In Silico Design and Evaluation of a Novel Therapeutic Agent Against the Spike Protein as a Novel Treatment Strategy for COVID-19 Treatment

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a viral respiratory disease that is associated with severe damage to other human organs. It causes by a novel coronavirus, and it is spreading all over the world. To date, there is some approved vaccine or therapeutic agent which could be effective against this disease. But their effectiveness against mutated strains is not studied completely. The spike glycoprotein on the surface of the coronaviruses gives the virus the ability to bind to host cell receptors and enter cells. Inhibition of attachment of these spikes can lead to virus neutralization by inhibiting viral entrance.

AIMS

In this study, we tried to use the virus entrance strategy against itself by utilizing virus receptor (ACE-2) in order to design an engineered protein consisting of a human Fc antibody fragment and a part of ACE-2, which reacts with virus RBD, and we also evaluated this interaction by computational methods and in silico methods. Subsequently, we have designed a new protein structure to bind with this site and inhibit the virus from attaching to its cell receptor, mechanically or chemically.

METHODS

Various in silico software, bioinformatics, and patent databases were used to retrieve the requested gene and protein sequences. The physicochemical properties and possibility of allergenicity were also examined. Three-dimensional structure prediction and molecular docking were also performed to develop the most suitable therapeutic protein.

RESULTS

The designed protein consisted of a total of 256 amino acids with a molecular weight of 28984.62 and 5.92 as a theoretical isoelectric point. Instability and aliphatic index and grand average of hydropathicity are 49.99, 69.57 and -0.594, respectively.

CONCLUSIONS

In silico studies can provide a good opportunity to study viral proteins and new drugs or compounds since they do not need direct exposure to infectious agents or equipped laboratories. The suggested therapeutic agent should be further characterized in vitro and in vivo.

Sequence Similarity among Structural Repeats in the Piezo Family of Mechanosensitive Ion Channels

Members of the Piezo family of mechanically activated cation channels are involved in multiple physiological processes in higher eukaryotes, including vascular development, cell differentiation, touch perception, hearing, and more, but they are also common in single-celled eukaryotic microorganisms. Mutations in these proteins in humans are associated with a variety of diseases, such as colorectal adenomatous polyposis, dehydrated hereditary stomatocytosis, and hereditary xerocytosis. Available 3D structures for Piezo proteins show nine regions of four transmembrane segments each that have the same fold. Despite the remarkable similarity among the nine characteristic structural repeats in the family, no significant sequence similarity among them has been reported. Using bioinformatics approaches and the Transporter Classification Database (TCDB) as reference, we reliably identified sequence similarity among repeats based on four lines of evidence: (1) hidden Markov model-profile similarities across repeats at the family level, (2) pairwise sequence similarities between different repeats across Piezo homologs, (3) Piezo-specific conserved sequence signatures that consistently identify the same regions across repeats, and (4) conserved residues that maintain the same orientation and location in 3D space.

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling

SARS-CoV-2 triggered a worldwide medical crisis, affecting the world’s social, emotional, physical, and economic equilibrium. However, treatment choices and targets for finding a solution to COVID-19’s threat are becoming limited. A viable approach to combating the threat of COVID-19 is by unraveling newer pharmacological and therapeutic targets pertinent in the viral survival and adaptive mechanisms within the host biological milieu which in turn provides the opportunity to discover promising inhibitors against COVID-19. Therefore, using high-throughput virtual screening, manually curated compounds library from some medicinal plants were screened against four main drivers of SARS-CoV-2 (spike glycoprotein, PLpro, 3CLpro, and RdRp). In addition, molecular docking, Prime MM/GBSA (molecular mechanics/generalized Born surface area) analysis, molecular dynamics (MD) simulation, and drug-likeness screening were performed to identify potential phytodrugs candidates for COVID-19 treatment. In support of these approaches, we used a series of computational modeling approaches to develop therapeutic agents against COVID-19. Out of the screened compounds against the selected SARS-CoV-2 therapeutic targets, only compounds with no violations of Lipinski’s rule of five and high binding affinity were considered as potential anti-COVID-19 drugs. However, lonchocarpol A, diplacol, and broussonol E (lead compounds) were recorded as the best compounds that satisfied this requirement, and they demonstrated their highest binding affinity against 3CLpro. Therefore, the 3CLpro target and the three lead compounds were selected for further analysis. Through protein–ligand mapping and interaction profiling, the three lead compounds formed essential interactions such as hydrogen bonds and hydrophobic interactions with amino acid residues at the binding pocket of 3CLpro. The key amino acid residues at the 3CLpro active site participating in the hydrophobic and polar inter/intra molecular interaction were TYR54, PRO52, CYS44, MET49, MET165, CYS145, HIS41, THR26, THR25, GLN189, and THR190. The compounds demonstrated stable protein–ligand complexes in the active site of the target (3CLpro) over a 100 ns simulation period with stable protein–ligand trajectories. Drug-likeness screening shows that the compounds are druggable molecules, and the toxicity descriptors established that the compounds demonstrated a good biosafety profile. Furthermore, the compounds were chemically reactive with promising molecular electron potential properties. Collectively, we propose that the discovered lead compounds may open the way for establishing phytodrugs to manage COVID-19 pandemics and new chemical libraries to prevent COVID-19 entry into the host based on the findings of this computational investigation.

Structure-based discovery of selective CYP17A1 inhibitors for Castration-resistant prostate cancer treatment

Prostate cancer (PCa) is the most common malignancy found in men and the second leading cause of cancer-related death worldwide. Castration-resistant PCa (CRPC) is defined by PCa cells that stop responding to hormone therapy. Cytochrome P450 17α-hydroxylase/17,20-lyase (CYP17A1) plays a critical role in the biosynthesis of androgens in humans. Androgen signaling cascade is a principal survival pathway for PCa cells and androgen-deprivation therapy (ADT) remains the key treatment for patients marked with locally advanced and metastatic PCa cells. Available synthetic drugs have been reported for toxicity, drug resistance, and decreasing efficacy. Thus, the design of novel selective inhibitors of CYP17A1 lyase would help circumvent associated side effects and improve pharmacological activities. Therefore, we employed structural bioinformatics techniques via molecular docking; molecular mechanics generalized born surface area (MM-GBSA), molecular dynamics (MD) simulation, and pharmacokinetic study to identify putative CYP17A1 lyase inhibitors. The results of the computational investigation showed that the Prunus dulcis compounds exhibited higher binding energy than the clinically approved abiraterone acetate. The stability of the ligand with the highest binding affinity (quercetin-3-o-rutinoside) was observed during MD simulation for 10 ns. Quercetin-3-o-rutinoside was observed to be stable within the active site of CYP17A1Lyase throughout the simulation period. The result of the pharmacokinetic study revealed that these compounds are promising therapeutic agents. Collectively, this study proposed that bioactive compounds from P. dulcis may be potential selective inhibitors of CYP17A1Lyase in CRPC treatments.

Anticancer Potential of Moringa oleifera on BRCA-1 Gene: Systems Biology

Breast cancer has consistently been a global challenge that is prevalent among women. There is a continuous increase in the high number of women mortality rates because of breast cancer and affecting nations at all modernization levels. Women with high-risk factors, including hereditary, obesity, and menopause, have the possibility of developing breast cancer growth. With the advent of radiotherapy, chemotherapy, hormone therapy, and surgery in breast cancer treatment, breast cancer survivors have increased. Also, the design and development of drugs targeting therapeutic enzymes effectively treat the tumour cells early. However, long-term use of anticancer drugs has been linked to severe side effects. This research aims to develop potential drug candidates from Moringa oleifera, which could serve as anticancer agents. In silico analysis using Schrödinger Molecular Drug Discovery Suite and SWISS ADME was employed to determine the therapeutic potential of phytochemicals from M oleifera against breast cancer via molecular docking, pharmacokinetic parameters, and drug-like properties. The result shows that rutin, vicenin-2, and quercetin-3-O-glucoside have the highest binding energy of −7.522, −6.808, and −6.635 kcal/mol, respectively, in the active site of BRCA-1. The essential amino acids involved in the protein-ligand interaction following active site analysis are ASN 1678, ASN 1774, GLY 1656, LEU 1657, GLN 1779, LYS 1702, SER 1655, PHE 1662, ARG 1699, GLU 1698, and VAL 1654. Thus, we propose that bioactive compounds from M oleifera may be potential novel drug candidates in the treatment of breast cancer.

Immuno-informatics design of a multimeric epitope peptide based vaccine targeting SARS-CoV-2 spike glycoprotein

Developing an efficacious vaccine for SARS-CoV-2 infection is critical to stemming COVID-19 fatalities and providing the global community with immune protection. We have used a bioinformatic approach to aid in designing an epitope peptide-based vaccine against the spike protein of the virus. Five antigenic B cell epitopes with viable antigenicity and a total of 27 discontinuous B cell epitopes were mapped out structurally in the spike protein for antibody recognition. We identified eight CD8+ T cell 9-mers and 12 CD4+ T cell 14-15-mer as promising candidate epitopes putatively restricted by a large number of MHC I and II alleles, respectively. We used this information to construct an in silico chimeric peptide vaccine whose translational rate was highly expressed when cloned in pET28a (+) vector. With our In silico test, the vaccine construct was predicted to elicit high antigenicity and cell-mediated immunity when given as a homologous prime-boost, triggering of toll-like receptor 5 by the adjuvant linker. The vaccine was also characterized by an increase in IgM and IgG and an array of Th1 and Th2 cytokines. Upon in silico challenge with SARS-CoV-2, there was a decrease in antigen levels using our immune simulations. We, therefore, propose that potential vaccine designs consider this approach.

The Relevance of Bioinformatics Applications in the Discovery of Vaccine Candidates and Potential Drugs for COVID-19 Treatment

The application of bioinformatics to vaccine research and drug discovery has never been so essential in the fight against infectious diseases. The greatest combat of the 21st century against a debilitating disease agent SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus discovered in Wuhan, China, December 2019, has piqued an unprecedented usage of bioinformatics tools in deciphering the molecular characterizations of infectious pathogens. With the viral genome data of SARS-COV-2 been made available barely weeks after the reported outbreak, bioinformatics platforms have become an all-time critical tool to gain time in the fight against the disease pandemic. Before the outbreak, different platforms have been developed to explore antigenic epitopes, predict peptide-protein docking and antibody structures, and simulate antigen-antibody reactions and lots more. However, the advent of the pandemic witnessed an upsurge in the application of these pipelines with the development of newer ones such as the Coronavirus Explorer in the development of efficacious vaccines, drug repurposing, and/or discovery. In this review, we have explored the various pipelines available for use, their relevance, and limitations in the timely development of useful therapeutic candidates from genomic data knowledge to clinical therapy.

The function annotations of ST3GAL4 in human LAMP1 and Lassa virus GP-C interaction from the perspective of systems virology

Lassa virus (LASV) is a single-stranded RNA virus that has plagued the Sub-Saharan part of Africa, precisely Nigeria where various pathogenic strains with varied genomic isoforms have been identified. The human lysosomal-associated membrane protein 1 (LAMP1) is alternately required for the micropinocytosis of LASV. Therefore, it is of interest to understand the mechanism of action of the host LAMP1 with LASV protein during infection. The role of ST3 beta-galactoside alpha-2, 3-sialyltransferase 4 (ST3GAL4) in the interaction between LASV (glycoprotein) GP-C and the human LAMP1 is relevant in this context. Deposited curated protein sequences of both LAMP1 and LASV GP-C were retrieved for the study. The ST3GAL4 associated data was constructed and analysed from weighted network analysis to infer the function annotations and molecular mediators that characterize the LASV infection. The gene network shows that glycoprotein sialylation, sialyltransferase enzymatic activities and glycosphingolipid biosynthesis are linked with the ST3GAL4 function. However, the physical interaction of FAM 213A, CD8B molecule and proprotein convertase subtilisin/kexin type 1 inhibitor (PCSK1N) with ST3GAL4 is intriguing in this perspective. There are 11 glycosylated asparagine sequons of the human LAMP1 but only nine were assigned a sialylated glycan cap to mediate the LASV GP-C and LAMP1 interaction having exceeded a recommended glycosylation threshold of 0.5. Therefore, the sialylated glycans of the human LAMP1 are a total of nine and these sialylated glycans mediate the molecular recognition between LASV and LAMP1. This study therefore, predicts that there is a cellular interchange between N-linked glycosylation properties of the human LAMP1 and LASV glycoprotein, and sialylation functions of ST3GAL4 in LASV infectivity. Further studies and the clinical trial of this predictive model on the sialylated glycans of LAMP1 will facilitate the understanding of the LASV micropinocytosis process in host cells.