@TOME 3.0: Interfacing Protein Structure Modeling and Ligand Docking.

Knowledge of protein-ligand complexes is essential for efficient drug design. Virtual docking can bring important information on putative complexes but it is still far from being simultaneously fast and accurate. Receptors are flexible and adapt to the incoming small molecules while docking is highly sensitive to small conformational deviations. Conformation ensemble is providing a mean to simulate protein flexibility. However, modeling multiple protein structures for many targets is seldom connected to ligand screening in an efficient and straightforward manner. @TOME-3 is an updated version of our former pipeline @TOME-2, in which protein structure modeling is now directly interfaced with flexible ligand docking. Sequence-sequence profile comparisons identify suitable PDB templates for structure modeling and ligands from these templates are used to deduce binding sites to be screened. In addition, bound ligand can be used as pharmacophoric restraint during the virtual docking. The latter is performed by PLANTS while the docking poses are analysed through multiple chemoinformatics functions. This unique combination of tools allows rapid and efficient ligand docking on multiple receptor conformations in parallel. @TOME-3 is freely available on the web at https://atome.cbs.cnrs.fr.

The structural landscape and diversity of Pyricularia oryzae MAX effectors revisited.

Magnaporthe AVRs and ToxB-like (MAX) effectors constitute a family of secreted virulence proteins in the fungus Pyricularia oryzae (syn. Magnaporthe oryzae), which causes blast disease on numerous cereals and grasses. In spite of high sequence divergence, MAX effectors share a common fold characterized by a ß-sandwich core stabilized by a conserved disulfide bond. In this study, we investigated the structural landscape and diversity within the MAX effector repertoire of P. oryzae. Combining experimental protein structure determination and in silico structure modeling we validated the presence of the conserved MAX effector core domain in 77 out of 94 groups of orthologs (OG) identified in a previous population genomic study. Four novel MAX effector structures determined by NMR were in remarkably good agreement with AlphaFold2 (AF2) predictions. Based on the comparison of the AF2-generated 3D models we propose a classification of the MAX effectors superfamily in 20 structural groups that vary in the canonical MAX fold, disulfide bond patterns, and additional secondary structures in N- and C-terminal extensions. About one-third of the MAX family members remain singletons, without strong structural relationship to other MAX effectors. Analysis of the surface properties of the AF2 MAX models also highlights the high variability within the MAX family at the structural level, potentially reflecting the wide diversity of their virulence functions and host targets.

Adaptive evolution in virulence effectors of the rice blast fungus Pyricularia oryzae.

Plant pathogens secrete proteins called effectors that target host cellular processes to promote disease. Recently, structural genomics has identified several families of fungal effectors that share a similar three-dimensional structure despite remarkably variable amino-acid sequences and surface properties. To explore the selective forces that underlie the sequence variability of structurally-analogous effectors, we focused on MAX effectors, a structural family of effectors that are major determinants of virulence in the rice blast fungus Pyricularia oryzae. Using structure-informed gene annotation, we identified 58 to 78 MAX effector genes per genome in a set of 120 isolates representing seven host-associated lineages. The expression of MAX effector genes was primarily restricted to the early biotrophic phase of infection and strongly influenced by the host plant. Pangenome analyses of MAX effectors demonstrated extensive presence/absence polymorphism and identified gene loss events possibly involved in host range adaptation. However, gene knock-in experiments did not reveal a strong effect on virulence phenotypes suggesting that other evolutionary mechanisms are the main drivers of MAX effector losses. MAX effectors displayed high levels of standing variation and high rates of non-synonymous substitutions, pointing to widespread positive selection shaping the molecular diversity of MAX effectors. The combination of these analyses with structural data revealed that positive selection acts mostly on residues located in particular structural elements and at specific positions. By providing a comprehensive catalog of amino acid polymorphism, and by identifying the structural determinants of the sequence diversity, our work will inform future studies aimed at elucidating the function and mode of action of MAX effectors.

SecretoMyc, a web-based database on mycobacteria secreted proteins and structure-based homology identification using bio-informatics tools.

To better understand the interaction between the host and the Mycobacterium tuberculosis pathogen, it is critical to identify its potential secreted proteins. While various experimental methods have been successful in identifying proteins under specific culture conditions, they have not provided a comprehensive characterisation of the secreted proteome. We utilized a combination of bioinformatics servers and in-house software to identify all potentially secreted proteins from six mycobacterial genomes through the three secretion systems: SEC, TAT, and T7SS. The results are presented in a database that can be crossed referenced to selected proteomics and transcriptomics studies (https://secretomyc.cbs.cnrs.fr). In addition, thanks to the recent availability of Alphafold models, we developed a tool in order to identify the structural homologues among the mycobacterial genomes.

A Mycobacterium tuberculosis Effector Targets Mitochondrion, Controls Energy Metabolism, and Limits Cytochrome c Exit.

Host metabolism reprogramming is a key feature of Mycobacterium tuberculosis (Mtb) infection that enables the survival of this pathogen within phagocytic cells and modulates the immune response facilitating the spread of the tuberculosis disease. Here, we demonstrate that a previously uncharacterized secreted protein from Mtb, Rv1813c, manipulates the host metabolism by targeting mitochondria. When expressed in eukaryotic cells, the protein is delivered to the mitochondrial intermembrane space and promotes the enhancement of host ATP production by boosting the oxidative phosphorylation metabolic pathway. Furthermore, the release of cytochrome c from mitochondria, an early apoptotic event in response to short-term oxidative stress, is delayed in Rv1813c-expressing cells. This study reveals a novel class of mitochondria targeting effectors from Mtb that might participate in host cell metabolic reprogramming and apoptosis control during Mtb infections. IMPORTANCE In this article, using a combination of techniques (bioinformatics, structural biology, and cell biology), we identified and characterized a new class of effectors present only in intracellular mycobacteria. These proteins specifically target host cell mitochondria when ectopically expressed in cells. We showed that one member of this family (Rv1813c) affects mitochondria metabolism in a way that might twist the immune response. This effector also inhibits the cytochrome c exit from mitochondria, suggesting that it might alter normal host cell apoptotic capacities, one of the first defenses of immune cells against Mtb infection.

A new family of structurally conserved fungal effectors displays epistatic interactions with plant resistance proteins.

Recognition of a pathogen avirulence (AVR) effector protein by a cognate plant resistance (R) protein triggers a set of immune responses that render the plant resistant. Pathogens can escape this so-called Effector-Triggered Immunity (ETI) by different mechanisms including the deletion or loss-of-function mutation of the AVR gene, the incorporation of point mutations that allow recognition to be evaded while maintaining virulence function, and the acquisition of new effectors that suppress AVR recognition. The Dothideomycete Leptosphaeria maculans, causal agent of oilseed rape stem canker, is one of the few fungal pathogens where suppression of ETI by an AVR effector has been demonstrated. Indeed, AvrLm4-7 suppresses Rlm3- and Rlm9-mediated resistance triggered by AvrLm3 and AvrLm5-9, respectively. The presence of AvrLm4-7 does not impede AvrLm3 and AvrLm5-9 expression, and the three AVR proteins do not appear to physically interact. To decipher the epistatic interaction between these L. maculans AVR effectors, we determined the crystal structure of AvrLm5-9 and obtained a 3D model of AvrLm3, based on the crystal structure of Ecp11-1, a homologous AVR effector candidate from Fulvia fulva. Despite a lack of sequence similarity, AvrLm5-9 and AvrLm3 are structural analogues of AvrLm4-7 (structure previously characterized). Structure-informed sequence database searches identified a larger number of putative structural analogues among L. maculans effector candidates, including the AVR effector AvrLmS-Lep2, all produced during the early stages of oilseed rape infection, as well as among effector candidates from other phytopathogenic fungi. These structural analogues are named LARS (for Leptosphaeria AviRulence and Suppressing) effectors. Remarkably, transformants of L. maculans expressing one of these structural analogues, Ecp11-1, triggered oilseed rape immunity in several genotypes carrying Rlm3. Furthermore, this resistance could be suppressed by AvrLm4-7. These results suggest that Ecp11-1 shares a common activity with AvrLm3 within the host plant which is detected by Rlm3, or that the Ecp11-1 structure is sufficiently close to that of AvrLm3 to be recognized by Rlm3.

Programmable receptors enable bacterial biosensors to detect pathological biomarkers in clinical samples.

Bacterial biosensors, or bactosensors, are promising agents for medical and environmental diagnostics. However, the lack of scalable frameworks to systematically program ligand detection limits their applications. Here we show how novel, clinically relevant sensing modalities can be introduced into bactosensors in a modular fashion. To do so, we have leveraged a synthetic receptor platform, termed EMeRALD (Engineered Modularized Receptors Activated via Ligand-induced Dimerization) which supports the modular assembly of sensing modules onto a high-performance, generic signaling scaffold controlling gene expression in E. coli. We apply EMeRALD to detect bile salts, a biomarker of liver dysfunction, by repurposing sensing modules from enteropathogenic Vibrio species. We improve the sensitivity and lower the limit-of-detection of the sensing module by directed evolution. We then engineer a colorimetric bactosensor detecting pathological bile salt levels in serum from patients having undergone liver transplant, providing an output detectable by the naked-eye. The EMeRALD technology enables functional exploration of natural sensing modules and rapid engineering of synthetic receptors for diagnostics, environmental monitoring, and control of therapeutic microbes.

Resolving the activation mechanism of the D99N antiterminator LicT protein.

LicT is an antiterminator protein of the BglG family whose members are key players in the control of carbohydrate catabolism in bacteria. These antiterminators are generally composed of three modules, an N-terminal RNA-binding domain (CAT) followed by two homologous regulation modules (PRD1 and PRD2) that control the RNA binding activity of the effector domain via phosphorylation on conserved histidines. Although several structures of isolated domains of BglG-like proteins have been described, no structure containing CAT and at least one PRD simultaneously has yet been reported in an active state, precluding detailed understanding of signal transduction between modules. To fulfill this gap, we recently reported the complete NMR sequence assignment of a constitutively active mutant (D99N) CAT-PRD1*, which contains the effector domain and the first regulation domain of LicT. As a follow-up, we have determined and report here the 3D solution structure of this active, dimeric LicT construct (40 kDa). The structure reveals how the mutation constrains the PRD1 regulation domain into an active conformation which is transduced to CAT via a network of negatively charged residues belonging to PRD1 dimeric interface and to the linker region. In addition, our data support a model where BglG-type antitermination regulatory modules can only adopt a single conformation compatible with the active structure of the effector domain, regardless of whether activation is mediated by mutation on the first or second PRD. The linker between the effector and regulation modules appears to function as an adaptable hinge tuning the position of the functional modules.

Structural Insights into of the Allosteric Activation of the LicT Antiterminator by PTS-Mediated Phosphorylation.

LicT belongs to an essential family of bacterial transcriptional antitermination proteins controlling the expression of sugar-metabolizing operons. When activated, they bind to nascent mRNAs, preventing premature arrest of transcription. The RNA binding capacity of the N-terminal domain CAT is controlled by phosphorylations of two homologous regulation modules by the phosphotransferase system (PTS). Previous studies on truncated and mutant proteins provided partial insight into the mechanism of signal transduction between the effector and regulatory modules. We report here the conformational and functional investigation on the allosteric activation of full-length LicT. Combining fluorescence anisotropy and NMR, we find a tight correlation between LicT RNA binding capacity and CAT closure upon PTS-mediated phosphorylation and phosphomimetic mutations. Our study highlights fine structural differences between activation processes. Furthermore, the NMR study of full-length proteins points to the back and forth propagation of structural restraints from the RNA binding to the distal regulatory module.

Comprehensive classification of the plant non-specific lipid transfer protein superfamily towards its sequence-structure-function analysis.

BACKGROUND: Non-specific Lipid Transfer Proteins (nsLTPs) are widely distributed in the plant kingdom and constitute a superfamily of related proteins. Several hundreds of different nsLTP sequences-and counting-have been characterized so far, but their biological functions remain unclear. It has been clear for years that they present a certain interest for agronomic and nutritional issues. Deciphering their functions means collecting and analyzing a variety of data from gene sequence to protein structure, from cellular localization to the physiological role. As a huge and growing number of new protein sequences are available nowadays, extracting meaningful knowledge from sequence-structure-function relationships calls for the development of new tools and approaches. As nsLTPs show high evolutionary divergence, but a conserved common right handed superhelix structural fold, and as they are involved in a large number of key roles in plant development and defense, they are a stimulating case study for validating such an approach. METHODS: In this study, we comprehensively investigated 797 nsLTP protein sequences, including a phylogenetic analysis on canonical protein sequences, three-dimensional structure modeling and functional annotation using several well-established bioinformatics programs. Additionally, two integrative methodologies using original tools were developed. The first was a new method for the detection of (i) conserved amino acid residues involved in structure stabilization and (ii) residues potentially involved in ligand interaction. The second was a structure-function classification based on the evolutionary trace display method using a new tree visualization interface. We also present a new tool for visualizing phylogenetic trees. RESULTS: Following this new protocol, an updated classification of the nsLTP superfamily was established and a new functional hypothesis for key residues is suggested. Lastly, this work allows a better representation of the diversity of plant nsLTPs in terms of sequence, structure and function.

KNOTTIN: the database of inhibitor cystine knot scaffold after 10 years, toward a systematic structure modeling.

Knottins, or inhibitor cystine knots (ICKs), are ultra-stable miniproteins with multiple applications in drug design and medical imaging. These widespread and functionally diverse proteins are characterized by the presence of three interwoven disulfide bridges in their structure, which form a unique pseudoknot. Since 2004, the KNOTTIN database (www.dsimb.inserm.fr/KNOTTIN/) has been gathering standardized information about knottin sequences, structures, functions and evolution. The website also provides access to bibliographic data and to computational tools that have been specifically developed for ICKs. Here, we present a major upgrade of our database, both in terms of data content and user interface. In addition to the new features, this article describes how KNOTTIN has seen its size multiplied over the past ten years (since its last publication), notably with the recent inclusion of predicted ICKs structures. Finally, we report how our web resource has proved usefulness for the researchers working on ICKs, and how the new version of the KNOTTIN website will continue to serve this active community.

Recognition of the Magnaporthe oryzae Effector AVR-Pia by the Decoy Domain of the Rice NLR Immune Receptor RGA5.

Nucleotide binding domain and leucine-rich repeat proteins (NLRs) are important receptors in plant immunity that allow recognition of pathogen effectors. The rice (Oryza sativa) NLR RGA5 recognizes the Magnaporthe oryzae effector AVR-Pia through direct interaction. Here, we gained detailed insights into the molecular and structural bases of AVR-Pia-RGA5 interaction and the role of the RATX1 decoy domain of RGA5. NMR titration combined with in vitro and in vivo protein-protein interaction analyses identified the AVR-Pia interaction surface that binds to the RATX1 domain. Structure-informed AVR-Pia mutants showed that, although AVR-Pia associates with additional sites in RGA5, binding to the RATX1 domain is necessary for pathogen recognition but can be of moderate affinity. Therefore, RGA5-mediated resistance is highly resilient to mutations in the effector. We propose a model that explains such robust effector recognition as a consequence, and an advantage, of the combination of integrated decoy domains with additional independent effector-NLR interactions.

Structure Analysis Uncovers a Highly Diverse but Structurally Conserved Effector Family in Phytopathogenic Fungi.

Phytopathogenic ascomycete fungi possess huge effector repertoires that are dominated by hundreds of sequence-unrelated small secreted proteins. The molecular function of these effectors and the evolutionary mechanisms that generate this tremendous number of singleton genes are largely unknown. To get a deeper understanding of fungal effectors, we determined by NMR spectroscopy the 3-dimensional structures of the Magnaporthe oryzae effectors AVR1-CO39 and AVR-Pia. Despite a lack of sequence similarity, both proteins have very similar 6 ß-sandwich structures that are stabilized in both cases by a disulfide bridge between 2 conserved cysteins located in similar positions of the proteins. Structural similarity searches revealed that AvrPiz-t, another effector from M. oryzae, and ToxB, an effector of the wheat tan spot pathogen Pyrenophora tritici-repentis have the same structures suggesting the existence of a family of sequence-unrelated but structurally conserved fungal effectors that we named MAX-effectors (Magnaporthe Avrs and ToxB like). Structure-informed pattern searches strengthened this hypothesis by identifying MAX-effector candidates in a broad range of ascomycete phytopathogens. Strong expansion of the MAX-effector family was detected in M. oryzae and M. grisea where they seem to be particularly important since they account for 5-10% of the effector repertoire and 50% of the cloned avirulence effectors. Expression analysis indicated that the majority of M. oryzae MAX-effectors are expressed specifically during early infection suggesting important functions during biotrophic host colonization. We hypothesize that the scenario observed for MAX-effectors can serve as a paradigm for ascomycete effector diversity and that the enormous number of sequence-unrelated ascomycete effectors may in fact belong to a restricted set of structurally conserved effector families.

Structure and modeling of knottins, a promising molecular scaffold for drug discovery.

The knottins are extremely stable miniproteins present in many species and are able to perform various tasks. Owing to its small size and its amazing stability, the knottin structural domain is considered as an excellent scaffold for drug development. Several recent databases and web servers dedicated to or aware of knottins have appeared and are shortly described. Altogether they provide a valuable ensemble of data and of specific tools that greatly facilitate knottin-based studies. The essential structural features of the knottin scaffold, which heavily rest on the three knotted disulfide bridges for its stability, are reviewed. These include small but well-conserved secondary structures and hydrogen bonding networks, but also several further interactions that have been shown to be essential for stability and/or activity. Examples are supplementary disulfide bridges, side chain hydrogen bonds, or circularization. General structure prediction and modeling tools are not well fitted to knottins, and several specific tools have been developed. Specifically, methods to assign a disulfide connectivity pattern to small disulfide-rich sequences or to build accurate 3D models of knottins are available and are discussed in the review. Although more works are still needed to better understand sequence-structure-function relationships, recent studies strongly suggest that existing applications of knottins as drugs (i.e. painkillers), molecules for diagnosis, or insecticidal crop treatment should rapidly generalize and extend to other fields as well, e.g. as antimicrobials.

Optimizing structural modeling for a specific protein scaffold: knottins or inhibitor cystine knots.

BACKGROUND: Knottins are small, diverse and stable proteins with important drug design potential. They can be classified in 30 families which cover a wide range of sequences (1621 sequenced), three-dimensional structures (155 solved) and functions (> 10). Inter knottin similarity lies mainly between 15% and 40% sequence identity and 1.5 to 4.5 Å backbone deviations although they all share a tightly knotted disulfide core. This important variability is likely to arise from the highly diverse loops which connect the successive knotted cysteines. The prediction of structural models for all knottin sequences would open new directions for the analysis of interaction sites and to provide a better understanding of the structural and functional organization of proteins sharing this scaffold. RESULTS: We have designed an automated modeling procedure for predicting the three-dimensionnal structure of knottins. The different steps of the homology modeling pipeline were carefully optimized relatively to a test set of knottins with known structures: template selection and alignment, extraction of structural constraints and model building, model evaluation and refinement. After optimization, the accuracy of predicted models was shown to lie between 1.50 and 1.96 Å from native structures at 50% and 10% maximum sequence identity levels, respectively. These average model deviations represent an improvement varying between 0.74 and 1.17 Å over a basic homology modeling derived from a unique template. A database of 1621 structural models for all known knottin sequences was generated and is freely accessible from our web server at http://knottin.cbs.cnrs.fr. Models can also be interactively constructed from any knottin sequence using the structure prediction module Knoter1D3D available from our protein analysis toolkit PAT at http://pat.cbs.cnrs.fr. CONCLUSIONS: This work explores different directions for a systematic homology modeling of a diverse family of protein sequences. In particular, we have shown that the accuracy of the models constructed at a low level of sequence identity can be improved by 1) a careful optimization of the modeling procedure, 2) the combination of multiple structural templates and 3) the use of conserved structural features as modeling restraints.

Knottin cyclization: impact on structure and dynamics.

BACKGROUND: Present in various species, the knottins (also referred to as inhibitor cystine knots) constitute a group of extremely stable miniproteins with a plethora of biological activities. Owing to their small size and their high stability, knottins are considered as excellent leads or scaffolds in drug design. Two knottin families contain macrocyclic compounds, namely the cyclotides and the squash inhibitors. The cyclotide family nearly exclusively contains head-to-tail cyclized members. On the other hand, the squash family predominantly contains linear members. Head-to-tail cyclization is intuitively expected to improve bioactivities by increasing stability and lowering flexibility as well as sensitivity to proteolytic attack. RESULTS: In this paper, we report data on solution structure, thermal stability, and flexibility as inferred from NMR experiments and molecular dynamics simulations of a linear squash inhibitor EETI-II, a circular squash inhibitor MCoTI-II, and a linear analog lin-MCoTI. Strikingly, the head-to-tail linker in cyclic MCoTI-II is by far the most flexible region of all three compounds. Moreover, we show that cyclic and linear squash inhibitors do not display large differences in structure or flexibility in standard conditions, raising the question as to why few squash inhibitors have evolved into cyclic compounds. The simulations revealed however that the cyclization increases resistance to high temperatures by limiting structure unfolding. CONCLUSION: In this work, we show that, in contrast to what could have been intuitively expected, cyclization of squash inhibitors does not provide clear stability or flexibility modification. Overall, our results suggest that, for squash inhibitors in standard conditions, the circularization impact might come from incorporation of an additional loop sequence, that can contribute to the miniprotein specificity and affinity, rather than from an increase in conformational rigidity or protein stability. Unfolding simulations showed however that cyclization is a stabilizing factor in strongly denaturing conditions. This information should be useful if one wants to use the squash inhibitor scaffold in drug design.

Structure and folding of disulfide-rich miniproteins: insights from molecular dynamics simulations and MM-PBSA free energy calculations.

The fold of small disulfide-rich proteins largely relies on two or more disulfide bridges that are main components of the hydrophobic core. Because of the small size of these proteins and their high cystine content, the cysteine connectivity has been difficult to ascertain in some cases, leading to uncertainties and debates in the literature. Here, we use molecular dynamics simulations and MM-PBSA free energy calculations to compare similar folds with different disulfide pairings in two disulfide-rich miniprotein families, namely the knottins and the short-chain scorpion toxins, for which the connectivity has been discussed. We first show that the MM-PBSA approach is able to discriminate the correct knotted topology of knottins from the laddered one. Interestingly, a comparison of the free energy components for kalata B1 and MCoTI-II suggests that cyclotides and squash inhibitors, although sharing the same scaffold, are stabilized through different interactions. Application to short-chain scorpion toxins suggests that the conventional cysteine pairing found in many homologous toxins is significantly more stable than the unconventional pairing reported for maurotoxin and for spinoxin. This would mean that native maurotoxin and spinoxin are not at the lowest free energy minimum and might result from kinetically rather than thermodynamically driven oxidative folding processes. For both knottins and toxins, the correct or conventional disulfide connectivities provide lower flexibilities and smaller deviations from the initial conformations. Overall, our work suggests that molecular dynamics simulations and the MM-PBSA approach to estimate free energies are useful tools to analyze and compare disulfide bridge connectivities in miniproteins.

KNOTTIN: the knottin or inhibitor cystine knot scaffold in 2007.

The KNOTTIN database provides standardized information on the small disulfide-rich proteins with a knotted topology called knottins or inhibitor cystine knots. Static pages present the essential historical or recent results about knottin discoveries, sequences, structures, syntheses, folding, functions, applications and bibliography. New tools, KNOTER3D and KNOTER1D, are provided to determine or predict if a user query (3D structure or sequence) is a knottin. These tools are now used to automate the database update. All knottin structures and sequences in the database are now standardized according to the knottin nomenclature based on loop lengths between knotted cysteines, and to the knottin numbering scheme. Therefore, the whole KNOTTIN database (sequences and structures) can now be searched using loop lengths, in addition to keyword and sequence (BLAST, HMMER) searches. Renumbered and structurally fitted knottin PDB files are available for download as well as renumbered sequences, sequence alignments and logos. The knottin numbering scheme is used for automatic drawing of standardized two-dimensional Colliers de Perles of any knottin structure or sequence in the database or provided by the user. The KNOTTIN database is available at http://knottin.cbs.cnrs.fr.

PAT: a protein analysis toolkit for integrated biocomputing on the web.

PAT, for Protein Analysis Toolkit, is an integrated biocomputing server. The main goal of its design was to facilitate the combination of different processing tools for complex protein analyses and to simplify the automation of repetitive tasks. The PAT server provides a standardized web interface to a wide range of protein analysis tools. It is designed as a streamlined analysis environment that implements many features which strongly simplify studies dealing with protein sequences and structures and improve productivity. PAT is able to read and write data in many bioinformatics formats and to create any desired pipeline by seamlessly sending the output of a tool to the input of another tool. PAT can retrieve protein entries from identifier-based queries by using pre-computed database indexes. Users can easily formulate complex queries combining different analysis tools with few mouse clicks, or via a dedicated macro language, and a web session manager provides direct access to any temporary file generated during the user session. PAT is freely accessible on the Internet at http://pat.cbs.cnrs.fr.

EvDTree: structure-dependent substitution profiles based on decision tree classification of 3D environments.

BACKGROUND: Structure-dependent substitution matrices increase the accuracy of sequence alignments when the 3D structure of one sequence is known, and are successful e.g. in fold recognition. We propose a new automated method, EvDTree, based on a decision tree algorithm, for automatic derivation of amino acid substitution probabilities from a set of sequence-structure alignments. The main advantage over other approaches is an unbiased automatic selection of the most informative structural descriptors and associated values or thresholds. This feature allows automatic derivation of structure-dependent substitution scores for any specific set of structures, without the need to empirically determine best descriptors and parameters. RESULTS: Decision trees for residue substitutions were constructed for each residue type from sequence-structure alignments extracted from the HOMSTRAD database. For each tree cluster, environment-dependent substitution profiles were derived. The resulting structure-dependent substitution scores were assessed using a criterion based on the mean ranking of observed substitution among all possible substitutions and in sequence-structure alignments. The automatically built EvDTree substitution scores provide significantly better results than conventional matrices and similar or slightly better results than other structure-dependent matrices. EvDTree has been applied to small disulfide-rich proteins as a test case to automatically derive specific substitutions scores providing better results than non-specific substitution scores. Analyses of the decision tree classifications provide useful information on the relative importance of different structural descriptors. CONCLUSIONS: We propose a fully automatic method for the classification of structural environments and inference of structure-dependent substitution profiles. We show that this approach is more accurate than existing methods for various applications. The easy adaptation of EvDTree to any specific data set opens the way for class-specific structure-dependent substitution scores which can be used in threading-based remote homology searches.