scholarly journals A De Novo Protein Binding Pair By Computational Design and Directed Evolution

2011 ◽  
Vol 42 (2) ◽  
pp. 250-260 ◽  
Author(s):  
John Karanicolas ◽  
Jacob E. Corn ◽  
Irwin Chen ◽  
Lukasz A. Joachimiak ◽  
Orly Dym ◽  
...  
Keyword(s):  
Protein Binding ◽  
Directed Evolution ◽  
De Novo ◽  
Computational Design

scholarly journals Computational Design of the Sequence and Structure of a Protein-Binding Peptide

2011 ◽  
Vol 133 (12) ◽  
pp. 4190-4192 ◽  
Author(s):  
Deanne W. Sammond ◽  
Dustin E. Bosch ◽  
Glenn L. Butterfoss ◽  
Carrie Purbeck ◽  
Mischa Machius ◽  
...  
Keyword(s):  
Protein Binding ◽  
Computational Design ◽  
Binding Peptide

Artificial Enzymes bringing together Computational Design and Directed Evolution

2021 ◽  
Author(s):  
Beatriz de Pina Mariz ◽  
Sara S Carvalho ◽  
Iris Batalha ◽  
Ana Sofia Pina
Keyword(s):  
Directed Evolution ◽  
Chemical Reactions ◽  
Computational Design ◽  
Industrial Processes ◽  
Artificial Enzymes ◽  
Ancient Times

Enzymes are proteins that catalyse chemical reactions and, as such, have been widely used to facilitate a variety of natural and industrial processes, dating back to ancient times. In fact,...

scholarly journals De novo design of self-assembling helical protein filaments

Science ◽  
2018 ◽  
Vol 362 (6415) ◽  
pp. 705-709 ◽  
Author(s):  
Hao Shen ◽  
Jorge A. Fallas ◽  
Eric Lynch ◽  
William Sheffler ◽  
Bradley Parry ◽  
...  
Keyword(s):  
De Novo ◽  
Computational Design ◽  
Building Blocks ◽  
Repeat Units ◽  
Self Assembling ◽  
Wide Range ◽  
Helical Protein ◽  
Monomeric Proteins

We describe a general computational approach to designing self-assembling helical filaments from monomeric proteins and use this approach to design proteins that assemble into micrometer-scale filaments with a wide range of geometries in vivo and in vitro. Cryo–electron microscopy structures of six designs are close to the computational design models. The filament building blocks are idealized repeat proteins, and thus the diameter of the filaments can be systematically tuned by varying the number of repeat units. The assembly and disassembly of the filaments can be controlled by engineered anchor and capping units built from monomers lacking one of the interaction surfaces. The ability to generate dynamic, highly ordered structures that span micrometers from protein monomers opens up possibilities for the fabrication of new multiscale metamaterials.

scholarly journals Protein structure prediction and design in a biologically-realistic implicit membrane

2019 ◽  
Author(s):  
Rebecca F. Alford ◽  
Patrick J. Fleming ◽  
Karen G. Fleming ◽  
Jeffrey J. Gray
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
Membrane Proteins ◽  
Membrane Protein ◽  
Protein Structure Prediction ◽  
Protein Design ◽  
Structure Prediction ◽  
De Novo ◽  
Computational Design ◽  
Amino Acid Distribution

ABSTRACTProtein design is a powerful tool for elucidating mechanisms of function and engineering new therapeutics and nanotechnologies. While soluble protein design has advanced, membrane protein design remains challenging due to difficulties in modeling the lipid bilayer. In this work, we developed an implicit approach that captures the anisotropic structure, shape of water-filled pores, and nanoscale dimensions of membranes with different lipid compositions. The model improves performance in computational bench-marks against experimental targets including prediction of protein orientations in the bilayer, ΔΔG calculations, native structure dis-crimination, and native sequence recovery. When applied to de novo protein design, this approach designs sequences with an amino acid distribution near the native amino acid distribution in membrane proteins, overcoming a critical flaw in previous membrane models that were prone to generating leucine-rich designs. Further, the proteins designed in the new membrane model exhibit native-like features including interfacial aromatic side chains, hydrophobic lengths compatible with bilayer thickness, and polar pores. Our method advances high-resolution membrane protein structure prediction and design toward tackling key biological questions and engineering challenges.Significance StatementMembrane proteins participate in many life processes including transport, signaling, and catalysis. They constitute over 30% of all proteins and are targets for over 60% of pharmaceuticals. Computational design tools for membrane proteins will transform the interrogation of basic science questions such as membrane protein thermodynamics and the pipeline for engineering new therapeutics and nanotechnologies. Existing tools are either too expensive to compute or rely on manual design strategies. In this work, we developed a fast and accurate method for membrane protein design. The tool is available to the public and will accelerate the experimental design pipeline for membrane proteins.

scholarly journals Enhancing a De Novo Enzyme Activity by Computationally-Focused, Ultra-Low-Throughput Sequence Screening

2020 ◽  
Author(s):  
Valeria A. Risso ◽  
Adrian Romero-Rivera ◽  
Luis I. Gutierrez-Rus ◽  
Mariano Ortega-Muñoz ◽  
Francisco Santoyo-Gonzalez ◽  
...  
Keyword(s):  
Directed Evolution ◽  
Active Site ◽  
De Novo ◽  
Enzymatic Reaction ◽  
Valence Bond ◽  
Computational Procedure ◽  
Enzyme Design ◽  
Computational Enzyme Design ◽  
Stability Ranking ◽  
Random Library

<div> <div> <div> <p>Directed evolution has revolutionized protein engineering. Still, enzyme optimization by random library screening remains a sluggish process, in large part due to futile probing of mutations that are catalytically neutral and/or impair stability and folding. FuncLib (funclib-weizmann.ac.il) is a novel automated computational procedure which uses phylogenetic analysis and Rosetta design to rank enzyme variants with multiple mutations, on the basis of a stability metric. Here, we use it to target the active site region of a minimalist-designed, de novo Kemp eliminase. The similarity between the Michaelis complex and transition state for the enzymatic reaction makes this a particularly challenging system to optimize. Yet, experimental screening of a very small number of active-site, multi-point variants at the top of the predicted stability ranking leads to catalytic efficiencies and turnover numbers (~2·104 M-1 s-1 and ~102 s-1) that compare well with modern natural enzymes, and that approach the catalysis levels for the best Kemp eliminases derived from extensive screening. This result illustrates the promise of FuncLib as a powerful tool with which to speed up directed evolution, by guiding screening to regions of the sequence space that encode stable and catalytically diverse enzymes. Empirical valence bond calculations reproduce the experimental activation energies for the optimized eliminases to within ~2 kcal·mol-1 and indicate that the improvements in activity are linked to better geometric preorganization of the active site. This raises the possibility of further enhancing the stability-guidance of FuncLib by EVB-based computational predictions of catalytic activity, as a generalized approach for computational enzyme design. </p> </div> </div> </div>

scholarly journals De Novo Molecule Design Through Molecular Generative Model Conditioned by 3D Information of Protein Binding Sites

2020 ◽  
Author(s):  
Mingyuan Xu ◽  
Ting Ran ◽  
Hongming Chen
Keyword(s):  
Protein Binding ◽  
De Novo ◽  
Structural Information ◽  
Chemical Space ◽  
Three Dimensional ◽  
Binding Pocket ◽  
Generative Model ◽  
Coarse Grained ◽  
Molecule Design ◽  
3D Information

<p><i>De novo</i> molecule design through molecular generative model is gaining increasing attention in recent years. Here a novel generative model was proposed by integrating the 3D structural information of the protein binding pocket into the conditional RNN (cRNN) model to control the generation of drug-like molecules. In this model, the composition of protein binding pocket is effectively characterized through a coarse-grain strategy and the three-dimensional information of the pocket can be represented by the sorted eigenvalues of the coulomb matrix (EGCM) of the coarse-grained atoms composing the binding pocket. In current work, we used our EGCM method and a previously reported binding pocket descriptor DeeplyTough to train cRNN models and compared their performance. It has been shown that the molecules generated with the control of protein environment information have a clear tendency on generating compounds with higher similarity to the original X-ray bound ligand than normal RNN model and also achieving better performance in terms of docking scores. Our results demonstrate the potential application of EGCM controlled generative model for the targeted molecule generation and guided exploration on the drug-like chemical space. </p><p> </p>

scholarly journals Computational design and experimental verification of a symmetric protein homodimer

2015 ◽  
Vol 112 (34) ◽  
pp. 10714-10719 ◽  
Author(s):  
Yun Mou ◽  
Po-Ssu Huang ◽  
Fang-Ciao Hsu ◽  
Shing-Jong Huang ◽  
Stephen L. Mayo
Keyword(s):  
Protein Interactions ◽  
De Novo ◽  
Computational Design ◽  
Atomic Level ◽  
Protein Interfaces ◽  
Unknown Structure ◽  
Α Helix ◽  
Distinct Features ◽  
Novel Protein

Homodimers are the most common type of protein assembly in nature and have distinct features compared with heterodimers and higher order oligomers. Understanding homodimer interactions at the atomic level is critical both for elucidating their biological mechanisms of action and for accurate modeling of complexes of unknown structure. Computation-based design of novel protein–protein interfaces can serve as a bottom-up method to further our understanding of protein interactions. Previous studies have demonstrated that the de novo design of homodimers can be achieved to atomic-level accuracy by β-strand assembly or through metal-mediated interactions. Here, we report the design and experimental characterization of a α-helix–mediated homodimer with C2 symmetry based on a monomeric Drosophila engrailed homeodomain scaffold. A solution NMR structure shows that the homodimer exhibits parallel helical packing similar to the design model. Because the mutations leading to dimer formation resulted in poor thermostability of the system, design success was facilitated by the introduction of independent thermostabilizing mutations into the scaffold. This two-step design approach, function and stabilization, is likely to be generally applicable, especially if the desired scaffold is of low thermostability.

scholarly journals Precise assembly of complex beta sheet topologies from de novo designed building blocks

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Indigo Chris King ◽  
James Gleixner ◽  
Lindsey Doyle ◽  
Alexandre Kuzin ◽  
John F Hunt ◽  
...  
Keyword(s):  
De Novo ◽  
Computational Design ◽  
Building Blocks ◽  
Beta Sheets ◽  
Protein Domain ◽  
Beta Sheet ◽  
Design Models ◽  
Natural Protein ◽  
Complex Protein ◽  
Alpha Beta

Design of complex alpha-beta protein topologies poses a challenge because of the large number of alternative packing arrangements. A similar challenge presumably limited the emergence of large and complex protein topologies in evolution. Here, we demonstrate that protein topologies with six and seven-stranded beta sheets can be designed by insertion of one de novo designed beta sheet containing protein into another such that the two beta sheets are merged to form a single extended sheet, followed by amino acid sequence optimization at the newly formed strand-strand, strand-helix, and helix-helix interfaces. Crystal structures of two such designs closely match the computational design models. Searches for similar structures in the SCOP protein domain database yield only weak matches with different beta sheet connectivities. A similar beta sheet fusion mechanism may have contributed to the emergence of complex beta sheets during natural protein evolution.

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