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      Structural similarity between HIV-1 gp41 and SARS-CoV S2 proteins suggests an analogous membrane fusion mechanism

      research-article
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      Theochem
      Elsevier B.V.
      SARS-CoV, Human immunodeficiency virus type 1, Structural similarity, Inhibitor

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          Abstract

          SARS-associated coronavirus (SARS-CoV) has been identified as the causal agent of a new emerging disease: severe acute respiratory syndrome (SARS). Its spike protein S2 is responsible for mediating fusion of viral and cellular membrane. In this study, we modeled the 3D structure of S2 subunit and compared this model with the core structure of gp41 from HIV-1. We found that SARS-CoV S2 and gp41 share the same two α helices, suggesting that the two viruses could follow an analogous membrane fusion mechanism. Further ligand-binding analysis showed that two inhibitors GGL and D-peptide from HIV-1 gp41 may serve as inhibitors for SARS-CoV entry.

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          Most cited references8

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          Core structure of gp41 from the HIV envelope glycoprotein.

          The envelope glycoprotein of human immunodeficiency virus type 1 (HIV-1) consists of a complex of gp120 and gp41. gp120 determines viral tropism by binding to target-cell receptors, while gp41 mediates fusion between viral and cellular membranes. Previous studies identified an alpha-helical domain within gp41 composed of a trimer of two interacting peptides. The crystal structure of this complex, composed of the peptides N36 and C34, is a six-helical bundle. Three N36 helices form an interior, parallel coiled-coil trimer, while three C34 helices pack in an oblique, antiparallel manner into highly conserved, hydrophobic grooves on the surface of this trimer. This structure shows striking similarity to the low-pH-induced conformation of influenza hemagglutinin and likely represents the core of fusion-active gp41. Avenues for the design/discovery of small-molecule inhibitors of HIV infection are directly suggested by this structure.
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            Can correct protein models be identified?

            The ability to separate correct models of protein structures from less correct models is of the greatest importance for protein structure prediction methods. Several studies have examined the ability of different types of energy function to detect the native, or native-like, protein structure from a large set of decoys. In contrast to earlier studies, we examine here the ability to detect models that only show limited structural similarity to the native structure. These correct models are defined by the existence of a fragment that shows significant similarity between this model and the native structure. It has been shown that the existence of such fragments is useful for comparing the performance between different fold recognition methods and that this performance correlates well with performance in fold recognition. We have developed ProQ, a neural-network-based method to predict the quality of a protein model that extracts structural features, such as frequency of atom-atom contacts, and predicts the quality of a model, as measured either by LGscore or MaxSub. We show that ProQ performs at least as well as other measures when identifying the native structure and is better at the detection of correct models. This performance is maintained over several different test sets. ProQ can also be combined with the Pcons fold recognition predictor (Pmodeller) to increase its performance, with the main advantage being the elimination of a few high-scoring incorrect models. Pmodeller was successful in CASP5 and results from the latest LiveBench, LiveBench-6, indicating that Pmodeller has a higher specificity than Pcons alone.
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              3D-Jury: a simple approach to improve protein structure predictions.

              Consensus structure prediction methods (meta-predictors) have higher accuracy than individual structure prediction algorithms (their components). The goal for the development of the 3D-Jury system is to create a simple but powerful procedure for generating meta-predictions using variable sets of models obtained from diverse sources. The resulting protocol should help to improve the quality of structural annotations of novel proteins. The 3D-Jury system generates meta-predictions from sets of models created using variable methods. It is not necessary to know prior characteristics of the methods. The system is able to utilize immediately new components (additional prediction providers). The accuracy of the system is comparable with other well-tuned prediction servers. The algorithm resembles methods of selecting models generated using ab initio folding simulations. It is simple and offers a portable solution to improve the accuracy of other protein structure prediction protocols. The 3D-Jury system is available via the Structure Prediction Meta Server (http://BioInfo.PL/Meta/) to the academic community. 3D-Jury is coupled to the continuous online server evaluation program, LiveBench (http://BioInfo.PL/LiveBench/)
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                Author and article information

                Contributors
                Journal
                Theochem
                Theochem
                Theochem
                Elsevier B.V.
                0166-1280
                0166-1280
                2 April 2004
                May 2004
                2 April 2004
                : 677
                : 1
                : 73-76
                Affiliations
                HKU-Pasteur Research Center, Bioinformatics, 8 Sassoon Road, Pokfulam, Hong Kong, China
                Author notes
                []Corresponding author. Tel.: +852-2816-8407; fax: +852-2872-5782 xwzhang@ 123456hkucc.hku.hk
                Article
                S0166-1280(04)00124-1
                10.1016/j.theochem.2004.02.018
                7141560
                32287546
                ef48fd64-2957-4a3e-9542-1e692d384153
                Copyright © 2004 Elsevier B.V. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 25 November 2003
                : 2 February 2004
                Categories
                Article

                sars-cov,human immunodeficiency virus type 1,structural similarity,inhibitor

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