Modern Paradigm Towards Potential Target Identification for Antiviral (SARS-nCoV-2) and Anticancer Lipopeptides: A Pharmacophore-Based Approach.

Background: Lipopeptides are potential microbial metabolites that are abandoned with broad spectrum biopharmaceutical properties ranging from antimicrobial, antiviral and anticancer, etc. Clinical studies are not much explored beyond the experimental methods to understand drug mechanisms on target proteins at the molecular level for large molecules. Due to the less available studies on potential target proteins of lipopeptide based drugs, their potential inhibitory role for more obvious treatment on disease have not been explored in the direction of lead optimization. However, Computational approaches need to be utilized to explore drug discovery aspects on lipopeptide based drugs, which are time saving and cost-effective techniques. Methods: Here a ligand-based drug discovery approach is coupled with reverse pharmacophore-mapping for the prediction of potential targets for antiviral (SARS-nCoV-2) and anticancer lipopeptides. Web-based servers PharmMapper and Swiss Target Prediction are used for the identification of target proteins for lipopeptides surfactin and iturin produced by Bacillus subtilis. Results: The studies have given the insight to treat the diseases with next-generation large molecule therapeutics. Results also indicate the affinity for Angiotensin-Converting Enzymes (ACE) and proteases as the potential viral targets for these categories of peptide therapeutics. A target protein for the Human Papilloma Virus (HPV) has also been mapped. Conclusion: The work will further help in exploring computer-aided drug designing of novel compounds with greater efficiency where the structure of the target proteins and lead compounds are known.

Global metabolome profiling of COVID-19 respiratory specimen using high-resolution mass spectrometry (HRMS).

Here we describe a protocol for identifying metabolites in respiratory specimens of patients that are SARS-CoV-2 positive, SARS-CoV-2 negative, or H1N1 positive. This protocol provides step-by-step instructions on sample collection from patients, followed by metabolite extraction. We use ultra-high-pressure liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry (HRMS) for data acquisition and describe the steps for data analysis. The protocol was standardized with specific customization for SARS-CoV-2-containing respiratory specimens. For complete details on the use and execution of this protocol, please refer to Maras et al. (2021).

Protocol for global proteome, virome, and metaproteome profiling of respiratory specimen (VTM) in COVID-19 patient by LC-MS/MS-based analysis.

In this protocol, we describe global proteome profiling for the respiratory specimen of COVID-19 patients, patients suspected with COVID-19, and H1N1 patients. In this protocol, details for identifying host, viral, or bacterial proteome (Meta-proteome) are provided. Major steps of the protocol include virus inactivation, protein quantification and digestion, desalting of peptides, high-resolution mass spectrometry (HRMS)-based analysis, and downstream bioinformatics analysis. For complete details on the use and execution of this profile, please refer to Maras et al. (2021).

Prakriti Analysis of COVID 19 Patients: An Observational Study.

RATIONALE & OBJECTIVE: The concept of Prakriti is unique to Ayurveda, which is used for deciding the preventive and curative strategy to be adopted in the treatment of patients. It is the total of anatomical, physiological, and psychological domains of an individual. The diseases often manifest by susceptibility that depends upon Prakriti of individuals. COVID 19 is a new disease, where the status of the susceptibility of its victim in terms of Prakriti is not known. This study has been undertaken to determine the Prakriti of COVID 19 positive patients. METHOD: The validated instrument CCRAS Prakriti assessment scale has been applied to the COVID 19 positive patients admitted between 16 May 2020 to 10 June 2020 at COVID hospital. RESULT: Data of 117 patients aged 10 to 80 years have been analyzed. The ratio of male-female patients was 1.8:1. Most patients belonged to Vata-KaphaPrakriti (27%).Individuals with their Prakriti found in order of frequency were Pitta-Kapha (21%), Kapha (20%), Vata (13%), Vata-Pitta (11%), Sama (4%) and Pitta (3%). CONCLUSION: Patients with Vata-Kapha, Pitta-Kapha, and Kapha dominant Prakriti have been found more in COVID19. The treatment strategies can be accordingly decided in respect of each patient.

Emerging strategies on in silico drug development against COVID-19: challenges and opportunities.

The importance of coronaviruses as human pathogen has been highlighted by the recent outbreak of SARS-CoV-2 leading to the search of suitable drugs to overcome respiratory infections caused by the virus. Due to the lack of specific drugs against coronavirus, the existing antiviral and antimalarial drugs are currently being administered to the patients infected with SARS-CoV-2. The scientists are also considering repurposing of some of the existing drugs as a suitable option in search of effective drugs against coronavirus till the establishment of a potent drug and/or vaccine. Computer-aided drug discovery provides a promising attempt to enable scientists to develop new and target specific drugs to combat any disease. The discovery of novel targets for COVID-19 using computer-aided drug discovery tools requires knowledge of the structure of coronavirus and various target proteins present in the virus. Targeting viral proteins will make the drug specific against the virus, thereby, increasing the chances of viral mortality. Hence, this review provides the structure of SARS-CoV-2 virus along with the important viral components involved in causing infection. It also focuses on the role of various target proteins in disease, the mechanism by which currently administered drugs act against the virus and the repurposing of few drugs. The gap arising from the absence of specific drugs is addressed by proposing potential antiviral drug targets which might provide insights into structure-based drug development against SARS-CoV-2.