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AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind that can predict three-dimensional (3D) structures of proteins from amino acid sequences with atomic-level accuracy. Protein structure prediction is one of the most challenging problems in computational biology and chemistry, and has puzzled scientists for 50 years. The advent of AF2 presents an unprecedented progress in protein structure prediction and has attracted much attention. Subsequent release of structures of more than 200 million proteins predicted by AF2 further aroused great enthusiasm in the science community, especially in the fields of biology and medicine. AF2 is thought to have a significant impact on structural biology and research areas that need protein structure information, such as drug discovery, protein design, prediction of protein function, et al. Though the time is not long since AF2 was developed, there are already quite a few application studies of AF2 in the fields of biology and medicine, with many of them having preliminarily proved the potential of AF2. To better understand AF2 and promote its applications, we will in this article summarize the principle and system architecture of AF2 as well as the recipe of its success, and particularly focus on reviewing its applications in the fields of biology and medicine. Limitations of current AF2 prediction will also be discussed.

Understanding transcriptional responses to chemical perturbations is central to drug discovery, but exhaustive experimental screening of disease-compound combinations is unfeasible. To overcome this limitation, here we introduce PRnet, a perturbation-conditioned deep generative model that predicts transcriptional responses to novel chemical perturbations that have never experimentally perturbed at bulk and single-cell levels. Evaluations indicate that PRnet outperforms alternative methods in predicting responses across novel compounds, pathways, and cell lines. PRnet enables gene-level response interpretation and in-silico drug screening for diseases based on gene signatures. PRnet further identifies and experimentally validates novel compound candidates against small cell lung cancer and colorectal cancer. Lastly, PRnet generates a large-scale integration atlas of perturbation profiles, covering 88 cell lines, 52 tissues, and various compound libraries. PRnet provides a robust and scalable candidate recommendation workflow and successfully recommends drug candidates for 233 diseases. Overall, PRnet is an effective and valuable tool for gene-based therapeutics screening. Understanding transcriptional responses to chemical perturbations is crucial for drug discovery. Here, authors present PRnet, a deep generative model that predicts gene responses to novel chemical perturbations, enabling in-silico drug screening and the identification of candidate compounds for various diseases.

Long noncoding RNAs contribute to the cell-type-specific regulation of gene expression. Fan and colleagues identify a unique conserved lncRNA, lncKdm2b , that is transcribed divergently from the Kdm2b gene and is necessary for ILC3 maintenance in the gut. Innate lymphoid cells (ILCs) communicate with other hematopoietic and nonhematopoietic cells to regulate immunity, inflammation and tissue homeostasis. How ILC lineages develop and are maintained remains largely unknown. In this study we observed that a divergent long noncoding RNA (lncRNA), lncKdm2b , was expressed at high levels in intestinal group 3 ILCs (ILC3s). LncKdm2b deficiency in the hematopoietic system led to reductions in the number and effector functions of ILC3s. LncKdm2b expression sustained the maintenance of ILC3s by promoting their proliferation through activation of the transcription factor Zfp292. Mechanistically, lncKdm2b recruited the chromatin organizer Satb1 and the nuclear remodeling factor (NURF) complex onto the Zfp292 promoter to initiate its transcription. Deletion of Zfp292 or Bptf also abrogated the maintenance of ILC3s, leading to susceptibility to bacterial infection. Therefore, our findings reveal that lncRNAs may represent an additional layer of regulation of ILC development and function.

Natural antisense long noncoding RNAs (lncRNAs) are widespread in many organisms. However, their biological functions remain largely unknown, particularly in plants. We report the identification and characterization of an endogenous lncRNA, TWISTED LEAF (TL), which is transcribed from the opposite strand of the R2R3 MYB transcription factor gene locus, OsMYB60, in rice (Oryza sativa). TL and OsMYB60 were found to be coexpressed in many different tissues, and the expression level of TL was higher than that of OsMYB60. Downregulation of TL by RNA interference (RNAi) and overexpression of OsMYB60 resulted in twisted leaf blades in transgenic rice. The expression level of OsMYB60 was significantly increased in TL-RNAi transgenic plants. This suggests that TL may play a cis-regulatory role on OsMYB60 in leaf morphological development. We also determined that the antisense transcription suppressed the sense gene expression by mediating chromatin modifications. We further discovered that a C2H2 transcription factor, OsZFP7, is an OsMYB60 binding partner and involved in leaf development. Taken together, these findings reveal that the cis-natural antisense lncRNA plays a critical role in maintaining leaf blade flattening in rice. Our study uncovers a regulatory mechanism of lncRNA in plant leaf development.

The piRNA machinery is known for its role in mediating epigenetic silencing of transposons. Recent studies suggest that this function also involves piRNA-guided cleavage of transposon-derived transcripts. As many piRNAs also appear to have the capacity to target diverse mRNAs, this raises the intriguing possibility that piRNAs may act extensively as siRNAs to degrade specific mRNAs. To directly test this hypothesis, we compared mouse PIWI （MI- WI）-associated piRNAs with experimentally identified cleaved mRNA fragments from mouse testes, and observed cleavage sites that predominantly occur at position 10 from the 5＇ end of putative targeting piRNAs. We also noted strong biases for U and A residues at nucleotide positions 1 and 10, respectively, in both piRNAs and mRNA frag- ments, features that resemble the pattern of piRNA amplification by the ＇ping-pong＇ cycle. Through mapping of MIWI-RNA interactions by CLIP-seq and gene expression profiling, we found that many potential piRNA-targeted mRNAs directly interact with MIWI and show elevated expression levels in the testes of Miwi catalytic mutant mice. Reporter-based assays further revealed the importance of base pairing between piRNAs and mRNA targets and the requirement for both the slicer activity and piRNA-loading ability of MIWI in piRNA-mediated target repression. Importantly, we demonstrated that proper turnover of certain key piRNA targets is essential for sperm formation. Together, these findings reveal the siRNA-like function of the piRNA machinery in mouse testes and its central requirement for male germ cell development and maturation.

Glioblastoma (GBM) ranks among the most lethal of human cancers, containing glioma stem cells (GSCs) that display therapeutic resistance. Here, we report that the lncRNA INHEG is highly expressed in GSCs compared to differentiated glioma cells (DGCs) and promotes GSC self-renewal and tumorigenicity through control of rRNA 2’-O-methylation. INHEG induces the interaction between SUMO2 E3 ligase TAF15 and NOP58, a core component of snoRNP that guides rRNA methylation, to regulate NOP58 sumoylation and accelerate the C/D box snoRNP assembly. INHEG activation enhances rRNA 2 ’ -O-methylation, thereby increasing the expression of oncogenic proteins including EGFR, IGF1R, CDK6 and PDGFRB in glioma cells. Taken together, this study identifies a lncRNA that connects snoRNP-guided rRNA 2’-O-methylation to upregulated protein translation in GSCs, supporting an axis for potential therapeutic targeting of gliomas. Long noncoding RNAs (lncRNAs) may contribute to cancer progression. Here the authors show that LncRNA INHEG modulates rRNA 2’-O-methylation and facilitates mRNA translation to promote glioma stem cell renewal and growth.

Non-alcoholic fatty liver disease (NAFLD) is the hepatic manifestation of the metabolic syndrome that elevates the risk of hepatocellular carcinoma (HCC). Although alteration of lipid metabolism has been increasingly recognized as a hallmark of cancer cells, the deregulated metabolic modulation of HCC cells in the NAFLD progression remains obscure. Here, we discovers an endoplasmic reticulum-residential protein, Nogo-B, as a highly expressed metabolic modulator in both murine and human NAFLD-associated HCCs, which accelerates high-fat, high-carbohydrate diet-induced metabolic dysfunction and tumorigenicity. Mechanistically, CD36-mediated oxLDL uptake triggers CEBPβ expression to directly upregulate Nogo-B, which interacts with ATG5 to promote lipophagy leading to lysophosphatidic acid-enhanced YAP oncogenic activity. This CD36-Nogo-B-YAP pathway consequently reprograms oxLDL metabolism and induces carcinogenetic signaling for NAFLD-associated HCCs. Targeting the Nogo-B pathway may represent a therapeutic strategy for HCC arising from the metabolic syndrome. Non alcoholic fatty liver disease (NAFLD) associates with an elevated risk of developing hepatocellular carcinoma (HCC). Here, the authors find that Nogo-B, an endoplasmic reticulum resident protein, is upregulated by lipid uptake and acts as an oncogene in NAFLD-associated HCC by promoting lipid droplet breakdown by lipophagy and triggering Hippo pathway dysregulation

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Extracellular vesicles (EV) are critical mediators of intercellular communication within the tumor microenvironment, and cancer-cell-secreted EVs often facilitate cancer progression. Here we show that in HBV-associated HCC, tumor-cell-derived EVs contain a TGFβ-inducible long noncoding RNA, termed HDAC2-AS2 . EVs enriched with HDAC2-AS2 facilitate cancer progression by suppressing cytotoxicity of intra-tumor CD8 + T cells. Mechanistically, in activated cytotoxic CD8 + T cells, translocation of the transcription factor cyclin-dependent kinase 9 (CDK9), to the cytoplasm is critical for functional integrity. HDAC2-AS2 targets and blocks cytosolic CDK9, and this results in exhaustion of PD-1 + CD8 + T cells and suppression of IFN-γ + CD8 + T cell cytotoxicity. Notably, we demonstrate that low CDK9 and high HDAC2-AS2 expressions are associated with poor survival of HCC, which can be rescued by anti-PD-1 therapy. These findings emphasize the significance of tumor-derived EVs in suppressing antitumor CD8 + T cell immunity to promote tumorigenesis, and highlight extracellular HDAC2-AS2 as a promising biomarker and therapeutic target for HCC. Here authors show that EVs derived from hepatocellular carcinomas may contain the long noncoding RNA, HDAC2-AS2, which suppresses antitumour CD8 + T cells by interfering with transcriptional and epigenetic regulation of their activated, cytotoxic functional state.

YTHDC2, a unique YTH-domain-containing protein that recognizes N6-methyladenosine (m 6 A) on RNA, plays critical roles in diverse pathological processes and represents a promising therapeutic target. Despite its potential, no potent small-molecule inhibitors have been reported to date. To bridge this gap, we develop EPMolGen, a deep learning-based molecular generative model that explicitly incorporates the electrostatic features of receptor proteins. The model achieves state-of-the-art performance in dry-lab validations. Using EPMolGen, we identify H3 , a YTHDC2 inhibitor with an IC 50 of 16.84 μM. Subsequent structural optimization of H3 yields DC2-C1 , a highly potent compound with an IC 50 of 0.168 μM against YTHDC2 and selectivity over other YTH-domain proteins. In cellular assays, DC2-C1 effectively targets YTHDC2. Notably, DC2-C1 treatment substantially reduces the expression levels of multiple target mRNAs of YTHDC2, leading to phenotypic suppression of related cells. Overall, this study highlights the great potential of deep learning in drug discovery and provides a promising lead compound for drug development targeting YTHDC2. YTHDC2 is a promising therapeutic target, but lacks potent inhibitors. Yang et al. develop a deep learning-based molecule generator EPMolGen. Using this model, they discover a potent, selective, and cell-active small molecule inhibitor of YTHDC2.

Dongfeng Gu and colleagues report a genome-wide association study for coronary artery disease in Han Chinese individuals. They identify four loci newly associated with coronary artery disease. We performed a meta-analysis of 2 genome-wide association studies of coronary artery disease comprising 1,515 cases and 5,019 controls followed by replication studies in 15,460 cases and 11,472 controls, all of Chinese Han ancestry. We identify four new loci for coronary artery disease that reached the threshold of genome-wide significance ( P < 5 × 10 −8 ). These loci mapped in or near TTC32 - WDR35 , GUCY1A3 , C6orf10-BTNL2 and ATP2B1 . We also replicated four loci previously identified in European populations (in or near PHACTR1 , TCF21 , CDKN2A-CDKN2B and C12orf51 ). These findings provide new insights into pathways contributing to the susceptibility for coronary artery disease in the Chinese Han population.