Structure and property based design of factor Xa inhibitors: pyrrolidin-2-ones with aminoindane and phenylpyrrolidine P4 motifs

Discovery of potential pharmacodynamic ingredients of Dang-Gui-Si-Ni decoction based on absorbed ingredients and molecular docking

ETHNOPHARMACOLOGICAL RELEVANCE

The Dang-Gui-Si-Ni (DGSN) decoction as a classic prescription has been widely used for thousands of years in the clinical practice of traditional Chinese medicine (TCM). Especially in recent years, the potential efficacy of TCM for the treatment of Raynaud's syndrome has attracted great attention as there are still no specific remedies for this disease. However, the active constituents and underlying mechanisms responsible for the therapeutic benefits are not well understood, which makes it difficult to ensure quality control or to design research and drug development strategies. To identify the potential pharmacodynamic ingredients (PPIs) of TCM will help to achieve suitable process control procedures for industrial production and large-scale manufacturing.

AIM OF THE STUDY

In the present study, we propose a multi-dimensional qualitative analysis method combining water-decoction spectra, in-vitro intestinal absorption spectra, in-vivo plasma spectra, and molecular docking of components to quickly identify the PPIs for the DGSN decoction of TCM.

MATERIALS AND METHODS

Water-based decoctions of DGSN were prepared in accordance with the clinical use registered in ancient books. Ultra-high-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q/TOF-MS) coupled with computerized modelling activity screening was used to quickly identify the PPIs of the DGSN decoction. Bioactive compounds absorbed in vitro were identified using the everted intestinal sac model from rats and compounds absorbed in vivo were confirmed in portal vein blood samples obtained following oral administration in rats. Molecular docking validation experiments were adopted to predict the binding activity to coagulation factors I, II, VII, X, and IX. The active components were further confirmed by pharmacodynamics analysis. The anticoagulant activity of the DGSN decoction was verified using rat models.

RESULTS

Thirty-one compounds were identified in the DGSN decoction. According to the in vivo experiments, 22 compounds that could be absorbed in vivo were detected by the everted intestinal sac model in rats. This model greatly reduces the scope of PPIs and is easy to perform. Ten compounds were detected in the portal vein blood in rats. The compounds detected in plasma provide stronger evidence supporting the PPIs. Molecular docking in vitro experiments indicated that 7 compounds exhibited better binding activity with coagulation factors I, II, VII, X, and IX. The animal experiments confirmed that the DGSN decoction could improve the microcirculation, providing indirect proof of anticoagulant activity suggested by the molecular docking studies. Finally, based on the multi-dimensional methods, 9 potential compounds present in the DGSN decoction were identified as PPIs (i.e., ferulic acid, paeoniflorin, albiflorin, chlorogenic acid, cryptochlorogenic acid, liquiritin, liquiritin apioside, cinnamaldehyde and glycyrrhizic acid).

CONCLUSION

Overall, this study combined the water-decoction spectra, intestinal absorption spectra in vitro, plasma spectra in vivo, and molecular docking studies to establish a multi-dimensional qualitative analysis method of the DGSN decoction. Meanwhile, 9 compounds in DGSN decoction were identified as PPIs using this method, and are proposed for application as quality standards for complex TCM prescriptions.

Tailor-Made Amino Acids and Fluorinated Motifs as Prominent Traits in Modern Pharmaceuticals

Structural analysis of modern pharmaceutical practices allows for the identification of two rapidly growing trends: the introduction of tailor-made amino acids and the exploitation of fluorinated motifs. Curiously, the former represents one of the most ubiquitous classes of naturally occurring compounds, whereas the latter is the most xenobiotic and comprised virtually entirely of man-made derivatives. Herein, 39 selected compounds, featuring both of these traits in the same molecule, are profiled. The total synthesis, source of the corresponding amino acids and fluorinated residues, and medicinal chemistry aspects and biological properties of the molecules are discussed.

Contemporary developments in the discovery of selective factor Xa inhibitors: A review

Thrombosis is a leading cause of death in cardiovascular diseases such as myocardial infarction (MI), unstable angina and acute coronary syndrome (ACS) in the industrialized world. Venous thromboembolism is observed in about 1 million people every year in United States causing significant morbidity and mortality. Conventional antithrombotic therapy has been reported to have several disadvantages and limitations like inconvenience in oral administration, bleeding risks (heparin analogs), narrow therapeutic window and undesirable interactions with food and drugs (vitamin K antagonist-warfarin). The unmet medical demand for orally active safe anticoagulants has generated widespread interest among the medicinal chemists engaged in this field. To modulate blood coagulation, various enzymes involved in the coagulation process have received great attention as potential targets by various research groups for the development of oral anticoagulants. Among these enzymes, factor Xa (FXa) has remained the centre of attention in the last decade. Intensive research efforts have been made by various research groups for the development of small, safe and orally bioavailable FXa inhibitors. This review is an attempt to compile the research work of various researchers in the direction of development of FXa inhibitors reported since 2010 onward.

CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma

The 2014 CSAR Benchmark Exercise was the last community-wide exercise that was conducted by the group at the University of Michigan, Ann Arbor. For this event, GlaxoSmithKline (GSK) donated unpublished crystal structures and affinity data from in-house projects. Three targets were used: tRNA (m1G37) methyltransferase (TrmD), Spleen Tyrosine Kinase (SYK), and Factor Xa (FXa). A particularly strong feature of the GSK data is its large size, which lends greater statistical significance to comparisons between different methods. In Phase 1 of the CSAR 2014 Exercise, participants were given several protein-ligand complexes and asked to identify the one near-native pose from among 200 decoys provided by CSAR. Though decoys were requested by the community, we found that they complicated our analysis. We could not discern whether poor predictions were failures of the chosen method or an incompatibility between the participant's method and the setup protocol we used. This problem is inherent to decoys, and we strongly advise against their use. In Phase 2, participants had to dock and rank/score a set of small molecules given only the SMILES strings of the ligands and a protein structure with a different ligand bound. Overall, docking was a success for most participants, much better in Phase 2 than in Phase 1. However, scoring was a greater challenge. No particular approach to docking and scoring had an edge, and successful methods included empirical, knowledge-based, machine-learning, shape-fitting, and even those with solvation and entropy terms. Several groups were successful in ranking TrmD and/or SYK, but ranking FXa ligands was intractable for all participants. Methods that were able to dock well across all submitted systems include MDock,1 Glide-XP,2 PLANTS,3 Wilma,4 Gold,5 SMINA,6 Glide-XP2/PELE,7 FlexX,8 and MedusaDock.9 In fact, the submission based on Glide-XP2/PELE7 cross-docked all ligands to many crystal structures, and it was particularly impressive to see success across an ensemble of protein structures for multiple targets. For scoring/ranking, submissions that showed statistically significant achievement include MDock1 using ITScore1,10 with a flexible-ligand term,11 SMINA6 using Autodock-Vina,12,13 FlexX8 using HYDE,14 and Glide-XP2 using XP DockScore2 with and without ROCS15 shape similarity.16 Of course, these results are for only three protein targets, and many more systems need to be investigated to truly identify which approaches are more successful than others. Furthermore, our exercise is not a competition.

Lead optimization mapper: automating free energy calculations for lead optimization

Alchemical free energy calculations hold increasing promise as an aid to drug discovery efforts. However, applications of these techniques in discovery projects have been relatively few, partly because of the difficulty of planning and setting up calculations. Here, we introduce lead optimization mapper, LOMAP, an automated algorithm to plan efficient relative free energy calculations between potential ligands within a substantial library of perhaps hundreds of compounds. In this approach, ligands are first grouped by structural similarity primarily based on the size of a (loosely defined) maximal common substructure, and then calculations are planned within and between sets of structurally related compounds. An emphasis is placed on ensuring that relative free energies can be obtained between any pair of compounds without combining the results of too many different relative free energy calculations (to avoid accumulation of error) and by providing some redundancy to allow for the possibility of error and consistency checking and provide some insight into when results can be expected to be unreliable. The algorithm is discussed in detail and a Python implementation, based on both Schrödinger's and OpenEye's APIs, has been made available freely under the BSD license.