Protein circular dichroism (CD) and infrared absorbance (IR) spectra are widely used to estimate the secondary structure content of proteins in solution. A range of algorithms have been used for CD analysis (SELCON, CONTIN, CDsstr, SOMSpec) and some of these have been applied to IR data, though IR is more commonly analysed by bandfitting or statistical approaches. In this work we provide a Python version of SELCON3 and explore how to combine CD and IR data to best effect. We used CD data in Δε/amino acid residue and scaled the IR spectra to similar magnitudes. Normalising the IR amide I spectra scaled to a maximum absorbance of 15 gives best general performance. Combining CD and IR improves predictions for both helix and sheet by ~2% and helps identify anomalously large errors for high helix proteins such as haemoglobin when using IR data alone and high sheet proteins when using CD data alone.

Metabolism is at the core of all functions of living cells as it provides Gibbs free energy and building blocks for synthesis of macromolecules, which are necessary for structures, growth, and proliferation. Metabolism is a complex network composed of thousands of reactions catalyzed by enzymes involving many co-factors and metabolites. Traditionally it has been difficult to study metabolism as a whole network and most traditional efforts were therefore focused on specific metabolic pathways, enzymes, and metabolites. By using engineering principles of mathematical modeling to analyze and study metabolism, as well as engineer it, that is, design and build, new metabolic features, it is possible to gain many new fundamental insights as well as applications in biotechnology. Here, we present the history and basic principles of engineering metabolism, as well as the newest developments in the field. We are using examples of applications in: (1) production of protein pharmaceuticals and chemicals; (2) basic studies of metabolism; and (3) impacting health care. We will end by discussing how engineering metabolism can benefit from advances in artificial intelligence (AI)-based models.

Integrins are critical transmembrane receptors that connect the extracellular matrix (ECM) to the intracellular cytoskeleton, playing a central role in mechanotransduction – the process by which cells convert mechanical stimuli into biochemical signals. The dynamic assembly and disassembly of integrin-mediated adhesions enable cells to adapt continuously to changing mechanical cues, regulating essential processes such as adhesion, migration, and proliferation. In this review, we explore the molecular clutch model as a framework for understanding the dynamics of integrin – ECM interactions, emphasizing the critical importance of force loading rate. We discuss how force loading rate bridges internal actomyosin-generated forces and ECM mechanical properties like stiffness and ligand density, determining whether sufficient force is transmitted to mechanosensitive proteins such as talin. This force transmission leads to talin unfolding and activation of downstream signalling pathways, ultimately influencing cellular responses. We also examine recent advances in single-molecule DNA tension sensors that have enabled direct measurements of integrin loading rates, refining the range to approximately 0.5–4 pN/s. These findings deepen our understanding of force-mediated mechanotransduction and underscore the need for improved sensor designs to overcome current limitations.

The TRiC/CCT complex assists in the folding of approximately 10% of cytosolic proteins through an ATP-driven conformational cycle, playing a crucial role in maintaining protein homeostasis. Despite our understanding of ATP-driven TRiC ring closing and substrate folding, the process and mechanisms underlying TRiC ring-opening and substrate release remain largely unexplored. In this study, by determining an ensemble of cryo-EM structures of yeast TRiC in the presence of ADP, including three intermediate transition states, we present a comprehensive picture of the TRiC ring-opening process. During this process, CCT3 detects the loss of γ-phosphate and initiates with the dynamics of its apical protrusion, and expands to the outward leaning of the consecutive CCT6/8/7/5 subunits. This is followed by significant movements of CCT2, CCT4, and especially CCT1 subunits, resulting in the opening of the TRiC rings. We also observed an unforeseen temporary separation between the two rings in the CCT2 side, coordinating the release of the originally locked CCT4 N-terminus, which potentially participates in the ring-opening process. Collectively, our study reveals a stepwise TRiC ring-opening mechanism, provides a comprehensive view of the TRiC conformational landscape, and sheds lights on its subunit specificity in sensing nucleotide status and substrate release. Our findings deepen our understanding of protein folding assisted by TRiC and may inspire new strategies for the diagnosis and treatment of related diseases.

Synthetic biology aims to create a viable synthetic cell. However, to achieve this goal, it is essential first to gain a profound understanding of the cellular systems used to build that cell, how to reconstitute those systems in the compartments, and how to track their function. Transcription and translation are two vital cellular systems responsible for the production of RNA and, consequently, proteins, without which the cell would not be able to maintain itself or fulfill its functions. This review discusses in detail how the Protein synthesis Using Recombinant Element (PURE) system and cell lysate are used to reconstitute transcription–translation in vitro. Furthermore, it examines how these systems can be encapsulated in GUVs using the existing methods. It also assesses approaches available to image transcription and translation with a diverse arsenal of fluorescence microscopy techniques and a broad collection of probes developed in recent decades. Finally, it highlights solutions for the challenge ahead, namely the decoupling of the two systems in PURE, and discusses the prospects of synthetic biology in the modern world.

DNA unzipping by nanopore translocation has implications in diverse contexts, from polymer physics to single-molecule manipulation to DNA–enzyme interactions in biological systems. Here we use molecular dynamics simulations and a coarse-grained model of DNA to address the nanopore unzipping of DNA filaments that are knotted. This previously unaddressed problem is motivated by the fact that DNA knots inevitably occur in isolated equilibrated filaments and in vivo. We study how different types of tight knots in the DNA segment just outside the pore impact unzipping at different driving forces. We establish three main results. First, knots do not significantly affect the unzipping process at low forces. However, knotted DNAs unzip more slowly and heterogeneously than unknotted ones at high forces. Finally, we observe that the microscopic origin of the hindrance typically involves two concurrent causes: the topological friction of the DNA chain sliding along its knotted contour and the additional friction originating from the entanglement with the newly unzipped DNA. The results reveal a previously unsuspected complexity of the interplay of DNA topology and unzipping, which should be relevant for interpreting nanopore-based single-molecule unzipping experiments and improving the modeling of DNA transactions in vivo.

Integrative modeling enables structure determination for large macromolecular assemblies by combining data from multiple experiments with theoretical and computational predictions. Recent advancements in AI-based structure prediction and cryo electron-microscopy have sparked renewed enthusiasm for integrative modeling; structures from AI-based methods can be integrated with in situ maps to characterize large assemblies. This approach previously allowed us and others to determine the architectures of diverse macromolecular assemblies, such as nuclear pore complexes, chromatin remodelers, and cell–cell junctions. Experimental data spanning several scales was used in these studies, ranging from high-resolution data, such as X-ray crystallography and AlphaFold structure, to low-resolution data, such as cryo-electron tomography maps and data from co-immunoprecipitation experiments. Two recurrent modeling challenges emerged across a range of studies. First, these assemblies contained significant fractions of disordered regions, necessitating the development of new methods for modeling disordered regions in the context of ordered regions. Second, methods needed to be developed to utilize the information from cryo-electron tomography, a timely challenge as structural biology is increasingly moving towards in situ characterization. Here, we recapitulate recent developments in the modeling of disordered proteins and the analysis of cryo-electron tomography data and highlight other opportunities for method development in the context of integrative modeling.

The molecular mechanism of olfaction, namely, how we smell with limited olfactory receptors to recognize exceedingly diverse and large numbers of scents remains unknown despite the recent advances in chemistry, chemical, structural, and molecular biology. Olfactory receptors are notoriously difficult to study because they are fully embedded in the cell membrane. After decades of efforts and significant funding, there are only three olfactory receptor structures known. To understand olfaction, we carried out the structural bioinformatic study of six human olfactory receptors including OR51E1, OR51E2, OR52cs, OR1A1, OR1A2, TAAR9, and their AlphaFold3 predicted water-soluble QTY variants with odorants. We applied the QTY code to replace leucine (L) with glutamine (Q), isoleucine (I) and valine (V) with threonine (T), and phenylalanine (F) with tyrosine (Y) only in the transmembrane helices. Therefore, these QTY variants become water-soluble. We also present the superimposed structures of native olfactory receptors and their water-soluble QTY variants. The superimposed structures show remarkable similarity with RMSDs between 0.441 and 1.275 Å despite significant changes to the protein sequence of the transmembrane domains (43.03%–50.31%). We also show the differences in hydrophobicity surfaces between the native olfactory receptors and their QTY variants. Furthermore, we also used AlphaFold3 and molecular dynamics to study the odorant octanoate with OR1A2 and spermidine with TAAR9. Our bioinformatics studies provide insight into the differences between the hydrophobic helices and hydrophilic helices, and will likely further stimulate designs of water-soluble integral transmembrane proteins and other aggregated proteins.

Single-stranded nucleic acid (ssNA) binding proteins must both stably protect ssNA transiently exposed during replication and other NA transactions, and also rapidly reorganize and dissociate to allow further NA processing. How these seemingly opposing functions can coexist has been recently elucidated by optical tweezers (OT) experiments that isolate and manipulate single long ssNA molecules to measure conformation in real time. The effective length of an ssNA substrate held at fixed tension is altered upon protein binding, enabling quantification of both the structure and kinetics of protein–NA interactions. When proteins exhibit multiple binding states, however, OT measurements may produce difficult to analyze signals including non-monotonic response to free protein concentration and convolution of multiple fundamental rates. In this review we compare single-molecule experiments with three proteins of vastly different structure and origin that exhibit similar ssNA interactions. These results are consistent with a general model in which protein oligomers containing multiple binding interfaces switch conformations to adjust protein:NA stoichiometry. These characteristics allow a finite number of proteins to protect long ssNA regions by maximizing protein–ssNA contacts while also providing a pathway with reduced energetic barriers to reorganization and eventual protein displacement when these ssNA regions are diminished.