Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics

TL;DR

This paper introduces CLaSS, a deep learning-based method for generating and screening antimicrobial molecules with desired attributes, leading to the discovery of novel potent AMPs with low toxicity and resistance mitigation.

Contribution

We develop CLaSS, a controllable molecule generation framework combining deep generative models and classifiers, enabling efficient design of antimicrobial peptides with specific properties.

Findings

Generated 20 peptides, 2 of which showed high antimicrobial potency

Discovered novel AMPs effective against resistant bacteria

Demonstrated low toxicity and resistance mitigation in tested peptides

Abstract

De novo therapeutic design is challenged by a vast chemical repertoire and multiple constraints, e.g., high broad-spectrum potency and low toxicity. We propose CLaSS (Controlled Latent attribute Space Sampling) - an efficient computational method for attribute-controlled generation of molecules, which leverages guidance from classifiers trained on an informative latent space of molecules modeled using a deep generative autoencoder. We screen the generated molecules for additional key attributes by using deep learning classifiers in conjunction with novel features derived from atomistic simulations. The proposed approach is demonstrated for designing non-toxic antimicrobial peptides (AMPs) with strong broad-spectrum potency, which are emerging drug candidates for tackling antibiotic resistance. Synthesis and testing of only twenty designed sequences identified two novel and minimalist AMPs with high potency against diverse Gram-positive and Gram-negative pathogens, including one multidrug-resistant and one antibiotic-resistant K. pneumoniae, via membrane pore formation. Both antimicrobials exhibit low in vitro and in vivo toxicity and mitigate the onset of drug resistance. The proposed approach thus presents a viable path for faster and efficient discovery of potent and selective broad-spectrum antimicrobials.