Title: Analysis of Binding Events + l
Version: 3.0.2
Description: A free software for a fast and easy analysis of 1:1 molecular interaction studies. This package is suitable for a high-throughput data analysis. Both the online app and the package are completely open source. You provide a table of sensogram, tell 'anabel' which method to use, and it takes care of all fitting details. The first two releases of 'anabel' were created and implemented as in (<doi:10.1177/1177932218821383>, <doi:10.1093/database/baz101>).
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.2
VignetteBuilder: knitr
LazyData: true
Imports: cli (≥ 3.4), dplyr (≥ 1.0), ggplot2 (≥ 3.3), kableExtra (≥ 1.3), minpack.lm (≥ 1.2), openxlsx (≥ 4.2), progress (≥ 1.2), purrr (≥ 0.3), qpdf, reshape2 (≥ 1.4), rlang (≥ 1.0), stats (≥ 4.0), tidyr (≥ 1.2), utils (≥ 4.0)
Depends: R (≥ 4.0)
Suggests: htmltools (≥ 0.5), knitr (≥ 1.36), rmarkdown (≥ 2.17), testthat (≥ 3.0.0), withr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2025-03-22 00:12:31 UTC; stefan
Author: Hoor Al-Hasani ORCID iD [aut], Oliver Selinger ORCID iD [aut], Stefan Kraemer ORCID iD [aut, cre]
Maintainer: Stefan Kraemer <stefan.kraemer.91@gmail.com>
Repository: CRAN
Date/Publication: 2025-03-28 13:00:07 UTC

anabel: Analysis of Binding Events + l

Description

A free software for a fast and easy analysis of 1:1 molecular interaction studies. This package is suitable for a high-throughput data analysis. Both the online app and the package are completely open source. You provide a table of sensogram, tell 'anabel' which method to use, and it takes care of all fitting details. The first two releases of 'anabel' were created and implemented as in (doi:10.1177/1177932218821383, doi:10.1093/database/baz101).

Author(s)

Maintainer: Stefan Kraemer stefan.kraemer.91@gmail.com (ORCID)

Authors:

Simulated data of binding curve for MCK.

Description

A dataset containing 5 different binding curves of different analyte concentrations. Ka = 1e+7nM, Kd = 1e-2

Usage

data(MCK_dataset)

Format

A data frame with 403 rows and 6 variables:

Time

time points of the binding interaction from start to end

Conc..50.nM.

binding curve generated with analyte concentration = 50nM

Conc..16.7.nM.

binding curve generated with analyte concentration = 16.7nM

Conc..5.56.nM.

binding curve generated with analyte concentration = 5.56nM

Conc..1.85.nM.

binding curve generated with analyte concentration = 1.85nM

Conc..6.17e.1.nM.

binding curve generated with analyte concentration = 0.617nM

Source

https://apps.cytivalifesciences.com/spr/

Simulated data of binding curve for MCK with linear drift.

Description

A dataset containing 5 different binding curves of different analyte concentrations with induced baseline drift = -0.01. Ka = 1e+7nM, Kd = 1e-2

Usage

data(MCK_dataset)

Format

A data frame with 403 rows and 6 variables:

Time

time points of the binding interaction from start to end

Conc..50.nM.

binding curve generated with analyte concentration = 50nM

Conc..16.7.nM.

binding curve generated with analyte concentration = 16.7nM

Conc..5.56.nM.

binding curve generated with analyte concentration = 5.56nM

Conc..1.85.nM.

binding curve generated with analyte concentration = 1.85nM

Conc..6.17e.1.nM.

binding curve generated with analyte concentration = 0.617nM

Source

https://apps.cytivalifesciences.com/spr/

Simulated data for SCA method.

Description

A simulated data containing interaction information of three binding curves all generated with concentration 5e-08,

Usage

data(SCA_dataset)

Format

A data frame with 453 rows and four variables:

Time

time points of the binding interaction from start till the experiment's end

Sample.A

sample one with Ka = 1e+7nM, Kd = 1e-2

Sample.B

sample two with Ka = 1e+6nM, Kd = 5e-2

Sample.C

sample four with Ka = 1e+6nM, Kd = 1e-3

Source

https://apps.cytivalifesciences.com/spr/

Simulated data for SCA method with linear drift.

Description

A simulated data containing interaction information of three binding curves all generated with concentration 5e-08, baseline drift = -0.019

Usage

data(SCA_dataset)

Format

A data frame with 453 rows and four variables:

Time

time points of the binding interaction from start till the experiment's end

Sample.A

sample one with Ka = 1e+7nM, Kd = 1e-2

Sample.B

sample two with Ka = 1e+6nM, Kd = 5e-2

Sample.C

sample four with Ka = 1e+6nM, Kd = 1e-3

Source

https://apps.cytivalifesciences.com/spr/

Simulated data of different binding curves for SCK method.

Description

A dataset contains one binding curve with 5 titrations-series (5 injection-series), as follows: tass: 50, 220, 390, 560, 730; tdiss: 150, 320, 490, 660, 830; conc: 6.17e-10 1.85e-09 5.56e-09 1.67e-08 5.00e-08 M

Usage

data(SCK_dataset)

Format

A data frame with 1091 rows and 6 variables:

Time

time points of the binding interaction from start to end

Sample.A

sample containing 5 titerations with Ka = 1e+6nM, Kd = 1e-2

Source

https://apps.cytivalifesciences.com/spr/

Simulated data of different binding curves for SCK method with exponential decay.

Description

A dataset contains one binding curve with 5 titrations-series (5 injection-series), as follows: tass: 50, 220, 390, 560, 730; tdiss: 150, 320, 490, 660, 830; conc: 6.17e-10 1.85e-09 5.56e-09 1.67e-08 5.00e-08 M

Usage

data(SCK_dataset)

Format

A data frame with 1091 rows and 6 variables:

Time

time points of the binding interaction from start to end

Sample.A

sample containing 5 titerations with Ka = 1e+6nM, Kd = 1e-2

Source

https://apps.cytivalifesciences.com/spr/

Convert a unit to molar

Description

convert the value into molar.

Usage

convert_toMolar(val, unit)

Arguments

val

numeric value of the analyte concentration

unit

character string indicating the unit from which, the analyte concentration will be converted into molar.

Details

supported units are: millimolar, micromolar, nanomolar and picomolar. The name of the unit could be written, or its abbreviation such as: nanomolar (nm), micromolar (mim), picomolar (pm), or millimolar (mm). The unite in either form is case insensitive.

Value

The value of analyte concentration in molar

Examples

convert_toMolar(120, "nanomolar")
convert_toMolar(120, "nm")
convert_toMolar(120, "millimolar")
convert_toMolar(120, "mm")
convert_toMolar(120, "micromolar")
convert_toMolar(120, "mim")
convert_toMolar(120, "picomolar")
convert_toMolar(120, "pm")

Analysis for 1:1 Biomolecular Interactions

Description

Analysis for 1:1 biomolecular interactions, using one of single-curve analysis (SCA), single-cycle kinetics (SCK) or multi-cycle kinetics (MCK)

Usage

run_anabel(
  input = NA,
  samples_names_file = NULL,
  tstart = NA,
  tend = NA,
  tass = NA,
  tdiss = NA,
  conc = NA,
  drift = FALSE,
  decay = FALSE,
  quiet = TRUE,
  method = "SCA",
  outdir = NA,
  generate_output = "none",
  generate_Report = FALSE,
  generate_Plots = FALSE,
  generate_Tables = FALSE,
  save_tables_as = "xlsx",
  debug_mode = FALSE
)

Arguments

input

Data.frame, an excel, or a csv file (full path) - required

samples_names_file

An optional data.frame, an excel, or a csv file (full path) containing the samples names. If provided, it must have two columns, Name and ID. ID: names of columns in the input file; Name: sample's names.

tstart

Numeric value of time's starting point (default: minimum time point in the input)

tend

Numeric value of time's ending point (default: maximum time point in the input)

tass

Numeric value of association time - required

tdiss

Numeric value of dissociation time - required

conc

Numeric value, the used concentration of the analyte; should be in molar (see convert_toMolar) - required

drift

Boolean value, to apply drift correction (default: FALSE)

decay

Boolean value, to apply surface decay correction (default: FALSE)

quiet

Boolean value, to suppress notifications, messages and warnings (default: TRUE)

method

a character string indicating which fitting method to be used. One of "SCA", "SCK", or "MCK", case insensitive (default: SCA).

outdir

Path and name of the output directory in which the results will be saved (default: NA)

generate_output

a character string indicating what kind of output will be generated. One of "none", "all", or "customized", case insensitive (default: none). If "all" or "customized" were given, outdir is required. If "customized" was given, at least one of generate_Plots, generate_Tables, or/and generate_Report must be set to TRUE

generate_Report

Boolean value, should anabel generate a summary report of the experiment? (default: FALSE)

generate_Plots

Boolean value, should anabel generate plots? (default: FALSE). generate_output must be set to "customized"

generate_Tables

Boolean value, should anabel generate tables? (default: FALSE)

save_tables_as

a character string indicating data format to save the tables with; could be "xlsx", "csv", "txt" or "rds", case insensitive, (default: xlsx)

debug_mode

Boolean value, anabel will return additional fitting details for each curve and the estimated response (default: FALSE)

Value

default returned value is a list of two data frames, the kinetics table and the fit value of each time point (fit_raw). If dev_mode was set to TRUE a third data frame will be returned containing the initial value of the parameters and the fitting function.

References

Determination of rate and equilibrium binding constants for macromolecular interactions by surface plasmon resonance. D J O'Shannessy, M Brigham-Burke, K K Soneson, P Hensley, I Brooks Analytical biochemistry 212, 457-468 (1993)

Analyzing a kinetic titration series using affinity biosensors. Robert Karlsson, Phinikoula S Katsamba, Helena Nordin, Ewa Pol, David G Myszka Analytical Biochemistry 349, 136–147 (2006)

Anabel: an online tool for the real-time kinetic analysis of binding events. Stefan D Krämer, Johannes Wöhrle , Christin Rath, Günter Roth Bioinformatics and Biology Insights 13, 1-10 (2019)

See Also

convert_toMolar

Examples


# To analyse data using MCK method:
run_anabel(
  input = MCK_dataset, tstart = 1, tass = 21, tdiss = 140,
  conc = c(3.9E-9, 1.6E-8, 6.2E-8, 2.5E-7, 1.0e-6), method = "MCK"
)