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Carloni, P.

Publications and source records attributed to Carloni, P..

At least 19 recordsLinked to original sources

Membrane Lipids and Water Shape the Unbinding Kinetics of ZM241385 from Human Adenosine A2A Receptor Variants

Ligand residence time is increasingly recognized as an important determinant of drug efficacy. In the human adenosine A2A receptor (hA2AR) bound to the high-affinity antagonist ZMA, mutations at the extracellular entrance of the binding pocket markedly accelerate ZMA dissociation while largely preserving binding affinity. This effect has been attributed to disruption of the E169ECL2-H7.29 salt bridge that constrains the extracellular entrance in the wild-type receptor. However, how the interaction network is reorganized after salt-bridge disruption remains unknown. Here, we combine well-tempered metadynamics and infrequent metadynamics simulations to characterize the ZMA dissociation pathway and transition-state ensemble. The simulations reproduce the experimentally observed trend in dissociation rates and reveal that the hydrogen-bond network stabilizing ZMA in the bound state is largely replaced by water-mediated interactions during unbinding. In the mutants, disruption of the E169ECL2-H7.29 interaction expands the binding pocket and increases hydration, while additional ligand-lipid interactions emerge specifically at the transition state. These interactions are substantially less frequent in the wild type, indicating that membrane lipids can directly participate in ligand escape when the extracellular gate is disrupted. Thus, the mutations selectively reshape the transition-state interaction network including recruitment of membrane lipids. Thus, the interaction of the latter with the ligand accompanies and may contribute to the mutants reduced dissociation barrier, thereby facilitating ligand release.

biophysics↗

From Atoms to Neuronal Spikes: A Multi-Scale Simulation Framework

Understanding how molecular events in ion channels impact neuronal excitability, as derived from the calculation of the time course of the membrane potentials, can help elucidate the mechanisms of neurological disease-linked mutations and support neuroactive drug design. Here, we propose a multi-scale simulation approach which couples molecular simulations with neuronal simulations to predict the variations in membrane potential and neural spikes. We illustrate this through two examples. First, molecular dynamics simulations predict changes in current and conductance through the AMPAR neuroreceptor when transitioning from the wild-type protein to certain disease-associated variants. The results of these simulations inform morphologically detailed models of cortical pyramidal neurons, which are simulated using the Arbor framework to determine neural spike activity. Based on these multiscale simulations, we suggest that disease associated AMPAR variants may significantly impact neuronal excitability. In the second example, the Arbor model is coupled with coarse-grained Monte Carlo gating simulations of voltage-gated (K+ and Na+) channels. The pre-dicted current from these ion channels altered the membrane potential and, in turn, the excitation state of the neuron was updated in Arbor. The resulting membrane potential was then fed back into the Monte Carlo simulations of the voltage-gated ion channels, resulting in a bidirectional coupling of current and membrane potential. This allowed the transitions of the states of the ion channels to influence the membrane potentials and vice versa. Our simulations also included the crucial -- so far unexplored -- effects of the composition of the lipid membrane embedding the ion channels on the membrane potential and revealed a significant impact of temperature on the neuronal excitability. Our combined approaches predicted membrane potentials consistent with electrophysiological recordings and established a multi-scale framework linking the atomistic perturbations to neuronal excitability.

neuroscience↗

A cytosolic function of DNMT1 controls neuronal morphogenesis via microtubule regulation

Proteins traditionally confined to a single cellular compartment are increasingly recognized to exert non-canonical functions in alternative domains. The DNA methyltransferase 1 (DNMT1), classically defined as the maintenance methyltransferase that preserves DNA methylation patterns during replication, exemplifies this versatility. Beyond its canonical role, DNMT1 is highly expressed in the developing and adult brain, where it contributes to transcriptional regulation in postmitotic neurons. Notably, cytoplasmic DNMT1 localization has been observed in neural cells, and emerging evidence links DNMT1 to mitochondrial function with implications for neurodegenerative disease, whereby the underlying functional mechanisms remain to be fully elucidated. Here, we identify a previously unrecognized cytosolic function of DNMT1 in developing cortical excitatory neurons. Through genetic perturbation, proteomics, and high-resolution imaging, we show that DNMT1 regulates dendritic and axonal branching independently of its catalytic activity and nuclear localization. Instead, DNMT1 operates as a cytosolic scaffold interacting with the polarity regulator DOCK7 to modulate Rac1-STMN1 signaling, microtubule dynamics, and organelle trafficking. These findings expand the conceptual framework of DNMT1 from a genome guardian to a dual-compartment regulator that coordinates cytoskeletal remodeling and mitochondrial positioning. Beyond advancing our understanding of neuronal morphogenesis, this work provides mechanistic insight into how DNMT1 mutations may lead to neurodegenerative diseases.

neuroscience↗

Insights on the effect of extracellular acidification on an HCNchannel: a molecular dynamics study

Extracellular acidification may affect the structure and function of ion channels by neutralizing acidic residues exposed to the extracellular space. However, the relationship between these changes in the protonation state and alterations in the channels structure and dynamics remains unclear. Here, we used atomistic simulations and graph-based algorithms to study mice hyperpolarization-activated cyclic nucleotide-gated type 2 channels, whose gating is facilitated by extracellular acidification. Our simulations revealed that E212, a residue facing the extracellular space, may be involved in complex hydrogen bond networks with the S4 helix, which plays a role in the gating mechanism. This network is partially disrupted at acidic pH levels, affecting the molecular interactions of the S4 helix. This, in turn, may alter the domains response to membrane voltage changes and, consequently, gating. We conclude that the H-bond network from an extracellular residue to the main gating domain may be an important factor in the observed channel activities at different pH levels. O_FIG O_LINKSMALLFIG WIDTH=157 HEIGHT=200 SRC="FIGDIR/small/674486v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@11a34c6org.highwire.dtl.DTLVardef@17ec631org.highwire.dtl.DTLVardef@5e9e4org.highwire.dtl.DTLVardef@3ea8fc_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

IR spectroscopy: from experimental spectra to high-resolution structural analysis by integrating simulations and machine learning

Understanding biomolecular function at the atomic scale requires detailed insight into the structural changes underlying dynamic processes. Vibrational infrared (IR) spectroscopy--when paired with biomolecular simulations and quantum-chemical calculations--determines bond length variations on the order of 0.01 [A], providing insights into these structutral changes. Here, we address the forward problem in IR spectroscopy: predicting high-accuracy vibrational spectra from known molecular structures identified by biomolecular simulations. Solving this problem lays the groundwork for the inverse problem: inferring structural ensembles directly from experimental IR spectra. We evaluate two computational approaches, normal mode analysis and Fourier-transformed dipole autocorrelation, against experimental IR spectra of N-Methylacetamide, a prototypical model for peptide bond vibrations. Spectra are derived from simulation models at multiple levels of theory, including hybrid quantum mechanics/molecular mechanics, machine-learned and classical molecular mechanics approaches. Our results highlight the capabilities and limitations of current theoretical biophysical approaches to decode structural information from experimental vibrational spectroscopy data. These insights underscore the potential of future artificial intelligence (AI)-enhanced models to enable direct IR-based structure determination. For example, resolving the so far experimentally inaccessible structures of toxic oligomers involved in neurodegenerative diseases, enabling improved disease diagnostics and targeted therapies. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/665767v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@6603d3org.highwire.dtl.DTLVardef@1852c85org.highwire.dtl.DTLVardef@2ddaccorg.highwire.dtl.DTLVardef@77b554_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

Structural and functional role of residues undergoing hereditary spastic paraplegias-linked mutations: insights from a simulation of the spiral to ring transition in katanin

Several dozen mutations in the large human spastin enzyme assembly have been associated with mobility impairment in hereditary spastic paraplegias. Some of them impact the structural determinants of two functional conformations of the protein, spiral and ring. Here we investigate the possible effect of the mutations on the transition between the two conformations, which is essential for the enzymatic function. By performing a variety of molecular simulations (including metadynamics) on the closely related protein katanin, we suggest that about one fourth of the known disease-associated mutations affect the transition and/or the stability of a previously unrecognized intermediate. The protocol used here can be applied to the study of conformational changes in other large biomolecular complexes. Significance StatementBy combining molecular dynamics and enhanced sampling simulations with custom-designed collective variables, we explore transient intermediate states in a large protein assembly, the severing enzyme katanin. This enzyme plays a critical role in neuronal microtubule remodeling. By targeting the transition between the spiral and ring conformations of the protein, we reveal mechanisms associated with neurodegenerative mutations that impair the function of spastin, a structurally and functionally similar enzyme. These findings provide insights that may inform future therapeutic strategies. They also expand our ability to simulate molecular processes relevant to health and disease, as our approach can be readily applied to study structural changes in other complex biological systems.

biophysics↗

pH-dependent structural dynamics of the neuropeptide Y in aqueous solution

ABSTRACT. The neuropeptide Y regulates key molecular processes in the brain. Its interaction with the cell membrane, where it binds to specialized receptors with key physiological roles, likely depends on the pH. The structural ensembles of the porcine and human peptides, solved by Nuclear Magnetic Resonance (NMR) acid pH in aqueous solution, indicate an -helical core with unstructured termini. However, the protonation states of the carboxylic and histidine residues of the peptide, and the interplay between protonation states and peptide conformational dynamics, have not been explored. Here we perform constant pH simulations and graph-based analyses to investigate dynamics and H-bond patterns of the neuropeptide Y in the pH range from 3.0 to 7.0. We find that an -helical core, as observed in the NMR experiments, is presented at all pH values, though its length can vary by 2-3 residues depending on the pH. The pKa of Asp16, part of the -helix, and of Asp11 may shift by more than on pH unit. Based on these findings, we suggest that performing constant pH simulations may be required to describe accurately the interactions of the peptide with its cellular partners at the pH values of interest.

biophysics↗

Transport mechanism of DgoT, a bacterial homolog of SLC17 organic anion transporters

The solute carrier 17 (SLC17) family contains anion transporters that accumulate neuro-transmitters in secretory vesicles, remove carboxylated monosaccharides from lysosomes, or extrude organic anions from the kidneys and the liver. We combined classical molecular dynamics simulations, Markov state modeling and hybrid first principles quantum mechani-cal/classical mechanical (QM/MM) simulations with experimental approaches to describe the transport mechanisms of a model bacterial protein, the D-galactonate transporter DgoT, at atomic resolution. We found that protonation of D46 and E133 precedes galactonate binding and that substrate binding induces closure of the extracellular gate, with the conserved R47 coupling substrate binding to transmembrane helix movement. After isomerization to an inward-facing conformation, deprotonation of E133 and subsequent proton transfer from D46 to E133 opens the intracellular gate and permits galactonate dissociation either in its unprotonated form or after proton transfer from E133. After release of the second proton, apo DgoT returns to the outward-facing conformation. Our results provide a framework to understand how various SLC17 transport functions with distinct transport stoichiometries can be attained through subtle variations in proton and substrate binding/unbinding.

biophysics↗

Physical Chemistry of Drug Permeation through the Cell Membrane with Atomistic Detail

We provide a molecular-level description of the thermodynamics and mechanistic aspects of drug permeation through the cell membrane. As a case study, we considered the anti-malaria, FDA approved drug chloroquine. Molecular dynamics simulations of the molecule (in its neutral and protonated form) were performed in the presence of different lipid bilayers, with the aim of uncovering key aspects of the permeation process, a fundamental step for drugs action. Free energy values obtained by well-tempered metadynamics simulations suggest that the neutral form is the only permeating protomer, consistent with experimental data. H-bond interactions of the drug with water molecules and membrane headgroups play a crucial role for permeation. The presence of the transmembrane potential, investigated here for the first time in a drug permeation study, does not qualitatively affect these conclusions. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/550356v1_ufig1.gif" ALT="Figure 1"> View larger version (71K): org.highwire.dtl.DTLVardef@d1f5b9org.highwire.dtl.DTLVardef@5b6b0forg.highwire.dtl.DTLVardef@1d1b55borg.highwire.dtl.DTLVardef@d96b52_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

AI-based novel-chemotype GPCRs drugs: introducing ligand type classifiers and systems biology

Identifying the correct chemotype of ligands targeting receptors (i.e., agonist or antagonist) is a challenge for in silico screening campaigns. Here we present an approach that identifies novel chemotype ligands by combining structural data with a random forest agonist/antagonist classifier and a signal-transduction kinetic model. As a test case, we apply this approach to identify novel antagonists of the human adenosine transmembrane receptor type 2A, an attractive target against Parkinsons disease and cancer. The identified antagonists were tested here in a radioligand binding assay. Among those, we found a promising ligand whose chemotype differs significantly from all so-far reported antagonists, with a binding affinity of 310{+/-}23.4 nM. Thus, our protocol emerges as a powerful approach to identify promising ligand candidates with novel chemotypes while preserving antagonistic potential and affinity in the nanomolar range.

bioinformatics↗

Impact of Phosphorylation on alpha-Synuclein Structural Determinants

Serine 129 can be phosphorylated in pathological inclusions formed by the intrinsically disordered protein human -synuclein (AS), a key player in Parkinsons disease and other synucleinopathies. Here, molecular simulations provide insight into the structural ensemble of phosphorylated AS. The simulations suggest that phosphorylation does not impact the structural content of the physiological AS conformational ensemble in aqueous solution, as the phosphate group is mostly solvated. The hydrophobic region of AS contains {beta}-hairpin structures, which may increase the propensity of the protein to undergo amyloid formation, as seen in the non-physiological (non-acetylated) form of the protein in a recent molecular simulation study. Our findings are consistent with existing experimental data, with the caveat of the observed limitations of the force field for the phosphorylated moiety. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/531864v4_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@108c32dorg.highwire.dtl.DTLVardef@45e5d7org.highwire.dtl.DTLVardef@f49cf6org.highwire.dtl.DTLVardef@16ceb61_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

Proton Transfers to DNA in Native Electrospray Ionization Mass Spectrometry: A QM/MM Study.

Native electrospray ionization - ion mobility mass spectrometry (N-ESI/IM-MS) is a powerful approach for low-resolution structural studies of DNAs in the free state and in complex with ligands. Solvent vaporization is coupled with proton transfers from ammonium ions to the DNA resulting in a reduction of the DNA charge. Here we provide insight on these processes by classical MD and QM/MM free energy calculations on the (GpCpGpApApGpC) heptamer, for which a wealth of experiments is available. Our multiscale simulations, consistent with experimental data, reveal a highly complex scenario: the proton either sits on one of the molecules or is fully delocalized on both, depending on the level of hydration of the analytes and on size of the droplets formed during the electrospray experiments. This work complements our previous study on the intramolecular proton transfer on the same heptamer occurring after the processes studied here, and, together, provide a first molecular view of proton transfer in N-ESI/IM-MS. TOC GRAPHICS O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/511116v1_ufig1.gif" ALT="Figure 1"> View larger version (67K): org.highwire.dtl.DTLVardef@3d85d3org.highwire.dtl.DTLVardef@11ce1d1org.highwire.dtl.DTLVardef@12d932corg.highwire.dtl.DTLVardef@1196de8_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

Modelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases

The seamless integration of human disease-related mutation data into protein structures is an essential component of any attempt to correctly assess the impact of the mutation. The key step preliminary to any structural modelling is the identification of the correct isoform onto which mutations should be mapped because there are several functionally different protein isoforms from the same gene. To handle large sets of data coming from omics techniques, this challenging task should be automatized. Here we present our code MoNvIso (Modelling eNvironment for Isoforms), which pinpoints the correct isoform associated with the mutation of interest and builds a structural model of both the wild type isoform and the related variants starting from the name of the gene and the list of mutations of interest.

bioinformatics↗

Water-triggered, irreversible conformational change of SARS-CoV-2 main protease on passing from the solid state to aqueous solution

The main protease from SARS-CoV-2 is a homodimer. Yet, a recent 0.1 ms long molecular dynamics simulation shows that it readily undergoes a symmetry breaking event on passing from the solid state to the aqueous solution. As a result, the subunits present distinct conformations of the binding pocket. By analysing this long time simulation, here we uncover a previously unrecognised role of water molecules in triggering the transition. Interestingly, each subunit presents a different collection of long-lived water molecules. Enhanced sampling methods performed here, along with machine learning approaches, further establish that the transition to the asymmetric state is essentially irreversible.

biophysics↗

An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADP-ribosylation hydrolases inhibitors

A variety of enhanced sampling methods can predict free energy landscapes associated with protein/ligand binding events, characterizing in a precise way the intermolecular interactions involved. Unfortunately, these approaches are challenged by not uncommon induced fit mecchanisms. Here, we present a variant of the recently reported volume-based metadynamics (MetaD) method which describes ligand binding even when it affects protein structure. The validity of the approach is established by applying it to a substrate/enzyme complexes of pharmacological relevance: this is the mono-ADP-ribose (ADPr) in complex with mono-ADP-ribosylation hydrolases (MacroD1 and MacroD2), where induced-fit phenomena are known to be operative. The calculated binding free energies are consistent with experiments, with an absolute error less than 0.5 kcal/mol. Our simulations reveal that in all circumstances the active loops, delimiting the boundaries of the binding site, rearrange from an open to a closed conformation upon ligand binding. The calculations further provide, for the first time, the molecular basis of the experimentally observed affinity changes in ADPr binding on passing from MacroD1 to MacroD2 and all its mutants. Our study paves the way to investigate in a completely general manner ligand binding to proteins and receptors.

biochemistry↗

A blueprint for high affinity SARS-CoV-2 Mpro inhibitors from activity-based compound library screening guided by analysis of protein dynamics

The SARS-CoV-2 coronavirus outbreak continues to spread at a rapid rate worldwide. The main protease (Mpro) is an attractive target for anti-COVID-19 agents. Unfortunately, unexpected difficulties have been encountered in the design of specific inhibitors. Here, by analyzing an ensemble of ~30,000 SARS-CoV-2 Mpro conformations from crystallographic studies and molecular simulations, we show that small structural variations in the binding site dramatically impact ligand binding properties. Hence, traditional druggability indices fail to adequately discriminate between highly and poorly druggable conformations of the binding site. By performing ~200 virtual screenings of compound libraries on selected protein structures, we redefine the proteins druggability as the consensus chemical space arising from the multiple conformations of the binding site formed upon ligand binding. This procedure revealed a unique SARS-CoV-2 Mpro blueprint that led to a definition of a specific structure-based pharmacophore. The latter explains the poor transferability of potent SARS-CoV Mpro inhibitors to SARS-CoV-2 Mpro, despite the identical sequences of the active sites. Importantly, application of the pharmacophore predicted novel high affinity inhibitors of SARS-CoV-2 Mpro, that were validated by in vitro assays performed here and by a newly solved X-ray crystal structure. These results provide a strong basis for effective rational drug design campaigns against SARS-CoV-2 Mpro and a new computational approach to screen protein targets with malleable binding sites.

biophysics↗

On the accuracy of molecular simulation-based predictions of koff values: a Metadynamics study

Molecular simulations have made great progresses in predicting koff values--the kinetic constant of drug unbinding, a key parameter for modern pharmacology--yet computed values under- or over-estimate experimental data in a system- and/or technique-dependent way. In an effort at gaining insights on this issue, here we used an established method to calculate koff values--frequency-adaptive metadynamics with force field-- and a subsequent QM/MM descriptions of the interactions. First, using force field-based metadynamics, we calculate koff of the Positron Emission Tomography (PET) ligand iperoxo targeting the human muscarinic acetylcholine receptor M2. In line with previously performed in silico studies, the prediction (3.7 {+/-} 0.7 * 10-4 s-1) turned out to differ significantly from the experimentally measured value (1.0 {+/-} 0.2 * 10-2 s-1). Next, we use DFT-based QM/MM simulations to show that this discrepancy arises from erroneous force field energetics at the transition state. It turns out that this discrepancy is partly caused by lack of electronic polarization and/or charge transfer in commonly employed force field. We expect these issues to arise also in other systems where charged portions of the system play a pivotal role, such as protein- or DNA-protein complexes. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/015396v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1ee4e1aorg.highwire.dtl.DTLVardef@49ba0forg.highwire.dtl.DTLVardef@565f25org.highwire.dtl.DTLVardef@80940e_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

Regulation of adenylyl cyclase 5 in striatal neurons confers the ability to detect coincident neuromodulatory signals

Long-term potentiation and depression of synaptic activity in response to stimuli is a key factor in reinforcement learning. Strengthening of the corticostriatal synapses depends on the second messenger cAMP, whose synthesis is catalysed by the enzyme adenylyl cyclase 5 (AC5), which is itself regulated by the stimulatory Golf and inhibitory Gi proteins. AC isoforms have been suggested to act as coincidence detectors, promoting cellular responses only when convergent regulatory signals occur close in time. However, the mechanism for this is currently unclear, and seems to lie in their diverse regulation patterns. Despite attempts to isolate the ternary complex, it is not known if Golf and Gi can bind to AC5 simultaneously, nor what activity the complex would have. Using protein structure-based molecular dynamics simulations, we show that this complex is stable and inactive. These simulations, along with Brownian dynamics simulations to estimate protein association rates constants, constrain a kinetic model that shows that the presence of this ternary inactive complex is crucial for AC5s ability to detect coincident signals, producing a synergistic increase in cAMP. These results reveal some of the prerequisites for corticostriatal synaptic plasticity, and explain recent experimental data on cAMP concentrations following receptor activation. Moreover, they provide insights into the regulatory mechanisms that control signal processing by different AC isoforms.\n\nAuthor summaryAdenylyl cyclases (ACs) are enzymes that can translate extracellular signals into the intracellular molecule cAMP, which is thus a 2nd messenger of extracellular events. The brain expresses nine membrane-bound AC variants, and AC5 is the dominant form in the striatum. The striatum is the input stage of the basal ganglia, a brain structure involved in reward learning, i.e. the learning of behaviors that lead to rewarding stimuli (such as food, water, sugar, etc). During reward learning, cAMP production is crucial for strengthening the synapses from cortical neurons onto the striatal principal neurons, and its formation is dependent on several neuromodulatory systems such as dopamine and acetylcholine. It is, however, not understood how AC5 is activated by transient (subsecond) changes in the neuromodulatory signals. Here we combine several computational tools, from molecular dynamics and Brownian dynamics simulations to bioinformatics approaches, to inform and constrain a kinetic model of the AC5-dependent signaling system. We use this model to show how the specific molecular properties of AC5 can detect particular combinations of co-occuring transient changes in the neuromodulatory signals which thus result in a supralinear/synergistic cAMP production. Our results also provide insights into the computational capabilities of the different AC isoforms.

neuroscience↗