Development of a sensitive and fast UHPLC-MS/MS method for determination of clopidogrel, clopidogrel acid and clopidogrel active metabolite H4 in human plasma.

BACKGROUND: Quantitation of CAM H4 in biological matrix has been a challenge due to low concentrations, instability and the existence of four CAM diastereomers. Historically, either inactive clopidogrel acid or CAM diastereomers without separation were measured for exposure and PK parameters. RESULTS: This study presents a sensitive and fast UHPLC-MS/MS method for simultaneous quantitation of clopidogrel, clopidogrel acid and active metabolite H4 in human plasma. The method demonstrated the separation of H4 from other isomers and yet retained clopidogrel acid. Matrix stabilities, accuracy and precision, recovery and matrix effect were evaluated during development. CONCLUSION: With LLOQ of 0.05 ng/ml for clopidogrel and H4, and 5.5 min LC gradient, it is the most sensitive and fastest method to our knowledge.

Development and validation of a HILIC-MS/MS method for quantification of decitabine in human plasma by using lithium adduct detection.

A highly sensitive, selective, and rugged quantification method was developed and validated for decitabine (5-aza-2'-deoxycytidine) in human plasma treated with 100µg/mL of tetrahydrouridine (THU). Chromatographic separation was accomplished using hydrophilic interaction liquid chromatography (HILIC) and detection used electrospray ionization (ESI) tandem mass spectrometry (MS/MS) by monitoring lithiated adducts of the analytes as precursor ions. The method involves simple acetonitrile precipitation steps (in an ice bath) followed by injection of the supernatant onto a Thermo Betasil Silica-100, 100×3.0mm, 5µm LC column. Protonated ([M+H](+)), sodiated ([M+Na](+)), and lithiated ([M+Li](+)) adducts as precursor ions for MS/MS detection were evaluated for best sensitivity and assay performance. During initial method development abundant sodium [M+Na](+) and potassium [M+K](+) adducts were observed while the protonated species [M+H](+) was present at a relative abundance of less than 5% in Q1. The alkali adducts were not be able to be minimized by the usual approach of increasing acid content in mobile phases. Significant analyte/internal standard (IS) co-suppression and inter-lot response differences were observed when using the sodium adduct as the precursor ion for quantification. By adding 2mM lithium acetate in aqueous mobile phase component, the lithium adduct effectively replaced other cationic species and was successfully used as the precursor ion for selected reaction monitoring (SRM) detection. The method demonstrated the separation of anomers and from other endogenous interferences using a 3-min gradient elution. Decitabine stock, working solution stabilities were investigated during method development. Three different peaks, including one from anomerization, were observed in the SRM transition of the analyte when it was in neutral aqueous solution. The assay was validated over a concentration range of 0.5-500ng/mL (or 0.44-440pg injected on column) in 50µL of human plasma. The accuracy and precision were within 8.6% relative error and 6.3% coefficient of variation, respectively. Decitabine was stable in THU treated human plasma for at least 68 days and after 5 freeze-thaw cycles when stored at -70°C. Stability of decitabine in THU treated human whole blood, matrix factor and recovery were also evaluated during method validation. The method was successfully used for clinical sample analysis.

Protein tyrosine phosphatases: strategies for distinguishing proteins in a family containing multiple drug targets and anti-targets.

PTP1B, but also proteins that are essential to cell development and survival. The availability of sequences and representative structures for the PTP family allows better identification of anti-targets, closely related family members likely to cross-react with directed inhibitors. Eight PTP subfamilies, classified by active site information and overall PTP catalytic domain structure similarity, are reviewed here: 1) the tyrosine-specific PTPs, 2) the dual-specificity PTPs, 3) the cdc25 subclass; 4) the Pten subclass; 5) the myotubularins, 6) the PRL subclass, 7) the low molecular weight PTPs, and 8) the newly defined cdc14 subclass. PTP subfamily classification and structure information can be incorporated into design strategies aimed at identifying potent and selective small molecule inhibitors. The accumulating inhibition data for compounds screened against panels of PTPs is reviewed. The in vitro data can yield clues to specificity so that individual subfamilies can be matched with effective scaffolds to jumpstart lead design and reduce false starts.

Prediction of deleterious functional effects of amino acid mutations using a library of structure-based function descriptors.

An automated, active site-focused, computational method is described for use in predicting the effects of engineered amino acid mutations on enzyme catalytic activity. The method uses structure-based function descriptors (Fuzzy Functional Forms trade mark or FFFs trade mark ) to automatically identify enzyme functional sites in proteins. Three-dimensional sequence profiles are created from the surrounding active site structure. The computationally derived active site profile is used to analyze the effect of each amino acid change by defining three key features: proximity of the change to the active site, degree of amino acid conservation at the position in related proteins, and compatibility of the change with residues observed at that position in similar proteins. The features were analyzed using a data set of individual amino acid mutations occurring at 128 residue positions in 14 different enzymes. The results show that changes at key active site residues and at highly conserved positions are likely to have deleterious effects on the catalytic activity, and that non-conservative mutations at highly conserved residues are even more likely to be deleterious. Interestingly, the study revealed that amino acid substitutions at residues in close contact with the key active site residues are not more likely to have deleterious effects than mutations more distant from the active site. Utilization of the FFF-derived structural information yields a prediction method that is accurate in 79-83% of the test cases. The success of this method across all six EC classes suggests that it can be used generally to predict the effects of mutations and nsSNPs for enzymes. Future applications of the approach include automated, large-scale identification of deleterious nsSNPs in clinical populations and in large sets of disease-associated nsSNPs, and identification of deleterious nsSNPs in drug targets and drug metabolizing enzymes.

Structure-based active site profiles for genome analysis and functional family subclassification.

In previous work, structure-based functional site descriptors, fuzzy functional forms (FFFs), were developed to recognize structurally conserved active sites in proteins. These descriptors identify members of protein families according to active-site structural similarity, rather than overall sequence or structure similarity. FFFs are defined by a minimal number of highly conserved residues and their three-dimensional arrangement. This approach is advantageous for function assignment across broad families, but is limited when applied to detailed subclassification within these families. In the work described here, we developed a method of three-dimensional, or structure-based, active-site profiling that utilizes FFFs to identify residues located in the spatial environment around the active site. Three-dimensional active-site profiling reveals similarities and differences among active sites across protein families. Using this approach, active-site profiles were constructed from known structures for 193 functional families, and these profiles were verified as distinct and characteristic. To achieve this result, a scoring function was developed that discriminates between true functional sites and those that are geometrically most similar, but do not perform the same function. In a large-scale retrospective analysis of human genome sequences, this profile score was shown to identify specific functional families correctly. The method is effective at recognizing the likely subtype of structurally uncharacterized members of the diverse family of protein kinases, categorizing sequences correctly that were misclassified by global sequence alignment methods. Subfamily information provided by this three-dimensional active-site profiling method yields key information for specific and selective inhibitor design for use in the pharmaceutical industry.