@article {46742, title = {Biosensors: frontiers in rapid detection of COVID-19}, journal = {3 Biotech}, volume = {10}, year = {2020}, month = {AUG}, pages = {385}, type = {Review}, abstract = {

The rapid community-spread of novel human coronavirus 2019 (nCOVID19 or SARS-Cov2) and morbidity statistics has put forth an unprecedented urge for rapid diagnostics for quick and sensitive detection followed by contact tracing and containment strategies, especially when no vaccine or therapeutics are known. Currently, quantitative real-time polymerase chain reaction (qRT-PCR) is being used widely to detect COVID-19 from various types of biological specimens, which is time-consuming, labor-intensive and may not be rapidly deployable in remote or resource-limited settings. This might lead to hindrance in acquiring realistic data of infectivity and community spread of SARS-CoV-2 in the population. This review summarizes the existing status of current diagnostic methods, their possible limitations, and the advantages of biosensor-based diagnostics over the conventional ones for the detection of SARS-Cov-2. Novel biosensors used to detect RNA-viruses include CRISPR-Cas9 based paper strip, nucleic-acid based, aptamer-based, antigen-Au/Ag nanoparticles-based electrochemical biosensor, optical biosensor, and Surface Plasmon Resonance. These could be effective tools for rapid, authentic, portable, and more promising diagnosis in the current pandemic that has affected the world economies and humanity. Present challenges and future perspectives of developing robust biosensors devices for rapid, scalable, and sensitive detection and management of COVID-19 are presented in light of the test-test-test theme of the World Health Organization (WHO).

}, keywords = {Biosensors, COVID-19, Rapid detection, SARS-CoV-2}, issn = {2190-572X}, doi = {10.1007/s13205-020-02369-0}, author = {Samson, Rachel and Navale, Govinda R. and Dharne, Mahesh S.} } @article {47362, title = {Antiviral drugs prioritization for COVID-19 management based on rational selection}, journal = {Current Science}, volume = {120}, year = {2021}, month = {MAY }, pages = {1464-1470}, type = {Article}, abstract = {

The SARS-CoV-2 infection has resulted in COVID-19 pandemic worldwide. It has infected around 0.1 billion individuals and caused 2 million fatalities across the globe till mid-January 2021. Drug repurposing has been utilized as the most preferred therapeutic intervention for COVID-19 mitigation due to its necessity and feasibility. To prioritize therapeutic regime against COVID-19, we used 61 antiviral drugs and their combinations. Selected molecules were subjected to virtual screening against: (i) human angiotensin-converting enzyme 2 receptor binding domain (hACE-2) which serves as an anchor for virus attachment and entry, (ii) SARS-CoV-2 RNA dependent RNA polymerase (RdRp) responsible for viral RNA replication, and (iii) SARS-CoV-2 main protease (M-Pro) needed for viral polyprotein slab proteolytic processing. Based on docking score, pharmacodynamic and pharmacokinetic parameters, combinations of Daclatasvir, Elbasvir, Indinavir, Ledipasvir, Paritaprevir and Rilpivirine were analysed further. Our analysis suggested Sofosbuvir in combination with Ledipasvir and Daclatasvir as potential therapeutic agents for SARS-CoV-2. The combined score suggests that these combinations have superior anti-SARS-CoV-2 potential than Remdesivir and other investigational drugs. The present work provides a rationale-based approach to select drugs with possible anti-SARS-CoV-2 activity for further clinical evaluation.

}, keywords = {Drug repurposing, hACE-2, main protease, RNA dependent RNA polymerase, SARS-CoV-2}, issn = {0011-3891}, doi = {10.18520/cs/v120/i9/1464-1470}, author = {Joshi, Rakesh S. and Giri, Ashok P. and Kulkarni, Mahesh J. and Gupta, Mahesh and Verma, Savita and Chaudhry, Dhruva and Deshmukh, Narendra and Chugh, Anita} } @article {47613, title = {Translating SARS-CoV-2 wastewater-based epidemiology for prioritizing mass vaccination: a strategic overview}, journal = {Environmental Science and Pollution Research}, volume = {28}, year = {2021}, month = {AUG}, pages = {42975-42980}, type = {Article}, abstract = {The inception of the novel coronavirus has forced the world into despair. Rapid progress has been made in addressing the situation, and various clinical diagnostic methods were developed for early detection of transmission. However, with a rapidly increasing number of infected populations worldwide, the testing of each individual was impractical. The wastewater-based epidemiology (WBE) has been implemented to evaluate disease outbreaks as an early warning system for pandemic preparedness. Numerous studies reported the presence of SARS-CoV-2 in the open drains and STPs across the globe via recovery efficiency of surrogate virus from existing virus concentration protocols. However, the such reported studies did not justify the use of WBE to identify or pinpoint the specific hotspots of transmission which could be prioritized for rapid efforts to contain or accelerate active vaccination efforts. Identifying precise locations of hotspots could be an essential aspect in controlling the outbreak and surge of wave by prioritizing the region for primary outbreak response. This article focuses on the issues relating to the primary focus for WBE that can be adapted, and its suitability for utilization in the mass vaccination program is discussed. Effective use of WBE information in terms of source tracking might be crucial as we move towards mass vaccination to control outbreaks of COVID-19 pandemic.}, keywords = {Epidemiology, Policy making, SARS-CoV-2, Vaccination, wastewater}, issn = {0944-1344}, doi = {10.1007/s11356-021-15169-7}, author = {Dharmadhikari, Tanmay and Yadav, Rakeshkumar and Dastager, Syed and Dharne, Mahesh} } @article {47763, title = {High throughput sequencing based direct detection of SARS-CoV-2 fragments in wastewater of Pune, West India}, journal = {Science of the Total Environment}, volume = {807}, year = {2022}, month = {FEB }, pages = {151038}, type = {Article}, abstract = {Given a large number of SARS-CoV-2 infected individuals, clinical detection has proved challenging. The wastewater-based epidemiological paradigm would cover the clinically escaped asymptomatic individuals owing to the faecal shedding of the virus. We hypothesised using wastewater as a valuable resource for analysing SARS-CoV-2 mutations circulating in the wastewater of Pune region (Maharashtra; India), one of the most affected during the covid-19 pandemic. We conducted study in open wastewater drains from December 2020- March 2021 to assess the presence of SARS-CoV-2 nucleic acid and further detect mutations using ARTIC protocol of MinION sequencing. The analysis revealed 108 mutations across six samples categorised into 39 types of mutations. We report the occurrence of mutations associated with Delta variant lineage in March-2021 samples, simultaneously also reported as a Variant of Concern (VoC) responsible for the rapid increase in infections. The study also revealed four mutations; S:N801, S:C480R, NSP14:C279F and NSP3:L550del not currently reported from wastewater or clinical data in India but reported worldwide. Further, a novel mutation NSP13:G206F mapping to NSP13 region was observed from wastewater. Notably, S:P1140del mutation was detected in December 2020 samples while it was reported in February 2021 from clinical data, indicating the instrumentality of wastewater data in early detection. This is the first study in India to demonstrate utility of sequencing in wastewater based epidemiology to identify mutations associated with SARS-CoV-2 virus fragments from wastewater as an early warning indicator system. (c) 2021 Elsevier B.V. All rights reserved.}, keywords = {ARTIC protocol, Epidemiology, Metagenomics, Nanopore sequencing, SARS-CoV-2, wastewater}, issn = {0048-9697}, doi = {10.1016/j.scitotenv.2021.151038}, author = {Dharmadhikari, Tanmay and Rajput, Vinay and Yadav, Rakeshkumar and Boargaonkar, Radhika and Patil, Dhawal and Kale, Saurabh and Kamble, Sanjay P. and Dastager, Syed G. and Dharne, Mahesh S.} } @article {48236, title = {Machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys}, journal = {Computers in Biology and Medicine}, volume = {146}, year = {2022}, month = {JUL}, pages = {105419}, type = {Article}, abstract = {

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8\% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6\%-80.2\%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.

}, keywords = {BBV152, Covaxin, COVID-19, Ensemble methods, Infection, machine learning, SARS-CoV-2}, issn = {0010-4825}, doi = {10.1016/j.compbiomed.2022.105419}, author = {Singh, Prateek and Ujjainiya, Rajat and Prakash, Satyartha and Naushin, Salwa and Sardana, Viren and Bhatheja, Nitin and Singh, Ajay Pratap and Barman, Joydeb and Kumar, Kartik and Gayali, Saurabh and Khan, Raju and Rawat, Birendra Singh and Tallapaka, Karthik Bharadwaj and Anumalla, Mahesh and Lahiri, Amit and Kar, Susanta and Bhosale, Vivek and Srivastava, Mrigank and Mugale, Madhav Nilakanth and Pandey, C. P. and Khan, Shaziya and Katiyar, Shivani and Raj, Desh and Ishteyaque, Sharmeen and Khanka, Sonu and Rani, Ankita and Promila and Sharma, Jyotsna and Seth, Anuradha and Dutta, Mukul and Saurabh, Nishant and Veerapandian, Murugan and Venkatachalam, Ganesh and Bansal, Deepak and Gupta, Dinesh and Halami, Prakash M. and Peddha, Muthukumar Serva and Veeranna, Ravindra P. and Pal, Anirban and Singh, Ranvijay Kumar and Anandasadagopan, Suresh Kumar and Karuppanan, Parimala and Rahman, Syed Nasar and Selvakumar, Gopika and Venkatesan, Subramanian and Karmakar, Malay Kumar and Sardana, Harish Kumar and Kothari, Anamika and Parihar, Devendra Singh and Thakur, Anupma and Saifi, Anas and Gupta, Naman and Singh, Yogita and Reddu, Ritu and Gautam, Rizul and Mishra, Anuj and Mishra, Avinash and Gogeri, Iranna and Rayasam, Geethavani and Padwad, Yogendra and Patial, Vikram and Hallan, Vipin and Singh, Damanpreet and Tirpude, Narendra and Chakrabarti, Partha and Maity, Sujay Krishna and Ganguly, Dipyaman and Sistla, Ramakrishna and Balthu, Narender Kumar and Kumar, Kiran A. and Ranjith, Siva and Kumar, B. Vijay and Jamwal, Piyush Singh and Wali, Anshu and Ahmed, Sajad and Chouhan, Rekha and Gandhi, Sumit G. and Sharma, Nancy and Rai, Garima and Irshad, Faisal and Jamwal, Vijay Lakshmi and Paddar, Masroor Ahmad and Khan, Sameer Ullah and Malik, Fayaz and Ghosh, Debashish and Thakkar, Ghanshyam and Barik, S. K. and Tripathi, Prabhanshu and Satija, Yatendra Kumar and Mohanty, Sneha and Khan, Md Tauseef and Subudhi, Umakanta and Sen, Pradip and Kumar, Rashmi and Bhardwaj, Anshu and Gupta, Pawan and Sharma, Deepak and Tuli, Amit and Chaudhuri, Saumya Ray and Krishnamurthi, Srinivasan and Prakash, L. and Rao, V. Ch and Singh, B. N. and Chaurasiya, Arvindkumar and Chaurasiya, Meera and Bhadange, Mayuri and Likhitkar, Bhagyashree and Mohite, Sharada and Patil, Yogita and Kulkarni, Mahesh and Joshi, Rakesh and Pandya, Vaibhav and Mahajan, Sachin and Patil, Amita and Samson, Rachel and Vare, Tejas and Dharne, Mahesh and Giri, Ashok and Mahajan, Sachin and Paranjape, Shilpa and Sastry, G. Narahari and Kalita, Jatin and Phukan, Tridip and Manna, Prasenjit and Romi, Wahengbam and Bharali, Pankaj and Ozah, Dibyajyoti and Sahu, RaviKumar and Dutta, Prachurjya and Singh, Moirangthem Goutam and Gogoi, Gayatri and Tapadar, Yasmin Begam and Babu, Elapavalooru V. S. S. K. and Sukumaran, Rajeev K. and Nair, Aishwarya R. and Puthiyamadam, Anoop and Valappil, Prajeesh Kooloth and Prasannakumari, Adrash Velayudhan Pillai and Chodankar, Kalpana and Damare, Samir and Agrawal, Ved Varun and Chaudhary, Kumardeep and Agrawal, Anurag and Sengupta, Shantanu and Dash, Debasis} } @article {49128, title = {AIDrugApp: artificial intelligence-based Web-App for virtual screening of inhibitors against SARS-COV-2}, journal = {Journal of Experimental \& Thereotical Artificial Intelligence }, volume = {35}, year = {2023}, month = {APR}, pages = {395-443}, type = {Article}, abstract = {

Currently, there is no effective cure for SARS-COVID-19 diseases. The identification of novel therapeutic targets and drug-like compounds is required for the development of anti-COVID-19 drugs. Virtual screening is currently the most significant component for identifying drug-like molecules from large datasets for drug design and development. However, there are no effective easily available and user-friendly applications for virtual screening of drug leads against SARS-COV-2. Therefore, we have developed a user-friendly web-app named {\textquoteleft}AIDrugApp{\textquoteright} for the virtual screening of inhibitor molecules against SARS-CoV-2. AIDrugApp is a novel open-access, deep learning AI-based inhibitory activity prediction and data statistics visualisation platform. Users can predict the inhibitory activities (Active/Inactive) and pIC-50 values of new compounds against SARS-CoV-2 replicase polyprotein, 3CLpro and human angiotensin-converting enzymes. It is also useful for virtual screening of chemical features of molecules towards SARS-COVID-19 clinical trial bioactivities. This paper presents the development and architecture of AIDrugApp. We also present two case studies where large sets of molecules were screened using the {\textquoteleft}Bioactivity Prediction{\textquoteright} module of our app. Screened molecules were analysed further for validation by molecular docking and ADME analysis to identify the potential drug candidates.

}, keywords = {ADME, deep neural network, drug designing, machine learning, Molecular docking, SARS-CoV-2, virtual screening, Web application}, issn = {0952-813X}, doi = {10.1080/0952813X.2022.2058619}, author = {Karade, Divya and Karade, Vikas} } @article {48489, title = {Comparative evaluation of advanced oxidation processes (AOPs) for reducing SARS-CoV-2 viral load from campus sewage water}, journal = {Journal of Environmental Chemical Engineering}, volume = {11}, year = {2023}, month = {JUN}, pages = {109673}, type = {Article}, abstract = {

Presence of SARS-CoV-2 in wastewater is a major concern as the wastewater meets rivers and other water bodies and is used by the population for various purposes. Hence it is very important to treat sewage water in an efficient manner in order to reduce the public health risk. In the present work, various advanced oxidation processes (AOPs) have been evaluated for disinfection of SARS-CoV-2 from sewage water collected from STP inlet of academic institutional residential. The sewage water was subjected to ten AOPs, which include Ozone (O3), Hydrodynamic cavitation (HC), Ultraviolet radiation (UV), and their hybrid combinations like HC/O3, HC/O3/ H2O2, HC/H2O2, O3/UV, UV/H2O2, UV/H2O2/O3, and O3/H2O2 to reduce SARS-CoV-2 viral load. Further, AOP treated sewage water was subjected to total nucleic acid isolation followed by RT-qPCR for viral load estimation. The sewage water treatment techniques were evaluated based on their viral concentration-reducing efficiency. It was found that ozone and ozone-coupled hybrid AOPs showed the most promising result with more than 98 \% SARS-CoV-2 viral load reducing efficiency from sewage water. Interestingly, the best six AOPs used in this study significantly reduced both the SARS-CoV-2 and PMMoV (faecal indicator) viral load and improved water quality in terms of increasing DO and decreasing TOC.

}, keywords = {AOPs and hybrid AOPs, Hydrodynamic cavitation, Ozonation, PMMoV, SARS-CoV-2, Sewage water treatment}, issn = {2213-2929}, doi = {10.1016/j.jece.2023.109673}, author = {Pramanik, Rinka and Bodawar, Narendra and Brahme, Aashay and Kamble, Sanjay and Dharne, Mahesh} } @article {48319, title = {Comprehensive molecular and clinical investigation of approved Anti-HCV drugs repurposing against SARS-CoV-2 infection: a glaring gap between benchside and bedside medicine}, journal = {Vaccines}, volume = {11}, year = {2023}, month = {MAR}, pages = {515}, type = {Article}, abstract = {

The limited availability of effective treatment against SARS-CoV-2 infection is a major challenge in managing COVID-19. This scenario has augmented the need for repurposing anti-virals for COVID-19 mitigation. In this report, the anti-SARS-CoV-2 potential of anti-HCV drugs such as daclatasvir (DCV) or ledipasvir (LDP) in combination with sofosbuvir (SOF) was evaluated. The binding mode and higher affinity of these molecules with RNA-dependent-RNA-polymerase of SARS-CoV-2 were apparent by computational analysis. In vitro anti-SARS-CoV-2 activity depicted that SOF/DCV and SOF/LDP combination has IC50 of 1.8 and 2.0 mu M, respectively, comparable to remdesivir, an approved drug for COVID-19. Furthermore, the clinical trial was conducted in 183 mild COVID-19 patients for 14 days to check the efficacy and safety of SOF/DCV and SOF/LDP compared to standard of care (SOC) in a parallel-group, hybrid, individually randomized, controlled clinical study. The primary outcomes of the study suggested no significant difference in negativity after 3, 7 and 14 days in both treatments. None of the patients displayed any worsening in the disease severity, and no mortality was observed in the study. Although, the post hoc exploratory analysis indicated significant normalization of the pulse rate showed in SOF/DCV and SOF/LDP treatment vs. SOC. The current study highlights the limitations of bench side models in predicting the clinical efficacy of drugs that are planned for repurposing.

}, keywords = {antiviral, COVID-19, daclatasvir, ledipasvir, SARS-CoV-2, sofosbuvir}, doi = {10.3390/vaccines11030515}, author = {Bansode, Sneha and Singh, Pawan Kumar and Tellis, Meenakshi and Chugh, Anita and Deshmukh, Narendra and Gupta, Mahesh and Verma, Savita and Giri, Ashok and Kulkarni, Mahesh and Joshi, Rakesh and Chaudhary, Dhruva} } @article {48990, title = {Discovery of SARS-CoV-2 inhibitors featuring novel histidine α-nitrile motif}, journal = {Chemistry and Biodiversity }, volume = {20}, year = {2023}, month = {DEC}, type = {Article}, abstract = {

As COVID-19 infection caused severe public health concerns recently, the development of novel antivirals has become the need of the hour. Main protease (Mpro) has been an attractive target for antiviral drugs since it plays a vital role in polyprotein processing and virus maturation. Herein we report the discovery of a novel class of inhibitors against the SARS-CoV-2, bearing histidine alpha-nitrile motif embedded on a simple dipeptide framework. In-vitro and in-silico studies revealed that the histidine alpha-nitrile motif envisioned to target the Mpro contributes to the inhibitory activity. Among a series of dipeptides synthesized featuring this novel structural motif, some dipeptides displayed strong viral reduction (EC50=0.48 mu M) with a high selectivity index, SI\>454.54. These compounds also exhibit strong binding energies in the range of -28.7 to -34.2 Kcal/mol. The simple dipeptide structural framework, amenable to quick structural variations, coupled with ease of synthesis from readily available commercial starting materials are the major attractive features of this novel class of SARS-CoV-2 inhibitors. The histidine alpha-nitrile dipeptides raise the hope of discovering potent drug candidates based on this motif to fight the dreaded SARS-CoV-2.

}, keywords = {dipeptide inhibitors, histidine alpha-nitrile, M-pro (main protease), molecular dynamics, SARS-CoV-2}, issn = {1612-1872}, doi = {10.1002/cbdv.202300957}, author = {Gone, Nilu Vijay and Enayathullah, Mohammed Ghalib and Thomas, Jessie and Rathee, Parth and Prabhakar, Rajeev and Bokara, Kiran Kumar and Sanjayan, Gangadhar J.} } @article {48995, title = {Genomic surveillance reveals early detection and transition of delta to omicron lineages of SARS-CoV-2 variants in wastewater treatment plants of Pune, India}, journal = {Environmental Science and Pollution Research }, volume = {30}, year = {2023}, month = {DEC}, pages = {118976-118988}, type = {Article}, abstract = {

The COVID-19 pandemic has emphasized the urgency for rapid public health surveillance methods to detect and monitor the transmission of infectious diseases. The wastewater-based epidemiology (WBE) has emerged as a promising tool for proactive analysis and quantification of infectious pathogens within a population before clinical cases emerge. In the present study, we aimed to assess the trend and dynamics of SARS-CoV-2 variants using a longitudinal approach. Our objective included early detection and monitoring of these variants to enhance our understanding of their prevalence and potential impact. To achieve our goals, we conducted real-time quantitative polymerase chain reaction (RT-qPCR) and Illumina sequencing on 442 wastewater (WW) samples collected from 10 sewage treatment plants (STPs) in Pune city, India, spanning from November 2021 to April 2022. Our comprehensive analysis identified 426 distinct lineages representing 17 highly transmissible variants of SARS-CoV-2. Notably, fragments of Omicron variant were detected in WW samples prior to its first clinical detection in Botswana. Furthermore, we observed highly contagious sub-lineages of the Omicron variant, including BA.1 (similar to 28\%), BA.1.X (1.0-72\%), BA.2 (1.0-18\%), BA.2.X (1.0-97.4\%) BA.2.12 (0.8-0.25\%), BA.2.38 (0.8-1.0\%), BA.2.75 (0.01-0.02\%), BA.3 (0.09-6.3\%), BA.4 (0.24-0.29\%), and XBB (0.01-21.83\%), with varying prevalence rates. Overall, the present study demonstrated the practicality of WBE in the early detection of SARS-CoV-2 variants, which could help track future outbreaks of SARS-CoV-2. Such approaches could be implicated in monitoring infectious agents before they appear in clinical cases.

}, keywords = {Bioinformatics pipeline, COVID-19, Early warning, India, Next-generation sequencing, Omicron, Public health, SARS-CoV-2, wastewater, Wastewater-based epidemiology}, issn = {0944-1344}, doi = {10.1007/s11356-023-30709-z}, author = {Rajput, Vinay and Pramanik, Rinka and Malik, Vinita and Yadav, Rakeshkumar and Samson, Rachel and Kadam, Pradnya and Bhalerao, Unnati and Tupekar, Manisha and Deshpande, Dipti and Shah, Priyanki and Shashidhara, L. S. and Boargaonkar, Radhika and Patil, Dhawal and Kale, Saurabh and Bhalerao, Asim and Jain, Nidhi and Kamble, Sanjay and Dastager, Syed and Karmodiya, Krishanpal and Dharne, Mahesh} } @article {49143, title = {Repurposing small molecules of Tephrosia purpurea against SARS-CoV-2 main protease}, journal = {Journal of Biomolecular Structure and Dynamics}, volume = {41}, year = {2023}, month = {SEP}, pages = {6822-6833}, type = {Article}, abstract = {

Coronavirus infection is a communicable disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged as a global pandemic with deteriorating effect on the world{\textquoteright}s population. Main protease (M-pro) of SARS-CoV-2 plays a significant role in the viral replication, transcription and disease propagation as well as a potential candidate for drug discovery and development for COVID-19 infection. The current study employed state of art structure-based drug discovery to decipher the role of phytochemicals of Tephrosia purpurea against M-pro. Tephrosia purpurea is being used as a traditional medicinal plant for the treatment of cough, breathlessness and fever as per the Indian Materia Medica. Screening of the phytochemicals of Tephrosia purpurea against M-pro was performed using molecular docking approach to identify the top 5 hits (+)-tephrorin B, deguelin, vitamin p, lanceolarin and 3beta-hydroxy-20(29)-lupene with binding energy of -8.4, -8.1, -8.0, -7.8, and -7.8 kcal/mol, respectively. Furthermore, identified top 5 hits were subjected to drug-likeness and toxicity prediction as well as MM-GBSA calculation. Out of the five molecules four molecules were predicted not to comprise any mutagenic and carcinogenic effects. Top two molecules based on the drug-likeness properties for oral bio-availability were further analysed by molecular dynamics simulation at 100 ns timescale. It was observed from the dynamic behaviour of the two complexes that the addition of these molecules changed the conformation and stability of the apo protein; thus may act as inhibitors for M-pro. Communicated by Ramaswamy H. Sarma

}, keywords = {molecular dynamics, SARS-CoV-2, Tephrosia purpurea}, issn = {0739-1102}, doi = {10.1080/07391102.2022.2112616}, author = {Sahoo, Rosaleen and Sahu, Parameswar and Swargam, Sandeep and Kumari, Indu and Behera, Banshidhar} } @article {49439, title = {Design of human ACE2 mimic miniprotein binders that interact with RBD of SARS-CoV-2 variants of concerns}, journal = {Journal of Biomolecular Structure \& Dynamics}, year = {2024}, month = {JAN}, type = {Article; Early Access}, abstract = {

The world of medicine demands from the research community solutions to the emerging problem of SARS-CoV-2 variants and other such potential global pandemics. With advantages of specificity over small molecule drugs and designability over antibodies, miniprotein therapeutics offers a unique solution to the threats of rapidly emerging SARS-CoV-2 variants. Unfortunately, most of the promising miniprotein binders are de novo designed and it is not viable to generate molecules for each new variant. Therefore in this study, we demonstrate a method for design of miniprotein mimics from the interaction interphase of human angiotensin converting enzyme 2 (ACE2). ACE2 is the natural interacting partner for the SARS-CoV-2 spike receptor binding domain (RBD) and acts as a recognition molecule for viral entry into the host cells. Starting with ACE2 N-terminal triple helix interaction interphase, we generated more than 70 miniprotein sequences. Employing Rosetta folding and docking scores we selected 10 promising miniprotein candidates amongst which 3 were found to be soluble in lab studies. Further, using molecular mechanics (MM) calculations on molecular dynamics (MD) trajectories we test interaction of miniproteins with RBD from various variants of concern (VOC). Presently, we report two key findings; miniproteins in this study are generated using less than 10 lab testing experiments, yet when tested through in-vitro experiments, they show submicro to nanomolar affinities towards SARS-CoV-2 RBD. Also in simulation studies, when compared with previously developed therapeutics, our miniproteins display remarkable ability to mimic ACE2 interphase; making them an ideal solution to the ever evolving problem of VOCs.

}, keywords = {ACE2 mimics, miniprotein, protein design, SARS-CoV-2, therapeutics, Variant of concern}, issn = {0739-1102}, doi = {10.1080/07391102.2024.2310789}, author = {Gaur, Neeraj K. and Khakerwala, Zeenat and Makde, Ravindra D.} } @article {49583, title = {Monitoring influenza A (H1N1, H3N2), RSV, and SARS-CoV-2 using wastewater-based epidemiology: A 2-year longitudinal study in an Indian megacity covering omicron and post-omicron phases}, journal = {Food and Environmental Virology}, volume = {17}, year = {2025}, month = {MAR}, pages = {3}, type = {Article}, abstract = {

{The bourgeoning field of wastewater-based epidemiology (WBE) for the surveillance of several respiratory viruses which includes Influenza A, H1N1pdm09, H3N2, respiratory syncytial viruses (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of interest for public health concerns. However, there are few long-term monitoring studies globally. In this study, respiratory viruses were detected and quantified from 11 sewer sheds by utilizing reverse transcription-quantitative polymerase chain reaction analysis in Pune city, India, from Jan 2022 to Dec 2023. The RNA fragments of respiratory viruses were detected in sewage samples before clinical cases were reported, underscoring the potential of WBE for early detection and monitoring within the population. The Spearman correlation of wastewater viral copies was positively and significantly correlated with the clinically positive case of H1N1pdm09 (rho = 0.55

}, keywords = {Influenza A, Quantitative reverse transcription-PCR, Respiratory viruses, SARS-CoV-2, Wastewater-based epidemiology}, issn = {1867-0334}, doi = {10.1007/s12560-024-09618-y}, author = {Pramanik, Rinka and Nannaware, Kiran and Malik, Vinita and Shah, Priyanki and Sangewar, Poornima and Gogate, Niharika and Shashidhara, L. S. and Boargaonkar, Radhika and Patil, Dhawal and Kale, Saurabh and Bhalerao, Asim and Jain, Nidhi and Kamble, Sanjay and Dastager, Syed and Dharne, Mahesh} }