Literature DB >> 17242380

The dominant role of side-chain backbone interactions in structural realization of amino acid code. ChiRotor: a side-chain prediction algorithm based on side-chain backbone interactions.

Velin Z Spassov1, Lisa Yan, Paul K Flook.   

Abstract

The basic differences between the 20 natural amino acid residues are due to differences in their side-chain structures. This characteristic design of protein building blocks implies that side-chain-side-chain interactions play an important, even dominant role in 3D-structural realization of amino acid codes. Here we present the results of a comparative analysis of the contributions of side-chain-side-chain (s-s) and side-chain-backbone (s-b) interactions to the stabilization of folded protein structures within the framework of the CHARMm molecular data model. Contrary to intuition, our results suggest that side-chain-backbone interactions play the major role in side-chain packing, in stabilizing the folded structures, and in differentiating the folded structures from the unfolded or misfolded structures, while the interactions between side chains have a secondary effect. An additional analysis of electrostatic energies suggests that combinatorial dominance of the interactions between opposite charges makes the electrostatic interactions act as an unspecific folding force that stabilizes not only native structure, but also compact random conformations. This observation is in agreement with experimental findings that, in the denatured state, the charge-charge interactions stabilize more compact conformations. Taking advantage of the dominant role of side-chain-backbone interactions in side-chain packing to reduce the combinatorial problem, we developed a new algorithm, ChiRotor, for rapid prediction of side-chain conformations. We present the results of a validation study of the method based on a set of high resolution X-ray structures.

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Year:  2007        PMID: 17242380      PMCID: PMC2203320          DOI: 10.1110/ps.062447107

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  28 in total

1.  Realistic modeling of the denatured states of proteins allows accurate calculations of the pH dependence of protein stability.

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2.  Free energy determinants of tertiary structure and the evaluation of protein models.

Authors:  D Petrey; B Honig
Journal:  Protein Sci       Date:  2000-11       Impact factor: 6.725

3.  Generalized dead-end elimination algorithms make large-scale protein side-chain structure prediction tractable: implications for protein design and structural genomics.

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Review 4.  Generalized born models of macromolecular solvation effects.

Authors:  D Bashford; D A Case
Journal:  Annu Rev Phys Chem       Date:  2000       Impact factor: 12.703

5.  Charge-charge interactions influence the denatured state ensemble and contribute to protein stability.

Authors:  C N Pace; R W Alston; K L Shaw
Journal:  Protein Sci       Date:  2000-07       Impact factor: 6.725

6.  Side-chain modeling with an optimized scoring function.

Authors:  Shide Liang; Nick V Grishin
Journal:  Protein Sci       Date:  2002-02       Impact factor: 6.725

7.  Extending the accuracy limits of prediction for side-chain conformations.

Authors:  Z Xiang; B Honig
Journal:  J Mol Biol       Date:  2001-08-10       Impact factor: 5.469

8.  PISCES: a protein sequence culling server.

Authors:  Guoli Wang; Roland L Dunbrack
Journal:  Bioinformatics       Date:  2003-08-12       Impact factor: 6.937

9.  GEM: a Gaussian Evolutionary Method for predicting protein side-chain conformations.

Authors:  Jinn-Moon Yang; Chi-Hung Tsai; Ming-Jing Hwang; Huai-Kuang Tsai; Jenn-Kang Hwang; Cheng-Yan Kao
Journal:  Protein Sci       Date:  2002-08       Impact factor: 6.725

10.  Backbone-dependent rotamer library for proteins. Application to side-chain prediction.

Authors:  R L Dunbrack; M Karplus
Journal:  J Mol Biol       Date:  1993-03-20       Impact factor: 5.469

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  34 in total

1.  Closing the side-chain gap in protein loop modeling.

Authors:  Karen A Rossi; Akbar Nayeem; Carolyn A Weigelt; Stanley R Krystek
Journal:  J Comput Aided Mol Des       Date:  2009-05-21       Impact factor: 3.686

2.  A fast and accurate computational approach to protein ionization.

Authors:  Velin Z Spassov; Lisa Yan
Journal:  Protein Sci       Date:  2008-08-19       Impact factor: 6.725

3.  Monoamine neurotransmitters as substrates for novel tick sulfotransferases, homology modeling, molecular docking, and enzyme kinetics.

Authors:  Emine Bihter Yalcin; Hubert Stangl; Sivakamasundari Pichu; Thomas N Mather; Roberta S King
Journal:  ACS Chem Biol       Date:  2010-11-15       Impact factor: 5.100

4.  OPUS-Rota: a fast and accurate method for side-chain modeling.

Authors:  Mingyang Lu; Athanasios D Dousis; Jianpeng Ma
Journal:  Protein Sci       Date:  2008-06-12       Impact factor: 6.725

5.  Glutaric Acidemia Type 1-Clinico-Molecular Profile and Novel Mutations in GCDH Gene in Indian Patients.

Authors:  Neerja Gupta; Pawan Kumar Singh; Manoj Kumar; Shivaram Shastri; Sheffali Gulati; Atin Kumar; Anuja Agarwala; Seema Kapoor; Mohandas Nair; Savita Sapra; Sudhisha Dubey; Ankur Singh; Punit Kaur; Madhulika Kabra
Journal:  JIMD Rep       Date:  2015-03-12

6.  Inhibitor resistance in the KPC-2 beta-lactamase, a preeminent property of this class A beta-lactamase.

Authors:  Krisztina M Papp-Wallace; Christopher R Bethel; Anne M Distler; Courtney Kasuboski; Magdalena Taracila; Robert A Bonomo
Journal:  Antimicrob Agents Chemother       Date:  2009-12-14       Impact factor: 5.191

7.  Enhancing resistance to cephalosporins in class C beta-lactamases: impact of Gly214Glu in CMY-2.

Authors:  Andrea Endimiani; Yohei Doi; Christopher R Bethel; Magdalena Taracila; Jennifer M Adams-Haduch; Alexandra O'Keefe; Andrea M Hujer; David L Paterson; Marion J Skalweit; Malcolm G P Page; Sarah M Drawz; Robert A Bonomo
Journal:  Biochemistry       Date:  2010-02-09       Impact factor: 3.162

Review 8.  Template-based protein modeling: recent methodological advances.

Authors:  Pankaj R Daga; Ronak Y Patel; Robert J Doerksen
Journal:  Curr Top Med Chem       Date:  2010       Impact factor: 3.295

9.  Peptide Solubility Limits: Backbone and Side-Chain Interactions.

Authors:  Rahul Sarma; Ka-Yiu Wong; Gillian C Lynch; B Montgomery Pettitt
Journal:  J Phys Chem B       Date:  2018-02-13       Impact factor: 2.991

10.  A report of rifampin-resistant leprosy from northern and eastern India: identification and in silico analysis of molecular interactions.

Authors:  Sundeep Chaitanya Vedithi; Mallika Lavania; Manoj Kumar; Punit Kaur; Ravindra P Turankar; Itu Singh; Astha Nigam; Utpal Sengupta
Journal:  Med Microbiol Immunol       Date:  2014-09-09       Impact factor: 3.402

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