ChemAxon in 3D Gábor Imre, Adrián Kalászi and Miklós Vargyas Solutions for Cheminformatics

Talk overview ChemAxons 2D tradition –visualize –depict/edit –search –calculate/predict properties 3D pearls

3D visualization

3D structure generation

3D search And what do we do with 3D structures? Like what, why, give motivation Perhaps we can show some cars without going to details, just en passant But we may refer to shapes

Advanced 3D visualization

3D structure generation Why is 3D structure generation hard What are the typical approaches

Our approach Chemically aware coordinate and conformer generation Reliable, robust

Searching in 3D Molecules are inherently spatial objects Typical searches are two-dimensional –Molecular descriptor –Fingerprint

3D alignment

Conformational flexibility

Multi-conformer rigid search One viable solution to tackle conformational flexibility The rigid apparatus can be applied Highly combinatorial: –All target conformation need to be considered –Do we have multiple query conformations? multiple conformations have to be generated

Multiple conformation generation Molecular mechanics based geometry optimization –Improved Dreiding force field to suite wider range of (small organic) molecules –Modified to support efficient optimization –Fast numeric optimization

3D alignment Minimizes atom-pair distance constraints

Alignment of challenging molecules

3D shape similarity T= + -

3D virtual screening 3D flexible virtual screening on 2D molecules with 2D query Maximizes colored shape intersection of the query and the target Calculates volume Tanimoto of the optimum 3D flexible alignment

3D pharmacophore fingerprint

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Summary 3D molecule alignment –Rigid – all conformations are intact –Flexible – all conformations may change –Combined – only the selected molecules are rigid, the others treated flexible –Atom pairing User defined Auto align – tries to find the optimal overlay Combined –Chemically sound conformations –Optional ring flexibility

Summary 3D virtual screening –Minimal and maximal interatomic distances are calculated between atoms of given types –The costly calculation of the fingerprint is done only once per library –The similarity search is as fast as with 2D fingerprint –All the popular similarity functions can be calculated: Tanimoto, Tversky, Dice, Euclidean.

MD Simple dreiding based MD Used internally by hyperfine Available as a plugin also Projected MD In development Rigid term energy redistribution Extremely fast conformational transitions due to the elimination of vibrational components

3D calculations Conformers plugin Coordinate / conformers generation Geometry optimization Energy calculation Geometry plugins Steric hindrance Molecular surface area Molecular projection area Molecular volume

Acknowledgement Dr. Ödön Farkas Dr. Imre Jákli Judit Vasko-Szedlar