Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 364

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Constant‐pH molecular dynamics using continuous titration coordinates

Lee, Michael S., Salsbury, Freddie R., Brooks, Charles L.·2004·Proteins: Structure, Function, and Bioinformatics
DOI 10.1002/prot.20128
Open this paper in CoChat — free account

Abstract

In this work, we explore the question of whether pK a calculations based on a microscopic description of the protein and a macroscopic description of the solvent can be implemented to examine conformationally dependent proton shifts in proteins. To this end, we introduce a new method for performing constant‐pH molecular dynamics (PHMD) simulations utilizing the generalized Born implicit solvent model. This approach employs an extended Hamiltonian in which continuous titration coordinates propagate simultaneously with the atomic motions of the system. The values adopted by these coordinates are modulated by potentials of mean force of isolated titratable model groups and the pH to control the proton occupation at particular sites in the polypeptide. Our results for four different proteins yield an absolute average error of ∼1.6 pK units, and point to the role that thermally driven relaxation of the protein environment in the vicinity of titrating groups plays in modulating the local pK a , thereby influencing the observed pK 1/2 values. While the accuracy of our method is not yet equivalent to methods that obtain pK 1/2 values through the ad hoc scaling of electrostatics, the present approach and constant pH methods in general provide a useful framework for studying pH‐dependent phenomena. Further work to improve our model to approach quantitative agreement with experiment is outlined. Proteins 2004. © 2004 Wiley‐Liss, Inc.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/prot.20128

Cites

49 of 49 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 364

Metadata

Authors
Lee, M. S., Salsbury, F. R., & Brooks, C. L.
Venue
Proteins: Structure, Function, and Bioinformatics
Publisher
Wiley
Published
2004-06-11
Volume
56
Issue
4
Pages
738-752
ISSN
  • 0887-3585 (ISSN-L)
  • 1097-0134
DOI
10.1002/prot.20128
OpenAlex
W2163168043
Cited by
364
References
49
FWCI
4.05
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.