Network and atomistic simulations unveil the structural determinants of mutations linked to retinal diseases

A number of incurable retinal diseases causing vision impairments derive from alterations in visual phototransduction. Unraveling the structural determinants of even monogenic retinal diseases would require network-centered approaches combined with atomistic simulations. The transducin G38D mutant associated with the Nougaret Congenital Night Blindness (NCNB) was thoroughly investigated by both mathematical modeling of visual phototransduction and atomistic simulations on the major targets of the mutational effect. Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype. Sub-microsecond molecular dynamics (MD) simulations coupled with Functional Mode Analysis improve the resolution of information, showing that such impairment is likely due to disruption of the PDEgamma binding cavity in transducin. Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site. These findings provide insights into the structural fundamentals of abnormal functioning of visual phototransduction caused by a missense mutation in one component of the signaling network. This combination of network-centered modeling with atomistic simulations represents a paradigm for future studies aimed at thoroughly deciphering the structural determinants of genetic retinal diseases. Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions

Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics:strength in unity

In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations

Cell-free expression and molecular modeling of the γ-secretase complex and G-protein-coupled receptors

Alzheimer’s disease (AD), which was first reported more than a century ago by Alhzeimer, is one of the commonest forms of dementia which affects >30 million people globally (>8 million in Europe). The origin and pathogenesis of AD is poorly understood and there is no cure available for the disease. AD is characterized by the accumulation of senile plaques composed of amyloid beta peptides (Ab 37-43) which is formed by the gamma secretase (GS) complex by cleaving amyloid precursor protein. Therefore GS can be an attractive drug target. Since GS processes several other substrates like Notch, CD44 and Cadherins, nonspecific inhibition of GS has many side effects. Due to the lack of crystal structure of GS, which is attributed to the extreme difficulties in purifying it, molecular modeling can be useful to understand its architecture. So far only low resolution cryoEM structures of the complex has been solved which only provides a rough structure of the complex at low 12-15 A resolution Furthermore the activity of GS in vitro can be achieved by means of cell-free (CF) expression. GS comprises catalytic subunits namely presenilins and supporting elements containing Pen-2, Aph-1 and Nicastrin. The origin of AD is hidden in the regulated intramembrnae proteolysis (RIP) which is involved in various physiological processes and also in leukemia. So far growth factors, cytokines, receptors, viral proteins, cell adhesion proteins, signal peptides and GS has been shown to undergo RIP. During RIP, the target proteins undergo extracellular shredding and intramembrane proteolysis. This thesis is based on molecular modeling, molecular dynamics (MD) simulations, cell-free (CF) expression, mass spectrometry, NMR, crystallization, activity assay etc of the components of GS complex and G-protein coupled receptors (GPCRs). First I validated the NMR structure of PS1 CTF in detergent micelles and lipid bilayers using coarse-grained MD simulations using MARTINI forcefield implemented in Gromacs. CTF was simulated in DPC micelles, DPPC and DLPC lipid bilayer. Starting from random configuration of detergent and lipids, micelle and lipid bilyer were formed respectively in presence of CTF and it was oriented properly to the micelle and bilyer during the simulation. Around DPC molecules formed micelle around CTF in agreement of the experimental results in which 80-85 DPC molecules are required to form micelles. The structure obtained in DPC was similar to that of NMR structure but differed in bilayer simulations showed the possibility of substrate docking in the conserved PAL motif. Simulations of CTF in implicit membrane (IMM1) in CHAMM yielded similar structure to that from coarse grained MD. I performed cell-free expression optimization, crystallization and NMR spectroscopy of Pen-2 in various detergent micelles. Additionally Pen-2 was modeled by a combination of rosetta membrane ab-initio method, HHPred distant homology modeling and incorporating NMR constraints. The models were validated by all atom and coarse grained MD simulations both in detergent micelles and POPC/DPPC lipid bilayers using MARTINI forcefield. GS operon consisting of all four subunits was co-expressed in CF and purified. The presence of of GS subunits after pull-down with Aph-1 was determined by western blotting (Pen-2) and mass spectrometry (Presenilin-1 and Aph-1). I also studied interactions of especially PS1 CTF, APP and NTF by docking and MD. I also made models and interfaces of Pen-2 with PS1 NTF and checked their stability by MD simulations and compared with experimental results. The goal is to model the interfaces between GS subunits using molecular modeling approaches based on available experimental data like cross-linking, mutations and NMR structure of C-terminal fragment of PS1 and transmembrane part of APP. The obtained interfaces of GS subunits may explain its catalysis mechanism which can be exploited for novel lead design. Due to lack of crystal/NMR structure of the GS subunits except the PS1 CTF, it is not possible to predict the effect of mutations in terms of APP cleavage. So I also developed a sequence based approach based on machine learning using support vector machine to predict the effect of PS1 CTF L383 mutations in terms of Aβ40/Aβ42 ratio with 88% accuracy. Mutational data derived from the Molgen database of Presenilin 1 mutations was using for training. GPCRs (also called 7TM receptors) form a large superfamily of membrane proteins, which can be activated by small molecules, lipids, hormones, peptides, light, pain, taste and smell etc. Although 50% of the drugs in market target GPCRs , only few are targeted therapeutically. Such wide range of targets is due to involvement of GPCRs in signaling pathways related to many diseases i.e. dementia (like Alzheimer's disease), metabolic (like diabetes) including endocrinological disorders, immunological including viral infections, cardiovascular, inflammatory, senses disorders, pain and cancer. Cannabinoid and adrenergic receptors belong to the class A (similar to rhodopsin) GPCRs. Docking of agonists and antagonists to CB1 and CB2 cannabinoid receptors revealed the importance of a centrally located rotamer toggle switch, and its possible role in the mechanism of agonist/antagonist recognition. The switch is composed of two residues, F3.36 and W6.48, located on opposite transmembrane helices TM3 and TM6 in the central part of the membranous domain of cannabinoid receptors. The CB1 and CB2 receptor models were constructed based on the adenosine A2A receptor template. The two best scored conformations of each receptor were used for the docking procedure. In all poses (ligand-receptor conformations) characterized by the lowest ligand-receptor intermolecular energy and free energy of binding the ligand type matched the state of the rotamer toggle switch: antagonists maintained an inactive state of the switch, whereas agonists changed it. In case of agonists of β2AR, the (R,R) and (S,S) stereoisomers of fenoterol, the molecular dynamics simulations provided evidence of different binding modes while preserving the same average position of ligands in the binding site. The (S,S) isomer was much more labile in the binding site and only one stable hydrogen bond was created. Such dynamical binding modes may also be valid for ligands of cannabinoid receptors because of the hydrophobic nature of their ligand-receptor interactions. However, only very long molecular dynamics simulations could verify the validity of such binding modes and how they affect the process of activation. Human N-formyl peptide receptors (FPRs) are G protein-coupled receptors (GPCRs) involved in many physiological processes, including host defense against bacterial infection and resolving inflammation. The three human FPRs (FPR1, FPR2 and FPR3) share significant sequence homology and perform their action via coupling to Gi protein. Activation of FPRs induces a variety of responses, which are dependent on the agonist, cell type, receptor subtype, and also species involved. FPRs are expressed mainly by phagocytic leukocytes. Together, these receptors bind a large number of structurally diverse groups of agonistic ligands, including N-formyl and nonformyl peptides of different composition, that chemoattract and activate phagocytes. For example, N-formyl-Met-Leu-Phe (fMLF), an FPR1 agonist, activates human phagocyte inflammatory responses, such as intracellular calcium mobilization, production of cytokines, generation of reactive oxygen species, and chemotaxis. This ligand can efficiently activate the major bactericidal neutrophil functions and it was one of the first characterized bacterial chemotactic peptides. Whereas fMLF is by far the most frequently used chemotactic peptide in studies of neutrophil functions, atomistic descriptions for fMLF-FPR1 binding mode are still scarce mainly because of the absence of a crystal structure of this receptor. Elucidating the binding modes may contribute to designing novel and more efficient non-peptide FPR1 drug candidates. Molecular modeling of FPR1, on the other hand, can provide an efficient way to reveal details of ligand binding and activation of the receptor. However, recent modelings of FPRs were confined only to bovine rhodopsin as a template. To locate specific ligand-receptor interactions based on a more appropriate template than rhodopsin we generated the homology models of FPR1 using the crystal structure of the chemokine receptor CXCR4, which shares over 30% sequence identity with FPR1 and is located in the same γ branch of phylogenetic tree of GPCRs (rhodopsin is located in α branch). Docking and model refinement procedures were pursued afterward. Finally, 40 ns full-atom MD simulations were conducted for the Apo form as well as for complexes of fMLF (agonist) and tBocMLF (antagonist) with FPR1 in the membrane. Based on locations of the N- and C-termini of the ligand the FPR1 extracellular pocket can be divided into two zones, namely, the anchor and activation regions. The formylated M1 residue of fMLF bound to the activation region led to a series of conformational changes of conserved residues. Internal water molecules participating in extended hydrogen bond networks were found to play a crucial role in transmitting the agonist-receptor interactions. A mechanism of initial steps of the activation concurrent with ligand binding is proposed. I accurately predicted the structure and ligand binding pose of dopamine receptor 3 (RMSD to the crystal structure: 2.13 Å) and chemokine receptor 4 (CXCR4, RMSD to the crystal structure 3.21 Å) in GPCR-Dock 2010 competition. The homology model of the dopamine receptor 3 was 8 th best overall in the competition

Calcium sensor proteins in hearing and sight. Biochemical investigation of diseases-associated variants.

Calcium is a cation which plays a pivotal role as second messenger, thus its concentration in cells needs to be finely regulated. Many systems work for that purpose, including Ca2+ sensor proteins, which undergo conformational changes upon Ca2+ coordination via EF-hands. Ca2+ sensors can be ubiquitous or tissue specific. Examples in this sense are represented by Guanylate Cyclase Activating Protein 1 (GCAP1) and Calcium- and Integrin-Binding Protein 2 (CIB2), involved in sight and hearing respectively. Missense point mutations in GCAP1 and CIB2 were found to be associated with genetic diseases characterized by retinal dystrophies and/or deafness. During my PhD, I focused my attention on the characterization of two point mutations namely p.Glu111Val (E111V) in GCAP1, leading to Cone/Rod dystrophy in an Italian family, and p.Glu64Asp (E64D) in CIB2, linked to Usher syndrome type 1J (USH1J), a rare disease characterized by the copresence of blindness and deafness. In particular, I spent the first part of the PhD investigating the role of CIB2 which is still under debate, finding that it is per se uncapable to work as a Ca2+ sensor under physiological conditions and that the conservative mutation linked to USH1J perturbs an allosteric communication between pseudo-EF1 and EF3, thus blocking the protein in an unfunctional conformation. Then, I characterized E111V GCAP1, finding that it is incapable of regulating its molecular target (Guanylate Cyclase), leading to a constitutive active enzyme and thus a progressively high concentrations of Ca2+ and cGMP in cells, which may explain the pathological phenotype. Looking for a potential therapeutic approach for Cone-Rod dystrophies, we found that the well-established Ca2+-relay model, explaining the gradual activation of Guanylate Cyclase by multiple GCAP molecules following gradual changes in intracellular Ca2+ concentrations, seems to be species-specific, since it apparently does not work in the same way in humans as in mouse and bovine photoreceptors. Finally, we identified a general method for the characterization of the interaction between a ubiquitous Ca2+ sensor protein (calmodulin) and inorganic CaF2 nanoparticles, suggesting their suitability as devices for nanomedicine applications

Calcium sensor proteins in health and disease and their potential use in nanomedicine

Proteins are biomolecules involved in virtually every process occurring in cells, characterized by a sequence of amino acids, which confer them peculiar structural features implying specific functions. Ca2+-sensor proteins are a family of proteins whose function is determined by structural changes occurring upon Ca2+-binding, taking part in a wide range of physiological and pathological processes, among which muscle contraction and phototransduction. Unraveling the complex machinery behind these physiological processes is fundamental not only for the sake of expanding our knowledge, but also to understand which mechanisms are altered in inherited pathological conditions, in order to develop potential therapeutic approaches that may help relieving or treating these disorders. Protein therapy is one of the most promising potential treatments, allowing for the substitution of dysfunctional protein pool with physiological variants. Here, a collection of biochemical and biophysical studies focused on the physiological and pathological aspects of some Ca2+-sensor proteins is presented, together with possible therapeutic implications in nanomedicine using CaF2 nanoparticles (NP) as protein carriers. The combination of experimental and computational techniques revealed itself a complementary and exhaustive approach, allowing for a multiscale investigation of protein structural and functional properties. Indeed, the high-resolution structural information provided by Molecular Dynamics (MD) simulations and Protein Structure Network (PSN) analysis can be proficiently integrated into the biophysical and biochemical experimental framework constituted by Circular Dichroism (CD) and fluorescence spectroscopy, Dynamic Light Scattering (DLS), Ca2+-binding assays and enzymatic assays. Such integrated approaches allowed us to discover that mutations of the Neuronal Calcium Sensor (NCS) protein Guanylate Cyclase Activating Protein 1 (GCAP1) associated to retinal dystrophies did not necessarily altered protein Ca2+-affinity, but rather that the pathological dysregulation of the target enzyme Guanylate Cyclase (GC) depended on more complex mechanisms, probably involving modified intramolecular communication. Moreover, PSN analysis of MD trajectories of GCAP1 highlighted that small conformational variations may strongly impact protein functionality, as the switch between activator and inhibiting states occurs through minor structural rearrangements subsequent to the Ca2+/Mg2+ exchange in specific binding sites. This suggested again that the investigation of intramolecular communication may be the key to clarify unknown complex mechanisms of not only of Ca2+-sensor proteins, but also of proteins belonging to different superfamilies