# Comparing AutoDock and Vina in Ligand/Decoy Discrimination for Virtual Screening
## 2 Materials and Methods
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Target Class** & \begin{tabular}{c} **DUD–E** \\ **Code** \\ \end{tabular} & \begin{tabular}{c} **PDB** \\ **Code** \\ \end{tabular} & \begin{tabular}{c} **Protein Name** \\ \end{tabular} & **Ligands** & **Decoys** & **Metal** \\ \hline \multirow{2}{*}{Metallo-enzymes} & **MP2K1** & 3 EQH & \
\begin{tabular}{c} Dual specificity mitogen-activated \\ protein kinase 1 \\ \end{tabular} & 121 & 8147 & Mg\({}^{2+}\) \\  & **ACE** & 3 BKL &
\begin{tabular}{c} Angiotensin-converting enzyme \\ \end{tabular} & 282 & 16,864 & Zn\({}^{2+}\) \\  & **AKT1** & 3 CQW & Serine/threonine-protein kinase AKT & 293 & 16,426 & Mn\({}^{2+}\) \\  & **ADA17** & 2O10 & protease & 532 & 35,809 & Zn\({}^{2+}\) \\  & **MMP13** & 830C & Matrix metalloproteinase 13 & 572 & 37,126 & Zn\({}^{2+}\) \\  & **PLK1** & 2 OWB & Serine/threonine-protein kinase & 107 & 6797 & Zn\({}^{2+}\) \\  & **CAH2** & 1 BCD & Carbonic anhydrase II & 492 & 31,132 & Zn\({}^{2+}\) \\  & **LKHA4** & 3 CHP & Leukotriene \(A4\) hydrolase & 171 & 9448 & Zn\({}^{2+}\) \\  & **FNTA** & 3\_e37 & protein farnesyltransferase-geganyl & 592 & 51,430 & Zn\({}^{2+}\) \\  & **KIFI1** & 3 CJO & Kinesin-like protein 1 & 116 & 6848 & Mg\({}^{2+}\) \\  & **ADA** & 2E1W & Adenosine deaminase & 93 & 5449 & Zn\({}^{2+}\) \\  & **COMT** & 3 BWM & Catechol O-methyltransferase transferase & 41 & 3848 & Mg\({}^{2+}\) \\  & **NOS1** & 1 QW6 & Nitric-oxide synthase, brain & 100 & 8050 & Zn\({}^{2+}\) \\  & **DEF** & 1 LRU & Peptide deformylase & 102 & 5696 & Zn\({}^{2+}\) \\  & **FPPS** & 1 ZW5 & Farnesyl diphosphate synthase & 85 & 8822 & Mg\({}^{2+}\) \\  & **HDAC2** & 3 MAX & histone deacetylase 2 & 185 & 10,300 & Zn\({}^{2+}\) \\  & **HDAC8** & 3F07 & histone deacetylase 8 & 170 & 10,448 & Zn\({}^{2+}\) \\  & **XIAP** & 3 HL5 & Inhibitor of apoptosis protein 3 & 100 & 5145 & Zn\({}^{2+}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._With the current protocol, the computational time for the virtual screening of the complete DUD-E dataset for Vina was of approximately 60 days in 24 CPUs. Calculations in AutoDock took on average 100 times more. At the end of this stage an optimized docking protocol was selected for each target with each docking program. These protocols were used for the corresponding 101 protein targets to dock the associated ligands and decoys. For each target, ranked lists of ligands and decoys were prepared with AutoDock and Vina, based on the corresponding scores. These lists were used to determine the values of AUCs, EF1% and EF20%, allowing a comparison of the performance of the two docking programs  
Figure 2: Comparison between the crystallographic (green) and “docked” (purple) poses of (a) glucocorticoid receptor (GCR) Autodock, (**a1**) GCR Vina, (**b**) CAH2 AutoDock, (**b1**) CAH2 Vina, (**c**) TYSY AutoDock, and (**c1**) TYSY Vina. in discriminating between ligands and decoys for each target. Average AUC, EF1% and EF20% were determined for the different families of protein targets and for the full 101 targets. All protein targets were characterized in terms of the number of the total amino acid residues and molecular weight. The corresponding binding pockets were evaluated in terms of their percentage of hydrophobic, polar, and charged amino acid residues. Average AUC, EF1% and EF20% were determined for different classes of protein targets based on the protein's size and type of residues at the binding pocket. The Molecular Operating Environment (MOE) [55] program was used to calculate the chemical and structural properties for all ligands tested. Some of these properties were analyzed in more detail. Examples include the ligand's molecular weight, volume, area, fraction of rotatable bonds, fraction of hydrophobic accessible surface area (FASA_H), fraction of polar accessible surface area (FASA_P), and fraction of positive and negative accessible surface areas (FASA+ and FASA\(-\)).