comparative evaluation of 11 scoring functions for molekular docking authors: renxiao wang, yipin lu...
TRANSCRIPT
Comparative Evaluation of 11 Scoring Functions for Molekular
DockingAuthors: Renxiao Wang, Yipin Lu
and Shaomeng Wang
Presented by Florian Lenz
Today‘s Docking Programs
• 1. Sampling
• 2. Selecting
• Scoring function are needed for both!– Guiding the sampling– Evaluating the results
Previous Studies
• Compared combinations of docking programs / scoring functions– one combination fails: blame the Scoring
Function, the Docking Program, or the combination?
– Even if all the functions are tested under the same conditions: A unmonitored sampling process could yield inadequate samples
Solution
• Only use ONE docking program, and a wide range of parameters
• Monitor the sampling results
• 100 different complexes
• Three kinds of tests:– Reproduce experimental determined structure– Reproduce experimental determined binding
affinities– Describe a funnel shaped energy surface
Selecting the test cases
• Starting point: 230 complexes
• Only these with a resolution better then 2.5 Å are used (172)
• Creating a diverse ensemble (100)
Sampling
• AutoDock using Genetic Algorithms• Protein-Conformation is fixed• Ligand:
– Every rotatable single bond may rotate– Flexibility of cyclic part is neglected– Translation: 0.5 Å, Rotation: 15°, Torsion: 15°
• Docking Box: 30x30x30 Å around the observed binding position
• For each complex: 100 sampled conformation and the „real“ conformation
Monitoring• Repetition: Aim is not to find energy
minimum, but to create a diverse test set– RMSD must cover a wide range (0 to 15 Å)– # of clusters between 30 and 70– Enough results near the “real” position and
meaningful conformations.
• Key Parameter: Length of the GA-Runs– Too short -> Results are too close to initial
position– Too long -> Results enrich at very few
clusters
Problems with too long/short runs
• For every complex, the numbers of generations have to be determined separately
• If even 200 generations don‘t lead to a satisfying result, the complex is discarded
Example for a monitored ensemble
The 11 scoring functions
• 3 force-field based: AutoDock, G-Score and D-Score
• 6 empirical: LigScore, PLP, LUDI, F-Score, ChemScore and X-Score
• Knowledge-based: PMF and DrugScore
First Tests: Docking Accuracy• „How close is the ligand in the best scored solution to its
“real” position?“
1. Tests: Docking Accuracy
Type of Interaction vs. Docking Accuracy
(CVDW)(VDW) + (CH-bond)(HB) + (Chydrophobic)(HS) + (Crotor)(RT)+C0
Consensus ScoringExample:
1st place with X-Score, 7th place with LigScore = ((1+7)/2=) 4th place X-Score+LigScore
2nd Test: Binding Affinity Prediction
• Compare the ranking by scores with the ranking of the free energies.
• Using Spearman Correlation:
•dj is the distance between the rank by score and the rank by free energy for complex number j•Rs = 1 correspond to a perfect correlation•Rs= -1 correspond to a perfect inverse correlation•Rs = 0 correspond to a complete disorder
2nd Test: Binding Affinity Prediction
Best Result: X-Score (Rs = 0.660
4th best result: G-Score (Rs = 0.569)
2nd Test: Binding Affinity Prediction
3rd Test: Funnel Shaped Energy Surface
• Theory stems from Protein Folding
• Ligand is guided by decreasing free energy
• Scoring functions should show a correlation between RMSD Value and score
• How does the Ligand reach the binding pocket of the Protein?
3rd Test: Funnel Shaped Energy Surface
Example: PDB Entry 1cbx (Carboxypeptidase with Benzylsuccinate)
X-Score (Rs: 0.877) LigScore (Rs: 0.135)
3rd Test: Funnel Shaped Energy Surface
Side Result: The Outliers
• In seven ensembles, none of the 11 function was able to pick a conformation with a RMSD below 2.0 Å
• Analysis of these shows the general problems of today’s scoring functions– Indirect interactions (1CLA, 2CLA, 3CLA)– Very shallow groove instead of binding pocket
(1THA, 1RGL, 1TET)
Indirect Interactions
• In samples, water molecules are not included• F-Score predicted that the ligand binds on the surface• DrugScore, LigScore and PLP found another little hole
in the protein to put the ligand in
Very shallow groove
• Correct “binding pocket”• But only partial overlapping and wrong
orientation
Most important results
• Empirical Function worked best in Docking Accuracy
• Consensus scoring of the six best functions greatly improves the success rate (above 80%)
• Prediction of Binding Affinities was less encouraging
• There are examples, to which none function could find a good solution to
Thank You