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.

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.

Nanostructured lipid carriers containing benznidazole: physicochemical, biopharmaceutical and cellular in vitro studies.

Chagas disease is a neglected endemic disease prevalent in Latin American countries, affecting around 8 million people. The first-line treatment, benznidazole (BNZ), is effective in the acute stage of the disease but has limited efficacy in the chronic stage, possibly because current treatment regimens do not eradicate transiently dormant Trypanosoma cruzi amastigotes. Nanostructured lipid carriers (NLC) appear to be a promising approach for delivering pharmaceutical active ingredients as they can have a positive impact on bioavailability by modifying the absorption, distribution, and elimination of the drug. In this study, BNZ was successfully loaded into nanocarriers composed of myristyl myristate/Crodamol oil/poloxamer 188 prepared by ultrasonication. A stable NLC formulation was obtained, with ≈80% encapsulation efficiency (%EE) and a biphasic drug release profile with an initial burst release followed by a prolonged phase. The hydrodynamic average diameter and zeta potential of NLC obtained by dynamic light scattering were approximately 150 nm and -13 mV, respectively, while spherical and well-distributed nanoparticles were observed by transmission electron microscopy. Fourier-transform infrared spectroscopy, differential scanning calorimetry, thermogravimetric analysis, and small-angle X-ray scattering analyses of the nanoparticles indicated that BNZ might be dispersed in the nanoparticle matrix in an amorphous state. The mean size, zeta potential, polydispersity index, and %EE of the formulation remained stable for at least six months. The hemolytic effect of the nanoparticles was insignificant compared to that of the positive lysis control. The nanoparticle formulation exhibited similar performance in vitro against T. cruzi compared to free BNZ. No formulation-related cytotoxic effects were observed on either Vero or CHO cells. Moreover, BNZ showed a 50% reduction in CHO cell viability at 125 µg/mL, whereas NLC-BNZ and non-loaded NLC did not exert a significant effect on cell viability at the same concentration. These results show potential for the development of new nanomedicines against T. cruzi.

Synthesis and biological evaluation of new antiseizure compounds derived from valproic acid.

Background: New hybrid compounds were synthesized by linking the valproic acid (VPA) structure with other anticonvulsant/anti-inflammatory scaffolds. Materials & methods: The chemistry involved the incorporation of the linker oxymethyl ester into VPA, followed by reaction with the second scaffold. The antiseizure effects were investigated by the maximal electroshock seizure test, and the most active compound was additionally evaluated in the 6 Hz test and pentylenetetrazol test in mice. Results: The compounds showed protection against seizures. The hybrid structure with the butylparaben scaffold exhibited an ED50 of 8.265 mg/kg (0.0236 mmol/Kg) in the maximal electroshock seizure test and 50.00 mg/kg (0.147 mmol/kg) in the 6 Hz test. Conclusion: The antiseizure activity of the synthesized compounds highlighted the potential of hybrid structures to treat multifactorial diseases such as epilepsy.

This article focuses on the design of new anticonvulsant compounds that combine the chemical structure of valproic acid with other interesting scaffolds with anticonvulsant or anti-inflammatory properties. These compounds protected against in vivo acute seizure models (mice). The results revealed the capacity of combining known scaffolds into a single structure to generate new active compounds with multitarget purposes.

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.

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.

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.

Novel Phenobarbital-Loaded Nanostructured Lipid Carriers for Epilepsy Treatment: From QbD to In Vivo Evaluation.

Pharmacological treatments of central nervous system diseases are always challenging due to the restrictions imposed by the blood-brain barrier: while some drugs can effectively cross it, many others, some antiepileptic drugs among them, display permeability issues to reach the site of action and exert their pharmacological effects. The development of last-generation therapeutic nanosystems capable of enhancing drug biodistribution has gained ground in the past few years. Lipid-based nanoparticles are promising systems aimed to improve or facilitate the passage of drugs through biological barriers, which have demonstrated their effectiveness in various therapeutic fields, without signs of associated toxicity. In the present work, nanostructured lipid carriers (NLCs) containing the antiepileptic drug phenobarbital were designed and optimized by a quality by design approach (QbD). The optimized formulation was characterized by its entrapment efficiency, particle size, polydispersity index, and Z potential. Thermal properties were analyzed by DSC and TGA, and morphology and crystal properties were analyzed by AFM, TEM, and XRD. Drug localization and possible interactions between the drug and the formulation components were evaluated using FTIR. In vitro release kinetic, cytotoxicity on non-tumoral mouse fibroblasts L929, and in vivo anticonvulsant activity in an animal model of acute seizures were studied as well. The optimized formulation resulted in spherical particles with a mean size of ca. 178 nm and 98.2% of entrapment efficiency, physically stable for more than a month. Results obtained from the physicochemical and in vitro release characterization suggested that the drug was incorporated into the lipid matrix losing its crystalline structure after the synthesis process and was then released following a slower kinetic in comparison with the conventional immediate-release formulation. The NLC was non-toxic against the selected cell line and capable of delivering the drug to the site of action in an adequate amount and time for therapeutic effects, with no appreciable neurotoxicity. Therefore, the developed system represents a promising alternative for the treatment of one of the most prevalent neurological diseases, epilepsy.

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.

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.

Antiseizure medication discovery: Recent and future paradigm shifts.

Despite the ever-increasing number of available options for the treatment of epilepsies and the remarkable advances on the understanding of their pathophysiology, the proportion of refractory patients has remained approximately unmodified during the last 100 years. How efficient are we translating positive outcomes from basic research to clinical trials and/or the clinical scenario? It is possible that fresh thinking and exploration of new paradigms are required to arrive at truly novel therapeutic solutions, as seemingly proven by recently approved first-in-class antiseizure medications and drug candidates undergoing late clinical trials. Here, the author discusses some approximations in line with the network pharmacology philosophy, which may result in highly innovative (and, hopefully, safer and/or more efficacious) medications for the control of seizures, as embodied with some recent examples in the field, namely tailored multi-target agents and low-affinity ligands.

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.

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.

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.

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.

Can drug repurposing strategies be the solution to the COVID-19 crisis?

Introduction: The COVID-19 pandemic resulted in disastrous human and economic costs, mainly due to the initial lack of specific treatments. Complementary to immunotherapies, drug repurposing is possibly the best option to arrive at COVID-19 treatments in the short term.Areas covered: Repurposing prospects undergoing clinical trials or with some level of evidence emerging from clinical studies are overviewed. The authors discuss some possible intellectual property and commercial barriers to drug repurposing, and strategies to facilitate equitable access to incoming therapeutic solutions, highlighting the importance of collaborative drug discovery models. Based on a critical analysis of the available literature about in silico screens against SARS-CoV-2 main protease, the authors illustrate how frequently overconfident conclusions are being drawn in COVID-19-related literature.Expert opinion: Most of the current clinical trials on potential COVID-19 treatments are, in fact, drug repurposing examples. In October 2020, the FDA approved a repurposed antiviral, remdesivir, as the first treatment for COVID-19. Considering the high expectations invested in approaching therapeutic solutions, the scientific community must be careful not to raise unrealistic expectations. Today more than ever, the conclusions drawn in scientific reports have to be fully supported by the level of evidence, avoiding any sort of unfounded speculation.

Trypanosomatid-Caused Conditions: State of the Art of Therapeutics and Potential Applications of Lipid-Based Nanocarriers.

Trypanosomatid-caused conditions (African trypanosomiasis, Chagas disease, and leishmaniasis) are neglected tropical infectious diseases that mainly affect socioeconomically vulnerable populations. The available therapeutics display substantial limitations, among them limited efficacy, safety issues, drug resistance, and, in some cases, inconvenient routes of administration, which made the scenarios with insufficient health infrastructure settings inconvenient. Pharmaceutical nanocarriers may provide solutions to some of these obstacles, improving the efficacy-safety balance and tolerability to therapeutic interventions. Here, we overview the state of the art of therapeutics for trypanosomatid-caused diseases (including approved drugs and drugs undergoing clinical trials) and the literature on nanolipid pharmaceutical carriers encapsulating approved and non-approved drugs for these diseases. Numerous studies have focused on the obtention and preclinical assessment of lipid nanocarriers, particularly those addressing the two currently most challenging trypanosomatid-caused diseases, Chagas disease, and leishmaniasis. In general, in vitro and in vivo studies suggest that delivering the drugs using such type of nanocarriers could improve the efficacy-safety balance, diminishing cytotoxicity and organ toxicity, especially in leishmaniasis. This constitutes a very relevant outcome, as it opens the possibility to extended treatment regimens and improved compliance. Despite these advances, last-generation nanosystems, such as targeted nanocarriers and hybrid systems, have still not been extensively explored in the field of trypanosomatid-caused conditions and represent promising opportunities for future developments. The potential use of nanotechnology in extended, well-tolerated drug regimens is particularly interesting in the light of recent descriptions of quiescent/dormant stages of Leishmania and Trypanosoma cruzi, which have been linked to therapeutic failure.

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.