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Compound databases of natural products play a crucial role in drug discovery and development projects and have implications in other areas, such as food chemical research, ecology and metabolomics. Recently, we put together the first version of the Latin American Natural Product database (LANaPDB) as a collective effort of researchers from six countries to ensemble a public and representative library of natural products in a geographical region with a large biodiversity. The present work aims to conduct a comparative and extensive profiling of the natural product-likeness of an updated version of LANaPDB and the individual ten compound databases that form part of LANaPDB. The natural product-likeness profile of the Latin American compound databases is contrasted with the profile of other major natural product databases in the public domain and a set of small-molecule drugs approved for clinical use. As part of the extensive characterization, we employed several chemoinformatics metrics of natural product likeness. The results of this study will capture the attention of the global community engaged in natural product databases, not only in Latin America but across the world.
Assuntos
Produtos Biológicos , Produtos Biológicos/química , Produtos Biológicos/farmacologia , América Latina , Bibliotecas de Moléculas Pequenas/farmacologia , Bibliotecas de Moléculas Pequenas/química , Descoberta de Drogas , Quimioinformática , Bases de Dados de Compostos QuímicosRESUMO
The Glycine Transporter Type 1 (GlyT1) significantly impacts central nervous system functions, influencing glycinergic and glutamatergic neurotransmission. Bitopertin, the first GlyT1 inhibitor in clinical trials, was developed for schizophrenia treatment but showed limited efficacy. Despite this, bitopertin's repositioning could advance treating various pathologies. This study aims to understand bitopertin's mechanism of action using computational methods, exploring off-target effects, and providing a comprehensive pharmacological profile. Similarity Ensemble Approach (SEA) and SwissTargetPrediction initially predicted targets, followed by molecular modeling on SWISS-MODEL and GalaxyWeb servers. Binding sites were identified using PrankWeb, and molecular docking was performed with DockThor and GOLD software. Molecular dynamics analyses were conducted on the Visual Dynamics platform. Reverse screening on SEA and SwissTargetPrediction identified GlyT1 (SLC6A9), GlyT2 (SLC6A5), PROT (SLC6A7), and DAT (SLC6A3) as potential bitopertin targets. Homology modeling on SwissModel generated high-resolution models, optimized further on GalaxyWeb. PrankWeb identified similar binding sites in GlyT1, GlyT2, PROT, and DAT, indicating potential interaction. Docking studies suggested bitopertin's interaction with GlyT1 and proximity to GlyT2 and PROT. Molecular dynamics confirmed docking results, highlighting bitopertin's target stability beyond GlyT1. The study concludes that bitopertin potentially interacts with multiple SLC6 family targets, indicating a broader pharmacological property.
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Proteínas da Membrana Plasmática de Transporte de Glicina , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Proteínas da Membrana Plasmática de Transporte de Glicina/metabolismo , Proteínas da Membrana Plasmática de Transporte de Glicina/antagonistas & inibidores , Humanos , Sítios de Ligação , Piperazinas/farmacologia , Piperazinas/química , Simulação por Computador , Reposicionamento de Medicamentos , SulfonasRESUMO
Designing and developing inhibitors against the epigenetic target DNA methyltransferase (DNMT) is an attractive strategy in epigenetic drug discovery. DNMT1 is one of the epigenetic enzymes with significant clinical relevance. Structure-based de novo design is a drug discovery strategy that was used in combination with similarity searching to identify a novel DNMT inhibitor with a novel chemical scaffold and warrants further exploration. This study aimed to continue exploring the potential of de novo design to build epigenetic-focused libraries targeted toward DNMT1. Herein, we report the results of an in-depth and critical comparison of ligand- and structure-based de novo design of screening libraries focused on DNMT1. The newly designed chemical libraries focused on DNMT1 are freely available on GitHub.
Assuntos
DNA (Citosina-5-)-Metiltransferase 1 , Desenho de Fármacos , Inibidores Enzimáticos , Ligantes , DNA (Citosina-5-)-Metiltransferase 1/antagonistas & inibidores , DNA (Citosina-5-)-Metiltransferase 1/metabolismo , Inibidores Enzimáticos/química , Inibidores Enzimáticos/farmacologia , Humanos , Bibliotecas de Moléculas Pequenas/farmacologia , Bibliotecas de Moléculas Pequenas/química , Relação Estrutura-AtividadeRESUMO
Natural product databases are an integral part of chemoinformatics and computer-aided drug design. Despite their pivotal role, a distinct scarcity of projects in Latin America, particularly in Mexico, provides accessible tools of this nature. Herein, we introduce BIOMX-DB, an open and freely accessible web-based database designed to address this gap. BIOMX-DB enhances the features of the existing Mexican natural product database, BIOFACQUIM, by incorporating advanced search, filtering, and download capabilities. The user-friendly interface of BIOMX-DB aims to provide an intuitive experience for researchers. For seamless access, BIOMX-DB is freely available at www.biomx-db.com.
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Plant-insect interactions are a driving force into ecosystem evolution and community dynamics. Many insect herbivores enter diapause, a developmental arrest stage in anticipation of adverse conditions, to survive and thrive through seasonal changes. Herein, we investigated the roles of medium- to non-polar metabolites during larval development and diapause in a specialist insect herbivore, Chlosyne lacinia, reared on Aldama robusta leaves. Varying metabolites were determined using gas chromatography-mass spectrometry (GC-MS)-based metabolomics. Sesquiterpenes and steroids were the main metabolites putatively identified in A. robusta leaves, whereas C. lacinia caterpillars were characterized by triterpenes, steroids, fatty acids, and long-chain alkanes. We found out that C. lacinia caterpillars biosynthesized most of the identified steroids and fatty acids from plant-derived ingested metabolites, as well as all triterpenes and long-chain alkanes. Steroids, fatty acids, and long-chain alkanes were detected across all C. lacinia instars and in diapausing caterpillars. Sesquiterpenes and triterpenes were also detected across larval development, yet they were not detected in diapausing caterpillars, which suggested that these metabolites were converted to other molecules prior to the diapause stage. Our findings shed light on the chemical content variation across C. lacinia development and diapause, providing insights into the roles of metabolites in plant-insect interactions.
Assuntos
Diapausa , Lepidópteros , Sesquiterpenos , Triterpenos , Animais , Cromatografia Gasosa-Espectrometria de Massas , Ecossistema , Metabolômica/métodos , Esteroides/metabolismo , Sesquiterpenos/metabolismo , Ácidos Graxos/metabolismo , Alcanos , Triterpenos/metabolismo , LarvaRESUMO
SARS-CoV-2 Main Protease (Mpro) is an enzyme that cleaves viral polyproteins translated from the viral genome, which is critical for viral replication. Mpro is a target for anti-SARS-CoV-2 drug development. Herein, we performed a large-scale virtual screening by comparing multiple structural descriptors of reference molecules with reported anti-coronavirus activity against a library with >17 million compounds. Further filtering, performed by applying two machine learning algorithms, identified eighteen computational hits as anti-SARS-CoV-2 compounds with high structural diversity and drug-like properties. The activities of twelve compounds on Mpro's enzymatic activity were evaluated by fluorescence resonance energy transfer (FRET) assays. Compound 13 (ZINC13878776) significantly inhibited SARS-CoV-2 Mpro activity and was employed as a reference for an experimentally hit expansion. The structural analogues 13a (ZINC4248385), 13b (ZNC13523222), and 13c (ZINC4248365) were tested as Mpro inhibitors, reducing the enzymatic activity of recombinant Mpro with potency as follows: 13c > 13 > 13b > 13a. Then, their anti-SARS-CoV-2 activities were evaluated in plaque reduction assays using Vero CCL81 cells. Subtoxic concentrations of compounds 13a, 13c, and 13b displayed in vitro antiviral activity with IC50 in the mid micromolar range. Compounds 13a-c could become lead compounds for the development of new Mpro inhibitors with improved activity against anti-SARS-CoV-2.
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INTRODUCTION: We developed Data Base similarity (DBsimilarity), a user-friendly tool designed to organize structure databases into similarity networks, with the goal of facilitating the visualization of information primarily for natural product chemists who may not have coding experience. METHOD: DBsimilarity, written in Jupyter Notebooks, converts Structure Data File (SDF) files into Comma-Separated Values (CSV) files, adds chemoinformatics data, constructs an MZMine custom database file and an NMRfilter candidate list of compounds for rapid dereplication of MS and 2D NMR data, calculates similarities between compounds, and constructs CSV files formatted into similarity networks for Cytoscape. RESULTS: The Lotus database was used as a source for Ginkgo biloba compounds, and DBsimilarity was used to create similarity networks including NPClassifier classification to indicate biosynthesis pathways. Subsequently, a database of validated antibiotics from natural products was combined with the G. biloba compounds to identify promising compounds. The presence of 11 compounds in both datasets points to possible antibiotic properties of G. biloba, and 122 compounds similar to these known antibiotics were highlighted. Next, DBsimilarity was used to filter the NPAtlas database (selecting only those with MIBiG reference) to identify potential antibacterial compounds using the ChEMBL database as a reference. It was possible to promptly identify five compounds found in both databases and 167 others worthy of further investigation. CONCLUSION: Chemical and biological properties are determined by molecular structures. DBsimilarity enables the creation of interactive similarity networks using Cytoscape. It is also in line with a recent review that highlights poor biological plausibility and unrealistic chromatographic behaviors as significant sources of errors in compound identification.
Assuntos
Produtos Biológicos , Produtos Biológicos/química , Espectroscopia de Ressonância Magnética/métodos , Bases de Dados Factuais , Extratos Vegetais/química , AntibacterianosRESUMO
A quimioinformática, definida como o emprego de técnicas informáticas na solução de problemas da química, evolui em conjunto com o desenvolvimento de ferramentas computacionais e é de grande relevância para o planejamento racional de fármacos ao otimizar etapas do desenvolvimento de novas moléculas e economizar recursos e tempo. Dentre as técnicas disponíveis destacam-se o planejamento de fármacos baseado na estrutura e no ligante, que quando combinadas auxiliam na identificação e otimização de moléculas ativas frente a alvos farmacológicos. A Dihidrofolato Redutase (DHFR) é uma importante enzima da via dos folatos que catalisa a redução do dihidrofolato em tetrahidrofolato, utilizando NADPH como cofator, reação essencial para a replicação celular, visto que este ciclo resulta na síntese de precursores das bases nitrogenadas que compõem o DNA, consequentemente, inibidores de DHFR são utilizados no tratamento de infecções bacterianas e alguns tipos de câncer. Trypanosoma cruzi, protozoário causador da doença de chagas, é um dos organismos que expressam a DHFR, além do próprio Homo sapiens. Analisaram-se ligantes conhecidos e as estruturas da proteína expressa pelos dois organismos, visando identificar pontos de divergência que possam ser explorados no planejamento de moléculas seletivas para o tratamento da doença de Chagas. Os 6 modelos cristalográficos de T. cruzi e 2 de H. sapiens foram obtidos do banco de dados de proteínas (PDB) após aplicação de filtros de qualidade. Foram analisadas as sequências de aminoácidos dos modelos, com o uso do Cluster Ômega, sua estrutura tridimensional com os programas Pymol e Chimera X, além da análise das cavidades proteicas com o CavityPlus, que também gerou os farmacóforos de ambos alvos. A análise de estrutura primária identificou mutações em três aminoácidos nos cristais do parasita, que podem ser explicados por diferentes caminhos evolutivos de grupos segregados, embora nenhuma mutação observada esteja em regiões de sítio ativo. A análise dos modelos permitiu que fossem identificados os 25 aminoácidos que estão a menos de 5 Å de distância dos ligantes de T. cruzi, sendo 5 aminoácidos responsáveis por interações de hidrogênio com pelo menos um dos ligantes analisados. Destes, 18 se repetem na proteína humana ou são substituídos por outro aminoácido que mantém a mesma interação. Quanto às diferenças observadas, destacam-se a asparagina 44 substituída por uma prolina na proteína humana e a prolina 92, substituída por uma lisina. A análise de cavidades identificou três cavidades em cada proteína, embora somente as cavidades correspondentes ao sítio ativo sejam druggables. A cavidade da proteína humana é maior e mais alongada, além de apresentar o aspecto de um túnel, enquanto a cavidade da proteína parasita é mais aberta, tal abertura permite que ligantes com o anel benzeno meta substituídos explorem uma região existente na cavidade de T. cruzi que é fechada na humana. O farmacóforo de ambas proteínas foi identificado, apresentando diferenças no tamanho e angulação que também podem ser explorados no planejamento de fármacos seletivos
Chemoinformatic, defined as the use of informatic techniques to solve chemical problems, has evolved together with new computational tools and it is quite important for rational drug designing, by optimizing different steps on the development pipeline of new molecules, saving resources and time. From all the available tools, structure and ligand based drug design shall be highlighted, when combined, they support the identification and optimization of active molecules from pharmaceutical targets. Dihydrofolate reductase (DHFR) is an important enzyme of the folate pathway that catalyzes the reduction of dihydrofolate to tetrahydrofolate, by using NADPH as cofactor. This reaction is essential for cell replication, as this pathway results in the synthesis of nucleobases that build the DNA. That's the reason why DHFR inhibitors are used for treating bacterial infections and some types of cancer. Trypanosoma cruzi, a protozoa that causes Chagas disease, is one of the organisms that express DHFR, besides Homo sapiens itself. This work analyzed known ligands and the structure of the protein expressed by both organisms, aiming to identify divergence points that could be explored for designing selective drugs for Chagas disease treatment. The 6 proteins crystallographic models from T. cruzi and 2 from H. sapiens were obtained from protein data bank (PDB) after the application of quality filters. The amino acid sequence of each model was analyzed by Clustal Omega, its tridimensional structure by Pymol and Chimera X and the cavity analysis by CavityPlus, that also generated the pharmacophore from both targets. The primary structure analysis identified mutations on three amino acids on the parasite christal, which may be explained by different evolutive paths from segregated groups, although none of the observed mutations are on the active site region. The model's analysis allowed the identification of 24 amino acids that are closer than 5 Å from the T. cruzi ligands, 5 of them responsible for hydrogen interactions on at least one of the ligands analyzed. 18 of them are repeated on the human protein or are replaced by another amino acid that preserves the same interaction. As by the differences observed that shall be highlighted, asparagine 44 is replaced by a proline on the human protein, and proline 92 by a lysin. The cavity analysis identified three cavities on each protein, although only the cavities of the active site are druggables. The human protein cavity is bigger and longer, besides it looks like its a tunnel, when the parasite protein is open, that opening allows ligands with benzene ring meta substituted to explore the existing regions of the T. cruzi protein that is closed on the human protein. Lastly, the pharmacophore from both proteins was identified, it shows differences on size and angulation that also could be explored in the designing of selective drugs
Assuntos
Preparações Farmacêuticas/análise , Células/classificação , Quimioinformática/instrumentação , Aminoácidos/agonistas , Neoplasias/patologia , Asparagina/análogos & derivados , DNA/efeitos adversosRESUMO
Peripheral venous hypertension has emerged as a prominent characteristic of venous disease (VD). This disease causes lower limb edema due to impaired blood transport in the veins. The phlebotonic drugs in use showed moderate evidence for reducing edema slightly in the lower legs and little or no difference in the quality of life. To enhance the probability of favorable experimental results, a virtual screening procedure was employed to identify molecules with potential therapeutic activity in VD. Compounds obtained from multiple databases, namely AC Discovery, NuBBE, BIOFACQUIM, and InflamNat, were compared with reference compounds. The examination of structural similarity, targets, and signaling pathways in venous diseases allows for the identification of compounds with potential usefulness in VD. The computational tools employed were rcdk and chemminer from R-Studio and Cytoscape. An extended fingerprint analysis allowed us to obtain 1846 from 41,655 compounds compiled. Only 229 compounds showed pharmacological targets in the PubChem server, of which 84 molecules interacted with the VD network. Because of their descriptors and multi-target capacity, only 18 molecules of 84 were identified as potential candidates for experimental evaluation. We opted to evaluate the berberine compound because of its affordability, and extensive literature support. The experiment showed the proposed activity in an acute venous hypertension model.
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Medicamentos de Ervas Chinesas , Hipertensão , Humanos , Farmacologia em Rede , Qualidade de Vida , Transdução de Sinais , Edema/tratamento farmacológico , Hipertensão/tratamento farmacológico , Medicamentos de Ervas Chinesas/farmacologia , Simulação de Acoplamento MolecularRESUMO
Lipophilicity is a physicochemical property with wide relevance in drug design, computational biology, food, environmental and medicinal chemistry. Lipophilicity is commonly expressed as the partition coefficient for neutral molecules, whereas for molecules with ionizable groups, the distribution coefficient (D) at a given pH is used. The logDpH is usually predicted using a pH correction over the logPN using the pKa of ionizable molecules, while often ignoring the apparent ion pair partitioning ( P IP app ) ${{\rm{(}}P_{{\rm{IP}}}^{{\rm{app}}} )}$ . In this work, we studied the impact of ( P IP app ) ${{\rm{(}}P_{{\rm{IP}}}^{{\rm{app}}} )}$ on the prediction of both the experimental lipophilicity of small molecules and experimental lipophilicity-based applications and metrics such as lipophilic efficiency (LipE), distribution of spiked drugs in milk products, and pH-dependent partition of water contaminants in synthetic passive samples such as silicones. Our findings show that better predictions are obtained by considering the apparent ion pair partitioning. In this context, we developed machine learning algorithms to determine the cases that P I app ${P_{\rm{I}}^{{\rm{app}}} }$ should be considered. The results indicate that small, rigid, and unsaturated molecules with logPN close to zero, which present a significant proportion of ionic species in the aqueous phase, were better modeled using the apparent ion pair partitioning ( P IP app ) ${{\rm{(}}P_{{\rm{IP}}}^{{\rm{app}}} )}$ . Finally, our findings can serve as guidance to the scientific community working in early-stage drug design, food, and environmental chemistry.