Search

MERS-CoV, a zoonotic virus, poses a serious threat to public health globally. Thus, it is imperative to develop an effective vaccination strategy for protection against MERS-CoV. Immunoinformatics and computational biology tools provide a faster and more cost-effective strategy to design potential vaccine candidates. In this work, the spike proteins from different strains of MERS-CoV were selected to predict HTL-epitopes that show affinity for T-helper MHC-class II HTL allelic determinant (HLA-DRB1:0101). The antigenicity and conservation of these epitopes among the selected spike protein variants in different MERS-CoV strains were analyzed. The analysis identified five epitopes with high antigenicity: QSIFYRLNGVGITQQ, DTIKYYSIIPHSIRS, PEPITSLNTKYVAPQ, INGRLTTLNAFVAQQ and GDMYVYSAGHATGTT. Then, a multi-epitope vaccine candidate was designed using linkers and adjuvant molecules. Finally, the vaccine construct was subjected to molecular docking with TLR5 (Toll-like receptor-5). The proposed vaccine construct had strong binding energy of −32.3 kcal/mol when interacting with TLR5.Molecular dynamics simulation analysis showed that the complex of the vaccine construct and TLR5 is stable. Analysis using in silico immune simulation also showed that the prospective multi-epitope vaccine design had the potential to elicit a response within 70 days, with the immune system producing cytokines and immunoglobulins. Finally, codon adaptation and in silico cloning analysis showed that the candidate vaccine could be expressed in the Escherichia coli K12 strain. Here we also designed support vaccine construct MEV-2 by using B-cell and CD8+ CTL epitopes to generate the complete immunogenic effect. This study opens new avenues for the extension of research on MERS vaccine development. Communicated by Ramaswamy H. Sarma

This article presents an experimental and numerical investigation of Mode-I fracture control in aerospace grade unidirectional laminated composites (AS4/914) using the smart material approach. The P1 type macro fiber composites (MFC) actuators are selected for current research because of their higher free strain, high mechanical flexibility, and good blocking force. The opening mode (Mode-I) interlaminar fracture tests have been carried out on DCB specimens having surface bonded MFC actuator patches under the application of electric voltage within a range of 0–1500 V. These fracture control tests have been performed on pre-cracked (PC) and non pre-cracked (NPC) double cantilever beam specimens. The modified pin force model has been adopted for the evaluation of actuation forces in surface bonded MFC actuators. The XIGA-CZM based numerical formulation is utilized for numerical fracture modeling under electromechanical loading conditions. The MFC actuators have significant control over Mode-I fracture energy under the application of peak operating voltage. The numerical model using a modified pin force model in combination with XIGA-CZM based fracture model shows a good agreement with experimental observations.

Human replication protein A (RPA) is a heterotrimeric ssDNA binding protein responsible for many aspects of cellular DNA metabolism. The binding and dissociation of the four individual DNA binding domains (DBDs) from DNA result in configurational dynamics of the RPA-DNA complexes. This dynamics is essential for replacement of RPA by downstream proteins in various cellular metabolic pathways. RPA plays several important functions at telomeres where it binds to and melts telomeric G-quadruplexes, non-canonical DNA structures formed at the G-rich telomeric ssDNA overhangs. Here, we combine single-molecule total internal reflection fluorescence microscopy (smTIRFM) and mass photometry (MP) with biophysical and biochemical analyses to demonstrate that heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) specifically remodels RPA bound to telomeric ssDNA by dampening the RPA configurational dynamics and forming a stable ternary complex. Uniquely, among hnRNPA1 target RNAs, telomeric repeat-containing RNA (TERRA) is selectively capable of releasing hnRNPA1 from the RPA-telomeric DNA complex. We speculate that this telomere specific RPA-DNA-hnRNPA1 complex is an important structure in telomere protection.One Sentence SummaryAt the single-stranded ends of human telomeres, the heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) binds to and modulates conformational dynamics of the ssDNA binding protein RPA forming a ternary complex which is controlled by telomeric repeat-containing RNA (TERRA).

In humans, DNA polymerase δ (Pol δ) holoenzymes, comprised of Pol δ and the processivity sliding clamp, proliferating cell nuclear antigen (PCNA), carry out DNA synthesis during lagging strand DNA replication, initiation of leading strand DNA replication, and the major DNA damage repair and tolerance pathways. Pol δ holoenzymes are assembled at primer/template (P/T) junctions and initiate DNA synthesis in a coordinated process involving the major single strand DNA-binding protein complex, replication protein A (RPA), the processivity sliding clamp loader, replication factor C (RFC), PCNA, and Pol δ. Each of these factors interact uniquely with a P/T junction and most directly engage one another. Currently, the interplay between these macromolecular interactions is largely unknown. In the present study, novel Förster Resonance Energy Transfer (FRET) assays reveal that dynamic interactions of RPA with a P/T junction during assembly of a Pol δ holoenzyme and initiation of DNA synthesis maintain RPA at a P/T junction and accommodate RFC, PCNA, and Pol δ, maximizing the efficiency of each process. Collectively, these studies significantly advance our understanding of human DNA replication and DNA repair.

In recent years, the pharmaceutical business has seen a considerable increase in data digitization. With digitization, however, comes the challenge of obtaining, analyzing, and applying knowledge to solve complex clinical problems. Artificial intelligence (AI), which entails a variety of advanced tools and networks that can mimic human intellect, can overcome such challenges with traditional pharmaceutical development. Artificial intelligence and machine learning have a vast role in therapeutic development, including the prediction of drug target and properties of small molecules. By predicting the 3D protein structure, AI techniques, such as Alpha Fold, can help with structure-based drug development. Machine learning algorithms have been utilized to anticipate the properties of small molecules based on their chemical structure. Many researches have shown the importance of using in silico predictive ADMET (absorption, distribution, metabolism, excretion, and toxicity) models to speed up the discovery of small compounds with enhanced efficacy, safety, and dosage. This chapter discusses various roles of these methods in the development of effective therapeutics.

Modern optical communication heavily relies on coherent optical orthogonal frequency division multiplexing (CO-OFDM) modulation. But the usage of optical OFDM for fiber optic communication is still constrained in comparison to other modes of communication like visible light communication (VLC) and wireless communication due to a number of issues such as various sorts of fiber impairments including dispersion and attenuation. In this research paper, a novel optical OFDM modulation technique has been proposed. It is quadrature phase shift keying (QPSK) CO-OFDM modulation with Bessel optical filter in fiber optical link and is named as QCOB. This modulation technique works for optical fiber transmission. Its testing has been carried out for parameters like bit error rate (BER) and quality-factor (Q-factor) over a range of fiber length, fiber dispersion coefficient and input power. This modulation employs coherent optical OFDM with QPSK for subcarrier modulation. The optical link utilizes a Bessel optical filter. Improved results have been achieved over conventional QPSK CO-OFDM (QCO). The obtained results demonstrate the superiority of the QCOB technique in terms of performance enhancement and fiber impairment reduction. In comparison to the QCO technique, the BER performance (reduction in BER) of the QCOB technique shows an improvement of around 7.4, 100, 14.4, 46.4 and 3.4% for dispersion coefficient values of 10, 20, 30, 50 and 100 (in ps/nm-km), respectively.

The use of multiple carriers in Orthogonal Frequency Division Modulation (OFDM) makes it bandwidth-efficient and suitable for modern communication such as Long-Term Evolution (LTE), Digital Subscriber Line (DSL) internet access, optical fiber communication, digital television, audio broadcasting, etc. In this paper, four modulation formats by using Coherent Optical Orthogonal Frequency Division Modulations (CO-OFDM) have been analyzed. These are Single Port Dual Polarization (SP DP) 16 QAM, Single-Port Single Polarization (SP SP) 16 QAM, Dual Port Single Polarization (DP SP) QPSK 16-QAM, and Single Port Dual Polarization (SP DP) QPSK. Operation characteristics such as Bit Error Rate (BER) versus fiber-length and BER versus bit-rate have been examined. The range of fiber length used for this investigation is from 0 Km to 1000 Km with loop count equal to 2 and the range of bit rate of operation is from 20 Gbps to 200 Gbps. The present investigation helps in determining the relative suitability of CO-OFDM formats at various bit-rates of operation for different fiber lengths.

Background: Since December 2019, a novel coronavirus, SARS-CoV-2, has caused global public health issues after being reported for the first time in Wuhan province of China. So far, there have been approximately 14.8 million confirmed cases and 0.614 million deaths due to the SARS-CoV-2 infection globally, and still, numbers are increasing. Although the virus has caused a global public health concern, no effective treatment has been developed. Objective: One of the strategies to combat the COVID-19 disease caused by SARS-CoV-2 is the development of vaccines that can make humans immune to these infections. Considering this approach, in this study, an attempt has been made to design epitope-based vaccine for combatting COVID-19 disease by analyzing the complete proteome of the virus by using immuno-informatics tools. Methods: The protein sequence of the SARS-CoV-2 was retrieved and the individual proteins were checked for their allergic potential. Then, from non-allergen proteins, antigenic epitopes were identified that could bind with MHCII molecules. The epitopes were modeled and docked to predict the interaction with MHCII molecules. The stability of the epitope-MHCII complex was further analyzed by performing a molecular dynamics simulation study. The selected vaccine candidates were also analyzed for their global population coverage and conservancy among SARS-related coronavirus species. Results: The study has predicted 5 peptide molecules that can act as potential candidates for epitope- based vaccine development. Among the 5 selected epitopes, the peptide LRARSVSPK can be the most potent epitope because of its high geometric shape complementarity score, low ACE and very high response towards it by the world population (81.81% global population coverage). Further, molecular dynamic simulation analysis indicated the formation of a stable epitope-MHCII complex. The epitope LRARSVSPK was also found to be highly conserved among the SARS-CoV- -2 isolated from different countries. Conclusion: The study has predicted T-cell epitopes that can elicit a robust immune response in the global human population and act as potential vaccine candidates. However, the ability of these epitopes to act as vaccine candidate needs to be validated in wet lab studies.

1.AbstractMany types of DNA damage stall replication fork progression, including abasic sites. AP-Endonuclease 1 (APE1) has been shown to cleave abasic sites in ssDNA substrates. Importantly, APE1 cleavage of ssDNA at a replication fork has significant biological implications by generating double strand breaks that could collapse the replication fork. Despite this, the molecular basis and efficiency of APE1 processing abasic sites at a replication fork remains elusive. Here, we investigate APE1 cleavage of several abasic substrates that mimic potential APE1 interactions at replication forks. We determine that APE1 has robust activity on these substrates, similar to dsDNA, and report rapid rates for cleavage and product release. X-ray crystal structures visualize the APE1 active site, highlighting that a similar mechanism is used to process ssDNA substrates as canonical APE1 activity on dsDNA. However, mutational analysis reveals R177 to be uniquely critical for the APE1 ssDNA cleavage mechanism. Additionally, we investigate the interplay between APE1 and Replication Protein A (RPA), the major ssDNA-binding protein at replication forks, revealing that APE1 can cleave an abasic site while RPA is still bound to the DNA substrate. Together, this work provides molecular level insights into abasic ssDNA processing by APE1, including the presence of RPA.

Around the world, emergence and re-emergence of Dengue Virus (DENV) are one of the serious public health concerns. The infection of DENV to human population is mainly caused by the bite of an Aedes...

Whipple’s disease is one of the rare maladies in terms of spread but very fatal one as it is linked with many disorders (like Gastroenteritis, Endocarditis etc.). Also, current regimens include less effective drugs which require long duration follows up. This exploratory study was conducted to commence the investigation for crafting multi target epitope vaccine against its bacterial pathogen Tropheryma whipplei. The modern bioinformatics tools like VaxiJen, NETMHCII PAN 3.2, ALLERGEN-FP, PATCH-DOCK, TOXIC-PRED, MHCPRED and IEDB were deployed, which makes the study more intensive in analyzing proteome of T. whipplei as these methods are based on robust result generating statistical algorithms ANN, HMM, and ML. This Immuno-Informatics approach leads us in the prediction of two epitopes: VLMVSAFPL and IRYLAALHL interacting with 4 and 6 HLA DRB1 alleles of MHC Class II respectively. VLMVSAFPL epitope is a part of DNA-directed RNA polymerase subunit beta, and IRYLAALHL epitope is a part of membranous protein insertase YidC of this bacterium. Molecular-Docking and Molecular-Simulation analysis yields the perfect interaction based on Atomic contact energy, binding scores along with RMSD values (0 to 1.5 Ǻ) in selection zone. The IEDB (Immune epitope database) population coverage analysis exhibits satisfactory relevance with respect to world population.

Background:: The scientific community has supported from the medicinal flora of ancient as well as modern times in extracting chemicals, which holds therapeutic potential. In many previous studies, it was discovered Amentoflavone as an anti-viral agent and its presence as a bioactive constituent in many plants of different families Selaginellaceae, Euphorbiaceae, and Calophyllaceae etc. Withania somnifera (Ashwagandha) is already considered significant anti-viral agent in traditional medicine, and it is the main source of Somniferine-A, Withanolide-B. Objective:: In this study phytochemicals such as Withanolide-B, Somniferine-A, Stigmasterol, Amentoflavone, and Chavicine were analyzed to screen protein inhibitors out of them; such proteins are involved in SARS-Cov-2's internalization and interaction with human cytological domains. This will help in developing check point for SARS-Cov-2 internalization. Material and methods:: Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME, MDWeb, Molsoft, ProTox-II, and LigPlot were deployed to examine the action of pharmacoactive agents against SARS-Cov-2. The many tools deployed in the study were based on finest algorithms like Artificial neural networking, Machine Learning, and Artificial intelligence. Results:: On the basis of binding energies less than equal to -8.5 kcal/mol. Amentoflavone, Stigmasterol, and Somniferine-A were found to be most effective against COVID-19 disease as these chemical agents exhibit hydrogen bond interactions and competitively inhibit major proteins (SARS-Cov-2 Spike, Human ACE-2 receptor, Human Furin protease, SARS-Cov-2 RNA binding protein) that are found to involved in its infection and pathogenesis. Simulation analysis provides more validity to the selection of drug candidate Amentoflavone. ADMET properties were found to be in feasible range for putative drug candidates. Conclusion:: Computational analysis was successfully deployed in searching pharmacoactive phytochemicals Like Amentoflavone, Somniferine-A, and Stigmasterol that can bring control over COVID-19 expansion. This new methodology was found to be efficient, as reduces monetary expenditures and time consumption, aftermath molecular wet-lab validations will provide better approval for finalizing our selected drug model for controlling COVID-19 pandemic.

Replication Protein A (RPA) binds to single-stranded DNA (ssDNA) and recruits over three dozen RPA-interacting proteins (RIPs) to coordinate multiple aspects of DNA metabolism including DNA replication, repair, and recombination. Rtt105 is a molecular chaperone that regulates nuclear localization of RPA. Whether and how Rtt105 regulates the activities of RPA is poorly understood. Here, we show that Rtt105 binds to multiple DNA binding and protein-interaction domains of RPA and configurationally staples the complex. In the absence of ssDNA, Rtt105 inhibits RPA binding to Rad52, thus preventing spurious binding to RPA-interacting proteins (RIPs). When ssDNA is available, Rtt105 promotes formation of high-density RPA nucleoprotein filaments and dissociates during this process. Free Rtt105 further stabilizes the RPA-ssDNA filaments by inhibiting RPA facilitated exchange. Collectively, our data suggest that Rtt105 sequesters free RPA in the nucleus to prevent untimely RIP interaction, while stabilizing RPA-ssDNA filaments at DNA lesion sites.

Background The Tropheryma whipplei causes acute gastroenteritis to neuronal damages in Homo sapiens. Genomics and codon adaptation studies would be helpful advancements of disease evolution prediction, prevention, and treatment of disease. The codon usage data and codon usage measurement tools were deployed to detect the rare, very rare codons, and also synonymous codons usage. The higher effective number of codon usage values indicates the low codon usage bias in T. whipplei and also in the 23S and 16S ribosomal RNA genes. Results In T. whipplei, it was found to hold low codon biasness in genomic sets. The synonymous codons possess the base content in 3rd position that was calculated as A3S% (24.47 and 22.88), C3S% (20.99 and 22.88), T3S% (21.47 and 19.53), and G3S% (33.08 and 34.71) for 23s and 16s rRNA, respectively. Conclusion Amino acids like valine, aspartate, leucine, and phenylalanine hold high codon usage frequency and also found to be present in epitopes KPSYLSALSAHLNDK and FKSFNYNVAIGVRQP that were screened from proteins excinuclease ABC subunit UvrC and 3-oxoacyl-ACP reductase FabG, respectively. This method opens novel ways to determine epitope-based peptide vaccines against different pathogenic organisms.

Prosopis cineraria commonly known as Druce are valuable herb that holds antibacterial role, antifungal properties. We identified different peptides from this plant by deploying CADD (Computer-aided-drug-designing) approaches, these peptide sequences are as follows seq1 (RHDEEEEKAKV),seq3(KSNSTVEISQNVQSVDSSKM),seq4(KQVAEMNKPAVGSKTSDANHDLKS),seq5(KTKSAGNDSIQSTKPVPSALTVDKA),seq6(RELEDSNIHHVAASVVLESKSSRT), and seq8(LYSKVELHPFGLHNLGNSCYANAVFSV), these peptides holds therapeutic properties as shows interaction with chitin, a major constituent of fungal cell wall. Molecular docking was conducted by using AutoDock-Vina tool and the results were found to be promising where all binding energies were found in the range of − 9.1 to − 7.5 kcal/mol, it indicates strong binding of peptide sequences with chitin molecule. Even the toxicity analysis supports the considered peptide sequences to hold therapeutic role against fungus with non-toxic effect on humans. These peptides were successfully predicted as important therapeutic agents of P. cinerariaseed that can initiate chitin breakdown, due to their possible strong interaction with fungal cell wall and it also suggests this medicinal plant holds the key for multiple fungal disease treatments. This study will open new research dimensions and integration of computational biology with microbial pathology that will assist scientific and medical community to develop rapid disease prevention strategies against fungal pathogenesis.

Orthohantavirus, a zoonotic virus responsible for causing human cardio-pulmonary disease, is proven to be a fatal disease. Due to the paucity of regimens to cure the disease and efficient management to eradicate this deadly virus, there is a constant need to expand in-silico approaches belonging to immunology domain to formulate best feasible peptide-based vaccine against it. In lieu of that, we have predicted and validated an epitope of nine-residue-long sequence "MIGLLSSRI". The predicted epitope has shown best interactions with HLA alleles of MHC Class II proteins, namely HLA DRB1_0101, DRB1_0401, DRB1_0405, DRB1_0701, DRB1_0901, DRB1_1302, and DRB1_1501. The structure of the epitope was modeled by deploying PEPFOLD 3.5 and verified by Ramachandran plot analysis. Molecular docking and simulation studies reveal that this epitope has satisfactory binding scores, ACE value and global energies for docked complexes along with selectable range of RMSD and RMSF values. Also, the predicted epitope "MIGLLSSRI" exhibits population coverage of more than 62% in world population and maximum of 70% in the United States of America. In this intensive study, we have used many tools like AllergenFP, NETMHCII 3.2, VaxiJen, ToxinPred, PEPFOLD 3.5, DINC, IEDB-Population coverage, MHCPred and JCat server. Most of these tools are based on modern innovative statistical algorithms like HMM, ANN, ML, etc. that help in better predictions of putative candidates for vaccine crafting. This innovative methodology is facile, cost-effective and time-efficient, which could facilitate designing of a vaccine against this virus.

Omega-3 fatty acid plays a vital role as precaution agents in order to control depression and hyper cholesterol while act as an anti-inflammatory sensor. It binds to GPR120 and PPARγ proteins which inhibit phosphorylation of NFκB protein. In this research docking studies of PPARγ with omega-3 fatty acids, biochanin A and genistein including the docked complexes of PPARγ and selected ligands with NFκB are done. Furthermore, GPR120 was docked with all ligands and complexes of GPR120 and selected ligands with NFκB after which the best result was analyzed based upon the complimentary score of geometric shape, approximate atomic contact energy and interface area of complex. It was predicted that PPARγ has shown HPA (heneicosapentaenoic acid), ETE (eicosatrienoic acid)and ETA (eicosatetraenoic acid) as best leads and GPR120 showed heneicosapentaenoic acid (HPA), eicosatetraenoic acid (ETA), eicosatrienoic acid (ETE) as the best leads according to the geometric shape configuration of omega 3-fatty acid.

Nipah virus was first appeared in Malaysian 1998, which further found be outburst in neighbor countries i.e. Bangladesh, Singapore, and India. Currently there is no effective drug or vaccine available only supportive care and prevention are way to manage it. Epitope based vaccine could be the best way to cure Nipah virus infection. In this study, the proteome of Nipah virus was retrieve from UniProt database and were subjected to check for allergenicity using Allergen FP v.1.0 tool. NetMHCII 2.3 server screened epitopes from non-allergen proteins and Vaxijen tool was used to identify the most antigenic epitopes binds with MHC class II molecules. Two potent T cell epitopes LLFVFGPNL and KYKIKSNPL were found, which binds with HLA-DRB1*01:01 and HLA-DRB1*07:01 MHC class II alleles. PepstrMod and Swiss-Model server were used to build 3D structure model of epitopes and alleles, respectively. Further identified epitopes were docked with HLA alleles using AutoDock vina tool to confirm binding ability. The epitopes LLFVFGPNL and KYKIKSNPL had binding affinity of − 8.1 kcal/mol and − 5.7 kcal/mol with HLA-DRB1*01:01 and HLA-DRB1*07:01 alleles, respectively. Solidity of predicted epitope—allele docked complex were evaluating by molecular dynamics simulation.HLA distribution analysis was performed for predicted epitopes using the population coverage tool of Immune Epitope Database (IEDB). These predicted epitopes cover maximum number of populations in India as well as worldwide. Therefore, these epitopes could be potent vaccine candidates to counter Nipah virus by testing in wet lab.

This article presents an effective study for characterization of interlaminar Mode I fracture process zone (FPZ) in unidirectional CFRP laminated composite structure. Mode I fracture toughness testing has been carried out on double cantilever beam (DCB) specimens. Experimental studies have been carried out on non-precraked DCB specimens in order to obtain the amount of energy released during crack initiation from the natural crack front. The energy release rate (ERR) is obtained from experimental data as a function of crack growth ( Δ a ) and pre-crack tip opening displacement ( δ ∗ ) by utilizing five data reduction schemes. The analytical function between ERR and δ ∗ is used to construct fibre bridging law using J-integral approach. The obtained traction separation laws from each data reduction scheme is implemented into cohesive zone modelling (CZM) for numerical simulation. Fractured surfaces have been examined by means of Scanning electron microscope (SEM). Numerical studies have been carried out for both non-precracked and precracked specimens using combined framework of fracture mechanics using extended isogeometric analysis (XIGA) and damage mechanics using CZM approach. It has been observed that crack travels catastrophically in non-precracked (NPC) specimens due to fast dissipation of excess energy. Introduction of fibre bridging law, obtained from experimental investigation, into CZM in combined framework of XIGA methodology shows a good agreement with experimental results.

Coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected 235.6 million people worldwide. In the present study, RNA-dependent RNA polymerase (RdRp) (PDB Id: 6M71) of SARS-CoV-2, an essential enzyme needed for subgenomic replication and amplification of RNA, was selected. Similar to other RdRps, it is a conserved protein and a popular target for antiviral drug therapy. Based on a computational approach, potential RdRp inhibitors were identified. The absorption, distribution, metabolism, excretion, and toxicity (ADMET) of selected molecules were determined using computation tools. The potential inhibitors were docked to the RdRp and later confirmed by Molecular Dynamics (MD) using the "Flare" module of Cresset software. Drummondin E and Flinderole B had higher drug similarity scores among the compounds selected in this study. Both these compounds are noncarcinogenic, nonirritant, nontumorigenic, and nonmutagenic. Molecular docking studies showed that both compounds can bind to RdRp. The best ligand interaction patterns were validated by MD using the "Flare" module. MD was performed for the period of 100 ns with the time step of 1 fs. The simulation results suggest that Thr-680, Arg-624, Lys-676, and Val-557 are key interacting partners in the Drummondin E-RdRp complex, while Asp-618, Asp-760, Asp-623, Arg-624, and Asp-761 are the interacting partners in the Flinderole B-RdRp complex. Based on the

The characteristics of all optical networks such as high speed, data carrying capacity and transparency make them suitable for emerged networks domain. This paper presents an overview of research challenges in the field of all optical communication networks. Various subdomains of an all optical system, for example device-level designs, communication technique-level designs and network-level designs have been extensively investigated and presented in this paper. Further, the related research issues under each category of these domains have been discussed. These issues constitute the basic criterion for further development in all optical domain.

Neural networks play very significant role when it comes to analysis of proteins and nucleic acid sequences. Many of the pattern recognition software are based on neural networks for prediction of biological patterns. Modern sequencing advancement fuels up the collection of data related to DNA, RNA, and protein sequences. The complexity and enormous size of this data require best computational algorithms for analysis and interpretation. This information will assist in developing useful insight for biomolecular structural predictions and prediction of interactions between such molecules. A neural system investigation framework is a succession of computations that attempts to see concealed associations in a lot of data through a technique that imitates the way where the human mind works. In this sense, neural frameworks suggest systems of neurons, artificial in nature. Vectors and matrices based linear algebra and topology designs supported various types of neural architectures. Neural frameworks can conform to advancing info; so the framework makes the best result without hoping to refresh the yield rules. The possibility of neural frameworks, which has its basic establishments in man-made consciousness, is rapidly getting ubiquity in the progression of in silico designing systems. Here, we talk about and sum up the uses of Neural Networks in computational biology, with a specific spotlight on applications in protein and Nucleic acid bioinformatics. We concluded with giving basic insights of neural networks in multiple domains of life sciences like gene prediction, protein structure prediction, epitope prediction, expression, co-expression, protein–protein interaction, and many other domains.

Big data is an enormous amount of data generated in internet, it is sort of information about all type of activities performed in real and uploaded via web interfaces to servers. In agriculture many research institutions play major role in breeding programs, pest management, quality improvement, and nutritional uplift in crop variety of interest. The information generated during such experiments is very useful and for its storage data management schemes were initiated, that lead to develop specific servers for various floral segments—medicinal plants, cereals, horticulture crops, and oil crops, etc. Transcriptomic and proteomic information produced by deploying modern in-silico analysis on NGS, microarray, spectroscopy data sets of plant species, is maintained by many primary databases like NCBI GenBank, EMBL, and JDB. Also the structural information databases like RCSB-Pdb plays crucial role in retrieval and biochemical analysis of proteins. Big data analysis opens new dimensions for scientific community to do rapid and easy screening before performing any practical wet-lab initiatives. The tools are sophisticated as based on AI, ML, and ANN, that makes them error free. Big data and IoT works collaboratively to achieve integration of all the domains of agricultural sciences and resolves socio-economic problems of farmers. This chapter focuses on developing understanding of big data handling and its analytics in agriculture.

Genomics delivers purposeful biological information, as it is a part of life science dealing about the comprehension and planning of genomes. A genome is the complex arrangement of genetic sets present in a cell or a whole living being. It is a useful measure of information when you consider that the human genome has in excess of 3 billion DNA base sets. It is a stunning measure of data that people have experienced difficulty in wielding, despite the fact that nature figured out how to pack everything into each cell in the human body. Customized medication is clinical consideration related to every patient’s hereditary cosmetics. It implies mass, mechanical production system like medication reaches a conclusion, and medication intended to convey greatest advantage to the individual turns into the standard. This would kill a great deal of awful side-effects related with standard medicines presently, decrease or dispose of hypersensitive responses, diminish the expense of medical care, and lessen patient sufferings, as enduring more successful therapies. So as to really perform customized medication, every patient’s genome should initially be converted into advanced information which is then handled, put away, and recovered varying. Accordingly the triple play of genomics, bioinformatics and customized medication is vital. Everything sounds so basic yet it is so confounded. Numerous medications and preventive therapies are neglected to convey ideal reaction to wide populace. PM is a combinational way to deal with individual specific heath care. The patient specific medication development advanced through bioinformatics tools. Bioinformatics devices may furnish better conclusions in genomic level with prior identification of infection and better focused on treatment through productive PM improvement. Variety in sex, racial, ethnic, genetic polymorphisms, and other ecological variables influence the in resistant reaction to a specific therapy.

Highlights • The growth supplements remarkably enhanced the cordycepin production. • Hypoxanthine and adenosine yielded higher amount of cordycepin. • The potent growth supplements activated cordycepin biosynthesis pathway. • Upregulation of RNR, NT5E, ADEK and purA mRNA expression was observed., Cordycepin is a crucial bioactive compound produced by the fungus Cordyceps spp. Its therapeutic potential has been recognized for a wide range of biological properties such as anticancer, anti-diabetic, antidepressant, antioxidant, immunomodulation, etc. Moreover, its human random clinical trials depicted a promising anti-inflammatory activity that reduced the airway inflammation remarkably in asthmatic patients. But its overexploitation and low production of cordycepin in naturally growing biomass are insufficient to meet its existing market demand for its therapeutic use. Therefore, strategies for enhancement of cordycepin production in Cordyceps spp. are warranted. However, specifically, wild type Ophiocordyceps sinensis possesses a very low content of cordycepin and has restricted growth in natural mycelial biomass. To overcome these limitations, this study attempted to enhance cordycepin production in its mycelial biomass in vitro under submerged conditions by adding various growth supplements. The effect of these growth supplements was evaluated by reversed-phase high-performance liquid chromatography (RP-HPLC) which demonstrated that among nucleosides- hypoxanthine and adenosine; amino acids-glycine and glutamine; plant hormones- 1-naphthaleneacetic acid (NAA) and 3-indoleacetic acid (IAA); vitamin-thiamine (B1) from each group of growth supplements yielded a higher amount of cordycepin with 466.48 ± 3.88, 380.23 ± 1.78, 434.97 ± 2.32, 269.78 ± 2.92, 227.61 ± 2.34, 226.02 ± 1.69 and 185.26 ± 2.35 mg/L respectively as compared to control with 13.66 ± 0.64 mg/L. Further, at the transcriptional level, quantitative real time-polymerase chain reaction (qRT-PCR) analysis of genes associated with metabolism and cordycepin biosynthesis depicted significant upregulation of major downstream genes- NT5E, RNR, purA, and ADEK which corroborated well with RP-HPLC analysis. Taken together, the present study identified growth supplements as potential precursors to activate the cordycepin biosynthesis pathway leading to improved cordycepin production in O. sinensis.

The current outbreak of Coronavirus Disease 2019 (COVID-19) pandemic has reported thousands of deaths worldwide due to the rapid transmission rate and the lack of antiviral drugs and vaccinations. There is an urgent need to develop potential antiviral drug candidates for the prevention of COVID-19 infection. In the present study, a series of potential inhibitors targeting SARS-CoV 3CL protease were rationally designed by incorporating gamma lactam ring, and various fluoro substituted heterocyclic ring systems to the flavonoid scaffold. The prediction of drug-likeness, oral bioavailability, toxicity, synthetic accessibility, and ADMET properties was made by computational means. Quercetin was used as standard. The binding affinity of the ligands towards the 3CL protease target was examined using docking simulations. The designed ligands possess favourable pharmacokinetic and pharmacodynamic properties. Ligand L4, L8, and L14 appeared to be the lead compounds in the series and can be considered for further in-vivo and in-vitro validation., Graphical abstract Image, graphical abstract