Pipeline of the binding site similarity analysis.

<p>Starting from 543 drugs, we identify 164 promiscuous drugs, each binding to three or more non-redundant targets (712 in total). The binding site alignment with SMAP is performed for all 2284 structures (i.e. the redundant targets). Subsequently, target pairs are clustered by 95% sequence identity – giving 712 non-redundant targets – and ranked with LigandRMSD.</p

The 10 drugs with the most similar binding sites.

<p>For each entry, the minimum, lower () and upper quartile (), the median (), average () and maximum sequence identity (among pairs with similar binding sites) is given. NANA stands for 2-deoxy-2,3-de-hydro-N-acetyl-neuraminic acid.</p

The 10 most promiscuous drugs.

<p>NANA stands for 2-deoxy-2,3-dehydro-N-acetylneuraminic acid.</p

Target similarity.

<p>The heatmaps for the targets of methotrexate (A), acarbose (B) and quercetin (C) show that the target sequences are dissimilar (left), the global structural similarity (middle) is comparable to the sequence identity and the binding sites are overall more similar (right). (<b>A</b>) Two DHFR (1dg5, 3dl6) with a conserved 3D structure and similar binding sites for methotrexate are highlighted. (<b>B</b>) Although the proteins 4--glucanotransferase (1k1x) and glucoamylase (2f6d) have globally distinct sequences and structures, they bind acarbose in a very similar way. (<b>C</b>) The two protein kinases PI3KCG (3lj3) and PIM1 (3ma3) share a similar binding pocket for quercetin.</p

Drug promiscuity: Ligand flexibility vs. binding site similarity.

<p>(<b>A</b>) A flexible ligand, tretinoin (on the left), with two distinct conformations is able to bind to very different binding sites. (<b>B</b>) The drug BVDU (orange) binding to a viral thymidine kinase (green, 1osn) and a human heat shock protein (blue, homology model <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065894#pone.0065894-Heinrich1" target="_blank">[32]</a>). The two targets share a similar binding site, which allows the promiscuous binding of the drug in the same conformation.</p

Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key

<div><p>Drug repositioning applies established drugs to new disease indications with increasing success. A pre-requisite for drug repurposing is drug promiscuity (polypharmacology) – a drug’s ability to bind to several targets. There is a long standing debate on the reasons for drug promiscuity. Based on large compound screens, hydrophobicity and molecular weight have been suggested as key reasons. However, the results are sometimes contradictory and leave space for further analysis. Protein structures offer a structural dimension to explain promiscuity: Can a drug bind multiple targets because the drug is flexible or because the targets are structurally similar or even share similar binding sites? We present a systematic study of drug promiscuity based on structural data of PDB target proteins with a set of 164 promiscuous drugs. We show that there is no correlation between the degree of promiscuity and ligand properties such as hydrophobicity or molecular weight but a weak correlation to conformational flexibility. However, we do find a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets. In particular, 71% of the drugs have at least two targets with similar binding sites. In order to overcome issues in detection of remotely similar binding sites, we employed a score for binding site similarity: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary structural binding site alignments. Three representative examples, namely the anti-cancer drug methotrexate, the natural product quercetin and the anti-diabetic drug acarbose are discussed in detail. Our findings suggest that global structural and binding site similarity play a more important role to explain the observed drug promiscuity in the PDB than physicochemical drug properties like hydrophobicity or molecular weight. Additionally, we find ligand flexibility to have a minor influence.</p></div

The most flexible drugs.

<p>Drugs with ≥4 conformer clusters. For each drug, the total number of clusters (i.e. the number of conformers in all PDB structures) and the minimum/maximum/average number of cluster members (i.e. similar conformers of one drug) in such a cluster is given.</p

Structural details of binding site similar targets.

<p>The binding site alignments for the targets of (<b>A</b>) methotrexate, (<b>B</b>) acarbose and (<b>C</b>) quercetin (highlighted in blue in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065894#pone-0065894-g007" target="_blank">Figure 7</a>) are visualized. Binding sites are highlighted in red and ligands are displayed in orange. PDB IDs are given below the structures. If the given ID is a representative of a cluster, the PDB ID of the underlying structures is given in parentheses.</p

Conformer count of promiscuous drugs in the PDB.

<p>Conformer count of promiscuous drugs in the PDB.</p

Comparison of the SMAP P-Value to LigandRMSD.

<p>A P-Value of gives a significant binding site alignment. The LigandRMSD gives the conformational similarity between the bound ligands and is ≤3 Å for similar binding sites. The thresholds are displayed as solid lines in the plot. In total, 3948 non-redundant target pairs were compared.</p