Large-scale application of free energy perturbation calculations for antibody design

Zhu, Fangqiang; Bourguet, Feliza; Bennett, William F.; Lau, Edmond Y.; Arrildt, Kathryn T.; Segelke, Brent W.; Zemła, Adam; Desautels, Thomas; Faissol, Daniel M.

doi:10.1038/s41598-022-14443-z

Cited by 14 publications

(11 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MM-PBSA is not the only possible choice for the computation of the binding free energies. Other methodologies such as alchemical transformation, free energy perturbation (FEP) [ 50 , 51 ] or computing the potential of mean force (PMF) necessary to pull apart the two proteins [ 28 , 51 , 52 ] have proved their feasibility, and can be used as valid alternative.…”

Section: Discussionmentioning

confidence: 99%

In Silico Maturation of a Nanomolar Antibody against the Human CXCR2

et al. 2022

View full text Add to dashboard Cite

The steady increase in computational power in the last 50 years is opening unprecedented opportunities in biology, as computer simulations of biological systems have become more accessible and can reproduce experimental results more accurately. Here, we wanted to test the ability of computer simulations to replace experiments in the limited but practically useful scope of improving the biochemical characteristics of the abN48 antibody, a nanomolar antagonist of the CXC chemokine receptor 2 (CXCR2) that was initially selected from a combinatorial antibody library. Our results showed a good correlation between the computed binding energies of the antibody to the peptide target and the experimental binding affinities. Moreover, we showed that it is possible to design new antibody sequences in silico with a higher affinity to the desired target using a Monte Carlo Metropolis algorithm. The newly designed sequences had an affinity comparable to the best ones obtained using in vitro affinity maturation and could be obtained within a similar timeframe. The methodology proposed here could represent a valid alternative for improving antibodies in cases in which experiments are too expensive or technically tricky and could open an opportunity for designing antibodies for targets that have been elusive so far.

show abstract

Section: Discussionmentioning

confidence: 99%

In Silico Maturation of a Nanomolar Antibody against the Human CXCR2

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Free energy perturbation (FEP) is a rigorous, physicsbased method that employs MD simulations to calculate free energy differences. As reported recently [zhu2022], we implemented an automated protocol for large-scale FEP calculations to evaluate the effect of antibody mutation on conformational stability. The structure of the COV2-2130 Fab was taken from the crystal structure 7L7E.…”

Section: Methodsmentioning

confidence: 99%

“…We then followed the FEP protocol described in Ref. [zhu2022]. Using FEP, we calculated ΔΔG Stability , the change in the antibody conformational stability, for 512 single mutations of 29 residues on the COV2-2130 Fab near the binding interface.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Computationally restoring the potency of a clinical antibody against SARS-CoV-2 Omicron subvariants

Desautels

Arrildt

Zemła

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

The COVID-19 pandemic has highlighted how viral variants that escape monoclonal antibodies can limit options to control an outbreak. With the emergence of the SARS-CoV-2 Omicron variant, many clinically used antibody drug products lost in vitro and in vivo potency, including AZD7442 and its constituent, AZD1061. Rapidly modifying such antibodies to restore efficacy to emerging variants is a compelling mitigation strategy. We therefore sought to computationally design an antibody that restores neutralization of BA.1 and BA.1.1 while simultaneously maintaining efficacy against SARS-CoV-2 B.1.617.2 (Delta), beginning from COV2-2130, the progenitor of AZD1061. Here we describe COV2-2130 derivatives that achieve this goal and provide a proof-of-concept for rapid antibody adaptation addressing escape variants. Our best antibody achieves potent and broad neutralization of BA.1, BA.1.1, BA.2, BA.2.12.1, BA.4, BA.5, and BA.5.5 Omicron subvariants, where the parental COV2-2130 suffers significant potency losses. This antibody also maintains potency against Delta and WA1/2020 strains and provides protection in vivo against the strains we tested, WA1/2020, BA.1.1, and BA.5. Because our design approach is computational - driven by high-performance computing-enabled simulation, machine learning, structural bioinformatics and multi-objective optimization algorithms - it can rapidly propose redesigned antibody candidates aiming to broadly target multiple escape variants and virus mutations known or predicted to enable escape.

show abstract

“…In addition to the time-consuming and costly mutational studies, there are also various computational approaches to predict the effect of single mutations on protein–protein binding affinities [ 43 , 44 , 45 , 46 , 47 , 48 , 49 ]. Of the computational approaches, especially molecular dynamics (MD), simulations-based free-energy calculations have been shown to produce useful (relative or absolute) predictions on free-energy changes upon single mutations [ 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ]. The exponential growth in computational power has facilitated the utilization of such computationally expensive calculations.…”

Section: Introductionmentioning

confidence: 99%

High-Throughput Molecular Dynamics-Based Alchemical Free Energy Calculations for Predicting the Binding Free Energy Change Associated with the Selected Omicron Mutations in the Spike Receptor-Binding Domain of SARS-CoV-2

Bhadane

Salo‐Ahen

2022

Biomedicines

View full text Add to dashboard Cite

The ongoing pandemic caused by SARS-CoV-2 has gone through various phases. Since the initial outbreak, the virus has mutated several times, with some lineages showing even stronger infectivity and faster spread than the original virus. Among all the variants, omicron is currently classified as a variant of concern (VOC) by the World Health Organization, as the previously circulating variants have been replaced by it. In this work, we have focused on the mutations observed in omicron sub lineages BA.1, BA.2, BA.4 and BA.5, particularly at the receptor-binding domain (RBD) of the spike protein that is responsible for the interactions with the host ACE2 receptor and binding of antibodies. Studying such mutations is particularly important for understanding the viral infectivity, spread of the disease and for tracking the escape routes of this virus from antibodies. Molecular dynamics (MD) based alchemical free energy calculations have been shown to be very accurate in predicting the free energy change, due to a mutation that could have a deleterious or a stabilizing effect on either the protein itself or its binding affinity to another protein. Here, we investigated the significance of five spike RBD mutations on the stability of the spike protein binding to ACE2 by free energy calculations using high throughput MD simulations. For comparison, we also used conventional MD simulations combined with a Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) based approach, and compared our results with the available experimental data. Overall, the alchemical free energy calculations performed far better than the MM-GBSA approach in predicting the individual impact of the mutations. When considering the experimental variation, the alchemical free energy method was able to produce a relatively accurate prediction for N501Y, the mutant that has previously been reported to increase the binding affinity to hACE2. On the other hand, the other individual mutations seem not to have a significant effect on the spike RBD binding affinity towards hACE2.

show abstract

Large-scale application of free energy perturbation calculations for antibody design

Cited by 14 publications

References 43 publications

In Silico Maturation of a Nanomolar Antibody against the Human CXCR2

In Silico Maturation of a Nanomolar Antibody against the Human CXCR2

Computationally restoring the potency of a clinical antibody against SARS-CoV-2 Omicron subvariants

High-Throughput Molecular Dynamics-Based Alchemical Free Energy Calculations for Predicting the Binding Free Energy Change Associated with the Selected Omicron Mutations in the Spike Receptor-Binding Domain of SARS-CoV-2

Contact Info

Product

Resources

About