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1.
Nat Commun ; 11(1): 4941, 2020 10 02.
Artigo em Inglês | MEDLINE | ID: mdl-33009412

RESUMO

Methods to directly inhibit gene expression using small molecules hold promise for the development of new therapeutics targeting proteins that have evaded previous attempts at drug discovery. Among these, small molecules including the drug-like compound PF-06446846 (PF846) selectively inhibit the synthesis of specific proteins, by stalling translation elongation. These molecules also inhibit translation termination by an unknown mechanism. Using cryo-electron microscopy (cryo-EM) and biochemical approaches, we show that PF846 inhibits translation termination by arresting the nascent chain (NC) in the ribosome exit tunnel. The arrested NC adopts a compact α-helical conformation that induces 28 S rRNA nucleotide rearrangements that suppress the peptidyl transferase center (PTC) catalytic activity stimulated by eukaryotic release factor 1 (eRF1). These data support a mechanism of action for a small molecule targeting translation that suppresses peptidyl-tRNA hydrolysis promoted by eRF1, revealing principles of eukaryotic translation termination and laying the foundation for new therapeutic strategies.


Assuntos
Terminação Traducional da Cadeia Peptídica , Preparações Farmacêuticas/metabolismo , Linhagem Celular , Humanos , Modelos Moleculares , Mutação/genética , Conformação Proteica , RNA Ribossômico/metabolismo , Ribossomos/metabolismo , Ribossomos/ultraestrutura
2.
Nat Protoc ; 15(9): 2837-2866, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32814837

RESUMO

The accurate resolution of the binding mechanism of a ligand to its molecular target is fundamental to develop a successful drug design campaign. Free-energy calculations, which provide the energy value of the ligand-protein binding complex, are essential for resolving the binding mode of the ligand. The accuracy of free-energy calculation methods is counteracted by their poor user-friendliness, which hampers their broad application. Here we present the Funnel-Metadynamics Advanced Protocol (FMAP), which is a flexible and user-friendly graphical user interface (GUI)-based protocol to perform funnel metadynamics, a binding free-energy method that employs a funnel-shape restraint potential to reveal the ligand binding mode and accurately calculate the absolute ligand-protein binding free energy. FMAP guides the user through all phases of the free-energy calculation process, from preparation of the input files, to production simulation, to analysis of the results. FMAP delivers the ligand binding mode and the absolute protein-ligand binding free energy as outputs. Alternative binding modes and the role of waters are also elucidated, providing a detailed description of the ligand binding mechanism. The entire protocol on the paradigmatic system benzamidine-trypsin, composed of ~105 k atoms, took ~2.8 d using the Cray XC50 piz Daint cluster at the Swiss National Supercomputing Centre.


Assuntos
Gráficos por Computador , Modelos Moleculares , Ligantes , Terapia de Alvo Molecular , Preparações Farmacêuticas/metabolismo , Ligação Proteica , Conformação Proteica , Termodinâmica , Fatores de Tempo , Interface Usuário-Computador
3.
BMC Bioinformatics ; 21(1): 322, 2020 Jul 20.
Artigo em Inglês | MEDLINE | ID: mdl-32689927

RESUMO

BACKGROUND: The study of DNA binding protein (DBP)-drug interactions can open a breakthrough for the treatment of genetic diseases and cancers. Currently, network-based methods are widely used for protein-drug interaction prediction, and many hidden relationships can be found through network analysis. We proposed a DCA (drug-cluster association) model for predicting DBP-drug interactions. The clusters are some similarities in the drug-binding site trimmers with their physicochemical properties. First, DBPs-drug binding sites are extracted from scPDB database. Second, each binding site is represented as a trimer which is obtained by sliding the window in the binding sites. Third, the trimers are clustered based on the physicochemical properties. Fourth, we build the network by generating the interaction matrix for representing the DCA network. Fifth, three link prediction methods are detected in the network. Finally, the common neighbor (CN) method is selected to predict drug-cluster associations in the DBP-drug network model. RESULT: This network shows that drugs tend to bind to positively charged sites and the binding process is more likely to occur inside the DBPs. The results of the link prediction indicate that the CN method has better prediction performance than the PA and JA methods. The DBP-drug network prediction model is generated by using the CN method which predicted more accurately drug-trimer interactions and DBP-drug interactions. Such as, we found that Erythromycin (ERY) can establish an interaction relationship with HTH-type transcriptional repressor, which is fitted well with silico DBP-drug prediction. CONCLUSION: The drug and protein bindings are local events. The binding of the drug-DBPs binding site represents this local binding event, which helps to understand the mechanism of DBP-drug interactions.


Assuntos
Biologia Computacional/métodos , Proteínas de Ligação a DNA/metabolismo , Bases de Dados Factuais , Interações Medicamentosas , Preparações Farmacêuticas/metabolismo , Sítios de Ligação , Simulação por Computador , Proteínas de Ligação a DNA/química , Humanos , Preparações Farmacêuticas/química , Ligação Proteica
4.
Mol Cell ; 79(1): 191-198.e3, 2020 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-32619469

RESUMO

We recently used CRISPRi/a-based chemical-genetic screens and cell biological, biochemical, and structural assays to determine that rigosertib, an anti-cancer agent in phase III clinical trials, kills cancer cells by destabilizing microtubules. Reddy and co-workers (Baker et al., 2020, this issue of Molecular Cell) suggest that a contaminating degradation product in commercial formulations of rigosertib is responsible for the microtubule-destabilizing activity. Here, we demonstrate that cells treated with pharmaceutical-grade rigosertib (>99.9% purity) or commercially obtained rigosertib have qualitatively indistinguishable phenotypes across multiple assays. The two formulations have indistinguishable chemical-genetic interactions with genes that modulate microtubule stability, both destabilize microtubules in cells and in vitro, and expression of a rationally designed tubulin mutant with a mutation in the rigosertib binding site (L240F TUBB) allows cells to proliferate in the presence of either formulation. Importantly, the specificity of the L240F TUBB mutant for microtubule-destabilizing agents has been confirmed independently. Thus, rigosertib kills cancer cells by destabilizing microtubules, in agreement with our original findings.


Assuntos
Antineoplásicos/farmacologia , Proliferação de Células , Glicina/análogos & derivados , Microtúbulos/efeitos dos fármacos , Neoplasias/patologia , Preparações Farmacêuticas/metabolismo , Sulfonas/farmacologia , Tubulina (Proteína)/metabolismo , Células Cultivadas , Cristalografia por Raios X , Contaminação de Medicamentos , Glicina/farmacologia , Humanos , Mutação , Neoplasias/tratamento farmacológico , Neoplasias/metabolismo , Preparações Farmacêuticas/química , Conformação Proteica , Tubulina (Proteína)/química , Tubulina (Proteína)/genética
5.
BMC Bioinformatics ; 21(1): 309, 2020 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-32664863

RESUMO

BACKGROUND: Despite continued efforts using chemical similarity methods in virtual screening, currently developed approaches suffer from time-consuming multistep procedures and low success rates. We recently developed a machine learning-based chemical binding similarity model considering common structural features from molecules binding to the same, or evolutionarily related targets. The chemical binding similarity measures the resemblance of chemical compounds in terms of binding site similarity to better describe functional similarities that arise from target binding. In this study, we have shown how the chemical binding similarity could be used in virtual screening together with the conventional structure-based methods. RESULTS: The chemical binding similarity, receptor-based pharmacophore, chemical structure similarity, and molecular docking methods were evaluated to identify an effective virtual screening procedure for desired target proteins. When we tested the chemical binding similarity method with test sets of 51 kinases, it outperformed the traditional structural similarity-based methods as well as structure-based methods, such as molecular docking and receptor-based pharmacophore modeling, in terms of finding active compounds. We further validated the results by performing virtual screening (using the chemical binding similarity and receptor-based pharmacophore methods) against a completely blind dataset for mitogen-activated protein kinase kinase 1 (MEK1), ephrin type-B receptor 4 (EPHB4) and wee1-like protein kinase (WEE1). The in vitro kinase binding assay confirmed that 6 out of 13 (46.2%) for MEK1 and 2 out of 12 (16.7%) for EPHB4 were newly identified only by the chemical binding similarity model. CONCLUSIONS: We report that the virtual screening results could further be improved by combining the chemical binding similarity model with 3D-QSAR pharmacophore and molecular docking models. Not only the new inhibitors are identified in this study, but also many of the identified molecules have low structural similarity scores against already reported inhibitors and that show the revelation of novel scaffolds.


Assuntos
Simulação de Acoplamento Molecular , Relação Quantitativa Estrutura-Atividade , Área Sob a Curva , Sítios de Ligação , Humanos , Aprendizado de Máquina , Compostos Orgânicos/química , Compostos Orgânicos/metabolismo , Preparações Farmacêuticas/química , Preparações Farmacêuticas/metabolismo , Ligação Proteica , Proteínas Quinases/química , Proteínas Quinases/metabolismo , Curva ROC
6.
SAR QSAR Environ Res ; 31(6): 457-475, 2020 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-32627677

RESUMO

In silico methods are often used for predicting pharmacokinetic properties of drugs due to their simplicity and cost-effectiveness. This study evaluates the penetration of 83 active pharmaceutical ingredients into human breast milk with an experimental milk-to-plasma ratio (M/P) obtained from the literature. Multiple linear regression (MLR), partial least squares (PLS) and random forest (RF) regression methods were compared to uncover the relationship between physicochemical, pharmacokinetic and membrane crossing properties of active pharmaceutical ingredients (APIs) using their rapid reference measurement value (Rf values), thin-layer chromatography (TLC) data from albumin-impregnated plates. Molecular descriptors of APIs proven to be important for their crossing into breast milk, including protein binding, ionisation state and lipophilicity and TLC data, have been included in the development of the prediction models. The best regression results were achieved by MLR (r 2 = 0.83 and r 2 = 0.86, n = 28) and RF (r 2 = 0.85, n = 58). In addition, the discriminant function analysis (DFA) was performed on acidic, basic and neutral drugs separately and showed a prediction accuracy of 93%, with M/P included as the discriminating variable.


Assuntos
Análise dos Mínimos Quadrados , Modelos Lineares , Leite Humano/química , Preparações Farmacêuticas/metabolismo , Relação Quantitativa Estrutura-Atividade , Preparações Farmacêuticas/química
7.
BMC Bioinformatics ; 21(1): 231, 2020 Jun 05.
Artigo em Inglês | MEDLINE | ID: mdl-32503412

RESUMO

BACKGROUND: During the last decade, there has been a surge towards computational drug repositioning owing to constantly increasing -omics data in the biomedical research field. While numerous existing methods focus on the integration of heterogeneous data to propose candidate drugs, it is still challenging to substantiate their results with mechanistic insights of these candidate drugs. Therefore, there is a need for more innovative and efficient methods which can enable better integration of data and knowledge for drug repositioning. RESULTS: Here, we present a customizable workflow (PS4DR) which not only integrates high-throughput data such as genome-wide association study (GWAS) data and gene expression signatures from disease and drug perturbations but also takes pathway knowledge into consideration to predict drug candidates for repositioning. We have collected and integrated publicly available GWAS data and gene expression signatures for several diseases and hundreds of FDA-approved drugs or those under clinical trial in this study. Additionally, different pathway databases were used for mechanistic knowledge integration in the workflow. Using this systematic consolidation of data and knowledge, the workflow computes pathway signatures that assist in the prediction of new indications for approved and investigational drugs. CONCLUSION: We showcase PS4DR with applications demonstrating how this tool can be used for repositioning and identifying new drugs as well as proposing drugs that can simulate disease dysregulations. We were able to validate our workflow by demonstrating its capability to predict FDA-approved drugs for their known indications for several diseases. Further, PS4DR returned many potential drug candidates for repositioning that were backed up by epidemiological evidence extracted from scientific literature. Source code is freely available at https://github.com/ps4dr/ps4dr.


Assuntos
Preparações Farmacêuticas/metabolismo , Interface Usuário-Computador , Ensaios Clínicos como Assunto , Biologia Computacional/métodos , Reposicionamento de Medicamentos , Estudo de Associação Genômica Ampla , Humanos , Transcriptoma , Fluxo de Trabalho
8.
FEBS Open Bio ; 10(6): 995-1004, 2020 06.
Artigo em Inglês | MEDLINE | ID: covidwho-186395

RESUMO

A novel coronavirus [severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or 2019 novel coronavirus] has been identified as the pathogen of coronavirus disease 2019. The main protease (Mpro , also called 3-chymotrypsin-like protease) of SARS-CoV-2 is a potential target for treatment of COVID-19. A Mpro homodimer structure suitable for docking simulations was prepared using a crystal structure (PDB ID: 6Y2G; resolution 2.20 Å). Structural refinement was performed in the presence of peptidomimetic α-ketoamide inhibitors, which were previously disconnected from each Cys145 of the Mpro homodimer, and energy calculations were performed. Structure-based virtual screenings were performed using the ChEMBL database. Through a total of 1 485 144 screenings, 64 potential drugs (11 approved, 14 clinical, and 39 preclinical drugs) were predicted to show high binding affinity with Mpro . Additional docking simulations for predicted compounds with high binding affinity with Mpro suggested that 28 bioactive compounds may have potential as effective anti-SARS-CoV-2 drug candidates. The procedure used in this study is a possible strategy for discovering anti-SARS-CoV-2 drugs from drug libraries that may significantly shorten the clinical development period with regard to drug repositioning.


Assuntos
Betacoronavirus/enzimologia , Quimases/metabolismo , Infecções por Coronavirus/metabolismo , Descoberta de Drogas/métodos , Reposicionamento de Medicamentos/métodos , Preparações Farmacêuticas/metabolismo , Pneumonia Viral/metabolismo , Inibidores de Serino Proteinase/metabolismo , Proteínas Virais/metabolismo , Betacoronavirus/efeitos dos fármacos , Domínio Catalítico , Quimases/antagonistas & inibidores , Quimases/química , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/virologia , Cristalização , Bases de Dados de Compostos Químicos , Humanos , Modelos Moleculares , Simulação de Acoplamento Molecular , Pandemias , Preparações Farmacêuticas/química , Pneumonia Viral/tratamento farmacológico , Pneumonia Viral/virologia , Inibidores de Serino Proteinase/química , Proteínas Virais/química
9.
Yakugaku Zasshi ; 140(5): 599-608, 2020.
Artigo em Japonês | MEDLINE | ID: mdl-32378658

RESUMO

Although oral drugs account for 80% of the world drug market, many difficulties arise in their development. The drug absorption profile after oral administration may be influenced by multiple factors, including dosing conditions and physiological state of the gastrointestinal (GI) tract. Variability in GI fluid volume may influence the absorption characteristics. Indeed, the contributions of passive diffusion, transporters, and metabolic enzymes depend on GI drug concentration, which is influenced by changes in GI fluid volume. However, this important variable has been neglected in many prediction methods for oral drug absorption and drug interactions, and for convenience it is often assumed that the GI water volume is fixed at a constant value. Major global regulatory agencies such as the U.S. Food and Drug Administration (FDA), European Medicines Agency (EMA), and Japanese Pharmaceuticals and Medical Devices Agency (PMDA) recommend using a constant fluid volume of 250 mL (the fluid volume of a glass of water) to estimate the theoretical GI concentration of drugs after oral administration. However, the actual volume of water in the GI tract is both time- and site-dependent as a result of water intake, absorption, secretion, and GI transit. This review article summarizes our data showing that luminal water volume is influenced by the osmolality of the applied solution, and illustrates how this effect may contribute to changes in GI drug concentration, resulting in altered drug absorption.


Assuntos
Interações Medicamentosas , Trato Gastrointestinal/metabolismo , Absorção Intestinal , Preparações Farmacêuticas/administração & dosagem , Preparações Farmacêuticas/metabolismo , Membro 1 da Subfamília B de Cassetes de Ligação de ATP , Administração Oral , Água Corporal/metabolismo , Humanos , Modelos Biológicos , Concentração Osmolar , Valor Preditivo dos Testes
10.
J Chromatogr A ; 1622: 461160, 2020 Jul 05.
Artigo em Inglês | MEDLINE | ID: mdl-32450990

RESUMO

The glutathione (GSH) trapping assay is commonly utilized for the screening and characterization of reactive metabolites produced by drug metabolism. This study describes a fluorous derivatization method for a more sensitive and selective analysis of reactive metabolites trapped by GSH using liquid chromatography-tandem mass spectrometry (LC-MS/MS). In this study, the GSH-trapped reactive metabolites, which were obtained after incubation of the test compounds with human liver microsome (HLM) in the presence of GSH and NADPH, were derivatized using the perfluoroalkylamine reagent through oxazolone chemistry. Since this reaction enabled the selective modification of the α-carboxyl group in GSH, the structural compositions of the metabolites were not affected by the derivatization. Furthermore, the selective analysis of the resulting derivatives could be performed using perfluoroalkyl-modified stationary phase LC separation via the interaction between the perfluoroalkyl-containing compounds, such as fluorous affinity, followed by detection with the precursor ion and/or enhanced product ion scan modes in MS/MS. Finally, we demonstrated the applicability of this method by analyzing perfluoroalkyl derivatives of some drug metabolites trapped by GSH in HLM incubation.


Assuntos
Cromatografia Líquida/métodos , Flúor/química , Glutationa/análise , Espectrometria de Massas em Tandem/métodos , Glutationa/química , Humanos , Microssomos Hepáticos/metabolismo , Preparações Farmacêuticas/química , Preparações Farmacêuticas/metabolismo
11.
PLoS One ; 15(5): e0230950, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32365122

RESUMO

A pharmacogenomics-based pathway represents a series of reactions that occur between drugs and genes in the human body after drug administration. PG-path is a pharmacogenomics-based pathway that standardizes and visualizes the components (nodes) and actions (edges) involved in pharmacokinetic and pharmacodynamic processes. It provides an intuitive understanding of the drug response in the human body. A pharmacokinetic pathway visualizes the absorption, distribution, metabolism, and excretion (ADME) at the systemic level, and a pharmacodynamic pathway shows the action of the drug in the target cell at the cellular-molecular level. The genes in the pathway are displayed in locations similar to those inside the body. PG-path allows personalized pathways to be created by annotating each gene with the overall impact degree of deleterious variants in the gene. These personalized pathways play a role in assisting tailored individual prescriptions by predicting changes in the drug concentration in the plasma. PG-path also supports counseling for personalized drug therapy by providing visualization and documentation.


Assuntos
Biologia Computacional/métodos , Redes e Vias Metabólicas/genética , Preparações Farmacêuticas/metabolismo , Farmacogenética/métodos , Medicina de Precisão/métodos , Software , Bases de Dados Genéticas , Tratamento Farmacológico/métodos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/genética , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/metabolismo , Absorção Gastrointestinal/genética , Estudos de Associação Genética , Humanos , Inativação Metabólica/efeitos dos fármacos , Inativação Metabólica/genética , Armazenamento e Recuperação da Informação/métodos , Redes e Vias Metabólicas/efeitos dos fármacos , Modelos Teóricos
12.
FEBS Open Bio ; 10(6): 995-1004, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32374074

RESUMO

A novel coronavirus [severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or 2019 novel coronavirus] has been identified as the pathogen of coronavirus disease 2019. The main protease (Mpro , also called 3-chymotrypsin-like protease) of SARS-CoV-2 is a potential target for treatment of COVID-19. A Mpro homodimer structure suitable for docking simulations was prepared using a crystal structure (PDB ID: 6Y2G; resolution 2.20 Å). Structural refinement was performed in the presence of peptidomimetic α-ketoamide inhibitors, which were previously disconnected from each Cys145 of the Mpro homodimer, and energy calculations were performed. Structure-based virtual screenings were performed using the ChEMBL database. Through a total of 1 485 144 screenings, 64 potential drugs (11 approved, 14 clinical, and 39 preclinical drugs) were predicted to show high binding affinity with Mpro . Additional docking simulations for predicted compounds with high binding affinity with Mpro suggested that 28 bioactive compounds may have potential as effective anti-SARS-CoV-2 drug candidates. The procedure used in this study is a possible strategy for discovering anti-SARS-CoV-2 drugs from drug libraries that may significantly shorten the clinical development period with regard to drug repositioning.


Assuntos
Betacoronavirus/enzimologia , Quimases/metabolismo , Infecções por Coronavirus/metabolismo , Descoberta de Drogas/métodos , Reposicionamento de Medicamentos/métodos , Preparações Farmacêuticas/metabolismo , Pneumonia Viral/metabolismo , Inibidores de Serino Proteinase/metabolismo , Proteínas Virais/metabolismo , Betacoronavirus/efeitos dos fármacos , Domínio Catalítico , Quimases/antagonistas & inibidores , Quimases/química , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/virologia , Cristalização , Bases de Dados de Compostos Químicos , Humanos , Modelos Moleculares , Simulação de Acoplamento Molecular , Pandemias , Preparações Farmacêuticas/química , Pneumonia Viral/tratamento farmacológico , Pneumonia Viral/virologia , Inibidores de Serino Proteinase/química , Proteínas Virais/química
13.
Pharm Res ; 37(6): 93, 2020 May 11.
Artigo em Inglês | MEDLINE | ID: mdl-32394114

RESUMO

PURPOSE: Here, first experiences with a prototype tool for high throughput (passive) permeability profiling, a 96-well plate comprising the Permeapad® membrane, are reported. The permeabilities of a set of drugs were determined and compared to published measures of oral absorption, such as human fraction absorbed (Fa) and in vitro permeability values obtained using other tools. METHODS: The tool consists of a 96-well bottom and screen plate with the artificial, phospholipid-based barrier (Permeapad®) mounted between the plates' lower and upper compartments. The permeability of 14 model compounds including high- and low-absorption drugs, cationic, anionic, zwitterionic and neutral molecules, was determined by quantifying the compounds' transport over time, deriving the steady-state flux from the linear part of the cumulative curves and calculating the apparent permeability (Papp). The membrane structure was investigated in a high-resolution digital light microscope. RESULTS: The Permeapad® 96-well plate was found suited to distinguish high and low absorption drugs and yielded a hyperbolic correlation to Fa. The Papp values obtained were congruent with those determined with in-house prepared Permeapad® in the Franz cell set-up. Furthermore, good to excellent correlations were seen with Caco-2 permeability (R2 = 0.70) and PAMPA permeability (R2 = 0.89). Microscopic investigation of the Permeapad® barrier revealed the formation of phospholipid vesicles and myelin figures in aqueous environment. CONCLUSION: The Permeapad® 96-well plate permeation set-up is a promising new tool for rapid and reproducible passive permeability profiling.


Assuntos
Portadores de Fármacos/química , Ensaios de Triagem em Larga Escala/métodos , Preparações Farmacêuticas/metabolismo , Fosfolipídeos/química , Células CACO-2 , Humanos , Membranas Artificiais , Modelos Biológicos , Modelos Químicos , Estrutura Molecular , Permeabilidade , Polivinil/química , Soluções/química , Relação Estrutura-Atividade
14.
Xenobiotica ; 50(11): 1370-1379, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32401667

RESUMO

We previously reported a prediction method for human pharmacokinetics (PK) using single species allometric scaling (SSS) and the complex Dedrick plot in chimeric mice with humanized liver to predict the total clearance (CLt), distribution volumes in steady state (Vdss) and plasma concentration-time profiles of several drugs metabolized by cytochrome P450 (P450) and non-P450 enzymes. In the present study, we examined eight compounds (bosentan, cerivastatin, fluvastatin, pitavastatin, pravastatin, repaglinide, rosuvastatin, valsartan) as typical organic anion transporting polypeptide (OATP) substrates and six compounds metabolized by P450 and non-P450 enzymes to evaluate the predictability of CLt, Vdss and plasma concentration-time profiles after intravenous administration to chimeric mice. The predicted CLt and Vdss of drugs that undergo OATP-mediated uptake and P450/non-P450-mediated metabolism reflected the observed data from humans within a threefold error range. We also examined the possibility of predicting plasma concentration-time profiles of drugs that undergo OATP-mediated uptake using the complex Dedrick plot in chimeric mice. Most profiles could be superimposed with observed profiles from humans within a two- to threefold error range. PK prediction using SSS and the complex Dedrick plot in chimeric mice can be useful for evaluating drugs that undergo both OATP-mediated uptake and P450/non-P450-mediated metabolism.


Assuntos
Fígado/metabolismo , Transportadores de Ânions Orgânicos/metabolismo , Preparações Farmacêuticas/metabolismo , Animais , Humanos , Inativação Metabólica , Taxa de Depuração Metabólica , Camundongos , Farmacocinética
15.
PLoS One ; 15(4): e0230726, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32251481

RESUMO

State-of-the-art approaches for the prediction of drug-target interactions (DTI) are based on various techniques, such as matrix factorisation, restricted Boltzmann machines, network-based inference and bipartite local models (BLM). In this paper, we propose the framework of Asymmetric Loss Models (ALM) which is more consistent with the underlying chemical reality compared with conventional regression techniques. Furthermore, we propose to use an asymmetric loss model with BLM to predict drug-target interactions accurately. We evaluate our approach on publicly available real-world drug-target interaction datasets. The results show that our approach outperforms state-of-the-art DTI techniques, including recent versions of BLM.


Assuntos
Biologia Computacional/métodos , Terapia de Alvo Molecular , Preparações Farmacêuticas/metabolismo , Modelos Lineares
18.
J Chromatogr A ; 1621: 461027, 2020 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-32276854

RESUMO

In the present study, 88 structurally- diverse drugs were investigated by biopartitioning micellar chromatography (BMC) using Brij-35 as surfactant under different chromatographic conditions. It was found that temperature and presence of NaCl have only a minor effect in BMC retention. Correlation of BMC retention factors with octanol-water partitioning required the inclusion of fractions of ionized species as additional parameters, showing that there is a weaker effect of ionization in BMC environment. Compared to Immobilized Artificial Membrane (IAM) Chromatography, BMC retention factors cover a relatively narrow span, two-fold smaller than retention factors on IAM stationary phases as a result of the presence of micelles facilitating elution of lipophilic compounds and the absence of secondary attractive electrostatic interactions in the BMC environment. Similarities/dissimilarities between BMC, octanol-water partitioning and IAM Chromatography were investigated by Linear Free Energy Relationships (LSER). BMC retention factors were used to construct relationships with cell permeability,% Human Oral Absorption (%HOA) and Plasma Protein Binding (%PPB). Linear BMC models were obtained with Caco-2 cell lines and Parallel Artificial Membrane Permeability Assay (PAMPA). For %HOA, a hyperbolic model was established upon incorporation of topological polar surface area (tPSA) as additional parameter. A sigmoidal model was constructed for %PPB and a linear one for the corresponding thermodynamic binding constant logK. In both cases inclusion of the fraction of anionic species with a positive sign was required reflecting the preference of human albumin for acidic drugs.


Assuntos
Cromatografia Líquida , Modelos Biológicos , Preparações Farmacêuticas/metabolismo , Absorção Fisiológica , Proteínas Sanguíneas/metabolismo , Células CACO-2 , Permeabilidade da Membrana Celular , Humanos , Modelos Lineares , Membranas Artificiais , Micelas , Octanóis/química , Polietilenoglicóis/química , Tensoativos/química , Termodinâmica , Água/química
19.
Drug Metab Rev ; 52(1): 139-156, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-32116054

RESUMO

There are more than 1000 species of microbes reside in the human gut, umbering∼1014 microbes. As the invisible organ of human beings, gut microbiota can usually participate in drug metabolism by producing specific enzymes, such as reductase and hydrolytic enzyme, thus affecting the efficacy, toxicity, and bioavailability of drugs. At least 30 commercially available drugs have been shown to be substrates of gut microbes-derived enzymes, and an increasing number of drugs may have the potential to contact with the distal gut with the help of improved release systems or poor solubility/permeability, more drugs are expected to be found to be metabolized through the gut flora. By collecting examples of intestinal flora participating in the metabolism of synthetic drugs and traditional Chinese medicine components, this article provides a comprehensive reference for future researchers to study drug metabolism by intestinal flora. Noticeably, the composition and quantity of intestinal flora varies among individuals, and can be affected by some drug administration (such as antibiotics) or environmental changes (acute plateau hypoxia). This seems to suggest that intestinal flora could have the potential to be a new drug target to affect the efficacy of drugs which can be metabolized by Intestinal flora. Accordingly, understanding the impact of intestinal flora on drug metabolism and clarifying the drug transformation process is of great significance for guiding rational clinical use, individualized use, toxicological evaluation, and promoting drug discovery and development.


Assuntos
Microbioma Gastrointestinal/fisiologia , Preparações Farmacêuticas/metabolismo , Animais , Medicamentos de Ervas Chinesas/metabolismo , Trato Gastrointestinal/metabolismo , Trato Gastrointestinal/microbiologia , Humanos , Farmacocinética
20.
Subcell Biochem ; 94: 383-397, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32189308

RESUMO

Albumin is widely conserved from vertebrates to invertebrates, and nature of mammalian albumins permit them to bind various endogenous ligands and drugs in the blood. It is known that at least two major ligand binding sites are present on the albumin molecule, which are referred to as Site I and Site II. These binding sites are thought to be almost completely conserved among mammals, even though the degree of binding to these sites are different depending on the physical and chemical properties of drugs and differences in the microenvironment in the binding pockets. In addition, the binding sites for medium and long-chain fatty acids are also well conserved among mammals, and it is considered that there are at least seven binding sites, including Site I and Site II. These bindings properties of albumin in the blood are also widely known to be important for transporting drugs and fatty acids to various tissues. It can therefore be concluded that albumin is one of the most important serum proteins for various ligands, and information on human albumin can be very useful in predicting the ligand binding properties of the albumin of other vertebrates.


Assuntos
Ácidos Graxos/metabolismo , Preparações Farmacêuticas/metabolismo , Albumina Sérica/metabolismo , Animais , Sítios de Ligação , Ácidos Graxos/química , Humanos , Preparações Farmacêuticas/química , Ligação Proteica , Albumina Sérica/química
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