Absorption, Distribution, Metabolism And Excretion Properties Research Articles

Use of hybrid molecular simulation techniques for systematic analysis of polyphenols as promising therapeutic agent against SARS-CoV-2

In our current study, we systematically report the four phenol classes via three-layer in silico screening approaches consisting of quantum chemical methods, molecular docking and molecular dynamics simulations. We studied the interactions of main protease (Mpro) and Nsp9 proteins of SARS-CoV-2 with four classes of polyphenolic compounds, where both proteins are crucial for virus replication. The phenols are extensively reported for medicinal applications, as these are antioxidants, anti-parasitic, anti-viral, anti-diabetic and anti-inflammatory compounds. Initial molecular docking study shows that among forty phenolic compounds the L9, L17, L26 and, L32 reveal the best binding energies with Mpro protein. Their values of docking score in terms of binding energy with Mpro protein is ranging from -5.7 to -6.8 kcal.mol−1. While on the other hands, L8, L11, L22 and, L34 exhibit the best docking scores with Nsp9 protein, which are ranging from -5.8 to -6.8 kcal.mol−1. Additionally, the lead compounds (ligands) were studied by quantum chemical methods for their optimized or the lowest energy structures, electronic properties, frontier molecular orbitals (FMOs) as well as molecular electrostatic potentials (MEPs). The global chemical descriptors are also calculated to explain the global reactivity trend for the lead compounds. To mimic the aqueous like environment, we added ions according to the electrostatic potential of the macromolecule, water molecules are being added to create physiologically relevant environment for studying biological molecules. Proteins, nucleic acids, and other biomolecules are typically surrounded by water molecules in biological systems. The addition of water molecules in MD simulations may provide a more accurate representation of their natural environment. The molecular dynamics simulations are performed for the complexes of best-docked lead compounds and for both proteins (Mpro and, Nsp9) over multiple replicate trajectories of 320 ns. The flexibility and stability behavior of the lead compounds in terms of RMSD and RMSF plots are analyzed through MD simulations results. The binding free energy of the best-docked lead compounds with both proteins in terms of Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis are calculated, which are found as -8.79 and -3.97 kcal.mol−1 for Mpro-L32 and Nsp9-L8 complexes, respectively. The pharmacokinetic analysis of the lead compounds are also performed to disclose their ADME (absorption, distribution, metabolism, and excretion) and toxic character using online server pkCSM. This allowed for a comprehensive understanding of how these compounds would behave in the organism, specifically focusing on their ADME properties. We believe that the current study can evoke the interest of scientific community by providing fundamental insights, which will ultimately lead in-vivo and in-vitro analysis to assess the studied phenolic therapeutic inhibitors against the SARS-CoV-2.

Evaluation of the antibacterial and inhibitory activity of the MepA efflux pump of Staphylococcus aureus by riparins I, II, III, and IV

The efflux pump mechanism contributes to the antibiotic resistance of widely distributed strains of Staphylococcus aureus. Therefore, in the present work, the ability of the riparins N-(4-methoxyphenethyl)benzamide (I), 2-hydroxy-N-[2-(4-methoxyphenyl)ethyl]benzamide (II), 2, 6-dihydroxy-N-[ 2-(4-methoxyphenyl)ethyl]benzamide (III), and 3,4,5-trimethoxy-N-[2-(4-methoxyphenethyl)benzamide (IV) as potential inhibitors of the MepA efflux pump in S. aureus K2068 (fluoroquinolone-resistant). In addition, we performed checkerboard assays to obtain more information about the activity of riparins as potential inhibitors of MepA efflux and also analyzed the ability of riparins to act on the permeability of the bacterial membrane of S. aureus by the fluorescence method with SYTOX Green. A molecular coupling assay was performed to characterize the interaction between riparins and MepA, and ADMET (absorption, distribution, metabolism, and excretion) properties were analyzed. We observed that I-IV riparins did not show direct antibacterial activity against S. aureus. However, combination assays with substrates of MepA, ciprofloxacin, and ethidium bromide (EtBr) revealed a potentiation of the efficacy of these substrates by reducing the minimum inhibitory concentration (MIC). Furthermore, increased EtBr fluorescence emission was observed for all riparins. The checkerboard assay showed synergism between riparins I, II, and III, ciprofloxacin, and EtBr. Furthermore, riparins III and IV exhibited permeability in the S. aureus membrane at a concentration of 200 μg/mL. Molecular docking showed that riparins I, II, and III bound in a different region from the binding site of chlorpromazine (standard pump inhibitor), indicating a possible synergistic effect with the reference inhibitor. In contrast, riparin IV binds in the same region as the chlorpromazine binding site. From the in silico ADMET prediction based on MPO, it could be concluded that the molecules of riparin I-IV present their physicochemical properties within the ideal pharmacological spectrum allowing their preparation as an oral drug. Furthermore, the prediction of cytotoxicity in liver cell lines showed a low cytotoxic effect for riparins I-IV.

Synthesis, Hirshfeld surface analysis, spectral investigations, DFT calculations, ADME studies and molecular docking of Hexahydropyrimidines derivative against dimeric Apolipoprotein A-IV

On Ethyl 6-(4-chlorophenyl)-4-hydroxy-2-oxo-4-(trifluoromethyl)hexahydropyrimidine-5-carboxylate (ECHFPC), X-ray crystallographic, FT-IR, DFT, MEP, UV-Vis, Molecular docking studies and ADME properties are conducted. From X-ray diffraction studies it shows that the structure belongs to a monoclinic system with space group P21/c. The molecular surface and hydrogen bonding interactions in the ECHFPC crystal structure were found and studied using a 2D fingerprint plot and Hirshfeld Surfaces. The calculated optimized geometry of the ECHFPC molecule is determined using DFT–B3LYP calculations with the 6-31++G (d, p) basis set and the experimental bond length and bond angles are compared. Molecular Electrostatic Potential (MEP) aids in the optimization of protein-ligand electrostatic interactions. The measured vibrational frequencies of the FT-IR spectrum are compared with experimental values and it shows good agreement. The small molecule (ECHFPC) docking experiments with the target protein revealed that it is a good molecule that docks well with dimeric Apolipoprotein A-IV protein. The comparison of ECHFPC with Statin drugs available in the market with dimeric Apolipoprotein A-IV (PDB ID: 3S84) was also discussed. The online server preADMET was used to measure the absorption, distribution, metabolism and excretion (ADME) properties.

Permeability Data of Organosulfur Garlic Compounds Estimated by Immobilized Artificial Membrane Chromatography: Correlation Across Several Biological Barriers.

Among healthy vegetables, those of the genus Allium stand out. Antioxidant and anti-inflammatory properties have been associated with these vegetables, attributed mainly to organosulfur compounds (OSCs). In turn, they are linked to a protective effect counteracting cardiovascular disease development. Now, to really ensure the bioactive efficacy of the said compounds once consumed, it is necessary to previously evaluate the ADME (absorption, distribution, metabolism, and excretion) profile. Alternatively, in vitro and in silico methods attempt to avoid or reduce experimental animals’ use and provide preliminary information on drugs’ ability to overcome the various biological barriers inherent in the ADME process. In this sense, in silico methods serve to provide primary information on drugs’ bioavailability mechanisms. High-performance liquid chromatography (HPLC) using a stationary phase composed of phospholipids, the so-called immobilized artificial membrane (IAM), has been widely recognized as a valuable alternative method to extract and quantify information about the structure and physicochemical properties of organic compounds which are extensively used in studies of quantitative structure–activity relationships (QSARs). In the present study, the chromatographic capacity factors (log k’ (IAM)) for 28 OSCs were determined by IAM-HPLC. In order to evaluate the ability of the IAM phase in assessing lipophilicity of the compounds under study, several quantitative structure–retention relationships (QSRRs) were derived from exploring fundamental intermolecular interactions that govern the retention of compounds under study on IAM phases. As expected, the hydrophobic factors are of prime importance for the IAM retention of these compounds. However, the molecular flexibility and specific polar interactions expressed by several electronic descriptors (relative negative charge, RNCG, and Mulliken electronegativity) are also involved. We also evaluated the IAM phase ability to assess several ADME parameters for the OSCs under study obtained using the SwissADME web tool integrated into the SwissDrugDesign workspace and the PreADMET web tool. The human gastrointestinal absorption (HIA), blood–brain barrier (BBB) permeation, and skin permeability were investigated through QSAR modeling, using several chemometric approaches. The ADME properties under study are strongly dependent on hydrophobic factors as expressed by log k’(IAM), which provide evidence for the great potential of the IAM phases in the development of QSAR models.

Transition-metal complexes of N,N′-di(4-bromophenyl)-4-hydroxycoumarin-3-carboximidamide: synthesis, characterization, biological activities, ADMET and drug-likeness analysis

Coordination compounds of N,N’-di(4-bromophenyl)-4-hydroxycoumarin-3-carboximidamide (L1) were synthesized via the reaction of Cu (II), Co (II) and Zn (II) salts in molar ratio 1 : 1 in the presence of ammoniac as basic media. The Ligands and the complexes formed were characterized using FT-IR, UV–visible and fluorescence spectrophotometric analyses, mass spectrometry, elemental analyses and NMR spectroscopy. It was concluded that N,N’-di(4-bromophenyl)-4-hydroxycoumarin-3-carboximidamide (L1) coordinated as a mono ligand for all the complexes; it also coordinated via the –OH and –NH groups. The electrochemical behaviour of these compounds was determined by cyclic voltammetry. The synthesized compounds were screened for their antimicrobial and antioxidant activities. All the complexes except that of copper show good activities against the S. aureus and those of cobalt and zinc have very interesting diameters of inhibition but lower antioxidant activity than the ligand L1. Parameters drug-likeness and ADMET (Absorption, Distribution, Metabolism, and Excretion) properties have been calculated.

Synthesis, Spectroscopic Characterizations of Novel Norcantharimides, Their ADME Properties and Docking Studies Against COVID-19 Mpr°.

A series of novel Norcantharimide derivatives were synthesized and their structures were characterized by FTIR, 1H and 13C NMR spectroscopy as well as elemental analyses. The absorption, distribution, metabolism and excretion (ADME) properties of the synthesized molecules were investigated. The results obtained in silico demonstrated that these molecules can be considered as orally active drug candidates due to their physicochemical properties. Also, docking studies demonstrated that all derivatives exhibit a good theoretical affinity with MolDock Score in between 124–138 against the main protease of Coronavirus Disease 2019 (COVID‐19 Mpr°) that caused worldwide epidemics. We believe that newly synthesized norcantharimide derivatives can guide many future studies in organic synthesis, medicine and pharmaceutical applications.

Identification of potential inhibitors targeted for strengthening search of anti-leishmanial therapeutics

Visceral leishmaniasis (VL: a fatal disease) is reported to occur at the rate of 70,000 to 90,000 per year, according to WHO. VL is caused by Leishmania donovani species causing 90% cases of VL. Current treatment regime is not satisfactory due to substantial toxic side effects of existing antileishmanial therapy and the emergence of drug resistance from different part of the world. These issues make existing therapy unsuitable management of VL. There are various studies dedicated to overcoming the shortcomings in antileishmanial therapeutics. Likewise, in this study, we have targeted HSP100 (heat shock protein) of L. donovani for identification of potent antileishmanial. HSP100 protein is released when the Leishmania parasite encounters heat stress in macrophage of mammalian host making it an effective target. This in silico study was carried out with 10 unexplored ligands and Miltefosine (an established anti-leishmanial drug used as control) via targeting L. donovani HSP100. We report that two test ligands Diospyrin and Benzoxaborole had outstanding docking potential with L. donovani HSP100 and were chosen for further analysis of drug-likeness and ADMET (absorption distribution, metabolism, and excretion) properties. These two ligands docking scores were better than the antileishmanial Miltefosine and had better ADMET properties as a drug candidate. The result gave us a lead and confirmation to support our hypothesis that HSP100 can be a potential drug target of L. donovani and Diospyrin and Benzoxaborole can be potent antileishmanial molecules.

An international effort to promote the regulatory use of PBK models based on non-animal data

Abstract The Organisation for Economic Co-operation and Development (OECD) coordinates international efforts to promote the regulatory use of Physiologically Based Kinetic (PBK) models based on non-animal data. The new generation PBK models rely on in vitro and in silico ADME (Absorption, Distribution, Metabolism and Excretion) data and aim to provide internal dose metrics that are considered more predictive when establishing biological responses that are needed in chemical risk assessment. However, the uncertainty derived from the chemical-dependent parameters (physicochemical and ADME properties) of PBK models for chemicals with no in vivo data need to be clearly communicated to the regulators evaluating data derived from these tools. This manuscript highlights these international efforts that aim to enhance regulatory acceptance of new generation PBK models through the development of a harmonised approach for characterising, validating and reporting them.

De Novo Design of New Inhibitor of Mutated Tyrosine-Kinase for the Myeloid Leukemia Treatment.

Chronic myelogenous leukemia is associated with hematopoietic stem cells that are manifested primarily with expansion myelopoiesis. It is the first cancer directly associated with a genetic abnormality. Specifically, it is associated to a particular cytogenetic abnormality, known as Philadelphia chromosome (Ph), which results from a fusion between part of the BCR ("breakpoint cluster region") gene from chromosome 22 and the Abelson (ABL) gene on chromosome 9 and leads to the formation a new gene leukemia-specific, the BCR-ABL. Since 2011, there are several tyrosine-kinase inhibitors in the market. Due to mutations in the tyrosine-kinase domain, these inhibitors are becoming less effective in the leukemia treatment, and then there is a need for new more effective inhibitors. The aim of this work is to obtain new tyrosine-kinase inhibitors using in silico tools like de novo drug design, docking and absorption, distribution, metabolism and excretion studies. Using the proposed methodology, an initial library of more than 6000 molecules was obtained. This library was then filtered out using the Tanimoto metric to compute the similarity between the molecules using as parameter the 2D linear hashed fingerprint with a 64-bit address space. The resulting library was then used to run docking studies together with the reference market drugs and their ADME (absorption, distribution, metabolism and excretion) properties were determined. Three compounds with better inhibition capacity and better ADME properties that the commercially available not only for the wild form of enzymes under study but also to its mutated forms were obtained. The fragment based drug design method used in this work turns to be a good alternative to create new drugs that can control this neoplasm. Based on the calculated GScore, the de novo designed molecules have better inhibitor capacity than the tyrosine-kinase inhibitors most used in the market. These molecules shown strong potential to become drugs capable to inhibit all mutations, mainly the T315I mutation, now the leading cause of deaths due to the difficulty of inhibitors to control it.

Characterization of preclinical in vitro and in vivo ADME properties and prediction of human PK using a physiologically based pharmacokinetic model for YQA‐14, a new dopamine D3 receptor antagonist candidate for treatment of drug addiction

YQA-14 is a novel and selective dopamine D3 receptor antagonist, with potential for the treatment of drug addiction. However, earlier compounds in its structural class tend to have poor oral bioavailability. The objectives of this study were to characterize the preclinical absorption, distribution, metabolism and excretion (ADME) properties and pharmacokinetics (PK) of YQA-14, then to simulate the clinical PK of YQA-14 using a physiologically based pharmacokinetics (PBPK) model to assess the likelihood of developing YQA-14 as a clinical candidate. For human PK prediction, PBPK models were first built in preclinical species, rats and dogs, for validation purposes. The model was then modified by input of human in vitro ADME data obtained from in vitro studies. The study data showed that YQA-14 is a basic lipophilic compound, with rapid absorption (Tmax ~ 1 h) in both rats and dogs. Liver microsomal clearances and in vivo clearances were moderate in rats and dogs consistent with the moderate bioavailability observed in both species. The PBPK models built for rats and dogs simulated the observed PK data well in both species. The PBPK model refined with human data predicted that YQA-14 would have a clearance of 8.0 ml/min/kg, a volume distribution of 1.7 l/kg and a bioavailability of 16.9%. These acceptable PK properties make YQA-14 an improved candidate for further research and development as a potential dopamine D3R antagonism for the treatment of drug addiction in the clinic.

Predicting human exposure of active drug after oral prodrug administration, using a joined in vitro/in silico–in vivo extrapolation and physiologically-based pharmacokinetic modeling approach

Introduction: Predicting the pharmacokinetics (PK) of prodrugs and their corresponding active drugs is challenging, as there are many variables to consider. Prodrug conversion characteristics in different tissues are generally measured, but integrating these variables to a PK profile is not a common practice. In this paper, a joined in vitro/in silico–in vivo extrapolation (IVIVE) and physiologically-based pharmacokinetic (PBPK) modeling approach is presented to predict active drug exposure in human after oral prodrug administration. Methods: Physico-chemical and in vitro assays as well as in silico predictions were proposed to characterize key pharmacokinetic properties (e.g. clearance, volume of distribution, conversion rates) of three marketed prodrugs. These data were used to parameterize a PBPK model for simulating human PK profiles of the active drugs after prodrug administration, which were compared to literature data by evaluating the accuracy and uncertainty of the predictions. Results: For mycophenate mofetil and midodrine the PK of their active moieties could be adequately predicted. The assumptions of the PBPK–IVIVE approach were valid, i.e. being hepatically cleared, converted in the gut lumen, blood and liver and not metabolized in the gut wall. However, the observed profiles after oral bambuterol administration clearly fell outside the prediction interval as the PBPK model failed to predict the observed bioavailability. Discussion: Adding quantitative information about prodrug conversion in the gut, liver and blood to a PBPK model for the absorption, distribution, metabolism and excretion (ADME) properties of prodrugs and their active moieties resulted, retrospectively, in reasonable predictions of the human PK when the ADME properties are well understood. Also in a prospective compound selection process, this integrative approach can improve decision making on prodrug candidates by putting relative differences in prodrug conversion of a large number of candidates into the perspective of their human PK profile, before conducting any in vivo experiments.

Differences in the pharmacokinetics of currently approved antimalarial drugs in uncomplicated malaria patients compared to healthy subjects

For an effective antimalarial therapy, maintenance of antimalarial drug concentrations well above minimum parasiticidal concentration for certain time duration is required in the target compartments (eg., blood, liver). On the other hand, malaria parasite infection may affect few physiological functions (eg., hepatic metabolism, protein binding) that may affect the pharmacokinetics and tissue disposition of antimalarial drugs. The altered PK in turn can affect the concentrations of the drugs and consequently their efficacy. Therefore, this work was undertaken to understand whether there is any difference in the pharmacokinetics (PK) of currently approved/available antimalarial drugs between malaria patients and healthy subjects. The pharmacokinetic data of approved drugs was obtained from various public resources and the data was compiled for absorption, distribution, metabolism and elimination (ADME) properties. These ADME properties were further analyzed against the information available on reported physiological changes (e.g. reduced hepatic blood flow in patients, changes in CYP enzyme levels, etc.) to understand the possible contributing factors for potential alterations in the pharmacokinetics of drugs in patients. Pre-clinical information available for these drugs were also retrieved and used for the present investigation. The results indicated that there was a significant alteration in the pharmacokinetic properties of most of the currently available/ approved antimalarial drugs in malarial patients compared to healthy subjects. The correlation analysis indicated that physiological changes such as hepatic blood flow, CYP enzyme expression/activity and protein binding may be the potential reasons for the observed differences. This analysis could be useful to envisage changes in the PK properties of the drugs based on their ADME properties and further aid in the development of future antimalarial drugs.

Dendrimer Pharmacokinetics: The Effect of Size, Structure and Surface Characteristics on ADME Properties

Dendrimers show increasing promise as drug-delivery vectors and can be generated with a wide range of scaffold structures, sizes and surface functionalities. To this point, the majority of studies of dendrimer-based drug-delivery systems have detailed pharmacodynamic outcomes, or have followed the pharmacokinetics of a solubilized or conjugated drug. By contrast, detailed commentary on the in vivo fate of the dendrimer carrier is less evident, even though the pharmacokinetics of the carrier will likely dictate both pharmacodynamic and toxicokinetic outcomes. In the current article, the influence of size, structure and surface functionality on the absorption, distribution, metabolism and elimination (ADME) properties of dendrimers have been examined and the implications of these findings for delivery system design are discussed.

In Silico Prediction of Cytochrome P450-Mediated Drug Metabolism

The application of combinatorial chemistry and high-throughput screening technique enables the large number of chemicals to be generated and tested simultaneously, which will facilitate the drug development and discovery. At the same time, it brings about a challenge of how to efficiently identify the potential drug candidates from thousands of compounds. A way used to deal with the challenge is to consider the drug pharmacokinetic properties, such as absorption, distribution, metabolism and excretion (ADME), in the early stage of drug development. Among ADME properties, metabolism is of importance due to the strong association with efficacy and safety of drug. The review will focus on in silico approaches for prediction of Cytochrome P450-mediated drug metabolism. We will describe these predictive methods from two aspects, structure-based and data-based. Moreover, the applications and limitations of various methods will be discussed. Finally, we provide further direction toward improving the predictive accuracy of these in silico methods.

The TeGenero Incident and the Duff Report Conclusions: A Series of Unfortunate Events or an Avoidable Event?

The administration of the first dose of a novel pharmaceutical compound to humans is the culmination of many years of efforts by many people. There is often a feeling of relief that the compound has made it this far and a feeling of great optimism and anticipation. However, it also can be a time of great trepidation because it is the first opportunity to determine the accuracy of the projections of the compound’s efficacy, ADME (absorption, distribution, metabolism, and elimination) properties, and most important, safety in humans. The administration of the first dose to humans usually results in a celebration by the development project team, although the first few dose levels of the initial clinical trial are usually uneventful and not much can be learned regarding the compound’s efficacy, ADME properties, and safety due to the low doses used in these initial dose cohorts. This is particularly true for nononcology compounds that are typically evaluated first in normal healthy volunteers (NHV) who would be expected to derive no benefit from the compound and thus generally receive a first-in-human (FIH) dose that is not anticipated to have pharmacologic activity. Unfortunately, in some instances, things do not go as anticipated. Sometimes it is learned from these early dose cohorts that the projections of the pharmacokinetics (PK) of the compound are wrong, or that the compound will not be as efficacious in humans as in animals. Sometimes the compound is found to have a side-effect profile in humans that was not predicted from the animal toxicology studies. Usually such side effects are relatively benign, consisting of headaches, nausea, drowsiness and other nuisance events which would have been difficult to appreciate in animal studies. On very rare occasions, the side effects may be more severe and, even more rarely, life-threatening. One such example of the latter was the ‘‘TeGenero Incident’’ (Expert Group on Phase One Clinical Trials 2006; Gambrill 2006). Serious, life-threatening adverse events were observed in all dosed subjects after the administration of TGN1412, a new class of monoclonal antibody (mAb) with a stimulatory mode of action on a subset of T cells known as regulatory T cells (Tregs; Expert Group on Phase One Clinical Trials 2006). This antibody was a humanized IgG4k mAb that was derived from the precursor mouse mAb 5.11A1 by grafting of the complementarity-determining regions (CDR). TGN1412 binds to CD28 and activates T cells without need for T cell receptor (TCR) preactivation, resulting in polyclonal T cell expansion and activation and concentration-dependent IL-2 production. As such, TGN1412 was termed a ‘‘superagonist.’’ The intent was to develop TGN1412 as a treatment for B cell chronic lymphocytic leukemia, in which T cells are deficient, and for autoimmune diseases, such as rheumatoid arthritis, in which Treg cell expansion might be beneficial. The TeGenero incident spurred a subsequent investigation by an expert scientific group (ESG) on Phase 1 Clinical Trials, appointed by the Medicines and Healthcare Products Regulatory Agency (MHRA) and under the leadership of Professor Gordon Duff, which culminated in a report known as ‘‘the Duff Report.’’ The objective of this article is to review the TeGenero incident and the Duff Report and to comment on whether the TeGenero incident was predictable and/or avoidable. Address correspondence to: Christopher Horvath, DVM, MS, DACVP, Vice President, PreClinical Sciences, Taligen Therapeutics, Cambridge, MA 02142; e-mail: chorvath@taligentherapeutics.com. Abbreviations: ABPI, Association of the British Pharmaceutical Industry; ADME, Absorption, Distribution, Metabolism, and Excretion; BBC, British Broadcasting Company; BIA, BioIndustry Association; CBER, FDA Center for Biologics Evaluation and Research; CD, cluster of differentiation; CDER, FDA Center for Drug Evaluation and Research; CDR, complementaritydetermining region; CHM, Commission on Human Medicines; CHMP, Committee for Medicinal Products for Human Use; CPMP, Committee for Proprietary Medicinal Products; CRS, cytokine release syndrome; CTA, clinical trial authorization; DIC, disseminated intravascular coagulation; DLT, doselimiting toxicity; EAG, expert advisory group; Emax, maximum effect; EMEA, European Medicines Agency; ESG, Expert Scientific Group on Phase 1 Clinical Trials; EU, European Union; EUDRA, European Drug Regulatory Authorities; Fc, Fragment, crystallizable; FcR, Fc receptor; FcRn, neonatal Fc receptor; FDA, Food and Drug Administration; FIH, first-in-human; FOI, Freedom of Information; HED, human equivalent dose; HNSTD, highest nonseverely toxic dose; IB, Investigator’s Brochure; IgG, immunoglobulin isotype G; IL2, Interleukin–2; IMPD, Investigational Medicinal Product Dossier; IND, Investigational New Drug; mAb, monoclonal antibody; MABEL, minimum anticipated biological effect (dose) level; MHRA, Medicines and Healthcare Products Regulatory Agency; MOA, mechanism of action; MRSD, maximum recommended starting dose; MTED, minimum toxic effect dose; NHV, normal healthy volunteer; NOAEL, no observed adverse effect (dose) level; NOEL, no observed effect (dose) level; PAD, pharmacologically active dose; PD, pharmacodynamic(s); PK, pharmacokinetic(s); RSS, Royal Statistical Society; Siglecs, Sialic acid binding Ig-like lectins; SUSAR, suspected unexpected serious adverse reaction; TCR, T cell receptor; UK, United Kingdom.

In SilicoScreening of the Library of Pyrimidine Derivatives as Thymidylate Synthase Inhibitors for Anticancer Activity

We here report the virtual screening of several series of pyrimidine derivatives forin silicoThymidylate Synthase (TS) inhibition to arrive at possible potential inhibitors of TS with acceptable pharmacokinetic or ADME (Absorption, Distribution, Metabolism and Excretion) properties. Library of the molecules was constructed based upon structural modifications of pyrimidines nucleus. Structural modifications in descending order were performed for the series of pyrimidines,vizfrom pyrimidines with five membered heterocyclic ring to pyrimidines with four membered heterocyclic ring to simple pyrimindine carboxylates in an order to arrive at pyrimidines with better inhibition scores (G-Scores) as compared with Raltitrexed (RTX) and active metabolite of 5-Fluorouracil (5-FUMP). The molecules with betterG-Scores were subjected to predict pharmacokinetic or ADME properties. The molecules with acceptable ADME properties and betterG-Scores were prioritized for synthesis and anticancer evaluation. Three molecules from pyrimidine carboxylate series PIC1-31were found acceptable withG-Scores and pharmacokinetic properties. Thus a library of pyrimidine derivatives was constructed based upon the feasibility of synthesis and in silico screened to prioritize the molecules and to obtain potential lead molecules as TS inhibitors.

Structure – ADME relationship: still a long way to go?

Background: Theoretical models for predicting absorption, distribution, metabolism and excretion (ADME) properties play increasingly important roles in support of the drug development process. Objective: We briefly review the in silico prediction models for three important ADME properties, namely, aqueous solubility, human intestinal absorption, and oral bioavailability. Methods: Rather than giving detailed descriptions of the ADME prediction models, we focus on the discussions of the prediction accuracies of the in silico models. Results/conclusion: We find that the robustness and predictive capability of the ADME models are directly associated with the complexity of the ADME property. For the ADME properties involving complex phenomena, such as bioavailability, the in silico models usually cannot give satisfactory predictions. Moreover, the lack of large and high-quality data sets also greatly hinder the reliability of ADME predictions. While considerable progress has been achieved in ADME predictions, many challenges remain to be overcome.

Computational design of novel cyclic urea as HIV-1 protease inhibitor

AbstractA series of novel cyclic urea molecules 5,6-dihydroxy-1,3-diazepane-2,4,7-trione as HIV-1 protease inhibitors were designed using computational techniques. The designed molecules were compared with the known cyclic urea molecules by performing docking studies, calculating their ADME (Absorption, Distribution, Metabolism, and Excretion) properties and protein ligand interaction energy. These novel molecules were designed by substituting the P 1/P′ 1 positions (4th and 7th position of 1, 3-diazepan-2-one) with double bonded oxygens. This reduces the molecular weight and increases the bioavailability, indicating better ADME properties. The docking studies showed good binding affinity towards HIV-1 protease. The biological activity of these inhibitors were predicted by a model equation generated by the regression analysis between biological activity (log 1/K i ) of known inhibitors and their protein ligand interaction energy. The synthetic studies are in progress.

Development of an ADME and drug–drug interactions knowledge database for the acceleration of drug discovery and development

It is widely recognised that predicting or determining the absorption, distribution, metabolism and excretion (ADME) properties of a compound as early as possible in the drug discovery process helps to prevent costly late-stage failures. Although in recent years high-throughput in vitro absorption distribution metabolism excretion toxicity (ADMET) screens have been implemented, more efficient in silico filters are still highly needed to predict and model the most relevant metabolic and pharmacokinetic end points, and thereby accelerate drug discovery and development. The usefulness of the data generated and published for the chemist, biologist or project manager who ultimately wants to understand and optimise the ADME properties of lead compounds cannot be argued with. Collecting and comparing data is an overwhelming task for the time-pressed scientist. Aureus Pharma provides a uniquely specialised solution for knowledge generation in drug discovery. AurSCOPE® ADME/DDI (drug–drug interaction) is a fully annotated, structured knowledge database containing all the pertinent biological and chemical information on the metabolic properties of drugs. This Aureus knowledge database has proven to be highly useful in designing predictive models and identifying potential drug–drug interactions.

TruPK – human pharmacokinetic models for quantitative ADME prediction

The use of in silico prediction of absorption, distribution, metabolism and excretion (ADME) properties is gaining acceptance as a useful assessment tool for early identification of likely drug candidate failures. However, it has been difficult to locate reliable models for the prediction of human pharmacokinetics (PK) in silico Currently available methods for estimating ADME and toxicity properties, such as in vitro and animal models, are not very predictive of what is observed in the clinic. Existing in silico ADME prediction tools concentrate on physicochemical properties, such as solubility, log P, rule-of-five compliance, Caco-2 permeability, blood–brain barrier and so on, or only classify drug-like candidates as ‘poor’, ‘medium’ or ‘good’ for a PK parameter, without ascribing values. Although physiology-based pharmacokinetic -models can predict ADME properties, they rely on using various measured properties as input for better accuracy. Strand Genomics has developed a tool, truPK, that predicts the properties of a molecule (bioavailability, protein binding, volume of distribution, elimination half-life and absorption rate) that affect its dose and dose frequency in humans. truPK’s five models built using sophisticated machine methods have predicted with > 75% accuracies in external validation sets.