Repositioning FDA Drugs as Potential Cruzain Inhibitors from Trypanosoma cruzi: Virtual Screening, In Vitro and In Vivo Studies

Unravelling driver genes as potential therapeutic targets in ovarian cancer via integrated bioinformatics approach

Target-driven cancer therapy is a notable advancement in precision oncology that has been accompanied by substantial medical accomplishments. Ovarian cancer is a highly frequent neoplasm in women and exhibits significant genomic and clinical heterogeneity. In a previous publication, we presented an extensive bioinformatics study aimed at identifying specific biomarkers associated with ovarian cancer. The findings of the network analysis indicate the presence of a cluster of nine dysregulated hub genes that exhibited significance in the underlying biological processes and contributed to the initiation of ovarian cancer. Here in this research article, we are proceeding our previous research by taking all hub genes into consideration for further analysis. GEPIA2 was used to identify patterns in the expression of critical genes. The KM plotter analysis indicated that the out of all genes 5 genes are statistically significant. The cBioPortal platform was further used to investigate the frequency of genetic mutations across the board and how they affected the survival of the patients. Maximum mutation was reported by ELAVL2. In order to discover viable therapeutic candidates after competitive inhibition of ELAVL2 with small molecular drug complex, high throughput screening and docking studies were used. Five compounds were identified. Overall, our results suggest that the ELAV-like protein 2-ZINC03830554 complex was relatively stable during the molecular dynamic simulation. The five compounds that have been found can also be further examined as potential therapeutic possibilities. The combined findings suggest that ELAVL2, together with their genetic changes, can be investigated in therapeutic interventions for precision oncology, leveraging early diagnostics and target-driven therapy.

Discovery of Novel Inhibitors of Cruzain Cysteine Protease of Trypanosoma cruzi

Chagas disease (CD) is a parasitic disease endemic in several developing countries. According to the World Health Organization, approximately 6-8 million people worldwide are inflicted by CD. The scarcity of new drugs, mainly for the chronic phase, is the main reason for treatment limitation in CD. Therefore, there is an urgent need to discover new targets for which new therapeutical agents could be developed. Cruzain cysteine protease (CCP) is a promising alternative because this enzyme exhibits pleiotropic effects by acting as a virulence factor, modulating host immune cells, and interacting with host cells. This systematic review was conducted to discover new compounds that act as cruzain inhibitors, and their effects in vitro were studied through enzymatic assays and molecular docking. Additionally, the advances and perspectives of these inhibitors are discussed. These findings are expected to contribute to medicinal chemistry in view of the design of new, safe, and efficacious inhibitors against Trypanosoma cruzi CCP detected in the last decade (2013-2022) to provide scaffolds for further optimization, aiming toward the discovery of new drugs.

Phenothiazine-based virtual screening, molecular docking, and molecular dynamics of new trypanothione reductase inhibitors of Trypanosoma cruzi

Phenothiazine derivatives can unselectively inhibit the trypanothione-dependent antioxidant system enzyme trypanothione reductase (TR). A virtual screening of 2163 phenothiazine derivatives from the ZINC15 and PubChem databases docked on the active site of T. cruzi TR showed that 285 compounds have higher affinity than the natural ligand trypanothione disulfide. 244 compounds showed higher affinity toward the parasite's enzyme than to its human homolog glutathione reductase. Protein-ligand interaction profiling predicted that the main interactions for the top scored compounds were with residues important for trypanothione disulfide binding: Phe396, Pro398, Leu399, His461, Glu466, and Glu467, particularly His461, which participates in catalysis. Two compounds with the desired profiles, ZINC1033681 (Zn_C687) and ZINC10213096 (Zn_C216), decreased parasite growth by 20 % and 50 %, respectively. They behaved as mixed-type inhibitors of recombinant TR, with Ki values of 59 and 47 μM, respectively. This study provides a further understanding of the potential of phenothiazine derivatives as TR inhibitors.

Navigating drug repurposing for Chagas disease: advances, challenges, and opportunities

Chagas disease is a vector-borne illness caused by the protozoan parasite Trypanosoma cruzi (T. cruzi). It poses a significant public health burden, particularly in the poorest regions of Latin America. Currently, there is no available vaccine, and chemotherapy has been the traditional treatment for Chagas disease. However, the treatment options are limited to just two outdated medicines, nifurtimox and benznidazole, which have serious side effects and low efficacy, especially during the chronic phase of the disease. Collectively, this has led the World Health Organization to classify it as a neglected disease. To address this problem, new drug regimens are urgently needed. Drug repurposing, which involves the use of existing drugs already approved for the treatment of other diseases, represents an increasingly important option. This approach offers potential cost reduction in new drug discovery processes and can address pharmaceutical bottlenecks in the development of drugs for Chagas disease. In this review, we discuss the state-of-the-art of drug repurposing approaches, including combination therapy with existing drugs, to overcome the formidable challenges associated with treating Chagas disease. Organized by original therapeutic area, we describe significant recent advances, as well as the challenges in this field. In particular, we identify candidates that exhibit potential for heightened efficacy and reduced toxicity profiles with the ultimate objective of accelerating the development of new, safe, and effective treatments for Chagas disease.

Identification of inhibitors as drug candidates against Chagas disease

Chagas disease, after more than a century after its discovery, is still a major public health problem. It is estimated that approximately 10 million people worldwide are infected with T. cruzi. However, the situation is more critical in Latin America and other regions where the disease is endemic. The largest number of cases occurs in Brazil, Argentina, and Mexico as more than 100 million people in these regions are located in areas with a high risk of contamination by the vector. The need for new therapeutic alternatives is urgent, as the available drugs have severe limitations such as low efficacy and high toxicity. From this scenario, in this work, we employed the virtual screening technique using cruzain and BDF2 as key biological targets for the survival of the parasite. Our objective was to identify potential inhibitors of T. cruzi trypomastigotes, which could be considered drug candidates against Chagas disease. For this, we employed different in silico methodologies and the obtained results were corroborated using in vitro biological assays. For the VS studies, a database containing synthetic compounds was simulated at the binding site of cruzain and BDF2. In addition, pharmacophoric models were constructed in the initial phases of VS, as well as other advanced analyses (molecular dynamics simulations, calculations of binding free energy, and ADME prediction) were carried out and the results allowed the selection of potential inhibitors of T. cruzi. Based on the obtained data, 32 different compounds commercially available were subjected to biological tests against the trypomastigote form of T. cruzi. As result, 11 of those compounds displayed significant activity against T. cruzi and can be considered potential candidates for the treatment of Chagas disease.

Are patents important indicators of innovation for Chagas disease treatment?

INTRODUCTION

Chagas disease is a neglected, endemic disease in 21 countries, spreading to non-endemic countries too. Like other neglected diseases affecting primarily low- and middle-income countries, low investment and the absence of new chemical entities from the industry occurred. Increased knowledge about the parasite, drug targets, and vector control has been observed, but this was not translated into new drugs. The partnerships of pharmaceutical companies with academies and consolidated networks to increment the new drugs and treatment research in Chagas disease are shown. The current review analyzes in detail the patents dealing with compounds candidates for new drugs and treatment. The patent search was performed using Orbit Intelligence® software in the 2001-2021 period.

AREAS COVERED

The author focused specifically on patents for the treatment, the new candidates disclosed in the patents, and the barriers to innovation.

EXPERT OPINION

Patents in Chagas disease have been increasing in the last years, although they do not bring new compounds to an effective treatment.

In Vitro and In Silico Analysis of New n-Butyl and Isobutyl Quinoxaline-7-carboxylate 1,4-di-N-oxide Derivatives against Trypanosoma cruzi as Trypanothione Reductase Inhibitors

American trypanosomiasis is a worldwide health problem that requires attention due to ineffective treatment options. We evaluated n-butyl and isobutyl quinoxaline-7-carboxylate 1,4-di-N-oxide derivatives against trypomastigotes of the Trypanosoma cruzi strains NINOA and INC-5. An in silico analysis of the interactions of 1,4-di-N-oxide on the active site of trypanothione reductase (TR) and an enzyme inhibition study was carried out. The n-butyl series compound identified as T-150 had the best trypanocidal activity against T. cruzi trypomastigotes, with a 13% TR inhibition at 44 μM. The derivative T-147 behaved as a mixed inhibitor with Ki and Ki' inhibition constants of 11.4 and 60.8 µM, respectively. This finding is comparable to the TR inhibitor mepacrine (Ki = 19 µM).

The repositioned drugs disulfiram/diethyldithiocarbamate combined to benznidazole: Searching for Chagas disease selective therapy, preventing toxicity and drug resistance

Chagas disease (CD) affects at least 6 million people in 21 South American countries besides several thousand in other nations all over the world. It is estimated that at least 14,000 people die every year of CD. Since vaccines are not available, chemotherapy remains of pivotal relevance. About 30% of the treated patients cannot complete the therapy because of severe adverse reactions. Thus, the search for novel drugs is required. Here we tested the benznidazole (BZ) combination with the repositioned drug disulfiram (DSF) and its derivative diethyldithiocarbamate (DETC) upon Trypanosoma cruzi in vitro and in vivo. DETC-BZ combination was synergistic diminishing epimastigote proliferation and enhancing selective indexes up to over 10-fold. DETC was effective upon amastigotes of the BZ- partially resistant Y and the BZ-resistant Colombiana strains. The combination reduced proliferation even using low concentrations (e.g., 2.5 µM). Scanning electron microscopy revealed membrane discontinuities and cell body volume reduction. Transmission electron microscopy revealed remarkable enlargement of endoplasmic reticulum cisternae besides, dilated mitochondria with decreased electron density and disorganized kinetoplast DNA. At advanced stages, the cytoplasm vacuolation apparently impaired compartmentation. The fluorescent probe H2-DCFDA indicates the increased production of reactive oxygen species associated with enhanced lipid peroxidation in parasites incubated with DETC. The biochemical measurement indicates the downmodulation of thiol expression. DETC inhibited superoxide dismutase activity on parasites was more pronounced than in infected mice. In order to approach the DETC effects on intracellular infection, peritoneal macrophages were infected with Colombiana trypomastigotes. DETC addition diminished parasite numbers and the DETC-BZ combination was effective, despite the low concentrations used. In the murine infection, the combination significantly enhanced animal survival, decreasing parasitemia over BZ. Histopathology revealed that low doses of BZ-treated animals presented myocardial amastigote, not observed in combination-treated animals. The picrosirius collagen staining showed reduced myocardial fibrosis. Aminotransferase de aspartate, Aminotransferase de alanine, Creatine kinase, and urea plasma levels demonstrated that the combination was non-toxic. As DSF and DETC can reduce the toxicity of other drugs and resistance phenotypes, such a combination may be safe and effective.

Computational Methods for Structure-Based Drug Design Through System Biology

The advances in computational chemistry and biology, computer science, structural biology, and molecular biology go in parallel with the rapid progress in target-based systems. This technique has become a powerful tool in medicinal chemistry for the identification of hit molecules. The recent developments in target-based systems have played a major role in the creation of libraries of compounds, and it has also been widely applied for the design of molecular docking methods. The main advantage of this method is that it hits the fragment that has the strongest binding, has relatively small size, and leads to better compounds in terms of pharmacokinetic properties when compared with virtual screening (VS) and high-throughput screening (HTS) hits. De novo design is an essential aspect of target-based systems and requires the synthesis of chemical to allow the design of promising compound.

Impact of different protonation states on virtual screening performance against cruzain

The cysteine protease cruzain is a Chagas disease target, exploited in computational studies. However, there is no consensus on the protonation states of the active site residues Cys25, His162, and Glu208 at the enzyme's active pH range. We evaluated the impact of different protonation states of these residues on docking calculations. Through a retrospective study with cruzain inhibitors and decoys, we compared the performance of virtual screening using four grids, varying protonation states of Cys25, His162, and Glu208. Based on enrichment factors and ROC plots, docking with the four grids affected compound ranking and the overall charge of top-ranking compounds. Different grids can be complementary and synergistic, increasing the odds of finding different ligands with diverse chemical properties.

Structural Optimization and Biological Activity of Pyrazole Derivatives: Virtual Computational Analysis, Recovery Assay and 3D Culture Model as Potential Predictive Tools of Effectiveness against Trypanosoma cruzi

Chagas disease, a chronic and silent disease caused by Trypanosoma cruzi, is currently a global public health problem. The treatment of this neglected disease relies on benznidazole and nifurtimox, two nitroheterocyclic drugs that show limited efficacy and severe side effects. The failure of potential drug candidates in Chagas disease clinical trials highlighted the urgent need to identify new effective chemical entities and more predictive tools to improve translational success in the drug development pipeline. In this study, we designed a small library of pyrazole derivatives (44 analogs) based on a hit compound, previously identified as a T. cruzi cysteine protease inhibitor. The in vitro phenotypic screening revealed compounds 3g, 3j, and 3m as promising candidates, with IC₅₀ values of 6.09 ± 0.52, 2.75 ± 0.62, and 3.58 ± 0.25 µM, respectively, against intracellular amastigotes. All pyrazole derivatives have good oral bioavailability prediction. The structure–activity relationship (SAR) analysis revealed increased potency of 1-aryl-1H-pyrazole-imidazoline derivatives with the Br, Cl, and methyl substituents in the para-position. The 3m compound stands out for its trypanocidal efficacy in 3D microtissue, which mimics tissue microarchitecture and physiology, and abolishment of parasite recrudescence in vitro. Our findings encourage the progression of the promising candidate for preclinical in vivo studies.

Recent Advances in the Development of Triose Phosphate Isomerase Inhibitors as Antiprotozoal Agents

BACKGROUND

Parasitic diseases caused by protozoa such as Chagas disease, leishmaniasis, malaria, African trypanosomiasis, amebiasis, trichomoniasis, and giardiasis are considered serious public health problems in developing countries. Drug-resistance among parasites justifies the search for new therapeutic drugs and the identification of new targets becomes a valuable approach. In this scenario, glycolysis pathway which consists of the conversion of glucose into pyruvate plays an important role in the protozoa energy supply and it is therefore considered as a promising target. In this pathway, triose phosphate isomerase (TIM) plays an essential role in efficient energy production. Furthermore, protozoa TIM show structural differences with human enzyme counterparts suggesting the possibility of obtaining selective inhibitors. Therefore, TIM is considered a valid approach to develop new antiprotozoal agents, inhibiting the glycolysis in the parasite.

OBJECTIVE

In this review, we discuss the drug design strategies, structure-activity relationship, and binding modes of outstanding TIM inhibitors against Trypanosoma cruzi, Trypanosoma brucei, Plasmodium falciparum, Giardia lamblia, Leishmania mexicana, Trichomonas vaginalis, and Entamoeba histolytica.

RESULTS

TIM inhibitors showed mainly aromatic systems and symmetrical structure, where the size and type of heteroatom are important for enzyme inhibition. This inhibition is mainly based on the interaction with i) the interfacial region of TIM inducing changes on the quaternary and tertiary structure or ii) with the TIM catalytic region were the main pathways that disabled the catalytic activity of the enzyme.

CONCLUSION

Benzothiazole, benzoxazole, benzimidazole, and sulfhydryl derivatives stand out as TIM inhibitors. In silico and in vitro studies demonstrate that the inhibitors bind mainly at the TIM dimer interface. In this review, the development of new TIM inhibitors as antiprotozoal drugs is demonstrated as an important pharmaceutical strategy that may lead to new therapies for these ancient parasitic diseases.

Identification of known drugs as potential SARS-CoV-2 Mpro inhibitors using ligand- and structure-based virtual screening

Background: The new coronavirus pandemic has had a significant impact worldwide, and therapeutic treatment for this viral infection is being strongly pursued. Efforts have been undertaken by medicinal chemists to discover molecules or known drugs that may be effective in COVID-19 treatment – in particular, targeting the main protease (Mpro) of the virus. Materials & methods: We have employed an innovative strategy – application of ligand- and structure-based virtual screening – using a special compilation of an approved and diverse set of SARS-CoV-2 crystallographic complexes that was recently published. Results and conclusion: We identified seven drugs with different original indications that might act as potential Mpro inhibitors and may be preferable to other drugs that have been repurposed. These drugs will be experimentally tested to confirm their potential Mpro inhibition and thus their effectiveness against COVID-19.

Treasuring the computational approach in medicinal plant research

Medicinal plants serve as a valuable source of secondary metabolites since time immemorial. Computational Research in 21st century is giving more attention to medicinal plants for new drug design as pharmacological screening of bioactive compound was time consuming and expensive. Computational methods such as Molecular Docking, Molecular Dynamic Simulation and Artificial intelligence are significant Insilico tools in medicinal plant research. Molecular docking approach exploits the mechanism of potential phytochemicals into the target active site to elucidate its interactions and biological therapeutic properties. MD simulation illuminates the dynamic behavior of biomolecules at atomic level with fine quality representation of biomolecules. Dramatical advancement in computer science is illustrating the biological mechanism via these tools in different diseases treatment. The advancement comprises speed, the system configuration, and other software upgradation to insights into the structural explanation and optimization of biomolecules. A probable shift from simulation to artificial intelligence has in fact accelerated the art of scientific study to a sky high. The most upgraded algorithm in artificial intelligence such as Artificial Neural Networks, Deep Neural Networks, Neuro-fuzzy Logic has provided a wide opportunity in easing the time required in classical experimental strategy. The notable progress in computer science technology has paved a pathway for understanding the pharmacological functions and creating a roadmap for drug design and development and other achievement in the field of medicinal plants research. This review focus on the development and overview in computational research moving from static molecular docking method to a range of dynamic simulation and an advanced artificial intelligence such as machine learning.

Toward an Understanding of Pan-Assay Interference Compounds and Promiscuity: A Structural Perspective on Binding Modes

Pan-assay interference compounds (PAINS) are promiscuous compound classes that produce false positive hits in high-throughput screenings. Yet, the mechanisms of PAINS activity are poorly understood. Although PAINS are often associated with protein reactivity, several recent studies have shown that they also mediate noncovalent interactions. Aiming at a deep understanding of PAINS promiscuity, we performed an analysis of the Protein Data Bank to characterize the binding modes of PAINS. We explored the binding mode conservation of 34 PAINS classes present in 871 ligands and among 517 protein targets. The two major findings of this work are the following: First, different PAINS classes exhibit different levels of binding mode conservation. Our novel classification of PAINS based on binding mode similarity enables a rational assessment of PAINS from a structural perspective. Second, PAINS classes with variable binding modes can bind with high affinity. The evaluation of noncovalent binding modes of PAINS-like compounds sheds light on the mechanisms of promiscuous binding. Our findings could facilitate the decisions on how to deal with PAINS and help scientists to understand why PAINS produce hits in their screenings.

QSAR Modeling for Multi-Target Drug Discovery: Designing Simultaneous Inhibitors of Proteins in Diverse Pathogenic Parasites

Parasitic diseases remain as unresolved health issues worldwide. While for some parasites the treatments involve drug combinations with serious side effects, for others, chemical therapies are inefficient due to the emergence of drug resistance. This urges the search for novel antiparasitic agents able to act through multiple mechanisms of action. Here, we report the first multi-target model based on quantitative structure-activity relationships and a multilayer perceptron neural network (mt-QSAR-MLP) to virtually design and predict versatile inhibitors of proteins involved in the survival and/or infectivity of different pathogenic parasites. The mt-QSAR-MLP model exhibited high accuracy (>80%) in both training and test sets for the classification/prediction of protein inhibitors. Several fragments were directly extracted from the physicochemical and structural interpretations of the molecular descriptors in the mt-QSAR-MLP model. Such interpretations enabled the generation of four molecules that were predicted as multi-target inhibitors against at least three of the five parasitic proteins reported here with two of the molecules being predicted to inhibit all the proteins. Docking calculations converged with the mt-QSAR-MLP model regarding the multi-target profile of the designed molecules. The designed molecules exhibited drug-like properties, complying with Lipinski’s rule of five, as well as Ghose’s filter and Veber’s guidelines.

A dynamic simulation study of FDA drug from zinc database against COVID-19 main protease receptor

The sudden outbreak of COVID-19 has been responsible for several deaths across the globe. Due to its high contagious nature, it spreads from one human to another very quickly. Now it becomes a global public health threat with no approved treatments. In silico techniques can accelerate the drug development process. Our research aimed to identify the novel drugs for inhibition of Main protease (Mpro) enzyme of COVID-19 by performing in silico approach. In this context, a library consisting of 3180 FDA-approved drugs from ‘the ZINC database’ was used to identify novel drug candidates against ‘the Mpro’ of SARS-CoV-2. Initially, the top 10 drugs out of 3180 drugs were selected by molecular docking according to their binding score. Among 10 selected drugs; seven drugs that showed binding with Mpro enzyme residue Glu166 were subjected to100 ns Molecular dynamics (MD) simulation. Out of seven compounds, four namely, ZINC03831201, ZINC08101052, ZINC01482077, and ZINC03830817 were found significant based on MD simulation results. Furthermore, RMSD, RMSF, RG, SASA, PCA, MMPBSA (for last 40 ns) were calculated for the 100 ns trajectory period. Currently, the world needs potent drugs in a short period and this work suggests that these four drugs could be used as novel drugs against COVID-19 and it also provides new lead compounds for further in vitro, in vivo, and ongoing clinical studies against SARS-CoV-2.

Communicated by Ramaswamy H. Sarma

Computational Drug Repositioning for Chagas Disease Using Protein-Ligand Interaction Profiling

Chagas disease, caused by Trypanosoma cruzi (T. cruzi), affects nearly eight million people worldwide. There are currently only limited treatment options, which cause several side effects and have drug resistance. Thus, there is a great need for a novel, improved Chagas treatment. Bifunctional enzyme dihydrofolate reductase-thymidylate synthase (DHFR-TS) has emerged as a promising pharmacological target. Moreover, some human dihydrofolate reductase (HsDHFR) inhibitors such as trimetrexate also inhibit T. cruzi DHFR-TS (TcDHFR-TS). These compounds serve as a starting point and a reference in a screening campaign to search for new TcDHFR-TS inhibitors. In this paper, a novel virtual screening approach was developed that combines classical docking with protein-ligand interaction profiling to identify drug repositioning opportunities against T. cruzi infection. In this approach, some food and drug administration (FDA)-approved drugs that were predicted to bind with high affinity to TcDHFR-TS and whose predicted molecular interactions are conserved among known inhibitors were selected. Overall, ten putative TcDHFR-TS inhibitors were identified. These exhibited a similar interaction profile and a higher computed binding affinity, compared to trimetrexate. Nilotinib, glipizide, glyburide and gliquidone were tested on T. cruzi epimastigotes and showed growth inhibitory activity in the micromolar range. Therefore, these compounds could lead to the development of new treatment options for Chagas disease.

In Silico Drug Repositioning for Chagas Disease

Chagas disease is an infectious tropical disease included within the group of neglected tropical diseases. Though historically endemic to Latin America, it has lately spread to high-income countries due to human migration. At present, there are only two available drugs, nifurtimox and benznidazole, approved for this treatment, both with considerable side-effects (which often result in treatment interruption) and limited efficacy in the chronic stage of the disease in adults. Drug repositioning involves finding novel therapeutic indications for known drugs, including approved, withdrawn, abandoned and investigational drugs. It is today a broadly applied approach to develop innovative medications, since indication shifts are built on existing safety, ADME and manufacturing information, thus greatly shortening development timeframes. Drug repositioning has been signaled as a particularly interesting strategy to search for new therapeutic solutions for neglected and rare conditions, which traditionally present limited commercial interest and are mostly covered by the public sector and not-for-profit initiatives and organizations. Here, we review the applications of computer-aided technologies as systematic approaches to drug repositioning in the field of Chagas disease. In silico screening represents the most explored approach, whereas other rational methods such as network-based and signature-based approximations have still not been applied.

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.

Advances in Docking

BACKGROUND

Design of small molecules which are able to bind to the protein responsible for a disease is the key step of the entire process of the new medicine discovery. Atomistic computer modeling can significantly improve effectiveness of such design. The accurate calculation of the free energy of binding a small molecule (a ligand) to the target protein is the most important problem of such modeling. Docking is one of the most popular molecular modeling methods for finding ligand binding poses in the target protein and calculating the protein-ligand binding energy. This energy is used for finding the most active compounds for the given target protein. This short review aims to give a concise description of distinctive features of docking programs focusing on computation methods and approximations influencing their accuracy.

METHODS

This review is based on the peer-reviewed research literature including author's own publications. The main features of several representative docking programs are briefly described focusing on their characteristics influencing docking accuracy: force fields, energy calculations, solvent models, algorithms of the best ligand pose search, global and local optimizations, ligand and target protein flexibility, and the simplifications made for the docking accelerating. Apart from other recent reviews focused mainly on the performance of different docking programs, in this work, an attempt is made to extract the most important functional characteristics defining the docking accuracy. Also a roadmap for increasing the docking accuracy is proposed. This is based on the new generation of docking programs which have been realized recently. These programs and respective new global optimization algorithms are described shortly.

RESULTS

Several popular conventional docking programs are considered. Their search of the best ligand pose is based explicitly or implicitly on the global optimization problem. Several algorithms are used to solve this problem, and among them, the heuristic genetic algorithm is distinguished by its popularity and an elaborate design. All conventional docking programs for their acceleration use the preliminary calculated grids of protein-ligand interaction potentials or preferable points of protein and ligand conjugation. These approaches and commonly used fitting parameters restrict strongly the docking accuracy. Solvent is considered in exceedingly simplified approaches in the course of the global optimization and the search for the best ligand poses. More accurate approaches on the base of implicit solvent models are used frequently for more careful binding energy calculations after docking. The new generation of docking programs are developed recently. They find the spectrum of low energy minima of a protein-ligand complex including the global minimum. These programs should be more accurate because they do not use a preliminary calculated grid of protein-ligand interaction potentials and other simplifications, the energy of any conformation of the molecular system is calculated in the frame of a given force field and there are no fitting parameters. A new docking algorithm is developed and fulfilled specially for the new docking programs. This algorithm allows docking a flexible ligand into a flexible protein with several dozen mobile atoms on the base of the global energy minimum search. Such docking results in improving the accuracy of ligand positioning in the docking process. The adequate choice of the method of molecular energy calculations also results in the better docking positioning accuracy. An advancement in the application of quantum chemistry methods to docking and scoring is revealed.

CONCLUSION

The findings of this review confirm the great demand in docking programs for discovery of new medicine substances with the help of molecular modeling. New trends in docking programs design are revealed. These trends are focused on the increase of the docking accuracy at the expense of more accurate molecular energy calculations without any fitting parameters, including quantum-chemical methods and implicit solvent models, and by using new global optimization algorithms which make it possible to treat flexibility of ligands and mobility of protein atoms simultaneously. Finally, it is shown that all the necessary prerequisites for increasing the docking accuracy can be accomplished in practice.

Crystal violet structural analogues identified by in silico drug repositioning present anti-Trypanosoma cruzi activity through inhibition of proline transporter TcAAAP069

BACKGROUND

Crystal violet (CV) was used for several years in blood banks to eliminate the parasite Trypanosoma cruzi in endemic areas in order to prevent transfusion-transmitted Chagas disease. One mechanism of action described for CV involves inhibition of proline uptake. In T. cruzi, proline is essential for host cell infection and intracellular differentiation among other processes, and can be obtained through the proline permease TcAAAP069.

METHODOLOGY/PRINCIPAL FINDINGS

CV inhibited proline transporter TcAAAP069 and parasites overexpressing this permease were 47-fold more sensitive to this compound than control parasites. Using CV as reference molecule, loratadine, cyproheptadine, olanzapine and clofazimine were identified as structurally related compounds to CV (structural analogues) by in silico drug repurposing through a similarity-based virtual screening protocol. All these already-approved drugs for clinical use inhibited TcAAAP069 activity with different efficacies and also presented trypanocidal action in epimastigotes, trypomastigotes and amastigotes of the Y, CL Brener and Dm28c T. cruzi strains. Finally, a synergistic effect between benznidazole and the CV chemical analogues was evidenced by combination and dose-reduction indexes values in epimastigotes and trypomastigotes of the Y strain.

CONCLUSIONS/SIGNIFICANCE

Loratadine, cyproheptadine and clofazimine inhibit TcAAAP069 proline transporter and also present trypanocidal effect against all T. cruzi life stages in strains from three different DTUs. These CV structural analogues could be a starting point to design therapeutic alternatives to treat Chagas disease by finding new indications for old drugs. This approach, called drug repurposing is a recommended strategy by the World Health Organization to treat neglected diseases, like Chagas disease, and combination therapy may improve the possibility of success of repositioned drugs.

The Thiol-polyamine Metabolism of Trypanosoma cruzi: Molecular Targets and Drug Repurposing Strategies

Chagas´ disease continues to be a challenging and neglected public health problem in many American countries. The etiologic agent, Trypanosoma cruzi, develops intracellularly in the mammalian host, which hinders treatment efficacy. Progress in the knowledge of parasite biology and host-pathogen interaction has not been paralleled by the development of novel, safe and effective therapeutic options. It is then urgent to seek for novel therapeutic candidates and to implement drug discovery strategies that may accelerate the discovery process. The most appealing targets for pharmacological intervention are those essential for the pathogen and, whenever possible, absent or significantly different from the host homolog. The thiol-polyamine metabolism of T. cruzi offers interesting candidates for a rational design of selective drugs. In this respect, here we critically review the state of the art of the thiolpolyamine metabolism of T. cruzi and the pharmacological potential of its components. On the other hand, drug repurposing emerged as a valid strategy to identify new biological activities for drugs in clinical use, while significantly shortening the long time and high cost associated with de novo drug discovery approaches. Thus, we also discuss the different drug repurposing strategies available with a special emphasis in their applications to the identification of drug candidates targeting essential components of the thiol-polyamine metabolism of T. cruzi.

Current advances in drug discovery for Chagas disease

Chagas disease, also known as American trypanosomiasis, is one of the 17 neglected tropical diseases (NTDs) according to World Health Organization. It is estimated that 8-10 million people are infected worldwide, mainly in Latin America. Chagas disease is caused by the parasite Trypanosoma cruzi and is characterized by two phases: acute and chronic. The current therapy for Chagas disease is limited to drugs such as nifurtimox and benznidazole, which are effective in treating only the acute phase of the disease. In addition, several side effects ranging from hypersensitivity to bone marrow depression and peripheral polyneuropathy have been associated with these drugs. Therefore, the current challenge is to find new effective and safe drugs against this NTD. The aim of this review is to describe the advances in the medicinal chemistry of new anti-chagasic compounds reported in the literature in the last five years. We report promising prototypes for drug discovery identified through target-based and phenotype-based strategies and present some important targets for the development of new synthetic compounds.

Repositioning of Omarigliptin as a once-weekly intranasal Anti-parkinsonian Agent

Drug repositioning is a revolution breakthrough of drug discovery that presents outstanding privilege with already safer agents by scanning the existing candidates as therapeutic switching or repurposing for marketed drugs. Sitagliptin, vildagliptin, saxagliptin & linagliptin showed antioxidant and neurorestorative effects in previous studies linked to DPP-4 inhibition. Literature showed that gliptins did not cross the blood brain barrier (BBB) while omarigliptin was the first gliptin that crossed it successfully in the present work. LC-MS/MS determination of once-weekly anti-diabetic DPP-4 inhibitors; omarigliptin & trelagliptin in plasma and brain tissue was employed after 2 h of oral administration to rats. The brain/plasma concentration ratio was used to deduce the penetration power through the BBB. Results showed that only omarigliptin crossed the BBB due to its low molecular weight & lipophilic properties suggesting its repositioning as antiparkinsonian agent. The results of BBB crossing will be of interest for researchers interested in Parkinson's disease. A novel intranasal formulation was developed using sodium lauryl sulphate surfactant to solubilize the lipophilic omarigliptin with penetration enhancing & antimicrobial properties. Intranasal administration showed enhanced brain/plasma ratio by 3.3 folds compared to the oral group accompanied with 2.6 folds increase in brain glucagon-like peptide-1 concentration compared to the control group.

Computational Methods to Discover Compounds for the Treatment of Chagas Disease

Infectious diseases continue to be a major public health. Among these diseases, American trypanosomiasis or Chagas disease (CD) is a major cause of morbidity and death for millions of people in Latin America. The two drugs currently available for the treatment of CD have poor efficacy and major side effects. Thus, there is a pressing need to develop safe and effective drugs against this disease. Herein we review the diversity and coverage of chemical space of compounds tested as inhibitors of Trypanosoma cruzi, a parasite causing CD. We also review major molecular targets currently pursued to kill the parasite and recent computational approaches to identify inhibitors for such targets.