Scientists Are Worried About New COVID-19 Variants —But Most Americans Aren ’ t
Scientists are warning that ever more dangerous forms of SARS-CoV-2 continue to emerge and threaten to drive potential surges in the coming months. On Oct. 4, White House chief medical advisor Dr. Anthony Fauci said that as we head into the winter months, “We should anticipate that we very well may get another variant that would emerge that would elude the immune response that we’ve gotten from infection and/or from vaccination.” A Pew Research Center survey published on Oct. 5 polled nearly 11,000 American adults from Sept. 13 to 18 and found that 69% of Americans believe new variants won’t have a...
Source: TIME: Health - October 5, 2022 Category: Consumer Health News Authors: Tara Law Tags: Uncategorized COVID-19 healthscienceclimate Source Type: news

SIREN study, UKHSA(updated 4th October 2022)
Providing vital research into coronavirus (COVID-19) immunity and vaccine effectiveness nationally. 4 October 2022Added link to ' Burden of SARS-CoV-2 infection in healthcare workers during second wave in England and impact of vaccines ' . 26 July 2022Added site contributors list. (Source: Current Awareness Service for Health (CASH))
Source: Current Awareness Service for Health (CASH) - October 4, 2022 Category: Consumer Health News Source Type: news

Some Coronaviruses Kill, While Others Cause a Common Cold. We Are Getting Closer to Knowing Why
This article is republished from The Conversation under a Creative Commons license. Read the original article. (Source: IPS Inter Press Service - Health)
Source: IPS Inter Press Service - Health - October 4, 2022 Category: International Medicine & Public Health Authors: External Source Tags: Headlines Health Source Type: news

Majority of North Carolinians have antibodies against coronavirus
<div class="rxbodyfield">NIEHS COVID-19 serological surveillance study tracked the presence and rate of development of anti-SARS-CoV-2 antibodies in North Carolina.</div> (read more) (Source: Environmental Factor - NIEHS Newsletter)
Source: Environmental Factor - NIEHS Newsletter - October 4, 2022 Category: Environmental Health Source Type: news

Two Are Better Than One: Expanding Our Covid-19 Vaccine Antigens
Like influenza, SARS-CoV-2 is an expert at mutating and evading prior immunity. This includes vaccine-induced immunity. New research suggests that expanding the target area of our vaccines to include the virus' nucleocapsid protein may offer stronger and broader protection. (Source: Forbes.com Healthcare News)
Source: Forbes.com Healthcare News - October 3, 2022 Category: Pharmaceuticals Authors: William A. Haseltine, Contributor Tags: Healthcare /healthcare Innovation /innovation Coronavirus business pharma & Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations
Chem Phys. 2023 Jan 1;564:111709. doi: 10.1016/j.chemphys.2022.111709. Epub 2022 Sep 26.ABSTRACTInhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine com...
Source: Chemical Physics - October 3, 2022 Category: Chemistry Authors: Trung Hai Nguyen Nguyen Minh Tam Mai Van Tuan Peng Zhan Van V Vu Duong Tuan Quang Son Tung Ngo Source Type: news