Biomedical subjects

M Michael Gromiha

Publications and source records attributed to M Michael Gromiha.

At least 37 records · Page 2Linked to original sources

PubMed2005

TMBETA-NET: discrimination and prediction of membrane spanning beta-strands in outer membrane proteins.

We have developed a web-server, TMBETA-NET for discriminating outer membrane proteins and predicting their membrane spanning beta-strand segments. The amino acid compositions of globular and outer membrane proteins have been systematically analyzed and a statistical method has been proposed for discriminating outer membrane proteins. The prediction of membrane spanning segments is mainly based on feed forward neural network and refined with beta-strand length. Our program takes the amino acid sequence as input and displays the type of the protein along with membrane-spanning beta-strand segments as a stretch of highlighted amino acid residues. Further, the probability of residues to be in transmembrane beta-strand has been provided with a coloring scheme. We observed that outer membrane proteins were discriminated with an accuracy of 89% and their membrane spanning beta-strand segments at an accuracy of 73% just from amino acid sequence information. The prediction server is available at http://psfs.cbrc.jp/tmbeta-net/.

Amino Acids↗

PubMed2005

SRide: a server for identifying stabilizing residues in proteins.

Residues expected to play key roles in the stabilization of proteins [stabilizing residues (SRs)] are selected by combining several methods based mainly on the interactions of a given residue with its spatial, rather than its sequential neighborhood and by considering the evolutionary conservation of the residues. A residue is selected as a stabilizing residue if it has high surrounding hydrophobicity, high long-range order, high conservation score and if it belongs to a stabilization center. The definition of all these parameters and the thresholds used to identify the SRs are discussed in detail. The algorithm for identifying SRs was originally developed for TIM-barrel proteins [M. M. Gromiha, G. Pujadas, C. Magyar, S. Selvaraj, and I. Simon (2004), Proteins, 55, 316-329] and is now generalized for all proteins of known 3D structure. SRs could be applied in protein engineering and homology modeling and could also help to explain certain folds with significant stability. The SRide server is located at http://sride.enzim.hu.

Amino Acids↗

PubMed2005

Influence of DNA stiffness in protein-DNA recognition.

Protein-DNA recognition plays an essential role in the regulation of gene expression. The protein-DNA binding specificity is based on direct atomic contacts between protein and DNA and/or the conformational properties of DNA. In this work, we have analyzed the influence of DNA stiffness (E) to the specificity of protein-DNA complexes. The average DNA stiffness parameters for several protein-DNA complexes have been computed using the structure based sequence dependent stiffness scale. The relationship between DNA stiffness and experimental protein-DNA binding specificity has been brought out. We have investigated the importance of DNA stiffness with the aid of experimental free energy changes (DeltaDeltaG) due to binding in several protein-DNA complexes, such as, ETS proteins, 434, lambda, Mnt and trp repressors, 434 cro protein, EcoRV endonuclease V and zinc fingers. We found a correlation in the range 0.65-0.97 between DeltaDeltaG and E in these examples. Further, we have qualitatively analyzed the effect of mutations in the target sequence of lambda repressor and we observed that the DNA stiffness could correctly identify 70% of the correct bases among the considered nine positions.

Base Sequence↗

PubMed2005

Structural analysis of residues involving cation-pi interactions in different folding types of membrane proteins.

Cation-pi interactions play an important role to the stability of protein structures. In our earlier work, we have analyzed the influence and energetic contribution of cation-pi interactions in three-dimensional structures of membrane proteins. In this work, we investigate the characteristic features of residues that are involved in cation-pi interactions. We have computed several parameters, such as surrounding hydrophobicity, number of long-range contacts, conservation score and normalized B-factor for all these residues and identified their location, whether in the membrane or at surface. We found that the cation-pi interactions are mainly formed by long-range interactions. The cationic residues involved in cation-pi interactions have higher surrounding hydrophobicity than their average values in the whole dataset and an opposite trend is observed for aromatic residues. In transmembrane helical proteins, except Phe, all other residues that are responsible for cation-pi interactions are highly conserved with other related protein sequences whereas in transmembrane strand proteins, an appreciable conservation is observed only for Arg. The analysis on the flexibility of residues reveals that the cation-pi interaction forming residues are more stable than other residues. The results obtained in the present study would be helpful to understand the role of cation-pi interactions in the structure and folding of membrane proteins.

Amino Acids↗

PubMed2005

Relative importance of secondary structure and solvent accessibility to the stability of protein mutants. A case study with amino acid properties and energetics on T4 and human lysozymes.

Understanding the factors influencing the stability of protein mutants is an important task in molecular and computational biology. In this work, we have approached this problem by examining the relative importance of secondary structure and solvent accessibility of the mutant residue for understanding/predicting the stability of protein mutants. We have used hydrophobic, electrostatic and hydrogen bond free energy terms and nine unique physicochemical, energetic and conformational properties of amino acids in the present study and these parameters have been related with changes in thermal stability (DeltaTm) of all the single mutants of lysozymes based on single and multiple correlation coefficients. As expected the properties reflecting hydrophobicity and hydrophobic free energy play a major role to distinguish stabilizing and destabilizing mutants. The hydrophobic free energy due to carbon and nitrogen atoms distinguish the stability of coil and strand mutations to the accuracy of 100 and 90%, respectively. In agreement with previous results, the subgroup classification based on secondary structure and the information about its location in the structure yielded good relationship with the experimental DeltaTm. We revealed that the secondary structure information is equally or more important than solvent accessibility for understanding the stability of protein mutants. The comparison of amino acid properties with free-energy terms indicate that the energetic contribution explains the mutant stability better in coil region whereas the amino acid properties do better in strand region. Further, the combination of free energies with amino acid properties increased the correlation significantly. The present study demonstrates the importance of classifying the mutants based on secondary structure to the stability of proteins upon mutations.

Amino Acids↗

PubMed2005

Application of residue distribution along the sequence for discriminating outer membrane proteins.

Discriminating outer membrane proteins from other folding types of globular and membrane proteins is an important problem both for detecting outer membrane proteins from genomic sequences and for the successful prediction of their secondary and tertiary structures. In this work, we have systematically analyzed the distribution of amino acid residues in the sequences of globular and outer membrane proteins. We observed that the occurrence of two neighboring aliphatic and polar residues is significantly higher in outer membrane proteins than in globular proteins. From the information about the dipeptide composition we have devised a statistical method for discriminating outer membrane proteins from other globular and membrane proteins. Our approach correctly picked up the outer membrane proteins with an accuracy of 95% for the training set of 337 proteins. On the other hand, our method has correctly excluded the globular proteins at an accuracy of 79% in a non-redundant dataset of 674 proteins. Furthermore, the present method is able to correctly exclude alpha-helical membrane proteins up to an accuracy of 87%. These accuracy levels are comparable to other methods in the literature. The influence of protein size and structural class for discrimination is discussed.

Amino Acid Sequence↗

PubMed2005

Importance of main-chain hydrophobic free energy to the stability of thermophilic proteins.

Living organisms are found in the most unexpected places, including deep-sea vents at 100 degrees C and several hundred bars pressure, in hot springs. Needless to say, the proteins found in thermophilic species are much more stable than their mesophilic counterparts. There are no obvious reasons to say that one would be more stable than others. Even examination of the amino acids and comparison of structural features of thermophiles with mesophilies cannot bring satisfactory explanation for the thermal stability of such proteins. In order to bring out the hidden information behind the thermal stabilization of such proteins in terms of energy factors and their combinations, analysis were made on good resolution structures of thermophilic and their mesophilic homologous from 23 different families. From the structural coordinates, free energy contributions due to hydrophobic, electrostatic, hydrogen bonding, disulfide bonding and van der Waals interactions are computed. In this analysis, a vast majority of thermophilic proteins adopt slightly lower free energy contribution in each energy terms than its mesophilic counterparts. The major observation noted from this study is the lower hydrophobic free energy contribution due to carbon atoms and main-chain nitrogen atoms in all the thermophilic proteins. The possible combination of different free energy terms shows majority of the thermophilic proteins have lower free energy strategy than their mesophilic homologous. The derived results show that the hydrophobic free energy due to carbon and nitrogen atoms and such combinations of free energy components play a vital role in the thermostablisation of such proteins.

Animals↗

PubMed2005

Integration of bioinformatics and computational biology to understand protein-DNA recognition mechanism.

Transcription factors play essential role in the gene regulation in higher organisms, binding to multiple target sequences and regulating multiple genes in a complex manner. In order to decipher the mechanism of gene regulation, it is important to understand the molecular mechanism of protein-DNA recognition. Here we describe a strategy to approach this problem, using various methods in bioinformatics and computational biology. We have used a knowledge-based approach, utilizing rapidly increasing structural data of protein-DNA complexes, to derive empirical potential functions for the specific interactions between bases and amino acids as well as for DNA conformation, from the statistical analyses on the structural data. Then these statistical potentials are used to quantify the specificity of protein-DNA recognition. The quantification of specificity has enabled us to establish the structure-function analysis of transcription factors, such as the effects of binding cooperativity on target recognition. The method is also applied to real genome sequences, predicting potential target sites. We are also using computer simulations of protein-DNA interactions and DNA conformation in order to complement the empirical method. The integration of these approaches together will provide deeper insight into the mechanism of protein-DNA recognition and improve the target prediction of transcription factors.

Binding Sites↗

PubMed2004

A simple statistical method for discriminating outer membrane proteins with better accuracy.

MOTIVATION: Discriminating outer membrane proteins from other folding types of globular and membrane proteins is an important task both for identifying outer membrane proteins from genomic sequences and for the successful prediction of their secondary and tertiary structures. RESULTS: We have systematically analyzed the amino acid composition of globular proteins from different structural classes and outer membrane proteins. We found that the residues, Glu, His, Ile, Cys, Gln, Asn and Ser, show a significant difference between globular and outer membrane proteins. Based on this information, we have devised a statistical method for discriminating outer membrane proteins from other globular and membrane proteins. Our approach correctly picked up the outer membrane proteins with an accuracy of 89% for the training set of 337 proteins. On the other hand, our method has correctly excluded the globular proteins at an accuracy of 79% in a non-redundant dataset of 674 proteins. Furthermore, the present method is able to correctly exclude alpha-helical membrane proteins up to an accuracy of 80%. These accuracy levels are comparable to other methods in the literature, and this is a simple method, which could be used for dissecting outer membrane proteins from genomic sequences. The influence of protein size, structural class and specific residues for discrimination is discussed.

Algorithms↗

PubMed2004

Look-up tables for protein solvent accessibility prediction and nearest neighbor effect analysis.

We developed dictionaries of two-, three-, and five-residue patterns in proteins and computed the average solvent accessibility of the central residues in their native proteins. These dictionaries serve as a look-up table for making subsequent predictions of solvent accessibility of amino acid residues. We find that predictions made in this way are very close to those made using more sophisticated methods of solvent accessibility prediction. We also analyzed the effect of immediate neighbors on the solvent accessibility of residues. This helps us in understanding how the same residue type may have different accessible surface areas in different proteins and in different positions of the same protein. We observe that certain residues have a tendency to increase or decrease the solvent accessibility of their neighboring residues in C- or N-terminal positions. Interestingly, the C-terminal and N-terminal neighbor residues are found to have asymmetric roles in modifying solvent accessibility of residues. As expected, similar neighbors enhance the hydrophobic or hydrophilic character of residues. Detailed look-up tables are provided on the web at www.netasa.org/look-up/.

Amino Acid Sequence↗

PubMed2004

Characteristic features of amino acid residues in coiled-coil protein structures.

Detailed analyses of protein structures provide an opportunity to understand conformation and function in terms of amino acid sequence and composition. In this work, we have systematically analyzed the characteristic features of the amino acid residues found in alpha-helical coiled-coils and, in so doing, have developed indices for their properties, conformational parameters, surrounding hydrophobicity and flexibility. As expected, there is preference for hydrophobic (Ala, Leu), positive (Lys, Arg) and negatively (Glu) charged residues in coiled-coil domains. However, the surrounding hydrophobicity of residues in coiled-coil domains is significantly less than that for residues in other regions of coiled-coil proteins. The analysis of temperature factors in coiled-coil proteins shows that the residues in these domains are more stable than those in other regions. Further, we have delineated the medium- and long-range contacts in coiled-coil domains and compared the results with those obtained for other (non-coiled-coil) parts of the same proteins and non-coiled-coil helical segments of globular proteins. The residues in coiled-coil domains are largely influenced by medium-range contacts, whereas long-range interactions play a dominant role in other regions of these same proteins as well as in non-coiled-coil helices. We have also revealed the preference of amino acid residues to form cation-pi interactions and we found that Arg is more likely to form such interactions than Lys. The parameters developed in this work can be used to understand the folding and stability of coiled-coil proteins in general.

Amino Acids↗

PubMed2004

Importance of hydrophobic cluster formation through long-range contacts in the folding transition state of two-state proteins.

Understanding the folding pathways of proteins is a challenging task. The Phi value approach provides a detailed understanding of transition-state structures of folded proteins. In this work, we have computed the hydrophobicity associated with each residue in the folded state of 16 two-state proteins and compared the Phi values of each mutant residue. We found that most of the residues with high Phi value coincide with local maximum in surrounding hydrophobicity, or have nearby residues that show such maximum in hydrophobicity, indicating the importance of hydrophobic interactions in the transition state. We have tested our approach to different structural classes of proteins, such as alpha-helical, SH3 domains of all-beta proteins, beta-sandwich, and alpha/beta proteins, and we observed a good agreement with experimental results. Further, we have proposed a hydrophobic contact network pattern to relate the Phi values with long-range contacts, which will be helpful to understand the transition-state structures of folded proteins. The present approach could be used to identify potential hydrophobic clusters that may form through long-range contacts during the transition state.

Acid Anhydride Hydrolases↗

PubMed2004

Locating the stabilizing residues in (alpha/beta)8 barrel proteins based on hydrophobicity, long-range interactions, and sequence conservation.

In nature, 1 out of every 10 proteins has an (alpha/beta)(8) (TIM)-barrel fold, and in most cases, pairwise comparisons show no sequence similarity between them. Hence, delineating the key residues that induce very different sequences to share a common fold is important for understanding the folding and stability of TIM-barrel domains. In this work, we propose a new consensus approach for locating these stabilizing residues based on long-range interactions, hydrophobicity, and conservation of amino acid residues. We have identified 957 stabilizing residues in 63 proteins from a nonredundant set of 71 TIM-barrel domains. Most of these residues are located in the 8-stranded beta-sheet, with nearly one half of them oriented toward the interior of the barrel and the other half oriented toward the surrounding alpha-helices. Several stabilizing residues are found in the N- and C-terminal loops, whereas very few appear in the alpha-helices that surround the internal beta-sheet. Further, these 957 residues are placed in 434 stabilizing segments of various sizes, and each domain contains 1-10 of these segments. We found that 8 segments per domain is the most abundant one, and two thirds of the proteins have 7-9 stabilizing segments. Finally, we verified the identified residues with experimental temperature factors and found that these residues are among the ones with less mobility in the considered proteins. We suggest that our new protocol serves as a powerful tool to identify the stabilizing residues in TIM-barrel domains, which can be used as potential candidates for studying protein folding and stability by means of protein engineering experiments.

Conserved Sequence↗

PubMed2004

Neural network-based prediction of transmembrane beta-strand segments in outer membrane proteins.

Prediction of transmembrane beta-strands in outer membrane proteins (OMP) is one of the important problems in computational chemistry and biology. In this work, we propose a method based on neural networks for identifying the membrane-spanning beta-strands. We introduce the concept of "residue probability" for assigning residues in transmembrane beta-strand segments. The performance of our method is evaluated with single-residue accuracy, correlation, specificity, and sensitivity. Our predicted segments show a good agreement with experimental observations with an accuracy level of 73% solely from amino acid sequence information. Further, the predictive power of N- and C-terminal residues in each segments, number of segments in each protein, and the influence of cutoff probability for identifying membrane-spanning beta-strands will be discussed. We have developed a Web server for predicting the transmembrane beta-strands from the amino acid sequence, and the prediction results are available at http://psfs.cbrc.jp/tmbeta-net/.

Algorithms↗

PubMed2004

Intermolecular and intramolecular readout mechanisms in protein-DNA recognition.

Protein-DNA recognition plays an essential role in the regulation of gene expression. Regulatory proteins are known to recognize specific DNA sequences directly through atomic contacts (intermolecular readout) and/or indirectly through the conformational properties of the DNA (intramolecular readout). However, little is known about the respective contributions made by these so-called direct and indirect readout mechanisms. We addressed this question by making use of information extracted from a structural database containing many protein-DNA complexes. We quantified the specificity of intermolecular (direct) readout by statistical analysis of base-amino acid interactions within protein-DNA complexes. The specificity of the intramolecular (indirect) readout due to DNA was quantified by statistical analysis of the sequence-dependent DNA conformation. Systematic comparison of these specificities in a large number of protein-DNA complexes revealed that both intermolecular and intramolecular readouts contribute to the specificity of protein-DNA recognition, and that their relative contributions vary depending upon the protein-DNA complexes. We demonstrated that combination of the intermolecular and intramolecular energies derived from the statistical analyses lead to enhanced specificity, and that the combined energy could explain experimental data on binding affinity changes caused by base mutations. These results provided new insight into the relationship between specificity and structure in the process of protein-DNA recognition, which would lead to prediction of specific protein-DNA binding sites.

Bacterial Proteins↗

PubMed2004

Role of non-covalent interactions for determining the folding rate of two-state proteins.

Understanding the factors influencing the folding rate of proteins is a challenging problem. In this work, we have analyzed the role of non-covalent interactions for the folding rate of two-state proteins by free-energy approach. We have computed the free-energy terms, hydrophobic, electrostatic, hydrogen-bonding and van der Waals free energies. The hydrophobic free energy has been divided into the contributions from different atoms, carbon, neutral nitrogen and oxygen, charged nitrogen and oxygen, and sulfur. All the free-energy terms have been related with the folding rates of 28 two-state proteins with single and multiple correlation coefficients. We found that the hydrophobic free energy due to carbon atoms and hydrogen-bonding free energy play important roles to determine the folding rate in combination with other free energies. The normalized energies with total number of residues showed better results than the total energy of the protein. The comparison of amino acid properties with free-energy terms indicates that the energetic terms explain better the folding rate than amino acid properties. Further, the combination of free energies with topological parameters yielded the correlation of 0.91. The present study demonstrates the importance of topology for determining the folding rate of two-state proteins.

Binding Sites↗

PubMed2004

Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information.

MOTIVATION: Though vitally important to cell function, the mechanism of protein-DNA binding has not yet been completely understood. We therefore analysed the relationship between DNA binding and protein sequence composition, solvent accessibility and secondary structure. Using non-redundant databases of transcription factors and protein-DNA complexes, neural network models were developed to utilize the information present in this relationship to predict DNA-binding proteins and their binding residues. RESULTS: Sequence composition was found to provide sufficient information to predict the probability of its binding to DNA with nearly 69% sensitivity at 64% accuracy for the considered proteins; sequence neighbourhood and solvent accessibility information were sufficient to make binding site predictions with 40% sensitivity at 79% accuracy. Detailed analysis of binding residues shows that some three- and five-residue segments frequently bind to DNA and that solvent accessibility plays a major role in binding. Although, binding behaviour was not associated with any particular secondary structure, there were interesting exceptions at the residue level. Over-representation of some residues in the binding sites was largely lost at the total sequence level, but a different kind of compositional preference was observed in DNA-binding proteins.

Algorithms↗

PubMed2004

ProTherm, version 4.0: thermodynamic database for proteins and mutants.

Release 4.0 of ProTherm, thermodynamic database for proteins and mutants, contains approximately 14,500 numerical data (approximately 450% of the first version) of several thermodynamic parameters along with experimental methods and conditions, and structural, functional and literature information. The sequence and structural information of proteins is connected with thermodynamic data through links between entries in Protein Data Bank, Protein Information Resource and SWISS-PROT and the data in ProTherm. We have separated the Gibbs free energy change obtained at extrapolated temperature from the data on denaturation temperature measured by the thermal denaturation method. We have added the statistics of amino acid replacements and links to homologous structures to each protein. Further, we have improved the search and display options to enhance search capability through the web interface. ProTherm is freely available at http://gibk26. bse.kyutech.ac.jp/jouhou/Protherm/protherm.html.

Animals↗