<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Niveditha, Divya</style></author><author><style face="normal" font="default" size="100%">Khan, Soumen</style></author><author><style face="normal" font="default" size="100%">Khilari, Ajinkya</style></author><author><style face="normal" font="default" size="100%">Nadkarni, Sanica</style></author><author><style face="normal" font="default" size="100%">Bhalerao, Unnati</style></author><author><style face="normal" font="default" size="100%">Kadam, Pradnya</style></author><author><style face="normal" font="default" size="100%">Yadav, Ritu</style></author><author><style face="normal" font="default" size="100%">Kanekar, Jugal B.</style></author><author><style face="normal" font="default" size="100%">Shah, Nikita</style></author><author><style face="normal" font="default" size="100%">Likhitkar, Bhagyashree</style></author><author><style face="normal" font="default" size="100%">Sawant, Rutuja</style></author><author><style face="normal" font="default" size="100%">Thakur, Shikha</style></author><author><style face="normal" font="default" size="100%">Tupekar, Manisha</style></author><author><style face="normal" font="default" size="100%">Nagar, Dhriti</style></author><author><style face="normal" font="default" size="100%">Rao, Anjani G.</style></author><author><style face="normal" font="default" size="100%">Jagtap, Rutuja</style></author><author><style face="normal" font="default" size="100%">Jogi, Shraddha</style></author><author><style face="normal" font="default" size="100%">Belekar, Madhuri</style></author><author><style face="normal" font="default" size="100%">Pathak, Maitreyee</style></author><author><style face="normal" font="default" size="100%">Shah, Priyanki</style></author><author><style face="normal" font="default" size="100%">Ranade, Shatakshi</style></author><author><style face="normal" font="default" size="100%">Phadke, Nikhil</style></author><author><style face="normal" font="default" size="100%">Das, Rashmita</style></author><author><style face="normal" font="default" size="100%">Joshi, Suvarna</style></author><author><style face="normal" font="default" size="100%">Karyakarte, Rajesh</style></author><author><style face="normal" font="default" size="100%">Ghose, Aurnab</style></author><author><style face="normal" font="default" size="100%">Kadoo, Narendra</style></author><author><style face="normal" font="default" size="100%">Shashidhara, L. S.</style></author><author><style face="normal" font="default" size="100%">Monteiro, Joy Merwin</style></author><author><style face="normal" font="default" size="100%">Shanmugam, Dhanasekaran</style></author><author><style face="normal" font="default" size="100%">Raghunathan, Anu</style></author><author><style face="normal" font="default" size="100%">Karmodiya, Krishanpal</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Infection and Public Health</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Delta</style></keyword><keyword><style  face="normal" font="default" size="100%">Omicron</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2 genomic surveillance</style></keyword><keyword><style  face="normal" font="default" size="100%">Variant of concern</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing (WGS)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">1290-1300</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Background: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data.Methods: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a ``band of five'' outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5).Results: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. Conclusions: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implica-tions for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.&amp;amp; COPY; 2023 Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	6.7&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gaur, Neeraj K.</style></author><author><style face="normal" font="default" size="100%">Khakerwala, Zeenat</style></author><author><style face="normal" font="default" size="100%">Makde, Ravindra D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Design of human ACE2 mimic miniprotein binders that interact with RBD of SARS-CoV-2 variants of concerns</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Biomolecular Structure &amp; Dynamics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ACE2 mimics</style></keyword><keyword><style  face="normal" font="default" size="100%">miniprotein</style></keyword><keyword><style  face="normal" font="default" size="100%">protein design</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">therapeutics</style></keyword><keyword><style  face="normal" font="default" size="100%">Variant of concern</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	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.&lt;/p&gt;
</style></abstract><work-type><style face="normal" font="default" size="100%">Article; Early Access</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	4.4&lt;/p&gt;
</style></custom4></record></records></xml>