A Combined Ligand- and Structure-Based Virtual Screening To Identify Novel NaV1.2 Blockers: In Vitro Patch Clamp Validation and In Vivo Anticonvulsant Activity.

Epilepsy is a neurological disorder characterized by recurrent seizures that arise from abnormal electrical activity in the brain. Voltage-gated sodium channels (NaVs), responsible for the initiation and propagation of action potentials in neurons, play a critical role in the pathogenesis of epilepsy. This study sought to discover potential anticonvulsant compounds that interact with NaVs, specifically, the brain subtype hNaV1.2. A ligand-based QSAR model and a docking model were constructed, validated, and applied in a parallel virtual screening over the DrugBank database. Montelukast, Novobiocin, and Cinnarizine were selected for in vitro testing, using the patch-clamp technique, and all of them proved to inhibit hNaV1.2 channels heterologously expressed in HEK293 cells. Two hits were evaluated in the GASH/Sal model of audiogenic seizures and demonstrated promising activity, reducing the severity of sound-induced seizures at the doses tested. The combination of ligand- and structure-based models presents a valuable approach for identifying potential NaV inhibitors. These findings may provide a basis for further research into the development of new antiseizure drugs for the treatment of epilepsy.

A combined ligand and target-based virtual screening strategy to repurpose drugs as putrescine uptake inhibitors with trypanocidal activity.

Chagas disease, also known as American trypanosomiasis, is a neglected tropical disease caused by the protozoa Trypanosoma cruzi, affecting nearly 7 million people only in the Americas. Polyamines are essential compounds for parasite growth, survival, and differentiation. However, because trypanosomatids are auxotrophic for polyamines, they must be obtained from the host by specific transporters. In this investigation, an ensemble of QSAR classifiers able to identify polyamine analogs with trypanocidal activity was developed. Then, a multi-template homology model of the dimeric polyamine transporter of T. cruzi, TcPAT12, was created with Rosetta, and then refined by enhanced sampling molecular dynamics simulations. Using representative snapshots extracted from the trajectory, a docking model able to discriminate between active and inactive compounds was developed and validated. Both models were applied in a parallel virtual screening campaign to repurpose known drugs as anti-trypanosomal compounds inhibiting polyamine transport in T. cruzi. Montelukast, Quinestrol, Danazol, and Dutasteride were selected for in vitro testing, and all of them inhibited putrescine uptake in biochemical assays, confirming the predictive ability of the computational models. Furthermore, all the confirmed hits proved to inhibit epimastigote proliferation, and Quinestrol and Danazol were able to inhibit, in the low micromolar range, the viability of trypomastigotes and the intracellular growth of amastigotes.

Triclabendazole and clofazimine reduce replication and spermine uptake in vitro in Toxoplasma gondii.

Toxoplasmosis is a worldwide zoonosis caused by the protozoan parasite Toxoplasma gondii. Although this infection is generally asymptomatic in immunocompetent individuals, it can cause serious clinical manifestations in newborns with congenital infection or in immunocompromised patients. As current treatments are not always well tolerated, there is an urgent need to find new drugs against human toxoplasmosis. Drug repurposing has gained considerable momentum in the last decade and is a particularly attractive approach for the search of therapeutic alternatives to treat rare and neglected diseases. Thus, in this study, we investigated the antiproliferative effect of several repurposed drugs. Of these, clofazimine and triclabendazole displayed a higher selectivity against T. gondii, affecting its replication. Furthermore, both compounds inhibited spermine incorporation into the parasite, which is necessary for the formation of other polyamines. The data reported here indicate that clofazimine and triclabendazole could be used for the treatment of human toxoplasmosis and confirms that drug repurposing is an excellent strategy to find new therapeutic targets of intervention.

iRaPCA and SOMoC: Development and Validation of Web Applications for New Approaches for the Clustering of Small Molecules.

The clustering of small molecules implies the organization of a group of chemical structures into smaller subgroups with similar features. Clustering has important applications to sample chemical datasets or libraries in a representative manner (e.g., to choose, from a virtual screening hit list, a chemically diverse subset of compounds to be submitted to experimental confirmation, or to split datasets into representative training and validation sets when implementing machine learning models). Most strategies for clustering molecules are based on molecular fingerprints and hierarchical clustering algorithms. Here, two open-source in-house methodologies for clustering of small molecules are presented: iterative Random subspace Principal Component Analysis clustering (iRaPCA), an iterative approach based on feature bagging, dimensionality reduction, and K-means optimization; and Silhouette Optimized Molecular Clustering (SOMoC), which combines molecular fingerprints with the Uniform Manifold Approximation and Projection (UMAP) and Gaussian Mixture Model algorithm (GMM). In a benchmarking exercise, the performance of both clustering methods has been examined across 29 datasets containing between 100 and 5000 small molecules, comparing these results with those given by two other well-known clustering methods, Ward and Butina. iRaPCA and SOMoC consistently showed the best performance across these 29 datasets, both in terms of within-cluster and between-cluster distances. Both iRaPCA and SOMoC have been implemented as free Web Apps and standalone applications, to allow their use to a wide audience within the scientific community.

Structure-Based Virtual Screening Identifies Novobiocin, Montelukast, and Cinnarizine as TRPV1 Modulators with Anticonvulsant Activity In Vivo.

The transient receptor potential vanilloid 1 (TRPV1) receptor is a nonselective cation channel, known to be involved in the regulation of many important physiological and pathological processes. In the last few years, it has been proposed as a promising target to develop novel anticonvulsant compounds. However, thermoregulatory effects associated with the channel inhibition have hampered the path for TRPV1 antagonists to become marketed drugs. In this regard, we conducted a structure-based virtual screening campaign to find potential TRPV1 modulators among approved drugs, which are known to be safe and thermally neutral. To this end, different docking models were developed and validated by assessing their pose and score prediction powers. Novobiocin, montelukast, and cinnarizine were selected from the screening as promising candidates for experimental testing and all of them exhibited nanomolar inhibitory activity. Moreover, the in vivo profiles showed promising results in at least one of the three models of seizures tested.

Tetracycline Derivatives Inhibit Plasmodial Cysteine Protease Falcipain-2 through Binding to a Distal Allosteric Site.

Allosteric inhibitors regulate enzyme activity from remote and usually specific pockets. As they promise an avenue for less toxic and safer drugs, the identification and characterization of allosteric inhibitors has gained great academic and biomedical interest in recent years. Research on falcipain-2 (FP-2), the major papain-like cysteine hemoglobinase of Plasmodium falciparum, might benefit from this strategy to overcome the low selectivity against human cathepsins shown by active site-directed inhibitors. Encouraged by our previous finding that methacycline inhibits FP-2 noncompetitively, here we assessed other five tetracycline derivatives against this target and characterized their inhibition mechanism. As previously shown for methacycline, tetracycline derivatives inhibited FP-2 in a noncompetitive fashion, with Ki values ranging from 121 to 190 µM. A possible binding to the S' side of the FP-2 active site, similar to that described by X-ray crystallography (PDB: 6SSZ) for the noncompetitive inhibitor E-chalcone 48 (EC48), was experimentally discarded by kinetic analysis using a large peptidyl substrate spanning the whole active site. By combining lengthy molecular dynamics (MD) simulations that allowed methacycline to diffuse from solution to different FP-2 surface regions and free energy calculations, we predicted the most likely binding mode of the ligand. Of note, the proposed binding pose explains the low differences in Ki values observed for the tested tetracycline derivatives and the calculated binding free energies match the experimental values. Overall, this study has implications for the design of novel allosteric inhibitors against FP-2 and sets the basis for further optimization of the tetracycline scaffold to produce more potent and selective inhibitors.

Identification of New Carbonic Anhydrase VII Inhibitors by Structure-Based Virtual Screening.

Human carbonic anhydrase VII (hCA VII) constitutes a promising molecular target for the treatment of epileptic seizures and other central nervous system disorders due to its almost exclusive expression in neurons. Achieving isoform selectivity is one of the main challenges for the discovery of new hCA inhibitors, since nonspecific inhibition may lead to tolerance and side effects. In the present work, we report the development of a molecular docking protocol based on AutoDock4Zn for the search of new hCA VII inhibitors by virtual screening. The docking protocol was applied to the screening of two sets of compounds: a ZINC15 subset of sulfur-containing structures and an in-house library consisting of synthetic and commercial candidates (including approved drugs). Five compounds were selected from the first screening campaign and three from the second one, and they were tested in vitro against the enzyme. Among the eight selected structures, four showed Ki values in the low nanomolar range. These confirmed hits include three approved drugs: meloxicam, piroxicam, and nitrofurantoin, which also showed good selectivity for hCA VII versus hCA II.

Homology Modeling and Molecular Dynamics Simulations of Trypanosoma cruzi Phosphodiesterase b1.

Cyclic nucleotide phosphodiesterases have been implicated in the proliferation, differentiation and osmotic regulation of trypanosomatids; in some trypanosomatid species, they have been validated as molecular targets for the development of new therapeutic agents. Because the experimental structure of Trypanosoma cruzi PDEb1 (TcrPDEb1) has not been solved so far, an homology model of the target was created using the structure of Trypanosoma brucei PDEb1 (TbrPDEb1) as a template. The model was refined by extensive enhanced sampling molecular dynamics simulations, and representative snapshots were extracted from the trajectory by combined clustering analysis. This structural ensemble was used to develop a structure-based docking model of the target. The docking accuracy of the model was validated by redocking and cross-docking experiments using all available crystal structures of TbrPDEb1, whereas the scoring accuracy was validated through a retrospective screen, using a carefully curated dataset of compounds assayed against TbrPDEb1 and/or TcrPDEb1. Considering the results from in silico validations, the model may be applied in prospective virtual screening campaigns to identify novel hits, as well as to guide the rational design of potent and selective inhibitors targeting this enzyme.

Strengths and Weaknesses of Docking Simulations in the SARS-CoV-2 Era: the Main Protease (Mpro) Case Study.

The scientific community is working against the clock to arrive at therapeutic interventions to treat patients with COVID-19. Among the strategies for drug discovery, virtual screening approaches have the capacity to search potential hits within millions of chemical structures in days, with the appropriate computing infrastructure. In this article, we first analyzed the published research targeting the inhibition of the main protease (Mpro), one of the most studied targets of SARS-CoV-2, by docking-based methods. An alarming finding was the lack of an adequate validation of the docking protocols (i.e., pose prediction and virtual screening accuracy) before applying them in virtual screening campaigns. The performance of the docking protocols was tested at some level in 57.7% of the 168 investigations analyzed. However, we found only three examples of a complete retrospective analysis of the scoring functions to quantify the virtual screening accuracy of the methods. Moreover, only two publications reported some experimental evaluation of the proposed hits until preparing this manuscript. All of these findings led us to carry out a retrospective performance validation of three different docking protocols, through the analysis of their pose prediction and screening accuracy. Surprisingly, we found that even though all tested docking protocols have a good pose prediction, their screening accuracy is quite limited as they fail to correctly rank a test set of compounds. These results highlight the importance of conducting an adequate validation of the docking protocols before carrying out virtual screening campaigns, and to experimentally confirm the predictions made by the models before drawing bold conclusions. Finally, successful structure-based drug discovery investigations published during the redaction of this manuscript allow us to propose the inclusion of target flexibility and consensus scoring as alternatives to improve the accuracy of the methods.

New anticonvulsant candidates prevent P-glycoprotein (P-gp) overexpression in a pharmacoresistant seizure model in mice.

Despite the approval of a considerable number of last generation antiepileptic drugs (AEDs) (only in the last decade, six drugs have gained Food and Drug Administration approval), the global figures of seizure control have seemingly not improved, and available AED can still be regarded as symptomatic treatments. Fresh thinking in AEDs drug discovery, including the development of drugs with novel mechanisms of action, is required to achieve truly innovative antiepileptic medications. The transporter hypothesis proposes that inadequate penetration of AEDs across the blood-brain barrier, caused by increased expression of efflux transporters such as P-glycoprotein (P-gp), contributes to drug-resistant epilepsy. Neuroinflammation due to high levels of glutamate has been identified as one of the causes of P-gp upregulation, and several studies in animal models of epilepsy suggest that antiinflammatory drugs might prevent P-gp overexpression and, thus, avoid the development of refractory epilepsy. We have applied ligand-based in silico screening to select compounds that exert dual anticonvulsant and antiinflammatory effects. Five of the hits were tested in animal models of seizure, with protective effects. Later, two of them (sebacic acid (SA) and gamma-decanolactone) were submitted to the recently described MP23 model of drug-resistant seizures. All in all, SA displayed the best profile, showing activity in the maximal electroshock seizure (MES) and pentylenetetrazol (PTZ) seizure models, and reversing resistance to phenytoin (PHT) and decreasing the P-gp upregulation in the MP23 model. Furthermore, pretreatment with SA in the pilocarpine status epilepticus (SE) model resulted in decreased histamine release in comparison with nontreated animals. This is the first report of the use of the MP23 model to screen for novel anticonvulsant compounds that may avoid the development of P-gp-related drug resistance.

Ensemble learning application to discover new trypanothione synthetase inhibitors.

Trypanosomatid-caused diseases are among the neglected infectious diseases with the highest disease burden, affecting about 27 million people worldwide and, in particular, socio-economically vulnerable populations. Trypanothione synthetase (TryS) is considered one of the most attractive drug targets within the thiol-polyamine metabolism of typanosomatids, being unique, essential and druggable. Here, we have compiled a dataset of 401 T. brucei TryS inhibitors that includes compounds with inhibitory data reported in the literature, but also in-house acquired data. QSAR classifiers were derived and validated from such dataset, using publicly available and open-source software, thus assuring the portability of the obtained models. The performance and robustness of the resulting models were substantially improved through ensemble learning. The performance of the individual models and the model ensembles was further assessed through retrospective virtual screening campaigns. At last, as an application example, the chosen model-ensemble has been applied in a prospective virtual screening campaign on DrugBank 5.1.6 compound library. All the in-house scripts used in this study are available on request, whereas the dataset has been included as supplementary material.

Application of target repositioning and in silico screening to exploit fatty acid binding proteins (FABPs) from Echinococcus multilocularis as possible drug targets.

Fatty acid binding proteins (FABPs) are small intracellular proteins that reversibly bind fatty acids and other hydrophobic ligands. In cestodes, due to their inability to synthesise fatty acids and cholesterol de novo, FABPs, together with other lipid binding proteins, have been proposed as essential, involved in the trafficking and delivery of such lipophilic metabolites. Pharmacological agents that modify specific parasite FABP function may provide control of lipid signalling pathways, inflammatory responses and metabolic regulation that could be of crucial importance for the parasite development and survival. Echinococcus multilocularis and Echinococcus granulosus are, respectively, the causative agents of alveolar and cystic echinococcosis (or hydatidosis). These diseases are included in the World Health Organization's list of priority neglected tropical diseases. Here, we explore the potential of FABPs from cestodes as drug targets. To this end, we have applied a target repurposing approach to identify novel inhibitors of Echinococcus spp. FABPs. An ensemble of computational models was developed and applied in a virtual screening campaign of DrugBank library. 21 hits belonging to the applicability domain of the ensemble models were identified, and 3 of the hits were assayed against purified E. multilocularis FABP, experimentally confirming the model's predictions. Noteworthy, this is to our best knowledge the first report on isolation and purification of such four FABP, for which initial structural and functional characterization is reported here.

A structure-based approach towards the identification of novel antichagasic compounds: Trypanosoma cruzi carbonic anhydrase inhibitors.

Trypanosoma cruzi carbonic anhydrase (TcCA) has recently emerged as an interesting target for the design of new compounds to treat Chagas disease. In this study we report the results of a structure-based virtual screening campaign to identify novel and selective TcCA inhibitors. The combination of properly validated computational methodologies such as comparative modelling, molecular dynamics and docking simulations allowed us to find high potency hits, with KI values in the nanomolar range. The compounds also showed trypanocidal effects against T. cruzi epimastigotes and trypomastigotes. All the candidates are selective for inhibiting TcCA over the human isoform CA II, which is encouraging in terms of possible therapeutic safety and efficacy.

Anticonvulsant effect of sodium cyclamate and propylparaben on pentylenetetrazol-induced seizures in zebrafish.

Screening for novel anticonvulsant drugs requires appropriate animal seizure models. Zebrafish provide small, accessible, and cost-efficient preclinical models applicable to high-throughput small molecule screening. Based on previous results in rodents, we have here examined the effects of artificial sweetener sodium cyclamate and antimicrobial agent sodium propylparaben on a model of pentylenetetrazole (PTZ)-induced seizures in zebrafish. Sodium cyclamate reduced the bursts of hyperactivity, the spasms, increased the latency to spasms, and the latency to seizure, while propylparaben increased the latency to spasms. The results show the potential of zebrafish to detect novel anticonvulsant compounds while they also demonstrate the ability of two commonly ingested chemical compounds to modify the seizure threshold when were administrated at low concentration.

Development and Validation of a Computational Model Ensemble for the Early Detection of BCRP/ABCG2 Substrates during the Drug Design Stage.

Breast Cancer Resistance Protein (BCRP) is an ATP-dependent efflux transporter linked to the multidrug resistance phenomenon in many diseases such as epilepsy and cancer and a potential source of drug interactions. For these reasons, the early identification of substrates and nonsubstrates of this transporter during the drug discovery stage is of great interest. We have developed a computational nonlinear model ensemble based on conformational independent molecular descriptors using a combined strategy of genetic algorithms, J48 decision tree classifiers, and data fusion. The best model ensemble consists in averaging the ranking of the 12 decision trees that showed the best performance on the training set, which also demonstrated a good performance for the test set. It was experimentally validated using the ex vivo everted rat intestinal sac model. Five anticonvulsant drugs classified as nonsubstrates for BRCP by the model ensemble were experimentally evaluated, and none of them proved to be a BCRP substrate under the experimental conditions used, thus confirming the predictive ability of the model ensemble. The model ensemble reported here is a potentially valuable tool to be used as an in silico ADME filter in computer-aided drug discovery campaigns intended to overcome BCRP-mediated multidrug resistance issues and to prevent drug-drug interactions.

Discovery of novel polyamine analogs with anti-protozoal activity by computer guided drug repositioning.

Chagas disease is a parasitic infection caused by the protozoa Trypanosoma cruzi that affects about 6 million people in Latin America. Despite its sanitary importance, there are currently only two drugs available for treatment: benznidazole and nifurtimox, both exhibiting serious adverse effects and limited efficacy in the chronic stage of the disease. Polyamines are ubiquitous to all living organisms where they participate in multiple basic functions such as biosynthesis of nucleic acids and proteins, proliferation and cell differentiation. T. cruzi is auxotroph for polyamines, which are taken up from the extracellular medium by efficient transporters and, to a large extent, incorporated into trypanothione (bis-glutathionylspermidine), the major redox cosubstrate of trypanosomatids. From a 268-compound database containing polyamine analogs with and without inhibitory effect on T. cruzi we have inferred classificatory models that were later applied in a virtual screening campaign to identify anti-trypanosomal compounds among drugs already used for other therapeutic indications (i.e. computer-guided drug repositioning) compiled in the DrugBank and Sweetlead databases. Five of the candidates identified with this strategy were evaluated in cellular models from different pathogenic trypanosomatids (T. cruzi wt, T. cruzi PAT12, T. brucei and Leishmania infantum), and in vitro models of aminoacid/polyamine transport assays and trypanothione synthetase inhibition assay. Triclabendazole, sertaconazole and paroxetine displayed inhibitory effects on the proliferation of T. cruzi (epimastigotes) and the uptake of putrescine by the parasite. They also interfered with the uptake of others aminoacids and the proliferation of infective T. brucei and L. infantum (promastigotes). Trypanothione synthetase was ruled out as molecular target for the anti-parasitic activity of these compounds.

Sulfamide derivatives with selective carbonic anhydrase VII inhibitory action.

A set of N,N'-disubstituted sulfamides and sodium cyclamate have been tested for their inhibitory action against six isoforms of carbonic anhydrase (CA, EC 4.2.1.1) found in the brain, that is, CA I, CA II, CA VII, CA IX, CA XII and CA XIV, some of which are involved in epileptogenesis. The biological data showed interesting results for CA VII inhibition, the isozyme thought to be a novel antiepileptic target. Strong CA VII inhibitors, with Ki values in the low nanomolar-subnanomolar range were identified. Some of these derivatives showed selectivity for inhibition of CA VII versus the ubiquitous isoform CA II, for which the Ki values were in the micromolar range. Molecular modeling approaches were employed to understand the binding interactions between these compounds and the two CA isoforms, since the mechanism of action of such disubstituted sulfamides was not yet investigated by means of X-ray crystallography.

Identification of levothyroxine antichagasic activity through computer-aided drug repurposing.

Cruzipain (Cz) is the major cysteine protease of the protozoan Trypanosoma cruzi, etiological agent of Chagas disease. A conformation-independent classifier capable of identifying Cz inhibitors was derived from a 163-compound dataset and later applied in a virtual screening campaign on the DrugBank database, which compiles FDA-approved and investigational drugs. 54 approved drugs were selected as candidates, 3 of which were acquired and tested on Cz and T. cruzi epimastigotes proliferation. Among them, levothyroxine, traditionally used in hormone replacement therapy in patients with hypothyroidism, showed dose-dependent inhibition of Cz and antiproliferative activity on the parasite.

Application of computer-aided drug repurposing in the search of new cruzipain inhibitors: discovery of amiodarone and bromocriptine inhibitory effects.

Cruzipain (Cz) is the major cystein protease of the protozoan Trypanosoma cruzi , etiological agent of Chagas disease. From a 163 compound data set, a 2D-classifier capable of identifying Cz inhibitors was obtained and applied in a virtual screening campaign on the DrugBank database, which compiles FDA-approved and investigational drugs. Fifty-four approved drugs were selected as candidates, four of which were acquired and tested on Cz and T. cruzi epimastigotes. Among them, the antiparkinsonian and antidiabetic drug bromocriptine and the antiarrhythmic amiodarone showed dose-dependent inhibition of Cz and antiproliferative activity on the parasite.

Making the most effective use of available computational methods for drug repositioning.

INTRODUCTION: Over the last decades, there has been substantial debate around the apparent drop in productivity in the pharmaceutical sector. The development of second or further medical uses for known drugs is a possible answer to expedite the development of new therapeutic solutions. Computational methods are among the main strategies for exploring drug repurposing opportunities in a systematic manner. AREAS COVERED: This article reviews three general approximations to systematically discover new therapeutic uses for existing drugs: disease-, target-, and drug-centric approaches, along with some recently reported computational methods associated with them. EXPERT OPINION: Computational methods are essential for organizing and analyzing the large volume of available biomedical data, which has grown exponentially in the era of big data. The clearest trend in the field involves the use of integrative approaches where different types of data are combined into multipartite networks. Every aspect of computer-guided drug repositioning has currently incorporated state-of-the-art machine learning tools to boost their pattern recognition and predictive capabilities. Remarkably, a majority of the recently reported platforms are publicly available as web apps or open-source software. The introduction of nationwide electronic health records provides invaluable real-world data to detect unknown relationships between approved drug treatments and diseases.