Direct Refolding Paths between two Secondary Structures

Heuristics to explore direct, optimal (re-)folding paths between two secondary structures.

Functions

int vrna_path_findpath_saddle(vrna_fold_compound_t *fc, const char *s1, const char *s2, int width)

#include <ViennaRNA/landscape/findpath.h>

Find energy of a saddle point between 2 structures (search only direct path)

This function uses an inplementation of the findpath algorithm [Flamm et al., 2001] for near-optimal direct refolding path prediction.

Model details, and energy parameters are used as provided via the parameter ‘fc’. The vrna_fold_compound_t does not require memory for any DP matrices, but requires all most basic init values as one would get from a call like this:

fc = vrna_fold_compound(sequence, NULL, VRNA_OPTION_DEFAULT);

SWIG Wrapper Notes:: This function is attached as an overloaded method path_findpath_saddle() to objects of type fold_compound. The optional parameter width defaults to 1 if it is omitted. See, e.g. RNA.fold_compound.path_findpath_saddle() in the Python API.

Parameters:

fc – The vrna_fold_compound_t with precomputed sequence encoding and model details
s1 – The start structure in dot-bracket notation
s2 – The target structure in dot-bracket notation
width – A number specifying how many strutures are being kept at each step during the search

Returns:

The saddle energy in 10cal/mol

int vrna_path_findpath_saddle_ub(vrna_fold_compound_t *fc, const char *s1, const char *s2, int width, int maxE)

#include <ViennaRNA/landscape/findpath.h>

Find energy of a saddle point between 2 structures (search only direct path)

This function uses an inplementation of the findpath algorithm [Flamm et al., 2001] for near-optimal direct refolding path prediction.

Model details, and energy parameters are used as provided via the parameter ‘fc’. The vrna_fold_compound_t does not require memory for any DP matrices, but requires all most basic init values as one would get from a call like this:

fc = vrna_fold_compound(sequence, NULL, VRNA_OPTION_DEFAULT);

SWIG Wrapper Notes:: This function is attached as an overloaded method path_findpath_saddle() to objects of type fold_compound. The optional parameter width defaults to 1 if it is omitted, while the optional parameter maxE defaults to INF. In case the function did not find a path with \(E_{saddle} < E_{max}\) the function returns a NULL object, i.e. undef for Perl and None for Python. See, e.g. RNA.fold_compound.path_findpath_saddle() in the Python API.

Warning

The argument maxE ( \(E_{max}\)) enables one to specify an upper bound, or maximum free energy for the saddle point between the two input structures. If no path with \(E_{saddle} < E_{max}\) is found, the function simply returns maxE

Parameters:

fc – The vrna_fold_compound_t with precomputed sequence encoding and model details
s1 – The start structure in dot-bracket notation
s2 – The target structure in dot-bracket notation
width – A number specifying how many strutures are being kept at each step during the search
maxE – An upper bound for the saddle point energy in 10cal/mol

Returns:

The saddle energy in 10cal/mol

vrna_path_t *vrna_path_findpath(vrna_fold_compound_t *fc, const char *s1, const char *s2, int width)

#include <ViennaRNA/landscape/findpath.h>

Find refolding path between 2 structures (search only direct path)

This function uses an inplementation of the findpath algorithm [Flamm et al., 2001] for near-optimal direct refolding path prediction.

Model details, and energy parameters are used as provided via the parameter ‘fc’. The vrna_fold_compound_t does not require memory for any DP matrices, but requires all most basic init values as one would get from a call like this:

fc = vrna_fold_compound(sequence, NULL, VRNA_OPTION_DEFAULT);

SWIG Wrapper Notes:: This function is attached as an overloaded method path_findpath() to objects of type fold_compound. The optional parameter width defaults to 1 if it is omitted. See, e.g. RNA.fold_compound.path_findpath() in the Python API.

Parameters:

fc – The vrna_fold_compound_t with precomputed sequence encoding and model details
s1 – The start structure in dot-bracket notation
s2 – The target structure in dot-bracket notation
width – A number specifying how many strutures are being kept at each step during the search

Returns:

The saddle energy in 10cal/mol

vrna_path_t *vrna_path_findpath_ub(vrna_fold_compound_t *fc, const char *s1, const char *s2, int width, int maxE)

#include <ViennaRNA/landscape/findpath.h>

Find refolding path between 2 structures (search only direct path)

This function uses an inplementation of the findpath algorithm [Flamm et al., 2001] for near-optimal direct refolding path prediction.

Model details, and energy parameters are used as provided via the parameter ‘fc’. The vrna_fold_compound_t does not require memory for any DP matrices, but requires all most basic init values as one would get from a call like this:

fc = vrna_fold_compound(sequence, NULL, VRNA_OPTION_DEFAULT);

SWIG Wrapper Notes:: This function is attached as an overloaded method path_findpath() to objects of type fold_compound. The optional parameter width defaults to 1 if it is omitted, while the optional parameter maxE defaults to INF. In case the function did not find a path with \(E_{saddle} < E_{max}\) the function returns an empty list. See, e.g. RNA.fold_compound.path_findpath() in the Python API.

Warning

The argument maxE enables one to specify an upper bound, or maximum free energy for the saddle point between the two input structures. If no path with \(E_{saddle} < E_{max}\) is found, the function simply returns NULL

Parameters:

fc – The vrna_fold_compound_t with precomputed sequence encoding and model details
s1 – The start structure in dot-bracket notation
s2 – The target structure in dot-bracket notation
width – A number specifying how many strutures are being kept at each step during the search
maxE – An upper bound for the saddle point energy in 10cal/mol

Returns:

The saddle energy in 10cal/mol

vrna_path_options_t vrna_path_options_findpath(int width, unsigned int type)

#include <ViennaRNA/landscape/paths.h>

Create options data structure for findpath direct (re-)folding path heuristic.

This function returns an options data structure that switches the vrna_path_direct() and vrna_path_direct_ub() API functions to use the findpath [Flamm et al., 2001] heuristic. The parameter width specifies the width of the breadth-first search while the second parameter type allows one to set the type of the returned (re-)folding path.

Currently, the following return types are available:

A list of dot-bracket structures and corresponding free energy (flag: VRNA_PATH_TYPE_DOT_BRACKET)
A list of transition moves and corresponding free energy changes (flag: VRNA_PATH_TYPE_MOVES)

SWIG Wrapper Notes:: This function is available as overloaded function path_options_findpath(). The optional parameter width defaults to 10 if omitted, while the optional parameter type defaults to VRNA_PATH_TYPE_DOT_BRACKET. See, e.g. RNA.path_options_findpath() in the Python API.

Parameters:

width – Width of the breath-first search strategy
type – Setting that specifies how the return (re-)folding path should be encoded

Returns:

An options data structure with settings for the findpath direct path heuristic

vrna_path_t *vrna_path_direct(vrna_fold_compound_t *fc, const char *s1, const char *s2, vrna_path_options_t options)

#include <ViennaRNA/landscape/paths.h>

Determine an optimal direct (re-)folding path between two secondary structures.

This is the generic wrapper function to retrieve (an optimal) (re-)folding path between two secondary structures s1 and s2. The actual algorithm that is used to generate the (re-)folding path is determined by the settings specified in the options data structure. This data structure also determines the return type, which might be either:

a list of dot-bracket structures with corresponding free energy, or
a list of transition moves with corresponding free energy change

If the options parameter is passed a NULL pointer, this function defaults to the findpath heuristic [Flamm et al., 2001] with a breadth-first search width of \( 10 \), and the returned path consists of dot-bracket structures with corresponding free energies.

SWIG Wrapper Notes:: This function is attached as an overloaded method path_direct() to objects of type fold_compound. The optional parameter options defaults to NULL if it is omitted. See, e.g. RNA.fold_compound.path_direct() in the Python API.

Parameters:

fc – The vrna_fold_compound_t with precomputed sequence encoding and model details
s1 – The start structure in dot-bracket notation
s2 – The target structure in dot-bracket notation
options – An options data structure that specifies the path heuristic and corresponding settings (maybe NULL)

Returns:

An optimal (re-)folding path between the two input structures

vrna_path_t *vrna_path_direct_ub(vrna_fold_compound_t *fc, const char *s1, const char *s2, int maxE, vrna_path_options_t options)

#include <ViennaRNA/landscape/paths.h>

Determine an optimal direct (re-)folding path between two secondary structures.

This function is similar to vrna_path_direct(), but allows to specify an upper-bound for the saddle point energy. The underlying algorithms will stop determining an (optimal) (re-)folding path, if none can be found that has a saddle point below the specified upper-bound threshold maxE.

SWIG Wrapper Notes:: This function is attached as an overloaded method path_direct() to objects of type fold_compound. The optional parameter maxE defaults to #INT_MAX - 1 if it is omitted, while the optional parameter options defaults to NULL. In case the function did not find a path with \(E_{saddle} < E_{max}\) it returns an empty list. See, e.g. RNA.fold_compound.path_direct() in the Python API.

Warning

The argument maxE enables one to specify an upper bound, or maximum free energy for the saddle point between the two input structures. If no path with \(E_{saddle} < E_{max}\) is found, the function simply returns NULL

Parameters:

fc – The vrna_fold_compound_t with precomputed sequence encoding and model details
s1 – The start structure in dot-bracket notation
s2 – The target structure in dot-bracket notation
maxE – Upper bound for the saddle point along the (re-)folding path
options – An options data structure that specifies the path heuristic and corresponding settings (maybe NULL)

Returns:

An optimal (re-)folding path between the two input structures