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Combining crystallographic and binding affinity data towards a novel dataset of small molecule overlays 结合晶体学和结合亲和数据对一个新的小分子覆盖数据集。
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-12-04 DOI: 10.1007/s10822-024-00581-1
Sophia M. N. Hönig, Torben Gutermuth, Christiane Ehrt, Christian Lemmen, Matthias Rarey

Although small molecule superposition is a standard technique in drug discovery, a rigorous performance assessment of the corresponding methods is currently challenging. Datasets in this field are sparse, small, tailored to specific applications, unavailable, or outdated. The newly developed LOBSTER set described herein offers a publicly available and method-independent dataset for benchmarking and method optimization. LOBSTER stands for “Ligand Overlays from Binding SiTe Ensemble Representatives”. All ligands were derived from the PDB in a fully automated workflow, including a ligand efficiency filter. So-called ligand ensembles were assembled by aligning identical binding sites. Thus, the ligands within the ensembles are superimposed according to their experimentally determined binding orientation and conformation. Overall, 671 representative ligand ensembles comprise 3583 ligands from 3521 proteins. Altogether, 72,734 ligand pairs based on the ensembles were grouped into ten distinct subsets based on their volume overlap, for the benefit of introducing different degrees of difficulty for evaluating superposition methods. Statistics on the physicochemical properties of the compounds indicate that the dataset represents drug-like compounds. Consensus Diversity Plots show predominantly high Bemis–Murcko scaffold diversity and low median MACCS fingerprint similarity for each ensemble. An analysis of the underlying protein classes further demonstrates the heterogeneity within our dataset. The LOBSTER set offers a variety of applications like benchmarking multiple as well as pairwise alignments, generating training and test sets, for example based on time splits, or empirical software performance evaluation studies. The LOBSTER set is publicly available at https://doi.org/10.5281/zenodo.12658320, representing a stable and versioned data resource. The Python scripts are available at https://github.com/rareylab/LOBSTER, open-source, and allow for updating or recreating superposition sets with different data sources.

Simplified illustration of the LOBSTER dataset generation.

虽然小分子叠加是药物发现的标准技术,但对相应方法的严格性能评估目前具有挑战性。该领域的数据集稀疏、小、针对特定应用量身定制、不可用或过时。本文描述的新开发的LOBSTER集提供了一个公开可用的、与方法无关的数据集,用于基准测试和方法优化。龙虾代表“结合位点集合代表的配体叠加”。所有的配体都是在一个完全自动化的工作流程中从PDB中提取的,包括一个配体效率过滤器。所谓的配体组合是通过排列相同的结合位点来组装的。因此,根据实验确定的结合取向和构象,组合内的配体是叠加的。总的来说,671个有代表性的配体集合包含3583个配体,来自3521个蛋白质。总的来说,基于这些组合的72,734对配体基于它们的体积重叠被分为10个不同的子集,以便引入不同程度的难度来评估叠加方法。对化合物的物理化学性质的统计表明,该数据集代表药物样化合物。一致性多样性图显示,每个集合的Bemis-Murcko骨架多样性显著较高,而MACCS指纹相似度中值较低。对潜在蛋白质类别的分析进一步证明了我们数据集中的异质性。LOBSTER集提供了各种各样的应用程序,如基准测试多重和成对对齐,生成训练和测试集,例如基于时间分裂,或经验软件性能评估研究。LOBSTER集可以在https://doi.org/10.5281/zenodo.12658320上公开获得,它表示稳定且有版本的数据资源。Python脚本可从https://github.com/rareylab/LOBSTER(开源)获取,并允许使用不同的数据源更新或重新创建叠加集。
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引用次数: 0
Promoter recognition specificity of Corynebacterium glutamicum stress response sigma factors σD and σH deciphered using computer modeling and point mutagenesis 利用计算机建模和点突变破译谷氨酸棒杆菌应激反应sigma因子σD和σH的启动子识别特异性。
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-11-25 DOI: 10.1007/s10822-024-00577-x
J. Blumenstein, H. Dostálová, L. Rucká, V. Štěpánek, T. Busche, J. Kalinowski, M. Pátek, I. Barvík

This study aimed to reveal interactions of the stress response sigma subunits (factors) σD and σH of RNA polymerase and promoters in Gram-positive bacterium Corynebacterium glutamicum by combining wet-lab obtained data and in silico modeling. Computer modeling-guided point mutagenesis of C. glutamicum σH subunit led to the creation of a panel of σH variants. Their ability to initiate transcription from naturally occurring hybrid σDH-dependent promoter Pcg0441 and two control canonical promoters (σD-dependent PrsdA and σH-dependent PuvrD3) was measured and interpreted using molecular dynamics simulations of homology models of all complexes. The results led us to design the artificial hybrid promoter PD35H10 combining the −10 element of the PuvrD3 promoter and the −35 element of the PrsdA promoter. This artificial hybrid promoter PD35-rsdAH10-uvrD3 showed almost optimal properties needed for the bio-orthogonal transcription (not interfering with the native biological processes).

本研究旨在通过将湿实验室获得的数据与硅学建模相结合,揭示革兰氏阳性菌谷氨酸棒杆菌(Corynebacterium glutamicum)RNA聚合酶的应激反应sigma亚基(因子)σD和σH与启动子之间的相互作用。计算机建模指导下的谷氨酸棒杆菌σH亚基点突变产生了一系列σH变体。通过对所有复合体的同源模型进行分子动力学模拟,我们测量并解释了它们从天然存在的σD/σH依赖性混合启动子Pcg0441和两个对照规范启动子(σD依赖性PrsdA和σH依赖性PuvrD3)启动转录的能力。这些结果促使我们设计了人工混合启动子 PD35H10,它结合了 PuvrD3 启动子的 -10 元件和 PrsdA 启动子的 -35 元件。这种人工混合启动子 PD35-rsdAH10-uvrD3 几乎表现出了生物正交转录(不干扰原生生物过程)所需的最佳特性。
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引用次数: 0
Understanding the relationship between preferential interactions of peptides in water-acetonitrile mixtures with protein-solvent contact surface area 了解肽在水-乙腈混合物中的优先相互作用与蛋白质-溶剂接触表面积之间的关系。
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-11-13 DOI: 10.1007/s10822-024-00579-9
Monika Phougat, Narinder Singh Sahni, Devapriya Choudhury

The influence of polar, water-miscible organic solvents (POS) on protein structure, stability, and functional activity is a subject of significant interest and complexity. This study examines the effects of acetonitrile (ACN), a semipolar, aprotic solvent, on the solvation properties of blocked Ace-Gly-X-Gly-Nme tripeptides (where Ace and Nme stands for acetyl and N-methyl amide groups respectively and X is any amino acid) through extensive molecular dynamics simulations. Individual simulations were conducted for each peptide, encompassing five different ACN concentrations within the range of χACN = 0.1–0.9. The preferential solvation parameter (Γ) calculated using the Kirkwood-Buff integral method was used for the assessment of peptide interactions with water/ACN. Additionally, weighted Voronoi tessellation was applied to obtain a three-way data set containing four time-averaged contact surface area types between peptide atoms and water/ACN atoms. A mathematical technique known as N-way Partial Least Squares (NPLS) was utilized to anticipate the preferential interactions between peptides and water/ACN from the contact surface areas. Furthermore, the temperature dependency of peptide-solvent interactions was investigated using a subset of 10 amino acids representing a range of hydrophobicities. MD simulations were conducted at five temperatures, spanning from 283 to 343 K, with subsequent analysis of data focusing on both preferential solvation and peptide-solvent contact surface areas. The results demonstrate the efficacy of utilizing contact surface areas between the peptide and solvent constituents for successfully predicting preferential interactions in water/ACN mixtures across various ACN concentrations and temperatures.

极性水溶性有机溶剂(POS)对蛋白质结构、稳定性和功能活性的影响是一个非常有趣和复杂的课题。本研究通过大量分子动力学模拟,研究了半极性钝化溶剂乙腈(ACN)对阻断的 Ace-Gly-X-Gly-Nme 三肽(其中 Ace 和 Nme 分别代表乙酰基和 N-甲基酰胺基团,X 代表任何氨基酸)溶解特性的影响。在 χACN = 0.1-0.9 的范围内,对每种肽进行了五种不同浓度的 ACN 模拟。使用柯克伍德-巴夫积分法计算的优先溶解参数(Γ)用于评估多肽与水/ACN 的相互作用。此外,还采用加权沃罗诺网格划分法获得了三向数据集,其中包含肽原子与水/ACN 原子间的四种时间平均接触表面积类型。利用一种称为 N 向偏最小二乘法(NPLS)的数学技术,从接触表面积中预测肽与水/ACN 之间的优先相互作用。此外,还使用代表一系列疏水性的 10 个氨基酸子集研究了肽与溶剂相互作用的温度依赖性。在 283 至 343 K 的五个温度范围内进行了 MD 模拟,随后对数据进行了分析,重点是优先溶解和肽-溶剂接触表面积。结果表明,利用肽和溶剂成分之间的接触表面积可以成功预测水/ACN 混合物在不同 ACN 浓度和温度下的优先相互作用。
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引用次数: 0
Identification of novel inhibitors targeting PI3Kα via ensemble-based virtual screening method, biological evaluation and molecular dynamics simulation 通过基于集合的虚拟筛选方法、生物学评价和分子动力学模拟,鉴定靶向 PI3Kα 的新型抑制剂
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-11-11 DOI: 10.1007/s10822-024-00580-2
Hui Zhang, Hua-Zhao Qi, Ya-Juan Li, Xiu-Yun Shi, Mei-Ling Hu, Xiang-Long Chen, Yuan Li

PIK3CA gene encoding PI3K p110α is one of the most frequently mutated and overexpressed in majority of human cancers. Development of potent and selective novel inhibitors targeting PI3Kα was considered as the most promising approaches for cancer treatment. In this investigation, a virtual screening platform for PI3Kα inhibitors was established by employing machine learning methods, pharmacophore modeling, and molecular docking approaches. 28 potential PI3Kα inhibitors with different scaffolds were selected from the databases with 295,024 compounds. Among the 28 hits, hit15 exhibited the best inhibitory effect against PI3Kα with IC50 value less than 1.0 µM. The molecular dynamics simulation indicated that hit15 could stably bind to the active site of PI3Kα, interact with some residues by hydrophobic, electrostatic and hydrogen bonding interactions, and finally induced PI3Kα active pocket substantial conformation changes. Stable H-bond interactions were formed between hit15 and residues of Lys776, Asp810 and Asp933. The binding free energy of PI3Kα-hit15 was − 65.3 kJ/mol. The free energy decomposition indicated that key residues of Asp805, Ile848 and Ile932 contributed stronger energies to the binding free energy. The above results indicated that hit15 with novel scaffold was a potent PI3Kα inhibitor and considered as a promising candidate for further drug development to treat various cancers with PI3Kα over activated.

Graphical Abstract

编码 PI3K p110α 的 PIK3CA 基因是大多数人类癌症中最常发生突变和过度表达的基因之一。开发针对 PI3Kα 的强效、选择性新型抑制剂被认为是最有希望的癌症治疗方法。在这项研究中,通过采用机器学习方法、药理模型和分子对接方法,建立了一个 PI3Kα 抑制剂的虚拟筛选平台。从295,024个化合物的数据库中筛选出28个具有不同支架的潜在PI3Kα抑制剂。在这28个化合物中,第15个化合物对PI3Kα的抑制效果最好,IC50值小于1.0 µM。分子动力学模拟结果表明,hit15能稳定地结合到PI3Kα的活性位点,通过疏水、静电和氢键作用与一些残基相互作用,最终诱导PI3Kα活性口袋发生实质性的构象变化。hit15与Lys776、Asp810和Asp933残基之间形成了稳定的氢键相互作用。PI3Kα-hit15 的结合自由能为 - 65.3 kJ/mol。自由能分解结果表明,Asp805、Ile848 和 Ile932 等关键残基对结合自由能的贡献较大。上述结果表明,具有新型支架的hit15是一种强效的PI3Kα抑制剂,有望作为候选药物进一步开发,用于治疗PI3Kα过度激活的各种癌症。
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引用次数: 0
Comparative assessment of physics-based in silico methods to calculate relative solubilities 对基于物理的计算相对溶解度的硅学方法进行比较评估
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-10-29 DOI: 10.1007/s10822-024-00576-y
Adiran Garaizar Suarez, Andreas H. Göller, Michael E. Beck, Sadra Kashef Ol Gheta, Katharina Meier

Relative solubilities, i.e. whether a given molecule is more soluble in one solvent compared to others, is a critical parameter for pharmaceutical and agricultural formulation development and chemical synthesis, material science, and environmental chemistry. In silico predictions of this crucial variable can help reducing experiments, waste of solvents and synthesis optimization. In this study, we evaluate the performance of different physics-based methods for predicting relative solubilities. Our assessment involves quantum mechanics-based COSMO-RS and molecular dynamics-based free energy methods using OPLS4, the open-source OpenFF Sage, and GAFF force fields, spanning over 200 solvent–solute combinations. Our investigation highlights the important role of compound multimerization, an effect which must be accounted for to obtain accurate relative solubility predictions. The performance landscape of these methods is varied, with significant differences in precision depending on both the method used and the solute considered, thereby offering an improved understanding of the predictive power of physics-based methods in chemical research.

相对溶解度,即特定分子在一种溶剂中是否比在其他溶剂中更易溶解,是医药和农业配方开发、化学合成、材料科学和环境化学的一个关键参数。对这一关键变量进行硅学预测有助于减少实验、溶剂浪费和合成优化。在本研究中,我们评估了不同物理方法在预测相对溶解度方面的性能。我们的评估涉及基于量子力学的 COSMO-RS 和基于分子动力学的自由能方法,使用 OPLS4、开源 OpenFF Sage 和 GAFF 力场,涵盖 200 多种溶剂-溶质组合。我们的研究强调了化合物多聚化的重要作用,要获得准确的相对溶解度预测,必须考虑到这种效应。这些方法的性能各不相同,其精度因所使用的方法和所考虑的溶质而存在显著差异,从而使人们更好地了解了基于物理的方法在化学研究中的预测能力。
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引用次数: 0
Computational Identification and Illustrative Standard for Representation of Unimolecular G-Quadruplex Secondary Structures (CIIS-GQ) 单分子 G-四重二级结构的计算识别和图示标准 (CIIS-GQ)
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-10-29 DOI: 10.1007/s10822-024-00573-1
Tugay Direk, Osman Doluca

G-quadruplexes refer to a large group of nucleic acid–based structures. In recent years, they have been attracting attention due to their biological roles in the telomeres and promoter regions. These structures show wide diversity in topology, however, development of methods for structural classification of G-quadruplexes has been evaded for a long time. There has been a limited number of studies aiming to bring forth a secondary structure classification method. The situation was even more complex than imagined, since the discovery of bulged and mismatched G-quadruplexes while most of the available tools fail to distinguish these non-canonical G-quadruplex motifs. Moreover, the interpretation of their analysis output still requires expert knowledge. In this study, we propose a new method for identification of unimolecular G-Quadruplexes and classification by secondary structures based on three-dimensional structural data. Briefly, coordinates of guanines are processed to identify tetrads, loops and bulges. Then, we present the secondary structure in the form of a depiction which shows the loop types, bulges, and guanines that participate in each tetrad. Moreover, CIIS-GQ identifies non-guanine nucleotides that joins the G-tetrads and forms multiplets. Finally, the results of our study are compared with DSSR and ElTetrado classification methods, and the advantages of the proposed depiction method for representing secondary structures were discussed. The source code of the method can be accessed via https://github.com/TugayDirek/CIIS-GQ.

G 型四聚体是指一大类基于核酸的结构。近年来,由于它们在端粒和启动子区域的生物学作用,它们一直备受关注。这些结构在拓扑结构上表现出广泛的多样性,然而,G-四重链结构分类方法的开发却迟迟没有进展。旨在提出二级结构分类方法的研究数量有限。情况比想象的还要复杂,因为人们发现了隆起和不匹配的 G 型四重结构,而大多数现有工具都无法区分这些非经典的 G 型四重结构图案。此外,对其分析结果的解释仍然需要专业知识。在这项研究中,我们提出了一种基于三维结构数据的新方法,用于识别单分子 G 型四核苷酸并根据二级结构进行分类。简而言之,通过处理鸟嘌呤的坐标来识别四聚体、环和凸起。然后,我们以描述的形式呈现二级结构,显示环路类型、隆起和参与每个四元组的鸟嘌呤。此外,CIIS-GQ 还能识别连接 G 四元组并形成多聚体的非鸟嘌呤核苷酸。最后,我们将研究结果与 DSSR 和 ElTetrado 分类方法进行了比较,并讨论了所提出的描述二级结构方法的优势。该方法的源代码可通过 https://github.com/TugayDirek/CIIS-GQ 访问。
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引用次数: 0
Steered molecular dynamics simulation as a post-process to optimize the iBRAB-designed Fab model 引导分子动力学模拟,作为优化 iBRAB 设计的 Fab 模型的后处理。
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-10-24 DOI: 10.1007/s10822-024-00575-z
Phuc-Chau Do, Vy T. T. Le

Therapeutic monoclonal antibodies are an effective method of treating acute infectious diseases. However, knowing which of the produced antibodies in the vast number of human antibodies can cure the disease requires a long time and advanced technology. The previously introduced iBRAB method relies on studied antibodies to design a broad-spectrum antibody capable of neutralizing antigens of many different Influenza A viral strains. To evaluate the antigen-binding fragment as an applicable drug, the therapeutic antibody profiles providing guidelines collected from clinically staged therapeutic antibodies were used to access different measurements. Although the evaluated values were within an accepted range, the modification in the amino acid sequence is required for better properties. Thus, using the steered molecular dynamics (SMD) simulation to determine the binding capacity of amino acids in the functional region, the profile of interacted amino acids of Fab with the antigen was established for modified reference. As a result, the model was modified with amino acids elimination at positions 96–97 in the heavy chain and 26–27, 91, 96–97, and 102–103 in the light chain, which has better Therapeutic Antibody Profiler evaluations than the original designation. Thus again, SMD simulation is a promising computational approach for post-modification in rational drug design.

治疗性单克隆抗体是治疗急性传染病的有效方法。然而,要知道在数量庞大的人类抗体中,哪一种抗体能够治疗疾病,需要很长的时间和先进的技术。之前推出的 iBRAB 方法就是依靠研究抗体来设计一种能中和多种不同甲型流感病毒株抗原的广谱抗体。为了将抗原结合片段作为适用药物进行评估,我们利用从临床阶段性治疗抗体中收集的治疗抗体图谱提供指南,以获得不同的测量值。虽然评估值在可接受的范围内,但仍需要对氨基酸序列进行修改,以获得更好的特性。因此,利用定向分子动力学(SMD)模拟来确定功能区氨基酸的结合能力,建立了 Fab 与抗原相互作用氨基酸的轮廓,作为修改后的参考。因此,对模型进行了修改,删除了重链中 96-97 位和轻链中 26-27、91、96-97 和 102-103 位的氨基酸,其治疗抗体分析仪评估结果优于最初的指定结果。因此,SMD 模拟再次成为合理药物设计中一种很有前途的后修饰计算方法。
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引用次数: 0
Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands 基于结构的姿势预测:非认知对接扩展到大环配体
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-10-16 DOI: 10.1007/s10822-024-00574-0
Ann E. Cleves, Himani Tandon, Ajay N. Jain

So-called “cross-docking” is the prediction of the bound configuration of small-molecule ligands that differ from the cognate ligand of a protein co-crystal structure. This is a much more challenging problem than re-docking the cognate ligand, particularly when the new ligand is structurally dissimilar from prior known ones. We have updated the previously introduced PINC (“PINC Is Not Cognate”) benchmark which introduced the idea of temporal segregation to measure cross-docking performance. The temporal set encompasses 846 future ligands for ten targets based on information from the earliest 25% of X-ray co-crystal structures known for each target. Here, we extend the benchmark to include thirteen targets where the bound poses of 128 macrocyclic ligands are to be predicted based on knowledge from structures of bound non-macrocyclic ligands. Performance was roughly equivalent for both the temporally-split non-macrocyclic ligand set and the macrocycle prediction set. Using standard and fully automatic protocols for the Surflex-Dock and ForceGen methods, across the combined 974 non-macrocyclic and macrocyclic ligands, the top-scoring pose family was correct 68% of the time, with the top-two pose families achieving a 79% success rate. Correct poses among all those predicted were identified 92% of the time. These success rates far exceeded those observed for the alternative methods AutoDock Vina and Gnina on both sets.

所谓 "交叉对接 "是指预测与蛋白质共晶体结构中的同源配体不同的小分子配体的结合构型。这是一个比重新对接同源配体更具挑战性的问题,尤其是当新配体在结构上与之前的已知配体不同时。我们更新了之前推出的 PINC("PINC Is Not Cognate")基准,该基准引入了时间隔离的概念来衡量交叉对接性能。基于每个靶标已知的最早 25% 的 X 射线共晶体结构信息,时间集包含了 10 个靶标的 846 种未来配体。在此,我们将基准扩展到 13 个目标,其中 128 种大环配体的结合位置将根据结合的非大环配体的结构知识进行预测。时间上分离的非大环配体集和大环预测集的性能大致相同。使用 Surflex-Dock 和 ForceGen 方法的标准和全自动协议,在总共 974 种非大环配体和大环配体中,得分最高的姿势族在 68% 的情况下是正确的,得分最高的两个姿势族的成功率达到 79%。在所有预测的配体中,正确配体的识别率为 92%。这些成功率远远超过了 AutoDock Vina 和 Gnina 这两种方法的成功率。
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引用次数: 0
De novo drug design through gradient-based regularized search in information-theoretically controlled latent space 在信息论控制的潜空间中,通过基于梯度的正则化搜索进行新药设计。
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-08-27 DOI: 10.1007/s10822-024-00571-3
Hyosoon Jang, Sangmin Seo, Sanghyun Park, Byung Ju Kim, Geon-Woo Choi, Jonghwan Choi, Chihyun Park

Over the last decade, automatic chemical design frameworks for discovering molecules with drug-like properties have significantly progressed. Among them, the variational autoencoder (VAE) is a cutting-edge approach that models the tractable latent space of the molecular space. In particular, the usage of a VAE along with a property estimator has attracted considerable interest because it enables gradient-based optimization of a given molecule. However, although successful results have been achieved experimentally, the theoretical background and prerequisites for the correct operation of this method have not yet been clarified. In view of the above, we theoretically analyze and rigorously reconstruct the entire framework. From the perspective of parameterized distribution and the information theory, we first describe how the previous model overcomes the limitations of the beta VAE in discovering molecules with the desired properties. Furthermore, we describe the prerequisites for training the above model. Next, from the log-likelihood perspective of each term, we reformulate the objectives for exploring latent space to generate drug-like molecules. The distributional constraints are defined in this study, which will break away from the invalid molecular search. We demonstrated that our model could discover a novel chemical compound for targeting BCL-2 family proteins in de novo approach. Through the theoretical analysis and practical implementation, the importance of the aforementioned prerequisites and constraints to operate the model was verified.

过去十年间,用于发现具有类似药物特性的分子的自动化学设计框架取得了长足进步。其中,变异自动编码器(VAE)是一种前沿方法,可对分子空间的可控潜空间进行建模。特别是,变异自编码器与性质估计器的结合使用引起了相当大的兴趣,因为它可以对给定的分子进行基于梯度的优化。然而,尽管实验取得了成功的结果,但这种方法正确运行的理论背景和先决条件尚未得到澄清。有鉴于此,我们对整个框架进行了理论分析和严格重构。从参数化分布和信息论的角度,我们首先描述了前一种模型如何克服贝塔 VAE 在发现具有所需性质的分子方面的局限性。此外,我们还介绍了训练上述模型的前提条件。接下来,我们从每个项的对数似然的角度,重新阐述了探索潜空间以生成类药物分子的目标。本研究定义了分布约束,这将摆脱无效的分子搜索。我们证明了我们的模型可以从头开始发现靶向 BCL-2 家族蛋白的新型化合物。通过理论分析和实际应用,验证了上述前提条件和约束条件对模型运行的重要性。
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引用次数: 0
Computational design and experimental confirmation of a disulfide-stapled YAP helixα1-trap derived from TEAD4 helical hairpin to selectively capture YAP α1-helix with potent antitumor activity 从 TEAD4 螺旋发夹衍生出的二硫键 YAP 螺旋α1-捕获器的计算设计和实验证实,该捕获器可选择性捕获 YAP α1-螺旋,并具有强大的抗肿瘤活性。
IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Pub Date : 2024-08-23 DOI: 10.1007/s10822-024-00572-2
Kaipeng Li, Lijun Liu

Human Hippo signaling pathway is an evolutionarily conserved regulator network that controls organ development and has been implicated in various cancers. Transcriptional enhanced associate domain-4 (TEAD4) is the final nuclear effector of Hippo pathway, which is activated by Yes-associated protein (YAP) through binding to two separated YAP regions of α1-helix and Ω-loop. Previous efforts have all been addressed on deriving peptide inhibitors from the YAP to target TEAD4. Instead, we herein attempted to rationally design a so-called ‘YAP helixα1-trap’ based on the TEAD4 to target YAP by using dynamics simulation and energetics analysis as well as experimental assays at molecular and cellular levels. The trap represents a native double-stranded helical hairpin covering a specific YAP-binding site on TEAD4 surface, which is expected to form a three-helix bundle with the α1-helical region of YAP, thus competitively disrupting TEAD4–YAP interaction. The hairpin was further stapled by a disulfide bridge across its two helical arms. Circular dichroism characterized that the stapling can effectively constrain the trap into a native-like structured conformation in free state, thus largely minimizing the entropy penalty upon its binding to YAP. Affinity assays revealed that the stapling can considerably improve the trap binding potency to YAP α1-helix by up to 8.5-fold at molecular level, which also exhibited a good tumor-suppressing effect at cellular level if fused with TAT cell permeation sequence. In this respect, it is considered that the YAP helixα1-trap-mediated blockade of Hippo pathway may be a new and promising therapeutic strategy against cancers.

人类Hippo信号通路是一个进化保守的调控网络,它控制着器官的发育,并与多种癌症有关。转录增强关联结构域-4(TEAD4)是Hippo通路的最终核效应物,它通过与YAP的两个分离区域α1-螺旋和Ω-环结合而被YAP激活。以前的研究都是针对 TEAD4 从 YAP 中提取多肽抑制剂。而在本文中,我们试图通过动力学模拟和能效分析,以及分子和细胞水平的实验检测,在 TEAD4 的基础上合理设计一种所谓的 "YAP 螺旋α1-陷阱 "来靶向 YAP。该捕获器代表了一种覆盖 TEAD4 表面特定 YAP 结合位点的原生双链螺旋发夹,预计它将与 YAP 的 α1-helical 区域形成三螺旋束,从而竞争性地破坏 TEAD4 与 YAP 的相互作用。发夹通过横跨其两个螺旋臂的二硫桥进一步钉合。圆二色性表征了订书钉在自由状态下可以有效地将捕获器约束成类似于本地结构的构象,从而在很大程度上减少了其与 YAP 结合时的熵罚。亲和力试验表明,订书钉能在分子水平上显著提高捕获物与 YAP α1-螺旋的结合力,最高可达 8.5 倍,如果与 TAT 细胞渗透序列融合,还能在细胞水平上表现出良好的肿瘤抑制作用。因此,YAP α1-螺旋捕获器介导的 Hippo 通路阻断可能是一种新的、有前景的癌症治疗策略。
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Journal of Computer-Aided Molecular Design
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