Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design

Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model.National Institute of General Medical Sciences (U.S.) (Award R01 GM110048

With or without force? : European public opinion on democracy promotion

A Large part of the education provided at colleges and universities of today requires for thestudent to be more independent in their studies. This demands that the physical space,where the students choose to study, is designed in a way that can encourage and supportlearning. It seems as though that many of the learning spaces of today don’t always meetthe students’ needs. The university library at the University of Umeå is currently planningto design new learning spaces for the students. The aim of this study is to examine how thephysical learning space can be designed to engage and encourage the students in theirlearning process. Based on literature describing learning spaces we have initially identified three mainareas to examine- Learning, Information Technology and Learning space design. Theseareas are all important features in the design of new learning spaces. With informationdrawn from that literature we conducted an empirical study at the library of the Universityof Umeå. The empirical study was carried out through observations and focus groupinterviews. To give us more insight about the students’ thoughts about the learning spacewe also compared our findings with a survey conducted by the library personnel in 2008and 2010. The result of our study shows that there are some areas to be improved in theexisting learning space. The students are working more collaboratively which requiresmore group areas. Our study also shows that flexibility, more student interaction and asocial and engaging environment are all important features in the design of new learningspaces

Peptide Ligands for Pro-survival Protein Bfl-1 from Computationally Guided Library Screening

Pro-survival members of the Bcl-2 protein family inhibit cell death by binding short helical BH3 motifs in pro-apoptotic proteins. Mammalian pro-survival proteins Bcl-x[subscript L], Bcl-2, Bcl-w, Mcl-1, and Bfl-1 bind with varying affinities and specificities to native BH3 motifs, engineered peptides, and small molecules. Biophysical studies have determined interaction patterns for these proteins, particularly for the most-studied family members Bcl-x[subscript L] and Mcl-1. Bfl-1 is a pro-survival protein implicated in preventing apoptosis in leukemia, lymphoma, and melanoma. Although Bfl-1 is a promising therapeutic target, relatively little is known about its binding preferences. We explored the binding of Bfl-1 to BH3-like peptides by screening a peptide library that was designed to sample a high degree of relevant sequence diversity. Screening using yeast-surface display led to several novel high-affinity Bfl-1 binders and to thousands of putative binders identified through deep sequencing. Further screening for specificity led to identification of a peptide that bound to Bfl-1 with K[subscript d] < 1 nM and very slow dissociation from Bfl-1 compared to other pro-survival Bcl-2 family members. A point mutation in this sequence gave a peptide with ~50 nM affinity for Bfl-1 that was selective for Bfl-1 in equilibrium binding assays. Analysis of engineered Bfl-1 binders deepens our understanding of how the binding profiles of pro-survival proteins differ and may guide the development of targeted Bfl-1 inhibitors.National Institute of General Medical Sciences (U.S.) (Award GM084181)National Institute of General Medical Sciences (U.S.) (Award P50-GM68762

Protein 3D Structure Computed from Evolutionary Sequence Variation

The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. Deciphering the evolutionary record held in these sequences and exploiting it for predictive and engineering purposes presents a formidable challenge. The potential benefit of solving this challenge is amplified by the advent of inexpensive high-throughput genomic sequencing

Trends in template/fragment-free protein structure prediction

Predicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward

Sequence Motifs in MADS Transcription Factors Responsible for Specificity and Diversification of Protein-Protein Interaction

Protein sequences encompass tertiary structures and contain information about specific molecular interactions, which in turn determine biological functions of proteins. Knowledge about how protein sequences define interaction specificity is largely missing, in particular for paralogous protein families with high sequence similarity, such as the plant MADS domain transcription factor family. In comparison to the situation in mammalian species, this important family of transcription regulators has expanded enormously in plant species and contains over 100 members in the model plant species Arabidopsis thaliana. Here, we provide insight into the mechanisms that determine protein-protein interaction specificity for the Arabidopsis MADS domain transcription factor family, using an integrated computational and experimental approach. Plant MADS proteins have highly similar amino acid sequences, but their dimerization patterns vary substantially. Our computational analysis uncovered small sequence regions that explain observed differences in dimerization patterns with reasonable accuracy. Furthermore, we show the usefulness of the method for prediction of MADS domain transcription factor interaction networks in other plant species. Introduction of mutations in the predicted interaction motifs demonstrated that single amino acid mutations can have a large effect and lead to loss or gain of specific interactions. In addition, various performed bioinformatics analyses shed light on the way evolution has shaped MADS domain transcription factor interaction specificity. Identified protein-protein interaction motifs appeared to be strongly conserved among orthologs, indicating their evolutionary importance. We also provide evidence that mutations in these motifs can be a source for sub- or neo-functionalization. The analyses presented here take us a step forward in understanding protein-protein interactions and the interplay between protein sequences and network evolution

Energetics and Dynamics Across the Bcl-2-Regulated Apoptotic Pathway Reveal Distinct Evolutionary Determinants of Specificity and Affinity

Critical regulatory pathways are replete with instances of intra- and interfamily protein-protein interactions due to the pervasiveness of gene duplication throughout evolution. Discerning the specificity determinants within these systems has proven a challenging task. Here, we present an energetic analysis of the specificity determinants within the Bcl-2 family of proteins (key regulators of the intrinsic apoptotic pathway) via a total of ∼20 μs of simulation of 60 distinct protein-protein complexes. We demonstrate where affinity and specificity of protein-protein interactions arise across the family, and corroborate our conclusions with extensive experimental evidence. We identify energy and specificity hotspots that may offer valuable guidance in the design of targeted therapeutics for manipulating the protein-protein interactions within the apoptosis-regulating pathway. Moreover, we propose a conceptual framework that allows us to quantify the relationship between sequence, structure, and binding energetics. This approach may represent a general methodology for investigating other paralogous protein-protein interaction sites.</p

Computational design of self-assembling cyclic protein homo-oligomers

Self-assembling cyclic protein homo-oligomers play important roles in biology, and the ability to generate custom homo-oligomeric structures could enable new approaches to probe biological function. Here we report a general approach to design cyclic homo-oligomers that employs a new residue-pair-transform method to assess the designability of a protein-protein interface. This method is sufficiently rapid to enable the systematic enumeration of cyclically docked arrangements of a monomer followed by sequence design of the newly formed interfaces. We use this method to design interfaces onto idealized repeat proteins that direct their assembly into complexes that possess cyclic symmetry. Of 96 designs that were characterized experimentally, 21 were found to form stable monodisperse homo-oligomers in solution, and 15 (four homodimers, six homotrimers, six homotetramers and one homopentamer) had solution small-angle X-ray scattering data consistent with the design models. X-ray crystal structures were obtained for five of the designs and each is very close to their corresponding computational model