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1.
Environ Health Perspect ; 130(2): 27012, 2022 02.
Artigo em Inglês | MEDLINE | ID: mdl-35192406

RESUMO

BACKGROUND: Modern chemical toxicology is facing a growing need to Reduce, Refine, and Replace animal tests (Russell 1959) for hazard identification. The most common type of animal assays for acute toxicity assessment of chemicals used as pesticides, pharmaceuticals, or in cosmetic products is known as a "6-pack" battery of tests, including three topical (skin sensitization, skin irritation and corrosion, and eye irritation and corrosion) and three systemic (acute oral toxicity, acute inhalation toxicity, and acute dermal toxicity) end points. METHODS: We compiled, curated, and integrated, to the best of our knowledge, the largest publicly available data sets and developed an ensemble of quantitative structure-activity relationship (QSAR) models for all six end points. All models were validated according to the Organisation for Economic Co-operation and Development (OECD) QSAR principles, using data on compounds not included in the training sets. RESULTS: In addition to high internal accuracy assessed by cross-validation, all models demonstrated an external correct classification rate ranging from 70% to 77%. We established a publicly accessible Systemic and Topical chemical Toxicity (STopTox) web portal (https://stoptox.mml.unc.edu/) integrating all developed models for 6-pack assays. CONCLUSIONS: We developed STopTox, a comprehensive collection of computational models that can be used as an alternative to in vivo 6-pack tests for predicting the toxicity hazard of small organic molecules. Models were established following the best practices for the development and validation of QSAR models. Scientists and regulators can use the STopTox portal to identify putative toxicants or nontoxicants in chemical libraries of interest. https://doi.org/10.1289/EHP9341.


Assuntos
Alternativas aos Testes com Animais , Simulação por Computador , Substâncias Perigosas , Animais , Cosméticos/toxicidade , Substâncias Perigosas/toxicidade , Praguicidas/toxicidade , Preparações Farmacêuticas , Relação Quantitativa Estrutura-Atividade
2.
Front Immunol ; 12: 642383, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34135888

RESUMO

Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor.


Assuntos
Inteligência Artificial , Descoberta de Drogas/métodos , Schistosoma/efeitos dos fármacos , Esquistossomose/tratamento farmacológico , Esquistossomicidas , Animais , Humanos
3.
ChemMedChem ; 16(7): 1093-1103, 2021 04 08.
Artigo em Inglês | MEDLINE | ID: mdl-33247522

RESUMO

Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making them interesting targets in many diseases. Protein kinase 7 (PK7) is an orphan kinase from the Plasmodium genus, essential for the sporogonic cycle of these parasites. Here, we applied a robust and integrative artificial intelligence-assisted virtual-screening (VS) approach using shape-based and machine learning models to identify new potential PK7 inhibitors with in vitro antiplasmodial activity. Eight virtual hits were experimentally evaluated, and compound LabMol-167 inhibited ookinete conversion of Plasmodium berghei and blood stages of Plasmodium falciparum at nanomolar concentrations with low cytotoxicity in mammalian cells. As PK7 does not have an essential role in the Plasmodium blood stage and our virtual screening strategy aimed for both PK7 and blood-stage inhibition, we conducted an in silico target fishing approach and propose that this compound might also inhibit P. falciparum PK5, acting as a possible dual-target inhibitor. Finally, docking studies of LabMol-167 with P. falciparum PK7 and PK5 proteins highlighted key interactions for further hit-to lead optimization.


Assuntos
Antimaláricos/farmacologia , Inteligência Artificial , Quinases de Proteína Quinase Ativadas por Mitógeno/antagonistas & inibidores , Plasmodium falciparum/efeitos dos fármacos , Inibidores de Proteínas Quinases/farmacologia , Proteínas de Protozoários/antagonistas & inibidores , Antimaláricos/química , Relação Dose-Resposta a Droga , Avaliação Pré-Clínica de Medicamentos , Quinases de Proteína Quinase Ativadas por Mitógeno/metabolismo , Estrutura Molecular , Testes de Sensibilidade Parasitária , Plasmodium falciparum/metabolismo , Inibidores de Proteínas Quinases/química , Proteínas de Protozoários/metabolismo , Relação Estrutura-Atividade
4.
Front Chem ; 7: 773, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31824917

RESUMO

Malaria is a tropical infectious disease that affects over 219 million people worldwide. Due to the constant emergence of parasitic resistance to the current antimalarial drugs, the discovery of new antimalarial drugs is a global health priority. Multi-target drug discovery is a promising and innovative strategy for drug discovery and it is currently regarded as one of the best strategies to face drug resistance. Aiming to identify new multi-target antimalarial drug candidates, we developed an integrative computational approach to select multi-kinase inhibitors for Plasmodium falciparum calcium-dependent protein kinases 1 and 4 (CDPK1 and CDPK4) and protein kinase 6 (PK6). For this purpose, we developed and validated shape-based and machine learning models to prioritize compounds for experimental evaluation. Then, we applied the best models for virtual screening of a large commercial database of drug-like molecules. Ten computational hits were experimentally evaluated against asexual blood stages of both sensitive and multi-drug resistant P. falciparum strains. Among them, LabMol-171, LabMol-172, and LabMol-181 showed potent antiplasmodial activity at nanomolar concentrations (EC50 ≤ 700 nM) and selectivity indices >15 folds. In addition, LabMol-171 and LabMol-181 showed good in vitro inhibition of P. berghei ookinete formation and therefore represent promising transmission-blocking scaffolds. Finally, docking studies with protein kinases CDPK1, CDPK4, and PK6 showed structural insights for further hit-to-lead optimization studies.

5.
Comput Struct Biotechnol J ; 17: 352-361, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30949306

RESUMO

Leishmaniasis is a neglected tropical disease caused by parasites of the genus Leishmania (NTD) endemic in 98 countries. Although some drugs are available, current treatments deal with issues such as toxicity, low efficacy, and emergence of resistance. Therefore, there is an urgent need to identify new targets for the development of new antileishmanial drugs. Protein kinases (PKs), which play an essential role in many biological processes, have become potential drug targets for many parasitic diseases. A refined bioinformatics pipeline was applied in order to define and compare the kinomes of L. infantum and L. braziliensis, species that cause cutaneous and visceral manifestations of leishmaniasis in the Americas, the latter being potentially fatal if untreated. Respectively, 224 and 221 PKs were identified in L. infantum and L. braziliensis overall. Almost all unclassified eukaryotic PKs were assigned to six of nine major kinase groups and, consequently, most have been classified into family and subfamily. Furthermore, revealing the kinomes for both Leishmania species allowed for the prioritization of potential drug targets that could be explored for discovering new drugs against leishmaniasis. Finally, we used a drug repurposing approach and prioritized seven approved drugs and investigational compounds to be experimentally tested against Leishmania. Trametinib and NMS-1286937 inhibited the growth of L. infantum and L. braziliensis promastigotes and amastigotes and therefore might be good candidates for the drug repurposing pipeline.

6.
PLoS Comput Biol ; 14(10): e1006515, 2018 10.
Artigo em Inglês | MEDLINE | ID: mdl-30346968

RESUMO

The development of novel therapeutics is urgently required for diseases where existing treatments are failing due to the emergence of resistance. This is particularly pertinent for parasitic infections of the tropics and sub-tropics, referred to collectively as neglected tropical diseases, where the commercial incentives to develop new drugs are weak. One such disease is schistosomiasis, a highly prevalent acute and chronic condition caused by a parasitic helminth infection, with three species of the genus Schistosoma infecting humans. Currently, a single 40-year old drug, praziquantel, is available to treat all infective species, but its use in mass drug administration is leading to signs of drug-resistance emerging. To meet the challenge of developing new therapeutics against this disease, we developed an innovative computational drug repurposing pipeline supported by phenotypic screening. The approach highlighted several protein kinases as interesting new biological targets for schistosomiasis as they play an essential role in many parasite's biological processes. Focusing on this target class, we also report the first elucidation of the kinome of Schistosoma japonicum, as well as updated kinomes of S. mansoni and S. haematobium. In comparison with the human kinome, we explored these kinomes to identify potential targets of existing inhibitors which are unique to Schistosoma species, allowing us to identify novel targets and suggest approved drugs that might inhibit them. These include previously suggested schistosomicidal agents such as bosutinib, dasatinib, and imatinib as well as new inhibitors such as vandetanib, saracatinib, tideglusib, alvocidib, dinaciclib, and 22 newly identified targets such as CHK1, CDC2, WEE, PAKA, MEK1. Additionally, the primary and secondary targets in Schistosoma of those approved drugs are also suggested, allowing for the development of novel therapeutics against this important yet neglected disease.


Assuntos
Biologia Computacional/métodos , Reposicionamento de Medicamentos/métodos , Inibidores de Proteínas Quinases/farmacologia , Schistosoma/efeitos dos fármacos , Esquistossomicidas/farmacologia , Animais , Bases de Dados de Proteínas , Reprodutibilidade dos Testes
7.
Curr Top Med Chem ; 14(16): 1899-912, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25262801

RESUMO

Virtual screening (VS) techniques are well-established tools in the modern drug discovery process, mainly used for hit finding in drug discovery. The availability of knowledge of structural information, which includes an increasing number of 3D protein structures and the readiness of free databases of commercially available smallmolecules, provides a broad platform for VS. This review summarizes the current developments in VS regarding chemical databases and highlights the achievements as well as the challenges with an emphasis on a recent example of the successful application for the identification of new hits for sterol 14α-demethylase (CYP51) of Trypanosoma cruzi.


Assuntos
Inibidores de 14-alfa Desmetilase/farmacologia , Avaliação Pré-Clínica de Medicamentos , Esterol 14-Desmetilase/metabolismo , Inibidores de 14-alfa Desmetilase/síntese química , Inibidores de 14-alfa Desmetilase/química , Animais , Química Farmacêutica , Humanos , Trypanosoma cruzi/enzimologia
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