Design of an hexapeptide database for proteomics studies

•

1 recomendación•436 vistas

Generate a database of hexapeptides using the combination of all 15 amino acids: No included: Metionine (M), Triptophan (W), Cysteine (C), Isoleucine (I), Aspártic (D). Index the database in Mascot for searching of peptide archives.

Ingeniería

Insilico Design of a
hexapeptide database
Autor: Jeovanis Gil Valdés
Yasset Perez Riverol

Introducción
• Generate a database of hexapeptides using the
combination of all 15 aminoacids: No included:
Metionine (M), Triptophan (W), Cysteine (C),
Isoleucine (I), Aspártic (D).
• Idenx the database in Mascot for searching of
peptide archives.

Number of Peptides by Mass
Number Peptides vs Mass Value
10000
8000
6000
4000
2000
0
475
737
785
818
845
871
896
922
955
1034
Mass Value
Number of Peptides
Count Peptides
The number of posible heaxapeptides
correspond with the number of permutations with
repetition of N elements in p posicions:
PR = Np = 156 = 11’390’625.
The number of aminoacids compositions
correspond with the number of combinations
with repetition of N elements in p posicions:
N k
⎛ + −
= N p p n
( 1)!/ !( 1)!
1
⎞
− − + = ⎟⎟⎠
⎜⎜⎝
p
CR
CR = 20!/6! 14! = 38’760
Mav = 824.187237 Da.
Mmax = 1111.417485 (YYYYYYD)
Mmin = 475.166265 (GGGGGGD)
Cmax = 8820 (Mass:821.403155)
P = 0.000113379.

Peptide Distribution by Mass
3,20,50,100 PPM

Aminoacid compositions
Number of unique composition masses:
CMU = 15'106.
Composi'on
aminoacid
Count
%
Ppep'des
%
Mases
19
0,28
0,03
18
0,36
0,03
17
0,46
0,05
16
0,38
0,05
15
0,87
0,12
14
1,19
0,18
13
1,92
0,30
12
2,39
0,42
11
3,24
0,64
10
3,59
0,77
9
4,45
1,03
8
6,59
1,75
7
7,31
2,26
6
7,82
2,88
5
9,30
4,24
4
11,62
6,84
3
13,26
11,53
2
13,37
19,46
1
11,61
47,43

Aminoacid compositions
Aminoacid
frecuency
Aminoacid
composi'on
with
this
aminoacid
Q-‐
1
6791
N-‐
1
6789
L-‐
1
6745
V-‐
1
6701
T-‐
1
6700
S-‐
1
6698
G-‐
1
6621

References
Introducing an Asp-Pro linker in the synthesis of random one-bead-one-compound
hexapeptide libraries compatible with ESI-MS analysis. Y Masforrol, J Gil, LJ
González, Y Pérez-Riverol, J Fernández-de-Cossío, et al. ACS combinatorial
science 14 (3), 145-149

Más contenido relacionado

Destacado

2. better control, better life dr. ko koko ko

Glucagon-Like Peptide-1 (GLP-1) Receptor AgonistsMarket Research Reports, Inc.

Protein dockingSaramita De Chakravarti

Insilico Analysis towards Infuenza Virus- A Homology modelling and molecular ...Subhasree Pal

Parallel conformational search of small moleculesYasset Perez-Riverol

Drug discovery Using BioinformaticSuhad Jihad

Incretin Therapyko ko

Homology modeling and molecular dockingRangika Munaweera

Drug Target IdentificationArvind306

RasaSameer A

Target identification in drug discoverySwati Kumari

Protein-ligand dockingbaoilleach

Protein-Ligand Dockingbaoilleach

Future of health CareJames Canton

MOLECULAR DOCKINGSaramita De Chakravarti

Molecular dockingpalliyath91

Structure based drug designADAM S

Molecular dockingRahul B S

Drug discovery and developmentrahul_pharma

Destacado (19)

2. better control, better life dr. ko ko

Glucagon-Like Peptide-1 (GLP-1) Receptor Agonists

Protein docking

Insilico Analysis towards Infuenza Virus- A Homology modelling and molecular ...

Parallel conformational search of small molecules

Drug discovery Using Bioinformatic

Incretin Therapy

Homology modeling and molecular docking

Drug Target Identification

Rasa

Target identification in drug discovery

Protein-ligand docking

Protein-Ligand Docking

Future of health Care

MOLECULAR DOCKING

Molecular docking

Structure based drug design

Molecular docking

Drug discovery and development

Más de Yasset Perez-Riverol

Introduction to Proteogenomics Yasset Perez-Riverol

Biocontainers 2019: Presentation for the ELIXIR All HandsYasset Perez-Riverol

Mapping millions of peptidoforms to Genome CoordinatesYasset Perez-Riverol

Systematic integration of millions of peptidoform evidences into Ensembl and ...Yasset Perez-Riverol

Biocontainers Hackathon IntroductionYasset Perez-Riverol

BioContainers on ELIXIR All Hands 2017Yasset Perez-Riverol

PRIDE and ProteomeXchange – Making proteomics data accessible and reusableYasset Perez-Riverol

Yasset perezriverol csi2011Yasset Perez-Riverol

Yasset iso point-cigb-2012Yasset Perez-Riverol

SintCompound: A Small Compound Database for Virtual ScreeningYasset Perez-Riverol

Más de Yasset Perez-Riverol (10)

Introduction to Proteogenomics

Biocontainers 2019: Presentation for the ELIXIR All Hands

Mapping millions of peptidoforms to Genome Coordinates

Systematic integration of millions of peptidoform evidences into Ensembl and ...

Biocontainers Hackathon Introduction

BioContainers on ELIXIR All Hands 2017

PRIDE and ProteomeXchange – Making proteomics data accessible and reusable

Yasset perezriverol csi2011

Yasset iso point-cigb-2012

SintCompound: A Small Compound Database for Virtual Screening

Último

Current Transformer Drawing and GTP for MSETCLDeelipZope

DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINEslot gacor bisa pakai pulsa

Internship report on mechanical engineeringmalavadedarshan25

★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR9953056974 Low Rate Call Girls In Saket, Delhi NCR

Introduction to IEEE STANDARDS and its different types.pptxupamatechverse

Analog to Digital and Digital to Analog ConverterAbhinavSharma374939

MANUFACTURING PROCESS-II UNIT-5 NC MACHINE TOOLSSIVASHANKAR N

(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Serviceranjana rawat

Microscopic Analysis of Ceramic Materials.pptxpurnimasatapathy1234

IVE Industry Focused Event - Defence Sector 2024Mark Billinghurst

APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSKurinjimalarL3

Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR9953056974 Low Rate Call Girls In Saket, Delhi NCR

Biology for Computer Engineers Course Handout.pptxDeepakSakkari2

Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur EscortsCall Girls in Nagpur High Profile

ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...ZTE

Coefficient of Thermal Expansion and their Importance.pptxAsutosh Ranjan

(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...ranjana rawat

247267395-1-Symmetric-and-distributed-shared-memory-architectures-ppt (1).pptssuser5c9d4b1

Introduction and different types of Ethernet.pptxupamatechverse

HARDNESS, FRACTURE TOUGHNESS AND STRENGTH OF CERAMICSRajkumarAkumalla

Design of an hexapeptide database for proteomics studies

1. Insilico Design of a hexapeptide database Autor: Jeovanis Gil Valdés Yasset Perez Riverol

2. Introducción • Generate a database of hexapeptides using the combination of all 15 aminoacids: No included: Metionine (M), Triptophan (W), Cysteine (C), Isoleucine (I), Aspártic (D). • Idenx the database in Mascot for searching of peptide archives.

3. Number of Peptides by Mass Number Peptides vs Mass Value 10000 8000 6000 4000 2000 0 475 737 785 818 845 871 896 922 955 1034 Mass Value Number of Peptides Count Peptides The number of posible heaxapeptides correspond with the number of permutations with repetition of N elements in p posicions: PR = Np = 156 = 11’390’625. The number of aminoacids compositions correspond with the number of combinations with repetition of N elements in p posicions: N k ⎛ + − = N p p n ( 1)!/ !( 1)! 1 ⎞ − − + = ⎟⎟⎠ ⎜⎜⎝ p CR CR = 20!/6! 14! = 38’760 Mav = 824.187237 Da. Mmax = 1111.417485 (YYYYYYD) Mmin = 475.166265 (GGGGGGD) Cmax = 8820 (Mass:821.403155) P = 0.000113379.

5. Peptide Distribution by Mass 3,20,50,100 PPM

6. Aminoacid compositions Number of unique composition masses: CMU = 15'106. Composi'on aminoacid Count % Ppep'des % Mases 19 0,28 0,03 18 0,36 0,03 17 0,46 0,05 16 0,38 0,05 15 0,87 0,12 14 1,19 0,18 13 1,92 0,30 12 2,39 0,42 11 3,24 0,64 10 3,59 0,77 9 4,45 1,03 8 6,59 1,75 7 7,31 2,26 6 7,82 2,88 5 9,30 4,24 4 11,62 6,84 3 13,26 11,53 2 13,37 19,46 1 11,61 47,43

7. Aminoacid compositions Aminoacid frecuency Aminoacid composi'on with this aminoacid Q-‐ 1 6791 N-‐ 1 6789 L-‐ 1 6745 V-‐ 1 6701 T-‐ 1 6700 S-‐ 1 6698 G-‐ 1 6621

8. References Introducing an Asp-Pro linker in the synthesis of random one-bead-one-compound hexapeptide libraries compatible with ESI-MS analysis. Y Masforrol, J Gil, LJ González, Y Pérez-Riverol, J Fernández-de-Cossío, et al. ACS combinatorial science 14 (3), 145-149

Design of an hexapeptide database for proteomics studies

Recomendados

Recomendados

Más contenido relacionado

Destacado

Destacado (19)

Más de Yasset Perez-Riverol

Más de Yasset Perez-Riverol (10)

Último

Último (20)

Design of an hexapeptide database for proteomics studies