Drug search for leishmaniasis: a virtual screening approach by grid computing

GSK-3 kinase a putative therapeutic target in trypanosomatid parasites

Trypanosomatids are an important group of parasites that predominate in tropical and subtropical areas of the planet, which cause diseases that are classified as forgotten and neglected by the world health organization. In this group of parasites, we find Trypanosoma cruzi, Trypanosoma brucei, Trypanosoma brucei rhodesiense and Leishmania spp, for which there is no vaccine available, and its control has focused mainly on pharmacological treatment. Due to the poverty situation where these diseases are found and the biological complexity of these parasites, there are multiple variables to control, including the diversity of species, the complexity of their life cycles, drug resistance, cytotoxicity, the limited use in pregnant women, the high costs of treatment and the little-known pharmacological mechanisms of action, among others. It is therefore necessary to find new strategies and approaches for the treatment of these parasitic diseases. Among these new approaches is the rational search for new targets based on the allosteric inhibition of protein kinases, which have been little studied in trypanosomatids. Among these kinases, we find Glycogen Synthase Kinase-3 (GSK-3), a kinase of great pharmacological interest, which is under intense basic and clinical research by pharmaceutical companies for the treatment of cancer. This kinase, highly studied in the PI3K/AKT/mTOR pathway signaling in humans, has an orthologous gene in these parasites (GSK-3 s), which has proven to be essential for them in response to different challenges; Therefore, it is notable to increase research in this kinase in order to achieve a broad structural and functional characterization in the different species of trypanosomatids.

The Application of MD Simulation to Lead Identification, Vaccine Design, and Structural Studies in Combat against Leishmaniasis - A Review

Drug discovery, vaccine design, and protein interaction studies are rapidly moving toward the routine use of molecular dynamics simulations (MDS) and related methods. As a result of MDS, it is possible to gain insights into the dynamics and function of identified drug targets, antibody-antigen interactions, potential vaccine candidates, intrinsically disordered proteins, and essential proteins. The MDS appears to be used in all possible ways in combating diseases such as cancer, however, it has not been well documented as to how effectively it is applied to infectious diseases such as Leishmaniasis. As a result, this review aims to survey the application of MDS in combating leishmaniasis. We have systematically collected articles that illustrate the implementation of MDS in drug discovery, vaccine development, and structural studies related to Leishmaniasis. Of all the articles reviewed, we identified that only a limited number of studies focused on the development of vaccines against Leishmaniasis through MDS. Also, the PCA and FEL studies were not carried out in most of the studies. These two were globally accepted utilities to understand the conformational changes and hence it is recommended that this analysis should be taken up in similar approaches in the future.

In Silico Exploration of the Trypanothione Reductase (TryR) of L. mexicana

Human leishmaniasis is a neglected tropical disease which affects nearly 1.5 million people every year, with Mexico being an important endemic region. One of the major defense mechanisms of these parasites is based in the polyamine metabolic pathway, as it provides the necessary compounds for its survival. Among the enzymes in this route, trypanothione reductase (TryR), an oxidoreductase enzyme, is crucial for the Leishmania genus' survival against oxidative stress. Thus, it poses as an attractive drug target, yet due to the size and features of its catalytic pocket, modeling techniques such as molecular docking focusing on that region is not convenient. Herein, we present a computational study using several structure-based approaches to assess the druggability of TryR from L. mexicana, the predominant Leishmania species in Mexico, beyond its catalytic site. Using this consensus methodology, three relevant pockets were found, of which the one we call σ-site promises to be the most favorable one. These findings may help the design of new drugs of trypanothione-related diseases.

Screening of the antileishmanial and antiplasmodial potential of synthetic 2-arylquinoline analogs

In this study, six analogs of 2-arylquinoline were synthesized and evaluated for their in vitro and in vivo antiplasmodial and leishmanicidal activity. At a later stage, hemolytic activity and druggability were tested in vitro and in silico, respectively, observing as a result: firstly, compounds showed half-maximal effective concentration (EC50) values between 3.6 and 19.3 µM. Likewise, a treatment using the compounds 4a-f caused improvement in most of the treated hamsters and cured some of them. Regarding the antiplasmodial activity, the compounds showed moderate to high activity, although they did not show hemolytic activity. Furthermore, 4e and 4f compounds were not able to control P. berghei infection when administered to animal models. Molecular dynamic simulations, molecular docking and ligand binding affinity indicate good characteristics of the studied compounds, which are expected to be active. And lastly, the compounds are absorbable at the hematoencephalic barrier but not in the gastrointestinal tract. In summary, ADMET properties suggest that these molecules may be used as a safe treatment against Leishmania.

In Vitro and In Silico Antiviral Activity of Di-Halogenated Compounds Derived from L-Tyrosine against Human Immunodeficiency Virus 1 (HIV-1)

HIV-1 infection is considered one of the major public health problems worldwide. Due to the limited access to antiretroviral therapy, the associated side effects, and the resistance that the virus can generate, it has become necessary to continue the development of new antiviral agents. The study aimed to identify potential antiviral agents for HIV-1 by evaluating the in vitro and in silico activity of 16 synthetic di-halogenated compounds derived from L-Tyrosine. The compounds were tested for cytotoxicity, which was determined using MTT, and a combined antiviral screening strategy (pre- and post-infection treatment) was performed against R5 and X4 strains of HIV-1. The most promising compounds were evaluated against a pseudotyped virus (HIV-GFP-VSV-G), and the effectiveness of these compounds was measured through GFP flow cytometry. Also, the antiviral effect of these compounds was evaluated in PBMCs using flow cytometry and ELISA for p24. The TODB-2M, TODC-2M, TODC-3M, and YDC-3M compounds showed low toxicity and significant inhibitory activity against HIV-1. In silico docking and molecular dynamics assays suggest that the compounds' antiviral activity may be due to interaction with reverse transcriptase, viral protease, or envelope gp120.

Recent Advances in Chemotherapeutics for Leishmaniasis: Importance of the Cellular Biochemistry of the Parasite and Its Molecular Interaction with the Host

Leishmaniasis, a category 1 neglected protozoan disease caused by a kinetoplastid pathogen called Leishmania, is transmitted through dipteran insect vectors (phlebotomine, sand flies) in three main clinical forms: fatal visceral leishmaniasis, self-healing cutaneous leishmaniasis, and mucocutaneous leishmaniasis. Generic pentavalent antimonials have long been the drug of choice against leishmaniasis; however, their success is plagued with limitations such as drug resistance and severe side effects, which makes them redundant as frontline therapy for endemic visceral leishmaniasis. Alternative therapeutic regimens based on amphotericin B, miltefosine, and paromomycin have also been approved. Due to the unavailability of human vaccines, first-line chemotherapies such as pentavalent antimonials, pentamidine, and amphotericin B are the only options to treat infected individuals. The higher toxicity, adverse effects, and perceived cost of these pharmaceutics, coupled with the emergence of parasite resistance and disease relapse, makes it urgent to identify new, rationalized drug targets for the improvement in disease management and palliative care for patients. This has become an emergent need and more relevant due to the lack of information on validated molecular resistance markers for the monitoring and surveillance of changes in drug sensitivity and resistance. The present study reviewed the recent advances in chemotherapeutic regimens by targeting novel drugs using several strategies including bioinformatics to gain new insight into leishmaniasis. Leishmania has unique enzymes and biochemical pathways that are distinct from those of its mammalian hosts. In light of the limited number of available antileishmanial drugs, the identification of novel drug targets and studying the molecular and cellular aspects of these drugs in the parasite and its host is critical to design specific inhibitors targeting and controlling the parasite. The biochemical characterization of unique Leishmania-specific enzymes can be used as tools to read through possible drug targets. In this review, we discuss relevant metabolic pathways and novel drugs that are unique, essential, and linked to the survival of the parasite based on bioinformatics and cellular and biochemical analyses.

Targeting trypanosomes: how chemogenomics and artificial intelligence can guide drug discovery

Trypanosomatids are protozoan parasites that cause human and animal neglected diseases. Despite global efforts, effective treatments are still much needed. Phenotypic screens have provided several chemical leads for drug discovery, but the mechanism of action for many of these chemicals is currently unknown. Recently, chemogenomic screens assessing the susceptibility or resistance of parasites carrying genome-wide modifications started to define the mechanism of action of drugs at large scale. In this review, we discuss how genomics is being used for drug discovery in trypanosomatids, how integration of chemical and genomics data from these and other organisms has guided prioritisations of candidate therapeutic targets and additional chemical starting points, and how these data can fuel the expansion of drug discovery pipelines into the era of artificial intelligence.

In vitro and in silico study of an exclusive insertion in the nicotinamide/nicotinate mononucleotide adenylyltransferase from Leishmania braziliensis

The intracellular parasite Leishmania braziliensis is the causal agent of cutaneous and mucocutaneous leishmaniasis, a group of endemic diseases in tropical regions, including Latin America. New therapeutic targets are required to inhibit the pathogen without affecting the host. The enzyme nicotinamide/nicotinate mononucleotide adenylyltransferase (NMNAT; EC: 2.7.7.1/18) is a potential target, since it catalyzes the final step in the biosynthesis of nicotinamide adenine dinucleotide (NAD⁺), which is an essential metabolite in multiple cellular processes. In this work, we produced and evaluated the catalytic activity of the recombinant protein 6HisΔ_241-249LbNMNAT to study the functional relevance of the exclusive insertion present in the enzyme of L. braziliensis (LbNMNAT), but absent in the primary structure of human NMNATs. Our results indicate that the 241-249 insertion constitutes a structural element that connects the protein structure Rossmann topology with the carboxyl-terminal domain of the enzyme. The removal of this region drastically decreases the solubility, and enzymatic activity of the recombinant, causing its inactivation. Molecular dynamics simulations were carried out with the wild-type and truncated enzymes to verify additional changes in their stability, which indicated a better stability in the wild-type protein. These findings constitute an initial step to identify a new inhibition mechanism for the development of focused pharmacological strategies on exclusive insertions from the LbNMNAT protein.

Metabolic Pathways of Leishmania Parasite: Source of Pertinent Drug Targets and Potent Drug Candidates

Leishmaniasis is a tropical disease caused by a protozoan parasite Leishmania that is transmitted via infected female sandflies. At present, leishmaniasis treatment mainly counts on chemotherapy. The currently available drugs against leishmaniasis are costly, toxic, with multiple side effects, and limitations in the administration route. The rapid emergence of drug resistance has severely reduced the potency of anti-leishmanial drugs. As a result, there is a pressing need for the development of novel anti-leishmanial drugs with high potency, low cost, acceptable toxicity, and good pharmacokinetics features. Due to the availability of preclinical data, drug repurposing is a valuable approach for speeding up the development of effective anti-leishmanial through pointing to new drug targets in less time, having low costs and risk. Metabolic pathways of this parasite play a crucial role in the growth and proliferation of Leishmania species during the various stages of their life cycle. Based on available genomics/proteomics information, known pathways-based (sterol biosynthetic pathway, purine salvage pathway, glycolysis, GPI biosynthesis, hypusine, polyamine biosynthesis) Leishmania-specific proteins could be targeted with known drugs that were used in other diseases, resulting in finding new promising anti-leishmanial therapeutics. The present review discusses various metabolic pathways of the Leishmania parasite and some drug candidates targeting these pathways effectively that could be potent drugs against leishmaniasis in the future.

RE, Marín-Villa M. In Silico, In Vitro, and Pharmacokinetic Studies of UBMC-4, a Potential Novel Compound for Treating against Trypanosoma cruzi

The lack of therapeutic alternatives for the treatment of Chagas disease, a neglected disease, drives the discovery of new drugs with trypanocidal activity. Consequently, we conducted in vitro studies using UBMC-4, a potential Trypanosoma cruzi AKT-like pleckstrin homology (PH) domain inhibitory compound found using bioinformatics tools. The half effective concentration (EC50) on intracellular amastigotes was determined at 1.85 ± 1 μM showing low cytotoxicity (LC50) > 40 μM on human cell lines tested. In order to study the lethal effect caused by the compound on epimastigotes, morphological changes were assessed by scanning and transmission electron microscopy. Progressive alterations such as flagellum inactivation, cell size reduction, nuclear structure alteration, condensation of chromatin towards the nuclear periphery, vacuole formation, and mitochondrial swelling with kinetoplast integrity loss were evidenced. In addition, apoptosis-like markers in T. cruzi were assessed by flow cytometry, demonstrating that the effect of UBMC-4 on T. cruzi AKT-like kinase reduced the tolerance to nutritional stress-triggered, apoptosis-like events, including DNA fragmentation, mitochondrial damage, and loss of plasma membrane integrity. After this, UBMC-4 was formulated for oral administration and pharmacokinetics were analyzed in a mouse model. Finally, upon oral administration of 200 mg/kg in mice, we found that a UBMC-4 plasma concentration remaining in circulation beyond 24 h after administration is well described by the two-compartment model. We conclude that UBMC-4 has an effective trypanocidal activity in vitro at low concentrations and this effect is evident in T. cruzi cell structures. In mice, UBMC-4 was well absorbed and reached plasma concentrations higher than the EC50, showing features that would aid in developing a new drug to treat Chagas disease.

Prediction of potential cysteine synthase inhibitors of Leishmania braziliensis and Leishmania major parasites by computational screening

Leishmaniasis is a neglected tropical disease considered a public health problem that requires innovative strategies for its chemotherapeutic control. In the present investigation, a molecular docking approach was carried out using the protein cysteine synthase (CS) of Leishmania braziliensis (CSLb) and Leishmania major (CSLm) parasites to identify new compounds as potential candidates for the development of selective leishmaniasis therapy. CS protein sequence similarity, active site, structural modeling, molecular docking, and ADMET properties of compounds were analyzed using bioinformatics tools. Molecular docking analyses identified 1000 ligands with highly promising binding affinity scores for both CS proteins. A total of 182 compounds for CSLb and 173 for CSLm were selected for more detailed characterization based on the binding energy and frequency values and ADMET properties. Based on Principal Component Analysis (PCA) and K-means clusterization for both CS proteins, we classified compounds into 5 clusters for CSLb and 7 for CSLm, thus providing an excellent starting point for verification of enzyme inhibition in in vitro studies. We found the ZINC16524774 compound predicted to have a high affinity and stability for both CSLb and CSLm proteins, which was also evaluated through molecular dynamics simulations. Compounds within each of the five clusters also displayed pharmacological and structural properties that make them attractive drug candidates for the development of selective cutaneous leishmaniasis chemotherapy.

Assay development in leishmaniasis drug discovery: a comprehensive review

INTRODUCTION

Cutaneous, muco-cutaneous and visceral leishmaniasis occur due to an infection with the protozoan parasite Leishmania. The current therapeutic options are limited mainly due to extensive toxicity, emerging resistance and variation in efficacy based on species and strain of the Leishmania parasite. There exists a high unmet medical need to identify new chemical starting points for drug discovery to tackle the disease.

AREAS COVERED

The authors have highlighted the recent progress, limitations and successes achieved in assay development for leishmaniasis drug discovery.

EXPERT OPINION

It is true that sophisticated and robust phenotypic in vitro assays have been developed during the last decade, however limitations and challenges remain with respect to variation in activity reported between different research groups and success in translating in vitro outcomes in vivo. The variability is not only due to strain and species differences but also a lack of well-defined criteria and assay conditions, e.g. culture media, host cell type, assay formats, parasite form used, multiplicity of infection and incubation periods. Thus, there is an urgent need for more physiologically relevant assays that encompass multi-species phenotypic approaches to identify new chemical starting points for leishmaniasis drug discovery.

Improving Structure-Based Virtual Screening with Ensemble Docking and Machine Learning

One of the main challenges of structure-based virtual screening (SBVS) is the incorporation of the receptor's flexibility, as its explicit representation in every docking run implies a high computational cost. Therefore, a common alternative to include the receptor's flexibility is the approach known as ensemble docking. Ensemble docking consists of using a set of receptor conformations and performing the docking assays over each of them. However, there is still no agreement on how to combine the ensemble docking results to obtain the final ligand ranking. A common choice is to use consensus strategies to aggregate the ensemble docking scores, but these strategies exhibit slight improvement regarding the single-structure approach. Here, we claim that using machine learning (ML) methodologies over the ensemble docking results could improve the predictive power of SBVS. To test this hypothesis, four proteins were selected as study cases: CDK2, FXa, EGFR, and HSP90. Protein conformational ensembles were built from crystallographic structures, whereas the evaluated compound library comprised up to three benchmarking data sets (DUD, DEKOIS 2.0, and CSAR-2012) and cocrystallized molecules. Ensemble docking results were processed through 30 repetitions of 4-fold cross-validation to train and validate two ML classifiers: logistic regression and gradient boosting trees. Our results indicate that the ML classifiers significantly outperform traditional consensus strategies and even the best performance case achieved with single-structure docking. We provide statistical evidence that supports the effectiveness of ML to improve the ensemble docking performance.

Identification of Potential Kinase Inhibitors within the PI3K/AKT Pathway of Leishmania Species

Leishmaniasis is a public health disease that requires the development of more effective treatments and the identification of novel molecular targets. Since blocking the PI3K/AKT pathway has been successfully studied as an effective anticancer strategy for decades, we examined whether the same approach would also be feasible in Leishmania due to their high amount and diverse set of annotated proteins. Here, we used a best reciprocal hits protocol to identify potential protein kinase homologues in an annotated human PI3K/AKT pathway. We calculated their ligandibility based on available bioactivity data of the reported homologues and modelled their 3D structures to estimate the druggability of their binding pockets. The models were used to run a virtual screening method with molecular docking. We found and studied five protein kinases in five different Leishmania species, which are AKT, CDK, AMPK, mTOR and GSK3 homologues from the studied pathways. The compounds found for different enzymes and species were analysed and suggested as starting point scaffolds for the design of inhibitors. We studied the kinases’ participation in protein–protein interaction networks, and the potential deleterious effects, if inhibited, were supported with the literature. In the case of Leishmania GSK3, an inhibitor of its human counterpart, prioritized by our method, was validated in vitro to test its anti-Leishmania activity and indirectly infer the presence of the enzyme in the parasite. The analysis contributes to improving the knowledge about the presence of similar signalling pathways in Leishmania, as well as the discovery of compounds acting against any of these kinases as potential molecular targets in the parasite.

A computer-aided approach to identify novel Leishmania major protein disulfide isomerase inhibitors for treatment of leishmaniasis

Leishmaniasis is an infectious disease caused by parasites of the genus Leishmania and transmitted by the bite of a sand fly. To date, most available drugs for treatment are toxic and beyond the economic means of those affected by the disease. Protein disulfide isomerase (PDI) is a chaperone protein that plays a major role in the folding of newly synthesized proteins, specifically assisting in disulfide bond formation, breakage, or rearrangement in all non-native proteins. In previous work, we demonstrated that Leishmania major PDI (LmPDI) has an essential role in pathogen virulence. Furthermore, inhibition of LmPDI further blocked parasite infection in macrophages. In this study, we utilized a computer-aided approach to design a series of LmPDI inhibitors. Fragment-based virtual screening allowed for the understanding of the inhibitors' modes of action on LmPDI active sites. The generated compounds obtained after multiple rounds of virtual screening were synthesized and significantly inhibited target LmPDI reductase activity and were shown to decrease in vitro parasite growth in human monocyte-derived macrophages. This novel cheminformatics and synthetic approach led to the identification of a new series of compounds that might be optimized into novel drugs, likely more specific and less toxic for the treatment of leishmaniasis.

Computational approaches for drug discovery against trypanosomatid-caused diseases

During three decades, only about 20 new drugs have been developed for malaria, tuberculosis and all neglected tropical diseases (NTDs). This critical situation was reached because NTDs represent only 10% of health research investments; however, they comprise about 90% of the global disease burden. Computational simulations applied in virtual screening (VS) strategies are very efficient tools to identify pharmacologically active compounds or new indications for drugs already administered for other diseases. One of the advantages of this approach is the low time-consuming and low-budget first stage, which filters for testing experimentally a group of candidate compounds with high chances of binding to the target and present trypanocidal activity. In this work, we review the most common VS strategies that have been used for the identification of new drugs with special emphasis on those applied to trypanosomiasis and leishmaniasis. Computational simulations based on the selected protein targets or their ligands are explained, including the method selection criteria, examples of successful VS campaigns applied to NTDs, a list of validated molecular targets for drug development and repositioned drugs for trypanosomatid-caused diseases. Thereby, here we present the state-of-the-art of VS and drug repurposing to conclude pointing out the future perspectives in the field.

Outwitting an Old Neglected Nemesis: A Review on Leveraging Integrated Data-Driven Approaches to Aid in Unraveling of Leishmanicides of Therapeutic Potential

The global prevalence of leishmaniasis has increased with skyrocketed mortality in the past decade. The causative agent of leishmaniasis is Leishmania species, which infects populations in almost all the continents. Prevailing treatment regimens are consistently inefficient with reported side effects, toxicity and drug resistance. This review complements existing ones by discussing the current state of treatment options, therapeutic bottlenecks including chemoresistance and toxicity, as well as drug targets. It further highlights innovative applications of nanotherapeutics-based formulations, inhibitory potential of leishmanicides, anti-microbial peptides and organometallic compounds on leishmanial species. Moreover, it provides essential insights into recent machine learning-based models that have been used to predict novel leishmanicides and also discusses other new models that could be adopted to develop fast, efficient, robust and novel algorithms to aid in unraveling the next generation of anti-leishmanial drugs. A plethora of enriched functional genomic, proteomic, structural biology, high throughput bioassay and drug-related datasets are currently warehoused in both general and leishmania-specific databases. The warehoused datasets are essential inputs for training and testing algorithms to augment the prediction of biotherapeutic entities. In addition, we demonstrate how pharmacoinformatics techniques including ligand-, structure- and pharmacophore-based virtual screening approaches have been utilized to screen ligand libraries against both modeled and experimentally solved 3D structures of essential drug targets. In the era of data-driven decision-making, we believe that highlighting intricately linked topical issues relevant to leishmanial drug discovery offers a one-stop-shop opportunity to decipher critical literature with the potential to unlock implicit breakthroughs.

Leishmania mexicana Trypanothione Reductase Inhibitors: Computational and Biological Studies

Leishmanicidal drugs have many side effects, and drug resistance to all of them has been documented. Therefore, the development of new drugs and the identification of novel therapeutic targets are urgently needed. Leishmania mexicana trypanothione reductase (LmTR), a NADPH-dependent flavoprotein oxidoreductase important to thiol metabolism, is essential for parasite viability. Its absence in the mammalian host makes this enzyme an attractive target for the development of new anti-Leishmania drugs. Herein, a tridimensional model of LmTR was constructed and the molecular docking of 20 molecules from a ZINC database was performed. Five compounds (ZINC04684558, ZINC09642432, ZINC12151998, ZINC14970552, and ZINC11841871) were selected (docking scores -10.27 kcal/mol to -5.29 kcal/mol and structurally different) and evaluated against recombinant LmTR (rLmTR) and L. mexicana promastigote. Additionally, molecular dynamics simulation of LmTR-selected compound complexes was achieved. The five selected compounds inhibited rLmTR activity in the range of 32.9% to 40.1%. The binding of selected compounds to LmTR involving different hydrogen bonds with distinct residues of the molecule monomers A and B is described. Compound ZINC12151998 (docking score -10.27 kcal/mol) inhibited 32.9% the enzyme activity (100 µM) and showed the highest leishmanicidal activity (IC₅₀ = 58 µM) of all the selected compounds. It was more active than glucantime, and although its half-maximal cytotoxicity concentration (CC₅₀ = 53 µM) was higher than that of the other four compounds, it was less cytotoxic than amphotericin B. Therefore, compound ZINC12151998 provides a promising starting point for a hit-to-lead process in our search for new anti-Leishmania drugs that are more potent and less cytotoxic.

Predicting the Affinity of Peptides to Major Histocompatibility Complex Class II by Scoring Molecular Dynamics Simulations

Predicting the binding affinity of peptides able to interact with major histocompatibility complex (MHC) molecules is a priority for researchers working in the identification of novel vaccines candidates. Most available approaches are based on the analysis of the sequence of peptides of known experimental affinity. However, for MHC class II receptors, these approaches are not very accurate, due to the intrinsic flexibility of the complex. To overcome these limitations, we propose to estimate the binding affinity of peptides bound to an MHC class II by averaging the score of the configurations from finite-temperature molecular dynamics simulations. The score is estimated for 18 different scoring functions, and we explored the optimal manner for combining them. To test the predictions, we considered eight peptides of known binding affinity. We found that six scoring functions correlate with the experimental ranking of the peptides significantly better than the others. We then assessed a set of techniques for combining the scoring functions by linear regression and logistic regression. We obtained a maximum accuracy of 82% for the predicted sign of the binding affinity using a logistic regression with optimized weights. These results are potentially useful to improve the reliability of in silico protocols to design high-affinity binding peptides for MHC class II receptors.

Virtual and experimental screening of phenylfuranchalcones as potential anti-Leishmania candidates

Discovery of novel or repurposed chemical treatments for leishmaniasis is a priority given the limited number of therapeutic alternatives available. One way to accelerate the finding is by implementing virtual screening methodologies using structural information, with subsequent experimental validations. Here we tested a library of 48 phenylfuranchalcones as anti-Leishmania agents that can be associated to the potential inhibition of a protein target within the parasite. For that purpose, a list of 43 protein structures from different Leishmania species was prepared to dock the virtual compound library. The protein with the best predicted scores was used as reference to select a subset of previously synthesized compounds for in vitro validation of their cytotoxicity and anti-Leishmania activity. We found a set of active compounds (EC₅₀ < 25 μM) that were compared with the computational results using Spearman correlations. The analysis allowed us to propose the inhibition of a phosphodiesterase enzyme as the potential mechanism of action.

Chemoinformatics Strategies for Leishmaniasis Drug Discovery

Leishmaniasis is a fatal neglected tropical disease (NTD) that is caused by more than 20 species of Leishmania parasites. The disease kills approximately 20,000 people each year and more than 1 billion are susceptible to infection. Although counting on a few compounds, the therapeutic arsenal faces some drawbacks such as drug resistance, toxicity issues, high treatment costs, and accessibility problems, which highlight the need for novel treatment options. Worldwide efforts have been made to that aim and, as well as in other therapeutic areas, chemoinformatics have contributed significantly to leishmaniasis drug discovery. Breakthrough advances in the comprehension of the parasites’ molecular biology have enabled the design of high-affinity ligands for a number of macromolecular targets. In addition, the use of chemoinformatics has allowed highly accurate predictions of biological activity and physicochemical and pharmacokinetics properties of novel antileishmanial compounds. This review puts into perspective the current context of leishmaniasis drug discovery and focuses on the use of chemoinformatics to develop better therapies for this life-threatening condition.

Efficiency of Stratification for Ensemble Docking Using Reduced Ensembles

Molecular docking can account for receptor flexibility by combining the docking score over multiple rigid receptor conformations, such as snapshots from a molecular dynamics simulation. Here, we evaluate a number of common snapshot selection strategies using a quality metric from stratified sampling, the efficiency of stratification, which compares the variance of a selection strategy to simple random sampling. We also extend the metric to estimators of exponential averages (which involve an exponential transformation, averaging, and inverse transformation) and minima. For docking sets of over 500 ligands to four different proteins of varying flexibility, we observe that, for estimating ensemble averages and exponential averages, many clustering algorithms have similar performance trends: for a few snapshots (less than 25), medoids are the most efficient, while, for a larger number, optimal (the allocation that minimizes the variance) and proportional (to the size of each cluster) allocation become more efficient. Proportional allocation appears to be the most consistently efficient for estimating minima.