Enhanced dead-end elimination in the search for the global minimum energy conformation of a collection of protein side chains

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

doi:10.1093/protein/8.8.815

Cited by 91 publications

(72 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(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

View full text Add to dashboard Cite

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...

show abstract

Section: Protein Design Methodologymentioning

confidence: 99%

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

et al. 2006

View full text Add to dashboard Cite

show abstract

“…Rotamers were taken from the Dunbrack 2002 rotamer library [52]. We used our implementation of the dead end elimination (DEE) and A* branch and bound algorithms [53][54][55][56][57][58] to find the optimal structure for each sequence. Given this structure, we calculated its folding energy E f old repack using the potential used for repacking.…”

Section: Methodsmentioning

confidence: 99%

“…Two Monte Carlo searches were run-one using repacking, minimization, and re-evaluation according to E f old min;GB to score each sequence (direct design) and the other using CE equivalent of the same energy function (CE design). The DEE and A* branch and bound algorithms for repacking [53][54][55][56][57][58] were implemented in C. CHARMM [49] was used for continuous side-chain minimization and calculation of the van der Waals and EEF1 portions of the potential. PEP [60] was used to calculate atomic Born radii.…”

Section: Methodsmentioning

confidence: 99%

Ultra-fast Evaluation of Protein Energies Directly from Sequence

Grigoryan¹,

Zhou²,

Lustig³

et al. 2005

PLoS Comp Biol

View full text Add to dashboard Cite

The structure, function, stability, and many other properties of a protein in a fixed environment are fully specified by its sequence, but in a manner that is difficult to discern. We present a general approach for rapidly mapping sequences directly to their energies on a pre-specified rigid backbone, an important sub-problem in computational protein design and in some methods for protein structure prediction. The cluster expansion (CE) method that we employ can, in principle, be extended to model any computable or measurable protein property directly as a function of sequence. Here we show how CE can be applied to the problem of computational protein design, and use it to derive excellent approximations of physical potentials. The approach provides several attractive advantages. First, following a onetime derivation of a CE expansion, the amount of time necessary to evaluate the energy of a sequence adopting a specified backbone conformation is reduced by a factor of 10 7 compared to standard full-atom methods for the same task. Second, the agreement between two full-atom methods that we tested and their CE sequence-based expressions is very high (root mean square deviation 1.1-4.7 kcal/mol, R 2 ¼ 0.7-1.0). Third, the functional form of the CE energy expression is such that individual terms of the expansion have clear physical interpretations. We derived expressions for the energies of three classic protein design targets-a coiled coil, a zinc finger, and a WW domain-as functions of sequence, and examined the most significant terms. Single-residue and residue-pair interactions are sufficient to accurately capture the energetics of the dimeric coiled coil, whereas higher-order contributions are important for the two more globular folds. For the task of designing novel zinc-finger sequences, a CE-derived energy function provides significantly better solutions than a standard design protocol, in comparable computation time. Given these advantages, CE is likely to find many uses in computational structural modeling.

show abstract

“…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

View full text Add to dashboard Cite

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.

show abstract

Enhanced dead-end elimination in the search for the global minimum energy conformation of a collection of protein side chains

Cited by 91 publications

References 0 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

Ultra-fast Evaluation of Protein Energies Directly from Sequence

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

Contact Info

Product

Resources

About