Protein side-chain modeling

MJ Bower, FE Cohen, RL Dunbrack Jr. Prediction of protein side-chain rotamers from a backbone-dependent rotamer library A new homology modeling tool. J Mol Biol 267 1268-1282, 1997. 

A step closer toward realism is taken by off-lattice models in which the backbone is specified in some detail, while side chains, if they are represented at all, are taken to be single, unified spheres [44-50]. One indication that this approach is too simplistic was given in [51], which proved that for a backbone representation in which only Ca carbons were modeled, no contact potential could stabilize the native conformation of a single protein against its nonnative ( decoy ) conformations. However, Irback and co-workers were able to fold real protein sequences, albeit short ones, using a detailed backbone representation, with coarse-grained side chains modeled as spheres [49, 52-54]. 

Figure 8-24 (A) MolScript ribbon drawing of the periplasmic histidine-binding protein HisJ, a component of an ABC transporter system of Salmonella. The bound L-histidine is shown as a ball-and-stick model. (B) Stereoscopic view of the histidinebinding site showing hydrogen-bonding interactions of protein side chains with the histidine. From Oh et al.i60 Courtesy of Giovanna Ferro-Luzzi Ames.

Fig. 24 The side-chain models of amphiphilic polymers a amphiphilic homopolymer (poly-A), b regular alternating HA copolymer, c regular multiblock HA copolymer, and d protein-like HA copolymer. Each hydrophobic monomer unit (H) is considered as a single interaction site (bead) each amphiphilic group (A) is modeled by a dumbbell consisting of hydrophobic (H) and hydrophilic (P) beads...

F. Eisen me tiger, P. Algos, and R. Abagytn. A method to configure protein side-chains Doom the main-chain trace in homology modeling. A MoL Btoi. 2/3 849-860... 

Wang C, Schueler-Furman O, Baker D. Improved side chain modeling for protein-protein docking. Protein Sci. 2005 14 1328-1339. 

Chorismate mutase provides an example of an enzyme where QM/MM calculations have identified an important catalytic principle at work [8], This enzyme catalyses the Claisen rearrangement of chorismate to prephenate. The reaction within the enzyme is not believed to involve chemical catalysis, and this pericylic reaction also occurs readily in solution. Lyne et al. [8] investigated the reaction in chorismate mutase in QM/MM calculations, at the AMI QM level (AMI was found to perform acceptably well for this reaction in comparisons with ab initio results for the reaction in the gas phase [8]). Different sizes of QM system were tested in the QM/MM studies (e.g. including the substrate and no, or up to three, protein side chains), and similar results found in all cases. The reaction was modelled by minimization along an approximate reaction coordinate, defined as the ratio of the forming C-C and breaking C-0 bonds. Values of the reaction coordinate were taken from the AMI intrinsic reaction coordinate for the gas-phase reaction. 

Residual dipolar couplings have been used by Mittermaier and Kay187 to probe the torsion angle dynamics of protein side-chains. Using the B1 domain of peptostreptococcal protein L, they show that the residual dipolar couplings can be used to distinguish static from mobile side-chains, and that the motions of most mobile side-chains can be adequately explained by rotamer-jump models. 

Analysis of the TBPA-Ti complex (39,40) indicates that the binding site for the hormone is located deep inside the channel. The hormone makes extensive interactions with the protein side chains that project into the channel. The 4 -hydroxyl of Ti interacts with a patch of hydroxy-amino acids of the protein while each of the iodines makes contact with a number of hydro-phobic protein residues. The T amino acid side chain functional groups are in appropriate positions to interact with glutamic acid and lysine residues. Thus, this channel provides a favorable environment for each of the characteristic substituents of the thyroid hormone (40). However, because of the Ti orientation disorder in the protein complex, this structural model is not a sensitive measure of the observed correlations between diphenyl ether conformations and binding affinity data. 

Samudrala and Moult described a method for handling context sensitivity of protein structure prediction, that is, simultaneous loop and side-chain modeling, using a graph theory method [198, 209] and an all-atom distance-dependent statistical potential energy function [199]. Their program RAMP is listed in Table 5.6. 

J. Mendes, C. M. Soares, M. A. Carrondo. Improvement of side-chain modeling in proteins with the self-consistent mean field theory method based on an analysis of the factors influencing prediction. Biopolymers. 1999, 50, 111-131. 

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