Literature DB >> 30252159

DelPhiPKa: Including salt in the calculations and enabling polar residues to titrate.

Swagata Pahari1, Lexuan Sun1, Sankar Basu1, Emil Alexov1.   

Abstract

DelPhiPKa is a widely used and unique approach to compute pKa 's of ionizable groups that does not require molecular surface to be defined. Instead, it uses smooth Gaussian-based dielectric function to treat computational space via Poisson-Boltzmann equation (PBE). Here, we report an expansion of DelPhiPKa functionality to enable inclusion of salt in the modeling protocol. The method considers the salt mobile ions in solvent phase without defining solute-solvent boundary. Instead, the ions are penalized to enter solute interior via a desolvation penalty term in the Boltzmann factor in the framework of PBE. Hence, the concentration of ions near the protein is balanced by the desolvation penalty and electrostatic interactions. The study reveals that correlation between experimental and calculated pKa 's is improved significantly by taking into consideration the presence of salt. Furthermore, it is demonstrated that DelphiPKa reproduces the salt sensitivity of experimentally measured pKa 's. Another new development of DelPhiPKa allows for computing the pKa 's of polar residues such as cysteine, serine, threonine and tyrosine. With this regard, DelPhiPKa is benchmarked against experimentally measured cysteine and tyrosine pKa 's and for cysteine it is shown to outperform other existing methods (DelPhiPKa RMSD of 1.73 vs RMSD between 2.40 and 4.72 obtained by other existing pKa prediction methods).
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  Gaussian-based dielectric function; Poisson-Boltzmann equation; electrostatics; pKa's; proteins; salt concentration

Mesh:

Substances:

Year:  2018        PMID: 30252159      PMCID: PMC6294708          DOI: 10.1002/prot.25608

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  40 in total

1.  Improving macromolecular electrostatics calculations.

Authors:  J E Nielsen; K V Andersen; B Honig; R W Hooft; G Klebe; G Vriend; R C Wade
Journal:  Protein Eng       Date:  1999-08

Review 2.  What are the dielectric "constants" of proteins and how to validate electrostatic models?

Authors:  C N Schutz; A Warshel
Journal:  Proteins       Date:  2001-09-01

3.  A summary of the measured pK values of the ionizable groups in folded proteins.

Authors:  Gerald R Grimsley; J Martin Scholtz; C Nick Pace
Journal:  Protein Sci       Date:  2009-01       Impact factor: 6.725

4.  Very fast prediction and rationalization of pKa values for protein-ligand complexes.

Authors:  Delphine C Bas; David M Rogers; Jan H Jensen
Journal:  Proteins       Date:  2008-11-15

Review 5.  Calculations of electrostatic interactions in biological systems and in solutions.

Authors:  A Warshel; S T Russell
Journal:  Q Rev Biophys       Date:  1984-08       Impact factor: 5.318

6.  The determinants of pKas in proteins.

Authors:  J Antosiewicz; J A McCammon; M K Gilson
Journal:  Biochemistry       Date:  1996-06-18       Impact factor: 3.162

7.  Salt effects on ionization equilibria of histidines in myoglobin.

Authors:  Y H Kao; C A Fitch; S Bhattacharya; C J Sarkisian; J T Lecomte; B García-Moreno E
Journal:  Biophys J       Date:  2000-09       Impact factor: 4.033

8.  Empirical parametrization of pK values for carboxylic acids in proteins using a genetic algorithm.

Authors:  Raquel Godoy-Ruiz; Raul Perez-Jimenez; Maria M Garcia-Mira; Isabel M Plaza del Pino; Jose M Sanchez-Ruiz
Journal:  Biophys Chem       Date:  2004-12-23       Impact factor: 2.352

9.  pKa predictions for proteins, RNAs, and DNAs with the Gaussian dielectric function using DelPhi pKa.

Authors:  Lin Wang; Lin Li; Emil Alexov
Journal:  Proteins       Date:  2015-10-16

10.  Charge-charge interactions are key determinants of the pK values of ionizable groups in ribonuclease Sa (pI=3.5) and a basic variant (pI=10.2).

Authors:  Douglas V Laurents; Beatrice M P Huyghues-Despointes; Marta Bruix; Richard L Thurlkill; David Schell; Stephanie Newsom; Gerald R Grimsley; Kevin L Shaw; Saul Treviño; Manuel Rico; James M Briggs; Jan M Antosiewicz; J Martin Scholtz; C Nick Pace
Journal:  J Mol Biol       Date:  2003-01-31       Impact factor: 5.469

View more
  13 in total

Review 1.  Cysteine Oxidation in Proteins: Structure, Biophysics, and Simulation.

Authors:  Diego Garrido Ruiz; Angelica Sandoval-Perez; Amith Vikram Rangarajan; Emma L Gunderson; Matthew P Jacobson
Journal:  Biochemistry       Date:  2022-09-26       Impact factor: 3.321

2.  Polyamine blockade and binding energetics in the MthK potassium channel.

Authors:  Antonio Suma; Daniele Granata; Andrew S Thomson; Vincenzo Carnevale; Brad S Rothberg
Journal:  J Gen Physiol       Date:  2020-07-06       Impact factor: 4.086

3.  Modeling Electrostatic Force in Protein-Protein Recognition.

Authors:  H B Mihiri Shashikala; Arghya Chakravorty; Emil Alexov
Journal:  Front Mol Biosci       Date:  2019-09-25

4.  DelPhi Suite: New Developments and Review of Functionalities.

Authors:  Chuan Li; Zhe Jia; Arghya Chakravorty; Swagata Pahari; Yunhui Peng; Sankar Basu; Mahesh Koirala; Shailesh Kumar Panday; Marharyta Petukh; Lin Li; Emil Alexov
Journal:  J Comput Chem       Date:  2019-06-25       Impact factor: 3.376

5.  Proteome-pI 2.0: proteome isoelectric point database update.

Authors:  Lukasz Pawel Kozlowski
Journal:  Nucleic Acids Res       Date:  2022-01-07       Impact factor: 16.971

6.  Protein pK a Prediction with Machine Learning.

Authors:  Zhitao Cai; Fangfang Luo; Yongxian Wang; Enling Li; Yandong Huang
Journal:  ACS Omega       Date:  2021-12-07

7.  Prediction of protein pK a with representation learning.

Authors:  Hatice Gokcan; Olexandr Isayev
Journal:  Chem Sci       Date:  2022-02-01       Impact factor: 9.825

8.  Evolutionary information helps understand distinctive features of the angiotensin II receptors AT1 and AT2 in amniota.

Authors:  Rym Ben Boubaker; Asma Tiss; Daniel Henrion; Hajer Guissouma; Marie Chabbert
Journal:  PLoS Comput Biol       Date:  2022-02-24       Impact factor: 4.475

9.  Computational Resources for Bioscience Education.

Authors:  Rajiv K Kar
Journal:  Appl Biochem Biotechnol       Date:  2021-06-08       Impact factor: 2.926

10.  Assessment of proton-coupled conformational dynamics of SARS and MERS coronavirus papain-like proteases: Implication for designing broad-spectrum antiviral inhibitors.

Authors:  Jack A Henderson; Neha Verma; Robert C Harris; Ruibin Liu; Jana Shen
Journal:  J Chem Phys       Date:  2020-09-21       Impact factor: 3.488

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.