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Elife ; 102021 08 03.
Artigo em Inglês | MEDLINE | ID: mdl-34340747


The discovery of a drug requires over a decade of intensive research and financial investments - and still has a high risk of failure. To reduce this burden, we developed the resource, which incorporates 250,000 bioactive molecules, and studied their enzymatic metabolic targets, fate, and toxicity. includes a unique fingerprint that identifies reactive similarities between drug-drug and drug-metabolite pairs. We validated the application, scope, and performance of over similar methods in the field on golden standard datasets describing drugs and metabolites sharing reactivity, drug toxicities, and drug targets. We use to evaluate inhibition and toxicity by the anticancer drug 5-fluorouracil, and suggest avenues to alleviate its side effects. We propose shikimate 3-phosphate for targeting liver-stage malaria with minimal impact on the human host cell. Finally, suggests over 1300 candidate drugs and food molecules to target COVID-19 and explains their inhibitory mechanism for further experimental screening. The database is accessible online to systematically identify the reactivity of small molecules and druggable enzymes with practical applications in lead discovery and drug repurposing.

Desenho de Fármacos , Descoberta de Drogas/métodos , Reposicionamento de Medicamentos , Preparações Farmacêuticas/metabolismo , Animais , Antimetabólitos Antineoplásicos/química , Antimetabólitos Antineoplásicos/metabolismo , Antivirais/química , Antivirais/farmacologia , COVID-19/tratamento farmacológico , Bases de Dados de Produtos Farmacêuticos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/etiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/metabolismo , Fluoruracila/química , Fluoruracila/metabolismo , Humanos , Preparações Farmacêuticas/química , Fluxo de Trabalho
Nat Commun ; 12(1): 1760, 2021 03 19.
Artigo em Inglês | MEDLINE | ID: mdl-33741955


Plant natural products (PNPs) and their derivatives are important but underexplored sources of pharmaceutical molecules. To access this untapped potential, the reconstitution of heterologous PNP biosynthesis pathways in engineered microbes provides a valuable starting point to explore and produce novel PNP derivatives. Here, we introduce a computational workflow to systematically screen the biochemical vicinity of a biosynthetic pathway for pharmaceutical compounds that could be produced by derivatizing pathway intermediates. We apply our workflow to the biosynthetic pathway of noscapine, a benzylisoquinoline alkaloid (BIA) with a long history of medicinal use. Our workflow identifies pathways and enzyme candidates for the production of (S)-tetrahydropalmatine, a known analgesic and anxiolytic, and three additional derivatives. We then construct pathways for these compounds in yeast, resulting in platforms for de novo biosynthesis of BIA derivatives and demonstrating the value of cheminformatic tools to predict reactions, pathways, and enzymes in synthetic biology and metabolic engineering.

Produtos Biológicos/metabolismo , Vias Biossintéticas/genética , Biologia Computacional/métodos , Engenharia Metabólica/métodos , Noscapina/metabolismo , Saccharomyces cerevisiae/metabolismo , Alcaloides/biossíntese , Benzilisoquinolinas/metabolismo , Noscapina/química , Plantas/genética , Plantas/metabolismo , Saccharomyces cerevisiae/genética , Software
ACS Synth Biol ; 9(6): 1479-1482, 2020 06 19.
Artigo em Inglês | MEDLINE | ID: mdl-32421310


The ATLAS of Biochemistry is a repository of both known and novel predicted biochemical reactions between biological compounds listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG). ATLAS was originally compiled based on KEGG 2015, though the number of KEGG reactions has increased by almost 20 percent since then. Here, we present an updated version of ATLAS created from KEGG 2018 using an increased set of generalized reaction rules. Furthermore, we improved the accuracy of the enzymes that are predicted for catalyzing novel reactions. ATLAS now contains ∼150 000 reactions, out of which 96% are novel. In this report, we present detailed statistics on the updated ATLAS and highlight the improvements with regard to the previous version. Most importantly, 107 reactions predicted in the original ATLAS are now known to KEGG, which validates the predictive power of our approach. The updated ATLAS is available at

Bases de Dados Factuais , Enzimas/metabolismo , Redes e Vias Metabólicas
Proc Natl Acad Sci U S A ; 116(15): 7298-7307, 2019 04 09.
Artigo em Inglês | MEDLINE | ID: mdl-30910961


Thousands of biochemical reactions with characterized activities are "orphan," meaning they cannot be assigned to a specific enzyme, leaving gaps in metabolic pathways. Novel reactions predicted by pathway-generation tools also lack associated sequences, limiting protein engineering applications. Associating orphan and novel reactions with known biochemistry and suggesting enzymes to catalyze them is a daunting problem. We propose the method BridgIT to identify candidate genes and catalyzing proteins for these reactions. This method introduces information about the enzyme binding pocket into reaction-similarity comparisons. BridgIT assesses the similarity of two reactions, one orphan and one well-characterized nonorphan reaction, using their substrate reactive sites, their surrounding structures, and the structures of the generated products to suggest enzymes that catalyze the most-similar nonorphan reactions as candidates for also catalyzing the orphan ones. We performed two large-scale validation studies to test BridgIT predictions against experimental biochemical evidence. For the 234 orphan reactions from the Kyoto Encyclopedia of Genes and Genomes (KEGG) 2011 (a comprehensive enzymatic-reaction database) that became nonorphan in KEGG 2018, BridgIT predicted the exact or a highly related enzyme for 211 of them. Moreover, for 334 of 379 novel reactions in 2014 that were later cataloged in KEGG 2018, BridgIT predicted the exact or highly similar enzymes. BridgIT requires knowledge about only four connecting bonds around the atoms of the reactive sites to correctly annotate proteins for 93% of analyzed enzymatic reactions. Increasing to seven connecting bonds allowed for the accurate identification of a sequence for nearly all known enzymatic reactions.

Bases de Dados de Proteínas , Enzimas , Anotação de Sequência Molecular , Análise de Sequência de Proteína , Sítios de Ligação , Enzimas/química , Enzimas/genética