The rapid growth of resistant microorganisms has caused serious public health issues and poses great pressure on the current healthcare system. In this environment, the necessity of new antibiotic materials is even more prominent. Antimicrobial polymers are a class of polymers that have the ability to eradicate or impede the proliferation of microbes on their surfaces or within their surrounding environment. The mechanism of action of antibacterial polymers also makes them a perfect fit for medical devices. Despite great growing needs, the design of new antibacterial polymers with desired antimicrobial properties is still challenging. In this work, we present the first open-source database for antimicrobial polymers which consists of 489 entries, with 177 unique polymers exhibiting diverse structures and properties. Multiple predictive models were also designed and trained to classify the antimicrobial properties of these polymers. The best-performing random forest model showed an average accuracy of 86.7% in a 10-fold cross-validation test. We also developed multiple guiding pipelines for the design of novel antimicrobial polymers.

中文翻译：

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推进抗菌聚合物开发：新颖的数据库和通过机器学习加速设计


耐药微生物的快速增长造成了严重的公共卫生问题，给当前的医疗保健系统带来了巨大的压力。在这种环境下，新型抗生素材料的必要性就更加凸显。抗菌聚合物是一类能够根除或阻止其表面或周围环境内微生物增殖的聚合物。抗菌聚合物的作用机制也使其非常适合医疗设备。尽管需求不断增长，但设计具有所需抗菌性能的新型抗菌聚合物仍然具有挑战性。在这项工作中，我们提出了第一个抗菌聚合物开源数据库，其中包含 489 个条目，其中 177 种独特的聚合物表现出不同的结构和性能。还设计和训练了多个预测模型来对这些聚合物的抗菌特性进行分类。表现最好的随机森林模型在 10 倍交叉验证测试中显示平均准确率为 86.7%。我们还开发了多种用于新型抗菌聚合物设计的指导管道。