Multivariate Secondary Structure Estimation (SSE) with High Throughput CD

By Leah Pandiscia, PhD

Introduction

High Throughput CD System for Automated Protein Secondary Structure Estimation

This application note evaluates the use of the J-1500 high throughput CD (HTCD) system for automated protein secondary structure estimation. Measurements reveal information regarding the secondary structure or backbone conformation of a protein. CD measurements can be used to determination the secondary structure content of a biomolecule to elucidate the relationship between structure and function or verify protein stability. The high throughput CD system with JASCO’s multivariate Secondary Structure Estimation (SSE) program can be used to quickly analyze CD data for routine quantitative research and quality control. A large number of samples can be automatically measured and efficiently analyzed using the High-Throughput CD (HTCD) system with Spectra Manager and multivariate SSE program.

The secondary structure of eight proteins are evaluated using the Multivariate SSE program.

High throughput Circular Dichroism System — J-1500 Circular Dichroism Spectrometer

Experimental

Measurement conditions
Data acquisition interval	0.1 nm	Response time	2 seconds
Spectral bandwidth	1 nm	Scan speed	100 nm/min
Accumulations	2 times	Path length	1 mm

Keywords

Protein secondary structure estimation, protein SSE, circular dichroism, high throughput circular dichrosim, high throughput CD, HTCD, Multivariate, Biochemistry, Pharmaceuticals, multiplate, 96 well plate

Results

Prior to obtaining the sequence measurement, the pathlength and mean residue molar concentrations have to be specified so that the optical constants can be automatically calculated for the secondary structure estimation (Figure 1).

Figure 1. Multivariate parameter setup specifying path length and mean residue molar concentration

CD measurements in the far-UV region were obtained for eight 0.1 mg/mL protein samples with varying secondary structure compositions and are shown in Figure 2.

The secondary structure estimated using PLS multivariate analysis of the protein spectra are shown in Figure 1 . Table 1 compares these results with X-ray crystallography data. Figure 3 shows the secondary structure results from the JWMVS program.

Table 1. Comparison of Multivariate SSE results with X-ray crystallography data

		Helix (%)	Sheet (%)	Turn (%)	Other (%)
Lysozyme (Lyz)	PLS	42.8	0.4	24.4	32.4
X-ray	41	4	19	35
Cytochrome C (CytC)	PLS	42.6	3.1	18.1	36.2
X-ray	42	8	9	42
Concanavalin A (ConA)	PLS	5.1	44.6	13.9	36.4
X-ray	2	36	12	49
β-Lactoglobulin	PLS	17.8	35.5	12.3	34.4
X-ray	13	34	13	41
Trypsin Inhibitor	PLS	13.9	25.3	17.3	43.5
X-ray	2	33	10	55
Ribonuclease A (RNaseA)	PLS	21.5	14.7	22.4	41.4
X-ray	22	19	11	48
Human Serum Albumin (HSA)	PLS	66.8	1.3	8.2	23.7
X-ray	72	0	8	20
Hemoglobin (Hb)	PLS	61.1	0	18	20.9
X-ray	75	0	10	15

¹ W. C. Johnson, Proteins: Structure, Function, and Genetics (1999), 35, 307-312.
² PDB: Trypsin inhibitor: 1ba7 (DSSP), HAS: 1bm0 (DSSP)

Figure 3. Results using the Multivariate SSE program

Conclusion

This application note illustrates the use of the Multivariate SSE program to estimate secondary structure following CD measurement. The PLS method shows good agreement with secondary structure results obtained by X-ray crystallography.

This document has been prepared based on information available at the time of publication and is subject to revision without notice. Although the contents are checked with the utmost care, we do not guarantee their accuracy or completeness. JASCO Corporation assumes no responsibility or liability for any loss or damage incurred as a result of the use of any information contained in this document. Copyright and other intellectual property rights in this document remain the property of JASCO Corporation. Please do not attempt to copy, modify, redistribute, or sell etc. in whole or in part without prior written permission.

About the Author

Leah Pandiscia received her PhD from Drexel University where she studied Biophysical Chemistry. She is a Spectroscopy Applications Scientist.

Introduction

High Throughput CD System for Automated Protein Secondary Structure Estimation

The secondary structure of eight proteins are evaluated using the Multivariate SSE program.

Experimental

Measurement conditions
Data acquisition interval	0.1 nm	Response time	2 seconds
Spectral bandwidth	1 nm	Scan speed	100 nm/min
Accumulations	2 times	Path length	1 mm

Keywords

Results

CD measurements in the far-UV region were obtained for eight 0.1 mg/mL protein samples with varying secondary structure compositions and are shown in Figure 2.

Table 1. Comparison of Multivariate SSE results with X-ray crystallography data

		Helix (%)	Sheet (%)	Turn (%)	Other (%)
Lysozyme (Lyz)	PLS	42.8	0.4	24.4	32.4
X-ray	41	4	19	35
Cytochrome C (CytC)	PLS	42.6	3.1	18.1	36.2
X-ray	42	8	9	42
Concanavalin A (ConA)	PLS	5.1	44.6	13.9	36.4
X-ray	2	36	12	49
β-Lactoglobulin	PLS	17.8	35.5	12.3	34.4
X-ray	13	34	13	41
Trypsin Inhibitor	PLS	13.9	25.3	17.3	43.5
X-ray	2	33	10	55
Ribonuclease A (RNaseA)	PLS	21.5	14.7	22.4	41.4
X-ray	22	19	11	48
Human Serum Albumin (HSA)	PLS	66.8	1.3	8.2	23.7
X-ray	72	0	8	20
Hemoglobin (Hb)	PLS	61.1	0	18	20.9
X-ray	75	0	10	15

¹ W. C. Johnson, Proteins: Structure, Function, and Genetics (1999), 35, 307-312.
² PDB: Trypsin inhibitor: 1ba7 (DSSP), HAS: 1bm0 (DSSP)

JASCO

Industry

Technique

Multivariate Secondary Structure Estimation (SSE) with High Throughput CD

Introduction

High Throughput CD System for Automated Protein Secondary Structure Estimation

Experimental

Keywords

Results

Conclusion

About the Author

Designed in Tokyo. TRUSTED globally.

Industry

Technique

Introduction

High Throughput CD System for Automated Protein Secondary Structure Estimation

Experimental

Keywords

Results

Conclusion

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J-1500

Automated HTCD

About the Author