Biology subjects

Warrender, A. K.

Publications and source records attributed to Warrender, A. K..

3 recordsLinked to original sources

bioRxiv2025

Generative design of antibody Fc-variants with synthetic and programmable functional profiles

Beyond antigen recognition, antibodies direct diverse immune effector functions through their constant (Fc) domain. While the Fc domain is central to antibody biology and therapeutic efficacy, our understanding of how Fc sequence encodes function remains limited, as most of Fc sequence space has not been experimentally mapped or linked to Fc-receptor engagement. Furthermore, the extensive overlap in Fc-receptor binding sites on the Fc domain has impeded efforts to engineer antibodies with tailored, multi-receptor engagement profiles that can precisely control downstream immunity. Here we introduce a novel framework for Fc engineering that integrates protein engineering with deep learning to rationally predict and engineer antibody Fc function. Using a yeast-based, aglycosylated Fc display system, we performed deep mutational scanning across the entire human IgG1 Fc domain, allowing the rational design of a diverse combinatorial library of more than 108 Fc-variants. This library was sorted based on binding to a panel of eight canonical Fc-receptors, and the resulting populations were deep sequenced to generate a high-quality dataset comprising millions of unique Fc sequences annotated with their respective Fc-receptor binding profiles. Deep learning-based classifiers trained on this dataset accurately predicted Fc-receptor binding activity from Fc sequence across all Fc-receptors tested. We further developed FcGPT, a domain-specific autoregressive protein language model pre-trained on over three million unique Fc sequences, and refined by post-training through reinforcement learning with experimental feedback (RLXF) and synthetic verifiers. FcGPT enables the computational design of novel Fc-variants with user-defined Fc-receptor binding profiles, providing a foundational tool for understanding and programming antibody-mediated immunity.

bioengineering↗

bioRxiv2025

A ternary switch determines ERα LBD conformation

The transcription factor estrogen receptor (ER) is the primary driver of ER+ breast cancer progression and a target of multiple FDA-approved anticancer drugs. Ligand-dependent activity of ER is determined by the conformation of helix-12 (H12) within the ligand binding domain (LBD), but how H12 transitions from an unliganded (apo) state to active (estrogen-bound) or inactive (SERM/SERD-bound) states remains unresolved. Here, we present the first crystal structure of an apo ER LBD, revealing a third distinct H12 conformation that regulates receptor activity. Structural mass-spectrometry, small-angle X-ray scattering, functional analysis and molecular dynamics simulations reveal that the apo conformation of H12 is stable in the absence of ligand, but is destabilised by Y537S and D538G breast cancer mutations driving constitutive activation. We propose a model in which H12 functions as a ternary molecular switch to determine receptor activity. These findings provide critical insights into the ligand-dependent and -independent regulation of ER and have significant implications for therapeutic intervention.

biochemistry↗

bioRxiv2023

Cooperative conformational transitions and the temperature dependence of enzyme catalysis

Many enzymes display non-Arrhenius behaviour with curved Arrhenius plots in the absence of denaturation. There has been significant debate about the origin of this behaviour and recently the role of the activation heat capacity [Formula] has been widely discussed. If enzyme-catalysed reactions occur with appreciable negative values of [Formula] (arising from narrowing of the conformational space along the reaction coordinate), then curved Arrhenius plots are a consequence. To investigate these phenomena in detail, we have collected high precision temperature-rate data over a wide temperature interval for a model glycosidase enzyme MalL, and a series of mutants that change the temperature-dependence of the enzyme-catalysed rate. We use these data to test a range of models including macromolecular rate theory (MMRT) and an equilibrium model. In addition, we have performed extensive molecular dynamics (MD) simulations to characterise the conformational landscape traversed by MalL in the enzyme-substrate complex and an enzyme-transition state complex. We have crystallised the enzyme in a transition state-like conformation in the absence of a ligand and determined an X-ray crystal structure at very high resolution (1.10 [A]). We show (using simulation) that this enzyme-transition state conformation has a more restricted conformational landscape than the wildtype enzyme. We coin the term "transition state-like conformation (TLC)" to apply to this state of the enzyme. Together, these results imply a cooperative conformational transition between an enzyme-substrate conformation (ES) and a transition-state-like conformation (TLC) that precedes the chemical step. We present a two-state model as an extension of MMRT (MMRT-2S) that describes the data along with a convenient approximation with linear temperature dependence of the activation heat capacity (MMRT-1L) that can be used where fewer data points are available. Our model rationalises disparate behaviour seen for MalL and a thermophilic alcohol dehydrogenase and is consistent with a raft of data for other enzymes. Our model can be used to characterise the conformational changes required for enzyme catalysis and provides insights into the role of cooperative conformational changes in transition state stabilisation that are accompanied by changes in heat capacity for the system along the reaction coordinate. TLCs are likely to be of wide importance in understanding the temperature dependence of enzyme activity, and other aspects of enzyme catalysis.

biochemistry↗