Determination of the Protein-Protein Interactions within Acyl Carrier Protein (MmcB)-Dependent Modifications in the Biosynthesis of Mitomycin

Mitomycin has a unique chemical structure and contains densely assembled functionalities with extraordinary antitumor activity. The previously proposed mitomycin C biosynthetic pathway has caused great attention to decipher the enzymatic mechanisms for assembling the pharmaceutically unprecedented chemical scaffold. Herein, we focused on the determination of acyl carrier protein (ACP)-dependent modification steps and identification of the protein–protein interactions between MmcB (ACP) with the partners in the early-stage biosynthesis of mitomycin C. Based on the initial genetic manipulation consisting of gene disruption and complementation experiments, genes mitE, mmcB, mitB, and mitF were identified as the essential functional genes in the mitomycin C biosynthesis, respectively. Further integration of biochemical analysis elucidated that MitE catalyzed CoA ligation of 3-amino-5-hydroxy-bezonic acid (AHBA), MmcB-tethered AHBA triggered the biosynthesis of mitomycin C, and both MitB and MitF were MmcB-dependent tailoring enzymes involved in the assembly of mitosane. Aiming at understanding the poorly characterized protein–protein interactions, the in vitro pull-down assay was carried out by monitoring MmcB individually with MitB and MitF. The observed results displayed the clear interactions between MmcB and MitB and MitF. The surface plasmon resonance (SPR) biosensor analysis further confirmed the protein–protein interactions of MmcB with MitB and MitF, respectively. Taken together, the current genetic and biochemical analysis will facilitate the investigations of the unusual enzymatic mechanisms for the structurally unique compound assembly and inspire attempts to modify the chemical scaffold of mitomycin family antibiotics.     

Quantitative FRET (qFRET) Technology for the Determination of Protein–Protein Interaction Affinity in Solution

Protein–protein interactions play pivotal roles in life, and the protein interaction affinity confers specific protein interaction events in physiology or pathology. Förster resonance energy transfer (FRET) has been widely used in biological and biomedical research to detect molecular interactions in vitro and in vivo. The FRET assay provides very high sensitivity and efficiency. Several attempts have been made to develop the FRET assay into a quantitative measurement for protein–protein interaction affinity in the past. However, the progress has been slow due to complicated procedures or because of challenges in differentiating the FRET signal from other direct emission signals from donor and receptor. This review focuses on recent developments of the quantitative FRET analysis and its application in the determination of protein–protein interaction affinity (K_D), either through FRET acceptor emission or donor quenching methods. This paper mainly reviews novel theatrical developments and experimental procedures rather than specific experimental results. The FRET-based approach for protein interaction affinity determination provides several advantages, including high sensitivity, high accuracy, low cost, and high-throughput assay. The FRET-based methodology holds excellent potential for those difficult-to-be expressed proteins and for protein interactions in living cells.     

MolADI: A Web Server for Automatic Analysis of Protein–Small Molecule Dynamic Interactions

Protein–ligand interaction analysis is important for drug discovery and rational protein design. The existing online tools adopt only a single conformation of the complex structure for calculating and displaying the interactions, whereas both protein residues and ligand molecules are flexible to some extent. The interactions evolved with time in the trajectories are of greater interest. MolADI is a user-friendly online tool which analyzes the protein–ligand interactions in detail for either a single structure or a trajectory. Interactions can be viewed easily with both 2D graphs and 3D representations. MolADI is available as a web application.     

The Structural and Dynamical Properties of the Hydration of SNase Based on a Molecular Dynamics Simulation

The dynamics of protein–water fluctuations are of biological significance. Molecular dynamics simulations were performed in order to explore the hydration dynamics of staphylococcal nuclease (SNase) at different temperatures and mutation levels. A dynamical transition in hydration water (at ~210 K) can trigger larger-amplitude fluctuations of protein. The protein–water hydrogen bonds lost about 40% in the total change from 150 K to 210 K, while the Mean Square Displacement increased by little. The protein was activated when the hydration water in local had a comparable trend in making hydrogen bonds with protein– and other waters. The mutations changed the local chemical properties and the hydration exhibited a biphasic distribution, with two time scales. Hydrogen bonding relaxation governed the local protein fluctuations on the picosecond time scale, with the fastest time (24.9 ps) at the hydrophobic site and slowest time (40.4 ps) in the charged environment. The protein dynamic was related to the water’s translational diffusion via the relaxation of the protein–water’s H-bonding. The structural and dynamical properties of protein–water at the molecular level are fundamental to the physiological and functional mechanisms of SNase.     

Atomistic Simulation of Lysozyme in Solutions Crowded by Tetraethylene Glycol: Force Field Dependence

The behavior of biomolecules in crowded environments remains largely unknown due to the accuracy of simulation models and the limited experimental data for comparison. Here we chose a small crowder of tetraethylene glycol (PEG-4) to investigate the self-crowding of PEG-4 solutions and molecular crowding effects on the structure and diffusion of lysozyme at varied concentrations from dilute water to pure PEG-4 liquid. Two Amber-like force fields of Amber14SB and a99SB-disp were examined with TIP3P (fast diffusivity and low viscosity) and a99SB-disp (slow diffusivity and high viscosity) water models, respectively. Compared to the Amber14SB protein simulations, the a99SB-disp model yields more coordinated water and less PEG-4 molecules, less intramolecular hydrogen bonds (HBs), more protein–water HBs, and less protein–PEG HBs as well as stronger interactions and more hydrophilic and less hydrophobic contacts with solvent molecules. The a99SB-disp model offers comparable protein–solvent interactions in concentrated PEG-4 solutions to that in pure water. The PEG-4 crowding leads to a slow-down in the diffusivity of water, PEG-4, and protein, and the decline in the diffusion from atomistic simulations is close to or faster than the hard sphere model that neglects attractive interactions. Despite these differences, the overall structure of lysozyme appears to be maintained well at different PEG-4 concentrations for both force fields, except a slightly large deviation at 370 K at low concentrations with the a99SB-disp model. This is mainly attributed to the strong intramolecular interactions of the protein in the Amber14SB force field and to the large viscosity of the a99SB-disp water model. The results indicate that the protein force fields and the viscosity of crowder solutions affect the simulation of biomolecules under crowding conditions.     

Combining Molecular Dynamic Information and an Aspherical-Atom Data Bank in the Evaluation of the Electrostatic Interaction Energy in Multimeric Protein-Ligand Complex: A Case Study for HIV-1 Protease

Computational analysis of protein–ligand interactions is of crucial importance for drug discovery. Assessment of ligand binding energy allows us to have a glimpse of the potential of a small organic molecule to be a ligand to the binding site of a protein target. Available scoring functions, such as in docking programs, all rely on equations that sum each type of protein–ligand interactions in order to predict the binding affinity. Most of the scoring functions consider electrostatic interactions involving the protein and the ligand. Electrostatic interactions constitute one of the most important part of total interactions between macromolecules. Unlike dispersion forces, they are highly directional and therefore dominate the nature of molecular packing in crystals and in biological complexes and contribute significantly to differences in inhibition strength among related enzyme inhibitors. In this study, complexes of HIV-1 protease with inhibitor molecules (JE-2147 and darunavir) were analyzed by using charge densities from the transferable aspherical-atom University at Buffalo Databank (UBDB). Moreover, we analyzed the electrostatic interaction energy for an ensemble of structures, using molecular dynamic simulations to highlight the main features of electrostatic interactions important for binding affinity.     

The Consistency Factor and the Viscosity Exponent of Soybean-Protein-Isolate/Wheat-Gluten/Corn-Starch Blends by Using a Capillary Rheometry

Blends with different proportions of protein or starch show different rheological behaviors, which may be related to the fibrous structure formation of extruded textured plant proteins. The consistency factor K and the viscosity exponent n of soybean–protein–isolate (SPI)/wheat–gluten (WG)/corn–starch (CS) blends were investigated through capillary rheometry. All blends exhibited shear-thinning behavior at 80 °C and 50% moisture. The CS content in SPI/CS blends or WG content in SPI/WG blends showed a positive relation to the viscosity exponent n and a negative relation to the consistency factor K. However, there was no correlation between the CS content in WG/CS blends and n or K. The coefficient of determination of the linear relationship between K and mass fraction in SPI/CS, SPI/WG/CS, SPI/WG and WG/CS decreased from 0.872 to 0.073. SPI was more likely to form a non-interactive structure, while wheat-gluten was more likely to form a highly interactive structure. It turned out that the materials with globular morphology, such as soybean-protein-isolate and corn-starch, are likely to form a non-interactive structure.     

Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking

One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures.     

Mechanistic Insight into Binding of Huperzine A with Human Serum Albumin: Computational and Spectroscopic Approaches

Human serum albumin (HSA) is the most abundant protein in plasma synthesized by the liver and the main modulator of fluid distribution between body compartments. It has an amazing capacity to bind with multiple ligands, offering a store and transporter for various endogenous and exogenous compounds. Huperzine A (HpzA) is a natural sesquiterpene alkaloid found in Huperzia serrata and used in various neurological conditions, including Alzheimer’s disease (AD). This study elucidated the binding of HpzA with HSA using advanced computational approaches such as molecular docking and molecular dynamic (MD) simulation followed by fluorescence-based binding assays. The molecular docking result showed plausible interaction between HpzA and HSA. The MD simulation and principal component analysis (PCA) results supported the stable interactions of the protein–ligand complex. The fluorescence assay further validated the in silico study, revealing significant binding affinity between HpzA and HSA. This study advocated that HpzA acts as a latent HSA binding partner, which may be investigated further in AD therapy in experimental settings.     

Modeling the Dynamics of Protein–Protein Interfaces,How and Why?

Protein–protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein–protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein–protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein–protein interface.     

Phytochemical Profile and Antioxidant Activities of Coleus amboinicus Lour. Cultivated in Indonesia and Poland

Coleus amboinicus Lour., Lamiaceae, is a perennial herb that is native to Indonesia and also cultivated in Africa, Asia and Australia. The major phytochemicals responsible for its bioactivity are rosmarinic acid (RA) and its analogues, flavonoids and abietane diterpenoids. The possibility of cultivation in a colder climate would extend the use of this herb and provide new opportunities to herb growers and livestock farmers. Our study to compare feed value and phytochemical composition of C. amboinicus plants cultivated in its original region, Indonesia, and in Poland. The crude protein content was significantly higher in plants cultivated in Indonesia compared to those cultivated in Poland—21% and 13% of dry matter, respectively. The higher ADF contents were detected in C. amboinicus cultivated in Indonesia, 38–41%, in comparison to 34% in plants cultivated in Poland. The phytochemical composition was also significantly influenced by the cultivation location. Polish samples were higher in polyphenols (RA and its analogues), and also had 1.5–2-fold higher antioxidant potential, as measured by DPPH scavenging, phosphomolybdenum reduction and Fenton reaction driven lipid peroxidation. The Indonesian samples contained more diterpenoid compounds, such as dihydroxyroyleanone, and the sum of terpenoids was ca. 10 times higher than in samples from Poland (15.59–23.64 vs. 1.87 µg/g of extracts). In conclusion, C. amboinicus is suitable for cultivation in non-optimal climatic conditions but some nutritional properties and bioactivity are significantly affected.     

Aromatic Rings as Molecular Determinants for the Molecular Recognition of Protein Kinase Inhibitors

Protein kinases are key enzymes in many signal transduction pathways, and play a crucial role in cellular proliferation, differentiation, and various cell regulatory processes. However, aberrant function of kinases has been associated with cancers and many other diseases. Consequently, competitive inhibition of the ATP binding site of protein kinases has emerged as an effective means of curing these diseases. Over the past three decades, thousands of protein kinase inhibitors (PKIs) with varying molecular frames have been developed. Large-scale data mining of the Protein Data Bank resulted in a database of 2139 non-redundant high-resolution X-ray crystal structures of PKIs bound to protein kinases. This provided us with a unique opportunity to study molecular determinants for the molecular recognition of PKIs. A chemoinformatic analysis of 2139 PKIs resulted in findings that PKIs are “flat” molecules with high aromatic ring counts and low fractions of sp³ carbon. All but one PKI possessed one or more aromatic rings. More importantly, it was found that the average weighted hydrogen bond count is inversely proportional to the number of aromatic rings. Based on this linear relationship, we put forward the exchange rule of hydrogen bonding interactions and non-bonded π-interactions. Specifically, a loss of binding affinity caused by a decrease in hydrogen bonding interactions is compensated by a gain in binding affinity acquired by an increase in aromatic ring-originated non-bonded interactions (i.e., π–π stacking interactions, CH–π interactions, cation–π interactions, etc.), and vice versa. The very existence of this inverse relationship strongly suggests that both hydrogen bonding and aromatic ring-originated non-bonded interactions are responsible for the molecular recognition of PKIs. As an illustration, two representative PKI–kinase complexes were employed to examine the relative importance of different modes of non-bonded interactions for the molecular recognition of PKIs. For this purpose, two FDA-approved PKI drugs, ibrutinib and lenvatinib, were chosen. The binding pockets of both PKIs were thoroughly examined to identify all non-bonded intermolecular interactions. Subsequently, the strengths of interaction energies between ibrutinib and its interacting residues in tyrosine kinase BTK were quantified by means of the double hybrid DFT method B2PLYP. The resulting energetics for the binding of ibrutinib in tyrosine kinase BTK showed that CH–π interactions and π–π stacking interactions between aromatic rings of the drug and hydrophobic residues in its binding pocket dominate the binding interactions. Thus, this work establishes that, in addition to hydrogen bonding, aromatic rings function as important molecular determinants for the molecular recognition of PKIs. In conclusion, our findings support the following pharmacophore model for ATP-competitive kinase inhibitors: a small molecule features a scaffold of one or more aromatic rings which is linked with one or more hydrophilic functional groups. The former has the structural role of acting as a scaffold and the functional role of participating in aromatic ring-originated non-bonded interactions with multiple hydrophobic regions in the ATP binding pocket of kinases. The latter ensure water solubility and form hydrogen bonds with the hinge region and other hydrophilic residues of the ATP binding pocket.     

Native Structure-Based Peptides as Potential Protein–Protein Interaction Inhibitors of SARS-CoV-2 Spike Protein and Human ACE2 Receptor

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is a positive-strand RNA virus that causes severe respiratory syndrome in humans, which is now referred to as coronavirus disease 2019 (COVID-19). Since December 2019, the new pathogen has rapidly spread globally, with over 65 million cases reported to the beginning of December 2020, including over 1.5 million deaths. Unfortunately, currently, there is no specific and effective treatment for COVID-19. As SARS-CoV-2 relies on its spike proteins (S) to bind to a host cell-surface receptor angiotensin-converting enzyme-2(ACE2), and this interaction is proved to be responsible for entering a virus into host cells, it makes an ideal target for antiviral drug development. In this work, we design three very short peptides based on the ACE2 sequence/structure fragments, which may effectively bind to the receptor-binding domain (RBD) of S protein and may, in turn, disrupt the important virus-host protein–protein interactions, blocking early steps of SARS-CoV-2 infection. Two of our peptides bind to virus protein with affinity in nanomolar range, and as very short peptides have great potential for drug development.     

Glycan–protein cross-linking mass spectrometry reveals sialic acid-mediated protein networks on cell surfaces

A cross-linking method is developed to elucidate glycan-mediated interactions between membrane proteins through sialic acids. The method provides information on previously unknown extensive glycomic interactions on cell membranes. The vast majority of membrane proteins are glycosylated with complicated glycan structures attached to the polypeptide backbone. Glycan–protein interactions are fundamental elements in many cellular events. Although significant advances have been made to identify protein–protein interactions in living cells, only modest advances have been made on glycan–protein interactions. Mechanistic elucidation of glycan–protein interactions has thus far remained elusive. Therefore, we developed a cross-linking mass spectrometry (XL-MS) workflow to directly identify glycan–protein interactions on the cell membrane using liquid chromatography-mass spectrometry (LC-MS). This method involved incorporating azido groups on cell surface glycans through biosynthetic pathways, followed by treatment of cell cultures with a synthesized reagent, N-hydroxysuccinimide (NHS)–cyclooctyne, which allowed the cross-linking of the sialic acid azides on glycans with primary amines on polypeptide backbones. The coupled peptide–glycan–peptide pairs after cross-linking were identified using the latest techniques in glycoproteomic and glycomic analyses and bioinformatics software. With this approach, information on the site of glycosylation, the glycoform, the source protein, and the target protein of the cross-linked pair were obtained. Glycoprotein–protein interactions involving unique glycoforms on the PNT2 cell surface were identified using the optimized and validated method. We built the GPX network of the PNT2 cell line and further investigated the biological roles of different glycan structures within protein complexes. Furthermore, we were able to build glycoprotein–protein complex models for previously unexplored interactions. The method will advance our future understanding of the roles of glycans in protein complexes on the cell surface.

The cell surface glycocalyx is highly interactive defined by extensive covalent and non-covalent interactions. A method for cross-linking and characterizing glycan–peptide interactions in situ is developed.     

Graph Neural Network for Protein–Protein Interaction Prediction: A Comparative Study

Proteins are the fundamental biological macromolecules which underline practically all biological activities. Protein–protein interactions (PPIs), as they are known, are how proteins interact with other proteins in their environment to perform biological functions. Understanding PPIs reveals how cells behave and operate, such as the antigen recognition and signal transduction in the immune system. In the past decades, many computational methods have been developed to predict PPIs automatically, requiring less time and resources than experimental techniques. In this paper, we present a comparative study of various graph neural networks for protein–protein interaction prediction. Five network models are analyzed and compared, including neural networks (NN), graph convolutional neural networks (GCN), graph attention networks (GAT), hyperbolic neural networks (HNN), and hyperbolic graph convolutions (HGCN). By utilizing the protein sequence information, all of these models can predict the interaction between proteins. Fourteen PPI datasets are extracted and utilized to compare the prediction performance of all these methods. The experimental results show that hyperbolic graph neural networks tend to have a better performance than the other methods on the protein-related datasets.     

Halogen Bonding in Haspin-Halogenated Tubercidin Complexes: Molecular Dynamics and Quantum Chemical Calculations

Haspin, an atypical serine/threonine protein kinase, is a potential target for cancer therapy. 5-iodotubercidin (5-iTU), an adenosine derivative, has been identified as a potent Haspin inhibitor in vitro. In this paper, quantum chemical calculations and molecular dynamics (MD) simulations were employed to identify and quantitatively confirm the presence of halogen bonding (XB), specifically halogen∙∙∙π (aromatic) interaction between halogenated tubercidin ligands with Haspin. Consistent with previous theoretical finding, the site specificity of the XB binding over the ortho-carbon is identified in all cases. A systematic increase of the interaction energy down Group 17, based on both quantum chemical and MD results, supports the important role of halogen bonding in this series of inhibitors. The observed trend is consistent with the experimental observation of the trend of activity within the halogenated tubercidin ligands (F < Cl < Br < I). Furthermore, non-covalent interaction (NCI) plots show that cooperative non-covalent interactions, namely, hydrogen and halogen bonds, contribute to the binding of tubercidin ligands toward Haspin. The understanding of the role of halogen bonding interaction in the ligand–protein complexes may shed light on rational design of potent ligands in the future.     

Magnetic Resonance Access to Transiently Formed Protein Complexes

Protein–protein interactions are of utmost importance to an understanding of biological phenomena since non-covalent and therefore reversible couplings between basic proteins leads to the formation of complex regulatory and adaptive molecular systems. Such systems are capable of maintaining their integrity and respond to external stimuli, processes intimately related to living organisms. These interactions, however, span a wide range of dissociation constants, from sub-nanomolar affinities in tight complexes to high-micromolar or even millimolar affinities in weak, transiently formed protein complexes. Herein, we demonstrate how novel NMR and EPR techniques can be used for the characterization of weak protein–protein (ligand) complexes. Applications to intrinsically disordered proteins and transiently formed protein complexes illustrate the potential of these novel techniques to study hitherto unobserved (and unobservable) higher-order structures of proteins.     

X-ray Structures and Computational Studies of Two Bioactive 2-(Adamantane-1-carbonyl)-N-substituted Hydrazine-1-carbothioamides

Two biologically active adamantane-linked hydrazine-1-carbothioamide derivatives, namely 2-(adamantane-1-carbonyl)-N-(tert-butyl)hydrazine-1-carbothioamide) 1 and 2-(adamantane-1-carbonyl)-N-cyclohexylhydrazine-1-carbothioamide 2, have been synthesized. X-ray analysis was conducted to study the effect of the t-butyl and cyclohexyl moieties on the intermolecular interactions and conformation of the molecules in the solid state. X-ray analysis reveals that compound 1 exhibits folded conformation, whereas compound 2 adopts extended conformation. The Hirshfeld surface analysis indicates that the contributions of the major intercontacts involved in the stabilization of the crystal structures do not change much as a result of the t-butyl and cyclohexyl moieties. However, the presence and absence of these contacts is revealed by the 2D-fingerprint plots. The CLP–Pixel method was used to identify the energetically significant molecular dimers. These dimers are stabilized by different types of intermolecular interactions such as N–H···S, N–H···O, C–H···S, C–H···O, H–H bonding and C–H···π interactions. The strength of these interactions was quantified by using the QTAIM approach. The results suggest that N–H···O interaction is found to be stronger among other interactions. The in vitro assay suggests that both compounds 1 and 2 exhibit urease inhibition potential, and these compounds also display moderate antiproliferative activities. Molecular docking analysis shows the key interaction between urease enzyme and title compounds.     

Physiological Importance of Molybdate Transporter Family 1 in Feeding the Molybdenum Cofactor Biosynthesis Pathway in Arabidopsis thaliana

Molybdate uptake and molybdenum cofactor (Moco) biosynthesis were investigated in detail in the last few decades. The present study critically reviews our present knowledge about eukaryotic molybdate transporters (MOT) and focuses on the model plant Arabidopsis thaliana, complementing it with new experiments, filling missing gaps, and clarifying contradictory results in the literature. Two molybdate transporters, MOT1.1 and MOT1.2, are known in Arabidopsis, but their importance for sufficient molybdate supply to Moco biosynthesis remains unclear. For a better understanding of their physiological functions in molybdate homeostasis, we studied the impact of mot1.1 and mot1.2 knock-out mutants, including a double knock-out on molybdate uptake and Moco-dependent enzyme activity, MOT localisation, and protein–protein interactions. The outcome illustrates different physiological roles for Moco biosynthesis: MOT1.1 is plasma membrane located and its function lies in the efficient absorption of molybdate from soil and its distribution throughout the plant. However, MOT1.1 is not involved in leaf cell imports of molybdate and has no interaction with proteins of the Moco biosynthesis complex. In contrast, the tonoplast-localised transporter MOT1.2 exports molybdate stored in the vacuole and makes it available for re-localisation during senescence. It also supplies the Moco biosynthesis complex with molybdate by direct interaction with molybdenum insertase Cnx1 for controlled and safe sequestering.     

Formation of a C–C double bond from two aliphatic carbons. Multiple C–H activations in an iridium pincer complex

The search for novel, atom-economic methods for the formation of C–C bonds is of crucial importance in synthetic chemistry. Especially attractive are reactions where C–C bonds are formed through C–H activation, but the coupling of unactivated, alkane-type C_sp³–H bonds remains an unsolved challenge. Here, we report iridium-mediated intramolecular coupling reactions involving up to four unactivated C_sp³–H bonds to give carbon–carbon double bonds under the extrusion of dihydrogen. The reaction described herein is completely reversible and the direction can be controlled by altering the reaction conditions. With a hydrogen acceptor present a C–C double bond is formed, while reacting under dihydrogen pressure leads to the reverse process, with some of the steps representing net C_sp³–C_sp³ bond cleavage. Mechanistic investigations revealed a conceptually-novel overall reactivity pattern where insertion or deinsertion of an Ir carbene moiety, formed via double C–H activation, into an Ir–C bond is responsible for the key C–C bond formation and cleavage steps.