Greg Lackner Marian High School December 14 th, 2011 Chemistry After Marian: What’s out there?
Greg Challis Department of Chemistry
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Transcript of Greg Challis Department of Chemistry
Greg Challis
Department of Chemistry
Lecture 1: Methods for in silico analysis of cryptic natural product biosynthetic gene clusters
Microbial Genomics and Secondary Metabolites Summer School, MedILS, Split, Croatia, 25-29 June 2007
Overview
• Introduction
cryptic (orphan) gene clusters in microbial genomes
• Clusters encoding nonribosomal peptide synthetases (NRPSs)
domains, modules, substrate specificity, predicting products
• Clusters encoding modular polyketide synthases (PKSs)
domains, modules, substrate specificity, predicting products
• Clusters encoding other biosynthetic systems
terpene synthases, iterative PKSs
Introduction
‘Cryptic’ (orphan) biosynthetic gene clusters
• Present in many of the 300 or so sequenced microbial genomes
e.g. Streptomyces avermitilisStreptomyces coelicolor
Bacillus subtilis
Pseudomonas fluorescensPseudomonas syringae
Nostoc punctiforme
Aspergillus nidulans
• May prove a valuable new source of bioactive metabolites
• Polyketide synthases
• Nonribosomal peptide synthetases
• Terpene synthases
Genome sequence of the model antibiotic-producer Streptomyces coelicolor M145
NH
N
HN
OMe
prodiginines
OO
O
O
OH
OH
OH
OHO
O CO2H
HO2C
actinorhodin
NH O
O HN
O
HN
HN
CO2H
O NH
O
HN
O
NH
OOH
NH
OHN
R'
HO2C HN
O
OH2NOC
NH
O
HN
O
NH
O
CO2H
OH
O
HO2C
OR
calcium-dependent antibiotic
O
CO2HO
methylenomycin A
Gene clusters directing complex metabolite biosynthesis in the S. coelicolor genome
Bentley et al. Nature (2002) 417, 141-147
Part 1: Nonribosomal peptide synthetase analysis
SO
H2N
Recap of NRPS organisation and function: the gramicidin S synthetase as an example
A E C A A AC C C A TE
module 1 module 2 module 3 module 4 module 5
S
NH
O
HN
NH
O
O
N
O
O
H2N
NH2
S
HN
NH
O
O
N
O
O
H2N
NH2
S
NH
O
N
O
O
H2N
S
N
O
O
H2N
SO
H2N
grsA grsBgrsT
synthetase 1 synthetase 2
PC
P
PC
P
PC
P
PC
P
PC
P
A = AdenylationPCP = peptidyl carrier proteinC = CondensationE = EpimerisationTE = Thioesterase
S
HN
OS
NH2
OS
H2N
O
NH2
S
NH2
O
Recap of NRPS organisation and function: the gramicidin S synthetase as an example
O
NH
NH
NHO
HN
HN
HN
O
O
O
O
O
O
H2N
NH2
N
ONH
N
OHN
TE
TE
S
NH
O
HN
NH
O
O
N
O
O
H2N
NH2
PC
P
O
NH
O
HN
NH
O
O
N
O
O
H2N
NH2
For further information see Lars Robbel’s poster
Nonribosomal peptide synthetases encoded by the S. coelicolor genome
A new S. coelicolor NRPS gene cluster
cchAcchBcchH
Flavin-dependent monooxygenase (cchB)
Non-ribosomal peptide synthetase (cchH)
Formyl-tetrahydrofolate-dependent formyl transferase (cchA)
MbtH-like protein (cchK)
Esterase (cchJ)
Challis and Ravel FEMS Microbiol. Lett. (2000) 187, 111-114
Export functions
Ferric-siderophore import
cchJcchI
Prediction of domain and module structure
Conserved Domain (CD) search
(http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi)
A E C A E C A
SH SHSH
Module 1 Module 2 Module 3
Deduced domain and module organization
Prediction of A-domain selectivity pocket residues
GrsA DASVWEMFMALLTGASLYIILKDTINDFVKFEQYINQKEITVITLPPTYVVHL-----DPERILSIQTLITAGSATSPSLVNKWKEK--VTYINAYGPTETTINcs1-M1 DIAVWELLAAFVGGARLVIAEHRLRGVVPHLPELMTDHRVTVAHFVPSVLEELLGWMADGGRVG-LRLVVCGGEAVPPSQRDRLLALSGARMVHAYGPTETTI
GrsA D A W T I A A INcs1-M1 D I W H V G A I
Stachelhaus, Mootz and Marahiel Chem. Biol. (1999) 6, 493-505Challis, Ravel and Townsend Chem. Biol. (2000) 7, 211-224
Empirical correlation between specificity pocket residues and substrate
Ser
Orn
hTyrCys (ACV)HPG
Leu, Ile, ValGlu (Fengycin)Leu (Eucarya)
Threonine
Asp, Asn, Gln
Valine
Ala, Dab
Cysteine
Trp, Phe
Tyr
Val, Ala (Eucarya)
Proline
Glu, Gln
Challis, Ravel and Townsend Chem. Biol. (2000) 7, 211-224
Prediction of substrates and possible products for the S. coelicolor cryptic NRPS
O
NHNH2
OH
HN
OH
O
H
O
NOH
O
NH2
OH O
NHNH2
OH
HN
OH
O
H
O
HN
N
O
OHH
Challis and Ravel FEMS Microbiol. Lett. (2000) 187, 111-114
A E C A E C A
SH SHSH
Module 1 Module 2 Module 3
A E C A E C A
SO
HN
H2NO
N
H2N
OHO
H
S
Module 1 Module 2 Module 3
O
NH2HOH
S
OH
A E C A E C A
SO
HN
H2NO
N
H2N
OHO
H
S
Module 1 Module 2 Module 3
O
NH2HOH
S
OH
Part 2: Modular polyketide synthase analysis
• Three large modular enzymes (DEBS 1-3), encoded by eryAI, eryAII, and eryAIII, assemble 6-DEB
O
O
Me
Me
Me
OH
Me
OH
O
Me
Me
OH
6-Deoxyerythronolide B
TE cyclizes
• Each module performs one chain extension
Recap of modular PKS organisation and function: the erythromycin synthase as an example
ACPKS
DH
ER
KR
SH SH
AT ACPKS
DH
ER
KR
SH S
O
O-
O
AT ACPKS
DH
ER
KR
S S
O
O-
O
O
R
AT ACPKS
DH
ER
KR
SH S
O
R
O
AT ACPKS
DH
ER
KR
SH S
O
R
HO
AT ACPKS
DH
ER
KR
SH S
O
R
AT ACPKS
DH
ER
KR
SH S
O
R
AT
Recap of modular PKS organisation and function: the erythromycin synthase as an example
-CO2
• Three large modular enzymes (DEBS 1-3), encoded by eryAI, eryAII, and eryAIII, assemble 6-DEB
O
O
Me
Me
Me
OH
Me
OH
O
Me
Me
OH
6-Deoxyerythronolide B
TE cyclizes
• Each module performs one chain extension
Recap of modular PKS organisation and function: the erythromycin synthase as an example
Gene clusters directing complex metabolite biosynthesis in the S. coelicolor genome
Bentley et al. Nature (2002) 417, 141-147
A new S. coelicolor modular PKS cluster
Genes encoding a modular PKS
Prediction of domain and modules in CpkA
Conserved Domain (CD) search
(http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi)
Prediction of domain and modules in CpkB
Prediction of domain and modules in CpkC
Prediction of domains and modules in CpkABC
Pawlik, Kotowska, Chater, Kuczek and Takano Arch. Microbiol. (2007) 187, 87-99
Prediction of AT domain substrate selectivity
Haydock et al. FEBS Lett. (1995) 374, 246-248Banskota et al. J. Antibiot. (2006) 59, 168-176
Prediction of KR domain stereoselectivity
Prediction of KR domain stereoselectivity
Caffrey ChemBioChem (2003) 4, 654-657Reid et al. Biochemistry (2003) 42, 72-79
Prediction of substrates and possible products for the S. coelicolor cryptic PKS
OH OH OH O
Hor
Non-linear enzymatic logic can complicate things!
S
N
OH
HN
S
OH S
N CO2HH
H
Haynes and Challis, Curr. Op. Drug Discov. Develop. (2007) 10, 203-218
Non-linear enzymatic logic can complicate things!
S
O
ACP ACP ACP ACP ACP
ER
ACP TEACP
H
CO2H
S
O
S
O
S
O
S
O
S
O
S
O
OHH
CO2H OHH
CO2H OHH
CO2H
OH
HO
OHH
CO2H
OH
HO
OHH
CO2H
OH
OH
HO
OHH
CO2H
Load
Module 1
Module 2
Module 3
Module 4
Module 5 + 6 + 7
Module 7
OH
O
O
H
OH
H
CO2H
OH
O
O
NC
H
OH
H
CO2H
BorI, Bor J
ATKS
KR
ATKS
KRDH
KS
DH
AT
KR
ATKS
KR
KS
DH
AT
KR
KS
KR
ATAT
3
3
Haynes and Challis, Curr. Op. Drug Discov. Develop. (2007) 10, 203-218
Part 3: Analysis of other biosynthetic systems
Terpene synthases
OPP
OPP
C10
C15
OPPC20
C30
mono-terpene
synthase
sesqui-terpene
synthase
di-terpene
synthase
tri-terpene
synthase
HO OH
O
SCoA
OH
OAmycolatopsis
orientalis
DpgA4 x Me
O O
O
NH
O HN
O
NH
O
NHMe
Cl
O
HN
H
OH
NH
OCl
OH
NHO
OHHO
H
HO2C
HOH
O
HOHO
O
OH
OH2N
HO Me
NH2
O
HO OH
O
OHH2N
HOOH
O
Streptomycesgriseus
5 x
OH OH
OH
HO
OH OH
OH
HO
OH OH
OHmelanin
RppA
Iterative polyketide synthases – type III PKSs
Conclusions
• Reasonably confident in silico predictions of domain / module organisation and substrate specificity of modular PKS / NRPS can be made
• Non-linear enzymatic logic can complicate the reliable prediction of product structure(s)
• For other types of biosynthetic system, reasonably confident predictions of substrate specificity can sometimes be made
• Prediction of chain length and substrate specificity in some iterative PKS systems, especially type III and fungal type I, remains difficult