Active Site Prediction Research Articles

Phylogenetic analyses, protein modeling and active site prediction of two pathogenesis related (PR2 and PR3) genes from bread wheat.

Wheat is a major staple food and has been extensively grown around the globe. Sessile nature of plants has exposed them to a lot of biotic and abiotic stresses including fungal pathogen attack. Puccinia graminis f.sp. tritici causes stem rust in the wheat crop and leads to 70% decrease in its production. Pathogenesis-related (PR) proteins provide plants with defense against different fungal pathogens as these proteins have antifungal activities. This study was designed to screen Pakistani wheat varieties for PR2 and PR3 proteins and their in silico characterization. PR2 and PR3 genes were screened and isolated by PCR amplification from wheat variety Chenab-70 and Frontana, respectively. The nucleotide sequences of PR2 and PR3 genes were deposited in GenBank with accession numbers MT303867 and MZ766118, respectively. Physicochemical properties, secondary and tertiary structure predictions, and molecular docking of protein sequences of PR2 and PR3 were performed using different bioinformatics tools and software. PR2 and PR3 genes were identified to encode β–1,3–glucanase and chitinase proteins, respectively. Molecular docking of both PR2 and PR3 proteins with beta-glucan and chitin (i.e. their respective ligands) showed crucial amino acid residues involved in molecular interactions. Conclusively, molecular docking analysis of β–1,3–glucanase and chitinase proteins revealed crucial amino acid residues which are involved in ligand binding and important interactions which might have important role in plant defense against fungal pathogens. Moreover, the active residues in the active sties of these proteins can be identified through mutational studies and resulting information might help understanding how these proteins are involved in plant defense mechanisms.

Identification of biomolecules for Alzheimer's disease using docking analysis of tau protein

Objective: In-silico methods to find and characterize the ligands against the active site of tau protein which could assist in the therapeutics of Alzheimer's disease. Methods: The aid of various bioinformatic tools such as phylogenetic analysis, homology modeling, and active site prediction led to the molecular docking analysis of the major malefactor for Alzheimer’s disease ‘microtubule- associated tau protein’. A three-dimensional structure of microtubule-related tau protein was created, and the Ramachandran plot was acquired for quality appraisal. Results: Procheck showed 62.95 of residues in the most preferred region with 20% residues in the additional allowed region and 5.7 % in the disallowed region of microtubule-associated tau protein. Screenings of the particles were done dependent on Lipinski's standard of five. Conclusion: Genistein, Hesperidin, and epigallocatechin-3 are the potential ligands in regulating microtubule-related tau protein and Epigallocatechin-3 gallate is the most potent among them and the most elevated negative free vitality of official with the maximum interacting surface territory throughout docking studies.

Bioinformatics Analysis of B. Abortus Strain 2308 Protein and Its Drug Docking

Brucellosis is among the fast-spreading disease on Earth causing casualties in livestock as well as in humans. It’s an alarming situation to kick off the study of Brucellosis causing agent. Brucellosis is an infective sickness caused by Brucella abortus. Here, we have carried out the Insilco analysis of Brucella abortus strain 2308. This strain is mainly responsible for the disease. Here, we have tried to study the B. abortus strain 2308 by the means of bioinformatics methodology. We have run several Insilco tools to predict its structure and function. Moreover, we have carried out the methodology of protein homology modelling on this strain. Furthermore, we have also carried out several protein chain analyses, protein-protein interface, structure alignment, structure prediction and active site prediction. To make our study more productive we have also performed drug docking. These results will add on a little info in the emerging bioinformatics data regarding Brucella abortus.

Catalyst-free activation of permanganate under visible light irradiation for sulfamethazine degradation: Experiments and theoretical calculation

In this study, visible light (VL) was adopted for permanganate (PM) activation without additional catalyst, where sulfamethazine (SMT) was selected as the probe compound. Experiment results showed that the VL/PM system can effectively degrade SMT through pseudo-first-order reaction kinetics. Influencing factors including PM dosage, solution pH, humid acid (HA) and coexisting anions (CO32−, SO42−, Cl− and NO3−) which affect SMT photo-degradation were also examined. Pyrophosphate (PP) had an inhibitory effect on SMT degradation due to the complexation of PP with Mn (III). Electron spin resonance (ESR) spectrometry and UV-Vis spectrophotometer proved that VL can activate PM to generate ·O2− and Mn (III) reactive species. Furthermore, based on the active site prediction, intermediates identification and Density Functional Theory (DFT) calculation, two main degradation pathways involving SMT molecular rearrangement and cleavage of S–N bond were proposed. Moreover, the energy barriers of the two degradation pathways were also calculated. This study offers a novel approach for aqueous SMT removal and deepens our understanding of the degradation mechanism of SMT through DFT calculation, which hopes to shed light on the future development of VL/PM treatment.

Identification of Novel Anticancer Agent by in silico Methods for Inhibition of KLK-12 Protein

A critical route for cancer metastases is pathological angiogenesis. The protein Kallikrein-12 (KLK-12) is a serine protease reported to be involved in a variety of biochemical processes that have a functional role in angiogenesis. The KLK-12 protein hydrolyzes the cysteine rich angiogenic inducer 61 (CYR61) protein and controls the bioavailability of angiogenesis-inducing growth factors. The work proposed involves the homology modeling of the KLK-12 protein, identify essential residues to be putatively linked to the natural substrate. Protein-protein docking is done to characterize Trp35, Gln36, Gly38, Trp82 and His107 residues of the active site, in addition to active site servers (active site prediction server and CASTp). Using Auto Dock Vina software, virtual screening studies were carried out to identify the substituted carboxamide scaffolds as a pharmacophore binding at the active site. Based on binding energy, ADME and visual inspection, an isochromene carboxamide moiety is identified as antiangiogenic and cancer antagonists.

In-silico studies on Myo inositol-1-phosphate synthase of Leishmania donovani in search of anti-leishmaniasis

Myo-inositol is one of the vital nutritional requirements for the Leishmania parasites’ survival and virulence in the mammalian host. . Myo-inositol-1-phosphate synthase (MIPS) is responsible for the synthesis of myo-inositol in Leishmania, which plays a vital role in Leishmania’s virulence to mammalian hosts. Earlier studies suggest MIP synthase as a potential drug target against which valproate was used as a drug. So, MIP synthase can be used as a target for anti-leishmanial drugs, and its inhibition may help in preventing leishmaniasis. The present study aims to identify valproate's potent analogs as drugs against MIP synthase of L. donovani (Ld-MIPS) with minimum side effects and toxicity to host. In this study, the three-dimensional structure of Ld-MIPS was built, followed by active site prediction. Ligand-based virtual screening was done using hybrid similarity recognition methods. The best 123 valproate analogs were filtered based on their quantitative structure activity relationship (QSAR) properties and were docked against Ld-MIPS using FlexX, PyRx and iGEMDOCK software. The topmost five ligands were selected for molecular dynamics simulation and pharmacokinetic analysis based on the docking score. Simulation studies up to 30 ns revealed that all five lead molecules bound with Ld-MIPS throughout MD simulation and there was no variation in their backbone. All the chosen inhibitors exhibited good pharmacokinetics/ADMET predictions with an excellent absorption profile, metabolism, oral bioavailability, solubility, excretion, and minimal toxicity, suggesting that these inhibitors may further be developed as anti-leishmaniasis drugs to prevent the spread of leishmaniasis. Communicated by Ramaswamy H. Sarma

Molecular docking and pharmacokinetic screening of eucalyptol (1,8 cineole) from eucalyptus essential oil against SARS-CoV-2

SARS-CoV-2 (COVID-19), member of corona virus family, is a positive single stranded RNA virus. Due to lack of drugs it is spreading its tentacles across the world. Being associated with cough, fever, and respiratory distress, this disease caused more than 15% mortality worldwide. Mpro/3CLpro has recently been regarded as a suitable target for drug design due to its vital role in virus replication. The current study focused on the inhibitory activity of eucalyptol (1,8 cineole), an essential oil component from eucalyptus oil, against Mpro/3CLprofrom SARS-CoV-2. Till date there is no work is undertaken on in-silico analysis of this compound against Mpro/3CLproof SARS-CoV-2. Molecular docking studies were conducted by using 1-click dock tool and Patchdock analysis. In-silico absorption, distribution, metabolism, excretion and toxicity (ADMET) profile were also studied. The calculated parameters such as docking score indicated effective binding of eucalyptol to COVID-19 Mpro protein. Active site prediction revealed the involvement of active site residues in ligand binding. Interactions results indicated that, Mpro/3CLpro/eucalyptol complexes forms hydrophobic interactions. ADMET studies provided guidelines and mechanistic scope for identification of potent anti-COVID 19 drug. Therefore, eucalyptol may represent potential herbal treatment to act as COVID-19 Mpro/3CLproinhibitor, a finding which must be validated in vivo.

Comparative modeling, structure and active site prediction of Sclerotinia disease-resistant gene BnaMPK3 in Oilseed rape (Brassica napus)

The prerequirement of genetic engineering is to have knowledge about structure and function of transgene and its encoded protein.

Computer-Aided Structure Prediction of Bluetongue Virus Coat Protein VP2 Assisted by Optimized Potential for Liquid Simulations (OPLS).

The capsid coated protein of Bluetongue virus (BTV) VP2 is responsible for BTV transmission by the Culicoides vector to vertebrate hosts. Besides, VP2 is responsible for BTV entry into permissive cells and hence plays a major role in disease progression. However, its mechanism of action is still unknown. The present investigation aimed to predict the 3D structure of Viral Protein 2 of the bluetongue virus assisted by Optimized Potential for Liquid Simulations (OPLS), structure validation, and an active site prediction. The 3D structure of the VP2 protein was built using a Python-based Computational algorithm. The templates were identified using Smith waterman's Local alignment. The VP2 protein structure validated using PROCHECK. Molecular Dynamics Simulation (MDS) studies were performed using an academic software Desmond, Schrodinger dynamics, for determining the stability of a model protein. The Ligand-Binding site was predicted by structure comparison using homology search and proteinprotein network analysis to reveal their stability and inhibition mechanism, followed by the active site identification. The secondary structure of the VP2 reveals that the protein contains 220 alpha helix atoms, 40 310 helix, 151 beta sheets, 134 coils and 424 turns, whereas the 3D structure of Viral Protein 2 of BTV has been found to have 15774 total atoms in the structure. However, 961 amino acids were found in the final model. The dynamical cross-correlation matrix (DCCM) analysis tool identifies putative protein domains and also confirms the stability of the predicted model and their dynamical behavior difference with the correlative fluctuations in motion. The biological interpretation of the Viral Protein 2 was carried out. DCCM maps were calculated, using a different coordinate reference frame, through which, protein domain boundaries and protein domain residue constituents were identified. The obtained model shows good reliability. Moreover, we anticipated that this research should play a promising role in the identification of novel candidates with the target protein to inhibit their functional significance.

Computational prediction of active sites and ligands in different AHL quorum quenching lactonases and acylases

With the emergence of multidrug-resistant 'superbug', conventional treatments become obsolete. Quorum quenching (QQ), enzyme-dependent alteration of quorum sensing (QS), is now considered as a promising antimicrobial therapy because of its potentiality to impede virulence gene expression without resulting in growth inhibition and antibiotic resistance. In our study, we intended to compare between two major QQ enzyme groups (i.e., AHL lactonases and AHL acylases) in terms of their structural and functional aspects. The amino acid composition-based principal component analysis (PCA) suggested that probably there is no structural and functional overlapping between the two groups of enzymes as well as within the lactonase enzymes but the acylases may functionally be affected by one another. In subcellular localization analysis, we also found that most lactonases are cytoplasmic while acylases are periplasmic. Investigation on the secondary structural features showed random coil dominates over alpha-helix and beta-sheet in all evaluated enzymes. For structural comparison, the tertiary structures of the selected proteins were modelled and submitted to the PMDB database (Accession ID: PM0081007 to PM0081018). Interestingly, sequence alignment revealed the presence of several conserved domains important for functions in both protein groups. In addition, three amino acid residues, namely aspartic acid, histidine, and isoleucine, were common in the active sites of all protein models while most frequent ligands were found to be 3C7, FEO, and PAC. Importantly, binding interactions of predicted ligands were similar to that of native QS signal molecules. Furthermore, hydrogen bonds analysis suggested six proteins are more stable than others. We believe that the knowledge of this comparative study could be useful for further research in the development of QSbased universal antibacterial strategies.

Bioactive molecules from eucalyptus essential oil as potential inhibitors of COVID 19 corona virus infection by molecular docking studies

Across the world, COVID-19, a positive single-stranded RNA virus member of corona virus family, is spreading its tentacles due to lack of drugs at present causing 15% mortality worldwide due to cough, fever and respiratory problems cause more than. Due to its vital role in polyprotein processing necessary for coronavirus reproduction, the main viral proteinase (Mpro/3CLpro) has recently been regarded as a suitable target for drug design against SARS infection. The present in silico docking study was designed to evaluate the effect of potent 12 bioactive molecules present in essential oils of eucalyptus plant leaves. In the present study, molecular docking studies were conducted using a 1-click dock. Docked complex analysis was carried out using the Biovia Discovery studio, Chimera and VMD tools. Active sites were obtained from CAST P analysis. The calculated parameters such as RMSD, docking score indicated effective binding of bioactive essential oil molecules, especially Jensenone, to COVID-19 proteinase. Active site prediction further validated the role of active site residues in ligand binding. Molecular interactions results indicated that Mpro/eucalyptol complexes form hydrophobic interactions, hydrogen bond interactions and strong ionic interactions. Therefore, eucalyptus essential oil bioactive compounds may represent potential treatment potential to act as COVID-19 Mpro inhibitor. However, further research is necessary to investigate their potential medicinal use.

Designing, docking and molecular dynamics simulation studies of novel cloperastine analogues as anti-allergic agents: homology modeling and active site prediction for the human histamine H1 receptor.

The present study predicts a three-dimensional model for the histamine H1 receptor and the design of antihistamine inhibitors using cloperastine as the core molecule by docking studies. In this work, we predicted a three-dimensional structure of the histamine H1 receptor using the MODELLER9V7 software. The protein structure was developed based on the crystal structure of the histamine H1 receptor, the lysozyme chimera of Escherichia virus T4 (PDB ID: 3RZE_A) target collected from the PDB data bank. Using molecular dynamics simulation methods, the final predicted structure is obtained and further analyzed by VERIFY3D and PROCHECK programs, confirming that the final model is reliable. The drug derivatives of cloperastine were designed and docking was performed with the designed ligands along with the drug. The predicted model of the histamine H1 receptor structure is stable and confirms that it is a reliable structure for docking studies. The results indicate that MET 183, THR 184 and ILE 187 in the histamine H1 receptor are important determinant residues for binding as they have strong hydrogen bonding with cloperastine derivatives. The drug derivatives were docked to the histamine H1 receptor protein by hydrogen bonding interactions and these interactions played an important role in the binding studies. The molecule 1-{2-[(4-chlorophenyl) (phenyl) methoxy] ethyl}-4-methylenepiperidine showed the best docking results with the histamine H1 receptor. The docking results predicted the best compounds, which may act as better drugs than cloperastine and in the future, these may be developed for anti-allergy therapy.

Substrate docking and molecular dynamic simulation for prediction of fungal enzymes from Trichoderma species-assisted extraction of nanocellulose from oil palm leaves

Fungi of the Trichoderma species are valued industrial enzymes in support of the ‘zero-waste’ technology to convert agro-industrial biomass into valuable products, i.e. nanocellulose (NC). In this study, an in silico approach using substrate docking and molecular dynamic (MD) simulation was used to predict the order of which the multilayers of cellulosic polymers, i.e. lignin, hemicellulose and cellulose in oil palm leaves (OPL) are degraded by fungal enzymes, endocellulase and exocellulase. The study aimed to establish the catalytic tendencies of the enzymes to optimally degrade the cellulosic components of OPL for high yield production of NC. Energy minimized endocellulase and exocellulase models revealed satisfactory scores of PROCHECK (90.0% and 91.2%), Verify3D (97.23% and 98.85%) and ERRAT (95.24% and 91.00%) assessments. Active site prediction by blind docking, COACH meta-server and multiple sequence alignment indicated the catalytic triads for endocellulase and exocellulase were Ser116–His205–Glu249 and Ser382–Arg124–Asp385, respectively. Binding energy of endocellulase docked with hemicellulose (−6.0 kcal mol−1) was the most favourable followed by lignin (−5.6 kcal mol−1) and cellulose (−4.4 kcal mol−1). Exocellulase, contrarily, bonded favorably with lignin (−8.7 kcal mol−1), closely followed by cellulose (−8.5 kcal mol−1) and hemicellulose (−8.4 kcal mol−1). MDs simulations showed that interactions of complexes, endocellulase–hemicellulose and the exocellulase–cellulose being the most stable. Thus, the findings of the study successfully identified the specific actions of sugar-acting enzymes for NC production. Communicated by Ramaswamy H. Sarma

Design, Synthesis, and Biological and In Silico Study of Fluorine‐Containing Quinoline Hybrid Thiosemicarbazide Analogues

A novel series of fluorine‐containing quinoline hybrid thiosemicarbazide analogues (8a–8l) were synthesized and tested for their biological activities. The antibacterial results demonstrated that compounds 8d and 8l [minimal inhibitory concentration (MIC) 62.5 μg/mL] were shown to have higher biological activity than ampicillin against Escherichia coli. Compound 8b (MIC 25 μg/mL) was shown to have the highest activity than was ampicillin against Staphylococcus aureus. The antifungal results demonstrated that compound 8j (MIC 100 μg/mL) has shown good activity. Most of the targeted compounds have shown potent antimalarial activity. Compounds 8d (0.19 μg/mL), 8g (0.30 μg/mL), 8h (0.36 μg/mL), 8k (0.10 μg/mL), 8l (0.28 μg/mL), 8k (0.10 μg/mL), and 8l (0.28 μg/mL) have notable activity than does the reference drug quinine. Compounds 8d (0.27 μg/mL), 8g (0.30 μg/mL), and 8k (0.17 μg/mL) have shown excellent activity against chloroquine‐resistant strain. The MTT assay performed on peripheral blood lymphocyte cultures showed a high percentage of lymphocyte viability [8d (99.64), 8g (99.46), 8h (98.83), and 8k (99.51)] at a maximum dose (10 μg/mL), depicting no cytotoxicity of these compounds on human lymphocytes in vitro. A molecular docking study was performed on Pf‐DHFR‐TS inhibitor. A molecular dynamics study has shown compound 8g to have better affinity with protein. ADME‐Tox and pharmacophore study of synthesized compounds suggested prediction of active site.

PCR Amplification and In-Silico Analysis of Putative Boiling Stable Protein Encoding Genes from Invasive Alien Plant Lantana camara

Lantana camara, a noxious weed flourishing worldwide is one of the world’s 10 worst weed causing biological pollution. In this study, we amplified and sequenced stress responsive boiling stable protein encoding genes from leaves of L. camara. We also describe in-silico characterization and molecular modeling of LCDHY hydrophilic protein through homology search, secondary structure prediction, active site prediction and 3D structure analysis. Clustal W analysis showed the presence of conserved amino acid sequence. 3D structure was predicted using Swiss-model server and homology modeling. Structure was refined by energy minimization and stereo-chemical qualities validated with PROCHECK, VADAR, QMEAN servers. Active sites were predicted form target protein structure. NEST analysis revealed structural motifs in functionally important regions of protein structure. Based on gene ontology (GO) terms in ProFunc server, putative functions of modeled LCDHY protein were predicted.

Coupling dynamics and evolutionary information with structure to identify protein regulatory and functional binding sites.

Binding sites in proteins can be either specifically functional binding sites (active sites) that bind specific substrates with high affinity or regulatory binding sites (allosteric sites), that modulate the activity of functional binding sites through effector molecules. Owing to their significance in determining protein function, the identification of protein functional and regulatory binding sites is widely acknowledged as an important biological problem. In this work, we present a novel binding site prediction method, Active and Regulatory site Prediction (AR-Pred), which supplements protein geometry, evolutionary, and physicochemical features with information about protein dynamics to predict putative active and allosteric site residues. As the intrinsic dynamics of globular proteins plays an essential role in controlling binding events, we find it to be an important feature for the identification of protein binding sites. We train and validate our predictive models on multiple balanced training and validation sets with random forest machine learning and obtain an ensemble of discrete models for each prediction type. Our models for active site prediction yield a median area under the curve (AUC) of 91% and Matthews correlation coefficient (MCC) of 0.68, whereas the less well-defined allosteric sites are predicted at a lower level with a median AUC of 80% and MCC of 0.48. When tested on an independent set of proteins, our models for active site prediction show comparable performance to two existing methods and gains compared to two others, while the allosteric site models show gains when tested against three existing prediction methods. AR-Pred is available as a free downloadable package at https://github.com/sambitmishra0628/AR-PRED_source.

An efficient metal-free phosphorus and oxygen co-doped g-C3N4 photocatalyst with enhanced visible light photocatalytic activity for the degradation of fluoroquinolone antibiotics

Non-metal doping has been frequently used in g-C3N4 (CN) as a feasible and economical technique for maintaining its metal-free properties, while improving its photocatalytic performance. In this study, a novel phosphorus and oxygen co-doped graphitic carbon nitride (POCN) was successfully synthesized through a one-step thermal polymerization method and exhibited remarkable photocatalytic activity for the photocatalytic degradation of fluoroquinolones (FQs). The degradation rate of enrofloxacin (ENFX) was 6.2 times higher than that of CN. Based on the results of X-ray photoelectron spectroscopy (XPS) and nuclear magnetic resonance spectroscopy (NMR), P atoms replaced the corner and bay carbon sites, whereas O atoms replaced the nitrogen sites in the g-C3N4 framework. The improvement of the photocatalytic effect of POCN0.01 was attributed to its narrow bandgap, effective charge separation and enhanced specific surface area. This is the first report to describe the use of phosphorus doping to promote the generation of reactive oxygen species (ROS). ROS scavenging tests revealed that O2− was the primary active species during the degradation of ENFX. Furthermore, pathways for the degradation of ENFX were proposed via the detection of intermediate products via HRAM LC–MS/MS and the prediction of active sites using the Fukui function.

Homology modeling, structure and active site prediction of stem rust resistant gene Sr22 in wheat cultivars

Abstract Protein structure and function is very important to study before gene transformation. Protein homology modeling is very important tool used to predict the structure of the protein. Sr22 gene codes for a Sr22 protein which confers resistance against Puccinia graminis. The homology modeling of Sr22 protein was obtained by using SWISS-MODEL web tool. Then the predicted model of Sr22 protein was superimposed to check the validation through errat. Errat score for this model was 77% which was further improved up to 80% by doing loop optimization of Sr22 using similar tool. 3D model of stem rust resistant protein was further used to analyze the activity of the protein. Active sites of Sr22 protein were detected by using ADDS (Automated active sites detection, docking and scoring) software. Total of 17 active sites were identified and active sites with the highest score were used in further studies. The information achieved may be useful to understand the mechanism resistance to stem rust disease in wheat which may further help to manipulate for sustainable resistance. Keywords: Active site prediction; Homology Modeling; Puccinia graminis; Sr22 protein; Stem Rust http://dx.doi.org/10.19045/bspab.2018.700216

Molecular Docking and Dynamics (MD) Simulation of 6-gingerol and 6-shogaol Against Human Estrogen Receptor Alpha (ERɑ)

Simulation and computational analysis of 6-gingerol and 6-shogaol is done to evaluate their binding affinity against ERα. Active site prediction was done using Computed Atlas of Surface Topography of Proteins (CASTp) to determine the binding pocket of ERα. Molecular docking and molecular dynamics (MD) simulation were done to assess the binding affinity and stability of the ligand-ERα complexes formed. Results showed that Tamoxifen have lowest binding energy (-9.61 ± 0.39 kcal/mol) followed by 6-gingerol (-6.59 ± 0.29 kcal/mol) and 6-shogaol (-5.70 ± 0.36 kcal/mol). Inhibition constant (Ki) range of TMX-ERα was found to be drastically lower than both 6GN-ERα and 6SG-ERα. Based on the difference in the binding energy range and inhibition constant, 6-gingerol and 6-shogaol showed less potential in substituting tamoxifen for the inhibition of ERɑ. Docking complexes formed was supported with stability in root mean square deviation (RMSD) and total binding energy of the complexes. The study is concluded that 6-gingerol have high level of interactions with the ERα active site in terms of hydrogen bonding whereas hydrophobic interactions are observed with both 6-gingerol and 6-shogaol. However, both ginger bioactive compounds poses low potential as substitute in comparison with tamoxifen against ERα.

Immunoinformatics Approach for Epitope-Based Peptide Vaccine Design and Active Site Prediction against Polyprotein of Emerging Oropouche Virus.

Oropouche virus (OROV) is an emerging pathogen which causes Oropouche fever and meningitis in humans. Several outbreaks of OROV in South America, especially in Brazil, have changed its status as an emerging disease, but no vaccine or specific drug target is available yet. Our approach was to identify the epitope-based vaccine candidates as well as the ligand-binding pockets through the use of immunoinformatics. In this report, we identified both T-cell and B-cell epitopes of the most antigenic OROV polyprotein with the potential to induce both humoral and cell-mediated immunity. Eighteen highly antigenic and immunogenic CD8+ T-cell epitopes were identified, including three 100% conserved epitopes (TSSWGCEEY, CSMCGLIHY, and LAIDTGCLY) as the potential vaccine candidates. The selected epitopes showed 95.77% coverage for the mixed Brazilian population. The docking simulation ensured the binding interaction with high affinity. A total of five highly conserved and nontoxic linear B-cell epitopes “NQKIDLSQL,” “HPLSTSQIGDRC,” “SHCNLEFTAITADKIMSL,” “PEKIPAKEGWLTFSKEHTSSW,” and “HHYKPTKNLPHVVPRYH” were selected as potential vaccine candidates. The predicted eight conformational B-cell epitopes represent the accessibility for the entered virus. In the posttherapeutic strategy, ten ligand-binding pockets were identified for effective inhibitor design against emerging OROV infection. Collectively, this research provides novel candidates for epitope-based peptide vaccine design against OROV.