CCL: FLAP 2.0 & WaterFLAP

 Sent to CCL by: Simon Cross [simon*moldiscovery.com]
 Dear Colleagues,
We are very proud to announce the release of FLAP 2.0 for virtual screening, pharmacophore modelling, 3D-QSAR, docking, and water prediction. FLAP is based on GRID Molecular Interaction Fields, in combination with pharmacophoric quadruplet fingerprints, and enables candidate similarity to be calculated to a template in both ligand-based and structure-based approaches.
The fingerprints can be used directly to compare structure, or to perform ligand-based alignment and structure-based pose prediction. These alignments are scored according to GRID MIF similarity, allowing candidates to be ranked according to how well they match the template. A wide range of GRID MIF similarities can be calculated, including a global similarity score. Additionally, target specific scores can be parameterised using known active/inactive data to train the method. For virtual screening, FLAP has been validated against a number of prospective targets to find adenosine receptor antagonists, folate cycle inhibitors, NorA inhibitors, and influenza viruses.
Pharmacophore elucidation can be performed from a set of active molecules, using the FLAPpharm approach that is based on FLAP ligand-based alignments. 3D-QSAR can be performed using the FLAP alignments, or alternatively a fuzzy maximal common subgraph based alignment, in addition to the GRID MIFs and statistical approaches such as PCA/PLS.
FLAP 2.0 contains a number of significant enhancements compared to FLAP 1.0. WaterFLAP is a new approach based on GRID MIFs to predict site water locations and networks; the waters are then scored using the new CRY field (combined hydrophobicity and lipophilicity), ENTR (to estimate the entropic character), and the OH2 water enthalpy. These scores quickly enable determination of structural, displaceable, and bulk waters, and have been used to predict the kinetics of binding. The docking algorithm FLAPdock has been extensively re-parameterised and validated on hundreds of crystal structures including the Astex and DUD datasets. Additionally, FLAPdock is able to use the WaterFLAP waters to guide pose prediction, giving improved results where bridging waters are critical for binding. The GRID procedure is now accessible from within FLAP to allow full binding site characterisation and analysis. 
 Key features include:
- Fast ligand-based and structure-based virtual screening using FLAP fingerprints - Improved virtual screening accuracy using FLAP alignment and GRID MIF scoring 
 - Optional user-specified pharmacophoric feature constraints
- Ligand-based alignment and structure-based pose prediction using GRID MIFs 
 - Pharmacophore elucidation and screening
 - Automatic pocket detection for structure-based design
 - GRID MIF calculation using all standard GRID probes
- Linear Discriminant Analysis enables the training of target focused scoring functions - Enrichment plot analysis enables screening approach validation prior to prospective screening 
 - Fuzzy maximal common substructure alignment
 - 3D-QSAR analysis
 - WaterFLAP water prediction, scoring, and analysis
 - FLAPdock docking using GRID MIFs and WaterFLAP waters
- MoKa integration for automatic protonation and tautomer enumeration and selection (requires FLAP-Suite edition) - VolSurf+ integration to enable virtual screening that includes pharmacokinetic properties (requires a separate VolSurf+ license) 
 FLAP is available for both Windows and Linux operating systems.
 More information about FLAP can be found here:
 http://www.moldiscovery.com/soft_flap.php
 Kind regards,
 Simon
 Dr. Simon Cross
 Snr Scientist & Product Manager
 Molecular Discovery Ltd
 Email: simon[at]moldiscovery[dot]com
Molecular Discovery provides robust, high-quality and innovative computational methods addressing pharmaceutical needs in the field of drug discovery, including methods for virtual screening, lead optimisation, ADME modelling and metabolism research.
Molecular Discovery software products offer calculation of accurate Molecular Interaction Fields for structure-based design (GRID), water prediction for structure-based design (FLAP), ligand-based and structure-based virtual screening (FLAP), pharmacophore elucidation (FLAP), metabolism prediction (MetaSite), metabolite identification (Mass-MetaSite), scaffold hopping (SHOP), pKa prediction (MoKa), 3D-QSAR modeling (FLAP, Pentacle) to improve efficiency in modern drug discovery. 
 More information can be found on the main page:
 http://www.moldiscovery.com/