Transmembrane protein-protein interactions
Membrane proteins account for about one-third of the proteomes of organisms and include structural proteins, channels, and receptors. The mutual interactions they establish play crucial roles in organisms, as they are behind many processes such as cell signaling and protein function. These proteins and their molecular complexes present potential pharmacological targets par excellence for a variety of diseases, with very important implications for the design and discovery of new drugs. Yet, structural data coming from experiments is very scarce for this family of proteins.
To overcome this problem, we have developed a computational knowledge-based approach to predict the transmembrane interactions of integral cell membrane proteins by computational approaches with the goal of understanding their modulation of cell signaling. Our approach uses data mining, sequence analysis, motif search, extraction, identification and characterization of the amino acid residues at the interface of the complexes, leading to the formulation of binding sites used to parse protein sequence datasets for generating new potential interacting protein partners. Our template motif-based approach using experimental PPI recognition sites leads us to predict new binding sites up to a desired amino acid mutation rate and to thousands of new binary complexes between membrane proteins. Because of their number and diversity, these complexes and their interfaces represent potential pharmacological targets for the discovery of drugs or peptides modulating or inhibiting the interaction.
An illustration of the outcome of a prediction of interactions between transmembrane segments of membrane proteins by TransINT showing: interaction number, organism name, and for each of the proteins A and B predicted to interact: UniProt ID, name of protein, interaction motif, number of contact residues andmotif’s mutation rate. The last column shows a link to additional information, such as amino acid sequence, specific interaction motif sequence, related 3D structures if available, transmembrane region, and others.
As soon as they are transcribed, all the RNA molecules in a cell are bound by different sets of RNA-binding proteins (RBP) whose task is one of regulating their correct processing, transport, stability and function/translation, all the way to degradation. RBPs are mostly nuclear proteins involved in RNA-splicing and can associate with stress granules under stress conditions. A subfamily of RBPs, the cold-shock domain proteins (CSP), binds single-stranded nucleotides (RNA or DNA) through one or several cold shock domains (CSD), a protein domain of about 70 amino acids found in prokaryotic and eukaryotic DNA- and RNA-binding proteins. The misregulation of the genes involved in ARN metabolism or the autophagy/proteasome pathway play a key role in the onset and the progression of several neurodegenerative diseases and of cancer. Besides transcription, translation is also altered to favor the expression of oncogenes involved in different processes like cancer invasiveness and drug resistance. On another hand, single-nucleotide variations of main misfolded proteins, sometimes located also in stress granules, are involved in tumor cell growth and several types of cancer (colon, skin, uterine, breast, lung, liver, etc.).
Our approach consists in applying and developing structural bioinformatics methodologies to generate accurate 3D models of the CSP-RNA molecular complexes of interest to the lab (YB-1, Lin28a, Lin28b, SOD1, FUS, TDP-43, CSDE1, RBM-45, G3BP1, …), leading to the prediction and analysis of physicochemical and biological properties that are difficult to access by experimental means, accelerating thus the understanding of the biological mechanisms of action and having important implications for the design and discovery of new drugs. The analysis of those complexes shall allow us to understand the different types of interaction taking place and the effects of pathogenic mutations that we are going to map on the 3D models of the complexes.
Experimental structural data coming from this laboratory (Atomic Force Microscopy and Nuclear Magnetic Resonance) will be complementary to the modeling of the CSP-RNA complexes.
B.Sc. in Chemistry (Licenciatura de Quimica). National Autonomous University of Mexico (UNAM), Mexico, Mexico, May 1977. Thesis: «A theoretical study in quantum chemistry on the conformations of an inorganic addition complex» (in Spanish).
Ph.D. in Physical-chemistry/Physics. Louisiana State University, Baton Rouge, Louisiana, USA, May 1983. Thesis «Statistical mechanics of conformational transitions in biopolymers » in Diss. Abst. Intnl. (in English).
H.D.R. in Structural Bioinformatics. Université de Paris VII Denis Diderot, Paris, France, January 2004. Thesis «Theoretical methods for the study of the structure, the function and the mechanisms of molecular recognition in biology» (in French).
Biology, Physics, Biochemistry, Computer science, Chemistry, Mathematics
FIELDS OF EXPERTISE
Structural bioinformatics, Model building, Molecular modeling and simulation
INSTRUCTOR 2005- 2010. UAM, Dept. of Biotechnology; Universidad Autonoma del Estado de Morelos, Centro de Biotecnologia; Escuela Superior de Medicina y Homéopatia, Instituto Politécnico Nacional, “Molecular Structural Bioinformatics: Theoretical and computational methods for the study of biological macromolecules”.
INSTRUCTOR 2004 UAM’s 30th anniversary. Mexico City, Mexico. Course in Molecular Structural Bioinformatics “Theoretical and computational methods for the study of biological macromolecules”.
LECTURER 2004 International School on Computational Sciences for Complex Systems in Biology (CSSB 2004). Rovereto, Italy. « Theoretical methods for the study of the 3D structure, the function and the recognition mechanisms of biological macromolecules ».
INSTRUCTOR 2004 EMBO course « Biomolecular Simulation », Institut Pasteur, Paris, France.
INSTRUCTOR 2003-2009. Departamento de Biotecnologia, Universidad Autonoma Metropolitana (UAM), Mexico, and Centro de Biotecnologia, Universidad Autonoma del Estado de Morelos (UAEM), Cuernavaca, Mexico. « Molecular structural bioinformatics: Theoretical and computational methods for the study of biological macromolecules ».
LECTURER 1999-2004. Institut Pasteur. DEA de Structure, Fonction et Ingénierie des Protéines, U. De Paris VII.
LECTURER 1990 – 1993. Université de Paris V, Faculté de Pharmacie. Master (DEA) of molecular pharmacochemistry, experimental pharmacology and metabolism.
LECTURER 1984 – 1986. Rutgers University, Chemistry Department.
TEACHING ASSISTANT 1977 – 1981. Louisiana State University, Chemistry Department.
CEDRE Franco-lebanese program Partenariats Hubert Curien with the laboratory of Dr. Georges KHAZEN (Lebanese American University, Lebanon). « Multiprotein complexes at the cell membrane: data mining and molecular recognition ».
FRR Fonds pour le Rayonnement de la Recherche financing program.. Université d’Evry-Val-d’Essonne, France.
ECOS-Nord Franco-mexican scientific cooperation program, « Study of the stability and inhibition of biological molecular systems of relevance in molecular medicine »
Master trainings, Doctorate theses, postdoctoral fellows and invited research associates.