Graphormer supervised de novo protein design method and function validation.

Protein design is central to nearly all protein engineering problems, as it can enable the creation of proteins with new biological functions, such as improving the catalytic efficiency of enzymes. One key facet of protein design, fixed-backbone protein sequence design, seeks to design new sequences that will conform to a prescribed protein backbone structure. Nonetheless, existing sequence design methods present limitations, such as low sequence diversity and shortcomings in experimental validation of the designed functional proteins. These inadequacies obstruct the goal of functional protein design. To improve these limitations, we initially developed the Graphormer-based Protein Design (GPD) model. This model utilizes the Transformer on a graph-based representation of three-dimensional protein structures and incorporates Gaussian noise and a sequence random masks to node features, thereby enhancing sequence recovery and diversity. The performance of the GPD model was significantly better than that of the state-of-the-art ProteinMPNN model on multiple independent tests, especially for sequence diversity. We employed GPD to design CalB hydrolase and generated nine artificially designed CalB proteins. The results show a 1.7-fold increase in catalytic activity compared to that of the wild-type CalB and strong substrate selectivity on p-nitrophenyl acetate with different carbon chain lengths (C2-C16). Thus, the GPD method could be used for the de novo design of industrial enzymes and protein drugs. The code was released at https://github.com/decodermu/GPD.

Phanto-IDP: compact model for precise intrinsically disordered protein backbone generation and enhanced sampling.

The biological function of proteins is determined not only by their static structures but also by the dynamic properties of their conformational ensembles. Numerous high-accuracy static structure prediction tools have been recently developed based on deep learning; however, there remains a lack of efficient and accurate methods for exploring protein dynamic conformations. Traditionally, studies concerning protein dynamics have relied on molecular dynamics (MD) simulations, which incur significant computational costs for all-atom precision and struggle to adequately sample conformational spaces with high energy barriers. To overcome these limitations, various enhanced sampling techniques have been developed to accelerate sampling in MD. Traditional enhanced sampling approaches like replica exchange molecular dynamics (REMD) and frontier expansion sampling (FEXS) often follow the MD simulation approach and still cost a lot of computational resources and time. Variational autoencoders (VAEs), as a classic deep generative model, are not restricted by potential energy landscapes and can explore conformational spaces more efficiently than traditional methods. However, VAEs often face challenges in generating reasonable conformations for complex proteins, especially intrinsically disordered proteins (IDPs), which limits their application as an enhanced sampling method. In this study, we presented a novel deep learning model (named Phanto-IDP) that utilizes a graph-based encoder to extract protein features and a transformer-based decoder combined with variational sampling to generate highly accurate protein backbones. Ten IDPs and four structured proteins were used to evaluate the sampling ability of Phanto-IDP. The results demonstrate that Phanto-IDP has high fidelity and diversity in the generated conformation ensembles, making it a suitable tool for enhancing the efficiency of MD simulation, generating broader protein conformational space and a continuous protein transition path.

Multi-indicator comparative evaluation for deep learning-based protein sequence design methods.

MOTIVATION: Proteins found in nature represent only a fraction of the vast space of possible proteins. Protein design presents an opportunity to explore and expand this protein landscape. Within protein design, protein sequence design plays a crucial role, and numerous successful methods have been developed. Notably, deep learning-based protein sequence design methods have experienced significant advancements in recent years. However, a comprehensive and systematic comparison and evaluation of these methods have been lacking, with indicators provided by different methods often inconsistent or lacking effectiveness. RESULTS: To address this gap, we have designed a diverse set of indicators that cover several important aspects, including sequence recovery, diversity, root-mean-square deviation of protein structure, secondary structure, and the distribution of polar and nonpolar amino acids. In our evaluation, we have employed an improved weighted inferiority-superiority distance method to comprehensively assess the performance of eight widely used deep learning-based protein sequence design methods. Our evaluation not only provides rankings of these methods but also offers optimization suggestions by analyzing the strengths and weaknesses of each method. Furthermore, we have developed a method to select the best temperature parameter and proposed solutions for the common issue of designing sequences with consecutive repetitive amino acids, which is often encountered in protein design methods. These findings can greatly assist users in selecting suitable protein sequence design methods. Overall, our work contributes to the field of protein sequence design by providing a comprehensive evaluation system and optimization suggestions for different methods.

Characteristic patterns of functional connectivity-mediated cerebral small vessel disease-related cognitive impairment and depression.

Cerebral small vessel disease is common in most individuals aged 60 years or older, and it is associated with cognitive dysfunction, depression, anxiety disorder, and mobility problems. Currently, many cerebral small vessel disease patients have both cognitive impairment and depressive symptoms, but the relationship between the 2 is unclear. The present research combined static and dynamic functional network connectivity methods to explore the patterns of functional networks in cerebral small vessel disease individuals with cognitive impairment and depression (cerebral small vessel disease-mild cognitive impairment with depression) and their relationship. We found specific functional network patterns in the cerebral small vessel disease-mild cognitive impairment with depression individuals (P < 0.05). The cerebral small vessel disease individuals with depression exhibited unstable dynamic functional network connectivity states (transitions likelihood: P = 0.040). In addition, we found that the connections within the lateral visual network between the sensorimotor network and ventral attention network could mediate white matter hyperintensity-related cognitive impairment (indirect effect: 0.064; 95% CI: 0.003, 0.170) and depression (indirect effect: -0.415; 95% CI: -1.080, -0.011). Cognitive function can negatively regulate white matter hyperintensity-related depression. These findings elucidate the association between cognitive impairment and depression and provide new insights into the underlying mechanism of cerebral small vessel disease-related cognitive dysfunction and depression.

Transcriptome-wide subtyping of pediatric and adult T cell acute lymphoblastic leukemia in an international study of 707 cases.

T cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy of T cell progenitors, known to be a heterogeneous disease in pediatric and adult patients. Here we attempted to better understand the disease at the molecular level based on the transcriptomic landscape of 707 T-ALL patients (510 pediatric, 190 adult patients, and 7 with unknown age; 599 from published cohorts and 108 newly investigated). Leveraging the information of gene expression enabled us to identify 10 subtypes (G1­G10), including the previously undescribed one characterized by GATA3 mutations, with GATA3R276Q capable of affecting lymphocyte development in zebrafish. Through associating with T cell differentiation stages, we found that high expression of LYL1/LMO2/SPI1/HOXA (G1­G6) might represent the early T cell progenitor, pro/precortical/cortical stage with a relatively high age of disease onset, and lymphoblasts with TLX3/TLX1 high expression (G7­G8) could be blocked at the cortical/postcortical stage, while those with high expression of NKX2-1/TAL1/LMO1 (G9­G10) might correspond to cortical/postcortical/mature stages of T cell development. Notably, adult patients harbored more cooperative mutations among epigenetic regulators, and genes involved in JAK-STAT and RAS signaling pathways, with 44% of patients aged 40 y or above in G1 bearing DNMT3A/IDH2 mutations usually seen in acute myeloid leukemia, suggesting the nature of mixed phenotype acute leukemia.

Map conformational landscapes of intrinsically disordered proteins with polymer physics quantities.

Disordered proteins are conformationally flexible proteins that are biologically important and have been implicated in devastating diseases such as Alzheimer's disease and cancer. Unlike stably folded structured proteins, disordered proteins sample a range of different conformations that needs to be accounted for. Here, we treat disordered proteins as polymer chains, and compute a dimensionless quantity called instantaneous shape ratio (Rs), as Rs = Ree2/Rg2, where Ree is end-to-end distance and Rg is radius of gyration. Extended protein conformations tend to have high Ree compared with Rg, and thus have high Rs values, whereas compact conformations have smaller Rs values. We use a scatter plot of Rs (representing shape) against Rg (representing size) as a simple map of conformational landscapes. We first examine the conformational landscape of simple polymer models such as Random Walk, Self-Avoiding Walk, and Gaussian Walk (GW), and we notice that all protein/polymer maps lie within the boundaries of the GW map. We thus use the GW map as a reference and, to assess conformational diversity, we compute the fraction of the GW conformations (fC) covered by each protein/polymer. Disordered proteins all have high fC scores, consistent with their disordered nature. Each disordered protein accesses a different region of the reference map, revealing differences in their conformational ensembles. We additionally examine the conformational maps of the nonviral gene delivery vector polyethyleneimine at various protonation states, and find that they resemble disordered proteins, with coverage of the reference map decreasing with increasing protonation state, indicating decreasing conformational diversity. We propose that our method of combining Rs and Rg in a scatter plot generates a simple, meaningful map of the conformational landscape of a disordered protein, which in turn can be used to assess conformational diversity of disordered proteins.

PTMint database of experimentally verified PTM regulation on protein-protein interaction.

MOTIVATION: Post-translational modification (PTM) is an important biochemical process. which includes six most well-studied types: phosphorylation, acetylation, methylation, sumoylation, ubiquitylation and glycosylation. PTM is involved in various cell signaling pathways and biological processes. Abnormal PTM status is closely associated with severe diseases (such as cancer and neurologic diseases) by regulating protein functions, such as protein-protein interactions (PPIs). A set of databases was constructed separately for PTM sites and PPI; however, the resource of regulation for PTM on PPI is still unsolved. RESULTS: Here, we firstly constructed a public accessible database of PTMint (PTMs that are associated with PPIs) (https://ptmint.sjtu.edu.cn/) that contains manually curated complete experimental evidence of the PTM regulation on PPIs in multiple organisms, including Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Saccharomyces cerevisiae and Schizosaccharomyces pombe. Currently, the first version of PTMint encompassed 2477 non-redundant PTM sites in 1169 proteins affecting 2371 protein-protein pairs involving 357 diseases. Various annotations were systematically integrated, such as protein sequence, structure properties and protein complex analysis. PTMint database can help to insight into disease mechanism, disease diagnosis and drug discovery associated with PTM and PPI. AVAILABILITY AND IMPLEMENTATION: PTMint is freely available at: https://ptmint.sjtu.edu.cn/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Systemic lupus erythematosus with chronic persistent intracranial hypertension: A case report.

OBJECTIVE: The aim is to investigate the clinical characteristics of systemic lupus erythematosus with intracranial hypertension. METHODS: The clinical characteristics of one case of systemic lupus erythematosus with chronic persistent intracranial hypertension were analyzed, and related literature was reviewed by searching Medline and Wanfang databases. RESULTS: Intracranial hypertension in SLE patients may occur at the onset or during the course of the disease. Our patient was diagnosed with IH 3 years after the onset of SLE. Headache and papilledema were the most common symptoms of intracranial hypertension, followed by nausea or vomiting, vision changes, and cerebral palsy. Our patient had a headache and cranial hypertension that lasted for years, but no papilledema was found. Corticosteroid is currently the mainstay of the treatment of IIH in patients with SLE, and immunosuppressive agents, acetazolamide, intravenous mannitol and furosemide are also used. However, our patient did not respond to these treatments and presents the characteristics of chronic persistent intracranial hypertension. CONCLUSION: Systemic lupus erythematosus with intracranial hypertension is a rare manifestation of SLE, which is not completely parallel to SLE activity. Headache and papilledema were the most common presenting symptoms. Different from previous reported cases, our patient had poor response to treatments, showing chronic and persistent characteristics.

Early Aggregation Mechanism of SOD128-38 Based on Force Field Parameter of 5-Cyano-Tryptophan.

The aggregation of superoxide dismutase 1 (SOD1) results in amyloid deposition and is involved in familial amyotrophic lateral sclerosis, a fatal motor neuron disease. There have been extensive studies of its aggregation mechanism. Noncanonical amino acid 5-cyano-tryptophan (5-CN-Trp), which has been incorporated into the amyloid segments of SOD1 as infrared probes to increase the structural sensitivity of IR spectroscopy, is found to accelerate the overall aggregation rate and potentially modulate the aggregation process. Despite these observations, the underlying mechanism remains elusive. Here, we optimized the force field parameters of 5-CN-Trp and then used molecular dynamics simulation along with the Markov state model on the SOD128-38 dimer to explore the kinetics of key intermediates in the presence and absence of 5-CN-Trp. Our findings indicate a significantly increased probability of protein aggregate formation in 5CN-Trp-modified ensembles compared to wildtype. Dimeric ß-sheets of different natures were observed exclusively in the 5CN-Trp-modified peptides, contrasting with wildtype simulations. Free-energy calculations and detailed analyses of the dimer structure revealed augmented interstrand interactions attributed to 5-CN-Trp, which contributed more to peptide affinity than any other residues. These results explored the key events critical for the early nucleation of amyloid-prone proteins and also shed light on the practice of using noncanonical derivatives to study the aggregation mechanism.

Four undescribed coumarin derivatives, with ten amides from the roots of Ficus hirta and their cytotoxic activities.

Four undescribed coumarin derivatives, ficusalt A (1) and ficusalt B (2), a pair of racemic coumarins, (±) ficudimer A (3a/3b), along with ten known amides, were isolated from the roots of Ficus hirta. Their structures were elucidated by several spectroscopic data analyses, including HRESIMS, NMR, and X-ray single-crystal diffraction. The cytotoxic activities of all compounds against HeLa, HepG2, MCF-7, and H460 cell lines were detected using the MTT assay. Among these, 5 showed the highest activity against HeLa cells. Subsequently, the apoptotic, anti-invasive, and anti-migration effects of 5 on HeLa cells were determined by flow cytometer, transwell invasion assay, and wound-healing assay, respectively. The result suggested that 5 distinctly induced the apoptosis in HeLa cells and inhibited their invasion and migration. Further studies on anticancer mechanisms were conducted using Western blotting. As a result, 5 increased the cleavage of PARP and the expression of pro-apoptotic protein Bax. Moreover, 5 notably upregulated the phosphorylation of p38 and JNK, whereas inhibited the expression of p-ERK and p-AKT. Our results demonstrated that 5 could be a potential leading compound for further application in the treatment of cervical cancer.

CRISPR/Cas9-mediated editing of GmDWF1 brassinosteroid biosynthetic gene induces dwarfism in soybean.

KEY MESSAGE: The study on the GmDWF1-deficient mutant dwf1 showed that GmDWF1 plays a crucial role in determining soybean plant height and yield by influencing the biosynthesis of brassinosteroids. Soybean has not adopted the Green Revolution, such as reduced height for increased planting density, which have proven beneficial for cereal crops. Our research identified the soybean genes GmDWF1a and GmDWF1b, homologous to Arabidopsis AtDWF1, and found that they are widely expressed, especially in leaves, and linked to the cellular transport system, predominantly within the endoplasmic reticulum and intracellular vesicles. These genes are essential for the synthesis of brassinosteroids (BR). Single mutants of GmDWF1a and GmDWF1b, as well as double mutants of both genes generated through CRISPR/Cas9 genome editing, exhibit a dwarf phenotype. The single-gene mutant exhibits moderate dwarfism, while the double mutant shows more pronounced dwarfism. Despite the reduced stature, all types of mutants preserve their node count. Notably, field tests have shown that the single GmDWF1a mutant produced significantly more pods than wild-type plants. Spraying exogenous brassinolide (BL) can compensate for the loss in plant height induced by the decrease in endogenous BRs. Comparing transcriptome analyses of the GmDWF1a mutant and wild-type plants revealed a significant impact on the expression of many genes that influence soybean growth. Identifying the GmDWF1a and GmDWF1b genes could aid in the development of compact, densely planted soybean varieties, potentially boosting productivity.

COVID-19 vaccination and infection status: a cross-sectional survey of patients with rheumatic diseases in China.

To evaluate the vaccination status and clinical practice of patients with rheumatic diseases (RD) during the COVID-19 pandemic in China and to explore the impact of vaccination on infection severity in patients with RD. A cross-sectional survey was conducted among RD patients in outpatient and inpatient settings of the Rheumatology and Immunology Department in our hospital. Participants' characteristics, vaccination status, COVID-19 infection status, and medication for acute COVID-19 were collected. A total of 749 valid surveys were included in the study. A total of 271 (36.2%) patients were not vaccinated, and 478 (63.8%) patients received at least one dose of COVID-19 vaccine. 83.3% of patients were vaccinated with inactivated vaccines. Several patients with RD experienced the disease flare (57, 11.9%) and some adverse reactions (31, 6.5%) after COVID-19 vaccination. The COVID-19 infection rate was 84.1% in our study, which was not reduced by vaccination. However, vaccinated patients with RD showed decreased frequencies of pneumonia and hospitalization, compared with those of unvaccinated patients. Independent factors associated with hospitalization were COVID-19 vaccination (OR = 0.422, 95% CI 0.227-0.783), advanced age (OR = 1.070, 95% CI 1.046-1.095), ILD (OR = 1.245, 95% CI 1.082-1.432), and glucocorticoid (OR = 4.977, 95% CI 2.326-10.647). Adverse reactions to vaccines and disease flare are not common in RD patients. Although COVID-19 vaccination could not reduce the risk of COVID-19 infection in RD patients, it may effectively decrease the frequencies of pneumonia and hospitalization after infection. It is recommended that patients with RD should receive COVID-19 vaccination if there are no contraindications because the benefits outweigh the risks.

Discovery of Sesquiterpene Lactones with Cytotoxicity from the Herb of Youngia japonica.

In the process of searching for anti-breast cancer agents, five sesquiterpene lactones (1-5), including two previously undescribed ones, yjaponica B-C (1-2), were isolated from the herb of Youngia japonica. Their structures were elucidated by spectroscopic data analyses and Marfey's method. Cytotoxic activities of all compounds against A549, U87, and 4T1 cell lines were tested using the CCK8 assay. The result showed that compound 3 possessed the highest cytotoxic activity against 4T1 cells with an IC50 value of 10.60 µM. Furthermore, compound 3 distinctly induced apoptosis, inhibited immigration, and blocked the cell cycle of 4T1 cells. In addition, compound 3 induced the production of reactive oxygen species. Further anticancer mechanism studies showed that compound 3 significantly upregulated expression of the cleaved caspase 3 and PARP, whereas it downregulated the expression of Bcl-2, cyclin D1, cyclin A2, CDK4, and CDK2. Taken together, our results demonstrate that compound 3 has a high potential of being used as a leading compound for the discovery of new anti-breast cancer agent.

In Situ Growth of Sodium Manganese Hexacyanoferrate on Carbon Nanotubes for High-Performance Sodium-Ion Batteries.

Sodium manganese hexacyanoferrate (NaMnHCF) has emerged as a research hotspot among Prussian blue analogs for sodium-ion battery cathode materials due to its advantages of high voltage, high specific capacity, and abundant raw materials. However, its practical application is limited by its poor electronic conductivity. In this study, we aim to solve this problem through the in situ growth of NaMnHCF on carbon nanotubes (CNTs) using a simple coprecipitation method. The results show that the overall electronic conductivity of NaMnHCF is significantly improved after the introduction of CNTs. The NaMnHCF@10%CNT sample presents a specific capacity of 90 mA h g-1, even at a current density of 20 C (2400 mA g-1). The study shows that the optimized composite exhibits a superior electrochemical performance at different mass loadings (from low to high), which is attributed to the enhanced electron transport and shortened electron pathway. Surprisingly, the cycling performance of the composites was also improved, resulting from decreased polarization and the subsequent reduction in the side reactions at the cathode/electrolyte interface. Furthermore, we revealed the evolution of potential plateau roots from the extraction of crystal water during the charge-discharge process of NaMnHCF based on the experimental results. This study is instructive not only for the practical application of NaMnHCF materials but also for advancing our scientific understanding of the behavior of crystal water during the charge-discharge process.

The Bax inhibitor GmBI-1α interacts with a Nod factor receptor and plays a dual role in the legume-rhizobia symbiosis.

The gene networks surrounding Nod factor receptors that govern the symbiotic process between legumes and rhizobia remain largely unexplored. Here, we identify 13 novel GmNFR1α-associated proteins by yeast two-hybrid screening, and describe a potential interacting protein, GmBI-1α. GmBI-1α had the highest positive correlation with GmNFR1α in a co-expression network analysis, and its expression at the mRNA level in roots was enhanced by rhizobial infection. Moreover, GmBI-1α-GmNFR1α interaction was shown to occur in vitro and in vivo. The GmBI-1α protein was localized to multiple subcellular locations, including the endoplasmic reticulum and plasma membrane. Overexpression of GmBI-1α increased the nodule number in transgenic hairy roots or transgenic soybean, whereas down-regulation of GmBI-1α transcripts by RNA interference reduced the nodule number. In addition, the nodules in GmBI-1α-overexpressing plants became smaller in size and infected area with reduced nitrogenase activity. In GmBI-1α-overexpressing transgenic soybean, the elevated GmBI-1α also promoted plant growth and suppressed the expression of defense signaling-related genes. Infection thread analysis of GmBI-1α-overexpressing plants showed that GmBI-1α promoted rhizobial infection. Collectively, our findings support a GmNFR1α-associated protein in the Nod factor signaling pathway and shed new light on the regulatory mechanism of GmNFR1α in rhizobial symbiosis.

Personal Precise Force Field for Intrinsically Disordered and Ordered Proteins Based on Deep Learning.

Intrinsically disordered proteins (IDPs) are proteins without a fixed three-dimensional (3D) structure under physiological conditions and are associated with Parkinson's disease, Alzheimer's disease, cancer, cardiovascular disease, amyloidosis, diabetes, and other diseases. Experimental methods can hardly capture the ensemble of diverse conformations for IDPs. Molecular dynamics (MD) simulations can sample continuous conformations that might provide a valuable complement to experimental data. However, the accuracy of MD simulations depends on the quality of force field. In particular, the evolutionary conservation and coevolution of IDPs introduce that current force fields could not precisely reproduce the conformation of IDPs. In order to improve the performance of force field, deep learning and reweighting methods were used to automatically generate personal force field parameters for intrinsically disordered and ordered proteins. At first, the deep learning method predicted more accuracy φ/ψ dihedral of residue than the previous method. Then, reweighting optimized the personal force field parameters for each residue. Finally, typical representative systems such as IDPs, structure protein, and fast-folding protein were used to evaluate this force field. The results indicate that two personal force field parameters (named PPFF1 and PPFF1_af2) could better reproduce the experimental observables than ff03CMAP force field. In summary, this strategy will provide feasibility for the development of precise personal force fields.

Phosphorylation Modification Force Field FB18CMAP Improving Conformation Sampling of Phosphoproteins.

Phosphorylation of proteins plays an important regulatory role at almost all levels of cellular organization. Molecular dynamics (MD) simulation is a promising tool to reveal the mechanism of how phosphorylation regulates many key biological processes at the atomistic level. MD simulation accuracy depends on force field precision, while the current force fields for phospho-amino acids have resulted in notable inconsistency with experimental data. Here, a new force field parameter (named FB18CMAP) is generated by fitting against quantum mechanics (QM) energy in aqueous solution with φ/ψ dihedral potential-energy surfaces optimized using CMAP parameters. MD simulations of phosphorylated dipeptides, intrinsically disordered proteins (IDPs), and ordered (folded) proteins show that FB18CMAP can mimic NMR observables and structural characteristics of phosphorylated dipeptides and proteins more accurately than the FB18 force field. These findings suggest that FB18CMAP performs well in both the simulation of ordered and disordered states of phosphorylated proteins.

Phosphorylation Regulation Mechanism of ß2 Integrin for the Binding of Filamin Revealed by Markov State Model.

Leukocyte adhesion deficiency-1 (LAD-1) disorder is a severe immunodeficiency syndrome caused by deficiency or mutation of ß2 integrin. The phosphorylation on threonine 758 of ß2 integrin acts as a molecular switch inhibiting the binding of filamin. However, the switch mechanism of site-specific phosphorylation at the atom level is still poorly understood. To resolve the regulation mechanism, all-atom molecular dynamics simulation and Markov state model were used to study the dynamic regulation pathway of phosphorylation. Wild type system possessed lower binding free energy and fewer number of states than the phosphorylated system. Both systems underwent local disorder-to-order conformation conversion when achieving steady states. To reach steady states, wild type adopted less number of transition paths/shortest path according to the transition path theory than the phosphorylated system. The underlying phosphorylated regulation pathway was from P1 to P0 and then P4 state, and the main driving force should be hydrogen bond and hydrophobic interaction disturbing the secondary structure of phosphorylated states. These studies will shed light on the pathogenesis of LAD-1 disease and lay a foundation for drug development.

Research and Evaluation of the Allosteric Protein-Specific Force Field Based on a Pre-Training Deep Learning Model.

Allosteric modulators are important regulation elements that bind the allosteric site beyond the active site, leading to the changes in dynamic and/or thermodynamic properties of the protein. Allosteric modulators have been a considerable interest as potential drugs with high selectivity and safety. However, current experimental methods have limitations to identify allosteric sites. Therefore, molecular dynamics simulation based on empirical force field becomes an important complement of experimental methods. Moreover, the precision and efficiency of current force fields need improvement. Deep learning and reweighting methods were used to train allosteric protein-specific precise force field (named APSF). Multiple allosteric proteins were used to evaluate the performance of APSF. The results indicate that APSF can capture different types of allosteric pockets and sample multiple energy-minimum reference conformations of allosteric proteins. At the same time, the efficiency of conformation sampling for APSF is higher than that for ff14SB. These findings confirm that the newly developed force field APSF can be effectively used to identify the allosteric pocket that can be further used to screen potential allosteric drugs based on these pockets.

Apocarotenoids from Equisetum debile Roxb. ex Vaucher regulate the lipid metabolism via the activation of the AMPK/ACC/SREBP-1c signaling pathway.

Sixteen undescribed apocarotenoids (1-16), along with 22 known analogues, were isolated from the aerial parts of Equisetum debile. Their structures, including absolute configurations, were elucidated by NMR, HRESIMS, X-ray diffraction analysis, the modified Mosher's method and the quantum-chemical calculation of electronic circular dichroism (ECD) spectra. Compounds 1-9, 11-12 are the first example of C16-apocarotenoids appeared in nature. The plausible biosynthetic pathway of 1-16 was proposed. Moreover, the isolates were evaluated for their lipid-lowering activity, and the results showed that 13, 14, 15, 22, 31, 32 and 33 could remarkably decrease the levels of both TC and TG in FFA induced HepG2 cells at 20 µM. The oil red staining assay further demonstrated the lipid-lowering effects of 13, 14 and 15. The western blot results indicated that compounds 13, 14 and 15 could regulate the lipid metabolism via the activation of the AMPK/ACC/SREBP-1c signaling pathway. A preliminary structure-activity relationship (SAR) study of the isolates indicated that the apocarotenoids with 6/5 ring system displayed more potent lipid-lowering effects.