Probing the Proton-Loading Site of Cytochrome C Oxidase Using Time-Resolved Fourier Transform Infrared Spectroscopy

Crystal structure analyses at atomic resolution and FTIR spectroscopic studies of cytochrome c oxidase have yet not revealed protonation or deprotonation of key sites of proton transfer in a time-resolved mode. Here, a sensitive technique to detect protolytic transitions is employed. In this work, probing a proton-loading site of cytochrome c oxidase from Paracoccus denitrificans with time-resolved Fourier transform infrared spectroscopy is presented for the first time. For this purpose, variants with single-site mutations of N131V, D124N, and E278Q, the key residues in the D-channel, were studied. The reaction of mutated CcO enzymes with oxygen was monitored and analyzed. Seven infrared bands in the “fast” kinetic spectra were found based on the following three requirements: (1) they are present in the “fast” phases of N131V and D124N mutants, (2) they have reciprocal counterparts in the “slow” kinetic spectra in these mutants, and (3) they are absent in “fast” kinetic spectra of the E278Q mutant. Moreover, the double-difference spectra between the first two mutants and E278Q revealed more IR bands that may belong to the proton-loading site protolytic transitions. From these results, it is assumed that several polar residues and/or water molecule cluster(s) share a proton as a proton-loading site. This site can be propionate itself (holding only a fraction of H+), His403, and/or water cluster(s)

Probing the Proton-Loading Site of Cytochrome C Oxidase Using Time-Resolved Fourier Transform Infrared Spectroscopy

Crystal structure analyses at atomic resolution and FTIR spectroscopic studies of cytochrome c oxidase have yet not revealed protonation or deprotonation of key sites of proton transfer in a time-resolved mode. Here, a sensitive technique to detect protolytic transitions is employed. In this work, probing a proton-loading site of cytochrome c oxidase from Paracoccus denitrificans with time-resolved Fourier transform infrared spectroscopy is presented for the first time. For this purpose, variants with single-site mutations of N131V, D124N, and E278Q, the key residues in the D-channel, were studied. The reaction of mutated CcO enzymes with oxygen was monitored and analyzed. Seven infrared bands in the “fast” kinetic spectra were found based on the following three requirements: (1) they are present in the “fast” phases of N131V and D124N mutants, (2) they have reciprocal counterparts in the “slow” kinetic spectra in these mutants, and (3) they are absent in “fast” kinetic spectra of the E278Q mutant. Moreover, the double-difference spectra between the first two mutants and E278Q revealed more IR bands that may belong to the proton-loading site protolytic transitions. From these results, it is assumed that several polar residues and/or water molecule cluster(s) share a proton as a proton-loading site. This site can be propionate itself (holding only a fraction of H+), His403, and/or water cluster(s)

Docking glycosaminoglycans to proteins: analysis of solvent inclusion

Glycosaminoglycans (GAGs) are anionic polysaccharides, which participate in key processes in the extracellular matrix by interactions with protein targets. Due to their charged nature, accurate consideration of electrostatic and water-mediated interactions is indispensable for understanding GAGs binding properties. However, solvent is often overlooked in molecular recognition studies. Here we analyze the abundance of solvent in GAG-protein interfaces and investigate the challenges of adding explicit solvent in GAG-protein docking experiments. We observe PDB GAG-protein interfaces being significantly more hydrated than protein–protein interfaces. Furthermore, by applying molecular dynamics approaches we estimate that about half of GAG-protein interactions are water-mediated. With a dataset of eleven GAG-protein complexes we analyze how solvent inclusion affects Autodock 3, eHiTs, MOE and FlexX docking. We develop an approach to de novo place explicit solvent into the binding site prior to docking, which uses the GRID program to predict positions of waters and to locate possible areas of solvent displacement upon ligand binding. To investigate how solvent placement affects docking performance, we compare these results with those obtained by taking into account information about the solvent position in the crystal structure. In general, we observe that inclusion of solvent improves the results obtained with these methods. Our data show that Autodock 3 performs best, though it experiences difficulties to quantitatively reproduce experimental data on specificity of heparin/heparan sulfate disaccharides binding to IL-8. Our work highlights the current challenges of introducing solvent in protein-GAGs recognition studies, which is crucial for exploiting the full potential of these molecules for rational engineering

Analysis of the impact of solvent on contacts prediction in proteins

<p>Abstract</p> <p>Background</p> <p>The correlated mutations concept is based on the assumption that interacting protein residues coevolve, so that a mutation in one of the interacting counterparts is compensated by a mutation in the other. Approaches based on this concept have been widely used for protein contacts prediction since the 90s. Previously, we have shown that water-mediated interactions play an important role in protein interfaces. We have observed that current "dry" correlated mutations approaches might not properly predict certain interactions in protein interfaces due to the fact that they are water-mediated.</p> <p>Results</p> <p>The goal of this study has been to analyze the impact of including solvent into the concept of correlated mutations. For this purpose we use linear combinations of the predictions obtained by the application of two different similarity matrices: a standard "dry" similarity matrix (DRY) and a "wet" similarity matrix (WET) derived from all water-mediated protein interfacial interactions in the PDB. We analyze two datasets containing 50 domains and 10 domain pairs from PFAM and compare the results obtained by using a combination of both matrices. We find that for both intra- and interdomain contacts predictions the introduction of a combination of a "wet" and a "dry" similarity matrix improves the predictions in comparison to the "dry" one alone.</p> <p>Conclusion</p> <p>Our analysis, despite the complexity of its possible general applicability, opens up that the consideration of water may have an impact on the improvement of the contact predictions obtained by correlated mutations approaches.</p

Insights into the structure and dynamics of lysyl oxidase propeptide, a flexible protein with numerous partners

Lysyl oxidase (LOX) catalyzes the oxidative deamination of lysine and hydroxylysine residues in collagens and elastin, which is the first step of the cross-linking of these extracellular matrix proteins. It is secreted as a proenzyme activated by bone morphogenetic protein-1, which releases the LOX catalytic domain and its bioactive N-terminal propeptide. We characterized the recombinant human propeptide by circular dichroism, dynamic light scattering, and small-angle X-ray scattering (SAXS), and showed that it is elongated, monomeric, disordered and flexible (Dmax: 11.7 nm, Rg: 3.7 nm). We generated 3D models of the propeptide by coarse-grained molecular dynamics simulations restrained by SAXS data, which were used for docking experiments. Furthermore, we have identified 17 new binding partners of the propeptide by label-free assays. They include four glycosaminoglycans (hyaluronan, chondroitin, dermatan and heparan sulfate), collagen I, cross-linking and proteolytic enzymes (lysyl oxidase-like 2, transglutaminase-2, matrix metalloproteinase-2), a proteoglycan (fibromodulin), one growth factor (Epidermal Growth Factor, EGF), and one membrane protein (tumor endothelial marker-8). This suggests new roles for the propeptide in EGF signaling pathway

Fragment­ based modeling of protein­-GAG complexes

International audienceGlycosaminoglycans (GAGs) are linear anionic periodic poly-saccharides that bind to their protein targets in the extracellular matrix, and so participate in many cell-signaling processes. They are very promising targets for the design of novel functional biomaterials with medical applications such as bone and skin regeneration [Scharnweber et al, JMSM 2015].Useful biological and therapeutical insights can be obtained from the structure of complexes between GAGs and their target proteins. However the experimental resolution as well as the modeling of their structure is highly challenging. The reasons are both GAG intrinsic properties, such as the high flexibility and conformational diversity of glycans, and the lack for computational tools particularly designed for protein-GAG systems. This currently limits the success of GAG docking to very short fragments [Samsonov and Pisabarro, Glycobiology 2016].We present here a new fragment-based method to dock GAGs on a coarsly known protein binding site. We combine flexible docking of trimeric GAG fragments with Autodock and combinatorial assembly of the compatible poses into GAGs chains, followed by fully flexible refinement. Tested on a benchmark of 13 complexes with various GAG types (heparin, chondroitin sulfate and hyaluronic acids), the method could model 5-mers to 7-mers with the accuracy of 5 Å RMSD to the experimental structure for all of them, and 3 Å RMSD for half of them. This is the first reported automatized fragment-based docking method to successfully dock such diverse GAGs. In principle, the independence of this approach on the ligand's length allows to dock very long GAG chains, which has been a bottleneck for previously applied docking approaches for these systems. The results of this work contribute to enrich the sparse pool of computational tools specifically developed for protein-GAG complexes

Protein-Ligand Interaction Energy-Based Entropy Calculations: Fundamental Challenges For Flexible Systems

Entropy calculations represent one of the most challenging steps in obtaining the binding free energy in biomolecular systems. A novel computationally effective approach (IE) was recently proposed to calculate the entropy based on the computation of protein-ligand interaction energy directly from molecular dynamics (MD) simulations. We present a study focused on the application of this method to flexible molecular systems and compare its performance with well-established normal mode (NM) and quasiharmonic (QH) entropy calculation approaches. Our results raise substantial concerns on the general applicability of IE in terms of reproducibility, reasonable absolute values of the entropy and agreement with NM and QM approaches. IE shows significant variation in the computed entropy values depending on the MD frames chosen for calculations. These deviations render reproducibility of IE calculations to be far from sufficient. We conclude that IE is recommended to be used after substantial modifications with respect to its sampling methodology