“…During docking, the protein structure is kept rigid by the software. In an earlier study, protein dynamics have been taken into account using a series of structures from a molecular dynamics (MD) simulation . The data correlate with those presented in this study for the heptamer.…”
Section: Discussionsupporting
confidence: 78%
“…Recently, a structure of p7 (GT5a) in a hexameric form was proposed by solution NMR spectroscopy . Docking studies of the ligands mentioned in this study with that p7 bundle support a similar ranking of the ligands as for bundles generated by the computational method mentioned earlier and also used in this study. Thus, the ranking remains unaffected despite structural diversity.…”
Section: Discussionsupporting
confidence: 70%
“…A series of docking approaches of known ligand affecting viral channel proteins have been undertaken with monomeric and hexameric as well as in this study with heptameric protein p7. A common feature of all poses is that poses at the loops and poses either within the pore or the intermonomer space of the bundle are preferred for all ligands.…”
Section: Discussionmentioning
confidence: 99%
“…Computational methods have been used to address putative binding sites of specific ligands to a bundle model . Some of them aim to reflect on the issue whether the in vitro / in vivo success of specific known ligands could have been identified on the level of ligand docking . In all these studies, computationally derived hexameric bundles of GT1a have been used.…”
Section: Introductionmentioning
confidence: 99%
“…In all these studies, computationally derived hexameric bundles of GT1a have been used. In one study, experimentally derived bundle models of p7 of GT1b and GT5a have been investigated …”
A series of ligands are known experimentally to affect the infectivity cycle of the hepatitis C virus. The target protein for the ligands is proposed to be p7, a 63 amino acid polytopic channel-forming protein, with possibly two transmembrane domains. Protein p7 is found to assemble into functional oligomers of various sizes, depending on the genotype (GT). Nine ligands are docked to various sites of a computationally derived heptameric bundle of p7 of GT1a. The energy of interaction, here binding energy, is calculated using three different docking programs (Autodock, MOE, LeadIT). Three protein regions are defined to which the ligands are placed, the loop region and the site with the termini as well as the mid-region which is supposed to track poses inside the putative pore. A common feature is that the loop sites and poses either within the pore or at the intermonomer space of the bundle are preferred for all ligands with proposed binding energies smaller than -10 kJ/mol. BIT225, benzamine, amantadine, and NN-DNJ show good overall scoring.
“…During docking, the protein structure is kept rigid by the software. In an earlier study, protein dynamics have been taken into account using a series of structures from a molecular dynamics (MD) simulation . The data correlate with those presented in this study for the heptamer.…”
Section: Discussionsupporting
confidence: 78%
“…Recently, a structure of p7 (GT5a) in a hexameric form was proposed by solution NMR spectroscopy . Docking studies of the ligands mentioned in this study with that p7 bundle support a similar ranking of the ligands as for bundles generated by the computational method mentioned earlier and also used in this study. Thus, the ranking remains unaffected despite structural diversity.…”
Section: Discussionsupporting
confidence: 70%
“…A series of docking approaches of known ligand affecting viral channel proteins have been undertaken with monomeric and hexameric as well as in this study with heptameric protein p7. A common feature of all poses is that poses at the loops and poses either within the pore or the intermonomer space of the bundle are preferred for all ligands.…”
Section: Discussionmentioning
confidence: 99%
“…Computational methods have been used to address putative binding sites of specific ligands to a bundle model . Some of them aim to reflect on the issue whether the in vitro / in vivo success of specific known ligands could have been identified on the level of ligand docking . In all these studies, computationally derived hexameric bundles of GT1a have been used.…”
Section: Introductionmentioning
confidence: 99%
“…In all these studies, computationally derived hexameric bundles of GT1a have been used. In one study, experimentally derived bundle models of p7 of GT1b and GT5a have been investigated …”
A series of ligands are known experimentally to affect the infectivity cycle of the hepatitis C virus. The target protein for the ligands is proposed to be p7, a 63 amino acid polytopic channel-forming protein, with possibly two transmembrane domains. Protein p7 is found to assemble into functional oligomers of various sizes, depending on the genotype (GT). Nine ligands are docked to various sites of a computationally derived heptameric bundle of p7 of GT1a. The energy of interaction, here binding energy, is calculated using three different docking programs (Autodock, MOE, LeadIT). Three protein regions are defined to which the ligands are placed, the loop region and the site with the termini as well as the mid-region which is supposed to track poses inside the putative pore. A common feature is that the loop sites and poses either within the pore or at the intermonomer space of the bundle are preferred for all ligands with proposed binding energies smaller than -10 kJ/mol. BIT225, benzamine, amantadine, and NN-DNJ show good overall scoring.
Membrane proteins perform a host of vital cellular functions. Deciphering the molecular mechanisms whereby they fulfill these functions requires detailed biophysical and structural investigations. Detergents have proven pivotal to extract the protein from its native surroundings. Yet, they provide a milieu that departs significantly from that of the biological membrane, to the extent that the structure, the dynamics, and the interactions of membrane proteins in detergents may considerably vary, as compared to the native environment. Understanding the impact of detergents on membrane proteins is, therefore, crucial to assess the biological relevance of results obtained in detergents. Here, we review the strengths and weaknesses of alkyl phosphocholines (or foscholines), the most widely used detergent in solution-NMR studies of membrane proteins. While this class of detergents is often successful for membrane protein solubilization, a growing list of examples points to destabilizing and denaturing properties, in particular for α-helical membrane proteins. Our comprehensive analysis stresses the importance of stringent controls when working with this class of detergents and when analyzing the structure and dynamics of membrane proteins in alkyl phosphocholine detergents.
A de novo assembly algorithm is provided to propose the assembly of bitopic transmembrane domains (TMDs) of membrane proteins. The algorithm is probed using, in particular, viral channel forming proteins (VCPs) such as M2 of influenza A virus, E protein of severe acute respiratory syndrome corona virus (SARS-CoV), 6K of Chikungunya virus (CHIKV), SH of human respiratory syncytial virus (hRSV), and Vpu of human immunodeficiency virus type 2 (HIV-2). The generation of the structures is based on screening a 7-dimensional space. Assembly of the TMDs can be achieved either by simultaneously docking the individual TMDs or via a sequential docking. Scoring based on estimated binding energies (EBEs) of the oligomeric structures is obtained by the tilt to decipher the handedness of the bundles. The bundles match especially well for all-atom models of M2 referring to an experimentally reported tetrameric bundle. Docking of helical poly-peptides to experimental structures of M2 and E protein identifies improving EBEs for positively charged (K,R,H) and aromatic amino acids (F,Y,W). Data are improved when using polypeptides for which the coordinates of the amino acids are adapted to the Cα coordinates of the respective experimentally derived structures of the TMDs of the target proteins.
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