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The regulation of protein function through ligand-induced conformational changes is crucial for many signal transduction processes. The binding of a ligand alters the delicate energy balance within the protein structure, eventually leading to such conformational changes. In this study, we elucidate the energetic and mechanical changes within the subdomains of the nucleotide binding domain (NBD) of the heat shock protein of 70 kDa (Hsp70) chaperone DnaK upon nucleotide binding. In an integrated approach using single molecule optical tweezer experiments, loop insertions, and steered coarse-grained molecular simulations, we find that the C-terminal helix of the NBD is the major determinant of mechanical stability, acting as a glue between the two lobes. After helix unraveling, the relative stability of the two separated lobes is regulated by ATP/ADP binding. We find that the nucleotide stays strongly bound to lobe II, thus reversing the mechanical hierarchy between the two lobes. Our results offer general insights into the nucleotide-induced signal transduction within members of the actin/sugar kinase superfamily.

Nanomanipulation of biomolecules by using single-molecule methods and computer simulations has made it possible to visualize the energy landscape of biomolecules and the structures that are sampled during the folding process. We use simulations and single-molecule force spectroscopy to map the complex energy landscape of GFP that is used as a marker in cell biology and biotechnology. By engineering internal disulfide bonds at selected positions in the GFP structure, mechanical unfolding routes are precisely controlled, thus allowing us to infer features of the energy landscape of the wild-type GFP. To elucidate the structures of the unfolding pathways and reveal the multiple unfolding routes, the experimental results are complemented with simulations of a self-organized polymer (SOP) model of GFP. The SOP representation of proteins, which is a coarse-grained description of biomolecules, allows us to perform forced-induced simulations at loading rates and time scales that closely match those used in atomic force microscopy experiments. By using the combined approach, we show that forced unfolding of GFP involves a bifurcation in the pathways to the stretched state. After detachment of an N-terminal α-helix, unfolding proceeds along two distinct pathways. In the dominant pathway, unfolding starts from the detachment of the primary N-terminal β-strand, while in the minor pathway rupture of the last, C-terminal β-strand initiates the unfolding process. The combined approach has allowed us to map the features of the complex energy landscape of GFP including a characterization of the structures, albeit at a coarse-grained level, of the three metastable intermediates.

The first step in the formation of the protease resistant form (PrP Sc ) of prion proteins involves a conformational transition of the monomeric cellular form of PrP C to a more stable aggregation prone state PrP C* . A search of PDBselect and Escherichia coli and yeast genomes shows that the exact pattern of charges in helix 1 (H1) is rare. Among the 23 fragments in PDBselect with the pattern of charges that match H1, 83% are helical. Mapping of the rarely found (in E. coli and yeast genomes) hydrophobicity patterns in helix 2 (H2) to known secondary structures suggests that the PrP C → PrP C* transition must be accompanied by alterations in conformations in second half of H2. We probe the dynamical instability in H1 and in the combined fragments of H2 and helix 3 (H3) from mPrP C (H2+H3), with intact disulfide bond, using all atom molecular dynamics (MD) simulations totaling 680 ns. In accord with recent experiments, we found that H1 is helical, whereas the double mutant H1[D147A–R151A] is less stable, implying that H1 is stabilized by the ( i , i + 4) charged residues. The stability of H1 suggests that it is unlikely to be involved in the PrP C → PrP C* transition. MD simulations of H2+H3 shows that the second half of H2 (residues 184–194) and parts of H3 (residues 200–204 and 215–223) undergo a transition from α-helical conformation to a β and/or random coil state. Simulations using two force fields (optimized potentials for liquid simulations and charmm ) give qualitatively similar results. We use the MD results to propose tentative structures for the PrP C* state.

In cells, microtubule location, length, and dynamics are regulated by a host of microtubule-associated proteins and enzymes that read where to bind and act based on the microtubule “tubulin code,” which is predominantly encoded in the tubulin carboxy-terminal tail (CTT). Katanin is a highly conserved AAA ATPase enzyme that binds to the tubulin CTTs to remove dimers and sever microtubules. We have previously demonstrated that short CTT peptides are able to inhibit katanin severing. Here, we examine the effects of CTT sequences on this inhibition activity. Specifically, we examine CTT sequences found in nature, alpha1A (TUBA1A), detyrosinated alpha1A, Δ2 alpha1A, beta5 (TUBB/TUBB5), beta2a (TUBB2A), beta3 (TUBB3), and beta4b (TUBB4b). We find that these natural CTTs have distinct abilities to inhibit, most noticeably beta3 CTT cannot inhibit katanin. Two non-native CTT tail constructs are also unable to inhibit, despite having 94% sequence identity with alpha1 or beta5 sequences. Surprisingly, we demonstrate that poly-E and poly-D peptides are capable of inhibiting katanin significantly. An analysis of the hydrophobicity of the CTT constructs indicates that more hydrophobic polypeptides are less inhibitory than more polar polypeptides. These experiments not only demonstrate inhibition, but also likely interaction and targeting of katanin to these various CTTs when they are part of a polymerized microtubule filament.

Tubulin heterodimers are the building blocks of microtubules, a major component of the cytoskeleton, whose mechanical properties are fundamental for the life of the cell. We uncover the microscopic origins of the mechanical response in microtubules by probing features of the energy landscape of the tubulin monomers and tubulin heterodimer. To elucidate the structures of the unfolding pathways and reveal the multiple unfolding routes, we performed simulations of a self-organized polymer (SOP) model of tubulin. The SOP representation, which is a coarse-grained description of chains, allows us to perform force-induced simulations at loading rates and time scales that closely match those used in single-molecule experiments. We show that the forced unfolding of each monomer involves a bifurcation in the pathways to the stretched state. After the unfolding of the C-term domain, the unraveling continues either from the N-term domain or from the middle domain, depending on the monomer and the pathway. In contrast to the unfolding complexity of the monomers, the dimer unfolds according to only one route corresponding to the unraveling of the C-term domain and part of the middle domain of β-tubulin. We find that this surprising behavior is due to the viscoelastic properties of the interface between the monomers. We map precise features of the complex energy landscape of tubulin by surveying the structures of the various metastable intermediates, which, in the dimer case, are characterized only by changes in the β-tubulin monomer.

Essential cellular processes of microtubule disassembly and protein degradation, which span lengths from tens of μm to nm, are mediated by specialized molecular machines with similar hexameric structure and function. Our molecular simulations at atomistic and coarse-grained scales show that both the microtubule-severing protein spastin and the caseinolytic protease ClpY, accomplish spectacular unfolding of their diverse substrates, a microtubule lattice and dihydrofolate reductase (DHFR), by taking advantage of mechanical anisotropy in these proteins. Unfolding of wild-type DHFR requires disruption of mechanically strong β-sheet interfaces near each terminal, which yields branched pathways associated with unzipping along soft directions and shearing along strong directions. By contrast, unfolding of circular permutant DHFR variants involves single pathways due to softer mechanical interfaces near terminals, but translocation hindrance can arise from mechanical resistance of partially unfolded intermediates stabilized by β-sheets. For spastin, optimal severing action initiated by pulling on a tubulin subunit is achieved through specific orientation of the machine versus the substrate (microtubule lattice). Moreover, changes in the strength of the interactions between spastin and a microtubule filament, which can be driven by the tubulin code, lead to drastically different outcomes for the integrity of the hexameric structure of the machine.

Owing to the cooperativity of protein structures, it is often almost impossible to identify independent subunits, flexible regions, or hinges simply by visual inspection of static snapshots. Here, we use single-molecule force experiments and simulations to apply tension across the substrate binding domain (SBD) of heat shock protein 70 (Hsp70) to pinpoint mechanical units and flexible hinges. The SBD consists of two nanomechanical units matching 3D structural parts, called the α- and β-subdomain. We identified a flexible region within the rigid β-subdomain that gives way under load, thus opening up the α/β interface. In exactly this region, structural changes occur in the ATP-induced opening of Hsp70 to allow substrate exchange. Our results show that the SBD’s ability to undergo large conformational changes is already encoded by passive mechanics of the individual elements.

This perspective discusses the present and future role of artificial intelligence (AI) and machine learning (ML) in surface-enhanced Raman scattering (SERS) sensing. Our goal is to guide the reader through current applications, mainly focused on discriminative approaches aimed at developing new and improved SERS diagnostic capabilities, towards the future role of AI in SERS sensing, with the use of generative approaches to design new materials and biomaterials.

By using techniques borrowed from statistical physics and neural networks, we determine the parameters, associated with a scoring function, that are chosen optimally to ensure complete success in threading tests in a training set of proteins. These parameters provide a quantitative measure of the propensities of amino acids to be buried or exposed and to be in a given secondary structure and are a good starting point for solving both the threading and design problems.

A strategy is outlined for obtaining the free energy of a typical designed heteropolymer. The design procedure considers the probability that the target conformation is occupied in comparison with all the other conformations that could house the given sequence. Numerical calculations on lattice heteropolymer models are presented to illustrate the key physical principles.