Inferring the stabilization effects of SARS-CoV-2 variants on the binding with ACE2 receptor

As the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic continues to spread, several variants of the virus, with mutations distributed all over the viral genome, are emerging. While most of the variants present mutations having little to no effects at the phenotypic level, some of these variants are spreading at a rate that suggests they may present a selective advantage. In particular, these rapidly spreading variants present specific mutations on the spike protein. These observations call for an urgent need to characterize the effects of these variants’ mutations on phenotype features like contagiousness and antigenicity. With this aim, we performed molecular dynamics simulations on a selected set of possible spike variants in order to assess the stabilizing effect of particular amino acid substitutions on the molecular complex. We specifically focused on the mutations that are both characteristic of the top three most worrying variants at the moment, i.e the English, South African, and Amazonian ones, and that occur at the molecular interface between SARS-CoV-2 spike protein and its human ACE2 receptor. We characterize these variants’ effect in terms of (i) residue mobility, (ii) compactness, studying the network of interactions at the interface, and (iii) variation of shape complementarity via expanding the molecular surfaces in the Zernike basis. Overall, our analyses highlighted greater stability of the three variant complexes with respect to both the wild type and two negative control systems, especially for the English and Amazonian variants. In addition, in the three variants, we investigate the effects a not-yet observed mutation in position 501 could provoke on complex stability. We found that a phenylalanine mutation behaves similarly to the English variant and may cooperate in further increasing the stability of the South African one, hinting at the need for careful surveillance for the emergence of these mutations in the population. Ultimately, we show that the proposed observables describe key features for the stability of the ACE2-spike complex and can help to monitor further possible spike variants.

Binding site identification of G protein-coupled receptors through a 3D Zernike polynomials-based method: application to C. elegans olfactory receptors

Studying the binding processes of G protein-coupled receptors (GPCRs) proteins is of particular interest both to better understand the molecular mechanisms that regulate the signaling between the extracellular and intracellular environment and for drug design purposes. In this study, we propose a new computational approach for the identification of the binding site for a specific ligand on a GPCR. The method is based on the Zernike polynomials and performs the ligand-GPCR association through a shape complementarity analysis of the local molecular surfaces. The method is parameter-free and it can distinguish, working on hundreds of experimentally GPCR-ligand complexes, binding pockets from randomly sampled regions on the receptor surface, obtaining an Area Under ROC curve of 0.77. Given its importance both as a model organism and in terms of applications, we thus investigated the olfactory receptors of the C. elegans, building a list of associations between 21 GPCRs belonging to its olfactory neurons and a set of possible ligands. Thus, we can not only carry out rapid and efficient screenings of drugs proposed for GPCRs, key targets in many pathologies, but also we laid the groundwork for computational mutagenesis processes, aimed at increasing or decreasing the binding affinity between ligands and receptors.

A Computational Approach to Investigate TDP-43 RNA-Recognition Motif 2 C-Terminal Fragments Aggregation in Amyotrophic Lateral Sclerosis

Many of the molecular mechanisms underlying the pathological aggregation of proteins observed in neurodegenerative diseases are still not fully understood. Among the aggregate-associated diseases, Amyotrophic Lateral Sclerosis (ALS) is of relevant importance. In fact, although understanding the processes that cause the disease is still an open challenge, its relationship with protein aggregation is widely known. In particular, human TDP-43, an RNA/DNA binding protein, is a major component of the pathological cytoplasmic inclusions observed in ALS patients. Indeed, the deposition of the phosphorylated full-length TDP-43 in spinal cord cells has been widely studied. Moreover, it has also been shown that the brain cortex presents an accumulation of phosphorylated C-terminal fragments (CTFs). Even if it is debated whether the aggregation of CTFs represents a primary cause of ALS, it is a hallmark of TDP-43 related neurodegeneration in the brain. Here, we investigate the CTFs aggregation process, providing a computational model of interaction based on the evaluation of shape complementarity at the molecular interfaces. To this end, extensive Molecular Dynamics (MD) simulations were conducted for different types of protein fragments, with the aim of exploring the equilibrium conformations. Adopting a newly developed approach based on Zernike polynomials, able to find complementary regions in the molecular surface, we sampled a large set of solvent-exposed portions of CTFs structures as obtained from MD simulations. Our analysis proposes and assesses a set of possible association mechanisms between the CTFs, which could drive the aggregation process of the CTFs. To further evaluate the structural details of such associations, we perform molecular docking and additional MD simulations to propose possible complexes and assess their stability, focusing on complexes whose interacting regions are both characterized by a high shape complementarity and involve β3 and β5 strands at their interfaces.

Design of catalytic metal-organic assemblies via shape complementarity and conformational constraints in dual curvature ligands

Non-covalent interactions play an essential role in the folding and self-assembly of large biological assemblies. These interactions are not only a driving force for the formation of large structures but also control conformation and com-plementary shapes of subcomponents that promote the diversity of structures and functions of the resulting assemblies. Understanding how non-covalent interactions direct self-assembly and the effect of conformation and complementary shapes on self-assembled structures will help design artificial supramolecular systems with extended components and functions. Herein, we develop a strategy for controlling more complex self-assembly with lower symmetry and flexible building blocks that combine endohedral non-covalent interactions with a dual curvature in the ligand backbone to give additional shape complementarity. A Diels-Alder reaction was used to break the symmetry of the diazaanthracene units of the ligands to give dual curvature ligands with different shapes and endohedral groups (L1-L3). The self-assembly studies of these ligands demonstrated that non-covalent interactions and shape complementary effectively control the self-assembly and enable the design of cages for supramolecular catalysis.

Capturing Surface Complementarity in Proteins using Unsupervised Learning and Robust Curvature Measure

The structure of a protein plays a pivotal role in determining its function. Often, the protein surface’s shape and curvature dictate its nature of interaction with other proteins and biomolecules. However, marked by corrugations and roughness, a protein’s surface representation poses significant challenges for its curvature-based characterization. In the present study, we employ unsupervised machine learning to segment the protein surface into patches. To measure the surface curvature of a patch, we present an algebraic sphere fitting method that is fast, accurate, and robust. Moreover, we use local curvatures to show the existence of “shape complementarity” in protein-protein, antigen-antibody, and protein-ligand interfaces. We believe that the current approach could help understand the relationship between protein structure and its biological function and can be used to find binding partners of a given protein.

Programmable Self-Assembly of Gold Nanoarrows via Regioselective Adsorption

Programing the self-assembly of colloidal nanoparticles into predetermined superstructures represents an attractive strategy to realize functional assemblies and novel nanodevices, but it remains a challenge. Herein, gold nanoarrows (GNAs) showing a distinct convex-concave structure were employed as unique building blocks for programmable self-assembly involving multiple assembly modes. Regioselective adsorption of 1,10-decanedithiol on the vertexes, edges, and facets of GNAs allowed for programmable self-assembly of GNAs with five distinct assembly modes, and regioselective blocking with 1-dodecanethiol followed by adsorption of 1,10-decanedithiol gave rise to programmable self-assembly with six assembly modes including three novel wing-engaged modes. The assembly mode was essentially determined by regioselective adsorption of the dithiol linker dictated by the local curvature together with the shape complementarity of GNAs. This approach reveals how the geometric morphology of nanoparticles affects their regioselective functionalization and drives their self-assembly.

A conserved epitope III on hepatitis C virus E2 protein has alternate conformations facilitating cell binding or virus neutralization

Epitope III, a highly conserved amino acid motif of 524APTYSW529 on the hepatitis C virus (HCV) E2 glycoprotein, resides in the critical loop that binds to the host receptor CD81, thus making it one of the most important antibody targets for blocking HCV infections. Here, we have determined the X-ray crystal structure of epitope III at a 2.0-Å resolution when it was captured by a site-specific neutralizing antibody, monoclonal antibody 1H8 (mAb1H8). The snapshot of this complex revealed that epitope III has a relatively rigid structure when confined in the binding grooves of mAb1H8, which confers the residue specificity at both ends of the epitope. Such a high shape complementarity is reminiscent of the “lock and key” mode of action, which is reinforced by the incompatibility of an antibody binding with an epitope bearing specific mutations. By subtly positioning the side chains on the three residues of Tyr527, Ser528, and Trp529 while preserving the spatial rigidity of the rest, epitope III in this cocrystal complex adopts a unique conformation that is different from previously described E2 structures. With further analyses of molecular docking and phage display–based peptide interactions, we recognized that it is the arrangements of two separate sets of residues within epitope III that create these discrete conformations for the epitope to interact selectively with either mAb1H8 or CD81. These observations thus raise the possibility that local epitope III conformational dynamics, in conjunction with sequence variations, may act as a regulatory mechanism to coordinate “mAb1H8-like” antibody-mediated immune defenses with CD81-initiated HCV infections.

In-Silico Evidence for a Two Receptor Based Strategy of SARS-CoV-2

We propose a computational investigation on the interaction mechanisms between SARS-CoV-2 spike protein and possible human cell receptors. In particular, we make use of our newly developed numerical method able to determine efficiently and effectively the relationship of complementarity between portions of protein surfaces. This innovative and general procedure, based on the representation of the molecular isoelectronic density surface in terms of 2D Zernike polynomials, allows the rapid and quantitative assessment of the geometrical shape complementarity between interacting proteins, which was unfeasible with previous methods. Our results indicate that SARS-CoV-2 uses a dual strategy: in addition to the known interaction with angiotensin-converting enzyme 2, the viral spike protein can also interact with sialic-acid receptors of the cells in the upper airways.