DTI_공부 2. Data Preprocessing Tool

BioAi96·2022년 10월 7일

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1. BioPython

Reading FASTA Files

parse(file_path, format)
ex) Counting GC Content in DNA

from Bio.SeqUtils import GC

Central dogma ( DNA --> RNA --> Protein )

Transcription : DNA --> RNA

template_dna = coding_dna.reverse_complement()
messenger_rna = coding_dna.transcribe() 
coding_dna = messenger_rna.back_transcribe()

Translation : RNA --> Protein

messenger_rna.translate() # *는 종결코돈
coding_dna.translate() # 바로 DNA에서 Protein으로 가능

Accessing NCBI databases with Biopython

from Bio import Entrez, SeqIO

Pairwise Sequence alignments in Biopython

Identify regions of similarity that may indicate functional, structural and evolutionary relationships between two biological sequence. ex) global/local alignment -- > result : match score & gap penalties

from Bio import pairwise2

BLAST in Biopython

blast program : blastn, blastp, blastx, tblast, tblastx

from Bio.BLAST import NCBIWWW

Motif objects in Biopython

from Bio import motifs
from Bio.Seq import Seq
instances = [
	seq("TACAA"),
    seq("TACGC")
    ]
m = motifs.create(instances) # motif로
m.instances # 다시 인스턴스로
m.counts
m.consensus # the largest values in the columns of the .counts matrix 
m.anticonsensus # the smallest values in the columns of the .counts matrix
m.degenerate_consensus

Indexing a FASTQ file / Sorting a sequence file(FASTA/FASTQ) / Filtering for FASTQ file

참고 : https://www.youtube.com/watch?v=ocA2IMe7dpA

2. RDkit

https://www.rdkit.org/
파이썬에서 약물을 다룰 때 주로 사용하는 package

Drawing Molecules(Jupyter)

from rdkit import Chem
from rdkit.Chem.Draw import IPythonConsole
from rdkit.Chem import Draw
IPythonConsole.ipython_useSVG=True  #< set this to False if you want PNGs instead of SVGs

mol = Chem.MolFromSmiles("C1CC2=C3C(=CC=C2)C(=CN3C1)[C@H]4[C@@H](C(=O)NC4=O)C5=CNC6=CC=CC=C65")

Bonds / Rings / Stereochemistry 분자의 화학적 요소 확인가능

Reactions

rxn = AllChem.ReactionFromSmarts('[cH1:1]1:[c:2](-[CH2:7]-[CH2:8]-[NH2:9]):[c:3]:[c:4]:[c:5]:[c:6]:1.[#6:11]-[CH1;R0:10]=[OD1]>>[c:1]12:[c:2](-[CH2:7]-[CH2:8]-[NH1:9]-[C:10]-2(-[#6:11])):[c:3]:[c:4]:[c:5]:[c:6]:1')

Fingerprint - 분자 내 주요 functional group을 나타냄

Chem.RDKFingerprint() : 2047개로 구분

유사도 계산(DTI에서도 자주 사용하지 않을까?)
Tanimoto similarity = 교집합의 갯수 / 합집합의 갯수
DataStructs.FingerprintSimilarity(fps[0],fps[1])

MACCkeys : 166개로 구분

MACCSkeys.GenMACCSKeys(x)

Morgan : 각 중심 원자에서 얼만큼 떨어진 이웃한 원자까지 고려할지 radius를 정함 --> ECFP

AllChem.GetMorganFingerprint(x, 2)

Descriptor - 분자의 특성 성질 또는 종합적인 구조/성질을 숫자로 나타내는 것 --> Drug likeness 에 있어서 중요

TPSA() : Total polar surface area
MolLogP() : logP 계산
BalabanJ() : Branch가 얼마나 많은가?
FractionCSP3() : sp3 carbon 비율
RingCount() : 고리 갯수
fr.imide() : imide 존재여부
fr.phenol() : phenol 존재여부
etc Descriptors 내 method : 425개 / 이와 유사한 rdMolDescriptors(182개)도 존재

참고 : https://www.laidd.org - [2022] RDKit의 기초와 이를 이용한 화학정보학 실습(이주용)

3. PDB-Cleaner

https://github.com/LePingKYXK/PDB_cleaner

Redundant info. in PDB file

--> ligands / alternate location / non-standard a.a residues / negative seq.num / seq. gaps / insertion code / multiple chains / hydrogen atoms
--> REMOVE!! --> SAVE

4. PDBtools

https://github.com/harmslab/pdbtools
For manipulating and doing calculations on wwPDB macromolecule structure files

Functions

1. Structure-based calculations : Geometry / Energy calculation / Structure properties

2. File/structure manipulation

5. PLIP

https://plip-tool.biotec.tu-dresden.de/plip-web/plip/index
4ASD.PDB

Information of
Hydrophobic Interaction
Hydrogen Bonds
Halogen Bonds

Objective

Main은 small molecule과 protein 간의 interaction을 찾아내는 것.
하지만, PLIP는 nucleic acid(DNA,RNA)의 결합도 찾아낼 수 있다.

Protein - RNA Interaction
FUS(zinc finger as receptor) <--> RNA(UGGUG as ligand)

FUS : RNA/DNA binding protein 인 FUS (Fused in sarcoma) 는 신경퇴행성질환인 근위축성 측삭경화증 (Amyothrophic lateral sclerosis)과 전측두엽성치매 (Frontotemproal dementia) 연관 유전자
PLIP detects π-stacking interactions of the central Phe438 with the flanking G2 and G3 of the RNA
S.M. - DNA Interaction
XR5944(cancer drug as ligand) <--> DNA(TFF1-ERE as receptor)
!XR5944 : Estrogen response element(ERE)를 특정하여 인식
PLIP identifies parallel π-stacking interactions(phenazine rings of the XR5944 - flanking base) & several hydrophobic interactions at the intercalation sites