1. Understanding biosynthesis of complex metabolites
using computational biology
D. Mohanty
National Institute of Immunology
New Delhi

3. Substrate Specificity of Catalytic Domains
PKS
NRPS
Modifying Domains
Acyl Transferase
(AT)
Adenylation
(A)
Acyl CoA Synthetases
(ACS)
Keto Synthases
(KS)
Condensation
(C)
Glycosyl Transferases
(GTr)
Chalcone Synthases
(CHS)
N-Acyl Transferases
(NAT)
Domains Involved in Protein-Protein Interactions
KS – ACP
AT – ACP
A – PCP
C – PCP
PapA5 – ACP

4. Levels of Functional Annotation
Sequence based methods: Fundamental for functional annotation
Drawback: Cannot predict substrate specificity

5. SCoA PCPS SCoA Luciferin Oxyluciferin Amino acid Coumarate
Amino acyl PCP
Coumaroyl CoA
SCoA
Fatty acid
Acyl CoA

6. Computational Chemistry Knowledge Based Approach
D F G H Y K L M V C
Homology modeling
Model protein based on known structure of a similar protein
Find the substrate which binds to the model protein
Range of possible
substrates

7. Design of novel polyketides/nonribisomal
Knowledge Based Approach
Sequence/structure information for large number of proteins with known specificity
Sequence-Product correlation
Predictive rules
Predicting substrate specificity of new members of the family
using evolutionary information
Design of novel proteins
with altered specificity.
In silico identification of PKS/NRPS products
Design of novel polyketides/nonribisomal
peptides

8. BIOSYNTHESIS OF A MODULAR PKS
rapamycin(immunosuppressant)
erythromycinA antibacterial)
rifamycin B(antituberculosis)
KS:KETOSYNTHASE; AT:ACYL TRANSFERASE; DH:DEHYDRATASE; ER:ENOYL REDUCTASE;
KR:KETOREDUCTASE; ACP:ACYL CARRIER PROTEEIN; TE:THIOESTERASE

9. ACYL TRANSFERASE (AT) DOMAIN
Involved in selection of starter and extender units during
Biosynthesis of Fatty acids and Polyketides
POSSIBLE STARTER AND EXTENDER UNITS
PKS
FAS
Isobutyryl CoA
Acetyl CoA
Acetyl CoA
Propionyl CoA
Malonyl CoA
Butyryl CoA
Benzoyl CoA
Methylmalonyl CoA
Acetyl CoA
Acetoacetyl CoA
Malonyl CoA

11. Yadav G, Gokhale R. S and Mohanty D. (2003) Nucl. Acids Res
PKSDB

12. Table 3 (a)

13. Substrate Specificity of AT domains of PKS
Yadav, G., Gokhale, R. S. and
Mohanty, D. (2003)
J. Mol. Biol. 328,
Trivedi et al. Mol Cell 2005, 17: 1-13

14. Classification of KS sequence into subfamilies: Modular or Iterative ?
KS domain dendrogram
Different sub-families of KS domain
sequences show distinct clustering.
How to Quantify this difference?

15. Identification of residues in KS which control number of iterations

16. Analyses of KS domains from iterative PKS
Threading of sequence onto known structural folds
Homology Models based on highest scoring structural templates
Active site residue extraction and analyses
Cavity Analyses of various models in terms of :
Volume
Hydrophobicity
Topology
Comparison across iterative PKS subfamilies

17. The E.coli KAS-II
Catalytic Pocket

18. Hydrophobicity of CLRs Cavity Volume Vs No. of Iterations
Plots of iterative KS model cavity parameters
Are we analyzing the correct cavity?
Saturation of Product Vs
Hydrophobicity of CLRs
Cavity Volume Vs No. of Iterations

19. Shapes of Active Sites of Iterative PKSs
MSAS
NAPTHOPYRONE

20. ACTIVE SITE RESIDUES OF ITERATIVE KS DOMAINS

21. CORRECT ORDER OF ORFs WITHIN A PKS BIOSYNTHETIC CLUSTER
Simocyclinone PKS
Mupirocin PKS cluster

22. ROLE OF LINKERS

24. INTERMODULAR DOCKING INTERACTIONS
Pairs tested 66
Both charged Interactions 20
One charged Interaction 11
At least One Good Interaction 23
Percentage of Total
82%
Both Bad Interactions
Cognate – Non Cognate Differentiation (An example):
Pair 1
Pair 2
Interface
Ery1-C
D E
Ery2-N
K R
Ery 1-2 (cognate)
D-K
E-R
+ +
Ery2-C
D K
Ery3-N
R D
Ery 2-3 (cognate)
D-R
K-D
Ery 1-3
Noncognate
E-D
+ -

25. PREDICTION OF ORF ORDER USING LINKER INTERACTIONS
The Spinosyn Biosynthetic cluster
ORFs:
ORDER
Interface 1
Interface 2
Interface 3
Interface 4
TOTAL:
Good – Bad - Neutral
. .
+ +
+ -
- -
- +
Charged Interaction (+) Bad Interaction(-) Neutral Interaction (.)

26. ORF ORDER PREDICTION FOR PKS CLUSTERS

27. Naturally occurring peptides produced by NRPSs.

28. Substrates of NRPS

29. Specificity determining residues (SDR)
Consensus Active Site Patterns Of Six Subfamilies
Acetyl
Medium
Long
Coumarate
Luciferase
NRPS W H I F * V Y G D T S P A K
95%
83%
93%
92%
100%
Lys 517
3.02 Å
Gly 324
4.82 Å
* No consensus
Specificity determining residues (SDR)
Active site pattern

30. Products 22
ORFs 74 C
181 A
151 M 14 T
161 Te
NRPSDB

31. Active site residues of Adenylation domains

32. SEARCHNRPS
Ansari MZ, Yadav, G., Gokhale, R. S. and Mohanty, D. (2004) Nucl. Acids Res. 32:W405-13 .

33. How good are models at such low sequence homology ?
Genetic algorithm for 250 runs.
Grid size: X 22.5 X 22.5 (Å)3
Cluster rmsd :1.7Å
Major cluster: 223
Minor cluster: 27
Crystal structure of the long chain CoA ligase (1V26)
Model of the same protein based on 1AMU
Ligand Rmsd = 2.3 Å
10/18

34. Glycosyltransferases (GT), enzymes that transfer sugars to other molecules.
R’ = Sugar, Lipid, Protein, DNA
Secondary metabolites
R=nucleoside
nucleoside monophosphate

35. GTr sequences cluster according to substrate specificity
Vancomycin group
Prediction accuracy = 77%
Orthosomycin group
Aminoglycoside AB
Hybrid NRPS-PKS
Polyene macrolide AB
Enediyne group
Angucycline AB
Aminocoumarin AB
Anthracycline group
Macrolide group
Aureolic acid AB

36. DVV and its binding residues TYD and its binding residues
Identifying substrate (donor/acceptor) binding residues
N-Domain
DVV and its binding residues
TYD and its binding residues
Linker
C-Domain
CGTDLMMLQMPPPELTGDDPYNT
SGSDMLGKRVPRLQSAGVPGFMT
TRGELGSEVFHSGTV
SRGEIGSEVHASGUA
1RRV
Best Match
Query V C T S 8 G 9 10 R 11 12 D 13 E 15 L I M 55 59 60 K 61 Q 62 65 P 66 67 68 73 76 A 80
102
103
141
143 Y F
166
218
245
246
293
294 H
296
309
311
313 U
314
317 N
331
332
Acceptor Binding Residues
Donor Binding Residues

37. Benchmark the Prediction Accuracy
GtfD
Correctly predicted the same site and 90% of the donor binding residues
GtfA C
% identity ~ 55% C
% identity ~ 20%
MurG
Correctly predicted approximately the same site and 50% of the donor binding residues C

38. Organization of SEARCHGTr and its backend database GTrDB
amino acid
Kamra P, Gokhale RS and Mohanty D (2005)
Nucl. Acids Res., In Press

39. PREDICT STRUCTURAL FOLD
CAT
NRPS
CRAT
PREDICT STRUCTURAL FOLD
AND CORRELATE WITH
KNOWN CHEMISTRY
PapA5
CAT Fold
E2p
BAHD

40. CAT Superfamily NRPS Domains B A H D C R T CAT N P S Epi Cyc Con D-X
L-X

41. Identification of crucial residues involved in protein-protein interaction
PapA5
(Crystal Structure)
MAS ACP
(Homology Model)
PapA5
Protein Docking
Mutational studies of these crucial residues
WT R234E R312E
Trivedi et. al. Mol. Cell. (2005) 17,

42. Acknowledgements Gitanjali Yadav Md. Zeeshan Ansari Pankaj Kamra
Dr. Rajesh S. Gokhale
Chemical Biology Group
Dr. S.K. Basu, Director, NII
BTIS, DBT, India

43. Substrates of Coumarate CoA Ligases Coenzyme A Cinnamate Coumarate
Caffeate
Sinapate
Ferulate
3,4-DMC

44. Adenylation domain
of NRPS
Substrates of NRPS
PCP Domain

45. Substrates of Fatty Acid CoA Ligases
Coenzyme A
Substrates of Fatty Acid CoA Ligases
Fatty acid CoA
Ligase
Acetic acid
n ~ : Medium chain fatty acid
n ~ 5 -11: Long chain fatty acid
n > 11 : Very Long chain fatty acid
Enzymic activation and transfer of fatty acids as acyl-adenylates in mycobacteria
Trivedi, O.A., Arora, P., Sridharan, V., Tickoo, R., Mohanty, D. and Gokhale, R.S Nature 428:441.