Similarities of protein topologies: evolutionary divergence, functional convergence or principles of folding?

1980 ◽  
Vol 13 (3) ◽  
pp. 339-386 ◽  
Author(s):  
O. B. Ptitsyn ◽  
A. V. Finkelstein
Keyword(s):  
Serine Proteases ◽  
Protein Structures ◽  
Three Dimensional ◽  
Sperm Whale ◽  
Globular Protein ◽  
Dimensional Structure ◽  
Evolutionary Divergence ◽  
Functional Convergence ◽  
Primary Structures ◽  
Sperm Whale Myoglobin

(A) Evolutionary similarities of protein structures Two decades have passed from the time that the three dimensional structure of the first globular protein, sperm whale myoglobin, was decoded (Kendrew et al. 1960). Its structure, which now looks so simple and habitual, then seemed to be unusually complicated. The decoding of the subsequent proteins, lysozyme (Blake et al. 1965), ribonuclease (Kartha, Bello & Harker, 1967), chymotrypsin (Matthews et al. 1967), carboxypeptidase (Lipscomb et al. 1969) redoubled the feeling of amazement and even of some confusion before the extremely complicated, intricate and, above all, absolutely unlike protein structures. Some consolation against this background was the evident and far-reaching similarity between the three-dimensional structures of myoglobin and hemoglobin subunits (Perutz, Kendrew & Watson, 1965) and an analogous similarity between the structures of chymotrypsin and other serine proteases, elastase (Shotton & Watson, 1970) and trypsin (Stroud, Kay & Dickerson, 1972). However this similarity was easily explained by the far-reaching homology between the primary structures of myoglobin and hemoglobin and between the primary structures of serine proteases.

The amino acid sequence of human myoglobin and its minor fractions

1974 ◽  
Vol 186 (1084) ◽  
pp. 249-279 ◽  
Keyword(s):  
Amino Acid ◽  
Amino Acid Sequence ◽  
Three Dimensional ◽  
Sperm Whale ◽  
Dimensional Structure ◽  
Human Haemoglobin ◽  
Human Myoglobin ◽  
Main Component ◽  
Haemoglobin Molecule ◽  
Sperm Whale Myoglobin

The complete amino acid sequence of human skeletal myoglobin is described. That of heart myoglobin is found by homology to be the same. When myoglobin is prepared some minor fractions may be obtained besides the main component. They are shown to be artefacts arising from deamidations. The likely three-dimensional structure of human myoglobin is discussed, taking that of sperm-whale myoglobin as a reference. Human myoglobin is compared with the α - and β -chains of human haemoglobin. There is a noteworthy similarity of internal residues and haem contacts, but little resemblance of sites where the haemoglobin chains form dimeric and tetrameric contacts, when they become subunits of the haemoglobin molecule.

The crystal structure of myoglobin. VI. Seal myoglobin

1960 ◽  
Vol 258 (1293) ◽  
pp. 181-201 ◽  
Keyword(s):  
Tertiary Structure ◽  
Heavy Atom ◽  
Three Dimensional ◽  
Sperm Whale ◽  
Fourier Synthesis ◽  
Heavy Atoms ◽  
Isomorphous Replacement ◽  
Unit Cells ◽  
The Common ◽  
Sperm Whale Myoglobin

Myoglobin from the common seal ( Phoca vitulina ) when crystallized from ammonium sulphate forms monoclinic crystals with space group the unit cell, a = 57·9Å, b = 29·6Å, c = 106·4Å, β = 102°15', contains four molecules. The method of isomorphous replacement has been used in an investigation of the centrosymmetric b -axis projection in which it has been possible to determine signs for nearly all the h0l reflexions having spacings greater than 4Å. Three independent heavy-atom derivatives were employed and the signs so determined have been used to compute a map of the electron density projected on the (010) plane. This projection has been interpreted in terms of the molecule of sperm-whale myoglobin, as deduced by Bodo, Dintzis, Kendrew & Wyckoff (1959) from a three-dimensional Fourier synthesis to 6Å resolution. The results of the interpretation show that the two myoglobin molecules are very similar in form (tertiary structure) in spite of the differences in their amino-acid composition. The relative orientation of the two unit cells with respect to the myoglobin molecule is given and a comparison is made of the positions of the heavy atoms in each molecule.

The structure of haemoglobin. IX. A three-dimensional Fourier synthesis at 5.5 Å resolution: description of the structure

1962 ◽  
Vol 265 (1321) ◽  
pp. 161-187 ◽  
Keyword(s):  
Tertiary Structure ◽  
Three Dimensional ◽  
Sperm Whale ◽  
Anomalous Scattering ◽  
Fourier Synthesis ◽  
Human Haemoglobin ◽  
Contour Maps ◽  
To Come ◽  
Polypeptide Chains ◽  
Sperm Whale Myoglobin

The electron density distribution in the unit cell is calculated at intervals of approximately 2Å and plotted in a series of sections parallel to (010). The contour maps show that haemoglobin consists of four subunits in a tetrahedral array. The subunits are identical in pairs in accordance with the twofold symmetry of the molecule. The two pairs are very similar in structure, and the members of each pair closely resemble the molecule of sperm-whale myoglobin. The four haem groups lie in separate pockets at the surface of the molecule. The positions of the iron atoms are confirmed by comparison of observed and calculated anomalous scattering effects, which also serve to determine the absolute configuration of the molecule. The four subunits found by X-ray analysis correspond to the four polypeptide chains into which haemoglobin can be divided by chemical methods. In horse haemoglobin the amino acid sequence within these chains is still partly unknown, but in human haemoglobin it has already been determined. Comparison of this sequence with the tertiary structure of the chains as now revealed in horse haemoglobin and with the atomic model of sperm-whale myoglobin recently obtained by Kendrew and his collaborators shows many interesting relations. Prolines appear to come where the chains turn corners or where their configuration is known to be non-helical. On the other hand, the chains also have corners which contain no proline. Certain residues appear to be structurally vital, because they appear in identical positions in myoglobin and in the two chains of haemoglobin, while in other parts of the molecule a wide variety of different side-chains appears to be allowed.

scholarly journals Solvent Accessibility of Residues Undergoing Pathogenic Variations in Humans: From Protein Structures to Protein Sequences

2021 ◽  
Vol 7 ◽  
Author(s):  
Castrense Savojardo ◽  
Matteo Manfredi ◽  
Pier Luigi Martelli ◽  
Rita Casadio
Keyword(s):  
Solvent Accessibility ◽  
Protein Structures ◽  
Three Dimensional ◽  
Protein Sequences ◽  
Large Data ◽  
Human Protein ◽  
Dimensional Structure ◽  
Wild Type ◽  
Solvent Exposure ◽  
Data Set

Solvent accessibility (SASA) is a key feature of proteins for determining their folding and stability. SASA is computed from protein structures with different algorithms, and from protein sequences with machine-learning based approaches trained on solved structures. Here we ask the question as to which extent solvent exposure of residues can be associated to the pathogenicity of the variation. By this, SASA of the wild-type residue acquires a role in the context of functional annotation of protein single-residue variations (SRVs). By mapping variations on a curated database of human protein structures, we found that residues targeted by disease related SRVs are less accessible to solvent than residues involved in polymorphisms. The disease association is not evenly distributed among the different residue types: SRVs targeting glycine, tryptophan, tyrosine, and cysteine are more frequently disease associated than others. For all residues, the proportion of disease related SRVs largely increases when the wild-type residue is buried and decreases when it is exposed. The extent of the increase depends on the residue type. With the aid of an in house developed predictor, based on a deep learning procedure and performing at the state-of-the-art, we are able to confirm the above tendency by analyzing a large data set of residues subjected to variations and occurring in some 12,494 human protein sequences still lacking three-dimensional structure (derived from HUMSAVAR). Our data support the notion that surface accessible area is a distinguished property of residues that undergo variation and that pathogenicity is more frequently associated to the buried property than to the exposed one.

Prediction of Structural and Functional Aspects of Protein

2014 ◽  
pp. 317-333
Author(s):  
Arun G. Ingale
Keyword(s):  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Sequence Information ◽  
Predict Protein Structure ◽  
Basic Ideas

To predict the structure of protein from a primary amino acid sequence is computationally difficult. An investigation of the methods and algorithms used to predict protein structure and a thorough knowledge of the function and structure of proteins are critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this chapter sheds light on the methods used for protein structure prediction. This chapter covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, it presents an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction, giving unique insight into the future applications of the modeled protein structures. In this chapter, current protein structure prediction methods are reviewed for a milieu on structure prediction, the prediction of structural fundamentals, tertiary structure prediction, and functional imminent. The basic ideas and advances of these directions are discussed in detail.

PREDICTION OF THE THREE-DIMENSIONAL STRUCTURE OF THE ENZYMATIC PART OF T-PA

1987 ◽  
Author(s):  
A Heckel ◽  
K M Hasselbach
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Active Site ◽  
Serine Proteases ◽  
Three Dimensional ◽  
Amino Acid Sequences ◽  
Dimensional Structure ◽  
Salt Bridges ◽  
Three Dimensional Structure ◽  
Insertions And Deletions

Up to now the three-dimensional structure of t-PA or parts of this enzyme is unknown. Using computer graphical methods the spatial structure of the enzymatic part of t-PA is predicted on the hypothesis, the three-dimensional backbone structure of t-PA being similar to that of other serine proteases. The t-PA model was built up in three steps:1) Alignment of the t-PA sequence with other serine proteases. Comparison of enzyme structures available from Brookhaven Protein Data Bank proved elastase as a basis for modeling.2) Exchange of amino acids of elastase differing from the t-PA sequence. The replacement of amino acids was performed such that backbone atoms overlapp completely and side chains superpose as far as possible.3) Modeling of insertions and deletions. To determine the spatial arrangement of insertions and deletions parts of related enzymes such as chymotrypsin or trypsin were used whenever possible. Otherwise additional amino acid sequences were folded to a B-turn at the surface of the proteine, where all insertions or deletions are located. Finally the side chain torsion angles of amino acids were optimised to prevent close contacts of neigh bouring atoms and to improve hydrogen bonds and salt bridges.The resulting model was used to explain binding of arginine 560 of plasminogen to the active site of t-PA. Arginine 560 interacts with Asp 189, Gly 19 3, Ser 19 5 and Ser 214 of t-PA (chymotrypsin numbering). Furthermore interaction of chromo-genic substrate S 2288 with the active site of t-PA was studied. The need for D-configuration of the hydrophobic amino acid at the N-terminus of this tripeptide derivative could be easily explained.

MRPC (Missing Regions in Polypeptide Chains): a knowledgebase

2019 ◽  
Vol 52 (6) ◽  
pp. 1422-1426
Author(s):  
Rajendran Santhosh ◽  
Namrata Bankoti ◽  
Adgonda Malgonnavar Padmashri ◽  
Daliah Michael ◽  
Jeyaraman Jeyakanthan ◽  
...  
Keyword(s):  
Protein Structures ◽  
Three Dimensional ◽  
Protein Molecule ◽  
Data Bank ◽  
Protein Crystal ◽  
Dimensional Structure ◽  
Protein Structure Analysis ◽  
Three Dimensional Structure ◽  
X Ray Crystallography ◽  
Polypeptide Chains

Missing regions in protein crystal structures are those regions that cannot be resolved, mainly owing to poor electron density (if the three-dimensional structure was solved using X-ray crystallography). These missing regions are known to have high B factors and could represent loops with a possibility of being part of an active site of the protein molecule. Thus, they are likely to provide valuable information and play a crucial role in the design of inhibitors and drugs and in protein structure analysis. In view of this, an online database, Missing Regions in Polypeptide Chains (MRPC), has been developed which provides information about the missing regions in protein structures available in the Protein Data Bank. In addition, the new database has an option for users to obtain the above data for non-homologous protein structures (25 and 90%). A user-friendly graphical interface with various options has been incorporated, with a provision to view the three-dimensional structure of the protein along with the missing regions using JSmol. The MRPC database is updated regularly (currently once every three months) and can be accessed freely at the URL http://cluster.physics.iisc.ac.in/mrpc.

scholarly journals Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics

2018 ◽  
Vol 19 (11) ◽  
pp. 3401 ◽  
Author(s):  
Ashutosh Srivastava ◽  
Tetsuro Nagai ◽  
Arpita Srivastava ◽  
Osamu Miyashita ◽  
Florence Tama
Keyword(s):  
Protein Dynamics ◽  
Computational Methods ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
X Ray ◽  
X Ray Crystallography ◽  
Insight Into

Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.

scholarly journals Prediction and Analysis of Surface Hydrophobic Residues in Tertiary Structure of Proteins

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Shambhu Malleshappa Gowder ◽  
Jhinuk Chatterjee ◽  
Tanusree Chaudhuri ◽  
Kusum Paul
Keyword(s):  
Tertiary Structure ◽  
Structural Information ◽  
Solvent Accessibility ◽  
Conservation Score ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Data Set ◽  
Hydrophobic Residues ◽  
Monomeric Proteins

The analysis of protein structures provides plenty of information about the factors governing the folding and stability of proteins, the preferred amino acids in the protein environment, the location of the residues in the interior/surface of a protein and so forth. In general, hydrophobic residues such as Val, Leu, Ile, Phe, and Met tend to be buried in the interior and polar side chains exposed to solvent. The present work depends on sequence as well as structural information of the protein and aims to understand nature of hydrophobic residues on the protein surfaces. It is based on the nonredundant data set of 218 monomeric proteins. Solvent accessibility of each protein was determined using NACCESS software and then obtained the homologous sequences to understand how well solvent exposed and buried hydrophobic residues are evolutionarily conserved and assigned the confidence scores to hydrophobic residues to be buried or solvent exposed based on the information obtained from conservation score and knowledge of flanking regions of hydrophobic residues. In the absence of a three-dimensional structure, the ability to predict surface accessibility of hydrophobic residues directly from the sequence is of great help in choosing the sites of chemical modification or specific mutations and in the studies of protein stability and molecular interactions.

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