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Journal articles on the topic 'Ramachandran plot'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Sheik, S. S., P. Sundararajan, A. S. Z. Hussain, and K. Sekar. "Ramachandran plot on the web." Bioinformatics 18, no. 11 (2002): 1548–49. http://dx.doi.org/10.1093/bioinformatics/18.11.1548.

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2

Carugo, Oliviero, and Kristina Djinović-Carugo. "A proteomic Ramachandran plot (PRplot)." Amino Acids 44, no. 2 (2012): 781–90. http://dx.doi.org/10.1007/s00726-012-1402-z.

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3

Iwaoka, M., M. Okada, and S. Tomoda. "Quantum Chemical Study of Ramachandran Plot." Seibutsu Butsuri 39, supplement (1999): S115. http://dx.doi.org/10.2142/biophys.39.s115_1.

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4

K. Gopalakrishnan, G. Sowmiya, S. S. Sheik, and K. Sekar. "Ramachandran Plot on The Web (2.0)." Protein & Peptide Letters 14, no. 7 (2007): 669–71. http://dx.doi.org/10.2174/092986607781483912.

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5

Gopalakrishnan, K., S. Saravanan, R. Sarani, and K. Sekar. "RPMS: Ramachandran plot for multiple structures." Journal of Applied Crystallography 41, no. 1 (2008): 219–21. http://dx.doi.org/10.1107/s0021889807053708.

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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

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6

Mannige, Ranjan V. "An exhaustive survey of regular peptide conformations using a new metric for backbone handedness (h)." PeerJ 5 (May 16, 2017): e3327. http://dx.doi.org/10.7717/peerj.3327.

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The Ramachandran plot is important to structural biology as it describes a peptide backbone in the context of its dominant degrees of freedom—the backbone dihedral angles φ and ψ (Ramachandran, Ramakrishnan & Sasisekharan, 1963). Since its introduction, the Ramachandran plot has been a crucial tool to characterize protein backbone features. However, the conformation or twist of a backbone as a function of φ and ψ has not been completely described for both cis and trans backbones. Additionally, little intuitive understanding is available about a peptide’s conformation simply from knowing th

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7

Zhou, Alice Qinhua, Corey S. O'Hern, and Lynne Regan. "Revisiting the Ramachandran plot from a new angle." Protein Science 20, no. 7 (2011): 1166–71. http://dx.doi.org/10.1002/pro.644.

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8

Hollingsworth, Scott A., and P. Andrew Karplus. "A fresh look at the Ramachandran plot and the occurrence of standard structures in proteins." BioMolecular Concepts 1, no. 3-4 (2010): 271–83. http://dx.doi.org/10.1515/bmc.2010.022.

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AbstractThe Ramachandran plot is among the most central concepts in structural biology, seen in publications and textbooks alike. However, with the increasing numbers of known protein structures and greater accuracy of ultra-high resolution protein structures, we are still learning more about the basic principles of protein structure. Here, we use high-fidelity conformational information to explore novel ways, such as geo-style and wrapped Ramachandran plots, to convey some of the basic aspects of the Ramachandran plot and of protein conformation. We point out the pressing need for a standard

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9

Balasco, Nicole, Luciana Esposito, Alfonso De Simone, and Luigi Vitagliano. "Local Backbone Geometry Plays a Critical Role in Determining Conformational Preferences of Amino Acid Residues in Proteins." Biomolecules 12, no. 9 (2022): 1184. http://dx.doi.org/10.3390/biom12091184.

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The definition of the structural basis of the conformational preferences of the genetically encoded amino acid residues is an important yet unresolved issue of structural biology. In order to gain insights into this intricate topic, we here determined and compared the amino acid propensity scales for different (φ, ψ) regions of the Ramachandran plot and for different secondary structure elements. These propensities were calculated using the Chou–Fasman approach on a database of non-redundant protein chains retrieved from the Protein Data Bank. Similarities between propensity scales were evalua

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10

Porter, Lauren L., and George D. Rose. "Redrawing the Ramachandran plot after inclusion of hydrogen-bonding constraints." Proceedings of the National Academy of Sciences 108, no. 1 (2010): 109–13. http://dx.doi.org/10.1073/pnas.1014674107.

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A protein backbone has two degrees of conformational freedom per residue, described by its φ,ψ-angles. Accordingly, the energy landscape of a blocked peptide unit can be mapped in two dimensions, as shown by Ramachandran, Sasisekharan, and Ramakrishnan almost half a century ago. With atoms approximated as hard spheres, the eponymous Ramachandran plot demonstrated that steric clashes alone eliminate ¾ of φ,ψ-space, a result that has guided all subsequent work. Here, we show that adding hydrogen-bonding constraints to these steric criteria eliminates another substantial region of φ,ψ-space for a

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11

Chen, Y. W. "A program to generate the Ramachandran plot using Microsoft Excel." Journal of Applied Crystallography 27, no. 4 (1994): 660–61. http://dx.doi.org/10.1107/s0021889893014153.

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12

Porter, Lauren L., and George D. Rose. "Comment on “Revisiting the Ramachandran plot from a new angle”." Protein Science 20, no. 11 (2011): 1771–73. http://dx.doi.org/10.1002/pro.724.

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13

P., Praveen Reddy. "Modeling and validation of L-asparaginase enzyme, an anticancer agent using the tools of computational biology." International Journal of Research in Medical Sciences 8, no. 1 (2019): 211. http://dx.doi.org/10.18203/2320-6012.ijrms20195909.

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Background: The L-Asparaginase is a medically important drug. The L-Asparaginase enzyme, an anticancer agent produced by microorganisms is used for the treatment of patients suffering from lymphoma and leukemia. The L-Asparaginase is economical and its administration is easy when compared to other commercial drugs available in market. Many microbes have been reported to produce the L-Asparaginase.Methods: In the present work the sequence of L-Asparaginase enzyme protein was obtained from the Universal Protein Resource (UNIPROT) server. The sequence of L-Asparaginase was used to generate 3-D mo

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14

KOLASKAR, A. S., and SANGEETA SAWANT. "Prediction of conformational states of amino acids using a Ramachandran plot." International Journal of Peptide and Protein Research 47, no. 1-2 (2009): 110–16. http://dx.doi.org/10.1111/j.1399-3011.1996.tb00817.x.

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15

Parchaňský, Václav, Josef Kapitán, Jakub Kaminský, Jaroslav Šebestík, and Petr Bouř. "Ramachandran Plot for Alanine Dipeptide as Determined from Raman Optical Activity." Journal of Physical Chemistry Letters 4, no. 16 (2013): 2763–68. http://dx.doi.org/10.1021/jz401366j.

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16

Malika, Bourjila, El Gridani Abderrahmane, Tijar Rachida, El Merbouh Brahim, and Drissi El Bouzaidi Rachid. "Theoretical investigation of Ramachandran plot of N-formyl-L-alanine-amide." Chemistry International 4, no. 4 (2018): 216–20. https://doi.org/10.5281/zenodo.1475389.

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The full conformational space of N-formyl-L-alanine-amide was explored by the semi-empirical method AM1 coupled to the Multi Niche Crowding (MNC) genetic algorithm implemented in a package of programs developed in our laboratory. The structural and energy analysis of the resulting conformational space E(,ψ) exhibits 5 regions or minima ɣL, ɣD, ɛL, D and αD. The technique provides better detection of local and global minima within a reasonable time.

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17

Grygorenko, Oleksandr O., Daryna Demenko, Dmitry M. Volochnyuk, and Igor V. Komarov. "Following Ramachandran 2: exit vector plot (EVP) analysis of disubstituted saturated rings." New Journal of Chemistry 42, no. 11 (2018): 8355–65. http://dx.doi.org/10.1039/c7nj05015a.

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18

Hooft, Rob W. W., Chris Sander, and Gerrit Vriend. "Objectively judging the quality of a protein structure from a Ramachandran plot." Bioinformatics 13, no. 4 (1997): 425–30. http://dx.doi.org/10.1093/bioinformatics/13.4.425.

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19

Serov, A. E., E. R. Odintzeva, I. V. Uporov, and V. I. Tishkov. "Use of Ramachandran Plot for Increasing Thermal Stability of Bacterial Formate Dehydrogenase." Biochemistry (Moscow) 70, no. 7 (2005): 804–8. http://dx.doi.org/10.1007/s10541-005-0187-z.

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20

Zhou, Alice Qinhua, Corey S. O'Hern, and Lynne Regan. "Reply to: Comment on “Revisiting the Ramachandran plot from a new angle”." Protein Science 20, no. 11 (2011): 1774. http://dx.doi.org/10.1002/pro.722.

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21

Momen, Roya, Alireza Azizi, Lingling Wang та ін. "Exploration of the forbidden regions of the Ramachandran plot (ϕ-ψ) with QTAIM". Phys. Chem. Chem. Phys. 19, № 38 (2017): 26423–34. http://dx.doi.org/10.1039/c7cp05124g.

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Left: Response β is defined as: β = arccos(e̲<sub>2</sub>·y̲) with β* = arccos(e̲<sub>1</sub>·y̲). Right: QTAIM interpreted Ramachandran plots {(β<sub>ϕ</sub>,β<sub>ϕ</sub>*)-(β<sub>ψ</sub>,β<sub>ψ</sub>*)} ‘-’ is a hyphen and not a subtraction sign. Pale green and dark green crosses indicate the glycine, pink and red pluses represent the remaining amino acids (a.a.) in the magainin peptide structure.

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22

Malagón Bernal, Rafael Eduardo, Manuel Alejandro Fernández Navas, and Orlando Emilio Acevedo Sarmiento. "Modelo molecular teórico del receptor serotoninérgico 5HT2A acoplado a proteína G." Universitas Scientiarum 17, no. 2 (2012): 119. http://dx.doi.org/10.11144/javeriana.sc17-2.tmmo.

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<strong>Objective</strong> Build a theoretical molecular model of the tertiary structure of the Homo sapiens 5HT2A receptor from experimentally obtained structures as templates. <strong>Materials</strong> <strong>and methods</strong> In the construction of the theoretical model we considered the protocol established by Ballesteros and Weinstein for the construction of the G-protein coupled receptor, by the alignment of the amino acid sequence, hydrophobicity profiles, refinement of loops by spatial restrictions and energy minimization with the force field OP

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23

Tam, Benjamin, Zixin Qin, Bojin Zhao, Siddharth Sinha, Chon Lok Lei, and San Ming Wang. "Classification of MLH1 Missense VUS Using Protein Structure-Based Deep Learning-Ramachandran Plot-Molecular Dynamics Simulations Method." International Journal of Molecular Sciences 25, no. 2 (2024): 850. http://dx.doi.org/10.3390/ijms25020850.

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Pathogenic variation in DNA mismatch repair (MMR) gene MLH1 is associated with Lynch syndrome (LS), an autosomal dominant hereditary cancer. Of the 3798 MLH1 germline variants collected in the ClinVar database, 38.7% (1469) were missense variants, of which 81.6% (1199) were classified as Variants of Uncertain Significance (VUS) due to the lack of functional evidence. Further determination of the impact of VUS on MLH1 function is important for the VUS carriers to take preventive action. We recently developed a protein structure-based method named “Deep Learning-Ramachandran Plot-Molecular Dynam

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24

SZABADKA, ZOLTÁN, RAFAEL ÖRDÖG, and VINCE GROLMUSZ. "THE RAMACHANDRAN MAP OF MORE THAN 6,500 PERFECT POLYPEPTIDE CHAINS." Biophysical Reviews and Letters 02, no. 03n04 (2007): 267–71. http://dx.doi.org/10.1142/s1793048007000519.

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The Protein Data Bank (PDB) is the most important depository of protein structural information, containing more than 45,000 deposited entries today. Because of its inhomogeneous structure, its fully automated processing is almost impossible. In a previous work, we cleaned and re-structured the entries in the Protein Data Bank, and from the result we have built the RS-PDB database. Using the RS-PDB database, we draw a Ramachandran-plot from 6,593 "perfect" polypeptide chains found in the PDB, containing 1,192,689 residues. This is a more than tenfold increase in the size of data analyzed before

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25

Gromiha, M. Michael, M. Oobatake, H. Kono, H. Uedaira, and A. Sarai. "Importance of Mutant Position in Ramachandran Plot for Predicting Protein Stability upon Surface Mutations." Seibutsu Butsuri 40, supplement (2000): S117. http://dx.doi.org/10.2142/biophys.40.s117_2.

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26

Gopukumar, S. T., Sreeya G. Nair, R. Radha, N. V. Sugathan, Anooj E. S, and Lekshmi Gangadhar. "Three dimensional structure modeling and ramachandran plot analysis of autographa californica nucleopolyhdro viral protein." Annals of Tropical Medicine and Public Health 23, no. 06 (2020): 207–14. http://dx.doi.org/10.36295/asro.2020.23626.

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27

Gromiha, M. Michael, Motohisa Oobatake, Hidetoshi Kono, Hatsuho Uedaira, and Akinori Sarai. "Importance of mutant position in Ramachandran plot for predicting protein stability of surface mutations." Biopolymers 64, no. 4 (2002): 210–20. http://dx.doi.org/10.1002/bip.10125.

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28

Jiang, Zhongming, Malgorzata Biczysko, and Nigel W. Moriarty. "Accurate geometries for “Mountain pass” regions of the Ramachandran plot using quantum chemical calculations." Proteins: Structure, Function, and Bioinformatics 86, no. 3 (2018): 273–78. http://dx.doi.org/10.1002/prot.25451.

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29

Cao, Chen, Lincong Wang, Xiaoyang Chen, Shuxue Zou, Guishen Wang, and Shutan Xu. "Amino Acids in Nine Ligand-Prefer Ramachandran Regions." BioMed Research International 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/757495.

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Several secondary structures, such asπ-helix and left-handed helix, have been frequently identified at protein ligand-binding sites. A secondary structure is considered to be constrained to a specific region of dihedral angles. However, a comprehensive analysis of the correlation between main chain dihedral angles and ligand-binding sites has not been performed. We undertook an extensive analysis of the relationship between dihedral angles in proteins and their distance to ligand-binding sites, frequency of occurrence, molecular potential energy, amino acid composition, van der Waals contacts,

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30

Schweitzer-Stenner, Reinhard. "Exploring Nearest Neighbor Interactions and Their Influence on the Gibbs Energy Landscape of Unfolded Proteins and Peptides." International Journal of Molecular Sciences 23, no. 10 (2022): 5643. http://dx.doi.org/10.3390/ijms23105643.

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The Flory isolated pair hypothesis (IPH) is one of the corner stones of the random coil model, which is generally invoked to describe the conformational dynamics of unfolded and intrinsically disordered proteins (IDPs). It stipulates, that individual residues sample the entire sterically allowed space of the Ramachandran plot without exhibiting any correlations with the conformational dynamics of its neighbors. However, multiple lines of computational, bioinformatic and experimental evidence suggest that nearest neighbors have a significant influence on the conformational sampling of amino aci

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31

Kumar, Mayank, та R. S. Rathore. "RamPlot: a webserver to draw 2D, 3D and assorted Ramachandran (φ, ψ) maps". Journal of Applied Crystallography 58, № 2 (2025): 630–36. https://doi.org/10.1107/s1600576725001669.

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The Ramachandran steric map of torsion angles (φ, ψ) introduced in 1963 has been widely used for protein structure validation and model building. Many developments in the field have made it essential to develop a utility to plot assorted types of maps for the following specific reasons: (i) to investigate different types (Gly, Val/Ile, pre/trans/cis-Pro and general) of 2D and 3D maps, addressing the diverse steric environments and frequency distribution of conformations, (ii) to examine polypeptides containing non-standard residues, (iii) for better visualization and analysis of conformational

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32

Ho, Bosco K., Annick Thomas та Robert Brasseur. "Revisiting the Ramachandran plot: Hard-sphere repulsion, electrostatics, and H-bonding in the α-helix". Protein Science 12, № 11 (2009): 2508–22. http://dx.doi.org/10.1110/ps.03235203.

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33

Abubakar, Hassana, Yakubu Ndatsu, Achimugu Dickson Musa, et al. "Three-dimensional structure and functional studies of neopullulanase from Thermus brockianus." Chemical and Environmental Science Archive 03, no. 02 (2023): 24–28. http://dx.doi.org/10.47587/cesa.2023.3201.

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The structural guided-rational design has been suggested to meet the demand for pullulanase in starch industries. Neopullulanase (EC 3.2.1.135), a pullulan hydrolase type I belonging to the alpha-amylase family that hydrolysis α -1,4-glucosidic bonds in pullulan to produce panose is one such enzyme that can be manipulated. Therefore, this study aimed at modeling three 3- dimensional structures of neopullulanase from Thermus brockianus, a thermophilic bacteria belonging to the thermus genus. The multiple sequence alignment was carried out with Clustal Omega while the domain and 3D structure of

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34

Pandit, Rakesh K. R., Dinesh Gupta, and Tapan K. Mukherjee. "IDENTIFICATION OF POTENTIAL SALMONELLA TYPHI BETA-LACTAMASE TEM 1 INHIBITORS USING PEPTIDOMIMETICS, VIRTUAL SCREENING, AND MOLECULAR DYNAMICS SIMULATIONS." International Journal of Pharmacy and Pharmaceutical Sciences 10, no. 1 (2018): 91. http://dx.doi.org/10.22159/ijpps.2018v10i1.21520.

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Objective: The purpose of this study was to identify a potential peptidomimetic S. typhi Beta-lactamase TEM 1 inhibitor to tackle the antibiotic resistance among S. typhi.Methods: The potential peptidomimetic inhibitor was identified by in silico docking of the small peptide WFRKQLKW with S. typhi Beta-lactamase TEM 1. The 3D coordinate geometry of the residues of small peptide interacting with the active site of the receptor was generated and mimics were identified using PEP: MMs: MIMIC server. All the identified mimics were docked at the active site of the receptor using Autodock 4.2 and the

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35

Torshin, Ivan Yu, Natalya G. Esipova та Vladimir G. Tumanyan. "Alternatingly twisted β-hairpins and nonglycine residues in the disallowed II′ region of the Ramachandran plot". Journal of Biomolecular Structure and Dynamics 32, № 2 (2013): 198–208. http://dx.doi.org/10.1080/07391102.2012.759451.

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36

Maxwell, Peter I., and Paul L. A. Popelier. "Unfavorable regions in the ramachandran plot: Is it really steric hindrance? The interacting quantum atoms perspective." Journal of Computational Chemistry 38, no. 29 (2017): 2459–74. http://dx.doi.org/10.1002/jcc.24904.

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37

Gupta, Nisha, Jai Shankar Paul та S. K. Jadhav. "In Silico Approaches to Reveal Structural Insights, Stability and Catalysis of Bacillus-Derived α-Amylases Prior to Advance Lab Experiments". Journal of Computational Biophysics and Chemistry 20, № 08 (2021): 853–67. http://dx.doi.org/10.1142/s2737416521500538.

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[Formula: see text]-amylase is the most widely used Glycoside Hydrolase (GH) in industries for decades. It randomly cleaves the [Formula: see text]-D-(1, 4) glucosidic bonds of [Formula: see text]-polysaccharides (starch and glycogen) to release glucose and short-chain oligosaccharides. Substantial advances have taken place in research related to [Formula: see text]-amylases. However, bioinformatics study needs a little more exploration before conducting wet-lab experiments. We aimed to perform a comparative structure-function relationship study of 10 different Bacillus-derived [Formula: see t

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38

Coe, James V., Steven V. Nystrom, Zhaomin Chen, et al. "Extracting Infrared Spectra of Protein Secondary Structures Using a Library of Protein Spectra and the Ramachandran Plot." Journal of Physical Chemistry B 119, no. 41 (2015): 13079–92. http://dx.doi.org/10.1021/acs.jpcb.5b08052.

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39

Krebs, Frederik C., and Mikkel Jørgensen. "On the Conformational Properties of [n]Cyclophanes. A New Application of the Ramachandran Plot Using Crystallographic Data." Journal of Organic Chemistry 65, no. 12 (2000): 3846–49. http://dx.doi.org/10.1021/jo000166i.

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40

Nazari-Robati, Mahdieh, Khosro Khajeh, Mahdi Aminian, Nasrin Mollania, and Abolfazl Golestani. "Enhancement of thermal stability of chondroitinase ABC I by site-directed mutagenesis: An insight from Ramachandran plot." Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics 1834, no. 2 (2013): 479–86. http://dx.doi.org/10.1016/j.bbapap.2012.11.002.

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41

Tam, Benjamin, Siddharth Sinha, and San Ming Wang. "Combining Ramachandran plot and molecular dynamics simulation for structural-based variant classification: Using TP53 variants as model." Computational and Structural Biotechnology Journal 18 (2020): 4033–39. http://dx.doi.org/10.1016/j.csbj.2020.11.041.

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42

Keating, Kevin S., Elisabeth L. Humphris, and Anna Marie Pyle. "A new way to see RNA." Quarterly Reviews of Biophysics 44, no. 4 (2011): 433–66. http://dx.doi.org/10.1017/s0033583511000059.

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AbstractUnlike proteins, the RNA backbone has numerous degrees of freedom (eight, if one counts the sugar pucker), making RNA modeling, structure building and prediction a multidimensional problem of exceptionally high complexity. And yet RNA tertiary structures are not infinite in their structural morphology; rather, they are built from a limited set of discrete units. In order to reduce the dimensionality of the RNA backbone in a physically reasonable way, a shorthand notation was created that reduced the RNA backbone torsion angles to two (η and θ, analogous to φ and ψ in proteins). When th

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43

Yashvardhini, Niti. "Genome sequence analysis of nsp15 from SARS-CoV-2." Bioinformation 18, no. 4 (2022): 432–37. http://dx.doi.org/10.6026/97320630018432.

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SARS-CoV-2 (Severe Acute Respiratory Syndrome), a causative agent of COVID-19 disease created a pandemic situation worldwide. Nsp15 is a uridine specific endoribonuclease encoded by the genome of SARS-CoV-2. It plays important role in processing viral RNA and, thus evades the host immune system. Therefore, it is of interest to identify mutants of nsp15 amongst Asian SARS-CoV-2 isolates, where a total of 1795 mutations, from 7793 sequences of Asia submitted till 31st January 2022, amongst which A231V, H234Y, K109N, K259R and S261A mutations were found frequent. Hence, we report data on the pred

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44

Vyshnavi, Hima, Aswin Mohan, Shahanas Naisam, Suvanish Kumar, and Nidhin Sreekumar. "Homology Modeling and Evaluation of Sars-Cov-2 Spike Protein Mutant." International Journal of Quantitative Structure-Property Relationships 6, no. 4 (2021): 38–55. http://dx.doi.org/10.4018/ijqspr.2021100103.

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Severe acute respiratory syndrome coronavirus 2 (SARS‐Cov-2), a global pandemic, affected the world, increasing every day. A mutated variant D614G, showing more virulence and transmission, was studied for forecasting the emergence of more virulent and pathogenic viral strains. This study focuses on structure modeling and validation. Characterization of proteins homologous to wild spike protein was done, and homology models of the mutated variant were modeled using these proteins. Validation of models was done using Ramachandran plot and ERRAT plot. Molecular dynamics simulation was used to val

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45

Simon, M. Longela* Håvard J. Haugen Jiri Vymetal and Jiri Vondrášek. "SERINE PHOSPHORYLATION EFFECT ON SECONDARY STRUCTURE PREDICTION OF INTRINSICALLY UNSTRUCTURED AND ORDERED STRUCTURED PENTAPEPTIDES BY RAMACHANDRAN ANALYSIS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 7 (2016): 864–72. https://doi.org/10.5281/zenodo.57943.

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Many proteins associated with cell signalling pathways are often targets of post-translational modifications such as phosphorylation, glycosylation, ubiquitination, nitrosylation, methylation, acetylation, lipidation and proteolysis. Such modifications can lead to the induction or disruption of secondary structural elements of the modified protein. This paper describes the structural behaviour of a set of intrinsically disordered peptides (IDP) and ordered structured peptides (OP) modified by phosphorylation on a serine residue. These pentapeptides (IDP and OP) derived from fragmentation of pr

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46

Adegoke, Afeez Babatunde. "Molecular Dynamic (MD) Simulation and Modeling the Bio-molecular Structure of Human UDP glucose -6-dehydrogenase Isoform 1 (hUGDH) Related to Prostate Cancer." BASRA JOURNAL OF SCIENCE 38, no. 3 (2020): 448–66. http://dx.doi.org/10.29072/basjs.202036.

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Computational methods were used to investigate both the physical and chemical properties of UDP-glucose 6-dehydrogenase (hUGDH). Secondary structure analysis of the query model was done using the Self-Optimized Prediction method With Alignment (SOPMA), the secondary structure predictions comprise of 40.69% Alpha helixes (Hh), 17.61% Extended strand (Ee), 7.69% Beta turn (Tt) and 34.01% of Random coil (Cc) with aliphatic index of 90.00 and instability index of 33.26 which classify the protein model to be thermally stable irrespective of it environment. Comparative modeling was used to predict a

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Valli S, Abiraami, and Mythili T. "BIOINFORMATIC STUDY OF AN ANTITUMOR PROTEIN, AZURIN." Asian Journal of Pharmaceutical and Clinical Research 11, no. 6 (2018): 169. http://dx.doi.org/10.22159/ajpcr.2018.v11i6.23339.

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Objective: The main objective of this study is to analyze the structure and function of an antitumor protein, azurin, thereby giving validation to the protein structure and existing physicochemical properties in the anticancer protein which are responsible for the anticancer activity.Methods: Protein sequence analysis was done using Basic Local Alignment Search Tool (BLAST) with ten different randomly selected species of Pseudomonas obtained from GenBank. The physicochemical properties, prediction of secondary structure, identification of motifs and domains, three-dimensional (3-D) structure o

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Widjaja, Vianney, Albert Lim, Benedicta Aini, Gabrielle Audrey Gandasasmita, Jeremie Theddy Darmawan, and Arli Aditya Parikesit. "Identification of Uncharacterized Plasmodium falciparum Proteins via In-silico Analysis." BIOEDUSCIENCE 6, no. 2 (2022): 198–210. http://dx.doi.org/10.22236/j.bes/628770.

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Background: Numerous types of research on malaria were done over a long period of time but there are still some unknowns. However, it is globally known that malaria is caused by the Plasmodium parasite, mainly and most lethally by Plasmodium falciparum. The purpose of this research is to understand the structure and function of three uncharacterized P. falciparum proteins (PF3D7_1468000, PF3D7_1147400, PF3D7_1351100) using bioinformatic methods in hopes to learn more about malaria. Methods: The three uncharacterized P. falciparum proteins were inserted into Phyre2 for knowing the protein homol

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Akanksha, Mishra, Sairkar Pramod, Silawat Nipun, Maruf Khan Mohd., and Kothari Anil. "Structural Homology Modeling of C-Terminal Domain of the Dystrophin Protein: An in-Silico Approach." Structural Homology Modeling of C-Terminal Domain of the Dystrophin Protein: An in-Silico Approach 9, no. 1 (2024): 8. https://doi.org/10.5281/zenodo.10639763.

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Dystrophin is one of the most significant and well-researched cytoskeletal proteins that is prominently expressed in skeletal and cardiac muscles. It is a large 400-kD protein, which is encoded by the largest gene in the human body- DMD gene. A significant decrease in dystrophin levels in muscles results in a gradual and severe skeletal muscular weakening. Lack of dystrophin results in muscular dystrophies such as DMD (Duchenne muscular dystrophy) and BMD (Becker muscular dystrophy. Understanding the dystrophin protein's structure is crucial for developing a cure for the disease. Comprehensive

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Bhatt, Tarun K. "Structural Characterization of Histone Deacetylase from Plasmodium Falciparum." Asian Journal of Science and Applied Technology 1, no. 2 (2012): 28–30. http://dx.doi.org/10.51983/ajsat-2012.1.2.733.

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Histone deacetylase (HDAC) is the key enzyme responsible for epigenetic regulation of an organism. This protein has been involved in transcriptional regulation of many proteins associated with chromatin remodelling. Homologs of histone deacetylase are also found in malaria parasite Plasmodium falciparum where it plays major role in regulation of key pathways of parasite. In this study, we determined the three-dimensional structure of histone deacetylase from Plasmodium falciparum (PfHDAC) by using homology modelling tools available at Swiss Modeller server and Modweb. Modelled structure was al

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