Julia-BioStructures
Description
BioStructures提供了读取，写入和操纵大分子结构（蛋白质）的功能。可以将Protein Data Bank（PDB），mmCIF和MMTF格式的文件读入。还提供了访问PDB的功能。
Web
GitHub - BioJulia/BioStructures.jl: A Julia package to read, write and manipulate macromolecular structures (particularly proteins)
Cite
Greener JG, Selvaraj J and Ward BJ. BioStructures.jl: read, write and manipulate macromolecular structures in Julia, Bioinformatics 36(14):4206-4207 (2020) - link - PDF
Language
Julia：https://cn.julialang.org/
Installation:
]
add BioStructuresUsage
Home · BioStructures.jl
# 下载pdb文件
using BioStructures
# 显示当前文件夹
pwd()
# 下载到当前文件夹中
downloadpdb("1EN2")
[ Info: Downloading file from PDB: 1EN2
"path/to/1EN2.pdb"
#将pdb文件解析到一个Structure-Model-Chain-Residue-Atom框架中
struc = read("/path/to/pdb/file.pdb", PDB)
ProteinStructure 1EN2.pdb with 1 models, 2 chains (A,B), 85 residues, 754 atoms
#可以使用read（“ / path / to / cif / file.cif”，MMCIF）将mmCIF文件读入相同的数据结构。
#使用MMCIFDict将mmCIF读入到字典中
julia> mmcif_dict = MMCIFDict("/path/to/cif/file.cif")
mmCIF dictionary with 716 fields
#可以通过类似与字典的方式访问MMCIFDict
julia> mmcif_dict["_entity_src_nat.common_name"]
1-element Array{String,1}:
"great nettle"
#要将MMCIFDict或MMTFDict转换为Structure-Model-Chain-Residue-Atom框架，
#可以使用ProteinStructure构造函数，例如 蛋白质ProteinStructure(mmcif_dict)可以按以下方式访问struc的元素：
Command | Returns | Return type |
|---|---|---|
struc[1] | Model 1 | Model |
struc[1]["A"] | Model 1, chain A | Chain |
struc[1]['A'] | Shortcut to above if the chain ID is a single character | Chain |
struc["A"] | The lowest model (model 1), chain A | Chain |
struc["A"]["50"] | Model 1, chain A, residue 50 | AbstractResidue |
struc["A"][50] | Shortcut to above if it is not a hetero residue and the insertion code is blank | AbstractResidue |
struc["A"]["H_90"] | Model 1, chain A, hetero residue 90 | AbstractResidue |
struc["A"][50]["CA"] | Model 1, chain A, residue 50, atom name CA | AbstractAtom |
struc["A"][15]["CG"]['A'] | For disordered atoms, access a specific location | Atom |
无序原子存储在DisorderedAtom容器,如果对它不感兴趣，则可以忽略无序。
无序残基（即具有不同残基名称的点突变）存储在DisorderedResidue容器中。
例如：
julia> struc[1]
Model 1 with 2 chains (A,B), 85 residues, 754 atoms
julia> struc[1]["A"]
Chain A with 85 residues, 77 other molecules, 698 atoms
julia> struc["A"][50]["CA"]
Atom CA with serial 411, coordinates [2.143, -0.866, 34.446]
julia> x(struc["A"][50]["CA"])
2.143
julia> coords(struc["A"][50]["CA"])
3-element Array{Float64,1}:
2.143
-0.866
34.446属性
参见：https://biojulia.net/BioStructures.jl/stable/documentation/#Manipulating-structures
可以使用x!, y!, z!来设置原子的坐标。和coords!
操作结构
基本按下图所示
for mod in struc
for ch in mod
for res in ch
for at in res
# Do something
end
end
end
endModels按照数字排列；
- chains按chains ID字符排序，空链为最后；
- residue 按 residue 编号排序，和插入代码排序，标准残基后带有杂残基；
- atom 按 atom 序号排序。
- 如果需要第一个子元素，则可以先使用。例如，first（struc [1]）获取模型1中的第一条链。由于定义了元素的顺序，因此可以使用sort函数。例如，sort（res）如上所述对残基列表进行排序，或者sort（res，by = resname）将按残基名称按字母顺序对其进行排序。
- collect可用于获取子元素数组。收集原子，收集残基，收集链和收集模型从结构元素或元素数组返回特定类型的数组。由于大多数操作使用单个的原子或残基，因此默认情况下不会使用无序原子或者残基，仅存在一个实体。可以通过在collectatoms或collectresidues中将expand_disordered设置为true来更改它。
Selectors 是作为附加参数传递给这些函数的函数。仅保留传递给所有选择器时返回true的元素。例如：
Command | Action | Return type |
|---|---|---|
collect(struc['A'][50]) | Collect the sub-elements of an element, e.g. atoms from a residue | Array{AbstractAtom,1} |
collectresidues(struc) | Collect the residues of an element | Array{AbstractResidue,1} |
collectatoms(struc) | Collect the atoms of an element | Array{AbstractAtom,1} |
collectatoms(struc, calphaselector) | Collect the Cα atoms of an element | Array{AbstractAtom,1} |
collectatoms(struc, calphaselector, disorderselector) | Collect the disordered Cα atoms of an element | Array{AbstractAtom,1} |
code
julia> collect(struc['A'][50])
4-element Array{AbstractAtom,1}:
Atom N with serial 410, coordinates [3.193, 0.151, 34.344]
Atom CA with serial 411, coordinates [2.143, -0.866, 34.446]
Atom C with serial 412, coordinates [0.822, -0.238, 34.87]
Atom O with serial 413, coordinates [0.703, 0.947, 35.143]
创造一个新的选择子 atomnameselector or resnameselector
cdeltaselector(at::AbstractAtom) = atomnameselector(at, ["CD"])
创造一个选择子，选择X坐标均小于0的原子
julia> xselector(at) = x(at) < 0
julia> collectatoms(struc, xselector)
137-element Array{AbstractAtom,1}: Atom N with serial 9, coordinates [-2.607, 4.673, 13.504] Atom CA with serial 10, coordinates [-3.091, 6.01, 13.918] Atom C with serial 11, coordinates [-3.361, 6.101, 15.403] Atom O with serial 12, coordinates [-3.742, 5.121, 16.05] Atom CB with serial 13, coordinates [-4.348, 6.395, 13.124] Atom CG with serial 14, coordinates [-4.11, 6.337, 11.619] Atom CD with serial 15, coordinates [-4.277, 7.652, 10.942] Atom NE with serial 16, coordinates [-3.441, 8.73, 11.457] Atom CZ with serial 17, coordinates [-3.55, 9.979, 10.98] Atom NH1 with serial 18, coordinates [-4.444, 10.212, 10.022] Atom NH2 with serial 19, coordinates [-2.804, 10.949, 11.444] Atom N with serial 20, coordinates [-3.248, 7.317, 15.948] Atom CA with serial 21, coordinates [-3.419, 7.555, 17.361] Atom C with serial 22, coordinates [-3.637, 9.026, 17.672] ? Atom O with serial 777, coordinates [-1.326, 14.783, 10.991] Atom O with serial 787, coordinates [-3.992, 5.719, 31.647] Atom O with serial 788, coordinates [-0.321, 12.255, 8.483] Atom O with serial 790, coordinates [-3.066, 4.753, 29.076] Atom O with serial 791, coordinates [-0.945, 1.949, 9.712] Atom O with serial 792, coordinates [-7.059, 6.398, 16.836] Atom O with serial 794, coordinates [-6.832, 2.828, 21.276] Atom O with serial 798, coordinates [-2.996, 7.951, 27.405] Atom O with serial 799, coordinates [-4.774, 1.179, 18.535] Atom O with serial 801, coordinates [-8.668, 12.634, 15.67] Atom O with serial 810, coordinates [-4.389, 3.044, 11.77] Atom O with serial 814, coordinates [-6.184, 3.543, 26.723] Atom O with serial 819, coordinates [-0.903, 8.986, 28.883]- 得到蛋白的一级序列
julia> LongAminoAcidSeq(struc['A'], standardselector)
85aa Amino Acid Sequence:
RCGSQGGGSTCPGLRCCSIWGWCGDSEPYCGRTCENKCW…RCGAAVGNPPCGQDRCCSVHGWCGGGNDYCSGGNCQYRC相关空间计算
一系列的函数用于计算蛋白的空间质量
Command | Returns |
|---|---|
distance | Minimum distance between two elements |
sqdistance | Minimum square distance between two elements |
coordarray | Atomic coordinates in ? of an element as a 2D Array with each column corresponding to one atom |
bondangle | Angle between three atoms |
dihedralangle | Dihedral angle defined by four atoms |
omegaangle | Omega dihedral angle between a residue and the previous residue |
phiangle | Phi dihedral angle between a residue and the previous residue |
psiangle | Psi dihedral angle between a residue and the next residue |
omegaangles | Vector of omega dihedral angles of an element |
phiangles | Vector of phi dihedral angles of an element |
psiangles | Vector of psi dihedral angles of an element |
ramachandranangles | Vectors of phi and psi angles of an element |
ContactMap | ContactMap of two elements, or one element with itself |
DistanceMap | DistanceMap of two elements, or one element with itself |
showcontactmap | Print a representation of a ContactMap to stdout or a specified IO instance |
Transformation | The 3D transformation to map one set of coordinates onto another |
applytransform! | Modify all coordinates in an element according to a transformation |
applytransform | Modify coordinates according to a transformation |
superimpose! | Superimpose one element onto another |
rmsd | RMSD between two elements, with or without superimposition |
displacements | Vector of displacements between two elements, with or without superimposition |
MetaGraph | Construct a MetaGraph of contacting elements |
omegaangle, phiangle and psiangle函数可以测量一对残基或链和位置。omegaangle and phiangle函数测量给定序号的残基与序号之前的残基之间的角度。psiangle 函数测量给定序号的残基与序号之后的残基之间的角度。
例如：
julia> distance(struc['A'][10], struc['A'][20])
10.782158874733762
julia> rad2deg(bondangle(struc['A'][50]["N"], struc['A'][50]["CA"], struc['A'][50]["C"]))
110.77765846083398
julia> rad2deg(dihedralangle(struc['A'][50]["N"], struc['A'][50]["CA"], struc['A'][50]["C"], struc['A'][51]["N"]))
-177.38288114072924
julia> rad2deg(psiangle(struc['A'][50], struc['A'][51]))
-177.38288114072924
julia> rad2deg(psiangle(struc['A'], 50))
-177.38288114072924ContactMap 采用结构或列表（如链或 Vector[Atom]）作为输入，并返回一个 ContactMap 对象。该对象显示基于指定距离的元素之间的接触。可以给ContactMap两个结构元素作为参数，在这种情况下，将返回一个非对称的2D数组显示接触。可以使用contact.data访问ContactMap的基础BitArray。
julia> contacts = ContactMap(collectatoms(struc['A'], cbetaselector), 8.0)
Contact map of size (85, 85)
julia> using Plots
julia> plot(contacts)
julia> showcontactmap(contacts)
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julia> contacts.data
85×85 BitArray{2}:
1 1 1 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 … 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 … 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 1 1 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 1 0 0 0 0 1 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 … 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1
0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0
? ? ? ? ? ? ? ? ? ?
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 1 1 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 … 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 0 1 1 0 0 0 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 … 1 1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1
0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1
0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1
0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 1 1 1 1 1
dists = DistanceMap(collectatoms(struc['A'], cbetaselector))
using Plots
plot(dists)
基于Kabsch algorithm的序列以及结构比对
# Change the coordinates of element 1 to superimpose it onto element 2
# Do sequence alignment with standard residues and calculate the transformation with Cα atoms (the default)
superimpose!(el1, el2, standardselector)
# The transformation object for the above superimposition
Transformation(el1, el2, standardselector)
# Calculate the transformation with backbone atoms
superimpose!(el1, el2, standardselector, alignatoms=backboneselector)
# Calculate RMSD on Cα atoms (the default) after superimposition
rmsd(el1, el2, standardselector)
# Superimpose based on backbone atoms and calculate RMSD based on Cβ atoms
rmsd(el1, el2, standardselector, alignatoms=backboneselector, rmsdatoms=cbetaselector)
# Do not do a superimposition - assumes the elements are already superimposed
rmsd(el1, el2, standardselector, superimpose=false)蛋白结构中的接触形成图，可以使用MetaGraph检索该图形。可以使用 LightGraphs.jl.来进行分析
julia> mg = MetaGraph(collectatoms(struc["A"], cbetaselector), 8.0)
{85, 423} undirected Int64 metagraph with Float64 weights defined by :weight (default weight 1.0)
julia> using LightGraphs, MetaGraphs
# Number of vertices
julia> nv(mg)
85
# Number of edges
julia> ne(mg)
423
julia> get_prop(mg, :contactdist)
8.0
julia> mg[10, :element]
Atom CB with serial 71, coordinates [-3.766, 4.031, 23.526]
读取蛋白文件
julia> struc = read("/path/to/1EN2.pdb", PDB)
ProteinStructure 1EN2.pdb with 1 models, 1 chains (A), 85 residues, 754 atoms Keyword Argument | Description |
|---|---|
structure_name::AbstractString | The name given to the returned ProteinStructure; defaults to the file name |
remove_disorder::Bool=false | Whether to remove atoms with alt loc ID not ' ' or 'A' |
read_std_atoms::Bool=true | Whether to read standard ATOM records |
read_het_atoms::Bool=true | Whether to read HETATOM records |
gzip::Bool=false | Whether the file is gzipped (MMTF and mmCIF files only) |
结构转化为DataFrame
julia> df = DataFrame(collectatoms(struc));
julia> first(df, 3)
3×17 DataFrame. Omitted printing of 5 columns
│ Row │ ishetero │ serial │ atomname │ altlocid │ resname │ chainid │ resnumber │ inscode │ x │ y │ z │ occupancy │
│ │ Bool │ Int64 │ String │ Char │ String │ String │ Int64 │ Char │ Float64 │ Float64 │ Float64 │ Float64 │
├─────┼──────────┼────────┼──────────┼──────────┼─────────┼─────────┼───────────┼─────────┼─────────┼─────────┼─────────┼───────────┤
│ 1 │ false │ 1 │ N │ ' ' │ GLU │ A │ 94 │ ' ' │ 15.637 │ -47.066 │ 18.179 │ 1.0 │
│ 2 │ false │ 2 │ CA │ ' ' │ GLU │ A │ 94 │ ' ' │ 14.439 │ -47.978 │ 18.304 │ 1.0 │
│ 3 │ false │ 3 │ C │ ' ' │ GLU │ A │ 94 │ ' ' │ 14.141 │ -48.183 │ 19.736 │ 1.0 │
julia> df = DataFrame(collectresidues(struc));
julia> first(df, 3)
3×8 DataFrame
│ Row │ ishetero │ resname │ chainid │ resnumber │ inscode │ countatoms │ modelnumber │ isdisorderedres │
│ │ Bool │ String │ String │ Int64 │ Char │ Int64 │ Int64 │ Bool │
├─────┼──────────┼─────────┼─────────┼───────────┼─────────┼────────────┼─────────────┼─────────────────┤
│ 1 │ false │ GLU │ A │ 94 │ ' ' │ 9 │ 1 │ false │
│ 2 │ false │ GLU │ A │ 95 │ ' ' │ 9 │ 1 │ false │
│ 3 │ false │ VAL │ A │ 96 │ ' ' │ 7 │ 1 │ false │输出蛋白结构
writepdb("1EN2_out.pdb", struc)
# Only backbone atoms are written out
writepdb("1EN2_out.pdb", struc, backboneselector)
writemmcif("1EN2_out.dic", mmcif_dict)
#查看某原子的recordline
julia> pdbline(struc["A"][50]["CA"])
"ATOM 411 CA GLY A 50 2.143 -0.866 34.446 1.00 18.12 C "
#产生新行
julia> pdbline(AtomRecord(false, 669, "CA", ' ', "ILE", "A", 90, ' ', [31.743, 33.11, 31.221], 1.00, 25.76, "C", ""))
"ATOM 669 CA ILE A 90 31.743 33.110 31.221 1.00 25.76 C "结构可视化
using Bio3DView
using Blink
viewpdb("1CRN")
几个例子
- PDB records for all Cα atoms within 5 ? of residue 38绘制蛋白的温度因子
using Plots
calphas = collectatoms(struc, calphaselector)
plot(resnumber.(calphas),
tempfactor.(calphas),
xlabel="Residue number",
ylabel="Temperature factor",
label="")
- 展示38位氨基酸附近5A之内的所有的Cα原子
julia> for at in calphas
if distance(struc['A'][38], at) < 5.0 && resnumber(at) != 38
println(pdbline(at))
end
endATOM 144 CA CYS A 17 4.659 6.900 21.426 1.00 10.21 C
ATOM 302 CA ASN A 37 1.497 10.964 24.209 1.00 12.65 C
ATOM 319 CA CYS A 39 6.632 10.077 25.433 1.00 11.58 C
ATOM 436 CA ASN A 55 0.391 2.709 32.223 1.00 19.27 C
ATOM 444 CA PRO A 56 2.969 5.491 31.927 1.00 13.73 C
ATOM 451 CA PRO A 57 5.722 5.426 29.322 1.00 12.65 C- 发现蛋白蛋白接触面处的氨基酸
for res_a in collectresidues(struc_2["A"], standardselector)
for res_b in collectresidues(struc_2["B"], standardselector)
if distance(res_a, res_b) < 5.0
println(resnumber(res_a), "A ", resnumber(res_b), "B")
end
end
end
317A 737B
319A 740B
319A 745B
359A 167B
360A 168B
522A 230B
523A 230B
558A 45B
558A 281B
558A 282B
559A 45B
559A 282B
560A 38B
560A 282B
560A 283B
560A 284B
562A 38B
562A 41B
562A 42B
...- 展示蛋白结构的拉氏图
using Plots
phi_angles, psi_angles = ramachandranangles(struc, standardselector)
scatter(rad2deg.(phi_angles),rad2deg.(psi_angles),title="Ramachandran plot",xlabel="Phi / degrees", ylabel="Psi / degrees", label="", xticks=[-180, -90, 0, 90, 180], yticks=[-180, -90, 0, 90, 180], xlims=(-180, 180), ylims=(-180, 180))
- 计算NMR结构中两个模型的重（非氢）原子之间的RMSD和位移：
julia> downloadpdb("1SSU")
julia> struc_nmr = read("1SSU.pdb", PDB)
julia> rmsd(struc_nmr[5], struc_nmr[10], superimpose=false, rmsdatoms=heavyatomselector)
julia> displacements(struc_nmr[5], struc_nmr[10], superimpose=false, rmsdatoms=heavyatomselector)
4.898672575300373 3.6131684156706565 3.2852496099992163 1.7051043956309546 1.246148466275186 0.6438858594502602 0.24807257002740143 0.5844458914219525 0.4401829165244831 0.2674864482548598 0.6890362835148812 0.8433089588045419 0.616994327364523 0.21171915359740148 ? 0.9053982549132731 1.0637509106929124 2.2037803883327394 3.8408021297640422 2.8143350902122513 6.430908256226332 8.973943893294631 12.156951756094124 13.640643129999406 11.927246916199898 11.46172796745761 10.091456336921842 9.652495273244115- 与Julia生态系统中的其他软件包可以实现互操作性。例如，使用NearestNeighbors.jl查找每个残基最近的10个残基：
julia> using NearestNeighbors
[ Info: Precompiling NearestNeighbors [b8a86587-4115-5ab1-83bc-aa920d37bbce]
julia> struc = retrievepdb("1AKE")
[ Info: File exists: 1AKE ProteinStructure 1AKE.pdb with 1 models, 2 chains (A,B), 428 residues, 3804 atoms
julia> ca = coordarray(struc["A"], cbetaselector)
3×214 Array{Float64,2}: 24.677 28.653 23.802 25.789 22.088 21.919 19.604 18.092 20.574 … 7.414 9.597 14.144 11.762 9.84 14.508 17.321 15.055 53.31 49.266 48.88 43.561 45.547 39.891 39.512 36.96 38.908 52.565 47.611 50.369 54.334 50.063 47.961 52.16 55.001 39.58 38.349 35.202 33.72 29.675 30.945 26.973 23.169 19.047 33.084 34.097 33.555 36.399 39.295 38.63 38.292 41.318
julia> kdtree = KDTree(ca; leafsize=10)
KDTree{StaticArrays.SArray{Tuple{3},Float64,1,3},Euclidean,Float64} Number of points: 214 Dimensions: 3 Metric: Euclidean(0.0) Reordered: true
julia> idxs, dists = knn(kdtree, ca, 10, true)
([[1, 104, 80, 26, 2, 24, 3, 105, 213, 82], [2, 103, 104, 80, 3, 1, 81, 102, 101, 105], [3, 82, 105, 2, 4, 103, 1, 104, 107, 5], [4, 106, 83, 103, 5, 3, 6, 87, 107, 182], [5, 13, 84, 107, 6, 4, 17, 85, 3, 109], [6, 108, 7, 5, 4, 178, 106, 107, 179, 109], [7, 11, 109, 6, 8, 108, 13, 5, 110, 111], [8, 7, 11, 9, 171, 111, 116, 10, 168, 113], [9, 167, 10, 8, 116, 171, 168, 164, 120, 11], [10, 9, 11, 119, 12, 120, 116, 8, 111, 13] … [205, 200, 206, 204, 198, 208, 202, 16, 196, 209], [206, 203, 205, 207, 19, 209, 202, 16, 204, 210], [207, 206, 208, 204, 210, 203, 209, 211, 205, 200], [208, 196, 209, 207, 211, 205, 212, 204, 197, 200], [209, 208, 210, 212, 206, 213, 16, 205, 196, 20], [210, 209, 211, 207, 214, 213, 206, 212, 208, 23], [211, 212, 210, 208, 207, 209, 214, 213, 194, 196], [212, 194, 213, 211, 209, 208, 107, 105, 210, 196], [213, 214, 212, 209, 210, 24, 20, 105, 1, 211], [214, 213, 210, 211, 212, 24, 23, 209, 1, 20]], [[0.0, 5.379302371125837, 5.738340700934371, 5.7471726962046255, 5.803263995373641, 6.2698517526333895, 6.289468101517011, 7.548714526328312, 7.555936738750529, 8.120749534371813], [0.0, 4.112730601437444, 4.943904024149336, 5.153635706954848, 5.79523994326378, 5.803263995373641, 6.113403471062578, 7.130071388141919, 7.529867595117461, 7.635012901102395], [0.0, 4.752253991528648, 4.807276775888826, 5.79523994326378, 5.8682411334232025, 6.1936384298730305, 6.289468101517011, 6.455786938863458, 6.596865998335876, 6.677904910973202], [0.0, 4.598864425051035, 4.772305941575829, 5.235701576675279, 5.831262470511851, 5.8682411334232025, 6.012189700932599, 7.067439352410459, 7.117514243048626, 7.17806303956715], [0.0, 4.32352055621342, 4.971098570738667, 5.5090422942649475, 5.79929280171298, 5.831262470511851, 6.236849685538367, 6.66853724590333, 6.677904910973202, 6.712515698305665], [0.0, 4.563654347121392, 4.612987101651165, 5.79929280171298, 6.012189700932599, 6.03362793019258, 6.042733570165077, 6.561872750975902, 6.675025243397956, 6.7987706241643435], [0.0, 4.347957681486791, 4.607806202521975, 4.612987101651165, 4.823822550633469, 6.0827713256376805, 6.136970343744541, 7.063447104636657, 7.238687311937157, 7.376582270943636], [0.0, 4.823822550633469, 4.923382577050047, 5.190945193314992, 5.333387385142766, 5.667243245176615, 6.284191992611303, 6.472383641287034, 6.722325341725138, 7.02830036353029], [0.0, 4.580603126226939, 4.7337695338915715, 5.190945193314992, 5.764995836945593, 5.866839097844765, 6.010085357130961, 6.305834916963812, 6.804574417257852, 7.284529909335261], [0.0, 4.7337695338915715, 5.0027798272560435, 5.080148619873239, 5.419463718856319, 5.694080874030506, 5.724320483690618, 6.472383641287034, 7.020420642668072, 7.276900782613434] … [0.0, 4.965381556335825, 5.244736981012494, 5.438683848138262, 5.488500523822511, 5.873772893124147, 5.905328017985114, 6.101600199947552, 6.106085489083822, 6.533423987466296], [0.0, 5.104430428559095, 5.244736981012494, 5.3089409490029205, 5.337398804661314, 5.835905156871556, 6.200670044438746, 6.580556587402013, 6.831018811275522, 7.084954763440626], [0.0, 5.3089409490029205, 5.507610552680718, 5.565543459537445, 5.746624226448081, 6.446670768699146, 7.0948683567773125, 7.121938008716445, 7.32911195166236, 8.60757654627596], [0.0, 5.000595164577914, 5.345609132736888, 5.507610552680718, 5.752439221756283, 5.873772893124147, 6.692421833686218, 6.798922708782622, 7.116849162375159, 7.172625878992994], [0.0, 5.345609132736888, 5.429869703777433, 5.629083850858862, 5.835905156871556, 5.9783090418612534, 6.092611755232727, 6.533423987466296, 6.574575347503445, 6.866309124995759], [0.0, 5.429869703777433, 5.50657252744391, 5.746624226448081, 5.956953835644519, 6.261965027050219, 7.084954763440626, 7.289239054935711, 7.428671348229108, 7.72148573786159], [0.0, 5.162446416186807, 5.50657252744391, 5.752439221756283, 7.121938008716445, 7.180922781927127, 7.461407239924647, 7.833822757760096, 9.085469828247742, 9.513200775764174], [0.0, 4.845528763716093, 5.0654529906021235, 5.162446416186807, 5.629083850858862, 6.692421833686218, 7.054568307132619, 7.19152146628236, 7.289239054935711, 7.479374171680411], [0.0, 4.72892302749791, 5.0654529906021235, 5.9783090418612534, 6.261965027050219, 6.690919294088076, 7.006122037190048, 7.080867390369627, 7.555936738750529, 7.833822757760096], [0.0, 4.72892302749791, 5.956953835644519, 7.461407239924647, 7.555537902757153, 8.485650240258552, 9.063193752756252, 9.085676309444441, 9.922852865985668, 10.711033236807733]])Summary
- 总体来说在蛋白结构方面操作起来比较舒服
- 但是由于第一次接触Julia还需要熟练
- 某些安装包还是有些麻烦,例如plots
- 建议下载julia pro，作为ide，搭配atom使用
- 可能julia也支持jupyter？这个还需要看下，如果说支持jupyter，我收回上面那句话
本文参与?腾讯云自媒体同步曝光计划，分享自微信公众号。
原始发表：2021-02-05，如有侵权请联系?cloudcommunity@tencent.com 删除
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