Latent spaces for antimicrobial peptide design

Abstract

Current antibacterial treatments cannot overcome the rapidly growing resistance of bacteria to antibiotic drugs, and novel treatment methods are required. One option is the development of new antimicrobial peptides (AMPs),...

Progress and future of the computational design of antimicrobial peptides (AMPs): bio-inspired functional molecules

“…In molecule generation, VAEs have been used to generate SMILES strings and molecular graphs. 167–170…”

“…By appropriately tuning models and their associated latent spaces, targeted sampling of new antimicrobial peptides with ideal characteristics can be achieved. For the relevant test case of generating novel antimicrobial peptide sequences, Renaud and Mansbach 170 focus on the question of the quality of -latent spaces and their interpretability. To evaluate and compare the different behaviors of deep generative models with VAE-like latent spaces in terms of reconstruction accuracy, generative capability, and interpretability, we will use deep generative models with VAE-like latent spaces.…”

Digital biology approach for macroscale studies of biofilm growth and biocide effects with electron microscopy

“…14,15 In fact, the combination of models, that predict antimicrobial activity of molecules or generate novel compounds with the high-throughput mapping of experimental microscopic data may become a powerful strategy for the accelerated discovery of antibiofilm agents in the near future. 16–18…”

“…14,15 In fact, the combination of models, that predict antimicrobial activity of molecules or generate novel compounds with the high-throughput mapping of experimental microscopic data may become a powerful strategy for the accelerated discovery of antibiolm agents in the near future. [16][17][18] There are several denitions of biolms. [19][20][21] Generally, bio-lms are highly structured associations of microorganisms attached to the surface (which can be both biotic or abiotic) or forming oating mats on liquid surfaces.…”

Machine learning-enabled design features of antimicrobial peptides selectively targeting peri-implant disease progression

“…Within AMPs, antibacterial peptides account for the largest proportion of peptides with inhibitory activities ranging from broad-to specific-species (21). Complexity in structure-function relationships in AMPs is increasing with the increased number of peptide sequences that are isolated from a wide range of organisms, or designed using computational search methods, or developed as peptide-mimics as potential candidates (24)(25)(26)(27). Despite such progress, and the promise of AMPs as alternative treatments to antibiotics and antiseptics, still only a handful of AMPs have been applied to oral-craniofacial applications (28)(29)(30)(31)(32)(33).…”