Table 6b.

Studies including full receptor flexibility through a structural ensemble previously generated by MD

Method	Target	Flexibility	Results	Caveats	Author
MCSS	HIVp	Used quenched MD to generate new conformations or mapped a different conformation from the reference Flooded protein surface with functional group probes to identify regions of consensus	Local optimization of selected probes from MCSS improved interaction energy Protocols 2 and 3 yielded functionality maps that were the most divergent from the reference Protocol 4 yielded the most low-energy minima	Recovers local minima in addition to the binding site Very minor amount of protein flexibility included	Stultz & Karplus (1999)
MPS/dynamic pharmacophore	HIV integrase	Used MD to generate new conformations from a crystal structure Flooded probes to protein surface and determined consensus clusters	Flexible model recovered known inhibitors from a virtual screen Rigid model did not recover any known inhibitors Identified novel inhibitors for binding the target with experimental verified activity	No desolvation penalty Can recover local minima	Carlson et al. (1999, 2000)
MD+ LigBuilder	Alanine Racemase	Dynamic pharmacophore modeling similar to MPS, but can simultaneously search with multiple probes LigBuilder mapped surface properties of each conformation (11 total) after MD	Dynamic pharmacophore model identified 34 hits out of the set of 43 known binders, compared to the 27 identified by the static model	Very brief phase of MD for conformation generation	Mustata & Briggs (2002)
RCS	FKBP-12	Conformations generated by MD Rapid docking in AutoDock Refinement of high scoring complexes with MM/PBSA, which was necessary to recover the crystal pose	Correctly ranked the crystallographic pose as the highest rank with MM/PBSA for all three small molecules Noted that docking results were highly sensitive to protein conformation	Can be time-consuming Very short MD simulation (2 ns) for conformer generation Free energies were distributed within 2–3 kcal/mol, potentially resulting in misranking a binder as weak/potent	Lin et al. (2003)
Explicit solvent MD/AutoDock	p38 MAPK (5000 MD snapshots)	Performed 10 MD simulations of 30 ns at 1000 K, continued 3 runs to 60 ns upon conformational divergence from the initial structure Harmonic restraint on all heavy atoms, excluding the activation loop and nearby residues Applied AutoDock using snapshots from single simulation	Found 2 novel conformations of DFG motif Successfully docked 5 known inhibitors Conformers from simulation identified cryptic binding sites Docking failures were judged to be the result of conformational sampling	Extensive MD simulation (390 ns total) render this technique impractical for some SBDD applications	Frembgen- Kesner & Elcock (2006)
Flo98	C. hominis DHFR, T. gondii DHFR	Simulated annealing of active site MC search for optimal bound pose Averaged energy of 25 lowest energy protein-ligand complexes Developed homology model for TgDHFR	Calculated binding affinity was 72.9% correlated to experiment (ChDHFR) Identified alternate binding site Correlation between docking and activity (TgDHFR) was 50.2% by R2 Found that an averaged energy value outperformed individual values, by reducing error in pose evaluation by the scoring function	Enables limited flexibility of binding site residues only during global MC docking	Popov et al. (2007)
Reduced Receptor Ensemble	Avian flu neuramindase	Similar to MPS Generated MD ensemble Flooded ensemble with probes (CS-Map), created pharmacophore	Predicted novel hot spots potentially relevant for de novo ligand design Proposed a new inhibitor class	No experimental support of sites	Landon et al. (2008)
REMD/PLOP	Six cases	REMD used to generate low-energy loop conformations After clustering, loops refined with PLOP Lowest energy conformer used for docking with GLIDE	RMSD of docked pose between holo and predicted structure was 1.4–12.5 Å RMSD of docked pose between crystal and holo structure was 1.0–2.5 Å Failures resulted from sampling deficiencies and structural features unrelated to the loop Scoring favored closed conformation loops	Limited by efficiency of REMD for generating loop conformations	Wong & Jacobson (2008)
Ensemble reduction method	DHFR	Generated MD ensemble Used relative difference of interatomic distances for ensemble structures compared to an experimentally determined holo structure to define optimal conformations	Found that conservation of essential distances between the residues that were important for binding was best for selecting a representative ensemble Pruned the structural ensemble by 50–75% while retaining docking accuracy Some structures scored poses well but placed ligands incorrectly	Maintaining conserved core distances may limit exploration of important large-scale shifts No correlation between relative difference and docking score or correct pose	Bolstad & Anderson (2009)
Enhanced molecular docking	Human prion protein	Used 20-ns MD to generate 20 conformations for docking along with NMR structure Docked with AutoDock and GOLD Clustered results, ran 10 ns of MD, then six independent metadynamics simulations to find the free energies of binding/dissociation	Calculated dissociation dG was 7.8–8.6 kcal/mol while experimental dissociation dG was 7.5 kcal/mol Predicted multiple binding sites Affinities agreed with NMR experiment	Computationally intensive	Kranjc et al. (2009)
Explicit solvent MD/Glide	Reverse transcriptase (10 000), W191 G (7500)	Generated a conformational ensemble from MD of holo- and apo-crystal structures Docked ligand/decoy set to conformers in Glide	Found that MD could be used to move a conformation into a predictive range for docking MD and AUC were not correlated Identified a correlation between the average predictive power and the average flexibility of the binding site, such that highly flexible sites had less utility for docking Concluded that a broadly applicable protocol for the application of a structural ensemble to docking is still a distant goal	No single feature can be used to pick out conformations May require extensive knowledge of the system	Nichols et al. (2011)