In silico drug design strategies for discovering novel tuberculosis therapeutics.

INTRODUCTION: Tuberculosis remains a significant concern in global public health due to its intricate biology and propensity for developing antibiotic resistance. Discovering new drugs is a protracted and expensive endeavor, often spanning over a decade and incurring costs in the billions. However, computer-aided drug design (CADD) has surfaced as a nimbler and more cost-effective alternative. CADD tools enable us to decipher the interactions between therapeutic targets and novel drugs, making them invaluable in the quest for new tuberculosis treatments. AREAS COVERED: In this review, the authors explore recent advancements in tuberculosis drug discovery enabled by in silico tools. The main objectives of this review article are to highlight emerging drug candidates identified through in silico methods and to provide an update on the therapeutic targets associated with Mycobacterium tuberculosis. EXPERT OPINION: These in silico methods have not only streamlined the drug discovery process but also opened up new horizons for finding novel drug candidates and repositioning existing ones. The continued advancements in these fields hold great promise for more efficient, ethical, and successful drug development in the future.

Estudo estrutural e comparativo entre Sirtuínas 2 de diferentes espécies de Leishmania / Structural and comparative study between Sirtuins 2 of different species of Leishmania by means of Comparative Modeling and Molecular Dynamic

As leishmanioses são doenças negligenciadas que afetam mais de um bilhão e meio de pessoas ao redor do mundo, principalmente nos países em desenvolvimento, provocando grandes impactos socioeconômicos. Os fármacos disponíveis para o tratamento dessas doenças são ineficazes e apresentam graves efeitos adversos. O processo de pesquisa de novos fármacos envolve, entre outras coisas, a seleção de alvos bioquímicos essenciais para a sobrevivência e desenvolvimento do agente causador. Neste sentido, a Sirtuína 2, uma enzima epigenética com atividade hidrolase essencial para a sobrevivência dos parasitas do gênero Leishmania se apresenta como um alvo validado na busca de novos fármacos contra essas parasitoses. O planejamento de fármacos baseado na estrutura do receptor requer o conhecimento da estrutura tridimensional da proteína alvo. Desta forma, a elucidação estrutural e um estudo minucioso das Sirtuínas das várias espécies do gênero Leishmania apresenta-se como uma importante abordagem na aplicação desta estratégia na busca por agentes quimioterápicos. Até o momento, na família Trypanosomatidae, a única estrutura tridimensional resolvida experimentalmente de uma enzima Sirtuína 2 é a da espécie L. infantum. Assim, este trabalho aplicou a abordagem de Modelagem Comparativa utilizando o software Modeller na construção de modelos da Sir2rp1 das espécies L. infantum, L. major e L. braziliensis, cujas sequências de aminoácidos foram extraídas do banco de dados UNIProt. Os modelos construídos foram validados por meio da função de escore DOPE do Modeller e dos servidores PROCHECK, MolProbity e QMEAN, avaliando sua qualidade estereoquímica e seu enovelamento. Os ligantes naturais da enzima foram sobrepostos nos modelos construídos por alinhamento estrutural utilizando o software PyMol e os complexos validados foram submetidos a simulações de Dinâmica Molecular através do pacote GROMACS. Os complexos refinados foram então analisados por meio dos softwares PyMol e LigPlotPlus e dos pacotes GROMACS e gmx_MMPBSA, e foram estudados os sítios de ligação dos substratos e os resíduos de aminoácidos relevantes envolvidos em sua ligação e reconhecimento. A Modelagem Comparativa da Sirtuína 2 humana e seus homólogos das espécies L. infantum, L. major e L. braziliensis, as simulações de Dinâmica Molecular realizadas com os modelos enzimáticos construídos e validados complexados com seus ligantes naturais, os cálculos de energia de interação entre os modelos e seus substratos e o estudo estrutural comparativo realizado entre eles nos fornecem uma base teórica para a busca de novos inibidores da Sirtuína 2 que sejam mais seletivos e potentes contra as enzimas parasitárias, abrindo caminho para o desenvolvimento de candidatos a fármacos leishmanicidas mais seguros e eficazes

Leishmaniasis are neglected diseases that affect more than one and a half billion people around the world, mainly in developing countries, causing major socioeconomic impacts. The drugs available for the treatment of these diseases are ineffective and have serious adverse effects. The process of researching new drugs involves, among other things, the selection of biochemical targets essential for the survival and development of the causative agent. In this sense, Sirtuin 2, an epigenetic enzyme with hydrolase activity essential for the survival of parasites of the Leishmania genus, presents itself as a validated target in the search for new drugs against these parasites. Structure-Based Drug Design requires knowledge of the three-dimensional structure of the target protein. In this way, structural elucidation and a detailed study of Sirtuins from various species of the genus Leishmania presents itself as an important approach in the application of this strategy in the search for chemotherapeutic agents. To date, in the Trypanosomatidae family, the only experimentally resolved three-dimensional structure of a Sirtuin 2 enzyme is that of the species L. infantum. Thus, this work applied the Comparative Modeling approach using the Modeller software in the construction of Sir2rp1 models of the species L. infantum, L. major and L. braziliensis, whose amino acid sequences were retrieved from the UNIProt database. The constructed models were validated using Modeller's DOPE score function and the PROCHECK, MolProbity and QMEAN servers, evaluating their stereochemical quality and folding. The enzyme's natural ligands were superimposed on the built models by structural alignment using the PyMol software and the validated complexes were subjected to Molecular Dynamics simulations using the GROMACS package. The refined complexes were then analyzed using the PyMol and LigPlotPlus softwares and the GROMACS and gmx_MMPBSA packages, and the substrate binding sites and relevant amino acid residues involved in their binding and recognition were studied. The Comparative Modeling of human Sirtuin 2 and its homologues from the species L. infantum, L. major and L. braziliensis, the Molecular Dynamics simulations carried out with the constructed and validated enzymatic models complexed with their natural ligands, the interaction energy calculations between the models and their substrates and the comparative structural study carried out between them provide us with a theoretical basis for the search for new Sirtuin 2 inhibitors that are more selective and potent against the parasitic enzymes, paving the way for the development of safer and more effective leishmanicidal drug candidates

Molecular Targets for Chalcones in Antileishmanial Drug Discovery.

Leishmaniases are infectious diseases caused by flagellated protozoan parasites belonging to the genus Leishmania that infect cells of the mononuclear phagocytic system. These parasites are transmitted to humans by biting an infected female sandfly belonging to the genera Phlebotomus in the Old World and Lutzomyia in the New World. Despite representing a major public health problem, the therapeutic options are old and have several disadvantages. Given this scenario, developing vaccines or drugs for oral administration is necessary. Therefore, integrating computational and experimental strategies into the studies on molecular targets essential for the survival and virulence of the parasite is fundamental in researching and developing new treatments for leishmaniasis. In the effort to develop new vaccines and drugs, molecular docking methods are widely used as they explore the adopted conformations of small molecules within the binding sites of macromolecular targets and estimate the free energy of target-ligand binding. Privileged structures have been widely used as an effective model in medicinal chemistry for drug discovery. Chalcones are a common simple scaffold found in many compounds of natural and synthetic origin, where studies demonstrate the great pharmacological potential in treating leishmaniasis. This review is based on scientific articles published in the last ten years on molecular docking of chalcone derivatives for essential molecular targets of Leishmania. Thus, this review emphasizes how versatile chalcone derivatives can be used in developing new inhibitors of important molecular targets involved in the survival, growth, cell differentiation, and infectivity of the parasites that cause leishmaniasis.

Computational Design of Inhibitors Targeting the Catalytic ß Subunit of Escherichia coli FOF1-ATP Synthase.

With the uncontrolled growth of multidrug-resistant bacteria, there is an urgent need to search for new therapeutic targets, to develop drugs with novel modes of bactericidal action. FoF1-ATP synthase plays a crucial role in bacterial bioenergetic processes, and it has emerged as an attractive antimicrobial target, validated by the pharmaceutical approval of an inhibitor to treat multidrug-resistant tuberculosis. In this work, we aimed to design, through two types of in silico strategies, new allosteric inhibitors of the ATP synthase, by targeting the catalytic ß subunit, a centerpiece in communication between rotor subunits and catalytic sites, to drive the rotary mechanism. As a model system, we used the F1 sector of Escherichia coli, a bacterium included in the priority list of multidrug-resistant pathogens. Drug-like molecules and an IF1-derived peptide, designed through molecular dynamics simulations and sequence mining approaches, respectively, exhibited in vitro micromolar inhibitor potency against F1. An analysis of bacterial and Mammalia sequences of the key structural helix-turn-turn motif of the C-terminal domain of the ß subunit revealed highly and moderately conserved positions that could be exploited for the development of new species-specific allosteric inhibitors. To our knowledge, these inhibitors are the first binders computationally designed against the catalytic subunit of FOF1-ATP synthase.

Analysis of a novel class A β-lactamase OKP-B-6 of Klebsiella quasipneumoniae: structural characterisation and interaction with commercially available drugs

BACKGROUND Gram-negative and Gram-positive bacteria produce beta-lactamase as factors to overcome beta-lactam antibiotics, causing their hydrolysis and impaired antimicrobial action. Class A beta-lactamase contains the chromosomal sulfhydryl reagent variable (SHV, point mutation variants of SHV-1), LEN (Klebsiella pneumoniae strain LEN-1), and other K. pneumoniae beta-lactamase (OKP) found mostly in Klebsiella's phylogroups. The SHV known as extended-spectrum β-lactamase can inactivate most beta-lactam antibiotics. Class A also includes the worrisome plasmid-encoded Klebsiella pneumoniae carbapenemase (KPC-2), a carbapenemase that can inactivate most beta-lactam antibiotics, carbapenems, and some beta-lactamase inhibitors. OBJECTIVES So far, there is no 3D crystal structure for OKP-B, so our goal was to perform structural characterisation and molecular docking studies of this new enzyme. METHODS We applied a homology modelling method to build the OKP-B-6 structure, which was compared with SHV-1 and KPC-2 according to their electrostatic potentials at the active site. Using the DockThor-VS, we performed molecular docking of the SHV-1 inhibitors commercially available as sulbactam, tazobactam, and avibactam against the constructed model of OKP-B-6. FINDINGS From the point of view of enzyme inhibition, our results indicate that OKP-B-6 should be an extended-spectrum beta-lactamase (ESBL) susceptible to the same drugs as SHV-1. MAIN CONCLUSIONS This conclusion advantageously impacts the clinical control of the bacterial pathogens encoding OKP-B in their genome by using any effective, broad-spectrum, and multitarget inhibitor against SHV-containing bacteria.

Recent Studies on Neglected Drug Design.

BACKGROUND: Neglected diseases require special attention when looking for new therapeutic alternatives, as these are diseases of extreme complexity and severity that affect populations belonging to lower social classes who lack access to basic rights, such as sanitation. INTRODUCTION: Among the alternatives available for obtaining new drugs is Medicinal Chemistry, which is responsible for the discovery, identification, invention, and preparation of prototypes. In this perspective, the present work aims to make a bibliographic review on the recent studies of Medicinal Chemistry applied to neglected diseases. METHODS: A literature review was carried out by searching the "Web of Sciences" database, including recent articles published on the Neglected Drug Design. RESULTS: In general, it was noticed that the most studied neglected diseases corresponded to Chagas disease and leishmaniasis, with studies on organic synthesis, optimization of structures, and molecular hybrids being the most used strategies. It is also worth mentioning the growing number of computationally developed studies, providing speed and optimization of costs in the procurement process. CONCLUSION: The CADD approach and organic synthesis studies, when applied in the area of Medicinal Chemistry, have proven to be important in the research and discovery of drugs for Neglected Diseases, both in terms of planning the experimental methodology used to obtain it and in the selection of compounds with higher activity potential.

Structure determination and analyses of the GAPDH from the parasite Schistosoma mansoni, the first one from a platyhelminth.

The enzyme Glyceraldehyde-3-Phosphate Dehydrogenase from Schistosoma mansoni (SmGAPDH) is characterized as a therapeutical target for schistosomiasis. In this context, we report here the experimental structure, structural analyses and comparisons of SmGAPDH, the first one from a Platyhelminth. The enzyme was expressed, purified and assayed for crystallization, what allowed the obtainment of crystals of sufficient quality to collect X-ray diffraction data up to 2.51 Å resolution. SmGAPDH is the only GAPDH to present the sequence NNR (its residues 114-116) which leads to (especially R116) a hydrogen bond network that possibly reflects on the flexibility of residues to interact with the adenine part of NAD+, speculated to be important for differential drug design.

Insights into Newly Approved Drugs from a Medicinal Chemistry Perspective.

The development of new drugs is becoming notably harder each decade. To overcome the present pitfalls in the drug development pipeline, such as those related to potency, selectivity, or absorption, distribution, metabolism, excretion and toxicity properties, medicinal chemistry strategies need to be in continuous evolution and need to become even more multidisciplinary. In this review, we present how structure-based, ligand-based, and fragment-based drug design (SBDD, LBDD, and FBDD, respectively) and their respective techniques were used for the design and optimization of successful cases of New Molecular Entities (NMEs) approved by the Food and Drug Administration (FDA).

Planning new Trypanosoma cruzi CYP51 inhibitors using QSAR studies.

Chagas disease kills over 10,000 people per year, and approximately 8 million people are infected by Trypanosoma cruzi. The reference drug for treatment of the disease, benznidazole, is the same since the 70s. In recent years, many CYP51 inhibitors were tested against this parasite's target. One of them, posaconazole, was even tested in clinical trials that unfortunately were not successful. Nevertheless, there are still many evidences that CYP51 is a great potential target to treat T. cruzi infection. The research for new effective molecules that can cure the chronic phase of the disease is essential. 2D and 3D-quantitative structure activity relationship (QSAR) studies were conducted in this work to create three QSAR models using the chemical structures of 197 published compounds that already went through either in vivo or in vitro tests. After the analysis of the models, new analogues not yet synthesized were suggested here and had their biological activity and synthetic availability assessed.

Computer-Aided Drug Design Applied to Secondary Metabolites as Anticancer Agents.

Computer-Aided Drug Design (CADD) techniques have garnered a great deal of attention in academia and industry because of their great versatility, low costs, possibilities of cost reduction in in vitro screening and in the development of synthetic steps; these techniques are compared with highthroughput screening, in particular for candidate drugs. The secondary metabolism of plants and other organisms provide substantial amounts of new chemical structures, many of which have numerous biological and pharmacological properties for virtually every existing disease, including cancer. In oncology, compounds such as vimblastine, vincristine, taxol, podophyllotoxin, captothecin and cytarabine are examples of how important natural products enhance the cancer-fighting therapeutic arsenal. In this context, this review presents an update of Ligand-Based Drug Design and Structure-Based Drug Design techniques applied to flavonoids, alkaloids and coumarins in the search of new compounds or fragments that can be used in oncology. A systematical search using various databases was performed. The search was limited to articles published in the last 10 years. The great diversity of chemical structures (coumarin, flavonoids and alkaloids) with cancer properties, associated with infinite synthetic possibilities for obtaining analogous compounds, creates a huge chemical environment with potential to be explored, and creates a major difficulty, for screening studies to select compounds with more promising activity for a selected target. CADD techniques appear to be the least expensive and most efficient alternatives to perform virtual screening studies, aiming to selected compounds with better activity profiles and better "drugability".

High-Throughput Docking Using Quantum Mechanical Scoring.

Today high-throughput docking is one of the most commonly used computational tools in drug lead discovery. While there has been an impressive methodological improvement in docking accuracy, docking scoring still remains an open challenge. Most docking programs are rooted in classical molecular mechanics. However, to better characterize protein-ligand interactions, the use of a more accurate quantum mechanical (QM) description would be necessary. In this work, we introduce a QM-based docking scoring function for high-throughput docking and evaluate it on 10 protein systems belonging to diverse protein families, and with different binding site characteristics. Outstanding results were obtained, with our QM scoring function displaying much higher enrichment (screening power) than a traditional docking method. It is acknowledged that developments in quantum mechanics theory, algorithms and computer hardware throughout the upcoming years will allow semi-empirical (or low-cost) quantum mechanical methods to slowly replace force-field calculations. It is thus urgently needed to develop and validate novel quantum mechanical-based scoring functions for high-throughput docking toward more accurate methods for the identification and optimization of modulators of pharmaceutically relevant targets.

Binding Free Energy Calculation Using Quantum Mechanics Aimed for Drug Lead Optimization.

The routine use of in silico tools is already established in drug lead design. Besides the use of molecular docking methods to screen large chemical libraries and thus prioritize compounds for purchase or synthesis, more accurate calculations of protein-ligand binding free energy has shown the potential to guide lead optimization, thus saving time and resources. Theoretical developments and advances in computing power have allowed quantum mechanical-based methods applied to calculations on biomacromolecules to be increasingly explored and used, with the purpose of providing a more accurate description of protein-ligand interactions and an enhanced level of accuracy in the calculation of binding affinities. It should be noted that the quantum mechanical formulation includes, in principle, all contributions to the energy, considering terms usually neglected in molecular mechanics force fields, such as electronic polarization, metal coordination, and covalent binding; moreover, quantum mechanical approaches are systematically improvable. By treating all elements and interactions on equal footing, and avoiding the need of system-dependent parameterizations, they provide a greater degree of transferability. In this review, we illustrate the increasing relevance of quantum mechanical methods for binding free energy calculation in the context of structure-based drug lead optimization, showing representative applications of the different approaches available.

Molecular Docking Using Quantum Mechanical-Based Methods.

Computational methods are a powerful and consolidated tool in the early stage of the drug lead discovery process. Among these techniques, high-throughput molecular docking has proved to be extremely useful in identifying novel bioactive compounds within large chemical libraries. In the docking procedure, the predominant binding mode of each small molecule within a target binding site is assessed, and a docking score reflective of the likelihood of binding is assigned to them. These methods also shed light on how a given hit could be modified in order to improve protein-ligand interactions and are thus able to guide lead optimization. The possibility of reducing time and cost compared to experimental approaches made this technology highly appealing. Due to methodological developments and the increase of computational power, the application of quantum mechanical methods to study macromolecular systems has gained substantial attention in the last decade. A quantum mechanical description of the interactions involved in molecular association of biomolecules may lead to better accuracy compared to molecular mechanics, since there are many physical phenomena that cannot be correctly described within a classical framework, such as covalent bond formation, polarization effects, charge transfer, bond rearrangements, halogen bonding, and others, that require electrons to be explicitly accounted for. Considering the fact that quantum mechanics-based approaches in biomolecular simulation constitute an active and important field of research, we highlight in this work the recent developments of quantum mechanical-based molecular docking and high-throughput docking.

Pharmacophore and structure-based drug design, molecular dynamics and admet/tox studies to design novel potential pad4 inhibitors.

We have used docking (GLIDE), pharmacophore modeling (Discovery Studio), long trajectory molecular dynamics (Discovery Studio) and ADMET/Tox (QikProp and DEREK) to investigate PAD4 in order to determine potential novel inhibitors and hits. We have carried out virtual screening in the ZINC natural compounds database. Pharmacokinetics and Toxicity of the best hits were assessed using databases implemented in softwares that create models based on chemical structures taking into account consideration about the toxicophoric groups. A wide variety of pharmaceutical relevant properties are determined in order to make decisions about molecular suitability. After screening and analysis, the 6 most promising PAD4 inhibitors are suggested, with strong interactions (pi-stacking, hydrogen bonds, hydrophobic contacts) and suitable pharmacotherapeutic profile as well.

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

BACKGROUND Owing to increased spending on pharmaceuticals since 2010, discussions about rising costs for the development of new medical technologies have been focused on the pharmaceutical industry. Computational techniques have been developed to reduce costs associated with new drug development. Among these techniques, virtual high-throughput screening (vHTS) can contribute to the drug discovery process by providing tools to search for new drugs with the ability to bind a specific molecular target. OBJECTIVES In this context, Brazilian malaria molecular targets (BraMMT) was generated to execute vHTS experiments on selected molecular targets of Plasmodium falciparum. METHODS In this study, 35 molecular targets of P. falciparum were built and evaluated against known antimalarial compounds. FINDINGS As a result, it could predict the correct molecular target of market drugs, such as artemisinin. In addition, our findings suggested a new pharmacological mechanism for quinine, which includes inhibition of falcipain-II and a potential new antimalarial candidate, clioquinol. MAIN CONCLUSIONS The BraMMT is available to perform vHTS experiments using OCTOPUS or Raccoon software to improve the search for new antimalarial compounds. It can be retrieved from www.drugdiscovery.com.br or download of Supplementary data.

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.

Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges.

Structure-based virtual screening (VS) is a widely used approach that employs the knowledge of the three-dimensional structure of the target of interest in the design of new lead compounds from large-scale molecular docking experiments. Through the prediction of the binding mode and affinity of a small molecule within the binding site of the target of interest, it is possible to understand important properties related to the binding process. Empirical scoring functions are widely used for pose and affinity prediction. Although pose prediction is performed with satisfactory accuracy, the correct prediction of binding affinity is still a challenging task and crucial for the success of structure-based VS experiments. There are several efforts in distinct fronts to develop even more sophisticated and accurate models for filtering and ranking large libraries of compounds. This paper will cover some recent successful applications and methodological advances, including strategies to explore the ligand entropy and solvent effects, training with sophisticated machine-learning techniques, and the use of quantum mechanics. Particular emphasis will be given to the discussion of critical aspects and further directions for the development of more accurate empirical scoring functions.

Quantum Chemical Approaches in Structure-Based Virtual Screening and Lead Optimization.

Today computational chemistry is a consolidated tool in drug lead discovery endeavors. Due to methodological developments and to the enormous advance in computer hardware, methods based on quantum mechanics (QM) have gained great attention in the last 10 years, and calculations on biomacromolecules are becoming increasingly explored, aiming to provide better accuracy in the description of protein-ligand interactions and the prediction of binding affinities. In principle, the QM formulation includes all contributions to the energy, accounting for terms usually missing in molecular mechanics force-fields, such as electronic polarization effects, metal coordination, and covalent binding; moreover, QM methods are systematically improvable, and provide a greater degree of transferability. In this mini-review we present recent applications of explicit QM-based methods in small-molecule docking and scoring, and in the calculation of binding free-energy in protein-ligand systems. Although the routine use of QM-based approaches in an industrial drug lead discovery setting remains a formidable challenging task, it is likely they will increasingly become active players within the drug discovery pipeline.

Practices in Molecular Docking and Structure-Based Virtual Screening.

Drug discovery has evolved significantly over the past two decades. Progress in key areas such as molecular and structural biology has contributed to the elucidation of the three-dimensional structure and function of a wide range of biological molecules of therapeutic interest. In this context, the integration of experimental techniques, such as X-ray crystallography, and computational methods, such as molecular docking, has promoted the emergence of several areas in drug discovery, such as structure-based drug design (SBDD). SBDD strategies have been broadly used to identify, predict and optimize the activity of small molecules toward a molecular target and have contributed to major scientific breakthroughs in pharmaceutical R&D. This chapter outlines molecular docking and structure-based virtual screening (SBVS) protocols used to predict the interaction of small molecules with the phosphatidylinositol-bisphosphate-kinase PI3Kδ, which is a molecular target for hematological diseases. A detailed description of the molecular docking and SBVS procedures and an evaluation of the results are provided.

Kinetic parameters for the reaction of 1,2,4-trioxolanes and artemisinin with iron(II): New evidence for the source of antimalarial activity.

The Fenton-like reductive cleavage of antimalarial peroxides like artemisinin by iron(II) species is a chemical reaction whose mechanistic pathway has not been yet fully understood; it is, however, known that there is considerable production of radical species centered at both the oxygen and carbon, which are important to the therapeutical effects of those compounds. This article reports kinetic data for the reaction of artemisinin and two model 1,2,4-trioxolanes with iron(II) species and also a mechanistic interpretation of this reductive cleavage from transition state thermodynamics. The suggestion of the presence of an enhancing specific factor inside the plasmodium is made.