Guided diffusion for molecular generation with interaction prompt.

Molecular generative models have exhibited promising capabilities in designing molecules from scratch with high binding affinities in a predetermined protein pocket, offering potential synergies with traditional structural-based drug design strategy. However, the generative processes of such models are random and the atomic interaction information between ligand and protein are ignored. On the other hand, the ligand has high propensity to bind with residues called hotspots. Hotspot residues contribute to the majority of the binding free energies and have been recognized as appealing targets for designed molecules. In this work, we develop an interaction prompt guided diffusion model, InterDiff to deal with the challenges. Four kinds of atomic interactions are involved in our model and represented as learnable vector embeddings. These embeddings serve as conditions for individual residue to guide the molecular generative process. Comprehensive in silico experiments evince that our model could generate molecules with desired ligand-protein interactions in a guidable way. Furthermore, we validate InterDiff on two realistic protein-based therapeutic agents. Results show that InterDiff could generate molecules with better or similar binding mode compared to known targeted drugs.

In silico construction of a focused fragment library facilitating exploration of chemical space.

Fragment-based drug design (FBDD) has emerged as a captivating subject in the realm of computer-aided drug design, enabling the generation of novel molecules through the rearrangement of ring systems within known compounds. The construction of focused fragment library plays a pivotal role in FBDD, necessitating the compilation of all potential bioactive ring systems capable of interacting with a specific target. In our study, we propose a workflow for the development of a focused fragment library and combinatorial compound library. The fragment library comprises seed fragments and collected fragments. The extraction of seed fragments is guided by receptor information, serving as a prerequisite for establishing a focused libraries. Conversely, collected fragments are obtained using the feature graph method, which offers a simplified representation of fragments and strikes a balance between diversity and similarity when categorizing different fragments. The utilization of feature graph facilitates the rational partitioning of chemical space at fragment level, enabling the exploration of desired chemical space and enhancing the efficiency of screening compound library. Analysis demonstrates that our workflow enables the enumeration of a greater number of entirely new potential compounds, thereby aiding in the rational design of drugs.

Epigenetic target identification strategy based on multi-feature learning.

The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics increases. In this study, we introduce a novel epigenetic target identification strategy (ETI-Strategy) that integrates a multi-task graph convolutional neural network prior model and a protein-ligand interaction classification discriminating model using large-scale bioactivity data for a panel of 55 epigenetic targets. Our approach utilizes machine learning techniques to achieve an AUC value of 0.934 for the prior model and 0.830 for the discriminating model, outperforming inverse docking in predicting protein-ligand interactions. When comparing with other open-source target identification tools, it was found that only our tool was able to accurately predict all the targets corresponding to each compound. This further demonstrates the ability of our strategy to take full advantage of molecular-level information as well as protein-level information in molecular activity prediction. Our work highlights the contribution of machine learning in the identification of potential epigenetic targets and offers a novel approach for epigenetic drug discovery and development.Communicated by Ramaswamy H. Sarma.

[Effect of acrylic bone cement mixed with calcium sulfate combined with percutaneous kyphoplasty in the treatment of osteoporotic fractures].

OBJECTIVE: To investigate the clinical efficacy of acrylic cement (PMMA) mixed with calcium sulfate combined with percutaneous kyphoplasty (PKP) in the treatment of osteoporotic fracture (OVCF). METHODS: The clinical data of 191 patients with OVCF treated with PKP from January 2020 to March 2021 were retrospectively analyzed. Among them, 82 patients with 94 vertebral bodies were treated with PMMA mixed with calcium sulfate as the observation group, and 109 patients with 125 vertebral bodies were treated with pure PMMA as the control group. Among the 82 patients in the observation group, there were 16 males and 66 females, with a mean age of (75.35±11.22) years old, including 36 thoracic vertebrae and 58 lumbar vertebrae. In the control group, there were 109 patients, 22 males and 87 females, with an average age of (74.51±9.21) years old, including 63 thoracic vertebrae and 62 lumbar vertebrae. The visual analog scale (VAS) before operation and 1 day, 3 months and 1 year after operation were calculated. The Oswestry disability index (ODI), Cobb's angle, vertebral body height and the probability of postoperative bone cement leakage were used to analyze the efficacy of the two groups. RESULTS: All the patients were followed up for more than one year. Compared with the control group, there was no significant difference in operation time, bleeding volume and bone cement injection volume between the two groups(P>0.05), while the leakage rate of bone cement was significantly lower in the observation group (P<0.05). In addition, there was no significant difference in VAS, ODI, Cobb angle, and vertebral body height between the two groups before operation, and 1 day, 3 months, and 1 year after operation (P>0.05), but each index was improved compared with that before operation (P<0.05). CONCLUSION: PMMA mixed with calcium sulfate has equivalent efficacy in treating OVCF than PMMA alone, but can effectively reduce the probability of cement leakage.

RPBP: Deep Retrosynthesis Reaction Prediction Based on Byproducts.

Retrosynthesis prediction is crucial in organic synthesis and drug discovery, aiding chemists in designing efficient synthetic routes for target molecules. Data-driven deep retrosynthesis prediction has gained importance due to new algorithms and enhanced computing power. Although existing models show certain predictive power on the USPTO-50K benchmark data set, no one considers the effects of byproducts during the prediction process, which may be due to the lack of byproduct information in the benchmark data set. Here, we propose a novel two-stage retrosynthesis reaction prediction framework based on byproducts called RPBP. First, RPBP predicts the byproduct involved in the reaction based on the product molecule. Then, it handles an end-to-end prediction problem based on the prediction of reactants by product and byproduct. Unlike other methods that first identify the potential reaction center and then predict reactant molecules, RPBP considers additional information from byproducts, such as reaction reagents, conditions, and sites. Interestingly, adding byproducts reduces model learning complexity in natural language processing (NLP). Our RPBP model achieves 54.7% and 66.6% top-1 retrosynthesis prediction accuracy when the reaction class is unknown and known, respectively. It outperforms existing methods for known-class reactions, thanks to the rich chemical information in byproducts. The prediction of four kinase drugs from the literature demonstrates the model's practicality and potential to accelerate drug discovery.

Co-model for chemical toxicity prediction based on multi-task deep learning.

The toxicity of compounds is closely related to the effectiveness and safety of drug development, and accurately predicting the toxicity of compounds is one of the most challenging tasks in medicinal chemistry and pharmacology. In this paper, we construct three types of models for single and multi-tasking based on 2D and 3D descriptors, fingerprints and molecular graphs, and then validate the models with benchmark tests on the Tox21 data challenge. We found that due to the information sharing mechanism of multi-task learning, it could address the imbalance problem of the Tox21 data sets to some extent, and the prediction performance of the multi-task was significantly improved compared with the single task in general. Given the complement of the different molecular representations and modeling algorithms, we attempted to integrate them into a robust Co-Model. Our Co-Model performs well in various evaluation metrics on the test set and also achieves significant performance improvement compared to other models in the literature, which clearly demonstrates its superior predictive power and robustness.

Analysis of Chronic Low Back Pain Caused by Lumbar Microinstability After Percutaneous Endoscopic Transforaminal Discectomy: A Retrospective Study.

Objective: Chronic low back pain (CLBP) after percutaneous endoscopic transforaminal discectomy (PTED) surgery may be caused by preoperative lumbar microinstability (MI). However, there is a paucity of research on the relationship between lumbar microinstability and chronic low back pain. The purpose of this article is to assess the preoperative radiographic characteristics of patients and evaluate the effects of lumbar microinstability on patient-reported outcomes among single-level lumbar disc herniation (LDH) patients who underwent PTED. Methods: This study retrospectively reviewed the radiographic characteristics of a consecutive series of 127 patients with low back pain and leg pain caused by single-level LDH underwent PTED from August 2018 to March 2021. They were divided into three groups according to the radiographic parameters: the stable group (Group S), the dysfunctional group (Group D), and the microinstability group (Group M). The visual analogue scale (VAS) scores for leg and low back pain and Oswestry Disability Index (ODI) were evaluated preoperatively and postoperatively. Logistic regression analysis was used to identify independent risk factors for CLBP. Results: Compared with Group D and Group S, Group M had the highest ODI scores (P < 0.01) and VAS scores (low back pain) (P < 0.01) after 1 year, while there were no significant differences in the VAS scores for leg pain at different time points after surgery (P > 0.05). In addition, the logistic regression analysis results regarding CLBP revealed that muscle fatty degeneration on MRI (95% CI, 1.20-8.51, P = 0.02), and facet tropism (95% CI, 1.39 -11.37, P = 0.01) may be independent risk factors. Conclusion: Patients with lumbar microinstability may have CLBP after PTED, so patients with lumbar microinstability may need to take internal fixation surgery to solve their symptoms.

Exploring the inorganic and organic nitrate aerosol formation regimes at a suburban site on the North China Plain.

Nitrate-driven aerosol pollution frequently occurs during winter over the North China Plain (NCP). Extensive studies have focused on inorganic nitrate formation, but few have focused on organic nitrates in China, precluding a thorough understanding of the nitrogen cycle and nitrate aerosol formation. Here, the inorganic (NO3,inorg) and organic nitrate (NO3,org) formation regimes under aerosol liquid water (ALW) and aerosol acidity (pH) influences were investigated during winter over the NCP based on data derived from an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). The campaign-averaged concentration of the total nitrate was 5.3 µg m-3, with a 13% contribution from NO3,org, which exhibited a significantly decreased contribution with increasing haze episode evolution. The diurnal cycles of NO3,inorg and NO3,org were similar, with high concentrations during the nighttime at a high ALW level, revealing the important role of aqueous-phase processes. However, the correlations between the aerosol pH and NO3,inorg (R2 = 0.13, P < 0.01) and NO3,org (R2 = 0.63, P < 0.01) during polluted periods indicated a contrasting effect of aerosol pH on inorganic and organic nitrate formation. Our results provide a useful reference for smog chamber studies and promote a better understanding of organic nitrate formation via anthropogenic emissions.

Highly time-resolved chemical characterization and implications of regional transport for submicron aerosols in the North China Plain.

To investigate the regional transport and formation mechanisms of submicron aerosols in the North China Plan (NCP), for the first time, we conducted simultaneous combined observations of the non-refractory submicron aerosols (NR-PM1) chemical compositions using aerosol mass spectrometer at urban Beijing (BJ) and at regional background area of the NCP (XL), from November 2018 to January 2019. During the observation period, average mass concentrations of PM1 in BJ and XL were 26.6 ± 31.7 and 16.0 ± 18.7 µg m-3 respectively. The aerosol composition in XL showed a lower contribution of organic aerosol (33% vs. 43%) and higher fractions of nitrate (35% vs. 30%), ammonium (16% vs. 13%), and chlorine (2% vs. 1%) than in BJ. Additionally, a higher contribution of secondary organic aerosol (SOA) was also observed in XL, suggesting low primary emissions and highly oxidized OA in the background area. Nitrate displayed a significantly enhanced contribution with the aggravation of aerosol pollution in both BJ and XL, which was completely neutralized by excess ammonium at both sites, suggesting that the abundant ammonia emissions in the NCP favor nitrate formation on a regional scale. In addition, a higher proportion of nitrate in XL can be attributed to the more neutral and higher oxidation capacity of the background atmosphere. Heterogeneous aqueous reaction plays an important role in sulfate and SOA formation, and is more efficient in BJ which can be attributed to the higher aerosol surface areas at urban site. Regional transport from the southwestern regions of NCP showed a significant impact on the formation of haze episodes. Beside the invasion of transported pollutants, the abundant water vapor associated with the air mass to the downwind background area further enhanced local secondary transformation and expanded the regional scope of the haze pollution in the NCP.

Parkin-mediated mitophagy as a potential therapeutic target for intervertebral disc degeneration.

Intervertebral disc degeneration (IDD) is a complicated pathological condition blamed for low back pain. Mitochondrion is of vital importance for cellular homeostasis, and mitochondrial dysfunction is considered to be one of the major causes of cellular damage. Mitophagy is a cellular process to eliminate impaired mitochondria and showed protective effects in various diseases; however, its role in IDD is still not clear. Here, we explore the role of Parkin-mediated mitophagy in IDD. In this study, we found that Parkin was upregulated in degenerative nucleus pulposus (NP) tissues in vivo as well as in TNF-α stimulated NP cells in vitro. Knockdown of Parkin by siRNA showed that Parkin is crucial for apoptosis and mitochondrion homeostasis in NP cells. Further study showed that upregulation of Parkin by salidroside may eliminate impaired mitochondria and promote the survival of NP cells through activation of mitophagy in vitro. In in vivo study, we found that salidroside could inhibit the apoptosis of NP cells and ameliorate the progression of IDD. These results suggested that Parkin is involved in the pathogenesis of IDD and may be a potential therapeutic target for IDD.

Two-year continuous measurements of carbonaceous aerosols in urban Beijing, China: Temporal variations, characteristics and source analyses.

Organic carbon (OC) and elemental carbon (EC) in the PM2.5 of urban Beijing were measured hourly with a semi-continuous thermal-optical analyzer from Jan 1, 2013 to Dec 31, 2014. The annual average OC and EC concentrations in Beijing were 17.0 ±â€¯12.4 and 3.4 ±â€¯2.0 µg/m3 for 2013, and 16.8 ±â€¯14.5 and 3.5 ±â€¯2.9 µg/m3 for 2014. It is obvious that the annual average concentrations of OC and EC in 2014 were not less than those in 2013 while the annual average PM2.5 concentration (89.4 µg/m3) in 2014 was slightly reduced as compared to that (96.9 µg/m3) in 2013. Strong seasonality of the OC and EC concentrations were found with high values during the heating seasons and low values during the non-heating seasons. The diurnal cycles of OC and EC characterized by higher values at night and in the morning were caused by primary emissions, secondary transformation and stable meteorological condition. Due to increasing photochemical activity, the OC peaks were observed at approximately noon. No clear weekend effects were observed. Interestingly, in the early mornings on weekends in the autumn and winter, the OC and EC concentrations were close to or higher than those on weekdays. Our data also indicate that high OC and EC concentrations were closely associated with their potential source areas which were determined based on the potential source contribution function analysis. High potential source areas were identified and were mainly located in the south of Beijing and the plain of northern China. A much denser source region was recorded in the winter than in the other seasons, indicating that local and regional transport over regional scales are the most important. These results demonstrate that both regional transport from the southern regions and local accumulation could lead to the enhancements of OC and EC and likely contribute to the severe haze pollution in Beijing.