In the last few years, an array of novel technologies, especially the big family of scanning probe microscopy, now often integrated with other powerful imaging tools such as laser confocal microscopy and total internal reflection fluorescence microscopy, have been widely applied in the investigation of biomolecular interactions and dynamics. But it is still a great challenge to directly monitor the dynamics of biomolecular interactions with high spatial and temporal resolution in living cells. An innovative method termed "single-photon atomic force microscopy" (SP-AFM), superior to existing techniques in tracing biomolecular interactions and dynamics in vivo, was proposed on the basis of the combination of atomic force microscopy with the technologies of carbon nanotubes and single-photon detection. As a unique tool, SP-AFM, capable of simultaneous topography imaging and molecular identification at the subnanometer level by synchronous acquisitions and analyses of the surface topography and fluorescent optical signals while scanning the sample, could play a very important role in exploring biomolecular interactions and dynamics in living cells or in a complicated biomolecular background.
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http://dx.doi.org/10.1007/s00216-009-3426-0 | DOI Listing |
Sci Adv
January 2025
Department of Biomedical Engineering, Duke University, Durham, NC, USA.
Designing binders to target undruggable proteins presents a formidable challenge in drug discovery. In this work, we provide an algorithmic framework to design short, target-binding linear peptides, requiring only the amino acid sequence of the target protein. To do this, we propose a process to generate naturalistic peptide candidates through Gaussian perturbation of the peptidic latent space of the ESM-2 protein language model and subsequently screen these novel sequences for target-selective interaction activity via a contrastive language-image pretraining (CLIP)-based contrastive learning architecture.
View Article and Find Full Text PDFBiochemistry
January 2025
Biomolecular Research Institute, Boise State University, 1910 University Drive, Boise, Idaho 83725, United States.
The amino-terminal domain of collagen α1(XI) plays a key role in controlling fibrillogenesis. However, the specific mechanisms through which various isoforms of collagen α1(XI) regulate this process are not fully understood. We measured the kinetics of collagen type I self-assembly in the presence of specific collagen α1(XI) isoforms.
View Article and Find Full Text PDFJ Physiol
January 2025
Department of Physiology and Membrane Biology, University of California Davis School of Medicine, Sacramento, CA, USA.
The complex microbial community residing in the human gut has long been understood to regulate gastrointestinal physiology and to participate in digestive diseases, but its extraintestinal actions and influences are increasingly recognized. This article discusses bidirectional interactions between the gut microbiome and athletic performance, metabolism, longevity and the ability of the gut-brain axis to influence cognitive function and mental health.
View Article and Find Full Text PDFProtein Sci
February 2025
Department of Molecular Biology, University of Wyoming, Laramie, Wyoming, USA.
Organisms from all kingdoms of life depend on Late Embryogenesis Abundant (LEA) proteins to survive desiccation. LEA proteins are divided into broad families distinguished by the presence of family-specific motif sequences. The LEA_4 family, characterized by 11-residue motifs, plays a crucial role in the desiccation tolerance of numerous species.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Department of Chemistry, Chicago Center for Theoretical Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA.
Bottom-up coarse-grained (CG) modeling is an effective means of bypassing the limited spatiotemporal scales of conventional atomistic molecular dynamics while retaining essential information from the atomistic model. A central challenge in CG modeling is the trade-off between accuracy and efficiency, as the inclusion of often pivotal many-body interaction terms in the CG force-field renders simulation markedly slower than simple pairwise models. The Ultra Coarse-Graining (UCG) method incorporates many-body terms through discrete internal state variables that modulate the CG force-field according to, e.
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