Noncovalent antibody catenation on a target surface greatly increases the antigen-binding avidity.

Immunoglobulin G (IgG) antibodies are widely used for diagnosis and therapy. Given the unique dimeric structure of IgG, we hypothesized that, by genetically fusing a homodimeric protein (catenator) to the C-terminus of IgG, reversible catenation of antibody molecules could be induced on a surface where target antigen molecules are abundant, and that it could be an effective way to greatly enhance the antigen-binding avidity. A thermodynamic simulation showed that quite low homodimerization affinity of a catenator, e.g. dissociation constant of 100 µM, can enhance nanomolar antigen-binding avidity to a picomolar level, and that the fold enhancement sharply depends on the density of the antigen. In a proof-of-concept experiment where antigen molecules are immobilized on a biosensor tip, the C-terminal fusion of a pair of weakly homodimerizing proteins to three different antibodies enhanced the antigen-binding avidity by at least 110 or 304 folds from the intrinsic binding avidity. Compared with the mother antibody, Obinutuzumab(Y101L) which targets CD20, the same antibody with fused catenators exhibited significantly enhanced binding to SU-DHL5 cells. Together, the homodimerization-induced antibody catenation would be a new powerful approach to improve antibody applications, including the detection of scarce biomarkers and targeted anticancer therapies.

Pulmonary surfactant and COVID-19: A new synthesis

Chapter 1: COVID-19 pathogenesis poses paradoxes difficult to explain with traditional physiology. For instance, since type II pneumocytes are considered the primary cellular target of SARS-CoV-2;as these produce pulmonary surfactant (PS), the possibility that insufficient PS plays a role in COVID-19 pathogenesis has been raised. However, the opposite of predicted high alveolar surface tension is found in many early COVID-19 patients: paradoxically normal lung volumes and high compliance occur, with profound hypoxemia. That 'COVID anomaly' was quickly rationalised by invoking traditional vascular mechanisms-mainly because of surprisingly preserved alveolar surface in early hypoxemic cases. However, that quick rejection of alveolar damage only occurred because the actual mechanism of gas exchange has long been presumed to be non-problematic, due to diffusion through the alveolar surface. On the contrary, we provide physical chemical evidence that gas exchange occurs by an process of expansion and contraction of the three-dimensional structures of PS and its associated proteins. This view explains anomalous observations from the level of cryo-TEM to whole individuals. It encompasses results from premature infants to the deepest diving seals. Once understood, the COVID anomaly dissolves and is straightforwardly explained as covert viral damage to the 3D structure of PS, with direct treatment implications. As a natural experiment, the SARS-CoV-2 virus itself has helped us to simplify and clarify not only the nature of dyspnea and its relationship to pulmonary compliance, but also the fine detail of the PS including such features as water channels which had heretofore been entirely unexpected.Copyright ©

Multiscale Hybrid Modeling of Proteins in Solvent: SARS-CoV2 Spike Protein as Test Case for Lattice Boltzmann – All Atom Molecular Dynamics Coupling

Physiological solvent flows surround biological structures triggering therein collective motions. Notable examples are virus/host-cell interactions and solvent-mediated allosteric regulation. The present work describes a multiscale approach joining the Lattice Boltzmann fluid dynamics (for solvent flows) with the all-atom atomistic molecular dynamics (for proteins) to model functional interactions between flows and molecules. We present, as an applicative scenario, the study of the SARS-CoV-2 virus spike glycoprotein protein interacting with the surrounding solvent, modeled as a mesoscopic fluid. The equilibrium properties of the wild-type spike and of the Alpha variant in implicit solvent are described by suitable observables. The mesoscopic solvent description is critically compared to the all-atom solvent model, to quantify the advantages and limitations of the mesoscopic fluid description. ©2023 Global-Science Press.

Biomolecular Simulations in the Time of COVID19, and After.

COVID19 has changed life for people worldwide. Despite lockdowns globally, computational research has pressed on, working remotely and collaborating virtually on research questions in COVID19 and the virus it is caused by, SARS-CoV-2. Molecular simulations can help to characterize the function of viral and host proteins and have the potential to contribute to the search for vaccines and treatments. Changes in the modus operandi of research groups include broader adoption of the use of preprint servers, earlier and more open sharing of methods, models, and data, the use of social media to rapidly disseminate information, online seminars, and cloud-based virtual collaboration. Research funders and computing providers worldwide recognized the need to provide rapid and significant access to computational architectures. In this review, we discuss how the interplay of all of these factors is influencing the impact - both potential and realized - of biomolecular simulations in the fight against SARS-CoV-2.

Targeting RNA:protein interactions with an integrative approach leads to the identification of potent YBX1 inhibitors.

RNA-protein interactions (RPIs) are promising targets for developing new molecules of therapeutic interest. Nevertheless, challenges arise from the lack of methods and feedback between computational and experimental techniques during the drug discovery process. Here, we tackle these challenges by developing a drug screening approach that integrates chemical, structural and cellular data from both advanced computational techniques and a method to score RPIs in cells for the development of small RPI inhibitors; and we demonstrate its robustness by targeting Y-box binding protein 1 (YB-1), a messenger RNA-binding protein involved in cancer progression and resistance to chemotherapy. This approach led to the identification of 22 hits validated by molecular dynamics (MD) simulations and nuclear magnetic resonance (NMR) spectroscopy of which 11 were found to significantly interfere with the binding of messenger RNA (mRNA) to YB-1 in cells. One of our leads is an FDA-approved poly(ADP-ribose) polymerase 1 (PARP-1) inhibitor. This work shows the potential of our integrative approach and paves the way for the rational development of RPI inhibitors.

Biophysical characterization of the structure of a SARS-CoV-2 self-amplifying RNA (saRNA) vaccine.

The current SARS-Covid-2 (SARS-CoV-2) pandemic has led to an acceleration of messenger ribonucleic acid (mRNA) vaccine technology. The development of production processes for these large mRNA molecules, especially self-amplifying mRNA (saRNA), has required concomitant development of analytical characterization techniques. Characterizing the purity, shape and structure of these biomolecules is key to their successful performance as drug products. This article describes the biophysical characterization of the Imperial College London Self-amplifying viral RNA vaccine (IMP-1) developed for SARS-CoV-2. A variety of analytical techniques have been used to characterize the IMP-1 RNA molecule. In this article, we use ultraviolet spectroscopy, dynamic light scattering, size-exclusion chromatography small-angle X-ray scattering and circular dichroism to determine key biophysical attributes of IMP-1. Each technique provides important information about the concentration, size, shape, structure and purity of the molecule.

Timeline of changes in spike conformational dynamics in emergent SARS-CoV-2 variants reveal progressive stabilization of trimer stalk with altered NTD dynamics.

SARS-CoV-2 emergent variants are characterized by increased viral fitness and each shows multiple mutations predominantly localized to the spike (S) protein. Here, amide hydrogen/deuterium exchange mass spectrometry has been applied to track changes in S dynamics from multiple SARS-CoV-2 variants. Our results highlight large differences across variants at two loci with impacts on S dynamics and stability. A significant enhancement in stabilization first occurred with the emergence of D614G S followed by smaller, progressive stabilization in subsequent variants. Stabilization preceded altered dynamics in the N-terminal domain, wherein Omicron BA.1 S showed the largest magnitude increases relative to other preceding variants. Changes in stabilization and dynamics resulting from S mutations detail the evolutionary trajectory of S in emerging variants. These carry major implications for SARS-CoV-2 viral fitness and offer new insights into variant-specific therapeutic development.

The SARS-CoV-2 accessory protein Orf3a is not an ion channel, but does interact with trafficking proteins.

The severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) and SARS-CoV-1 accessory protein Orf3a colocalizes with markers of the plasma membrane, endocytic pathway, and Golgi apparatus. Some reports have led to annotation of both Orf3a proteins as viroporins. Here, we show that neither SARS-CoV-2 nor SARS-CoV-1 Orf3a form functional ion conducting pores and that the conductances measured are common contaminants in overexpression and with high levels of protein in reconstitution studies. Cryo-EM structures of both SARS-CoV-2 and SARS-CoV-1 Orf3a display a narrow constriction and the presence of a positively charged aqueous vestibule, which would not favor cation permeation. We observe enrichment of the late endosomal marker Rab7 upon SARS-CoV-2 Orf3a overexpression, and co-immunoprecipitation with VPS39. Interestingly, SARS-CoV-1 Orf3a does not cause the same cellular phenotype as SARS-CoV-2 Orf3a and does not interact with VPS39. To explain this difference, we find that a divergent, unstructured loop of SARS-CoV-2 Orf3a facilitates its binding with VPS39, a HOPS complex tethering protein involved in late endosome and autophagosome fusion with lysosomes. We suggest that the added loop enhances SARS-CoV-2 Orf3a's ability to co-opt host cellular trafficking mechanisms for viral exit or host immune evasion.

Revealing druggable cryptic pockets in the Nsp1 of SARS-CoV-2 and other ß-coronaviruses by simulations and crystallography.

Non-structural protein 1 (Nsp1) is a main pathogenicity factor of α- and ß-coronaviruses. Nsp1 of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suppresses the host gene expression by sterically blocking 40S host ribosomal subunits and promoting host mRNA degradation. This mechanism leads to the downregulation of the translation-mediated innate immune response in host cells, ultimately mediating the observed immune evasion capabilities of SARS-CoV-2. Here, by combining extensive molecular dynamics simulations, fragment screening and crystallography, we reveal druggable pockets in Nsp1. Structural and computational solvent mapping analyses indicate the partial crypticity of these newly discovered and druggable binding sites. The results of fragment-based screening via X-ray crystallography confirm the druggability of the major pocket of Nsp1. Finally, we show how the targeting of this pocket could disrupt the Nsp1-mRNA complex and open a novel avenue to design new inhibitors for other Nsp1s present in homologous ß-coronaviruses.

Artificial intelligence methods to repurpose and discover new drugs to fight the Coronavirus disease-2019 pandemic

The Coronavirus disease 2019 pandemic struck the world at the end of 2019 and, as of 2021, there are no specific drugs available against the causative agent, the severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2). From the onset of the pandemic, researchers have been trying to find drugs among the current therapeutic arsenal that could target crucial viral function, and many of these efforts resulted in clinical trials to repurpose a drug for this new indication. In this scenario, artificial intelligence (AI) is of fundamental importance, allowing academia and pharmaceutical companies to accelerate the discovery of biochemical insights from the chemical and biological information available in literature databases. This chapter will cover some AI methods that are being explored to repurpose drugs against SARS-CoV-2. It will be outlined how these methods work followed by a discussion of selected examples applying them to identify promising drugs. © 2022 Elsevier Inc. All rights reserved.

Use of Audiovisual Strategies as a Complementary Resource for Practical Courses in Biomedical Engineering

In recent years, the education has been influenced by the implementation of new learning strategies due to the confinement caused by the spread of COVID-19. Teachers adopted audiovisual resources that allow them to teach their classes remotely. However, the transition to this modality has been sudden, forced, and evolving “on the fly" in response to the pedagogical adaptations. A structured implementation of audiovisual media in education is required, since it represents an important part of access to information in our times. For this goal, we propose strategies for the development of complementary offline and online audiovisual content to help teach practical courses in a Biomedical Engineering bachelor program. In particular, we present content created for a Medical Imaging Systems course. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Protocol for high-throughput screening of SARS-CoV-2 main protease inhibitors using a robust fluorescence polarization assay.

Discovery of efficacious antiviral agents targeting SARS-CoV-2 main protease (Mpro) is of the highest importance to fight against COVID-19. Here, we describe a simple protocol for high-throughput screening of Mpro inhibitors using a robust fluorescence polarization (FP) assay. Candidate Mpro inhibitors from large compound libraries could be rapidly identified by monitoring the change of millipolarization unit value. This affordable FP assay can be modified to screen antiviral agents targeting virus protease. For complete details on the use and execution of this protocol, please refer to Li et al. (2022), Yan et al. (2021), and Yan et al. (2022c).

Supported Natural Membranes on Microspheres for Protein-Protein Interaction Studies.

Multiple biological and pathological processes, such as signaling, cell-cell communication, and infection by various viruses, occur at the plasma membrane. The eukaryotic plasma membrane is made up of thousands of different lipids, membrane proteins, and glycolipids, and its composition is dynamic and constantly changing. Due to the central importance of membranes on the one hand and their complexity on the other, membrane model systems are instrumental for interrogating membrane-related biological processes. Here, we develop a new tool for protein-membrane interaction studies. Our method is based on natural membranes obtained from extracellular vesicles. We form membrane bilayers supported on polystyrene microspheres that can be trapped and manipulated using optical tweezers. This method allows working with membrane proteins of interest within a background of native membrane components where their correct orientation is preserved. We demonstrate our method's applicability by successfully measuring the interaction forces between the Spike protein of SARS-CoV-2 and its human receptor, ACE2. We further show that these interactions are blocked by the addition of an antibody against the receptor binding domain of the Spike protein. Our approach is versatile and broadly applicable for various membrane biology and biophysics questions.

Structure of SARS-CoV-2 M protein in lipid nanodiscs.

SARS-CoV-2 encodes four structural proteins incorporated into virions, spike (S), envelope (E), nucleocapsid (N), and membrane (M). M plays an essential role in viral assembly by organizing other structural proteins through physical interactions and directing them to sites of viral budding. As the most abundant protein in the viral envelope and a target of patient antibodies, M is a compelling target for vaccines and therapeutics. Still, the structure of M and molecular basis for its role in virion formation are unknown. Here, we present the cryo-EM structure of SARS-CoV-2 M in lipid nanodiscs to 3.5 Å resolution. M forms a 50 kDa homodimer that is structurally related to the SARS-CoV-2 ORF3a viroporin, suggesting a shared ancestral origin. Structural comparisons reveal how intersubunit gaps create a small, enclosed pocket in M and large open cavity in ORF3a, consistent with a structural role and ion channel activity, respectively. M displays a strikingly electropositive cytosolic surface that may be important for interactions with N, S, and viral RNA. Molecular dynamics simulations show a high degree of structural rigidity in a simple lipid bilayer and support a role for M homodimers in scaffolding viral assembly. Together, these results provide insight into roles for M in coronavirus assembly and structure.

Work in Progress: Remote Laboratory Delivery with an At-Home Biomechanical Kinematic Data Acquisition Method

Under the remote learning mode due to COVID-19, educational laboratory modules lacking the active data acquisition step tend to lose students' engagement and diminish their eagerness to explore further knowledge. Such shortcomings are more profound in practical fields of study, such as Biomechanics. The goal of this paper is to present a remote laboratory delivery and evaluation method where students can apply principles of kinematic and kinetic biomechanical analysis on their own body motions with a computer vision algorithm to interactively solve a motion analysis problem. In this preliminary study, students were given the freedom to choose a specific body motion to be captured and analyzed, such as elbow, knee, wrist, and neck joint movements. Motion specifications included determination of the motion type, and also the starting and ending angular or linear positions. Readily available labels were utilized as passive joint markers. Students were then instructed to video record their joint motions using their laptop cameras. A custom video tracking algorithm specifically designed to track spatial locations was then employed to capture relative positions of the recorded motions. Laboratory instructions asked the students to perform kinematic calculations on the algorithm's generated positional data to determine joint velocities and accelerations, and then perform kinetic analyses to estimate the associated muscle forces. Laboratory requirements were concluded with a reflection prompt to evaluate the activity's workload and effort perceived by the students. These activities were delivered twice in two different academic terms. Samples of the produced kinematic data using our methods were verified in comparison with a standard physical motion capture system, where similar joint motion descriptive results were observed. Results show that the completion rate of laboratory requirements was 97% in the first term of delivery, and 100% in the second term, as supported by the full technical reports submissions that included critical data analysis and reflections of the laboratory experience. Student reflections were very positive and expressed how the lab activity was interesting as it kept a high level of engagement and provided a way to make connections between practice and theory. In conclusion, the proposed approach may improve the students' laboratory experience in learning biomechanics through a motion analysis scenario, and allow them to remotely be fully engaged, active, and passionate learners. © American Society for Engineering Education, 2022.

Electrostatics in Computational Biophysics and Its Implications for Disease Effects.

This review outlines the role of electrostatics in computational molecular biophysics and its implication in altering wild-type characteristics of biological macromolecules, and thus the contribution of electrostatics to disease mechanisms. The work is not intended to review existing computational approaches or to propose further developments. Instead, it summarizes the outcomes of relevant studies and provides a generalized classification of major mechanisms that involve electrostatic effects in both wild-type and mutant biological macromolecules. It emphasizes the complex role of electrostatics in molecular biophysics, such that the long range of electrostatic interactions causes them to dominate all other forces at distances larger than several Angstroms, while at the same time, the alteration of short-range wild-type electrostatic pairwise interactions can have pronounced effects as well. Because of this dual nature of electrostatic interactions, being dominant at long-range and being very specific at short-range, their implications for wild-type structure and function are quite pronounced. Therefore, any disruption of the complex electrostatic network of interactions may abolish wild-type functionality and could be the dominant factor contributing to pathogenicity. However, we also outline that due to the plasticity of biological macromolecules, the effect of amino acid mutation may be reduced, and thus a charge deletion or insertion may not necessarily be deleterious.

Pandemic evolution in basic control courses for undergraduate engineering students

Presenting automatic control concepts to biomedical engineers is a challenging task due to the lack of background and/or motivation of many students. In this paper, a learning-by-doing experience is shown, where the COVID-19 pandemic evolution is used as a teaching project along the course. By applying this methodology, students report a better understanding of the background concepts and their possible use in applications that they feel close to their interests © 2022 IEEE.

SARS-CoV-2 Delta Variant is Recognized Through GRP78 Host-Cell Surface Receptor, In Silico Perspective.

Different SARS-CoV-2 new variants emerged and spread during the past few months, sparking infections and death counts. The new variant B.1.617 (delta variant) sparked in India in the past few months, causing the highest records. The B.1.617 variant of SARS-CoV-2 has the double mutations E484Q and L452R on its spike Receptor Binding Domain (RBD). The first mutation is like the reported South African and the Brazilian variants (501.V2 and B.1.1.248). This mutation lies in the region C480-C488, which we predicted before to be recognized by the host-cell receptor; Glucose Regulated Protein 78 (GRP78). In the current study, we test the binding affinity of the host-cell receptor GRP78 to the delta variant spike RBD using molecular docking and molecular dynamics simulations of up to 100 ns. Additionally, the ACE2-RBD is tested by protein-protein docking. The results reveal equal average binding affinities of the GRP78 against wildtype and delta variant spikes. This supports our previous predictions of the contribution of GRP78 in SARS-CoV-2 spike recognition as an auxiliary route for entry.