Integrins 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.
COMPUTATIONAL TECHNIQUES TO EVALUATE AT ATOMIC LEVEL THE MECHANISM OF MOLECULAR BINDING / C. Paissoni ; tutor: L. Belvisi ; co-tutor: G. Musco ; coordinatore del corso di dottorato: M. Pizzotti. - Milano : Università degli studi di Milano. DIPARTIMENTO DI CHIMICA, 2017 Mar 28. ((29. ciclo, Anno Accademico 2016.
|Titolo:||COMPUTATIONAL TECHNIQUES TO EVALUATE AT ATOMIC LEVEL THE MECHANISM OF MOLECULAR BINDING|
|Supervisori e coordinatori interni:||PIZZOTTI, MADDALENA|
|Data di pubblicazione:||28-mar-2017|
|Parole Chiave:||Molecular Dynamics; Integrin; Docking; Computational Biology|
|Settore Scientifico Disciplinare:||Settore CHIM/06 - Chimica Organica|
|Citazione:||COMPUTATIONAL TECHNIQUES TO EVALUATE AT ATOMIC LEVEL THE MECHANISM OF MOLECULAR BINDING / C. Paissoni ; tutor: L. Belvisi ; co-tutor: G. Musco ; coordinatore del corso di dottorato: M. Pizzotti. - Milano : Università degli studi di Milano. DIPARTIMENTO DI CHIMICA, 2017 Mar 28. ((29. ciclo, Anno Accademico 2016.|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.13130/c-paissoni_phd2017-03-28|
|Appare nelle tipologie:||Tesi di dottorato|