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Structure-based prediction of T cell receptor recognition of unseen epitopes using TCRen 利用 TCRen 基于结构预测 T 细胞受体对未知表位的识别能力
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-07-10 DOI: 10.1038/s43588-024-00653-0
Vadim K. Karnaukhov, Dmitrii S. Shcherbinin, Anton O. Chugunov, Dmitriy M. Chudakov, Roman G. Efremov, Ivan V. Zvyagin, Mikhail Shugay
T cell receptor (TCR) recognition of foreign peptides presented by major histocompatibility complex protein is a major event in triggering the adaptive immune response to pathogens or cancer. The prediction of TCR–peptide interactions has great importance for therapy of cancer as well as infectious and autoimmune diseases but remains a major challenge, particularly for novel (unseen) peptide epitopes. Here we present TCRen, a structure-based method for ranking candidate unseen epitopes for a given TCR. The first stage of the TCRen pipeline is modeling of the TCR–peptide–major histocompatibility complex structure. Then a TCR–peptide residue contact map is extracted from this structure and used to rank all candidate epitopes on the basis of an interaction score with the target TCR. Scoring is performed using an energy potential derived from the statistics of TCR–peptide contact preferences in existing crystal structures. We show that TCRen has high performance in discriminating cognate versus unrelated peptides and can facilitate the identification of cancer neoepitopes recognized by tumor-infiltrating lymphocytes. TCRen predicts TCR specificity by modeling the TCR–peptide–MHC structure and estimating the TCR–peptide interaction energy using a statistical potential. The use of structural information allows TCRen to generalize to unseen epitopes, such as cancer neoepitopes.
T 细胞受体(TCR)识别由主要组织相容性复合体蛋白呈现的外来肽是触发对病原体或癌症的适应性免疫反应的主要事件。预测 TCR 与多肽的相互作用对癌症、传染病和自身免疫性疾病的治疗具有重要意义,但这仍然是一个重大挑战,尤其是对于新的(未见过的)多肽表位。在此,我们介绍一种基于结构的方法--TCRen,用于对给定 TCR 的候选未见表位进行排序。TCRen 管道的第一阶段是对 TCR-肽-主要组织相容性复合体结构进行建模。然后从该结构中提取 TCR-肽残基接触图,并根据与目标 TCR 的相互作用得分对所有候选表位进行排序。根据现有晶体结构中 TCR-肽接触偏好的统计数据得出的能量势进行评分。我们的研究表明,TCRen 在区分同源肽和非同源肽方面具有很高的性能,有助于识别肿瘤浸润淋巴细胞识别的癌症新表位。
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引用次数: 0
Unlocking T-cell receptor–epitope insights with structural analysis 通过结构分析揭开 T 细胞受体表位的神秘面纱
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-07-10 DOI: 10.1038/s43588-024-00654-z
Miaozhe Huo, Yuepeng Jiang, Shuai Cheng Li
A method leverages protein structural data to predict T-cell receptor–peptide interactions for unseen peptide epitopes, which can be particularly useful for applications in cancer immunotherapy, autoimmunity studies, and vaccine design.
有一种方法利用蛋白质结构数据来预测未见肽表位的 T 细胞受体与肽的相互作用,这对癌症免疫疗法、自身免疫研究和疫苗设计中的应用特别有用。
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引用次数: 0
Free-form and multi-physical metamaterials with forward conformality-assisted tracing 采用前向保形辅助追踪技术的自由形态和多物理超材料。
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-07-09 DOI: 10.1038/s43588-024-00660-1
Liujun Xu, Gaole Dai, Fubao Yang, Jinrong Liu, Yuhong Zhou, Jun Wang, Guoqiang Xu, Jiping Huang, Cheng-Wei Qiu
Transformation theory, active control and inverse design have been mainstream in creating free-form metamaterials. However, existing frameworks cannot simultaneously satisfy the requirements of isotropic, passive and forward design. Here we propose a forward conformality-assisted tracing method to address the geometric and single-physical-field constraints of conformal transformation. Using a conformal mesh composed of orthogonal streamlines and isotherms (or isothermal surfaces), this method quasi-analytically produces free-form metamaterials using only isotropic media. The geometric nature of this approach allows for universal regulation of both dissipative thermal fields and non-dissipative electromagnetic fields. We experimentally demonstrate free-form thermal cloaking in both two and three dimensions. Additionally, the multi-physical functionalities of our method, including optical cloaking, bending and thermo-electric transparency, confirm its broad applicability. Our method features improvements in efficiency, accuracy and adaptability over previous approaches. This study provides an effective method for designing complex metamaterials with arbitrary shapes across various physical domains. Here a conformality-assisted tracing method is proposed to devise free-form and three-dimensional conformal metamaterials, featuring accuracy and efficiency in handling complex geometry and adaptability to various diffusion and wave fields.
变换理论、主动控制和反向设计已成为创建自由形态超材料的主流。然而,现有框架无法同时满足各向同性、被动和正向设计的要求。在此,我们提出了一种正向保形辅助跟踪方法,以解决保形变换的几何和单物理场约束。该方法使用由正交流线和等温线(或等温面)组成的共形网格,仅使用各向同性介质就能准分析地生成自由形态超材料。这种方法的几何性质允许对耗散热场和非耗散电磁场进行通用调节。我们在实验中演示了二维和三维自由形态热隐形。此外,我们的方法还具有多种物理功能,包括光学隐形、弯曲和热电透明,这证实了它的广泛适用性。与之前的方法相比,我们的方法在效率、准确性和适应性方面都有所提高。这项研究为在各种物理领域设计具有任意形状的复杂超材料提供了有效方法。
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引用次数: 0
Enhancing human mobility research with open and standardized datasets 利用开放的标准化数据集加强人类流动性研究。
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-07-02 DOI: 10.1038/s43588-024-00650-3
Takahiro Yabe, Massimiliano Luca, Kota Tsubouchi, Bruno Lepri, Marta C. Gonzalez, Esteban Moro
Human mobility research intersects with various disciplines, with profound implications for urban planning, transportation engineering, public health, disaster management, and economic analysis. Here, we discuss the urgent need for open and standardized datasets in the field, including current challenges and lessons from other computational science domains, and propose collaborative efforts to enhance the validity and reproducibility of human mobility research.
人类流动性研究与多个学科交叉,对城市规划、交通工程、公共卫生、灾害管理和经济分析具有深远影响。在此,我们将讨论该领域对开放和标准化数据集的迫切需求,包括当前面临的挑战和其他计算科学领域的经验教训,并提出合作建议,以提高人类流动性研究的有效性和可重复性。
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引用次数: 0
Software in science is ubiquitous yet overlooked 科学领域的软件无处不在,但却被忽视。
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-07-01 DOI: 10.1038/s43588-024-00651-2
Alexandre Hocquet, Frédéric Wieber, Gabriele Gramelsberger, Konrad Hinsen, Markus Diesmann, Fernando Pasquini Santos, Catharina Landström, Benjamin Peters, Dawid Kasprowicz, Arianna Borrelli, Phillip Roth, Clarissa Ai Ling Lee, Alin Olteanu, Stefan Böschen
Software is much more than just code. It is time to confront the complexity of licenses, uses, governance, infrastructure and other facets of software in science. Their influence is ubiquitous yet overlooked.
软件不仅仅是代码。现在是时候正视许可证、使用、管理、基础设施和科学软件其他方面的复杂性了。它们的影响无处不在,但却被忽视了。
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引用次数: 0
Promising directions of machine learning for partial differential equations 偏微分方程机器学习的发展方向。
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-06-28 DOI: 10.1038/s43588-024-00643-2
Steven L. Brunton, J. Nathan Kutz
Partial differential equations (PDEs) are among the most universal and parsimonious descriptions of natural physical laws, capturing a rich variety of phenomenology and multiscale physics in a compact and symbolic representation. Here, we examine several promising avenues of PDE research that are being advanced by machine learning, including (1) discovering new governing PDEs and coarse-grained approximations for complex natural and engineered systems, (2) learning effective coordinate systems and reduced-order models to make PDEs more amenable to analysis, and (3) representing solution operators and improving traditional numerical algorithms. In each of these fields, we summarize key advances, ongoing challenges, and opportunities for further development. Machine learning has enabled major advances in the field of partial differential equations. This Review discusses some of these efforts and other ongoing challenges and opportunities for development.
偏微分方程(PDEs)是对自然物理规律最通用、最简洁的描述之一,它以紧凑的符号表示捕捉了丰富多样的现象学和多尺度物理学。在此,我们将探讨机器学习正在推动的几种有前途的多导方程研究途径,包括:(1) 为复杂的自然和工程系统发现新的支配多导方程和粗粒度近似值;(2) 学习有效坐标系和降阶模型,使多导方程更易于分析;(3) 表示求解算子并改进传统的数值算法。在上述每个领域,我们都总结了主要进展、当前挑战和进一步发展的机遇。
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引用次数: 0
An invitation to social scientists 向社会科学家发出邀请。
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-06-26 DOI: 10.1038/s43588-024-00656-x
Nature Computational Science wants to publish your computational social science research.
自然-计算科学》希望发表您的计算社会科学研究成果。
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引用次数: 0
The exciting potential and daunting challenge of using GPS human-mobility data for epidemic modeling 利用 GPS 人员流动数据进行流行病建模的巨大潜力和艰巨挑战。
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-06-19 DOI: 10.1038/s43588-024-00637-0
Francisco Barreras, Duncan J. Watts
Large-scale GPS location datasets hold immense potential for measuring human mobility and interpersonal contact, both of which are essential for data-driven epidemiology. However, despite their potential and widespread adoption during the COVID-19 pandemic, there are several challenges with these data that raise concerns regarding the validity and robustness of its applications. Here we outline two types of challenges—some related to accessing and processing these data, and some related to data quality—and propose several research directions to address them moving forward. While large-scale GPS location datasets have been instrumental to applications in epidemiology, there are still several challenges with these data that should be considered and addressed to make data-driven epidemiology more reliable.
大规模 GPS 定位数据集在测量人类流动性和人际接触方面具有巨大的潜力,而这两方面对于数据驱动的流行病学都至关重要。然而,尽管这些数据具有潜力并在 COVID-19 大流行期间被广泛采用,但这些数据仍面临着一些挑战,使人们对其应用的有效性和稳健性产生了担忧。在此,我们概述了两类挑战--一些与访问和处理这些数据有关,一些与数据质量有关--并提出了解决这些挑战的几个研究方向。
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引用次数: 0
The whole picture in digital pathology 数字病理学的全貌
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-06-19 DOI: 10.1038/s43588-024-00655-y
Ananya Rastogi
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引用次数: 0
An algorithmic framework for synthetic cost-aware decision making in molecular design 分子设计中合成成本感知决策的算法框架。
IF 12 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-06-17 DOI: 10.1038/s43588-024-00639-y
Jenna C. Fromer, Connor W. Coley
Small molecules exhibiting desirable property profiles are often discovered through an iterative process of designing, synthesizing and testing sets of molecules. The selection of molecules to synthesize from all possible candidates is a complex decision-making process that typically relies on expert chemist intuition. Here we propose a quantitative decision-making framework, SPARROW, that prioritizes molecules for evaluation by balancing expected information gain and synthetic cost. SPARROW integrates molecular design, property prediction and retrosynthetic planning to balance the utility of testing a molecule with the cost of batch synthesis. We demonstrate, through three case studies, that the developed algorithm captures the non-additive costs inherent to batch synthesis, leverages common reaction steps and intermediates, and scales to hundreds of molecules. The downselection of compounds for synthesis is a key challenge in molecular design cycles that typically relies on expert chemist intuition. Fromer and Coley propose a cost-aware method to automatically select compounds and synthetic routes.
表现出理想特性的小分子通常是通过设计、合成和测试成套分子的反复过程发现的。从所有可能的候选分子中选择要合成的分子是一个复杂的决策过程,通常依赖于化学家的直觉。在此,我们提出了一个定量决策框架 SPARROW,该框架通过平衡预期信息增益和合成成本来确定评估分子的优先次序。SPARROW 整合了分子设计、性质预测和逆合成规划,以平衡测试分子的效用和批量合成的成本。我们通过三个案例研究证明,所开发的算法能够捕捉到批量合成固有的非加成成本,利用常见的反应步骤和中间体,并可扩展到数百个分子。
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Nature computational science
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