Recent updates in click and computational chemistry for drug discovery and development.

Drug discovery is a costly and time-consuming process with a very high failure rate. Recently, click chemistry and computer-aided drug design (CADD) represent popular areas for new drug development. Herein, we summarized the recent updates in click and computational chemistry for drug discovery and development including clicking to effectively synthesize druggable candidates, synthesis and modification of natural products, targeted delivery systems, and computer-aided drug discovery for target identification, seeking out and optimizing lead compounds, ADMET prediction as well as compounds synthesis, hopefully, inspires new ideas for novel drug development in the future.

Synergism of amlodipine and telmisartan or candesartan on blood pressure reduction by using SynergyFinder 3.0 and probability sum test in vivo.

This study was designed to evaluate the synergism of two couples of antihypertensive drugs (amlodipine + telmisartan and amlodipine + candesartan) on blood pressure reduction in vivo by both SynergyFinder 3.0 and probability sum test. Spontaneously hypertensive rats were treated with intragastric administration of amlodipine (0.5, 1, 2, and 4 mg/kg), telmisartan (4, 8, and 16 mg/kg), candesartan (1, 2, and 4 mg/kg), nine combinations for amlodipine and telmisartan, and nine combinations for amlodipine and candesartan. The control rats were treated by 0.5% carboxymethylcellulose sodium. Blood pressure was recorded continuously up to 6 h after administration. Both SynergyFinder 3.0 and the probability sum test were used to evaluate the synergistic action. The synergisms calculated by SynergyFinder 3.0 are consistent with the probability sum test both in two different combinations. There is an obviously synergistic interaction between amlodipine and telmisartan or candesartan. The combinations of amlodipine and telmisartan (2 + 4 and 1 + 4 mg/kg) and amlodipine and candesartan (0.5 + 4 and 2 + 1 mg/kg) might exert an optimum synergism against hypertension. Compared with the probability sum test, SynergyFinder 3.0 is more stable and reliable to analyze the synergism.

Short-Term Effects of Particle Size and Constituents on Blood Pressure in Healthy Young Adults in Guangzhou, China.

Background Although several studies have focused on the associations between particle size and constituents and blood pressure, results have been inconsistent. Methods and Results We conducted a panel study, between December 2017 and January 2018, in 88 healthy university students in Guangzhou, China. Weekly systolic blood pressure and diastolic blood pressure were measured for each participant for 5 consecutive weeks, resulting in a total of 440 visits. Mass concentrations of particles with an aerodynamic diameter of ≤2.5 µm (PM2.5), ≤1.0 µm (PM1.0), ≤0.5 µm (PM0.5), ≤0.2 µm (PM0.2), and number concentrations of airborne particulates of diameter ≤0.1 µm were measured. Linear mixed-effect models were used to estimate the associations between blood pressure and particles and PM2.5 constituents 0 to 48 hours before blood pressure measurement. PM of all the fractions in the 0.2- to 2.5-µm range were positively associated with systolic blood pressure in the first 24 hours, with the percent changes of effect estimates ranging from 3.5% to 8.8% for an interquartile range increment of PM. PM0.2 was also positively associated with diastolic blood pressure, with an increase of 5.9% (95% CI, 1.0%-11.0%) for an interquartile range increment (5.8 µg/m3) at lag 0 to 24 hours. For PM2.5 constituents, we found positive associations between chloride and diastolic blood pressure (1.7% [95% CI, 0.1%-3.3%]), and negative associations between vanadium and diastolic blood pressure (-1.6% [95% CI, -3.0% to -0.1%]). Conclusions Both particle size and constituent exposure are significantly associated with blood pressure in the first 24 hours following exposure in healthy Chinese adults.

Short-Term Effects of Particle Sizes and Constituents on Blood Biomarkers among Healthy Young Adults in Guangzhou, China.

Evidence of the effects of various particle sizes and constituents on blood biomarkers is limited. We performed a panel study with five repeated measurements in 88 healthy college students in Guangzhou, China between December 2017 and January 2018. Mass concentrations of particles with aerodynamic diameters ≤ 2.5 µm (PM2.5), PM1, and PM0.5 and number concentrations of particles with aerodynamic diameters ≤ 200 nm (PN0.2) and PN0.1 were measured. We used linear mixed-effect models to explore the associations of size-fractionated particulate matter and PM2.5 constituents with five blood biomarkers 0-5 days prior to blood collection. We found that an interquartile range (45.9 µg/m3) increase in PM2.5 concentration was significantly associated with increments of 16.6, 3.4, 12.3, and 8.8% in C-reactive protein (CRP), monocyte chemoattractant protein-1 (MCP-1), soluble vascular cell adhesion molecule-1 (sVCAM-1), and endothelin-1(ET-1) at a 5-day lag, respectively. Similar estimates were observed for PM1, PM0.5, PN0.2, and PN0.1. For PM2.5 constituents, consistent positive associations were observed between F- and sVCAM-1 and CRP and between NH4+ and MCP-1, and negative associations were found between Na+ and MCP-1 and ET-1, between Cl- and MCP-1, and between Mg2+ and sVCAM-1. Our results suggested that both particle size and constituent exposure are significantly associated with circulating biomarkers among healthy Chinese adults. Particularly, PN0.1 at a 5-day lag and F- and NH4+ are the most associated with these blood biomarkers.

Associations of Particulate Matter Sizes and Chemical Constituents with Blood Lipids: A Panel Study in Guangzhou, China.

Existing evidence is scarce concerning the various effects of different PM sizes and chemical constituents on blood lipids. A panel study that involved 88 healthy college students with five repeated measurements (440 blood samples in total) was performed. We measured mass concentrations of particulate matter with diameters ≤ 2.5 µm (PM2.5), ≤1.0 µm (PM1.0), and ≤0.5 µm (PM0.5) as well as number concentrations of particulate matter with diameters ≤ 0.2 µm (PN0.2) and ≤0.1 µm (PN0.1). We applied linear mixed-effect models to assess the associations between short-term exposure to different PM size fractions and PM2.5 constituents and seven lipid metrics. We found significant associations of greater concentrations of PM in different size fractions within 5 days before blood collection with lower high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A (ApoA1) levels, higher apolipoprotein B (ApoB) levels, and lower ApoA1/ApoB ratios. Among the PM2.5 constituents, we observed that higher concentrations of tin and lead were significantly associated with decreased HDL-C levels, and higher concentrations of nickel were associated with higher HDL-C levels. Our results suggest that short-term exposure to PM in different sizes was deleteriously associated with blood lipids. Some constituents, especially metals, might be the major contributors to the detrimental effects.

Associations of ambient particulate matter with homocysteine metabolism markers and effect modification by B vitamins and MTHFR C677T gene polymorphism.

Evidence concerning effects of ambient air pollution on homocysteine (HCY) metabolism is scarce. We aimed to explore the associations between ambient particulate matter (PM) exposure and the HCY metabolism markers and to evaluate effect modifications by folate, vitamin B12, and methylenetetrahyfrofolate reductase (MTHFR) C677T gene polymorphism. Between December 1, 2017 and January 5, 2018, we conducted a panel study in 88 young college students in Guangzhou, China, and received 5 rounds of health examinations. Real-time concentrations of PMs with aerodynamic diameter ≤2.5 (PM2.5), ≤1.0 (PM1.0), and ≤0.1 (PM0.1) were monitored, and the serum HCY metabolism markers (i.e., HCY, S-Adenosylhomocysteine [SAH], and S-Adenosylmethionine [SAM]) were repeatedly measured. We applied linear mixed effect models combined with a distributed lag model to evaluate the associations of PMs with the HCY metabolism markers. We also explored effect modifications of folate, vitamin B12, and the MTHFR C677T polymorphism on the associations. We observed that higher concentrations of PM2.5 and PM1.0 were associated with higher serum levels of HCY, SAH, SAM, and SAM/SAH ratio (e.g., a 10 µg/m3 increase in PM2.5 during lag 0 day and lag 5 day was significantly associated with 1.3-19.4%, 1.3-28.2%, 6.2-64.4%, and 4.8-28.2% increase in HCY, SAH, SAM, and SAM/SAH ratio, respectively). In addition, we observed that the associations of PM2.5 with the HCY metabolism markers were stronger in participants with lower B vitamins levels. This study demonstrated that short-term exposure to PM2.5 and PM1.0 was deleteriously associated with the HCY metabolism markers, especially in people with lower B vitamins levels.