Demo Data from VLDB 2026 / reviewers in the wild / expert
Leonardo Pardo
dblp:44/4296
· DBLP profile ↗
5ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0003-1778-7420ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 5
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Bioinformatics and computational biology · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › drug discovery
drug design |
0.3 | 1 | 2018 | The size matters? A computational tool to design bivalent ligands · Bioinform. 2018 |
Bioinformatics and computational biology › protein structure analysis › membrane protein analysis
membrane protein structure |
0.2 | 1 | 2013 | Relation between sequence and structure in membrane proteins · Bioinform. 2013 |
Bioinformatics and computational biology
protein structure analysis |
0.2 | 1 | 2013 | Relation between sequence and structure in membrane proteins · Bioinform. 2013 |
Bioinformatics and computational biology › structural bioinformatics
sequence-structure relationship |
0.2 | 1 | 2013 | Relation between sequence and structure in membrane proteins · Bioinform. 2013 |
Bioinformatics and computational biology › structural bioinformatics
structural similarity |
0.2 | 1 | 2013 | Relation between sequence and structure in membrane proteins · Bioinform. 2013 |
Bioinformatics and computational biology › protein structure prediction › template-based modeling
homology modeling |
0.0 | 1 | 2013 | Relation between sequence and structure in membrane proteins · Bioinform. 2013 |
Methods — techniques the papers use, named apart from their topics
pharmacophore linking · 0.3molecular modeling · 0.3structural alignment · 0.2rmsd calculation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | The size matters? A computational tool to design bivalent ligandsabstractMotivation: Bivalent ligands are increasingly important such as for targeting G protein-coupled receptor (GPCR) dimers or proteolysis targeting chimeras (PROTACs). They contain two pharmacophoric units that simultaneously bind in their corresponding binding sites, connected with a spacer chain. Here, we report a molecular modelling tool that links the pharmacophore units via the shortest pathway along the receptors van der Waals surface and then scores the solutions providing prioritization for the design of new bivalent ligands. Results: Bivalent ligands of known dimers of GPCRs, PROTACs and a model bivalent antibody/antigen system were analysed. The tool could rapidly assess the preferred linker length for the different systems and recapitulated the best reported results. In the case of GPCR dimers the results suggest that in some cases these ligands might bind to a secondary binding site at the extracellular entrance (vestibule or allosteric site) instead of the orthosteric binding site. Availability and implementation: Freely accessible from the Molecular Operating Environment svl exchange server (https://svl.chemcomp.com/). Supplementary information: Supplementary data are available at Bioinformatics online. Laura Pérez-Benito, Andrew Henry, Minos-Timotheos Matsoukas, Laura Lopez, Daniel Pulido, Miriam Royo, Arnau Cordomí, Gary Tresadern, Leonardo Pardo |
Bioinform. | 9 |
| 2018 | Identifying human diamine sensors for death related putrescine and cadaverine moleculesabstractPungent chemical compounds originating from decaying tissue are strong drivers of animal behavior. Two of the best-characterized death smell components are putrescine (PUT) and cadaverine (CAD), foul-smelling molecules produced by decarboxylation of amino acids during decomposition. These volatile polyamines act as 'necromones', triggering avoidance or attractive responses, which are fundamental for the survival of a wide range of species. The few studies that have attempted to identify the cognate receptors for these molecules have suggested the involvement of the seven-helix trace amine-associated receptors (TAARs), localized in the olfactory epithelium. However, very little is known about the precise chemosensory receptors that sense these compounds in the majority of organisms and the molecular basis of their interactions. In this work, we have used computational strategies to characterize the binding between PUT and CAD with the TAAR6 and TAAR8 human receptors. Sequence analysis, homology modeling, docking and molecular dynamics studies suggest a tandem of negatively charged aspartates in the binding pocket of these receptors which are likely to be involved in the recognition of these small biogenic diamines. Cristina Izquierdo, José Carlos Gómez-Tamayo, Jean-Christophe Nebel, Leonardo Pardo, Angel Gonzalez |
PLoS Comput. Biol. | 4 |
| 2015 | TMalphaDB and TMbetaDB: web servers to study the structural role of sequence motifs in α-helix and β-barrel domains of membrane proteinsabstractBACKGROUND: Membrane proteins represent over 25 % of human protein genes and account for more than 60 % of drug targets due to their accessibility from the extracellular environment. The increasing number of available crystal structures of these proteins in the Protein Data Bank permits an initial estimation of their structural properties. DESCRIPTION: We have developed two web servers-TMalphaDB for α-helix bundles and TMbetaDB for β-barrels-to analyse the growing repertoire of available crystal structures of membrane proteins. TMalphaDB and TMbetaDB permit to search for these specific sequence motifs in a non-redundant structure database of transmembrane segments and quantify structural parameters such as ϕ and ψ backbone dihedral angles, χ1 side chain torsion angle, unit bend and unit twist. CONCLUSIONS: The structural information offered by TMalphaDB and TMbetaDB permits to quantify structural distortions induced by specific sequence motifs, and to elucidate their role in the 3D structure. This specific structural information has direct implications in homology modeling of the growing sequences of membrane proteins lacking experimental structure. TMalphaDB and TMbetaDB are freely available at http://lmc.uab.cat/TMalphaDB and http://lmc.uab.cat/TMbetaDB. Marc Perea, Ivar Lugtenburg, Eduardo Mayol, Arnau Cordomí, Xavier Deupí, Leonardo Pardo, Mireia Olivella |
BMC Bioinform. | 6 |
| 2015 | GPCRtm: An amino acid substitution matrix for the transmembrane region of class A G Protein-Coupled ReceptorsabstractBACKGROUND: Protein sequence alignments and database search methods use standard scoring matrices calculated from amino acid substitution frequencies in general sets of proteins. These general-purpose matrices are not optimal to align accurately sequences with marked compositional biases, such as hydrophobic transmembrane regions found in membrane proteins. In this work, an amino acid substitution matrix (GPCRtm) is calculated for the membrane spanning segments of the G protein-coupled receptor (GPCR) rhodopsin family; one of the largest transmembrane protein family in humans with great importance in health and disease. RESULTS: The GPCRtm matrix reveals the amino acid compositional bias distinctive of the GPCR rhodopsin family and differs from other standard substitution matrices. These membrane receptors, as expected, are characterized by a high content of hydrophobic residues with regard to globular proteins. On the other hand, the presence of polar and charged residues is higher than in average membrane proteins, displaying high frequencies of replacement within themselves. CONCLUSIONS: Analysis of amino acid frequencies and values obtained from the GPCRtm matrix reveals patterns of residue replacements different from other standard substitution matrices. GPCRs prioritize the reactivity properties of the amino acids over their bulkiness in the transmembrane regions. A distinctive role is that charged and polar residues seem to evolve at different rates than other amino acids. This observation is related to the role of the transmembrane bundle in the binding of ligands, that in many cases involve electrostatic and hydrogen bond interactions. This new matrix can be useful in database search and for the construction of more accurate sequence alignments of GPCRs. Santiago Ríos, Gianluigi Caltabiano, Mercedes Campillo, Leonardo Pardo, Angel Gonzalez |
BMC Bioinform. | 5 |
| 2013 | Relation between sequence and structure in membrane proteinsabstractMOTIVATION: Integral polytopic membrane proteins contain only two types of folds in their transmembrane domains: α-helix bundles and β-barrels. The increasing number of available crystal structures of these proteins permits an initial estimation of how sequence variability affects the structure conservation in their transmembrane domains. We, thus, aim to determine the pairwise sequence identity necessary to maintain the transmembrane molecular architectures compatible with the hydrophobic nature of the lipid bilayer. RESULTS: Root-mean-square deviation (rmsd) and sequence identity were calculated from the structural alignments of pairs of homologous polytopic membrane proteins sharing the same fold. Analysis of these data reveals that transmembrane segment pairs with sequence identity in the so-called 'twilight zone' (20-35%) display high-structural similarity (rmsd < 1.5 Å). Moreover, a large group of β-barrel pairs with low-sequence identity (<20%) still maintain a close structural similarity (rmsd < 2.5 Å). Thus, we conclude that fold preservation in transmembrane regions requires less sequence conservation than for globular proteins. These findings have direct implications in homology modeling of evolutionary-related membrane proteins. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Mireia Olivella, Angel Gonzalez, Leonardo Pardo, Xavier Deupí |
Bioinform. | 3 |