Characterization of novel proteins based on known protein structures 1 1Edited by R. Huber

Koppensteiner, Walter A.; Lackner, Peter; Wiederstein, Markus; Sippl, Manfred J.

doi:10.1006/jmbi.1999.3501

Cited by 45 publications

(38 citation statements)

References 78 publications

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“…3D-pssm uses profiles to represent both the target and the template proteins. Even with these developments, structure prediction achieves substantially lower performance than the suggested ideal values [15]. This is largely the result of pattern degeneracy between the known structures and structures being predicted [16].…”

Section: Modeling Using Sequence and Structurementioning

confidence: 98%

Profile combinatorics for fragment selection in comparative protein structure modeling

Sweeney

Alter

Raymer

et al. 2001

Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)

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Section: Modeling Using Sequence and Structurementioning

confidence: 98%

Profile combinatorics for fragment selection in comparative protein structure modeling

Sweeney

Alter

Raymer

et al. 2001

Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)

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“…At present, this approach allows us to an-notate about 60 -70% of genes from the newly sequenced genomes. Unfortunately, with increasing evolutionary distance, the functions of homologous proteins diverge and this often defines a practical limit of function annotation by homology (Coles et al, 1999;Koppensteiner et al, 2000;Pawlowski et al, 2000;Pearl et al, 2000).…”

Section: Structural Bioinformatics: Seeking Functional Insights From mentioning

confidence: 99%

Fold Predictions for Bacterial Genomes

Pawłowski

Rychlewski

Zhang

et al. 2001

Journal of Structural Biology

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“…This problem has no unique answer, as similar sequences usually share the same structure. In addition, there are many cases of nearly identical structures sharing no sequence similarity (Brenner & Levitt 2000;Devos & Valencia 2000;Koppensteiner et al 2000;Tian & Skolnick 2003). Nevertheless, in computational protein design, the goal is not to find all sequences folding in the given structure but just one with the required properties.…”

Section: Introductionmentioning

confidence: 99%

Challenges in the computational design of proteins

Suárez

Jaramillo

2009

J. R. Soc. Interface.

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Protein design has many applications not only in biotechnology but also in basic science. It uses our current knowledge in structural biology to predict, by computer simulations, an amino acid sequence that would produce a protein with targeted properties. As in other examples of synthetic biology, this approach allows the testing of many hypotheses in biology. The recent development of automated computational methods to design proteins has enabled proteins to be designed that are very different from any known ones. Moreover, some of those methods mostly rely on a physical description of atomic interactions, which allows the designed sequences not to be biased towards known proteins. In this paper, we will describe the use of energy functions in computational protein design, the use of atomic models to evaluate the free energy in the unfolded and folded states, the exploration and optimization of amino acid sequences, the problem of negative design and the design of biomolecular function. We will also consider its use together with the experimental techniques such as directed evolution. We will end by discussing the challenges ahead in computational protein design and some of their future applications.

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Characterization of novel proteins based on known protein structures 1 1Edited by R. Huber

Cited by 45 publications

References 78 publications

Profile combinatorics for fragment selection in comparative protein structure modeling

Profile combinatorics for fragment selection in comparative protein structure modeling

Fold Predictions for Bacterial Genomes

Challenges in the computational design of proteins

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