Molecular dynamics and density functional studies on the metabolic selectivity of antipsychotic thioridazine by cytochrome P450 2D6: Connection with crystallographic and metabolic results

Sasahara, Katsunori; Mashima, Akira; Yoshida, Tatsusada; Chuman, Hiroshi

doi:10.1016/j.bmc.2015.07.043

Cited by 11 publications

(10 citation statements)

References 37 publications

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“…Hence, QM calculation is very helpful in ADMET prediction. Extensively increasing studies involving the application of QM methods have been conducted to describe ADMET properties of new compounds (Li et al, 2012 ; Taxak et al, 2013 ; Kavitha et al, 2015 ; Sasahara et al, 2015 ; Evangelista et al, 2016 ; Mondal et al, 2017 ). The ab initio (Hartree-Fock), semiempirical (AM1 and PM3), and density functional theory (DFT) approaches are most commonly used in these studies (Silva-Junior et al, 2017 ).…”

Section: In Silico Approachesmentioning

confidence: 99%

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Computational Approaches in Preclinical Studies on Drug Discovery and Development

Zhou

et al. 2020

Front. Chem.

210

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Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

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Section: In Silico Approachesmentioning

confidence: 99%

“…The geometries compared well with the experimental value. Sasahara et al ( 2015 ) used the DFT method to evaluate the metabolic selectivity of antipsychotic thioridazine by CYP450 2D6. This study revealed the importance of the substrate orientation in the reaction center of this enzyme for the metabolic reaction.…”

Section: In Silico Approachesmentioning

confidence: 99%

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Zhou

et al. 2020

Front. Chem.

210

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“…While DFT studies on antipsychotic drugs [129][130][131][132] and of antidepressants [133][134][135] are commonly found in the literature, works on the antioxidant activity of such compounds are still scarce. In a recent study by some of us, [123] the free radical scavenging activity of fluoxetine (20) and serotonin (18, Scheme 4) was investigated using a meta-hybrid functional (M06-2X [136]) in the gas phase and in the solvent.…”

Section: In Silico Approachesmentioning

confidence: 99%

Antioxidant Potential of Psychotropic Drugs: From Clinical Evidence to In Vitro and In Vivo Assessment and toward a New Challenge for in Silico Molecular Design

et al. 2020

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Due to high oxygen consumption, the brain is particularly vulnerable to oxidative stress, which is considered an important element in the etiopathogenesis of several mental disorders, including schizophrenia, depression and dependencies. Despite the fact that it is not established yet whether oxidative stress is a cause or a consequence of clinic manifestations, the intake of antioxidant supplements in combination with the psychotropic therapy constitutes a valuable solution in patients’ treatment. Anyway, some drugs possess antioxidant capacity themselves and this aspect is discussed in this review, focusing on antipsychotics and antidepressants. In the context of a collection of clinical observations, in vitro and in vivo results are critically reported, often highlighting controversial aspects. Finally, a new challenge is discussed, i.e., the possibility of assessing in silico the antioxidant potential of these drugs, exploiting computational chemistry methodologies and machine learning. Despite the physiological environment being incredibly complex and the detection of meaningful oxidative stress biomarkers being all but an easy task, a rigorous and systematic analysis of the structural and reactivity properties of antioxidant drugs seems to be a promising route to better interpret therapeutic outcomes and provide elements for the rational design of novel drugs.

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“…The latter has proven to be of particular value for fast (1 ns production time) and accurate CYP2D6 binding affinity predictions (RMSD error < 1 kcal/mol) (Perić-Hassler et al, 2013). Several studies have employed MD simulations to investigate channel formation (de Waal et al, 2014), water dynamics (Santos et al, 2010), effect and importance of the membrane on CYP behavior (Barnaba, Gentry, Sumangala, & Ramamoorthy, 2017;Berka et al, 2013;Jeřábek et al, 2016;, binding and reaction mechanisms (Maréchal et al, 2008;Sasahara, Mashima, Yoshida, & Chuman, 2015), refinement of docking results (Wang et al, 2009), and CYP2D6 polymorphism (de Waal et al, 2014). These studies are essential for extending our current CYP2D6 knowledge and subsequent seamless integration of this information into advanced CYP2D6 in silico techniques.…”

Section: Molecular Dynamicsmentioning

confidence: 99%

Out‐compute drug side effects: Focus on cytochrome P450 2D6 modeling

Don

Smieško

2018

WIREs Comput Mol Sci

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Understanding the way in which drugs are metabolized by cytochrome P450 2D6 (CYP2D6) and hence the underlying mechanisms that define potential toxicity is crucial to avoid adverse reactions. The high occurrence of CYP2D6 polymorphs enhances the complexity of the toxicity assessment of a drug candidate and should be tackled from early drug discovery phase on. The recent increase in available mammalian CYP2D6 X-ray structures opens the gateway to the development of in silico three-dimensional CYP2D6 toxicity prediction techniques that address also the major clinically relevant allelic variants. This review presents the basic principles needed for comprehending the enzyme particularities, gives a concise overview of several clinical relevant allelic CYP2D6 variants, and explores the state-of-the-art CYP2D6 research field to accelerate the development and use of such integrative in silico modeling technologies. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Structure and Mechanism > Molecular Structures Software > Molecular Modeling K E Y W O R D S adverse effects, CYP2D6, cytochrome P450, polymorphism, rational drug design, toxicity 1 | INTRODUCTION 1.1 | Cytochrome P450 2D6 metabolic relevance in drug discoveryEarly toxicity evaluation is of great importance to improve the worrying drug attrition rates. In the last two decades, tighter drug safety regulations steered the pharmaceutical industry to invest more time and resources in reduction of drug failures due to toxicity in early drug development (Waring et al., 2015). Accurate prediction of the toxicity profile of a potential drug candidate is a multifaceted challenge, especially since in essence all molecules are toxic to some degree for living organisms. To define the border between toxic and nontoxic, both the pharmacokinetics and the pharmacodynamics of the drug need to be assessed. Absorption, distribution, metabolism, and excretion processes strongly impact the bioavailability and hence the extent of drug toxicity in the body. Xenobiotic metabolism is a critical process in drug clearance and avoiding any potential metabolic liability is one of the major endpoints addressed in assessment studies during the early phase clinical trials. Drugs administered orally can either be readily excreted or undergo a metabolic biotransformation by chemical modification of the compound into a more soluble product facilitating the renal excretion. The generally known four types of hepatic reactions during the biotransformation are categorized into phase I (oxidation, hydrolysis, and reduction) and phase II (conjugation). Phase I reactions are dominated by the cytochrome enzyme P450 superfamily (abbreviated P450 henceforth). Cytochrome

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Molecular dynamics and density functional studies on the metabolic selectivity of antipsychotic thioridazine by cytochrome P450 2D6: Connection with crystallographic and metabolic results

Cited by 11 publications

References 37 publications

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Antioxidant Potential of Psychotropic Drugs: From Clinical Evidence to In Vitro and In Vivo Assessment and toward a New Challenge for in Silico Molecular Design

Out‐compute drug side effects: Focus on cytochrome P450 2D6 modeling

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