• Title/Summary/Keyword: Protein Structure Prediction

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In silico target identification of biologically active compounds using an inverse docking simulation

  • Choi, Youngjin
    • CELLMED
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    • v.3 no.2
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    • pp.12.1-12.4
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    • 2013
  • Identification of target protein is an important procedure in the course of drug discovery. Because of complexity, action mechanisms of herbal medicine are rather obscure, unlike small-molecular drugs. Inverse docking simulation is a reverse use of molecular docking involving multiple target searches for known chemical structure. This methodology can be applied in the field of target fishing and toxicity prediction for herbal compounds as well as known drug molecules. The aim of this review is to introduce a series of in silico works for predicting potential drug targets and side-effects based on inverse docking simulations.

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

  • Md Foyzur Rahman;Rubait Hasan;Mohammad Shahangir Biswas;Jamiatul Husna Shathi;Md Faruk Hossain;Aoulia Yeasmin;Mohammad Zakerin Abedin;Md Tofazzal Hossain
    • Genomics & Informatics
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    • v.21 no.1
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    • pp.3.1-3.10
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    • 2023
  • Characterization as well as prediction of the secondary and tertiary structure of hypothetical proteins from their amino acid sequences uploaded in databases by in silico approach are the critical issues in computational biology. Severe acute respiratory syndrome-associated coronavirus (SARS-CoV), which is responsible for pneumonia alike diseases, possesses a wide range of proteins of which many are still uncharacterized. The current study was conducted to reveal the physicochemical characteristics and structures of an uncharacterized protein Q6S8D9_SARS of SARS-CoV. Following the common flowchart of characterizing a hypothetical protein, several sophisticated computerized tools e.g., ExPASy Protparam, CD Search, SOPMA, PSIPRED, HHpred, etc. were employed to discover the functions and structures of Q6S8D9_SARS. After delineating the secondary and tertiary structures of the protein, some quality evaluating tools e.g., PROCHECK, ProSA-web etc. were performed to assess the structures and later the active site was identified also by CASTp v.3.0. The protein contains more negatively charged residues than positively charged residues and a high aliphatic index value which make the protein more stable. The 2D and 3D structures modeled by several bioinformatics tools ensured that the proteins had domain in it which indicated it was functional protein having the ability to trouble host antiviral inflammatory cytokine and interferon production pathways. Moreover, active site was found in the protein where ligand could bind. The study was aimed to unveil the features and structures of an uncharacterized protein of SARS-CoV which can be a therapeutic target for development of vaccines against the virus. Further research are needed to accomplish the task.

Thermostability prediction of protein structure by using elastic network model (탄성망모델을 이용한 단백질 열안정성 해석)

  • Park, Young-Gul;Won, Chong-Jin;Jeong, Jay-I.
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.1643-1646
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    • 2008
  • In this study, an elastic network model is established in order to find dominant factors which reflect thermostability of protein structures. The connections in the elastic network model are selected with respect to the free energy between alpha-carbons, which is representatives of residues in the elastic network model. We carried out normal mode analysis and compared eigenvalues of the stiffness matrix from the elastic network model. In most cases, thermophilic proteins are observed to have higher values of lowest natural frequency than mesophiles and psychrophiles have. As a result, the thermophiles are calculated to be stiffer than other proteins in view of dynamic vibration.

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A Study on Construction of Integrated Prokaryotes Gene Prediction System (통합형 미생물 유전자 예측 시스템의 구축에 관한 연구)

  • Chang Jong-won;Ryoo Yoon-kyu;Ku Ja-hyo;Yoon Young-woo
    • Journal of the Institute of Convergence Signal Processing
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    • v.6 no.1
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    • pp.27-32
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    • 2005
  • As a large quantity of Genome sequencing has happened to be done a very much a surprising speed in short period, an automatic genome annotation process has become prerequisite. The most difficult process among with this kind of genome annotation works is to finding out the protein-coding genes within a genome. The main 2 subjects of gene prediction are Eukaryotes and Prokaryotes ; their genes have different structures, therefore, their gene prediction methods will also obviously varies. Until now, it is found that among of the 231 genome sequenced species, 200 have been found to be prokaryotes, therefore, for study of biotechnology studies, through comparative genomics, prokaryotes, rather than eukaryotes could may be more appropriate than eukaryotes. Even more, prokaryotes does not have the gene structure called an intron, so it makes the gene prediction easier. Former prokaryotes gene predictions have been shown to be 80%~ to 90% of accuracy. A recent study is aiming at 100% of gene prediction accuracy. In this paper, especially in the case of the E. coli K-12 and S. typhi genomes, gene prediction accuracy which showed 98.5% and 98.7% was more efficient than previous GLIMMER.

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Molecular docking of bioactive compounds derived from Moringa oleifera with p53 protein in the apoptosis pathway of oral squamous cell carcinoma

  • Rath, Sonali;Jagadeb, Manaswini;Bhuyan, Ruchi
    • Genomics & Informatics
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    • v.19 no.4
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    • pp.46.1-46.11
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    • 2021
  • Moringa oleifera is nowadays raising as the most preferred medicinal plant, as every part of the moringa plant has potential bioactive compounds which can be used as herbal medicines. Some bioactive compounds of M. oleifera possess potential anti-cancer properties which interact with the apoptosis protein p53 in cancer cell lines of oral squamous cell carcinoma. This research work focuses on the interaction among the selected bioactive compounds derived from M. oleifera with targeted apoptosis protein p53 from the apoptosis pathway to check whether the bioactive compound will induce apoptosis after the mutation in p53. To check the toxicity and drug-likeness of the selected bioactive compound derived from M. oleifera based on Lipinski's Rule of Five. Detailed analysis of the 3D structure of apoptosis protein p53. To analyze protein's active site by CASTp 3.0 server. Molecular docking and binding affinity were analyzed between protein p53 with selected bioactive compounds in order to find the most potential inhibitor against the target. This study shows the docking between the potential bioactive compounds with targeted apoptosis protein p53. Quercetin was the most potential bioactive compound whereas kaempferol shows poor affinity towards the targeted p53 protein in the apoptosis pathway. Thus, the objective of this research can provide an insight prediction towards M. oleifera derived bioactive compounds and target apoptosis protein p53 in the structural analysis for compound isolation and in-vivo experiments on the cancer cell line.

Backbone 1H, 15N, and 13C Resonances Assignment and Secondary Structure Prediction of SAV0506 from Staphylococcus aureus

  • Lee, In Gyun;Lee, Ki-Young;Kim, Ji-Hun;Chae, Susanna;Lee, Bong-Jin
    • Journal of the Korean Magnetic Resonance Society
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    • v.17 no.1
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    • pp.54-58
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    • 2013
  • SAV0506 is an 87 residue hypothetical protein from Staphylococcus aureus strain Mu50 and also predicted to have similar function to ribosome associated heat shock protein, Hsp 15. Hsp15 is thought to be involved in the repair mechanism of erroneously produced 50S ribosome subunit. In this report, we present the sequence specific backbone resonance assignment of SAV0506. About 82.5% of all resonances could be assigned unambiguously. By analyzing deviations of the $C{\alpha}$ and $C{\beta}$ chemical shift values, we could predict the secondary structure of SAV0506. This study is an essential step towards the structural characterization of SAV0506.

In Silico Structural and Functional Annotation of Hypothetical Proteins of Vibrio cholerae O139

  • Islam, Md. Saiful;Shahik, Shah Md.;Sohel, Md.;Patwary, Noman I.A.;Hasan, Md. Anayet
    • Genomics & Informatics
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    • v.13 no.2
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    • pp.53-59
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    • 2015
  • In developing countries threat of cholera is a significant health concern whenever water purification and sewage disposal systems are inadequate. Vibrio cholerae is one of the responsible bacteria involved in cholera disease. The complete genome sequence of V. cholerae deciphers the presence of various genes and hypothetical proteins whose function are not yet understood. Hence analyzing and annotating the structure and function of hypothetical proteins is important for understanding the V. cholerae. V. cholerae O139 is the most common and pathogenic bacterial strain among various V. cholerae strains. In this study sequence of six hypothetical proteins of V. cholerae O139 has been annotated from NCBI. Various computational tools and databases have been used to determine domain family, protein-protein interaction, solubility of protein, ligand binding sites etc. The three dimensional structure of two proteins were modeled and their ligand binding sites were identified. We have found domains and families of only one protein. The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera.

Backbone assignments of 1H, 15N and 13C resonances and secondary structure prediction of MRA1997 from Mycobacterium tuberculosis H37Rv

  • Kim, Hyojung;Kim, Yena;Lee, Ki-Young;Lee, Bong-Jin
    • Journal of the Korean Magnetic Resonance Society
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    • v.19 no.1
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    • pp.49-53
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    • 2015
  • MRA1997 is a 76-residue conserved hypothetical protein of Mycobacterium tuberculosis H37Ra, one of the most pathogenic bacterial species and the causative agent of tuberculosis. In this study, the sequence-specific backbone resonance assignment of MRA1997 was performed using NMR spectroscopy. Approximately 88.3% of the total resonances could be unambiguously assigned. By analyzing deviations of the $C{\alpha}$ and $C{\beta}$ chemical shift values, the secondary structure of MRA1997 was calculated. The result revealed that secondary structure of MRA 1997 consists of one ${\alpha}$-helix and five ${\beta}$-sheets. Our structural study will be a footstone towards the characterization of the three-dimensional structure of MRA1997.

3D Structure Prediction of Thromboxane A2 Receptor by Homology Modeling

  • Nagarajan, Santhosh Kumar;Madhavan, Thirumurthy
    • Journal of Integrative Natural Science
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    • v.8 no.1
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    • pp.75-79
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    • 2015
  • Thromboxane A2 receptors (TXA2-R) are the G protein coupled receptors localized on cell membranes and intracellular structures and play pathophysiological role in various thrombosis/hemostasis, modulation of the immune response, acute myocardial infarction, inflammatory lung disease, hypertension and nephrotic disease. TXA2 receptor antagonists have been evaluated as potential therapeutic agents for asthma, thrombosis and hypertension. The role of TXA2 in wide spectrum of diseases makes this as an important drug target. Hence in the present study, homology modeling of TXA2 receptor was performed using the crystal structure of squid rhodopsin and night blindness causing G90D rhodopsin. 20 models were generated using single and multiple templates based approaches and the best model was selected based on the validation result. We found that multiple template based approach have given better accuracy. The generated structures can be used in future for further binding site and docking analysis.

3D Structure Prediction of Human 5-Hydroxytryptamine Receptor 7 (5-HT7R)

  • Madhavan, Thirumurthy
    • Journal of Integrative Natural Science
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    • v.11 no.2
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    • pp.87-92
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    • 2018
  • 5-Hydroxytryptamine receptor 7 ($5-HT_7R$) is one of G-Protein coupled receptors, which is found to be involved in the pathophysiology of various neurological disorders including depression, sleep disorders, memory deficiency and neuropathic pain. After activation of $5-HT_7R$ by serotonin, it activates the production of the intracellular signaling molecule cyclic AMP. The availability of 3D structure of the receptor would enhance the development of new drugs. Hence, in the present study, homology modelling of human 5-hydroxytryptamine receptor 7 ($5-HT_7R$) was performed using comparative modelling (Easy Modeller) and threading (I-TASSER) approaches. The generated models were validated using Ramachandran plot and ERRAT plot and the best models were selected based on the validation results. The 3D model developed here could be useful for identifying crucial residues and further docking study.