Quantitation of oxidized and reduced albumin in mammals. An intriguing analytical question.

Oxidized albumin is considered a short-term biomarker of oxidative stress and its measurement in blood contributes to evaluate the impact of diseases, drugs, dialytic treatments, physical activity, environmental contaminants etc. on the red-ox balance of humans as well as of other mammalians. Nevertheless, the most common methods for quantifying the oxidized and reduced albumins are costly and time-consuming. Furthermore, there is a dearth of information regarding the proper ways to store human serum or plasma samples in order to prevent inaccurate quantification of these various albumin forms. This paper explores these aspects and proposes a few spectrophotometric assay procedures which make the quantitation of oxidized and reduced albumin very fast, precise and un-expensive in various mammals.

Regional myocardial perfusion imaging in predicting vessel-related outcome: interplay between the perfusion results and angiographic findings.

BACKGROUND: Despite myocardial perfusion imaging (MPI) by cadmium-zinc-telluride (CZT) single-photon emission computed tomography (SPECT) camera is largely used in the diagnosis and risk stratification of patients with suspected or known coronary artery disease (CAD), no data are available on the prognostic value of a regional MPI evaluation. We evaluated the prognostic value of regional MPI by the CZT camera in predicting clinical outcomes at the vessel level in patients with available angiographic data. METHODS AND RESULTS: Five hundred and forty-one subjects with suspected or known CAD referred to 99mTc-sestamibi gated CZT-SPECT cardiac imaging and with available angiographic data were studied. Both regional total perfusion deficit (TPD) and ischemic TPD (ITPD) were calculated separately for each vascular territory (left anterior descending, left circumflex, and right coronary artery). The outcome end points were cardiac death, target vessel-related myocardial infarction, or late coronary revascularization. The prevalence of CAD ≥ 50%, regional stress TPD, and regional ITPD was significantly higher in vessels with events as compared to those without (both P < 0.001). The receiver operating characteristics area under the curve for regional ITPD for the identification of vessel-related events was 0.81 (95% confidence interval 0.75-0.86). An ITPD value of 2.0% provided the best trade-off for identifying the vessel-related event. At multivariable analysis, both CAD ≥ 50% and ITPD ≥ 2.0% resulted in independent predictors of events. CONCLUSIONS: Regional myocardial perfusion assessed by the CZT camera demonstrated good reliability in predicting vessel-related events in patients with suspected or known CAD.

Impact of COVID-19 infection on short-term outcome in patients referred to stress myocardial perfusion imaging.

PURPOSE: We assessed the impact of COVID-19 infection on cardiovascular events in patients with suspected or known coronary artery disease (CAD) referred to stress single-photon emission computed tomography myocardial perfusion imaging (MPS). METHODS: A total of 960 consecutive patients with suspected or known CAD were submitted by referring physicians to stress MPS for assessment of myocardial ischemia between January 2018 and June 2019. All patients underwent stress-optional rest MPS. Perfusion defects were quantitated as % of LV myocardium and expressed as total perfusion defect (TPD), representing the defect extent and severity. A TPD ≥ 5% was considered abnormal. RESULTS: During a mean follow-up of 27 months (range 4-38) 31 events occurred. Moreover, 55 (6%) patients had a COVID-19 infection. The median time from index MPS to COVID-19 infection was 16 months (range 6-24). At Cox multivariable analysis, abnormal MPS and COVID-19 infection resulted as independent predictors of events. There were no significant differences in annualized event rate in COVID-19 patients with or without abnormal MPS (p = 0.56). Differently, in patients without COVID-19, the presence of abnormal MPS was associated with higher event rate (p < .001). Patients with infection compared to those without had a higher event rate in the presence of both normal and abnormal TPD. CONCLUSION: In patients with suspected or known CAD, the presence of COVID-19 infection during a short-term follow-up was associated with a higher rate of cardiovascular events.

Exploring the Role of L10 Loop in New Delhi Metallo-ß-lactamase (NDM-1): Kinetic and Dynamic Studies.

Four NDM-1 mutants (L218T, L221T, L269H and L221T/Y229W) were generated in order to investigate the role of leucines positioned in L10 loop. A detailed kinetic analysis stated that these amino acid substitutions modified the hydrolytic profile of NDM-1 against some ß-lactams. Significant reduction of kcat values of L218T and L221T for carbapenems, cefazolin, cefoxitin and cefepime was observed. The stability of the NDM-1 and its mutants was explored by thermofluor assay in real-time PCR. The determination of TmB and TmD demonstrated that NDM-1 and L218T were the most stable enzymes. Molecular dynamic studies were performed to justify the differences observed in the kinetic behavior of the mutants. In particular, L218T fluctuated more than NDM-1 in L10, whereas L221T would seem to cause a drift between residues 75 and 125. L221T/Y229W double mutant exhibited a decrease in the flexibility with respect to L221T, explaining enzyme activity improvement towards some ß-lactams. Distances between Zn1-Zn2 and Zn1-OH- or Zn2-OH- remained unaffected in all systems analysed. Significant changes were found between Zn1/Zn2 and first sphere coordination residues.

In Silico and In Vitro Analysis of Major Cannabis-Derived Compounds as Fatty Acid Amide Hydrolase Inhibitors.

Accumulated evidence suggests that enhancing the endocannabinoid (eCB) tone, in particular of anandamide (N-arachidonoylethanolamine, AEA), has therapeutic potential in many human diseases. Fatty acid amide hydrolase (FAAH) is a membrane-bound enzyme principally responsible for the degradation of AEA, and thus it represents a relevant target to increase signaling thereof. In recent years, different synthetic and natural compounds have been developed and tested on rat FAAH, but little is known of their effect on the human enzyme. Here, we sought to investigate six major cannabis-derived compounds to compare their action on rat and human FAAHs. To this aim, we combined an in silico analysis of their binding mode and affinity, with in vitro assays of their effect on enzyme activity. This integrated approach allowed to disclose differences in efficacy towards rat and human FAAHs, and to highlight the role of key residues involved in the inhibition of both enzymes. This study suggests that the therapeutic efficacy of compounds targeted towards FAAH should be always tested in vitro on both rat and human enzymes.

Chemical language modeling with structured state space sequence models.

Generative deep learning is reshaping drug design. Chemical language models (CLMs) - which generate molecules in the form of molecular strings - bear particular promise for this endeavor. Here, we introduce a recent deep learning architecture, termed Structured State Space Sequence (S4) model, into de novo drug design. In addition to its unprecedented performance in various fields, S4 has shown remarkable capabilities to learn the global properties of sequences. This aspect is intriguing in chemical language modeling, where complex molecular properties like bioactivity can 'emerge' from separated portions in the molecular string. This observation gives rise to the following question: Can S4 advance chemical language modeling for de novo design? To provide an answer, we systematically benchmark S4 with state-of-the-art CLMs on an array of drug discovery tasks, such as the identification of bioactive compounds, and the design of drug-like molecules and natural products. S4 shows a superior capacity to learn complex molecular properties, while at the same time exploring diverse scaffolds. Finally, when applied prospectively to kinase inhibition, S4 designs eight of out ten molecules that are predicted as highly active by molecular dynamics simulations. Taken together, these findings advocate for the introduction of S4 into chemical language modeling - uncovering its untapped potential in the molecular sciences.

Deep learning for low-data drug discovery: Hurdles and opportunities.

Deep learning is becoming increasingly relevant in drug discovery, from de novo design to protein structure prediction and synthesis planning. However, it is often challenged by the small data regimes typical of certain drug discovery tasks. In such scenarios, deep learning approaches-which are notoriously 'data-hungry'-might fail to live up to their promise. Developing novel approaches to leverage the power of deep learning in low-data scenarios is sparking great attention, and future developments are expected to propel the field further. This mini-review provides an overview of recent low-data-learning approaches in drug discovery, analyzing their hurdles and advantages. Finally, we venture to provide a forecast of future research directions in low-data learning for drug discovery.

Radiometric Assay of ABHD2 Activity.

The α,ß-hydrolase fold-containing protein 2 (ABHD2) is a serine hydrolase, responsible for the cleavage of endogenous 2-arachidonoylglycerol (2-AG). ABHD2 is activated by progesterone, thus, it is considered a nonnuclear receptor of this steroid hormone that terminates its biological effects. The products of ABHD2-catalyzed cleavage by the natural substrate 2-AG are glycerol and arachidonic acid; here, instead of 2-AG, the radioactive substrate 2-oleoyl-[3H]glycerol has been used as already done in various acylglycerol lipase activity assays. The amount of [3H]glycerol released allows to measure ABHD2 enzymatic activity.

Computational and Experimental Drug Repurposing of FDA-Approved Compounds Targeting the Cannabinoid Receptor CB1.

The cannabinoid receptor 1 (CB1R) plays a pivotal role in regulating various physiopathological processes, thus positioning itself as a promising and sought-after therapeutic target. However, the search for specific and effective CB1R ligands has been challenging, prompting the exploration of drug repurposing (DR) strategies. In this study, we present an innovative DR approach that combines computational screening and experimental validation to identify potential Food and Drug Administration (FDA)-approved compounds that can interact with the CB1R. Initially, a large-scale virtual screening was conducted using molecular docking simulations, where a library of FDA-approved drugs was screened against the CB1R's three-dimensional structures. This in silico analysis allowed us to prioritize compounds based on their binding affinity through two different filters. Subsequently, the shortlisted compounds were subjected to in vitro assays using cellular and biochemical models to validate their interaction with the CB1R and determine their functional impact. Our results reveal FDA-approved compounds that exhibit promising interactions with the CB1R. These findings open up exciting opportunities for DR in various disorders where CB1R signaling is implicated. In conclusion, our integrated computational and experimental approach demonstrates the feasibility of DR for discovering CB1R modulators from existing FDA-approved compounds. By leveraging the wealth of existing pharmacological data, this strategy accelerates the identification of potential therapeutics while reducing development costs and timelines. The findings from this study hold the potential to advance novel treatments for a range of CB1R -associated diseases, presenting a significant step forward in drug discovery research.

Prevalence of cancer therapy cardiotoxicity as assessed by imaging procedures: A scoping review.

BACKGROUND: Advances in treatment and optimization of chemotherapy protocols have greatly improved survival in cancer patients. Unfortunately, treatment can cause a reduction in left ventricular (LV) ejection fraction (EF) leading to cancer therapy-related cardiac dysfunction (CTRCD). We conducted a scoping review of published literature in order to identify and summarize the reported prevalence of cardiotoxicity evaluated by noninvasive imaging procedures in a wide-ranging of patients referred to cancer treatment as chemotherapy and/or radiation therapy. METHODS: Different databases were checked (PubMed, Embase, and Web of Science) to identify studies published from January 2000 to June 2021. Articles were included if they reported data on LVEF evaluation in oncological patients treated with chemotherapeutic agents and/or radiotherapy, measured by echocardiography and/or nuclear or cardiac magnetic resonance imaging test, providing criteria of CTRCD evaluation such as the specific threshold for LVEF decrease. RESULTS: From 963 citations identified, 46 articles, comprising 6841 patients, met the criteria for the inclusion in the scoping review. The summary prevalence of CTRCD as assessed by imaging procedures in the studies reviewed was 17% (95% confidence interval, 14-20). CONCLUSIONS: The results of our scoping review endorse the recommendations regarding imaging modalities to ensure identification of cardiotoxicity in patients undergoing cancer therapies. However, to improve patient management, more homogeneous CTRCD evaluation studies are required, reporting a detailed clinical assessment of the patient before, during and after treatment.

Advances in the discovery of fatty acid amide hydrolase inhibitors: what does the future hold?

INTRODUCTION: Fatty acid amide hydrolase (FAAH) is a membrane-bound enzyme, that inactivates endogenous signaling lipids of the fatty acid amide family, including the endocannabinoid anandamide (N-arachidonoylethanolamine, AEA). The latter compound has been shown to regulate a number of important pathophysiological conditions in humans, like feeding, obesity, immune response, reproductive events, motor coordination, and neurological disorders. Hence, direct manipulation of the endocannabinoid tone is thought to have therapeutic potential. A new opportunity to develop effective drugs may arise from multi-target directed ligand (MTDL) strategies, which brings the concept that a single compound can recognize different targets involved in the cascade of pathophysiological events. AREAS COVERED: This review reports the latest advances in the development of new single targeted and dual-targeted FAAH inhibitors over the past 5 years. EXPERT OPINION: In recent years, several FAAH inhibitors have been synthesized and investigated, yet to date none of them has reached the market as a systemic drug. Due to the diligence of inherent redundancy and robustness in many biological networks and pathways, multitarget inhibitors present a new prospect in the pharmaceutical industry for treatment of complex diseases.