67 research outputs found
Cryo-EM structure of cardiac amyloid fibrils from an immunoglobulin light chain (AL) amyloidosis patient
No full textGMXPBSA 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
COMPUTATIONAL TECHNIQUES TO EVALUATE AT ATOMIC LEVEL THE MECHANISM OF MOLECULAR BINDING
No full textIntegrins are an important class of transmembrane receptors that relay signals bidirectionally across the plasma membrane, regulating several cell functions and playing a key role in diverse pathological processes. Specifically, integrin subtype αIIbβ3 is involved in thrombosis and stroke, while subtypes αvβ3 and α5β1 play an important role in angiogenesis and tumor progression. They therefore emerged as attractive pharmacological targets. In the past decades several peptides and peptidomimetics targeting these proteins and based on the integrin recognition motif RGD (Arg-Gly-Asp) have been developed, whereby their affinity and selectivity for a specific integrin subtype have been fine-tuned by modulation of RGD flanking residues, by cyclization or by introduction of chemical modifications. Thus far, the design and development of RGD-based cyclopeptides have been mainly based on empirical approaches, requiring expensive and time-consuming synthesis campaigns. In this field, the employment of computational tools, that could be valuable to accelerate the drug design and optimization process, has been limited by the inherent difficulties to predict in silico the three-dimensional structure and the inhibitory activity of cyclopeptides. However, recent improvements in both computational resources and in docking and modeling techniques are expected to open new perspectives in the development of cyclopeptides as modulators of protein-protein interactions and, particularly, as integrin inhibitors.
Within this PhD project, I have investigated the applicability of computational techniques in predicting and rationalizing how the environment of the recognition-motif in cyclopeptides (i.e. flanking residues and introduction of chemical modification) could influence their integrin affinity and selectivity. These features can regulate integrin affinity both by favoring direct interactions with the receptor and/or by modulating the three-dimensional conformation properties of the recognition motif. To take into account both these aspects, I have proposed and optimized a multi-stage computational protocol in which an exhaustive conformational sampling of the investigated cyclopeptides is followed by docking calculations and re-scoring techniques. Specifically: i) the exhaustive sampling could be achieved by using Metadynamics in its Bias Exchange variant (BE-META), an enhanced sampling technique which represents a valuable methodology for the acceleration of rare events, allowing to cross the high free energy barriers characteristic of cyclopeptides and providing reliable estimations of the populations of the accessible conformers. ii) The docking calculations, complemented with the re-scoring technique MM-GB/SA (Molecular Mechanics Generalized Born Surface Area) and the cluster analysis of the decoy poses, allow to evaluate the ability of each peptide to engage interactions with the receptors and to rank the docking poses according to their binding ability; iii) a joint analysis of the previous outcomes results in a reliable ranking of cyclopeptides based on their binding affinity and in the rationalization of their structure-activity relationship. This computational protocol has been exploited in two different applications, illustrated within the thesis.
In the first application the protocol has been applied to rationalize how the introduction of chemical modifications, specifically backbone N-methylation, impacts on the equilibrium conformation and consequently on the integrin affinity of five RGD containing cyclic hexapeptides, which were previously generated by the group of professor Kessler to modulate their selectivity for αIIbβ3 integrin. The study revealed that backbone N-methylation affects the preferences of the φ dihedral angle of the methylated residue, specifically favoring the adoption of additional conformations, characterized by a 180° twist of the peptide bond plane preceding the methylated residue. These twists of dihedral angles were found to have relevant consequences on the cyclopeptides conformation, influencing the formation of intra-molecular hydrogen bonds as well as some structural features which are known to be fundamental in integrin binding. Both structural analysis and docking calculations allowed to identify the “bioactive” conformation (i.e. an extended RGD conformation able to recapitulate the canonical electrostatic and the additional stabilizing hydrophobic interactions). Of note, the cyclopeptides that are pre-organized, already in their free state, in this bioactive conformation are the ones displaying the best αIIbβ3 binding affinity in terms of IC50 values, confirming that pre-organization of cyclopeptides in solution can strongly affect their binding strength to the receptor and demonstrating that the knowledge of their conformational equilibrium is fundamental to provide reliable affinity predictions.
In the second application, I have focused my attention on cyclopeptides harboring a recently discovered integrin recognition motif: isoDGR (isoAsp-Gly-Arg), deriving from the spontaneous deamidation of NGR (Asp-Gly-Arg) sequence present in integrin natural ligands. As a preliminary step, I have systematically tested the accuracy of eight Molecular Mechanics force fields in reproducing the equilibrium properties of isoDGR-based cyclopeptides, for which NMR experiments have been acquired. The comparison between simulated and NMR-derived data (i.e. chemical shifts and J scalar couplings) revealed that, while most of the investigated force fields can properly reproduce the equilibrium conformational properties of cyclic peptides, only two of them (i.e. the AMBER force fields ff99sb-ildn and ff99sb*-ildn) are able to recover the NMR observables characteristics of the non-standard residue isoAspartate with an accuracy close to the systematic uncertainty. Overall, these results suggest that the transferability of force field parameters to non standard amino acids is not straightforward. However, two force fields allowed to obtain a satisfactory accuracy and have been therefore employed for the subsequent investigation. I thus applied the computational protocol to rationalize the diverse selectivity and affinity profiles for integrins αvβ3 and α5β1, both related to cancer, displayed by three isoDGR-based cyclic hexapeptides. These molecules differ in the residues flanking the isoDGR motif and show appealing tumor-homing properties; specifically it has been shown that one of these, c(CGisoDGRG), can be coupled with human serum albumin through a chemical linker to be used as a drug delivery agent for functionalized gold nanoparticles. Herein, I investigated the role of the chemical linker in improving affinity and selectivity of c(CGisoDGRG) for αvβ3. The application of the multi-stage protocol allowed to propose an explanation for the different selectivity profiles displayed by these molecules, where the direct interactions engaged by the flanking residues and/or their steric hindrance seem to be largely responsible for the observed different affinities. As a last result, through the combination of MD and NMR techniques, I demonstrated that the chemical linker improved the αvβ3 affinity of c(CGisoDGRG) by engaging direct interactions with the receptor and I proposed two possible complex models, which well-reproduce data from Saturation Transfer Difference experiments.
Overall, in this PhD work I have shown that the combination of different computational techniques, BE-META, docking and MM-GB/SA re-scoring, could be a reliable approach to perform structure-activity relationship studies in cyclopeptides. Specifically, the proposed protocol is able to predict the influence of the recognition motif environment (i.e. chemical modification and flanking residues) on integrin affinities. These two features regulate integrin affinity differently: the first one by conformational modulation of the recognition motif, the second by engaging direct interactions with the receptor. Of note, the approach can deal with both these mechanisms of affinity modulation. We expect that the protocol herein described could be used in future to screen novel peptides library or to complement biochemical experiments during the drug optimization stages, assisting organic chemists in the design of more effective integrin-targeting peptides
How to determine accurate conformational ensembles by metadynamics metainference : A chignolin study case
No full textThe reliability and usefulness of molecular dynamics simulations of equilibrium processes rests on their statistical precision and their capability to generate conformational ensembles in agreement with available experimental knowledge. Metadynamics Metainference (M&M), coupling molecular dynamics with the enhanced sampling ability of Metadynamics and with the ability to integrate experimental information of Metainference, can in principle achieve both goals. Here we show that three different Metadynamics setups provide converged estimate of the populations of the three-states
populated by a model peptide. Errors are estimated correctly by block averaging, but higher precision is obtained by performing independent replicates. One effect of Metadynamics is that of dramatically decreasing the number of effective frames resulting from the simulations and this is relevant for M&M where the number of replicas should be large enough to capture the conformational heterogeneity behind the experimental data. Our simulations allow also us to propose that monitoring the relative error associated with conformational averaging can help to determine the minimum number of replicas to be simulated in the context of M&M simulations. Altogether our data provides useful indication on how to generate sound conformational ensemble in
agreement with experimental data
Determination of Protein Structural Ensembles by Hybrid-Resolution SAXS Restrained Molecular Dynamics
No full textSmall-angle X-ray scattering (SAXS) experiments provide low-resolution but valuable information about the dynamics of biomolecular systems, which could be ideally integrated into molecular dynamics (MD) simulations to accurately determine conformational ensembles of flexible proteins. The applicability of this strategy is hampered by the high computational cost required to calculate scattering intensities from three-dimensional structures. We previously presented a hybrid resolution method that makes atomistic SAXS-restrained MD simulation feasible by adopting a coarse-grained approach to efficiently back-calculate scattering intensities; here, we extend this technique, applying it in the framework of metainference with the aim to investigate the dynamical behavior of flexible biomolecules. The efficacy of the method is assessed on the K63-diubiquitin, showing that the inclusion of SAXS restraints is effective in generating a reliable conformational ensemble, improving the agreement with independent experimental data
Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale
No full textThe current capacity of computers makes it possible to perform simulations of small systems with portable, explicit-solvent potentials achieving high degree of accuracy. However, simplified models must be employed to exploit the behavior of large systems or to perform systematic scans of smaller systems. While powerful algorithms are available to facilitate the sampling of the conformational space, successful applications of such models are hindered by the availability of simple enough potentials able to satisfactorily reproduce known properties of the system. We develop an interatomic potential to account for a number of properties of proteins in a computationally economic way. The potential is defined within an all-atom, implicit solvent model by contact functions between the different atom types. The associated numerical values can be optimized by an iterative Monte Carlo scheme on any available experimental data, provided that they are expressible as thermal averages of some conformational properties. We test this model on three different proteins, for which we also perform a scan of all possible point mutations with explicit conformational sampling. The resulting models, optimized solely on a subset of native distances, not only reproduce the native conformations within a few Angstroms from the experimental ones, but show the cooperative transition between native and denatured state and correctly predict the measured free-energy changes associated with point mutations. Moreover, differently from other structure-based models, our method leaves a residual degree of frustration, which is known to be present in protein molecules
Dynamics of bubbles under stochastic pressure forcing
No full textSeveral studies have investigated the dynamics of a single spherical bubble at rest under a nonstationary pressure forcing. However, attention has almost always been focused on periodic pressure oscillations, neglecting the case of stochastic forcing. This fact is quite surprising, as random pressure fluctuations are widespread in many applications involving bubbles (e.g., hydrodynamic cavitation in turbulent flows or bubble dynamics in acoustic cavitation), and noise, in general, is known to induce a variety of counterintuitive phenomena in nonlinear dynamical systems such as bubble oscillators. To shed light on this unexplored topic, here we study bubble dynamics as described by the Keller-Miksis equation, under a pressure forcing described by a Gaussian colored noise modeled as an Ornstein-Uhlenbeck process. Results indicate that, depending on noise intensity, bubbles display two peculiar behaviors: when intensity is low, the fluctuating pressure forcing mainly excites the free oscillations of the bubble, and the bubble's radius undergoes small amplitude oscillations with a rather regular periodicity. Differently, high noise intensity induces chaotic bubble dynamics, whereby nonlinear effects are exacerbated and the bubble behaves as an amplifier of the external random forcin
Disordered Regions Flanking the Binding Interface Modulate Affinity between CBP and NCOA
No full textRecognition motifs that mediate protein-protein interactions are usually embedded within longer intrinsically disordered regions. While binding interfaces involving the recognition motif in such interactions are well studied, less is known about the role of disordered regions flanking the motifs. The interaction between the transcriptional co-activators NCOA3 (ACTR) and CBP is mediated by coupled binding and folding of the two domains CID and NCBD. Here, we used circular dichroism and kinetics to directly quantify the contribution of the adjacent flanking regions of CID to its interaction with NCBD. Using N-and C terminal combinatorial variants we found that the flanking regions promote binding in an additive fashion while retaining a large degree of disorder in the complex. Experiments at different ionic strengths demonstrated that the increase in affinity is not mediated by electrostatic interactions from the flanking regions. Instead, site-directed mutagenesis and molecular dynamics simulations suggest that binding is promoted by short-lived non-specific hydrophobic contacts between the flanking regions and NCBD. Our findings are consistent with highly frustrated interactions outside of the canonical binding interface resulting in a slightly energetically favorable fuzzy binding. Modulation of affinity via flanking regions could represent a general mechanism for functional regulation by intrinsically disordered protein regions.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Martini bead form factors for nucleic acids and their application in the refinement of protein–nucleic acid complexes against SAXS data
No full textThe use of small-angle X-ray scattering (SAXS) in combination with molecular dynamics simulation is hampered by its heavy computational cost. The calculation of SAXS from atomic structures can be speeded up by using a coarse-grain representation of the structure. Following the work of Niebling, Bjorling & Westenhoff [J. Appl. Cryst. (2014), 47, 1190-1198], the Martini bead form factors for nucleic acids have been derived and then implemented, together with those previously determined for proteins, in the publicly available PLUMED library. A hybrid multi-resolution strategy has also been implemented to perform SAXS restrained simulations at atomic resolution by calculating the virtual positions of the Martini beads on the fly and using them for the calculation of SAXS. The accuracy and efficiency of the method are demonstrated by refining the structure of two protein-nucleic acid complexes. Instrumental for this result is the use of metainference, which allows the consideration and alleviation of the approximations at play in the present SAXS calculations
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
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