High-throughput physicochemical and in vitro ADMET screening

During drug discovery, it is important to optimise the affinity for the biomolecular target and also the properties of molecules that influence absorption, distribution, metabolism, excretion, and toxicity (ADMET). The goal is to improve the properties of a lead compound and select highly ‘developable’ candidates. Efficient pharmaceutical property profiling operations are now run in parallel to potency screening during lead optimization and provide data for compound prioritization and for the selection of compounds for in vivo studies. The main components of a profiling strategy suitable for early discovery are the measurement of selected physicochemical properties together with in vitro screening for metabolic stability. In addition, enzyme or cellular assays may be deployed for investigation of cellular permeability (including active and passive transport), plasma protein binding, toxicity, and the potential for drug-drug interactions. The four principal physicochemical parameters measured are lipophilicity, dissociation constant, permeability through artificial membranes, and aqueous solubility. An objective of property-based design is the identification of structure property relationships for ADMET that can suggest structural modifications that will also promote or retain high affinity for the biomolecular target. Sometimes this is not possible and new lead molecules may need to be identified to provide new starting points. A sub-optimal in vitro profile may be acceptable as long as there is a reasonable probability of achieving an adequate in vivo profile for clinical studies. In these cases, the application of composite models that can relate in vitro to in vivo behavior is important. Full ‘physiologically based pharmacokinetic’ (PBPK) models can be used; however, there are also simpler approaches available that may be adequate and more easily applied for ranking compounds within a series. Reliable in vitro—in vivo correlation is still very difficult because of the multiplicity of mechanisms involved. For the future, there is a need to develop better criteria for making mechanistically based classifications to develop differentiated models that are appropriate for different types of compound. It is also difficult to correct models for non-specific binding of drugs to membranes and proteins and we need better lipophilicity measures for accurately estimating the affinity of drugs for tissues. PBPK modeling leads to the exciting concept of the ‘virtual human’; however, PBPK models suitable for drug discovery applications are still in their infancy and it will be some time before their promise is fulfilled.     

Adapting the multilevel model for estimation of the reliable change index (RCI) with multiple timepoints and multiple sources of error

ObjectiveOne of the primary tools in the assessment of individual‐level patient outcomes is Jacobson and Truax, (1991’s) Reliable Change Index (RCI). Recent efforts to optimize the RCI have revolved around three issues: (a) extending the RCI beyond two timepoints, (b) estimating the RCI using scale scores from item response theory or factor analysis and (c) estimation of person‐ and time‐specific standard errors of measurement.MethodWe present an adaptation of a two‐stage procedure, a measurement error‐corrected multilevel model, as a tool for RCI estimation (with accompanying Statistical Analysis System syntax). Using DASS‐21 data from a community‐based mental health center (N = 379), we illustrate the potential for the model as unifying framework for simultaneously addressing all three limitations in modeling individual‐level RCI estimates.ResultsCompared to the optimal‐fitting RCI model (moderated nonlinear factor analysis scoring with measurement error correction), an RCI model that uses DASS‐21 total scores produced errors in RCI inferences in 50.8% of patients; this was largely driven by overestimation of the proportion of patients with statistically significant improvement.ConclusionEstimation of the RCI can now be enhanced by the use of latent variables, person‐ and time‐specific measurement errors, and multiple timepoints.     

Mutation in the K-ras gene at codon 12 does not correlate with disease progression in colorectal carcinoma patients treated with 5-FU/folinic acid biomodulated chemotherapy

To date the response rates to biomodulated 5-fluorouracil in patients with metastatic or unresectable colorectal carcinoma have been varied. Potentially responsive patients are difficult to identify and treatment schedules are both expensive and toxic. Thus, any method that could be used to predict patient response would be both clinically and economically valuable. Increased p53 protein levels have previously been shown to correlate with disease progression in a series of colorectal carcinoma patients treated with 5-FU/folinic acid biomodulated chemotherapy. In addition to mutation of the p53 tumour suppressor gene, mutation of the K-ras gene at codon 12 has also been shown to be a frequent occurrence in the step-wise progression from normal colonic mucosa to adenocarcinoma. Oncogenic activity in the ras family has recently been shown to correlate with decreased levels of apoptosis and thus increased resistance to both radiation and certain chemotherapeutic agents. The aim of the present study was therefore to investigate if a correlation existed between mutation of the K-ras gene at codon 12 and disease progression in the series of colorectal carcinoma patients previously evaluated for levels of p53 protein expression. Response to 5-FU/folinic acid was assessed radiologically by CAT scan (WHO criteria) and clinically by Karnofsky performance scale (KPS) 3 months after the initial treatment. The presence of a K-ras gene mutation was assessed with radiolabelled oligonucleotide probes on amplified patient DNA, dot blotted on to a nylon membrane. Fifty-two patients were assessed and 25% were found to possess mutations at codon 12 of their K-ras gene. In contrast to increased levels of p53 protein, K-ras mutation at codon 12 did not correlate with disease progression when assessed either radiologically or clinically.     

Modulatory effects of adiponectin on the polarization of tumor‐associated macrophages

The plasticity of macrophages with selective functional phenotypes partially arises in respective to their microenvironment. Tumor‐associated macrophages (TAMs) may promote disease progression with tumor specific manner. Here we report that in pediatric malignant soft‐tissue tumors, the presence of TAMs and expression of adiponectin (APN) are heterogeneous. Both APN and TAMs had high expression in rhabdomyosarcoma, especially in the malignant subtype, alveolar rhabdomyosarcoma. To investigate the mode of action of APN on TAM activation, a murine MN/MCA1 sarcoma model was used. The Results revealed that exogenous APN had no effect on MN/MCA1 proliferation but tumor size was markedly reduced in apn^?/? mice versus WT controls. The accumulation of TAMs in apn^?/? mice was also reduced which correlated to downregulated serum levels of MCP‐1. Likewise, TAMs in apn^?/? mice exhibited a M1‐like phenotype, characterized by increase in MHC II^high population and M1 phenotypic markers, such as iNOS gene and serum TNF‐α accompanied by a decrease in M2 markers, namely YM1 gene and serum IL‐10. In addition, APN deficiency increased the number of CD4⁺ T cells, CD8⁺ T cells and NK cells in tumors and reduced tumor metastasis. The altered phenotype of TAMs in apn^?/? mice was associated with a marked decrease in phospho‐p38 and treatment with a p38 MAPK inhibitor significantly reduced tumor size and increased MHC II expression on TAMs in WT mice, implying p38 MAPK signaling pathway may contribute to APN‐mediated TAM polarization. Collectively, our findings suggest that APN may have a potential role in regulating soft tissue sarcoma growth.     

Suppression of Anti-Inflammatory Mediators in Metabolic Disease May Be Driven by Overwhelming Pro-Inflammatory Drivers

Obesity is a multifactorial disease and is associated with an increased risk of developing metabolic syndrome and co-morbidities. Dysregulated expansion of the adipose tissue during obesity induces local tissue hypoxia, altered secretory profile of adipokines, cytokines and chemokines, altered profile of local tissue inflammatory cells leading to the development of low-grade chronic inflammation. Low grade chronic inflammation is considered to be the underlying mechanism that increases the risk of developing obesity associated comorbidities. The glucocorticoid induced protein annexin A1 and its N-terminal peptides are anti-inflammatory mediators involved in resolving inflammation. The aim of the current study was to investigate the role of annexin A1 in obesity and associated inflammation. To achieve this aim, the current study analysed data from two feasibility studies in clinical populations: (1) bariatric surgery patients (Pre- and 3 months post-surgery) and (2) Lipodystrophy patients. Plasma annexin A1 levels were increased at 3-months post-surgery compared to pre-surgery (1.2 ± 0.1 ng/mL, n = 19 vs. 1.6 ± 0.1 ng/mL, n = 9, p = 0.009) and positively correlated with adiponectin (p = 0.009, r = 0.468, n = 25). Plasma annexin A1 levels were decreased in patients with lipodystrophy compared to BMI matched controls (0.2 ± 0.1 ng/mL, n = 9 vs. 0.97 ± 0.1 ng/mL, n = 30, p = 0.008), whereas CRP levels were significantly elevated (3.3 ± 1.0 µg/mL, n = 9 vs. 1.4 ± 0.3 µg/mL, n = 31, p = 0.0074). The roles of annexin A1 were explored using an in vitro cell based model (SGBS cells) mimicking the inflammatory status that is observed in obesity. Acute treatment with the annexin A1 N-terminal peptide, AC2-26 differentially regulated gene expression (including PPARA (2.8 ± 0.7-fold, p = 0.0303, n = 3), ADIPOQ (2.0 ± 0.3-fold, p = 0.0073, n = 3), LEP (0.6 ± 0.2-fold, p = 0.0400, n = 3), NAMPT (0.4 ± 0.1-fold, p = 0.0039, n = 3) and RETN (0.1 ± 0.03-fold, p < 0.0001, n = 3) in mature obesogenic adipocytes indicating that annexin A1 may play a protective role in obesity and inflammation. However, this effect may be overshadowed by the continued increase in systemic inflammation associated with rapid tissue expansion in obesity.     

Application of Saliva Inhibition to Detect Underlying Alloantibodies in Bombay Blood Group

IntroductionThe Bombay phenotype is a rare blood group determined by the absence of H antigens. Bombay individuals produce anti-H, a clinically significant antibody that react against all ABO blood group. Anti-H can mask underlying alloantibody during antibody investigation, a challenge in current transfusion practice. The aim of this article is to explore saliva inhibition, a novel method to detect underlying alloantibody in Bombay individuals.Case PresentationThe case is a 93-year-old female transfused with pre-donated autologous blood for a surgery. We determined anti-H subclass and thermal amplitude, secretor status, and optimal ratio of saliva and Bombay plasma. Plasma samples containing anti-H were spiked with anti-Fy(a) to determine the effectiveness of saliva inhibition in uncovering underlying alloantibodies.ResultsAnti-H was confirmed to be predominately IgM with broad thermal amplitude. Tube immediate spin (IS) showed stronger anti-H reactivity compared to column agglutination technology (CAT). Spiked anti-Fy(a) was successfully detected using saliva inhibition method.ConclusionTube IS appears more sensitive to anti-H. Saliva inhibition appears to be a promising method to detect underlying alloantibody in the plasma of Bombay phenotype individuals.     

Mutation‐related magnetization‐transfer,not axon density,drives white matter differences in premanifest Huntington disease: Evidence from in vivo ultra‐strong gradient MRI

White matter (WM) alterations have been observed in Huntington disease (HD) but their role in the disease‐pathophysiology remains unknown. We assessed WM changes in premanifest HD by exploiting ultra‐strong‐gradient magnetic resonance imaging (MRI). This allowed to separately quantify magnetization transfer ratio (MTR) and hindered and restricted diffusion‐weighted signal fractions, and assess how they drove WM microstructure differences between patients and controls. We used tractometry to investigate region‐specific alterations across callosal segments with well‐characterized early‐ and late‐myelinating axon populations, while brain‐wise differences were explored with tract‐based cluster analysis (TBCA). Behavioral measures were included to explore disease‐associated brain‐function relationships. We detected lower MTR in patients'' callosal rostrum (tractometry: p = .03; TBCA: p = .03), but higher MTR in their splenium (tractometry: p = .02). Importantly, patients'' mutation‐size and MTR were positively correlated (all p‐values < .01), indicating that MTR alterations may directly result from the mutation. Further, MTR was higher in younger, but lower in older patients relative to controls (p = .003), suggesting that MTR increases are detrimental later in the disease. Finally, patients showed higher restricted diffusion signal fraction (FR) from the composite hindered and restricted model of diffusion (CHARMED) in the cortico‐spinal tract (p = .03), which correlated positively with MTR in the posterior callosum (p = .033), potentially reflecting compensatory mechanisms. In summary, this first comprehensive, ultra‐strong gradient MRI study in HD provides novel evidence of mutation‐driven MTR alterations at the premanifest disease stage which may reflect neurodevelopmental changes in iron, myelin, or a combination of these.     

BrainAGE and regional volumetric analysis of a Buddhist monk: a longitudinal MRI case study

ABSTRACT

Yongey Mingyur Rinpoche (YMR) is a Tibetan Buddhist monk, and renowned meditation practitioner and teacher who has spent an extraordinary number of hours of his life meditating. The brain-aging profile of this expert meditator in comparison to a control population was examined using a machine learning framework, which estimates “brain-age” from brain imaging. YMR’s brain-aging rate appeared slower than that of controls suggesting early maturation and delayed aging. At 41 years, his brain resembled that of a 33-year-old. Specific regional changes did not differentiate YMR from controls, suggesting that the brain-aging differences may arise from coordinated changes spread throughout the gray matter.