MolOptimizer: A Molecular Optimization Toolkit for Fragment-Based Drug Design

被引：1

作者：

Soffer, Adam ^{[1
,2
]}

Viswas, Samuel Joshua ^{[1
,2
]}

Alon, Shahar ^{[3
]}

Rozenberg, Nofar ^{[3
]}

Peled, Amit ^{[3
]}

Piro, Daniel ^{[3
]}

Vilenchik, Dan ^{[4
]}

Akabayov, Barak ^{[1
,2
]}

机构：

[1] Ben Gurion Univ Negev, Chem Dept, IL-8410501 Beer Sheva, Israel

[2] Ben Gurion Univ Negev, Data Sci Res Ctr, IL-8410501 Beer Sheva, Israel

[3] Ben Gurion Univ Negev, Dept Software Engn, IL-8410501 Beer Sheva, Israel

[4] Ben Gurion Univ Negev, Sch Comp & Elect Engn, IL-8410501 Beer Sheva, Israel

来源：

MOLECULES | 2024年 / 29卷 / 01期

关键词：

cheminformatics; fragment screening; hit-to-lead optimization; DOCKING;

D O I：

10.3390/molecules29010276

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

MolOptimizer is a user-friendly computational toolkit designed to streamline the hit-to-lead optimization process in drug discovery. MolOptimizer extracts features and trains machine learning models using a user-provided, labeled, and small-molecule dataset to accurately predict the binding values of new small molecules that share similar scaffolds with the target in focus. Hosted on the Azure web-based server, MolOptimizer emerges as a vital resource, accelerating the discovery and development of novel drug candidates with improved binding properties.

引用

页数：8

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