1,721,011 research outputs found
GMXPBSA 2.1 : a GROMACS tool to perform MM/PBSA and computational alanine scanning
No full textGMXPBSA 2.1 is a user-friendly suite of Bash/Perl scripts for streamlining MM/PBSA calculations on structural ensembles derived from GROMACS trajectories, to automatically calculate binding free energies for protein-protein or ligand-protein complexes [R.T. Bradshaw et al., Protein Eng. Des. Sel. 24 (2011) 197-207]. GMXPBSA 2.1 is flexible and can easily be customized to specific needs and it is an improvement of the previous GMXPBSA 2.0 [C. Paissoni et al., Comput. Phys. Commun. (2014), 185, 2920-2929]. Additionally, it performs computational alanine scanning (CAS) to study the effects of ligand and/or receptor alanine mutations on the free energy of binding. Calculations require only for protein-protein or protein-ligand MD simulations. GMXPBSA 2.1 performs different comparative analyses, including a posteriori generation of alanine mutants of the wild-type complex, calculation of the binding free energy values of the mutant complexes and comparison of the results with the wild-type system. Moreover, it compares the binding free energy of different complex trajectories, allowing the study of the effects of non-alanine mutations, post-translational modifications or unnatural amino acids on the binding free energy of the system under investigation. Finally, it can calculate and rank relative affinity to the same receptor utilizing MD simulations of proteins in complex with different ligands. In order to dissect the different MM/PBSA energy contributions, including molecular mechanic (MM), electrostatic contribution to solvation (PB) and nonpolar contribution to solvation (SA), the tool combines two freely available programs: the MD simulations software GROMACS [S. Pronk et al., Bioinformatics 29 (2013) 845-854] and the Poisson-Boltzmann equation solver APBS [N.A. Baker et al., Proc. Natl. Acad. Sci. U.S.A 98 (2001) 10037-10041]. All the calculations can be performed in single or distributed automatic fashion on a cluster facility in order to increase the calculation by dividing frames across the available processors. This new version with respect to our previously published GMXPBSA 2.0 fixes some problem and allows additional kind of calculations, such as CAS on single protein in order to individuate the hot-spots, more custom options to perform APBS calculations, improvements of speed calculation of APBS (precF set to 0), possibility to work with multichain systems (see Summary of revisions for more details). The program is freely available under the GPL license
Binding modes of the distamycin analogue FCE-24517 to d(CGTATACG)2.1H and13C sequence-specific assignments
No full textThe interaction of an analogue of distamycin, FCE-24517, with the 'AT-rich' DNA fragment d(CGTATACG)2, was studied in solution by the combined usage of 2D techniques, TOCSY, NOESY, ROESY and C-13/H-1 shift correlation experiments. The formation of tbe complex destroys the C2 symmetry of the double helix, leading to a doubling of the nucleotide resonances. Proton and carbon atoms were assigned in the complex in termsof specific strand and residue. The imino protons of the base pairs, involved in hydrogen bonding and the H-2 protons of adenine moieties, were determinant for defining the binding sites of the drug. The presence of multiple equilibrium reactions was proved by means of NOESY andROESY spectra, where all the chemical-exchange cross peaks were analysed. The FCE-24517 signals in the complex were attributed and some stereospecific assignments performed. Two sets of resonances for FCE wereidentified, showing that tbe drug exists in two different chemical environments, corresponding to two different modes of binding in slow chemical exchange. Significant intermolecular NOE interactions between the drug and the nucleotide have allowed the binding sites in the minorgroove of the DNA fragment to be located
A combination of Metadynamics and docking calculations rationalizes the effects induced by N-Methylation on RGD-cyclopeptides integrin affinity
No full textCyclopeptides are a promising class of compounds with favourable pharmacokinetic characteristics that can be used as therapeutics in modulation of protein-protein interactions. Nevertheless their application has been limited due to the difficulties to predict in silico their three-dimensional structure and inhibitory activity. Because of these challenges, their optimization for specific biological targets has been mainly based on empirical approaches. Computational tools could be fundamental in accelerating the drug design process, reducing the efforts dedicated to expensive and time-consuming compound synthesis.
In this scenario a detailed conformational search of ligands followed by docking calculations is highly recommendable to achieve reliable computational predictability. We have optimized a multi-stage computational approach[1] able to i. predict the affinity of a set of cyclopeptides for different integrins, ii. rationalize the interplay between conformational equilibria and receptor affinity. The protocol relies on the combination of enhanced sampling molecular dynamics technique (Bias-Exchange Metadynamics), docking calculations and re-scoring via Molecular Mechanics/Generalized-Born Surface Area. The reliability of our method was tested investigating the impact of single and multiple N-methylation on the equilibrium conformations of five RGD (Arg-Gly-Asp) cyclohexapeptides that were generated to increase their selectivity towards αIIbβ3 integrin.[2] We obtained excellent results: the conformational sampling was in good agreement with available NMR data and we were able to discriminate between binders and non-binders. Additionally we offered a structural rationale for why N-methylation increases peptides affinities towards a specific integrin.
Herein we have shown that Metadynamics can represent a promising in silico screening strategy, opening new perspectives in the application of cyclopeptides as therapeutic inhibitors. We expect that this combination of techniques will be successfully exploited in future to predict the conformational effects of methylation and other chemical modifications in cyclopeptides
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Computational techniques predict the effects induced by N-methylation of RGD-cyclopeptides on integrin affinity
No full textCyclopeptides are a promising class of compounds for inhibiting protein-protein interactions. In particular, they provide opportunities to increase molecular size and interactions, constraining ligands into pre-organized bioactive conformations. This strategy is extremely successful in the field of integrin inhibitors, where the high receptor affinity and selectivity displayed by RGD cyclopeptides has been mainly ascribed to their pre-organization in solution. Nevertheless, the difficulties to accurately predict the three-dimensional structure and the inhibitory activity of cyclopeptides have limited their application, requiring expensive and time-consuming synthesis campaigns for their optimization. Computational tools could be fundamental in accelerating the drug design process.
In this work we present a computational protocol[1] able to: i. predict the affinity of a set of cyclopeptides towards different integrins, ii. rationalize the interplay between conformational equilibria and receptor affinity. This protocol relies on a detailed conformational search of ligands, performed with an enhanced sampling molecular dynamic technique, followed by docking calculations. We have demonstrated the reliability of our method investigating the impact of single/multiple N-methylation on the equilibrium conformations of five RGD cyclopeptides, generated to increase their selectivity for αIIbβ3 integrin.[2] Therefore this protocol can represent a promising approach for in silico spatial screening. We expect that this combination of techniques will be successfully exploited in future to predict the conformational effects of methylations, other chemical modifications and flanking residues in cyclopeptides. Such an approach may be well exploited before entering time-consuming chemical synthesis and binding experiments
MetaD simulations rationalize the conformational effects induced by N-methylation of RGD cyclohexapeptides
No full textCyclic peptides are a promising class of compounds that can be used as therapeutics in modulation of protein-protein interactions thanks to their favourable pharmacokinetic characteristics. Nevertheless their application has been relatively limited due to the difficulties to accurately predict in silico their three-dimensional structure and their inhibitory activity. Because of these challenges, their optimization for specific biological targets has been mainly based on empirical approaches, requiring massive time-consuming synthesis campaigns of different variants to identify sets of molecules with appropriate conformational and target-binding properties. Computational tools could be fundamental in accelerating the drug design process, thus reducing the efforts dedicated to expensive and time consuming compound synthesis
In this scenario a detailed conformational search of ligands followed by docking calculations is highly recommendable to achieve reliable computational predictability. We have developed a multi-stage computational protocol[1] able i. to reliably predict the affinity of a set of cyclic-peptides towards different integrins, ii. to rationalize the interplay between conformational equilibria and receptor affinity. This protocol relies on the combination of enhanced sampling molecular dynamics technique (Bias Exchange Metadynamics, BE-META), docking calculations and re-scoring via Molecular Mechanics/Generalized Born Surface Area methods. We have explored the applicability and reliability of our method investigating the impact of single and multiple N-methylation on the equilibrium conformations of five head-to-tail cyclic RGD (Arg-Gly-Asp) hexapeptides that were generated to increase their selectivity towards αIIbβ3 integrin.[2] We obtained excellent results: we validated the conformational sampling obtaining a good agreement with available NMR data and demonstrated our prediction ability discriminating between binders and non-binders. Herein we have shown that BE-META can represent a promising in silico spatial screening strategy to predict the conformational effects of N-methylation in cyclic-peptides, opening new perspectives in their application as therapeutic inhibitors of protein-protein interactions. Moreover our results are relevant in the field of integrin-targeting RGD peptidomimetics, as they offer a structural rationale for why N-methylation increases peptides affinities towards a specific integrin.
We expect that this combination of techniques will be successfully exploited in future to predict the conformational effects of methylation also in other classes of cyclopeptides. Herein, the method could be easily extended to predict the conformational effect of other chemical modifications, of flanking residues or of d-amino acids. Such an approach may be well exploited before entering time-consuming chemical synthesis and binding experiments
GMXPBSA 2.0 : a GROMACS tool to perform MM/PBSA and computational alanine scanning
No full textGMXPBSA 2.0 is a user-friendly suite of Bash/Perl scripts for streamlining MM/PBSA calculations on structural ensembles derived from GROMACS trajectories, to automatically calculate binding free energies for protein-protein or ligand-protein complexes. GMXPBSA 2.0 is flexible and can easily be customized to specific needs. Additionally, it performs computational alanine scanning (CAS) to study the effects of ligand and/or receptor alanine mutations on the free energy of binding. Calculations require only for protein-protein or protein-ligand MD simulations. GMXPBSA 2.0 performs different comparative analysis, including a posteriori generation of alanine mutants of the wild-type complex, calculation of the binding free energy values of the mutant complexes and comparison of the results with the wild-type system. Moreover, it compares the binding free energy of different complexes trajectories, allowing the study the effects of non-alanine mutations, post-translational modifications or unnatural amino acids on the binding free energy of the system under investigation. Finally, it can calculate and rank relative affinity to the same receptor utilizing MD simulations of proteins in complex with different ligands. In order to dissect the different MM/PBSA energy contributions, including molecular mechanic (MM), electrostatic contribution to solvation (PB) and nonpolar contribution to solvation (SA), the tool combines two freely available programs: the MD simulations software GROMACS and the Poisson-Boltzmann equation solver APBS. All the calculations can be performed in single or distributed automatic fashion on a cluster facility in order to increase the calculation by dividing frames across the available processors. The program is freely available under the GPL license
Structural and functional characterization of the first PHD finger of Autoimmune Regulator (AIRE)
No full textMetadynamics simulations rationalize the conformational effects induced by N-methylation of RGD cyclohexapeptides
No full textCyclopeptides are a promising class of compounds with favourable pharmacokinetic characteristics that can be used as therapeutics in modulation of protein-protein interactions. Nevertheless their application has been limited due to the difficulties to predict in silico their three-dimensional structure and inhibitory activity. Because of these challenges, their optimization for specific biological targets has been mainly based on empirical approaches. Computational tools could be fundamental in accelerating the drug design process, reducing the efforts dedicated to expensive and time-consuming compound synthesis.
In this scenario a detailed conformational search of ligands followed by docking calculations is highly recommendable to achieve reliable computational predictability. We have developed a multi-stage computational protocol[1] able to i. predict the affinity of a set of cyclopeptides for different integrins, ii. rationalize the interplay between conformational equilibria and receptor affinity. The protocol relies on the combination of enhanced sampling molecular dynamics technique (Bias-Exchange Metadynamics), docking calculations and re-scoring via Molecular Mechanics/Generalized-Born Surface Area. The reliability of our method was tested investigating the impact of single and multiple N-methylation on the equilibrium conformations of five RGD (Arg-Gly-Asp) cyclohexapeptides that were generated to increase their selectivity towards αIIbβ3 integrin.[2] We obtained excellent results: the conformational sampling was in good agreement with available NMR data and we were able to discriminate between binders and non-binders. Additionally we offered a structural rationale for why N-methylation increases peptides affinities towards a specific integrin.
Herein we have shown that Metadynamics can represent a promising in silico screening strategy, opening new perspectives in the application of cyclopeptides as therapeutic inhibitors. We expect that this combination of techniques will be successfully exploited in future to predict the conformational effects of methylation and other chemical modifications in cyclopeptides
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