The SARS-CoV-2 Antibody and Drug Research Based on the Structure of the Spike Protein and the Mechanism of Cell Entry.

COVID-19 is a severe acute respiratory syndrome caused by a novel coronavirus, SARS-CoV- 2.COVID-19 is now a pandemic, and is not yet fully under control.As the surface spike protein (S) mediates the recognition between the virus and cell membrane and the process of cell entry, it plays an important role in the course of disease transmission.The study on the S protein not only elucidates the structure and function of virus-related proteins and explains their cellular entry mechanism, but also provides valuable information for the prevention, diagnosis and treatment of COVII)-19.Concentrated on the S protein of SARS-CoV-2, this review covers four aspects: (1 ) The structure of the S protein and its binding with angiotensin converting enzyme II (ACE2) , the specific receptor of SARS-CoV-2, is introduced in detail.Compared with SARS-CoV, the receptor binding domain (RBD) of the SARS-CoV- 2 S protein has a higher affinity with ACE2, while the affinity of the entire S protein is on the contrary.(2) Currently, the cell entry mechanism of SARS-CoV-2 meditated by the S protein is proposed to include endosomal and non-endosomal pathways.With the recognition and binding between the S protein and ACE2 or after cell entry, transmembrane protease serine 2(TMPRSS2) , lysosomal cathepsin or the furin enzyme can cleave S protein at S1/S2 cleavage site, facilitating the fusion between the virus and target membrane.(3) For the progress in SARS-CoV-2 S protein antibodies, a collection of significant antibodies are introduced and compared in the fields of the target, source and type.(4) Mechanisms of therapeutic treatments for SARS-CoV-2 varied.Though the antibody and medicine treatments related to the SARS-CoV-2 S protein are of high specificity and great efficacy, the mechanism, safety, applicability and stability of some agents are still unclear and need further assessment.Therefore, to curb the pandemic, researchers in all fields need more cooperation in the development of SARS-CoV-2 antibodies and medicines to face the great challenge.Copyright © Palaeogeography (Chinese Edition).All right reserved.

Fast de novo antibody structure prediction with atomic accuracy

Background: In the field of antibody engineering, an essential task is to design a novel antibody whose paratopes bind to a specific antigen with correct epitopes. Understanding antibody structure and its paratope can facilitate a mechanistic understanding of its function. Therefore, antibody structure prediction from its sequence alone has always been a highly valuable problem for de novo antibody design. AlphaFold2 (AF2), a breakthrough in the field of structural biology, provides a solution to this protein structure prediction problem by learning a deep learning model. However, the computational efficiency and undesirable prediction accuracy on antibody, especially on the complementarity-determining regions limit its applications in de novo antibody design. Method(s): To learn informative representation of antibodies, we trained a deep antibody language model (ALM) on curated sequences from observed antibody space database via a well-designed transformer model. We also developed a novel model named xTrimoABFold++ to predict antibody structure from antibody sequence only based on the pretrained ALM as well as efficient evoformers and structural modules. The model was trained end-to-end on the antibody structures in PDB by minimizing the ensemble loss of domain-specific focal loss on CDR and the frame aligned point loss. Result(s): xTrimoABFold++ outperforms AF2 and OmegaFold, HelixFold-Single with 30+% improvement on RMSD. Also, it is 151 times faster than AF2 and predicts antibody structure in atomic accuracy within 20 seconds. In recently released antibodies, for example, cemiplimab of PD1 (PDB: 7WVM) and cross-neutralizing antibody 6D6 of SARS-CoV-2 (PDB: 7EAN), the RMSD of xTrimoABFold++ are 0.344 and 0.389 respectively. Conclusion(s): To the best of our knowledge, xTrimoABFold++ achieved the state-of-the-art in antibody structure prediction. Its improvement on both accuracy and efficiency makes it a valuable tool for de novo antibody design, and could make further improvement in immuno-theory.

A comprehensive review on technological advances in alternate drug discovery process:Drug repurposing

The traditional de novo drug discovery is time consuming, costly and in some instances the drugs will fail to treat the disease which result in a huge loss to the organization. Drug repurposing is an alternative drug discovery process to overcome the limitations of the De novo drug discovery process. Ithelps for the identification of drugs to the rare diseases as well as in the pandemic situationwithin short span of time in a cost-effective way. The underlying principle of drug repurposing is that most of the drugs identified on a primary purpose have shown to treat other diseases also. One such example is Tocilizumab is primarily used for rheumatoid arthritis and it is repurposed to treat cancer and COVID-19. At present, nearly30% of the FDA approved drugs to treat various diseases are repurposed drugs. The drug repurposing is either drug-centric or disease centric and can be studied by using both experimental and in silico studies. The in silico repurpose drug discovery process is more efficient as it screens thousands of compounds from the diverse libraries within few days by various computational methods like Virtual screening, Docking, MD simulations,Machine Learning, Artificial Intelligence, Genome Wide Association Studies (GWAS), etc. with certain limitations.These limitationscan be addressed by effective integration of advanced technologies to identify a novel multi-purpose drug.Copyright © 2023, Association of Biotechnology and Pharmacy. All rights reserved.

Primary immunodeficiency associated with a SAMD9L mutation

Background: SAMD9L is a tumor suppressor involved in regulating the proliferation and maturation of cells, particularly those derived from the bone marrow, and appears to play an important role in cerebellar function. It can be activated in hematopoietic stem cells by type I and type II interferons. It has been hypothesized to act as a critical antiviral gatekeeper regulating interferon dependent demand driven hematopoiesis. Gain of function mutations can present with an immunodeficiency due to transient severe cytopenias during viral infection. Case presentation: We report a 3-year-old boy born full term with a history of severe thrombocytopenia requiring transfusions, developmental delay, ataxia, seizure disorder, and recurrent severe respiratory viral infections. His infectious history was significant for respiratory syncytial virus with shock requiring extracorporeal membrane oxygenation complicated by cerebral infarction and a group A streptococcus empyema, osteomyelitis requiring a left below the knee amputation, and infections with rhinovirus, COVID-19, and parainfluenza requiring hospitalizations for respiratory support. Initial immunologic evaluation was done during his hospitalization for parainfluenza. His full T cell subsets was significant for lymphopenia across all cell lines with CD3 934/microL, CD4 653/microL, CD8 227/microL, CD19 76/microL, and CD1656 61/microL. His mitogen stimulation assay to phytohemagglutinin and pokeweed was normal. Immunoglobulin panel showed a mildly decreased IgM of 25 mg/dL, but normal IgA and IgG. Vaccine titers demonstrated protective titers to 12/22 pneumococcus serotypes, varicella, diphtheria, mumps, rubella, and rubeola. Repeat full T cell subsets 6 weeks later revealed marked improvement in lymphocyte counts with CD3 3083/microL, CD4 2101/microL, CD8 839/microL, CD19 225/microL, and CD1656/microL. A primary immunodeficiency genetic panel was ordered and positive for a heterozygous SAMD9L c.1549T>C (p.Trp517Arg) mutation classified as a variant of unknown significance. Discussion(s): This patient's history of severe viral infections, ataxia, thrombocytopenia, and severe transient lymphopenia during infection is suggestive of a SAM9DL gain of function mutation. Protein modeling done by the laboratory suggests this missense mutation would affect protein structure. The mutation found has been observed in individuals with thrombocytopenia. This case highlights the importance of immunophenotyping both during acute illness and once recovered.Copyright © 2023 Elsevier Inc.

Computer-aided comprehensive explorations of RNA structural polymorphism through complementary simulation methods

While RNA folding was originally seen as a simple problem to solve, it has been shown that the promiscuous interactions of the nucleobases result in structural polymorphism, with several competing structures generally observed for non-coding RNA. This inherent complexity limits our understanding of these molecules from experiments alone, and computational methods are commonly used to study RNA. Here, we discuss three advanced sampling schemes, namely Hamiltonian-replica exchange molecular dynamics (MD), ratchet-and-pawl MD and discrete path sampling, as well as the HiRE-RNA coarse-graining scheme, and highlight how these approaches are complementary with reference to recent case studies. While all computational methods have their shortcomings, the plurality of simulation methods leads to a better understanding of experimental findings and can inform and guide experimental work on RNA polymorphism.Copyright ©

Attacking the SARS-CoV-2 Replication Machinery with the Pathogen Box's Molecules

Introduction: The world is currently facing a pandemic initiated by the new coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 virus. Viral transcription and replication are the fundamental processes of any virus. They allow the synthesis of genetic material and the consequent multiplication of the virus to infect other cells or organisms.Methods: The most important protein in SARS-CoV-2 is the RNA polymerase (RdRp or nsp12), responsible for both processes. The structure of this protein (PDB ID: 6M71) was used as a target in the application of computational strategies for a drug search, like virtual screening and molecular docking. Here, the Pathogen Box database of chemical compounds was used together with Remdesivir, Beclabuvir, and Sofosbuvir drugs as potential inhibitors of nsp12.Results: The results showed Top10 potential target inhibitors with binding energy (ΔG) higher than those of the positive controls, of which TCMDC-134153 and TCMDC-135052, both with ΔG = −7.53 kcal/mol, present interactions with three important residues of the nsp12 catalytic site.Conclusion: These proposed ligands would be used for subsequent validation by molecular dynamics, where they can be considered as drugs for the development of effective treatments against this new pandemic.

Global Trends in the Determination of Coronavirus PDB Protein Structures

This study aims to examine the international publication patterns of coronavirus protein database (PDB) structures, beginning when the first coronavirus virion PDB structures were published in 2002 to the present (2022). Sources of these depositions were extracted from their publications and used as indicators of how countries reacted to the pandemic through research output and were then compared to demographic and economic metrics. Of the approximately 40 countries examined, the United States, United Kingdom, and China had the highest number of proteins, demonstrating research productivity centeredness in highly developed countries. These countries all displayed a peak in protein depositions in 2020 or 2021, and slowed down in 2022 likely due to the peaking of the pandemic and a slowing necessity of response. Population size was found to contribute little to no factor in determining the number of coronavirus protein depositions while higher economic status measured by the GDP per capita did correlate with higher numbers of protein depositions (Jaffe et al, 2020). The number of confirmed Covid-19 cases showed a positive association with the number of PDB depositions per country, specifically in the United States. Furthermore, South Africa and Brazil, despite not being in the top 10 research-producing countries, had a high number of cases and PDB depositions, suggesting the strong impact of confirmed cases on coronavirus research output (Normile, 2022). This study's measure of how countries' economic status, population, and confirmed coronavirus cases affects their responses in terms of coronavirus protein research output suggests an unequal distribution in publication origins, which poses a challenge to global pandemic response coordination. This study continues an earlier study presented at the PDB50 - ASBMB on-line meeting, on May 4- 5, 2021 by Janet Gonzalez, Matthew K. McDevitt, David Roman, & Manfred Philipp. NA.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

Investigation of antiviral substances in Covid 19 by Molecular Docking: In Silico Study

Aims: This paper aimed to investigate the antiviral drugs against Sars-Cov-2 main protease (MPro) using in silico methods. Material(s) and Method(s): A search was made for antiviral drugs in the PubChem database and antiviral drugs such as Bictegravir, Emtricitabine, Entecavir, Lamivudine, Tenofovir, Favipiravir, Hydroxychloroquine, Lopinavir, Oseltamavir, Remdevisir, Ribavirin, Ritonavir were included in our study. The protein structure of Sars-Cov-2 Mpro (PDB ID: 6LU7) was taken from the Protein Data Bank (www.rcsb. Org) system and included in our study. Molecular docking was performed using AutoDock/Vina, a computational docking program. Protein-ligand interactions were performed with the AutoDock Vina program. 3D visualizations were made with the Discovery Studio 2020 program. N3 inhibitor method was used for our validation. Result(s): In the present study, bictegravir, remdevisir and lopinavir compounds in the Sars-Cov-2 Mpro structure showed higher binding affinity compared to the antiviral compounds N3 inhibitor, according to our molecular insertion results. However, the favipiravir, emtricitabine and lamuvidune compounds were detected very low binding affinity. Other antiviral compounds were found close binding affinity with the N3 inhibitor. Conclusion(s): Bictegravir, remdevisir and lopinavir drugs showed very good results compared to the N3 inhibitor. Therefore, they could be inhibitory in the Sars Cov-2 Mpro target.Copyright © 2023 Oner E et al.

Are Non-Structural Proteins From SARS-CoV-2 the Target of Hydroxychloroquine? An in Silico Study

COVID-19 is caused by SARS-CoV-2 which has structural and non-structural proteins (NSP) essential for infection and viral replication. There is a possible binding of SARS-CoV-2 to the beta-1 chain of hemoglobin in red blood cells and thus, decreasing the oxygen transport capacity. Since hydroxychloroquine (HCQ) can accumulate in red cells, there is a chance of interaction of this drug with the virus. To analyze possible interactions between SARS-CoV-2 NSP and hemoglobin with the HCQ using molecular docking and implications for the infected host. This research consisted of a study using bioinformatics tools. The files of the protein structures and HCQ were prepared using the AutoDock Tools software. These files were used to perform molecular docking simulations by AutoDock Vina. The binding affinity report of the generated conformers was analyzed using PyMol software, as well as the chemical bonds formed. The results showed that HCQ is capable of interacting with both SARS-CoV-2 NSP and human hemoglobin. The HCQ/NSP3 conformer, HCQ/NSP5, HCQ/NSP7-NSP8-NSP12, HCQ/NSP9, HCQ/NSP10-NSP16 showed binding affinity. In addition, the interaction between HCQ and hemoglobin resulted in polar bonds. Interaction between SARS-CoV-2 NSP and HCQ indicates that this drug possibly acts by preventing the continuity of infection.Copyright © 2023 Tehran University of Medical Sciences.

Post-translational modifications: Host defence mechanism, pathogenic weapon, and emerged target of anti-infective drugs

Post-translational modifications are changes introduced to proteins after their translation. They are the means to generate molecular diversity, expand protein function, control catalytic activity and trigger quick responses to a wide range of stimuli. Moreover, they regulate numerous biological processes, including pathogen invasion and host defence mechanisms. It is well established that bacteria and viruses utilize post-translational modifications on their own or their host's proteins to advance their pathogenicity. Doing so, they evade immune responses, target signaling pathways and manipulate host cytoskeleton to achieve survival, replication and propagation. Many bacterial species secrete virulence factors into the host and mediate hostpathogen interactions by inducing post-translational modifications that subvert fundamental cellular processes. Viral pathogens also utilize post translational modifications in order to overcome the host defence mechanisms and hijack its cellular machinery for their replication and propagation. For example, many coronavirus proteins are modified to achieve host invasion, evasion of immune responses and utilization of the host translational machinery. PTMs are also considered potential targets for the development of novel therapeutics from natural products with antibiotic properties, like lasso peptides and lantibiotics. The last decade, significant progress was made in understanding the mechanisms that govern PTMs and mediate regulation of protein structure and function. This urges the identification of relevant molecular targets, the design of specific drugs and the discovery of PTM-based medicine. Therefore, PTMs emerge as a highly promising field for the investigation and discovery of new therapeutics for many infectious diseases.Copyright © 2021 Bentham Science Publishers.

PREFMoDeL: A Systematic Review and Proposed Taxonomy of Biomolecular Features for Deep Learning

Of fundamental importance in biochemical and biomedical research is understanding a molecule's biological properties—its structure, its function(s), and its activity(ies). To this end, computational methods in Artificial Intelligence, in particular Deep Learning (DL), have been applied to further biomolecular understanding—from analysis and prediction of protein–protein and protein–ligand interactions to drug discovery and design. While choosing the most appropriate DL architecture is vitally important to accurately model the task at hand, equally important is choosing the features used as input to represent molecular properties in these DL models. Through hypothesis testing, bioinformaticians have created thousands of engineered features for biomolecules such as proteins and their ligands. Herein we present an organizational taxonomy for biomolecular features extracted from 808 articles from across the scientific literature. This objective view of biomolecular features can reduce various forms of experimental and/or investigator bias and additionally facilitate feature selection in biomolecular analysis and design tasks. The resulting dataset contains 1360 nondeduplicated features, and a sample of these features were classified by their properties, clustered, and used to suggest new features. The complete feature dataset (the Public Repository of Engineered Features for Molecular Deep Learning, PREFMoDeL) is released for collaborative sourcing on the web.

Immunological inflammatory factors in patients diagnosed with COVID-19

Introduction and Aim: Due to the Coronavirus outbreaks, the SARS-CoV-2, also known as COVID-19, has claimed several lives around the world, with the majority of them being elderly, suffering from underlying chronic illnesses, or living in vulnerable conditions. This study aimed to find the immunological factors CD-79, CD-4, IL-2, and TNF-B in COVID-19 patients utilizing nucleocapsid-(N), a protein structure that interacts with genomic RNA to create complexes. Material(s) and Method(s): SARS-COV-2 infection was detected using RT-PCR. The serum levels of IL-2 and TNF-B, as well as the concentrations of CD4 and CD79, were measured. This study included 100 COVID-19 patients. Result(s): The results showed that the serum concentration of TNF-beta and IL-2 in COVID19 patients was significantly higher than that in the general population (with acute and moderate illness) when compared to normal control groups (p<0.05). COVID-19 patients reported higher levels of CD79 as well as CD4 expression than healthy control groups in a study of activated markers. Conclusion(s): Infection with SARS-COV-2 has a high impact on various immunological and inflammatory markers in patients.Copyright © 2023, Indian Association of Biomedical Scientists. All rights reserved.

In Silico Modeling of COVID-19 Pandemic Course Differentiation Using the FOD Model

Background: The strange and still unclear scenarios of COVID-19 pandemic development have raised the question about the reason for the observed essential state and personal differences con-cerning the expansion and severity of the infection process. Some custom activities are taken into consid-eration in an attempt to explain the phenomenon. Alcohol in the diet is suggested in this paper as the possible factor which could explain the observed differentiation. It easily penetrates cells modifying their natural internal environment, and independently influences tissues as the toxic agent being the source of acetyl aldehyde. Objective(s): The process in which the cell seems to be the most sensitive to altered environmental conditions is the protein folding;in particular, its portion occurring in the endoplasmic reticulum where freshly synthesized polypeptides fold and then are introduced to the cell membrane influencing its property and in particular its fluidity, which is the critical parameter deciding the virus penetration into the cell. Method(s): The application of a mathematical model, fuzzy oil drop model FOD, expressing the influence of the environment on the protein folding process shows the mechanism of this influence. Result(s): The differences between statistical assessment of epidemy in Europe and the Far East, which may be correlated with alcohol consumption, suggest the influence of diet on the status of epidemy in these regions. Conclusion(s): The protein folding seems to be the process most sensitive to environmental conditions in the cell. The different diet customs, including the use of alcohol, may disturb the folding process, lower-ing as the result the number of proteins needed for cell membrane stability, thus increasing its fluidity and the cell susceptibility to virus penetration. Observations presented in this paper are based on the initial period of pandemic development and have not been intentionally modified to prevent the influence of additional factors, like government activities or virus mutations.Copyright © 2022 Bentham Science Publishers.

Epitopes Determination for OMICRON: The COVID"19 New Variant

ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS"CoV"2) has rapidly evolved in the last couple of years. This has created major havoc and concern because it has affected millions of people around the world. The new variants of covid"19 are classified into two types, VOI (variant of interest) and VOC (variant of concern). The major variants of concern (VOCs) have shared mutations in severe acute respiratory syndrome coronavirus 2 (SARS"CoV"2). The spike proteins of the novel coronavirus located mostly on the S1 unit result in a higher transmissibility rate and affect the viral virulence and clinical outcome. The spike protein and other non"structural protein mutations in VOCs may lead to escape the approved vaccinations. Here the VOC mutations i.e., OMICRON VARIANT have been discussed in detail, and the therapeutic strategies to enhance the host immune responses have been proposed. Additionally, a computational approach is proposed to design the drug and vaccine for the variant. The protein structure for the OMICRON variant has been predicted through bioinformatics tools and several databases have been used to identify suitable natural inhibitors. The OMICRON variant was analyzed to identify suitable vaccine candidates by identifying B"Cell epitopes. To design a drug, REPAGLINIDE and ENT"NATEGLINIDE were identified as natural inhibitors based on docking score. To design a vaccine the B"cell epitope i.e., CLIGAEYVNNSYECD was found to the highest antigenicity score. The present study identifies natural inhibitors and potential antigenic Epitopes which may be used as effective drug and vaccine candidates to suppress the novel coronavirus.

Chemi-Informatic Approach to Investigate Putative Pharmacoactive Agents of Plant Origin to Eradicate COVID-19

Background: The scientific community has supported the medicinal flora of ancient as well as modern times in extracting chemicals, which holds therapeutic potential. In many previous studies, Amentoflavone discovered as an anti-viral agent, and it is present as a bioactive constituent in many plants of different families like Selaginellaceae, Euphorbiaceae, and Calophyllaceae. Withania somnifera (Ashwagandha) is already considered a significant anti-viral agent in traditional medicine, and it is the main source of Somniferine-A and Withanolide-B. Objective(s): In this study, phytochemicals such as withanolide-b, somniferine-a, stigmasterol, amentoflavone, and chavicine were analyzed to screen protein inhibitors, out of them;such proteins are involved in the internalization and interaction of SARS-CoV-2 with human cytological domains. This will help in developing a checkpoint for SARS-CoV-2 internalization. Method(s): Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME, MDWeb, Molsoft, ProTox-II, and LigPlot were used to examine the action of pharmacoactive agents against SARS-CoV-2. The tools used in the study were based on the finest algorithms like artificial neural networking, machine learning, and artificial intelligence. Result(s): On the basis of binding energies less than equal to-8.5 kcal/mol, amentoflavone, stigmasterol, and somniferine-A were found to be the most effective against COVID-19 disease as these chemical agents exhibit hydrogen bond interactions and competitively inhibit major proteins (SARS-CoV-2 Spike, Human ACE-2 receptor, Human Furin protease, SARS-CoV-2 RNA binding protein) that are involved in its infection and pathogenesis. Simulation analysis provides more validity to the selection of the drug candidate Amentoflavone. ADMET properties were found to be in the feasible range for putative drug candidates. Conclusion(s): Computational analysis was successfully used for searching pharmacoactive phytochemicals like Amentoflavone, Somniferine-A, and Stigmasterol that can bring control over COVID-19 expansion. This new methodology was found to be efficient, as it reduces monetary expenditures and time consumption. Molecular wet-lab validations will provide approval for finalizing our selected drug model for controlling the COVID-19 pandemic.Copyright © 2022 Bentham Science Publishers.

All Domains of SARS-CoV-2 nsp1 Determine Translational Shutoff and Cytotoxicity of the Protein.

Replication of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strongly affects cellular metabolism and results in rapid development of the cytopathic effect (CPE). The hallmarks of virus-induced modifications are inhibition of translation of cellular mRNAs and redirection of the cellular translational machinery to the synthesis of virus-specific proteins. The multifunctional nonstructural protein 1 (nsp1) of SARS-CoV-2 is a major virulence factor and a key contributor to the development of translational shutoff. In this study, we applied a wide range of virological and structural approaches to further analyze nsp1 functions. The expression of this protein alone was found to be sufficient to cause CPE. However, we selected several nsp1 mutants exhibiting noncytopathic phenotypes. The attenuating mutations were detected in three clusters, located in the C-terminal helices, in one of the loops of the structured domain and in the junction of the disordered and structured fragment of nsp1. NMR-based analysis of the wild type nsp1 and its mutants did not confirm the existence of a stable ß5-strand that was proposed by the X-ray structure. In solution, this protein appears to be present in a dynamic conformation, which is required for its functions in CPE development and viral replication. The NMR data also suggest a dynamic interaction between the N-terminal and C-terminal domains. The identified nsp1 mutations make this protein noncytotoxic and incapable of inducing translational shutoff, but they do not result in deleterious effects on viral cytopathogenicity. IMPORTANCE The nsp1 of SARS-CoV-2 is a multifunctional protein that modifies the intracellular environment for the needs of viral replication. It is responsible for the development of translational shutoff, and its expression alone is sufficient to cause a cytopathic effect (CPE). In this study, we selected a wide range of nsp1 mutants exhibiting noncytopathic phenotypes. The attenuating mutations, clustered in three different fragments of nsp1, were extensively characterized via virological and structural methods. Our data strongly suggest interactions between the nsp1 domains, which are required for the protein's functions in CPE development. Most of the mutations made nsp1 noncytotoxic and incapable of inducing translational shutoff. Most of them did not affect the viability of the viruses, but they did decrease the rates of replication in cells competent in type I IFN induction and signaling. These mutations, and their combinations, in particular, can be used for the development of SARS-CoV-2 variants with attenuated phenotypes.

Predicting DNA-binding protein and coronavirus protein flexibility using protein dihedral angle and sequence feature.

The flexibility of protein structure is related to various biological processes, such as molecular recognition, allosteric regulation, catalytic activity, and protein stability. At the molecular level, protein dynamics and flexibility are important factors to understand protein function. DNA-binding proteins and Coronavirus proteins are of great concern and relatively unique proteins. However, exploring the flexibility of DNA-binding proteins and Coronavirus proteins through experiments or calculations is a difficult process. Since protein dihedral rotational motion can be used to predict protein structural changes, it provides key information about protein local conformation. Therefore, this paper introduces a method to improve the accuracy of protein flexibility prediction, DihProFle (Prediction of DNA-binding proteins and Coronavirus proteins flexibility introduces the calculated dihedral Angle information). Based on protein dihedral Angle information, protein evolution information, and amino acid physical and chemical properties, DihProFle realizes the prediction of protein flexibility in two cases on DNA-binding proteins and Coronavirus proteins, and assigns flexibility class to each protein sequence position. In this study, compared with the flexible prediction using sequence evolution information, and physicochemical properties of amino acids, the flexible prediction accuracy based on protein dihedral Angle information, sequence evolution information and physicochemical properties of amino acids improved by 2.2% and 3.1% in the nonstrict and strict conditions, respectively. And DihProFle achieves better performance than previous methods for protein flexibility analysis. In addition, we further analyzed the correlation of amino acid properties and protein dihedral angles with residues flexibility. The results show that the charged hydrophilic residues have higher proportion in the flexible region, and the rigid region tends to be in the angular range of the protein dihedral angle (such as the ψ angle of amino acid residues is more flexible than rigid in the range of 91°-120°). Therefore, the results indicate that hydrophilic residues and protein dihedral angle information play an important role in protein flexibility.

The origins of COVID-19 pandemic: A brief overview.

The novel coronavirus disease (COVID-19) outbreak that emerged at the end of 2019 has now swept the world for more than 2 years, causing immeasurable damage to the lives and economies of the world. It has drawn so much attention to discovering how the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated and entered the human body. The current argument revolves around two contradictory theories: a scenario of laboratory spillover events and human contact with zoonotic diseases. Here, we reviewed the transmission, pathogenesis, possible hosts, as well as the genome and protein structure of SARS-CoV-2, which play key roles in the COVID-19 pandemic. We believe the coronavirus was originally transmitted to human by animals rather than by a laboratory leak. However, there still needs more investigations to determine the source of the pandemic. Understanding how COVID-19 emerged is vital to developing global strategies for mitigating future outbreaks.

Distinguishing features of fold-switching proteins.

Though many folded proteins assume one stable structure that performs one function, a small-but-increasing number remodel their secondary and tertiary structures and change their functions in response to cellular stimuli. These fold-switching proteins regulate biological processes and are associated with autoimmune dysfunction, severe acute respiratory syndrome coronavirus-2 infection, and more. Despite their biological importance, it is difficult to computationally predict fold switching. With the aim of advancing computational prediction and experimental characterization of fold switchers, this review discusses several features that distinguish fold-switching proteins from their single-fold and intrinsically disordered counterparts. First, the isolated structures of fold switchers are less stable and more heterogeneous than single folders but more stable and less heterogeneous than intrinsically disordered proteins (IDPs). Second, the sequences of single fold, fold switching, and intrinsically disordered proteins can evolve at distinct rates. Third, proteins from these three classes are best predicted using different computational techniques. Finally, late-breaking results suggest that single folders, fold switchers, and IDPs have distinct patterns of residue-residue coevolution. The review closes by discussing high-throughput and medium-throughput experimental approaches that might be used to identify new fold-switching proteins.

Comparison of allosteric signaling in DnaK and BiP using mutual information between simulated residue conformations.

The heat shock protein 70 kDa (Hsp70) chaperone system serves as a critical component of protein quality control across a wide range of prokaryotic and eukaryotic organisms. Divergent evolution and specialization to particular organelles have produced numerous Hsp70 variants which share similarities in structure and general function, but differ substantially in regulatory aspects, including conformational dynamics and activity modulation by cochaperones. The human Hsp70 variant BiP (also known as GRP78 or HSPA5) is of therapeutic interest in the context of cancer, neurodegenerative diseases, and viral infection, including for treatment of the pandemic virus SARS-CoV-2. Due to the complex conformational rearrangements and high sequential variance within the Hsp70 protein family, it is in many cases poorly understood which amino acid mutations are responsible for biochemical differences between protein variants. In this study, we predicted residues associated with conformational regulation of human BiP and Escherichia coli DnaK. Based on protein structure networks obtained from molecular dynamics simulations, we analyzed the shared information between interaction timelines to highlight residue positions with strong conformational coupling to their environment. Our predictions, which focus on the binding processes of the chaperone's substrate and cochaperones, indicate residues filling potential signaling roles specific to either DnaK or BiP. By combining predictions of individual residues into conformationally coupled chains connecting ligand binding sites, we predict a BiP specific secondary signaling pathway associated with substrate binding. Our study sheds light on mechanistic differences in signaling and regulation between Hsp70 variants, which provide insights relevant to therapeutic applications of these proteins.