단백질 3차 구조를 구성하는 아미노산의 구조적 성질들의

분자 수준 해석과 통계적 해석

백승필, 최유성, 민경선, 유영제

서울대학교 응용화학부 효소 및 환경 생물공학 연구실

Molecular Calculation and Statistical Analysis of Amino Acid Conformational Properties

in the Three-Dimensional Protein Structure

Pack, Seung Pil, Choi, Yoo Seong, Min, Kyoung Sun, Yoo, Young Je,

Enzyme and Environmental Biotechnology Lab.,

Theories and Applications of Chem. Eng., 2002, Vol. 8, No. 1

화학공학의 이론과 응용 제8권 제1호 2002년

Theories and Applications of Chem. Eng., 2002, Vol. 8, No. 1

화학공학의 이론과 응용 제8권 제1호 2002년

School of Chemical Engineering, Seoul National University

Introduction

One of the major goals of structural biology is to elucidate the relationship between the three-dimensional structure, and various functions of proteins 1. If this relationship were known well, then the function of a protein could be reliably predicted, and enhanced or re-designed, in order to satisfy the practical end of human beings, as well academic interests2. Unfortunately, the relationship between function and structure is not that simple, since biophysical or biochemical phenomena resulting from three-dimensional protein structures is so complex. Recently, there has been much progress in computational biology, so called bioinformatics3. Many database algorithms and systems can help us analyze much biological information for understanding the relationships, and interactions, among biological molecules4. Especially, PDB5, SCOP, CATH, DALI, 3Dee, HOMSTRAD, and ENTREZ are famous, and feasible, database systems for analysis of protein structures. Using such database systems, various and complex, biophysical or biochemical properties of three-dimensional protein structures can be considered.

Amino acids, known as the building blocks, and components, of proteins, each have different characteristic in terms of their shape, volume, and chemical reactivity. The variety and specificity of protein three-dimensional structures, and biological functions, are due to a combination of 20 different amino acids. Thus, much experimental and theoretical research has been performed in order to investigate the biophysical and biochemical properties of them6. Research on the conformational properties of amino acids, in three-dimensional protein structures, are necessary for basic studies on the analysis of protein structures. However, it has been very difficult to obtain a representative pattern describing all the conformational properties of amino acids in three-dimensional proteins since experiments, or theories, considering one or two residual biophysical or biochemical properties, are insufficient for elucidating the complex biological relationships.

In this study, bioinformatical methods such as, computational calculation, and statistical analysis, were used for investigating the residual conformational properties of amino acid based on three-dimensional protein structures. 100 monomeric protein structures with less than 25% identity were considered as model systems, for the purpose of considering the whole protein structures. 13 kinds of residual conformational properties, including; exposure ratio, packing value, surface area, solvation free energy, residual energy, flexibility, secondary structure, stabilizing bonds and interactions, were calculated for each protein. These residual properties were statistically analyzed, and patterned, according to their amino acid types. Through hierarchical cluster analysis, based on several residual conformational properties, a relationship pattern for 20 amino acids was obtained in the view of the protein structure components.

Material and Methods

Protein model system

The monomeric protein structures were obtained from the Protein Data Bank (PDB) at the Research Collaboratory for Structural Bioinformatics (RCSB)5, based on the September-2001 release of the representative list found at the PDB Select site7. The model set contains structures determined at a resolution of 0-2.0 □ and R-factor <= 0.2 ; the maximum sequence identity between any two proteins is <= 25%; the protein size is 50-450 amino acids. The list was also culled to remove ASX or GLX amino acid residues, or other non-standard amino acid residues.

Computational calculation

Surface area, the ratio of side chain area to □random coil□ value, and the determination of exposed/buried residue were calculated by the Getarea 1.1 program, a web service provided by the Sealy Center for Structural Biology at University of Texas Medical Branch8. Solvation free energy, residual energy and a-carbon flexibility, were calculated by the Protable module of Biopolymer, on SYBYL. The number of hydrogen bonds, and neighboring amino acids, and the determination of secondary structure were also calculated by Protable module of Biopolymer, on SYBYL. The packing value for each residue is calculated by an extension of the occluded surface algorithm. The number of ion pairs (salt bridge interaction), the number of cation-pi interactions and the number of disulfide bonds are calculated by the Protein Explorer package 1.9 provided by Department of Microbiology, University of Massachusetts Amherst.

Statistical calculation

A frequency distribution histogram was used for the statistical analysis of each property, according to amino acid type. The calculated values of surface area, flexibility, solvation free energy, and residual energy were compared and re-arranged over the relative range. Then, according to amino acid type, the frequency of the same range were counted and summed over all the proteins investigated.

For the purpose of clustering amino acids in terms of conformational property, a hierarchical cluster analysis was conducted to arrange a set of classes into clusters. For estimation of dissimilarities between the clusters, the Square Euclidean Distance (SE_D) method was used and described as follows.

The WARD method9, one of the division methods for clustering, was applied in this study for making linkages and clusters among the amino acids.

Result and Discussion

In order to investigate the conformational properties, and relation pattern of amino acids, as basic data for analysis of bio-functional protein, 13 kinds of residual conformational properties were calculated using bioinformatical methods. 100 monomeric representative proteins were prepared, and considered, for overcoming a variety of protein structure, and obtaining information that is more general. Then, 13 residual conformational properties of 18,358 residues were statistically analyzed, and patterned, according to amino acid types, over all the proteins of the model system (Figure 1.) Several properties, such as exposure ratio, packing value, solvation free energy and stabilizing interactions showed interesting trends, and the possibility to serve as critical criteria in further research, for example, research on, site-specific immobilization, compact or uncompact part of a proteins, and stabilizing factors.

Figure 1. Residual distribution of exposure ratio (Ratio), packing value (Pack), surface area (S_area), flexibility (Flex), solvation free energy (S_FE), and residual energy (Re_E) according to amino acid

For arranging such residual conformational properties, hierarchical cluster analyses were performed, and the dendrogram obtained showed a relation pattern among the 20 amino acids (Figure 2.). Such cluster patterns can make it easier to find the similarities or dissimilarities of the conformational properties among amino acids in protein structures.

Figure 2. Dendrogram using Ward method for hierarchical cluster analysis of amino acids after considering the residual conformational properties.

In this study, various residual conformational properties were computationally calculated and statistically analyzed. The relation patterns among 20 amino acids were obtained, and their residual conformational properties considered. Such residual conformational results are expected to serve as basic data for analysis of local protein structures, and furthermore, for research on the relation between protein structures and functions.

References

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