Schrodinger ebootcamp #3, Summer 2016 EXPLORING METHODS FOR CONFORMER SEARCHING Jas Bhachoo, Senior Applications Scientist
Numerous applications
Generating conformations MM Agenda http://www.schrodinger.com/macromodel ConfGen http://www.schrodinger.com/confgen/ WhitePaper coming soon Clustering conformations http://wwwschrodingercom/scriptcenter Optimising conformations Scripts QM-MM Mogul CCDC
GENERATING CONFORMATIONS
Intro to MacroModel, ConfGen Conformational searches are a very important part of 3D-ligand-based design...when we have no crystal structure to guide us we need to generate plausible 3D-structures for our ligands. We may also be interested in conformations of protein-ligandsystems for lead optimization... The Schrödinger suite provides two related tools for this operation: MacroModel The underlying engine for conformational searches Capable of some highly advanced searching ConfGen Part of MacroModeland a separate product. Includes tweaks to the basic force-field to tailor conformations towards those found in protein-bound ligands Prime (complexes and macrocycles) and MM+QM (ligands)
Which to use when? MacroModel searches generate all of the possible conformers of a molecule Depending on the settings these will be the gas/solution phase conformers These are different from the bio-active conformers, and the output energy window produces greater number of structures MacroModel conformations are useful when we need to understand a molecule s solution phase behaviour accurately MacroModel is also useful in optimizing PL environments ConfGen is designed to generate bio-active conformations These are useful when we are considering a ligand bound to a protein Docking Generate addiitonal conformations outside of Glide Docking Shape similarity searching Pharmacophores
MacroModel Conformational Searching MacroModel facilitates conformational searching of large and small systems It has an advanced continuum solvation model that is able to mimic a variety of environments The environment of a system is crucial in obtaining a meaningful set of conformers Conformations of KFGLE-Peptide MacroModelfinds ~230 distinct conformers of KFGLE in water (left) These have minimal intramolecularhydrogenbonding and leave polar groups exposed Conversely in CHCl 3 (right) MacroModel finds fewer conformers (~150) These all bury the polar functionality, leaving exposed hydrophobicity
ConfGen Conformational Searching ConfGen attempts to mimic a general protein environment during its conformational searches This penalises compact conformations and rewards more extended forms Careful balancing of intramolecular interactions is the result of considerable parameterisation and research For virtual screening and most ligand-based drug design, ConfGen is the tool of choice Conformations of KFGLE-Peptide ConfGenselects a considerably more open conformation for the KFGLE-Peptide It is assumed that the charged and hydrophobic groups will find partners in the associated host
Minima of core rotatable bonds systematically identified and sampled Terminal rotamer groups then sampled Sampling Method in ConfGen No electrostatics Ring template library from Mmod 1-4 interactions to define potential 1. Core rotatable groups 2. Terminal rotamers
ConfGen - A New Fast 3D Conformation Generator Process 10-50 compounds/sec 25x faster then ConfGen (Intermediate mode) Good recovery of bioactive conformations 8 7 6 5 4 3 2 1 0 Time Per Compound (sec.) New ConfGen ConfGen Intermediate ConfGen Comprehensive Percent of Compounds 100 80 60 40 20 Reproduction of Bioactive Conformations New ConfGen ConfGen Intermediate ConfGen Comprehensive <0.5 <0.75 <1.0 <1.25 <1.5 <1.75 <2.0 <2.25 <2.5 <2.75 <3.0 RMSD Cutoff (Angstroms)
Old CG Settings ConfGen product page http://www.schrodinger.com/confgen/ http://www.schrodinger.com/confgen/publications WhitePaper coming soon
Simple interface ConfGen GUI Extra option to minimize output conformations While including min, does not improve matching crystal structure (as measured by RMSD), min can eliminate some close contacts
Sampling Methods in MacroModel Monte-Carlo Multiple Minima: A MC search of the specified torsional space. Works well for <15 torsions. More than this requires extended runtimes. In practice this is an extremely efficient search methodology which is easy to apply. Systematic Pseudo Monte-Carlo: Modified MC code, drives the search to regions of the PES not normally explored. Most suited to small molecule searches. Low Mode Searching: The eigenvectors of the molecular Hessian matrix give information on concerted motions of the system. These concerted motions are used as coordinates in the conformational search. Large Scale Low Mode Searching: A specially tuned version of the above code for larger systems. Particularly well suited to protein conformational searching. Mixed MCMM/Low Mode Searching: A hybrid technique where specific torsions can be varied outside a standard low mode search. This is an exceptionally powerful methodology for exploring normally difficult questions such as a ligand enclosed within a binding site.
MacroModel has a Consistent GUI, irrespective of the task From a simple minimisation to a full conformational search, the panels are consistent
CLUSTERING CONFORMATIONS
Clustering Scripts Clustering of Conformers: A graphical user interface and command-line script to cluster conformations based on Cartesian or torsional RMSD. User can specify the atoms to use (based on the ASL) and the clustering settings. [Script name: conformer_cluster.py (Revision 3.16] [Script type: Maestro/Python] Spectral clustering: A script that implements the Spectral Clustering method as described by Mark Brewer in 'Development of a Spectral Clustering Method for the Analysis of Molecular Data Sets,' J. Chem. Inf. Model, 2007, 47, 1727-1733. The cluster properties (cluster membership, cluster contribution and cluster eigenvalue) are added to the project table for each input entry. [Script name: spectral_cluster.py (Revision 3.3)] [Script type: Maestro/Python] [Requires: Canvas]
Processing with conformer_cluster.py 1. Select atoms (e.g. all ) and calculate RMSD matrix 2. Run clustering 3. Find out optimal number of clusters 4. Apply clustering
Clustering Statistics...
OPTIMISING CONFORMATIONS
Combining MacroModel with Jaguar Confsearch_jag_min_workflow.py (http://wwwschrodingercom/scriptcenter) Background
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Mogul, CCDC Mogul provides precise information on preferred molecular geometries by enabling access to millions of chemically classified bond lengths, valence angles, acyclic torsion angles, and ring conformations derived from the CSD. Mogul enables you to rapidly validate the complete geometry of a given query structure and identify any unusual features without the need to construct complex search queries, or carry out detailed data analyses. Medicinal Chemists rely on Mogul to Validate conformations (calculated ones, or filtering out PL focking solutions involving unlikely ligand conformation geometry validation, eg checking the molecular dimensions of new crystal structures Search for Mogul in Tasks in Maestro 11
Validate Ligand Conformations with CCDC Mogul Check torsions, angle, and bond geometries against structures in the CSD Use local or remote Mogul instance with Schrödinger s JobControl Mogul is separately licensed
Multi-Tiered View of Torsion, Angle, and Bond Distributions
USING THE INTERFACES
WHAT ABOUT PROTEIN-LIGAND COMPLEXES?
Protein-Ligand Min /Conformational Search MacroModel provides CS of both ligands and complexes Options for searching over the PE surface of a protein include Low Mode Analysis which is very useful for jumping wells on the PE surface in order to find lowest energy conformations, optimise PL interactions and model induced fit effects MacroModel offers comprehensive tools for defining constraints Below is the DHFR enzyme complexed with methotrexatemm substructure facility, is used to setup varying levels of LP flexibility during CS process Flexible regions in white, semi flexible in orange, frozen regions in magenta
MacroModel Substructure tab allows us to easily setup this kind of flexibility
MacroModel : Refining and Modelling LigandPoses in Active Site Docking will always find a good, low energy pose for a ligand But this may not be the global minima A more comprehensive search, including the protein may enable the system to find an even better solution Energy G Because of the exponential relationship between free-energy and binding, even a small G can correspond to a large real-world activity change Conformational Space MacroModel Embrace Allows congeneric ideas to be scored in a parameterless fashion -Permits extremely advanced conformational sampling to be performed to model induced fit effects
An Example of the Effect of MacroModel Embrace Conformational Searches HIV-Protease Inhibitor Docked to 1QBR Glide leaves the ligand in the cyan pose The napthyl-group is sensibly placed, but non-optimal Similarly a hydroxyl-group is missing out two key interactions The Glide generated pose scores poorly The orange pose is generated by Embrace CSearch, the napthylgroup has been flipped significantly, while the hydroxyl is now making its proper interactions This refined pose scores significantly better
Scoring the HIV-Protease Ligands: MacroModel Embrace The raw poses generated by Glide do a reasonable job of modelling the variation in potency However, asking Embrace to refine each of the poses by carrying out a conformational sampling of the ligand within the binding site, yields a superior correlation Embrace CSearch Refinement and Rescoring Pure minimisation (x) R 2 = 0.45 Embrace CSearch (ligand only) (o) R 2 = 0.53
Setting Up An Embrace Calculation Shows output pose from Docking and Embrace Calculation
Summary Together ConfGen and MacroModel can be used to search a wide range of molecules from ligands to protein/ligand complexes and other types of molecules Maestro makes setting up and running these calculations easy Wide range of speed/quality trade offs possible Small subsets of conformers generated by ConfGen can cover conformational space quite well Searching multiple structures in a single calculation automatically is supported Distributing calculations is supported
APPLICATION TEASER NEW PHASE
Schrödinger Has A Complete Suite of LBDD Solutions Pharmacophoremodeling (Phase) 3D QSAR (Field-Based QSAR) Shape screening (Shape Screening) Conformation generation (ConfGen) ADME property prediction (QikProp) QSAR/QSPR (Canvas, AutoQSAR) Significant ongoing investment in LBDD R&D Validate ligand conformations in Maestro with CCDC Mogul
Several Ways to Create Pharmacophore Hypotheses From multiple active ligands From one ligand conformation From apoprotein 2 From protein-ligand complex 1 1 Salam, N., Nuti, R., Sherman, W., J Chem Inf Model, 2009, 49(10), 2356. 2 Loving, K., Salam, N., Sherman, W., J Comput-Aid Design, 2009, 23(8), 541.
New Phase Interface for Maestro 11 Highly interactive Modify attributes of hypothesis directly from hypothesis Easy to use for experts and non-experts
Resources for All Demos
1. Two-dimensional Coordinate Scan A contour diagram describing the variation in energy of a molecule with respect to rotation of two dihedral angles Tasks > MacroModel Coordinate Scan Help, documentation index...search for macromodel scan
Tasks > MacroModel Minimization 2. Simple Minimization Help, documentation index...search for MacroModel minimization
3. CS in MM (Peptide example demo) Tasks > MacroModel conformational search Help, documentation index...search for MacroModel conformational searches
3b. CS in ConfGen (Peptide example demo) Simple GUI
Combining MacroModel with Jaguar Confsearch_jag_min_workflow.py (http://wwwschrodingercom/scriptcenter) Background
MacroModel Embrace Help, documentation index...search for MacroModel embrace
Python Scripts ~ 7 scripts associated with MacroModelon our Website http://wwwschrodingercom/scriptcenter