Highlights • Biofilms may have evolved as an adaptive response to environmental stresses. • Biofilm formation is a complex process involving sophisticated regulatory networks. • Biofilms are highly ...resistant to diverse antibiotics. • Resistance is adaptive and mediated through a plethora of molecular mechanisms. • Potential new therapeutics that specifically target biofilms are under development.
Peptides have a plethora of activities in biological systems that can potentially be exploited biotechnologically. Several peptides are used clinically, as well as in industry and agriculture. The ...increase in available ’omics data has recently provided a large opportunity for mining novel enzymes, biosynthetic gene clusters, and molecules. While these data primarily consist of DNA sequences, other types of data provide important complementary information. Due to their size, the approaches proven successful at discovering novel proteins of canonical size cannot be naïvely applied to the discovery of peptides. Peptides can be encoded directly in the genome as short open reading frames (smORFs), or they can be derived from larger proteins by proteolysis. Both of these peptide classes pose challenges as simple methods for their prediction result in large numbers of false positives. Similarly, functional annotation of larger proteins, traditionally based on sequence similarity to infer orthology and then transferring functions between characterized proteins and uncharacterized ones, cannot be applied for short sequences. The use of these techniques is much more limited and alternative approaches based on machine learning are used instead. Here, we review the limitations of traditional methods as well as the alternative methods that have recently been developed for discovering novel bioactive peptides with a focus on prokaryotic genomes and metagenomes.
3D printing has been intensively explored to fabricate customized structures of responsive materials including hydrogels, liquid‐crystal elastomers, shape‐memory polymers, and aqueous droplets. ...Herein, a new method and material system capable of 3D‐printing hydrogel inks with programed bacterial cells as responsive components into large‐scale (3 cm), high‐resolution (30 μm) living materials, where the cells can communicate and process signals in a programmable manner, are reported. The design of 3D‐printed living materials is guided by quantitative models that account for the responses of programed cells in printed microstructures of hydrogels. Novel living devices are further demonstrated, enabled by 3D printing of programed cells, including logic gates, spatiotemporally responsive patterning, and wearable devices.
A new paradigm in 3D printing is reported by using genetically programed cells as active components to print living materials and devices. The design principle and general method are provided to fabricate large‐scale, high‐resolution living materials, which are capable of integrating engineered cells into hydrogel constructs that maintain high viability of cells and respond to signaling chemicals in programed manners.
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Engineered probiotic bacteria represent an innovative approach for treating and detecting a wide range of diseases including those caused by infectious agents. Antimicrobial peptides ...(AMPs) are promising alternatives to conventional antibiotics for combating antibiotic-resistant infections. These molecules can be delivered orally to the gut by using engineered probiotics, which confer protection against AMP degradation, thus enabling numerous applications including treating drug-resistant enteric pathogens and remodeling the microbiota in real time. Here, we provide an update on the current state of the art on AMP-producing probiotics, discuss methods to enhance gut colonization, and end by outlining future perspectives.
Molecular interactions are essential for regulation of cellular processes from the formation of multi-protein complexes to the allosteric activation of enzymes. Identifying the essential residues and ...molecular features that regulate such interactions is paramount for understanding the biochemical process in question, allowing for suppression of a reaction through drug interventions or optimization of a chemical process using bioengineered molecules. In order to identify important residues and information pathways within molecular complexes, the dynamical network analysis method was developed and has since been broadly applied in the literature. However, in the dawn of exascale computing, this method is frequently limited to relatively small biomolecular systems. In this work, we provide an evolution of the method, application, and interface. All data processing and analysis are conducted through Jupyter notebooks, providing automatic detection of important solvent and ion residues, an optimized and parallel generalized correlation implementation that is linear with respect to the number of nodes in the system, and subsequent community clustering, calculation of betweenness of contacts, and determination of optimal paths. Using the popular visualization program visual molecular dynamics (VMD), high-quality renderings of the networks over the biomolecular structures can be produced. Our new implementation was employed to investigate three different systems, with up to 2.5M atoms, namely, the OMP-decarboxylase, the leucyl-tRNA synthetase complexed with its cognate tRNA and adenylate, and respiratory complex I in a membrane environment. Our enhanced and updated protocol provides the community with an intuitive and interactive interface, which can be easily applied to large macromolecular complexes.
Genetically modified microorganisms (GMMs) can enable a wide range of important applications including environmental sensing and responsive engineered living materials. However, containment of GMMs ...to prevent environmental escape and satisfy regulatory requirements is a bottleneck for real-world use. While current biochemical strategies restrict unwanted growth of GMMs in the environment, there is a need for deployable physical containment technologies to achieve redundant, multi-layered and robust containment. We developed a hydrogel-based encapsulation system that incorporates a biocompatible multilayer tough shell and an alginate-based core. This deployable physical containment strategy (DEPCOS) allows no detectable GMM escape, bacteria to be protected against environmental insults including antibiotics and low pH, controllable lifespan and easy retrieval of genomically recoded bacteria. To highlight the versatility of DEPCOS, we demonstrated that robustly encapsulated cells can execute useful functions, including performing cell-cell communication with other encapsulated bacteria and sensing heavy metals in water samples from the Charles River.
Deep generative models for peptide design Wan, Fangping; Kontogiorgos-Heintz, Daphne; de la Fuente-Nunez, Cesar
Digital discovery,
06/2022, Letnik:
1, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Computers can already be programmed for superhuman pattern recognition of images and text. For machines to discover novel molecules, they must first be trained to sort through the many ...characteristics of molecules and determine which properties should be retained, suppressed, or enhanced to optimize functions of interest. Machines need to be able to understand, read, write, and eventually create new molecules. Today, this creative process relies on deep generative models, which have gained popularity since powerful deep neural networks were introduced to generative model frameworks. In recent years, they have demonstrated excellent ability to model complex distribution of real-word data (
, images, audio, text, molecules, and biological sequences). Deep generative models can generate data beyond those provided in training samples, thus yielding an efficient and rapid tool for exploring the massive search space of high-dimensional data such as DNA/protein sequences and facilitating the design of biomolecules with desired functions. Here, we review the emerging field of deep generative models applied to peptide science. In particular, we discuss several popular deep generative model frameworks as well as their applications to generate peptides with various kinds of properties (
, antimicrobial, anticancer, cell penetration,
). We conclude our review with a discussion of current limitations and future perspectives in this emerging field.
By targeting invasive organisms, antibiotics insert themselves into the ancient struggle of the host-pathogen evolutionary arms race. As pathogens evolve tactics for evading antibiotics, therapies ...decline in efficacy and must be replaced, distinguishing antibiotics from most other forms of drug development. Together with a slow and expensive antibiotic development pipeline, the proliferation of drug-resistant pathogens drives urgent interest in computational methods that promise to expedite candidate discovery. Strides in artificial intelligence (AI) have encouraged its application to multiple dimensions of computer-aided drug design, with increasing application to antibiotic discovery. This review describes AI-facilitated advances in the discovery of both small molecule antibiotics and antimicrobial peptides. Beyond the essential prediction of antimicrobial activity, emphasis is also given to antimicrobial compound representation, determination of drug-likeness traits, antimicrobial resistance, and de novo molecular design. Given the urgency of the antimicrobial resistance crisis, we analyze uptake of open science best practices in AI-driven antibiotic discovery and argue for openness and reproducibility as a means of accelerating preclinical research. Finally, trends in the literature and areas for future inquiry are discussed, as artificially intelligent enhancements to drug discovery at large offer many opportunities for future applications in antibiotic development.
Abstract In the antimicrobial resistance era, carbon‐based nanomaterials (CBNs) such as fullerenes, carbon dots, graphene, and their derivatives are promising therapeutic tools in combating viral ...diseases. This review shows that these materials have broad‐spectrum antiviral activity against 33 viruses belonging to different Baltimore groups. CBNs also exhibit antimicrobial activity against bacteria and fungi and possess a low risk of selecting for resistance, since their primary mode of antimicrobial action involves physically damaging the microbes. CBNs also offer additional promising properties, including enhanced antiviral effectiveness under diverse types of irradiation and facilitating antiviral immune responses. Their potential as antiviral agents is still in its infancy and future research should focus on their toxicity, antiviral mechanisms, pharmacokinetics, and bioavailability. They are also potential antiviral materials for preventing the transmission of viral diseases for use in face masks, shields, hospital and airport surfaces, and elevators, among others. It is anticipated that CBNs will play an increasingly significant role in the fight against viruses and infectious diseases.
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