Extending the accuracy limits of prediction for side-chain conformations

Xiang, Zhaoyin; Honig, Barry

doi:10.1006/jmbi.2001.4865

Cited by 371 publications

(185 citation statements)

References 38 publications

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“…We modeled the parkin RING I domain structure with the JACKAL MOLECULAR MODELING PACKAGE (16), using the related human c-Cbl crystal structure (PDB ID code 1FBV) as a template. The alignment of c-Cbl and parkin RING I protein sequences was generated by SEGMENT ALIGN-MENT ALGORITHM (SEA) software (17)(18)(19).…”

Section: Mass Spectrometry (Ms)mentioning

confidence: 99%

Nitrosative stress linked to sporadic Parkinson's disease: S-nitrosylation of parkin regulates its E3 ubiquitin ligase activity

Yao

Nakamura

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

485

464

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Many hereditary and sporadic neurodegenerative disorders are characterized by the accumulation of aberrant proteins. In sporadic Parkinson's disease, representing the most prevalent movement disorder, oxidative and nitrosative stress are believed to contribute to disease pathogenesis, but the exact molecular basis for protein aggregation remains unclear. In the case of autosomal recessive-juvenile Parkinsonism, mutation in the E3 ubiquitin ligase protein parkin is linked to death of dopaminergic neurons. Here we show both in vitro and in vivo that nitrosative stress leads to S-nitrosylation of wild-type parkin and, initially, to a dramatic increase followed by a decrease in the E3 ligase-ubiquitin-proteasome degradative pathway. The initial increase in parkin's E3 ubiquitin ligase activity leads to autoubiquitination of parkin and subsequent inhibition of its activity, which would impair ubiquitination and clearance of parkin substrates. These findings may thus provide a molecular link between free radical toxicity and protein accumulation in sporadic Parkinson's disease

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Section: Mass Spectrometry (Ms)mentioning

confidence: 99%

Nitrosative stress linked to sporadic Parkinson's disease: S-nitrosylation of parkin regulates its E3 ubiquitin ligase activity

Yao

Nakamura

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

485

464

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“…A way to overcome the search-space limitation was suggested by Mendes et al (52); it presents a rotamer as a continuous ensemble of conformations that cluster around the classic rigid rotamer. A different approach to expanding the search space was recently devised by Honig and coworkers (19), which achieved accurate predictions by using an extensive rotamer library containing over 7,560 members, in which bond lengths and bond angles were taken from the database rather than simply assuming idealized values. Further, the performance of CHARMM (53) was better than that of AMBER in that work.…”

Section: Discussionmentioning

confidence: 99%

A stochastic algorithm for global optimization and for best populations: A test case of side chains in proteins

Glick

Rayan

Goldblum

2002

Proc. Natl. Acad. Sci. U.S.A.

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The problem of global optimization is pivotal in a variety of scientific fields. Here, we present a robust stochastic search method that is able to find the global minimum for a given cost function, as well as, in most cases, any number of best solutions for very large combinatorial ''explosive'' systems. The algorithm iteratively eliminates variable values that contribute consistently to the highest end of a cost function's spectrum of values for the full system. Values that have not been eliminated are retained for a full, exhaustive search, allowing the creation of an ordered population of best solutions, which includes the global minimum. We demonstrate the ability of the algorithm to explore the conformational space of side chains in eight proteins, with 54 to 263 residues, to reproduce a population of their low energy conformations. The 1,000 lowest energy solutions are identical in the stochastic (with two different seed numbers) and full, exhaustive searches for six of eight proteins. The others retain the lowest 141 and 213 (of 1,000) conformations, depending on the seed number, and the maximal difference between stochastic and exhaustive is only about 0.15 Kcal͞mol. The energy gap between the lowest and highest of the 1,000 low-energy conformers in eight proteins is between 0.55 and 3.64 Kcal͞mol. This algorithm offers real opportunities for solving problems of high complexity in structural biology and in other fields of science and technology.M any problems in life sciences and in other fields of science and technology are of high complexity, thus requiring sophisticated methods of searching and scoring to achieve the ability to study and to simulate them by means of a computer simulation. An excellent search method coupled with a highly reliable scoring method should allow comparisons to some natural phenomena. In this article, we have taken the approach of comparing best populations found by a stochastic search method to a full, exhaustive search, as the crucial test of this method. However, comparisons to experimental results also are included. The problem chosen to exemplify this method is the positions of side chains in proteins, which is essential for both theoretical and experimental purposes. On the theoretical side, it is a subproblem in de novo protein structure prediction. It is essential for structure-based drug design (1), for inverse folding and threading algorithms (2), for predicting the effect of mutations on structure (3), for ab initio predictions of tertiary structure (4), for homology-based modeling (5), and others. From the x-ray crystallographer's point of view, it could speed the placement of side chains using the electron density maps of the main chain before refinement calculations. The main limitation is the large amount of possible conformations that each side chain may adopt (6). An exhaustive search of all possible conformations is beyond the scope of state of the art computers.Current strategies for side chain addition to a given backbone differ in three categories. The ...

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“…First, the side-chain prediction algorithm used for these decoy sets may not be optimal. Tests of rebuilding side chains with the SCAP method 53 led to better overall DFIRE-AA scores (results not shown). The other issue is that the fraction of native contacts may have, in analogy to a scoring function, a narrow funnel versus backbone rmsd.…”

Section: Decoy Set Propertiesmentioning

confidence: 99%

Assessment of Detection and Refinement Strategies for de novo Protein Structures Using Force Field and Statistical Potentials

Lee

Olson

2006

J. Chem. Theory Comput.

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Abstract:De novo predictions of protein structures at high resolution are plagued by the problem of detecting the native conformation from false energy minima. In this work, we provide an assessment of various detection and refinement protocols on a small subset of the secondgeneration all-atom Rosetta decoy set (Tsai et al. Proteins 2003, 53, 76-87) using two potentials: the all-atom CHARMM PARAM22 force field combined with generalized Born/surfacearea (GB-SA) implicit solvation and the DFIRE-AA statistical potential. Detection schemes included DFIRE-AA conformational scoring and energy minimization followed by scoring with both GB-SA and DFIRE-AA potentials. Refinement methods included short-time (1-ps) molecular dynamics simulations, temperature-based replica exchange molecular dynamics, and a new computational unfold/refold procedure. Refinement methods include temperature-based replica exchange molecular dynamics and a new computational unfold/refold procedure. Our results indicate that simple detection with only minimization is the best protocol for finding the most nativelike structures in the decoy set. The refinement techniques that we tested are generally unsuccessful in improving detection; however, they provide marginal improvements to some of the decoy structures. Future directions in the development of refinement techniques are discussed in the context of the limitations of the protocols evaluated in this study.

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Extending the accuracy limits of prediction for side-chain conformations

Cited by 371 publications

References 38 publications

Nitrosative stress linked to sporadic Parkinson's disease: S-nitrosylation of parkin regulates its E3 ubiquitin ligase activity

Nitrosative stress linked to sporadic Parkinson's disease: S-nitrosylation of parkin regulates its E3 ubiquitin ligase activity

A stochastic algorithm for global optimization and for best populations: A test case of side chains in proteins

Assessment of Detection and Refinement Strategies for de novo Protein Structures Using Force Field and Statistical Potentials

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