Search

Knowledge of protein-ligand binding sites (LBSs) enables research ranging from protein function annotation to structure-based drug design. To this end, we have previously developed a stand-alone tool, P2Rank, and the web server PrankWeb (https://prankweb.cz/) for fast and accurate LBS prediction. Here, we present significant enhancements to PrankWeb. First, a new, more accurate evolutionary conservation estimation pipeline based on the UniRef50 sequence database and the HMMER3 package is introduced. Second, PrankWeb now allows users to enter UniProt ID to carry out LBS predictions in situations where no experimental structure is available by utilizing the AlphaFold model database. Additionally, a range of minor improvements has been implemented. These include the ability to deploy PrankWeb and P2Rank as Docker containers, support for the mmCIF file format, improved public REST API access, or the ability to batch download the LBS predictions for the whole PDB archive and parts of the AlphaFold database., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Our study presents a novel germline c.1715G>T (p.G572V) mutation in the gene encoding Toll-like receptor 8 (TLR8) causing an autoimmune and autoinflammatory disorder in a family with monozygotic male twins, who suffer from severe autoimmune hemolytic anemia worsening with infections, and autoinflammation presenting as fevers, enteritis, arthritis, and CNS vasculitis. The pathogenicity of the mutation was confirmed by in vitro assays on transfected cell lines and primary cells. The p.G572V mutation causes impaired stability of the TLR8 protein, cross-reactivity to TLR7 ligands and reduced ability of TLR8 to attenuate TLR7 signaling. This imbalance toward TLR7-dependent signaling leads to increased pro-inflammatory responses, such as nuclear factor-κB (NF-κB) activation and production of pro-inflammatory cytokines IL-1β, IL-6, and TNFα. This unique TLR8 mutation with partial TLR8 protein loss and hyperinflammatory phenotype mediated by TLR7 ligands represents a novel inborn error of immunity with childhood-onset and a good response to TLR7 inhibition., (© 2022 Wiley Periodicals LLC.)

The ER membrane protein complex (EMC) is required for the biogenesis of a subset of tail anchored (TA) and polytopic membrane proteins, including Rhodopsin-1 (Rh1) and the TRP channel. To understand the physiological implications of EMC-dependent membrane protein biogenesis, we perform a bioinformatic identification of Drosophila TA proteins. From 254 predicted TA proteins, screening in larval eye discs identified two proteins that require EMC for their biogenesis: fan and Xport-A. Fan is required for male fertility in Drosophila and we show that EMC is also required for this process. Xport-A is essential for the biogenesis of both Rh1 and TRP, raising the possibility that disruption of Rh1 and TRP biogenesis in EMC mutants is secondary to the Xport-A defect. We show that EMC is required for Xport-A TMD membrane insertion and that EMC-independent Xport-A mutants rescue Rh1 and TRP biogenesis in EMC mutants. Finally, our work also reveals a role for Xport-A in a glycosylation-dependent triage mechanism during Rh1 biogenesis in the endoplasmic reticulum., (© 2021 The Authors.)

Interactions among amino acid residues are the principal contributor to the stability of the three-dimensional structure of a protein. The Amino Acid Interactions (INTAA) web server (https://bioinfo.uochb.cas.cz/INTAA/) has established itself as a unique computational resource, which enables users to calculate the contribution of individual residues in a biomolecular structure to its total energy using a molecular mechanical scoring function. In this update, we describe major additions to the web server which help solidify its position as a robust, comprehensive resource for biomolecular structure analysis. Importantly, a new continuum solvation model was introduced, allowing more accurate representation of electrostatic interactions in aqueous media. In addition, a low-overhead pipeline for the estimation of evolutionary conservation in protein chains has been added. New visualization options were introduced as well, allowing users to easily switch between and interrelate the energetic and evolutionary views of the investigated structures., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Interaction with the DNA minor groove is a significant contributor to specific sequence recognition in selected families of DNA-binding proteins. Based on a statistical analysis of 3D structures of protein-DNA complexes, we propose that distortion of the DNA minor groove resulting from interactions with hydrophobic amino acid residues is a universal element of protein-DNA recognition. We provide evidence to support this by associating each DNA minor groove-binding amino acid residue with the local dimensions of the DNA double helix using a novel algorithm. The widened DNA minor grooves are associated with high GC content. However, some AT-rich sequences contacted by hydrophobic amino acids (e.g., phenylalanine) display extreme values of minor groove width as well. For a number of hydrophobic amino acids, distinct secondary structure preferences could be identified for residues interacting with the widened DNA minor groove. These results hold even after discarding the most populous families of minor groove-binding proteins.

Many membrane proteins are thought to function as dimers or higher oligomers, but measuring membrane protein oligomerization in lipid membranes is particularly challenging. Förster resonance energy transfer (FRET) and fluorescence cross-correlation spectroscopy are noninvasive, optical methods of choice that have been applied to the analysis of dimerization of single-spanning membrane proteins. However, the effects inherent to such two-dimensional systems, such as the excluded volume of polytopic transmembrane proteins, proximity FRET, and rotational diffusion of fluorophore dipoles, complicate interpretation of FRET data and have not been typically accounted for. Here, using FRET and fluorescence cross-correlation spectroscopy, we introduce a method to measure surface protein density and to estimate the apparent Förster radius, and we use Monte Carlo simulations of the FRET data to account for the proximity FRET effect occurring in confined two-dimensional environments. We then use FRET to analyze the dimerization of human rhomboid protease RHBDL2 in giant plasma membrane vesicles. We find no evidence for stable oligomers of RHBDL2 in giant plasma membrane vesicles of human cells even at concentrations that highly exceed endogenous expression levels. This indicates that the rhomboid transmembrane core is intrinsically monomeric. Our findings will find use in the application of FRET and fluorescence correlation spectroscopy for the analysis of oligomerization of transmembrane proteins in cell-derived lipid membranes., (Copyright © 2020 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Estimation of binding free energies is one of the central aims of simulations of biomolecular complexes. We explore the accuracy and efficiency of setups based on nonequilibrium pulling simulations applied to the estimation of binding affinities of DNA-binding proteins. Absolute binding free energies are calculated over a range of temperatures and compared to results obtained previously using an equilibrium method. We show that realistic binding affinities can be obtained with the presented nonequilibrium approach, which also entails lower computational requirements. Errors of the binding free energy estimates are investigated and are shown to be comparable to those observed previously. Bounds are provided on the convergence of the errors with respect to the number of pulling simulations performed and with respect to the applied pull rate.

We systematically investigate the applicability of a molecular dynamics-based setup for the calculations of standard binding free energies of biologically relevant protein-DNA complexes. The free energies are extracted from a potential of mean force calculated using umbrella sampling simulations. Two protein-DNA systems derived from a homeodomain transcription factor complex are studied in order to investigate the binding of both disordered and globular proteins. Free energies and trajectories obtained using two modern molecular mechanical force fields are compared to each other and to experimental data. The temperature dependence of the calculated standard binding free energies is investigated by performing all simulations over a range of temperatures. We show that the values of standard binding free energies obtained from these simulations are overestimated compared to experimental results. Significant differences are observed between the two protein-DNA systems and between the two force fields, which are explained by different propensities to form inter- and intramolecular contacts. The number of protein-DNA contacts increases with increasing temperature, in agreement with the experimentally known temperature dependence of enthalpies of binding. However, conclusions about the temperature dependence of the standard binding free energies cannot be made with confidence, as the differences among the values are on the order of statistical uncertainty.

Summary: Amino acid residues showing above background levels of conservation are often indicative of functionally significant regions within a protein. Understanding how the sequence conservation profile relates in space requires projection onto a protein structure, a potentially time-consuming process. 3DPatch is a web application that streamlines this task by automatically generating multiple sequence alignments (where appropriate) and finding structural homologs, presenting the user with a choice of structures matching their query, annotated with residue conservation scores in a matter of seconds., Availability and Implementation: 3DPatch is written in JavaScript and is freely available at http://www.skylign.org/3DPatch/. Mozilla Firefox, Google Chrome, and Safari web browsers are supported. Source code is available under MIT license at https://github.com/davidjakubec/3DPatch., Supplementary Information: Supplementary data are available at Bioinformatics online.

Domains are distinct units within proteins that typically can fold independently into recognizable three-dimensional structures to facilitate their functions. The structural and functional independence of protein domains is reflected by their apparent modularity in the context of multi-domain proteins. In this work, we examined the coupling of evolution of domain sequences co-occurring within multi-domain proteins to see if it proceeds independently, or in a coordinated manner. We used continuous information theory measures to assess the extent of correlated mutations among domains in multi-domain proteins from organisms across the tree of life. In all multi-domain architectures we examined, domains co-occurring within protein sequences had to some degree undergone concerted evolution. This finding challenges the notion of complete modularity and independence of protein domains, providing new perspective on the evolution of protein sequence and function., Competing Interests: The authors have declared that no competing interests exist.

Large biomolecules-proteins and nucleic acids-are composed of building blocks which define their identity, properties and binding capabilities. In order to shed light on the energetic side of interactions of amino acids between themselves and with deoxyribonucleotides, we present the Amino Acid Interaction web server (http://bioinfo.uochb.cas.cz/INTAA/). INTAA offers the calculation of the residue Interaction Energy Matrix for any protein structure (deposited in Protein Data Bank or submitted by the user) and a comprehensive analysis of the interfaces in protein-DNA complexes. The Interaction Energy Matrix web application aims to identify key residues within protein structures which contribute significantly to the stability of the protein. The application provides an interactive user interface enhanced by 3D structure viewer for efficient visualization of pairwise and net interaction energies of individual amino acids, side chains and backbones. The protein-DNA interaction analysis part of the web server allows the user to view the relative abundance of various configurations of amino acid-deoxyribonucleotide pairs found at the protein-DNA interface and the interaction energies corresponding to these configurations calculated using a molecular mechanical force field. The effects of the sugar-phosphate moiety and of the dielectric properties of the solvent on the interaction energies can be studied for the various configurations., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

In view of the importance of protein-DNA interactions in biological processes, we extracted from the Protein Data Bank several one-to-one complexes of amino acids with nucleotides that matched certain geometric and energetic specificity criteria and investigated them using quantum chemistry methods. The CCSD(T)/CBS interaction energies were used as a benchmark to compare the performance of the MP2.5, MP2-F12, DFT-D3, and PM6-D3H4 methods. All methods yielded good agreement with the reference values, with declining accuracy from MP2.5 to PM6-D3H4. Regardless of the site of interaction, the minima found after full optimization in implicit solvent with high dielectric constant were close to the structures experimentally detected in protein-DNA complexes. According to DFT-SAPT analysis, the nature of noncovalent interactions strongly depends on the type of amino acid. The negatively charged sugar-phosphate backbone of DNA heavily influences the strength of interactions and must be included in the computational model, especially in the case of interactions with charged amino acids.

Decades of intensive experimental studies of the recognition of DNA sequences by proteins have provided us with a view of a diverse and complicated world in which few to no features are shared between individual DNA-binding protein families. The originally conceived direct readout of DNA residue sequences by amino acid side chains offers very limited capacity for sequence recognition, while the effects of the dynamic properties of the interacting partners remain difficult to quantify and almost impossible to generalise. In this work we investigated the energetic characteristics of all DNA residue-amino acid side chain combinations in the conformations found at the interaction interface in a very large set of protein-DNA complexes by the means of empirical potential-based calculations. General specificity-defining criteria were derived and utilised to look beyond the binding motifs considered in previous studies. Linking energetic favourability to the observed geometrical preferences, our approach reveals several additional amino acid motifs which can distinguish between individual DNA bases. Our results remained valid in environments with various dielectric properties.

Representative pairs of amino acid side chains and nucleic acid bases extracted from available high-quality structures of protein-DNA complexes were analyzed using a range of computational methods. CCSD(T)/CBS interaction energies were calculated for the chosen 272 pairs. These reference interaction energies were used to test the MP2.5/CBS, MP2.X/CBS, MP2-F12, DFT-D3, PM6, and Amber force field methods. Method MP2.5 provided excellent agreement with reference data (root-mean-square error (RMSE) of 0.11 kcal/mol), which is more than 1 order of magnitude faster than the CCSD(T) method. When MP2-F12 and MP2.5 were combined, the results were within reasonable accuracy (0.20 kcal/mol), with a computational savings of almost 2 orders of magnitude. Therefore, this method is a promising tool for accurate calculations of interaction energies in protein-DNA motifs of up to ∼100 atoms, for which CCSD(T)/CBS benchmark calculations are not feasible. B3-LYP-D3 calculated with def2-TZVPP and def2-QZVP basis sets yielded sufficiently good results with a reasonably small RMSE. This method provided better results for neutral systems, whereas positively charged species exhibited the worst agreement with the benchmark data. The Amber force field yielded unbalanced results-performing well for systems containing nonpolar amino acids but severely underestimating interaction energies for charged complexes. The semiempirical PM6 method with corrections for hydrogen bonding and dispersion energy (PM6-D3H4) exhibited considerably smaller error than the Amber force field, which makes it an effective tool for modeling extended protein-ligand complexes (of up to 10,000 atoms).

The growing number of high-quality experimental (X-ray, NMR) structures of protein–DNA complexes has sufficient enough information to assess whether universal rules governing the DNA sequence recognition process apply. While previous studies have investigated the relative abundance of various modes of amino acid–base contacts (van der Waals contacts, hydrogen bonds), relatively little is known about the energetics of these noncovalent interactions. In the present study, we have performed the first large-scale quantitative assessment of binding preferences in protein–DNA complexes by calculating the interaction energies in all 80 possible amino acid–DNA base combinations. We found that several mutual amino acid–base orientations featuring bidentate hydrogen bonds capable of unambiguous one-to-one recognition correspond to unique minima in the potential energy space of the amino acid–base pairs. A clustering algorithm revealed that these contacts form a spatially well-defined group offering relatively little conformational freedom. Various molecular mechanics force field and DFT-D ab initio calculations were performed, yielding similar results.