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将蛋白质相互作用表面预测与基于片段的药物设计相结合:基于能量表面的片段自动设计新先导物。

Integrating Protein Interaction Surface Prediction with a Fragment-Based Drug Design: Automatic Design of New Leads with Fragments on Energy Surfaces.

机构信息

Department of Chemistry, University of Pavia, Via Taramelli 12, Pavia27100, Italy.

Department of Woman's and Child's Health, Pediatric Hematology, Oncology and Stem Cell Transplant Center, University of Padua, Via Giustiniani, 3, Padua35128, Italy.

出版信息

J Chem Inf Model. 2023 Jan 9;63(1):343-353. doi: 10.1021/acs.jcim.2c01408. Epub 2022 Dec 27.

DOI:10.1021/acs.jcim.2c01408
PMID:36574607
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9832486/
Abstract

Protein-protein interactions (PPIs) have emerged in the past years as significant pharmacological targets in the development of new therapeutics due to their key roles in determining pathological pathways. Herein, we present fragments on energy surfaces, a simple and general design strategy that integrates the analysis of the dynamic and energetic signatures of proteins to unveil the substructures involved in PPIs, with docking, selection, and combination of drug-like fragments to generate new PPI inhibitor candidates. Specifically, structural representatives of the target protein are used as inputs for the blind physics-based prediction of potential protein interaction surfaces using the matrix of low coupling energy decomposition method. The predicted interaction surfaces are subdivided into overlapping windows that are used as templates to direct the docking and combination of fragments representative of moieties typically found in active drugs. This protocol is then applied and validated using structurally diverse, important PPI targets as test systems. We demonstrate that our approach facilitates the exploration of the molecular diversity space of potential ligands, with no requirement of prior information on the location and properties of interaction surfaces or on the structures of potential lead compounds. Importantly, the hit molecules that emerge from our ab initio design share high chemical similarity with experimentally tested active PPI inhibitors. We propose that the protocol we describe here represents a valuable means of generating initial leads against difficult targets for further development and refinement.

摘要

蛋白质-蛋白质相互作用(PPIs)在过去几年中已成为开发新疗法的重要药理学靶点,因为它们在确定病理途径方面起着关键作用。在此,我们提出了关于能量表面的片段,这是一种简单而通用的设计策略,它将蛋白质动态和能量特征的分析与对接、选择和组合药物样片段相结合,以生成新的 PPI 抑制剂候选物。具体来说,使用目标蛋白质的结构代表作为输入,使用低耦合能量分解矩阵方法进行潜在蛋白质相互作用表面的盲目物理预测。预测的相互作用表面被细分为重叠窗口,这些窗口用作模板来指导片段的对接和组合,这些片段代表通常存在于活性药物中的部分。然后,使用结构多样的重要 PPI 靶标作为测试系统来应用和验证该方案。我们证明,我们的方法促进了潜在配体的分子多样性空间的探索,而无需事先了解相互作用表面的位置和性质或潜在先导化合物的结构的信息。重要的是,从我们的从头设计中出现的命中分子与经过实验测试的活性 PPI 抑制剂具有很高的化学相似性。我们提出,我们在这里描述的方案代表了针对难以开发的靶标生成初始先导化合物的有价值的手段,以进一步开发和改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/3de9368765bf/ci2c01408_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/335d463d2cdb/ci2c01408_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/27681ff59c92/ci2c01408_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/c3aba23c20a9/ci2c01408_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/947ec72514f7/ci2c01408_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/afa2556da7d0/ci2c01408_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/3de9368765bf/ci2c01408_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/335d463d2cdb/ci2c01408_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/27681ff59c92/ci2c01408_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/c3aba23c20a9/ci2c01408_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/947ec72514f7/ci2c01408_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/afa2556da7d0/ci2c01408_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d17/9832486/3de9368765bf/ci2c01408_0007.jpg

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