Computational analysis, design, and experimental validation of antibody binding affinity improvements beyond in vivo maturation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (leaves 98-110).This thesis presents novel methods for the analysis and design of high-affinity protein interactions using a combination of high-resolution structural data and physics-based molecular models. First, computational analysis was used to investigate the molecular basis for the affinity improvement of over 1000-fold of the fluorescein-binding antibody variant 4M5.3, engineered previously from the antibody 4-4-20 using directed evolution. Electrostatic calculations revealed mechanistic hypotheses for the role of four mutations in a portion of the improvement, subsequently validated by separate biochemical experiments. Next, methods were developed to computationally redesign protein interactions in order to rationally improve binding affinity. In the anti-lysozyme model antibody D1.3, modest binding improvements were achieved, with the results indicating potentially increased sucesss using predictions that emphasize electrostatics, as well as the need to address the over-prediction of large amino acids. New methods, taking advantage of the computed electrostatics of binding, yielded robust and significant improvements for both model and therapeutic antibodies.(cont.) The antibody D44.1 was improved 140-fold to 30 pM, and the FDA-approved antibody cetuximab (Erbitux) was improved 10-fold to 52 pM, with an experimental success rate of greater than 60% for single mutations designed to remove undersatisfied polar groups or improve misbalanced electrostatic interactions. Finally, a physics-based improvement to the calculation of the nonpolar component of solvation free energy was implemented and parameterized to address the over-prediction of large amino acids. These results demonstrate novel computational capabilities and indicate their applicability for enhancing and accelerating development of reagents and therapeutics.by Shaun Matthew Lippow.Ph.D

Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles

The stability, activity, and solubility of a protein sequence are determined by a delicate balance of molecular interactions in a variety of conformational states. Even so, most computational protein design methods model sequences in the context of a single native conformation. Simulations that model the native state as an ensemble have been mostly neglected due to the lack of sufficiently powerful optimization algorithms for multistate design. Here, we have applied our multistate design algorithm to study the potential utility of various forms of input structural data for design. To facilitate a more thorough analysis, we developed new methods for the design and high-throughput stability determination of combinatorial mutation libraries based on protein design calculations. The application of these methods to the core design of a small model system produced many variants with improved thermodynamic stability and showed that multistate design methods can be readily applied to large structural ensembles. We found that exhaustive screening of our designed libraries helped to clarify several sources of simulation error that would have otherwise been difficult to ascertain. Interestingly, the lack of correlation between our simulated and experimentally measured stability values shows clearly that a design procedure need not reproduce experimental data exactly to achieve success. This surprising result suggests potentially fruitful directions for the improvement of computational protein design technology

Engineering Enzyme Specificity Using Computational Design of a Defined-Sequence Library

Engineered biosynthetic pathways have the potential to produce high-value molecules from inexpensive feedstocks, but a key limitation is engineering enzymes with high activity and specificity for new reactions. Here, we developed a method for combining structure-based computational protein design with library-based enzyme screening, in which inter-residue correlations favored by the design are encoded into a defined-sequence library. We validated this approach by engineering a glucose 6-oxidase enzyme for use in a proposed pathway to convert D-glucose into D-glucaric acid. The most active variant, identified after only one round of diversification and screening of only 10,000 wells, is approximately 400-fold more active on glucose than is the wild-type enzyme. We anticipate that this strategy will be broadly applicable to the discovery of new enzymes for engineered biological pathways.United States. Office of Naval Research. Young Investigator Program (Grant N000140510656)National Science Foundation (U.S.) (Synthetic Biology Engineering Research Center. Grant EEC-0540879)MIT Faculty Start-up FundCodon Devices, Inc

Combining different design strategies for rational affinity maturation of the MICA‐NKG2D interface

We redesigned residues on the surface of MICA, a protein that binds the homodimeric immunoreceptor NKG2D, to increase binding affinity with a series of rational, incremental changes. A fixed‐backbone RosettaDesign protocol scored a set of initial mutations, which we tested by surface plasmon resonance for thermodynamics and kinetics of NKG2D binding, both singly and in combination. We combined the best four mutations at the surface with three affinity‐enhancing mutations below the binding interface found with a previous design strategy. After curating design scores with three cross‐validated tests, we found a linear relationship between free energy of binding and design score, and to a lesser extent, enthalpy and design score. Multiple mutants bound with substantial subadditivity, but in at least one case full additivity was observed when combining distant mutations. Altogether, combining the best mutations from the two strategies into a septuple mutant enhanced affinity by 50‐fold, to 50 nM, demonstrating a simple, effective protocol for affinity enhancement.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93571/1/PRO_2115_sm_Suppinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/93571/2/2115_ftp.pd

Pairwise selection assembly for sequence-independent construction of long-length DNA

The engineering of biological components has been facilitated by de novo synthesis of gene-length DNA. Biological engineering at the level of pathways and genomes, however, requires a scalable and cost-effective assembly of DNA molecules that are longer than ∼10 kb, and this remains a challenge. Here we present the development of pairwise selection assembly (PSA), a process that involves hierarchical construction of long-length DNA through the use of a standard set of components and operations. In PSA, activation tags at the termini of assembly sub-fragments are reused throughout the assembly process to activate vector-encoded selectable markers. Marker activation enables stringent selection for a correctly assembled product in vivo, often obviating the need for clonal isolation. Importantly, construction via PSA is sequence-independent, and does not require primary sequence modification (e.g. the addition or removal of restriction sites). The utility of PSA is demonstrated in the construction of a completely synthetic 91-kb chromosome arm from Saccharomyces cerevisiae

Prots: A fragment based protein thermo‐stability potential

Designing proteins with enhanced thermo‐stability has been a main focus of protein engineering because of its theoretical and practical significance. Despite extensive studies in the past years, a general strategy for stabilizing proteins still remains elusive. Thus effective and robust computational algorithms for designing thermo‐stable proteins are in critical demand. Here we report PROTS, a sequential and structural four‐residue fragment based protein thermo‐stability potential. PROTS is derived from a nonredundant representative collection of thousands of thermophilic and mesophilic protein structures and a large set of point mutations with experimentally determined changes of melting temperatures. To the best of our knowledge, PROTS is the first protein stability predictor based on integrated analysis and mining of these two types of data. Besides conventional cross validation and blind testing, we introduce hypothetical reverse mutations as a means of testing the robustness of protein thermo‐stability predictors. In all tests, PROTS demonstrates the ability to reliably predict mutation induced thermo‐stability changes as well as classify thermophilic and mesophilic proteins. In addition, this white‐box predictor allows easy interpretation of the factors that influence mutation induced protein stability changes at the residue level. Proteins 2012; © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/89526/1/23163_ftp.pd

Creating highly specific nucleases by fusion of active restriction endonucleases and catalytically inactive homing endonucleases

Zinc-finger nucleases and TALE nucleases are produced by combining a specific DNA-binding module and a non-specific DNA-cleavage module, resulting in nucleases able to cleave DNA at a unique sequence. Here a new approach for creating highly specific nucleases was pursued by fusing a catalytically inactive variant of the homing endonuclease I-SceI, as DNA binding-module, to the type IIP restriction enzyme PvuII, as cleavage module. The fusion enzymes were designed to recognize a composite site comprising the recognition site of PvuII flanked by the recognition site of I-SceI. In order to reduce activity on PvuII sites lacking the flanking I-SceI sites, the enzymes were optimized so that the binding of I-SceI to its sites positions PvuII for cleavage of the composite site. This was achieved by optimization of the linker and by introducing amino acid substitutions in PvuII which decrease its activity or disturb its dimer interface. The most specific variant showed a more than 1000-fold preference for the addressed composite site over an unaddressed PvuII site. These results indicate that using a specific restriction enzyme, such as PvuII, as cleavage module, offers an alternative to the otherwise often used catalytic domain of FokI, which by itself does not contribute to the specificity of the engineered nuclease

PROTDES: CHARMM toolbox for computational protein design

We present an open-source software able to automatically mutate any residue positions and find the best aminoacids in an arbitrary protein structure without requiring pairwise approximations. Our software, PROTDES, is based on CHARMM and it searches automatically for mutations optimizing a protein folding free energy. PROTDES allows the integration of molecular dynamics within the protein design. We have implemented an heuristic optimization algorithm that iteratively searches the best aminoacids and their conformations for an arbitrary set of positions within a structure. Our software allows CHARMM users to perform protein design calculations and to create their own procedures for protein design using their own energy functions. We show this by implementing three different energy functions based on different solvent treatments: surface area accessibility, generalized Born using molecular volume and an effective energy function. PROTDES, a tutorial, parameter sets, configuration tools and examples are freely available at http://soft.synth-bio.org/protdes.html

Synthetic Metabolism: Engineering Biology at the Protein and Pathway Scales

Biocatalysis has become a powerful tool for the synthesis of high-value compounds, particularly so in the case of highly functionalized and/or stereoactive products. Nature has supplied thousands of enzymes and assembled them into numerous metabolic pathways. Although these native pathways can be use to produce natural bioproducts, there are many valuable and useful compounds that have no known natural biochemical route. Consequently, there is a need for both unnatural metabolic pathways and novel enzymatic activities upon which these pathways can be built. Here, we review the theoretical and experimental strategies for engineering synthetic metabolic pathways at the protein and pathway scales, and highlight the challenges that this subfield of synthetic biology currently faces.Synthetic Biology Engineering Research CenterNational Science Foundation (Grant no. 0540879

Protein Design Using Continuous Rotamers

Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers) greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE) algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE. Availability: Software is available under the Lesser GNU Public License v3. Contact the authors for source code