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Sergeeva, A. P.

Publications and source records attributed to Sergeeva, A. P..

6 recordsLinked to original sources
bioRxiv2026

A functional investigation of antibody Fc-FcRn variant binding guided by *in silico* free energy perturbation methods

Accurate calculation of energy changes upon mutation is a key requirement for the effective use of computational methods in protein design. In this study, we applied free energy perturbation (FEP) calculations to predict the effects of mutations on the binding free energy between the immunoglobulin subtype G (IgG) antibody fragment-crystallizable (Fc) region and the neonatal Fc receptor (FcRn), an interaction that is primarily responsible for antibody half-life. We assembled an extensive experimental dataset of Fc-FcRn binding affinities for wild-type (wt) and mutant complexes, including values from literature and from newly measured results. Starting from a crystal structure of the M252Y/S254T/T256E ("YTE") Fc variant bound to FcRn, we prepared all-atom models of human IgG1-subtype wt and YTE variant Fc-FcRn complexes, adding explicit hydrogens and assigning protonation states for key ionizable residues. Initial results using standard FEP protocols to compute relative binding free energies were promising but exhibited multiple outliers. By accounting for coupling effects for FEP mutations near key histidine residues, we improved the results for several outliers, suggesting such coupling as an important approach for pH-sensitive systems. Further, upon determining new crystal structures of four Fc variants at multiple pH values, we observed subtle conformational changes in unbound Fc; by accounting for these conformational changes in FEP calculations, we additionally improved agreement with experiment. The detailed structural and energetic analyses of the Fc-FcRn system we present here thus provide an accurate energy-calculation framework to enable rational in silico design of novel Fc variants. SignificanceThe ability to determine changes in binding affinity upon mutation is critical to structure-based protein design. In this study, we demonstrate a successful computational approach using free energy perturbation (FEP) calculations on the antibody Fc-FcRn complex, a medically relevant system with implications for both therapeutic and prophylactic antibody use. Our successful calculation of accurate binding energies across a wide range of cases speaks to the power of the FEP methodology in navigating the free energy landscapes of dynamic molecular complexes. Furthermore, we show that accurate Fc-FcRn affinity calculations required careful consideration of conformational flexibility between bound and unbound states, contributing to our functional understanding of a system that will be important for future rational antibody-design efforts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/721095v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@f754d8org.highwire.dtl.DTLVardef@1e366beorg.highwire.dtl.DTLVardef@6e67caorg.highwire.dtl.DTLVardef@602a14_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗
bioRxiv2024

Robust prediction of relative binding energies for protein-protein complex mutations using free energy perturbation calculations

Computational free energy-based methods have the potential to significantly improve throughput and decrease costs of protein design efforts. Such methods must reach a high level of reliability, accuracy, and automation to be effectively deployed in practical industrial settings in a way that impacts protein design projects. Here, we present a benchmark study for the calculation of relative changes in protein-protein binding affinity for single point mutations across a variety of systems from the literature, using free energy perturbation (FEP+) calculations. We describe a method for robust treatment of alternate protonation states for titratable amino acids, which yields improved correlation with and reduced error compared to experimental binding free energies. Following careful analysis of the largest outlier cases in our dataset, we assess limitations of the default FEP+ protocols and introduce an automated script which identifies probable outlier cases that may require additional scrutiny and calculates an empirical correction for a subset of charge-related outliers. Through a series of three additional case study systems, we discuss how protein FEP+ can be applied to real-world protein design projects, and suggest areas of further study. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/590325v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1c5e607org.highwire.dtl.DTLVardef@1810ee5org.highwire.dtl.DTLVardef@1f8f1acorg.highwire.dtl.DTLVardef@c28053_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIReliable calculation of relative binding free energy changes for most protein mutations to within [~]1 kcal/mol. C_LIO_LIAutomated Protein FEP+ Groups treatment of alternate protonation states for titratable residues. C_LIO_LIApplication of FEP+ methodology to "real-world" protein design projects. C_LI

biophysics↗
bioRxiv2024

Cis inhibition of co-expressed DIPs and Dprs shapes neural development

In Drosophila, two interacting adhesion protein families, Dprs and DIPs, coordinate the assembly of neural networks. While intercellular DIP/Dpr interactions have been well characterized, DIPs and Dprs are often co-expressed within the same cells, raising the question as to whether they also interact in cis. We show, in cultured cells and in vivo, that DIP- and DIP-{delta} can interact in cis with their ligands, Dpr6/10 and Dpr12, respectively. When co-expressed in cis with their cognate partners, these Dprs regulate the extent of trans binding, presumably through competitive cis interactions. We demonstrate the neurodevelopmental effects of cis inhibition in fly motor neurons and in the mushroom body. We further show that a long disordered region of DIP- at the C-terminus is required for cis but not trans interactions, likely because it alleviates geometric constraints on cis binding. Thus, the balance between cis and trans interactions plays a role in controlling neural development.

biochemistry↗
bioRxiv2022

Free energy perturbation calculations of mutation effects on SARS-CoV-2 RBD::ACE2 binding affinity

The strength of binding between human angiotensin converting enzyme 2 (ACE2) and the receptor binding domain (RBD) of viral spike protein plays a role in the transmissibility of the SARS-CoV-2 virus. In this study we focus on a subset of RBD mutations that have been frequently observed in infected individuals and probe binding affinity changes to ACE2 using surface plasmon resonance (SPR) measurements and free energy perturbation (FEP) calculations. Our SPR results are largely in accord with previous studies but discrepancies do arise due to differences in experimental methods and to protocol differences even when a single method is used. Overall, we find that FEP performance is superior to that of other computational approaches examined as determined by agreement with experiment and, in particular, by its ability to identify stabilizing mutations. Moreover, the calculations successfully predict the observed cooperative stabilization of binding by the Q498R N501Y double mutant present in Omicron variants and offer a physical explanation for the underlying mechanism. Overall, our results suggest that despite the significant computational cost, FEP calculations may offer an effective strategy to understand the effects of interfacial mutations on protein-protein binding affinities and in practical applications such as the optimization of neutralizing antibodies.

biophysics↗
bioRxiv2021

Affinity Requirements For Control Of Synaptic Targeting And Neuronal Cell Survival By Heterophilic IgSF Cell Adhesion Molecules

Neurons in the developing brain express many different cell adhesion molecules (CAMs) on their surfaces, and CAM interactions are essential for the determination of synaptic connectivity patterns. CAM binding affinities can vary by more than 200-fold, but the significance of affinity differences among CAMs is unknown. Here we provide a systematic characterization of the in vivo consequences of altering CAM affinity. Interactions between DIP- and its binding partners Dpr6 and Dpr10 control synaptic targeting and cell survival for Drosophila optic lobe neurons. We generated mutations that change DIP-::Dpr10 binding affinity and introduced these into the endogenous loci. We show that cell survival and synaptic targeting have different affinity requirements, and that there is a threshold affinity required for targeting. Reducing affinity causes graded loss-of-function phenotypes, while increasing affinity rescues cells that would normally die. Affinity reduction can be compensated for by increasing gene copy number.

neuroscience↗
bioRxiv2020

DIP/Dpr interactions and the evolutionary design of specificity in protein families

Differential binding affinities among closely related protein family members underlie many biological phenomena, including cell-cell recognition. Drosophila DIP and Dpr proteins mediate neuronal targeting in the fly through highly specific protein-protein interactions. We show here that DIPs/Dprs segregate into seven specificity subgroups defined by binding preferences between their DIP and Dpr members. We then describe a novel sequence-, structure- and energy-based computational approach, combined with experimental binding affinity measurements, to reveal how specificity is coded on the canonical DIP/Dpr interface. We show that binding specificity of DIP/Dpr subgroups is controlled by "negative constraints", which interfere with binding. To achieve specificity, each subgroup utilizes a different combination of negative constraints, which are broadly distributed and cover the majority of the protein-protein interface. We discuss the structural origins of negative constraints, and potential general implications for the evolutionary origins of binding specificity in multi-protein families.

biophysics↗