Risk of bias assessment.

Background
In the search for better anticancer drugs, computer-aided drug design (CADD) techniques play an indispensable role in facilitating the lengthy and costly drug discovery process especially when natural products are involved. Anthraquinone is one of the most widely-recognized natural products with anticancer properties. This review aimed to systematically assess and synthesize evidence on the utilization of CADD techniques centered on the anthraquinone scaffold for cancer treatment.
Methods
The conduct and reporting of this review were done in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2020 guideline. The protocol was registered in the “International prospective register of systematic reviews” database (PROSPERO: CRD42023432904) and also published recently. The search strategy was designed based on the combination of concept 1 “CADD or virtual screening”, concept 2 “anthraquinone” and concept 3 “cancer”. The search was executed in PubMed, Scopus, Web of Science and MedRxiv on 30 June 2023.
Results
Databases searching retrieved a total of 317 records. After deduplication and applying the eligibility criteria, the final review ended up with 32 articles in which 3 articles were found by citation searching. The CADD methods used in the studies were either structure-based alone (69%) or combined with ligand-based methods via parallel (9%) or sequential (22%) approaches. Molecular docking was performed in all studies, with Glide and AutoDock being the most popular commercial and public software used respectively. Protein data bank was used in most studies to retrieve the crystal structure of the targets of interest while the main ligand databases were PubChem and Zinc. The utilization of in-silico techniques has enabled a deeper dive into the structural, biological and pharmacological properties of anthraquinone derivatives, revealing their remarkable anticancer properties in an all-rounded fashion.
Conclusion
By harnessing the power of computational tools and leveraging the natural diversity of anthraquinone compounds, researchers can expedite the development of better drugs to address the unmet medical needs in cancer treatment by improving the treatment outcome for cancer patients.

背景
在研发更优质抗肿瘤药物的进程中，计算机辅助药物设计（computer-aided drug design, CADD）技术在推动漫长且高投入的药物发现流程方面发挥着不可或缺的作用，在涉及天然产物的场景下尤为如此。蒽醌是目前公认的具有抗肿瘤活性的天然产物之一。本综述旨在系统评估并整合以蒽醌骨架为核心的CADD技术在肿瘤治疗领域应用的相关证据。
方法
本综述的实施与报告严格遵循《系统评价与Meta分析优先报告条目（PRISMA）》2020版指南。研究方案已在“国际系统评价前瞻性注册数据库”（PROSPERO: CRD42023432904）完成注册，并已于近期发表。检索策略基于三个概念组合构建：概念1“计算机辅助药物设计（CADD）或虚拟筛选”、概念2“蒽醌”、概念3“肿瘤”。本次检索于2023年6月30日在PubMed、Scopus、Web of Science及MedRxiv数据库中完成。
结果
数据库检索共获取317条记录。经去重及纳入排除标准筛选后，最终纳入32篇文献，其中3篇通过引文检索获得。本研究涉及的CADD方法可分为两类：仅基于结构的方法（占比69%），以及通过并行（9%）或序列（22%）方式与基于配体的方法结合的混合方法。所有研究均采用了分子对接技术，其中最常用的商用软件为格莱德（Glide），开源软件则为AutoDock。多数研究通过蛋白质数据银行获取目标靶点的晶体结构，主流配体数据库为PubChem与Zinc。计算机模拟（in silico）技术的应用使得研究者得以深入解析蒽醌衍生物的结构、生物学及药理学特性，全面揭示其优异的抗肿瘤活性。
结论
通过利用计算工具的优势并依托蒽醌类化合物的天然多样性，研究者能够加速开发更优质的抗肿瘤药物，通过改善癌症患者的治疗结局，满足肿瘤治疗领域尚未被满足的医疗需求。