HSP70 sequestration by free α-globin promotes ineffective erythropoiesis in ß-thalassaemia.

ß-Thalassaemia major (ß-TM) is an inherited haemoglobinopathy caused by a quantitative defect in the synthesis of ß-globin chains of haemoglobin, leading to the accumulation of free α-globin chains that form toxic aggregates. Despite extensive knowledge of the molecular defects causing ß-TM, little is known of the mechanisms responsible for the ineffective erythropoiesis observed in the condition, which is characterized by accelerated erythroid differentiation, maturation arrest and apoptosis at the polychromatophilic stage. We have previously demonstrated that normal human erythroid maturation requires a transient activation of caspase-3 at the later stages of maturation. Although erythroid transcription factor GATA-1, the master transcriptional factor of erythropoiesis, is a caspase-3 target, it is not cleaved during erythroid differentiation. We have shown that, in human erythroblasts, the chaperone heat shock protein70 (HSP70) is constitutively expressed and, at later stages of maturation, translocates into the nucleus and protects GATA-1 from caspase-3 cleavage. The primary role of this ubiquitous chaperone is to participate in the refolding of proteins denatured by cytoplasmic stress, thus preventing their aggregation. Here we show in vitro that during the maturation of human ß-TM erythroblasts, HSP70 interacts directly with free α-globin chains. As a consequence, HSP70 is sequestrated in the cytoplasm and GATA-1 is no longer protected, resulting in end-stage maturation arrest and apoptosis. Transduction of a nuclear-targeted HSP70 mutant or a caspase-3-uncleavable GATA-1 mutant restores terminal maturation of ß-TM erythroblasts, which may provide a rationale for new targeted therapies of ß-TM.

Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins.

Protein-RNA complexes are important for many biological processes. However, structural modeling of such complexes is hampered by the high flexibility of RNA. Particularly challenging is the docking of single-stranded RNA (ssRNA). We have developed a fragment-based approach to model the structure of ssRNA bound to a protein, based on only the protein structure, the RNA sequence and conserved contacts. The conformational diversity of each RNA fragment is sampled by an exhaustive library of trinucleotides extracted from all known experimental protein-RNA complexes. The method was applied to ssRNA with up to 12 nucleotides which bind to dimers of the RNA recognition motifs (RRMs), a highly abundant eukaryotic RNA-binding domain. The fragment based docking allows a precise de novo atomic modeling of protein-bound ssRNA chains. On a benchmark of seven experimental ssRNA-RRM complexes, near-native models (with a mean heavy-atom deviation of <3 Å from experiment) were generated for six out of seven bound RNA chains, and even more precise models (deviation < 2 Å) were obtained for five out of seven cases, a significant improvement compared to the state of the art. The method is not restricted to RRMs but was also successfully applied to Pumilio RNA binding proteins.

Raltegravir flexibility and its impact on recognition by the HIV-1 IN targets.

HIV-1 IN is a pertinent target for the development of AIDS chemotherapy. The first IN-specific inhibitor approved for the treatment of HIV/AIDS, RAL, was designed to block the ST reaction. We characterized the structural and conformational features of RAL and its recognition by putative HIV-1 targets - the unbound IN, the vDNA, and the IN•vDNA complex - mimicking the IN states over the integration process. RAL binding to the targets was studied by performing an extensive sampling of the inhibitor conformational landscape and by using four different docking algorithms: Glide, Autodock, VINA, and SurFlex. The obtained data evidenced that: (i) a large binding pocket delineated by the active site and an extended loop in the unbound IN accommodates RAL in distinct conformational states all lacking specific interactions with the target; (ii) a well-defined cavity formed by the active site, the vDNA, and the shortened loop in the IN•vDNA complex provide a more optimized inhibitor binding site in which RAL chelates Mg(2+) cations; (iii) a specific recognition between RAL and the unpaired cytosine of the processed DNA is governed by a pair of strong H-bonds similar to those observed in DNA base pair G-C. The identified RAL pose at the cleaved vDNA shed light on a putative step of RAL inhibition mechanism. This modeling study indicates that the inhibition process may include as a first step RAL recognition by the processed vDNA bound to a transient intermediate IN state, and thus provides a potentially promising route to the design of IN inhibitors with improved affinity and selectivity.

Rapid Design of Knowledge-Based Scoring Potentials for Enrichment of Near-Native Geometries in Protein-Protein Docking.

Protein-protein docking protocols aim to predict the structures of protein-protein complexes based on the structure of individual partners. Docking protocols usually include several steps of sampling, clustering, refinement and re-scoring. The scoring step is one of the bottlenecks in the performance of many state-of-the-art protocols. The performance of scoring functions depends on the quality of the generated structures and its coupling to the sampling algorithm. A tool kit, GRADSCOPT (GRid Accelerated Directly SCoring OPTimizing), was designed to allow rapid development and optimization of different knowledge-based scoring potentials for specific objectives in protein-protein docking. Different atomistic and coarse-grained potentials can be created by a grid-accelerated directly scoring dependent Monte-Carlo annealing or by a linear regression optimization. We demonstrate that the scoring functions generated by our approach are similar to or even outperform state-of-the-art scoring functions for predicting near-native solutions. Of additional importance, we find that potentials specifically trained to identify the native bound complex perform rather poorly on identifying acceptable or medium quality (near-native) solutions. In contrast, atomistic long-range contact potentials can increase the average fraction of near-native poses by up to a factor 2.5 in the best scored 1% decoys (compared to existing scoring), emphasizing the need of specific docking potentials for different steps in the docking protocol.