Structural insights into the mechanism of RNA recognition by the N-terminal RNA-binding domain of the SARS-CoV-2 nucleocapsid phosphoprotein

Computational evaluation of phytochemicals targeting DNA topoisomerase I in Leishmania donovani: molecular docking and molecular dynamics simulation studies

DNA topoisomerase I (Topo I) is a ubiquitous enzyme that plays a crucial role in resolving the topological constraints of supercoiled DNA during various cellular activities, including repair, replication, recombination, transcription, and chromatin remodeling. Multiple studies have confirmed the essential role of Topo I in nucleic acid metabolism of Leishmania donovani, the kinetoplastid parasite responsible for visceral leishmaniasis or kala-azar. Inhibition of this enzyme has shown promise as a strategy for therapy against visceral leishmaniasis. However, current treatment options suffer from limitations related to effectiveness, cost, and side effects. To address these challenges, computational methods have been employed in this study to investigate the inhibition of Leishmania donovani DNA topoisomerase I (LdTopo I) by phytochemicals derived from Indian medicinal plants known for their anti-leishmanial activity. A library of phytochemicals and known inhibitors was assembled, and virtual screening based on docking binding affinities was conducted to identify potent phytochemical inhibitors. To assess the drug-likeness of the docked phytochemicals, their physicochemical properties were predicted. Additionally, molecular dynamics (MD) simulations were performed on the docked complexes for a duration of 100 ns to evaluate their stability, intermolecular interactions, and dynamic behavior. Among all the docked phytochemicals, three compounds, namely CID23266147 (withanolide N), CID5488537 (fagopyrine), and CID100947536 (isozeylanone), exhibited the highest inhibitory potential against LdTopo I. These findings hold promise for the development of novel inhibitors targeting LdTopo I, which could potentially lead to improved therapies for visceral leishmaniasis.Communicated by Ramaswamy H. Sarma.

Comparative Atlas of SARS-CoV-2 Substitution Mutations: A Focus on Iranian Strains Amidst Global Trends

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new emerging coronavirus that caused coronavirus disease 2019 (COVID-19). Whole-genome tracking of SARS-CoV-2 enhanced our understanding of the mechanism of the disease, control, and prevention of COVID-19.

METHODS

we analyzed 3368 SARS-CoV-2 protein sequences from Iran and compared them with 15.6 million global sequences in the GISAID database, using the Wuhan-Hu-1 strain as a reference.

RESULTS

Our investigation revealed that NSP12-P323L, ORF9c-G50N, NSP14-I42V, membrane-A63T, Q19E, and NSP3-G489S were found to be the most frequent mutations among Iranian SARS-CoV-2 sequences. Furthermore, it was observed that more than 94% of the SARS-CoV-2 genome, including NSP7, NSP8, NSP9, NSP10, NSP11, and ORF8, had no mutations when compared to the Wuhan-Hu-1 strain. Finally, our data indicated that the ORF3a-T24I, NSP3-G489S, NSP5-P132H, NSP14-I42V, envelope-T9I, nucleocapsid-D3L, membrane-Q19E, and membrane-A63T mutations might be responsible factors for the surge in the SARS-CoV-2 Omicron variant wave in Iran.

CONCLUSIONS

real-time genomic surveillance is crucial for detecting new SARS-CoV-2 variants, updating diagnostic tools, designing vaccines, and understanding adaptation to new environments.

Impact of mutations on the stability of SARS-CoV-2 nucleocapsid protein structure

The nucleocapsid (N) protein of SARS-CoV-2 is known to participate in various host cellular processes, including interferon inhibition, RNA interference, apoptosis, and regulation of virus life cycles. Additionally, it has potential as a diagnostic antigen and/or immunogen. Our research focuses on examining structural changes caused by mutations in the N protein. We have modeled the complete tertiary structure of native and mutated forms of the N protein using Alphafold2. Notably, the N protein contains 3 disordered regions. The focus was on investigating the impact of mutations on the stability of the protein's dimeric structure based on binding free energy calculations (MM-PB/GB-SA) and RMSD fluctuations after MD simulations. The results demonstrated that 28 mutations out of 37 selected mutations analyzed, compared with wild-type N protein, resulted in a stable dimeric structure, while 9 mutations led to destabilization. Our results are important to understand the tertiary structure of the N protein dimer of SARS-CoV-2 and the effect of mutations on it, their behavior in the host cell, as well as for the research of other viruses belonging to the same genus additionally, to anticipate potential strategies for addressing this viral illness․.

Structural basis for the mechanism of interaction of SARS-CoV-2 B.1.640.2 variant RBD with the host receptors hACE2 and GRP78

The inflicted chaos instigated by the SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) globally continues with the emergence of novel variants. The current global outbreak is aggravated by the manifestation of novel variants, which affect the effectiveness of the vaccine, attachment with hACE2 (human Angiotensin-converting enzyme 2) and immune evasion. Recently, a new variant named University Hospital Institute (IHU) (B.1.640.2) was reported in France in November 2021 and is spreading globally affecting public healthcare. The B.1.640.2 SARS-CoV-2 strain revealed 14 mutations and 9 deletions in spike protein. Thus, it is important to understand how these variations in the spike protein impact the communication with the host. A protein coupling approach along with molecular simulation protocols was used to interpret the variation in the binding of the wild type (WT) and B.1.640.2 variant with hACE2 and Glucose-regulating protein 78 (GRP78) receptors. The initial docking scores revealed a stronger binding of the B.1.640.2-RBD with both the hACE2 and GRP78. To further understand the crucial dynamic changes, we looked at the structural and dynamic characteristics and also explored the variations in the bonding networks between the WT and B.1.640.2-RBD (receptor-binding domain) in association with hACE2 and GRP78, respectively. Our findings revealed that the variant complex demonstrated distinct dynamic properties in contrast to the wild type due to the acquired mutations. Finally, to provide conclusive evidence on the higher binding by the B.1.640.2 variant the TBE was computed for each complex. For the WT with hACE2 the TBE was quantified to be-61.38 ± 0.96 kcal/mol and for B.1.640.2 variant the TBE was estimated to be -70.47 ± 1.00 kcal/mol. For the WT-RBD-GRP78 the TBE -was computed to be 32.32 ± 0.56 kcal/mol and for the B.1.640.2-RBD a TBE of -50.39 ± 0.88 kcal/mol was reported. This show that these mutations are the basis for higher binding and infectivity produced by B.1.640.2 variant and can be targeted for drug designing against it.Communicated by Ramaswamy H. Sarma.

WGX50 mitigates doxorubicin-induced cardiotoxicity through inhibition of mitochondrial ROS and ferroptosis

BACKGROUND

Doxorubicin (DOX)-induced cardiotoxicity (DIC) is a major impediment to its clinical application. It is indispensable to explore alternative treatment molecules or drugs for mitigating DIC. WGX50, an organic extract derived from Zanthoxylum bungeanum Maxim, has anti-inflammatory and antioxidant biological activity, however, its function and mechanism in DIC remain unclear.

METHODS

We established DOX-induced cardiotoxicity models both in vitro and in vivo. Echocardiography and histological analyses were used to determine the severity of cardiac injury in mice. The myocardial damage markers cTnT, CK-MB, ANP, BNP, and ferroptosis associated indicators Fe2+, MDA, and GPX4 were measured using ELISA, RT-qPCR, and western blot assays. The morphology of mitochondria was investigated with a transmission electron microscope. The levels of mitochondrial membrane potential, mitochondrial ROS, and lipid ROS were detected using JC-1, MitoSOX™, and C11-BODIPY 581/591 probes.

RESULTS

Our findings demonstrate that WGX50 protects DOX-induced cardiotoxicity via restraining mitochondrial ROS and ferroptosis. In vivo, WGX50 effectively relieves doxorubicin-induced cardiac dysfunction, cardiac injury, fibrosis, mitochondrial damage, and redox imbalance. In vitro, WGX50 preserves mitochondrial function by reducing the level of mitochondrial membrane potential and increasing mitochondrial ATP production. Furthermore, WGX50 reduces iron accumulation and mitochondrial ROS, increases GPX4 expression, and regulates lipid metabolism to inhibit DOX-induced ferroptosis.

CONCLUSION

Taken together, WGX50 protects DOX-induced cardiotoxicity via mitochondrial ROS and the ferroptosis pathway, which provides novel insights for WGX50 as a promising drug candidate for cardioprotection.

Structural and pKa Estimation of the Amphipathic HR1 in SARS-CoV-2: Insights from Constant pH MD, Linear vs. Nonlinear Normal Mode Analysis

A comprehensive understanding of molecular interactions and functions is imperative for unraveling the intricacies of viral protein behavior and conformational dynamics during cellular entry. Focusing on the SARS-CoV-2 spike protein (SARS-CoV-2 sp), a Principal Component Analysis (PCA) on a subset comprising 131 A-chain structures in presence of various inhibitors was conducted. Our analyses unveiled a compelling correlation between PCA modes and Anisotropic Network Model (ANM) modes, underscoring the reliability and functional significance of low-frequency modes in adapting to diverse inhibitor binding scenarios. The role of HR1 in viral processing, both linear Normal Mode Analysis (NMA) and Nonlinear NMA were implemented. Linear NMA exhibited substantial inter-structure variability, as evident from a higher Root Mean Square Deviation (RMSD) range (7.30 Å), nonlinear NMA show stability throughout the simulations (RMSD 4.85 Å). Frequency analysis further emphasized that the energy requirements for conformational changes in nonlinear modes are notably lower compared to their linear counterparts. Using simulations of molecular dynamics at constant pH (cpH-MD), we successfully predicted the pKa order of the interconnected residues within the HR1 mutations at lower pH values, suggesting a transition to a post-fusion structure. The pKa determination study illustrates the profound effects of pH variations on protein structure. Key results include pKa values of 9.5179 for lys-921 in the D936H mutant, 9.50 for the D950N mutant, and a slightly higher value of 10.49 for the D936Y variant. To further understand the behavior and physicochemical characteristics of the protein in a biologically relevant setting, we also examine hydrophobic regions in the prefused states of the HR1 protein mutants D950N, D936Y, and D936H in our study. This analysis was conducted to ascertain the hydrophobic moment of the protein within a lipid environment, shedding light on its behavior and physicochemical properties in a biologically relevant context.

In silico evaluation of the inhibitory potential of nucleocapsid inhibitors of SARS-CoV-2: a binding and energetic perspective

The COVID-19 outbreak brought on by the SARS-CoV-2 virus continued to infect a sizable population worldwide. The SARS-CoV-2 nucleocapsid (N) protein is the most conserved RNA-binding structural protein and is a desirable target because of its involvement in viral transcription and replication. Based on this aspect, this study focused to repurpose antiviral compounds approved or in development for treating COVID-19. The inhibitors chosen are either FDA-approved or are currently being studied in clinical trials against COVID-19. Initially, they were designed to target stress granules and other RNA biology. We have utilized structure-based molecular docking and all-atom molecular dynamics (MD) simulation approach to investigate in detail the binding energy and binding modes of the different anti-N inhibitors to N protein. The result showed that five drugs including Silmitasterib, Ninetanidinb, Ternatin, Luteolin, Fedratinib, PJ34, and Zotatafin were found interacting with RNA binding sites as well as to predicted protein interface with higher binding energy. Overall, drug binding increases the stability of the complex with maximum stability found in the order, Silmitasertib > PJ34 > Zotatatafin. In addition, the frustration changes due to drug binding brings a decrease in local frustration and this decrease is mainly observed in α-helix, β3, β5, and β6 strands and are important for drug binding. Our in-silico data suggest that an effective interaction occurs for some of the tested drugs and prompt their further validation to reduce the rapid outspreading of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Phytocompound screening, antioxidant activity and molecular docking studies of pomegranate seed: a preventive approach for SARS-CoV-2 pathogenesis

A global hazard to public health has been generated by the coronavirus infection 2019 (COVID-19), which is spreading quickly. Pomegranate is a strong source of antioxidants and has demonstrated a number of pharmacological characteristics. This work was aimed to analyze the phytochemicals present in ethanolic pomegranate seed extract (PSE) and their in vitro antioxidant potential and further in-silico evaluation for antiviral potential against crystal structure of two nucleocapsid proteins i.e., N-terminal RNA binding domain (NRBD) and C-terminal Domain (CTD) of SARS-CoV-2. The bioactive components from ethanolic extract of PSE were assessed by gas chromatography-mass spectroscopy (GC-MS). Free radical scavenging activity of PSE was determined using DPPH dye. Molecular docking was executed through the Glide module of Maestro software. Lipinski's 5 rule was applied for drug-likeness characteristics using cheminformatics Molinspiration software while OSIRIS Data Warrior V5.5.0 was used to predict possible toxicological characteristics of components. Thirty-two phytocomponents was detected in PSE by GC-MS technique. Free radical scavenging assay revealed the high antioxidant capacity of PSE. Docking analysis showed that twenty phytocomponents from PSE exhibited good binding affinity (Docking score ≥ - 1.0 kcal/mol) towards NRBD and CTD nucleocapsid protein. This result increases the possibility that the top 20 hits could prevent the spread of SARS-CoV-2 by concentrating on both nucleocapsid proteins. Moreover, molecular dynamics (MD) simulation using GROMACS was used to check their binding efficacy and internal dynamics of top complexes with the lowest docking scores. The metrics root mean square deviation (RMSD), root mean square fluctuation (RMSF), intermolecular hydrogen bonding (H-bonds) and radius of gyration (Rg) revealed that the lead phytochemicals form an energetically stable complex with the target protein. Majority of the phytoconstituents exhibited drug-likeness with non-tumorigenic properties. Thus, the PSE phytoconstituents could be useful source of drug or nutraceutical development in SARS-CoV-2 pathogenesis.

Delineating Conformational Variability in Small Protein Structures Using Combinatorial Refinement Strategies

As small protein assemblies and even small proteins are becoming more amenable to cryo-Electron Microscopy (EM) structural studies, it is important to consider the complementary dynamic information present in the data. Current computational strategies are limited in their ability to resolve minute differences among low molecular weight entities. Here, we demonstrate a new combinatorial approach to delineate flexible conformations among small proteins using real-space refinement applications. We performed a meta-analysis of structural data for the SARS CoV-2 Nucleocapsid (N) protein using a combination of rigid-body refinement and simulated annealing methods. For the N protein monomer, we determined three new flexible conformers with good stereochemistry and quantitative comparisons provided new evidence of their dynamic properties. A similar analysis performed for the N protein dimer showed only minor structural differences among the flexible models. These results suggested a more stable view of the N protein dimer than the monomer structure. Taken together, the new computational strategies can delineate conformational changes in low molecular weight proteins that may go unnoticed by conventional assessments. The results also suggest that small proteins may be further stabilized for structural studies through the use of solution components that limit the movement of external flexible regions.

Structural communication fingerprinting and dynamic investigation of RBD-hACE2 complex from BA.1 × AY.4 recombinant variant (Deltacron) of SARS-CoV-2 to decipher the structural basis for enhanced transmission

The BA.1 × AY.4 recombinant variant (Deltacron) continues to inflict chaos globally due to its rapid transmission and infectivity. To decipher the mechanism of pathogenesis by the BA.1 × AY.4 recombinant variant (Deltacron), a protein coupling, protein structural graphs (PSG), residue communication and all atoms simulation protocols were used. We observed that the bonding network is altered by this variant; engaging new residues that helps to robustly bind. HADDOCK docking score for the wild type has been previously reported to be -111.8 ± 1.5 kcal/mol while the docking score for the Deltacron variant was calculated to be -128.3 ± 2.5 kcal/mol. The protein structural graphs revealed variations in the hub residues, number of nodes, inter and intra residues communities, and path communication perturbation caused by the acquired mutations in the Deltacron-RBD thus alter the binding approach and infectivity. Moreover, the dynamic behaviour reported a highly flexible structure with enhanced residues flexibility particularly by the loops required for interaction with ACE2. It was observed that these mutations have altered the secondary structure of the RBD mostly transited to the loops thus acquired higher flexible dynamics than the native structure during the simulation. The total binding free energy for each of these complexes, that is, WT-RBD and Deltacron-RBD were reported to be -61.38 kcal/mol and -70.47 kcal/mol. Protein's motion revealed a high trace value in the Deltacron variant that clearly depict more structural flexibility. The broad range of phase space covered by the Deltacron variant along PC1 and PC2 suggests that these mutations are important in contributing conformational heterogeneity or flexibility that consequently help the variant to bind more efficiently than the wild type. The current study provides a basis for structure-based drug designing against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

A systematic review on impact of SARS-CoV-2 infection

Innumerable pathogens including RNA viruses have catastrophic pandemic propensity, in turn, SARS-CoV-2 infection is highly contagious. Emergence of SARS-CoV-2 variants with high mutation rate additionally codifies infectious ability of virus and arisen clinical imputations to human health. Although, our knowledge of mechanism of virus infection and its impact on host system has been substantially demystified, uncertainties about the emergence of virus are still not fully understood. To date, there are no potentially curative drugs are identified against the viral infection. Even though, drugs are repurposed in the initial period of infection, many are significantly negative in clinical trials. Moreover, the infection is dependent on organ status, co-morbid conditions, variant of virus and geographic region. This review article aims to comprehensively describe the SARS-CoV-2 infection and the impacts in the host cellular system. This review also briefly provides an overview of genome, proteome and metabolome associated risk to infection and the advancement of therapeutics in SARS-CoV-2 infection management.

SARS-CoV-2 nucleocapsid: Biological functions and implication for disease diagnosis and vaccine design

The coronavirus disease 2019 (COVID-19) pandemic is transmitted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has affected millions of people all around the world, leading to more than 6.5 million deaths. The nucleocapsid (N) phosphoprotein plays important roles in modulating viral replication and transcription, virus-infected cell cycle progression, apoptosis, and regulation of host innate immunity. As an immunodominant protein, N protein induces strong humoral and cellular immune responses in COVID-19 patients, making it a key marker for studying N-specific B cell and T cell responses and the development of diagnostic serological assays and efficient vaccines. In this review, we focus on the structural and functional features and the kinetic and epitope mapping of B cell and T cell responses against SARS-CoV-2 N protein to extend our understanding on the development of sensitive and specific diagnostic immunological tests and effective vaccines.

Attenuation of Lipopolysaccharide-Induced Inflammatory Responses through Inhibition of the NF-κB Pathway and the Increased NRF2 Level by a Flavonol-Enriched n-Butanol Fraction from Uvaria alba

Pathologic hyperreactive inflammatory responses occur when there is excessive activation of a proinflammatory NF-κB pathway and a reduced cytoprotective NRF2 cascade. The noncytotoxic, highly selective COX-2 inhibitory flavonol-enriched butanol fraction (UaB) from Uvaria alba (U. alba) was investigated for its inflammatory modulating potential by targeting NF-κB activation and NRF2 activity. Enzyme-linked immunosorbent assay was initially performed to measure levels of proinflammatory mediators [nitric oxide (NO), prostaglandin E₂, and reactive oxygen species (ROS)] and cytokines [tumor necrosis factor-alpha (TNF-α), IL-1β, and IL-6], followed by reverse transcription-polymerase chain reaction and western blotting to determine mRNA and protein expression, respectively. Using immunofluorescence staining combined with western blot analysis, the activation of NF-κB was further investigated. NRF2 activity was also measured using a luciferase reporter assay. UaB abrogated protein and mRNA expressions of inducible nitric oxide synthase (iNOS), COX-2, TNF-α, IL-1β, and IL-6 in RAW 264.7 macrophages, thereby suppressing the production of proinflammatory mediators and cytokines. This was further validated when a concentration-dependent decrease in NO and ROS production was observed in zebrafish (Danio rerio) larvae. UaB also increased NRF2 activity in HaCaT/ARE cell line and attenuated NF-κB activation by inhibiting the nuclear translocation of transcription factor p65 in RAW 264.7 macrophages. Nontargeted LC-MS analysis of UaB revealed the presence of the flavonols quercitrin (1), quercetin (2), rutin (3), kaempferol (4), and kaempferol 3-O-rutinoside (5). Molecular docking indicates that major flavonol aglycones have high affinity toward COX-2 NSAID-binding sites, TNF-α, and TNF-α converting enzyme, while the glycosylated flavonoids showed strong binding toward iNOS and IKK-all possessing dynamic stability when performing molecular dynamics simulations at 140 ns. This is the first report to have elucidated the mechanistic anti-inflammatory potential of the Philippine endemic plant U. alba.

Identification of a novel linear B-cell epitope in porcine deltacoronavirus nucleocapsid protein

Porcine deltacoronavirus (PDCoV) is an emerging swine enteropathogenic coronavirus that caused diarrhea and/or vomiting in neonatal piglets worldwide. Coronaviruses nucleocapsid (N) protein is the most conserved structural protein for viral replication and possesses good antigenicity. In this study, three monoclonal antibodies (mAbs), 3B4, 4D3, and 4E3 identified as subclass IgG2aκ were prepared using the lymphocytic hybridoma technology against PDCoV N protein. Furthermore, the B-cell epitope recognized by mAb 4D3 was mapped by dozens of overlapping truncated recombinant proteins based on the western blotting. The polypeptide 28QFRGNGVPLNSAIKPVE44 (EP-4D3) in the N-terminal of PDCoV N protein was identified as the minimal linear epitope for binding mAb 4D3. And the EP-4D3 epitope's amino acid sequence homology study revealed that PDCoV strains are substantially conserved, with the exception of the Alanine43 substitution Valine43 in the China lineage, the Early China lineage, and the Thailand, Vietnam, and Laos lineage. The epitope sequences shared high similarity (94.1%) with porcine coronavirus HKU15-155 (PorCoV HKU15), Asian leopard cats coronavirus (ALCCoV), sparrow coronavirus HKU17 (SpCoV HKU17), and sparrow deltacoronavirus. In contrast, the epitope sequences shared a very low homology (11.8 to 29.4%) with other porcine CoVs (PEDV, TGEV, PRCV, SADS-CoV, PHEV). Overall, the study will enrich the biological function of PDCoV N protein and provide foundational data for further development of diagnostic applications. KEY POINTS: • Three monoclonal antibodies against PDCoV N protein were prepared. • Discovery of a novel B-cell liner epitope (28QFRGNGVPLNSAIKPVE44) of PDCoV N protein. • The epitope EP-4D3 was conserved among PDCoV strains.

Liquid-liquid phase separation of nucleocapsid proteins during SARS-CoV-2 and HIV-1 replication

The leap of retroviruses and coronaviruses from animal hosts to humans has led to two ongoing pandemics and tens of millions of deaths worldwide. Retrovirus and coronavirus nucleocapsid proteins have been studied extensively as potential drug targets due to their central roles in virus replication, among which is their capacity to bind their respective genomic RNAs for packaging into nascent virions. This review focuses on fundamental studies of these nucleocapsid proteins and how their intrinsic abilities to condense through liquid-liquid phase separation (LLPS) contribute to viral replication. Therapeutic targeting of these condensates and methodological advances are also described to address future questions on how phase separation contributes to viral replication.

Mutational analysis of the spike protein of SARS-COV-2 isolates revealed atomistic features responsible for higher binding and infectivity

Introduction: The perpetual appearance of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2), and its new variants devastated the public health and social fabric around the world. Understanding the genomic patterns and connecting them to phenotypic attributes is of great interest to devise a treatment strategy to control this pandemic. Materials and Methods: In this regard, computational methods to understand the evolution, dynamics and mutational spectrum of SARS-CoV-2 and its new variants are significantly important. Thus, herein, we used computational methods to screen the genomes of SARS-CoV-2 isolated from Pakistan and connect them to the phenotypic attributes of spike protein; we used stability-function correlation methods, protein-protein docking, and molecular dynamics simulation. Results: Using the Global initiative on sharing all influenza data (GISAID) a total of 21 unique mutations were identified, among which five were reported as stabilizing while 16 were destabilizing revealed through mCSM, DynaMut 2.0, and I-Mutant servers. Protein-protein docking with Angiotensin-converting enzyme 2 (ACE2) and monoclonal antibody (4A8) revealed that mutation G446V in the receptor-binding domain; R102S and G181V in the N-terminal domain (NTD) significantly affected the binding and thus increased the infectivity. The interaction pattern also revealed significant variations in the hydrogen bonding, salt bridges and non-bonded contact networks. The structural-dynamic features of these mutations revealed the global dynamic trend and the finding energy calculation further established that the G446V mutation increases the binding affinity towards ACE2 while R102S and G181V help in evading the host immune response. The other mutations reported supplement these processes indirectly. The binding free energy results revealed that wild type-RBD has a TBE of -60.55 kcal/mol while G446V-RBD reported a TBE of -73.49 kcal/mol. On the other hand, wild type-NTD reported -67.77 kcal/mol of TBE, R102S-NTD reported -51.25 kcal/mol of TBE while G181V-NTD reported a TBE of -63.68 kcal/mol. Conclusions: In conclusion, the current findings revealed basis for higher infectivity and immune evasion associated with the aforementioned mutations and structure-based drug discovery against such variants.

An insight into the simulation directed understanding of the mechanism in SARS CoV-2 N-CTD, dimer integrity, and RNA-binding: Identifying potential antiviral inhibitors

Coronavirus 2019 is a transmissible disease and has caused havoc throughout the world. The present study identifies the novel potential antiviral inhibitors against the nucleocapsid C-terminal domain that aids in RNA-binding and replication. A total of 485,629 compounds were screened, and MD was performed. The trajectory analysis (DCCM & PCA), structural integrity, and degree of compaction depicted the protein-ligand complex stability (PDB-PISA and R_gyr). Results obtained from screening shortlists 13 compounds possessing high Docking score. Further, seven compounds had a permissible RMSD limit (3 Å), with robust RMSF. Post-MD analysis of the top two compounds (204 and 502), DCCM & PCA analysis show a positive atomic displacements correlation among residues of active sites-dimer (Chain A and Chain B) & residual clustering. The ΔG_int of RNA-bound (-83.5 kcal/mol) and drug-bound N-CTD-204 (-40.8 kcal/mol) and 502(-39.7 kcal/mol) as compared to Apo (-35.95 kcal/mol) suggests stabilization of protein, with less RNA-binding possibility. The R_gyr values depict the loss of compactness on RNA-binding when compared to the drug-bound N-CTD complex. Further, overlapping the protein complexes (0 ns and 100 ns) display significant changes in RMSD of the protein (204-2.07 Å and 502-1.89 Å) as compared to the Apo (1.72 Å) and RNA-bound form (1.76 Å), suggesting strong interaction for compound 204 as compared to 502. ADMET profiling indicates that these compounds can be used for further experiments (in vitro and pre-clinical). Compound 204 could be a promising candidate for targeting the N-protein-RNA assembly and viral replication.

Synthesis, Biological Evaluation, and Molecular Dynamics of Carbothioamides Derivatives as Carbonic Anhydrase II and 15-Lipoxygenase Inhibitors

A series of hydrazine-1-carbothioamides derivatives (3a-3j) were synthesized and analyzed for inhibitory potential towards bovine carbonic anhydrase II (b-CA II) and 15-lipoxygenase (15-LOX). Interestingly, four derivatives, 3b, 3d, 3g, and 3j, were found to be selective inhibitors of CA II, while other derivatives exhibited CA II and 15-LOX inhibition. In silico studies of the most potent inhibitors of both b-CA II and 15-LOX were carried out to find the possible binding mode of compounds in their active site. Furthermore, MD simulation results confirmed that these ligands are stably bound to the two targets, while the binding energy further confirmed the inhibitory effects of the 3h compound. As these compounds may have a role in particular diseases, the reported compounds are of great relevance for future applications in the field of medicinal chemistry.

Sequence-structure functional implications and molecular simulation of high deleterious nonsynonymous substitutions in IDH1 revealed the mechanism of drug resistance in glioma

In the past few years, various somatic point mutations of isocitrate dehydrogenase (IDH) encoding genes (IDH1 and IDH2) have been identified in a broad range of cancers, including glioma. Despite the important function of IDH1 in tumorigenesis and its very polymorphic nature, it is not yet clear how different nsSNPs affect the structure and function of IDH1. In the present study, we employed different machine learning algorithms to screen nsSNPs in the IDH1 gene that are highly deleterious. From a total of 207 SNPs, all of the servers classified 80 mutations as deleterious. Among the 80 deleterious mutations, 14 were reported to be highly destabilizing using structure-based prediction methods. Three highly destabilizing mutations G15E, W92G, and I333S were further subjected to molecular docking and simulation validation. The docking results and molecular simulation analysis further displayed variation in dynamics features. The results from molecular docking and binding free energy demonstrated reduced binding of the drug in contrast to the wild type. This, consequently, shows the impact of these deleterious substitutions on the binding of the small molecule. PCA (principal component analysis) and FEL (free energy landscape) analysis revealed that these mutations had caused different arrangements to bind small molecules than the wild type where the total internal motion is decreased, thus consequently producing minimal binding effects. This study is the first extensive in silico analysis of the IDH1 gene that can narrow down the candidate mutations for further validation and targeting for therapeutic purposes.

Intrinsically disordered proteins in viral pathogenesis and infections

Disordered proteins serve a crucial part in many biological processes that go beyond the capabilities of ordered proteins. A large number of virus-encoded proteins have extremely condensed proteomes and genomes, which results in highly disordered proteins. The presence of these IDPs allows them to rapidly adapt to changes in their biological environment and play a significant role in viral replication and down-regulation of host defense mechanisms. Since viruses undergo rapid evolution and have a high rate of mutation and accumulation in their proteome, IDPs' insights into viruses are critical for understanding how viruses hijack cells and cause disease. There are many conformational changes that IDPs can adopt in order to interact with different protein partners and thus stabilize the particular fold and withstand high mutation rates. This chapter explains the molecular mechanism behind viral IDPs, as well as the significance of recent research in the field of IDPs, with the goal of gaining a deeper comprehension of the essential roles and functions played by viral proteins.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Structural and Dynamic Investigation of non-synonymous variations in Renin-AGT complex revealed altered binding via hydrogen bonding network reprogramming to accelerate the hypertension pathway

Hypertension is one of the major issues worldwide and one of the main factors involved in heart and kidney failure. Angiotensinogen and renin are key components of the renin-angiotensin-aldosterone system (RAAS), which plays an indispensable role in hypertension. The aimed of this study to find out the non-synonymous mutations and structure-based mutation-function correlation in the Renin-AGT complex and reveal the most deleterious mutations to accelerated hypertension. In the current study, we employed computational modelling and molecular simulation approaches to demonstrate the impact of specific mutations in the REN-AGT interface in hypertension. Computational algorithms i.e. PhD-SNP, PolyPhen-1, MAPP, SIFT, SNAP, PredictSNP, PolyPhen-2, and PANTHER predicted 20 mutations as deleterious in AGT while only five mutations were conformed as deleterious in the Renin protein. Investigation of the bonding analysis revealed that two mutations S107L and V193F in Renin altered the hydrogen-bonding paradigm at the interface site. Furthermore, exploration of structural-dynamic behaviors demonstrated by that these mutations also increases the structural stability to regulate the expression of disease pathway. The flexibility index of each residues and structural compactness analysis further validated the findings by portraying the difference in the dynamic behavior in contrast to the wild type. Binding energy calculations based on molecular mechanics/generalized Born surface area (MM/GBSA) methods were used which further established the binding differences between the wild type, S107L, and V193F mutant variants. The total binding energy for wild type, S107L, and V193F were reported to be -27.79 kcal/mol, -47.72 kcal/mol, and -38.25 kcal/mol respectively. In conclusion, these two mutations increase the binding free energy alongside the docking score to enhance the binding between Renin and AGT to overexpress this pathway in a hypertension disease condition. Patients with these mutations may be screened for potential therapeutic intervention.

Computational Investigations of Traditional Chinese Medicinal Compounds against the Omicron Variant of SARS-CoV-2 to Rescue the Host Immune System

Macrodomain-I of the NSP3 (non-structural protein 3) is responsible for immune response hijacking in the SARS-CoV-2 infection known as COVID-19. In the omicron variant (B.1.1.529), this domain harbors a new mutation, V1069I, which may increase the binding of ADPr and consequently the infection severity. This macrodomain-I, due to its significant role in infection, is deemed to be an important drug target. Hence, using structural bioinformatics and molecular simulation approaches, we performed a virtual screening of the traditional Chinese medicines (TCM) database for potential anti-viral drugs. The screening of 57,000 compounds yielded the 10 best compounds with docking scores better than the control ADPr. Among the top ten, the best three hits—TCM42798, with a docking score of −13.70 kcal/mol, TCM47007 of −13.25 kcal/mol, and TCM30675 of −12.49 kcal/mol—were chosen as the best hits. Structural dynamic features were explored including stability, compactness, flexibility, and hydrogen bonding, further demonstrating the anti-viral potential of these hits. Using the MM/GBSA approach, the total binding free energy for each complex was reported to be −69.78 kcal/mol, −50.11 kcal/mol, and −47.64 kcal/mol, respectively, which consequently reflect the stronger binding and inhibitory potential of these compounds. These agents might suppress NSP3 directly, allowing the host immune system to recuperate. The current study lays the groundwork for the development of new drugs to combat SARS-CoV-2 and its variants.

Repositioning of experimentally validated anti-breast cancer peptides to target FAK-PAX complex to halt the breast cancer progression: a biomolecular simulation approach

FAK (focal adhesin kinase), a tyrosine kinase, plays an imperative role in cell-cell communication, particularly in cell signaling systems. It is a multi-functional signaling protein, which integrates and transduces signals into cancer cells through growth factor receptors or integrin and its interaction with Paxillin (PAX). The molecular processes by which FAK promotes the development and progression of cancer have progressively established the possible relationship between FAK-PAX complex in many types of cancer. The interaction of FAX and PAX is very important in breast cancer and thus acts as an essential biomarker for drugs, vaccines or peptide inhibitor designing. In this regard, computational approaches, particularly peptide designing to target the binding interface of the interacting partners, would greatly assist the design of peptide inhibitors against various cancer. Accordingly, in this present study, we screened 236 experimentally validated anti-breast cancer peptides using computational drugs repositioning approach to design peptides targeting the FAK-PAX complex. Using protein-peptide docking the binding site for the HP1 was confirmed and a total of 236 anti-breast cancer peptides were screened. Among the 236, only 12 peptides reported a docking score better than the control. From these 12, Magainin with the docking score - 103.8 ± 10.3 kcal/mol, NRC-07 with the docking score - 100.8 ± 16.5 kcal/mol, and Indolicidin with the docking score - 101.7 ± 3.9 kcal/mol, peptides potentially inhibit the FAX-PAX binding. Calculation of protein's motion and FEL revealed the binding and inhibitory behavior. Moreover, binding free energy (MM/GBSA) confirmed that Magainin exhibited the total binding energy - 53.28 kcal/mol, NRC-07 possessed the TBE - 44.16 kcal/mol, and Indolicidin reported the TBE of - 40.48 kcal/mol, thus explaining the inhibitory potential of these peptides. In conclusion, these peptides exhibit strong inhibitory potential and could abrogate the FAK-PAX complex in in vitro models and thus may relieve the burden of breast cancer.

Characterization of proteome wide antigenic epitopes to design proteins specific and proteome-wide ensemble vaccines against heartland virus using structural vaccinology and immune simulation approaches

Heartland virus is a single-stranded negative-sense RNA virus that infects humans and causes lethargy, myalgia, headaches, nausea, diarrhea, weight loss, arthralgia, loss of appetite, leukopenia, and easy bruising due thrombocytopenia. The unavailability of antiviral drugs for HRTV infection is a major obstacle to treat this infection, therefore supportive care management is adopted in the case of a severe ailment. In this scientific study, proteins specific and proteome-wide Helper T-cell (HTL), linear B cell, and cytotoxic T-cell (CTL) epitopes mapping joined together with suitable linkers to design multi-epitopes subunit vaccine (MEVC). The constructed four vaccines from nucleocapsid protein, replicase, glycoprotein and finally whole proteome-wide constructs demonstrated stronger antigenic and non-allergenic behavior. Physiochemical properties evaluation also reported easy and efficient expression and downstream analysis of the constructs. Molecular docking of these constructs with toll-like receptor 7 (TLR7) revealed good binding and further validation based on MM/GBSA also demonstrated stronger interaction between the vaccine constructs and TLR7. Moreover, in silico cloning reported CAI value of 0.96 for each construct and excellent GC contents percentage required for experimental analysis. Furthermore, immune simulation-based immune response surveillance revealed that upon the injection of antigen the primary and secondary antibodies were produced between 5-15 days, and a more robust neutralization of the antigen by the proteome-wide vaccine construct was observed. This research could pave the way for the development of dynamic and efficient vaccines that contain a unique mix of numerous HRTV derived antigenic peptides to control HRTV infection.

Core amino acid substitutions in HCV-3a isolates from Pakistan and opportunities for multi-epitopic vaccines

Hepatitis C virus (HCV), which infected 71 million worldwide and about 5%-6% are from Pakistan, is an ssRNA virus, responsible for end-stage liver disease. To date, no effective therapy is available to cure this disease. Hence, it is important to study the most prevalent genotypes infecting human population and design novel vaccine or small molecule inhibitors to control the infections associated with HCV. Therefore, in this study clinical samples (n = 35; HCV-3a) from HCV patients were subjected to Sanger sequencing method. The sequencing of the core gene, which is generally considered as conserved, involved in the detection, quantitation and genotyping of HCV was performed. Multiple mutations, that is, R46C, R70Q, L91C, G60E, N/S105A, P108A, N110I, S116V, G90S, A77G and G145R that could be linked with response to antiviral therapies were detected. Phylogenetic analysis suggests emerging viral isolates are circulating in Pakistan. Using ab initio modelling technique, we predicted the 3D structure of core protein and subjected to molecular dynamics simulation to extract the most stable conformation of the structure for further analysis. Immunoinformatic approaches were used to propose a multi-epitopes vaccine against HCV by using core protein. The vaccine constructs consist of nine CTL and three HTL epitopes joined by different linkers were docked against the two reported Toll-like receptors (TLR-3 and TLR-8). Docking of vaccine construct with TLR-3 and TLR-8 shows proper binding and in silico expression of the vaccine resulted in a CAI value of 0.93. These analyses suggest that specific immune responses may be produced by the proposed vaccine.Communicated by Ramaswamy H. Sarma.

Antiviral activities of 4H-chromen-4-one scaffold-containing flavonoids against SARS-CoV-2 using computational and in vitro approaches

The widespread outbreak of the novel coronavirus called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused the main health challenge worldwide. This pandemic has attracted the attention of the research communities in various fields, prompting efforts to discover rapid drug molecules for the treatment of the life-threatening COVID-19 disease. This study is aimed at investigating 4H-chromen-4-one scaffold-containing flavonoids that combat the SARS-CoV-2 virus using computational and in vitro approaches. Virtual screening studies of the molecule's library for 4H-chromen-4-one scaffold were performed with the recently reported coronavirus main protease (M^pro, also called 3CL^pro) because it plays an essential role in the maturation and processing of the viral polyprotein. Based on the virtual screening, the top hit molecules such as isoginkgetin and afzelin molecules were selected for further estimating in vitro antiviral efficacies against SARS-CoV-2 in Vero cells. Additionally, these molecules were also docked with RNA-dependent RNA Polymerase (RdRp) to reveal the ligands-protein molecular interaction. In the in vitro study, isoginkgetin showed remarkable inhibition potency against the SARS-CoV-2 virus, with an IC₅₀ value of 22.81 μM, compared to remdesivir, chloroquine, and lopinavir with IC₅₀ values of 7.18, 11.63, and 11.49 μM, respectively. Furthermore, the complex stability of isoginkgetin with an active binding pocket of the SARS-CoV-2 M^pro and RdRp supports its inhibitory potency against the SARS-CoV-2. Thus, isoginkgetin is a potent leading drug candidate and needs to be used in in vivo trials for the treatment of SARS-CoV-2 infected patients.

Crystal structure of Acetyl-CoA carboxylase (AccB) from Streptomyces antibioticus and insights into the substrate-binding through in silico mutagenesis and biophysical investigations

Acetyl-CoA carboxylase (ACC) is crucial for polyketides biosynthesis and acts as an essential metabolic checkpoint. It is also an attractive drug target against obesity, cancer, microbial infections, and diabetes. However, the lack of knowledge, particularly sequence-structure function relationship to narrate ligand-enzyme binding, has hindered the progress of ACC-specific therapeutics and unnatural "natural" polyketides. Structural characterization of such enzymes will boost the opportunity to understand the substrate binding, designing new inhibitors and information regarding the molecular rules which control the substrate specificity of ACCs. To understand the substrate specificity, we determined the crystal structure of AccB (Carboxyl-transferase, CT) from Streptomyces antibioticus with a resolution of 2.3 Å and molecular modeling approaches were employed to unveil the molecular mechanism of acetyl-CoA recognition and processing. The CT domain of S. antibioticus shares a similar structural organization with the previous structures and the two steps reaction was confirmed by enzymatic assay. Furthermore, to reveal the key hotspots required for the substrate recognition and processing, in silico mutagenesis validated only three key residues (V223, Q346, and Q514) that help in the fixation of the substrate. Moreover, we also presented atomic level knowledge on the mechanism of the substrate binding, which unveiled the terminal loop (500-514) function as an opening and closing switch and pushes the substrate inside the cavity for stable binding. A significant decline in the hydrogen bonding half-life was observed upon the alanine substitution. Consequently, the presented structural data highlighted the potential key interacting residues for substrate recognition and will also help to re-design ACCs active site for proficient substrate specificity to produce diverse polyketides.

Elucidation of the conformational dynamics and assembly of Argonaute-RNA complexes by distinct yet coordinated actions of the supplementary microRNA

Argonaute (AGO) proteins, the core of RNA-induced silencing complex, are guided by microRNAs (miRNAs) to recognize target RNA for repression. The miRNA-target RNA recognition forms initially through pairing at the seed region while the additional supplementary pairing can enhance target recognition and compensate for seed mismatch. The extension of miRNA lengths can strengthen the target affinity when pairing both in the seed and supplementary regions. However, the mechanism underlying the effect of the supplementary pairing on the conformational dynamics and the assembly of AGO-RNA complex remains poorly understood. To address this, we performed large-scale molecular dynamics simulations of AGO-RNA complexes with different pairing patterns and miRNA lengths. The results reveal that the additional supplementary pairing can not only strengthen the interaction between miRNA and target RNA, but also induce the increased plasticity of the PAZ domain and enhance the domain connectivity among the PAZ, PIWI, N domains of the AGO protein. The strong community network between these domains tightens the mouth of the supplementary chamber of AGO protein, which prevents the escape of target RNA from the complex and shields it from solvent water attack. Importantly, the inner stronger matching pairs between the miRNA and target RNA can compensate for weaker mismatches at the edge of supplementary region. These findings provide guidance for the design of miRNA mimics and anti-miRNAs for both clinical and experimental use and open the way for further engineering of AGO proteins as a new tool in the field of gene regulation.

The Omicron (B.1.1.529) variant of SARS-CoV-2 binds to the hACE2 receptor more strongly and escapes the antibody response: Insights from structural and simulation data

As SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) continues to inflict chaos globally, a new variant officially known as B.1.1.529 was reported in South Africa and was found to harbor 30 mutations in the spike protein. It is too early to speculate on transmission and hospitalizations. Hence, more analyses are required, particularly to connect the genomic patterns to the phenotypic attributes to reveal the binding differences and antibody response for this variant, which can then be used for therapeutic interventions. Given the urgency of the required analysis and data on the B.1.1.529 variant, we have performed a detailed investigation to provide an understanding of the impact of these novel mutations on the structure, function, and binding of RBD to hACE2 and mAb to the NTD of the spike protein. The differences in the binding pattern between the wild type and B.1.1.529 variant complexes revealed that the key substitutions Asn417, Ser446, Arg493, and Arg498 in the B.1.1.529 RBD caused additional interactions with hACE2 and the loss of key residues in the B.1.1.529 NTD resulted in decreased interactions with three CDR regions (1-3) in the mAb. Further investigation revealed that B.1.1.529 displayed a stable dynamic that follows a global stability trend. In addition, the dissociation constant (K_D), hydrogen bonding analysis, and binding free energy calculations further validated the findings. Hydrogen bonding analysis demonstrated that significant hydrogen bonding reprogramming took place, which revealed key differences in the binding. The total binding free energy using MM/GBSA and MM/PBSA further validated the docking results and demonstrated significant variations in the binding. This study is the first to provide a basis for the higher infectivity of the new SARS-CoV-2 variants and provides a strong impetus for the development of novel drugs against them.

Discovery of Potential Therapeutic Drugs for COVID-19 Through Logistic Matrix Factorization With Kernel Diffusion

Coronavirus disease 2019 (COVID-19) is rapidly spreading. Researchers around the world are dedicated to finding the treatment clues for COVID-19. Drug repositioning, as a rapid and cost-effective way for finding therapeutic options from available FDA-approved drugs, has been applied to drug discovery for COVID-19. In this study, we develop a novel drug repositioning method (VDA-KLMF) to prioritize possible anti-SARS-CoV-2 drugs integrating virus sequences, drug chemical structures, known Virus-Drug Associations, and Logistic Matrix Factorization with Kernel diffusion. First, Gaussian kernels of viruses and drugs are built based on known VDAs and nearest neighbors. Second, sequence similarity kernel of viruses and chemical structure similarity kernel of drugs are constructed based on biological features and an identity matrix. Third, Gaussian kernel and similarity kernel are diffused. Forth, a logistic matrix factorization model with kernel diffusion is proposed to identify potential anti-SARS-CoV-2 drugs. Finally, molecular dockings between the inferred antiviral drugs and the junction of SARS-CoV-2 spike protein-ACE2 interface are implemented to investigate the binding abilities between them. VDA-KLMF is compared with two state-of-the-art VDA prediction models (VDA-KATZ and VDA-RWR) and three classical association prediction methods (NGRHMDA, LRLSHMDA, and NRLMF) based on 5-fold cross validations on viruses, drugs, and VDAs on three datasets. It obtains the best recalls, AUCs, and AUPRs, significantly outperforming other five methods under the three different cross validations. We observe that four chemical agents coming together on any two datasets, that is, remdesivir, ribavirin, nitazoxanide, and emetine, may be the clues of treatment for COVID-19. The docking results suggest that the key residues K353 and G496 may affect the binding energies and dynamics between the inferred anti-SARS-CoV-2 chemical agents and the junction of the spike protein-ACE2 interface. Integrating various biological data, Gaussian kernel, similarity kernel, and logistic matrix factorization with kernel diffusion, this work demonstrates that a few chemical agents may assist in drug discovery for COVID-19.

Comparative mutational analysis of SARS-CoV-2 isolates from Pakistan and structural-functional implications using computational modelling and simulation approaches

SARS-CoV-2, an RNA virus, has been prone to high mutations since its first emergence in Wuhan, China, and throughout its spread. Its genome has been sequenced continuously by many countries, including Pakistan, but the results vary. Understanding its genomic patterns and connecting them with phenotypic features will help in devising therapeutic strategies. Thus, in this study, we explored the mutation landscape of 250 Pakistani isolates of SARS-CoV-2 genomes to check the genome diversity and examine the impact of these mutations on protein stability and viral pathogenesis in comparison with a reference sequence (Wuhan NC 045512.2). Our results revealed that structural proteins mainly exhibit more mutations than others in the Pakistani isolates; in particular, the nucleocapsid protein is highly mutated. In comparison, the spike protein is the most mutated protein globally. Furthermore, nsp12 was found to be the most mutated NSP in the Pakistani isolates and worldwide. Regarding accessory proteins, ORF3A is the most mutated in the Pakistani isolates, whereas ORF8 is highly mutated in world isolates. These mutations decrease the structural stability of their proteins and alter different biological pathways. Molecular docking, the dissociation constant (KD), and MM/GBSA analysis showed that mutations in the S protein alter its binding with ACE2. The spike protein mutations D614G-S943T-V622F (-75.17 kcal/mol), D614G-Q677H (-75.78 kcal/mol), and N74K-D614G (-73.84 kcal/mol) exhibit stronger binding energy than the wild type (-66.34 kcal/mol), thus increasing infectivity. Furthermore, the simulation results strongly corroborated the predicted protein servers. Our analysis findings also showed that E, M, ORF6, ORF7A, ORF7B, and ORF10 are the most stable coding genes; they may be suitable targets for vaccine and drug development.

Computational modelling of potentially emerging SARS-CoV-2 spike protein RBDs mutations with higher binding affinity towards ACE2: A structural modelling study

The spike protein of SARS-CoV-2 and the host ACE2 receptor plays a vital role in the entry to the cell. Among which the hotspot residue 501 is continuously subjected to positive selection pressure and induces unusual virulence. Keeping in view the importance of the hot spot residue 501, we predicted the potentially emerging structural variants of 501 residue. We analyzed the binding pattern of wild type and mutants (Spike RBD) to the ACE2 receptor by deciphering variations in the amino acids' interaction networks by graph kernels along with evolutionary, network metrics, and energetic information. Our analysis revealed that N501I, N501T, and N501V increase the binding affinity and alter the intra and inter-residue bonding networks. The N501T has shown strong positive selection and fitness in other animals. Docking results and repeated simulations (three times) confirmed the structural stability and tighter binding of these three variants, correlated with the previous results following the global stability trend. Consequently, we reported three variants N501I, N501T, and N501V could worsen the situation further if they emerged. The relations between the viral fitness and binding affinity is a complicated game thus the emergence of high affinity mutations in the SARS-CoV-2 RBD brings up the question of whether or not positive selection favours these mutations or not?

Structural and Dynamic Insights into the W68L, L85P, and T87A Mutations of Mycobacterium tuberculosis Inducing Resistance to Pyrazinamide

Tuberculosis (TB), the most frequent bacterium-mediated infectious disease caused by Mycobacterium tuberculosis, has been known to infect humans since ancient times. Although TB is common worldwide, the most recent report by the WHO (World Health Organization) listed the three countries of India, China, and Russia with 27%, 14%, and 8% of the global burden of TB, respectively. It has been reported that resistance to TB drugs, particularly by the pncA gene to the pyrazinamide drug due to mutations, significantly affects the effective treatment of TB. Understanding the mechanism of drug resistance using computational methods is of great interest to design effective TB treatment, exploring the structural features with these tools. Thus, keeping in view the importance of these methods, we employed state-of-the-art computational methods to study the mechanism of resistance caused by the W68L, L85P, and T87A mutations recently reported in 2021. We employed a molecular docking approach to predict the binding conformation and studied the dynamic properties of each complex using molecular dynamics simulation approaches. Our analysis revealed that compared to the wildtype, these three mutations altered the binding pattern and reduced the binding affinity. Moreover, the structural dynamic features also showed that these mutations significantly reduced the structural stability and packing, particularly by the W68L and L85P mutations. Moreover, principal component analysis, free energy landscape, and the binding free energy results revealed variation in the protein's motion and the binding energy. The total binding free energy was for the wildtype -9.61 kcal/mol, W68L -7.57 kcal/mol, L85P -6.99 kcal/mol, and T87A -7.77 kcal/mol. Our findings can help to design a structure-based drug against the MDR (multiple drug-resistant) TB.

Probing the Formation, Structure and Free Energy Relationships of M Protein Dimers of SARS-CoV-2

The M protein of the novel coronavirus 2019 (SARS-CoV-2) is the major structural component of the viral envelope and is also the minimum requirement for virus particle budding. M proteins generally exist as dimers. In virus assembly, they are the main driving force for envelope formation through lateral interactions and interactions with other viral structural proteins that play a central role. We built 100 candidate models and finally analyzed the six most convincing structural features of the SARS-CoV-2 M protein dimer based on long-timescale molecular dynamics (MD) simulations, multiple free energy analyses (potential mean force (PMF) and molecular mechanics Poisson-Boltzmann surface area (MMPBSA)) and principal component analysis (PCA) to obtain the most reasonable structure. The dimer stability was found to depend on the Leu-Ile zipper motif and aromatic amino acids in the transmembrane domain (TMD). Furthermore, the C-terminal domain (CTD) effects were relatively small. These results highlight a model in which there is sufficient binding affinity between the TMDs of M proteins to form dimers through the residues at the interface of the three transmembrane helices (TMHs). This study aims to help find more effective inhibitors of SARS-CoV-2 M dimers and to develop vaccines based on structural information.

Drug similarity and structure-based screening of medicinal compounds to target macrodomain-I from SARS-CoV-2 to rescue the host immune system: a molecular dynamics study

The outbreak of the recent coronavirus (SARS-CoV-2), which causes a severe pneumonia infection, first identified in Wuhan, China, imposes significant risks to public health. Around the world, researchers are continuously trying to identify small molecule inhibitors or vaccine candidates by targeting different drug targets. The SARs-CoV-2 macrodomain-I, which helps in viral replication and hijacking the host immune system, is also a potential drug target. Hence, this study targeted viral macrodomain-I by using drug similarity, virtual screening, docking and re-docking approaches. A total of 64,043 compounds were screened, and potential hits were identified based on the docking score and interactions with the key residues. The top six hits were subjected to molecular dynamics simulation and Free energy calculations and repeated three times each. The per-residue energy decomposition analysis reported that these compounds significantly interact with Asp22, Ala38, Asn40, Val44, Phe144, Gly46, Gly47, Leu127, Ser128, Gly130, Ile131, Phe132 and Ala155 which are the critical active site residues. Here, we also used ADPr as a positive control to compare our results. Our results suggest that our identified hits by using such a complicated computational pipeline could inhibit the SARs-CoV-2 by targeting the macrodomain-1. We strongly recommend the experimental testing of these compounds, which could rescue the host immune system and could help to contain the disease caused by SARs-CoV-2.Communicated by Ramaswamy H. Sarma.

VDA-RWLRLS: An anti-SARS-CoV-2 drug prioritizing framework combining an unbalanced bi-random walk and Laplacian regularized least squares

BACKGROUND

A new coronavirus disease named COVID-19, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is rapidly spreading worldwide. However, there is currently no effective drug to fight COVID-19.

METHODS

In this study, we developed a Virus-Drug Association (VDA) identification framework (VDA-RWLRLS) combining unbalanced bi-Random Walk, Laplacian Regularized Least Squares, molecular docking, and molecular dynamics simulation to find clues for the treatment of COVID-19. First, virus similarity and drug similarity are computed based on genomic sequences, chemical structures, and Gaussian association profiles. Second, an unbalanced bi-random walk is implemented on the virus network and the drug network, respectively. Third, the results of the random walks are taken as the input of Laplacian regularized least squares to compute the association score for each virus-drug pair. Fourth, the final associations are characterized by integrating the predictions from the virus network and the drug network. Finally, molecular docking and molecular dynamics simulation are implemented to measure the potential of screened anti-COVID-19 drugs and further validate the predicted results.

RESULTS

In comparison with six state-of-the-art association prediction models (NGRHMDA, SMiR-NBI, LRLSHMDA, VDA-KATZ, VDA-RWR, and VDA-BiRW), VDA-RWLRLS demonstrates superior VDA prediction performance. It obtains the best AUCs of 0.885 8, 0.835 5, and 0.862 5 on the three VDA datasets. Molecular docking and dynamics simulations demonstrated that remdesivir and ribavirin may be potential anti-COVID-19 drugs.

CONCLUSIONS

Integrating unbalanced bi-random walks, Laplacian regularized least squares, molecular docking, and molecular dynamics simulation, this work initially screened a few anti-SARS-CoV-2 drugs and may contribute to preventing COVID-19 transmission.

Deciphering the Mechanism of Gilteritinib Overcoming Lorlatinib Resistance to the Double Mutant I1171N/F1174I in Anaplastic Lymphoma Kinase

Anaplastic lymphoma kinase (ALK) is validated as a therapeutic molecular target in multiple malignancies, such as non-small cell lung cancer (NSCLC). However, the feasibility of targeted therapies exerted by ALK inhibitors is inevitably hindered owing to drug resistance. The emergence of clinically acquired drug mutations has become a major challenge to targeted therapies and personalized medicines. Thus, elucidating the mechanism of resistance to ALK inhibitors is helpful for providing new therapeutic strategies for the design of next-generation drug. Here, we used molecular docking and multiple molecular dynamics simulations combined with correlated and energetical analyses to explore the mechanism of how gilteritinib overcomes lorlatinib resistance to the double mutant ALK I1171N/F1174I. We found that the conformational dynamics of the ALK kinase domain was reduced by the double mutations I1171N/F1174I. Moreover, energetical and structural analyses implied that the double mutations largely disturbed the conserved hydrogen bonding interactions from the hinge residues Glu1197 and Met1199 in the lorlatinib-bound state, whereas they had no discernible adverse impact on the binding affinity and stability of gilteritinib-bound state. These discrepancies created the capacity of the double mutant ALK I1171N/F1174I to confer drug resistance to lorlatinib. Our result anticipates to provide a mechanistic insight into the mechanism of drug resistance induced by ALK I1171N/F1174I that are resistant to lorlatinib treatment in NSCLC.

In-silico design of a multi-epitope for developing sero-diagnosis detection of SARS-CoV-2 using spike glycoprotein and nucleocapsid antigens

COVID-19 is a pandemic disease caused by novel corona virus, SARS-CoV-2, initially originated from China. In response to this serious life-threatening disease, designing and developing more accurate and sensitive tests are crucial. The aim of this study is designing a multi-epitope of spike and nucleocapsid antigens of COVID-19 virus by bioinformatics methods. The sequences of nucleotides obtained from the NCBI Nucleotide Database. Transmembrane structures of proteins were predicted by TMHMM Server and the prediction of signal peptide of proteins was performed by Signal P Server. B-cell epitopes' prediction was performed by the online prediction server of IEDB server. Beta turn structure of linear epitopes was also performed using the IEDB server. Conformational epitope prediction was performed using the CBTOPE and eventually, eight antigenic epitopes with high physicochemical properties were selected, and then, all eight epitopes were blasted using the NCBI website. The analyses revealed that α-helices, extended strands, β-turns, and random coils were 28.59%, 23.25%, 3.38%, and 44.78% for S protein, 21.24%, 16.71%, 6.92%, and 55.13% for N Protein, respectively. The S and N protein three-dimensional structure was predicted using the prediction I-TASSER server. In the current study, bioinformatics tools were used to design a multi-epitope peptide based on the type of antigen and its physiochemical properties and SVM method (Machine Learning) to design multi-epitopes that have a high avidity against SARS-CoV-2 antibodies to detect infections by COVID-19.

Annotation of Potential Vaccine Targets and Design of a Multi-Epitope Subunit Vaccine against Yersinia pestis through Reverse Vaccinology and Validation through an Agent-Based Modeling Approach

Yersinia pestis is responsible for plague and major pandemics in Asia and Europe. This bacterium has shown resistance to an array of drugs commonly used for the treatment of plague. Therefore, effective therapeutics measurements, such as designing a vaccine that can effectively and safely prevent Y. pestis infection, are of high interest. To fast-track vaccine development against Yersinia pestis, herein, proteome-wide vaccine target annotation was performed, and structural vaccinology-assisted epitopes were predicted. Among the total 3909 proteins, only 5 (rstB, YPO2385, hmuR, flaA1a, and psaB) were shortlisted as essential vaccine targets. These targets were then subjected to multi-epitope vaccine design using different linkers. EAAK, AAY, and GPGPG as linkers were used to link CTL, HTL, and B-cell epitopes, and an adjuvant (beta defensin) was also added at the N-terminal of the MEVC. Physiochemical characterization, such as determination of the instability index, theoretical pI, half-life, aliphatic index, stability profiling, antigenicity, allergenicity, and hydropathy of the ensemble, showed that the vaccine is highly stable, antigenic, and non-allergenic and produces multiple interactions with immune receptors upon docking. In addition, molecular dynamics simulation confirmed the stable binding and good dynamic properties of the vaccine-TLR complex. Furthermore, in silico and immune simulation of the developed MEVC for Y. pestis showed that the vaccine triggered strong immune response after several doses at different intervals. Neutralization of the antigen was observed at the third day of injection. Conclusively, the vaccine designed here for Y. pestis produces an immune response; however, further immunological testing is needed to unveil its real efficacy.

Direct Activation of Endothelial Cells by SARS-CoV-2 Nucleocapsid Protein Is Blocked by Simvastatin

Emerging evidence suggests that endothelial activation plays a central role in the pathogenesis of acute respiratory distress syndrome (ARDS) and multiorgan failure in patients with coronavirus disease 2019 (COVID-19). However, the molecular mechanisms underlying endothelial activation in COVID-19 patients remain unclear. In this study, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral proteins that potently activate human endothelial cells were screened to elucidate the molecular mechanisms involved in endothelial activation. It was found that nucleocapsid protein (NP) of SARS-CoV-2 significantly activated human endothelial cells through Toll-like receptor 2 (TLR2)/NF-κB and mitogen-activated protein kinase (MAPK) signaling pathways. Moreover, by screening a natural microbial compound library containing 154 natural compounds, simvastatin was identified as a potent inhibitor of NP-induced endothelial activation. Remarkably, though the protein sequences of N proteins from coronaviruses are highly conserved, only NP from SARS-CoV-2 induced endothelial activation. The NPs from other coronaviruses such as SARS-CoV, Middle East respiratory syndrome coronavirus (MERS-CoV), HUB1-CoV, and influenza virus H1N1 did not activate endothelial cells. These findings are consistent with the results from clinical investigations showing broad endotheliitis and organ injury in severe COVID-19 patients. In conclusion, the study provides insights on SARS-CoV-2-induced vasculopathy and coagulopathy and suggests that simvastatin, an FDA-approved lipid-lowering drug, may help prevent the pathogenesis and improve the outcome of COVID-19 patients.

IMPORTANCE Coronavirus disease 2019 (COVID-19), caused by the betacoronavirus SARS-CoV-2, is a worldwide challenge for health care systems. The leading cause of mortality in patients with COVID-19 is hypoxic respiratory failure from acute respiratory distress syndrome (ARDS). To date, pulmonary endothelial cells (ECs) have been largely overlooked as a therapeutic target in COVID-19, yet emerging evidence suggests that these cells contribute to the initiation and propagation of ARDS by altering vessel barrier integrity, promoting a procoagulative state, inducing vascular inflammation and mediating inflammatory cell infiltration. Therefore, a better mechanistic understanding of the vasculature is of utmost importance. In this study, we screened the SARS-CoV-2 viral proteins that potently activate human endothelial cells and found that nucleocapsid protein (NP) significantly activated human endothelial cells through TLR2/NF-κB and MAPK signaling pathways. Moreover, by screening a natural microbial compound library containing 154 natural compounds, simvastatin was identified as a potent inhibitor of NP-induced endothelial activation. Our results provide insights on SARS-CoV-2-induced vasculopathy and coagulopathy, and suggests that simvastatin, an FDA-approved lipid-lowering drug, may benefit to prevent the pathogenesis and improve the outcome of COVID-19 patients.

Bioinformatics analysis of the differences in the binding profile of the wild-type and mutants of the SARS-CoV-2 spike protein variants with the ACE2 receptor

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). Reports of new variants that potentially increase virulence and viral transmission, as well as reduce the efficacy of available vaccines, have recently emerged. In this study, we computationally analyzed the N439K, S477 N, and T478K variants for their ability to bind Angiotensin-converting enzyme 2 (ACE2). We used the protein-protein docking approach to explore whether the three variants displayed a higher binding affinity to the ACE2 receptor than the wild type. We found that these variants alter the hydrogen bonding network and the cluster of interactions. Additional salt bridges, hydrogen bonds, and a high number of non-bonded contacts (i.e., non-bonded interactions between atoms in the same molecule and those in other molecules) were observed only in the mutant complexes, allowing efficient binding to the ACE2 receptor. Furthermore, we used a 2.0-μs all-atoms simulation approach to detect differences in the structural dynamic features of the resulting protein complexes. Our findings revealed that the mutant complexes possessed stable dynamics, consistent with the global trend of mutations yielding variants with improved stability and enhanced affinity. Binding energy calculations based on molecular mechanics/generalized Born surface area (MM/GBSA) further revealed that electrostatic interactions principally increased net binding energies. The stability and binding energies of N439K, S477 N, and T478K variants were enhanced compared to the wild-type-ACE2 complex. The net binding energy of the systems was -31.86 kcal/mol for the wild-type-ACE2 complex, -67.85 kcal/mol for N439K, -69.82 kcal/mol for S477 N, and -69.64 kcal/mol for T478K. The current study provides a basis for exploring the enhanced binding abilities and structural features of SARS-CoV-2 variants to design novel therapeutics against the virus.

Screening Potential Drugs for COVID-19 Based on Bound Nuclear Norm Regularization

The novel coronavirus pneumonia COVID-19 infected by SARS-CoV-2 has attracted worldwide attention. It is urgent to find effective therapeutic strategies for stopping COVID-19. In this study, a Bounded Nuclear Norm Regularization (BNNR) method is developed to predict anti-SARS-CoV-2 drug candidates. First, three virus-drug association datasets are compiled. Second, a heterogeneous virus-drug network is constructed. Third, complete genomic sequences and Gaussian association profiles are integrated to compute virus similarities; chemical structures and Gaussian association profiles are integrated to calculate drug similarities. Fourth, a BNNR model based on kernel similarity (VDA-GBNNR) is proposed to predict possible anti-SARS-CoV-2 drugs. VDA-GBNNR is compared with four existing advanced methods under fivefold cross-validation. The results show that VDA-GBNNR computes better AUCs of 0.8965, 0.8562, and 0.8803 on the three datasets, respectively. There are 6 anti-SARS-CoV-2 drugs overlapping in any two datasets, that is, remdesivir, favipiravir, ribavirin, mycophenolic acid, niclosamide, and mizoribine. Molecular dockings are conducted for the 6 small molecules and the junction of SARS-CoV-2 spike protein and human angiotensin-converting enzyme 2. In particular, niclosamide and mizoribine show higher binding energy of −8.06 and −7.06 kcal/mol with the junction, respectively. G496 and K353 may be potential key residues between anti-SARS-CoV-2 drugs and the interface junction. We hope that the predicted results can contribute to the treatment of COVID-19.

Immunoinformatics and Immunogenetics-Based Design of Immunogenic Peptides Vaccine against the Emerging Tick-Borne Encephalitis Virus (TBEV) and Its Validation through In Silico Cloning and Immune Simulation

Pegivirus, HPgV, earlier known as Gb virus and hepatitis G virus, is an enveloped, positive-stranded RNA and lymphotropic virus classified into the Flaviviridae family. The transmission routes primarily involve blood products, with infections worldwide, leading up to 25% of persistent infections. To date, no effective therapeutic means are available to resolve Pegivirus infections. Effective vaccine therapeutics are the best alternative to manage this disease and any associated potential pandemic. Thus, whole proteome-based mining of immunogenic peptides, i.e., CTL (cytotoxic T lymphocytes), HTL (helper T lymphocytes) and B cell epitopes were mapped to design a vaccine ensemble. Our investigation revealed that 29 different epitopes impart a critical role in immune response induction, which was also validated by exploring its physiochemical properties and experimental feasibility. In silico expression and host immune simulation using an agent-based modeling approach confirmed the induction of both primary and secondary immune factors such as IL, cytokines and antibodies. The current study warrants further lab experiments to demonstrate its efficacy and safety.

Structural probing of HapR to identify potent phytochemicals to control Vibrio cholera through integrated computational approaches

Cholera is a severe small intestine bacterial disease caused by consumption of water and food contaminated with Vibrio cholera. The disease causes watery diarrhea leading to severe dehydration and even death if left untreated. In the past few decades, V. cholerae has emerged as multidrug-resistant enteric pathogen due to its rapid ability to adapt in detrimental environmental conditions. This research study aimed to design inhibitors of a master virulence gene expression regulator, HapR. HapR is critical in regulating the expression of several set of V. cholera virulence genes, quorum-sensing circuits and biofilm formation. A blind docking strategy was employed to infer the natural binding tendency of diverse phytochemicals extracted from medicinal plants by exposing the whole HapR structure to the screening library. Scoring function criteria was applied to prioritize molecules with strong binding affinity (binding energy < -11 kcal/mol) and as such two compounds: Strychnogucine A and Galluflavanone were filtered. Both the compounds were found favourably binding to the conserved dimerization interface of HapR. One rare binding conformation of Strychnogucine A was noticed docked at the elongated cavity formed by α1, α4 and α6 (binding energy of -12.5 kcal/mol). The binding stability of both top leads at dimer interface and elongated cavity was further estimated using long run of molecular dynamics simulations, followed by MMGB/PBSA binding free energy calculations to define the dominance of different binding energies. In a nutshell, this study presents computational evidence on antibacterial potential of phytochemicals capable of directly targeting bacterial virulence and highlight their great capacity to be utilized in the future experimental studies to stop the evolution of antibiotic resistance evolution.

Emerging Mutations in Nsp1 of SARS-CoV-2 and Their Effect on the Structural Stability

The genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encodes 16 non-structural (Nsp) and 4 structural proteins. Among the Nsps, Nsp1 inhibits host gene expression and also evades the immune system. This protein has been proposed as a target for vaccine development and also for drug design. Owing to its important role, the current study aimed to identify mutations in Nsp1 and their effect on protein stability and flexibility. This is the first comprehensive study in which 295,000 complete genomes have been screened for mutations after alignment with the Wuhan-Hu-1 reference genome (Accession NC_045512), using the CoVsurver app. The sequences harbored 933 mutations in the entire coding region of Nsp1. The most frequently occurring mutation in the 180-amino-acid Nsp1 protein was R24C (n = 1122), followed by D75E (n = 890), D48G (n = 881), H110Y (n = 860), and D144A (n = 648). Among the 933 non-synonymous mutations, 529 exhibited a destabilizing effect. Similarly, a gain in flexibility was observed in 542 mutations. The majority of the most frequent mutations were detected in the loop regions. These findings imply that Nsp1 mutations might be useful to exploit SARS-CoV-2's pathogenicity. Genomic sequencing of SARS-CoV-2 on a regular basis will further assist in analyzing variations among the drug targets and to test the diagnostic accuracy. This wide range of mutations and their effect on Nsp1's stability may have some consequences for the host's innate immune response to SARS-CoV-2 infection and also for the vaccines' efficacy. Based on this mutational information, geographically strain-specific drugs, vaccines, and antibody combinations could be a useful strategy against SARS-CoV-2 infection.

The proximal proteome of 17 SARS-CoV-2 proteins links to disrupted antiviral signaling and host translation

Viral proteins localize within subcellular compartments to subvert host machinery and promote pathogenesis. To study SARS-CoV-2 biology, we generated an atlas of 2422 human proteins vicinal to 17 SARS-CoV-2 viral proteins using proximity proteomics. This identified viral proteins at specific intracellular locations, such as association of accessary proteins with intracellular membranes, and projected SARS-CoV-2 impacts on innate immune signaling, ER-Golgi transport, and protein translation. It identified viral protein adjacency to specific host proteins whose regulatory variants are linked to COVID-19 severity, including the TRIM4 interferon signaling regulator which was found proximal to the SARS-CoV-2 M protein. Viral NSP1 protein adjacency to the EIF3 complex was associated with inhibited host protein translation whereas ORF6 localization with MAVS was associated with inhibited RIG-I 2CARD-mediated IFNB1 promoter activation. Quantitative proteomics identified candidate host targets for the NSP5 protease, with specific functional cleavage sequences in host proteins CWC22 and FANCD2. This data resource identifies host factors proximal to viral proteins in living human cells and nominates pathogenic mechanisms employed by SARS-CoV-2.

SARS-CoV-2 is the latest pathogenic coronavirus to emerge as a public health threat. We create a database of proximal host proteins to 17 SARS-CoV-2 viral proteins. We validate that NSP1 is proximal to the EIF3 translation initiation complex and is a potent inhibitor of translation. We also identify ORF6 antagonism of RNA-mediate innate immune signaling. We produce a database of potential host targets of the viral protease NSP5, and create a fluorescence-based assay to screen cleavage of peptide sequences. We believe that this data will be useful for identifying roles for many of the uncharacterized SARS-CoV-2 proteins and provide insights into the pathogenicity of new or emerging coronaviruses.