The Role of Protein Loops and Linkers in Conformational Dynamics and Allostery

Dynamic networks connect the USP14 active site region with the proteasome interaction surface

Ubiquitin-specific protease 14 (USP14) is a member of the USP family responsible for the catalytic removal of ubiquitin (Ub) from proteins directed to the proteasome, implicated in the pathogenesis of neurodegeneration and cancer. Crystallography and cryo-EM analysis have identified loop regions crucial for the deubiquitinase activity of USP14, specifically those involved in Ub and proteasome binding. However, the structural changes in USP14 upon ligand binding to these regions are minimal, indicating significant yet uncharacterized dynamic contributions to its function. In this study, through structural and dynamical NMR experiments and functional evaluation, we demonstrate that small mutations designed to impact Ub binding and catalytic activity without disturbing the USP structure display both local and long-range effects. The affected residues connect the catalytic site and the Ub binding region with the proteasome interaction surface through a network of loops, which show varied dynamics on the ps-ms time scale. Collectively, our findings experimentally reveal different aspects of dynamic connections within USP14, suggesting the presence of allosteric networks that link enzyme activity with regulatory function. The identification of coupled clusters of possible allostery participants in the free USP domain provides new insights into the dynamic regulation of USP14, with potential implications for understanding its role in cellular processes.

Advancements in protein structure prediction: A comparative overview of AlphaFold and its derivatives

This review provides a comprehensive analysis of AlphaFold (AF) and its derivatives (AF2 and AF3) in protein structure prediction. These tools have revolutionized structural biology with their highly accurate predictions, driving progress in protein modeling, drug discovery, and the study of protein dynamics. Its exceptional accuracy has redefined our understanding of protein folding, which enables groundbreaking advancements in protein design, disease research and discusses future integration with experimental techniques. In addition, their achievement features, architectures, important case studies, and noteworthy effects in the field of biology and medicine were evaluated. In consideration of the fact that AF2 is a relatively recent innovation, it has already been taken into account in many studies that highlight its applications in many ways. Moreover, the limitations of AF2 that directed to the introduction of AF3 are also reported, which is a great improvement as it provides precise predictions of the structures and interactions of proteins, DNA, RNA, and ligands, thereby aiding in the understanding of the molecular level. Addressing current challenges and forecasting future developments, this work underscores the lasting significance of AF in reshaping the scientific landscape of protein research.

In silico discovery of novel compounds for FAK activation using virtual screening, AI-based prediction, and molecular dynamics

Focal Adhesion Kinase (FAK) is a non-receptor tyrosine kinase that plays a crucial role in cell proliferation, migration, and signal transduction. FAK is overexpressed in metastatic and advanced-stage cancers, where it is considered a key kinase in cancer growth and metastasis. However, recent research has revealed that FAK activity decreases in various diseases. we aimed to identify compounds that could enhance FAK activity using structure-based virtual screening and artificial intelligence models from a vast chemical database. We began with an extensive chemical database containing over 10 million compounds and used our newly developed pipeline to screen candidate molecules. To select compounds structurally similar to ZINC40099027 (ZN27), a known FAK activator, we calculated Tanimoto Similarity scores and chose compounds with a score of at least 0.8. Clustering was performed using K-means based on the molecular properties. Subsequently, we utilized docking simulation, deep learning and SAScorer to evaluate and predict the protein-ligand docking affinity and physicochemical properties of the candidate compounds. The deep learning models were selected as state-of-the-art models: GLAM predicts the blood-brain barrier permeability of FAK, and elEmBERT predicts the potential toxicity of compound. The combined results were used to create an evaluation matrix. We selected 10 promising candidate compounds from the initial dataset of 10 million. To evaluate the stability of these top 10 candidate compounds in interaction with the FAK protein, we conducted Molecular Dynamics (MD) simulations. We performed a molecular dynamics simulation for a total of 50 ns and identified the top three promising candidate compounds.

The Evolving Landscape of Protein Allostery: From Computational and Experimental Perspectives

Protein allostery is a fundamental biological regulatory mechanism that allows communication between distant locations within a protein, modifying its function in response to signals. Experimental techniques, such as NMR spectroscopy and cryo-electron microscopy (cryo-EM), are critical validation tools for computational predictions and provide valuable insights into dynamic conformational changes. Combining these approaches has greatly improved our understanding of classical conformational allostery and complex dynamic coupling mechanisms. Recent advances in machine learning and enhanced sampling methods have broadened the scope of allostery research, identifying cryptic allosteric sites and directing new drug discovery approaches. Despite progress, bridging static structural data with dynamic functional states remains challenging. This review underscores the importance of combining experimental and computational approaches to comprehensively understand protein allostery and its diverse applications in biology and medicine.

Flexibility-Induced Collective Behavior Drives Symmetry Breaking in Discrimination of Undesired Ions

Structure flexibility is essential for the biological function of proteins. At the same time, many proteins need to discriminate ligands with subtle differences, with one example being ion selectivity. Investigating the mechanisms by which flexible proteins achieve such precise discrimination is crucial for advancing our understanding of their functions. In this work, we study transporter KCC4, which undergoes continuous conformation changes during ion transport and can realize K+ over Na+ selectivity. Our findings reveal that the center of the binding site no longer represents a stable equilibrium for the undesired Na+, and its binding mode exhibits bifurcation. Interestingly, protein conformation fluctuation can induce collective behavior throughout the entire binding region, which contributes to this bifurcation. Thus, the symmetry of the binding mode decreases from the inherent T d symmetry to a C2v symmetry, and the binding stability of Na+ is largely reduced. A similar phenomenon is observed in a GPCR, β2-AR, where a less favored ligand forms a biased binding mode with reduced stability. The mechanism underlying the selectivity in such flexible regions could be interpreted as spontaneous symmetry breaking, which may represent a general mechanism by which flexible proteins achieve efficient ligand discrimination.

Challenges and limitations of computer-aided drug design

Molecular Modelling in Drug Designing or Computer Aided Drug Designing (CADD) plays a significant role in new drug identification in the current world. However, it has sensitivity challenges and limitation because theoretical models involve assumption and approximations Computational models are not very accurate, some of the major challenges that face these models include the following. These include, for instance, molecular-docking or molecular-dynamics-simulation models which may not represent an accurate biological system and thus the predictions will be wrong. CADD depends on the availability of accurate, high-quality structural information for target proteins and ligand. Unfortunately, there are instances when experimental structures are not available, and homology models are employed, which can be imprecise. The computational cost is another drawback; only high accuracy simulations call for huge amounts of computational power and time well-suited for screening a multitude of agents. Moreover, they have weaknesses in determining pharmacokinetic and toxicity patterns of compounds that influence drug performance and effectiveness. In other words, even though CADD greatly helps drug discovery, it is still constrained by experimental validation to solve its drawbacks and optimize its foretelling.

E, R G, Paul SFD, R. M. Targeting beta-lactamase activity with Oxacyclohexadecan-2-one in carbapenem-resistant uropathogenic E. coli: A molecular simulation approach

Urinary tract infections caused by uropathogenic Escherichia coli (E. coli) are a global health concern, with rising rates and antibiotic resistance demanding novel treatments. Therefore, in this study, we explored the potential of Oxacyclohexadecan-2-one obtained from Moringa oleifera (M. oleifera) seed, as antibacterial agent against three majorly prevalent carbapenemase-producing E. coli proteins, blaNDM-1 (New Delhi metallo-betalactamase-1), blaNDM-5 (New Delhi metallo-betalactamase-5) and blaOXA-48 (Oxacillinase-48) from the strains Ecw3, EC-114 and T20 respectively. The ethanolic extract of M. oleifera seed was subjected to GC-MS, identifying 135 compounds. PyRx virtual screening, identified the top 10 ligands for each protein following the Rule of 5 and ProTox classes V and VI, with Oxacyclohexadecan-2-one (PubChem ID: 235414) showing best binding affinity across all 3 proteins with an optimized dose (LD50) of 5000mg/kg. Hence, molecular docking was carried out for ligand 235414 along with Imipenem, belonging to the same class V toxicity class with an optimized dose (LD50) of 5000mg/kg. Imipenem is a commonly used FDA drug to treat UTIs, which served as the control in the study. Oxacyclohexadecan-2-one showed higher binding affinity for the beta-lactamase proteins with a docking score of -6.45 kcal/mol, -6.05 kcal/mol and -7.34 kcal/mol compared to -3.41 kcal/mol, -3.99 kcal/mol and -6.36 kcal/mol of Imipenem for NDM-1, NDM-5 and OXA-48 respectively. Dynamic Simulation was performed for 100 ns for Oxacyclohexadecan-2-one and Imipenem bound protein complexes to determine the stability, fluctuations, compactness, bond interaction, solvent accessibility area, free energy landscape and the binding free energy. The results of molecular docking and dynamics were promising for the Oxacyclohexadecan-2-one, suggesting its potent inhibitory effect against the beta-lactamase producing proteins.

Emerging approaches to investigating functional protein dynamics in modular redox enzymes: Nitric oxide synthase as a model system

Approximately 80% of eukaryotic and 65% of prokaryotic proteins are composed of multiple folding units (i.e., domains) connected by flexible linkers. These dynamic protein architectures enable diverse, essential functions such as electron transfer, respiration, and biosynthesis. This review critically assesses recent advancements in methods for studying protein dynamics, with a particular focus on modular, multidomain nitric oxide synthase (NOS) enzymes. Moving beyond traditional static "snapshots" of protein structures, current research emphasizes the dynamic nature of proteins, viewing them as flexible architectures modulated by conformational changes and interactions. In this context, the review discusses key developments in the integration of quantitative crosslinking mass spectrometry (qXL MS) with AlphaFold 2 predictions, which provides a powerful approach to disentangling NOS structural dynamics and understanding their modulation by external regulatory cues. Additionally, advances in site-specific infrared (IR) spectroscopy offer exciting potential in providing rich details about the conformational dynamics of NOSs in docked states. Moreover, optimization of genetic code expansion machinery enables the generation of genuine phosphorylated NOS enzymes, paving the way for detailed biophysical and functional analyses of phosphorylation's role in shaping NOS activity and structural flexibility; notably, this approach also empowers site-specific IR probe labeling with cyano groups. By embracing and leveraging AI-driven tools like AlphaFold 2 for structural and conformational modeling, alongside solution-based biophysical methods such as qXL MS and site-specific IR spectroscopy, researchers will gain integrative insights into functional protein dynamics. Collectively, these breakthroughs highlight the transformative potential of modern approaches in driving fundamental biological chemistry research.

Molecular dynamics simulations: Insights into protein and protein ligand interactions

Molecular dynamics (MD) simulations are a powerful tool for studying biomolecular systems, offering in-depth insights into the dynamic behaviors of proteins and their interactions with ligands. This chapter delves into the fundamental principles and methodologies of MD simulations, exploring how they contribute to our understanding of protein structures, conformational changes, and the mechanisms underlying protein-ligand interactions. We discuss the computational techniques, force fields, and algorithms that drive MD simulations, highlighting their applications in drug discovery and design. Through case studies and practical examples, we illustrate the capabilities and limitations of MD simulations, emphasizing their role in predicting binding affinities, elucidating binding pathways, and optimizing lead compounds. This chapter offers a thorough understanding of how MD simulations can be leveraged to advance the study of protein-ligand interactions.

Identification of Scaffold Specific Energy Transfer Networks in the Enthalpic Activation of Orotidine 5'-Monophosphate Decarboxylase

Orotidine 5'-monophosphate decarboxylase (OMPDC) is one of the most efficient enzyme systems studied, enhancing the decarboxylation of OMP to uridine 5'-monophosphate (UMP) by ca. 17 orders of magnitude, primarily by reducing the enthalpy of activation by ca. 28 kcal/mol. Despite a substantial reduction in activation enthalpy, OMPDC requires 15 kcal/mol of activation energy post-ES complex formation. This study investigates the physical basis of how thermal energy from solvent collisions is directed into the active site of enzyme to enable efficient thermal activation of the reaction. Comparative study of temperature-dependent hydrogen-deuterium exchange mass spectrometry (TDHDX) for WT and mutant forms of enzymes has recently been shown to uncover site specific protein networks for thermal energy transfer from solvent to enzyme active sites. In this study, we interrogate region-specific changes in the enthalpic barrier for local protein flexibility using a native OMPDC from Methanothermobacter thermautotrophicus (Mt-OMPDC) and a single site variant (Leu123Ala) that alters the activation enthalpy for catalytic turnover. The data obtained implicate four spatially resolved, thermally sensitive networks that originate at different protein/solvent interfaces and terminate at sites surrounding the substrate near the substrate phosphate-binding region (R203), the substrate- ribose binding region (K42), and a reaction enhancing loop5 (S127). These are proposed to act synergistically, transiently optimizing the position and electrostatics of the reactive carboxylate of the substrate to facilitate activated complex formation. The uncovered complexity of thermal activation networks in Mt-OMPDC distinguishes this enzyme from other members of the TIM barrel family previously investigated by TDHDX. The new findings extend the essential role of protein scaffold dynamics in orchestrating enzyme activity, with broad implications for the design of highly efficient biocatalysts.

Leveraging the Thermodynamics of Protein Conformations in Drug Discovery

As the name implies, structure-based drug design requires confidence in the holo complex structure. The ability to clarify which protein conformation to use when ambiguity arises would be incredibly useful. We present a large scale validation of the computational method Protein Reorganization Free Energy Perturbation (PReorg-FEP) and demonstrate its quantitative accuracy in selecting the correct protein conformation among candidate models in apo or ligand induced states for 14 different systems. These candidate conformations are pulled from various drug discovery related campaigns: cryptic conformations induced by novel hits in lead identification, binding site rearrangement during lead optimization, and conflicting structural biology models. We also show an example of a pH-dependent conformational change, relevant to protein design.

The Conformational Space of the SARS-CoV-2 Main Protease Active Site Loops Is Determined by Ligand Binding and Interprotomer Allostery

The main protease (Mpro) of SARS-CoV-2 is essential for viral replication and is, therefore, an important drug target. Here, we investigate two flexible loops in Mpro that play a role in catalysis. Using all-atom molecular dynamics simulations, we analyze the structural ensemble of Mpro in an apo state and substrate-bound state. We find that the flexible loops can adopt open, intermediate (partly open), and closed conformations in solution, which differs from the partially closed state observed in crystal structures of Mpro. When the loops are in closed or intermediate states, the catalytic residues are more likely to be in close proximity, which is crucial for catalysis. Additionally, we find that substrate binding to one protomer of the homodimer increases the frequency of intermediate states in the bound protomer while also affecting the structural propensity of the apo protomer's flexible loops. Using dynamic network analysis, we identify multiple allosteric pathways connecting the two active sites of the homodimer. Common to these pathways is an allosteric hotspot involving the N-terminus, a critical region that comprises part of the binding pocket. Taken together, the results of our simulation study provide detailed insight into the relationships between the flexible loops and substrate binding in a prime drug target for COVID-19.

Allosteric Communication Mediated by Protein Contact Clusters: A Dynamical Model

Describing the puzzling phenomenon of long-range communication between distant protein sites, allostery is of paramount importance in biomolecular regulation and signal transduction. It is commonly assumed to arise from a conformational rearrangement of the protein, although the underlying dynamical process has remained largely elusive. This study introduces a dynamical model of allosteric communication based on "contact clusters"─localized groups of highly correlated contacts that facilitate interactions between secondary structures. The model shows that allostery involves a multistep process with cooperative contact changes within clusters and communication between distant clusters mediated by rigid secondary structures. Considering time-dependent experiments on a photoswitchable PDZ3 domain, extensive (in total ∼500 μs) molecular dynamics simulations are conducted that directly monitor the photoinduced allosteric transition. The structural reorganization is illustrated by the time evolution of the contact clusters and the ligand, which effects the nonlocal coupling between distant clusters. A time scale analysis reveals dynamics from nano- to microseconds, which are in excellent agreement with the experimentally measured time scales. While the simulation of larger systems may require enhanced sampling techniques, it is expected that the general picture of allostery mediated by communicating contact clusters will still be applicable.

Site-specific incorporation of 19F-nulcei at protein C-terminus to probe allosteric conformational transitions of metalloproteins

Allosteric conformational change is an important paradigm in the regulation of protein function, which is typically triggered by the binding of small cofactors, metal ions or protein partners. Here, we found those conformational transitions can be effectively monitored by 19F NMR, facilitated by a site-specific 19F incorporation strategy at the protein C-terminus using asparaginyl endopeptidase (AEP). Three case studies show that C-terminal 19F-nuclei can reveal protein dynamics not only adjacent but also distal to C-terminus, including those occurring in a hemoprotein neuroglobin (Ngb), calmodulin (CaM), and a cobalt metalloregulator (CoaR) responding to both cobalt and tetrapyrrole. In Ngb, the heme orientation disorder is affected by missense mutations that perturb backbone rigidity or surface charges close to the heme axial ligands. In CaM, the C-terminal 19F-nuclei is an ideal probe for detecting the binding states of Ca2+, peptides and inhibitors. Furthermore, multiple 19F-moieties were incorporated into the two domains of CoaR, revealing the intrinsically disordered C-terminal metal binding tail might be an allosteric conformational switch to maintain cobalt homeostasis and balance corrinoid biosynthesis. This study demonstrates that the AEP-based 19F-modification strategy can be applied to various targets to study allosteric regulation, especially for those biological processes modulated by the protein C-terminus.

Tracing the birth and intrinsic disorder of loops and domains in protein evolution

Protein loops and structural domains are building blocks of molecular structure. They hold evolutionary memory and are largely responsible for the many functions and processes that drive the living world. Here, we briefly review two decades of phylogenomic data-driven research focusing on the emergence and evolution of these elemental architects of protein structure. Phylogenetic trees of domains reconstructed from the proteomes of organisms belonging to all three superkingdoms and viruses were used to build chronological timelines describing the origin of each domain and its embedded loops at different levels of structural abstraction. These timelines consistently recovered six distinct evolutionary phases and a most parsimonious evolutionary progression of cellular life. The timelines also traced the birth of domain structures from loops, which allowed to model their growth ab initio with AlphaFold2. Accretion decreased the disorder of the growing molecules, suggesting disorder is molecular size-dependent. A phylogenomic survey of disorder revealed that loops and domains evolved differently. Loops were highly disordered, disorder increased early in evolution, and ordered and moderate disordered structures were derived. Gradual replacement of loops with α-helix and β-strand bracing structures over time paved the way for the dominance of more disordered loop types. In contrast, ancient domains were ordered, with disorder evolving as a benefit acquired later in evolution. These evolutionary patterns explain inverse correlations between disorder and sequence length of loops and domains. Our findings provide a deep evolutionary view of the link between structure, disorder, flexibility, and function.

Engineering the native ensemble to tune protein function: Diverse mutational strategies and interlinked molecular mechanisms

Natural proteins are fragile entities, intrinsically sensitive to perturbations both at the level of sequence and their immediate environment. Here, we highlight the diverse strategies available for engineering function through mutations influencing backbone conformational entropy, charge-charge interactions, and in the loops and hinge regions, many of which are located far from the active site. It thus appears that there are potentially numerous ways to microscopically vary the identity of residues and the constituent interactions to tune function. Functional modulation could occur via changes in native-state stability, altered thermodynamic coupling extents within the folded structure, redistributed dynamics, or through modulation of the population of conformational substates. As these mechanisms are intrinsically linked and given the pervasive long-range effects of mutations, it is crucial to consider the interaction network as a whole and fully map the native conformational landscape to place mutational effects in the context of allostery and protein evolution.

SOP-MULTI: A Self-Organized Polymer-Based Coarse-Grained Model for Multidomain and Intrinsically Disordered Proteins with Conformation Ensemble Consistent with Experimental Scattering Data

Multidomain proteins with long flexible linkers and full-length intrinsically disordered proteins (IDPs) are best defined as an ensemble of conformations rather than a single structure. Determining high-resolution ensemble structures of such proteins poses various challenges by using tools from experimental structural biophysics. Integrative approaches combining available low-resolution ensemble-averaged experimental data and in silico biomolecular reconstructions are now often used for the purpose. However, extensive Boltzmann weighted conformation sampling for large proteins, especially for ones where both the folded and disordered domains exist in the same polypeptide chain, remains a challenge. In this work, we present a 2-site per amino-acid resolution SOP-MULTI force field for simulating coarse-grained models of multidomain proteins. SOP-MULTI combines two well-established self-organized polymer models─: (i) SOP-SC models for folded systems and (ii) SOP-IDP for IDPs. For the SOP-MULTI, we introduce cross-interaction terms between the beads belonging to the folded and disordered regions to generate conformation ensembles for full-length multidomain proteins such as hnRNP A1, TDP-43, G3BP1, hGHR-ECD, TIA1, HIV-1 Gag, polyubiquitin, and FUS. When back-mapped to all-atom resolution, SOP-MULTI trajectories faithfully recapitulate the scattering data over the range of the reciprocal space. We also show that individual folded domains preserve native contacts with respect to solved folded structures, and root-mean-square fluctuations of residues in folded domains match those obtained from all-atom molecular dynamics simulation trajectories of the same folded systems. SOP-MULTI force field is made available as a LAMMPS-compatible user package along with setup codes for generating the required files for any full-length protein with folded and disordered regions.

Unveiling the biosynthesis mechanism of novel lantibiotic homicorcin: an in silico analysis

Jute endophyte Staphylococcus hominis strain MBL_AB63 was reported to produce a novel antimicrobial peptide, 'homicorcin'. This exhibits potential activity against a broad spectrum of Gram-positive bacteria. Eight genes were predicted to be involved in the sequential maturation of this peptide antibiotic, which includes structural (homA), dehydratase (homB), cyclase (homC), peptidase (homP), immunity (homI), oxidoreductase (homO), ATP-binding cassette transporter (homT1), and permease (homT2), respectively. Among the modification enzymes, HomB, HomC, and HomP exhibit sequence similarities with class I lantibiotic dehydratase, cyclase, and leader peptidase, respectively. The current study investigated the sequential modifications and secretion of homicorcin by constructing robust computational protein models and analyzing their interaction patterns using protein-protein docking techniques. To enhance comprehension of the protein arrangement, their subcellular localization was also extrapolated. The findings demonstrate a network of proteins that works in a synchronized manner, where HomC functions as an intermediary between HomB and the transporter (HomT). Following its dehydration by HomB and cyclization by HomC, the pro-homicorcin is taken out of the cell by the transporter and processed by HomP, resulting in the production of matured, processed homicorcin. This biosynthesis model for homicorcin will lay the groundwork for the sustainable and efficient production of this peptide antibiotic.

Deep mutational scanning of a multi-domain signaling protein reveals mechanisms of regulation and pathogenicity

Multi-domain signaling enzymes are often regulated through extensive inter-domain interactions, and disruption of inter-domain interfaces by mutations can lead to aberrant signaling and diseases. For example, the tyrosine phosphatase SHP2 contains two phosphotyrosine recognition domains that auto-inhibit its catalytic domain. SHP2 is canonically activated by binding of these non-catalytic domains to phosphoproteins, which destabilizes the auto-inhibited state, but numerous mutations at the main auto-inhibitory interface have been shown to hyperactivate SHP2 in cancers and developmental disorders. Hundreds of clinically observed mutations in SHP2 have not been characterized, but their locations suggest alternative modes of dysregulation. We performed deep mutational scanning on full-length SHP2 and the isolated phosphatase domain to dissect mechanisms of SHP2 dysregulation. Our analysis revealed mechanistically diverse mutational effects and identified key intra- and inter-domain interactions that contribute to SHP2 activity, dynamics, and regulation. Our datasets also provide insights into the potential pathogenicity of previously uncharacterized clinical variants.

RNA binding tunes the conformational plasticity and intradomain stability of TDP-43 tandem RNA recognition motifs

TAR DNA binding protein 43 (TDP-43) is a nuclear RNA/DNA-binding protein with pivotal roles in RNA-related processes such as splicing, transcription, transport, and stability. The high binding affinity and specificity of TDP-43 toward its cognate RNA sequences (GU-rich) is mediated by highly conserved residues in its tandem RNA recognition motif (RRM) domains (aa: 104-263). Importantly, the loss of RNA binding to the tandem RRMs caused by physiological stressors and chemical modifications promotes cytoplasmic mislocalization and pathological aggregation of TDP-43. Despite the substantial implications of RNA binding in TDP-43 function and pathology, its precise effects on the intradomain stability, and conformational dynamics of the tandem RRMs is not properly understood. Here, we employed all-atom molecular dynamics (MD) simulations to assess the effect of RNA binding on the conformational landscape and intradomain stability of TDP-43 tandem RRMs. RNA limits the overall conformational space of the tandem RRMs and promotes intradomain stability through a combination of specific base stacking interactions and transient electrostatic interactions. In contrast, tandem RRMs exhibit a high intrinsic conformational plasticity in the absence of RNA, which, surprisingly, is accompanied by a tendency of RRM1 to adopt partially unfolded conformations. Overall, our simulations reveal how RNA binding dynamically tunes the structural and conformational landscape of TDP-43 tandem RRMs, contributing to physiological function and mitigating pathological aggregation.

Alternansucrase as a key enabling tool of biotransformation from molecular features to applications: A review

Alternansucrase (ASR), classified in GH70, produces unique α-glucans with alternating α-1,3 and α-1,6 glycosidic linkages in the backbone chain from renewable sucrose which is easily obtained from nature with low cost. ASR has synthesized many products with valuable functionalities that hold enormous commercial interest and promising applications. The influence of biocatalysis and fermentation parameters on the yields, and properties of products are critical for the propositions made to promote the enzyme application. Investigations on ASR have been compiled in the review to provide information on the enzyme, products and parameters. This review summarizes studies on the characteristics, conversion mechanism, products, and beneficial applications of ASR and exhibits structure-based technologies to improve enzyme activity, specificity, and thermostability for industrial applications. Finally, prospects for further development are also proposed for various ASR applications in food and other fields.

Macromolecular crowding effects on protein dynamics

Macromolecular crowding experiments bridge the gap between in-vivo and in-vitro studies by mimicking some of the cellular complexities like high viscosity and limited space, while still manageable for experiments and analysis. Macromolecular crowding impacts all biological processes and is a focus of contemporary research. Recent reviews have highlighted the effect of crowding on various protein properties. One of the essential characteristics of protein is its dynamic nature; however, how protein dynamics get modulated in the crowded milieu has been largely ignored. This article discusses how protein translational, rotational, conformational, and solvation dynamics change under crowded conditions, summarizing key observations in the literature. We emphasize our research on microsecond conformational and water dynamics in crowded milieus and their impact on enzymatic activity and stability. Lastly, we provided our outlook on how this field might move forward in the future.

A designed Zn 2+ sensor domain transmits binding information to transmembrane histidine kinases

Generating stimulus-responsive, allosteric signaling de novo is a significant challenge in protein design. In natural systems like bacterial histidine kinases (HKs), signal transduction occurs when ligand binding initiates a signal that is amplified across biological membranes over long distances to induce large-scale rearrangements and phosphorylation relays. Here, we ask whether our understanding of protein design and multi-domain, intramolecular signaling has progressed sufficiently to enable engineering of a HK with tunable de novo components. We generated de novo metal-binding sensor domains and substituted them for the native sensor domain of a transmembrane HK, affording chimeras that transduce signals initiated from a de novo sensor. Signaling depended on the designed sensor's stability and the interdomain linker's phase and length. These results show the usefulness of de novo design to elucidate biochemical mechanisms and principles for design of new signaling systems.

A low-barrier proton shared between two aspartates acts as a conformational switch that changes the substrate specificity of the β-lactamase BlaC

Serine β-lactamases inactivate β-lactam antibiotics in a two-step mechanism comprising acylation and deacylation. For the deacylation step, a water molecule is activated by a conserved glutamate residue to release the adduct from the enzyme. The third-generation cephalosporin ceftazidime is a poor substrate for the class A β-lactamase BlaC from Mycobacterium tuberculosis but it can be hydrolyzed faster when the active site pocket is enlarged, as was reported for mutant BlaC P167S. The conformational change in the Ω-loop of the P167S mutant displaces the conserved glutamate (Glu166), suggesting it is not required for deacylation of the ceftazidime adduct. Here, we report the characterization of wild type BlaC and BlaC E166A at various pH values. The presence of Glu166 strongly enhances activity against nitrocefin but not ceftazidime, indicating it is indeed not required for deacylation of the adduct of the latter substrate. At high pH wild type BlaC was found to exist in two states, one of which converts ceftazidime much faster, resembling the open state previously reported for the BlaC mutant P167S. The pH-dependent switch between the closed and open states is caused by the loss at high pH of a low-barrier hydrogen bond, a proton shared between Asp172 and Asp179. These results illustrate how readily shifts in substrate specificity can occur as a consequence of subtle changes in protein structure.

A flexible linker of 8-amino acids between the membrane binding segment and the FMN domain of cytochrome P450 reductase is necessary for optimal activity

The diflavin NADPH-cytochrome P450 reductase (CYPOR) plays a critical role in human cytochrome P450 (CYP) activity by sequentially delivering two electrons from NADPH to CYP enzymes during catalysis. Although electron transfer to forty-eight human CYP enzymes by the FMN hydroquinone of CYPOR is well-known, the role of the linker between the NH2-terminus membrane-binding domain (MBD) and FMN domain in supporting the activity of P450 enzymes remains poorly understood. Here we demonstrate that a linker with at least eight residues is required to form a functional CYPOR-CYP2B4 complex. The linker has been shortened in two amino-acid increments from Phe44 to Ile57 using site directed mutagenesis. The ability of the deletion mutants to support cytochrome P450 2B4 (CYP2B4) catalysis and reduce ferric CYP2B4 was determined using an in vitro assay and stopped-flow spectrophotometry. Steady-state enzyme kinetics showed that shortening the linker by 8-14 amino acids inhibited (63-99%) the ability of CYPOR to support CYP2B4 activity and significantly increased the Km of CYPOR for CYP2B4. In addition, the reductase mutants decreased the rate of reduction of ferric CYP2B4 (46-95%) compared to wildtype when the linker was shortened by 8-14 residues. These results indicate that a linker with a minimum length of eight residues is necessary to enable the FMN domain of reductase to interact with CYP2B4 to form a catalytically competent complex. Our study provides evidence that the length of the MBD-FMN domain linker is a major determinant of the ability of CYPOR to support CYP catalysis and drug metabolism by P450 enzymes. PREAMBLE: This manuscript is dedicated in memory of Dr. James R. Kincaid who was the doctoral advisor to Dr. Freeborn Rwere and a longtime collaborator and friend of Dr. Lucy Waskell. Dr. James R. Kincaid was a distinguished professor of chemistry specializing in resonance Raman (rR) studies of heme proteins. He inspired Dr. Rwere (a Zimbabwean native) and three other Zimbabweans (Dr. Remigio Usai, Dr. Daniel Kaluka and Ms. Munyaradzi E. Manyumwa) to use lasers to document subtle changes occurring at heme active site of globin proteins (myoglobin and hemoglobin) and cytochrome P450 enzymes. Dr. Rwere appreciate his contributions to the development of talented Black scientists from Africa.

On Protein Loops, Prior Molecular States and Common Ancestors of Life

The principle of continuity demands the existence of prior molecular states and common ancestors responsible for extant macromolecular structure. Here, we focus on the emergence and evolution of loop prototypes - the elemental architects of protein domain structure. Phylogenomic reconstruction spanning superkingdoms and viruses generated an evolutionary chronology of prototypes with six distinct evolutionary phases defining a most parsimonious evolutionary progression of cellular life. Each phase was marked by strategic prototype accumulation shaping the structures and functions of common ancestors. The last universal common ancestor (LUCA) of cells and viruses and the last universal cellular ancestor (LUCellA) defined stem lines that were structurally and functionally complex. The evolutionary saga highlighted transformative forces. LUCA lacked biosynthetic ribosomal machinery, while the pivotal LUCellA lacked essential DNA biosynthesis and modern transcription. Early proteins therefore relied on RNA for genetic information storage but appeared initially decoupled from it, hinting at transformative shifts of genetic processing. Urancestral loop types suggest advanced folding designs were present at an early evolutionary stage. An exploration of loop geometric properties revealed gradual replacement of prototypes with α-helix and β-strand bracing structures over time, paving the way for the dominance of other loop types. AlphFold2-generated atomic models of prototype accretion described patterns of fold emergence. Our findings favor a ‛processual' model of evolving stem lines aligned with Woese's vision of a communal world. This model prompts discussing the 'problem of ancestors' and the challenges that lie ahead for research in taxonomy, evolution and complexity.

Hook loop dynamics engineering transcended the barrier of activity-stability trade-off and boosted the thermostability of enzymes

The improvement of enzyme thermostability often accompanies the decreased activity due to the loss of the key regions' flexibility. As a representative structure, unlocking the potential of loop dynamics will not only provide new ideas for stabilization strategies, but also help to deepen the understanding of the relationship between enzyme structural dynamics and function. In this study, a creative "hook loop dynamics engineering" (HLoD) strategy was successfully proposed for simultaneously improving the thermostability and maintaining activity of the model enzyme, Candida Antarctica lipase B. A small and smart mutant library involving five key residues located at the "hook loop" was meticulously identified and systematically investigated and thus yielded a five-point multiple mutant M1 (L147S/T244P/S250P/T256D/N292D), demonstrating a remarkable 7.0-fold increase in thermostability at 60 °C compared to the wild-type (WT). Furthermore, the activity of M1 remained comparable to that of WT, effectively transcending the barrier of activity-stability trade-off. Molecular dynamics simulations revealed that the precise regulation of hook loop dynamics via intermolecular interactions, such as salt bridges and hydrogen bonding, curbed the excessive flexibility of the pivotal regions α5 and α10 at high temperatures, thus driving the substantial enhancement of the thermostability of M1. Refining the dynamics of the flexible region via HLoD, which transcended the barrier of activity-stability trade-off, exhibited to be a robust and potentially universal strategy for designing enzymes with outstanding thermostability and activity.

N-terminal domain of polypyrimidine-tract binding protein is a dynamic folding platform for adaptive RNA recognition

The N-terminal RNA recognition motif domain (RRM1) of polypyrimidine tract binding protein (PTB) forms an additional C-terminal helix α3, which docks to one edge of the β-sheet upon binding to a stem-loop RNA containing a UCUUU pentaloop. Importantly, α3 does not contact the RNA. The α3 helix therefore represents an allosteric means to regulate the conformation of adjacent domains in PTB upon binding structured RNAs. Here we investigate the process of dynamic adaptation by stem-loop RNA and RRM1 using NMR and MD in order to obtain mechanistic insights on how this allostery is achieved. Relaxation data and NMR structure determination of the free protein show that α3 is partially ordered and interacts with the domain transiently. Stem-loop RNA binding quenches fast time scale dynamics and α3 becomes ordered, however microsecond dynamics at the protein-RNA interface is observed. MD shows how RRM1 binding to the stem-loop RNA is coupled to the stabilization of the C-terminal helix and helps to transduce differences in RNA loop sequence into changes in α3 length and order. IRES assays of full length PTB and a mutant with altered dynamics in the α3 region show that this dynamic allostery influences PTB function in cultured HEK293T cells.

Rational enzyme design by reducing the number of hotspots and library size

Biocatalysts that are eco-friendly, sustainable, and highly specific have great potential for applications in the production of fine chemicals, food, detergents, biofuels, pharmaceuticals, and more. However, due to factors such as low activity, narrow substrate scope, poor thermostability, or incorrect selectivity, most natural enzymes cannot be directly used for large-scale production of the desired products. To overcome these obstacles, protein engineering methods have been developed over decades and have become powerful and versatile tools for adapting enzymes with improved catalytic properties or new functions. The vastness of the protein sequence space makes screening a bottleneck in obtaining advantageous mutated enzymes in traditional directed evolution. In the realm of mathematics, there are two major constraints in the protein sequence space: (1) the number of residue substitutions (M); and (2) the number of codons encoding amino acids as building blocks (N). This feature review highlights protein engineering strategies to reduce screening efforts from two dimensions by reducing the numbers M and N, and also discusses representative seminal studies of rationally engineered natural enzymes to deliver new catalytic functions.

ATOMDANCE: Kernel-based denoising and choreographic analysis for protein dynamic comparison

Comparative methods in molecular evolution and structural biology rely heavily upon the site-wise analysis of DNA sequence and protein structure, both static forms of information. However, it is widely accepted that protein function results from nanoscale nonrandom machine-like motions induced by evolutionarily conserved molecular interactions. Comparisons of molecular dynamics (MD) simulations conducted between homologous sites representative of different functional or mutational states can potentially identify local effects on binding interaction and protein evolution. In addition, comparisons of different (i.e., nonhomologous) sites within MD simulations could be employed to identify functional shifts in local time-coordinated dynamics indicative of logic gating within proteins. However, comparative MD analysis is challenged by the large fraction of protein motion caused by random thermal noise in the surrounding solvent. Therefore, properly denoised MD comparisons could reveal functional sites involving these machine-like dynamics with good accuracy. Here, we introduce ATOMDANCE, a user-interfaced suite of comparative machine learning-based denoising tools designed for identifying functional sites and the patterns of coordinated motion they can create within MD simulations. ATOMDANCE-maxDemon4.0 employs Gaussian kernel functions to compute site-wise maximum mean discrepancy between learned features of motion, thereby assessing denoised differences in the nonrandom motions between functional or evolutionary states (e.g., ligand bound versus unbound, wild-type versus mutant). ATOMDANCE-maxDemon4.0 also employs maximum mean discrepancy to analyze potential random amino acid replacements allowing for a site-wise test of neutral versus nonneutral evolution on the divergence of dynamic function in protein homologs. Finally, ATOMDANCE-Choreograph2.0 employs mixed-model analysis of variance and graph network to detect regions where time-synchronized shifts in dynamics occur. Here, we demonstrate ATOMDANCE's utility for identifying key sites involved in dynamic responses during functional binding interactions involving DNA, small-molecule drugs, and virus-host recognition, as well as understanding shifts in global and local site coordination occurring during allosteric activation of a pathogenic protease.

pyGROMODS: a Python package for the generation of input files for molecular dynamic simulation with GROMACS

The pyGROMODS, an easy-to-use cross-platform python-based package, with a graphical user interface, for the generation of molecular dynamic (MD) input files and running MD simulation (MDS) of proteins, peptides, and protein-ligand complex using GROMACS, is here presented. Four routes, with underlining Python scripts, are implemented in pyGROMODS for the generation of MD input files. They are 'RLmulti' for processing multi-ligand protein complex, 'RLmany' for processing multiple ligands against a single protein target, 'RLsingle' for processing multiple pairs of proteins and ligands, and 'PPmore' for processing peptides or proteins without ligands or non-standard residues. In addition, using the package, the generated input files or appropriate input files from other sources can be uploaded to run MDS with GROMACS. The pyGROMODS is implemented with a unique ability to search the host machine systems for the installation of the required software, update and/or install required Python packages, allow the user to pre-define working directory, and generate unique workflow organization with well-defined folders and files in a well-organized manner. The pyGROMODS, which is released under the MIT License, is freely available for download via the GitHub (https://github.com/Dankem/pyGROMODS) and Zenodo (https://doi.org/10.5281/zenodo.7912747) repositories. The precompiled executables can also be downloaded from Zenodo (https://doi.org/10.5281/zenodo.8087090), and a video tutorial can be downloaded from https://youtu.be/I4OKc6uVx1M.Communicated by Ramaswamy H. Sarma.

Aggregation Inducing Reversible Conformational Isomerization of Surface Staple in Au18SR14 Nanoclusters

The conformation of molecules and materials is crucial in determining their properties and applications. Here, this work explores the reversible transformation between two distinct conformational isomers in metal nanoclusters. This work demonstrates the successful manipulation of a controllable and reversible isomerization of Au18SR14 within an aqueous solution through two distinct methods: ethanol addition and pH adjustment. The initial driver is the alteration of the solution environment, leading to the aggregation of Au18SR14 protected by ligands with smaller steric hindrance. At the atomic level, the folding mode of the unique Au4SR5 staple underpins the observed structural transformation. The reversal of staple conformation leads to color shifting between green and orange-red, and tailors a second emission peak at 725 nm originating from charge transfer from the thiolate to the Au9 core. This work not only deepens the understanding of the surface structure and dual-emission of metal nanoparticles, but also enhances the comprehension of their isomerization.

Highly Accurate and Efficient Deep Learning Paradigm for Full-Atom Protein Loop Modeling with KarmaLoop

Protein loop modeling is a challenging yet highly nontrivial task in protein structure prediction. Despite recent progress, existing methods including knowledge-based, ab initio, hybrid, and deep learning (DL) methods fall substantially short of either atomic accuracy or computational efficiency. To overcome these limitations, we present KarmaLoop, a novel paradigm that distinguishes itself as the first DL method centered on full-atom (encompassing both backbone and side-chain heavy atoms) protein loop modeling. Our results demonstrate that KarmaLoop considerably outperforms conventional and DL-based methods of loop modeling in terms of both accuracy and efficiency, with the average RMSDs of 1.77 and 1.95 Å for the CASP13+14 and CASP15 benchmark datasets, respectively, and manifests at least 2 orders of magnitude speedup in general compared with other methods. Consequently, our comprehensive evaluations indicate that KarmaLoop provides a state-of-the-art DL solution for protein loop modeling, with the potential to hasten the advancement of protein engineering, antibody-antigen recognition, and drug design.

Motif-VI loop acts as a nucleotide valve in the West Nile Virus NS3 Helicase

The Orthoflavivirus NS3 helicase (NS3h) is crucial in virus replication, representing a potential drug target for pathogenesis. NS3h utilizes nucleotide triphosphate (ATP) for hydrolysis energy to translocate on single-stranded nucleic acids, which is an important step in the unwinding of double-stranded nucleic acids. Intermediate states along the ATP hydrolysis cycle and conformational changes between these states, represent important yet difficult-to-identify targets for potential inhibitors. Extensive molecular dynamics simulations of West Nile virus NS3h+ssRNA in the apo, ATP, ADP+Pi and ADP bound states were used to model the conformational ensembles along this cycle. Energetic and structural clustering analyses depict a clear trend of differential enthalpic affinity of NS3h with ADP, demonstrating a probable mechanism of hydrolysis turnover regulated by the motif-VI loop (MVIL). Based on these results, MVIL mutants (D471L, D471N and D471E) were found to have a substantial reduction in ATPase activity and RNA replication compared to the wild-type. Simulations of the mutants in the apo state indicate a shift in MVIL populations favoring either a closed or open 'valve' conformation, affecting ATP entry or stabilization, respectively. Combining our molecular modeling with experimental evidence highlights a conformation-dependent role for MVIL as a 'valve' for the ATP-pocket, presenting a promising target for antiviral development.

Engineering Electron Transfer Pathway of Cytochrome P450s

Cytochrome P450s (P450s), a superfamily of heme-containing enzymes, existed in animals, plants, and microorganisms. P450s can catalyze various regional and stereoselective oxidation reactions, which are widely used in natural product biosynthesis, drug metabolism, and biotechnology. In a typical catalytic cycle, P450s use redox proteins or domains to mediate electron transfer from NAD(P)H to heme iron. Therefore, the main factors determining the catalytic efficiency of P450s include not only the P450s themselves but also their redox-partners and electron transfer pathways. In this review, the electron transfer pathway engineering strategies of the P450s catalytic system are reviewed from four aspects: cofactor regeneration, selection of redox-partners, P450s and redox-partner engineering, and electrochemically or photochemically driven electron transfer.

Leveraging Bidirectional Nature of Allostery To Inhibit Protein-Protein Interactions (PPIs): A Case Study of PCSK9-LDLR Interaction

The protein PCSK9 (proprotein convertase subtilisin/Kexin type 9) negatively regulates the recycling of LDLR (low-density lipoprotein receptor), leading to an elevated plasma level of LDL. Inhibition of PCSK9-LDLR interaction has emerged as a promising therapeutic strategy to manage hypercholesterolemia. However, the large interaction surface area between PCSK9 and LDLR makes it challenging to identify a small molecule competitive inhibitor. An alternative strategy would be to identify distal cryptic sites as targets for allosteric inhibitors that can remotely modulate PCSK9-LDLR interaction. Using several microseconds long molecular dynamics (MD) simulations, we demonstrate that on binding with LDLR, there is a significant conformational change (population shift) in a distal loop (residues 211-222) region of PCSK9. Consistent with the bidirectional nature of allostery, we establish a clear correlation between the loop conformation and the binding affinity with LDLR. Using a thermodynamic argument, we establish that the loop conformations predominantly present in the apo state of PCSK9 would have lower LDLR binding affinity, and they would be potential targets for designing allosteric inhibitors. We elucidate the molecular origin of the allosteric coupling between this loop and the LDLR binding interface in terms of the population shift in a set of salt bridges and hydrogen bonds. Overall, our work provides a general strategy toward identifying allosteric hotspots: compare the conformational ensemble of the receptor between the apo and bound states of the protein and identify distal conformational changes, if any. The inhibitors should be designed to bind and stabilize the apo-specific conformations.

Protein Allostery Study in Cells Using NMR Spectroscopy

Protein allostery is commonly observed in vitro. But how protein allostery behaves in cells is unknown. In this work, a protein monomer-dimer equilibrium system was built with the allosteric effect on the binding characterized using NMR spectroscopy through mutations away from the dimer interface. A chemical shift linear fitting method was developed that enabled us to accurately determine the dissociation constant. A total of 28 allosteric mutations were prepared and grouped to negative allosteric, nonallosteric, and positive allosteric modulators. ∼ 50% of mutations displayed the allosteric-state changes when moving from a buffered solution into cells. For example, there were no positive allosteric modulators in the buffered solution but eight in cells. The change in protein allostery is correlated with the interactions between the protein and the cellular environment. These interactions presumably drive the surrounding macromolecules in cells to transiently bind to the monomer and dimer mutational sites and change the free energies of the two species differently which generate new allosteric effects. These surrounding macromolecules create a new protein allostery pathway that is only present in cells.

Transient interdomain interactions in free USP14 shape its conformational ensemble

The deubiquitinase (DUB) ubiquitin-specific protease 14 (USP14) is a dual domain protein that plays a regulatory role in proteasomal degradation and has been identified as a promising therapeutic target. USP14 comprises a conserved USP domain and a ubiquitin-like (Ubl) domain separated by a 25-residue linker. The enzyme activity of USP14 is autoinhibited in solution, but is enhanced when bound to the proteasome, where the Ubl and USP domains of USP14 bind to the Rpn1 and Rpt1/Rpt2 units, respectively. No structure of full-length USP14 in the absence of proteasome has yet been presented, however, earlier work has described how transient interactions between Ubl and USP domains in USP4 and USP7 regulate DUB activity. To better understand the roles of the Ubl and USP domains in USP14, we studied the Ubl domain alone and in full-length USP14 by nuclear magnetic resonance spectroscopy and used small angle x-ray scattering and molecular modeling to visualize the entire USP14 protein ensemble. Jointly, our results show how transient interdomain interactions between the Ubl and USP domains of USP14 predispose its conformational ensemble for proteasome binding, which may have functional implications for proteasome regulation and may be exploited in the design of future USP14 inhibitors.

Design and computational evaluation of a novel multi-epitope hybrid vaccine against monkeypox virus: Potential targets and immunogenicity assessment for pandemic preparedness

Monkeypox is a type of DNA-enveloped virus that belongs to the orthopoxvirus family, closely related to the smallpox virus. It can cause an infectious disease in humans known as monkeypox disease. Although there are multiple drugs and vaccines designed to combat orthopoxvirus infections, with a primary focus on smallpox, the recent spread of the monkeypox virus to over 50 countries have ignited a mounting global concern. This unchecked viral proliferation has raised apprehensions about the potential for a pandemic corresponding to the catastrophic impact of COVID-19. This investigation explored the structural proteins of monkeypox virus as potential candidates for designing a novel hybrid multi-epitope vaccine. The epitopes obtained from the selected proteins were screened to ensure their non-allergenicity, non-toxicity, and antigenicity to trigger T and B-cell responses. The interaction of the vaccine with toll-like receptor-3 (TLR-3) and major histocompatibility complexes (MHCs) was assessed using Cluspro 2.0. To establish the reliability of the docked complexes, a comprehensive evaluation was conducted using Immune and MD Simulations and Normal Mode Analysis. However, to validate the computational results of this study, additional in-vitro and in-vivo research is essential.

A molecular dynamics simulation study of glycine/serine octapeptides labeled with 2,3-diazabicyclo[2.2.2]oct-2-ene fluorophore

The compound 2,3-diazabicyclo[2.2.2]oct-2-ene (DBO) is a versatile fluorophore widely used in Förster resonance energy transfer (FRET) spectroscopy studies due to its remarkable sensitivity, enabling precise donor-acceptor distance measurements, even for short peptides. Integrating time-resolved and FRET spectroscopies with molecular dynamics simulations provides a robust approach to unravel the structure and dynamics of biopolymers in a solution. This study investigates the structural behavior of three octapeptide variants: Trp-(Gly-Ser)3-Dbo, Trp-(GlyGly)3-Dbo, and Trp-(SerSer)3-Dbo, where Dbo represents the DBO-containing modified aspartic acid, using molecular dynamics simulations. Glycine- and serine-rich amino acid fragments, common in flexible protein regions, play essential roles in functional properties. Results show excellent agreement between end-to-end distances, orientational factors from simulations, and the available experimental and theoretical data, validating the reliability of the GROMOS force field model. The end-to-end distribution, modeled using three Gaussian distributions, reveals a complex shape, confirmed by cluster analysis highlighting a limited number of significant conformations dominating the peptide landscape. All peptides predominantly adopt a disordered state in the solvent, yet exhibit a compact shape, aligning with the model of disordered polypeptide chains in poor solvents. Conformations show marginal dependence on chain composition, with Ser-only chains exhibiting slightly more elongation. This study enhances our understanding of peptide behavior, providing valuable insights into their structural dynamics in solution.

Identification of the Thermal Activation Network in Human 15-Lipoxygenase-2: Divergence from Plant Orthologs and Its Relationship to Hydrogen Tunneling Activation Barriers

The oxidation of polyunsaturated fatty acids by lipoxygenases (LOXs) is initiated by a C-H cleavage step in which the hydrogen atom is transferred quantum mechanically (i.e., via tunneling). In these reactions, protein thermal motions facilitate the conversion of ground-state enzyme-substrate complexes to tunneling-ready configurations and are thus important for transferring energy from the solvent to the active site for the activation of catalysis. In this report, we employed temperature-dependent hydrogen-deuterium exchange mass spectrometry (TDHDX-MS) to identify catalytically linked, thermally activated peptides in a representative animal LOX, human epithelial 15-LOX-2. TDHDX-MS of wild-type 15-LOX-2 was compared to two active site mutations that retain structural stability but have increased activation energies (Ea) of catalysis. The Ea value of one variant, V427L, is implicated to arise from suboptimal substrate positioning by increased active-site side chain rotamer dynamics, as determined by X-ray crystallography and ensemble refinement. The resolved thermal network from the comparative Eas of TDHDX-MS between wild-type and V426A is localized along the front face of the 15-LOX-2 catalytic domain. The network contains a clustering of isoleucine, leucine, and valine side chains within the helical peptides. This thermal network of 15-LOX-2 is different in location, area, and backbone structure compared to a model plant lipoxygenase from soybean that exhibits a low Ea value of catalysis compared to the human ortholog. The presented data provide insights into the divergence of thermally activated protein motions in plant and animal LOXs and their relationships to the enthalpic barriers for facilitating hydrogen tunneling.

N-Glycosylation as a Modulator of Protein Conformation and Assembly in Disease

Glycosylation, a prevalent post-translational modification, plays a pivotal role in regulating intricate cellular processes by covalently attaching glycans to macromolecules. Dysregulated glycosylation is linked to a spectrum of diseases, encompassing cancer, neurodegenerative disorders, congenital disorders, infections, and inflammation. This review delves into the intricate interplay between glycosylation and protein conformation, with a specific focus on the profound impact of N-glycans on the selection of distinct protein conformations characterized by distinct interactomes-namely, protein assemblies-under normal and pathological conditions across various diseases. We begin by examining the spike protein of the SARS virus, illustrating how N-glycans regulate the infectivity of pathogenic agents. Subsequently, we utilize the prion protein and the chaperone glucose-regulated protein 94 as examples, exploring instances where N-glycosylation transforms physiological protein structures into disease-associated forms. Unraveling these connections provides valuable insights into potential therapeutic avenues and a deeper comprehension of the molecular intricacies that underlie disease conditions. This exploration of glycosylation's influence on protein conformation effectively bridges the gap between the glycome and disease, offering a comprehensive perspective on the therapeutic implications of targeting conformational mutants and their pathologic assemblies in various diseases. The goal is to unravel the nuances of these post-translational modifications, shedding light on how they contribute to the intricate interplay between protein conformation, assembly, and disease.

Translational fusion of terpene synthases for metabolic engineering: Lessons learned and practical considerations

The step catalyzed by terpene synthases is a well-recognized and significant bottleneck in engineered terpenoid bioproduction. Consequently, substantial efforts have been devoted towards increasing metabolic flux catalyzed by terpene synthases, employing strategies such as gene overexpression and protein engineering. Notably, numerous studies have demonstrated remarkable titer improvements by applying translational fusion, typically by fusing the terpene synthase with a prenyl diphosphate synthase that catalyzes the preceding step in the pathway. The main appeal of the translational fusion approach lies in its simplicity and orthogonality to other metabolic engineering tools. However, there is currently limited understanding of the underlying mechanism of flux enhancement, owing to the unpredictable and often protein-specific effects of translational fusion. In this chapter, we discuss practical considerations when engineering translationally fused terpene synthases, drawing insights from our experience and existing literature. We also provide detailed experimental workflows and protocols based on our previous work in budding yeast (Saccharomyces cerevisiae). Our intention is to encourage further research into the translational fusion of terpene synthases, anticipating that this will contribute mechanistic insights not only into the activity, behavior, and regulation of terpene synthases, but also of other enzymes.

A comparative study of protein structure prediction tools for challenging targets: Snake venom toxins

Protein structure determination is a critical aspect of biological research, enabling us to understand protein function and potential applications. Recent advances in deep learning and artificial intelligence have led to the development of several protein structure prediction tools, such as AlphaFold2 and ColabFold. However, their performance has primarily been evaluated on well-characterised proteins and their ability to predict sturtctures of proteins lacking experimental structures, such as many snake venom toxins, has been less scrutinised. In this study, we evaluated three modelling tools on their prediction of over 1000 snake venom toxin structures for which no experimental structures exist. Our findings show that AlphaFold2 (AF2) performed the best across all assessed parameters. We also observed that ColabFold (CF) only scored slightly worse than AF2, while being computationally less intensive. All tools struggled with regions of intrinsic disorder, such as loops and propeptide regions, and performed well in predicting the structure of functional domains. Overall, our study highlights the importance of exercising caution when working with proteins with no experimental structures available, particularly those that are large and contain flexible regions. Nonetheless, leveraging computational structure prediction tools can provide valuable insights into the modelling of protein interactions with different targets and reveal potential binding sites, active sites, and conformational changes, as well as into the design of potential molecular binders for reagent, diagnostic, or therapeutic purposes.

Relation between flexibility and intrinsically disorder regions in thermosensitive TRP channels reveal allosteric effects

How a protein propagates the conformational changes throughout its structure remains largely unknown. In thermosensitive TRP channels, this allosteric communication is triggered by ligand interaction or in response to temperature changes. Because dynamic allostery suggests a dynamic role of disordered regions, in this work we set out to thoroughly evaluate these regions in six thermosensitive TRP channels. Thus, by contrasting the intrinsic flexibility of the transmembrane region as a function of the degree of disorder in those proteins, we discovered several residues that do not show a direct correlation in both parameters. This kind of structural discrepancy revealed residues that are either reported to be dynamic, functionally relevant or are involved in signal propagation and probably part of allosteric networks. These discrepant, potentially dynamic regions are not exclusive of TRP channels, as this same correlation was found in the Kv Shaker channel.

Oliveira AS, Mulholland AJ, Serapian SA, Colombo G. Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations

Protein functions are dynamically regulated by allostery, which enables conformational communication even between faraway residues, and expresses itself in many forms, akin to different "languages": allosteric control pathways predominating in an unperturbed protein are often unintuitively reshaped whenever biochemical perturbations arise (e.g., mutations). To accurately model allostery, unbiased molecular dynamics (MD) simulations require integration with a reliable method able to, e.g., detect incipient allosteric changes or likely perturbation pathways; this is because allostery can operate at longer time scales than those accessible by plain MD. Such methods are typically applied singularly, but we here argue their joint application─as a "multilingual" approach─could work significantly better. We successfully prove this through unbiased MD simulations (∼100 μs) of the widely studied, allosterically active oncotarget K-Ras4B, solvated and embedded in a phospholipid membrane, from which we decrypt allostery using four showcase "languages": Distance Fluctuation analysis and the Shortest Path Map capture allosteric hotspots at equilibrium; Anisotropic Thermal Diffusion and Dynamical Non-Equilibrium MD simulations assess perturbations upon, respectively, either superheating or hydrolyzing the GTP that oncogenically activates K-Ras4B. Chosen "languages" work synergistically, providing an articulate, mutually coherent, experimentally consistent picture of K-Ras4B allostery, whereby distinct traits emerge at equilibrium and upon GTP cleavage. At equilibrium, combined evidence confirms prominent allosteric communication from the membrane-embedded hypervariable region, through a hub comprising helix α5 and sheet β5, and up to the active site, encompassing allosteric "switches" I and II (marginally), and two proposed pockets. Upon GTP cleavage, allosteric perturbations mostly accumulate on the switches and documented interfaces.

Structure-directed bioengineering the lid1 of cold-adapted Pseudomonas sp. TB11 esterase to boost catalytic capacity

Structure-guided bioengineering enzymes has been an efficient strategy to obtain biocatalyst with desirable properties. In this study, the cold-adapted esterase from Pseudomonas sp. (CPE) was optimized through bioinformatic-based structured-guided bioengineering on lid1 region. Substitutions of non-conserved Q55 led to noticeable increase in hydrolysis without sacrificing enzyme thermostability, activating effects of Ca2+ and organic solvents. Compared to the wild type, both of Q55V and Q55N among the constructed variants exhibited about a 2.0-fold and 6.5-fold higher hydrolytic activity toward short-chain and long-chain substrates, respectively. In contrast, lid swapping with the lid of Thermomyces lanuginosus lipase reduced the activity and thermostability of CPE. Catalytic kinetics revealed that substitution of Q55 with Y, V, N and R enhanced the substrate affinity of CPE. Hydrolysis by Q55V remarkedly enriched the characteristic flavor components of single cream. The study sheds light on structure-guided bioengineering of lid tailoring cold-adapted esterases with desired catalytic performance to meet the demand from biotechnological applications.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of co-operativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semi-quantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different degrees of rescuability observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same non-inducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscore the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions, and therefore provide quantitative guidance to allostery modulation for therapeutic and engineering applications.

Ab Initio Prediction of 3-D Conformations for Protein Long Loops with High Accuracy and Applications to Antibody CDRH3 Modeling

Residue-level potentials of mean force were widely used for protein backbone refinements to avoid simultaneous sampling of side-chain conformations. The interaction energy between the reduced side chains and backbone atoms was not considered explicitly. In this study, we developed novel methods to calculate the residue-atom interaction energy in combination with atomic and residue-level terms. The parameters were optimized step by step to remove the overcounting or overlap problem between different energy terms. The mixing energy functions were then used to evaluate the generated backbone conformations at the initial sampling stage of protein loop modeling (OSCAR-loop), including the interaction energy between the reduced loop residues and full atoms of the protein framework. The accuracies of top-ranked decoys were 1.18 and 2.81 Å for 8-residue and 12-residue loops, respectively. We then selected diverse decoys for side-chain modeling, backbone refinement, and energy minimization. The procedure was repeated multiple times to select one prediction with the lowest energy. Consequently, we obtained an accuracy of 0.74 Å for a prevailing test set of 12-residue loops, compared with >1.4 Å reported by other researchers. The OSCAR-loop was also effective for modeling the H3 loops of antibody complementary determining regions (CDRs) in the crystal environment. The prediction accuracy of OSCAR-loop (1.74 Å) was better than the accuracy of the Rosetta NGK method (3.11 Å) or those achieved by deep learning methods (>2.2 Å) for the CDRH3 loops of 49 targets in the Rosetta antibody benchmark. The performance of OSCAR-loop in a model environment was also discussed.

Motif-VI Loop Acts as a Nucleotide Valve in the West Nile Virus NS3 Helicase

The flavivirus NS3 helicase (NS3h), a highly conserved protein, plays a pivotal role in virus replication and thus represents a potential drug target for flavivirus pathogenesis. NS3h utilizes nucleotide triphosphate, such as ATP, for hydrolysis energy (ATPase) to translocate on single-stranded nucleic acids, which is an important step in the unwinding of double-stranded nucleic acids. The intermediate states along the ATP binding and hydrolysis cycle, as well as the conformational changes between these states, represent important yet difficult-to-identify targets for potential inhibitors. We use extensive molecular dynamics simulations of apo, ATP, ADP+Pi, and ADP bound to WNV NS3h+ssRNA to model the conformational ensembles along this cycle. Energetic and structural clustering analyses on these trajectories depict a clear trend of differential enthalpic affinity of NS3h with ADP, demonstrating a probable mechanism of hydrolysis turnover regulated by the motif-VI loop (MVIL). These findings were experimentally corroborated using viral replicons encoding three mutations at the D471 position. Replication assays using these mutants demonstrated a substantial reduction in viral replication compared to the wild-type. Molecular simulations of the D471 mutants in the apo state indicate a shift in MVIL populations favoring either a closed or open 'valve' conformation, affecting ATP entry or stabilization, respectively. Combining our molecular modeling with experimental evidence highlights a conformation-dependent role for MVIL as a 'valve' for the ATP-pocket, presenting a promising target for antiviral development.