Chemoinformatics Strategies for Leishmaniasis Drug Discovery

A QSAR Study for Antileishmanial 2-Phenyl-2,3-dihydrobenzofurans †

Leishmaniasis, a parasitic disease that represents a threat to the life of millions of people around the globe, is currently lacking effective treatments. We have previously reported on the antileishmanial activity of a series of synthetic 2-phenyl-2,3-dihydrobenzofurans and some qualitative structure-activity relationships within this set of neolignan analogues. Therefore, in the present study, various quantitative structure-activity relationship (QSAR) models were created to explain and predict the antileishmanial activity of these compounds. Comparing the performance of QSAR models based on molecular descriptors and multiple linear regression, random forest, and support vector regression with models based on 3D molecular structures and their interaction fields (MIFs) with partial least squares regression, it turned out that the latter (i.e., 3D-QSAR models) were clearly superior to the former. MIF analysis for the best-performing and statistically most robust 3D-QSAR model revealed the most important structural features required for antileishmanial activity. Thus, this model can guide decision-making during further development by predicting the activity of potentially new leishmanicidal dihydrobenzofurans before synthesis.

A review on new natural and synthetic anti-leishmanial chemotherapeutic agents and current perspective of treatment approaches

Leishmaniases are considered among the most neglected yet dangerous parasitic diseases worldwide. According to the recent WHO report (Weekly Epidemiological Record, Sep, 2021), 200 countries and territories reported leishmanises cases in 2020; of which 89 (45%) for CL, and 79 (40%) for VL were endemic. Indian subcontinent (India, Bangladesh and Nepal), one of the three eco-epidemiological hotspots of VL, currently reported 18% of the total cases of VL worldwide. Eastern Mediterranean region and the Region of the Americas together reported >90% of the new CL cases, of which >80% were from Afghanistan, Algeria, Brazil, Colombia, Iraq, Pakistan and the Syrian Arab Republic. While considering the current therapeutic options, conventional anti-leishmanial drugs have long been proved to be toxic and/or expensive and have resulted in extensive drug resistance in India. Recent searches for novel anti-leishmanial drugs have led to find out the prime cellular targets and metabolic pathways to bridge the gap between the known facts and unexplored data. Cutting edge knowledge based drug designing has simplified the search for novel molecules with leishmanicidal efficacy by identifying ligand-receptor interactions and has accelerated the cost effective primary discovery of molecules through computational validation against Leishmaniases. This review focuses on the limitations of conventional drugs, and discusses the chemotherapeutic potential of many novel natural and synthetic anti-leishmanial agents reported since the last decade. It is also interpreted that some of the reported molecules might be tested singly or as a part of combinatorial therapy on pre-clinical and clinical level.

Development of Novel Anti-Leishmanials: The Case for Structure-Based Approaches

The neglected tropical disease (NTD) leishmaniasis is the collective name given to a diverse group of illnesses caused by ~20 species belonging to the genus Leishmania, a majority of which are vector borne and associated with complex life cycles that cause immense health, social, and economic burdens locally, but individually are not a major global health priority. Therapeutic approaches against leishmaniasis have various inadequacies including drug resistance and a lack of effective control and eradication of the disease spread. Therefore, the development of a rationale-driven, target based approaches towards novel therapeutics against leishmaniasis is an emergent need. The utilization of Artificial Intelligence/Machine Learning methods, which have made significant advances in drug discovery applications, would benefit the discovery process. In this review, following a summary of the disease epidemiology and available therapies, we consider three important leishmanial metabolic pathways that can be attractive targets for a structure-based drug discovery approach towards the development of novel anti-leishmanials. The folate biosynthesis pathway is critical, as Leishmania is auxotrophic for folates that are essential in many metabolic pathways. Leishmania can not synthesize purines de novo, and salvage them from the host, making the purine salvage pathway an attractive target for novel therapeutics. Leishmania also possesses an organelle glycosome, evolutionarily related to peroxisomes of higher eukaryotes, which is essential for the survival of the parasite. Research towards therapeutics is underway against enzymes from the first two pathways, while the third is as yet unexplored.

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.

Colombian Contributions Fighting Leishmaniasis: A Systematic Review on Antileishmanials Combined with Chemoinformatics Analysis

Leishmaniasis is a parasitic morbid/fatal disease caused by Leishmania protozoa. Twelve million people worldwide are appraised to be currently infected, including ca. two million infections each year, and 350 million people in 88 countries are at risk of becoming infected. In Colombia, cutaneous leishmaniasis (CL) is a public health problem in some tropical areas. Therapeutics is based on traditional antileishmanial drugs, but this practice has several drawbacks for patients. Thus, the search for new antileishmanial agents is a serious need, but the lack of adequately funded research programs on drug discovery has hampered its progress. Some Colombian researchers have conducted different research projects focused on the assessment of the antileishmanial activity of naturally occurring and synthetic compounds against promastigotes and/or amastigotes. Results of such studies have separately demonstrated important hits and reasonable potential, but a holistic view of them is lacking. Hence, we present the outcome from a systematic review of the literature (under PRISMA guidelines) on those Colombian studies investigating antileishmanials during the last thirty-two years. In order to combine the general efforts aiming at finding a lead against Leishmania panamensis (one of the most studied and incident parasites in Colombia causing CL) and to recognize structural features of representative compounds, fingerprint-based analyses using conventional machine learning algorithms and clustering methods are shown. Abstraction from such a meta-description led to describe some function-determining molecular features and simplify the clustering of plausible isofunctional hits. This systematic review indicated that the Colombian efforts for the antileishmanials discovery are increasingly intensified, though improvements in the followed pathways must be definitively pursued. In this context, a brief discussion about scope, strengths and limitations of such advances and relationships is addressed.

Virtual Screening and the In Vitro Assessment of the Antileishmanial Activity of Lignans

Leishmaniasis is endemic in at least 98 countries. Due to the high toxicity and resistance associated with the drugs, we chose lignans as an alternative, due to their favorable properties of absorption, distribution, metabolism, excretion, and toxicity (ADMET). To investigate their leishmanicidal potential, the biological activities of a set of 160 lignans were predicted using predictive models that were built using data for Leishmania major and L. (Viannia) braziliensis. A combined analysis, based on ligand and structure, and several other computational approaches were used. The results showed that the combined analysis was able to select 11 lignans with potential activity against L. major and 21 lignans against L. braziliensis, with multitargeting effects and low or no toxicity. Of these compounds, four were isolated from the species Justicia aequilabris (Nees) Lindau. All of the identified compounds were able to inhibit the growth of L. braziliensis promastigotes, with the most active compound, (159) epipinoresinol-4-O-β-d-glucopyranoside, presenting an IC₅₀ value of 5.39 µM and IC₅₀ value of 36.51 µM for L. major. Our findings indicated the potential of computer-aided drug design and development and demonstrated that lignans represent promising prototype compounds for the development of multitarget drugs against leishmaniasis.

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.

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.