PatternQuery:How to build a query - Revision history

Lukas: /* How to think about queries */

2016-07-26T12:57:12Z

How to think about queries

← Older revision		Revision as of 12:57, 26 July 2016
Line 10:		Line 10:
	'''Get all the residues which are as much as 5Å away from any histidine residue and check if the given pattern contains at least 2 negatively charged amino acids.'''		'''Get all the residues which are as much as 5Å away from any histidine residue and check if the given pattern contains at least 2 negatively charged amino acids.'''

	From scratch you can't probably think out a solution right now, but when you decompose the problem into separate individual sub problems, it is not so difficult after all. (Whenever you are unsure about the meaning of the queries, consult the [[PatternQuery:Language Reference \| language reference]]). For the given problem, the decomposition is as follows:		From scratch you can't probably think out a solution right now, but when you decompose the problem into separate individual sub problems, it is not so difficult after all. (Whenever you are unsure about the meaning of the queries, consult the [[PatternQuery:Language Reference \| language reference]]). For the given problem, the decomposition and the corresponding queries are as follows:
			{{col-begin}}
			{{col-2}}
	#Select histidine residues		#Select histidine residues
	#Select residual surrounding of a pattern up to 5Å.		#Select residual surrounding of a pattern up to 5Å.
Line 17:		Line 18:
	#Count the amino acids.		#Count the amino acids.
	#Filter the histidine plus its surrounding matching the condition above.		#Filter the histidine plus its surrounding matching the condition above.
			{{col-2}}
	~~Now we are ready for constructing individual queries:~~
	#<code>[[PatternQuery:Language Reference#Residues \| Residues("HIS")]]</code>		#<code>[[PatternQuery:Language Reference#Residues \| Residues("HIS")]]</code>
	#<code>[[PatternQuery:Language Reference#AmbientResidues \| AmbientResidues(5)]]</code>		#<code>[[PatternQuery:Language Reference#AmbientResidues \| AmbientResidues(5)]]</code>
Line 24:		Line 24:
	#<code>[[PatternQuery:Language Reference#Count\| Count(residues)]]</code>		#<code>[[PatternQuery:Language Reference#Count\| Count(residues)]]</code>
	#<code>[[PatternQuery:Language Reference#Filter\| Filter(condition)]]</code>		#<code>[[PatternQuery:Language Reference#Filter\| Filter(condition)]]</code>
			{{col-end}}
	It wasn't that difficult, was it? When we have composed all the queries, we can compose them together in order to achieve our goal as highlighted in the query bellow and in the illustrative info-graphics:		It wasn't that difficult, was it? When we have composed all the queries, we can compose them together in order to achieve our goal as highlighted in the query bellow and in the illustrative info-graphics:

Lukas at 12:51, 26 July 2016

2016-07-26T12:51:26Z

Show changes

Lukas: /* Count() */

2016-07-26T12:50:38Z

Count()

← Older revision		Revision as of 12:50, 26 July 2016
Line 243:		Line 243:

	====Count()====		====Count()====
	* '''[PDB id: 1hho]''' Usually it is convenient to utilize this function inside a filtering query. <syntaxhighlight lang="python" inline>~~The~~ Count()</syntaxhighlight> query counts the number of occurrences of a pattern inside a different pattern.		* '''[PDB id: 1hho]''' Usually it is convenient to utilize this function inside a filtering query. The <syntaxhighlight lang="python" inline>Count()</syntaxhighlight> query counts the number of occurrences of a pattern inside a different pattern.
	* <syntaxhighlight lang="python" inline>Residues("HEM").ConnectedResidues(2).Filter(lambda m: m.Count(Atoms("S")) == 1)</syntaxhighlight> – Returns patterns composed of a HEM residue surrounded by two layers of bonded residues in case that the whole pattern contains exactly one sulphur atom.		* <syntaxhighlight lang="python" inline>Residues("HEM").ConnectedResidues(2).Filter(lambda m: m.Count(Atoms("S")) == 1)</syntaxhighlight> – Returns patterns composed of a HEM residue surrounded by two layers of bonded residues in case that the whole pattern contains exactly one sulphur atom.
	* <syntaxhighlight lang="python" inline>Residues("CYS").ConnectedResidues(1).Filter(lambda m: m.Count(Residues("VAL")) == 2)</syntaxhighlight> – Returns a cysteine residue which is surrounded from both sides by valine residues.		* <syntaxhighlight lang="python" inline>Residues("CYS").ConnectedResidues(1).Filter(lambda m: m.Count(Residues("VAL")) == 2)</syntaxhighlight> – Returns a cysteine residue which is surrounded from both sides by valine residues.
	* ''Type: Count(where: Pattern, what: PatternSeq) -> Integer''.		* ''Type: Count(where: Pattern, what: PatternSeq) -> Integer''.


	====Contains()====		====Contains()====

Lukas: /* Topology function */

2016-07-26T12:50:17Z

Topology function

← Older revision		Revision as of 12:50, 26 July 2016
Line 213:		Line 213:
	* <syntaxhighlight lang="python" inline>Atoms("Fe").AmbientAtoms(4)</syntaxhighlight> – returns all the atoms, which are closer than 4Å from the center of mass of iron atom.		* <syntaxhighlight lang="python" inline>Atoms("Fe").AmbientAtoms(4)</syntaxhighlight> – returns all the atoms, which are closer than 4Å from the center of mass of iron atom.
	* ''Type: AmbientAtoms(pattern: PatternSeq, r: Number) -> Patterns''		* ''Type: AmbientAtoms(pattern: PatternSeq, r: Number) -> Patterns''



	====AmbientResidues()====		====AmbientResidues()====
	* '''[PDB id: 1hho]''' Returns all the residues, which are within nA from the geometrical center of a given pattern.		* '''[PDB id: 1hho]''' Returns all the residues, which are within nÅ from the geometrical center of a given pattern.
	* <syntaxhighlight lang="python" inline>Residues("HEM").AmbientResidues(4)</syntaxhighlight> – returns all the residues, which are closer than 4Å from the center of mass of HEM residues.		* <syntaxhighlight lang="python" inline>Residues("HEM").AmbientResidues(4)</syntaxhighlight> – returns all the residues, which are closer than 4Å from the center of mass of HEM residues.
	* ''Type: AmbientResidues(pattern: PatternSeq, r: Number) -> Patterns'''		* ''Type: AmbientResidues(pattern: PatternSeq, r: Number) -> Patterns'''


	====Near()====		====Near()====
Line 227:		Line 227:
	* ''Type: Near(r: Number, patterns: PatternSeq+) -> Patterns''		* ''Type: Near(r: Number, patterns: PatternSeq+) -> Patterns''


			====Inside()====
			* '''[PDB id: 1hho]''' Inside query tries to identify given pattern within another pattern. It is particularly useful for location of specific atomic arrangements within a more general ones.
			* <syntaxhighlight lang="python" inline>Residues("Gly").Inside(Chains("A"))</syntaxhighlight> - Returns glycine residues found on the chain A.
			* <syntaxhighlight lang="python" inline>Atoms("S").Inside(HetResidues())</syntaxhighlight> - Returns sulphur atoms found in the heteroatom residues
			* ''Type: Inside(patterns: PatternSeq, where: PatternSeq) -> PatternSeq''

	===Filtering===		===Filtering===

Lukas at 12:38, 26 July 2016

2016-07-26T12:38:06Z

← Older revision		Revision as of 12:38, 26 July 2016
Line 1:		Line 1:
	<div class="toclimit-4">		<div class="toclimit-3">

	In order to tune up your queries before executing them on the whole database or just to work with the language interactively, feel free to use the [http://webchem.ncbr.muni.cz/Platform/PatternQuery/Index '''Explorer'''] application, where you can upload a PDB molecule of choice, or load a random sample from the PDB database based on selected properties.		In order to tune up your queries before executing them on the whole database or just to work with the language interactively, feel free to use the [http://webchem.ncbr.muni.cz/Platform/PatternQuery/Index '''Explorer'''] application, where you can upload a PDB molecule of choice, or load a random sample from the PDB database based on selected properties.
Line 49:		Line 49:

	==Atoms==		==Atoms==
	~~===~~ Basic queries ~~===~~		{{big \| Basic queries}}
	====Atoms()====		====Atoms()====
	* '''[PDB id: 2hhb]''' Returns a sequence of individual atoms based on element type provided in the argument. More elements can be specified, if separated by a comma. In case no argument is provided a list of all the atoms is returned.		* '''[PDB id: 2hhb]''' Returns a sequence of individual atoms based on element type provided in the argument. More elements can be specified, if separated by a comma. In case no argument is provided a list of all the atoms is returned.
Line 75:		Line 75:
	* <syntaxhighlight lang="python" inline>AtomIdRange(1, 10)</syntaxhighlight> – returns 10 atoms with IDs from the interval <1, 10>, as specified in the input file.		* <syntaxhighlight lang="python" inline>AtomIdRange(1, 10)</syntaxhighlight> – returns 10 atoms with IDs from the interval <1, 10>, as specified in the input file.
	* ''Type: AtomIdRange(minId: Integer, maxId: ?Integer) -> Atoms''		* ''Type: AtomIdRange(minId: Integer, maxId: ?Integer) -> Atoms''


	====NotAtomNames()====		====NotAtomNames()====
Line 80:		Line 81:
	* <syntaxhighlight lang="python" inline>NotAtomNames("C", "N", "CA", "O")</syntaxhighlight> – returns all the atoms with names other than C, CA, N and O. i.e. only the side chain atoms of the protein .		* <syntaxhighlight lang="python" inline>NotAtomNames("C", "N", "CA", "O")</syntaxhighlight> – returns all the atoms with names other than C, CA, N and O. i.e. only the side chain atoms of the protein .
	* ''Type: NotAtomNames(names: String+) -> Atom.''		* ''Type: NotAtomNames(names: String+) -> Atom.''


	====NotAtomIds()====		====NotAtomIds()====
Line 99:		Line 101:
	* <syntaxhighlight lang="python" inline>RingAtoms(Atoms("N"), Rings(2 * ["C"] + ["N"] + ["C"] + ["N"]))</syntaxhighlight> – Returns all the nitrogen atoms on the histidine side chain.		* <syntaxhighlight lang="python" inline>RingAtoms(Atoms("N"), Rings(2 * ["C"] + ["N"] + ["C"] + ["N"]))</syntaxhighlight> – Returns all the nitrogen atoms on the histidine side chain.
	* ''Type: RingAtoms(atom: Atoms, ring: ?Rings) -> Atoms.''		* ''Type: RingAtoms(atom: Atoms, ring: ?Rings) -> Atoms.''


	==Residues==		==Residues==
	~~===~~ Basic queries~~===~~		{{big \| Basic queries}}
	====Residues()====		====Residues()====
	* '''[PDB id: 2hhb]''' Returns a sequence of individual residues specified by a function argument. More residues can be specified, if separated by a comma.		* '''[PDB id: 2hhb]''' Returns a sequence of individual residues specified by a function argument. More residues can be specified, if separated by a comma.
Line 107:		Line 110:
	* <syntaxhighlight lang="python" inline>Residues ("HEM", "ALA")</syntaxhighlight> – Returns a set of HEM and ALA residues.		* <syntaxhighlight lang="python" inline>Residues ("HEM", "ALA")</syntaxhighlight> – Returns a set of HEM and ALA residues.
	* ''Type: Residues(names: Value*) -> Residues.''		* ''Type: Residues(names: Value*) -> Residues.''



Line 114:		Line 116:
	* <syntaxhighlight lang="python" inline>NotResidues("HEM")</syntaxhighlight> – returns a set of residues, which does not have a HEM in their name.		* <syntaxhighlight lang="python" inline>NotResidues("HEM")</syntaxhighlight> – returns a set of residues, which does not have a HEM in their name.
	* ''Type: NotResidues(names: Value+) -> Residues.''		* ''Type: NotResidues(names: Value+) -> Residues.''



Line 127:		Line 128:
	* <syntaxhighlight lang="python" inline>ResidueIdRange("A", 50, 100)</syntaxhighlight> – returns a set of residues on chain A from the ID 50 to 100.		* <syntaxhighlight lang="python" inline>ResidueIdRange("A", 50, 100)</syntaxhighlight> – returns a set of residues on chain A from the ID 50 to 100.
	* ''Type: ResidueIdRange(chain: String, min: Integer, max: Integer) -> Residues''.		* ''Type: ResidueIdRange(chain: String, min: Integer, max: Integer) -> Residues''.



Line 135:		Line 135:
	* <syntaxhighlight lang="python" inline>NotAminoAcids(NoWaters=False)</syntaxhighlight> – Returns all the nonstandard residues incorporated in the protein structure inclusive solvent (HOH and WAT residues).		* <syntaxhighlight lang="python" inline>NotAminoAcids(NoWaters=False)</syntaxhighlight> – Returns all the nonstandard residues incorporated in the protein structure inclusive solvent (HOH and WAT residues).
	* ''Type: NotAminoAcids() -> Residues''.		* ''Type: NotAminoAcids() -> Residues''.



Line 144:		Line 143:
	* <syntaxhighlight lang="python" inline>AminoAcids(ChargeType="Polar")</syntaxhighlight> – Returns all polar amino acids based on the type of their side chain.		* <syntaxhighlight lang="python" inline>AminoAcids(ChargeType="Polar")</syntaxhighlight> – Returns all polar amino acids based on the type of their side chain.
	* ''Type: AminoAcids() -> Residues.''		* ''Type: AminoAcids() -> Residues.''


	====HetResidues()====		====HetResidues()====
Line 149:		Line 149:
	* <syntaxhighlight lang="python" inline>HetResidues()</syntaxhighlight> – A set of hetatom residues.		* <syntaxhighlight lang="python" inline>HetResidues()</syntaxhighlight> – A set of hetatom residues.
	* ''Type: HetResidues() -> Residues''		* ''Type: HetResidues() -> Residues''


	==Patterns==		==Patterns==
	~~===~~Structure specification~~===~~		{{big \| Structure specification}}
	PQ can select residues or their parts based on their name or Id, however, the true power of PQ lies in its ability to utilize the chemical nature of the input structures and select patterns purely based on elements and the connectivity among them.
			PQ can select residues or their parts based on their name or Id, however, the true power of PQ lies in its ability to utilize the geometrical and chemical nature of the input structures and select patterns purely based on elements, topology and the connectivity among them.


Line 189:		Line 191:
	* <syntaxhighlight lang="python" inline> RegularMotifs(".P.").Filter(lambda l: l.Count(NotAminoAcids()) == 0)</syntaxhighlight> - Finds 3 consecutive residues, where the middle one is proline and verifies that neither of them is outside the ''standard 20''.		* <syntaxhighlight lang="python" inline> RegularMotifs(".P.").Filter(lambda l: l.Count(NotAminoAcids()) == 0)</syntaxhighlight> - Finds 3 consecutive residues, where the middle one is proline and verifies that neither of them is outside the ''standard 20''.
	* ''Type: RegularMotifs(regex: Value) -> Patterns''		* ''Type: RegularMotifs(regex: Value) -> Patterns''


	====Cluster()====		====Cluster()====
Line 231:		Line 234:
	* <syntaxhighlight lang="python" inline> Residues().Filter(lambda m: m.Count(Atoms("O")) == 2)</syntaxhighlight> returns all the residues containing exactly two oxygen atoms.		* <syntaxhighlight lang="python" inline> Residues().Filter(lambda m: m.Count(Atoms("O")) == 2)</syntaxhighlight> returns all the residues containing exactly two oxygen atoms.
	* ''Type: Filter(patterns: PatternSeq, filter: Pattern->Bool) -> Patterns''		* ''Type: Filter(patterns: PatternSeq, filter: Pattern->Bool) -> Patterns''


	====Count()====		====Count()====
Line 252:		Line 256:
	* For comparison please compare with the results of the query <syntaxhighlight lang="python" inline>Atoms("Zn").AmbientAtoms(4)</syntaxhighlight>		* For comparison please compare with the results of the query <syntaxhighlight lang="python" inline>Atoms("Zn").AmbientAtoms(4)</syntaxhighlight>
	* ''Type: IsConnected(pattern: Pattern) -> Bool.''		* ''Type: IsConnected(pattern: Pattern) -> Bool.''


	====IsConnectedTo()====		====IsConnectedTo()====
Line 263:		Line 268:
	* <syntaxhighlight lang="python" inline>Residues("ALA").Filter(lambda m: m.IsNotConnectedTo(Residues("GLY")))</syntaxhighlight> – Returns all the alanine residues which are not directly connected to the glycine residues.		* <syntaxhighlight lang="python" inline>Residues("ALA").Filter(lambda m: m.IsNotConnectedTo(Residues("GLY")))</syntaxhighlight> – Returns all the alanine residues which are not directly connected to the glycine residues.
	* ''Type: IsNotConnectedTo(current: Pattern, patterns: PatternSeq) -> Bool''		* ''Type: IsNotConnectedTo(current: Pattern, patterns: PatternSeq) -> Bool''



Line 271:		Line 275:
	* <syntaxhighlight lang="python" inline>Atoms("Fe"). ConnectedAtoms (2)</syntaxhighlight> – Previous selection and all the atoms which are covalently bonded to them (i.e. additional layer of bonded atom). In other words the output composes of all the atoms which are 2 bonds away from the iron atom.		* <syntaxhighlight lang="python" inline>Atoms("Fe"). ConnectedAtoms (2)</syntaxhighlight> – Previous selection and all the atoms which are covalently bonded to them (i.e. additional layer of bonded atom). In other words the output composes of all the atoms which are 2 bonds away from the iron atom.
	* ''Type: ConnectedAtoms(pattern: PatternSeq, n: Integer) -> Patterns''		* ''Type: ConnectedAtoms(pattern: PatternSeq, n: Integer) -> Patterns''

Lukas: /* Topology function */

2016-07-26T12:25:55Z

Topology function

Show changes

Lukas at 13:41, 25 April 2015

2015-04-25T13:41:47Z

Show changes

Lukas: Lukas moved page MotiveQuery:How to build a query to PatternQuery:How to build a query

2015-04-25T12:56:49Z

Lukas moved page MotiveQuery:How to build a query to PatternQuery:How to build a query

← Older revision	Revision as of 12:56, 25 April 2015
(No difference)

Lukas at 15:19, 20 April 2015

2015-04-20T15:19:54Z

Lukas: /* RegularMotifs() */

2015-04-20T12:59:02Z

RegularMotifs()

← Older revision		Revision as of 12:59, 20 April 2015
Line 182:		Line 182:

	====RegularMotifs()====		====RegularMotifs()====
	* From the primary sequence extracts sequence motifs based on the input regular expression. Please note, that MQ does not check whether there is a gap in the chain e.g. if HIS 28 is followed by the residue 30 ALA query ‘HA’ returns positive match for such example.		* '''[PDB id: 1het]''' From the primary sequence extracts sequence motifs based on the input regular expression. Please note, that MQ does not check whether there is a gap in the chain e.g. if HIS 28 is followed by the residue 30 ALA query ‘HA’ returns positive match for such example.
	* Additionally, modified residues are treated as they were not modified, as long as the information about modification is properly annotated in the ''MODRES'' or ''_pdbx_struct_mod_residue'' fields. Therefore, a letter ''P'' stands for a proline residue so as all its modifications, i.e. '''HYP''' (hydroxyproline).		* Additionally, modified residues are treated as they were not modified, as long as the information about modification is properly annotated in the ''MODRES'' or ''_pdbx_struct_mod_residue'' fields. Therefore, a letter ''P'' stands for a proline residue so as all its modifications, i.e. '''HYP''' (hydroxyproline).
	* <code> RegularMotifs("HH")</code> – Finds two consecutive histidine residues or their modifications. ~~'''[PDB id: 1het]'''~~		* <code> RegularMotifs("HH")</code> – Finds two consecutive histidine residues or their modifications.
	* <code> RegularMotifs("G.{1,2}G")</code> – Finds two glycine residues separated by one or two other residues. ~~'''[PDB id: 1het]'''~~		* <code> RegularMotifs("G.{1,2}G")</code> – Finds two glycine residues separated by one or two other residues.
	* <code> RegularMotifs("G.{1,2}G").Filter(lambda m: m.IsConnected())</code> – Finds two glycine residues separated by one or two residues and verifies that all of them are bonded. ~~'''[PDB id: 1het]'''~~		* <code> RegularMotifs("G.{1,2}G").Filter(lambda m: m.IsConnected())</code> – Finds two glycine residues separated by one or two residues and verifies that all of them are bonded.
	* <code> RegularMotifs(".P.").Filter(lambda l: l.Count(NotAminoAcids()) == 0)</code> - Finds a 3 consecutive residue and verifies that neither of them is outside the ''standard 20''. ~~'''[PDB id: 1het]'''~~		* <code> RegularMotifs(".P.").Filter(lambda l: l.Count(NotAminoAcids()) == 0)</code> - Finds a 3 consecutive residue and verifies that neither of them is outside the ''standard 20''.
	* ''Type: RegularMotifs(regex: Value) -> Fragments''		* ''Type: RegularMotifs(regex: Value) -> Fragments''

← Older revision		Revision as of 15:19, 20 April 2015
Line 1:		Line 1:
	<div class="toclimit-4">		<div class="toclimit-4">

	In order to tune up your queries before executing them on the whole database or just to ~~try out an interactive~~ work with the language, feel free to use [http://webchem.ncbr.muni.cz/Platform/MotiveQuery/Index '''Explorer'''] application, where you can upload a PDB molecule of choice, or load a random sample from the PDB database based on selected properties.		In order to tune up your queries before executing them on the whole database or just to work with the language interactively, feel free to use the [http://webchem.ncbr.muni.cz/Platform/MotiveQuery/Index '''Explorer'''] application, where you can upload a PDB molecule of choice, or load a random sample from the PDB database based on selected properties.

	You can either try one of our ready-to-use examples or try to make up one of your own.		You can either try one of our ready-to-use examples or try to make up one of your own.

	==How to think about queries==		==How to think about queries==
	When building queries, you have to decompose the problem in smaller chunks, think a query for each of the pieces and ~~them~~ wisely bind them together. Let us have a goal:		When building queries, you have to decompose the problem into smaller chunks, think of a query for each of the pieces and then wisely bind them together. Let us have a goal:

	'''Get all the residues which are as much as 5Å away from any histidine residue and check if the given fragment contains at least 2 negatively charged amino acids.'''		'''Get all the residues which are as much as 5Å away from any histidine residue and check if the given fragment contains at least 2 negatively charged amino acids.'''

	From scratch you can't probably think out a solution right now, but when you decompose the problem into separate individual sub problems, it is not so difficult after all. (Whenever you are unsure about the meaning of the queries, consult the [[MotiveQuery:Language Reference \| language reference]]). For given problem, the decomposition is as follows:		From scratch you can't probably think out a solution right now, but when you decompose the problem into separate individual sub problems, it is not so difficult after all. (Whenever you are unsure about the meaning of the queries, consult the [[MotiveQuery:Language Reference \| language reference]]). For the given problem, the decomposition is as follows:

	#Select histidine residues		#Select histidine residues
Line 37:		Line 37:
	==Ready-to-use examples==		==Ready-to-use examples==

	Now when we are aware of how to think about queries, you are ready to browse a plenty of different examples listed below. The text is separated to three plus one part which differs by data type queries are operated (Atoms, Residues and Fragments). The first two categories deal with only basic ''Atom'' or ''Residue'' selections. Outputs of these two types of queries are Atoms and Residues respectively. Last category is Fragments, which ~~contain numerous~~ advanced queries ~~demonstrating~~ versatility and power of '''MQ'''. These queries operate on all results provided by both Atom and Residue queries. On the top of that, you can browse several use biologically relevant [[MotiveQuery:Use Cases \| use cases]].		Now when we are aware of how to think about queries, you are ready to browse a plenty of different examples listed below. The text is separated into three plus one part which differs by data type queries are operated (Atoms, Residues and Fragments). The first two categories deal with only basic ''Atom'' or ''Residue'' selections. Outputs of these two types of queries are Atoms and Residues respectively. Last category is 'Fragments', which contains a number of advanced queries, these queries demonstrate versatility and a power of '''MQ'''. These queries operate on all results provided by both Atom and Residue queries. On the top of that, you can browse several use biologically relevant [[MotiveQuery:Use Cases \| use cases]].


Line 182:		Line 182:

	====RegularMotifs()====		====RegularMotifs()====
	* '''[PDB id: 1het]''' ~~From~~ the primary sequence ~~extracts sequence motifs~~ based on the input regular expression. Please note, that MQ does not check ~~whether there is~~ a gap in the chain e.g. if HIS 28 is followed by the residue 30 ALA query ‘HA’ returns positive match for such example.		* '''[PDB id: 1het]''' Sequence motifs is extracted from the primary sequence based on the input regular expression. Please note, that MQ does not check presence of a gap gap in the chain e.g. if HIS 28 is followed by the residue 30 ALA query ‘HA’ returns positive match for such example.
	* ~~Additionally, modified residues are treated as they were not modified, as long as~~ the information about ~~modification~~ is ~~properly annotated~~ in ~~the~~ ''MODRES'' or ''_pdbx_struct_mod_residue'' fields. Therefore, a letter ''P'' stands for a proline residue so as all its modifications, i.e. '''HYP''' (hydroxyproline).		* In case the information about posttranslational modifications is present in ''MODRES'' or ''_pdbx_struct_mod_residue'' fields, modified residues are treated as standard amino acids. Therefore, a letter ''P'' stands for a proline residue so as all its modifications, e.g. '''HYP''' (hydroxyproline).
	* <code> RegularMotifs("HH")</code> – Finds two consecutive histidine residues or their modifications.		* <code> RegularMotifs("HH")</code> – Finds two consecutive histidine residues or their modifications.
	* <code> RegularMotifs("G.{1,2}G")</code> – Finds two glycine residues separated by one or two other residues.		* <code> RegularMotifs("G.{1,2}G")</code> – Finds two glycine residues separated by one or two other residues.
	* <code> RegularMotifs("G.{1,2}G").Filter(lambda m: m.IsConnected())</code> – Finds two glycine residues separated by one or two residues and verifies that all of them are bonded.		* <code> RegularMotifs("G.{1,2}G").Filter(lambda m: m.IsConnected())</code> – Finds two glycine residues separated by one or two residues and verifies that all of them are bonded.
	* <code> RegularMotifs(".P.").Filter(lambda l: l.Count(NotAminoAcids()) == 0)</code> - Finds a 3 consecutive ~~residue~~ and verifies that neither of them is outside the ''standard 20''.		* <code> RegularMotifs(".P.").Filter(lambda l: l.Count(NotAminoAcids()) == 0)</code> - Finds 3 consecutive residues, where the middle one is proline and verifies that neither of them is outside the ''standard 20''.
	* ''Type: RegularMotifs(regex: Value) -> Fragments''		* ''Type: RegularMotifs(regex: Value) -> Fragments''

	====Cluster()====		====Cluster()====
	* Clusters ~~identified~~ results to a single fragment based on their distance ~~in angstroms~~. On contrary to the <code>Near()</code> query <code>Cluster()</code> does not provide a count check. See example below.		* Clusters identifies results to a single fragment based on their distance [Å]. On contrary to the <code>Near()</code> query <code>Cluster()</code> does not provide a count check. See example below.
	* <code>Cluster(5, Residues("Ala"))</code> – Returns all the alanine residues which are at most 5A distant to each other.		* <code>Cluster(5, Residues("Ala"))</code> – Returns all the alanine residues which are at most 5A distant to each other.
	* <code>Cluster(3, RingAtoms(Atoms("N"), Rings(2 * ["C"] + ["N"] + ["C"] + ["N"])))</code> – Returns all the nitrogen atoms from particular rings to a single fragment in case the atoms are at most 3A distant to each other.		* <code>Cluster(3, RingAtoms(Atoms("N"), Rings(2 * ["C"] + ["N"] + ["C"] + ["N"])))</code> – Returns all the nitrogen atoms from particular rings to a single fragment in case the atoms are at most 3A distant to each other.
	* <code>Cluster(2 , Atoms("C"), Atoms("C"))</code> – Returns all the carbon atoms which are pairwise closer than 2A. In case any other carbon atom would be inside this 2A sphere, it is also included in the result. Therefore, if you insist on exactly 2 carbon atoms to be returned, use <code>Near()</code> query instead.		* <code>Cluster(2 , Atoms("C"), Atoms("C"))</code> – Returns all the carbon atoms which are pairwise closer than 2Å. In case any other carbon atom would be inside this 2Å sphere, it is also included in the result. Therefore, if you insist on exactly 2 carbon atoms to be returned, use <code>Near()</code> query instead.
	* ''Type: Cluster(r: Number, fragments: FragmentSeq) -> Fragments''		* ''Type: Cluster(r: Number, fragments: FragmentSeq) -> Fragments''

Line 207:		Line 207:
	===Topology function===		===Topology function===
	====AmbientAtoms()====		====AmbientAtoms()====
	* '''[PDB id: 1hho]''' Returns all the atoms, which are within ~~n A~~ from the geometrical center of a given fragment.		* '''[PDB id: 1hho]''' Returns all the atoms, which are within nÅ from the geometrical center of a given fragment.
	* <code>Atoms("Fe").AmbientAtoms(4)</code> – returns all the atoms, which are closer than 4A from the center of mass of iron atom.		* <code>Atoms("Fe").AmbientAtoms(4)</code> – returns all the atoms, which are closer than 4Å from the center of mass of iron atom.
	* ''Type: AmbientAtoms(fragment: FragmentSeq, r: Number) -> Fragments''		* ''Type: AmbientAtoms(fragment: FragmentSeq, r: Number) -> Fragments''

Line 214:		Line 214:

	====AmbientResidues()====		====AmbientResidues()====
	* '''[PDB id: 1hho]''' Returns all the residues, which are within ~~n A~~ from the geometrical center of a given fragment.		* '''[PDB id: 1hho]''' Returns all the residues, which are within nÅ from the geometrical center of a given fragment.
	* <code>Residues("HEM").AmbientResidues(4)</code> – returns all the residues, which are closer than 4A from the center of mass of HEM residues.		* <code>Residues("HEM").AmbientResidues(4)</code> – returns all the residues, which are closer than 4Å from the center of mass of HEM residues.
	* ''Type: AmbientResidues(fragment: FragmentSeq, r: Number) -> Fragments'		* ''Type: AmbientResidues(fragment: FragmentSeq, r: Number) -> Fragments'

	====Near()====		====Near()====
	* '''[PDB id: 1hho]''' Clusters all the specified fragments, which are pairwise closer ~~in Angströms~~ than a specified argument. Additionally, it checks if the fragment contains exactly specified fragments. On the contrary to the Cluster() query this does the ‘count check’.		* '''[PDB id: 1hho]''' Clusters all the specified fragments, which are pairwise closer [Å] than a specified argument. Additionally, it checks if the fragment contains exactly specified fragments. On the contrary to the Cluster() query this does the ‘count check’.
	* <code>Near(0, Rings(6['C']), Rings(4['C'] + ['N']))</code> – Returns fragments containing only purine. In this example the purine part of tryptophan side chain will be returned.		* <code>Near(0, Rings(6['C']), Rings(4['C'] + ['N']))</code> – Returns fragments containing only purine. In this example the purine part of tryptophan side chain will be returned.
	* <code>Near(2 , Atoms("C"), Atoms("C"), Atoms("C"), Atoms("C"))</code> – Returns fragments which contain exactly 4 carbon atoms within a sphere of 2A.		* <code>Near(2 , Atoms("C"), Atoms("C"), Atoms("C"), Atoms("C"))</code> – Returns fragments which contain exactly 4 carbon atoms within a sphere of 2Å.
	* ''Type: Near(r: Number, fragments: FragmentSeq+) -> Fragments''		* ''Type: Near(r: Number, fragments: FragmentSeq+) -> Fragments''

Line 227:		Line 227:
	===Filtering===		===Filtering===
	====Filter()====		====Filter()====
	* '''[PDB id: 1hho]''' ~~Basically, an argument of~~ the function ~~is a Boolean condition, which~~ is evaluated of each ~~and every~~ fragment of input fragment sequence~~. Referred~~ to as ‘m’ in the following text. Only results satisfying the condition are returned, others are filtered out. Technically, it uses lambda abstraction for filtering a collection of input fragments. The usage is the same as in the Python programming language, and therefore, your previous Python experiences are beneficial.		* '''[PDB id: 1hho]''' Filtering is used for removing unwanted fragments from the result. A condition given as a function argument is evaluated for each fragment from input fragment sequence referred to as ‘m’ in the following text. Only results satisfying the condition are returned, others are filtered out. Technically, it uses lambda abstraction for filtering a collection of input fragments. The usage is the same as in the Python programming language, and therefore, your previous Python experiences are beneficial.
	* <code>Residues().Filter(lambda m: m.IsConnectedTo(Atoms("Fe"))) </code> – returns a set of fragments from all residues which are covalently bonded to the iron atom (excluded the HEM residue).		* <code>Residues().Filter(lambda m: m.IsConnectedTo(Atoms("Fe"))) </code> – returns a set of fragments from all residues which are covalently bonded to the iron atom (excluded the HEM residue).
	* <code> Residues().Filter(lambda m: m.Count(Atoms("O")) == 2)</code> returns all the residues containing exactly two oxygen atoms.		* <code> Residues().Filter(lambda m: m.Count(Atoms("O")) == 2)</code> returns all the residues containing exactly two oxygen atoms.
Line 237:		Line 237:
	* <code>Residues("CYS").ConnectedResidues(1).Filter(lambda m: m.Count(Residues("VAL")) == 2)</code> – Returns a cysteine residue which is surrounded from both sides by valine residues.		* <code>Residues("CYS").ConnectedResidues(1).Filter(lambda m: m.Count(Residues("VAL")) == 2)</code> – Returns a cysteine residue which is surrounded from both sides by valine residues.
	* ''Type: Count(where: Fragment, what: FragmentSeq) -> Integer''.		* ''Type: Count(where: Fragment, what: FragmentSeq) -> Integer''.