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1. (WO2018104385) CODON OPTIMIZATION
Latest bibliographic data on file with the International BureauSubmit observation

Pub. No.: WO/2018/104385 International Application No.: PCT/EP2017/081685
Publication Date: 14.06.2018 International Filing Date: 06.12.2017
IPC:
C12N 15/67 (2006.01) ,C40B 30/02 (2006.01) ,G06F 19/10 (2011.01) ,G06F 19/24 (2011.01)
C CHEMISTRY; METALLURGY
12
BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
N
MICRO-ORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICRO-ORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
15
Mutation or genetic engineering; DNA or RNA concerning genetic engineering, vectors, e.g. plasmids, or their isolation, preparation or purification; Use of hosts therefor
09
Recombinant DNA-technology
63
Introduction of foreign genetic material using vectors; Vectors; Use of hosts therefor; Regulation of expression
67
General methods for enhancing the expression
C CHEMISTRY; METALLURGY
40
COMBINATORIAL TECHNOLOGY
B
COMBINATORIAL CHEMISTRY; LIBRARIES, e.g. CHEMICAL LIBRARIES, IN SILICO LIBRARIES
30
Methods of screening libraries
02
In silico screening
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
F
ELECTRIC DIGITAL DATA PROCESSING
19
Digital computing or data processing equipment or methods, specially adapted for specific applications
10
Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
F
ELECTRIC DIGITAL DATA PROCESSING
19
Digital computing or data processing equipment or methods, specially adapted for specific applications
10
Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
24
for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
Applicants:
MAX-PLANCK-GESELLSCHAFT ZUR FÖRDERUNG DER WISSENSCHAFTEN E.V. [DE/DE]; Hofgartenstraße 8 80539 Munich, DE
Inventors:
LIPOWSKY, Reinhard; DE
RUDORF, Sophia; DE
LÖSSNER, Holger; DE
TRÖSEMEIER, Jan-Hendrik; DE
KOCH, Ina; DE
KAMP, Christel; DE
Agent:
VOSSIUS & PARTNER (NO 31); Siebertstraße 3 81675 München, DE
Priority Data:
16202752.807.12.2016EP
Title (EN) CODON OPTIMIZATION
(FR) OPTIMISATION DE CODON
Abstract:
(EN) Method for determining an optimized nucleotide sequence encoding a predetermined amino acid sequence, wherein the nucleotide sequence is optimized for expression in a host cell, and wherein the method comprises the steps of: (a) generating a plurality of candidate nucleotide sequences encoding the predetermined amino acid sequence; (b) obtaining a sequence score based on a scoring function based on a plurality of sequence features that influence protein expression in the host cell using a statistical machine learning algorithm, wherein the plurality of sequence features comprises one or more sequence features selected from the group consisting of protein per time, average elongation rate and accuracy for each of the plurality of candidate nucleotide sequences of step (a); and (c) determining the candidate nucleotide sequence with optimized protein expression in the host cell as the optimized nucleotide sequence.
(FR) L'invention concerne un procédé de détermination d'une séquence nucléotidique optimisée codant pour une séquence d'acides aminés prédéterminée, la séquence nucléotidique étant optimisée pour l'expression dans une cellule hôte et le procédé comprenant les étapes consistant à : (a) générer une pluralité de séquences nucléotidiques candidates codant pour la séquence d'acides aminés prédéterminée ; (b) obtenir un score de séquence sur la base d'une fonction de notation basée sur une pluralité de caractéristiques de séquence qui influencent l'expression protéinique dans la cellule hôte à l'aide d'un algorithme d'apprentissage machine statistique, la pluralité de caractéristiques de séquence comprenant une ou plusieurs caractéristiques de séquence sélectionnées dans le groupe constitué par la protéine par temps, la vitesse moyenne d'allongement et la précision pour chacune de la pluralité de séquences nucléotidiques candidates de l'étape (a) ; et (c) déterminer la séquence nucléotidique candidate présentant une expression protéinique optimisée dans la cellule hôte en tant que séquence nucléotidique optimisée.
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Designated States: AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW
African Regional Intellectual Property Organization (ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Organization (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)
Publication Language: English (EN)
Filing Language: English (EN)