Recent breakthroughs in protein structure prediction have opened new avenues for genome-wide drug discovery, yet existing virtual screening methods remain computationally prohibitive. We present DrugCLIP, a contrastive learning framework that achieves ultrafast and accurate virtual screening, up to 10 million times faster than docking, while consistently outperforming various baselines on in silico benchmarks. In wet-lab validations, DrugCLIP achieved a 15% hit rate for norepinephrine transporter, and structures of two identified inhibitors were determined in complex with the target protein. For thyroid hormone receptor interactor 12, a target that lacks holo structures and small-molecule binders, DrugCLIP achieved a 17.5% hit rate using only AlphaFold2-predicted structures. Finally, we released GenomeScreenDB, an open-access database providing precomputed results for ~10,000 human proteins screened against 500 million compounds, pioneering a drug discovery paradigm in the post-AlphaFold era.

CpG island hypermethylation, a hallmark of cancer, exhibits substantial heterogeneity across tumors, presenting both opportunities and challenges for cancer diagnostics and therapeutics. While this heterogeneity offers potential for patient stratification to predict clinical outcomes and personalize treatments, it complicates the development of robust biomarkers for early detection. Understanding the mechanisms driving this heterogeneity is essential for advancing biomarker design. Here, simulation-based analyses demonstrate that tumor purity and the high prevalence of low epi-mutation samples significantly obscure the identification of negative, rather than positive, regulators of CpG island hypermethylation, limiting a comprehensive understanding of heterogeneity sources. By addressing these confounders, we identify impaired DNA methylation maintenance, as indicated by global hypomethylation levels, as the primary contributor to CpG island hypermethylation variability among known regulators. This finding is supported by integrative analyses of datasets from The Cancer Genome Atlas (TCGA) Pan-Cancer Atlas, Genomics of Drug Sensitivity in Cancer (GDSC1000) cancer cell lines, and epi-allele analyses of two independent whole-genome bisulfite sequencing cohorts, using a newly developed method, MeHist (https://github.com/vhang072/MeHist). Furthermore, we assess widely used hypermethylation biomarkers across ten cancer types and find that 65 out of 246 (26.4%) are significantly influenced by impaired methylation maintenance. Incorporating hypomethylation and hypermethylation markers improves the robustness of cancer detection, as validated across multiple plasma cell-free DNA datasets. In summary, our findings highlight the value of simulation-guided integrative analysis in mitigating confounding effects and identify impaired DNA methylation maintenance as a key regulator of CpG island hypermethylation heterogeneity.

Modern Von Neumann-based computers are increasingly inadequate to meet current computational demands. Braininspired computing (BIC) offers a promising alternative, aiming to emulate the efficiency, adaptability, and learning capabilities of the human brain. Despite significant progress, a unified technological solution for BIC has yet to emerge. This talk reviews recent BIC advancements, covering theories, chips, software, and systems. Key challenges and potential solutions for robust BIC systems and the development of general purposed BIC are also examined.

Numerous protein-coding genes are associated with human diseases, yet approximately 90% of them lack targeted therapeutic intervention. While conventional computational methods such as molecular docking have facilitated the discovery of potential hit compounds, the development of genome-wide virtual screening against the expansive chemical space remains a formidable challenge. Here we introduce DrugCLIP, a novel framework that combines contrastive learning and dense retrieval to achieve rapid and accurate virtual screening. Compared to traditional docking methods, DrugCLIP improves the speed of virtual screening by several orders of magnitude. In terms of performance, DrugCLIP not only surpasses docking and other deep learning-based methods across two standard benchmark datasets but also demonstrates high efficacy in wet-lab experiments. Specifically, DrugCLIP successfully identified agonists with < 100 nM affinities for 5HT2AR, a key target in psychiatric diseases. For another target NET, whose structure is newly solved and not included in the training set, our method achieved a hit rate of 15%, with 12 diverse molecules exhibiting affinities better than Bupropion. Additionally, two chemically novel inhibitors were validated by structure determination with Cryo-EM. Building on this foundation, we present the results of a pioneering trillion-scale genome-wide virtual screening, encompassing approximately 10,000 AlphaFold2 predicted proteins within the human genome and 500 million molecules from the ZINC and Enamine REAL database. This work provides an innovative perspective on drug discovery in the post-AlphaFold era, where comprehensive targeting of all disease-related proteins is within reach. ### Competing Interest Statement The authors have declared no competing interest.

Trajectory inference methods are frequently used for cell fate analysis, however, most of them are similarity-based and lack an understanding of the causality underlying differentiation processes. Here, we present CIBER, a C ausal I nference– B ased framework for the E valuation of feature effects and the R econstruction of cellular differentiation networks. CIBER provides a novel paradigm for dissecting cell state transitions other than trajectory inference and differential analysis. It is a versatile framework that can be applied to various types of data, including transcriptomic, epigenomic and microarray data. It can identify both known and potential cell-lineage structures with minimal prior knowledge. By integrating the CIBER-learned network with structural causal model and applying in silico perturbation as inventions, we generated an effect matrix that quantifies the impact of different features on each differentiation branch. Using this effect matrix, CIBER can identify crucial features involved in haematopoiesis, even if these features show no significant difference in expression between lineages. Moreover, CIBER can predict novel regulation associations and provide insight into the potential mechanism underlying the influence of transcription factors on biological processes. To validate CIBER’s capabilities, we conducted in vivo experiments on Bcl11b , a non-differentially expressed transcription factor identified by CIBER. Our results demonstrate that dysfunction of Bcl11b leads to a bias towards myeloid lineage differentiation at the expense of lymphoid lineage, which is consistent with our predictions.

Spiders are renowned for their efficient capture of flying insects using intricate aerial webs. How the spider nervous systems evolved to cope with this specialized hunting strategy and various environmental clues in an aerial space remains unknown. Here we report a brain-cell atlas of >30,000 single-cell transcriptomes from a web-building spider ( Hylyphantes graminicola ). Our analysis revealed the preservation of ancestral neuron types in spiders, including the potential coexistence of noradrenergic and octopaminergic neurons, and many peptidergic neuronal types that are lost in insects. By comparing the genome of two newly sequenced plesiomorphic burrowing spiders with three aerial web-building spiders, we found that the positively selected genes in the ancestral branch of web-building spiders were preferentially expressed (42%) in the brain, especially in the three mushroom body-like neuronal types. By gene enrichment analysis and RNAi experiments, these genes were suggested to be involved in the learning and memory pathway and may influence the spiders’ web-building and hunting behaviour. Our results provide key sources for understanding the evolution of behaviour in spiders and reveal how molecular evolution drives neuron innovation and the diversification of associated complex behaviours.

17 Most existing trajectory inference methods are similarity-based and lack an understanding 18 of the latent causality among differentiation processes. Here, we present CIBER, a Causal 19 Inference–Based framework for the Evaluation of feature effects and the Reconstruction 20 of cellular differentiation networks. CIBER is suitable for various types of omics data, 21 including profilings of gene expression and chromatin accessibility. We show that CIBER 22 can capture known cell-lineage structures and identify potential novo differentiation 23 branches. By combining the CIBER-learned network with the structural causal model and 24 applying in silico perturbation, we constructed an effect-matrix that quantifies the impacts 25 of different features on each branch. We subsequently identified features important to the 26 network structure through differentiation driver feature (DDF) analysis. We demonstrated 27 that DDF analysis can identify features crucial to haematopoiesis but show no significant 28

Multiple new variants of SARS-CoV-2 have been identified as the COVID-19 pandemic spreads across the globe. However, most epidemic models view the virus as static and unchanging and thus fail to address the consequences of the potential evolution of the virus. Here, we built a competitive susceptible-infected-removed (coSIR) model to simulate the competition between virus strains of differing severities or transmissibility under various virus control policies. The coSIR model predicts that although the virus is extremely unlikely to evolve into a “super virus” that causes an increased fatality rate, virus variants with less severe symptoms can lead to potential new outbreaks and can cost more lives over time. The present model also demonstrates that the protocols restricting the transmission of the virus, such as wearing masks and social distancing, are the most effective strategy in reducing total mortality. A combination of adequate testing and strict quarantine is a powerful alternative to policies such as mandatory stay-at-home orders, which may have an enormous negative impact on the economy. In addition, building Mobile Cabin Hospitals can be effective and efficient in reducing the mortality rate of highly infectious virus strains.

This Supporting Information includes the simulation code on the training of the nonlinear memristor neural network using the self-adaptive learning method discussed in the main text.The demonstrated network is LeNet-5 and can be easily extended to be larger scale networks.

Neuromorphic electronics, an emerging field that aims for building electronic mimics of the biological brain, holds promise for reshaping the frontiers of information technology and enabling a more intelligent and efficient computing paradigm. As their biological brain counterpart, the neuromorphic electronic systems are complex, having multiple levels of organization. Inspired by David Marr's famous three‐level analytical framework developed for neuroscience, the advances in neuromorphic electronic systems are selectively surveyed and given significance to these research endeavors as appropriate from the computational level, algorithmic level, or implementation level. Under this framework, the problem of how to build a neuromorphic electronic system is defined in a tractable way. In conclusion, the development of neuromorphic electronic systems confronts a similar challenge to the one neuroscience confronts, that is, the limited constructability of the low‐level knowledge (implementations and algorithms) to achieve high‐level brain‐like (human‐level) computational functions. An opportunity arises from the communication among different levels and their codesign. Neuroscience lab‐on‐neuromorphic chip platforms offer additional opportunity for mutual benefit between the two disciplines.

棘白菌素是一类新型抗真菌药物,包括卡泊芬净、米卡芬净、阿尼芬净,其抗菌原理为干扰真菌细胞壁1,3-β-D-葡聚糖的合成,使真菌细胞壁发生渗透性改变,导致真菌细胞破裂死亡.棘白菌素类药物可用于治疗念珠菌引起的感染,具有抗菌谱广、安全性高等优点.近年来念珠菌对棘白菌素不同水平耐药的报道逐渐增多,其机制主要是念珠菌细胞壁葡聚糖合成酶编码基因FKS热点区(HS)的碱基突变,进而导致棘白菌素对葡聚糖合成酶的亲和力降低出现耐药.本文从棘白菌素类药物抗真菌特点、念珠菌对棘白菌素耐药的流行病学及耐药机制3个方面综述棘白菌素抗真菌药物的概况.

Background Recently, liquid biopsy for cancer detection has pursued great progress. However, there are still a lack of high quality markers. It is a challenge to detect cancer stably and accurately in plasma cell free DNA (cfDNA), when the ratio of cancer signal is low. Repetitive genes or elements may improve the robustness of signals. In this study, we focused on ribosomal DNA which repeats hundreds of times in human diploid genome and investigated performances for cancer detection in plasma. Results We collected bisulfite sequencing samples including normal tissues and 4 cancer types and found that intergenic spacer (IGS) of rDNA has high methylation levels and low variation in normal tissues and plasma. Strikingly, IGS of rDNA shows significant hypo-methylation in tumors compared with normal tissues. Further, we collected plasma bisulfite sequencing data from 224 healthy subjects and cancer patients. Means of AUC in testing set were 0.96 (liver cancer), 0.94 (lung cancer and), 0.92 (colon cancer) with classifiers using only 10 CpG sites. Due to the feature of high copy number, when liver cancer plasma WGBS was down-sampled to 10 million raw reads (0.25× whole genome coverage), the prediction performance decreased only a bit (mean AUC=0.93). Finally, methylation of rDNA could also be used for monitor cancer progression and treatment. Conclusion Taken together, we provided the high-resolution map of rDNA methylation in tumors and supported that methylation of rDNA was a competitive and robust marker for detecting cancer and monitoring cancer progression in plasma. * AFP : alpha-fetoprotein AUC : area under curves bp : base pair cfDNA : cell free DNA CpG : cytosine-phosphate-guanine ctDNA : circulating tumor DNA C.V. : coefficient of variance ETS : external transcribed spacer IGS : intergenic spacer ITS : internal transcribed spacer KNN : k-nearest neighbor M : million rDNA : ribosomal DNA ROC : Receiver operating characteristic RRBS : reduced representation bisulfite sequencing SVM : support vector machine (SVM) classifier WGBS : Whole genome bisulfite sequencing

Concomitance of diverse synaptic plasticity across different timescales produces complex cognitive processes. To achieve comparable cognitive complexity in memristive neuromorphic systems, devices that are capable of emulating short-term (STP) and long-term plasticity (LTP) concomitantly are essential. In existing memristors, however, STP and LTP can only be induced selectively because of the inability to be decoupled using different loci and mechanisms. In this work, the first demonstration of truly concomitant STP and LTP is reported in a three-terminal memristor that uses independent physical phenomena to represent each form of plasticity. The emerging layered material Bi2 O2 Se is used for memristors for the first time, opening up the prospects for ultrathin, high-speed, and low-power neuromorphic devices. The concerted action of STP and LTP allows full-range modulation of the transient synaptic efficacy, from depression to facilitation, by stimulus frequency or intensity, providing a versatile device platform for neuromorphic function implementation. A heuristic recurrent neural circuitry model is developed to simulate the intricate "sleep-wake cycle autoregulation" process, in which the concomitance of STP and LTP is posited as a key factor in enabling this neural homeostasis. This work sheds new light on the development of generic memristor platforms for highly dynamic neuromorphic computing.

机械感受如触觉、听觉、本体感受等感觉信息对于调控生物体的行为具有至关重要的意义.近年来,越来越多的研究发现机械感受离子通道或蛋白对于维持机体正常生命活动极其重要,很多机械感受受体在体内分布广泛,在不同的组织中可发挥着不同的功能(如NompC与piezo)[1-8].在听觉传导中,跨膜离子通道样蛋白TMC (transmembrane channel-like)蛋白家族的几个成员发挥着巨大的作用.

Rewarding experiences are often well remembered, and such memory formation is known to be dependent on dopamine modulation of the neural substrates engaged in learning and memory; however, it is unknown how and where in the brain dopamine signals bias episodic memory toward preceding rather than subsequent events. Here we found that photostimulation of channelrhodopsin-2-expressing dopaminergic fibers in the dentate gyrus induced a long-term depression of cortical inputs, diminished theta oscillations, and impaired subsequent contextual learning. Computational modeling based on this dopamine modulation indicated an asymmetric association of events occurring before and after reward in memory tasks. In subsequent behavioral experiments, preexposure to a natural reward suppressed hippocampus-dependent memory formation, with an effective time window consistent with the duration of dopamine-induced changes of dentate activity. Overall, our results suggest a mechanism by which dopamine enables the hippocampus to encode memory with reduced interference from subsequent experience.

Precise patterning of dendritic arbors is critical for the wiring and function of neural circuits. Dendrite-extracellular matrix (ECM) adhesion ensures that the dendrites of Drosophila dendritic arborization (da) sensory neurons are properly restricted in a 2D space, and thereby facilitates contact-mediated dendritic self-avoidance and tiling. However, the mechanisms regulating dendrite-ECM adhesion in vivo are poorly understood. Here, we show that mutations in the semaphorin ligand sema-2b lead to a dramatic increase in self-crossing of dendrites due to defects in dendrite-ECM adhesion, resulting in a failure to confine dendrites to a 2D plane. Furthermore, we find that Sema-2b is secreted from the epidermis and signals through the Plexin B receptor in neighboring neurons. Importantly, we find that Sema-2b/PlexB genetically and physically interacts with TORC2 complex, Tricornered (Trc) kinase, and integrins. These results reveal a novel role for semaphorins in dendrite patterning and illustrate how epidermal-derived cues regulate neural circuit assembly.

Drosophila larval locomotion, which entails rhythmic body contractions, is controlled by sensory feedback from proprioceptors. The molecular mechanisms mediating this feedback are little understood. By using genetic knock-in and immunostaining, we found that the Drosophila melanogaster transmembrane channel-like (tmc) gene is expressed in the larval class I and class II dendritic arborization (da) neurons and bipolar dendrite (bd) neurons, both of which are known to provide sensory feedback for larval locomotion. Larvae with knockdown or loss of tmc function displayed reduced crawling speeds, increased head cast frequencies, and enhanced backward locomotion. Expressing Drosophila TMC or mammalian TMC1 and/or TMC2 in the tmc-positive neurons rescued these mutant phenotypes. Bending of the larval body activated the tmc-positive neurons, and in tmc mutants this bending response was impaired. This implicates TMC's roles in Drosophila proprioception and the sensory control of larval locomotion. It also provides evidence for a functional conservation between Drosophila and mammalian TMCs.

Mechanosensation, one of the fastest sensory modalities, mediates diverse behaviors including those pertinent for survival. It is important to understand how mechanical stimuli trigger defensive behaviors. Here, we report that Drosophila melanogaster adult flies exhibit a kicking response against invading parasitic mites over their wing margin with ultrafast speed and high spatial precision. Mechanical stimuli that mimic the mites' movement evoke a similar kicking behavior. Further, we identified a TRPV channel, Nanchung, and a specific Nanchung-expressing neuron under each recurved bristle that forms an array along the wing margin as being essential sensory components for this behavior. Our electrophysiological recordings demonstrated that the mechanosensitivity of recurved bristles requires Nanchung and Nanchung-expressing neurons. Together, our results reveal a novel neural mechanism for innate defensive behavior through mechanosensation. SIGNIFICANCE STATEMENT We discovered a previously unknown function for recurved bristles on the Drosophila melanogaster wing. We found that when a mite (a parasitic pest for Drosophila) touches the wing margin, the fly initiates a swift and accurate kick to remove the mite. The fly head is dispensable for this behavior. Furthermore, we found that a TRPV channel, Nanchung, and a specific Nanchung-expressing neuron under each recurved bristle are essential for its mechanosensitivity and the kicking behavior. In addition, touching different regions of the wing margin elicits kicking directed precisely at the stimulated region. Our experiments suggest that recurved bristles allow the fly to sense the presence of objects by touch to initiate a defensive behavior (perhaps analogous to touch-evoked scratching; Akiyama et al., 2012).