On the Role of the Crystal Environment in Determining Protein Side-chain Conformations

Jacobson, Matthew P.; Friesner, Richard A.; Xiang, Zhaoyin; Honig, Barry

doi:10.1016/s0022-2836(02)00470-9

Cited by 1,077 publications

(951 citation statements)

References 38 publications

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“…Indeed, as we discuss in detail elsewhere, crystal packing effects play a strong role in stabilizing observed conformations of surface side chains. 18 …”

Section: Computational Models and Methodsmentioning

confidence: 99%

Force Field Validation Using Protein Side Chain Prediction

et al. 2002

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The prediction of protein side chain conformations is used to evaluate the accuracy of force field parameters. Specifically, new torsional parameters have recently been reported for the OPLS-AA force field, which achieved substantially better accuracy with respect to high level gas-phase quantum chemical calculations [J. Phys. Chem. B 2001, 105, 6474]. Here we demonstrate that these new parameters also lead to qualitatively improved side chain prediction accuracy. The primary emphasis is on the prediction of single side chain conformations, with the rest of the protein held fixed at the native configuration. Errors due to incomplete sampling can thus be essentially eliminated, using a combination of rotamer search and energy minimization. In addition, the protein environment is modeled realistically using implicit solvation and an explicit representation of crystal packing effects. Aided by the development of new algorithms, these calculations have been performed with modest computational requirements (a cluster of PCs) on a database of 36 proteins (∼5000 total residues). The side chain prediction tests that we employ are quite general and can be used to evaluate nonbonded or solvation parameters as well. As such, they provide a useful complement to decoy studies for force field validation.

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“…Indeed, as we discuss in detail elsewhere, crystal packing effects play a strong role in stabilizing observed conformations of surface side chains. 18 …”

Section: Computational Models and Methodsmentioning

confidence: 99%

Force Field Validation Using Protein Side Chain Prediction

et al. 2002

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“…Our algorithm for side-chain optimization has been described previously 1 and is summarized here. Sampling is accomplished primarily by using a highly detailed (10°resolution) rotamer library constructed by Xiang and Honig 31 from a database of 297 proteins.…”

Section: Side-chain Optimizationmentioning

confidence: 99%

“…The calculations are performed in the crystal environment to obtain a more realistic comparison with X-ray crystallographic data. Although effects of the crystal environment on loop geometry are typically much smaller than on side-chain orientation (a subject we have discussed previously 1 ), individual cases can manifest nontrivial differences, and obtaining an understanding of these differences is a useful endeavor in its own right.…”

Section: Introductionmentioning

confidence: 99%

A hierarchical approach to all‐atom protein loop prediction

et al. 2004

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The application of all-atom force fields (and explicit or implicit solvent models) to protein homology-modeling tasks such as side-chain and loop prediction remains challenging both because of the expense of the individual energy calculations and because of the difficulty of sampling the rugged all-atom energy surface. Here we address this challenge for the problem of loop prediction through the development of numerous new algorithms, with an emphasis on multiscale and hierarchical techniques. As a first step in evaluating the performance of our loop prediction algorithm, we have applied it to the problem of reconstructing loops in native structures; we also explicitly include crystal packing to provide a fair comparison with crystal structures. In brief, large numbers of loops are generated by using a dihedral angle-based buildup procedure followed by iterative cycles of clustering, side-chain optimization, and complete energy minimization of selected loop structures. We evaluate this method by using the largest test set yet used for validation of a loop prediction method, with a total of 833 loops ranging from 4 to 12 residues in length. Average/median backbone rootmean-square deviations (RMSDs) to the native structures (superimposing the body of the protein, not the loop itself) are 0.42/0.24 Å for 5 residue loops, 1.00/0.44 Å for 8 residue loops, and 2.47/1.83 Å for 11 residue loops. Median RMSDs are substantially lower than the averages because of a small number of outliers; the causes of these failures are examined in some detail, and many can be attributed to errors in assignment of protonation states of titratable residues, omission of ligands from the simulation, and, in a few cases, probable errors in the experimentally determined structures. When these obvious problems in the data sets are filtered out, average RMSDs to the native structures improve to 0.43 Å for 5 residue loops, 0.84 Å for 8 residue loops, and 1.63 Å for 11 residue loops. In the vast majority of cases, the method locates energy minima that are lower than or equal to that of the minimized native loop, thus indicating that sampling rarely limits prediction accuracy. The overall results are, to our knowledge, the best reported to date, and we attribute this success to the combination of an accurate all-atom energy function, efficient methods for loop buildup and side-chain optimization, and, especially for the longer loops, the hierarchical refinement protocol.

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“…[91][92][93][94][95] Initial CODV models are designed by the following 3D-modeling strategy (Fig. S1).…”

Section: Initial Design Of Codv Proteinsmentioning

confidence: 99%

CODV-Ig, a universal bispecific tetravalent and multifunctional immunoglobulin format for medical applications

Steinmetz

Vallée

Beil

et al. 2016

mAbs

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Bispecific immunoglobulins (Igs) typically contain at least two distinct variable domains (Fv) that bind to two different target proteins. They are conceived to facilitate clinical development of biotherapeutic agents for diseases where improved clinical outcome is obtained or expected by combination therapy compared to treatment by single agents. Almost all existing formats are linear in their concept and differ widely in drug-like and manufacture-related properties. To overcome their major limitations, we designed cross-over dual variable Ig-like proteins (CODV-Ig). Their design is akin to the design of circularly closed repeat architectures. Indeed, initial results showed that the traditional approach of utilizing (G4S) x linkers for biotherapeutics design does not identify functional CODV-Igs. Therefore, we applied an unprecedented molecular modeling strategy for linker design that consistently results in CODV-Igs with excellent biochemical and biophysical properties. CODV architecture results in a circular self-contained structure functioning as a self-supporting truss that maintains the parental antibody affinities for both antigens without positional effects. The format is universally suitable for therapeutic applications targeting both circulating and membrane-localized proteins. Due to the full functionality of the Fc domains, serum half-life extension as well as antibody-or complement-dependent cytotoxicity may support biological efficiency of CODV-Igs. We show that judicious choice in combination of epitopes and paratope orientations of bispecific biotherapeutics is anticipated to be critical for clinical outcome. Uniting the major advantages of alternative bispecific biotherapeutics, CODV-Igs are applicable in a wide range of disease areas for fast-track multi-parametric drug optimization.

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On the Role of the Crystal Environment in Determining Protein Side-chain Conformations

Cited by 1,077 publications

References 38 publications

Force Field Validation Using Protein Side Chain Prediction

Force Field Validation Using Protein Side Chain Prediction

A hierarchical approach to all‐atom protein loop prediction

CODV-Ig, a universal bispecific tetravalent and multifunctional immunoglobulin format for medical applications

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