Literature DB >> 33196841

ProThermDB: thermodynamic database for proteins and mutants revisited after 15 years.

Rahul Nikam1, A Kulandaisamy1, K Harini1, Divya Sharma1, M Michael Gromiha1.   

Abstract

ProThermDB is an updated version of the thermodynamic database for proteins and mutants (ProTherm), which has ∼31 500 data on protein stability, an increase of 84% from the previous version. It contains several thermodynamic parameters such as melting temperature, free energy obtained with thermal and denaturant denaturation, enthalpy change and heat capacity change along with experimental methods and conditions, sequence, structure and literature information. Besides, the current version of the database includes about 120 000 thermodynamic data obtained for different organisms and cell lines, which are determined by recent high throughput proteomics techniques using whole-cell approaches. In addition, we provided a graphical interface for visualization of mutations at sequence and structure levels. ProThermDB is cross-linked with other relevant databases, PDB, UniProt, PubMed etc. It is freely available at https://web.iitm.ac.in/bioinfo2/prothermdb/index.html without any login requirements. It is implemented in Python, HTML and JavaScript, and supports the latest versions of major browsers, such as Firefox, Chrome and Safari.
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Year:  2021        PMID: 33196841      PMCID: PMC7778892          DOI: 10.1093/nar/gkaa1035

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  37 in total

1.  Relationship between amino acid properties and protein stability: buried mutations.

Authors:  M M Gromiha; M Oobatake; H Kono; H Uedaira; A Sarai
Journal:  J Protein Chem       Date:  1999-07

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

Authors:  K Abdulla Bava; M Michael Gromiha; Hatsuho Uedaira; Koji Kitajima; Akinori Sarai
Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

3.  Predicting protein thermal stability changes upon point mutations using statistical potentials: Introducing HoTMuSiC.

Authors:  Fabrizio Pucci; Raphaël Bourgeas; Marianne Rooman
Journal:  Sci Rep       Date:  2016-03-18       Impact factor: 4.379

4.  MPTherm-pred: Analysis and Prediction of Thermal Stability Changes upon Mutations in Transmembrane Proteins.

Authors:  A Kulandaisamy; Jan Zaucha; Dmitrij Frishman; M Michael Gromiha
Journal:  J Mol Biol       Date:  2020-09-11       Impact factor: 5.469

5.  Catalytic inactivation of human phospholipase D2 by a naturally occurring Gly901Asp mutation.

Authors:  Yoshiji Yamada; Yoshiko Banno; Hitoshi Yoshida; Ryosuke Kikuchi; Yukihiro Akao; Takashi Murate; Yoshinori Nozawa
Journal:  Arch Med Res       Date:  2006-08       Impact factor: 2.235

6.  Modeling backbone flexibility improves protein stability estimation.

Authors:  Shuangye Yin; Feng Ding; Nikolay V Dokholyan
Journal:  Structure       Date:  2007-12       Impact factor: 5.006

Review 7.  Molecular mechanisms of disease-causing missense mutations.

Authors:  Shannon Stefl; Hafumi Nishi; Marharyta Petukh; Anna R Panchenko; Emil Alexov
Journal:  J Mol Biol       Date:  2013-07-16       Impact factor: 5.469

8.  UniProt: a worldwide hub of protein knowledge.

Authors: 
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

9.  DDGun: an untrained method for the prediction of protein stability changes upon single and multiple point variations.

Authors:  Ludovica Montanucci; Emidio Capriotti; Yotam Frank; Nir Ben-Tal; Piero Fariselli
Journal:  BMC Bioinformatics       Date:  2019-07-03       Impact factor: 3.169

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  18 in total

1.  Turning Failures into Applications: The Problem of Protein ΔΔG Prediction.

Authors:  Rita Casadio; Castrense Savojardo; Piero Fariselli; Emidio Capriotti; Pier Luigi Martelli
Journal:  Methods Mol Biol       Date:  2022

2.  Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset.

Authors:  Corrado Pancotti; Silvia Benevenuta; Giovanni Birolo; Virginia Alberini; Valeria Repetto; Tiziana Sanavia; Emidio Capriotti; Piero Fariselli
Journal:  Brief Bioinform       Date:  2022-03-10       Impact factor: 11.622

3.  Large-scale design and refinement of stable proteins using sequence-only models.

Authors:  Jedediah M Singer; Scott Novotney; Devin Strickland; Hugh K Haddox; Nicholas Leiby; Gabriel J Rocklin; Cameron M Chow; Anindya Roy; Asim K Bera; Francis C Motta; Longxing Cao; Eva-Maria Strauch; Tamuka M Chidyausiku; Alex Ford; Ethan Ho; Alexander Zaitzeff; Craig O Mackenzie; Hamed Eramian; Frank DiMaio; Gevorg Grigoryan; Matthew Vaughn; Lance J Stewart; David Baker; Eric Klavins
Journal:  PLoS One       Date:  2022-03-14       Impact factor: 3.240

Review 4.  Protein Design: From the Aspect of Water Solubility and Stability.

Authors:  Rui Qing; Shilei Hao; Eva Smorodina; David Jin; Arthur Zalevsky; Shuguang Zhang
Journal:  Chem Rev       Date:  2022-08-03       Impact factor: 72.087

Review 5.  Protein Function Analysis through Machine Learning.

Authors:  Chris Avery; John Patterson; Tyler Grear; Theodore Frater; Donald J Jacobs
Journal:  Biomolecules       Date:  2022-09-06

Review 6.  How Functional Genomics Can Keep Pace With VUS Identification.

Authors:  Corey L Anderson; Saba Munawar; Louise Reilly; Timothy J Kamp; Craig T January; Brian P Delisle; Lee L Eckhardt
Journal:  Front Cardiovasc Med       Date:  2022-07-04

7.  Spatial organization of hydrophobic and charged residues affects protein thermal stability and binding affinity.

Authors:  Fausta Desantis; Mattia Miotto; Lorenzo Di Rienzo; Edoardo Milanetti; Giancarlo Ruocco
Journal:  Sci Rep       Date:  2022-07-15       Impact factor: 4.996

8.  DDGun: an untrained predictor of protein stability changes upon amino acid variants.

Authors:  Ludovica Montanucci; Emidio Capriotti; Giovanni Birolo; Silvia Benevenuta; Corrado Pancotti; Dennis Lal; Piero Fariselli
Journal:  Nucleic Acids Res       Date:  2022-05-07       Impact factor: 19.160

9.  Structure-conditioned amino-acid couplings: How contact geometry affects pairwise sequence preferences.

Authors:  Jack Holland; Gevorg Grigoryan
Journal:  Protein Sci       Date:  2022-02-15       Impact factor: 6.725

10.  The 2021 Nucleic Acids Research database issue and the online molecular biology database collection.

Authors:  Daniel J Rigden; Xosé M Fernández
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

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