In Silico Structure-Based Vaccine Design.

Structure-based vaccine design (SBVD) is an important technique in computational vaccine design that uses structural information on a targeted protein to design novel vaccine candidates. This increasing ability to rapidly model structural information on proteins and antibodies has provided the scientific community with many new vaccine targets and novel opportunities for future vaccine discovery. This chapter provides a comprehensive overview of the status of in silico SBVD and discusses the current challenges and limitations. Key strategies in the field of SBVD are exemplified by a case study on design of COVID-19 vaccines targeting SARS-CoV-2 spike protein.

Quantitative structure-activity relationships, molecular docking and molecular dynamics simulations reveal drug repurposing candidates as potent SARS-CoV-2 main protease inhibitors.

The current outbreak of COVID-19 is leading an unprecedented scientific effort focusing on targeting SARS-CoV-2 proteins critical for its viral replication. Herein, we performed high-throughput virtual screening of more than eleven thousand FDA-approved drugs using backpropagation-based artificial neural networks (q2LOO = 0.60, r2 = 0.80 and r2pred = 0.91), partial-least-square (PLS) regression (q2LOO = 0.83, r2 = 0.62 and r2pred = 0.70) and sequential minimal optimization (SMO) regression (q2LOO = 0.70, r2 = 0.80 and r2pred = 0.89). We simulated the stability of Acarbose-derived hexasaccharide, Naratriptan, Peramivir, Dihydrostreptomycin, Enviomycin, Rolitetracycline, Viomycin, Angiotensin II, Angiotensin 1-7, Angiotensinamide, Fenoterol, Zanamivir, Laninamivir and Laninamivir octanoate with 3CLpro by 100 ns and calculated binding free energy using molecular mechanics combined with Poisson-Boltzmann surface area (MM-PBSA). Our QSAR models and molecular dynamics data suggest that seven repurposed-drug candidates such as Acarbose-derived Hexasaccharide, Angiotensinamide, Dihydrostreptomycin, Enviomycin, Fenoterol, Naratriptan and Viomycin are potential SARS-CoV-2 main protease inhibitors. In addition, our QSAR models and molecular dynamics simulations revealed that His41, Asn142, Cys145, Glu166 and Gln189 are potential pharmacophoric centers for 3CLpro inhibitors. Glu166 is a potential pharmacophore for drug design and inhibitors that interact with this residue may be critical to avoid dimerization of 3CLpro. Our results will contribute to future investigations of novel chemical scaffolds and the discovery of novel hits in high-throughput screening as potential anti-SARS-CoV-2 properties.Communicated by Ramaswamy H. Sarma.

Drug Repurposing Against Angiotensin-Converting Enzyme-Related Carboxypeptidase (ACE2) Through Computational Approach.

Ongoing novel coronavirus (COVID-19) with high mortality is an infectious disease in the world which epidemic in 2019 with human-human transmission. According to the literature, S-protein is one of the main proteins of COVID-19 that bind to the human cell receptor angiotensin-converting enzyme 2 (ACE2). In this study, it was attempted to identify the main effective drugs approved that may be repurposed to the binding site of ACE2. High throughput virtual screening based on the docking study was performed to know which one of the small-molecules had a potential interaction with ACE2 structure. Forasmuch as investigating and identifying the best ACE2 inhibitors among more than 3,500 small-molecules is time-consuming, supercomputer was utilized to apply docking-based virtual screening. Outputs of the proposed computational model revealed that vincristine, vinbelastin and bisoctrizole can significantly bind to ACE2 and may interface with its normal activity.

Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein-Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design.

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein-protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.

Discovery of SARS-CoV-2 Nsp14 and Nsp16 Methyltransferase Inhibitors by High-Throughput Virtual Screening.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses mRNA capping to evade the human immune system. The cap formation is performed by the SARS-CoV-2 mRNA cap methyltransferases (MTases) nsp14 and nsp16, which are emerging targets for the development of broad-spectrum antiviral agents. Here, we report results from high-throughput virtual screening against these two enzymes. The docking of seven million commercially available drug-like compounds and S-adenosylmethionine (SAM) co-substrate analogues against both MTases resulted in 80 virtual screening hits (39 against nsp14 and 41 against nsp16), which were purchased and tested using an enzymatic homogeneous time-resolved fluorescent energy transfer (HTRF) assay. Nine compounds showed micromolar inhibition activity (IC50 < 200 µM). The selectivity of the identified inhibitors was evaluated by cross-checking their activity against human glycine N-methyltransferase. The majority of the compounds showed poor selectivity for a specific MTase, no cytotoxic effects, and rather poor cell permeability. Nevertheless, the identified compounds represent good starting points that have the potential to be developed into efficient viral MTase inhibitors.

Identification of Mpro inhibitors of SARS-CoV-2 using structure based computational drug repurposing.

The recent outbreak of COVID-19, caused by the novel pathogen SARS-coronavirus 2 (SARS-CoV-2) is a severe health emergency. In this pandemic, drug repurposing seems to be the most promising alternative to identify effective therapeutic agents for immediate treatment of infected patients. The present study aimed to evaluate all the drugs present in drug bank as potential novel SARS-CoV-2 inhibitors, using computational drug repurposing studies. Docking-based virtual screening and binding energy prediction were performed, followed by Absorption Distribution Metabolism Excretion calculation. Hydroxychloroquine and Nelfinavir have been identified as the best potential inhibitor against the SARS-CoV-2, therefore, they were used as reference compounds in computational DR studies. The docking study revealed 13 best compounds based on their highest binding affinity, binding energy, and dock score concerning the other screened compounds. Out of 13, only 4 compounds were further shortlisted based on their binding energy and best ADME properties. The hierarchical virtual screening yielded the best 04 drugs, DB07042 (compound 2), DB13035 (compound 3), DB13604 (compound 5) and DB08253 (compound 6), with commendable binding energies in kcal/mol, i.e. -65.45, -62.01, -52.09 and -51.70 respectively. Further, Molecular dynamics simulation with 04 best-retrieved hits has confirmed stable trajectories in protein in terms of root mean square deviation and root mean square fluctuation. During 30 ns simulation, the interactions were also found similar to the docking-based studies. However, clinical studies are necessary to investigate their therapeutic use against this outbreak.

A short survey of dengue protease inhibitor development in the past 6 years (2015-2020) with an emphasis on similarities between DENV and SARS-CoV-2 proteases.

Dengue remains a disease of significant concern, responsible for nearly half of all arthropod-borne disease cases across the globe. Due to the lack of potent and targeted therapeutics, palliative treatment and the adoption of preventive measures remain the only available options. Compounding the problem further, the failure of the only dengue vaccine, Dengvaxia®, also delivered a significant blow to any hopes for the treatment of dengue fever. However, the success of Human Immuno-deficiency Virus (HIV) and Hepatitis C Virus (HCV) protease inhibitors in the past have continued to encourage researchers to investigate other viral protease targets. Dengue virus (DENV) NS2B-NS3 protease is an attractive target partly due to its role in polyprotein processing and also for being the most conserved domain in the viral genome. During the early days of the COVID-19 pandemic, a few cases of Dengue-COVID 19 co-infection were reported. In this review, we compared the substrate-peptide residue preferences and the residues lining the sub-pockets of the proteases of these two viruses and analyzed the significance of this similarity. Also, we attempted to abridge the developments in anti-dengue drug discovery in the last six years (2015-2020), focusing on critical discoveries that influenced the research.

Meticulous assessment of natural compounds from NPASS database for identifying analogue of GRL0617, the only known inhibitor for SARS-CoV2 papain-like protease (PLpro) using rigorous computational workflow.

The latest global outbreak of 2019 respiratory coronavirus disease (COVID-19) is triggered by the inception of novel coronavirus SARS-CoV2. If recent events are of any indicators of the epidemics of past, it is undeniable to state a fact that the SARS-CoV2 viral infection is highly transmissible with respect to its previously related SARS-CoV's. Papain-like protease (PLpro) is an enzyme that is required by the virus itself for replicating into the host system; and it does so by processing its polyproteins into a functional replicase complex. PLpro is also known for downregulating the genes responsible for producing interferons, an essential family of molecules produced in response to viral infection, thus making this protein an indispensable drug target. In this study, PLpro inhibitors were identified through high throughput structure-based virtual screening approach from NPASS natural product library possessing ~ 35,000 compounds. Top five hits were scrutinised based on structural aromaticity and ability to interact with a key active site residue of PLpro, Tyr268. For second level of screening, the MM-GBSA End-Point Binding Free Energy Calculation of the docked complexes was performed, which identified Caesalpiniaphenol A as the best hit. Caesalpiniaphenol A not only possess a double ring aromatic moiety but also has lowest minimum binding energy, which is at par with the control GRL0617, the only known inhibitor of SARS-CoV2 PLpro. Details of the Molecular Dynamics (MD) simulation and ADMET analysis helped to conclusively determine Caesalpiniaphenol A as potentially an inhibitor of SARS-CoV2 PLpro.

Neutralization of SARS-CoV-2 Spike Protein via Natural Compounds: A Multilayered High Throughput Virtual Screening Approach.

BACKGROUND: Previously human society has faced various unprecedented pandemics in the history and viruses have majorly held the responsibilities of those outbreaks. Furthermore, due to amplified global connection and speedy modernization, epidemic outbreaks caused by novel and re-emerging viruses signify potential risk to community health. Despite great advancements in immunization and drug discovery processes, various viruses still lack prophylactic vaccines and efficient antiviral therapies. Although, vaccine is a prophylaxes option, but it cannot be applied to infected patients, hence therapeutic interventions are urgently needed to control the ongoing global SARS- CoV-2 pandemic condition. To spot the novel antiviral therapy is of decisive importance and Mother Nature is an excellent source for such discoveries. METHODOLOGY: In this article, prompt high through-put virtual screening for vetting the best possible drug candidates from natural compounds' databases has been implemented. Herein, time tested rigorous multi-layered drug screening process to narrow down 66,969 natural compounds for the identification of potential lead(s) is implemented. Druggability parameters, different docking approaches and neutralization tendency of the natural products were employed in this study to screen the best possible natural compounds from the digital libraries. CONCLUSION: The results of this study conclude that compounds PALA and HMCA are potential inhibitors of SARS-CoV-2 spike protein and can be further explored for experimental validation. Overall, the methodological approach reported in this article can be suitably used to find the potential drug candidates against SARS-CoV2 in the burning situation of COVID-19 with less expenditure and a concise span of time.

Bioinformatic study to discover natural molecules with activity against COVID-19.

Background: In 2020, the world has struggled to deal with coronavirus disease 2019 (COVID-19), which started in 2019 in China and has spread throughout the globe, affecting at least 31,175,835 humans globally and claiming 962,634 lives reported till 22nd September, 2020 by the World Health Organization. The main causative agent for this disease is known as severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). So far, there is no cure or proven therapeutics available till date. Therefore, we undertook this study to find the most probable drug candidate through a bioinformatics study. Methods: Thus, we virtually screened the Zinc natural database using HTVS tool through molecular docking studies to analyze molecules recommended for the treatment of COVID-19. Results: Ramipril benzyl ester, propafenone dimer and Lariciresinol are three important drugs found from the present study due to their medicinal application which could be helpful in treating the disease. Stylopine, quillaic acid, cinobufagin, vitisinol C, segetalin A, scopolamine, 3-oxo glycyrrhetinic acid, conchinone B, lactimidomycin and cardinalins 4 are the other lead molecules that could be used as therapeutics against COVID-19 disease. Conclusions: The studied molecules could act as an effective inhibitory drug against COVID-19.

Targeting the SARS-CoV-2 main protease using FDA-approved Isavuconazonium, a P2-P3 α-ketoamide derivative and Pentagastrin: An in-silico drug discovery approach.

The SARS-CoV-2 main protease (Mpro) is an attractive target towards discovery of drugs to treat COVID-19 because of its key role in virus replication. The atomic structure of Mpro in complex with an α-ketoamide inhibitor (Lig13b) is available (PDB ID:6Y2G). Using 6Y2G and the prior knowledge that protease inhibitors could eradicate COVID-19, we designed a computational study aimed at identifying FDA-approved drugs that could interact with Mpro. We searched the DrugBank and PubChem for analogs and built a virtual library containing ∼33,000 conformers. Using high-throughput virtual screening and ligand docking, we identified Isavuconazonium, a ketoamide inhibitor (α-KI) and Pentagastrin as the top three molecules (Lig13b as the benchmark) based on docking energy. The ΔGbind of Lig13b, Isavuconazonium, α-KI, Pentagastrin was -28.1, -45.7, -44.7, -34.8 kcal/mol, respectively. Molecular dynamics simulation revealed that these ligands are stable within the Mpro active site. Binding of these ligands is driven by a variety of non-bonded interaction, including polar bonds, H-bonds, van der Waals and salt bridges. The overall conformational dynamics of the complexed-Mpro was slightly altered relative to apo-Mpro. This study demonstrates that three distinct classes molecules, Isavuconazonium (triazole), α-KI (ketoamide) and Pentagastrin (peptide) could serve as potential drugs to treat patients with COVID-19.

Screening of FDA Approved Drugs Against SARS-CoV-2 Main Protease: Coronavirus Disease.

At the end of December 2019, a new strain of coronavirus was identified in the Wuhan city of Hubei province in China. Within a shorter period of time, an unprecedented outbreak of this strain was witnessed over the entire Wuhan city. This novel coronavirus strain was later officially renamed as COVID-19 (Coronavirus disease 2019) by the World Health Organization. The mode of transmission was human-to-human contact and hence resulted in a rapid surge across the globe where more than 24 million people have been infected with COVID-19. In the current scenario, finding potent drug candidates for the treatment of COVID-19 has emerged as the most challenging task for clinicians and researchers worldwide. Identification of new drugs and vaccine development may take from a few months to years based on the clinical trial processes. To overcome the several limitations involved in identifying and bringing out potent drug candidates for treating COVID-19, in the present study attempts were made to screen the FDA approved drugs using High Throughput Virtual Screening (HTVS). The COVID-19 main protease (COVID-19 Mpro) was chosen as the drug target for which the FDA approved drugs were initially screened with HTVS. The drug candidates that exhibited favorable docking score, energy, and emodel calculations were further taken for performing Induced Fit Docking (IFD) using Schrodinger's GLIDE. From the flexible docking results, the following four FDA approved drugs Sincalide, Pentagastrin, Ritonavir, and Phytonadione were identified. In particular, Sincalide and Pentagastrin can be considered potential key players for the treatment of COVID-19 disease.