FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2127221680> ?p ?o ?g. }

• W2127221680 endingPage "1223" @default.
• W2127221680 startingPage "1212" @default.
• W2127221680 abstract "It is generally accepted that the functional activity of biological macromolecules requires tightly packed three-dimensional structures. Recent theoretical and experimental evidence indicates, however, the importance of molecular flexibility for the proper functioning of some proteins. We examined high resolution structures of proteins in various functional categories with respect to the secondary structure assessment. The latter was considered as a characteristic of the inherent flexibility of a polypeptide chain. We found that the proteins in functionally competent conformational states might be comprised of 20–70% flexible residues. For instance, proteins involved in gene regulation, e.g. transcription factors, are on average largely disordered molecules with over 60% of amino acids residing in “coiled” configurations. In contrast, oxygen transporters constitute a class of relatively rigid molecules with only 30% of residues being locally flexible. Phylogenic comparison of a large number of protein families with respect to the propagation of secondary structure illuminates the growing role of the local flexibility in organisms of greater complexity. Furthermore the local flexibility in protein molecules appears to be dependent on the molecular confinement and is essentially larger in extracellular proteins. It is generally accepted that the functional activity of biological macromolecules requires tightly packed three-dimensional structures. Recent theoretical and experimental evidence indicates, however, the importance of molecular flexibility for the proper functioning of some proteins. We examined high resolution structures of proteins in various functional categories with respect to the secondary structure assessment. The latter was considered as a characteristic of the inherent flexibility of a polypeptide chain. We found that the proteins in functionally competent conformational states might be comprised of 20–70% flexible residues. For instance, proteins involved in gene regulation, e.g. transcription factors, are on average largely disordered molecules with over 60% of amino acids residing in “coiled” configurations. In contrast, oxygen transporters constitute a class of relatively rigid molecules with only 30% of residues being locally flexible. Phylogenic comparison of a large number of protein families with respect to the propagation of secondary structure illuminates the growing role of the local flexibility in organisms of greater complexity. Furthermore the local flexibility in protein molecules appears to be dependent on the molecular confinement and is essentially larger in extracellular proteins. Over the last 2 decades, the extent of structural research has led to a large number of three-dimensional (3D) 1The abbreviations used are: used: 3D, three-dimensional; DSSP, a database of secondary structure assignments for all protein entries in the Protein Data Bank; GO, gene ontology; NMR, nuclear magnetic resonance; PDB, Protein Data Bank; PDOC, PROSITE documentation; PROSITE, database of protein families and domains; MSDSD, Macromolecular Structure Database Search Database. 1The abbreviations used are: used: 3D, three-dimensional; DSSP, a database of secondary structure assignments for all protein entries in the Protein Data Bank; GO, gene ontology; NMR, nuclear magnetic resonance; PDB, Protein Data Bank; PDOC, PROSITE documentation; PROSITE, database of protein families and domains; MSDSD, Macromolecular Structure Database Search Database. structures of biologically active macromolecules and their complexes. Enormous structural information (over 34,000 entries) is currently available from the Protein Data Bank (PDB) that includes details of protein organization, of their interactions with nucleic acids and ligands, and of their conformational behavior. Structural data provide the essential framework for characterizing molecular mechanisms of biological activity, for analyzing evolutionary relationships, and for illuminating our understanding of biological function (Ref. 1Dodson G. Verma C.S. Protein flexibility: its role in structure and mechanism revealed by molecular simulations.Cell. Mol. Life Sci. 2006; 63: 207-219Crossref PubMed Scopus (39) Google Scholar and references therein). Although proteins often are pictured as rigid entities corresponding to some average structure (immersed in a featureless solvent continuum), it has long been known that they have a rather fluid, dynamic structure with rapid conformational fluctuations (2Cooper A. Thermodynamic fluctuations in protein molecules.Proc. Natl. Acad. Sci. U. S. A. 1976; 73: 2740-2741Crossref PubMed Scopus (349) Google Scholar). Subnanosecond dynamics of proteins studied by NMR (3Allerhand A. Doddrell D. Glushko V. Cochran D. Wenkert E. Lawson P. Gurd F. Conformation and segmental motion of native and denatured ribonuclease A in solution. Application of natural-abundance carbon-13 partially relaxed Fourier transform nuclear magnetic resonance.J. Am. Chem. Soc. 1971; 93: 544-546Crossref PubMed Scopus (166) Google Scholar), nitroxide spin labeling (4Likhtenshtein G.I. Grebenshchikov Yu. B. Avilova T.V. An investigation of the microrelief and conformational mobility of proteins by the ESR method.Mol. Biol. 1972; 6: 52-60PubMed Google Scholar), dielectric relaxation (5Pennock B.E. Schwan H.P. Further observations on the electrical properties of hemoglobin-bound water.J. Phys. Chem. 1969; 73: 2600-2610Crossref PubMed Scopus (145) Google Scholar), and fluorescence experiments (1Dodson G. Verma C.S. Protein flexibility: its role in structure and mechanism revealed by molecular simulations.Cell. Mol. Life Sci. 2006; 63: 207-219Crossref PubMed Scopus (39) Google Scholar) have advanced such descriptive terms as “breathing” (6Englander S.W. Downer N.W. Teitelbaum H. Hydrogen exchange.Annu. Rev. Biochem. 1972; 41: 903-924Crossref PubMed Scopus (430) Google Scholar), “relaxation,” “segmental motion,” and “mobile defect” (7Eftink M.R. Ghiron C.A. Dynamics of a protein matrix revealed by fluorescence quenching.Proc. Natl. Acad. Sci. U. S. A. 1975; 72: 3290-3294Crossref PubMed Scopus (142) Google Scholar) to portray the conformational mobility of proteins in functionally competent states. The presence of substantial >1-Å breathing motions has been recognized in early NMR studies on the flipping of the buried aromatic residues in the pancreatic trypsin inhibitor (8Wüthrch K. Wagner G. NMR investigations of the dynamics of the aromatic amino acid residues in the basic pancreatic trypsin inhibitor.FEBS Lett. 1975; 50: 265-268Crossref PubMed Scopus (137) Google Scholar). Hemoglobin and myoglobin offer another striking example of the dynamic nature of biological activity where small structural fluctuations of the protein matrix allow O2 molecule to move to and from the heme pocket (9Perutz M.F. Mathews F.S. An x-ray study of azide methaemoglobin.J. Mol. Biol. 1966; 21: 199-202Crossref PubMed Scopus (241) Google Scholar, 10Frauenfelder H. Petsko G.A. Tsernoglou D. Temperature-dependent X-ray diffraction as a probe of protein structural dynamics.Nature. 1979; 280: 558-563Crossref PubMed Scopus (898) Google Scholar, 11Case D.A. Karplus M. Dynamics of ligand binding to heme proteins.J. Mol. Biol. 1979; 132: 343-368Crossref PubMed Scopus (391) Google Scholar). Buried water molecules, which are observed in most proteins, were shown to exchange with surface water molecules at the microsecond timescale, and that process necessitates large and correlated fluctuations in the host protein (12Denisov V.P. Peters J. Horlein H.D. Halle B. Using buried water molecules to explore the energy landscape of proteins.Nat. Struct. Biol. 1996; 3: 505-509Crossref PubMed Scopus (162) Google Scholar, 13Verma C.S. Fischer S. Protein stability and ligand binding: new paradigms from in-silico experiments.Biophys. Chem. 2005; 115: 295-302Crossref PubMed Scopus (13) Google Scholar). Furthermore the reduced activity of the protein mutants in some cases might be a consequence of reduced fluctuations and flexibility in the molecule away from that which has evolved for optimal functioning (1Dodson G. Verma C.S. Protein flexibility: its role in structure and mechanism revealed by molecular simulations.Cell. Mol. Life Sci. 2006; 63: 207-219Crossref PubMed Scopus (39) Google Scholar). Indeed the conformational lability in proteins, coordinated with the chemical requirements at each stage of their reactions, is a major component in enzyme catalysis, allosteric regulation, antigen-antibody interactions, and protein-DNA binding (1Dodson G. Verma C.S. Protein flexibility: its role in structure and mechanism revealed by molecular simulations.Cell. Mol. Life Sci. 2006; 63: 207-219Crossref PubMed Scopus (39) Google Scholar). The concept of inherent and correlated protein motions has become a landmark in biophysics and structural biology that underlies our understanding of molecular recognition (14Schulz G.E. Nucleotide binding proteins.in: Balaban M. Molecular Mechanisms of Biological Recognition. Elsevier, Amsterdam1979: 79-94Google Scholar, 15Dunker A.K. Garner E. Guillot S. Romero P. Albrecht K. Hart J. Obradovic Z. Kissinger C. Villafranca J.E. Protein disorder and the evolution of molecular recognition: theory, predictions and observations.Pac. Symp. Biocomput. 1998; 3: 473-484Google Scholar). Although an importance of protein flexibility has been widely evoked in the literature, it has been more difficult to characterize experimentally. Proteins are composed of discrete atoms, which are constantly undergoing thermal fluctuations from rapid (picosecond) vibrations, through slower (multinanosecond) global reorientations and side chain isomerization, to long time scale (microsecond to second) conformational changes (16Karplus M. McCammon J.A. The internal dynamics of globular proteins.CRC Crit. Rev. Biochem. 1981; 9: 293-349Crossref PubMed Scopus (409) Google Scholar). The reality of these fluctuations is evident in the PDB, which reports not only a set of fixed coordinates but also the temperature B-factors (Debye-Waller factors). The latter denotes the thermal fluctuations of the protein and provides information about the mobility of each atom in the structure (17Rasmussen B.F. Stock A.M. Ringe D. Petsko G.A. Crystalline ribonuclease A loses function below the dynamical transition at 220 K.Nature. 1992; 357: 423-424Crossref PubMed Scopus (505) Google Scholar, 18Trueblood K.N. Bürghi H.-B. Burzlaff H. Dunitz J.D. Gramaccioli C.M. Schulz H.H. Shmueli U. Abrahams S.C. Atomic displacement parameter nomenclature. Report of a subcommittee on atomic displacement parameter nomenclature.Acta Crystallogr. Sect. A. 1996; 52: 770-781Crossref Scopus (288) Google Scholar, 19Drenth J. Principles of Protein Crystallography. Springer-Verlag, New York1994Crossref Google Scholar). The crystallographic parameters have been successfully used to derive overall and intrinsic motions (20Sternberg M.J. Grace D.E. Phillips D.C. Dynamic information from protein crystallography: an analysis of temperature factors from refinement of the hen egg-white lysozyme structure.J. Mol. Biol. 1979; 130: 231-252Crossref PubMed Scopus (127) Google Scholar), to identify higher atomic mobility at the active site, and even to allocate a component in the amplitudes of atomic vibration that are derived from the overall global motion of the protein (21Artymiuk P.J. Blake C.C. Grace D.E. Oatley S.J. Phillips D.C. Sternberg M.J. Crystallographic studies of the dynamic properties of lysozyme.Nature. 1979; 280: 563-568Crossref PubMed Scopus (330) Google Scholar). Furthermore the analysis of the 3D structures of wild type proteins and their synthetic analogs (22Phillips Jr., G.N. Comparison of the dynamics of myoglobin in different crystal forms.Biophys. J. 1990; 57: 381-383Abstract Full Text PDF PubMed Scopus (68) Google Scholar) as well as the proteins that crystallize in a different space group (23Davies D.R. Cohen G.H. Interactions of protein antigens with antibodies.Proc. Natl. Acad. Sci. U. S. A. 1996; 93: 7-12Crossref PubMed Scopus (483) Google Scholar) promotes the idea that the B-factors reveal the effect of different packing constraints on the protein flexibility. Further statistical-mechanical study of a large group of protein structures clearly demonstrated that the B-profile is, in fact, essentially determined by spatial variations in local packing density (24Halle B. Flexibility and packing in proteins.Proc. Natl. Acad. Sci. U. S. A. 2002; 99: 1274-1279Crossref PubMed Scopus (211) Google Scholar). Note that NMR data can also be used to characterize the flexibility of a protein (25Ishima R. Torchia D.A. Protein dynamics from NMR.Nat. Struct. Biol. 2000; 7: 740-743Crossref PubMed Scopus (453) Google Scholar), but in practice the number of atoms within a molecule is so large that drawing conclusions from the data is difficult. A simple method to predict protein flexibility using secondary chemical shifts has been developed recently that allows quantitative, site-specific mapping of protein backbone mobility without the need of a 3D structure or NMR relaxation experiments (26Berjanskii M.V. Wishart D.S. A simple method to predict protein flexibility using secondary chemical shifts.J. Am. Chem. Soc. 2005; 127: 14970-14971Crossref PubMed Scopus (327) Google Scholar). Numerous studies have attempted to identify flexible regions in proteins as well as to understand their role in overall protein dynamics and functionality. However, different groups use different definitions and various experimental approaches to identify this fold characteristic. One class of “intrinsically disordered” flexible regions was defined as the regions that are invisible in electron density maps of x-ray diffraction (27Dunker A.K. Obradovic Z. The protein trinity—linking function and disorder.Nat. Biotechnol. 2001; 19: 805-806Crossref PubMed Scopus (496) Google Scholar, 28Romero P. Obradovic Z. Dunker A.K. Folding minimal sequences: the lower bound for sequence complexity of globular proteins.FEBS Lett. 1999; 462: 363-367Crossref PubMed Scopus (67) Google Scholar, 29Obradovic Z. Peng K. Vucetic S. Radivojac P. Brown C.J. Dunker A.K. Predicting intrinsic disorder from amino acid sequence.Proteins. 2003; 53: 566-572Crossref PubMed Scopus (363) Google Scholar, 30Romero P. Obradovic Z. Kissinger C. Villafranca J.E. Garner E. Guilliot S. Dunker A.K. Thousands of proteins likely to have long disordered regions.Pac. Symp. Biocomput. 1998; 3: 437-448Google Scholar, 31Radivojac P. Obradovic Z. Smith D.K. Zhu G. Vucetic S. Brown C.J. Lawson J.D. Dunker A.K. Protein flexibility and intrinsic disorder.Protein Sci. 2004; 13: 71-80Crossref PubMed Scopus (257) Google Scholar). Other researchers focus on extended (>70 consecutive residues) regions of a very low regular secondary structure that are particularly abundant in eukaryotic proteomes, conserved during evolution, and over-represented in regulatory and promiscuously interacting proteins (32Liu J. Tan H. Rost B. Loopy proteins appear conserved in evolution.J. Mol. Biol. 2002; 322: 53-64Crossref PubMed Scopus (159) Google Scholar, 33Liu J. Rost B. NORSp: predictions of long regions without regular secondary structure.Nucleic Acids Res. 2003; 31: 3833-3835Crossref PubMed Scopus (124) Google Scholar, 34Schlessinger A. Rost B. Protein flexibility and rigidity predicted from sequence.Proteins. 2005; 61: 115-126Crossref PubMed Scopus (145) Google Scholar). In fact, many proteins contain recognizable small “modules” that recur in other proteins in various combinations and in some cases can fold independently. They can be covalently linked to generate multimodular proteins and serve as self-directed structural units (35Thornton J.M. Orengo C.A. Todd A.E. Pearl F.M.G. Proteins folds, functions and evolution.J. Mol. Biol. 1999; 293: 333-342Crossref PubMed Scopus (137) Google Scholar). Such domains can function independently, can be expressed in genomes, and are often rearranged through alternative splicing. These structural units are inferred to be a good evolutionary unit and are often used instead of whole proteins for annotations of the protein space (36Shakhnovich B.E. Harvey J.M. Comeau S. Lorenz D. DeLisi C. Shakhnovich E. ELISA: structure-function inferences based on statistically significant and evolutionarily inspired observations.BMC Bioinformatics. 2003; 4: 34-41Crossref PubMed Scopus (13) Google Scholar). Yet if misplaced they can trigger dramatic biological consequences: oncoproteins comprising DNA-binding domains are capable of initiating transcription albeit being a small part of a largely unfolded chimeric polypeptide chain (37Uren A. Tcherkasskaya O. Toretsky J.A. Recombinant EWS-FLI1 oncoprotein activates transcription.Biochemistry. 2004; 43: 13579-13589Crossref PubMed Scopus (47) Google Scholar). In this regard, the crystallographic B-factors when considered over the length of a protein chain show that some segments undergo movements on a much larger scale than the rest of the protein, suggesting that the analysis of the B-distributions can be used to identify and predict flexible regions (38Karplus P.A. Schulz G.E. Prediction of chain flexibility in proteins.Naturwissenschaften. 1985; 72: 212-213Crossref Scopus (939) Google Scholar, 39Vihinen M. Torkkila E. Riikonen P. Accuracy of protein flexibility predictions.Proteins. 1994; 19: 141-149Crossref PubMed Scopus (255) Google Scholar, 40Kundu S. Melton J.S. Sorensen D.C. Phillips Jr., G.N. Dynamics of proteins in crystals: comparison of experiment with simple models.Biophys. J. 2002; 83: 723-732Abstract Full Text Full Text PDF PubMed Scopus (218) Google Scholar, 41Smith D.K. Radivojac P. Obradovic Z. Dunker A.K. Zhu G. Improved amino acid flexibility parameters.Protein Sci. 2003; 12: 1060-1072Crossref PubMed Scopus (137) Google Scholar). Moreover the scheme was proposed to discriminate the amino acid residues according to their flexibility based on the B-factors of their Cα atoms (38Karplus P.A. Schulz G.E. Prediction of chain flexibility in proteins.Naturwissenschaften. 1985; 72: 212-213Crossref Scopus (939) Google Scholar, 39Vihinen M. Torkkila E. Riikonen P. Accuracy of protein flexibility predictions.Proteins. 1994; 19: 141-149Crossref PubMed Scopus (255) Google Scholar, 41Smith D.K. Radivojac P. Obradovic Z. Dunker A.K. Zhu G. Improved amino acid flexibility parameters.Protein Sci. 2003; 12: 1060-1072Crossref PubMed Scopus (137) Google Scholar). Altogether four categories with distinct flexibility were recognized that include low B-factor ordered regions, high B-factor ordered regions, and short and long disordered regions with the last two categories being the regions of missing electron density (31Radivojac P. Obradovic Z. Smith D.K. Zhu G. Vucetic S. Brown C.J. Lawson J.D. Dunker A.K. Protein flexibility and intrinsic disorder.Protein Sci. 2004; 13: 71-80Crossref PubMed Scopus (257) Google Scholar). The amino acid compositions of these categories differ significantly, whereas the biophysical properties of high B-factor ordered regions are relatively close to those of the short disordered regions. They provide a higher flexibility, hydrophilicity, and absolute net and total charge. The low B-factor ordered regions are enriched in hydrophobic residues and depleted in the total number of charged residues compared with the other categories (31Radivojac P. Obradovic Z. Smith D.K. Zhu G. Vucetic S. Brown C.J. Lawson J.D. Dunker A.K. Protein flexibility and intrinsic disorder.Protein Sci. 2004; 13: 71-80Crossref PubMed Scopus (257) Google Scholar). The “significantly-greater-than-chance” predictability of these categories from sequence suggests that they are, most likely, encoded at the primary structure level (31Radivojac P. Obradovic Z. Smith D.K. Zhu G. Vucetic S. Brown C.J. Lawson J.D. Dunker A.K. Protein flexibility and intrinsic disorder.Protein Sci. 2004; 13: 71-80Crossref PubMed Scopus (257) Google Scholar). The impact of local flexibility in proteins on biological activity remains unclear. It is clear, however, that even such a coarse grained aspect of protein structure as the secondary structure assigned from x-ray crystals captures flexibility relevant for protein function (42Andersen C.A.F. Palmer A.G. Brunak S. Rost B. Continuum secondary structure captures protein flexibility.Structure (Lond.). 2002; 10: 175-185Abstract Full Text Full Text PDF PubMed Scopus (121) Google Scholar). Structural complexity of biological macromolecules allows for a large variety of mechanisms to regulate the molecular recognition, including key-lock binding, template-assisted folding, folding by association, conformational selection, etc. Whether the recognition involves inducible or constitutive binding, the interaction per se depends on and affects the secondary structure of the individual protein (43Wright P.E. Dyson H.J. Intrinsically unstructured proteins: reassessing the protein structure-function paradigm.J. Mol. Biol. 1999; 293: 321-331Crossref PubMed Scopus (2330) Google Scholar, 44Dyson H.J. Wright P.E. Coupling of folding and binding for unstructured proteins.Curr Opin. Struct. Biol. 2002; 12: 54-60Crossref PubMed Scopus (1125) Google Scholar, 45Dyson H.J. Wright P.E. Unfolded proteins and protein folding studied by NMR.Chem. Rev. 2004; 104: 3607-3622Crossref PubMed Scopus (531) Google Scholar, 46Dunker A.K. Brown C.J. Lawson J.D. Iakoucheva L.M. Obradovic Z. Intrinsic disorder and protein function.Biochemistry. 2002; 41: 6573-6582Crossref PubMed Scopus (1486) Google Scholar, 47Demchenko A.P. Recognition between flexible protein molecules: induced and assisted folding.J. Mol. Recognit. 2001; 14: 42-61Crossref PubMed Scopus (133) Google Scholar). It seems reasonable therefore to analyze the deviation of the secondary structure (assigned by crystallography and NMR data) in various protein families with specific emphasis on the residues embedded in configurations with high flexibility. Such residues do not necessarily represent the class of natively disordered residues with high inherent flexibility but constitute a more flexible class than rigid helical or stranded regions. Mining conventional biophysical data might facilitate the discovery of underlying trends in structure-function relationships that were missed previously (48Tcherkasskaya O. Uversky V.N. Polymeric aspects of protein folding: a brief overview.Protein Pept. Lett. 2003; 10: 239-245Crossref PubMed Scopus (27) Google Scholar, 49Tcherkasskaya O. Davidson E.A. Uversky V.N. Biophysical constraints for protein structure prediction.J. Proteome Res. 2003; 2: 37-42Crossref PubMed Scopus (49) Google Scholar). Here we examine the impact of local flexibility in proteins on molecular recognition and structure-function relationships utilizing gene-regulating molecules as a starting point. Transcription factors (TFs) are modular molecules with separate domains mediating DNA binding, transcriptional activation, and repression. They are regulators of cell cycle progression, differentiation, and survival and are often altered in human diseases. Eukaryotic transcription factors contain a minimum of two domains that are responsible for the sequence-specific DNA recognition and transcriptional activation (50Kant S. Bagaria A. Ramakumar S. Putative homeodomain proteins identified in prokaryotes based on pattern and sequence similarity.Biochem. Biophys. Res. Comm. 2002; 299: 229-232Crossref PubMed Scopus (5) Google Scholar, 51Brivanlou A.H. Darnell J.E. Transcription—signal transduction and the control of gene expression.Science. 2002; 295: 813-818Crossref PubMed Scopus (502) Google Scholar). Most DNA-binding domains adopt folded structures in the absence of DNA, and conformational transitions induced by DNA binding are rather local (43Wright P.E. Dyson H.J. Intrinsically unstructured proteins: reassessing the protein structure-function paradigm.J. Mol. Biol. 1999; 293: 321-331Crossref PubMed Scopus (2330) Google Scholar, 44Dyson H.J. Wright P.E. Coupling of folding and binding for unstructured proteins.Curr Opin. Struct. Biol. 2002; 12: 54-60Crossref PubMed Scopus (1125) Google Scholar, 45Dyson H.J. Wright P.E. Unfolded proteins and protein folding studied by NMR.Chem. Rev. 2004; 104: 3607-3622Crossref PubMed Scopus (531) Google Scholar). Yet transcriptional activation domains might be both non-globular and unstructured and become partly ordered upon binding. Thus, local disorder appears to be an important facet of proteins involved in gene regulation, allowing for a variety of mechanisms in molecular networking (43Wright P.E. Dyson H.J. Intrinsically unstructured proteins: reassessing the protein structure-function paradigm.J. Mol. Biol. 1999; 293: 321-331Crossref PubMed Scopus (2330) Google Scholar, 45Dyson H.J. Wright P.E. Unfolded proteins and protein folding studied by NMR.Chem. Rev. 2004; 104: 3607-3622Crossref PubMed Scopus (531) Google Scholar). Despite the successes in protein domain assignment and comparison (50Kant S. Bagaria A. Ramakumar S. Putative homeodomain proteins identified in prokaryotes based on pattern and sequence similarity.Biochem. Biophys. Res. Comm. 2002; 299: 229-232Crossref PubMed Scopus (5) Google Scholar), there have been only a few breakthroughs in the area of quantifying the structure-function relationship. In fact, most of the databases classify the protein space by occurrence of a particular type of secondary structure (e.g. all α, all β, etc.) or global fold (e.g. Rossman, ferrodoxin, α/β-cylinder, α+β-plaits, etc.). Analyzing the secondary structure in proteins with various biological activities will aid greatly in understanding the role of structure-function relationships in evolutionary biology. In this report, we introduce the parameter of the effective flexibility in proteins and analyze its variation through the functional space. We elucidate the impact of molecular confinement on inherited conformational lability of proteins and demonstrate the growing role of intrinsic flexibility in organisms of higher complexity that require intricate molecular networking (52Fernandez A. Scott R. Berry R.S. The non-conserved wrapping of conserved protein folds reveals a trend toward increasing connectivity in proteomic networks.Proc. Natl. Acad. Sci. U. S. A. 2004; 101: 2823-2827Crossref PubMed Scopus (29) Google Scholar). Structural data were collected using the annotations reported in the PBD and, later, utilizing an automated search with cross-referencing of protein structure with protein function, taxonomy, and gene ontology. Initially complete entries for high resolution structures (containing B-values, secondary structure indexes, experimental conditions, resolution characteristics, etc.) were taken from an unbiased selection of the PDB entries. In the case of TFs, this procedure resulted in 353 structures that included individual TF chains and multisubunit complexes with DNA. Given the significant redundancy of the PDB, the recovered data set was revised manually. Structures determined with resolution >3 Å and R-factor ≥0.25 were excluded from analysis as was NMR data averaged over less than 20 models, synthetic constructs, mutated proteins, and short polypeptides (<50 amino acids). The multiple entries were substituted by the average values of appropriate parameters. Of the remaining 112 structures of TF chains and single chain-DNA complexes, 98 structures (98 chains) were complete in all respects and were found to be acceptable (Table I). A similar approach was utilized to generate the structural set for oxygen transporters. In this case, a PDB query provided the original set of 497 entries (1,275 chains). Exclusion of structures with poor resolution, synthetic constructs, mutated proteins, duplicates, and multimeric complexes (>2 chains) left only 41 structures (57 chains) that were found acceptable for the analysis (Table II).Table IPDB codes of 98 high resolution structures of TF proteins selected for analysis1ARD1BF51BGF1BHI1BM81BOR1BQV1BVO1CDW1CIT1CMO1COK1D5V1D8J/KaDenotes double entries, e.g. 1D8J and 1D8K and similar entries across the table. This usually includes NMR structures averaged over ≥20 samples and that reported for Min Average. For double entries, the average value of molecular parameters was used in consequent analysis.1DL61DP71DXS1E2X1E3O1EAN1ETC/DaDenotes double entries, e.g. 1D8J and 1D8K and similar entries across the table. This usually includes NMR structures averaged over ≥20 samples and that reported for Min Average. For double entries, the average value of molecular parameters was used in consequent analysis.1F621FLI1FTT1FU91FV51FYK1GAT/UaDenotes double entries, e.g. 1D8J and 1D8K and similar entries across the table. This usually includes NMR structures averaged over ≥20 samples and that reported for Min Average. For double entries, the average value of molecular parameters was used in consequent analysis.1GCC1GNF1H951HDP1HH21HKS/TaDenotes double entries, e.g. 1D8J and 1D8K and similar entries across the table. This usually includes NMR structures averaged over ≥20 samples and that reported for Min Average. For double entries, the average value of molecular parameters was used in consequent analysis.1HZ41I111I1S1I271I4W1I6A1J4W1J5K1JN71K1V1K991KHM1KQ81L3G1LFB1LV21M1H1NPR1MB11MN41MNN1NFA1NHA1OCT1OCP1ODH1OPC1P971PFJ1POU1PXE1PYC1PZW1Q1H1QQH1RLY/O4aDenotes double entries, e.g. 1D8J and 1D8K and similar entries across the table. This usually includes NMR structures averaged over ≥20 samples and that reported for Min Average. For double entries, the average value of molecular parameters was used in consequent analysis.1RXR1SKN1SP11SP21TF31TFB1TGH1TTU1UBD1UL41UL51UUS/RaDenotes double entries, e.g. 1D8J and 1D8K and similar entries across the table. This usually includes NMR structures averaged over ≥20 samples and that reported for Min Average. F" @default.
• W2127221680 created "2016-06-24" @default.
• W2127221680 creator A5000225034 @default.
• W2127221680 creator A5009077731 @default.
• W2127221680 creator A5026109246 @default.
• W2127221680 creator A5053990108 @default.
• W2127221680 creator A5083199032 @default.
• W2127221680 date "2006-07-01" @default.
• W2127221680 modified "2023-10-14" @default.
• W2127221680 title "Local Flexibility in Molecular Function Paradigm" @default.
• W2127221680 cites W121768123 @default.
• W2127221680 cites W1487346929 @default.
• W2127221680 cites W1494258879 @default.
• W2127221680 cites W1965291453 @default.
• W2127221680 cites W1966781760 @default.
• W2127221680 cites W1978159970 @default.
• W2127221680 cites W1984627474 @default.
• W2127221680 cites W1984965754 @default.
• W2127221680 cites W1987960749 @default.
• W2127221680 cites W1988624456 @default.
• W2127221680 cites W1989186646 @default.
• W2127221680 cites W1990200822 @default.
• W2127221680 cites W1991060322 @default.
• W2127221680 cites W1995679281 @default.
• W2127221680 cites W2004405255 @default.
• W2127221680 cites W2004486076 @default.
• W2127221680 cites W2008708467 @default.
• W2127221680 cites W2012268513 @default.
• W2127221680 cites W2015954194 @default.
• W2127221680 cites W2016170088 @default.
• W2127221680 cites W2021191010 @default.
• W2127221680 cites W2021646539 @default.
• W2127221680 cites W2024808207 @default.
• W2127221680 cites W2032168101 @default.
• W2127221680 cites W2032781098 @default.
• W2127221680 cites W2036792999 @default.
• W2127221680 cites W2045499719 @default.
• W2127221680 cites W2052606462 @default.
• W2127221680 cites W2055713335 @default.
• W2127221680 cites W2058146658 @default.
• W2127221680 cites W2069796695 @default.
• W2127221680 cites W2072133388 @default.
• W2127221680 cites W2072302548 @default.
• W2127221680 cites W2073745520 @default.
• W2127221680 cites W2082835240 @default.
• W2127221680 cites W2083445427 @default.
• W2127221680 cites W2083724830 @default.
• W2127221680 cites W2085277871 @default.
• W2127221680 cites W2087202599 @default.
• W2127221680 cites W2089907517 @default.
• W2127221680 cites W2090614522 @default.
• W2127221680 cites W2092782587 @default.
• W2127221680 cites W2098664089 @default.
• W2127221680 cites W2101600610 @default.
• W2127221680 cites W2107442223 @default.
• W2127221680 cites W2111705861 @default.
• W2127221680 cites W2118258049 @default.
• W2127221680 cites W2119735994 @default.
• W2127221680 cites W2121704271 @default.
• W2127221680 cites W2128021885 @default.
• W2127221680 cites W2129359219 @default.
• W2127221680 cites W2129748900 @default.
• W2127221680 cites W2136135359 @default.
• W2127221680 cites W2136166518 @default.
• W2127221680 cites W2141803423 @default.
• W2127221680 cites W2143011057 @default.
• W2127221680 cites W2143251450 @default.
• W2127221680 cites W2146279689 @default.
• W2127221680 cites W2149653886 @default.
• W2127221680 cites W2152265734 @default.
• W2127221680 cites W2168970921 @default.
• W2127221680 cites W2171190723 @default.
• W2127221680 cites W4250873843 @default.
• W2127221680 doi "https://doi.org/10.1074/mcp.m500315-mcp200" @default.
• W2127221680 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/16571897" @default.
• W2127221680 hasPublicationYear "2006" @default.
• W2127221680 type Work @default.
• W2127221680 sameAs 2127221680 @default.
• W2127221680 citedByCount "43" @default.
• W2127221680 countsByYear W21272216802012 @default.
• W2127221680 countsByYear W21272216802013 @default.
• W2127221680 countsByYear W21272216802014 @default.
• W2127221680 countsByYear W21272216802015 @default.
• W2127221680 countsByYear W21272216802016 @default.
• W2127221680 countsByYear W21272216802017 @default.
• W2127221680 countsByYear W21272216802020 @default.
• W2127221680 countsByYear W21272216802022 @default.
• W2127221680 crossrefType "journal-article" @default.
• W2127221680 hasAuthorship W2127221680A5000225034 @default.
• W2127221680 hasAuthorship W2127221680A5009077731 @default.
• W2127221680 hasAuthorship W2127221680A5026109246 @default.
• W2127221680 hasAuthorship W2127221680A5053990108 @default.
• W2127221680 hasAuthorship W2127221680A5083199032 @default.
• W2127221680 hasBestOaLocation W21272216801 @default.
• W2127221680 hasConcept C105795698 @default.
• W2127221680 hasConcept C14036430 @default.
• W2127221680 hasConcept C185592680 @default.
• W2127221680 hasConcept C2780598303 @default.

• next