Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2

The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 (hACE2) represents the first required step for cellular entry. SARS-CoV-2 has continued to evolve with the emergence of several novel variants, and amino acid changes in the RBD have been implicated with increased fitness and potential for immune evasion. Reliably predicting the effect of amino acid changes on the ability of the RBD to interact more strongly with the hACE2 can help assess the implications for public health and the potential for spillover and adaptation into other animals. Here, we introduce a two-step framework that first relies on 48 independent 4-ns molecular dynamics (MD) trajectories of RBD−hACE2 variants to collect binding energy terms decomposed into Coulombic, covalent, van der Waals, lipophilic, generalized Born solvation, hydrogen bonding, π−π packing, and self-contact correction terms. The second step implements a neural network to classify and quantitatively predict binding affinity changes using the decomposed energy terms as descriptors. The computational base achieves a validation accuracy of 82.8% for classifying single–amino acid substitution variants of the RBD as worsening or improving binding affinity for hACE2 and a correlation coefficient of 0.73 between predicted and experimentally calculated changes in binding affinities. Both metrics are calculated using a fivefold cross-validation test. Our method thus sets up a framework for screening binding affinity changes caused by unknown single– and multiple–amino acid changes offering a valuable tool to predict host adaptation of SARS-CoV-2 variants toward tighter hACE2 binding.

The First Report of Target-Site Resistance to Glyphosate in Sweet Summer Grass (Moorochloa eruciformis)

Sweet summer grass is a problematic weed in the central Queensland region of Australia. This study found glyphosate resistance in two biotypes (R1 and R2) of sweet summer grass. The level of resistance in these biotypes was greater than 8-fold. The glyphosate dose required to reduce dry matter by 50% (GR50) for the resistant populations varied from 1993 to 2100 g ha−1. A novel glyphosate resistance double point mutation in the 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) gene was identified for the first time in sweet summer grass. Multiple mutations, including multiple amino acid changes at the glyphosate target site, as well as mutations involving two nucleotide changes at a single amino acid codon, were observed. Both resistant biotypes exhibited a nucleotide change of CAA to ACA in codon 106, which predicts an amino acid change of proline to a threonine (Pro-106-Thr). In addition, the R1 biotype also possessed a mutation at codon 100, where a nucleotide substitution of T for G occurred (GCT to TCT), resulting in a substitution of serine for alanine (Ala-100-Ser). Understanding the molecular mechanism of glyphosate resistance will help to design effective management strategies to control invasive weeds.

An Evolutionary Perspective of the Lipocalin Protein Family

The protein family of Lipocalins is ubiquitously present throughout the tree of life, with the exception of the phylum Archaea. Phylogenetic relationships of chordate Lipocalins have been proposed in the past based on protein sequence similarities, but their highly divergent primary structures and a shortage of experimental annotations in genome projects have precluded a well-supported hypothesis for their evolution. In this work we propose a novel topology for the phylogenetic tree of chordate Lipocalins, inferred from multiple amino acid sequence alignments. Sixteen jawed vertebrates with fair coverage by genomic sequencing were compared. The selected species span an evolutionary range of ∼400 million years, allowing for a balanced representation of all major vertebrate clades. A consensus phylogenetic tree is proposed following a comparison of sequence-based maximum-likelihood trees and protein structure dendrograms. This new phylogeny suggests an APOD-like common ancestor in early chordates, which gave rise, via whole-genome or tandem duplications, to the six Lipocalins currently present in fish (APOD, RBP4, PTGDS, AMBP, C8G, and APOM). Further gene duplications of APOM and PTGDS resulted in the altogether 15 Lipocalins found in contemporary mammals. Insights into the functional impact of relevant amino acid residues in early diverging Lipocalins are also discussed. These results should foster the experimental exploration of novel functions alongside the identification of new members of the Lipocalin family.

Molecular evolution and structural analyses of the spike glycoprotein from Brazilian SARS-CoV-2 genomes: the impact of the fixation of selected mutations

The COVID-19 pandemic caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has reached by July 2021 almost 200 million cases and more than 4 million deaths worldwide since its beginning in late 2019, leading to enhanced concern in the scientific community and the general population. One of the most important pieces of this host-pathogen interaction is the spike protein, which binds to the human Angiotensin-converting enzyme 2 (hACE2) cell receptor, mediates the membrane fusion and is the major target of neutralizing antibodies against SARS-CoV-2. The multiple amino acid substitutions observed in this region, specially in the Receptor Binding Domain (RBD), mainly after almost one year of its emergence (late 2020), have enhanced the hACE2 binding affinity and led to several modifications in the mechanisms of SARS-CoV-2 pathogenesis, improving the viral fitness and/or promoting immune evasion, with potential impact in the vaccine development. In this way, the present work aimed to evaluate the effect of positively selected mutations fixed in the Brazilian SARS-CoV-2 lineages and to check for mutational evidence of coevolution. Additionally, we evaluated the impact of selected mutations identified in some of the VOC and VOI lineages (C.37, B.1.1.7, P.1, and P.2) of Brazilian samples on the structural stability of the spike protein, as well as their possible association with more aggressive infection profiles by estimating the binding affinity in the RBD-hACE2 complex. We identified 48 sites under selective pressure in Brazilian spike sequences, 17 of them with the strongest evidence by the HyPhy tests, including VOC related mutation sites 138, 142, 222, 262, 484, 681, and 845, among others. The coevolutionary analysis identified a number of 28 coevolving sites that were found not to be conditionally independent, such as the couple E484K - N501Y from P.1 and B.1.351 lineages. Finally, the molecular dynamics and free energy estimates showed the structural stabilizing effect and the higher impact of E484K for the improvement of the binding affinity between the spike RBD and the hACE2 in P.1 and P.2 lineages, as well as the stabilizing and destabilizing effects for the positively selected sites.

Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike protein and the human ACE2 receptor

The association of the receptor binding domain (RBD) of SARS-CoV-2 viral spike with human angiotensin converting enzyme (hACE2) represents the first required step for viral entry. Amino acid changes in the RBD have been implicated with increased infectivity and potential for immune evasion. Reliably predicting the effect of amino acid changes in the ability of the RBD to interact more strongly with the hACE2 receptor can help assess the public health implications and the potential for spillover and adaptation into other animals. Here, we introduce a two-step framework that first relies on 48 independent 4-ns molecular dynamics (MD) trajectories of RBD-hACE2 variants to collect binding energy terms decomposed into Coulombic, covalent, van der Waals, lipophilic, generalized Born electrostatic solvation, hydrogen-bonding, π-π packing and self-contact correction terms. The second step implements a neural network to classify and quantitatively predict binding affinity using the decomposed energy terms as descriptors. The computational base achieves an accuracy of 82.2% in terms of correctly classifying single amino-acid substitution variants of the RBD as worsening or improving binding affinity for hACE2 and a correlation coefficient r of 0.69 between predicted and experimentally calculated binding affinities. Both metrics are calculated using a 5-fold cross validation test. Our method thus sets up a framework for effectively screening binding affinity change with unknown single and multiple amino-acid changes. This can be a very valuable tool to predict host adaptation and zoonotic spillover of current and future SARS-CoV-2 variants.

Rapid increase of SARS-CoV-2 variant B.1.1.7 detected in sewage samples from England between October 2020 and January 2021

SARS-CoV-2 variants with multiple amino acid mutations in the spike protein are emerging in different parts of the world raising concerns on their possible impact on human immune response to the virus and vaccine efficacy against them. Recently, a variant named lineage B.1.1.7 was detected and shown to be rapidly spreading across the UK since November 2020. As surveillance for these SARS-CoV-2 variants of concern (VOCs) becomes critical, we have investigated the use of environmental surveillance (ES) for the rapid detection and quantification of B.1.1.7 viruses in sewage as a way of monitoring its expansion that is independent on the investigation of identified clinical cases. B.1.1.7 mutations in viral sequences from sewage were first identified in a sample collected in London on 10th November 2020 and shown to rapidly increase in frequency to >95% in January 2021, in agreement with clinical data over the same period. We show that ES can provide an early warning of VOCs becoming prevalent in the population and that, as well as B.1.1.7, our method can potentially detect VOCs B.1.351 and P.1, first identified in South Africa and Brazil, respectively, and other viruses also carrying critical spike mutation E484K, known to have an effect on virus antigenicity.

Nef Obtained from Individuals with HIV-1 Vary in Their Ability to Antagonize SERINC3- and SERINC5-Mediated HIV-1 Restriction

Nef is a multifunctional viral protein that has the ability to downregulate cell surface molecules, including CD4 and major histocompatibility complex class I (MHC-I) and, as recently shown, also members of the serine incorporator family (SERINC). Here, we analyzed the impact of naturally occurring mutations in HIV-1 Nef on its ability to counteract SERINC restriction and the clinical course of infection. HIV-1 Nef sequences were obtained from 123 participants of the Amsterdam Cohort Studies and showed multiple amino acid variations and mutations. Most of the primary Nef proteins showed increased activity to counteract SERINC3 and SERINC5 as compared to NL4-3 Nef. Several mutations in Nef were associated with either an increased or decreased infectivity of Bal26-pseudotyped HIV-1 produced in the presence of SERINC3 or SERINC5. The 8R, 157N and R178G Nef mutations were shown to have an effect on disease progression. Survival analysis showed an accelerated disease progression of individuals infected with HIV-1 carrying arginine or asparagine at position 8 or 157 in Nef, respectively, or the R178G Nef mutation. Here, we observed that naturally occurring mutations in Nef affect the ability of Nef to counteract SERINC3- and SERINC5-mediated inhibition of viral infectivity. The majority of these Nef mutations had no significant effect on HIV-1 pathogenesis and only the 8R, 157N and R178G mutations were associated with disease course.

The N-terminal domain of Spike protein contributes to antigenicity difference between porcine epidemic diarrhea virus genotypes G1 and G2

Porcine epidemic diarrhea virus (PEDV) strains have been clarified into two genotypes, G1 and G2, based on the sequence of the spike (S) gene. Amino acid mutations that distinguish the two PEDV genotypes were mostly located in the N-terminal domain (NTD) (aa 1-380) of S protein. The fact of increased outbreaks of G2 subtype PEDV and the failure of G1 subtype PEDV strain (CV777)-based vaccine in China since 2010 suggested that multiple amino acid mutations located in the NTD altered the antigenicity of S protein. To determine the role of the NTD of S protein in the antigenicity difference, the NTD of the CV777 vaccine strain (G1) and CH/ZMDZY/11 strain (G2) was expressed in E. coli, respectively. polyclonal antibodies (PAbs) against genotype-specific S proteins were prepared by immunizing BALB/c mice using purified S proteins. Antigenicity was systematically compared by detection of PAbs against two genotype PEDV strains and purified S proteins using Western blot, indirect enzyme-linked immunosorbent assay (ELISA), indirect immunofluorescence assay (IFA), and serum cross-neutralization assay (SN). Consistent with the multiple amino acid mutations in the NTD of S protein, different antigenic cross-reactivity between the two genotypes was demonstrated. There was six-fold and more than twenty-fold difference in ELISA and SN titer between anti-CV777 S protein antibodies against G1 and G2 subtype strains, respectively. There was twofold and eight-fold difference in ELISA and SN titer between anti-ZMDZY S protein antibodies against G1 and G2 genotype strains, respectively. The results proved that the NTD of S protein contributes to the antigenicity difference between PEDV genotypes G1 and G2, and highlighted a G2 strain should be used to develop a vaccine for providing better protection against prevalent genotype of PEDV.