Drug repositioning applies existing drugs to new disease indications. A prerequisite for drug repurposing is drug promiscuity - a drug's ability to bind to several targets, possibly leading to side effects on the other hand. One reason for drug promiscuity is binding site similarity between (otherwise unrelated) proteins. In this thesis, a new algorithm for remote binding site similarity assessment and its application to the whole of the Protein Data Bank (PDB) is presented, forming the base for off-target identification and drug repositioning. The present thesis contributes to a long-standing debate on the reasons for drug promiscuity, being one of the pioneer studies investigating these from a protein structural point of view. Except for a small influence of flexibility, the analysis of all promiscuous drugs in the PDB revealed that drug properties are of minor importance. However, a strong correlation between promiscuity and binding site similarity of protein targets is found (r = 0.81), suggesting binding site similarity as the main reason for drug promiscuity. For 71 % of the promiscuous drugs at least one pair of their targets' binding sites is similar and for 18 % all are similar. In order to overcome issues in detection of remotely similar binding sites, a score for binding site similarity is developed: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary binding site alignments and also works on distinct ligands on a structural proteome scale. To answer the question on which other targets might be hit when targeting a particular protein, an all-to-all binding site alignment of 32,202 protein structures is analyzed. Of the hundreds of million possible protein pairs, 0.27 % were found to have similar binding sites. Extrapolating to the human proteome, for one human protein are 54 proteins with a similar binding site expected on average. Clearly, this is in contrast to the one drug-one target paradigm in drug development. Based on these data, disadvantageous off-targets can be uncovered and drug-repositioning candidates inferred. The enormous potential is demonstrated with the example of Viagra, proposing it for repositioning to Alzheimer's disease and prostate cancer. The findings in this thesis question the established single-target dogma in drug discovery. Drugs are triggered to modulate multiple targets simultaneously by the widespread binding site similarity. With the presented pipeline, drug targets can be reliably predicted: Starting from a target protein, additional targets are predicted based on binding site similarity and prioritized according to the resulting ligand structural overlap. Identifying drug targets helps to understand severe side effects and opens the door for drug repositioning.

Drug repositioning applies existing drugs to new disease indications. A prerequisite for drug repurposing is drug promiscuity - a drug's ability to bind to several targets, possibly leading to side effects on the other hand. One reason for drug promiscuity is binding site similarity between (otherwise unrelated) proteins. In this thesis, a new algorithm for remote binding site similarity assessment and its application to the whole of the Protein Data Bank (PDB) is presented, forming the base for off-target identification and drug repositioning. The present thesis contributes to a long-standing debate on the reasons for drug promiscuity, being one of the pioneer studies investigating these from a protein structural point of view. Except for a small influence of flexibility, the analysis of all promiscuous drugs in the PDB revealed that drug properties are of minor importance. However, a strong correlation between promiscuity and binding site similarity of protein targets is found (r = 0.81), suggesting binding site similarity as the main reason for drug promiscuity. For 71 % of the promiscuous drugs at least one pair of their targets' binding sites is similar and for 18 % all are similar. In order to overcome issues in detection of remotely similar binding sites, a score for binding site similarity is developed: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary binding site alignments and also works on distinct ligands on a structural proteome scale. To answer the question on which other targets might be hit when targeting a particular protein, an all-to-all binding site alignment of 32,202 protein structures is analyzed. Of the hundreds of million possible protein pairs, 0.27 % were found to have similar binding sites. Extrapolating to the human proteome, for one human protein are 54 proteins with a similar binding site expected on average. Clearly, this is in contrast to the one drug-one target paradigm in drug development. Based on these data, disadvantageous off-targets can be uncovered and drug-repositioning candidates inferred. The enormous potential is demonstrated with the example of Viagra, proposing it for repositioning to Alzheimer's disease and prostate cancer. The findings in this thesis question the established single-target dogma in drug discovery. Drugs are triggered to modulate multiple targets simultaneously by the widespread binding site similarity. With the presented pipeline, drug targets can be reliably predicted: Starting from a target protein, additional targets are predicted based on binding site similarity and prioritized according to the resulting ligand structural overlap. Identifying drug targets helps to understand severe side effects and opens the door for drug repositioning.

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Im Rahmen der vorliegenden Dissertation wurden Enzyme des Oxylipinstoffwechsels in P. patens funktionell und strukturell charakterisiert. Dafür wurden die bifunktionelle PpLOX1 und zwei AOCs (PpAOC1 und PpAOC2) ausgewählt. Mittels verschiedener biochemischer, bioinformatischer und biophysikalischer Methoden wurden diese Enzyme bezüglich Funktion, Aktivität und Struktur charakterisiert. Desweiteren wurden nach erfolgreicher Kristallisation von PpAOC1 und PpAOC2 die hochaufgelösten Röntgenkristallstrukturen beider Enzyme im Grundzustand sowie im Komplex mit Substratanalogen gelöst. Für PpAOC2 wurden dabei zwei verschiedene Bindemodi des Liganden beobachtet. Der Einfluß der Aminosäurereste Arg-345, Arg-638 und Tyr-851 auf den Reaktionsmechanismus von PpLOX1 wurde durch zielgerichtete Mutagenese und nachfolgende Analyse der Produktbildung durch die erhaltenen Varianten untersucht. Es wurden keine signifikanten Unterschiede bei der Umsetzung verschiedener Fettsäuren durch das Ausgangsenzym oder die Varianten R345L bzw. R638L gefunden. Dagegen zeigte die Doppelvariante R345L/R638L eine stark verringerte Menge an gebildeten Produkten. Demnach scheint zumindest das Vorliegen einer dieser beiden positiv geladenen Reste wichtig für die Umsetzung der Substrate zu sein. Möglicherweise wird die negativ geladene Carboxylatgruppe der jeweiligen Fettsäure durch elektrostatische Wechselwirkungen über Arg-345 oder Arg-638 gebunden. Die Variante Y851I bildete geringere Mengen von 12-ODTE, Keto-Fettsäuren und auch weniger Produkt als das Ausgangsenzym. Demnach scheint auch dieser Rest an der Katalyse beteiligt zu sein. Da aber für die Variante Y851F sogar ein erhöhter Anteil an 12-ODTE gefunden wurde, scheint der voluminöse und hydrophobe aromatische Ring, und nicht die Hydroxyl-Gruppe des Tyrosin, wichtig zu sein. Die gereinigten Enzyme PpAOC1 und PpAOC2 wurden für Aktivitätstest mit verschiedenen C20-Fettsäure-Hydroperoxiden verwendet. Beide Enzyme zeigten Aktivität gegenüber den 15-Hydroperoxiden von EPA und ETA, jedoch nicht von AA. Darüber hinaus besitzt PpAOC2, aber nicht PpAOC1, Aktivität für die 12-Hydroperoxide welche sich von AA, EPA und DGLA ableiten. Es wurden zusätzlich zu 11-OPTA bislang nicht beschriebene zyklische Verbindungen gebildet, deren chemische Struktur durch Fragmentierung mittels ESI-MS/MS aufgeklärt wurde. In den vorliegenden Studien zu PpAOC1 und PpAOC2 wurde das Glutamat an Position 18 jeweils durch Glutamin oder Aspartat ausgetauscht. Es wurde gezeigt, dass der konservierte Glutamatrest und seine negative Carboxylatgruppe in beiden Enzymen essenziell für die Katalyse ist. Dagegen wurde für die Variante R22L lediglich ein Einfluß auf die Aktivität in PpAOC2 gefunden. Im aktiven Zentrum von PpAOC1 werden zwei Wassermoleküle von vier Aminosäureresten koordiniert, während in PpAOC2 ein Wassermolekül von zwei Aminosäureresten gebunden ist. Inwiefern diese Wassermoleküle an der Katalyse beteiligt sind, konnte bisher nicht eindeutig geklärt werden.