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疾病领域	数量

神经系统疾病	2
内分泌与代谢疾病	1
肿瘤	1

排名前五的药物类型	数量

小分子化药	1
化学药	1

排名前五的靶点	数量

TMEM175	1
TEAD	1

关联

2

项与 Baobab AiBIO Co., Ltd. 相关的药物

BAB-301

靶点

TMEM175

作用机制

TMEM175调节剂

在研机构

Baobab AiBIO Co., Ltd.初创企业

原研机构

Baobab AiBIO Co., Ltd.初创企业

在研适应症

帕金森病

非在研适应症-

最高研发阶段临床前

首次获批国家/地区-

首次获批日期-

BAB-104

靶点

TEAD

作用机制

TEAD 抑制剂

在研机构

Baobab AiBIO Co., Ltd.初创企业

原研机构

Baobab AiBIO Co., Ltd.初创企业

在研适应症

胶质母细胞瘤 [+1]

非在研适应症-

最高研发阶段临床前

首次获批国家/地区-

首次获批日期-

100 项与 Baobab AiBIO Co., Ltd. 相关的临床结果

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0 项与 Baobab AiBIO Co., Ltd. 相关的专利（医药）

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8

项与 Baobab AiBIO Co., Ltd. 相关的文献（医药）

2023-12-01·Molecular Cancer Therapeutics

Abstract B142: Discovery of novel and potent TEAD inhibitors, orally available small molecules with anti-tumor activity in hippo pathway- dysregulated cancers

作者: Kim, Minhye ; No, Kyoung Tai ; Kim, Yongchan ; Cho, Seon Yeon ; Kim, Hanseong ; Park, Sungil ; Beak, Soojeong ; Moon, Sungho ; Lee, In Sang ; Kim, Jung-In ; Kim, Jinhyuk

AbstractHippo pathway plays a critical role in cell apoptosis, proliferation, tissue homeostasis. Dysregulation of Hippo pathway was reported to related to overall aspects of tumorigenesis. The higher expression a YAP/TAZ and TEADs or mutation of core components of hippo pathway, such as NF2, MST1/2 and LATS1/2 were reported in various cancer subtypes including mesothelioma, meningioma, glioblastoma, non-small cell lung cancer. TEAD auto-palmitoylation is required for protein stability and its transcriptional activity. Inhibiting TEAD activity regulation present attractive strategy for therapeutic intervention in the Hippo pathway. There are increasing proof that the inhibitor to central pocket of TEAD can be promising candidate for cancer treatment. We validated and optimized the hits, derived from our in silico screening system. Our lead compounds inhibiting palmitoylation of TEADs are the potent in vitro activities in TEAD reporter assay and hippo pathway-dysregulated mesotheliomas. In addition, these compounds reduced the expression of TEAD target genes. Furthermore, our compounds strongly inhibited tumor growth in NF2 deficient mouse xenograft model without any adverse events. In these models, our compounds showed excellent PK-PD correlation. Using these compounds, we also tested the possibility as therapy for combination drugs with KRAS inhibitor, EGFR inhibitors. In summary, we have potent TEAD inhibitor series, that showed inhibitory activities of tumor growth in NF2 deficient in vivo models, and may have therapeutic potential in diverse solid tumors.Citation Format: Sungho Moon, Seon Yeon Cho, Minhye Kim, Soojeong Beak, Jinhyuk Kim, Yongchan Kim, Sungil Park, Jung-In Kim, Hanseong Kim, In Sang Lee, Kyoung Tai No. Discovery of novel and potent TEAD inhibitors, orally available small molecules with anti-tumor activity in hippo pathway- dysregulated cancers [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B142.

Scientific Reports3区 · 综合性期刊

Quantum computational study of chloride attack on chloromethane for chemical accuracy and quantum noise effects with UCCSD and k-UpCCGSD ansatzes

3区 · 综合性期刊

ArticleOA

作者: No, Kyoung Tai ; Jeon, Hyeon-Nae ; Lim, Hocheol ; Oh, Byungdu ; Rhee, June-Koo

AbstractQuantum computing is expected to play an important role in solving the problem of huge computational costs in various applications by utilizing the collective properties of quantum states, including superposition, interference, and entanglement, to perform computations. Quantum mechanical (QM) methods are candidates for various applications and can provide accurate absolute energy calculations in structure-based methods. QM methods are powerful tools for describing reaction pathways and their potential energy surfaces (PES). In this study, we applied quantum computing to describe the PES of the bimolecular nucleophilic substitution (SN2) reaction between chloromethane and chloride ions. We performed noiseless and noise simulations using quantum algorithms and compared the accuracy and noise effects of the ansatzes. In noiseless simulations, the results from UCCSD and k-UpCCGSD are similar to those of full configurational interaction (FCI) with the same active space, which indicates that quantum algorithms can describe the PES of the SN2 reaction. In noise simulations, UCCSD is more susceptible to quantum noise than k-UpCCGSD. Therefore, k-UpCCGSD can serve as an alternative to UCCSD to reduce quantum noisy effects in the noisy intermediate-scale quantum era, and k-UpCCGSD is sufficient to describe the PES of the SN2 reaction in this work. The results showed the applicability of quantum computing to the SN2 reaction pathway and provided valuable information for structure-based molecular simulations with quantum computing.

BMC Bioinformatics

Prediction of polyreactive and nonspecific single-chain fragment variables through structural biochemical features and protein language-based descriptors

Article

作者: No, Kyoung Tai ; Lim, Hocheol

AbstractBackgroundMonoclonal antibodies (mAbs) have been used as therapeutic agents, which must overcome many developability issues after the discovery from in vitro display libraries. Especially, polyreactive mAbs can strongly bind to a specific target and weakly bind to off-target proteins, which leads to poor antibody pharmacokinetics in clinical development. Although early assessment of polyreactive mAbs is important in the early discovery stage, experimental assessments are usually time-consuming and expensive. Therefore, computational approaches for predicting the polyreactivity of single-chain fragment variables (scFvs) in the early discovery stage would be promising for reducing experimental efforts. ResultsHere, we made prediction models for the polyreactivity of scFvs with the known polyreactive antibody features and natural language model descriptors. We predicted 19,426 protein structures of scFvs with trRosetta to calculate the polyreactive antibody features and investigated the classifying performance of each factor for polyreactivity. In the known polyreactive features, the net charge of the CDR2 loop, the tryptophan and glycine residues in CDR-H3, and the lengths of the CDR1 and CDR2 loops, importantly contributed to the performance of the models. Additionally, the hydrodynamic features, such as partial specific volume, gyration radius, and isoelectric points of CDR loops and scFvs, were newly added to improve model performance. Finally, we made the prediction model with a robust performance (

$$\mathrm{AUC}=0.840$$

AUC=0.840) with an ensemble learning of the top 3 best models.ConclusionThe prediction models for polyreactivity would help assess polyreactive scFvs in the early discovery stage and our approaches would be promising to develop machine learning models with quantitative data from high throughput assays for antibody screening.

100 项与 Baobab AiBIO Co., Ltd. 相关的药物交易

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100 项与 Baobab AiBIO Co., Ltd. 相关的转化医学

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