July 25, 2017Download PDF
Clomipramine is a tricyclic antidepressant drug discovered in the middle of the sixties and still in use today in the treatment of various diseases. However, this molecule is responsible for several secondary effects and some of its “off targets” are well described in the literature. Based on the now accepted principle that similar receptors bind similars ligands1, we have developed BioBind a patented comparison algorithm dedicated to the retrieval and assessment of local surface similarities. Clomipramine appears to be a good “real life” candidate to challenge BioBind. In a couple of hours, BioBind was able to retrieve all known targets having structural data described in the literature and to provide a valuable list of unknown yet sensible putative targets currently being experimentally validated. This analysis hence demonstrates the robustness and relevance of BioBind. BioBind is integrated into BioSight*, our fully secured web platform
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Clomipramine is a tricyclic antidepressant drug discovered in the middle of the sixties2 and still in use today in the treatment of various diseases despite a large panel of side effects. Clomipramine constitutes an excellent test case to evaluate the efficacy and reliability of BioBind3, a BIONEXT’s algorithm, especially because of (i) the existence of a fair amount of known targets providing a reasonable number of controls, (ii) new targets remain to be found4 and the large bibliography generated throughout the years offers relevant means for a critical analysis of predictions. Altogether, the present test case is as close as possible to a real life application.
Despite an evident pharmaceutical interest for clomipramine, there is still no available crystal structure of a human biological target in complex with this drug in the Protein Data Bank (PDB). Hence, our analysis relied on the existing structure of a bacte- rial mutated biogenic amine transporter (PDB code 4MMA) whose mutation in the clomipramine pocket is believed to allow it to mimic observed behaviours in human homologous proteins otherwise absent in wild-type strains3. To date, crystal structures exist for only four clomipramine targets: muscarinic acetylcholine receptors mAChr2 and mAChr3, dopaminergic receptor D3 and histaminergic receptor H1. The analysis was performed using BioBind, a comparison algorithm dedicated to the retrieval and assessment of local surface similarities. Surfaces are encoded at the level of atoms using models borrowed to the alpha-shape theory, which allows for a straightforward definition of surface fragments, as well as to compute and map geometric and polar interaction properties on surface atoms. Using as inputs a query region at the surface of a query macromolecule and a databank of full macromolecule surfaces used as putative targets, the goal of the algorithm is to detect regions on the target sharing some similarity with the query, score the similarity and provide a 3D alignment of these target regions. In order to demonstrate the strength and relevance of BIONEXT’s algorithm, the generated results were compared to those of a similar analysis using ProBis, a reference software for the detection of structurally similar binding sites5.
Using as query the structure of the bacterial amine transporter (PDB code 4MMA), the structure of the muscarinic acetylcholine receptor mAChr2 (PDB code 4MQT, chain A), a neurotransmitter receptor known to bind clomipramine6, was among the first ranked predictions. Despite the clear dissimilarity in the global fold of the two proteins as can be seen in Fig.1, the two pockets shown in Fig.2 are highly similar. Notably, a striking superimposition is observed between the carboxylic groups that are involved in the binding of the ligand in the two structures. Interestingly, the two positively charged interacting nitrogens in both ligands are perfectly aligned as well.
BioBind sorts from the most to the less similar all structures included in the structural database. Applied to clomipramine with PDB code 4MQT as query, one could retrieve known targets on the first ranks, listed in the following table:
- Reference targets, such as the muscarinic acetylcholine receptor mAChr3, histaminergic receptor H1 and dopa- minergic receptor D3.
- Targets sharing endogenous ligands with the reference targets, such as human acetylcholinesterase, and Beta-2 adrenergic receptor (Alpha type is not crystallized).
A more careful study of the other predictions reveals putative clomipramine binders with various levels of confidence evaluated through conscientious bibliographic analysis and inspection of output alignments. These undisclosed targets are currently being experimentally verified by experts under NDA.
BioBind, a BIONEXT’s patented algorithm, is able to help anyone identify secondary interactions, provided known structural data availability.
BioBind, based on the alpha-shape surface representation combined to the physicochemical properties of the atoms, compares a local pattern to a reference provided by the user. Applied to clomipramine, BioBind was able not only to spot the correct pocket in the known secondary target mAChr2 receptor, but also to provide an alignment consistent with the interaction mode of the ligands in both structures. Moreover, our approach successfully retrieved all known targets having structural data described in the literature and provided a valuable list of unknown yet sensible putative and experimentally validated targets in a couple of hours.
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- Zohar, Joseph (2012). Obsessive-compulsive disorder current science and clinical practice. Chichester, West Sussex, UK: Wiley-Blackwell. p. 32. ISBN 9781118308011. [return]
- Bionext SA, 2010. Method for Characterising Three-Dimensional Objects. WO2011009965A1. [return]
- Wang, H. et al. (2013) Structural basis for action by diverse antidepressants on biogenic amine transporters. Nature 503(7474):141-145. [return]
- Konc, J., & Janežic, D. (2010). ProBiS: a web server for detection of structurally similar protein binding sites. Nucleic Acids Research, 38 (Web Server issue), W436–W440. [return]
- Kruse, A. C., & Al. (2013). Activation and allosteric modulation of a muscarinic acetylcholine receptor. Nature, 504(7478), 101–106. [return]