nimna

Nucleic acid folding and design.

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nimna

nim nucleic acid folding.

What is nimna?

nimna is a set of bindings to ViennaRNA, a library for RNA and DNA folding applications. It consists of a very thin c2nim wrapper RNA.nim, as well as a high level interface nimna.nim, which wraps the many pointers used in the ViennaRNA into garbage collected ref objects to make the library easier to use. Furthermore, it provides nucleic acid design functionality in the form of an 'artificial immune-system' algorithm in design.nim.

Installation

Installation of nimna and its dependencies is automatically handled using nimble install. This tries to autodetect, whether a suitable dynamic library version of libRNA exists on your computer. If that is not the case, it pulls all files necessary for installation from the web and installs them. In case of Windows, the ViennaRNA installer is started and you may need to complete the some installation steps manually, while for *nix ViennaRNA is built from source. As such, it suffices for most use-cases to just perform:

$ nimble install nimna

or

$ nimble install <this repository's url>

As nimble currently does not allow uninstall hooks, nimna provides a command to clean up dependencies, should you want to uninstall nimna:

$ nimnacleanup

This removes the dependency folder in the nimna package. If this is not done, nimble cannot fully remove nimna's package directory, leaving the deps folder to lie around.

What can I do with it?

nimna currently provides the functionality implemented in ViennaRNA, as well as some extra bits. As nimna's current status is a work-in-progress, the set of available functionality will be steadily growing. You can find more documentation, as well as short examples for every submodule here

Here's an incomplete list of what can be done with nimna:

Partition function (pf) and minimum free energy (mfe) folding

Folding for single molecules:

let
  sequence = compound"CCCCCAAAGGGGG"
  mfeResult = sequence.mfe
  pfResult = sequence.pf
echo mfeResult.struc # prints (((((...)))))
echo mfeResult.E     # prints the free energy
                     # of folding in kcal/mol
echo pfResult.struc  # prints (((((...)))))
echo pfResult.E      # prints the ensemble free
                     # energy of folding in kcal/mol

Folding for dimers and alignments works analogously after creation of suitable Compound objects.

Free energy evaluation of structures

When no full folding prediction is required, nimna allows for the computation of free energies of given secondary structures for a Compound:

echo sequence.eval("(((((...)))))") # Prints the free
                                    # energy of folding
                                    # for the given
                                    # structure.
echo sequence.evalRemove(
  "(((((...)))))", 0, 12) # Prints the free energy of
                          # removing the base pair of
                          # the first and last
                          # nucleotides
echo sequence.evalAdd(
  ".((((...)))).", 0, 12) # Prints the free energy of
                          # adding a base pair between
                          # the first and last
                          # nucleotides

Access to base pairing probabilities

When using partition function folding (pf), base pairing probabilities are set in the Compound object, an immutable view of which can be created later:

let probs = sequence.probabilities
echo probs[i, j] # prints the probability of bases
                 # i and j in `sequence` forming
                 # a base pair.
echo sequence.prob(i, j) # prints the same as above.

A Probabilities object created from a Compound may be iterated over using a set of iterators provided in nimna:

for elem in probs.items:
  echo elem # prints each and every
            # entry in the probability matrix.

for pos, prob in probs.pairs:
  echo pos.i, " : ", pos.j, " : ", prob
  # prints the base positions together
  # with the associated probabilities.

for i, j, prob in probs.triples:
  echo i, " : ", j, " : ", prob
  # prints the same as above.

for pos in probs.positions:
  for elem in pos:
    echo elem # for every base in the Compound
              # prints the base pairing probability
              # of that base with all other bases.

Fine tuning of folding parameters

Although standard folding parameters are often deemed sufficient for many use cases, tuning of parameters may be required for more specialized analyses. To that end nimna provides the means to adjust the folding parameters at will:

# Use the `settings` macro to create a new
# set of folding parameters:
let
  settings = settings(
    temperature = 25.0, # Set the folding
                        # temperature to 25°C
    noGU = 1            # Disallow G--U base pairs
  )
  # Parameters for mfe folding
  mfeParams = settings.toParams
  # Parameters for pf folding
  pfParams = settings.toScaledParams

# Now, update the compound with those parameters:
sequence.update(mfeParams) # Update parameters
                           # for mfe folding only.
sequence.update(pfParams)  # Update parameters
                           # for pf folding only.
sequence.update(settings)  # Update all parameters.

Application of soft and hard constraints to compounds

For certain applications, for example for working with aptamers protein binding domains, Ag-nanocluster forming sequences and other sequences with strong outside (i.e. non DNA/RNA) influences on folding, it is necessary to inform the folding algorithm about the presence of those structures. This is done using (hard or soft) constraints encoding the outside influence, its free energy of interaction and the resulting secondary structure resulting upon interaction. To that end, nimna provides access to the full spectrum of constraints implemented in ViennaRNA.

Hard constraints force the nucleic acid to fold in certain ways, regardless of other, perhaps more favourable interactions involved. They are set using forceX, where X is one of paired, unpaired:

# Given a compound `sequence`, constrain its
# i'th and j'th base to pair:
sequence.forcePaired(i, j)
# constrain its k'th base to stay unpaired:
sequence.forceUnpaired(k)
# constrain it according to a dot-bracket string:
sequence.constrain("x((((xxx))))x") # 'x' means:
                                    # must not pair
# lift all constraints
sequence.liftConstraints

Soft constraints register base pairs or motifs with a certain preferred free energy of interaction, which are then incorporated into folding prediction. This allows for correct folding, when lower energy interactions outside the constraints are available. They are set using preferX, where X is one of paired, unpaired:

# Given a compound `sequence`, add a beneficial
# free energy contribution of -10.0 kcal/mol to
# the base pairing of its i'th and j'th base:
sequence.preferPaired(i, j, -10.0)
# Do the same for its k'th base to stay unpaired:
sequence.preferUnpaired(k, -10.0)
# Do the same for a motif `CCAA` in `sequence`
sequence.preferMotif("CCAA", -10)
# Lift all preferences
sequence.liftPreferences

Nucleic acid design

nimna provides an 'artificial immune system'-based nucleic acid design algorithm for automatic design of nucleic acids according to a user-specified fitness function:

# Define a fitness function:
proc fitness(c: Compound): float =
  c.eval("(((((((...))))..)))")

# create a new `DesignEngine`:
let design = newEngine(20, fitness)
# constrain the sequence space to be searched:
design.pattern = "NNNNNNNATGCNNNYHGNN"
# specify a structure for structure-consistent mutation.
# this ensures, that the three base pairs around the
# three-nucleotide-loop are mutated together, such that
# they form Watson-Crick base pairs:
design.structure = "....(((...)))......"
# set the folding parameters:
design.settings = settings(temperature = 25.0)
# set the mutation probability:
design.mutationProbability = 0.6
# run the algorithm for 100 steps:
design.step(100)
# print the best sequence according to
# the fitness function:
echo design.best.sequence

A more complete list of available functionality

  • Folding:
    • Partition function folding for one or more molecules, as well as alignments.
    • Minimum free energy folding for one or more molecules, as well as alignments..
    • Centroid structure folding for one or more molecules.
    • 2DFold (MFE and partition function).
    • Maximum expected accuracy folding.
    • Generation of suboptimal structures and energies.
  • Constraints:
    • Hard constraints are fully supported.
    • Soft constraints are fully supported.
    • Structured ligand binding constraints are fully supported.
  • Model Details:
    • Updating of model details associated with a molecule.
    • Generating MFE and PF parameters from model details.
    • Macro for easily generating model details.
  • Parameters:
    • Updating of parameters associated with a molecule.
  • Probability Matrix:
    • Probability matrix exposed as Probabilities = ref object.
    • Extracting values from the probability matrix of partition function folding.
    • Generating a Density Plot of the base pairing probability in a terminal emulator.
  • Nucleic acid design:
    • Generating nucleic acid sequences corresponding to local minima in user-defined fitness functions.
  • Miscellaneous:
    • Generating reasonably random DNA/RNA sequences.
    • Evaluating energies of secondary structures.
    • Sampling secondary structures from ensembles computed with pf and pf2D.
    • Iterators for all types which can be iterated over.
    • Reading and writing parameter files.

A short example:

# We want to fold a sequence at multiple temperatures,
# and see how the base pairing probabilities change:
import nimna
import strutils

let rna = compound"GGGGGAGGAAACCTTCCCC"

for deltaT in 0..200:
  let T = 20.0 + deltaT.float / 10.0
  discard rna.update(settings(temperature = T)).pf
  if deltaT != 0:
    # This makes use of ANSI-escapes to move the cursor
    # up to the beginning of the plot, to write over it
    # again, so we can have a nice animation.
    echo "\e[$1A" % $(rna.length + 2)
  rna.densityPlot

iGEM disclaimer

nimna is not a project of a Heidelberg iGEM team, future or past. Certainly, it was inspired by the work of the Heidelberg iGEM team 2015 but it is its own project, which I work on, on my own time and which will be maintained and supported, in contrast to some iGEM code out there.

Need help? Read Nimble
Author:
mjendrusch
Available versions:
License: MIT

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