Mechanistic Elucidation of Protease–Substrate and Protein–Protein Interactions for Targeting Viral Infections

Viral infections represent an old threat to global health, with multiple epidemics and pandemics in the history of mankind. Despite several advances in the development of antiviral substances and vaccines, many viral species are still not targeted. Additionally, new viral species emerge, posing a menace without precedent to humans and animals and causing fatalities, disabilities, environmental harm, and economic losses. In this thesis, we present rational modeling approaches for targeting specific protease-substrate and protein-protein interactions pivotal for the viral replication cycle. Over the course of this work, antiviral research is supported beginning with the development of small molecular antiviral substances, going through the modeling of a potential immunogenic epitope for vaccine development, towards the establishment of descriptors for susceptibility of animals to a viral infection. Notably, all the research was done under scarce data availability, highlighting the predictive power of computational methods and complementarity between in-silico and in-vitro or in-vivo methods

Modeling SARS-CoV-2 spike/ACE2 protein–protein interactions for predicting the binding affinity of new spike variants for ACE2, and novel ACE2 structurally related human protein targets, for COVID-19 handling in the 3PM context

Aims The rapid spread of new SARS-CoV-2 variants has highlighted the crucial role played in the infection by mutations occurring at the SARS-CoV-2 spike receptor binding domain (RBD) in the interactions with the human ACE2 receptor. In this context, it urgently needs to develop new rapid tools for quickly predicting the affinity of ACE2 for the SARS-CoV-2 spike RBD protein variants to be used with the ongoing SARS-CoV-2 genomic sequencing activities in the clinics, aiming to gain clues about the transmissibility and virulence of new variants, to prevent new outbreaks and to quickly estimate the severity of the disease in the context of the 3PM. Methods In our study, we used a computational pipeline for calculating the interaction energies at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface for a selected group of characterized infectious variants of concern/interest (VoC/ VoI). By using our pipeline, we built 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for the VoC B.1.1.7-United Kingdom (carrying the mutations of concern/interest N501Y, S494P, E484K at the RBD), P.1- Japan/Brazil (RBD mutations: K417T, E484K, N501Y), B.1.351-South Africa (RBD mutations: K417N, E484K, N501Y), B.1.427/B.1.429-California (RBD mutations: L452R), the B.1.141 (RBD mutations: N439K), and the recent B.1.617.1- India (RBD mutations: L452R; E484Q) and the B.1.620 (RBD mutations: S477N; E484K). Then, we used the obtained 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for predicting the interaction energies at the protein–protein interface. Results Along SARS-CoV-2 mutation database screening and mutation localization analysis, it was ascertained that the most dangerous mutations at VoC/VoI spike proteins are located mainly at three regions of the SARS-CoV-2 spike “boat-shaped” receptor binding motif, on the RBD domain. Notably, the P.1 Japan/Brazil variant present three mutations, K417T, E484K, N501Y, located along the entire receptor binding motif, which apparently determines the highest interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface, among those calculated. Conversely, it was also observed that the replacement of a single acidic/hydrophilic residue with a basic residue (E484K or N439K) at the “stern” or “bow” regions, of the boat-shaped receptor binding motif on the RBD, appears to determine an interaction energy with ACE2 receptor higher than that observed with single mutations occurring at the “hull” region or with other multiple mutants. In addition, our pipeline allowed searching for ACE2 structurally related proteins, i.e., THOP1 and NLN, which deserve to be investigated for their possible involvement in interactions with the SARS-CoV-2 spike protein, in those tissues showing a low expression of ACE2, or as a novel receptor for future spike variants. A freely available web-tool for the in silico calculation of the interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface, starting from the sequences of the investigated spike and/or ACE2 variants, was made available for the scientific community at: https:// www. mitoa irm. it/ covid 19aff​initi es. Conclusion In the context of the PPPM/3PM, the employment of the described pipeline through the provided webservice, together with the ongoing SARS-CoV-2 genomic sequencing, would help to predict the transmissibility of new variants sequenced from future patients, depending on SARS-CoV-2 genomic sequencing activities and on the specific amino acid replacement and/or on its location on the SARS-CoV-2 spike RBD, to put in play all the possible counteractions for preventing the most deleterious scenarios of new outbreaks, taking into consideration that a greater transmissibility has not to be necessarily related to a more severe manifestation of the disease

Computer-Aided vaccine design for selected positive-sense single stranded RNA viruses

Spontaneous mutations and lack of replication fidelity in positive-sense single stranded RNA viruses (+ssRNA virus) result in emergence of genetic variants with diverse viral morphogenesis and surface proteins that affect its antigenicity. This high mutability in +ssRNA viruses has induced antiviral drug resistance and ability to overcome vaccines that subsequently resulted in rapid viral evolution and high mortality rate in human and livestock. Computer aided vaccine design and immunoinformatics play a crucial role in expediting the vaccine production protocols, antibody production and identifying suitable immunogenic regions or epitopes from the genome sequences of the pathogens. T cell and B cell epitopes can be identified in pathogens by immunoinformatics algorithms and methods that enhance the analysis of protective immunity, vaccine safety, immunity modelling and vaccine efficacy. This rapid and cost-effective computational vaccine design promotes development of potential vaccine that could induce immune response in host against rapidly mutating pathogens like +ssRNA viruses. Epitope-based vaccine is a striking concept that has been widely employed in recent years to construct vaccines targeting rapidly mutating +ssRNA viruses. Therefore, the present review provides an overview about the current progress and methodology in computer-aided vaccine design for the most notable +ssRNA viruses namely Hepatitis C virus, Dengue virus, Chikungunya virus and Coronaviruses. This review also highlights the applications of various immunoinformatics tools for vaccine design and for modelling immune response against +ssRNA viruses

Bisindolylmaleimide IX: a Novel Anti-SARS-CoV2 Agent Targeting Viral Main Protease 3CLpro Demonstrated by Virtual Screening Pipeline and In-Vitro Validation Assays

SARS-CoV-2, the virus that causes COVID-19 consists of several enzymes with essential functions within its proteome. Here, we focused on repurposing approved and investigational drugs/compounds. We targeted seven proteins with enzymatic activities known to be essential at different stages of the viral cycle including PLpro, 3CLpro, RdRP, Helicase, ExoN, NendoU, and 2′-O-MT. For virtual screening, energy minimization of a crystal structure of the modeled protein was carried out using the Protein Preparation Wizard (Schrodinger LLC 2020-1). Following active site selection based on data mining and COACH predictions, we performed a high-throughput virtual screen of drugs and investigational molecules (n = 5903). The screening was performed against viral targets using three sequential docking modes (i.e., HTVS, SP, and XP). Virtual screening identified ∼290 potential inhibitors based on the criteria of energy, docking parameters, ligand, and binding site strain and score. Drugs specific to each target protein were further analyzed for binding free energy perturbation by molecular mechanics (prime MM-GBSA) and pruning the hits to the top 32 candidates. The top lead from each target pool was further subjected to molecular dynamics simulation using the Desmond module. The resulting top eight hits were tested for their SARS-CoV-2 anti-viral activity in-vitro. Among these, a known inhibitor of protein kinase C isoforms, Bisindolylmaleimide IX (BIM IX), was found to be a potent inhibitor of SARS-CoV-2. Further, target validation through enzymatic assays confirmed 3CLpro to be the target. This is the first study that has showcased BIM IX as a COVID-19 inhibitor thereby validating our pipeline

Spike Protein Structural Dynamics of SARS-CoV-2 Coronaviruses Studied Using Molecular Dynamics

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has overwhelmingly impacted the global population, accounting for millions of confirmed infections and deaths over the last year. The virus’s influence on the health and safety of individuals, the economy, and daily life has been disruptive and devastating. While SARS-CoV-2 and SARS-CoV-1, two closely related members of the SARS coronaviruses, have shown the ability to cross the species barrier and infect humans, SARS-CoV-2 has predominantly been the virus responsible for the number of infections presently known. SARS-CoV-2 has also proven to be volatile, as many variants have recently materialized based on amino acid structure mutations. Understanding the differential behavior of the SARS coronaviruses and the many SARS-CoV-2 variants may provide insight into interpreting how the spreading of COVID-19 occurs and could lead to further intuition and discovery. Specifically, studying the structural dynamics of spike proteins that play a crucial role in host cell receptor recognition could expedite the development of vaccines and antivirals that identify sites as potential drug targets. All variants of SARS-CoV-2 recognize the same receptor in humans, yet oftentimes the variants themselves exhibit varying degrees of characteristics such as transmissibility and infectivity. It is implied that the spike proteins, which are the most variable region in the entire genome, may potentially be a source of the different traits these variants present. Specifically, in the lab, we aimed to investigate the activation process of the spike protein and the conformational changes that must occur for the receptor-binding motif (RBM) to be made available for binding to the human receptor (ACE2). We analyzed and targeted the D614G mutation present in many of the SARS-CoV-2 variants and compared it to the differential characteristics present in the wild-type form of the virus. To visualize a detailed account of prefusion spike protein binding to ACE2, we used an extensive set of equilibrium microsecond-level all-atom molecular dynamics simulations. These models are both atomistic and dynamic, allowing us to visualize differences in protein conformation over time at remarkable degrees. The differential behaviors analyzed aided in determining the dynamical changes of the spike proteins and not just their inactive and active states. We determined that the D614G mutation altered sets of interactions throughout the spike protein, potentially resulting in different structural conformations. We also concluded that the D614G variant favored an active state due to increased relative stability, while the original Wild Type variant preferred an inactive state. These results suggest that the D614G mutation may cause variability in the activation mechanisms and stability of virus variants, potentially playing a crucial role in determining the differential characteristics that the viruses possess

Differential Electrostatic Interaction Patterns in SARS-CoV-1 and SARS-CoV-2 variants: A Molecular Dynamics Simulation Study

The SARS-related coronavirus (SARS-rCoV) is a highly contagious virus that has raised significant worldwide health concerns. It caused outbreaks in 2002-2003 and more recently in 2019-2020 with SARS-CoV-2. SARS-CoV-2 is responsible for the COVID-19 pandemic, which has resulted in a significant global impact on health and the economy. The spike protein of the virus plays a critical role in its infectivity and transmission, and the receptor-binding domain (RBD) within the spike protein is of particular interest, as it is responsible for binding to the human angiotensin-converting enzyme 2 (ACE2) receptor. In this study, we used Molecular dynamics (MD) simulations to investigate the electrostatic interaction patterns in the active and inactive models of SARS-CoV-1, SARS-CoV-2, and several variants of SARS-CoV-2, including the Alpha, Beta, Delta, and Epsilon variants. MD simulations are a computational method that allows us to model the motion of atoms and molecules over time, providing insights into the structure and behavior of biological molecules. The findings indicate differential electrostatic interaction patterns between the RBD of SARS-CoV-1 and SARS-CoV-2 spike protein. The RBD of SARS-CoV-2 exhibited a slower conformational pattern, which could influence higher stability, potentially affecting its binding affinity with the ACE2 receptor. Additionally, the Delta variant demonstrated significant differences in electrostatic interactions compared to the original SARS-CoV-2 strain, particularly in the N-terminal domain (NTD) and RBD regions. These findings suggest that Delta variant mutations could affect the RBD’s binding affinity to the ACE2 receptor, impacting transmission and virulence. Overall, this study highlights electrostatic interaction patterns in SARS-CoV-1, SARS-CoV-2, and variants, with implications for the development of long-term effective vaccines and therapeutics. Understanding the spike protein’s molecular basis may enable designing more effective treatments and strategies to prevent the spread of these viruses

Differential Electrostatic Interaction Patterns in SARS-CoV-1 and SARS-CoV-2 variants: A Molecular Dynamics Simulation Study

The SARS-related coronavirus (SARS-rCoV) is a highly contagious virus that has raised significant worldwide health concerns. It caused outbreaks in 2002-2003 and more recently in 2019-2020 with SARS-CoV-2. SARS-CoV-2 is responsible for the COVID-19 pandemic, which has resulted in a significant global impact on health and the economy. The spike protein of the virus plays a critical role in its infectivity and transmission, and the receptor-binding domain (RBD) within the spike protein is of particular interest, as it is responsible for binding to the human angiotensin-converting enzyme 2 (ACE2) receptor. In this study, we used Molecular dynamics (MD) simulations to investigate the electrostatic interaction patterns in the active and inactive models of SARS-CoV-1, SARS-CoV-2, and several variants of SARS-CoV-2, including the Alpha, Beta, Delta, and Epsilon variants. MD simulations are a computational method that allows us to model the motion of atoms and molecules over time, providing insights into the structure and behavior of biological molecules. The findings indicate differential electrostatic interaction patterns between the RBD of SARS-CoV-1 and SARS-CoV-2 spike protein. The RBD of SARS-CoV-2 exhibited a slower conformational pattern, which could influence higher stability, potentially affecting its binding affinity with the ACE2 receptor. Additionally, the Delta variant demonstrated significant differences in electrostatic interactions compared to the original SARS-CoV-2 strain, particularly in the N-terminal domain (NTD) and RBD regions. These findings suggest that Delta variant mutations could affect the RBD’s binding affinity to the ACE2 receptor, impacting transmission and virulence. Overall, this study highlights electrostatic interaction patterns in SARS-CoV-1, SARS-CoV-2, and variants, with implications for the development of long-term effective vaccines and therapeutics. Understanding the spike protein’s molecular basis may enable designing more effective treatments and strategies to prevent the spread of these viruses

Molecular Basis of SARS-CoV-2 Infection and Rational Design of Potential Antiviral Agents: Modeling and Simulation Approaches

The emergence in late 2019 of the coronavirus SARS-CoV-2 has resulted in the breakthrough of the COVID-19 pandemic that is presently affecting a growing number of countries. The development of the pandemic has also prompted an unprecedented effort of the scientific community to understand the molecular bases of the virus infection and to propose rational drug design strategies able to alleviate the serious COVID-19 morbidity. In this context, a strong synergy between the structural biophysics and molecular modeling and simulation communities has emerged, resolving at the atomistic level the crucial protein apparatus of the virus and revealing the dynamic aspects of key viral processes. In this Review, we focus on how in silico studies have contributed to the understanding of the SARS-CoV-2 infection mechanism and the proposal of novel and original agents to inhibit the viral key functioning. This Review deals with the SARS-CoV-2 spike protein, including the mode of action that this structural protein uses to entry human cells, as well as with nonstructural viral proteins, focusing the attention on the most studied proteases and also proposing alternative mechanisms involving some of its domains, such as the SARS unique domain. We demonstrate that molecular modeling and simulation represent an effective approach to gather information on key biological processes and thus guide rational molecular design strategies

Elucidating conserved sub-units from beta-coronavirus species for the creation of novel, cross-clade, and stable chimera sars-cov-2 spike proteins as future proof vaccine candidates

The COVID-19 pandemic caused by the SARS-CoV-2 outbreak triggered extensive scientific research. In this thesis, the spike (S) protein of the SARS-CoV-2 was studied in depth to gain useful insights to create a future proof vaccine. The structural information and structural stability of chimeric beta-coronavirus S proteins were investigated using bioinformatics techniques, structural predictions and molecular dynamics simulations. The study initially targeted the entire S protein of chimeric betacoronaviruses, but due to certain constraints, the study shifted the direction onto conserved regions of the S2 subunit only to generate chimeric sequences from different beta coronaviruses, in order to obtain vaccine candidates with broad immune coverage. For practicality, ten chimeric S2 sequences were carefully selected to study chimeric viral protein structures. This study used AlphaFold2 to predict 3D structures of the chimeric S2 protein sequences. Molecular dynamics simulations further elucidated their structural stabilities. The results lay the foundation for novel future proof vaccine design