The dead-end elimination theorem and its use in protein side-chain positioning

Desmet, Jan; Maeyer, Marc De; Hazes, Bart; Lasters, Ignace

doi:10.1038/356539a0

Cited by 653 publications

(568 citation statements)

References 12 publications

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“…(41)(42)(43)(44)(45)(46) The Dunbrack and Karplus rotamer library (47) was used, augmented by rotamers at ± 10° of χ 1 and χ 2 for each rotamer. Hydroxyl groups on Ser, Thr and Tyr were sampled at ± 60° and 180°.…”

Section: Protein Design Methodologymentioning

confidence: 99%

Rational Design of New Binding Specificity by Simultaneous Mutagenesis of Calmodulin and a Target Peptide

et al. 2006

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Calcium-saturated calmodulin (CaM) binds and influences the activity of a varied collection of target proteins in most cells. This promiscuity underlies CaM's role as a shared participant in calciumdependent signal transduction pathways, but imposes a handicap on popular CaM-based calcium biosensors, which display an undesired tendency to cross-react with cellular proteins. Designed CaM/ target pairs that retain high affinity for one another, but lack affinity for wild-type CaM and its natural interaction partners, would therefore be useful as sensor components, and possibly also as elements of "synthetic" cellular signaling networks. Here we have adopted a rational approach to creating suitably modified CaM/target complexes by using computational design methods to guide parallel site-directed mutagenesis of both binding partners. A hierarchical design procedure was applied to suggest a small number of complementary mutations on CaM and on a peptide ligand derived from skeletal muscle light chain kinase (M13). Experimental analysis showed that the procedure was successful in identifying CaM and M13 mutants with novel specificity for one another. Importantly, the designed complexes retained affinity comparable to the wild-type CaM/M13 complex. These results represent a step toward the creation of CaM and M13 derivatives with specificity fully orthogonal to the wild-type proteins, and show that qualitatively accurate predictions may be obtained from computational methods applied simultaneously to two proteins involved in multiple linked binding equilibria. Figure 1A). (2,3) Calcium-loaded CaM binds to isolated target sequences with affinity comparable to its complexes with the intact proteins, and with dissociation constants often in the nanomolar range. With few exceptions, CaM ligands tend to be highly basic, presenting lysine and arginine residues that form salt-bridge networks with negatively-charged and polar amino-acid side chains bordering the binding cleft on CaM ( Figure 1B). In addition, many CaM targets appear to be anchored by a key pair of bulky groups spaced apart by 2.5 or 3.5 helical turns. (4) Deletion or mutation of these anchor residues dramatically reduces CaMbinding affinity. (5,6) Considerable interest in CaM/peptide interactions has revolved around potential applications in biotechnology. CaM-affinity chromatography (7) The ability to understand and control determinants of binding specificity at the CaM/target interface is important both for biotechnological applications and for appreciation of how CaM transduces metabolic signals via multiple protein interaction networks. Many studies have probed the contributions of both the charged and hydrophobic anchor residues to CaM binding affinity, (5,6,(19)(20)(21)(22)) but relatively few have sought to manipulate specificity through purposeful mutagenesis of one or both binding partners. A step in this direction was taken by Mayo and colleagues,(23,24) and involved the integration of computational and experimental methods to bias CaM spe...

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Section: Protein Design Methodologymentioning

confidence: 99%

Rational Design of New Binding Specificity by Simultaneous Mutagenesis of Calmodulin and a Target Peptide

et al. 2006

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“…For the DEE, we adopted the original algorithm of Desmet et al (1992) and Lasters and Desmet (1993). First, E , and E2 of Equation 2 are calculated for all rotamers, and rotamers having high interaction energies (>30 kcal/mol) with the backbone atoms are eliminated.…”

Section: Methodsmentioning

confidence: 99%

“…Whereas all these algorithms are based on approximations, Desmet et al (1992) used Equation 2 to develop an exact method called dead-end elimination (DEE), which is able to determine the global minimum energy structure for all possible combinations of side-chain conformations.…”

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confidence: 99%

Determinants of protein side‐chain packing

1994

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The problem of protein side-chain packing for a given backbone trace is investigated using 3 different prediction models. The first requires an exhaustive search of all possible combinations of side-chain conformers, using the dead-end elimination theorem. The second considers only side-chain-backbone interactions, whereas the third neglects side-chain-backbone interactions and instead keeps side-chain-side-chain interactions. Predictions of sidechain conformations for 11 proteins using all 3 models show that removal of side-chain-side-chain interactions does not cause a large decrease in the prediction accuracy, whereas the model having only side-chain-side-chain interactions still retains a significant level of accuracy. These results suggest that the 2 classes of interactions, sidechain-backbone and side-chain-side-chain, are consistent with each other and work concurrently to stabilize the native conformations. This is confirmed by analyses of energy spectra of the side-chain conformations derived from the fourth prediction model, the Independent model, which gives almost the same quality of the prediction as the dead-end elimination. The analyses indicate that the 2 classes of interactions simultaneously increase the energy difference between the native and nonnative conformations.Keywords: consistency in side-chain packing; dead-end elimination; energy spectra; Independent model; prediction of side-chain conformation; side-chain packing; side-chain rotamer Individual proteins are characterized by their native backbone folds and side-chain arrangements. Because more than half of the degrees of freedom are required in defining the latter, the problem of side-chain packing is an important subproblem in protein folding. To tackle this problem of side-chain packing, it has often been assumed that the main-chain atoms are fixed at their native coordinates ( The number of possible combinations of side-chain conformations (c, and cj in E 2 ) is still too large to be enumerated exhaustively, but due to the simplicity of Equation 2, various heuristic approaches have successfully predicted side-chain con-

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“…Furthermore, exact filtering algorithms, among them integer programming, 21 dead-end elimination (DEE), 12,13,23 and A*, 24 can advance the R 4 process by eliminating possibilities. 17 For example, in DEE the relative global energy, E global , of an IP is composed of the linear sum of the energy contributions from the backbone, the self and interaction with backbone energy, E(i r ), of rotamer, r, at its position, i, and its pairwise interaction energy with rotamer at nearby position, j: best case, arrangement of rotamer, i r , still has a higher energy than the maximum energy, or worst case, arrangement of an alternate rotamer, i t :…”

Section: Computational Filtering (Cf) Approachesmentioning

confidence: 99%

Protein Interfacial Pocket Engineering via Coupled Computational Filtering and Biological Focusing Criterion

2007

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Abstract-To engineer bio-macromolecular systems, protein-substrate interactions and their configurations need to be understood, harnessed, and utilized. Due to the inherent large numbers of combinatorial configurations and conformational complexity, methods that rely on heuristics or stochastics, such as practical computational filtering (CF) or biological focusing (BF) criterions, when used alone rarely yield insights into these complexes or successes in (re)designing them. Here we use a coupled CF-BF criterion upon an amenable interfacial pocket (IP) of a protein scaffold complexed with its substrate to undergo residue replacement and R-group refinement (R 4 ) to filter out energetically unfavorable residues and R-group conformations, and focus in on those that are evolutionarily favorable. We show that this coupled filtering and focusing can efficiently provide a putative engineered IP candidate and validate it computationally and empirically. The CF-BF criterion may permit holistic understanding of the nuances of existing protein IPs and their scaffolds and facilitate bioengineering efforts to alter substrate specificity. Such approach may contribute to accelerated elucidation of engineering principles of biomacromolecular systems.

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The dead-end elimination theorem and its use in protein side-chain positioning

Cited by 653 publications

References 12 publications

Rational Design of New Binding Specificity by Simultaneous Mutagenesis of Calmodulin and a Target Peptide

Rational Design of New Binding Specificity by Simultaneous Mutagenesis of Calmodulin and a Target Peptide

Determinants of protein side‐chain packing

Protein Interfacial Pocket Engineering via Coupled Computational Filtering and Biological Focusing Criterion

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