基于结构的药效团建模、虚拟筛选、分子对接和生物学评价鉴定PD1/PD-L1抑制剂。

IF 2.8 4区 医学 Q3 CHEMISTRY, MEDICINAL Molecular Informatics Pub Date : 2023-06-01 DOI:10.1002/minf.202200254
Gopi Mohan C, Anju Pushkaran, Kumaran K, Ann MariaT, Raja Biswas
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引用次数: 1

摘要

PD-1/PD-L1是免疫治疗败血症的关键药物靶点。化学信息学技术包括基于结构的3D药效团模型开发,然后对小分子数据库进行虚拟筛选,以确定抗PD-L1途径抑制的小分子。雷替曲塞和沙非胺作为有效的再用途药物,以及其他三种Specs数据库化合物使用计算机方法。这些化合物是根据药效团匹配评分和与PD-L1蛋白活性位点的结合亲和力筛选的。对这些筛选的化合物进行了计算机药代动力学分析,以测试其生物活性。接下来,实验验证了最佳的四个虚拟筛选命中进行了体外血液相容性和细胞毒性。其中,雷替曲塞、沙芬酰胺和Specs化合物(AK-968/40642641)有效地增加了免疫细胞的增殖和IFN-γ的产生。这些化合物可以作为有效的PDL-1抑制剂用于败血症的辅助治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Identification of a PD1/PD-L1 inhibitor by structure-based pharmacophore modelling, virtual screening, molecular docking and biological evaluation.

PD-1/PD-L1 is a critical druggable target for immunotherapy against sepsis. Chemoinformatics techniques involved the structure-based 3D pharmacophore model development followed by virtual screening of small molecule databases to identify the small molecules against PD-L1 pathway inhibition. Raltitrexed and Safinamide act as potent repurposed drugs, and three other Specs database compounds using in silico methods. These compounds were screened based on the pharmacophore fit score and binding affinity towards the active site of the PD-L1 protein. In silico pharmacokinetic profiling of these screened compounds was done to test their biological activity. Next, experimental validation of the best four virtually screened hits was done in vitro for its hemocompatibility and cytotoxicity. Among these, Raltitrexed, Safinamide and Specs compound (AK-968/40642641) effectively increased the proliferation of immune cells and IFN-γ production. These compounds can act as potent PDL-1 inhibitors for adjuvant therapy against sepsis.

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来源期刊
Molecular Informatics
Molecular Informatics CHEMISTRY, MEDICINAL-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.30
自引率
2.80%
发文量
70
审稿时长
3 months
期刊介绍: Molecular Informatics is a peer-reviewed, international forum for publication of high-quality, interdisciplinary research on all molecular aspects of bio/cheminformatics and computer-assisted molecular design. Molecular Informatics succeeded QSAR & Combinatorial Science in 2010. Molecular Informatics presents methodological innovations that will lead to a deeper understanding of ligand-receptor interactions, macromolecular complexes, molecular networks, design concepts and processes that demonstrate how ideas and design concepts lead to molecules with a desired structure or function, preferably including experimental validation. The journal''s scope includes but is not limited to the fields of drug discovery and chemical biology, protein and nucleic acid engineering and design, the design of nanomolecular structures, strategies for modeling of macromolecular assemblies, molecular networks and systems, pharmaco- and chemogenomics, computer-assisted screening strategies, as well as novel technologies for the de novo design of biologically active molecules. As a unique feature Molecular Informatics publishes so-called "Methods Corner" review-type articles which feature important technological concepts and advances within the scope of the journal.
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