TY  - JOUR
AB  - ConspectusThe escalating threat of antimicrobial resistance (AMR) poses a significant global health crisis, potentially surpassing cancer as a leading cause of death by 2050. Traditional antibiotic discovery methods have not kept pace with the rapidly evolving resistance mechanisms of pathogens, highlighting the urgent need for novel therapeutic strategies. In this context, antimicrobial peptides (AMPs) represent a promising class of therapeutics due to their selectivity toward bacteria and slower induction of resistance compared to classical, small molecule antibiotics. However, designing effective AMPs remains challenging because of the vast combinatorial sequence space and the need to balance efficacy with low toxicity. Addressing this issue is of paramount importance for chemists and researchers dedicated to developing next-generation antimicrobial agents.Artificial intelligence (AI) presents a powerful tool to revolutionize AMP discovery. By leveraging AI, we can navigate the immense sequence space more efficiently, identifying peptides with optimal therapeutic properties. This Account explores the emerging application of AI in AMP discovery, focusing on two primary strategies: AMP mining, and AMP generation, as well as the use of discriminative methods as a valuable toolbox.AMP mining involves scanning biological sequences to identify potential AMPs. Discriminative models are then used to predict the activity and toxicity of these peptides. This approach has successfully identified numerous promising candidates, which were subsequently validated experimentally, demonstrating the potential of AI in AMP design and discovery.AMP generation, on the other hand, creates novel peptide sequences by learning from existing data through generative modeling. This class of models optimizes for desired properties, such as increased activity and reduced toxicity, potentially producing synthetic peptides that surpass naturally occurring ones. Despite the risk of generating unrealistic sequences, generative models hold the promise of accelerating the discovery of highly effective and highly novel and diverse AMPs.In this Account, we describe the technical challenges and advancements in these AI-based approaches. We discuss the importance of integrating various data sources and the role of advanced algorithms in refining peptide predictions. Additionally, we highlight the future potential of AI to not only expedite the discovery process but also to uncover peptides with unprecedented properties, paving the way for next-generation antimicrobial therapies.In conclusion, the synergy between AI and AMP discovery opens new frontiers in the fight against AMR. By harnessing the power of AI, we can design novel peptides that are both highly effective and safe, offering hope for a future where AMR is no longer a looming threat. Our paper underscores the transformative potential of AI in drug discovery, advocating for its continued integration into biomedical research.
AU  - Szymczak, P.
AU  - Zarzecki, W.*
AU  - Wang, J.*
AU  - Duan, Y.*
AU  - Coelho, L.P.*
AU  - de la Fuente-Nunez, C.*
AU  - Szczurek, E.
C1  - 74855
C2  - 57620
CY  - 1155 16th St, Nw, Washington, Dc 20036 Usa
SP  - 1831−1846
TI  - AI-driven antimicrobial peptide discovery: Mining and generation.
JO  - Acc. Chem. Res.
VL  - 58
IS  - 12
PB  - Amer Chemical Soc
PY  - 2025
SN  - 0001-4842
ER  - 

TY  - JOUR
AB  - When applied to biomolecules, solid-state NMR suffers from low sensitivity and resolution. The major obstacle to applying proton detection in the solid state is the proton dipolar network, and deuteration can help avoid this problem. In the past, researchers had primarily focused on the investigation of exchangeable protons in these systems. In this Account, we review NMR spectroscopic strategies that allow researchers to observe aliphatic non-exchangeable proton resonances in proteins with high sensitivity and resolution. Our labeling scheme is based on u-[(2)H,(13)C]-glucose and 5-25% H2O (95-75% D2O) in the M9 bacterial growth medium, known as RAP (reduced adjoining protonation). We highlight spectroscopic approaches for obtaining resonance assignments, a prerequisite for any study of structure and dynamics of a protein by NMR spectroscopy. Because of the dilution of the proton spin system in the solid state, solution-state NMR (1)HCC(1)H type strategies cannot easily be transferred to these experiments. Instead, we needed to pursue ((1)H)CC(1)H, CC(1)H, (1)HCC or ((2)H)CC(1)H type experiments. In protonated samples, we obtained distance restraints for structure calculations from samples grown in bacteria in media containing [1,3]-(13)C-glycerol, [2]-(13)C-glycerol, or selectively enriched glucose to dilute the (13)C spin system. In RAP-labeled samples, we obtained a similar dilution effect by randomly introducing protons into an otherwise deuterated matrix. This isotopic labeling scheme allows us to measure the long-range contacts among aliphatic protons, which can then serve as restraints for the three-dimensional structure calculation of a protein. Due to the high gyromagnetic ratio of protons, longer range contacts are more easily accessible for these nuclei than for carbon nuclei in homologous experiments. Finally, the RAP labeling scheme allows access to dynamic parameters, such as longitudinal relaxation times T1, and order parameters S(2) for backbone and side chain carbon resonances. We expect that these measurements will open up new opportunities to obtain a more detailed description of protein backbone and side chain dynamics.
AU  - Asami, S.
AU  - Reif, B.
C1  - 27582
C2  - 32732
CY  - Washington
SP  - 2089-2097
TI  - Proton-detected solid-state NMR spectroscopy at aliphatic sites: Application to crystalline systems.
JO  - Acc. Chem. Res.
VL  - 46
IS  - 9
PB  - Amer. Chemical Soc.
PY  - 2013
SN  - 0001-4842
ER  - 

TY  - JOUR
AB  - Researchers need to study the biokinetics of inhaled biopersistent nano- and micrometer-sized particles (NPs and μPs) to assess their toxicity and to develop an understanding of their potential risks. When particles are inhaled, they do not necessarily remain at their sites of deposition in the respiratory tract. Instead they can undergo numerous transport processes within the various tissues of the lungs, including clearance from the lungs. In this context, we would like to understand how the biokinetic studies performed in animals can be extrapolated to humans. Interestingly, the particle retention is much shorter in rodent lungs and declines much faster than it does in human, simian, and canine lungs. The predominant long-term clearance pathway for both NPs and μPs in humans and other animal species is macrophage-mediated particle transport from the peripheral lungs toward ciliated airways and the larynx. However, the transport rate is 10 times higher in rodents than in other species. In addition to particle clearance out of the lung, we also observe particle redistribution from the epithelium toward and within the interstitium and lymph nodes of the lung and particle translocation to blood circulation leading to subsequent accumulation in secondary organs. While μPs have limited access to interstitial spaces in the rodent lungs, NPs rapidly relocate in the epithelium and the underlying interstitium. By contrast, indirect evidence shows that both NPs and μPs are relocated into the epithelium and interstitial spaces of the human, simian, and canine lungs. Only NPs translocate into the circulatory system and subsequently accumulate in the secondary organs and tissues of the body. Translocated NP fractions are rather low, but they depend strongly on the physicochemical properties of the NP and their surface properties. Growing evidence indicates that the binding and conjugation of proteins to NPs play an essential role in translocation across cellular membranes and organ barriers. In summary, particle biokinetics result from a multitude of highly dynamic processes, which depend not only on physicochemical properties of the particles but also on a multitude of cellular and molecular responses and interactions. Given the rather small accumulation in secondary organs after acute inhalation exposures, it appears likely that adverse effects caused by NPs accumulated in secondary organs may only occur after chronic exposure over extended time periods. Therefore adverse health effects in secondary organs such as the cardiovascular system that are associated with chronic exposure of ambient urban air pollution are less likely to result from particle translocation. Instead, chronic particle inhalation could trigger or modulate the autonomous nervous system or the release of soluble mediators into circulation leading to adverse health effects.
AU  - Kreyling, W.G.
AU  - Semmler-Behnke, M.
AU  - Takenaka, S.
AU  - Möller, W.
C1  - 10809
C2  - 30372
SP  - 714-722
TI  - Differences in the biokinetics of inhaled nano- versus micrometer-sized particles.
JO  - Acc. Chem. Res.
VL  - 46
IS  - 3
PB  - American Chemical Society
PY  - 2013
SN  - 0001-4842
ER  -