A New Strategy for Multitarget Drug Discovery/Repositioning Through the Identification of Similar 3D Amino Acid Patterns Among Proteins Structures: The Case of Tafluprost and its Effects on Cardiac Ion Channels

The identification of similar three-dimensional (3D) amino acid patterns among different proteins might be helpful to explain the polypharmacological profile of many currently used drugs. Also, it would be a reasonable first step for the design of novel multitarget compounds. Most of the current computational tools employed for this aim are limited to the comparisons among known binding sites, and do not consider several additional important 3D patterns such as allosteric sites or other conserved motifs. In the present work, we introduce Geomfinder2.0, which is a new and improved version of our previously described algorithm for the deep exploration and discovery of similar and druggable 3D patterns. As compared with the original version, substantial improvements that have been incorporated to our software allow: (i) to compare quaternary structures, (ii) to deal with a list of pairs of structures, (iii) to know how druggable is the zone where similar 3D patterns are detected and (iv) to significantly reduce the execution time. Thus, the new algorithm achieves up to 353x speedup as compared to the previous sequential version, allowing the exploration of a significant number of quaternary structures in a reasonable time. In order to illustrate the potential of the updated Geomfinder version, we show a case of use in which similar 3D patterns were detected in the cardiac ions channels NaV1.5 and TASK-1. These channels are quite different in terms of structure, sequence and function and both have been regarded as important targets for drugs aimed at treating atrial fibrillation. Finally, we describe the in vitro effects of tafluprost (a drug currently used to treat glaucoma, which was identified as a novel putative ligand of NaV1.5 and TASK-1) upon both ion channels’ activity and discuss its possible repositioning as a novel antiarrhythmic drug.

LigRMSD: a web server for automatic structure matching and RMSD calculations among identical and similar compounds in protein-ligand docking

MOTIVATION

Root mean square deviation (RMSD) is one of the most useful and straightforward features for structural comparison between different conformations of the same molecule. Commonly, protein-ligand docking programs have included some utilities that allow the calculation of this value; however, they only work efficiently when exists a complete atom label equivalence between the evaluated conformations.

RESULTS

We present LigRMSD, a free web-server for the automatic matching and RMSD calculations among identical or similar chemical compounds. This server allows the user to submit only a pair of identical or similar molecules or dataset of similar compounds to compare their three-dimensional conformations.

AVAILABILITY AND IMPLEMENTATION

LigRMSD can be freely accessed at https://ligrmsd.appsbio.utalca.cl.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Synthesis of Novel Nicotinic Ligands with Multimodal Action: Targeting Acetylcholine α4β2, Dopamine and Serotonin Transporters

Nicotinic acetylcholine receptors (nAChRs), serotonin transporters (SERT) and dopamine transporters (DAT) represent targets for the development of novel nicotinic derivatives acting as multiligands associated with different health conditions, such as depressive, anxiety and addiction disorders. In the present work, a series of functionalized esters structurally related to acetylcholine and nicotine were synthesized and pharmacologically assayed with respect to these targets. The synthesized compounds were studied in radioligand binding assays at α4β2 nAChR, h-SERT and h-DAT. SERT experiments showed not radioligand [³H]-paroxetine displacement, but rather an increase in the radioligand binding percentage at the central binding site was observed. Compound 20 showed K_i values of 1.008 ± 0.230 μM for h-DAT and 0.031 ± 0.006 μM for α4β2 nAChR, and [³H]-paroxetine binding of 191.50% in h-SERT displacement studies, being the only compound displaying triple affinity. Compound 21 displayed K_i values of 0.113 ± 0.037 μM for α4β2 nAChR and 0.075 ± 0.009 μM for h-DAT acting as a dual ligand. Molecular docking studies on homology models of α4β2 nAChR, h-DAT and h-SERT suggested potential interactions among the compounds and agonist binding site at the α4/β2 subunit interfaces of α4β2 nAChR, central binding site of h-DAT and allosteric modulator effect in h-SERT.

3D similarities between the binding sites of monoaminergic target proteins

The study of binding site similarities can be relevant to understand the interaction of different drugs at several molecular targets. The increasing availability of protein crystal structures and the development of novel algorithms designed to evaluate three-dimensional similarities, represent a great opportunity to explore the existence of electronic and shape features shared by clinically relevant proteins, which could assist drug design and discovery. Proteins involved in the recognition of monoaminergic neurotransmitters, such as monoamine transporters or monoamine oxidases (MAO) have been related to several psychiatric and neurological disorders such as depression or Parkinson’s disease. In this work, we evaluated the possible existence of similarities among the binding sites of the serotonin transporter (SERT), the dopamine transporter (DAT), MAO-A and MAO-B. This study was carried out using molecular simulation methodologies linked to the statistical algorithm PocketMatch, which was modified in order to obtain similarities profiles. Our results show that DAT and SERT exhibit a high degree of 3-D similarities all along the pathway that is presumably involved in the substrate transport process. Distinct differences, on the other hand, were found both at the extracellular and the intracellular ends of the transporters, which might be involved in the selective initial recognition of the corresponding substrate. Similarities were also found between the active (catalytic) site of MAO-A and the extracellular vestibule of SERT (the S2 binding site). These results suggest some degree of structural convergence for these proteins, which have different functions, tissue distribution and genetic origin, but which share the same endogenous ligand (serotonin). Beyond the functional implications, these findings are valuable for the design of both selective and non-selective ligands.

Geomfinder: a multi-feature identifier of similar three-dimensional protein patterns: a ligand-independent approach

Background

Since the structure of proteins is more conserved than the sequence, the identification of conserved three-dimensional (3D) patterns among a set of proteins, can be important for protein function prediction, protein clustering, drug discovery and the establishment of evolutionary relationships. Thus, several computational applications to identify, describe and compare 3D patterns (or motifs) have been developed. Often, these tools consider a 3D pattern as that described by the residues surrounding co-crystallized/docked ligands available from X-ray crystal structures or homology models. Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc. This makes necessary the development of new ligand-independent methods to search and compare 3D patterns in all available protein structures.

Results

Here we introduce Geomfinder, an intuitive, flexible, alignment-free and ligand-independent web server for detailed estimation of similarities between all pairs of 3D patterns detected in any two given protein structures. We used around 1100 protein structures to form pairs of proteins which were assessed with Geomfinder. In these analyses each protein was considered in only one pair (e.g. in a subset of 100 different proteins, 50 pairs of proteins can be defined). Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility of Geomfinder, which was able to discriminate between similar and different 3D patterns related to binding sites of common substrates in a range of diverse proteins.

Conclusions

Geomfinder allows detecting similar 3D patterns between any two pair of protein structures, regardless of the divergency among their amino acids sequences. Although the software is not intended for simultaneous multiple comparisons in a large number of proteins, it can be particularly useful in cases such as the structure-based design of multitarget drugs, where a detailed analysis of 3D patterns similarities between a few selected protein targets is essential.

Electronic supplementary material

The online version of this article (doi:10.1186/s13321-016-0131-9) contains supplementary material, which is available to authorized users.