Showing papers by "Vincent Zoete published in 2013"

Shaping the interaction landscape of bioactive molecules.

Abstract: MOTIVATION: Most bioactive molecules perform their action by interacting with proteins or other macromolecules. However, for a significant fraction of them, the primary target remains unknown. In addition, the majority of bioactive molecules have more than one target, many of which are poorly characterized. Computational predictions of bioactive molecule targets based on similarity with known ligands are powerful to narrow down the number of potential targets and to rationalize side effects of known molecules. RESULTS: Using a reference set of 224 412 molecules active on 1700 human proteins, we show that accurate target prediction can be achieved by combining different measures of chemical similarity based on both chemical structure and molecular shape. Our results indicate that the combined approach is especially efficient when no ligand with the same scaffold or from the same chemical series has yet been discovered. We also observe that different combinations of similarity measures are optimal for different molecular properties, such as the number of heavy atoms. This further highlights the importance of considering different classes of similarity measures between new molecules and known ligands to accurately predict their targets. CONTACT: olivier.michielin@unil.ch or vincent.zoete@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SwissBioisostere: a database of molecular replacements for ligand design

Abstract: The SwissBioisostere database (http://www.swissbioisostere.ch) contains information on molecular replacements and their performance in biochemical assays. It is meant to provide researchers in drug discovery projects with ideas for bioisosteric modifications of their current lead molecule, as well as to give interested scientists access to the details on particular molecular replacements. As of August 2012, the database contains 21,293,355 datapoints corresponding to 5,586,462 unique replacements that have been measured in 35,039 assays against 1948 molecular targets representing 30 target classes. The accessible data were created through detection of matched molecular pairs and mining bioactivity data in the ChEMBL database. The SwissBioisostere database is hosted by the Swiss Institute of Bioinformatics and available via a web-based interface.

Structure-Based, Rational Design of T Cell Receptors

Abstract: Adoptive cell transfer using engineered T cells is emerging as a promising treatment for metastatic melanoma Such an approach allows one to introduce T cell receptor (TCR) modifications that, while maintaining the specificity for the targeted antigen, can enhance the binding and kinetic parameters for the interaction with peptides (p) bound to major histocompatibility complexes (MHC) Using the well-characterized 2C TCR/SIYR/H-2K(b) structure as a model system, we demonstrated that a binding free energy decomposition based on the MM-GBSA approach provides a detailed and reliable description of the TCR/pMHC interactions at the structural and thermodynamic levels Starting from this result, we developed a new structure-based approach, to rationally design new TCR sequences, and applied it to the BC1 TCR targeting the HLA-A2 restricted NY-ESO-1157-165 cancer-testis epitope Fifty-four percent of the designed sequence replacements exhibited improved pMHC binding as compared to the native TCR, with up to 150-fold increase in affinity, while preserving specificity Genetically engineered CD8(+) T cells expressing these modified TCRs showed an improved functional activity compared to those expressing BC1 TCR We measured maximum levels of activities for TCRs within the upper limit of natural affinity, K D = ∼1 - 5 μM Beyond the affinity threshold at K D < 1 μM we observed an attenuation in cellular function, in line with the "half-life" model of T cell activation Our computer-aided protein-engineering approach requires the 3D-structure of the TCR-pMHC complex of interest, which can be obtained from X-ray crystallography We have also developed a homology modeling-based approach, TCRep 3D, to obtain accurate structural models of any TCR-pMHC complexes when experimental data is not available Since the accuracy of the models depends on the prediction of the TCR orientation over pMHC, we have complemented the approach with a simplified rigid method to predict this orientation and successfully assessed it using all non-redundant TCR-pMHC crystal structures available These methods potentially extend the use of our TCR engineering method to entire TCR repertoires for which no X-ray structure is available We have also performed a steered molecular dynamics study of the unbinding of the TCR-pMHC complex to get a better understanding of how TCRs interact with pMHCs This entire rational TCR design pipeline is now being used to produce rationally optimized TCRs for adoptive cell therapies of stage IV melanoma

RNA pentaloop structures as effective targets of regulators belonging to the RsmA/CsrA protein family.

Abstract: In the Gac/Rsm signal transduction pathway of Pseudomonas fluorescens CHA0, the dimeric RNA-binding proteins RsmA and RsmE, which belong to the vast bacterial RsmA/CsrA family, effectively repress translation of target mRNAs containing a typical recognition sequence near the translation start site. Three small RNAs (RsmX, RsmY, RsmZ) with clustered recognition sequences can sequester RsmA and RsmE and thereby relieve translational repression. According to a previously established structural model, the RsmE protein makes optimal contacts with an RNA sequence 5'- (A)/(U)CANGGANG(U)/(A)-3', in which the central ribonucleotides form a hexaloop. Here, we questioned the relevance of the hexaloop structure in target RNAs. We found that two predicted pentaloop structures, AGGGA (in pltA mRNA encoding a pyoluteorin biosynthetic enzyme) and AAGGA (in mutated pltA mRNA), allowed effective interaction with the RsmE protein in vivo. By contrast, ACGGA and AUGGA were poor targets. Isothermal titration calorimetry measurements confirmed the strong binding of RsmE to the AGGGA pentaloop structure in an RNA oligomer. Modeling studies highlighted the crucial role of the second ribonucleotide in the loop structure. In conclusion, a refined structural model of RsmE-RNA interaction accommodates certain pentaloop RNAs among the preferred hexaloop RNAs.

Protein pocket and ligand shape comparison and its application in virtual screening.

Abstract: Understanding molecular recognition is one major requirement for drug discovery and design. Physicochemical and shape complementarity between two binding partners is the driving force during complex formation. In this study, the impact of shape within this process is analyzed. Protein binding pockets and co-crystallized ligands are represented by normalized principal moments of inertia ratios (NPRs). The corresponding descriptor space is triangular, with its corners occupied by spherical, discoid, and elongated shapes. An analysis of a selected set of sc-PDB complexes suggests that pockets and bound ligands avoid spherical shapes, which are, however, prevalent in small unoccupied pockets. Furthermore, a direct shape comparison confirms previous studies that on average only one third of a pocket is filled by its bound ligand, supplemented by a 50 % subpocket coverage. In this study, we found that shape complementary is expressed by low pairwise shape distances in NPR space, short distances between the centers-of-mass, and small deviations in the angle between the first principal ellipsoid axes. Furthermore, it is assessed how different binding pocket parameters are related to bioactivity and binding efficiency of the co-crystallized ligand. In addition, the performance of different shape and size parameters of pockets and ligands is evaluated in a virtual screening scenario performed on four representative targets.

Monoubiquitination and activity of the paracaspase MALT1 requires glutamate 549 in the dimerization interface.

Abstract: The mucosa-associated lymphoid tissue protein-1 (MALT1, also known as paracaspase) is a protease whose activity is essential for the activation of lymphocytes and the growth of cells derived from human diffuse large B-cell lymphomas of the activated B-cell subtype (ABC DLBCL). Crystallographic approaches have shown that MALT1 can form dimers via its protease domain, but why dimerization is relevant for the biological activity of MALT1 remains largely unknown. Using a molecular modeling approach, we predicted Glu 549 (E549) to be localized within the MALT1 dimer interface and thus potentially relevant. Experimental mutation of this residue into alanine (E549A) led to a complete impairment of MALT1 proteolytic activity. This correlated with an impaired capacity of the mutant to form dimers of the protease domain in vitro, and a reduced capacity to promote NF-κB activation and transcription of the growth-promoting cytokine interleukin-2 in antigen receptor-stimulated lymphocytes. Moreover, this mutant could not rescue the growth of ABC DLBCL cell lines upon MALT1 silencing. Interestingly, the MALT1 mutant E549A was unable to undergo monoubiquitination, which we identified previously as a critical step in MALT1 activation. Collectively, these findings suggest a model in which E549 at the dimerization interface is required for the formation of the enzymatically active, monoubiquitinated form of MALT1.

Physicochemical properties of exogenous molecules correlated with their biological efficacy as protectors against carcinogenesis and inflammation

Abstract: A large number of molecules referred to here as M, several of which are extracted from plants, belong to different chemical classes and exhibit chemoprotective activity against carcinogenesis and inflammation in rodents and in vitro cell culture. The aim of this article is to review and analyse our previous investigations on linear correlations observed between physicochemical parameters of the tested molecules M and their biological efficacies measured in vivo and/or in vitro. The principal physicochemical parameters studied characterise the energy required to oxidise M into M•+, E(M•+/M), namely its first vertical ionisation potential, and the energy liberated by the addition of an electron to M, i.e. its vertical electron affinity. These physicochemical properties were determined experimentally using diverse techniques and theoretically using mainly semiempirical (AM1) and density functional theory (DFT) quantum mechanical methods.

Recurrent Structural Motifs in Non-Homologous Protein Structures

Abstract: We have extracted an extensive collection of recurrent structural motifs (RSMs), which consist of sequentially non-contiguous structural motifs (4–6 residues), each of which appears with very similar conformation in three or more mutually unrelated protein structures. We find that the proteins in our set are covered to a substantial extent by the recurrent non-contiguous structural motifs, especially the helix and strand regions. Computational alanine scanning calculations indicate that the average folding free energy changes upon alanine mutation for most types of non-alanine residues are higher for amino acids that are present in recurrent structural motifs than for amino acids that are not. The non-alanine amino acids that are most common in the recurrent structural motifs, i.e., phenylalanine, isoleucine, leucine, valine and tyrosine and the less abundant methionine and tryptophan, have the largest folding free energy changes. This indicates that the recurrent structural motifs, as we define them, describe recurrent structural patterns that are important for protein stability. In view of their properties, such structural motifs are potentially useful for inter-residue contact prediction and protein structure refinement.

Prediction of Cross-Recognition of Peptide-HLA A2 by Melan-A-Specific Cytotoxic T Lymphocytes Using Three-Dimensional Quantitative Structure-Activity Relationships

Abstract: The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.