Development of a novel multi‑epitope vaccine against the pathogenic human polyomavirus V6/7 using reverse vaccinology

BACKGROUND

Human polyomaviruses contribute to human oncogenesis through persistent infections, but currently there is no effective preventive measure against the malignancies caused by this virus. Therefore, the development of a safe and effective vaccine against HPyV is of high priority.

METHODS

First, the proteomes of 2 polyomavirus species (HPyV6 and HPyV7) were downloaded from the NCBI database for the selection of the target proteins. The epitope identification process focused on selecting proteins that were crucial, associated with virulence, present on the surface, antigenic, non-toxic, and non-homologous with the human proteome. Then, the immunoinformatic methods were used to identify cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes from the target antigens, which could be used to create epitope-based vaccine. The physicochemical features of the designed vaccine were predicted through various online servers. The binding pattern and stability between the vaccine candidate and Toll-like receptors were analyzed through molecular docking and molecular dynamics (MD) simulation, while the immunogenicity of the designed vaccines was assessed using immune simulation.

RESULTS

Online tools were utilized to forecast the most optimal epitope from the immunogenic targets, including LTAg, VP1, and VP1 antigens of HPyV6 and HPyV7. A multi-epitope vaccine was developed by combining 10 CTL, 7 HTL, and 6 LBL epitopes with suitable linkers and adjuvant. The vaccine displayed 98.35% of the world's population coverage. The 3D model of the vaccine structure revealed that the majority of residues (87.7%) were located in favored regions of the Ramachandran plot. The evaluation of molecular docking and MD simulation revealed that the constructed vaccine exhibits a strong binding (-1414.0 kcal/mol) towards the host's TLR4. Moreover, the vaccine-TLR complexes remained stable throughout the dynamic conditions present in the natural environment. The immune simulation results demonstrated that the vaccine design had the capacity to elicit robust immune responses in the host.

CONCLUSION

The multi-parametric analysis revealed that the designed vaccine is capable of inducing sustained immunity against the selected polyomaviruses, although further in-vivo investigations are needed to verify its effectiveness.

Development of a novel squalene/α-tocopherol-based self-emulsified nanoemulsion incorporating Leishmania peptides for induction of antigen-specific immune responses

Vaccination has emerged as the most effective strategy to confront infectious diseases, among which is leishmaniasis, that threat public health. Despite laborious efforts there is still no vaccine for humans to confront leishmaniasis. Multi-epitope protein/peptide vaccines present a number of advantages, however their use along with appropriate adjuvants that may also act as antigen carriers is considered essential to overcome subunit vaccines' low immunogenicity. In the present study, a stable self-emulsified nanoemulsion was developed and double-adjuvanted with squalene and α-tocopherol. The prepared nanoemulsion droplets exhibited low cytotoxicity in a certain range of concentrations, while they were efficiently taken up by macrophages and dendritic cells in vitro as well as in vivo in secondary lymphoid organs. To further characterize nanoformulation's potent antigen delivery capability, three multi-epitope Leishmania peptides were incorporated into the nanoemulsion. Peptide encapsulation resulted in dendritic cells' functional differentiation characterized by elevated levels of maturation markers and intracellular cytokine production. Intramuscular administration of the nanoemulsion incorporating Leishmania peptides induced antigen-specific spleen cell proliferation as well as elicitation of CD4+ central memory cells, supporting the potential of the developed nanoformulation to successfully act also as an antigen delivery vehicle and thus encouraging further preclinical studies on its vaccine candidate potency.

Computational formulation of a multiepitope vaccine unveils an exceptional prophylactic candidate against Merkel cell polyomavirus

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin malignancy caused by human Merkel cell polyomavirus (MCV), leading to the most aggressive skin cancer in humans. MCV has been identified in approximately 43%-100% of MCC cases, contributing to the highly aggressive nature of primary cutaneous carcinoma and leading to a notable mortality rate. Currently, no existing vaccines or drug candidates have shown efficacy in addressing the ailment caused by this specific pathogen. Therefore, this study aimed to design a novel multiepitope vaccine candidate against the virus using integrated immunoinformatics and vaccinomics approaches. Initially, the highest antigenic, immunogenic, and non-allergenic epitopes of cytotoxic T lymphocytes, helper T lymphocytes, and linear B lymphocytes corresponding to the virus whole protein sequences were identified and retrieved for vaccine construction. Subsequently, the selected epitopes were linked with appropriate linkers and added an adjuvant in front of the construct to enhance the immunogenicity of the vaccine candidates. Additionally, molecular docking and dynamics simulations identified strong and stable binding interactions between vaccine candidates and human Toll-like receptor 4. Furthermore, computer-aided immune simulation found the real-life-like immune response of vaccine candidates upon administration to the human body. Finally, codon optimization was conducted on the vaccine candidates to facilitate the in silico cloning of the vaccine into the pET28+(a) cloning vector. In conclusion, the vaccine candidate developed in this study is anticipated to augment the immune response in humans and effectively combat the virus. Nevertheless, it is imperative to conduct in vitro and in vivo assays to evaluate the efficacy of these vaccine candidates thoroughly. These evaluations will provide critical insights into the vaccine's effectiveness and potential for further development.

In silico formulation of a next-generation multiepitope vaccine for use as a prophylactic candidate against Crimean-Congo hemorrhagic fever

BACKGROUND

Crimean-Congo hemorrhagic fever (CCHF) is a widespread disease transmitted to humans and livestock animals through the bite of infected ticks or close contact with infected persons' blood, organs, or other bodily fluids. The virus is responsible for severe viral hemorrhagic fever outbreaks, with a case fatality rate of up to 40%. Despite having the highest fatality rate of the virus, a suitable treatment option or vaccination has not been developed yet. Therefore, this study aimed to formulate a multiepitope vaccine against CCHF through computational vaccine design approaches.

METHODS

The glycoprotein, nucleoprotein, and RNA-dependent RNA polymerase of CCHF were utilized to determine immunodominant T- and B-cell epitopes. Subsequently, an integrative computational vaccinology approach was used to formulate a multi-epitopes vaccine candidate against the virus.

RESULTS

After rigorous assessment, a multiepitope vaccine was constructed, which was antigenic, immunogenic, and non-allergenic with desired physicochemical properties. Molecular dynamics (MD) simulations of the vaccine-receptor complex show strong stability of the vaccine candidates to the targeted immune receptor. Additionally, the immune simulation of the vaccine candidates found that the vaccine could trigger real-life-like immune responses upon administration to humans.

CONCLUSIONS

Finally, we concluded that the formulated multiepitope vaccine candidates would provide excellent prophylactic properties against CCHF.

Machine intelligence-guided selection of optimized inhibitor for human immunodeficiency virus (HIV) from natural products

The human immunodeficiency virus (HIV) connects to the cluster of differentiation (CD4) and any of the entry co-receptors (CCR5 and CXCR4); followed by unloading the viral genome, reverse transcriptase, and integrase enzymes within the host cell. The co-receptors facilitate the entry of virus and vital enzymes, leading to replication and pre-maturation of viral particles within the host. The protease enzyme transforms the immature viral vesicles into the mature virion. The pivotal role of co-receptors and enzymes in homeostasis and growth makes the crucial target for anti-HIV drug discovery, and the availability of X-ray crystal structures is an asset. Here, we used the machine intelligence-driven framework (A-HIOT) to identify and optimize target-based potential hit molecules for five significant protein targets from the ZINC15 database (natural products dataset). Following validation with dynamic motion behavior analysis and molecular dynamics simulation, the optimized hits were evaluated using in silico ADMET filtration. Furthermore, three molecules were screened, optimized, and validated: ZINC00005328058 for CCR5 and protease, ZINC000254014855 for CXCR4 and integrase, and ZINC000000538471 for reverse transcriptase. In clinical trials, the ZINC000254014855 and ZINC000254014855 were passed in primary screens for vif-HIV-1, and we reported the specific receptor as well as interactions. As a result, the validated molecules may be investigated further in experimental studies targeting specific receptors in order to design and synergize an anti-HIV regimen.

Immunoinformatics Approach to Design a Multi-Epitope Nanovaccine against Leishmania Parasite: Elicitation of Cellular Immune Responses

Leishmaniasis is a vector-borne disease caused by an intracellular parasite of the genus Leishmania with different clinical manifestations that affect millions of people worldwide, while the visceral form may be fatal if left untreated. Since the available chemotherapeutic agents are not satisfactory, vaccination emerges as the most promising strategy for confronting leishmaniasis. In the present study, a reverse vaccinology approach was adopted to design a pipeline starting from proteome analysis of three different Leishmania species and ending with the selection of a pool of MHCI- and MHCII-binding epitopes. Epitopes from five parasite proteins were retrieved and fused to construct a multi-epitope chimeric protein, named LeishChim. Immunoinformatics analyses indicated that LeishChim was a stable, non-allergenic and immunogenic protein that could bind strongly onto MHCI and MHCII molecules, suggesting it as a potentially safe and effective vaccine candidate. Preclinical evaluation validated the in silico prediction, since the LeishChim protein, encapsulated simultaneously with monophosphoryl lipid A (MPLA) into poly(D,L-lactide-co-glycolide) (PLGA) nanoparticles, elicited specific cellular immune responses when administered to BALB/c mice. These were characterized by the development of memory CD4⁺ T cells, as well as IFNγ- and TNFα-producing CD4⁺ and CD8⁺ T cells, supporting the potential of LeishChim as a vaccine candidate.

Mapping Potential Vaccine Candidates Predicted by VaxiJen for Different Viral Pathogens between 2017-2021-A Scoping Review

Reverse vaccinology (RV) is a promising alternative to traditional vaccinology. RV focuses on in silico methods to identify antigens or potential vaccine candidates (PVCs) from a pathogen's proteome. Researchers use VaxiJen, the most well-known RV tool, to predict PVCs for various pathogens. The purpose of this scoping review is to provide an overview of PVCs predicted by VaxiJen for different viruses between 2017 and 2021 using Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) guidelines. We used the term 'vaxijen' to search PubMed, Scopus, Web of Science, EBSCOhost, and ProQuest One Academic. The protocol was registered at the Open Science Framework (OSF). We identified articles on this topic, charted them, and discussed the key findings. The database searches yielded 1033 articles, of which 275 were eligible. Most studies focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), published between 2020 and 2021. Only a few articles (8/275; 2.9%) conducted experimental validations to confirm the predictions as vaccine candidates, with 2.2% (6/275) articles mentioning recombinant protein expression. Researchers commonly targeted parts of the SARS-CoV-2 spike (S) protein, with the frequently predicted epitopes as PVCs being major histocompatibility complex (MHC) class I T cell epitopes WTAGAAAYY, RQIAPGQTG, IAIVMVTIM, and B cell epitope IAPGQTGKIADY, among others. The findings of this review are promising for the development of novel vaccines. We recommend that vaccinologists use these findings as a guide to performing experimental validation for various viruses, with SARS-CoV-2 as a priority, because better vaccines are needed, especially to stay ahead of the emergence of new variants. If successful, these vaccines could provide broader protection than traditional vaccines.

25 (S)-Hydroxycholesterol acts as a possible dual enzymatic inhibitor of SARS-CoV-2 Mpro and RdRp-: an insight from molecular docking and dynamics simulation approaches

The coronavirus disease (COVID-19) pandemic has rapidly extended globally and killed approximately 5.83 million people all over the world. But, to date, no effective therapeutic against the disease has been developed. The disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and enters the host cell through the spike glycoprotein (S protein) of the virus. Subsequently, RNA-dependent RNA polymerase (RdRp) and main protease (M^pro) of the virus mediate viral transcription and replication. Mechanistically inhibition of these proteins can hinder the transcription as well as replication of the virus. Recently oxysterols and its derivative, such as 25 (S)-hydroxycholesterol (25-HC) has shown antiviral activity against SARS-CoV-2. But the exact mechanisms and their impact on RdRp and M^pro have not been explored yet. Therefore, the study aimed to identify the inhibitory activity of 25-HC against the viral enzymes RdRp and M^pro simultaneously. Initially, a molecular docking simulation was carried out to evaluate the binding activity of the compound against the two proteins. The pharmacokinetics (PK) and toxicity parameters were analyzed to observe the 'drug-likeness' properties of the compound. Additionally, molecular dynamics (MD) simulation was performed to confirm the binding stability of the compound to the targeted protein. Furthermore, molecular mechanics generalized Born surface area (MM-GBSA) was used to predict the binding free energies of the compound to the targeted protein. Molecular docking simulation identified low glide energy -51.0 kcal/mol and -35.0 kcal/mol score against the RdRp and M^pro, respectively, where MD simulation found good binding stability of the compound to the targeted proteins. In addition, the MM/GBSA approach identified a good value of binding free energies (ΔG bind) of the compound to the targeted proteins. Therefore, the study concludes that the compound 25-HC could be developed as a treatment and/or prevention option for SARS-CoV-2 disease-related complications. Although, experimental validation is suggested for further evaluation of the work.Communicated by Ramaswamy H. Sarma.

Toward the Identification of Natural Antiviral Drug Candidates against Merkel Cell Polyomavirus: Computational Drug Design Approaches

Merkel cell carcinoma (MCC) is a rare form of aggressive skin cancer mainly caused by Merkel cell polyomavirus (MCPyV). Most MCC tumors express MCPyV large T (LT) antigens and play an important role in the growth-promoting activities of oncoproteins. Truncated LT promotes tumorigenicity as well as host cell proliferation by activating the viral replication machinery, and inhibition of this protein in humans drastically lowers cellular growth linked to the corresponding cancer. Our study was designed with the aim of identifying small molecular-like natural antiviral candidates that are able to inhibit the proliferation of malignant tumors, especially those that are aggressive, by blocking the activity of viral LT protein. To identify potential compounds against the target protein, a computational drug design including molecular docking, ADME (absorption, distribution, metabolism, and excretion), toxicity, molecular dynamics (MD) simulation, and molecular mechanics generalized Born surface area (MM-GBSA) approaches were applied in this study. Initially, a total of 2190 phytochemicals isolated from 104 medicinal plants were screened using the molecular docking simulation method, resulting in the identification of the top five compounds having the highest binding energy, ranging between −6.5 and −7.6 kcal/mol. The effectiveness and safety of the selected compounds were evaluated based on ADME and toxicity features. A 250 ns MD simulation confirmed the stability of the selected compounds bind to the active site (AS) of the target protein. Additionally, MM-GBSA analysis was used to determine the high values of binding free energy (ΔG bind) of the compounds binding to the target protein. The five compounds identified by computational approaches, Paulownin (CID: 3084131), Actaealactone (CID: 11537736), Epigallocatechin 3-O-cinnamate (CID: 21629801), Cirsilineol (CID: 162464), and Lycoricidine (CID: 73065), can be used in therapy as lead compounds to combat MCPyV-related cancer. However, further wet laboratory investigations are required to evaluate the activity of the drugs against the virus.

Evaluation of in vitro and in silico anti-inflammatory potential of some selected medicinal plants of Bangladesh against cyclooxygenase-II enzyme

ETHNOPHARMACOLOGICAL RELEVANCE

Medicinal plants are sources of chemical treasures that can be used in treatment of different diseases, including inflammatory disorders. Traditionally, Heritiera littoralis, Ceriops decandra, Ligustrum sinense, and Polyscias scutellaria are used to treat pain, hepatitis, breast inflammation. The present research was designed to explore phytochemicals from the ethanol extracts of H. littoralis, C. decandra, L. sinense, and P. scutellaria to discern the possible pharmacophore (s) in the treatment of inflammatory disorders.

MATERIAL AND METHODS

The chemical compounds of experimental plants were identified through GC-MS analysis. Furthermore, in-vitro anti-inflammatory activity was assessed in human erythrocytes and an in-silico study was appraised against COX-2.

RESULTS

The experimental extracts totally revealed 77 compounds in GC-MS analysis and all the extracts showed anti-inflammatory activity in in-vitro assays. The most favorable phytochemicals as anti-inflammatory agents were selected via ADMET profiling and molecular docking with specific protein of the COX-2 enzyme. Molecular dynamics simulation (MDS) confirmed the stability of the selected natural compound at the binding site of the protein. Three phytochemicals exhibited the better competitive result than the conventional anti-inflammatory drug naproxen in molecular docking and MDS studies.

CONCLUSION

Both experimental and computational studies have scientifically revealed the folklore uses of the experimental medicinal plants in inflammatory disorders. Overall, N-(2-hydroxycyclohexyl)-4-methylbenzenesulfonamide (PubChem CID: 575170); Benzeneethanamine, 2-fluoro-. beta., 3, 4-trihydroxy-N-isopropyl (PubChem CID: 547892); and 3,5-di-tert-butylphenol (PubChem CID: 70825) could be the potential leads for COX-2 inhibitor for further evaluation of drug-likeliness.

Designing of a multi-epitopes-based peptide vaccine against rift valley fever virus and its validation through integrated computational approaches

Since its discovery, the Rift Valley Fever virus (RVFV) has been the source of numerous outbreaks in the Arab Peninsulas and Africa, wreaking havoc on humans and animals. The lack of therapeutics or licensed human vaccines limits the options for controlling RVFV outbreaks. Therefore, RVFV has been prioritized for rapid research and innovation of prevention strategies to control and prevent its outbreaks. The purpose of this study was to design a multi-epitope-based peptide vaccine (MEBPV) against RVFV. Bioinformatics approaches were used to design a potent MEBPV that can potentially activate both CD8⁺ and CD4⁺ T-cell immune responses, and several computational tools were employed to investigate its biological activities. Three antigenic proteins (Nucleocapsid (N), Glycoprotein C (GC), and Glycoprotein N (GN)) from the RVFV were chosen and potential immunogenic T- and B -cell epitopes were predicted from them. Based on in silico analysis, a MEBPV based on highly scored T and B-cell epitopes (6 CTL, 5 HTL, and 4 LBL) combined with linkers and adjuvants was developed. The finest predicted model was used for docking studies with Toll-like receptors (TLR3 and TLR8) and MHC molecules (MHC I and MHC II) after predicting and analyzing the tertiary structure of MEBPV. The designed MEBPV was then tested for stability with TLR3 and TLR8 receptors using molecular dynamics (MD) simulation and MMGBSA analysis. The MEBPV -TLR3, MEBPV -TLR8, MEBPV-MHC I and MEBPV -MHC II docked models were found stable during simulation time in MD and MMGBSA studies. In silico analysis revealed that the constructed vaccine could elicit both cell-mediated and humoral immune responses simultaneously. The proposed MEBPV could be a strong candidate against RVFV, but it will need to be tested in the laboratory to guarantee its safety and immunogenicity.

Spike protein recognizer receptor ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2

Angiotensin-converting enzyme 2 (ACE2), also known as peptidyl-dipeptidase A, belongs to the dipeptidyl carboxydipeptidases family has emerged as a potential antiviral drug target against SARS-CoV-2. Most of the ACE2 inhibitors discovered till now are chemical synthesis; suffer from many limitations related to stability and adverse side effects. However, natural, and selective ACE2 inhibitors that possess strong stability and low side effects can be replaced instead of those chemicals' inhibitors. To envisage structurally diverse natural entities as an ACE2 inhibitor with better efficacy, a 3D structure-based-pharmacophore model (SBPM) has been developed and validated by 20 known selective inhibitors with their correspondence 1166 decoy compounds. The validated SBPM has excellent goodness of hit score and good predictive ability, which has been appointed as a query model for further screening of 11,295 natural compounds. The resultant 23 hits compounds with pharmacophore fit score 75.31 to 78.81 were optimized using in-silico ADMET and molecular docking analysis. Four potential natural inhibitory molecules namely D-DOPA (Amb17613565), L-Saccharopine (Amb6600091), D-Phenylalanine (Amb3940754), and L-Mimosine (Amb21855906) have been selected based on their binding affinity (−7.5, −7.1, −7.1, and −7.0 kcal/mol), respectively. Moreover, 250 ns molecular dynamics (MD) simulations confirmed the structural stability of the ligands within the protein. Additionally, MM/GBSA approach also used to support the stability of molecules to the binding site of the protein that also confirm the stability of the selected four natural compounds. The virtual screening strategy used in this study demonstrated four natural compounds that can be utilized for designing a future class of potential natural ACE2 inhibitor that will block the spike (S) protein dependent entry of SARS-CoV-2 into the host cell.

Designing of a Multi-epitope Vaccine against the Structural Proteins of Marburg Virus Exploiting the Immunoinformatics Approach

Marburg virus disease (MVD) caused by the Marburg virus (MARV) generally appears with flu-like symptoms and leads to severe hemorrhagic fever. It spreads via direct contact with infected individuals or animals. Despite being considered to be less threatening in terms of appearances and the number of infected patients, the high fatality rate of this pathogenic virus is a major concern. Until now, no vaccine has been developed to combat this deadly virus. Therefore, vaccination for this virus is necessary to reduce its mortality. Our current investigation focuses on the design and formulation of a multi-epitope vaccine based on the structural proteins of MARV employing immunoinformatics approaches. The screening of potential T-cell and B-cell epitopes from the seven structural proteins of MARV was carried out through specific selection parameters. Afterward, we compiled the shortlisted epitopes by attaching them to an appropriate adjuvant and linkers. Population coverage analysis, conservancy analysis, and MHC cluster analysis of the shortlisted epitopes were satisfactory. Importantly, physicochemical characteristics, human homology assessment, and structure validation of the vaccine construct delineated convenient outcomes. We implemented disulfide bond engineering to stabilize the tertiary or quaternary interactions. Furthermore, stability and physical movements of the vaccine protein were explored using normal-mode analysis. The immune simulation study of the vaccine complexes also exhibited significant results. Additionally, the protein-protein docking and molecular dynamics simulation of the final construct exhibited a higher affinity toward toll-like receptor-4 (TLR4). From simulation trajectories, multiple descriptors, namely, root mean square deviations (rmsd), radius of gyration (Rg), root mean square fluctuations (RMSF), solvent-accessible surface area (SASA), and hydrogen bonds, have been taken into account to demonstrate the inflexible and rigid nature of receptor molecules and the constructed vaccine. Inclusively, our findings suggested the vaccine constructs' ability to regulate promising immune responses against MARV pathogenesis.

Compounds Identified from Marine Mangrove Plant (Avicennia alba) as Potential Antiviral Drug Candidates Against WDSV, an In-Silico Approach

Walleye dermal sarcoma virus (WDSV) is a type of retrovirus, which affects most of the adult walleye fishes during the spawning time. The virus causes multiple epithelial tumors on the fish’s skin and fins that are liable for more than 50% of the mortality rate of fish around the world. Till now, no effective antiviral drug or vaccine candidates have been developed that can block the progression of the disease caused by the pathogen. It was found that the 582-amino-acid (aa) residues long internal structural gag polyprotein of the virus plays an important role in virus budding and virion maturation outside of the cell. Inhibition of the protein can block the budding and virion maturation process and can be developed as an antiviral drug candidate against the virus. Therefore, the study aimed to identify potential natural antiviral drug candidates from the tropical mangrove marine plant Avicennia alba, which will be able to block the budding and virion maturation process by inhibiting the activity of the gag protein of the virus. Initially, a homology modeling approach was applied to identify the 3D structure, followed by refinement and validation of the protein. The refined protein structures were then utilized for molecular docking simulation. Eleven phytochemical compounds have been isolated from the marine plant and docked against the virus gag polyprotein. Three compounds, namely Friedlein (CID244297), Phytosterols (CID12303662), and 1-Triacontanol (CID68972) have been selected based on their docking score −8.5 kcal/mol, −8.0 kcal/mol and −7.9 kcal/mol, respectively, and were evaluated through ADME (Absorption, Distribution, Metabolism and Excretion), and toxicity properties. Finally, molecular dynamics (MD) simulation was applied to confirm the binding stability of the protein-ligands complex structure. The ADME and toxicity analysis reveal the efficacy and non-toxic properties of the compounds, where MD simulation confirmed the binding stability of the selected three compounds with the targeted protein. This computational study revealed the virtuous value of the selected three compounds against the targeted gag polyprotein and will be effective and promising antiviral candidates against the pathogen in a significant and worthwhile manner. Although in vitro and in vivo study is required for further evaluation of the compounds against the targeted protein.

Pharmacoinformatics and molecular dynamics simulation-based phytochemical screening of neem plant (Azadiractha indica) against human cancer by targeting MCM7 protein

Minichromosome maintenance complex component 7 (MCM7) belongs to the minichromosome maintenance family that is important for the initiation of eukaryotic DNA replication. Overexpression of the MCM7 protein is relative to cellular proliferation and responsible for aggressive malignancy in various cancers. Mechanistically, inhibition of MCM7 significantly reduces the cellular proliferation associated with cancer. To date, no effective small molecular candidate has been identified that can block the progression of cancer induced by the MCM7 protein. Therefore, the study has been designed to identify small molecular-like natural drug candidates against aggressive malignancy associated with various cancers by targeting MCM7 protein. To identify potential compounds against the targeted protein a comprehensive in silico drug design including molecular docking, ADME (Absorption, Distribution, Metabolism and Excretion), toxicity, and molecular dynamics (MD) simulation approaches has been applied. Seventy phytochemicals isolated from the neem tree (Azadiractha indica) were retrieved and screened against MCM7 protein by using the molecular docking simulation method, where the top four compounds have been chosen for further evaluation based on their binding affinities. Analysis of ADME and toxicity properties reveals the efficacy and safety of the selected four compounds. To validate the stability of the protein-ligand complex structure MD simulations approach has also been performed to the protein-ligand complex structure, which confirmed the stability of the selected three compounds including CAS ID:105377-74-0, CID:12308716 and CID:10505484 to the binding site of the protein. In the study, a comprehensive data screening process has performed based on the docking, ADMET properties, and MD simulation approaches, which found a good value of the selected four compounds against the targeted MCM7 protein and indicates as a promising and effective human anticancer agent.