Division of Computational Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee, Scotland, United Kingdom.
Sir William Dunn School of Pathology, South Parks Road, University of Oxford, Oxford, Oxfordshire, United Kingdom.
PLoS Comput Biol. 2022 Mar 2;18(3):e1009922. doi: 10.1371/journal.pcbi.1009922. eCollection 2022 Mar.
SARS-CoV-2 Spike (Spike) binds to human angiotensin-converting enzyme 2 (ACE2) and the strength of this interaction could influence parameters relating to virulence. To explore whether population variants in ACE2 influence Spike binding and hence infection, we selected 10 ACE2 variants based on affinity predictions and prevalence in gnomAD and measured their affinities and kinetics for Spike receptor binding domain through surface plasmon resonance (SPR) at 37°C. We discovered variants that reduce and enhance binding, including three ACE2 variants that strongly inhibited (p.Glu37Lys, ΔΔG = -1.33 ± 0.15 kcal mol-1 and p.Gly352Val, predicted ΔΔG = -1.17 kcal mol-1) or abolished (p.Asp355Asn) binding. We also identified two variants with distinct population distributions that enhanced affinity for Spike. ACE2 p.Ser19Pro (ΔΔG = 0.59 ± 0.08 kcal mol-1) is predominant in the gnomAD African cohort (AF = 0.003) whilst p.Lys26Arg (ΔΔG = 0.26 ± 0.09 kcal mol-1) is predominant in the Ashkenazi Jewish (AF = 0.01) and European non-Finnish (AF = 0.006) cohorts. We compared ACE2 variant affinities to published SARS-CoV-2 pseudotype infectivity data and confirmed that ACE2 variants with reduced affinity for Spike can protect cells from infection. The effect of variants with enhanced Spike affinity remains unclear, but we propose a mechanism whereby these alleles could cause greater viral spreading across tissues and cell types, as is consistent with emerging understanding regarding the interplay between receptor affinity and cell-surface abundance. Finally, we compared mCSM-PPI2 ΔΔG predictions against our SPR data to assess the utility of predictions in this system. We found that predictions of decreased binding were well-correlated with experiment and could be improved by calibration, but disappointingly, predictions of highly enhanced binding were unreliable. Recalibrated predictions for all possible ACE2 missense variants at the Spike interface were calculated and used to estimate the overall burden of ACE2 variants on Covid-19.
SARS-CoV-2 刺突（Spike）与人类血管紧张素转换酶 2（ACE2）结合，这种相互作用的强度可能会影响与毒力相关的参数。为了探索 ACE2 群体变异是否影响 Spike 结合从而影响感染，我们根据亲和力预测和 gnomAD 中的流行情况选择了 10 个 ACE2 变异体，并通过表面等离子体共振（SPR）在 37°C 下测量了它们与 Spike 受体结合域的亲和力和动力学。我们发现了降低和增强结合的变异体，包括三个强烈抑制（p.Glu37Lys，ΔΔG = -1.33 ± 0.15 kcal mol-1 和 p.Gly352Val，预测ΔΔG = -1.17 kcal mol-1）或完全抑制（p.Asp355Asn）结合的 ACE2 变异体。我们还鉴定了两个具有不同群体分布的变异体，它们增强了与 Spike 的亲和力。ACE2 p.Ser19Pro（ΔΔG = 0.59 ± 0.08 kcal mol-1）在 gnomAD 非洲队列中占主导地位（AF = 0.003），而 p.Lys26Arg（ΔΔG = 0.26 ± 0.09 kcal mol-1）在 Ashkenazi 犹太（AF = 0.01）和欧洲非芬兰（AF = 0.006）队列中占主导地位。我们比较了 ACE2 变异体的亲和力与已发表的 SARS-CoV-2 假型感染性数据，并证实对 Spike 亲和力降低的 ACE2 变异体能保护细胞免受感染。具有增强 Spike 亲和力的变异体的影响尚不清楚，但我们提出了一种机制，即这些等位基因可能导致病毒在组织和细胞类型中更广泛地传播，这与受体亲和力和细胞表面丰度之间相互作用的新理解一致。最后，我们比较了 mCSM-PPI2 ΔΔG 预测与我们的 SPR 数据，以评估该系统中预测的效用。我们发现，与实验相比，对结合力降低的预测相关性很好，并且可以通过校准来提高，但令人失望的是，对高度增强的结合力的预测是不可靠的。计算了 Spike 界面上所有可能的 ACE2 错义变异体的重新校准预测，并用于估计 ACE2 变异体对新冠病毒的总体负担。
