论文标题

基于云的实时分子筛选平台与moleformer

Cloud-Based Real-Time Molecular Screening Platform with MolFormer

论文作者

Belgodere, Brian, Chenthamarakshan, Vijil, Das, Payel, Dognin, Pierre, Kurien, Toby, Melnyk, Igor, Mroueh, Youssef, Padhi, Inkit, Rigotti, Mattia, Ross, Jarret, Schiff, Yair, Young, Richard A.

论文摘要

随着自动化许多具有高保真性的化学任务的前景,化学语言处理模型正在快速迅速出现。在这里,我们提出了一个基于云的实时平台,该平台允许用户实际上筛选感兴趣的分子。为此,使用了从最近提出的大型化学语言模型(称为Moleformer)推断出的分子嵌入。该平台目前支持三个任务:最近的邻居检索,化学空间可视化和财产预测。根据该平台的功能并获得的结果,我们认为这样的平台可以在自动化化学和化学工程研究中起关键作用,并协助药物发现和材料设计任务。在\ url {www.ibm.biz/molecular_demo}提供我们平台的演示。

With the prospect of automating a number of chemical tasks with high fidelity, chemical language processing models are emerging at a rapid speed. Here, we present a cloud-based real-time platform that allows users to virtually screen molecules of interest. For this purpose, molecular embeddings inferred from a recently proposed large chemical language model, named MolFormer, are leveraged. The platform currently supports three tasks: nearest neighbor retrieval, chemical space visualization, and property prediction. Based on the functionalities of this platform and results obtained, we believe that such a platform can play a pivotal role in automating chemistry and chemical engineering research, as well as assist in drug discovery and material design tasks. A demo of our platform is provided at \url{www.ibm.biz/molecular_demo}.

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