparative molecular field analysis (CoMFA)\nwith Q2 = 0.666, R2 = 0.978, and comparative molecular similarity indices analysis\n(CoMSIA) with Q2 = 0.721, R2 = 0.972. These results proved that all the models have good\npredictability of the bioactivities of inhibitors. Furthermore, the QSAR models indicated\nthat a hydrogen bond acceptor substituent would be disfavored at the A and B groups, while hydrophobic groups would be favored at the B site. The three-dimensional (3D)\nmodel of the CYP11B1 was generated based on the crystal structure of the CYP11B2\n(PDB code 4DVQ). In order to probe the ligand-binding modes, Surflex-dock was\nemployed to dock CYP11B1 inhibitory compounds into the active site of the receptor. The\ndocking result showed that the imidazolidine ring of CYP11B1 inhibitors form H bonds\nwith the amino group of residue Arg155 and Arg519, which suggested that an\nelectronegative substituent at these positions could enhance the activities of compounds.\nAll the models generated by GALAHAD QSAR and Docking methods provide guidance\nabout how to design novel and potential drugs for Cushing�s syndrome treatment....
Indirubin derivatives and analogs comprise a significant\ngroup of ATP-competitive inhibitors. The inhibitory\neffects of ChEMBL474807 (1-(4-amino-1,2,5-oxadiazol-3-\nyl)-5-(piperidin-1-ylmethyl)-N?-(pyridin-4-ylmethylene)-1H-\n1,2,3-triazole-4-carbohydrazide) on two enzymes, namely\nglycogen synthase kinase-3? (GSK-3?) and cyclindependent\nkinase-2 (CDK-2), were analyzed. The close resemblance\nof the amino acid sequences of these two enzymes\n(with 25 % identity and 41 % similarity) explains why\nindirubin derivatives are inhibitors of both of the enzymes\nstudied. The docking and molecular dynamics investigation\nperformed here led to the identification of the interactions\nresponsible for stabilizing the ligand ChEMBL474807 at the\nactive sites of the enzymes considered. The structural and\nenergetic data collected during our investigations clearly indicate\nthat there are important differences in the behavior of the\nligand at the two active sites investigated here....
Structural and energetic properties of benzoic acid\ncrystals at pressure elevated from ambient condition up to\n2.21 GPa were characterized. The directly observed variations\nof cell parameters and consequently cell volume are associated\nwith many other changes including energetic, geometric,\nand electronic characteristics. First of all the non-monotonous\nchange of lattice energy are noticed with the rise of pressure\nsince the increase of stabilization up to 1GPa is followed by\nsystematic decrease of lattice energies after extending the hydrostatic\ncompression. There is also an observed increase of\nC2 2 (8) synthon stabilization interaction with increase of pressure.\nThe lattice response rather than interaction within\nsynthons are source of observed pressure-related trend of lattice\nenergy changes. The energy decomposition analysis revealed\nthat the total steric interactions determine the overall\ntrend of lattice energy change with the rise of pressure. Besides\ngeometric aromaticity index was used as a measure of\ngeometric changes. Serious discrepancies were noticed between\nHOMA values computed with the use of experimental\nand optimized geometries of the ring. Even inclusion of uncertainties\nof experimental geometries related to limited precision\nof X-ray diffraction measurements does not cancel\nmentioned discrepancies. Although HOMA exhibit similar\ntrends at modest pressures the diversity became surprisingly\nhigh at more extreme conditions. This might suggest limitations\nof periodic DFT computations at elevated pressures and\nthe experimentally observed breaking of molecules at very\nhigh pressures will probably not be accounted properly in this\napproach. Also limitation of direct use of experimental geometries\nwere highlighted....
The present art of drug discovery and design of new drugs is based on suicidal\nirreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible\ninhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and\nthe reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed\nsome significant advantages over non-covalent inhibitors such as covalent warheads can\ntarget rare, non-conserved residue of a particular target protein and thus led to development\nof highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with\nshallow binding cleavage which will led to development of novel inhibitors with increased\npotency than non-covalent inhibitors. Several computational approaches have been\ndeveloped to simulate covalent interactions; however, this is still a challenging area to\nexplore. Covalent molecular docking has been recently implemented in the computer-aided\ndrug design workflows to describe covalent interactions between inhibitors and biological\ntargets. In this review we highlight: (i) covalent interactions in biomolecular systems;\n(ii) the mathematical framework of covalent molecular docking; (iii) implementation of\ncovalent docking protocol in drug design workflows; (iv) applications covalent docking:\ncase studies and (v) shortcomings and future perspectives of covalent docking. To the best\nof our knowledge; this review is the first account that highlights different aspects of covalent\ndocking with its merits and pitfalls. We believe that the method and applications highlighted\nin this study will help future efforts towards the design of irreversible inhibitors....
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