Estimation of the number of α‐helical and β‐strand segments in proteins using circular dichroism spectroscopy

Protein Science - Tập 8 Số 2 - Trang 370-380 - 1999
Narasimha Sreerama1, S.Yu. Venyaminov2, Robert W. Woody3
1Department of Biochemistry and Molecular Biology, Colorado State University, Fort Collins 80523, USA.
2Department of Pharmacology, Mayo Foundation, Rochester, Minnesota, 55905
3Department of Biochemistry and Molecular Biology, Colorado State University, Fort Collins, Colorado 80523

Tóm tắt

AbstractA simple approach to estimate the number of α‐helical and β‐strand segments from protein circular dichroism spectra is described. The α‐helix and β‐sheet conformations in globular protein structures, assigned by DSSP and STRIDE algorithms, were divided into regular and distorted fractions by considering a certain number of terminal residues in a given α‐helix or β‐strand segment to be distorted. The resulting secondary structure fractions for 29 reference proteins were used in the analyses of circular dichroism spectra by the SELCON method. From the performance indices of the analyses, we determined that, on an average, four residues per α‐helix and two residues per β‐strand may be considered distorted in proteins. The number of α‐helical and β‐strand segments and their average length in a given protein were estimated from the fraction of distorted α‐helix and β‐strand conformations determined from the analysis of circular dichroism spectra. The statistical test for the reference protein set shows the high reliability of such a classification of protein secondary structure. The method was used to analyze the circular dichroism spectra of four additional proteins and the predicted structural characteristics agree with the crystal structure data.

Từ khóa


Tài liệu tham khảo

10.1016/S0022-2836(77)80200-3

10.1093/protein/5.3.191

Bolotina IA, 1980, Determination of the secondary structure of proteins from the circular dichroism spectra. 1. Protein reference spectra for α‐, β‐and irregular structures, Mol Biol (Eng Transl Mol Biol), 14, 701

10.1016/0022-2836(80)90282-X

10.1016/0003-9861(92)90143-K

10.1016/S0006-291X(71)80225-5

10.1021/bi00713a027

10.1016/0003-2697(86)90241-1

10.1016/S0969-2126(97)00200-1

Forsythe GE, 1977, Computer methods for mathematical computations.

10.1002/prot.340230412

10.1016/0022-2836(78)90297-8

10.1006/abio.1996.0084

10.1021/bi00838a031

10.1021/bi00508a007

Jones G., 1998, Current state‐of‐the art and future possibilities for synchrotron radiation circular dichroism (SRCD), 5

10.1002/bip.360221211

10.1002/bip.360301311

10.1016/0022-2836(77)90207-8

10.1016/0003-2697(87)90135-7

10.1016/0731-7085(89)80049-4

10.1039/fd9949900287

10.1021/bi961178u

10.1021/bi00234a036

10.1073/pnas.37.4.205

10.1093/protein/4.6.669

10.1021/bi00504a006

Shubin VV, 1990, Prediction of protein secondary structure of globular proteins using circular dichroism spectra, Mol Biol (Eng Transl Mol Biol), 24, 165

10.1002/prot.340060105

10.1006/abio.1993.1079

10.1021/bi00199a028

Sreerama N, 1994, Protein secondary structure from circular dichroism spectroscopy. Combining variable selection principle and cluster analysis with neural network, ridge regression and self‐consistent methods, J Mol Biol, 242, 497, 10.1016/S0022-2836(84)71597-X

10.1016/0003-2697(90)90396-Q

10.1016/0003-2697(91)90421-O

Venyaminov SY, 1996, Circular dichroism and the conformational analysis of biomolecules., 69, 10.1007/978-1-4757-2508-7_3

10.1016/S0022-2836(83)80285-X

10.1093/protein/3.6.479