Model editing with Sculptor

Contents

Purpose

Sculptor can be used to improve a molecular replacement model using additional information available from an alignment and/or structure. It is based on an algorithm outlined in Schwarzenbacher et al. (2004).

Conventions

The following terms are used with the special meaning:

Usage

There is a standalone sculptor_new program available from the command line. The unified model preparation program sculpt_ensemble is available from the command line and also from the PHENIX GUI.

Input files

  • Structure (compulsory): the structure to be modified. Specific parts can be selected using CNS-style atom selection syntax. Chains are divided into protein, DNA, RNA, hetero, monosaccharide and other chain categories, and processed according to instructions given for the appropriate chain type. Accepted formats: PDB. Recognized extensions: .pdb, .ent.
  • Alignments: sequence alignment with the target sequence. The alignment contains information that can be exploited in model improvement (this is currently only implemented for protein chains). The chains are automatically associated with the corresponding alignment based on a sequence comparison. The target sequence is also automatically identified if it is provided through the target_sequence keyword, otherwise the first sequence in the alignment is used as target. Alignment input is optional, in case it is not provided, an alignment will be made up using the chain sequence with itself. Accepted extensions (with the corresponding format) are .aln (CLUSTAL format), .pir (PIR-format) and .ali (relaxed PIR-like format).
  • Homology search files: hits from a homology search. These work very similarly to a set of alignment files. It is assumed that the first sequence in each alignment is the target sequence (the sequence used for searching homologues). Accepted extensions (with the corresponding format) are .xml (BLAST-family XML output) and .hhr (HHPRED output).
  • Sequence files: target sequence. In case no alignment is available, Sculptor can be instructed to prepare an alignment using the sequences of model chains assigned on the chain_ids parameter (please note that in this case this alignment will be used for the specified chains, and any user-supplied alignments will be ignored). Multiple sequence files can be provided when target sequences for distinct protein chains differ. Accepted extensions are .fasta, .faa or .fa for FASTA format, .pir for PIR-format and .seq or .dat for a relaxed PIR/FASTA-like format.
  • Error files and Superposition error files: error estimates coming either from a model quality assessment program (MQAP) or from a superposition. Errors from MQAPs can be used in mainchain processing and also in B-factor weighting, while those from a superposition can only be used for mainchain processing. The inputs are kept separate, and hence it is possible to use two different error estimates for each macromolecule chain.

Output files

The fully processed structure is output. The file is named according to the following convention: root_pdb.pdb, where root is a user-defined parameter (accessible from the output scope), and pdb is the basename of the input PDB file.

Outline of the procedure

The workflow consists of several stages that can be independently configured. These are listed in order of execution. For a summary of all keywords with the corresponding defaults, see the Additional information section.

Preprocessing

  • selection: selects a subset of the input PDB file, using

    CNS-style atom selection syntax. Default: all.

  • remove_alternate_conformations: selects the first alternate

    conformation for disordered entities, and discards the rest. Also involes sanitize_occupancies.

  • sanitize_occupancies: resets all occupancies to 1.0.

  • keep_crystal_symmetry: retain the CRYST record of the model structure.

In addition, chains will be analysed, hetero, sugar and solvent atoms will be separated from protein/DNA/RNA chains if they are not separated by TER cards.

Chain-to-alignment matching

Parameters in the chain_to_alignment_matching scope control how a sequence from an alignment is matched to the sequence of a macromolecule chain, and what constitutes an acceptable match. The sequence from the alignment is considered strictly consecutive, while gaps are allowed in the sequence derived from the protein chain (this is governed by the consecutivity parameter; geometry means that a chain segment is strictly consecutive if there is a bond to the neighbouring residue, and numbering means that residue numbering should be used to decide whether a residue is connected to neighbouring ones). The min_sequence__identity parameter is used as a threshold to accept a possible match between the two sequences.

Error estimates

These parameters control how error estimates input are matched to macromolecule chains. In addition, if no external errors are available, the modelling program * Rosetta * is installed and configured to be used with PHENIX, and there is network connectivity, Sculptor can be instructed to calculate an error estimate (calculate_if not_provided parameter and homology_modelling scope) by first making a homology model using * Rosetta * and then submitting this to the ProQ2 server. Raw results * obtained will be written out if the output_prefix parameter is set. Please note that this only works for protein chains. For more information, see the the simple_homology_model documentation.

Please note that the input/obtained error estimates are only used if a suitable processing method is selected. Such methods are available in the Deletion and B-factor prediction sections.

Chain processing

Protein chains

Deletion

Discards residues from a model chain that are unlikely to improve signal in molecular replacement. This information is calculated either from the alignment or from estimated errors.

There are multiple algorithms available:

  • gap: Deletes residues that are not present in the target (model residue is aligned with a gap). For this algorithm, the supplied alignment is used as a pairwise alignment.
  • threshold_based_similarity: Deletes residues for which the sequence similarity is below a certain threshold. All sequences in a multiple alignment contribute to the score. Details of the sequence similarity calculation are given in the section Sequence similarity calculation.
  • completeness_based_similarity: Deletes the same number of residues (modified by a fractional offset) as the gap algorithm would but residues that get removed are the ones with the lowest sequence similarity. This way the default values are valid over a much larger sequence similarity range than those in threshold_based_similarity. All sequences in a multiple alignment contribute to the score. Details of the sequence similarity calculation are given in the section Sequence similarity calculation.
  • remove_long: Deletes residues from the model if these are aligned with gaps and at least minimum_length long.
  • rms: Deletes residues whose estimated error is over a certain threshold. Missing values are filled in using parameters in the missing_value_substitution scope (see Missing value substitution).
  • superposition: Deletes residues whose superposition error is over a certain threshold. Missing values are filled in using parameters in the missing_value_substitution scope (see Missing value substitution).

These algorithms can also be used together in any combination. In this case, a residue will be deleted if assigned for deletion by any active algorithms.

Polishing

Makes small adjustments to the mainchain of a chain (taking results from deletion into account) to make it obey basic macromolecular features.

  • remove_short. Deletes additional residue segments from the molecule so that no continuous segment is shorter than a preset limit (determined by the minimum_length parameter of the remove_short scope). Segment boundaries are determined from spatial connectivity of residues. This algorithm is primarily intended to remove "floating" residues that are the result of extensive loop truncation.
  • undo_short. Reinstate short segment that are assigned for deletion. The maximum length is controlled by the maximum_length parameter.
  • keep_regular. Reinstate deleted residues if they are in regular secondary structure and the segment marked for deletion is shorter than the maximum_length parameter of the keep_regular scope.

These algorithms can also be used together in combination. In this case, the chain will be processed sequentially by both algorithms.

Atom mapping

This governs how the sidechain of an amino acid residue in the model is morphed into the target type.

  • connectivity. This uses atom-connectivity-based similarity to match one sidechain to another. The matching can take into account whether the chemical element of the model and target type agree (match_chemical_elements keyword).
  • geometry. This uses the actual observed geometry of the sidechain in the model structure and tries to map it onto all known rotamers of the target amino acid, and selects the rotamer that results in the highest number of atoms mapped. Geometric matching is done via matching distances, and the tolerance is controlled by the tolerance keyword. The algorithm can also take into account the chemical elements explicitly, but this is probably not as useful, since implicitly these are always taken into account through bond lengths and angles. Rotamer information is obtained through the monomer library, and hence this algorithm only works well if the monomer library contains this information. With this algorithm, matching a particular sidechain with the same type can result in a partial match if the observed sidechain conformation is not rotameric. The keyword match_if_identical controls whether matching should be performed in this case or just an identity atom map should be used.

Pruning

This phase determines the level distance from the Calpha atom up to which a residue sidechain in the model is potentially similar to its counterpart in the target.

  • null. No pruning is applied (unmatched atoms will still be discarded).
  • schwarzenbacher. Implements the algorithm published by Schwarzenbacher et al. (2004), who propose that for optimal molecular replacement results a residue sidechain should be truncated if aligned with a non-identical residue, and not truncated otherwise. The level of truncation is controlled by the pruning_level parameter, and defaults to 3 (which corresponds to Cgamma) and can be controlled by the pruning_level parameter of the schwarzenbacher scope.
  • Similarity. Uses sequence similarity values for deciding the level of truncation. Residues above full_truncation_limit are not truncated at all, those below the full_truncation_limit are truncated to Cbeta, and those in between are truncated according to the pruning_level parameter (all available from the similarity scopei). Results tend to be similar to those given by the Schwarzenbacher algorithm; however, it is possible to get high similarity values (and full sidechain preservation) for certain substitutions (i.e. TYR to PHE), and low-sequence similarity zones can end up being truncated to Cbeta. Details of the sequence similarity calculation are given in the section Sequence similarity calculation.

These algorithms can also be used together in any combination, in which case the sidechain will be truncated to the shortest value suggested.

B-factor prediction

B-factor prediction tries to increase B-factors for atoms that are likely to be more flexible or more in error. The calculation takes simple physical properties into account, and these are linearly transformed to B-factors (controlled by the factor parameter of the corresponding scope). If this value is lower than the minimum (from the bfactorscope) parameter, a constant is added to all B-factors so that the lowest of those equals to minimum (this is primarily intended to avoid negative B-factors).

  • original. This uses the original B-factor of atoms. This is primarily intended as a contributor to a combination, but can also be used to manipulate current B-factors, e.g. set them to a constant value.
  • asa. This calculates accessible surface area for an isolated chain and transforms the raw values to B-factors. A high ASA-value indicates a potential for flexibility. The calculation can be configured by the precision and probe_radius parameters of the asa scope.
  • similarity. Low sequence similarity regions tend to be more dissimilar. Details of the sequence similarity calculation are given in the section Sequence similarity calculation.
  • rms. Use error estimates (either input or those calculated within the program) to weight atoms. The theoretical scale factor of 8/3 * pi^2 is already built into the calculation, but this can be adjusted if necessary. Missing values are filled in using parameters in the missing_value_substitution scope (see Missing value substitution).

Algorithms can be used in combination, in which case the sum of the predicted B-factors is used. This mode can also be used to map sequence similarity or accessible surface area to residues/atoms for display purposes.

Renumber

Renumbers residues according to the target or model sequence. It is also possible to turn renumbering off (option original).

Rename

Renames residues according their counterpart in the target sequence. Please note that this is only a name change. Sidechain atoms are always mapped onto their target counterparts, and deleted if not present in the target. On the other hand, the addition of atoms that are present in the target and not in the model does not take place if renaming is not performed.

Completion

Controls the addition of missing atoms.

  • cbeta. Adds Cbeta atom if the residue is not glycine, and C, N and Calpha atoms are all present. A common Cbeta position is used for all non-proline residues, and a slightly differing ones for prolines.
  • cbeta_and_pro. Fills in Cbeta where possible for non-proline residues, and the whole sidechain for prolines.
  • sidechain. Fills in missing atoms for all sidechains. The algorithm tries to get as close as possible to the atoms present in the structure, but in the general case, all sidechain atoms within the residue may move slightly.

DNA/RNA chains

Deletion

Discards residues from a model chain that are unlikely to improve signal in molecular replacement.

There are two algorithms available:

  • all: Deletes all residues.
  • superposition: Deletes residues whose superposition error is over a certain threshold. Missing values are filled in using parameters in the missing_value_substitution scope (see Missing value substitution).

These algorithms can also be used together in any combination. In this case, a residue will be deleted if assigned for deletion by any active algorithms.

Polishing

Makes small adjustments to the mainchain of a chain (taking results from deletion into account) to make it obey basic macromolecular features.

  • remove_short. Deletes additional residue segments from the molecule so that no continuous segment is shorter than a preset limit (determined by the minimum_length parameter of the remove_short scope). Segment boundaries are determined from spatial connectivity of residues. This algorithm is primarily intended to remove "floating" residues that are the result of extensive loop truncation.

These algorithms can also be used together in combination. In this case, the chain will be processed sequentially by both algorithms.

Monosaccharide chains

This can be used to trim existing glucosyl chains based on the distance from the residue to which they are attached. Connectivity of glycosyl chains is worked out from distance tests, and the maximum_bond_length parameter can be used to adjust this slightly. Branched glycosyl chains are also handled.

Hetero chains

Residues in these chains are normally deleted, unless an exception is made by specifying the residue codes that are to be retained. This is primarily intended to keep a known ligands of protein classes (e.g. HEM).

Other chains

These are removed from the model.

Sequence similarity calculation

Sequence similarity is calculated from the full alignment supplied (taking all present sequences into account), using a scoring matrix (currently blosum50, blosum62, dayhoff and identity are available). Raw scores are then smoothed using one of two alogrithms:

Sequence similarity calculation is configured individually for the steps that are using it.

Missing value substitution

Governs how missing error values are substituted.

Missing value substitution is configured individually for the steps that are using it.

Command line

phenix.sculptor \
    [ command-line switches ] \
    [ PHIL-format parameter files ] \
    [ PHIL command-line assignments ] \
    [ PDB-files ] \
    [ alignment files ]

Command-line switches

-h, --help            show this help message and exit
--show-defaults       print PHIL and exit
-i, --stdin           read PHIL from stdin as well
-v, --verbosity       set verbosity level (info,debug,verbose)
--version             show program's version number and exit
--text-logfile FILE   Verbatim copy of log stream
--html-logfile FILE   Verbatim copy of log stream in HTML

PHIL arguments

Everything not starting with a dash ('-') is interpreted as a PHIL argument. This can be a PHIL-format file containing parameters, command-line assignment or a file whose type is automatically recognized (based on file extension). Note that sequence files are not accepted on the command line, since associated chains could not easily be guessed and require a fully specified parameter scope.

Specific limitations and possible problems

Processing features

  • Very short residue segments (shorter in min_hss_length consecutive residues than min_hss_length parameter in the chain_to_alignment_matching scope) cannot be reliably aligned to the sequence, and these may be discarded from the model.
  • The similarity algorithm from the deletion scope may result in residues that are aligned with a gap being included in the model. Although this possibly indicates an error in the alignment and is potentially beneficial for molecular replacement, this causes a problem at the rename stage, as there is no 3-letter residue name for a "-"; these residues are named according to the gapname parameter (default: ALA).
  • Residue numbers for gap residues are built up using the residue number of the previous non-gap residue and an insertion code (A-Z, depending on the number of gap residues after the previous non-gap residue).

Error messages

  • No pdb files specified: there are no PDB files to process.
  • Applicable chain_ids not specified for ..: the input file requires the specification chainIDs (sequence file, error files and superposition error files).
  • No atoms left after atom selection: the atom selection provided results in an empty structure.
  • Error while reading alignment: ..: some error occurred while trying to read an alignment file:
    • ..: input alignment is empty: no alignment sequences were found in alignment file ..
    • ..: no alignment sequences match: the target sequence specified for alignment file .. does not match any alignment sequences.
  • Cannot open file: a file cannot be opened for reading (possibly does not exist).
  • No hit with index .. in ..: the requested homology search hit from homology search file .. does not exist.

Warning messages

Alignment

  • Aligner: no aligned candidates: no alignment sequence match the observed chain sequence. In this case a dummy alignment will be used.
  • No sequences read from file: the sequence file given as the target sequence does not contain any sequences.
  • Multiple sequences found, using first: the sequence file given as the target sequence contains multiple sequences.

Sequence files

  • File contains multiple sequences, only the first will be used: the sequence file given as the target sequence contains multiple sequences.

Error files

  • Duplicate resid: '..': resid .. occurs multiple times.
  • Cannot convert '..' to floating-point number: the error value is non-numeric.
  • Error file specified for chain fail criteria: the error values that are specified for a particular chain are rejected, because they fail the set criteria.

Error estimation

  • Homology modelling failed: no homology model can be created.
  • ProQ2 error estimation failed: no error values could be obtained from the ProQ2 server.
  • ProQ2 structure contains multiple chains: although a single chain was submitted to ProQ2, the results returned contain multiple chains.
  • Chain '..' is not '..': chain .. is not recognised as a macromolecular chain.
  • PDB could not be matched to sequence: sequence-to-structure matching fail for the returned results.

References

[Schwarzenbacher2004]The importance of alignment accuracy for molecular replacement. R. Schwarzenbacher, A. Godzik, S. K. Grzechnik and L. Jaroszewski Acta Cryst. D60, 1229-1236 (2004)

Citation

Improvement of molecular-replacement models with Sculptor. G. Bunkoczi and R. J. Read Acta Cryst. D67, 303-312 (2011)

Additional information

List of all available keywords

  • inputInput files
    • modelInput pdb file
      • file_name = None PDB file name
      • selection = all Selection string
      • remove_alternate_conformations = False Remove alternate conformations
      • sanitize_occupancies = False Sets occupancies > 1.0 to 1.0
      • keep_crystal_symmetry = False Keeps the crystal symmetry of the model
    • alignmentInput alignment file
      • file_name = None Alignment file name
      • target_sequence = None Target sequence file name (to locate target sequence in alignment)
    • homology_searchAlignment from homology search file
      • file_name = None Homology search file
      • use = None Which alignments to use
    • sequenceInput sequence file
      • file_name = None Sequence file
      • chain_ids = None Which chain IDs the target sequence applies
    • errorsEstimated errors for chain
      • file_name = None Error file name
      • chain_ids = None Which chain IDs the error file corresponds to
    • superposition_errorsSuperposition errors for chain
      • file_name = None Error file name
      • chain_ids = None Which chain IDs the error file corresponds to
  • outputOutput options
    • job_title = None Job title in PHENIX GUI, not used on command line
    • folder = . Output file folder
    • root = sculpt Output file root
    • format = *pdb Output file format
  • chain_to_alignment_matchingChain-to-alignment matching options
    • consecutivity = *geometry numbering Consecutivity criterion to detect chain breaks
    • min_hss_length = 3 Minimum length of a sequence fragment to be included in chain alignment
    • max_seed_hss_count = 12 Number of HSS to use in extensive search
    • max_completion_hss_count = 6 Number of HSS to use in gap filling
    • min_sequence_overlap = 10 Minimum overlap between sequences to perform full alignment
    • min_sequence_identity = 0.80 Minimum sequence identity of accepted chain alignment
  • error_searchParameters for matching error files and/or estimating errors
    • min_sequence_identity = 0.8 Minimum sequence identity to accept error file
    • min_sequence_overlap = 0.8 Minimum sequence overlap to accept error file
    • calculate_if_not_provided = False Use Rosetta and the ProQ2 server to get error estimates
    • output_prefix = None File name for results of intermediate steps
    • homology_modellingParameters for homology modelling
      • min_residue_margin = 2 Minimum number of residues to cut back on both sides of loops
      • residue_distance = 2.5 Distance covered by a single residue (in A)
      • min_edge_segment_length = 5 Discard edge segments if shorter (after considering gap margins)
      • min_internal_segment_length = 2 Discard internal segments if shorter (after considering gap margins)
      • max_loop_length = 60 Maximum loop length
      • rosetta_max_build_attempts = 1000 Maximum build attempts to close loop
      • rosetta_bump_overlap_factor = 0.1 Allows some atomic overlap in initial loop closures
      • rosetta_loop_closure = kic *ngk Algorithm for Rosetta loop closure
      • rosetta_loop_refinement = default quick test fast *no Algorithm for Rosetta loop refinement
  • sculptParameters for sculpting
    • proteinOptions to process protein chains
      • completion = sidechain cbeta_and_pro cbeta Method to build missing sidechain atoms
      • mainchainOptions for main chain processing
        • remove_unaligned = True Delete residues that could not be matched to an alignment
        • deletionMainchain deletion algorithms
          • use = *gap threshold_based_similarity completeness_based_similarity residue_count_based_similarity remove_long rms superposition Algorithm to use
          • gapDelete residue if aligned with gap
            • threshold_based_similarityDelete residue if sequence similarity is low
              • threshold = -0.20 Threshold to accept a residue
              • similarity_calculationConfigure sequence similarity calculation
                • matrix = blosum50 *blosum62 dayhoff identity Similarity matrix
                • smoothingConfigure raw similarity smoothing
                  • use = *linear spatial Method to use
                  • linearParameters for linear averaging
                    • window = 5 Averaging window width
                    • weighting = *triangular uniform Weighting scheme
                  • spatialParameters for spatial averaging
                    • gap_bleed_length = 3 Alignment positions affected by gaps
                    • maximum_distance = 10 Spatial distance for averaging
            • completeness_based_similarityDelete residues based on sequence similarity to get same number of gaps as the Schwarzenbacher algorithm
              • offset = 0.0 Completeness in fraction of model length (0.0 = completeness from Schwarzenbacher algorithm, useful range: +/-0.05)
              • similarity_calculationConfigure sequence similarity calculation
                • matrix = blosum50 *blosum62 dayhoff identity Similarity matrix
                • smoothingConfigure raw similarity smoothing
                  • use = *linear spatial Method to use
                  • linearParameters for linear averaging
                    • window = 5 Averaging window width
                    • weighting = *triangular uniform Weighting scheme
                  • spatialParameters for spatial averaging
                    • gap_bleed_length = 3 Alignment positions affected by gaps
                    • maximum_distance = 10 Spatial distance for averaging
            • residue_count_based_similarityDelete residues based on sequence similarity to delete the same number of residues as the Schwarzenbacher algorithm
              • offset = 0.0 Completeness in fraction of model length (0.0 = completeness from Schwarzenbacher algorithm, useful range: +/-0.05)
              • similarity_calculationConfigure sequence similarity calculation
                • matrix = blosum50 *blosum62 dayhoff identity Similarity matrix
                • smoothingConfigure raw similarity smoothing
                  • use = *linear spatial Method to use
                  • linearParameters for linear averaging
                    • window = 5 Averaging window width
                    • weighting = *triangular uniform Weighting scheme
                  • spatialParameters for spatial averaging
                    • gap_bleed_length = 3 Alignment positions affected by gaps
                    • maximum_distance = 10 Spatial distance for averaging
            • remove_longDelete gap segments if longer than a threshold
              • minimum_length = 3 Minimum length for mainchain segment to remove
            • rmsDelete residues if estimated error is larger than a threshold
              • threshold = 5.0 Maximum allowed error for a residue
              • missing_value_substitutionPolicy to fill in missing values
                • use = *maximum_value scaled_interpolated_value Algorithm to use
                • maximum_valueSubstitute maximum from the sequence
                  • scaled_interpolated_valueSubstitute interpolated value scaled with the distance
                    • extrapolation_step_scale = 1.20 Stepwise scale factor for extrapolation
                    • interpolation_step_scale = 1.10 Stepwise scale factor for extrapolation
              • superpositionDelete residues if estimated error is larger than a threshold
                • threshold = 2.0 Maximum allowed error for a residue
                • missing_value_substitutionPolicy to fill in missing values
                  • use = *maximum_value scaled_interpolated_value Algorithm to use
                  • maximum_valueSubstitute maximum from the sequence
                    • scaled_interpolated_valueSubstitute interpolated value scaled with the distance
                      • extrapolation_step_scale = 1.20 Stepwise scale factor for extrapolation
                      • interpolation_step_scale = 1.10 Stepwise scale factor for extrapolation
              • polishingMainchain polishing algorithms
                • use = remove_short undo_short keep_regular Algorithm to use
                • remove_shortDelete short unconnected segments
                  • minimum_length = 3 Minimum length
                • undo_shortDelete short gaps
                  • maximum_length = 2 Maximum length
                • keep_regularKeep residues in secondary structure
                  • maximum_length = 1 Maximum length
            • bfactorConfigure B-factor modification
              • use = *original asa similarity rms Algorithm to use
              • minimum_b = 10.00 Minimum B-factor
              • originalUse original bfactors to predict new B-values
                • factor = 1.00 Scale factor
              • asaUse accessible surface area to predict new B-values
                • precision = 960 Number of points per atom
                • probe_radius = 1.40 Radius for probing surface accessibility
                • factor = 2.00 Scale factor
              • similarityUse sequence similarity to predict new B-values
                • factor = -100.00 Scale factor
                • similarity_calculationConfigure sequence similarity calculation
                  • matrix = blosum50 *blosum62 dayhoff identity Similarity matrix
                  • smoothingConfigure raw similarity smoothing
                    • use = *linear spatial Method to use
                    • linearParameters for linear averaging
                      • window = 5 Averaging window width
                      • weighting = *triangular uniform Weighting scheme
                    • spatialParameters for spatial averaging
                      • gap_bleed_length = 3 Alignment positions affected by gaps
                      • maximum_distance = 10 Spatial distance for averaging
              • rmsUse external RMS error estimates to calculate B-values
                • factor = 1.00 Scale factor
                • missing_value_substitutionPolicy to fill in missing values
                  • use = *maximum_value scaled_interpolated_value Algorithm to use
                  • maximum_valueSubstitute maximum from the sequence
                    • scaled_interpolated_valueSubstitute interpolated value scaled with the distance
                      • extrapolation_step_scale = 1.20 Stepwise scale factor for extrapolation
                      • interpolation_step_scale = 1.10 Stepwise scale factor for extrapolation
              • renumberResidue renumbering
                • use = model *target original Method to use
                • start = 1 Start residue number
              • pruningOptions for sidechain pruning
                • use = null *schwarzenbacher similarity Algorithm to use
                • pruning_level_unaligned = 2 Pruning level for residues that could not be matched to an alignment
                • nullDo not impose bond distance threshold
                  • schwarzenbacherTruncate atoms if target residue != source residue
                    • pruning_level = 2 Level of truncation
                  • similarityTruncate atoms based on sequence similarity
                    • pruning_level = 2 Level of intermediate truncation
                    • full_length_limit = 0.2 Limit of no truncation
                    • full_truncation_limit = -0.2 Limit for full truncation
                    • similarity_calculationConfigure sequence similarity calculation
                      • matrix = blosum50 *blosum62 dayhoff identity Similarity matrix
                      • smoothingConfigure raw similarity smoothing
                        • use = *linear spatial Method to use
                        • linearParameters for linear averaging
                          • window = 1 Averaging window width
                          • weighting = *triangular uniform Weighting scheme
                        • spatialParameters for spatial averaging
                          • gap_bleed_length = 3 Alignment positions affected by gaps
                          • maximum_distance = 10 Spatial distance for averaging
                • renameResidue renaming
                  • use = original *target Method to use
                  • keep_ptm = False Preserve post-translational modification of model residue if base residue types agree
                  • gapname = ALA Name residues corresponding to alignment gaps
                • mappingOptions for sidechain mapping
                  • use = *connectivity geometry Algorithm to use
                  • map_if_identical = True Do mapping procedure for identical residues types
                  • connectivityMatch atoms by connectivity
                    • match_chemical_elements = True Take chemical element into account
                  • geometryMatch atoms by geometry considering all rotamers
                    • match_chemical_elements = False Take chemical element into account
                    • tolerance = 0.1 Distance tolerance
                    • fine_sampling = False Use fine sampling for rotamers
              • dnaOptions to process DNA chains
                • mainchainOptions for main chain processing
                  • remove_unaligned = True Delete residues that could not be matched to an alignment
                  • deletionMainchain deletion algorithms
                    • use = *all superposition Algorithm to use
                    • allDelete all residues
                      • superpositionDelete residues if estimated error is larger than a threshold
                        • threshold = 2.0 Maximum allowed error for a residue
                        • missing_value_substitutionPolicy to fill in missing values
                          • use = *maximum_value scaled_interpolated_value Algorithm to use
                          • maximum_valueSubstitute maximum from the sequence
                            • scaled_interpolated_valueSubstitute interpolated value scaled with the distance
                              • extrapolation_step_scale = 1.20 Stepwise scale factor for extrapolation
                              • interpolation_step_scale = 1.10 Stepwise scale factor for extrapolation
                      • polishingMainchain polishing algorithms
                        • use = remove_short Algorithm to use
                        • remove_shortDelete short unconnected segments
                          • minimum_length = 3 Minimum length
                  • rnaOptions to process RNA chains
                    • mainchainOptions for main chain processing
                      • remove_unaligned = True Delete residues that could not be matched to an alignment
                      • deletionMainchain deletion algorithms
                        • use = *all superposition Algorithm to use
                        • allDelete all residues
                          • superpositionDelete residues if estimated error is larger than a threshold
                            • threshold = 2.0 Maximum allowed error for a residue
                            • missing_value_substitutionPolicy to fill in missing values
                              • use = *maximum_value scaled_interpolated_value Algorithm to use
                              • maximum_valueSubstitute maximum from the sequence
                                • scaled_interpolated_valueSubstitute interpolated value scaled with the distance
                                  • extrapolation_step_scale = 1.20 Stepwise scale factor for extrapolation
                                  • interpolation_step_scale = 1.10 Stepwise scale factor for extrapolation
                          • polishingMainchain polishing algorithms
                            • use = remove_short Algorithm to use
                            • remove_shortDelete short unconnected segments
                              • minimum_length = 3 Minimum length
                      • heteroOptions to process hetero chains
                        • keep = None Keep named hetero residues
                      • monosaccharideOptions to process glycosyl chains
                        • maximum_depth = 0 Keep chain up to maximum depth (None to keep all)
                        • maximum_bond_length = 1.5 Maximum bond length for glycosidic bond