An atlas of protein homo-oligomerization across domains of life

Protein structures are essential to understanding cellular processes in molecular detail. While advances in artificial intelligence revealed the tertiary structure of proteins at scale, their quaternary structure remains mostly unknown. We devise a scalable strategy based on AlphaFold2 to predict homo-oligomeric assemblies across four proteomes spanning the tree of life. Our results suggest that approximately 45% of an archaeal proteome and a bacterial proteome and 20% of two eukaryotic proteomes form homomers. Our predictions accurately capture protein homo-oligomerization, recapitulate megadalton complexes, and unveil hundreds of homo-oligomer types, including three confirmed experimentally by structure determination. Integrating these datasets with omics information suggests that a majority of known protein complexes are symmetric. Finally, these datasets provide a structural context for interpreting disease mutations and reveal coiled-coil regions as major enablers of quaternary structure evolution in human. Our strategy is applicable to any organism and provides a comprehensive view of homo-oligomerization in proteomes.

Nematostatic activity of isoprenylated guanidine alkaloids from Pterogyne nitens and their interaction with acetylcholinesterase

Although new nematicides have appeared, the demand for new products less toxic and more efficient for the control of plant-parasitic nematodes are still high. Consequently, studies on natural secondary metabolites from plants, to develop new nematicides, have increased. In this work, nineteen extracts from eleven Brazilian plant species were screened for activity against Meloidogyne incognita. Among them, the extracts of Piterogyne nitens showed a potent nematostatic activity. The alkaloid fraction obtained from the ethanol extract of leaves of P. nitens was more active than the coming extract. Due to the promising activity from the alkaloid fraction, three isoprenylated guanidine alkaloids isolated from this fraction, galegine (1), pterogynidine (2), and pterogynine (3) were tested, showing similar activity to the alkaloid fraction, which was comparable to that of the positive control Temik at 250 μg/mL. At lower concentrations (125-50 μg/mL), compound 2 showed to be the most active one. As several nematicides act through inhibition of acetylcholinesterase (AChE), the guanidine alkaloids were also employed in two in vitro AChE assays. In both cases, compound 2 was more active than compounds 1 and 3. Its activity was considered moderated compared to the control (physostigmine). Compound 2 was selected for an in silico study with the electric eel (Electrophorus electricus) AChE, showing to bind mostly to the same site of physostigmine in the AChEs, pointing out that this could be the mechanism of action for this compound. These results suggested that the guanidine alkaloids 1,2 and 3 from P. nitens are promising for the development of new products to control M. incognita, especially guanidine 2, and encourage new investigations to confirm the mechanism of action, as well as to determine the structure-activity relationship of the guanidine alkaloids.

Local Normal Mode Analysis for Fast Loop Conformational Sampling

We propose and validate a novel method to efficiently explore local protein loop conformations based on a new formalism for constrained normal mode analysis (NMA) in internal coordinates. The manifold of possible loop configurations imposed by the position and orientation of the fixed loop ends is reduced to an orthogonal set of motions (or modes) encoding concerted rotations of all the backbone dihedral angles. We validate the sampling power on a set of protein loops with highly variable experimental structures and demonstrate that our approach can efficiently explore the conformational space of closed loops. We also show an acceptable resemblance of the ensembles around equilibrium conformations generated by long molecular simulations and constrained NMA on a set of exposed and diverse loops. In comparison with other methods, the main advantage is the lack of restrictions on the number of dihedrals that can be altered simultaneously. Furthermore, the method is computationally efficient since it only requires the diagonalization of a tiny matrix, and the modes of motions are energetically contextualized by the elastic network model, which includes both the loop and the neighboring residues.

Epitope-Analyzer: A structure-based webtool to analyze broadly neutralizing epitopes

The antigenic epitope regions of pathogens (e.g., viruses) are recognized by antibodies (Abs) and subsequently cleared by the host immune system, thereby protecting us from disease. Some of these epitopes are conserved among different variants or subgroups of pathogens (e.g., Influenza (FLU) viruses, Coronaviruses), hence can be targeted for potential broad-neutralization. Here we report a web-based tool, Epitope Analyzer (EA), that rapidly identifies conformational epitope and paratope residues in an antigen-antibody complex structure. Furthermore, the tool provides the ways and means to analyze broadly neutralizing epitopes by comparing the equivalent epitope residues in similar antigen structures. The similarity in the epitope residues between (multiple) pairs of similar antigen molecules suggest the presence of conserved epitopes that can be targeted by broadly neutralizing antibodies. These details can be used as a guide in developing effective treatments, such as the design of novel vaccines and formulation of cocktail of broadly neutralizing antibodies, against multiple variants or subgroups of viruses. The web application can be freely accessed from the URL, http://viperdb.scripps.edu/ea.php.

KORP-PL: a coarse-grained knowledge-based scoring function for protein-ligand interactions

MOTIVATION

Despite the progress made in studying protein-ligand interactions and the widespread application of docking and affinity prediction tools, improving their precision and efficiency still remains a challenge. Computational approaches based on the scoring of docking conformations with statistical potentials constitute a popular alternative to more accurate but costly physics-based thermodynamic sampling methods. In this context, a minimalist and fast sidechain-free knowledge-based potential with a high docking and screening power can be very useful when screening a big number of putative docking conformations.

RESULTS

Here, we present a novel coarse-grained potential defined by a 3D joint probability distribution function that only depends on the pairwise orientation and position between protein backbone and ligand atoms. Despite its extreme simplicity, our approach yields very competitive results with the state-of-the-art scoring functions, especially in docking and screening tasks. For example, we observed a twofold improvement in the median 5% enrichment factor on the DUD-E benchmark compared to Autodock Vina results. Moreover, our results prove that a coarse sidechain-free potential is sufficient for a very successful docking pose prediction.

AVAILABILITYAND IMPLEMENTATION

The standalone version of KORP-PL with the corresponding tests and benchmarks are available at https://team.inria.fr/nano-d/korp-pl/ and https://chaconlab.org/modeling/korp-pl.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Structural Insights into the Binding Modes of Viral RNA-Dependent RNA Polymerases Using a Function-Site Interaction Fingerprint Method for RNA Virus Drug Discovery

The coronavirus disease of 2019 (COVID-19) pandemic speaks to the need for drugs that not only are effective but also remain effective given the mutation rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To this end, we describe structural binding-site insights for facilitating COVID-19 drug design when targeting RNA-dependent RNA polymerase (RDRP), a common conserved component of RNA viruses. We combined an RDRP structure data set, including 384 RDRP PDB structures and all corresponding RDRP-ligand interaction fingerprints, thereby revealing the structural characteristics of the active sites for application to RDRP-targeted drug discovery. Specifically, we revealed the intrinsic ligand-binding modes and associated RDRP structural characteristics. Four types of binding modes with corresponding binding pockets were determined, suggesting two major subpockets available for drug discovery. We screened a drug data set of 7894 compounds against these binding pockets and presented the top-10 small molecules as a starting point in further exploring the prevention of virus replication. In summary, the binding characteristics determined here help rationalize RDRP-targeted drug discovery and provide insights into the specific binding mechanisms important for containing the SARS-CoV-2 virus.

Studying dynamics without explicit dynamics: A structure-based study of the export mechanism by AcrB

Resistance-nodulation-cell division family proteins are transmembrane proteins identified as large spectrum drug transporters involved in multidrug resistance. A prototypical case in this superfamily, responsible for antibiotic resistance in selected gram-negative bacteria, is AcrB. AcrB forms a trimer using the proton motive force to efflux drugs, implementing a functional rotation mechanism. Unfortunately, the size of the system (1049 amino acid per monomer and membrane) has prevented a systematic dynamical exploration, so that the mild understanding of this coupled transport jeopardizes our ability to counter it. The large number of crystal structures of AcrB prompts studies to further our understanding of the mechanism. To this end, we present a novel strategy based on two key ingredients, which are to study dynamics by exploiting information embodied in the numerous crystal structures obtained to date, and to systematically consider subdomains, their dynamics, and their interactions. Along the way, we identify the subdomains responsible for dynamic events, refine the states (A, B, E) of the functional rotation mechanism, and analyze the evolution of intramonomer and intermonomer interfaces along the functional cycle. Our analysis shows the relevance of AcrB's efflux mechanism as a template within the HAE1 family but not beyond. It also paves the way to targeted simulations exploiting the most relevant degrees of freedom at certain steps, and to a targeting of specific interfaces to block the drug efflux. Our work shows that complex dynamics can be unveiled from static snapshots, a strategy that may be used on a variety of molecular machines of large size.

Topology-independent and global protein structure alignment through an FFT-based algorithm

MOTIVATION

Protein structure alignment is one of the fundamental problems in computational structure biology. A variety of algorithms have been developed to address this important issue in the past decade. However, due to their heuristic nature, current structure alignment methods may suffer from suboptimal alignment and/or over-fragmentation and thus lead to a biologically wrong alignment in some cases. To overcome these limitations, we have developed an accurate topology-independent and global structure alignment method through an FFT-based exhaustive search algorithm, which is referred to as FTAlign.

RESULTS

Our FTAlign algorithm was extensively tested on six commonly used datasets and compared with seven state-of-the-art structure alignment approaches, TMalign, DeepAlign, Kpax, 3DCOMB, MICAN, SPalignNS and CLICK. It was shown that FTAlign outperformed the other methods in reproducing manually curated alignments and obtained a high success rate of 96.7 and 90.0% on two gold-standard benchmarks, MALIDUP and MALISAM, respectively. Moreover, FTAlign also achieved the overall best performance in terms of biologically meaningful structure overlap (SO) and TMscore on both the sequential alignment test sets including MALIDUP, MALISAM and 64 difficult cases from HOMSTRAD, and the non-sequential sets including MALIDUP-NS, MALISAM-NS, 199 topology-different cases, where FTAlign especially showed more advantage for non-sequential alignment. Despite its global search feature, FTAlign is also computationally efficient and can normally complete a pairwise alignment within one second.

AVAILABILITY AND IMPLEMENTATION

http://huanglab.phys.hust.edu.cn/ftalign/.

Protein multiple alignments: sequence-based versus structure-based programs

MOTIVATION

Multiple sequence alignment programs have proved to be very useful and have already been evaluated in the literature yet not alignment programs based on structure or both sequence and structure. In the present article we wish to evaluate the added value provided through considering structures.

RESULTS

We compared the multiple alignments resulting from 25 programs either based on sequence, structure or both, to reference alignments deposited in five databases (BALIBASE 2 and 3, HOMSTRAD, OXBENCH and SISYPHUS). On the whole, the structure-based methods compute more reliable alignments than the sequence-based ones, and even than the sequence+structure-based programs whatever the databases. Two programs lead, MAMMOTH and MATRAS, nevertheless the performances of MUSTANG, MATT, 3DCOMB, TCOFFEE+TM_ALIGN and TCOFFEE+SAP are better for some alignments. The advantage of structure-based methods increases at low levels of sequence identity, or for residues in regular secondary structures or buried ones. Concerning gap management, sequence-based programs set less gaps than structure-based programs. Concerning the databases, the alignments of the manually built databases are more challenging for the programs.

AVAILABILITY AND IMPLEMENTATION

All data and results presented in this study are available at: http://wwwabi.snv.jussieu.fr/people/mathilde/download/AliMulComp/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Microsecond Simulation of the Proteoglycan-like Region of Carbonic Anhydrase IX and Design of Chemical Inhibitors Targeting pH Homeostasis in Cancer Cells

Carbonic anhydrase IX (CAIX) is a membrane-bound enzyme associated with tumor hypoxia and found to be over expressed in various tumor conditions. Targeting CAIX catalytic activity is proven to be efficient modality in modulating pH homeostasis in cancer cells. Proteoglycan-like (PG) region is unique to CAIX and is proposed to serve as an antenna enhancing the export of protons in conjunction with facilitated efflux of lactate ions via monocarboxylate transporters. Moreover, the PG region is also reported to contribute to the assembly and maturation of focal adhesion links during cellular attachment and dispersion on solid supports. Thus, drug targeting of this region shall efficiently modulate pH homeostasis and cell adhesion in cancer cells. As the PG region is intrinsically disordered, the complete crystal structure is not elucidated. Hence, in this study, we intend to sample the conformational landscape of the PG region at microsecond scale simulation in order to sample the most probable conformations that shall be utilized for structure-based drug design. In addition, the sampled conformations were subjected to high-throughput virtual screening against NCI and Maybridge datasets to identify potential hits based on consensus scoring and validation by molecular dynamics simulation. Further, the identified hits were experimentally validated for efficacy by in vitro and direct enzymatic assays. The results reveal 5-(2-aminoethyl)-1,2,3-benzenetriol to be the most promising hit as it showed significant CAIX inhibition at all levels of in silico and experimental validation.

Geometric description of self-interaction potential in symmetric protein complexes

Proteins can self-associate with copies of themselves to form symmetric complexes called homomers. Homomers are widespread in all kingdoms of life and allow for unique geometric and functional properties, as reflected in viral capsids or allostery. Once a protein forms a homomer, however, its internal symmetry can compound the effect of point mutations and trigger uncontrolled self-assembly into high-order structures. We identified mutation hot spots for supramolecular assembly, which are predictable by geometry. Here, we present a dataset of descriptors that characterize these hot spot positions both geometrically and chemically, as well as computer scripts allowing the calculation and visualization of these properties for homomers of choice. Since the biological relevance of homomers is not readily available from their X-ray crystallographic structure, we also provide reliability estimates obtained by methods we recently developed. These data have implications in the study of disease-causing mutations, protein evolution and can be exploited in the design of biomaterials.

Design Type(s)	protein interaction analysis objective • protein structure prediction objective • modeling and simulation objective
Measurement Type(s)	protein complex
Technology Type(s)	computational modeling technique
Factor Type(s)	Filtering • source
Sample Characteristic(s)	laboratory environment

Machine-accessible metadata file describing the reported data (ISA-Tab format)

Identification of Novel Interaction Partners of Ets-1: Focus on DNA Repair

The transcription factor Ets-1 (ETS proto-oncogene 1) shows low expression levels except in specific biological processes like haematopoiesis or angiogenesis. Elevated levels of expression are observed in tumor progression, resulting in Ets-1 being named an oncoprotein. It has recently been shown that Ets-1 interacts with two DNA repair enzymes, PARP-1 (poly(ADP-ribose) polymerase 1) and DNA-PK (DNA-dependent protein kinase), through two different domains and that these interactions play a role in cancer. Considering that Ets-1 can bind to distinctly different domains of two DNA repair enzymes, we hypothesized that the interaction can be transposed onto homologs of the respective domains. We have searched for sequence and structure homologs of the interacting ETS(Ets-1), BRCT(PARP-1) and SAP(DNA-PK) domains, and have identified several candidate binding pairs that are currently not annotated as such. Many of the Ets-1 partners are associated to DNA repair mechanisms. We have applied protein-protein docking to establish putative interaction poses and investigated these using centrality analyses at the protein residue level. Most of the identified poses are virtually similar to our recently established interaction model for Ets-1/PARP-1 and Ets-1/DNA-PK. Our work illustrates the potentially high number of interactors of Ets-1, in particular involved in DNA repair mechanisms, which shows the oncoprotein as a potential important regulator of the mechanism.

Protein model quality assessment using 3D oriented convolutional neural networks

Motivation

Protein model quality assessment (QA) is a crucial and yet open problem in structural bioinformatics. The current best methods for single-model QA typically combine results from different approaches, each based on different input features constructed by experts in the field. Then, the prediction model is trained using a machine-learning algorithm. Recently, with the development of convolutional neural networks (CNN), the training paradigm has changed. In computer vision, the expert-developed features have been significantly overpassed by automatically trained convolutional filters. This motivated us to apply a three-dimensional (3D) CNN to the problem of protein model QA.

Results

We developed Ornate (Oriented Routed Neural network with Automatic Typing)—a novel method for single-model QA. Ornate is a residue-wise scoring function that takes as input 3D density maps. It predicts the local (residue-wise) and the global model quality through a deep 3D CNN. Specifically, Ornate aligns the input density map, corresponding to each residue and its neighborhood, with the backbone topology of this residue. This circumvents the problem of ambiguous orientations of the initial models. Also, Ornate includes automatic identification of atom types and dynamic routing of the data in the network. Established benchmarks (CASP 11 and CASP 12) demonstrate the state-of-the-art performance of our approach among single-model QA methods.

Availability and implementation

The method is available at https://team.inria.fr/nano-d/software/Ornate/. It consists of a C++ executable that transforms molecular structures into volumetric density maps, and a Python code based on the TensorFlow framework for applying the Ornate model to these maps.

Supplementary information

Supplementary data are available at Bioinformatics online.

The CYP71AZ P450 Subfamily: A Driving Factor for the Diversification of Coumarin Biosynthesis in Apiaceous Plants

The production of coumarins and furanocoumarins (FCs) in higher plants is widely considered a model illustration of the adaptation of plants to their environment. In this report, we show that the multiplication of cytochrome P450 variants within the CYP71AZ subfamily has contributed to the diversification of these molecules. Multiple copies of genes encoding this enzyme family are found in Apiaceae, and their phylogenetic analysis suggests that they have different functions within these plants. CYP71AZ1 from Ammi majus and CYP71AZ3, 4, and 6 from Pastinaca sativa were functionally characterized. While CYP71AZ3 merely hydroxylated esculetin, the other enzymes accepted both simple coumarins and FCs. Superimposing in silico models of these enzymes led to the identification of different conformations of three regions in the enzyme active site. These sequences were subsequently utilized to mutate CYP71AZ4 to resemble CYP71AZ3. The swapping of these regions lead to significantly modified substrate specificity. Simultaneous mutations of all three regions shifted the specificity of CYP71AZ4 to that of CYP71AZ3, exclusively accepting esculetin. This approach may explain the evolution of this cytochrome P450 family regarding the appearance of FCs in parsnip and possibly in the Apiaceae.

Inferring and Using Protein Quaternary Structure Information from Crystallographic Data

A precise knowledge of the quaternary structure of proteins is essential to illuminate both their function and their evolution. The major part of our knowledge on quaternary structure is inferred from X-ray crystallography data, but this inference process is hard and error-prone. The difficulty lies in discriminating fortuitous protein contacts, which make up the lattice of protein crystals, from biological protein contacts that exist in the native cellular environment. Here, we review methods devised to discriminate between both types of contacts and describe resources for downloading protein quaternary structure information and identifying high-confidence quaternary structures. The use of high-confidence datasets of quaternary structures will be critical for the analysis of structural, functional, and evolutionary properties of proteins.

Classification and Exploration of 3D Protein Domain Interactions Using Kbdock

Comparing and classifying protein domain interactions according to their three-dimensional (3D) structures can help to understand protein structure-function and evolutionary relationships. Additionally, structural knowledge of existing domain-domain interactions can provide a useful way to find structural templates with which to model the 3D structures of unsolved protein complexes. Here we present a straightforward guide to using the "Kbdock" protein domain structure database and its associated web site for exploring and comparing protein domain-domain interactions (DDIs) and domain-peptide interactions (DPIs) at the Pfam domain family level. We also briefly explain how the Kbdock web site works, and we provide some notes and suggestions which should help to avoid some common pitfalls when working with 3D protein domain structures.

Samira-VP: A simple protein alignment method with rechecking the alphabet vector positions

Protein structure alignment and comparisons that are based on an alphabetical demonstration of protein structure are more simple to run with faster evaluation processes; thus, their accuracy is not as reliable as three-dimension (3D)-based tools. As a 1D method candidate, TS-AMIR used the alphabetic demonstration of secondary-structure elements (SSE) of proteins and compared the assigned letters to each SSE using the [Formula: see text]-gram method. Although the results were comparable to those obtained via geometrical methods, the SSE length and accuracy of adjacency between SSEs were not considered in the comparison process. Therefore, to obtain further information on accuracy of adjacency between SSE vectors, the new approach of assigning text to vectors was adopted according to the spherical coordinate system in the present study. Moreover, dynamic programming was applied in order to account for the length of SSE vectors. Five common datasets were selected for method evaluation. The first three datasets were small, but difficult to align, and the remaining two datasets were used to compare the capability of the proposed method with that of other methods on a large protein dataset. The results showed that the proposed method, as a text-based alignment approach, obtained results comparable to both 1D and 3D methods. It outperformed 1D methods in terms of accuracy and 3D methods in terms of runtime.

A bacterial artificial chromosome (BAC) genomic approach reveals partial clustering of the furanocoumarin pathway genes in parsnip

Furanocoumarins are specialized metabolites that are involved in the defense of plants against phytophagous insects. The molecular and functional characterization of the genes involved in their biosynthetic pathway is only partially complete. Many recent reports have described gene clusters responsible for the biosynthesis of specialized metabolites in plants. To investigate possible co-localization of the genes involved in the furanocoumarin pathway, we sequenced parsnip BAC clones spanning two different gene loci. We found that two genes previously identified in this pathway, CYP71AJ3 and CYP71AJ4, were located on the same BAC, whereas a third gene, PsPT1, belonged to a different BAC clone. Chromosome mapping using fluorescence in situ hybridization (FISH) indicated that PsPT1 and the CYP71AJ3-CYP71AJ4 clusters are located on two different chromosomes. Sequencing the BAC clone harboring PsPT1 led to the identification of a gene encoding an Fe(II) α-ketoglutarate-dependent dioxygenase (PsDIOX) situated in the neighborhood of PsPT1 and confirmed the occurrence of a second gene cluster involved in the furanocoumarin pathway. This enzyme metabolizes p-coumaroyl CoA, leading exclusively to the synthesis of umbelliferone, an important intermediate compound in furanocoumarin synthesis. This work provides an insight into the genomic organization of genes from the furanocoumarin biosynthesis pathway organized in more than one gene cluster. It also confirms that the screening of a genomic library and the sequencing of BAC clones represent a valuable tool to identify genes involved in biosynthetic pathways dedicated to specialized metabolite synthesis.

Modeling and minimizing CAPRI round 30 symmetrical protein complexes from CASP-11 structural models

Many of the modeling targets in the blind CASP-11/CAPRI-30 experiment were protein homo-dimers and homo-tetramers. Here, we perform a retrospective docking-based analysis of the perfectly symmetrical CAPRI Round 30 targets whose crystal structures have been published. Starting from the CASP "stage-2" fold prediction models, we show that using our recently developed "SAM" polar Fourier symmetry docking algorithm combined with NAMD energy minimization often gives acceptable or better 3D models of the target complexes. We also use SAM to analyze the overall quality of all CASP structural models for the selected targets from a docking-based perspective. We demonstrate that docking only CASP "center" structures for the selected targets provides a fruitful and economical docking strategy. Furthermore, our results show that many of the CASP models are dockable in the sense that they can lead to acceptable or better models of symmetrical complexes. Even though SAM is very fast, using docking and NAMD energy minimization to pull out acceptable docking models from a large ensemble of docked CASP models is computationally expensive. Nonetheless, thanks to our SAM docking algorithm, we expect that applying our docking protocol on a modern computer cluster will give us the ability to routinely model 3D structures of symmetrical protein complexes from CASP-quality models. Proteins 2017; 85:463-469. © 2016 Wiley Periodicals, Inc.

Calculating and scoring high quality multiple flexible protein structure alignments

MOTIVATION

Calculating multiple protein structure alignments (MSAs) is important for understanding functional and evolutionary relationships between protein families, and for modeling protein structures by homology. While incorporating backbone flexibility promises to circumvent many of the limitations of rigid MSA algorithms, very few flexible MSA algorithms exist today. This article describes several novel improvements to the Kpax algorithm which allow high quality flexible MSAs to be calculated. This article also introduces a new Gaussian-based MSA quality measure called 'M-score', which circumvents the pitfalls of RMSD-based quality measures.

RESULTS

As well as calculating flexible MSAs, the new version of Kpax can also score MSAs from other aligners and from previously aligned reference datasets. Results are presented for a large-scale evaluation of the Homstrad, SABmark and SISY benchmark sets using Kpax and Matt as examples of state-of-the-art flexible aligners and 3DCOMB as an example of a state-of-the-art rigid aligner. These results demonstrate the utility of the M-score as a measure of MSA quality and show that high quality MSAs may be achieved when structural flexibility is properly taken into account.

AVAILABILITY AND IMPLEMENTATION

Kpax 5.0 may be downloaded for academic use at http://kpax.loria.fr/

CONTACT

dave.ritchie@inria.fr

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A new protein structure representation for efficient protein function prediction

One of the challenging problems in bioinformatics is the prediction of protein function. Protein function is the main key that can be used to classify different proteins. Protein function can be inferred experimentally with very small throughput or computationally with very high throughput. Computational methods are sequence based or structure based. Structure-based methods produce more accurate protein function prediction. In this article, we propose a new protein structure representation for efficient protein function prediction. The representation is based on three-dimensional patterns of protein residues. In the analysis, we used protein function based on enzyme activity through six mechanistically diverse enzyme superfamilies: amidohydrolase, crotonase, haloacid dehalogenase, isoprenoid synthase type I, and vicinal oxygen chelate. We applied three different classification methods, naïve Bayes, k-nearest neighbors, and random forest, to predict the enzyme superfamily of a given protein. The prediction accuracy using the proposed representation outperforms a recently introduced representation method that is based only on the distance patterns. The results show that the proposed representation achieved prediction accuracy up to 98%, with improvement of about 10% on average.

The antiproliferative response of indole-3-carbinol in human melanoma cells is triggered by an interaction with NEDD4-1 and disruption of wild-type PTEN degradation

Human melanoma cells displaying distinct PTEN genotypes were used to assess the cellular role of this important tumor-suppressor protein in the antiproliferative response induced by the chemopreventative agent indole-3-carbinol (I3C), a natural indolecarbinol compound derived from the breakdown of glucobrassicin produced in cruciferous vegetables such as broccoli and Brussels sprouts. I3C induced a G1-phase cell-cycle arrest and apoptosis by stabilization of PTEN in human melanoma cells that express wild-type PTEN, but not in cells with mutant or null PTEN genotypes. Importantly, normal human epidermal melanocytes were unaffected by I3C treatment. In wild-type PTEN-expressing melanoma xenografts, formed in athymic mice, I3C inhibited the in vivo tumor growth rate and increased PTEN protein levels in the residual tumors. Mechanistically, I3C disrupted the ubiquitination of PTEN by NEDD4-1 (NEDD4), which prevented the proteasome-mediated degradation of PTEN without altering its transcript levels. RNAi-mediated knockdown of PTEN prevented the I3C-induced apoptotic response, whereas knockdown of NEDD4-1 mimicked the I3C apoptotic response, stabilized PTEN protein levels, and downregulated phosphorylated AKT-1 levels. Co-knockdown of PTEN and NEDD4-1 revealed that I3C-regulated apoptotic signaling through NEDD4-1 requires the presence of the wild-type PTEN protein. Finally, in silico structural modeling, in combination with isothermal titration calorimetry analysis, demonstrated that I3C directly interacts with purified NEDD4-1 protein.

IMPLICATIONS

This study identifies NEDD4-1 as a new I3C target protein, and that the I3C disruption of NEDD4-1 ubiquitination activity triggers the stabilization of the wild-type PTEN tumor suppressor to induce an antiproliferative response in melanoma. Mol Cancer Res; 12(11); 1621-34. ©2014 AACR.

KBDOCK 2013: a spatial classification of 3D protein domain family interactions

Comparing, classifying and modelling protein structural interactions can enrich our understanding of many biomolecular processes. This contribution describes Kbdock (http://kbdock.loria.fr/), a database system that combines the Pfam domain classification with coordinate data from the PDB to analyse and model 3D domain–domain interactions (DDIs). Kbdock can be queried using Pfam domain identifiers, protein sequences or 3D protein structures. For a given query domain or pair of domains, Kbdock retrieves and displays a non-redundant list of homologous DDIs or domain–peptide interactions in a common coordinate frame. Kbdock may also be used to search for and visualize interactions involving different, but structurally similar, Pfam families. Thus, structural DDI templates may be proposed even when there is little or no sequence similarity to the query domains.

Dynamic Programming Used to Align Protein Structures with a Spectrum Is Robust

Several efficient algorithms to conduct pairwise comparisons among large databases of protein structures have emerged in the recent literature. The central theme is the design of a measure between the C_α atoms of two protein chains, from which dynamic programming is used to compute an alignment. The efficiency and efficacy of these algorithms allows large-scale computational studies that would have been previously impractical. The computational study herein shows that the structural alignment algorithm eigen-decomposition alignment with the spectrum (EIGAs) is robust against both parametric and structural variation.