diff --git a/drug-target/global.R b/drug-target/global.R
index 076c508..a0c997c 100644
--- a/drug-target/global.R
+++ b/drug-target/global.R
@@ -818,8 +818,8 @@ if (interactive()){
         ### NGLViewer ####
         # Structure Viewer WebGL/NGLViewR window
         output$structure <- renderNGLVieweR({
-          #ngl_gene=isolate(input$switch_target)
-          ngl_gene=input$switch_target
+          ngl_gene=isolate(input$switch_target)
+          # ngl_gene=input$switch_target
           ngl_drug=target_map[[ngl_gene]]
           ngl_pdb_file=paste0(load_dir, "Data/", ngl_drug, '/output/depth/', ngl_gene, '_complex.pdb')
           print(ngl_pdb_file)
diff --git a/ml/global.R b/ml/global.R
index ba92a9d..7a2c5a3 100644
--- a/ml/global.R
+++ b/ml/global.R
@@ -147,22 +147,22 @@ makeplot = function(x, # the DataFrame to plot
     y_coord_min = 0
   }
   if (display_infobox) {
-    metadata=t(plot_data[1,colnames(plot_data)[colnames(plot_data) %in% metadata_cols]])
+    metadata=plot_data[1,colnames(plot_data)[colnames(plot_data) %in% metadata_cols]]
     if (display_combined){
       metatext=paste0("Train/Test: ",
-                      metadata[1], "/", metadata[2],
-                      "\nTrain/Test Target Ratio: ", metadata[3], "/", metadata[4],
-                      "\nResampling: ", metadata[5],
-                      "\nFeatures: ", metadata[6],
+                      metadata$n_training_size, "/", metadata$n_test_size,
+                      "\nTrain/Test Target Ratio: ", metadata$n_trainingY_ratio, "/", metadata$n_testY_ratio,
+                      "\nResampling: ", metadata$resampling,
+                      "\nFeatures: ", metadata$n_features,
                       "\nGenes Trained: ", combined_training_genes,
                       "\nTest Gene: ", gene
       )
     } else {
       metatext=paste0("Train/Test: ",
-                      metadata[1], "/", metadata[2],
-                      "\nTrain/Test Target Ratio: ", metadata[3], "/", metadata[4],
-                      "\nResampling: ", metadata[5],
-                      "\nFeatures: ", metadata[6],
+                      metadata$n_training_size, "/", metadata$n_test_size,
+                      "\nTrain/Test Target Ratio: ", metadata$n_trainingY_ratio, "/", metadata$n_testY_ratio,
+                      "\nResampling: ", metadata$resampling,
+                      "\nFeatures: ", metadata$n_features,
                       "\nTest Gene: ", gene
       )
     }
@@ -171,7 +171,7 @@ makeplot = function(x, # the DataFrame to plot
     
     grob <- grobTree(textGrob(metatext,
                               x=0.01,
-                              y=0.90,
+                              y=0.80,
                               hjust=0,
                               gp=gpar(col="black")
     )
@@ -192,12 +192,12 @@ makeplot = function(x, # the DataFrame to plot
     ) +
     coord_cartesian(ylim = c(y_coord_min, 1)) +
     annotation_custom(grob) +
-    geom_label(aes_string(label=selection),
-               position=position_dodge(width = -0.75),
-               #vjust = 1.5,
-               alpha=0.75,
-               fill="white"
-               
+    geom_text(aes_string(label=selection),
+              position=position_dodge(width = -0.75),
+              vjust = -0.5,
+              alpha=0.75,
+              fill="white"
+              
     ) +
     scale_color_manual(values = colour_range) +
     scale_fill_manual(values = colour_range) +