Generating Synthetically Accessible Ligands by De Novo Design Synthetic Sprout A Peter Johnson Krisztina Boda Attilla Ting Jon Baber

SPROUT is the De Novo design system developed in Leeds SPROUT components  Identification of potential interaction sites complementary to the receptor, ie H bonding, hydrophobic sites, metal co- ordination sites etc.  Automated docking of small fragments at the interaction sites.  Generation of hypothetical structures by linking the docked fragments together.  Tools for scoring, sorting and navigating the answer set.

Example: 3D shapes of sites H-bond acceptor site H-bond donor site Hydrogen Bond Sites

Boundary Surface

Docking of small fragments at target sites Target sites are generated either by SPROUT module HIPPO (or similar system) or come from a pharmacophore hypothesis. Small fragments with complementary functionality are selected by the user and automatically docked into the target site(s). In addition to these small fragments, it is also possible to dock large fragments which are known to satisfy several of the target sites. Such a large fragment can then act as a “seed” for further growth. A successful dock must place the small fragment at the target site with the correct orientation to satisfy any directional constraints. The docking process is very fast and uses a novel hierarchical least squares optimisation procedure.

Structure generation The SPIDER module links the target sites together in a pairwise fashion to make complete molecular structures which satisfy target sites. It does this by sequentially adding new fragments in an exhaustive fashion. There is no element of random choice in this process, which means that various heuristics have to be adopted to avoid a combinatorial explosion. The main approximations employed are: There is a sampling of all the possible conformations about single bonds. Growth is only permitted from atoms/bonds which are closest to the target site which is to be reached

Main algorithm of SPIDER Multiphase heuristic graph search on a forest ( set of trees) Two trees are searched and removed in each phase and a new tree generated which contains skeletons connections both set of sites Each phase consists of a bi-directional search Breadth First Search (BFS) Depth First Search (DFS) Typical saving bi-directional search 10 successors, 6 level: 2x10 3 << 10 6

Connection of Partial Structures Common template is located in two structures (one from each tree) Structures are overlayed by the common template Combined structure is docked to the united set of target sites also considering the steric constraints of the receptor site Side effect joins are axamined for validity (e.g. fusion on figure)

Navigating the answer sets Estimated binding energy score n Ranking final de novo set n Ranking and pruning (with caution) intermediate trees to reduce combinatorial problem. Estimated ease of synthesis score n Ranking final de novo answer set n Too slow (~1 structure per minute) to be useful for intermediate pruning n Need faster methods for intermediate pruning

Recent Advances n Parallelization of structure generation –Farm of SG’s or pcs –SPROUT server – BEOWOLF cluster currently 11 dual processor 600Mhz Pentium III n VLSPROUT screens virtual libraries n SYNSPROUT generates synthetically accessible ligands n Receptor SPROUT generates potential synthetic receptors for small movecules

The perennial modellers problem Hypothetical ligands, including those predicted to bind very strongly, have no practical value unless they can be readily synthesised. Our attempts to provide solutions: CAESApost design estimation of synthetic accessibility SynSPROUTsynthetic constraints built into the de novo design process VLSPROUTeven greater synthetic constraints – only members of a specific virtual library are generated

Synthetic Sprout Approach Pool of readily available starting materials, e.g. subset of ACD Knowledge Base of reliable high yielding reactions, e.g. esterification, amide formation, reductive amination.. Readily synthesable Putative ligand structures VIRTUAL SYNTHESIS IN RECEPTOR CAVITY

Creation of Starting Material Libraries n Obvious Classes eg amino acids n “Drug like” starting materials selected by hand n “Drug like” starting materials generated automatically by retrosynthetic analysis of drug databases

EXPLANATION Ether Formation IF Ether THEN disconnect bond between 2 and 3 add-atom O[Hs=1], Cl, Br 3 with – add-hydrogen to 2 END-THEN EXPLANATION Ether Formation IF Ether THEN disconnect bond between 2 and 3 add-atom O[Hs=1], Cl, Br 3 with – add-hydrogen to 2 END-THEN EXPLANATION Amide Formation IF Amide THEN disconnect bond between 1 and 3 add-atom O[Hs=1] to 1 with – add-hydrogen to 2 END-THEN EXPLANATION Amide Formation IF Amide THEN disconnect bond between 1 and 3 add-atom O[Hs=1] to 1 with – add-hydrogen to 2 END-THEN EXPLANATION Amide Formation IF Amide THEN disconnect bond between 1 and 3 add-atom O[Hs=1] to 1 with – add-hydrogen to 2 END-THEN EXPLANATION Amide Formation IF Amide THEN disconnect bond between 1 and 3 add-atom O[Hs=1] to 1 with – add-hydrogen to 2 END-THEN Retro-Synthetic Knowledge Base Retro-Synthetic Rule EXPLANATION Amide Formation IF Amide THEN disconnect bond between 1 and 3 add-atom O[Hs=1] to 1 with – add-hydrogen to 2 END-THEN EXPLANATION Ether Formation IF Ether THEN disconnect bond between 2 and 3 add-atom O[Hs=1], Cl, Br 3 with – add-hydrogen to 2 END-THEN EXPLANATION Ether Formation IF Ether THEN disconnect bond between 2 and 3 add-atom O[Hs=1], Cl, Br 3 with – add-hydrogen to 2 END-THEN EXPLANATION Ether Formation IF Ether THEN disconnect bond between 2 and 3 add-atom O[Hs=1], Cl, Br 3 with – add-hydrogen to 2 END-THEN

Automatic Template Library Generation Synthetic Template Library Corina Omega Synthetic Knowledge Base Functional groups Perception Knowledge Bases Aromatic Normalisation Hybridisation H-bonding properties Single 3D Conformer Generation Multiple Conformer Generation 2D Drug-like Structures Retro-Synthetic Knowledge Base Fragmentation Filter Clustering Ring Perception Retro-Synthetic rules Retro-synthetic patterns

Automatic Chemical Perception n Information Perceived –Aromatic atoms and bonds –Normalised bonds –Hybridisation including induced hybridisation –H-Donors / Acceptors –Number of hydrogens attached to an atom –Number of connections to an atom –Number of available electron pairs –Charge at an atom CHEMICAL-LABEL X[SPCENTRE=2]-N[HS=0,1,2];[SPCENTRE=3] EXPLANATION N with lone pair next to sp2 centre behaves as sp2. IF NitrogenWithLP--SP2 THEN set-av-eps 2 to 0 set-hybridisation 2 to 2 END-THEN Example from Hybridisation knowledge base Rule based system where rules are encoded using the PATRAN language (similar to SMILES)

Perception - Binding Properties O Single atom based Vs C Functional group based –D - H donor –A - H acceptor –J - Joinable* –H - Hydrophobic –N - None O - original method C - current method * According to reaction knowledge base

Synthetic Template Primary Amine (Donor) Carboxylic Acid (Acceptor) Phenol (Acceptor-Donor) A A AD H A D H A A

Synthetic Knowledge Base Synthetic Rules EXPLANATION Amide Formation 1 IF Carboxylic Acid INTER Primary Amine THEN destroy-atom 3 form-bond - between 1 and 5 change-hybridization 5 to SP2 Dihedral 0 0 Dihedral Bond-length 1.35 END-THEN Joining Rules Steps of formation Hybridization change Bond type Bond length Dihedral angles/penalties

Acceptor Site Donor site De-novo Design Using Synthetic Sprout 2. Reductive Amination ( Carbonyl - Primary Amine ) 1.Amide Formation ( Carboxylic Acid -Primary Amine )

New Problems - Hybridisation change (SP3  SP2) SP3 SP2 Hybridisation change in Amide Formation 2. ( Carboxylic Acid - Secondary Amine ) Secondary Amine Nitrogen becomes SP2

Hybridisation change (SP2  SP3) SP2 SP3 Carbonyl Carbon becomes SP2 Hybridisation change in Reductive Amination 1. ( Carbonyl - Primary Amine )

Selection of Synthetic Reactions Amide Formation Ether Formation Ullman reaction Amine Alkylation Ester Formation Aldol Wittig Imine C-S-C Formation Reductive Amination

CDK2 Docked:890 Docked:780 Docked:935 Docked: Library : 300 fragments/1055 conformations Run time : 10 h Amide Alkylation 2 ( Secondary Amide – Primary Alkyl Halide ) 2 Wittig Reaction ( Carbonyl = Primary Alkyl Halide ) 3 Ether Formation 1 ( Alcohol - Alcohol ) 4 & 5 Amine Alkylation 1 (Primary Amine - Primary Alkyl Halide ) Act Score : -7.80

SynSPROUT Current status Works well for small starting material libraries (low hundreds). Several libraries now built including amino acid library for peptide generation. Library from MDDR being built. Potential for suggesting starting points for new combinatorial libraries Future work Extend types of chemistry allowed Develop algorithms which would permit the use of libraries of hundreds of thousands of starting materials (such as ACD). Parallelisation helps but on its own is not sufficient to cope with the inevitable combinatorial explosion.

Acknowledgements Co-workers : Krisztina Boda Attilla Ting Jon Baber Special thanks to Open Eye Scientific Software for providing access to OMEGA