Towards The Rational Design Of A Target-Specific Antibody

Antibodies and antibody-fragments have emerged as promising tools for many therapeutic and biotechnological applications. Antibody fragments (e.g., scFvs, Fabs, VHHs) derive functionality via their variable domains, which bind to a target (antigen) of interest. Antibody fragments obtained from conventional antibodies (i.e., human or mice IgGs) comprise two chains: variable heavy and variable light. Nanobodies (hereafter VHHs) are unique antibodies found in camelids. VHHs are the smallest naturally occurring binding domains and derive functionality via a single variable domain on a heavy chain. Only 3 hypervariable loops (H1, H2, H3) form the antigen-binding surface as opposed to 6 loops in conventional antibody fragments (3 from heavy and 3 from light chain). Due to their small size and surprising ability to bind a wide range of antigens with high specificity and affinity, VHHs are excellent candidates for antibody engineering. Despite their recent discovery, many engineered VHHs have already entered into clinical trials for treatment of a range of human diseases. It is our aim to rationally engineer VHHs with specificity for a target antigen by tailoring the hypervariable loops. As a first step toward such a goal, the design of loops with a desired conformation was considered. As proof-of-concept and to build our understanding of the binding loops of VHH antibodies, the study focused on the H1 loop of the anti-human Chorionic Gonadotropin (hCG) llama VHH that exhibits a noncanonical conformation. This loop was redesigned to "tilt" the stability of the loop structure from a noncanonical conformation to a (humanized) type 1 canonical conformation by studying the effect of selected mutations to the amino acid sequence of the H1, H2, and proximal residues. To test and extend our understanding of antigen-binding by VHHs, a dual modelingexperimental approach was pursued for designing a VHH specific to Alpha-Synuclein (AS). AS is the main pathological marker and perhaps the causative agent of Parkinson's disease. Starting from an immunized Camelid library against the Non-amyloid component (NAC) region of A53T mutant of AS (A53T), a bacteria-based selection technique was used to obtain a NAC-specific VHH, followed by computational modeling of the VHH and the VHH-NAC binding. The use of FLITRAP (an E. Coli based high-throughput screening technique) allows us to select for a soluble and intracellularly stable VHH (intrabody). Furthermore, using computational modeling the following tasks were completed: 1) Propose possible conformations of the VHH binding region, 2) Postulate viable modes of VHH binding to the NAC region, 3) Propose mutations that would enhance binding and ultimately, 4) Validate the proposed predictions through experiments. Counterintuitively, it was found that while mutations targeting the central hydrophobic NAC region only led to weak binding affinities, mutations, at the periphery of the binding site, that target the charged flanking hydrophilic residues of NAC are key to substantially increase binding affinity. The main goal of this research was hence to demonstrate the possibility of developing a model of binding in-silico starting from the amino acid sequence of the Antibody and the antigen and using it to predict affinity-enhancing mutations. This work differs from many other structure-based design studies in that the crystal structure of neither the Antibody, the antigen, or the complex is known; it hence tackles a much more challenging (but common) situation. This work also differs from high-throughput screening techniques based on multiple rounds of screening to obtain a high-affinity binder. Our dual experimental-modeling approach can be considered as an important step towards developing rational design strategies based on ab-initio modeling and bottom-up design approaches, which would ultimately enable us to gain a deeper understanding of protein surfaces and interactions

Induced fit with replica exchange improves protein complex structure prediction.

Despite the progress in prediction of protein complexes over the last decade, recent blind protein complex structure prediction challenges revealed limited success rates (less than 20% models with DockQ score > 0.4) on targets that exhibit significant conformational change upon binding. To overcome limitations in capturing backbone motions, we developed a new, aggressive sampling method that incorporates temperature replica exchange Monte Carlo (T-REMC) and conformational sampling techniques within docking protocols in Rosetta. Our method, ReplicaDock 2.0, mimics induced-fit mechanism of protein binding to sample backbone motions across putative interface residues on-the-fly, thereby recapitulating binding-partner induced conformational changes. Furthermore, ReplicaDock 2.0 clocks in at 150-500 CPU hours per target (protein-size dependent); a runtime that is significantly faster than Molecular Dynamics based approaches. For a benchmark set of 88 proteins with moderate to high flexibility (unbound-to-bound iRMSD over 1.2 Å), ReplicaDock 2.0 successfully docks 61% of moderately flexible complexes and 35% of highly flexible complexes. Additionally, we demonstrate that by biasing backbone sampling particularly towards residues comprising flexible loops or hinge domains, highly flexible targets can be predicted to under 2 Å accuracy. This indicates that additional gains are possible when mobile protein segments are known

Tilting the Balance between Canonical and Noncanonical Conformations for the H1 Hypervariable Loop of a Llama VHH through Point Mutations

Nanobodies are single-domain antibodies found in camelids. These are the smallest naturally occurring binding domains and derive functionality via three hypervariable loops (H1–H3) that form the binding surface. They are excellent candidates for antibody engineering because of their favorable characteristics like small size, high solubility, and stability. To rationally engineer antibodies with affinity for a specific target, the hypervariable loops can be tailored to obtain the desired binding surface. As a first step toward such a goal, we consider the design of loops with a desired conformation. In this study, we focus on the H1 loop of the anti-hCG llama nanobody that exhibits a noncanonical conformation. We aim to “tilt” the stability of the H1 loop structure from a noncanonical conformation to a (humanized) type 1 canonical conformation by studying the effect of selected mutations to the amino acid sequence of the H1, H2, and proximal residues. We use all-atomistic, explicit-solvent, biased molecular dynamic simulations to simulate the wild-type and mutant loops in a prefolded framework. We thus find mutants with increasing propensity to form a stable type 1 canonical conformation of the H1 loop. Free energy landscapes reveal the existence of conformational isomers of the canonical conformation that may play a role in binding different antigenic surfaces. We also elucidate the approximate mechanism and kinetics of transitions between such conformational isomers by using a Markovian model. We find that a particular three-point mutant has the strongest thermodynamic propensity to form the H1 type 1 canonical structure but also to exhibit transitions between conformational isomers, while a different, more rigid three-point mutant has the strongest propensity to be kinetically trapped in such a canonical structure