Functional protein dynamics in a crystal.

Proteins are molecular machines and to understand how they work, we need to understand how they move. New pump-probe time-resolved X-ray diffraction methods open up ways to initiate and observe protein motions with atomistic detail in crystals on biologically relevant timescales. However, practical limitations of these experiments demands parallel development of effective molecular dynamics approaches to accelerate progress and extract meaning. Here, we establish robust and accurate methods for simulating dynamics in protein crystals, a nontrivial process requiring careful attention to equilibration, environmental composition, and choice of force fields. With more than seven milliseconds of sampling of a single chain, we identify critical factors controlling agreement between simulation and experiments and show that simulated motions recapitulate ligand-induced conformational changes. This work enables a virtuous cycle between simulation and experiments for visualizing and understanding the basic functional motions of proteins.

Thermodynamic and molecular dynamic insights into how fusion influences peptide-tag recognition of an antibody.

To understand the effect of protein fusion on the recognition of a peptide-tag by an antibody, we fused a CCR5-derived peptide-tag (pep1) to GFP and investigated its recognition by an anti-pep1 antibody, 4B08. First, to characterize the thermodynamic properties associated with the pep1-4B08 binding, isothermal titration calorimetry experiments were conducted. It was found that pep1 fused to the C-terminus of GFP (GFP-CT) enhanced the enthalpic gain by 2.1 kcal mol-1 and the entropic loss only by 0.9 kcal mol-1, resulting in an 8-fold increase in the binding affinity compared to the unfused pep1. On the other hand, pep1 fused to the N-terminus of GFP (GFP-NT) enhanced the enthalpic gain by 3.0 kcal mol-1 and the entropic loss by 3.2 kcal mol-1, leading to no significant enhancement of the binding affinity. To gain deeper insights, molecular dynamics simulations of GFP-NT, GFP-CT, and pep1 were performed. The results showed that the location of the fusion point sensitively affects the interaction energy, the solvent accessible surface area, and the fluctuation of pep1 in the unbound state, which explains the difference in the experimental thermodynamic properties.

Identification of small molecule inhibitors against Lin28/let-7 to suppress tumor progression and its alleviation role in LIN28-dependent glucose metabolism.

The reciprocal suppression of an RNA-binding protein LIN28 (human abnormal cell lineage 28) and miRNA Let-7 (Lethal 7) is considered to have a prime role in hepatocellular carcinoma (HCC). Though targeting this inhibition interaction is effective for therapeutics, it causes other unfavorable effects on glucose metabolism and increased insulin resistance. Hence, this study aims to identify small molecules targeting Lin28/let-7 interaction along with additional potency to improve insulin sensitivity. Of 22,14,996 small molecules screened by high throughput virtual screening, 6 molecules, namely 41354, 1558, 12437, 23837, 15710, and 8319 were able to block the LIN28 interaction with let-7 and increase the insulin sensitivity via interacting with PPARγ (peroxisome proliferator-activated receptors γ). MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) analysis is used to re-score the binding affinity of docked complexes. Upon further analysis, it is also seen that these molecules have superior ADME (Absorption, Distribution, Metabolism, and Excretion) properties and form stable complexes with the targets for a significant period in a biologically simulated environment (Molecular Dynamics simulation) for 100 ns. From our results, we hypothesize that these identified 6 small molecules can be potential candidates for HCC treatment and the glucose metabolic disorder caused by the HCC treatment.

Functional expression, purification, biochemical and biophysical characterizations, and molecular dynamics simulation of a histidine acid phosphatase from Saccharomyces cerevisiae.

A histidine acid phosphatase (HAP) (PhySc) with 99.50% protein sequence similarity with PHO5 from Saccharomyces cerevisiae was expressed functionally with the molecular mass of ∼110 kDa through co-expression along with the set of molecular chaperones dnaK, dnaJ, GroESL. The purified HAP illustrated the optimum activity of 28.75 ± 0.39 U/mg at pH 5.5 and 40 ˚C. The Km and Kcat values towards calcium phytate were 0.608 ± 0.09 mM and 650.89 ± 3.6 s- 1. The half-lives (T1/2) at 55 and 60 ˚C were 2.75 min and 55 s, respectively. The circular dichroism (CD) demonstrated that PhySc includes 30.5, 28.1, 21.3, and 20.1% of random coils, α-Helix, ß-Turns, and ß-Sheet, respectively. The Tm recorded by CD for PhySc was 56.5 ± 0.34˚C. The molecular docking illustrated that His59 and Asp322 act as catalytic residues in the PhySc. MD simulation showed that PhySc at 40 ˚C has higher structural stability over those of the temperatures 60 and 80 ˚C that support the thermodynamic in vitro investigations. Secondary structure content results obtained from MD simulation indicated that PhySc consists of 34.03, 33.09, 17.5, 12.31, and 3.05% of coil, helix, turn, sheet, and helix310, respectively, which is almost consistent with the experimental results.

Molecular dynamics in multidimensional space explains how mutations affect the association path of neomycin to a riboswitch.

Riboswitches are messenger RNA (mRNA) fragments binding specific small molecules to regulate gene expression. A synthetic N1 riboswitch, inserted into yeast mRNA controls the translation of a reporter gene in response to neomycin. However, its regulatory activity is sensitive to single-point RNA mutations, even those distant from the neomycin binding site. While the association paths of neomycin to N1 and its variants remain unknown, recent fluorescence kinetic experiments indicate a two-step process driven by conformational selection. This raises the question of which step is affected by mutations. To address this, we performed all-atom two-dimensional replica-exchange molecular dynamics simulations for N1 and U14C, U14C[Formula: see text], U15A, and A17G mutants, ensuring extensive conformational sampling of both RNA and neomycin. The obtained neomycin association and binding paths, along with multidimensional free-energy profiles, revealed a two-step binding mechanism, consisting of conformational selection and induced fit. Neomycin binds to a preformed N1 conformation upon identifying a stable upper stem and U-turn motif in the riboswitch hairpin. However, the positioning of neomycin in the binding site occurs at different RNA-neomycin distances for each mutant, which may explain their different regulatory activities. The subsequent induced fit arises from the interactions of the neomycin's N3 amino group with RNA, causing the G9 backbone to rearrange. In the A17G mutant, the critical C6-A17/G17 stacking forms at a closer RNA-neomycin distance compared to N1. These findings together with estimated binding free energies coincide with experiments and elucidate why the A17G mutation decreases and U15A enhances N1 activity in response to neomycin.

Identifying Residues for Substrate Recognition in Human GPAT4 by Molecular Dynamics Simulations.

Glycerol-3-phosphate acyltransferase (GPAT) catalyzes the first step in triacylglycerol synthesis. Understanding its substrate recognition mechanism may help to design drugs to regulate the production of glycerol lipids in cells. In this work, we investigate how the native substrate, glycerol-3-phosphate (G3P), and palmitoyl-coenzyme A (CoA) bind to the human GPAT isoform GPAT4 via molecular dynamics simulations (MD). As no experimentally resolved GPAT4 structure is available, the AlphaFold model is employed to construct the GPAT4-substrate complex model. Using another isoform, GPAT1, we demonstrate that once the ligand binding is properly addressed, the AlphaFold complex model can deliver similar results to the experimentally resolved structure in MD simulations. Following the validated protocol of complex construction, we perform MD simulations using the GPAT4-substrate complex. Our simulations reveal that R427 is an important residue in recognizing G3P via a stable salt bridge, but its motion can bring the ligand to different binding hotspots on GPAT4. Such high flexibility can be attributed to the flexible region that exists only on GPAT4 and not on GPAT1. Our study reveals the substrate recognition mechanism of GPAT4 and hence paves the way towards designing GPAT4 inhibitors.

Revealing the Interaction Mechanism between Mycobacterium tuberculosis GyrB and Novobiocin, SPR719 through Binding Thermodynamics and Dissociation Kinetics Analysis.

With the rapid emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb), various levels of resistance against existing anti-tuberculosis (TB) drugs have developed. Consequently, the identification of new anti-TB targets and drugs is critically urgent. DNA gyrase subunit B (GyrB) has been identified as a potential anti-TB target, with novobiocin and SPR719 proposed as inhibitors targeting GyrB. Therefore, elucidating the molecular interactions between GyrB and its inhibitors is crucial for the discovery and design of efficient GyrB inhibitors for combating multidrug-resistant TB. In this study, we revealed the detailed binding mechanisms and dissociation processes of the representative inhibitors, novobiocin and SPR719, with GyrB using classical molecular dynamics (MD) simulations, tau-random acceleration molecular dynamics (τ-RAMD) simulations, and steered molecular dynamics (SMD) simulations. Our simulation results demonstrate that both electrostatic and van der Waals interactions contribute favorably to the inhibitors' binding to GyrB, with Asn52, Asp79, Arg82, Lys108, Tyr114, and Arg141 being key residues for the inhibitors' attachment to GyrB. The τ-RAMD simulations indicate that the inhibitors primarily dissociate from the ATP channel. The SMD simulation results reveal that both inhibitors follow a similar dissociation mechanism, requiring the overcoming of hydrophobic interactions and hydrogen bonding interactions formed with the ATP active site. The binding and dissociation mechanisms of GyrB with inhibitors novobiocin and SPR719 obtained in our work will provide new insights for the development of promising GyrB inhibitors.

Mulberry Leaf Compounds and Gut Microbiota in Alzheimer's Disease and Diabetes: A Study Using Network Pharmacology, Molecular Dynamics Simulation, and Cellular Assays.

Recently, studies have reported a correlation that individuals with diabetes show an increased risk of developing Alzheimer's disease (AD). Mulberry leaves, serving as both a traditional medicinal herb and a food source, exhibit significant hypoglycemic and antioxidative properties. The flavonoid compounds in mulberry leaf offer therapeutic effects for relieving diabetic symptoms and providing neuroprotection. However, the mechanisms of this effect have not been fully elucidated. This investigation aimed to investigate the combined effects of specific mulberry leaf flavonoids (kaempferol, quercetin, rhamnocitrin, tetramethoxyluteolin, and norartocarpetin) on both type 2 diabetes mellitus (T2DM) and AD. Additionally, the role of the gut microbiota in these two diseases' treatment was studied. Using network pharmacology, we investigated the potential mechanisms of flavonoids in mulberry leaves, combined with gut microbiota, in combating AD and T2DM. In addition, we identified protein tyrosine phosphatase 1B (PTP1B) as a key target for kaempferol in these two diseases. Molecular docking and molecular dynamics simulations showed that kaempferol has the potential to inhibit PTP1B for indirect treatment of AD, which was proven by measuring the IC50 of kaempferol (279.23 µM). The cell experiment also confirmed the dose-dependent effect of kaempferol on the phosphorylation of total cellular protein in HepG2 cells. This research supports the concept of food-medicine homology and broadens the range of medical treatments for diabetes and AD, highlighting the prospect of integrating traditional herbal remedies with modern medical research.

An Ensemble Docking Approach for Analyzing and Designing Aptamer Heterodimers Targeting VEGF165.

Vascular endothelial growth factor 165 (VEGF165) is a prominent isoform of the VEGF-A protein that plays a crucial role in various angiogenesis-related diseases. It is homodimeric, and each of its monomers is composed of two domains connected by a flexible linker. DNA aptamers, which have emerged as potent therapeutic molecules for many proteins with high specificity and affinity, can also work for VEGF165. A DNA aptamer heterodimer composed of monomers of V7t1 and del5-1 connected by a flexible linker (V7t1:del5-1) exhibits a greater binding affinity with VEGF165 compared to either of the two monomers alone. Although the structure of the complex formed between the aptamer heterodimer and VEGF165 is unknown due to the highly flexible linkers, gaining structural information will still be valuable for future developments. Toward this end of accessing structural information, we adopt an ensemble docking approach here. We first obtain an ensemble of structures for both VEGF165 and the aptamer heterodimer by considering both small- and large-scale motions. We then proceed through an extraction process based on ensemble docking, molecular dynamics simulations, and binding free energy calculations to predict the structures of the VEGF165/V7t1:del5-1 complex. Through the same procedures, we reach a new aptamer heterodimer that bears a locked nucleic acid-modified counterpart of V7t1, namely RNV66:del5-1, which also binds well with VEGF165. We apply the same protocol to the monomeric units V7t1, RNV66, and del5-1 to target VEGF165. We observe that V7t1:del5-1 and RNV66:del5-1 show higher binding affinities with VEGF165 than any of the monomers, consistent with experiments that support the notion that aptamer heterodimers are more effective anti-VEGF165 aptamers than monomeric aptamers. Among the five different aptamers studied here, the newly designed RNV66:del5-1 shows the highest binding affinity with VEGF165. We expect that our ensemble docking approach can help in de novo designs of homo/heterodimeric anti-angiogenic drugs to target the homodimeric VEGF165.

Discovery of a novel SHP2 allosteric inhibitor using virtual screening, FMO calculation, and molecular dynamic simulation.

CONTEXT: SHP2 is a non-receptor protein tyrosine phosphatase to remove tyrosine phosphorylation. Functionally, SHP2 is an essential bridge to connect numerous oncogenic cell-signaling cascades including RAS-ERK, PI3K-AKT, JAK-STAT, and PD-1/PD-L1 pathways. This study aims to discover novel and potent SHP2 inhibitors using a hierarchical structure-based virtual screening strategy that combines molecular docking and the fragment molecular orbital method (FMO) for calculating binding affinity (referred to as the Dock-FMO protocol). For the SHP2 target, the FMO method prediction has a high correlation between the binding affinity of the protein-ligand interaction and experimental values (R2 = 0.55), demonstrating a significant advantage over the MM/PBSA (R2 = 0.02) and MM/GBSA (R2 = 0.15) methods. Therefore, we employed Dock-FMO virtual screening of ChemDiv database of ∼2,990,000 compounds to identify a novel SHP2 allosteric inhibitor bearing hydroxyimino acetamide scaffold. Experimental validation demonstrated that the new compound (E)-2-(hydroxyimino)-2-phenyl-N-(piperidin-4-ylmethyl)acetamide (7188-0011) effectively inhibited SHP2 in a dose-dependent manner. Molecular dynamics (MD) simulation analysis revealed the binding stability of compound 7188-0011 and the SHP2 protein, along with the key interacting residues in the allosteric binding site. Overall, our work has identified a novel and promising allosteric inhibitor that targets SHP2, providing a new starting point for further optimization to develop more potent inhibitors. METHODS: All the molecular docking studies were employed to identify potential leads with Maestro v10.1. The protein-ligand binding affinities of potential leads were further predicted by FMO calculations at MP2/6-31G* level using GAMESS v2020 system. MD simulations were carried out with AmberTools18 by applying the FF14SB force field. MD trajectories were analyzed using VMD v1.9.3. MM/GB(PB)SA binding free energy analysis was carried out with the mmpbsa.py tool of AmberTools18. The docking and MD simulation results were visualized through PyMOL v2.5.0.

Molecular dynamic investigation for Roco4 kinase inhibitor as treatment options for parkinsonism.

CONTEXT: Parkinson's disease is a neurodegenerative condition characterized by the degeneration of dopaminergic neurons, resulting in motor disabilities such as rigidity, bradykinesia, postural instability, and resting tremors. While the exact cause of Parkinson's remains uncertain, both familial and sporadic forms are often associated with the G2019S mutation found in the kinase domain of LRRK2. Roco4 is an analogue of LRRK2 protein in Dictyostelium discoideum which is an established model organism to investigate LRRK2 inhibitors. In this study, the potential treatment of Parkinson's was explored by inhibiting the activity of the mutated LRRK2 protein using Roco4 as the base protein structure. Mongolicain-A and Bacoside-A exhibited significant selectivity towards the G2019S mutation, displaying a binding affinity of - 12.3 Kcal/mol and - 11.4 Kcal/mol respectively. Mongolicain-A demonstrated increased specificity towards Roco4, while Bacoside-A demonstrated significant binding affinity to all 34 kinases proteins alike. The Molecular Dynamics Studies (MDS) results strongly suggests that Mongolicain-A is a significant inhibitor of Roco4 kinase. ADMET and drugability analysis also suggests that among the two best ligands, Mongolicain-A demonstrates significant physicochemical properties to be suitable for best drug like molecule. Based on the in-silico molecular docking, molecular dynamic simulation, ADMET and drugability analyses, it is strongly suggested that, Mongolicain-A could be a potential candidate for treatment and management of Parkinson's disease via inhibition of LRRK2 protein. Further in-vitro and in-vivo investigations are in demand to validate these findings. METHODS: To identify potential inhibitors, 3069 phytochemicals were screened using molecular docking via AutoDock Vina. Molecular Dynamics Simulation was carried out using GROMACS 2022.2 for a duration of 100ns per complex to study the stability and inhibition potential of the protein ligand complexes. ADMET analysis was carriedout using Molinspiration and preADMET web tool.

Molecular dynamics simulation of the effect of temperature on the conformation of ubiquitin protein.

CONTENT: Ubiquitin, a ubiquitous small protein found in all living organisms, is crucial for tagging proteins earmarked for degradation and holds pivotal importance in biomedicine. Protein functionality is intricately linked to its structure. To comprehend the impact of diverse temperatures on ubiquitin protein structure, our study delved into the energy landscape, hydrogen bonding, and overall structural stability of ubiquitin protein at varying temperatures. Through meticulous analysis of root mean square deviation and root mean square fluctuation, we validated the robustness of the simulation conditions employed. Within our simulated system, the bonding energy and electrostatic potential energy exhibited linear augmentation, while the van der Waals energy demonstrated a linear decline. Additionally, our findings highlighted that the α-Helix secondary structure of the ubiquitin protein gradually transitions toward helix destabilization under high-temperature conditions. The secondary structure of ubiquitin protein experiences distinct changes under varying temperatures. The outcomes of our molecular simulations offer a theoretical framework that enhances our comprehension of how temperature impacts the structural stability of ubiquitin protein. These insights contribute not only to a deeper understanding of iniquity's behavior but also hold broader implications in the realm of biomedicine and beyond. METHODS: All the MD simulations were performed using the GROMACS software with GROMOS96 force field and SPC for water. The ubiquitin protein was put in the center of a cubic box with a length of 8 nm, a setting that allowed > 0.8 nm in the minimal distance between the protein surface and the box wall. To remove the possible coordinate collision of the configurations, in the beginning, the steepest descent method was used until the maximum force between atoms was under 100 kJ/mol·nm with a 0.01 nm step size. Minimization was followed by 30 ps of position-restrained MD simulation. The protein was restrained to its initial position, and the solvent was freely equilibrated. The product phase was obtained with the whole system simulated for 10 ns without any restraint using an integral time step of 1 fs with different temperatures. The cutoff for short-range electronic interaction was set to 1.5 nm. The long-range interactions were treated with a particle-mesh Ewald (PME) method with a grid width of 1.2 nm.

SARS-CoV-2 Omicron Subvariants Do Not Differ Much in Binding Affinity to Human ACE2: A Molecular Dynamics Study.

The emergence of the variant of concern Omicron (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exacerbates the COVID-19 pandemic due to its high contagious ability. Studies have shown that the Omicron binds human ACE2 more strongly than the wild type. The prevalence of Omicron in new cases of COVID-19 promotes novel lineages with improved receptor binding affinity and immune evasion. To shed light on this open problem, in this work, we investigated the binding free energy of the receptor binding domain of the Omicron lineages BA.2, BA.2.3.20, BA.3, BA4/BA5, BA.2.75, BA.2.75.2, BA.4.6, XBB.1, XBB.1.5, BJ.1, BN.1, BQ.1.1, and CH.1.1 to human ACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. The results show that these lineages have increased binding affinity compared to the BA.1 lineage, and BA.2.75 and BA.2.75.2 subvariants bind ACE2 more strongly than others. However, in general, the binding affinities of the Omicron lineages do not differ significantly from each other. The electrostatic force dominates over the van der Waals force in the interaction between Omicron lineages and human cells. Based on our results, we argue that viral evolution does not further improve the affinity of SARS-CoV-2 for ACE2 but may increase immune evasion.

Photophysics of a nucleic acid-protein crosslinking model strongly depends on solvation dynamics: an experimental and theoretical study.

We present a combined experimental and theoretical study of the photophysics of 5-benzyluracil (5BU) in methanol, which is a model system for interactions between nucleic acids and proteins. A molecular dynamics study of 5BU in solution through efficient DFT-based hybrid ab initio potentials revealed a remarkable conformational flexibility - allowing the population of two main conformers - as well as specific solute-solvent interactions, which both appear as relevant factors for the observed 5BU optical absorption properties. The simulated absorption spectrum, calculated on such an ensemble, enabled a molecular interpretation of the experimental UV-Vis lowest energy band, which is also involved in the induced photo-reactivity upon irradiation. In particular, the first two excited states (mainly involving the uracil moiety) both contribute to the 5BU lowest energy absorption. Moreover, as a key finding, the nature and brightness of such electronic transitions are strongly influenced by 5BU conformation and the microsolvation of its heteroatoms.

How ATP suppresses the fibrillation of amyloid peptides: analysis of the free-energy contributions.

Recent experiments have revealed that adenosine triphosphate (ATP) suppresses the fibrillation of amyloid peptides - a process closely linked to neurodegenerative diseases such as Alzheimer's and Parkinson's. Apart from the adsorption of ATP onto amyloid peptides, the molecular understanding is still limited, leaving the underlying mechanism for the fibrillation suppression by ATP largely unclear, especially in regards to the molecular energetics. Here we provide an explanation at the molecular scale by quantifying the free energies using all-atom molecular dynamics simulations. We found that the changes of the free energies due to the addition of ATP lead to a significant equilibrium shift towards monomeric peptides in agreement with experiments. Despite ATP being a highly charged species, the decomposition of the free energies reveals that the van der Waals interactions with the peptide are decisive in determining the relative stabilization of the monomeric state. While the phosphate moiety exhibits strong electrostatic interactions, the compensation by the water solvent results in a minor, overall Coulomb contribution. Our quantitative analysis of the free energies identifies which intermolecular interactions are responsible for the suppression of the amyloid fibril formation by ATP and offers a promising method to analyze the roles of similarly complex cosolvents in aggregation processes.

De novo design of drug-binding proteins with predictable binding energy and specificity.

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule-binding proteins with tuned interaction energies is feasible entirely from computation.

A combination of virtual screening, molecular dynamics simulation, MM/PBSA, ADMET, and DFT calculations to identify a potential DPP4 inhibitor.

DPP4 inhibitors can control glucose homeostasis by increasing the level of GLP-1 incretins hormone due to dipeptidase mimicking. Despite the potent effects of DPP4 inhibitors, these compounds cause unwanted toxicity attributable to their effect on other enzymes. As a result, it seems essential to find novel and DPP4 selective compounds. In this study, we introduce a potent and selective DPP4 inhibitor via structure-based virtual screening, molecular docking, molecular dynamics simulation, MM/PBSA calculations, DFT analysis, and ADMET profile. The screened compounds based on similarity with FDA-approved DPP4 inhibitors were docked towards the DPP4 enzyme. The compound with the highest docking score, ZINC000003015356, was selected. For further considerations, molecular docking studies were performed on selected ligands and FDA-approved drugs for DPP8 and DPP9 enzymes. Molecular dynamics simulation was run during 200 ns and the analysis of RMSD, RMSF, Rg, PCA, and hydrogen bonding were performed. The MD outputs showed stability of the ligand-protein complex compared to available drugs in the market. The total free binding energy obtained for the proposed DPP4 inhibitor was more negative than its co-crystal ligand (N7F). ZINC000003015356 confirmed the role of the five Lipinski rule and also, have low toxicity parameter according to properties. Finally, DFT calculations indicated that this compound is sufficiently soft.

Long-range electron proton coupling in respiratory complex I - insights from molecular simulations of the quinone chamber and antiporter-like subunits.

Respiratory complex I is a redox-driven proton pump. Several high-resolution structures of complex I have been determined providing important information about the putative proton transfer paths and conformational transitions that may occur during catalysis. However, how redox energy is coupled to the pumping of protons remains unclear. In this article, we review biochemical, structural and molecular simulation data on complex I and discuss several coupling models, including the key unresolved mechanistic questions. Focusing both on the quinone-reductase domain as well as the proton-pumping membrane-bound domain of complex I, we discuss a molecular mechanism of proton pumping that satisfies most experimental and theoretical constraints. We suggest that protonation reactions play an important role not only in catalysis, but also in the physiologically-relevant active/deactive transition of complex I.

Multilevel superposition for deciphering the conformational variability of protein ensembles.

The dynamics and variability of protein conformations are directly linked to their functions. Many comparative studies of X-ray protein structures have been conducted to elucidate the relevant conformational changes, dynamics and heterogeneity. The rapid increase in the number of experimentally determined structures has made comparison an effective tool for investigating protein structures. For example, it is now possible to compare structural ensembles formed by enzyme species, variants or the type of ligands bound to them. In this study, the author developed a multilevel model for estimating two covariance matrices that represent inter- and intra-ensemble variability in the Cartesian coordinate space. Principal component analysis using the two estimated covariance matrices identified the inter-/intra-enzyme variabilities, which seemed to be important for the enzyme functions, with the illustrative examples of cytochrome P450 family 2 enzymes and class A $\beta$-lactamases. In P450, in which each enzyme has its own active site of a distinct size, an active-site motion shared universally between the enzymes was captured as the first principal mode of the intra-enzyme covariance matrix. In this case, the method was useful for understanding the conformational variability after adjusting for the differences between enzyme sizes. The developed method is advantageous in small ensemble-size problems and hence promising for use in comparative studies on experimentally determined structures where ensemble sizes are smaller than those generated, for example, by molecular dynamics simulations.

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.