Evidence map›Paper›PMID 26505480›Full record

ArticlePLoS computational biology2015

Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning.

Lane W Votapka, Rommie E Amaro

Abstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Article
  2. Article
  3. Predicting Biomolecular Binding Kinetics: A Review.Journal of chemical theory and computation · 2023
    Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Protein storytelling through physics.Science (New York, N.Y.) · 2020
    Review
  17. Value of Temporal Information When Analyzing Reaction Coordinates.Journal of chemical theory and computation · 2020
    Article
  18. Article
  19. Article
  20. Encounter complexes and hidden poses of kinase-inhibitor binding on the free-energy landscape.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
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.

Lane W VotapkaDepartment of Chemistry and Biochemistry and National Biomedical Computation Resource, University of California, San Diego, San Diego, California, United States of America.
Rommie E AmaroDepartment of Chemistry and Biochemistry and National Biomedical Computation Resource, University of California, San Diego, San Diego, California, United States of America.

Funding

National Biomedical Computation Resource - Competitive Revision SupplementP41GM103426 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI AMARO, ROMMIE E · 2012 to 2019
$14.0M
A Structural Systems Biology Approach to Drug DiscoveryDP2OD007237 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI AMARO, ROMMIE E · 2010 to 2015
$2.9M
NIGMS NIH HHS P41 GM103426NIH HHS DP2 OD007237NIH HHS DP2-OD007237
6 · The paper itself

Abstract

The kinetic rate constants of binding were estimated for four biochemically relevant molecular systems by a method that uses milestoning theory to combine Brownian dynamics simulations with more detailed molecular dynamics simulations. The rate constants found using this method agreed well with experimentally and theoretically obtained values. We predicted the association rate of a small charged molecule toward both a charged and an uncharged spherical receptor and verified the estimated value with Smoluchowski theory. We also calculated the kon rate constant for superoxide dismutase with its natural substrate, O2-, in a validation of a previous experiment using similar methods but with a number of important improvements. We also calculated the kon for a new system: the N-terminal domain of Troponin C with its natural substrate Ca2+. The kon calculated for the latter two systems closely resemble experimentally obtained values. This novel multiscale approach is computationally cheaper and more parallelizable when compared to other methods of similar accuracy. We anticipate that this methodology will be useful for predicting kinetic rate constants and for understanding the process of binding between a small molecule and a protein receptor.

Indexed as

AlgorithmsModels, ChemicalModels, StatisticalMolecular Dynamics SimulationBinding SitesDiffusionKineticsProtein BindingProtein ConformationProteinsProteins

Identifiers

PMID26505480
PMCPMC4624728

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.