Computational and experimental validation of phthalocyanine and hypericin as effective SARS-CoV-2 fusion inhibitors.

Phthalocyanine and hypericin have been previously identified as possible SARS-CoV-2 Spike glycoprotein fusion inhibitors through a virtual screening procedure. In this paper, atomistic simulations of metal-free phthalocyanines and atomistic and coarse-grained simulations of hypericins, placed around a complete model of the Spike embedded in a viral membrane, allowed to further explore their multi-target inhibitory potential, uncovering their binding to key protein functional regions and their propensity to insert in the membrane. Following computational results, pre-treatment of a pseudovirus expressing the SARS-CoV-2 Spike protein with low compounds concentrations resulted in a strong inhibition of its entry into cells, suggesting the activity of these molecules should involve the direct targeting of the viral envelope surface. The combination of computational and in vitro results hence supports the role of hypericin and phthalocyanine as promising SARS-CoV-2 entry inhibitors, further endorsed by literature reporting the efficacy of these compounds in inhibiting SARS-CoV-2 activity and in treating hospitalized COVID-19 patients.Communicated by Ramaswamy H. Sarma.

Computational analysis of protein stability and allosteric interaction networks in distinct conformational forms of the SARS-CoV-2 spike D614G mutant: reconciling functional mechanisms through allosteric model of spike regulation.

In this study, we used an integrative computational approach to examine molecular mechanisms underlying functional effects of the D614G mutation by exploring atomistic modeling of the SARS-CoV-2 spike proteins as allosteric regulatory machines. We combined coarse-grained simulations, protein stability and dynamic fluctuation communication analysis with network-based community analysis to examine structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. Through distance fluctuations communication analysis, we probed stability and allosteric communication propensities of protein residues in the native and mutant SARS-CoV-2 spike proteins, providing evidence that the D614G mutation can enhance long-range signaling of the allosteric spike engine. By combining functional dynamics analysis and ensemble-based alanine scanning of the SARS-CoV-2 spike proteins we found that the D614G mutation can improve stability of the spike protein in both closed and open forms, but shifting thermodynamic preferences towards the open mutant form. Our results revealed that the D614G mutation can promote the increased number of stable communities and allosteric hub centers in the open form by reorganizing and enhancing the stability of the S1-S2 inter-domain interactions and restricting mobility of the S1 regions. This study provides atomistic-based view of allosteric communications in the SARS-CoV-2 spike proteins, suggesting that the D614G mutation can exert its primary effect through allosterically induced changes on stability and communications in the residue interaction networks.Communicated by Ramaswamy H. Sarma.

Food Plant Secondary Metabolites Antiviral Activity and Their Possible Roles in SARS-CoV-2 Treatment: An Overview.

Natural products and plant extracts exhibit many biological activities, including that related to the defense mechanisms against parasites. Many studies have investigated the biological functions of secondary metabolites and reported evidence of antiviral activities. The pandemic emergencies have further increased the interest in finding antiviral agents, and efforts are oriented to investigate possible activities of secondary plant metabolites against human viruses and their potential application in treating or preventing SARS-CoV-2 infection. In this review, we performed a comprehensive analysis of studies through in silico and in vitro investigations, also including in vivo applications and clinical trials, to evaluate the state of knowledge on the antiviral activities of secondary metabolites against human viruses and their potential application in treating or preventing SARS-CoV-2 infection, with a particular focus on natural compounds present in food plants. Although some of the food plant secondary metabolites seem to be useful in the prevention and as a possible therapeutic management against SARS-CoV-2, up to now, no molecules can be used as a potential treatment for COVID-19; however, more research is needed.

Ultra-Large-Scale Screening of Natural Compounds and Free Energy Calculations Revealed Potential Inhibitors for the Receptor-Binding Domain (RBD) of SARS-CoV-2.

The emergence of immune-evading variants of SARS-CoV-2 further aggravated the ongoing pandemic. Despite the deployments of various vaccines, the acquired mutations are capable of escaping both natural and vaccine-induced immune responses. Therefore, further investigation is needed to design a decisive pharmacological treatment that could efficiently block the entry of this virus into cells. Hence, the current study used structure-based methods to target the RBD of the recombinant variant (Deltacron) of SARS-CoV-2, which was used as a model variant. From the virtual drug screenings of various databases, a total of four hits were identified as potential lead molecules. Key residues were blocked by these molecules with favorable structural dynamic features. The binding free energies further validated the potentials of these molecules. The TBE for MNP was calculated to be -32.86 ± 0.10 kcal/mol, for SANC00222 the TBE was -23.41 ± 0.15 kcal/mol, for Liriodenine the TBE was -34.29 ± 0.07 kcal/mol, while for Carviolin the TBE was calculated to be -27.67 ± 0.12 kcal/mol. Moreover, each complex demonstrated distinct internal motion and a free energy profile, indicating a different strategy for the interaction with and inhibition of the RBD. In conclusion, the current study demands further in vivo and in vitro validation for the possible usage of these compounds as potential drugs against SARS-CoV-2 and its variants.

Mucormycosis Vaccine Design using Bioinformatic Tools

Mucormycosis is an infection that occurs due to the presence of filamentous molds. Rhizopus delemar is a major cause of mucormycosis. The infection may be due to the inoculation of spores into wounds, inhalation of the spores, or the consumption of contaminated food. Mucormycosis cases have risen during the second wave of COVID-19 infections in India. Therefore, there is an urgent requirement for a vaccine against mucormycosis. The development of these vaccines is costly and time-consuming. Different methods have been used to decrease the expense and duration of time required for the development of a vaccine. One such method is the use of bioinformatics techniques for the development of vaccines. In this paper, the screening of epitopes through the bioinformatic tools predicts that the RO3G_11882 protein of Rhizopus delemar can be used for preparing immunological constructs. Binding and molecular simulation tests predict that the nanomeric epitope VLALHNFLL has low energy minimization values which provide stability to the peptide-MHC complex and sufficient binding with MHC class II molecules. This peptide sequence needs to further go through wet lab tests, for developing a vaccine against Mucormycosis. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Natural Polyphenols Inhibit the Dimerization of the SARS-CoV-2 Main Protease: The Case of Fortunellin and Its Structural Analogs.

3CL-Pro is the SARS-CoV-2 main protease (MPro). It acts as a homodimer to cleave the large polyprotein 1ab transcript into proteins that are necessary for viral growth and replication. 3CL-Pro has been one of the most studied SARS-CoV-2 proteins and a main target of therapeutics. A number of drug candidates have been reported, including natural products. Here, we employ elaborate computational methods to explore the dimerization of the 3CL-Pro protein, and we formulate a computational context to identify potential inhibitors of this process. We report that fortunellin (acacetin 7-O-neohesperidoside), a natural flavonoid O-glycoside, and its structural analogs are potent inhibitors of 3CL-Pro dimerization, inhibiting viral plaque formation in vitro. We thus propose a novel basis for the search of pharmaceuticals as well as dietary supplements in the fight against SARS-CoV-2 and COVID-19.

In-silico immunoinformatic analysis of SARS-CoV-2 virus for the development of putative vaccine construct.

COVID-19 (CoronaVirus disease 2019) is caused by the SARS-CoV-2 virus (severe acute respiratory syndrome corona virus 2). SARS-CoV-2 virus is highly contagious and affects the human respiratory tract resulting in symptoms such as high fever, body ache, cough, dysfunctions of tastebuds and smelling sense of body. The objective of the present study involves immunoinformatic analysis to predict COVID-19 protein for vaccine construct based on the genomic information SARS-CoV-2 virus. At present, as per WHO estimates, around 133 COVID-19 novel vaccines under development. Three amino acid sequences of SARS-CoV-2 were retrieved from the NCBI database for the analysis of vaccine construct. This study involves computational and immunoinformatic methods. The Immunoinformatic tools used in the present study are NetCTL server, IFN epitope server, Toxin PRED, BCPred, CTL + HTL + ADJUVANTS + LINKERS, AlgPredserver, VaxiJenserver, ProtParam to predict vaccine construct. The secondary and tertiary structure prediction is done by PSIPRED, I-TASSER, Galaxy refine, prosA + Ramachandran. Finally, docking of the vaccine constructs and ligand was done with the help of Cluspro 2.0. C-ImmSimm webserver to simulate the potential vaccine construct. The present study demonstrated three potential Vaccine constructs for the SARS-CoV-2 virus, which were docked with TLR8 (Toll-likereceptor8). Interestingly from these, all constructs one having a high potential for the inhibition effect of the SARS-CoV-2virus. Immunological simulation data shows significant elevated amount of memory B cell; also, the high response was seen in TH(Helper) and TC(cytotoxic) cell population from the vaccine construct proposed in the current study. Hence, these constructs are suitable vaccine candidates that might be useful in developing a novel vaccine.

Exploration of natural compounds with anti-SARS-CoV-2 activity via inhibition of SARS-CoV-2 Mpro.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a dreaded pandemic in lack of specific therapeutic agent. SARS-CoV-2 Mpro, an essential factor in viral pathogenesis, is recognized as a prospective therapeutic target in drug discovery against SARS-CoV-2. To tackle this pandemic, Food and Drug Administration-approved drugs are being screened against SARS-CoV-2 Mpro via in silico and in vitro methods to detect the best conceivable drug candidates. However, identification of natural compounds with anti-SARS-CoV-2 Mpro potential have been recommended as rapid and effective alternative for anti-SARS-CoV-2 therapeutic development. Thereof, a total of 653 natural compounds were identified against SARS-CoV-2 Mpro from NP-lib database at MTi-OpenScreen webserver using virtual screening approach. Subsequently, top four potential compounds, i.e. 2,3-Dihydroamentoflavone (ZINC000043552589), Podocarpusflavon-B (ZINC000003594862), Rutin (ZINC000003947429) and Quercimeritrin 6"-O-L-arabinopyranoside (ZINC000070691536), and co-crystallized N3 inhibitor as reference ligand were considered for stringent molecular docking after geometry optimization by DFT method. Each compound exhibited substantial docking energy >-12 kcal/mol and molecular contacts with essential residues, including catalytic dyad (His41 and Cys145) and substrate binding residues, in the active pocket of SARS-CoV-2 Mpro against N3 inhibitor. The screened compounds were further scrutinized via absorption, distribution, metabolism, and excretion - toxicity (ADMET), quantum chemical calculations, combinatorial molecular simulations and hybrid QM/MM approaches. Convincingly, collected results support the potent compounds for druglikeness and strong binding affinity with the catalytic pocket of SARS-CoV-2 Mpro. Hence, selected compounds are advocated as potential inhibitors of SARS-CoV-2 Mpro and can be utilized in drug development against SARS-CoV-2 infection.

Discovery of Small-Molecule Inhibitors of SARS-CoV-2 Proteins Using a Computational and Experimental Pipeline.

A rapid response is necessary to contain emergent biological outbreaks before they can become pandemics. The novel coronavirus (SARS-CoV-2) that causes COVID-19 was first reported in December of 2019 in Wuhan, China and reached most corners of the globe in less than two months. In just over a year since the initial infections, COVID-19 infected almost 100 million people worldwide. Although similar to SARS-CoV and MERS-CoV, SARS-CoV-2 has resisted treatments that are effective against other coronaviruses. Crystal structures of two SARS-CoV-2 proteins, spike protein and main protease, have been reported and can serve as targets for studies in neutralizing this threat. We have employed molecular docking, molecular dynamics simulations, and machine learning to identify from a library of 26 million molecules possible candidate compounds that may attenuate or neutralize the effects of this virus. The viability of selected candidate compounds against SARS-CoV-2 was determined experimentally by biolayer interferometry and FRET-based activity protein assays along with virus-based assays. In the pseudovirus assay, imatinib and lapatinib had IC50 values below 10 µM, while candesartan cilexetil had an IC50 value of approximately 67 µM against Mpro in a FRET-based activity assay. Comparatively, candesartan cilexetil had the highest selectivity index of all compounds tested as its half-maximal cytotoxicity concentration 50 (CC50) value was the only one greater than the limit of the assay (>100 µM).

In silico characterization of mutations circulating in SARS-CoV-2 structural proteins.

SARS-CoV-2 has recently emerged as a pandemic that has caused more than 2.4 million deaths worldwide. Since the onset of infections, several full-length sequences of viral genome have been made available which have been used to gain insights into viral dynamics. We utilised a meta-data driven comparative analysis tool for sequences (Meta-CATS) algorithm to identify mutations in 829 SARS-CoV-2 genomes from around the world. The algorithm predicted sixty-one mutations among SARS-CoV-2 genomes. We observed that most of the mutations were concentrated around three protein coding genes viz nsp3 (non-structural protein 3), RdRp (RNA-directed RNA polymerase) and Nucleocapsid (N) proteins of SARS-CoV-2. We used various computational tools including normal mode analysis (NMA), C-α discrete molecular dynamics (DMD) and all-atom molecular dynamic simulations (MD) to study the effect of mutations on functionality, stability and flexibility of SARS-CoV-2 structural proteins including envelope (E), N and spike (S) proteins. PredictSNP predictor suggested that four mutations (L37H in E, R203K and P344S in N and D614G in S) out of seven were predicted to be neutral whilst the remaining ones (P13L, S197L and G204R in N) were predicted to be deleterious in nature thereby impacting protein functionality. NMA, C-α DMD and all-atom MD suggested some mutations to have stabilizing roles (P13L, S197L and R203K in N protein) where remaining ones were predicted to destabilize mutant protein. In summary, we identified significant mutations in SARS-CoV-2 genomes as well as used computational approaches to further characterize the possible effect of highly significant mutations on SARS-CoV-2 structural proteins.Communicated by Ramaswamy H. Sarma.