Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool

Bower, Michael J.; Cohen, Fred E.; Dunbrack, Roland L.

doi:10.1006/jmbi.1997.0926

Cited by 543 publications

(501 citation statements)

References 57 publications

(132 reference statements)

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“…The crystal structure of Protein Data Bank entry 1AUR 32 was used to build a model of OVCA2 using the side chain conformation prediction program SCWRL. 28 The sequence identity between OVCA2 and the crystal structure is only 13%, but the same fold was identified with high confidence with 3 different programs, PSI-BLAST, 26 , 3d-pssm 33 and Threader. 34 The significance of this domain within the DHFRs, however, has yet to be reported.…”

Section: Ovca2 Protein Modelmentioning

confidence: 87%

“…Upon completion, this matrix was used to search a database of protein sequences in the Protein Data Bank 27 of experimentally determined protein structures. A model of OVCA2 was built using the side-chain conformation prediction program SCRWL, 28 which works by building side chains on a template backbone by first placing residues according to a backbone-dependent rotamer library, 29 followed by a combinatorial search to remove steric overlaps.…”

Section: Homology Modeling Of Ovca2mentioning

confidence: 99%

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OVCA2 is downregulated and degraded during retinoid‐induced apoptosis

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Vanderveer

Milling

et al. 2002

Intl Journal of Cancer

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Retinoids, the natural and synthetic derivatives of vitamin A, have been shown to regulate the growth and differentiation of a wide variety of cell types and consequently have enormous potential as chemotherapeutic agents. We have previously identified 2 genes, termed OVCA1 and OVCA2, which are located in a small region showing a high frequency of allelic loss in breast and ovarian tumors and share a common exon. Recent studies have suggested that expression of OVCA1 may be influenced by retinoids. Therefore, we analyzed the expression of OVCA1 and OVCA2 in cells in response to treatment with all-trans retinoic acid (RA) and N-(4-hydroxyphenyl)retinamide (4HPR), or under conditions of low serum and confluence, to determine further the roles of OVCA1 and OVCA2 in cell growth, apoptosis and differentiation. We show that OVCA2 mRNA and protein are ubiquitously expressed and that they are downregulated in the lung cancer cell line Calu-6 after treatment with RA and 4HPR. In addition, we observed that OVCA2 protein is proteolytically degraded in response to RA and 4HPR treatment in a time-and dose-dependent manner in the promyelocytic leukemia cell line HL60. In contrast, expression of the candidate tumor suppressor OVCA1 was not downregulated by these treatments. Furthermore, we demonstrate that OVCA2 is evolutionarily conserved and shows regional homology with dihydrofolate reductases (DHFRs), specifically with hydrolase folds found in ␣-␤ hydrolases. Our results are in contrast to a previous report and show that OVCA2, not OVCA1 mRNA and protein, is downregulated in response to RA and 4HPR.

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Section: Ovca2 Protein Modelmentioning

confidence: 87%

Section: Homology Modeling Of Ovca2mentioning

confidence: 99%

OVCA2 is downregulated and degraded during retinoid‐induced apoptosis

Prowse

Vanderveer

Milling

et al. 2002

Intl Journal of Cancer

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“…At this day, SCWRL is the most widely used method [89][90][91]. It is based on a simple scoring function and a backbone dependent rotamer library.…”

Section: Introductionmentioning

confidence: 99%

Protein contacts, inter-residue interactions and side-chain modelling

Faure¹,

Bornot²,

Brevern³

2008

Biochimie

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To cite this version:Guilhem Faure, Aurélie Bornot, Alexandre De Brevern. Protein contacts, inter-residue interactions and side-chain modelling.: protein contacts. Biochimie, Elsevier, 2008, 90 (4) AbstractThree-dimensional structures of proteins are the support of their biological functions.Their folds are stabilized by contacts between residues. Inner protein contacts are generally described through direct atomic contacts, i.e. interactions between side-chain atoms, while contact prediction methods mainly used inter-C distances. In this paper, we have analyzed the protein contacts on a recent high quality non-redundant databank using different criteria.First, we have studied the average number of contacts depending on the distance threshold to define a contact. Preferential contacts between types of amino acids have been highlighted.Detailed analyses have been done concerning the proximity of contacts in the sequence, the size of the proteins and fold classes. The strongest differences have been extracted, highlighting important residues.Then, we studied the influence of five different side-chain conformation prediction methods (SCWRL, IRECS, SCAP, SCATD and SSCOMP) on the distribution of contacts.The prediction rates of these different methods are quite similar. However, using a distance criterion between side-chains, the results are quite different, e.g. SCAP predicts 50% more contacts than observed, unlike other methods that predict fewer contacts than observed.Contacts deduced are quite distinct from one method to another with at most 75% contacts in common. Moreover, distributions of amino acid preferential contacts present unexpected behaviors distinct from previously observed in the X-ray structures, especially at the surface of proteins. For instance, the interactions involving Tryptophan greatly decrease.

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“…3,4 Sidechain packing has been studied intensively for various reasons, notably: 1) It is thought to be a crucial piece of the protein folding puzzle; 5,6 2) The selection of protein sequences through evolution may have been influenced by how well a sequence can be packed for a particular fold; 4 3) Accurate packing algorithms are necessary for complete protein structure prediction; and 4) Existing threading and homology modeling algorithms may be significantly improved by a better understanding of how sidechains are stabilized in the core. 7,8 A plethora of computational methods for modeling protein sidechains and energetics exist, 3,7,9,10 and yet which ones best capture the underlying physics is unclear. This is due, in part, to the use of energy functions containing many different types of interactions.…”

Section: Introductionmentioning

confidence: 99%

Excluded volume in protein side-chain packing

Kussell

Shimada

Shakhnovich

2001

Journal of Molecular Biology

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The excluded volume occupied by protein sidechains and the requirement of high packing density in the protein interior should severely limit the number of sidechain conformations compatible with a given native backbone. To examine the relationship between sidechain geometry and sidechain packing, we use an all-atom Monte Carlo simulation to sample the large space of sidechain conformations. We study three models of excluded volume and use umbrella sampling to effectively explore the entire space. We find that while excluded volume constraints reduce the size of conformational space by many orders of magnitude, the number of allowed conformations is still large. An average repacked conformation has 20% of its χ angles in a non-native state, a marked reduction from the expected 67% in the absence of excluded volume. Interestingly, well-packed conformations with up to 50% non-native χ's exist. The repacked conformations have native packing density as measured by a standard Voronoi procedure. Entropy is distributed non-uniformly over positions, and we partially explain the observed distribution using rotamer probabilities derived from the pdb database. 1In several cases, native rotamers which occur infrequently in the pdb database are seen with high probability in our simulation, indicating that sequence-specific excluded volume interactions can stabilize rotamers that are rare for a given backbone. In spite of our finding that 65% of the native rotamers and 85% of χ 1 angles can be correctly predicted on the basis of excluded volume only, 95% of positions can accomodate more than 1 rotamer in simulation. We estimate that in order to quench the sidechain entropy observed in the presence of excluded volume interactions, other interactions (hydrophobic, polar, electrostatic) must provide an additional stabilization of at least 0.6 kT per residue in order to single out the native state.2

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Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool

Cited by 543 publications

References 57 publications

OVCA2 is downregulated and degraded during retinoid‐induced apoptosis

OVCA2 is downregulated and degraded during retinoid‐induced apoptosis

Protein contacts, inter-residue interactions and side-chain modelling

Excluded volume in protein side-chain packing

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