Evidence map›Paper›PMID 26202905›Full record

ReviewBiopolymers2016

Computation of pH-dependent binding free energies.

M Olivia Kim, J Andrew McCammon

Abstract readReview
In one paragraph

Review in Biopolymers, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Accurately Predicting Protein pJournal of chemical theory and computation · 2023
    Article
  4. Article
  5. Article
  6. Review
  7. Calculation ofMolecules (Basel, Switzerland) · 2018
    Article
  8. Article
  9. Article
  10. Review
  11. Docking Screens for Novel Ligands Conferring New Biology.Journal of medicinal chemistry · 2016
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

M Olivia KimDepartment of Pharmacology, University of California San Diego, La Jolla, CA, 92093.
J Andrew McCammonDepartment of Pharmacology, University of California San Diego, La Jolla, CA, 92093.

Funding

National Biomedical Computation Resource - Competitive Revision SupplementP41GM103426 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI AMARO, ROMMIE E · 2012 to 2019
$14.0M
THEORY OF BIOMOLECULAR DIFFUSIONR01GM031749 · NIGMS · UNIVERSITY OF HOUSTON · PI HUBER, GARY ALEXANDER, MCCAMMON, JAMES ANDREW · 1985 to 2022
$7.8M
Howard Hughes Medical InstituteNIGMS NIH HHS GM31749NIGMS NIH HHS P41 GM103426NIGMS NIH HHS R01 GM031749
6 · The paper itself

Abstract

Protein-ligand binding accompanies changes in the surrounding electrostatic environments of the two binding partners and may lead to changes in protonation upon binding. In cases where the complex formation results in a net transfer of protons, the binding process is pH-dependent. However, conventional free energy computations or molecular docking protocols typically employ fixed protonation states for the titratable groups in both binding partners set a priori, which are identical for the free and bound states. In this review, we draw attention to these important yet largely ignored binding-induced protonation changes in protein-ligand association by outlining physical origins and prevalence of the protonation changes upon binding. Following a summary of various theoretical methods for pKa prediction, we discuss the theoretical framework to examine the pH dependence of protein-ligand binding processes.

Indexed as

Computer SimulationModels, ChemicalThermodynamicsHydrogen-Ion ConcentrationProteinsProteinsbinding free energypH dependencepKaprotein-ligand bindingprotonation

Identifiers

PMID26202905
PMCPMC4623928

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.