Carla Molteni

A multi-modal, operando characterisation approach was used to revisit the correlation of electrochemical potassiation and structural evolution in graphite, hence unravelling the specific mechanisms of K-ion storage.

The glycine receptor (GlyR) is a pentameric ligand-gated ion channel that plays important physiological roles in the nervous system. Its malfunction is related to neurological disorders, including startle disease (hyperekplexia), which is characterized by exaggerated startle responses to sudden unexpected stimuli, such as noise or touch. Here, we unravel the molecular mechanisms of action of a specific mutation that is linked to startle disease: Asn46Lys (N46K). This residue, in the GlyR extracellular domain, is not directly involved in neurotransmitter binding but can disrupt the neurotransmitter pathway. To understand how, we performed molecular dynamics simulations of the wild-type and mutated extracellular domain of a homomeric α1 GlyR, assessing the effects of the Asn46Lys mutation. We then sampled multiple unbinding and binding events by means of metadynamics simulations, with a funnel restraint to limit the exploration in the solvent. By evaluating the binding free energy landscape, we observed a substantial reduction in neurotransmitter binding affinity, which is consistent with experiments. We suggest that such a reduction is linked to the interaction of its crucial glutamic acid residue with the lysine mutation competing with the glycine ligand.

The glycine receptor (GlyR) is a pentameric ligand-gated ion channel that plays important physiological roles in the nervous system. Its malfunction is related to neurological disorders including startle disease (hyperekplexia), which is characterized by exaggerated startle responses to sudden unexpected stimuli, such as noise or touch. Here, we unravel the molecular mechanisms of action of a specific mutation that is linked to startle disease: Asn46Lys (N46K). This residue, in the GlyR extracellular domain, is not directly involved in neurotransmitter binding but can disrupt the neurotransmitter pathway. To understand how, we performed molecular dynamics simulations of the wild-type and mutated extracellular domain of a homomeric alpha1 GlyR, assessing the effects of the Asn46Lys mutation. We then sampled multiple unbinding and binding events by means of metadynamics simulations, with a funnel restraint to limit the exploration in the solvent. By evaluating the binding free energy landscape, we observed a substantial reduction in neurotransmitter binding affinity, which is consistent with experiments. We suggest that such reduction is linked to the interaction of its crucial glutamic acid residue with the lysine mutation competing with the glycine ligand.

The glycine receptor, a pentameric ligand-gated ion channel, plays a vital role in inhibitory neurotransmission, reflexes, and neuronal excitability. It is crucial to maintaining the balance and responsiveness of the nervous system to sensory input. The binding of ligands, in this case, glycines, in the extracellular domain (ECD) of the receptor initiates a series of conformational rearrangements that culminate in the opening of the ion channel in the transmembrane domain. There are five binding sites for orthosteric ligands at the interface among the five subunits of the receptor. Experiments suggest that two or three bound glycines are sufficient to activate the receptor and that the occupancy of binding sites affects (un)binding rates. Here, we evaluated the dynamics and interplay of empty and occupied binding pockets and their potential cooperativity. We investigated ECD models for the glycine receptor, built from cryo-EM data, by performing molecular dynamics simulations for different combinations of ligand occupancies. We highlighted the role of glycine in contracting the binding site, optimizing the water content to the amount necessary to mediate crucial interactions and dragging Loop C to cover the pocket. Each subunit participates in two adjacent binding pockets acting, in turn, as the principal and complementary subunit, with structures such as Loop B and Loop F being directly connected. This suggests a combination of push-pull mechanisms mediated by ligands in a potentially frustrated system, which may favor specific occupancy patterns or alternation of binding sites with different levels of contraction.

The glycine receptor, a pentameric ligand-gated ion channel, plays a vital role in inhibitory neurotransmission, reflexes and neuronal excitability. It is crucial to maintaining the balance and responsiveness of the nervous system to sensory input. The binding of ligands, in this case glycines, in the extracellular domain (ECD) of the receptor initiates a series of conformational re-arrangements that culminate in the opening of the ion channel in the transmembrane domain. There are five binding sites for orthosteric ligands at the interface between the five subunits of the receptor. Experiments suggest that two or three bound glycines are sufficient to activate the receptor and that the occupancy of binding sites affects (un)binding rates. Here we evaluate the dynamics and interplay of empty and occupied binding pockets and their potential cooperativity. We investigate an ECD model for the glycine receptor, built from cryoEM data, by performing molecular dynamics simulations for different combination of ligand occupancies. We highlight the role of glycine in contracting the binding site, optimizing the water content to the amount necessary to mediate crucial interactions, and dragging Loop C to cover the pocket. Each subunit participates in two adjacent binding pockets acting in turn as principal and complementary subunit, with structures, like Loop B and Loop F, directly connected. This suggests a combination of push-pull mechanisms mediated by ligands in a potentially frustrated system, which may favour specific occupancy patterns and/or alternation of binding sites with different levels of contraction.

Ice nucleation and growth are critical in many fields, including atmospheric science, cryobiology, and aviation. However, understanding the detailed mechanisms of ice crystal growth remains challenging. In this work, crystallization at the ice/quasi-liquid layer (QLL) interface of the basal and primary prism (prism1) surfaces of hexagonal ice (Ih) was investigated using molecular dynamics simulations across a wide range of temperatures for the TIP4P/Ice model, with comparisons to the mW coarse-grained model. Together with elucidating the temperature-dependent mechanisms of crystallization, face-specific growth rates were systematically estimated. While the prism surface generally exhibits faster growth rates than the basal surface, a temperature-dependent crossover in growth rates between the basal and prism surfaces is observed in TIP4P/Ice simulations, which correlates with crossovers in QLL thickness and properties and with the well-known column to platelets transition in ice-crystal habits at low vapor pressure. This observation helps decode the complex dependence between crystal morphology and temperature in ice crystals.

We study the effect of size on the vibrational modes and frequencies of nanoparticles, by applying a newly developed, robust, and efficient first-principles-based method that we present in outline. We focus on rutile TiO2, a technologically important material whose bulk exhibits a softening of a transverse acoustic mode close to q = (1/2, 1/2, 1/4), which becomes unstable with the application of negative pressure. We demonstrate that, under these conditions, nanoparticles above a critical size exhibit unstable localized modes and we calculate their characteristic localization length and decomposition with respect to bulk phonons. We propose that such localized soft modes could initiate coherent structural phase transformations in small nanoparticles above a critical size.

The temperature dependence of the quasi-liquid layer on the surfaces of hexagonal and cubic ice is investigated with molecular dynamics simulations and a selection of different methods to discriminate the phase of molecules.

The determination of drug residence times, which define the time an inhibitor is in complex with its target, is a fundamental part of the drug discovery process. Synthesis and experimental measurements of kinetic rate constants are, however, expensive and time consuming. In this work, we aimed to obtain drug residence times computationally. Furthermore, we propose a novel algorithm to identify molecular design objectives based on ligand unbinding kinetics. We designed an enhanced sampling technique to accurately predict the free-energy profiles of the ligand unbinding process, focusing on the free-energy barrier for unbinding. Our method first identifies unbinding paths determining a corresponding set of internal coordinates (ICs) that form contacts between the protein and the ligand; it then iteratively updates these interactions during a series of biased molecular dynamics (MD) simulations to reveal the ICs that are important for the whole of the unbinding process. Subsequently, we performed finite-temperature string simulations to obtain the free-energy barrier for unbinding using the set of ICs as a complex reaction coordinate. Importantly, we also aimed to enable the further design of drugs focusing on improved residence times. To this end, we developed a supervised machine learning (ML) approach with inputs from unbiased “downhill” trajectories initiated near the transition state (TS) ensemble of the string unbinding path. We demonstrate that our ML method can identify key ligand–protein interactions driving the system through the TS. Some of the most important drugs for cancer treatment are kinase inhibitors. One of these kinase targets is cyclin-dependent kinase 2 (CDK2), an appealing target for anticancer drug development. Here, we tested our method using two different CDK2 inhibitors for the potential further development of these compounds. We compared the free-energy barriers obtained from our calculations with those observed in available experimental data. We highlighted important interactions at the distal ends of the ligands that can be targeted for improved residence times. Our method provides a new tool to determine unbinding rates and to identify key structural features of the inhibitors that can be used as starting points for novel design strategies in drug discovery.

Tree ring features are affected by environmental factors and therefore are the basis for dendrochronological studies to reconstruct past environmental conditions. Oak wood often provides the data for these studies because of the durability of oak heartwood and hence the availability of samples spanning long time periods of the distant past. Wood formation is regulated in part by epigenetic mechanisms such as DNA methylation. Studies of the methylation state of DNA preserved in oak heartwood thus could identify epigenetic tree ring features informing on past environmental conditions. In this study, we aimed to establish protocols for the extraction of DNA, the high-throughput sequencing of whole-genome DNA libraries (WGS) and the profiling of DNA methylation by whole-genome bisulfite sequencing (WGBS) for oak (Quercus robur) heartwood drill cores taken from the trunks of living standing trees spanning the AD 1776-2014 time period. Heartwood contains little DNA, and large amounts of phenolic compounds known to hinder the preparation of high-throughput sequencing libraries. Whole-genome and DNA methylome library preparation and sequencing consistently failed for oak heartwood samples more than 100 and 50 years of age, respectively. DNA fragmentation increased with sample age and was exacerbated by the additional bisulfite treatment step during methylome library preparation. Relative coverage of the non-repetitive portion of the oak genome was sparse. These results suggest that quantitative methylome studies of oak hardwood will likely be limited to relatively recent samples and will require a high sequencing depth to achieve sufficient genome coverage.