Dynamic Profiling of β-Coronavirus 3CL M^proProtease Ligand-Binding Sites

Data availability statement: The trajectories of Mpro simulations and models of the metastable states can be downloaded from 10.5281/zenodo.4782284.β-coronavirus (CoVs) alone has been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a backup against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensable role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand–protein interactions. Herein, we provide a comprehensive comparison of all nonredundant ligand-binding sites available for SARS-CoV2, SARS-CoV, and MERS-CoV Mpro. Extensive adaptive sampling has been used to investigate structural conservation of ligand-binding sites using Markov state models (MSMs) and compare conformational dynamics employing convolutional variational auto-encoder-based deep learning. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across β-CoV homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor.There was no funding for this wor

Quantifying the effects of climate change on hydrological regime and stream biota in a groundwater-dominated catchment: A modelling approach combining SWAT-MODFLOW with flow-biota empirical models

Climate change may affect stream ecosystems through flow regime alterations, which can be particularly complex in streams with a significant groundwater contribution. To quantify the impacts of climate change on hydrological regime and subsequently the stream biota, we linked SWAT-MODFLOW (A model coupling the Soil and Water Assessment Tool and the Modular Finite-difference Flow Model) with flow-biota empirical models that included indices for three key biological taxonomic identities (fish, macroinvertebrates and macrophytes) and applied the model-complex to a groundwater-dominated catchment in Denmark. Effects of predicted climate change towards the end of this century relative to the reference period (1996-2005) were tested with two contrasting climate change scenarios of different greenhouse gas emissions (Representative Concentration Pathway 2.6 (RCP 2.6) and RCP 8.5) and analysed for all subbasins grouped into streams of three size classes. The total water yield in the catchment did not change significantly (-1 +/- 4 (SD) mm yr(-1)) from the baseline in the RCP2.6 scenario, while it increased by 9 = 11 mm yr(-1) in the RCP8.5 scenario. The three stream size classes underwent different alterations in flow regime and also demonstrated different biotic responses to climate change. All large and some small streams were impacted most heavily by the climate change, where fish and macrophyte indices decreased up to 14.4% and 11.2%, respectively, whereas these indices increased by up to 14.4% and 6.0%, respectively, in the medium and some small streams. The climate change effects were, as expected, larger in the RCP8.5 scenario than in the RCP2.6 scenario. Our study is the first to quantify the impacts of streamflow alterations induced by climate change on stream biota beyond specific species

3rd National Conference on Image Processing, Computing, Communication, Networking and Data Analytics

This volume contains contributed articles presented in the conference NCICCNDA 2018, organized by the Department of Computer Science and Engineering, GSSS Institute of Engineering and Technology for Women, Mysore, Karnataka (India) on 28th April 2018