Topic: Structural Bioinformatics and Molecular Dynamics
THE EFFECT OF INHA FLEXIBILITY IN DOCKING SIMULATIONS WITH
E Cohen1, K Machado1, O Norberto De Souza1
1Laborat´orio de Bioinform´atica, Modelagem e Simulac¸˜ao de Biossistemas - LABIO, Faculdadesde Inform´atica (PPGCC) e Biociˆencias (PPGBCM), PUCRS, Porto Alegre - RS
Molecular docking is an important step of the rational drug design process. It predicts the best
orientation and conformation a small molecule (ligand) will bind to a protein receptor, in a wayto form a stable complex. A detailed understanding of the interactions within the complex can beused to predict the affinity and the binding mode between the two molecules. Proteins are veryflexible in their natural environment. They can assume an ensemble of different conformations intheir native state. To computationally simulate the receptor flexibility during molecular dockingis not an easy task. Conversely, we know that it is no longer acceptable to consider receptorsas rigid bodies; the ensemble of conformations available to a receptor may play an importantrole on how a ligand will bind to its active site. The aim of this work is to contribute to a betterunderstanding of the effect of receptor explicit flexibility on molecular docking. Among the severaldifferent approaches to incorporate the receptor flexibility in molecular docking, we chose to usea trajectory from a molecular dynamics (MD) simulation. Due to its importance as a drug targetagainst tuberculosis, we use InhA, the enoyl reductase enzyme from Mycobacterium tuberculosisas receptor.
We used three flexible models of the InhA receptor: the wild type (InhA wt) and
the mutants InhA I21V and InhA I16T. MD simulations trajectories for at least 3,100 ps for eachmodel were generated previously. These flexible models were tested against flexible ethionamide(ETH) and triclosan (TCL) ligands retrieved from the ZINC database. The crystal structure ofInhA (PDB ID: 1ENY) was used as a control for a rigid receptor. Consideration of the receptorflexibility demands the preparation of many data files. Hence the experiments were automatedby using FReDOWS. FReDOWS is a scientific workflow modeled through the JaWe editor, andexecuted by Enhydra Shark. It uses AutoDock 3.05 for the docking simulations to evaluate thereceptor-ligand affinity and binding modes. Docking was performed using each snapshot from theMD trajectory. Each flexible-receptor docking generated 3,100 output files, corresponding to thefull MD trajectory. These files were further processed to find out the best estimated free energyof binding (FEB) calculated by AutoDock3.05. Since we performed blind docking, the root-meansquare deviation (RMSD) values are not meaningful. Therefore, at this stage of the work we onlylooked at the best FEB reported in the docking outputs. For the ETH ligand we have not foundsignificant differences in the FEB for the three flexible and the rigid receptor models. Significantdifferences can be seen in the experiments with TCL. The average FEB varied from -13.14 ± 0.54,-11.16 ± 0.66, -12.72 ± 0.53 Kcal/mol for InhA wt, InhA I21V, InhA I16T, respectively. Thelowest FEB for the crystal structure was -10.78 Kcal/mol. These values represent a difference ofabout 2.5 Kcal/mol when compared with the three flexible models. From this analysis we canstate two basic conclusions: first, the flexible models were able to discriminate the InhA affinityfor the TCL ligand. They showed that TCL binds more strongly to InhA wt than to the mutants.
Second, flexible receptor models can accommodate a more diverse range of ligand conformations.
This indicates that they are more prone to select a new ligand capable of binding to InhA than itwould do if we used only the crystal structure. More discussions will be presented in the poster.
Supported by: CNPq.
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