RPMS: Ramachandran plot for multiple structures

2008 ◽  
Vol 41 (1) ◽  
pp. 219-221 ◽  
Author(s):  
K. Gopalakrishnan ◽  
S. Saravanan ◽  
R. Sarani ◽  
K. Sekar
Keyword(s):  
Amino Acid ◽  
Protein Structures ◽  
Data Bank ◽  
Amino Acid Residues ◽  
Ramachandran Plot ◽  
Homologous Protein ◽  
Internet Computing ◽  
Multiple Structures ◽  
Atomic Coordinates ◽  
Local Machine

An interactive internet computing server,RPMS(Ramachandran plot for multiple structures) has been developed to visualize the Ramachandran angles of several highly homologous protein structures in a single plot. Options are provided for users to locate the amino acid residues in various regions of the plot. To perform the above, users need to enter the Protein Data Bank (PDB) identification codes. In addition, users can upload the atomic coordinates from the local machine. A Java graphics interface has been deployed and the server has been interfaced with a locally maintained PDB anonymous FTP server, which is updated weekly. The serverRPMScan be accessed through the Bioinformatics web server at http://cluster.physics.iisc.ernet.in/rpms/.

Statistical Force-Field for Structural Modeling Using Chemical Cross-Linking/mass Spectrometry Distance Constraints

2018 ◽  
Author(s):  
Allan J. R. Ferrari ◽  
Fabio C. Gozzo ◽  
Leandro Martinez
Keyword(s):  
Mass Spectrometry ◽  
Amino Acid ◽  
Force Field ◽  
Protein Structures ◽  
Protein Structure Determination ◽  
Structural Modeling ◽  
Cross Linking ◽  
Amino Acid Residues ◽  
Distance Constraints ◽  
Chemical Cross Linking

<div><p>Chemical cross-linking/Mass Spectrometry (XLMS) is an experimental method to obtain distance constraints between amino acid residues, which can be applied to structural modeling of tertiary and quaternary biomolecular structures. These constraints provide, in principle, only upper limits to the distance between amino acid residues along the surface of the biomolecule. In practice, attempts to use of XLMS constraints for tertiary protein structure determination have not been widely successful. This indicates the need of specifically designed strategies for the representation of these constraints within modeling algorithms. Here, a force-field designed to represent XLMS-derived constraints is proposed. The potential energy functions are obtained by computing, in the database of known protein structures, the probability of satisfaction of a topological cross-linking distance as a function of the Euclidean distance between amino acid residues. The force-field can be easily incorporated into current modeling methods and software. In this work, the force-field was implemented within the Rosetta ab initio relax protocol. We show a significant improvement in the quality of the models obtained relative to current strategies for constraint representation. This force-field contributes to the long-desired goal of obtaining the tertiary structures of proteins using XLMS data. Force-field parameters and usage instructions are freely available at http://m3g.iqm.unicamp.br/topolink/xlff <br></p></div><p></p><p></p>

scholarly journals Insights into the quaternary association of proteins through structure graphs: a case study of lectins

2005 ◽  
Vol 391 (1) ◽  
pp. 1-15 ◽  
Author(s):  
K. V. Brinda ◽  
Avadhesha Surolia ◽  
Sarawathi Vishveshwara
Keyword(s):  
Amino Acid ◽  
Protein Structures ◽  
Present Review ◽  
Dimensional Structure ◽  
Protein Oligomerization ◽  
Amino Acid Residues ◽  
Sequence Motifs ◽  
Structural Determinants ◽  
Legume Lectin ◽  
Quaternary Structures

The unique three-dimensional structure of both monomeric and oligomeric proteins is encoded in their sequence. The biological functions of proteins are dependent on their tertiary and quaternary structures, and hence it is important to understand the determinants of quaternary association in proteins. Although a large number of investigations have been carried out in this direction, the underlying principles of protein oligomerization are yet to be completely understood. Recently, new insights into this problem have been gained from the analysis of structure graphs of proteins belonging to the legume lectin family. The legume lectins are an interesting family of proteins with very similar tertiary structures but varied quaternary structures. Hence they have become a very good model with which to analyse the role of primary structures in determining the modes of quaternary association. The present review summarizes the results of a legume lectin study as well as those obtained from a similar analysis carried out here on the animal lectins, namely galectins, pentraxins, calnexin, calreticulin and rhesus rotavirus Vp4 sialic-acid-binding domain. The lectin structure graphs have been used to obtain clusters of non-covalently interacting amino acid residues at the intersubunit interfaces. The present study, performed along with traditional sequence alignment methods, has provided the signature sequence motifs for different kinds of quaternary association seen in lectins. Furthermore, the network representation of the lectin oligomers has enabled us to detect the residues which make extensive interactions (‘hubs’) across the oligomeric interfaces that can be targetted for interface-destabilizing mutations. The present review also provides an overview of the methodology involved in representing oligomeric protein structures as connected networks of amino acid residues. Further, it illustrates the potential of such a representation in elucidating the structural determinants of protein–protein association in general and will be of significance to protein chemists and structural biologists.

scholarly journals Possible role for a human adenovirus in the pathogenesis of celiac disease.

1984 ◽  
Vol 160 (5) ◽  
pp. 1544-1557 ◽  
Author(s):  
M F Kagnoff ◽  
R K Austin ◽  
J J Hubert ◽  
J E Bernardin ◽  
D D Kasarda
Keyword(s):  
Celiac Disease ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Monozygotic Twins ◽  
Human Adenovirus ◽  
Adenovirus Type ◽  
Data Bank ◽  
Antigenic Determinants ◽  
Amino Acid Residues ◽  
Primary Amino

Celiac disease in humans is activated by the dietary ingestion of wheat, rye, triticale, barley, and possibly oats. Gliadins in wheat and similar proteins in the other grains are known to activate disease in susceptible individuals. There is a striking association between celiac disease and HLA-B8, -DR3 and/or -DR7, and -DC3. Nonetheless, less than 0.2% of individuals with those serologic HLA specificities develop celiac disease and disease is not always concordant among monozygotic twins. We propose that additional environmental factors may be important in the pathogenesis of celiac disease. To investigate that possibility, we examined a data bank of protein sequences for other proteins that might share amino acid sequence homologies with A-gliadin, an alpha-gliadin component known to activate celiac disease and whose complete primary amino acid sequence is known. These studies demonstrate that A-gliadin shares a region of amino acid sequence homology with the 54-kD E1b protein of human adenovirus type 12 (Ad12), an adenovirus usually isolated from the intestinal tract. The region spans 12 amino acid residues, includes 8 residue identities and an identical pentapeptide, and is hydrophilic in both proteins. Antibody reactive with the 54-kD Ad12 E1b protein cross-reacts with A-gliadin, a 119 amino acid cyanogen bromide peptide of A-gliadin that spans the region of homology and a synthetic heptapeptide of A-gliadin from within the region of homology. We suggest that an encounter of the immune system with antigenic determinants produced during intestinal viral infection may be important in the pathogenesis of celiac disease.

PROTEIN METAL BINDING RESIDUE PREDICTION BASED ON NEURAL NETWORKS

2005 ◽  
Vol 15 (01n02) ◽  
pp. 71-84 ◽  
Author(s):  
CHIN-TENG LIN ◽  
KEN-LI LIN ◽  
CHIH-HSIEN YANG ◽  
I-FANG CHUNG ◽  
CHUEN-DER HUANG ◽  
...  
Keyword(s):  
Neural Networks ◽  
Amino Acid ◽  
Metal Ions ◽  
Metal Binding ◽  
Protein Structures ◽  
Direct Analysis ◽  
Sequence Information ◽  
Amino Acid Residues ◽  
Binding Residue

Over one-third of protein structures contain metal ions, which are the necessary elements in life systems. Traditionally, structural biologists were used to investigate properties of metalloproteins (proteins which bind with metal ions) by physical means and interpreting the function formation and reaction mechanism of enzyme by their structures and observations from experiments in vitro. Most of proteins have primary structures (amino acid sequence information) only; however, the 3-dimension structures are not always available. In this paper, a direct analysis method is proposed to predict the protein metal-binding amino acid residues from its sequence information only by neural networks with sliding window-based feature extraction and biological feature encoding techniques. In four major bulk elements (Calcium, Potassium, Magnesium, and Sodium), the metal-binding residues are identified by the proposed method with higher than 90% sensitivity and very good accuracy under 5-fold cross validation. With such promising results, it can be extended and used as a powerful methodology for metal-binding characterization from rapidly increasing protein sequences in the future.

scholarly journals The Potential Role of 6-gingerol and 6-shogaol as ACE Inhibitors in Silico Study

2020 ◽  
Vol 8 (2) ◽  
pp. 210
Author(s):  
Yohanes Bare ◽  
Maria Helvina ◽  
Gabriella Chandrakirana Krisnamurti ◽  
Mansur S
Keyword(s):  
Amino Acid ◽  
Angiotensin Converting Enzyme ◽  
Binding Site ◽  
Potential Role ◽  
Enzyme Inhibitor ◽  
Renin Angiotensin System ◽  
Data Bank ◽  
Amino Acid Residues ◽  
Converting Enzyme

Hypertension has become the third highest cause of death in Indonesia. The condition is correlated with angiotensin-converting enzyme (ACE), and possibly managed with the use of drugs. In addition, some natural compounds, including 6-shogaol and 6-gingerol from ginger, are used to decrease blood pressure. However, the mechanism and binding site of these compounds to ACE protein is currently unclear. This study, therefore, aims to investigate the potential role of these compounds as an angiotensin-converting enzyme inhibitor. The ACE protein was downloaded from Protein Data Bank (PDB) database with the ID: 3bkk, while the 6-shogaol (CID: 5281794) and 6-gingerol (CID: 44559528) ligands were obtained from the PubChem database. Meanwhile, molecular docking was established using HEX 8.0.0 software. The analysis examined the amino acid residues and the bonds formed from these interactions. According to the results, fourteen amino acid residues were formed by the interaction between 6-shogaol and ACE, while the interaction between 6-gingerol and ACE formed eight amino acids. Also, thirteen amino acid residues in the novelty binding site of ACE were discovered to be blocked by the ligands from ginger. Therefore, the compounds have potential roles as inhibitors, and this possibly helps to prevent regulation of the renin-angiotensin system. These interactions also formed hydrogen bonds, as well as electrostatic, unfavorable, and hydrophobic sites, making the binding stronger than others. 

Polymorphism of cow colostrum proteinase inhibitor

1981 ◽  
Vol 46 (3) ◽  
pp. 807-816 ◽  
Author(s):  
Věra Jonáková ◽  
Dana Čechová ◽  
Otakar Mach
Keyword(s):  
Amino Acid ◽  
Primary Structure ◽  
Proteinase Inhibitor ◽  
Protein Structures ◽  
Amino Acid Residues ◽  
Net Charge ◽  
C Terminus ◽  
Isoelectric Points ◽  
The Individual ◽  
Protein Moiety

Cow colostrum contains three isoinhibitors A, B, and C, which are glycoproteins. In this study isoinhibitor A was isolated and characterized and the structure of its protein moiety compared with the known protein structures of isoinhibitors B and C. It was found that the primary structure of isoinhibitor A is identical with the primary structure of isoinhibitor B except that the C-terminus of its molecule is shorter by five amino acid residues. Four discrete chromatographic forms (I-IV) with different isoelectric points (pI 3.8 - I, 4.0 - II, 4.3 - III, and 4.5 - IV) were isolated by chromatography on SE-Sephadex, Form I is identical with isoinhibitor A. Forms II, III, and IV are represented by mixtures of isoinhibitors A, B, and C with a heterogeneous carbohydrate moiety which affects the total net charge of the individual inhibitor forms.

Statistical Force-Field for Structural Modeling Using Chemical Cross-Linking/mass Spectrometry Distance Constraints

2018 ◽  
Author(s):  
Allan J. R. Ferrari ◽  
Fabio C. Gozzo ◽  
Leandro Martinez
Keyword(s):  
Mass Spectrometry ◽  
Amino Acid ◽  
Force Field ◽  
Protein Structures ◽  
Protein Structure Determination ◽  
Structural Modeling ◽  
Cross Linking ◽  
Amino Acid Residues ◽  
Distance Constraints ◽  
Chemical Cross Linking

<div><p>Chemical cross-linking/Mass Spectrometry (XLMS) is an experimental method to obtain distance constraints between amino acid residues, which can be applied to structural modeling of tertiary and quaternary biomolecular structures. These constraints provide, in principle, only upper limits to the distance between amino acid residues along the surface of the biomolecule. In practice, attempts to use of XLMS constraints for tertiary protein structure determination have not been widely successful. This indicates the need of specifically designed strategies for the representation of these constraints within modeling algorithms. Here, a force-field designed to represent XLMS-derived constraints is proposed. The potential energy functions are obtained by computing, in the database of known protein structures, the probability of satisfaction of a topological cross-linking distance as a function of the Euclidean distance between amino acid residues. The force-field can be easily incorporated into current modeling methods and software. In this work, the force-field was implemented within the Rosetta ab initio relax protocol. We show a significant improvement in the quality of the models obtained relative to current strategies for constraint representation. This force-field contributes to the long-desired goal of obtaining the tertiary structures of proteins using XLMS data. Force-field parameters and usage instructions are freely available at http://m3g.iqm.unicamp.br/topolink/xlff <br></p></div><p></p><p></p>

УРОВНИ ИЕРАРХИЧЕСКОЙ ОРГАНИЗАЦИИ БЕЛКОВЫХ ПОСЛЕДОВАТЕЛЬНОСТЕЙ. АНАЛИЗ ЭНТРОПИЙНЫХ ХАРАКТЕРИСТИК

2020 ◽  
Vol 65 (6) ◽  
pp. 1065-1071
Author(s):  
А.Н. Некрасов ◽  
◽  
Ю.П. Козмин ◽  
С.В. Козырев ◽  
Н.Г. Есипова ◽  
...  
Keyword(s):  
Mathematical Method ◽  
Amino Acid ◽  
Secondary Structure ◽  
Protein Sequences ◽  
Amino Acid Residues ◽  
Homologous Protein ◽  
Levels Of Organization

This research investigates 24 647 non-homologous protein sequences. The occurrence profile of peptapeptides was constructed for every sequence and hierarchically organized elements of various sizes were revealed by a special mathematical method in each profile. The correlations between these hierarchical elements were analyzed and it was shown that in a tested set of protein sequences there are 11 levels of protein organization with elements ranging in length from 7 to 56 amino acid residues. It was suggested that the identified levels of organization correspond to elements of a super-secondary structure with different topology.

USING RIGIDITY ANALYSIS TO PROBE MUTATION-INDUCED STRUCTURAL CHANGES IN PROTEINS

2012 ◽  
Vol 10 (03) ◽  
pp. 1242010 ◽  
Author(s):  
FILIP JAGODZINSKI ◽  
JEANNE HARDY ◽  
ILEANA STREINU
Keyword(s):  
Amino Acid ◽  
Amino Acid Substitution ◽  
Structural Changes ◽  
Protein Structures ◽  
Data Bank ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Single Amino Acid ◽  
Fast Evaluation

Predicting the effect of a single amino acid substitution on the stability of a protein structure is a fundamental task in macromolecular modeling. It has relevance to drug design and understanding of disease-causing protein variants. We present KINARI-Mutagen, a web server for performing in silico mutation experiments on protein structures from the Protein Data Bank. Our rigidity-theoretical approach permits fast evaluation of the effects of mutations that may not be easy to perform in vitro, because it is not always possible to express a protein with a specific amino acid substitution. We use KINARI-Mutagen to identify critical residues, and we show that our predictions correlate with destabilizing mutations to glycine. In two in-depth case studies we show that the mutated residues identified by KINARI-Mutagen as critical correlate with experimental data, and would not have been identified by other methods such as Solvent Accessible Surface Area measurements or residue ranking by contributions to stabilizing interactions. We also generate 48 mutants for 14 proteins, and compare our rigidity-based results against experimental mutation stability data. KINARI-Mutagen is available at http://kinari.cs.umass.edu .

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