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A novel coronavirus (2019-nCoV) or Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) that affects humans has been discovered in Wuhan, China, in 2019. Its genome has been sequenced, and the genetic data was quickly made public. We discovered a novel proprotein convertase subtilisin kexin-9 (PCSK9) cleavage site in the Spike protein of the 2019-nCoV. The recent research also demonstrates that the previously found proprotein convertase 3 (PC3) or furin cleavage site, which was assumed to be unique, is already present in animal corona viruses. In this article, we suggest that the combination of the both proprotein convertase PC3 cleavage site and the PCSK9 site renders SARS-CoV-2 unique in terms of the pathogenicity, potential functional effects, and implications for the development of antiviral drugs.

Furin, a pro-protein convertase, plays a significant role as a biological scissor in bacterial, viral, and even mammalian substrates which in turn decides the fate of many viral and bacterial infections along with the numerous ailments caused by cancer, diabetes, inflammations, and neurological disorders. In the wake of the current pandemic caused by the virus SARS COV-2, furin has become the center of attraction for researchers as the spike protein contains a polybasic furin cleavage site. In the present work, we have searched for novel inhibitors against this interesting human target from FDA-approved antivirals. To enhance the selection of new inhibitors we employed Kohonen’s artificial neural network-based self-organizing maps for ligand-based virtual screening. Promising results were obtained which can help in drug repurposing and network pharmacology studies addressing the errors generated due to promiscuity/polypharmacology. We found 15 existing FDA antivirals having the potential to inhibit furin. Among these, six compounds have targets on many important human proteins (LDLR, FCGR1A, PCK1, TLR7, DNA, and PNP) also. These 15 drugs inhibiting furin could be studied in patients infected with many viruses including SARS COV-2. We also propose two promising candidate FDA drugs GS-441524 and Grazoprevir (MK-5172) for repurposing as inhibitors of furin. The best results were observed with GS-441524.

Identification of microRNAs from plants is a crucial step for understanding the mechanisms of pathways and regulation of genes. A number of tools have been developed for the detection of microRNAs from small RNA-seq data. However, there is a lack of pipeline for detection of miRNA from EST dataset even when a huge resource is publicly available and the method is known. Here we present miRDetect, a python implementation to detect novel miRNA precursors from plant EST data using homology and machine learning approach. 10-fold cross validation was applied to choose best classifier based on ROC, accuracy, MCC and F1-scores using 112 features. miRDetect achieved a classification accuracy of 93.35% on a Random Forest classifier and outperformed other precursor detection tools in terms of performance. The miRDetect pipeline aids in identifying novel plant precursors using a mixed approach and will be helpful to researchers with less informatics background.

Leptospira species are the etiological agent of an emerging zoonotic disease known as "Leptospirosis" that substantially affects both human health and economy across the globe. Despite the global importance of the disease, pathogenetic features, host-adaptation and proper diagnosis of this bacteria remains lacking. To accomplish these gaps, pan-genome of Leptospira genus was explored in the present study. The pan-genome of Leptospira genus was comprised of core (692) and accessory parts (softcore:1804, shell:6432, cloud:16,600). The functional analysis revealed the abundancy of "Translation, ribosomal structure and biogenesis" COG class in core-genes; whereas in accessory parts, genes involved in signal transduction was the most abundant. Furthermore, pathogen-host interaction (PHI) analysis of core and accessory proteins with human proteins showed the presence of a total of 599 and 510 interactions, respectively. There were eight hubs in core PHI network and five hubs in PHI network of accessory proteins. The human's proteins involved in these interactions were found functionally enriched in metabolic processes, responses to stimulus and immune system processes. Further, pan-genome based phylogeny separated the Leptospira genus in three major clades (belonging to P1, P2 and S) which relates with their pathogenicity level. Additionally, pathogenic and saprophytic clade specific genes of Leptospira have also been identified and functionally annotated for COG, KEGG and virulence factors. The results revealed the presence of 102 pathogenic and 215 saprophytic group specific gene clusters. The COG functional annotation of pathogen specific genes showed that defence mechanism followed by signal transduction mechanisms category were most significantly enriched COG categories; whereas in saprophytic group, signal transduction mechanisms was the most abundant COG, suggesting their role in adaptation and hence important for microbe's evolution and survival. In conclusion, this study provides a new insight of genomic features of Leptospira genus which may further be implemented for development of better control actions of the disease.

Leptospirosis is the most emerging zoonotic disease of epidemic potential caused by pathogenic species of Leptospira. The bacterium invades the host system and causes the disease by interacting with the host proteins. Analyzing these pathogen-host protein interactions (PHPIs) may provide deeper insight into the disease pathogenesis. For this analysis, inter-species as well as intra-species protein interactions networks of Leptospira interrogans and human were constructed and investigated. The topological analyses of these networks showed lesser connectivity in inter-species network than intra-species, indicating the perturbed nature of the inter-species network. Hence, it can be one of the reasons behind the disease development. A total of 35 out of 586 PHPIs were identified as key interactions based on their sub-cellular localization. Two outer membrane proteins (GpsA and MetXA) and two periplasmic proteins (Flab and GlyA) participating in PHPIs were found conserved in all pathogenic, intermediate and saprophytic spp. of Leptospira. Furthermore, the bacterial membrane proteins involved in PHPIs were found playing major roles in disruption of the immune systems and metabolic processes within host and thereby causing infectious disease. Thus, the present results signify that the membrane proteins participating in such interactions hold potential to serve as effective immunotherapeutic candidates for vaccine development.

Furin, a pro-protein convertase, plays a significant role of biological scissor in bacterial, viral, and even mammalian substrates which in turn decides the fate of many viral and bacterial infections along with the numerous ailments caused by cancer, diabetes, inflammations, and neurological disorders. In the wake of the current pandemic caused by the virus SARS COV-2, furin has become the center of attraction for researchers. In the present work, we have searched for novel inhibitors against this interesting human target from FDA-approved antivirals. To enhance the selection of new inhibitors we employed Kohonen’s-artificial neural network-based self-organizing maps for ligand based virtual screening. Promising results were obtained which can help in drug repurposing and network pharmacology studies addressing the errors due to promiscuity/polypharmacology. We found 15 existing FDA antivirals having the potential to inhibit furin. Among these, six compounds have targets on other important human proteins (LDLR, FCGR1A, PCK1, TLR7, DNA and PNP) also. These 15 drugs inhibiting furin could be studied in patients having many viral infections including SARS COV-2, which is known to have many interacting motifs like NSPs, ORFs, and spike protein. We also propose two promising candidate FDA drugs GS-441524 and Grazoprevir (MK-5172) to repurpose as inhibitors of furin. The best results were observed with GS-441524.

The emergence situation of coronavirus disease 2019 (COVID-19) pandemic has realised the global scientific communities to develop strategies for immediate priorities and long-term approaches for utilization of existing knowledge and resources which can be diverted to pandemic preparedness planning. Lack of proper vaccine candidate and therapeutic management has accelerated the researchers to repurpose the existing drugs with known preclinical and toxicity profiles, which can easily enter Phase 3 or 4 or can be used directly in clinical settings. We focused to justify even exploration of supplements, nutrients and vitamins to dampen the disease burden of the current pandemic may play a crucial role for its management. We have explored structure based virtual screening of 15 vitamins against non-structural (NSP3, NSP5, ORF7a, NSP12, ORF3a), structural (Spike & Hemagglutinin esterase) and host protein furin. The in silico analysis exhibited that vitamin B12, Vitamin B9, Vitamin D3 determined suitable binding while vitamin B15 manifested remarkable H-bond interactions with all targets. Vitamin B12 bestowed the lowest energies with human furin and SARS-COV-2 RNA dependent RNA polymerase. Furin mediated cleavage of the viral spike glycoprotein is directly related to enhanced virulence of SARS-CoV-2. In contrast to these, vitamin B12 showed zero affinity with SARS-CoV-2 spike protein. These upshots intimate that Vitamin B12 could be the wonder molecule to shrink the virulence by hindering the furin mediated entry of spike to host cell. These identified molecules may effectively assist in SARS-CoV-2 therapeutic management to boost the immunity by inhibiting the virus imparting relief in lung inflammation.

Green nanotechnology is very effective, emerging, and eco-friendly in the modern scientific field. Currently it is materializing an ample range of nanoparticles synthesized through various methods, that is, physical (thermal), chemical, and biological (using microbes, fungi, plant extract). Recently utilization of nanoparticles has been made in every field of commercialization due to their immense physicochemical properties and beneficial point of views. Nanoagriculture is a young field which is associated with novel nanopesticides, nanofertilizers for crop protection, nanosensors to track the precision farming and pathogens, and stress tolerating nanoparticles to maintain the soil conditions. There is increasing employment of nanoparticles in the food industries in food safety, packaging, self-life extension, detection of pathogens, and processing of food and food products. In addition to biological methods, myconanotechnology has acquired tremendous attention for the fabrication of a wide range of nanoparticles and nanomaterials. Verticillium sp., Aspergillus flavus, Aspergillus fumigatus, Phanerochaete chrysoparium, and Fusarium oxysporum have been reported for the biosynthesis of metal NPs in an efficient manner. In this review the mycogenic synthesis of nanoparticles and nanomaterial is discussed along with its mechanism and potential for application in agricultural sectors and food industries.

With pollutants contaminating every environ at a greater-than-ever rate and the world rallying to meet it head-on, it is important that modern technology to be leveraged to play various roles for the cause to further improve the efficacy of global efforts. Quantitative and qualitative assessment and monitoring of pollution in different environs is one such key role that provides us with crucial data to understand the effects of pollution in various environs and allows us to plan and assess the effectiveness of potential mitigation efforts and chart a way toward a future of sustainable development. It also enables the stakeholders to take informed overarching decisions on a global scale and, at the same time, provides valuable data-sets for various kinds of studies which further cement our understanding of the innumerable phenomena involved from fresh and revolutionary perspectives.

Microbial enzymes from different classes of microscopic organisms such as bacteria and fungi have been associated with the biodegradation of poisonous natural toxic compounds. These chemicals are the best tools for bioremediation and the strategy is a practical and eco-friendly biotechnology. In the recent past there has been the development of processes in this field and the increase in research areas is the need of the hour. The microbial enzymes play a key role in reduction of toxic pollutants and moreover acquire unique beneficial materials. These microbes through a biochemical reaction extract energy to cleave the bonds and result in the production of harmless compounds. The mechanisms of microbial enzymes responsible for bioremediation are studied extensively, such as laccases and hydrolases. This chapter deals with the information on microbial enzymes from various microorganisms and the mechanisms for the biodegradation of an extensive range of pollutants. The important factors affecting the degradation processes are also discussed in this chapter, providing extensive information for further research in this area.

Biofilms is a natural phenomenon that can be found as biological slims in lakes, rivers, rocks, etc. Natural biofilms are slow growing, while new techniques involves use of single- or dual-species biofilms. Biofiltration process involves use of biofilms in which desired biomass supplemented with essential nutrients attach to immobilized support. Innovations in biofiltration techniques helps to remove high amounts of effluents from the wastewater so that water can be reused for various processes. Use of biofilms for wastewater treatment proved its capacity to enhance the overall pollutants degradation efficiency and are cost effective. Different types of biofilms used for various wastewater treatment, more recent studies on biomass helps to remove organic as well as inorganic pollutants from the wastewater. A comprehensive study of microbial composition, intrinsic kinetics, biofilm performance, elucidation of substrate degradation mechanisms, and modeling adhesion of microorganisms to support materials can lead to the “biofiltration revolution” in wastewater treatment.

The industrially developed countries possibly raising the rate of pollution in order to increase their economic activity, causing the environmental damage to a greater extent. More specifically the enormous quantity of water used by the textile industry hence, producing a significant amount of liquid effluent pollutants for processing of fabrics and generating toxic dyes to the environment. Annually the environment is discharged with near about 50,000 tons of synthetic dyes whic cause momentous water pollution worldwide. Various chemical, physical, and biological methods have been used for the reduction of these dyes from textile waste water which is not only costly and time-consuming but has problems in proper disposals. To conquer these problems, the photocatalytic degradation of dyes has been achieved by green-synthesized metal and metal oxide nanoparticles. The green approach of nanoparticle synthesis has gained more attention by researchers because of its nontoxic, ecofriendly, biocompatible, and for its sustainable nature. Hence, the destructive effects of traditional nanoparticle synthesis have replaced by mechanistic and rate-limiting green approach. Recently, the nanoparticles are vastly applied in various biomedical fields and also in photocatalysis process. The nanoparticles also show its application as catalyst, bioimaging, sensors, antioxidants, biotransformation, fuel cells, antimicrobial agents, etc. due to its free radical scavenging nature and smaller size. Recently, the attracting function of nanoparticle is the possible alternative to photocatalytic degradation of toxic chemicals or dyes than that of traditional methods. In this process, the UV–visible light along with catalysts is exposed to the pollutants or toxic chemicals for its degradation, which is inexpensive and there is no chance of formation of polycyclic compounds. In this chapter, we emphasized on the mechanistic green synthesis process of metal and metal oxide (Ag, Au, CuO, ZnO, etc.) nanoparticles using natural extract. We have also explored the possible role of reducing agent from various phytochemicals (i.e., flavonoids, alkaloids, terpenoids, amides, and aldehydes) and other biological components to determine the rate-limiting steps during green synthesis with its biophysical characterization and possible photocatalytic degradation of dyes from textile industry. Hope the present work shall explore new possibilities in safe degradation of textile dyes and reduce the water pollution to a greater extent.

Life on the planet earth has existed for billions of years, animal for hundreds of millions of years, and man for a few million years with a harmonious ecological development. The balanced situation was not affected significantly by man until this century. Man is the original and basic pollutant who has caused the disturbance in nature reason being the rate at which chemical and other industries are pumping material into water and the atmosphere. Natural process of recycling, mostly bacterial and photochemical does exist for dealing with the ingress of new materials into the waters and atmosphere, however is unable to catch up with the rate happening. The result is visible pollution, and a whole series of changes which come upon the loss of long-lasting balanced system. The development of electrochemical detectors for high performance liquid chromatography is also a major breakthrough in the determination of organics based on oxidation at solid electrodes. Voltammetric experiments allow determination of compounds in solution which have an oxidizable or reducible moiety; as a result numerous metals, nonmetals, anions, organics, organometallics, and heterocyclic compounds can be determined in a wide variety of sample matrices. Organic applications of voltammetry have been reviewed extensively. This chapter is dealing with the extensive use of electrochemical techniques in the field of determination of pesticides and development of sensors for pesticide detection in water samples.

The advent of metagenomics, understanding the microbial in community level has revolutionized the field of microbial biotechnology due to its widespread application including the identification of novel microbes for the wastewater remediation. Metagenomics allows the recovery of genetic material directly from environmental niches and is widely employed as a powerful tool to identify enzymes with novel biocatalytic activities from the uncultivable microbial communities. This modern approach reveals much untold cross-talking and provides new perspectives for environmental management. Advancement of the next generation sequencing and bioinformatics tools not only supplies the knowledge of microbial metabolism but also provides information on genes involved in coding enzymes and valuable pathways of novel microorganisms, which play an important role in the biogeochemical cycles and degradation and detoxification of environmental pollutants. The process exploring pollution sites, construction, and screening of complex metagenomic DNA libraries followed by its application to isolate new enzymes and drugs of industrial importance. The review focused on this indispensable approach and tools used for screening strategies that allow efficient screening of large collections of microbes useful for the microbial prospecting and metabolic engineering.

The food industry is one of the most resource-demanding branches of industry due to the diverse consumption and array of functional food products that exist globally, which establishes a significant problem of compositions of food industry wastewater. The industry uses large amounts of water for many different functions such as raw materials, sanitary water for food processing, transportation, cooking, dissolving, auxiliary water, cooling, cleaning, etc. Wastewater from the food industry has high amounts of organic matter, but the organic compounds present in the effluent are generally biodegradable, and conventional anaerobic or aerobic biological methods of effluent treatment can be applied. On the other hand, some compounds that are poisonous to a microbial consortium may be present in the effluent because of diverse consumption. The effluent may essentially contain large amounts of suspended solids, nitrogen in several chemical forms, fats, oils, phosphorus, chlorides, and high organic matter. Numerous kinds of wastewater treatments are available such as physical, chemical, and biological and their combinations for the food industry. Advanced oxidation processes (AOP) are a chemical treatment category that is used to oxidize organic compounds found in wastewater, which are complicated to handle biologically, for conversion into simple finished products. This chapter deals with the various technological aspects of advanced oxidation of effluent from the food industry.

Dyes are a major class of organic compounds which find a multitude of applications in human life. The dyes belong to mostly synthetic organics and are toxic, nonbiodegradable, and resistant to direct degradation by sunlight and, therefore, they remain as persistent pollutants. The removal of these nonbiodegradable organic chemicals from the environment is a crucial ecological problem. Some common techniques, such as adsorption using activated carbon, flocculation, electrocoagulation, UV light degradation, and redox treatments, are being routinely used for abating dyes. In the present scenario, due to the incompetence of the techniques in one way or the other, there is requirement of improved wastewater treatment measures. Green-synthesized metallic nanoparticles, being nontoxic, inexpensive, and stable under ambient conditions, are ideal to be used for clean technology. In recent past efforts have been done to develop metal nanoparticles with high photocatalytic activities for their application in solving environmental problems. The significant photocatalytic performance of metallic nanoparticles is originated mainly due to the presence of surface proteins which act as an effective host for dyes and facilitates absorption of dye. The approach is highly advantageous as it does not yield toxic intermediate products, making it suitable for cleaning polluted water bodies that contain low to medium concentration of contaminants. Only a handful of studies have been made in this field and hence the noble metals have been widely implemented as promising candidates for the photocatalytic degradation reactions of dyes such as methyl violet, safranin, eosin methylene blue, and methyl orange.

Researchers have started constructing systems that could automatically analyze the medical images. In the initial phase (starting from 1970 to 1990), image processing was carried out using a sequential application of pixel analysis and mathematical model. By the end of 1990, supervised learning became popular in medical image processing, in which the trained images were used to design the models. But the conventional machine learning techniques require a crucial process of feature extraction to be carried out by the researchers. The next level of development is to construct the system, which can do feature learning automatically and can represent the images in an optimal way. Here lies the basis of many deep learning (DL) techniques in which the network comprises multiple layers that process the input image to output result by doing the feature extraction by itself. The most popular and efficient DL model for medical image processing is the convolutional neural network (CNN). There are various medical imaging modalities with the help of which critical images of the patient's body structures are captured and are fed to the CNN model for the analysis. In this chapter, authors have done a detailed discussion on different CNN architectures and their applications in the medical imaging domain. Moreover, a state-of-the-art comparison has been carried out between several existing works inside medical imaging based on CNN. Lastly, this chapter concludes with several critical remarks highlighting future challenges and their solutions.

The natural water reservoirs are continuously being depleted due to heavy effluent discharge from the textile and other dye industries. Synthetic organic dyes have been extensively used during the productions. As the discharge of these dyes has a severe threat to the environment. It is being very hard to eradicate these dyes as it possesses complex molecular structure. The conventional methods are inefficient to degrade in heavy loads of the contamination and are expensive to use it. In past couple of decades, application of nanoparticles is efficiently being used for its versatile chemical nature and reactivity. It is remarkable because of minute size and multipurpose usage which proved to be a great alternative toward the dye degradation and treatment of the waste water. Also the fabrication and generation of the nanoparticles are ecofriendly, easily approachable, and cost-effective. It has been reported that biologically synthesized nanoparticles were found to have the ability to degrade toxic dyes. In this review, the biogenic sources of the nanoparticles and the photocatalytic activity are being explored to emphasize the dye degradation activity. Photocatalytic degradation method is one of the most convenient methods to get eradicated the dyes from water; in addition to that it has high efficiency for mineralization and produces nontoxic compounds as by-products by light irradiation without casing secondary pollution. As the metal/metal oxide nanoparticles play a vital role as a photocatalyst being as an ecofriendly, cost-effective, and sustainable water treatment technique. Surface response curve is a statistical approach that is useful in the optimization and commonly used for experimental design of chemical reactions and industrial processes. Mathematical modeling (MM), on the other hand, is the art of explaining a system and to study the effects of different components, and to make predictions about behavior. In this project report, the role of nanomaterials in water treatment and dye degradation has been discussed. Sustainable dye degradation and synthesizing nanomaterials using MM are also focused. In the present chapter, dye degradation by MM and response surface methodology has been reviewed.

Moving bed biofilm reactors (MBBRs) rely on the growth of biofilms on “carriers” in aeration tanks for wastewater treatment. These carriers are made of materials with density close to that of water. MBBRs are considered to be more efficient as compared to other conventional processes and have many advantages, such as lesser size, more resilience toward toxic shock, etc., and are also independent of the performance of secondary clarifiers. Increase in efficiency is achieved by using both attached biofilms and suspended bacteria, as in the case of hybrid MBBRs. Biogas can also be produced from wastewater by using anaerobic MBBRs.

Toll-Like Receptors (TLRs) are a group of Pattern Recognition Receptors (PRRs) which bind to the exogenous pathogen associated molecular patterns (PAMPs) like other PRRs; hence the main function is to sense the harmness and mediate the innate immune response to pathogens. TLRs play an important role in innate immune responses to infection. The host has evolved to use other TLR and PAMP agonists as agents to stimulate a protective inflammatory immune response against infection. Because only a small number of doses are given, TLR agonists appear to have greater potential and fewer safety concerns than other uses as vaccine adjuvants. In the present days, development of peptides targeting immune response can be approved for survival in biological monitoring systems before vaccine exposures. Peptide vaccines are easy to synthesize, more stable and relatively safe. In addition, production of peptides becomes simple, easily reproducible, fast and cost effective. Getting vaccinated against Covid-19, which has become a pandemic in the human population, is the most practical way to control the outbreak. The new coronavirus does not contain a drug or vaccine to prevent it from spreading to humans. To getting a proper vaccine candidate against the novel coronavirus, the present study used the reverse vaccinology approach by using a complete set of SARS-CoV-2 proteins; such as: Spike, Envelope, Nucleocapsid, Membrane, NSPs, and ORFs to extract the antigenic elements that produce B-cell, T-cell and IFN positive epitopes. These epitopes with precise binding to the Toll-Like receptors (1-10) have developed epitope based vaccine candidates. We have prioritized a set of epitopes based on their antigenicity, allergenicity, sequence conservation and projected population coverage world-wide. The selected epitopes were employed for in-silico docking interactions with Toll-Like receptors and molecular dynamic simulation confirmed the stability of the vaccine candidates resulting epitope of spike proteins with both the TLR 7 and 8 shows the best binding affinity. We believe that this ideal epitope vaccine candidate could enhance the immune response of the host and reduce the reinfection risk.