HelixMO: Sample-Efficient Molecular Optimization in Scene-Sensitive Latent Space

Chen, Zhiyuan; Fang, Xiaomin; Zixu, Hua,; Huang, Yueyang; Wang, Fan; Wu, Hua

doi:10.1109/bibm55620.2022.9995561

Cited by 1 publication

(2 citation statements)

References 21 publications

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“…Drug discovery (DD) is costly and time-consuming . On average, bringing a new drug to the market takes 10 years and approximately 2.7 billion dollars .…”

Section: Introductionmentioning

confidence: 99%

“…Drug discovery (DD) is costly and time-consuming. 1 On average, bringing a new drug to the market takes 10 years and approximately 2.7 billion dollars. 2 Given these constraints, the modern pharmaceutical industry prioritizes using computational tools to minimize the number of candidates that must undergo costly preclinical and clinical testing, thus saving money and speeding up the process.…”

Section: Introductionmentioning

confidence: 99%

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GENERA: A Combined Genetic/Deep-Learning Algorithm for Multiobjective Target-Oriented De Novo Design

Lamanna,

Delre,

Marcou

et al. 2023

J. Chem. Inf. Model.

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This study introduces a new de novo design algorithm called GENERA that combines the capabilities of a deep-learning algorithm for automated drug-like analogue design, called DeLA-Drug, with a genetic algorithm for generating molecules with desired target-oriented properties. Specifically, GENERA was applied to the angiotensin-converting enzyme 2 (ACE2) target, which is implicated in many pathological conditions, including COVID-19. The ability of GENERA to de novo design promising candidates for a specific target was assessed using two docking programs, PLANTS and GLIDE. A fitness function based on the Pareto dominance resulting from computed PLANTS and GLIDE scores was applied to demonstrate the algorithm's ability to perform multiobjective optimizations effectively. GENERA can quickly generate focused libraries that produce better scores compared to a starting set of known ACE-2 binders. This study is the first to utilize a DL-based algorithm designed for analogue generation as a mutational operator within a GA framework, representing an innovative approach to target-oriented de novo design.

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“…Drug discovery (DD) is costly and time-consuming . On average, bringing a new drug to the market takes 10 years and approximately 2.7 billion dollars .…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%