Synthesis, design, and optimization of a potent and selective series of pyridylpiperazines as promising antimalarial agents.

An optimization of the pyridylpiperazine series against Plasmodium falciparum has been performed, exploring a structure-activity relationship carried out on the toluyl fragment of hit 1, a compound with low micromolar activity against Plasmodium falciparum discovered by high-throughput screening. After confirming the crucial role played by this aryl fragment in the antiplasmodial activity, the replacement of the ortho-methyl substituent of 1 by halogenated ones led to an improvement for four analogs, either in terms of potency, expected pharmacokinetics profile, or both. Further introduction of endocyclic nitrogens in this fragment identified two more optimized compounds, 20 and 23, which are expected to be much more metabolically stable than 1. Additional assessment of the cytotoxicity, Ligand Lipophilic Efficiency, potency against the chloroquine-resistant Dd2 strain and in silico ADMET predictions revealed a satisfactory profile for most compounds, ultimately identifying the four optimized compounds 7, 9, 20 and 23 as promising compounds for further lead optimization of this series against Plasmodium falciparum.

Optimization of benzenesulfonyl derivatives as anti-Trypanosomatidae agents: Structural design, synthesis, and pharmacological assessment against Trypanosoma cruzi and Leishmania infantum.

Leishmaniasis and Chagas disease are neglected tropical diseases caused by Trypanosomatidae parasites. Given the numerous limitations associated with current treatments, such as extended treatment duration, variable efficacy, and severe side effects, there is an urgent imperative to explore novel therapeutic options. This study details the early stages of hit-to-lead optimization for a benzenesulfonyl derivative, denoted as initial hit, against Trypanossoma cruzi (T. cruzi), Leishmania infantum (L. infantum) and Leishmania braziliensis (L. braziliensis). We investigated structure - activity relationships using a series of 26 newly designed derivatives, ultimately yielding potential lead candidates with potent low-micromolar and sub-micromolar activities against T. cruzi and Leishmania spp, respectively, and low in vitro cytotoxicity against mammalian cells. These discoveries emphasize the significant promise of this chemical class in the fight against Chagas disease and leishmaniasis.

Hit-to-lead optimization of a pyrazinylpiperazine series against Leishmania infantum and Leishmania braziliensis.

An early hit-to-lead optimization of a novel pyrazinylpiperazine series against L. infantum and L. braziliensis has been performed after an extensive SAR focusing on the benzoyl fragment of hit (4). Deletion of the meta-Cl of (4) led to the obtention of the para-hydroxyl derivative (12), on which the design of most monosubstituted derivatives of the SAR was based. Further optimization of the series, involving disubstituted benzoyl fragments and the hydroxyl substituent of (12), allowed the obtention of a total of 15 compounds with increased antileishmanial potency (IC50 < 10 µM), nine of which displayed activity in the low micromolar range (IC50 < 5 µM). This optimization ultimately identified the ortho, meta-dihydroxyl derivative (46) as an early lead for this series (IC50 (L. infantum) = 2.8 µM, IC50 (L. braziliensis) = 0.2 µM). Additional assessment of some selected compounds against other trypanosomatid parasites revealed that this series is selective towards Leishmania parasites, and in silico ADMET predictions revealed satisfactory profiles for these compounds, allowing further lead optimization of the pyrazinylpiperazine class against Leishmania.

Development of New Potential Inhibitors of ß1 Integrins through In Silico Methods-Screening and Computational Validation.

Integrins are transmembrane receptors that play a critical role in many biological processes which can be therapeutically modulated using integrin blockers, such as peptidomimetic ligands. This work aimed to develop new potential ß1 integrin antagonists using modeled receptors based on the aligned crystallographic structures and docked with three lead compounds (BIO1211, BIO5192, and TCS2314), widely known as α4ß1 antagonists. Lead-compound complex optimization was performed by keeping intact the carboxylate moiety of the ligand, adding substituents in two other regions of the molecule to increase the affinity with the target. Additionally, pharmacokinetic predictions were performed for the ten best ligands generated, with the lowest docking interaction energy obtained for α4ß1 and BIO5192. Results revealed an essential salt bridge between the BIO5192 carboxylate group and the Mg2+ MIDAS ion of the integrin. We then generated more than 200 new BIO5192 derivatives, some with a greater predicted affinity to α4ß1. Furthermore, the significance of retaining the pyrrolidine core of the ligand and increasing the therapeutic potential of the new compounds is emphasized. Finally, one novel molecule (1592) was identified as a potential drug candidate, with appropriate pharmacokinetic profiles, similar dynamic behavior at the integrin interaction site compared with BIO5192, and a higher predicted affinity to VLA-4.

Therapeutic Potential of Flavonoid Derivatives for Certain Neglected Tropical Diseases.

BACKGROUND: Neglected tropical diseases (NTDs) are infectious diseases that mostly affect people living in tropical and subtropical regions, especially in impoverished areas. Ubiquitously found in plants, flavonoids are a group of compounds that have been reported to exhibit a wide range of biological activities against parasites (Leishmania sp., Trypanosoma cruzi, Trypanosoma brucei, Brugia malayi, etc.) that cause certain NTDs. AIMS: The present study aims to highlight and discuss our recent reports on the implication of flavonoids in drug development for NTDs, such as leishmaniasis, Chagas disease, African trypanosomiasis, filariasis, among others. RESULTS: Today, studies show that flavonoids exhibit in vitro antileishmanial, anti-trypanosomiasis, antifilarial activities, among others. Furthermore, the molecular hybridization of flavonoids with the triazole groups has led to the development of compounds with improved biological activity. The incorporation of chemical groups, such as NO2, F, and Cl groups, during the process of design and synthesis, leads to the enhancement of pharmacological activity. CONCLUSION: Flavonoids are useful metabolites that can be prospected as potential leads for the development of new agents against certain NTDs. However, research opportunities, including cytotoxicity and in vivo studies, mechanisms of action, bioavailability of these compounds, remain to be investigated in the future.

Anti-inflammatory, ulcerogenic and platelet activation evaluation of novel 1,4-diaryl-1,2,3-triazole neolignan-celecoxib hybrids.

This study reports the synthesis of novel neolignans-celecoxib hybrids and the evaluation of their biological activity. Analogs8-13(L13-L18) exhibited anti-inflammatory activity, inhibited glycoprotein expression (P-selectin) related to platelet activation, and were considered non- ulcerogenic in the animal model, even with the administration of 10 times higher than the dose used in reference therapy. In silico drug-likeness showed that the analogs are compliant with Lipinski's rule of five. A molecular docking study showed that the hybrids8-13(L13-L18) fitted similarly with celecoxib in the COX-2 active site. According to this data, it is possible to infer that extra hydrophobic interactions and the hydrogen interactions with the triazole core may improve the selectivity towards the COX-2 active site. Furthermore, the molecular docking study with P-selectin showed the binding affinity of the analogs in the active site, performing important interactions with amino acid residues such as Tyr 48. Whereas the P-selectin is a promising target to the design of new anti-inflammatory drugs with antithrombotic properties, a distinct butterfly-like structure of 1,4-diaryl-1,2,3-triazole neolignan-celecoxib hybrids synthesized in this work may be a safer alternative to the traditional COX-2 inhibitors.

Chagas Disease Drug Discovery in Latin America-A Mini Review of Antiparasitic Agents Explored Between 2010 and 2021.

Chagas disease is a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi that endangers almost 70 million people worldwide. The only two drugs that are currently approved for its treatment, benznidazole and nifurtimox, have controversial efficacy in adults and restricting safety issues, leaving thousands of patients without a suitable treatment. The neglect of Chagas disease is further illustrated by the lack of a robust and diverse drug discovery and development portfolio of new chemical entities, and it is of paramount importance to build a strong research and development network for antichagasic drugs. Focusing on drug discovery programs led by scientists based in Latin America, the main endemic region for this disease, we discuss herein what has been published in the last decade in terms of identification of new antiparasitic drugs to treat Chagas disease, shining a spotlight on the origin, chemical diversity, level of characterization of hits, and strategies used for optimization of lead compounds. Finally, we identify strengths and weaknesses in these drug discovery campaigns and highlight the importance of multidisciplinary collaboration and knowledge sharing.

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.

Homologation: A Versatile Molecular Modification Strategy to Drug Discovery.

Homologation is a concept introduced by Gerhard in 1853 to describe a homologous series in organic chemistry. Since then, the concept has been adapted and used in medicinal chemistry as one of the most important strategies for molecular modification. The homologation types, their influence on physico-chemical properties and molecular conformation are presented and discussed. Its application in lead-identification and lead optimization steps, as well as its impact on pharmacodynamics/pharmacokinetic properties and on protein structure is highlighted from selected examples. • Homologation: definition and types • Homologous series in nature • Comparative physico-chemical and conformational properties • Application in lead-identification and lead-optimization • Impact on pharmacodynamic property • Impact on pharmacokinetic property • Impact on protein structure • Concluding remarks • Acknowledgment • References.

Discovery of Novel TASK-3 Channel Blockers Using a Pharmacophore-Based Virtual Screening.

TASK-3 is a two-pore domain potassium (K2P) channel highly expressed in the hippocampus, cerebellum, and cortex. TASK-3 has been identified as an oncogenic potassium channel and it is overexpressed in different cancer types. For this reason, the development of new TASK-3 blockers could influence the pharmacological treatment of cancer and several neurological conditions. In the present work, we searched for novel TASK-3 blockers by using a virtual screening protocol that includes pharmacophore modeling, molecular docking, and free energy calculations. With this protocol, 19 potential TASK-3 blockers were identified. These molecules were tested in TASK-3 using patch clamp, and one blocker (DR16) was identified with an IC50 = 56.8 ± 3.9 µM. Using DR16 as a scaffold, we designed DR16.1, a novel TASK-3 inhibitor, with an IC50 = 14.2 ± 3.4 µM. Our finding takes on greater relevance considering that not many inhibitory TASK-3 modulators have been reported in the scientific literature until today. These two novel TASK-3 channel inhibitors (DR16 and DR16.1) are the first compounds found using a pharmacophore-based virtual screening and rational drug design protocol.

Chemical Intuition in Drug Design and Discovery.

The medicinal chemist plays the most important role in drug design, discovery and development. The primary goal is to discover leads and optimize them to develop clinically useful drug candidates. This process requires the medicinal chemist to deal with large sets of data containing chemical descriptors, pharmacological data, pharmacokinetics parameters, and in silico predictions. The modern medicinal chemist has a large number of tools and technologies to aid him in creating strategies and supporting decision-making. Alongside with these tools, human cognition, experience and creativity are fundamental to drug research and are important for the chemical intuition of medicinal chemists. Therefore, fine-tuning of data processing and in-house experience are essential to reach clinical trials. In this article, we will provide an expert opinion on how chemical intuition contributes to the discovery of drugs, discuss where it is involved in the modern drug discovery process, and demonstrate how multidisciplinary teams can create the optimal environment for drug design, discovery, and development.

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.

Prediction and Optimization of Pharmacokinetic and Toxicity Properties of the Ligand.

A crucial factor for the approval and success of any drug is how it behaves in the body. Many drugs, however, do not reach the market due to poor efficacy or unacceptable side effects. It is therefore important to take these into consideration early in the drug development process, both in the prioritization of potential hits, and optimization of lead compounds. In silico approaches offer a cost and time-effective approach to rapidly screen and optimize pharmacokinetic and toxicity properties. Here we demonstrate the use of the comprehensive analysis system pkCSM, to allow early identification of potential problems, prioritization of hits, and optimization of leads.

From Protein Structure to Small-Molecules: Recent Advances and Applications to Fragment-Based Drug Discovery.

Fragment-based drug discovery (FBDD) is a broadly used strategy in structure-guided ligand design, whereby low-molecular weight hits move from lead-like to drug-like compounds. Over the past 15 years, an increasingly important role of the integration of these strategies into industrial and academic research platforms has been successfully established, allowing outstanding contributions to drug discovery. One important factor for the current prominence of FBDD is the better coverage of the chemical space provided by fragment-like libraries. The development of the field relies on two features: (i) the growing number of structurally characterized drug targets and (ii) the enormous chemical diversity available for experimental and virtual screenings. Indeed, fragment-based campaigns have contributed to address major challenges in lead optimization, such as the appropriate physicochemical profile of clinical candidates. This perspective paper outlines the usefulness and applications of FBDD approaches in medicinal chemistry and drug design.

Application of computational methods for anticancer drug discovery, design, and optimization / Aplicación de métodos computacionales para el descubrimiento, diseño y optimización de fármacos contra el cáncer

Abstract: Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.

Resumen: El desarrollo de un nuevo fármaco es un proceso complejo y arriesgado que requiere una enorme cantidad de tiempo y dinero. Se estima que el proceso estándar para producir un nuevo fármaco, desde su descubrimiento hasta que acaba en el mercado, puede tardar hasta 15 años y tener un costo de mil millones de dólares (USD). Por fortuna, este escenario ha cambiado recientemente con la llegada de nuevas tecnologías y metodologías. Entre ellas, los métodos computacionales se han convertido en un componente determinante en muchos programas de descubrimiento de fármacos. En un esfuerzo por incrementar las posibilidades de encontrar nuevas moléculas con potencial farmacológico, se utilizan técnicas como el cribado virtual de quimiotecas construidas con base en ligandos o estructuras para la identificación de hits y hasta para la optimización de compuestos líder. En lo que respecta al diseño y descubrimiento de nuevos candidatos a fármacos contra el cáncer, estos enfoques tienen, a la fecha, un impacto importante y aportan nuevas posibilidades terapéuticas. En este artículo se revisa el concepto del diseño racional de moléculas con potencial farmacológico, ilustrando los principios clave con algunos de los ejemplos más representativos y exitosos de moléculas identificadas mediante estas aproximaciones. Se incluyen casos desarrollados en el campo del diseño de fármacos contra el cáncer con la finalidad de mostrar cómo, con la ayuda del diseño asistido por computadora, se pueden generar nuevos fármacos que den esperanza a millones de pacientes.

Investigating molecular dynamics-guided lead optimization of EGFR inhibitors.

The epidermal growth factor receptor (EGFR) is part of an extended family of proteins that together control aspects of cell growth and development, and thus a validated target for drug discovery. We explore in this work the suitability of a molecular dynamics-based end-point binding free energy protocol to estimate the relative affinities of a virtual combinatorial library designed around the EGFR model inhibitor 6{1} as a tool to guide chemical synthesis toward the most promising compounds. To investigate the validity of this approach, selected analogs including some with better and worse predicted affinities relative to 6{1} were synthesized, and their biological activity determined. To understand the binding determinants of the different analogs, hydrogen bonding and van der Waals contributions, and water molecule bridging in the EGFR-analog complexes were analyzed. The experimental validation was in good qualitative agreement with our theoretical calculations, while also a 6-dibromophenyl-substituted compound with enhanced inhibitory effect on EGFR compared to the reference ligand was obtained.

Application of computational methods for anticancer drug discovery, design, and optimization.

Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.