scholarly journals PLUG (Pruning of Local Unrealistic Geometries) removes restrictions on biophysical modeling for protein design

2018 ◽  
Vol 87 (1) ◽  
pp. 62-73 ◽  
Author(s):  
Mark A. Hallen
Keyword(s):  
Protein Design ◽  
Biophysical Modeling

scholarly journals OSPREY 3.0: Open-Source Protein Redesign for You, with Powerful New Features

2018 ◽  
Author(s):  
Mark A. Hallen ◽  
Jeffrey W. Martin ◽  
Adegoke Ojewole ◽  
Jonathan D. Jou ◽  
Anna U. Lowegard ◽  
...  
Keyword(s):  
Protein Binding ◽  
Open Source ◽  
Protein Design ◽  
Open Source Software ◽  
Ease Of Use ◽  
Biophysical Modeling ◽  
Order Of Magnitude ◽  
Design Software ◽  
Protein Redesign ◽  
New Algorithms

We present OSPREY 3.0, a new and greatly improved release of the OSPREY protein design software. OSPREY 3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions of OSPREY when running the same algorithms on the same hardware. Moreover, OSPREY 3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions of OSPREY, OSPREY 3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically that OSPREY 3.0 accurately predicts the effect of mutations on protein-protein binding. OSPREY 3.0 is available at http://www.cs.duke.edu/donaldlab/osprey.php as free and open-source software.

scholarly journals PLUG (Pruning of Local Unrealistic Geometries) removes restrictions on biophysical modeling for protein design

2018 ◽  
Author(s):  
Mark A. Hallen
Keyword(s):  
Protein Design ◽  
Conformational Space ◽  
Biophysical Model ◽  
Biophysical Modeling ◽  
Backbone Flexibility ◽  
Energy Functions ◽  
Design Algorithm ◽  
Dead End ◽  
Pruning Algorithms ◽  
Design Calculations

AbstractProtein design algorithms must search an enormous conformational space to identify favorable conformations. As a result, those that perform this search with guarantees of accuracy generally start with a conformational pruning step, such as dead-end elimination (DEE). However, the mathematical assumptions of DEE-based pruning algorithms have up to now severely restricted the biophysical model that can feasibly be used in protein design. To lift these restrictions, I propose to prune local unrealistic geometries (PLUG) using a linear programming-based method. PLUG’s biophysical model consists only of well-known lower bounds on interatomic distances. PLUG is intended as pre-processing for energy-based protein design calculations, whose biophysical model need not support DEE pruning. Based on 96 test cases, PLUG is at least as effective at pruning as DEE for larger protein designs—the type that most require pruning. When combined with the LUTE protein design algorithm, PLUG greatly facilitates designs that account for continuous entropy, large multistate designs with continuous flexibility, and designs with extensive continuous backbone flexibility and advanced non-pairwise energy functions. Many of these designs are tractable only with PLUG, either for empirical reasons (LUTE’s machine learning step achieves an accurate fit only after PLUG pruning), or for theoretical reasons (many energy functions are fundamentally incompatible with DEE).

Protein-design papers challenged

Nature ◽  
2009 ◽  
Author(s):  
Erika Check Hayden
Keyword(s):  
Protein Design

Automatic Procedures for Protein Design

2001 ◽  
Vol 4 (8) ◽  
pp. 643-659 ◽  
Author(s):  
Alfonso Jaramillo ◽  
Lorenz Wernisch ◽  
Stephanie Hery ◽  
Shosana Wodak
Keyword(s):  
Protein Design

scholarly journals Influence of protein (human galectin-3) design on aspects of lectin activity

2020 ◽  
Vol 154 (2) ◽  
pp. 135-153 ◽  
Author(s):  
Gabriel García Caballero ◽  
Donella Beckwith ◽  
Nadezhda V. Shilova ◽  
Adele Gabba ◽  
Tanja J. Kutzner ◽  
...  
Keyword(s):  
Protein Design ◽  
Full Range ◽  
Biological Information ◽  
The Novel ◽  
Modular Assembly ◽  
Binding Partners ◽  
Galectin 3 ◽  
Potential Applications ◽  
Similar Affinity

Abstract The concept of biomedical significance of the functional pairing between tissue lectins and their glycoconjugate counterreceptors has reached the mainstream of research on the flow of biological information. A major challenge now is to identify the principles of structure–activity relationships that underlie specificity of recognition and the ensuing post-binding processes. Toward this end, we focus on a distinct feature on the side of the lectin, i.e. its architecture to present the carbohydrate recognition domain (CRD). Working with a multifunctional human lectin, i.e. galectin-3, as model, its CRD is used in protein engineering to build variants with different modular assembly. Hereby, it becomes possible to compare activity features of the natural design, i.e. CRD attached to an N-terminal tail, with those of homo- and heterodimers and the tail-free protein. Thermodynamics of binding disaccharides proved full activity of all proteins at very similar affinity. The following glycan array testing revealed maintained preferential contact formation with N-acetyllactosamine oligomers and histo-blood group ABH epitopes irrespective of variant design. The study of carbohydrate-inhibitable binding of the test panel disclosed up to qualitative cell-type-dependent differences in sections of fixed murine epididymis and especially jejunum. By probing topological aspects of binding, the susceptibility to inhibition by a tetravalent glycocluster was markedly different for the wild-type vs the homodimeric variant proteins. The results teach the salient lesson that protein design matters: the type of CRD presentation can have a profound bearing on whether basically suited oligosaccharides, which for example tested positively in an array, will become binding partners in situ. When lectin-glycoconjugate aggregates (lattices) are formed, their structural organization will depend on this parameter. Further testing (ga)lectin variants will thus be instrumental (i) to define the full range of impact of altering protein assembly and (ii) to explain why certain types of design have been favored during the course of evolution, besides opening biomedical perspectives for potential applications of the novel galectin forms.

scholarly journals Searching for the Pareto frontier in multi-objective protein design

2017 ◽  
Vol 9 (4) ◽  
pp. 339-344 ◽  
Author(s):  
Vikas Nanda ◽  
Sandeep V. Belure ◽  
Ofer M. Shir
Keyword(s):  
Protein Design ◽  
Pareto Frontier ◽  
Multi Objective

scholarly journals Bottom-up de novo protein design

2021 ◽  
Vol 18 (3) ◽  
pp. 233-233
Author(s):  
Arunima Singh
Keyword(s):  
Protein Design ◽  
De Novo ◽  
Bottom Up ◽  
De Novo Protein Design
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