Ruth Nussinov

Principles of Protein-Protein Interactions: What are the Preferred Ways For Proteins To Interact?

Koc University, Center for Computational Biology and Bioinformatics and College of Engineering, Rumelifeneri Yolu, 34450 Sariyer Istanbul, Turkey; Basic Research Program, SAIC−Frederick, Inc., Center for Cancer Research Nanobiology Program, NCIsFrederick, Frederick, Maryland 21702; and Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel

Aβ(1–42) fibril structure illuminates self-recognition and replication of amyloid in Alzheimer's disease

Increasing evidence has suggested that formation and propagation of misfolded aggregates of 42-residue human amyloid β (Aβ(1–42)), rather than of the more abundant Aβ(1–40), provokes the Alzheimers disease cascade. However, structural details of misfolded Aβ(1–42) have remained elusive. Here we present the atomic model of an Aβ(1–42) amyloid fibril, from solid-state NMR (ssNMR) data. It displays triple parallel-β-sheet segments that differ from reported structures of Aβ(1–40) fibrils. Remarkably, Aβ(1–40) is incompatible with the triple-β-motif, because seeding with Aβ(1–42) fibrils does not promote conversion of monomeric Aβ(1–40) into fibrils via cross-replication. ssNMR experiments suggest that C-terminal Ala42, absent in Aβ(1–40), forms a salt bridge with Lys28 to create a self-recognition molecular switch that excludes Aβ(1–40). The results provide insight into the Aβ(1–42)-selective self-replicating amyloid-propagation machinery in early-stage Alzheimers disease.

Tree graphs of RNA secondary structures and their comparisons

To facilitate comparison of RNA secondary structures each structure is represented as an ordered labeled tree. Several alternate secondary structures yielding a set of trees can be computed for any given RNA molecule (sequence). Frequently recurring subtrees are searched in this set of trees. The consensus structure motifs are then selected and used to construct a secondary structure model of the RNA. Given the difficulties involved in RNA secondary structure calculations, this procedure may significantly improve our predictive capabilities. In addition, the change of secondary structures between two different RNA sequences is described as a transformation of ordered trees. The transferable ratio of tree A from tree B is defined as a proportion of the largest common subtrees in trees A and B occurring in tree A. The method is applied to the study of the mechanism of human alpha 1 globin pre-mRNA splicing. In the study, two tentative splicing mechanisms, A and B, with different orders of intron excision from alpha 1 globin pre-mRNA have been stimulated. A possible relationship between the structural features of the secondary structures and the order of intron excision in the pathway of precursor splicing of human alpha 1 globin is discussed.

The Underappreciated Role of Allostery in the Cellular Network

Allosteric propagation results in communication between distinct sites in the protein structure; it also encodes specific effects on cellular pathways, and in this way it shapes cellular response. One example of long-range effects is binding of morphogens to cell surface receptors, which initiates a cascade of protein interactions that leads to genome activation and specific cellular action. Allosteric propagation results from combinations of multiple factors, takes place through dynamic shifts of conformational ensembles, and affects the equilibria of macromolecular interactions. Here, we (a) emphasize the well-known yet still underappreciated role of allostery in conveying explicit signals across large multimolecular assemblies and distances to specify cellular action; (b) stress the need for quantitation of the allosteric effects; and finally, (c) propose that each specific combination of allosteric effectors along the pathway spells a distinct function. The challenges are colossal; the inspiring reward will be predicting function, misfunction, and outcomes of drug regimes.

Restricted Mobility of Conserved Residues in Protein-Protein Interfaces in Molecular Simulations☆☆

Conserved residues in protein-protein interfaces correlate with residue hot-spots. To obtain insight into their roles, we have studied their mobility. We have performed 39 explicit solvent simulations of 15 complexes and their monomers, with the interfaces varying in size, shape, and function. The dynamic behavior of conserved residues in unbound monomers illustrates significantly lower flexibility as compared to their environment, suggesting that already before binding they are constrained in a boundlike configuration. To understand this behavior, we have analyzed the inter- and intrachain hydrogen-bond residence-time in the interfaces. We find that conserved residues are not involved significantly in hydrogen bonds across the interface as compared to nonconserved. However, the monomer simulations reveal that conserved residues contribute dominantly to hydrogen-bond formation before binding. Packing of conserved residues across the trajectories is significantly higher before and after the binding, rationalizing their lower mobility. Backbone torsional angle distributions show that conserved residues assume restricted regions of space and the most visited conformations in the bound and unbound trajectories are similar, suggesting that conserved residues are preorganized. Combined with previous studies, we conclude that conserved residues, hot spots, anchor, and interface-buried residues may be similar residues, fulfilling similar roles.

The Design of Covalent Allosteric Drugs

A key issue in drug discovery is how to reduce drug dosage and increase specificity while retaining or increasing efficacy, as high dosage is often linked to toxicity. There are two types of drugs on the market: orthosteric and allosteric. Orthosteric drugs can be noncovalent or covalent. The latter are advantageous because they may be prescribed in lower doses, but their potential off-target toxicity is a primary concern. The chief advantages of allosteric drugs are their higher specificity and their consequently lower chance of toxic side effects. Covalent allosteric drugs combine the pharmacological merits of covalent drugs with the additional benefit of the higher specificity of allosteric drugs. In a recent promising step in therapeutic drug development, allosteric, disulfide-tethered fragments successfully modulated the activity of a protein kinase and K-Ras.

Release Factors eRF1 and RF2 A UNIVERSAL MECHANISM CONTROLS THE LARGE CONFORMATIONAL CHANGES

Class I release factors 1 and 2 (RF1 and RF2) terminate protein synthesis by recognizing stop codons on the mRNA via their conserved amino acid motifs (NIKS in eRF1 and SPF in RF2) and by the conserved tripeptide (GGQ) interactions with the ribosomal peptidyltransferase center. Crystal structures of eRF1 and RF2 do not fit their ribosomal binding pocket (∼73 Å). Cryoelectron microscopy indicates large conformational changes in the ribosome-bound RF2. Here, we investigate the conformational dynamics of the eRF1 and RF2 using molecular dynamics simulation, structural alignment, and electrostatic analysis of domain interactions. We show that relaxed eRF1 has a shape remarkably similar to the ribosome-bound RF2 observed by cryoelectron microscopy. The similarity between the two release factors is as good as between elongation factor G and elongation factor Tu-guanosine-5′(β,γ-imido)triphosphate-tRNA. Further, the conformational transitions and dynamics of eRF1 and RF2 between the free and ribosome-bound states are most likely controlled by protonation of conserved histidines. For eRF1, the distance between the NIKS and GGQ motifs shrinks from 97.5 Å in the crystal to 70–80 Å. For RF2, the separation between SPF and GGQ elongates from 32 Å in the crystal to 50 Å. Coulombic interaction strongly favors the open conformation of eRF1; however, solvation and histidine protonation modulate the domain interactions, making the closed conformation of eRF1 more accessible. Thus, RF1 and RF2 function like molecular machines, most likely fueled by histidine protonation. The unified conformational control and the shapes of eRF1 and RF2 support the proposition that the termination of protein synthesis involves similar mechanisms across species.

An efficient string matching algorithm with k differences for nucleotide and amino acid sequences.

There are a few algorithms designed to solve the problem of the optimal alignment of one sequence, the pattern, of length m, with another, longer sequence the text, of length n. These algorithms allow mismatches, deletions and insertions. Algorithms to date run in O(mn) time. Let us define an integer, k, which is the maximal number of differences allowed. We present a simple algorithm showing that sequences can be optimally aligned in O(k2n) time. For long sequences the gain factor over the currently used algorithms is very large.

RNA pseudoknots downstream of the frameshift sites of retroviruses

Abstract RNA pseudoknot structural motifs could have implications for a wide range of biological processes of RNAs. In this study, the potential RNA pseudoknots just downstream from the known and suspected retroviral frameshift sites were predicted in the Rous sarcoma virus, primate immunodeficiency viruses (HIV-1, HIV-2, and SIV), equine infectious anemia virus, visna virus, bovine leukemia virus, human T-cell leukemia virus (types I and II), mouse mammary tumor virus, Mason-Pfizer monkey virus, and simian SRV-1 type-D retrovirus. Also, the putative RNA pseudoknots were detected in the gag-pol overlaps of two retrotransposons of Drosophila, 17.6 and gypsy, and the mouse intracisternal A particle. For each sequence, the thermodynamic stability and statistical significance of the secondary structure involved in the predicted tertiary structure were assessed and compared. Our results show that the stem-loop structures in the pseudoknots are both thermodynamically highly stable and statistically significant relative to other such configurations that potentially occur in the gag-pool or gag-pro and pro-pol junction domains of these viruses (300 nucleotides upstream and downstream from the possible frameshift sites are included). Moreover, the structural features of the predicted pseudoknots following the frameshift site of propol overlaps of the HTLV-1 and HTLV-2 retroviruses are structurally well conserved. The occurence of eight compensatory base changes in the tertiary interaction of the two related sequences allow the conservation of their tertiary structures in spite of the sequence divergence. The results support the possible control mechanism for frameshifting proposed by Brierley et al. [1] and Jacks et al. [2, 3].

Mechanism of Membrane Permeation Induced by Synthetic β-Hairpin Peptides

We have investigated the membrane destabilizing properties of synthetic amphiphilic cationic peptides, MAX1 and MAX35, which have the propensity to form β-hairpin structures under certain conditions, and a control non-β-hairpin-forming peptide MAX8V16E. All three peptides bind to liposomes containing a mixture of zwitterionic POPC and negatively charged POPS lipids as determined by Zeta potential measurements. Circular dichroism measurements indicated folding of MAX1 and MAX35 in the presence of the POPC/POPS liposomes, whereas no such folding was observed with MAX8V16E. There was no binding or folding of these peptides to liposomes containing only POPC. MAX1 and MAX35 induced release of contents from negatively charged liposomes, whereas MAX8V16E failed to promote solute release under identical conditions. Thus, MAX1 and MAX35 bind to, and fold at the surface of negatively charged liposomes adopting a lytic conformation. We ruled out leaky fusion as a mechanism of release by including 2 mol % PEG-PE in the liposomes, which inhibits aggregation/fusion but not folding of MAX or MAX-induced leakage. Using a concentration-dependent quenching probe (calcein), we determined that MAX-induced leakage of liposome contents was an all-or-none process. At MAX1 concentrations, which cause release of ~50% of the liposomes that contain small (R(h) <1.5 nm) markers, only ~15% of those liposomes release a fluorescent dextran of 40 kDa. A multimeric model of the pore is presented based on these results. Atomistic molecular dynamics simulations show that barrels consisting of 10 β-hairpin MAX1 and MAX35 peptides are relatively more stable than MAX8V16E barrels in the bilayer, suggesting that barrels of this size are responsible for the peptides lytic action.