Cues to Opening Mechanisms From in Silico Electric Field Excitation of Cx26 Hemichannel and in Vitro Mutagenesis Studies in HeLa Transfectans

Molecular Dynamics Simulation of Permeation Through Connexin Channels

Molecular dynamics (MD) simulations are a collection of computational tools that can be used to trace intermolecular interactions at the sub-nanometer level. They offer possibilities that are often unavailable to experimental methods, making MD an ideal complementary technique for the understanding a plethora of biological processes. Thanks to significant efforts by many groups of developers around the world, setting up and running MD simulations has become progressively simpler. However, simulating ionic permeation through membrane channels still presents significant caveats.MD simulations of connexin (Cx) hemichannels (HCs) are particularly problematic because HCs create wide pores in the plasma membrane, and the lateral sizes of the extracellular and intracellular regions are quite different. In this chapter, we provide a detailed instruction to perform MD simulations aimed at computationally modeling the permeation of inorganic ions and larger molecules through Cx HCs.

RAGE engagement by SARS-CoV-2 enables monocyte infection and underlies COVID-19 severity

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fueled the COVID-19 pandemic with its enduring medical and socioeconomic challenges because of subsequent waves and long-term consequences of great concern. Here, we chart the molecular basis of COVID-19 pathogenesis by analyzing patients' immune responses at single-cell resolution across disease course and severity. This approach confirms cell subpopulation-specific dysregulation in COVID-19 across disease course and severity and identifies a severity-associated activation of the receptor for advanced glycation endproducts (RAGE) pathway in monocytes. In vitro THP1-based experiments indicate that monocytes bind the SARS-CoV-2 S1-receptor binding domain (RBD) via RAGE, pointing to RAGE-Spike interaction enabling monocyte infection. Thus, our results demonstrate that RAGE is a functional receptor of SARS-CoV-2 contributing to COVID-19 severity.

Pragmatic Coarse-Graining of Proteins: Models and Applications

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

The SIRAH force field: A suite for simulations of complex biological systems at the coarse-grained and multiscale levels

The different combinations of molecular dynamics simulations with coarse-grained representations have acquired considerable popularity among the scientific community. Especially in biocomputing, the significant speedup granted by simplified molecular models opened the possibility of increasing the diversity and complexity of macromolecular systems, providing realistic insights on large assemblies for more extended time windows. However, a holistic view of biological ensembles' structural and dynamic features requires a self-consistent force field, namely, a set of equations and parameters that describe the intra and intermolecular interactions among moieties of diverse chemical nature (i.e., nucleic and amino acids, lipids, solvent, ions, etc.). Nevertheless, examples of such force fields are scarce in the literature at the fully atomistic and coarse-grained levels. Moreover, the number of force fields capable of handling simultaneously different scales is restricted to a handful. Among those, the SIRAH force field, developed in our group, furnishes a set of topologies and tools that facilitate the setting up and running of molecular dynamics simulations at the coarse-grained and multiscale levels. SIRAH uses the same classical pairwise Hamiltonian function implemented in the most popular molecular dynamics software. In particular, it runs natively in AMBER and Gromacs engines, and porting it to other simulation packages is straightforward. This review describes the underlying philosophy behind the development of SIRAH over the years and across families of biological molecules, discussing current limitations and future implementations.

In Silico Maturation of a Nanomolar Antibody against the Human CXCR2

The steady increase in computational power in the last 50 years is opening unprecedented opportunities in biology, as computer simulations of biological systems have become more accessible and can reproduce experimental results more accurately. Here, we wanted to test the ability of computer simulations to replace experiments in the limited but practically useful scope of improving the biochemical characteristics of the abN48 antibody, a nanomolar antagonist of the CXC chemokine receptor 2 (CXCR2) that was initially selected from a combinatorial antibody library. Our results showed a good correlation between the computed binding energies of the antibody to the peptide target and the experimental binding affinities. Moreover, we showed that it is possible to design new antibody sequences in silico with a higher affinity to the desired target using a Monte Carlo Metropolis algorithm. The newly designed sequences had an affinity comparable to the best ones obtained using in vitro affinity maturation and could be obtained within a similar timeframe. The methodology proposed here could represent a valid alternative for improving antibodies in cases in which experiments are too expensive or technically tricky and could open an opportunity for designing antibodies for targets that have been elusive so far.

Construction of a Deep Neural Network Energy Function for Protein Physics

The traditional approach of computational biology consists of calculating molecule properties by using approximate classical potentials. Interactions between atoms are described by an energy function derived from physical principles or fitted to experimental data. Their functional form is usually limited to pairwise interactions between atoms and does not consider complex multibody effects. More recently, neural networks have emerged as an alternative way of describing the interactions between biomolecules. In this approach, the energy function does not have an explicit functional form and is learned bottom-up from simulations at the atomistic or quantum level. In this study, we attempt a top-down approach and use deep learning methods to obtain an energy function by exploiting the large amount of experimental data acquired with years in the field of structural biology. The energy function is represented by a probability density model learned from a large repertoire of building blocks representing local clusters of amino acids paired with their sequence signature. We demonstrated the feasibility of this approach by generating a neural network energy function and testing its validity on several applications such as discriminating decoys, assessing qualities of structural models, sampling structural conformations, and designing new protein sequences. We foresee that, in the future, our methodology could exploit the continuously increasing availability of experimental data and simulations and provide a new method for the parametrization of protein energy functions.

Rapid Assessment of Binding Affinity of SARS-COV-2 Spike Protein to the Human Angiotensin-Converting Enzyme 2 Receptor and to Neutralizing Biomolecules Based on Computer Simulations

SARS-CoV-2 infects humans and causes Coronavirus disease 2019 (COVID-19). The S1 domain of the spike glycoprotein of SARS-CoV-2 binds to human angiotensin-converting enzyme 2 (hACE2) via its receptor-binding domain, while the S2 domain facilitates fusion between the virus and the host cell membrane for entry. The spike glycoprotein of circulating SARS-CoV-2 genomes is a mutation hotspot. Some mutations may affect the binding affinity for hACE2, while others may modulate S-glycoprotein expression, or they could result in a virus that can escape from antibodies generated by infection with the original variant or by vaccination. Since a large number of variants are emerging, it is of vital importance to be able to rapidly assess their characteristics: while changes of binding affinity alone do not always cause direct advantages for the virus, they still can provide important insights on where the evolutionary pressure is directed. Here, we propose a simple and cost-effective computational protocol based on Molecular Dynamics simulations to rapidly screen the ability of mutated spike protein to bind to the hACE2 receptor and selected neutralizing biomolecules. Our results show that it is possible to achieve rapid and reliable predictions of binding affinities. A similar approach can be used to perform preliminary screenings of the potential effects of S-RBD mutations, helping to prioritize the more time-consuming and expensive experimental work.

Virus-inspired designs of antimicrobial nanocapsules

Antimicrobial resistance is becoming a serious burden for drug design. The challenges are in finding novel approaches for effectively targeting a number of different bacterial strains, and in delivering these to the site of action. We propose here a novel approach that exploits the assembly of antimicrobial peptidic units in nanocapsules that can penetrate and rupture the bacterial membrane. Additionally, the chemical versatility of the designed units can be tailored to specific targets and to the delivery of genetic material in the cell. The proposed design exploits a β-annulus (sequence ITHVGGVGGSIMAPVAVSRQLVGS) triskelion unit from the Tomato Bushy Stunt Virus, able to self assemble in solution, and functionalised with antimicrobial sequences to form dodecahedral antimicrobial nanocapsules. The stability and the activity of the antimicrobial β-annulus capsule is measured by molecular dynamics simulations in water and in the presence of model membranes.

Simulations on Simple Models of Connexin Hemichannels Indicate That Ca2+ Blocking Is Not a Pure Electrostatic Effect

Connexin hemichannels allow the unspecific but regulated interchange of molecules from ions to second messenger and ATP, between the eukariotic cell and its extracellular space. The transport of ions and water through hemichannels is important for physiological functions and also in the progression of several pathological conditions. Extracellular Ca2+ concentration is one of the regulators that drives the channel to a closed state. However the relation between their functional and structural states is far for being totally understood. In this work, we modelled connexin hemichannels using simple systems based on a fixed array of carbon atoms and assess the Ca2+ regulation using molecular dynamics simulations. The two proposed mechanism described so far for calcium action were studied combined, e.g., an electrostatic effect and a pore stretching. Our results show that the addition of positive charge density inside the channel cannot stop the flow of potassium, chloride nor water. Only a pore stretching at the center of the pore can explain the channel blocking.

Dissecting the role of glutamine in seeding peptide aggregation

Poly glutamine and glutamine-rich peptides play a central role in a plethora of pathological aggregation events. However, biophysical characterization of soluble oligomers -the most toxic species involved in these processes- remains elusive due to their structural heterogeneity and dynamical nature. Here, we exploit the high spatio-temporal resolution of coarse-grained simulations as a computational microscope to characterize the aggregation propensity and morphology of a series of polyglutamine and glutamine-rich peptides. Comparative analysis of ab-initio aggregation pinpointed a double role for glutamines. In the first phase, glutamines mediate seeding by pairing monomeric peptides, which serve as primers for higher-order nucleation. According to the glutamine content, these low molecular-weight oligomers may then proceed to create larger aggregates. Once within the aggregates, buried glutamines continue to play a role in their maturation by optimizing solvent-protected hydrogen bonds networks.

Physical interactions driving the activation/inhibition of calcium/calmodulin dependent protein kinase II

CaMKII is a protein kinase whose function is regulated by the binding of the Calcium/Calmodulin complex (Ca²⁺/CaM). It is a major player in the Long Term Potentiation process where it acts as a molecular switch, oscillating between inhibited and active conformations. The mechanism for the switching is thought to be initiated by Ca²⁺/CaM binding, which allows the trans-phosphorylation of a subunit of CaMKII by a neighboring kinase, leading to the active state of the system. A combination of all-atom and coarse-grained MD simulations with free energy calculations, led us to reveal an interplay of electrostatic forces exerted by Ca²⁺/CaM on CaMKII, which initiate the activation process. The highly electrically charged Ca²⁺/CaM neutralizes basic regions in the linker domain of CaMKII, facilitating its opening and consequent activation. The emerging picture of CaMKII's behavior highlights the preponderance of electrostatic interactions, which are modulated by the presence of Ca²⁺/CaM and the phosphorylation of key sites.

Harnessing the therapeutic potential of antibodies targeting connexin hemichannels

BACKGROUND

Connexin hemichannels have been implicated in pathology-promoting conditions, including inflammation, numerous widespread human diseases, including cancer and diabetes, and several rare diseases linked to pathological point mutations.

METHODS

We analysed the literature focusing on antibodies capable of modulating hemichannel function, highlighting generation methods, applications to basic biomedical research and translational potential.

RESULTS

Anti-hemichannel antibodies generated over the past 3 decades targeted mostly connexin 43, with a focus on cancer treatment. A slow transition from relatively unselective polyclonal antibodies to more selective monoclonal antibodies resulted in few products with interesting characteristics that are under evaluation for clinical trials. Selection of antibodies from combinatorial phage-display libraries, has permitted to engineer a monoclonal antibody that binds to and blocks pathological hemichannels formed by connexin 26, 30 and 32.

CONCLUSIONS

All known antibodies that modulate connexin hemichannels target the two small extracellular loops of the connexin proteins. The extracellular region of different connexins is highly conserved, and few residues of each connexins are exposed. The search for new antibodies may develop an unprecedented potential for therapeutic applications, as it may benefit tremendously from novel whole-cell screening platforms that permit in situ selection of antibodies against membrane proteins in native state. The demonstrated efficacy of mAbs in reaching and modulating hemichannels in vivo, together with their relative specificity for connexins overlapping epitopes, should hopefully stimulate an interest for widening the scope of anti-hemichannel antibodies. There is no shortage of currently incurable diseases for which therapeutic intervention may benefit from anti-hemichannel antibodies capable of modulating hemichannel function selectively and specifically.

Structural determinants underlying permeant discrimination of the Cx43 hemichannel

Connexin (Cx) gap junction channels comprise two hemichannels in neighboring cells, and their permeability is well-described, but permeabilities of the single Cx hemichannel remain largely unresolved. Moreover, determination of isoform-specific Cx hemichannel permeability is challenging because of concurrent expression of other channels with similar permeability profiles and inhibitor sensitivities. The mammalian Cx hemichannels Cx30 and Cx43 are gated by extracellular divalent cations, removal of which promotes fluorescent dye uptake in both channels but atomic ion conductance only through Cx30. To determine the molecular determinants of this difference, here we employed chimeras and mutagenesis of predicted pore-lining residues in Cx43. We expressed the mutated channels in Xenopus laevis oocytes to avoid background activity of alternative channels. Oocytes expressing a Cx43 hemichannel chimera containing the N terminus or the first extracellular loop from Cx30 displayed ethidium uptake and, unlike WT Cx43, ion conduction, an observation further supported by molecular dynamics simulations. Additional C-terminal truncation of the chimeric Cx43 hemichannel elicited an even greater ion conductance with a magnitude closer to that of Cx30. The inhibitory profile for the connexin hemichannels depended on the permeant, with conventional connexin hemichannel inhibitors having a higher potency toward the ion conductance pathway than toward fluorescent dye uptake. Our results demonstrate a permeant-dependent, isoform-specific inhibition of connexin hemichannels. They further reveal that the outer segments of the pore-lining region, including the N terminus and the first extracellular loop, together with the C terminus preclude ion conductance of the open Cx43 hemichannel.

Microarray-based screening system identifies temperature-controlled activity of Connexin 26 that is distorted by mutations

Here, we show that human Connexin 26 (hCx26 or Cx26WT) hemichannel opening rapidly enables the transport of small molecules when triggered by temperature and by compensation of the Ca²⁺ blockade with EDTA. Point mutations within Cx26 were analysed by a novel optical microarray-based Lucifer Yellow uptake assay or by two electrode voltage clamp (TEVC) on frog oocytes to monitor simultaneous activities of channel proteins. Point mutations L90P, F161S, R184P or K188N influenced the temperature-dependent activity drastically. Since several mutations blocked trafficking, the temperature-dependent activity of the recombinant synthesized and purified wild-type Cx26WT and Cx26K188N hemichannel was tested by liposome flux assay (LFA) and on a microarray-based Lucifer Yellow uptake assay under warm conditions (>30 °C). The data from TEVC measurements and dye flux experiments showed that the mutations gave no or only a weak activity at increased temperature (>30 °C). We conclude that the position K188 in the Cx26WT forms a temperature-sensitive salt bridge with E47 whereas the exchange to K188N destabilizes the network loop- gating filter, which was recently identified as a part of the flexible Ca²⁺ binding site. We assume that the temperature sensitivity of Cx26 is required to protect cells from uncontrolled release or uptake activities through Cx26 hemichannels.

Fat SIRAH: Coarse-Grained Phospholipids To Explore Membrane-Protein Dynamics

The capability to handle highly heterogeneous molecular assemblies in a consistent manner is among the greatest challenges faced when deriving simulation parameters. This is particularly the case for coarse-grained (CG) simulations in which chemical functional groups are lumped into effective interaction centers for which transferability between different chemical environments is not guaranteed. Here, we introduce the parametrization of a set of CG phospholipids compatible with the latest version of the SIRAH force field for proteins. The newly introduced lipid species include different acylic chain lengths and partial unsaturation, as well as polar and acidic head groups that show a very good reproduction of structural membrane determinants, such as areas per lipid, thickness, order parameter, etc., and their dependence with temperature. Simulation of membrane proteins showed unprecedented accuracy in the unbiased description of the thickness-dependent membrane-protein orientation in systems where this information is experimentally available (namely, the SarcoEndoplasmic Reticulum Calcium-SERCA-pump and its regulator Phospholamban). The interactions that lead to this faithful reproduction can be traced down to the single amino acid-lipid interaction level and show full agreement with biochemical data present in the literature. Finally, the present parametrization is implemented in the GROMACS and AMBER simulation packages facilitating its use by a wide portion of the biocomputing community.

Magnesium interactions with a CX26 connexon in lipid bilayers

Following our previous work, where we described the interaction of calcium with the Cx26 hemichannel, we further explore the same system by atomistic molecular dynamics simulations considering a different di-cation, magnesium. Specifically, the interaction of magnesium di-cation with the previously reported calcium binding sites (ASP2, ASP117, ASP159, GLU114, GLU119, GLU120, and VAL226) was investigated to identify similarities and differences between them. In order to do so, four extensive simulations were carried out. Two of them considered a Cx26 hemichannel embedded on a POPC bilayer with one of the di-cations and a sodium-chlorine solution. For the remaining two, no di-cations were included and a sodium-chlorine or potassium-chlorine solution was considered. Potassium has a similar atomic mass to calcium, and sodium to magnesium, but they both differ in charge (1e and 2e respectively). Magnesium and calcium, even having the same charge, showed different affinity for the explored protein. From the calcium binding sites referred above, we found that the magnesium di-cations only binds strongly to the GLU114 site of one connexin. For the sodium and potassium simulations, no specific interactions with the protein were found. Altogether, these results suggest that mass and steric effects play an important role in determining cation binding to Cx26 hemichannels.

Tubulin response to intense nanosecond-scale electric field in molecular dynamics simulation

Intense pulsed electric fields are known to act at the cell membrane level and are already being exploited in biomedical and biotechnological applications. However, it is not clear if electric pulses within biomedically-attainable parameters could directly influence intra-cellular components such as cytoskeletal proteins. If so, a molecular mechanism of action could be uncovered for therapeutic applications of such electric fields. To help clarify this question, we first identified that a tubulin heterodimer is a natural biological target for intense electric fields due to its exceptional electric properties and crucial roles played in cell division. Using molecular dynamics simulations, we then demonstrated that an intense - yet experimentally attainable - electric field of nanosecond duration can affect the bβ-tubulin’s C-terminus conformations and also influence local electrostatic properties at the GTPase as well as the binding sites of major tubulin drugs site. Our results suggest that intense nanosecond electric pulses could be used for physical modulation of microtubule dynamics. Since a nanosecond pulsed electric field can penetrate the tissues and cellular membranes due to its broadband spectrum, our results are also potentially significant for the development of new therapeutic protocols.

From quantum to subcellular scales: multi-scale simulation approaches and the SIRAH force field

Modern molecular and cellular biology profits from astonishing resolution structural methods, currently even reaching the whole cell level. This is encompassed by the development of computational methods providing a deep view into the structure and dynamics of molecular processes happening at very different scales in time and space. Linking such scales is of paramount importance when aiming at far-reaching biological questions. Computational methods at the interface between classical and coarse-grained resolutions are gaining momentum with several research groups dedicating important efforts to their development and tuning. An overview of such methods is addressed herein, with special emphasis on the SIRAH force field for coarse-grained and multi-scale simulations. Moreover, we provide proof of concept calculations on the implementation of a multi-scale simulation scheme including quantum calculations on a classical fine-grained/coarse-grained representation of double-stranded DNA. This opens the possibility to include the effect of large conformational fluctuations in chromatin segments on, for instance, the reactivity of particular base pairs within the same simulation framework.

The SIRAH 2.0 Force Field: Altius, Fortius, Citius

A new version of the coarse-grained (CG) SIRAH force field for proteins has been developed. Modifications to bonded and non-bonded interactions on the existing molecular topologies significantly ameliorate the structural description and flexibility of a non-redundant set of proteins. The SIRAH 2.0 force field has also been ported to the popular simulation package AMBER, which along with the former implementation in GROMACS expands significantly the potential range of users and performance of this CG force field on CPU/GPU codes. As a non-trivial example of its application, we undertook the structural and dynamical analysis of the most abundant and conserved calcium-binding protein, calmodulin (CaM). CaM is composed of two calcium-binding motifs called EF-hands, which in the presence of calcium specifically recognize a cognate peptide by embracing it. CG simulations of CaM bound to four calcium ions in the presence or absence of a binding peptide (holo and apo forms, respectively) resulted in good and stable ion coordination. The simulation of the holo form starting from an experimental structure sampled near-native conformations, retrieving quasi-atomistic precision. Removing the binding peptide enabled the EF-hands to perform large reciprocal movements, comparable to those observed in NMR structures. On the other hand, the isolated peptide starting from the helical conformation experienced spontaneous unfolding, in agreement with previous experimental data. However, repositioning the peptide in the neighborhood of one EF-hand not only prevented the peptide from unfolding but also drove CaM to a fully bound conformation, with both EF-hands embracing the cognate peptide, resembling the experimental holo structure. Therefore, SIRAH 2.0 shows the capacity to handle a number of structurally and dynamically challenging situations, including metal ion coordination, unbiased conformational sampling, and specific protein-peptide recognition.