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Dive into the research topics where Alexey G. Murzin is active.

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Featured researches published by Alexey G. Murzin.


Journal of Molecular Biology | 1995

SCOP : A structural classification of proteins database for the investigation of sequences and structures

Alexey G. Murzin; Steven E. Brenner; Tim Hubbard; Cyrus Chothia

To facilitate understanding of, and access to, the information available for protein structures, we have constructed the Structural Classification of Proteins (scop) database. This database provides a detailed and comprehensive description of the structural and evolutionary relationships of the proteins of known structure. It also provides for each entry links to co-ordinates, images of the structure, interactive viewers, sequence data and literature references. Two search facilities are available. The homology search permits users to enter a sequence and obtain a list of any structures to which it has significant levels of sequence similarity. The key word search finds, for a word entered by the user, matches from both the text of the scop database and the headers of Brookhaven Protein Databank structure files. The database is freely accessible on World Wide Web (WWW) with an entry point to URL http: parallel scop.mrc-lmb.cam.ac.uk magnitude of scop.


Nucleic Acids Research | 1997

SCOP: a Structural Classification of Proteins database

Tim Hubbard; Bart Ailey; Steven E. Brenner; Alexey G. Murzin; Cyrus Chothia

The Structural Classification of Proteins (SCOP) database provides a detailed and comprehensive description of the relationships of all known proteins structures. The classification is on hierarchical levels: the first two levels, family and superfamily, describe near and far evolutionary relationships; the third, fold, describes geometrical relationships. The distinction between evolutionary relationships and those that arise from the physics and chemistry of proteins is a feature that is unique to this database, so far. SCOP also provides for each structure links to atomic co-ordinates, images of the structures, interactive viewers, sequence data, data on any conformational changes related to function and literature references. The database is freely accessible on the World Wide Web (WWW) with an entry point at URL http://scop.mrc-lmb.cam.ac.uk/scop/


Nucleic Acids Research | 2007

Data growth and its impact on the SCOP database: new developments

Antonina Andreeva; Dave Howorth; John-Marc Chandonia; Steven E. Brenner; Tim Hubbard; Cyrus Chothia; Alexey G. Murzin

The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. The SCOP hierarchy comprises the following levels: Species, Protein, Family, Superfamily, Fold and Class. While keeping the original classification scheme intact, we have changed the production of SCOP in order to cope with a rapid growth of new structural data and to facilitate the discovery of new protein relationships. We describe ongoing developments and new features implemented in SCOP. A new update protocol supports batch classification of new protein structures by their detected relationships at Family and Superfamily levels in contrast to our previous sequential handling of new structural data by release date. We introduce pre-SCOP, a preview of the SCOP developmental version that enables earlier access to the information on new relationships. We also discuss the impact of worldwide Structural Genomics initiatives, which are producing new protein structures at an increasing rate, on the rates of discovery and growth of protein families and superfamilies. SCOP can be accessed at http://scop.mrc-lmb.cam.ac.uk/scop.


Nature | 2002

Structure of the HP1 chromodomain bound to histone H3 methylated at lysine 9

Peter R. Nielsen; Daniel Nietlispach; Helen R. Mott; Juliana Callaghan; Andrew J. Bannister; Tony Kouzarides; Alexey G. Murzin; Natalia V. Murzina; Ernest D. Laue

Specific modifications to histones are essential epigenetic markers—heritable changes in gene expression that do not affect the DNA sequence. Methylation of lysine 9 in histone H3 is recognized by heterochromatin protein 1 (HP1), which directs the binding of other proteins to control chromatin structure and gene expression. Here we show that HP1 uses an induced-fit mechanism for recognition of this modification, as revealed by the structure of its chromodomain bound to a histone H3 peptide dimethylated at Nζ of lysine 9. The binding pocket for the N-methyl groups is provided by three aromatic side chains, Tyr 21, Trp 42 and Phe 45, which reside in two regions that become ordered on binding of the peptide. The side chain of Lys 9 is almost fully extended and surrounded by residues that are conserved in many other chromodomains. The QTAR peptide sequence preceding Lys 9 makes most of the additional interactions with the chromodomain, with HP1 residues Val 23, Leu 40, Trp 42, Leu 58 and Cys 60 appearing to be a major determinant of specificity by binding the key buried Ala 7. These findings predict which other chromodomains will bind methylated proteins and suggest a motif that they recognize.


Nucleic Acids Research | 2002

SCOP database in 2002: refinements accommodate structural genomics.

Loredana Lo Conte; Steven E. Brenner; Tim Hubbard; Cyrus Chothia; Alexey G. Murzin

The SCOP (Structural Classification of Proteins) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. Protein domains in SCOP are grouped into species and hierarchically classified into families, superfamilies, folds and classes. Recently, we introduced a new set of features with the aim of standardizing access to the database, and providing a solid basis to manage the increasing number of experimental structures expected from structural genomics projects. These features include: a new set of identifiers, which uniquely identify each entry in the hierarchy; a compact representation of protein domain classification; a new set of parseable files, which fully describe all domains in SCOP and the hierarchy itself. These new features are reflected in the ASTRAL compendium. The SCOP search engine has also been updated, and a set of links to external resources added at the level of domain entries. SCOP can be accessed at http://scop.mrc-lmb.cam.ac.uk/scop.


Cell | 1997

The solution structure of the S1 RNA binding domain: a member of an ancient nucleic acid-binding fold.

Mark Bycroft; Tim Hubbard; Mark R. Proctor; Stefan M. V. Freund; Alexey G. Murzin

The S1 domain, originally identified in ribosomal protein S1, is found in a large number of RNA-associated proteins. The structure of the S1 RNA-binding domain from the E. coli polynucleotide phosphorylase has been determined using NMR methods and consists of a five-stranded antiparallel beta barrel. Conserved residues on one face of the barrel and adjacent loops form the putative RNA-binding site. The structure of the S1 domain is very similar to that of cold shock protein, suggesting that they are both derived from an ancient nucleic acid-binding protein. Enhanced sequence searches reveal hitherto unidentified S1 domains in RNase E, RNase II, NusA, EMB-5, and other proteins.


Journal of Molecular Biology | 1992

β-Trefoil fold: Patterns of structure and sequence in the Kunitz inhibitors interleukins-1β and 1α and fibroblast growth factors

Alexey G. Murzin; Arthur M. Lesk; Cyrus Chothia

Abstract Previous crystallographic analyses of the Kunitz inhibitors from soybean, Erythrina caffra and wheat, the interleukins-1β and 1α and the acidic and basic fibroblast growth factors have shown that they contain a most unusual fold. It is formed by six two-stranded hairpins. Three of these form a barrel structure and the other three are in a triangular array that caps the barrel. The arrangement of the secondary structures gives the molecules a pseudo 3-fold axis. Although the different proteins have very similar structures, many of their sequences have no significant similarities overall. The structural determinants of this fold are described and discussed in this paper. The barrels in the different proteins have the same geometrical features: six strands tilted at 56 ° to the barrel axis; a barrel diameter of 16 A, and the β-sheet hydrogen bonded so that it is staggered with a shear number of 12. These features fit McLachlans equations for ideal barrels formed by β-sheets. The wide diameter of the barrels is filled by layers of residues that, while not identical in the different proteins, are, in almost all cases, large. The structure of the triangular array of hairpins is determined by the coiling of the strands and the packing of hairpin residues against each other and against residues from the interior of the barrel. The major sequence requirements of this fold are large or medium hydrophobic resiudes at 18 buried sites. In the different structures the total volume of these residues is 3000(±120) A 3 . The polyhedron model of protein architecture is used to demonstrate that the main, and in particular the symmetrical, features of this fold arise from the ideal and equal packing of six hairpins, modified only slightly to form hydrogen bonds between the hairpins.


Current Opinion in Structural Biology | 1998

HOW FAR DIVERGENT EVOLUTION GOES IN PROTEINS

Alexey G. Murzin

In theory, mutations of protein sequences may eventually generate different functions as well as different structures. The observation of such records of protein evolution have been obscured by the dissipation of memory about the ancestors. In the past year, new advances in our understanding of divergent evolution were allowed by new protein structure determinations, including the ClpP proteases, steroid delta-isomerase, carboxypeptidase G2, the thrombin inhibitor triabin and the chloroplast Rieske protein. There is strong evidence for their distant homology with proteins of known structure despite significant functional or structural differences.


The EMBO Journal | 1995

NMR solution structure of a dsRNA binding domain from Drosophila staufen protein reveals homology to the N-terminal domain of ribosomal protein S5.

Mark Bycroft; Stefan Grünert; Alexey G. Murzin; Mark R. Proctor; D St Johnston

The double‐stranded RNA binding domain (dsRBD) is an approximately 65 amino acid motif that is found in a variety of proteins that interact with double‐stranded (ds) RNA, such as Escherichia coli RNase III and the dsRNA‐dependent kinase, PKR. Drosophila staufen protein contains five copies of this motif, and the third of these binds dsRNA in vitro. Using multinuclear/multidimensional NMR methods, we have determined that staufen dsRBD3 forms a compact protein domain with an alpha‐beta‐beta‐beta‐alpha structure in which the two alpha‐helices lie on one face of a three‐stranded anti‐parallel beta‐sheet. This structure is very similar to that of the N‐terminal domain of a prokaryotic ribosomal protein S5. Furthermore, the consensus derived from all known S5p family sequences shares several conserved residues with the dsRBD consensus sequence, indicating that the two domains share a common evolutionary origin. Using in vitro mutagenesis, we have identified several surface residues which are important for the RNA binding of the dsRBD, and these all lie on the same side of the domain. Two residues that are essential for RNA binding, F32 and K50, are also conserved in the S5 protein family, suggesting that the two domains interact with RNA in a similar way.


Current Opinion in Structural Biology | 1996

Structural classification of proteins: new superfamilies

Alexey G. Murzin

The structural classification of proteins reveals that it is already more likely to find that a new protein structure has similarity to another structure than to find that it has a new fold. Reviewed here are those new superfamilies that include proteins of general interest: Sonic hedgehog, macrophage migration inhibitory factor, nuclear transport factor-2, double stranded RNA binding domain, GroES, the proteasome, new ATP-hydrolyzing ligases and flavoproteins.

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Cyrus Chothia

Laboratory of Molecular Biology

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Antonina Andreeva

Laboratory of Molecular Biology

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Alex Bateman

European Bioinformatics Institute

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Benjamin Falcon

Laboratory of Molecular Biology

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Michel Goedert

Laboratory of Molecular Biology

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Sjors H.W. Scheres

Laboratory of Molecular Biology

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