Cloud-Based Real-Time Molecular Screening Platform with MolFormer

被引：0

作者：

Belgodere, Brian ^{[1
]}

Chenthamarakshan, Vijil ^{[1
]}

Das, Payel ^{[1
]}

Dognin, Pierre ^{[1
]}

Kurien, Toby ^{[1
]}

Melnyk, Igor ^{[1
]}

Mroueh, Youssef ^{[1
]}

Padhi, Inkit ^{[1
]}

Rigotti, Mattia ^{[1
]}

Ross, Jarret ^{[1
]}

Schiff, Yair ^{[1
]}

Young, Richard A. ^{[1
]}

机构：

[1] IBM Res, Cambridge, MA 02142 USA

来源：

MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2022, PT VI | 2023年 / 13718卷

关键词：

Molecular screening; Drug discovery; Cloud platform;

D O I：

10.1007/978-3-031-26422-1_47

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 www.ibm.biz/molecular demo.

引用

页码：641 / 644

页数：4

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