Brazilian malaria molecular targets (BraMMT): selected receptors for virtual high-throughput screening experiments

Rational-Based Discovery of Novel β-Carboline Derivatives as Potential Antimalarials: From In Silico Identification of Novel Targets to Inhibition of Experimental Cerebral Malaria

Malaria is an infectious disease widespread in underdeveloped tropical regions. The most severe form of infection is caused by Plasmodium falciparum, which can lead to development of cerebral malaria (CM) and is responsible for deaths and significant neurocognitive sequelae throughout life. In this context and considering the emergence and spread of drug-resistant P. falciparum isolates, the search for new antimalarial candidates becomes urgent. β-carbolines alkaloids are good candidates since a wide range of biological activity for these compounds has been reported. Herein, we designed 20 chemical entities and performed an in silico virtual screening against a pool of P. falciparum molecular targets, the Brazilian Malaria Molecular Targets (BRAMMT). Seven structures showed potential to interact with PfFNR, PfPK7, PfGrx1, and PfATP6, being synthesized and evaluated for in vitro antiplasmodial activity. Among them, compounds 3−6 and 10 inhibited the growth of the W2 strain at µM concentrations, with low cytotoxicity against the human cell line. In silico physicochemical and pharmacokinetic properties were found to be favorable for oral administration. The compound 10 provided the best results against CM, with important values of parasite growth inhibition on the 5th day post-infection for both curative (67.9%) and suppressive (82%) assays. Furthermore, this compound was able to elongate mice survival and protect them against the development of the experimental model of CM (>65%). Compound 10 also induced reduction of the NO level, possibly by interaction with iNOS. Therefore, this alkaloid showed promising activity for the treatment of malaria and was able to prevent the development of experimental cerebral malaria (ECM), probably by reducing NO synthesis.

In vitro and in silico assessment of new beta amino ketones with antiplasmodial activity

BACKGROUND

Based on the current need for new drugs against malaria, our study evaluated eight beta amino ketones in silico and in vitro for potential antimalarial activity.

METHODS

Using the Brazilian Malaria Molecular Targets (BraMMT) and OCTOPUS® software programs, the pattern of interactions of beta-amino ketones was described against different proteins of P. falciparum and screened to evaluate their physicochemical properties. The in vitro antiplasmodial activities of the compounds were evaluated using a SYBR Green-based assay. In parallel, in vitro cytotoxic data were obtained using the MTT assay.

RESULTS

Among the eight compounds, compound 1 was the most active and selective against P. falciparum (IC50 = 0.98 µM; SI > 60). Six targets were identified in BraMMT that interact with compounds exhibiting a stronger binding energy than the crystallographic ligand: P. falciparum triophosphate phosphoglycolate complex (1LYX), P. falciparum reductase (2OK8), PfPK7 (2PML), P. falciparum glutaredoxin (4N0Z), PfATP6, and PfHT.

CONCLUSIONS

The physicochemical properties of compound 1 were compatible with the set of criteria established by the Lipinski rule and demonstrated its potential as a drug prototype for antiplasmodial activity.

Antimicrobial activity of clioquinol and nitroxoline: a scoping review

Clioquinol and nitroxoline, two drugs with numerous pharmacological properties fallen into disuse for many decades. The first was considered dangerous due to contraindications and the second mainly because was taken as ineffective, despite its known antibacterial activity. In the last decades, the advances in pharmaceutical chemistry, molecular biology, toxicology and genetics allowed to better understand the cellular action of these compounds, some toxicological issues and/or activity scopes. Thus, a new opportunity for these drugs to be considered as potential antimicrobial agents has arisen. This review contemplates the trajectory of clioquinol and nitroxoline from their emergence to the present day, emphasizing the new studies that indicate the possibility of reintroduction for specific cases.

Evaluation of antiplasmodial activity in silico and in vitro of N-acylhydrazone derivatives

N-acylhydrazones are considered privileged structures in medicinal chemistry, being part of antimicrobial compounds (for example). In this study we show the activity of N-acylhydrazone compounds, namely AH1, AH2, AH4, AH5 in in vitro tests against the chloroquine-resistant strain of Plasmodium falciparum (W2) and against WI26 VA-4 human cell lines. All compounds showed low cytotoxicity (LC₅₀ > 100 µM). The AH5 compound was the most active against Plasmodium falciparum, with an IC₅₀ value of 0.07 μM. AH4 and AH5 were selected among the tested compounds for molecular docking calculations to elucidate possible targets involved in their mechanism of action and the SwissADME analysis to predict their pharmacokinetic profile. The AH5 compound showed affinity for 12 targets with low selectivity, while the AH4 compound had greater affinity for only one target (3PHC). These compounds met Lipinski's standards in the ADME in silico tests, indicating good bioavailability results. These results demonstrate that these N-acylhydrazone compounds are good candidates for future preclinical studies against malaria.

Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.

Dehydrobufotenin extracted from the Amazonian toad Rhinella marina (Anura: Bufonidae) as a prototype molecule for the development of antiplasmodial drugs

Background:

The resistance against antimalarial drugs represents a global challenge in the fight and control of malaria. The Brazilian biodiversity can be an important tool for research and development of new medicinal products. In this context, toxinology is a multidisciplinary approach on the development of new drugs, including the isolation, purification, and evaluation of the pharmacological activities of natural toxins. The present study aimed to evaluate the cytotoxicity, as well as the antimalarial activity in silico and in vitro of four compounds isolated from Rhinella marina venom as potential oral drug prototypes.

Methods:

Four compounds were challenged against 35 target proteins from P. falciparum and screened to evaluate their physicochemical properties using docking assay in Brazilian Malaria Molecular Targets (BraMMT) software and in silico assay in OCTOPUS® software. The in vitro antimalarial activity of the compounds against the 3D7 Plasmodium falciparum clones were assessed using the SYBR Green I based assay (IC₅₀). For the cytotoxic tests, the LD₅₀ was determined in human pulmonary fibroblast cell line using the [3(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] (MTT) assay.

Results:

All compounds presented a ligand-receptor interaction with ten Plasmodium falciparum-related protein targets, as well as antimalarial activity against chloroquine resistant strain (IC₅₀ = 3.44 μM to 19.11 μM). Three of them (dehydrobufotenine, marinobufagin, and bufalin) showed adequate conditions for oral drug prototypes, with satisfactory prediction of absorption, permeability, and absence of toxicity. In the cell viability assay, only dehydrobufotenin was selective for the parasite.

Conclusions:

Dehydrobufotenin revealed to be a potential oral drug prototype presenting adequate antimalarial activity and absence of cytotoxicity, therefore should be subjected to further studies.

Uncovering New Drug Properties in Target-Based Drug-Drug Similarity Networks

Despite recent advances in bioinformatics, systems biology, and machine learning, the accurate prediction of drug properties remains an open problem. Indeed, because the biological environment is a complex system, the traditional approach—based on knowledge about the chemical structures—can not fully explain the nature of interactions between drugs and biological targets. Consequently, in this paper, we propose an unsupervised machine learning approach that uses the information we know about drug–target interactions to infer drug properties. To this end, we define drug similarity based on drug–target interactions and build a weighted Drug–Drug Similarity Network according to the drug–drug similarity relationships. Using an energy-model network layout, we generate drug communities associated with specific, dominant drug properties. DrugBank confirms the properties of 59.52% of the drugs in these communities, and 26.98% are existing drug repositioning hints we reconstruct with our DDSN approach. The remaining 13.49% of the drugs seem not to match the dominant pharmacologic property; thus, we consider them potential drug repurposing hints. The resources required to test all these repurposing hints are considerable. Therefore we introduce a mechanism of prioritization based on the betweenness/degree node centrality. Using betweenness/degree as an indicator of drug repurposing potential, we select Azelaic acid and Meprobamate as a possible antineoplastic and antifungal, respectively. Finally, we use a test procedure based on molecular docking to analyze Azelaic acid and Meprobamate’s repurposing.

In silico tools to study molecular targets of neglected diseases: inhibition of TcSir2rp3, an epigenetic enzyme of Trypanosoma cruzi

There is a growing interest to study and address neglected tropical diseases (NTD). To this end, in silico methods can serve as the bridge that connects academy and industry, encouraging the development of future treatments against these diseases. This chapter discusses current challenges in the development of new therapies, available computational methods and successful cases in computer-aided design with particular focus on human trypanosomiasis. Novel targets are also discussed. As a case study, we identify amentoflavone as a potential inhibitor of TcSir2rp3 (sirtuine) from Trypanosoma cruzi (20.03 μM) with a workflow that integrates chemoinformatic approaches, molecular modeling, and theoretical affinity calculations, as well as in vitro assays.

Structure-Based Virtual Screening: From Classical to Artificial Intelligence

The drug development process is a major challenge in the pharmaceutical industry since it takes a substantial amount of time and money to move through all the phases of developing of a new drug. One extensively used method to minimize the cost and time for the drug development process is computer-aided drug design (CADD). CADD allows better focusing on experiments, which can reduce the time and cost involved in researching new drugs. In this context, structure-based virtual screening (SBVS) is robust and useful and is one of the most promising in silico techniques for drug design. SBVS attempts to predict the best interaction mode between two molecules to form a stable complex, and it uses scoring functions to estimate the force of non-covalent interactions between a ligand and molecular target. Thus, scoring functions are the main reason for the success or failure of SBVS software. Many software programs are used to perform SBVS, and since they use different algorithms, it is possible to obtain different results from different software using the same input. In the last decade, a new technique of SBVS called consensus virtual screening (CVS) has been used in some studies to increase the accuracy of SBVS and to reduce the false positives obtained in these experiments. An indispensable condition to be able to utilize SBVS is the availability of a 3D structure of the target protein. Some virtual databases, such as the Protein Data Bank, have been created to store the 3D structures of molecules. However, sometimes it is not possible to experimentally obtain the 3D structure. In this situation, the homology modeling methodology allows the prediction of the 3D structure of a protein from its amino acid sequence. This review presents an overview of the challenges involved in the use of CADD to perform SBVS, the areas where CADD tools support SBVS, a comparison between the most commonly used tools, and the techniques currently used in an attempt to reduce the time and cost in the drug development process. Finally, the final considerations demonstrate the importance of using SBVS in the drug development process.

Molecular Architect: A User-Friendly Workflow for Virtual Screening

Computer-assisted drug design (CADD) methods have greatly contributed to the development of new drugs. Among CADD methodologies, virtual screening (VS) can enrich the compound collection with molecules that have the desired physicochemical and pharmacophoric characteristics that are needed to become drugs. Many free tools are available for this purpose, but they are difficult to use and do not have a graphical user interface. Furthermore, several free tools must be used to carry out the entire VS process, requiring the user to process the results of one software program so that they can be used in another program, adding a potential source of human error. Moreover, some software programs require knowledge of advanced computational skills, such as programming languages. This context has motivated us to develop Molecular Architect (MolAr). MolAr is a workflow with a simple and intuitive interface that acts in an integrated and automated form to perform the entire VS process, from protein preparation (homology modeling and protonation state) to virtual screening. MolAr carries out VS through AutoDock Vina, DOCK 6, or a consensus of the two. Two case studies were conducted to demonstrate the performance of MolAr. In the first study, the feasibility of using MolAr for DNA-ligand systems was assessed. Both AutoDock Vina and DOCK 6 showed good results in performing VS in DNA-ligand systems. However, the use of consensus virtual screening was able to enrich the results. According to the area under the ROC curve and the enrichment factors, consensus VS was better able to predict the positions of the active ligands. The second case study was performed on 8 targets from the DUD-E database and 10 active ligands for each target. The results demonstrated that using the final ligand conformation provided by AutoDock Vina as an input for DOCK 6 improved the DOCK 6 ROC curves by up to 42% in VS. These case studies demonstrated that MolAr is capable conducting the VS process and is an easy-to-use and effective tool. MolAr is available for download free of charge at http: //www.drugdiscovery.com.br/software/.