Abstract 3518: AB248 is a CD8+ T cell selective IL-2 designed for superior safety and anti-tumor efficacy

High dose IL-2 was the first modern immunotherapy to show complete responses in a subset of cancer patients. The liabilities of IL-2 prompted development of second-generation molecules, which signal through the IL-2Rβγ (“not-α” IL-2 and IL-15 variants). Although these molecules avoid vascular leak syndrome, their clinical efficacy appears to be suboptimal compared to high dose IL-2 [1]. Furthermore, not-α IL-2s show biased expansion of NK cells over CD8+ T cells in patients due to their high expression of IL-2Rβ on NK cells, which can act as a sink and contribute to toxicity, and these molecules do not eliminate IL-2Rβγ-mediated activation of Tregs [2, 3]. To maximize the therapeutic potential of IL-2, we developed AB248, a cis-targeted IL-2 fusion protein that selectively signals on CD8+ T-cells with limited activity on the highly IL-2/IL-15-sensitive NK cells and immunosuppressive Tregs. We have previously shown that selective expansion of CD8+ T cells over NK cells and Tregs is achieved in vivo using muAB248, AB248’s murine surrogate. Furthermore, a single dose of muAB248 elicits strong efficacy in multiple tumor models without body weight loss. Here, we detail the properties of AB248, a fusion of a human CD8-targeting antibody that selectively binds to CD8+ T cells over NK cells, and an IL-2 mutein with reduced affinity to IL-2Rα and IL-2Rβ. In STAT5 assays, AB248 showed approximately 1000-fold preference for the activation of CD8+ T cells over NK cells and Tregs. AB248 mediated a dose-dependent selective expansion of CD8 T cells over NK and Tregs in non-human primates. Furthermore, AB248 reproduced the expected in vitro gene signatures of an IL2Rβγ agonist, demonstrating that AB248 recapitulates native IL-2Rβγ signaling selectively on CD8+ T cells.We previously demonstrated in mice that while the efficacy of not-α IL-2 was mediated by CD8+ T cells and not NK cells, toxicity as measured by body weight loss was dependent upon NK cells but not CD8+ T cells. Here, we show that human NK cells may also drive IL-2βγ agonist-induced toxicities. Both IL-2 and not-α IL-2 induced IFN-γ secretion from human PBMCs, whereas AB248 did not. Strikingly, depletion of CD56+ NK cells eliminated IL-2-induced cytokine secretion, demonstrating that human NK cells are capable of spontaneously secreting IFN-γ in response to IL-2 signaling. In the context of TCR stimulation, AB248 induced robust secretion of effector cytokines from CD8+ T cells, but no cytokine secretion was seen in absence of TCR activation. Our data suggest that while AB248 can induce antigen-independent expansion of CD8+ T cells, it only induces effector cytokine secretion in the context of an additional activating signal via the TCR. Collectively, these data show that AB248 demonstrates an improved safety and efficacy profile as compared to not-α IL-2 and is a promising immuno-oncology therapeutic. Ref: 1. Overwijk, Ann. Rev. Med., 2020; 2. Janku, AACR, 2021; 3. Italiano, JCO, 2021

Citation Format: Kelly D. Moynihan, Danielle Pappas, Terrence Park, Wei Chen, Irene Ni, Paul Bessette, Henry Nguyen, David Liu, Mike Chin, Ruth Lan, Aaron Arvey, Ton N. Schumacher, Yik Andy Yeung, Ivana Djuretic. AB248 is a CD8+ T cell selective IL-2 designed for superior safety and anti-tumor efficacy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3518.

Age-associated changes in the circulating human antibody repertoire are upregulated in autoimmunity

Background

The immune system undergoes a myriad of changes with age. While it is known that antibody-secreting plasma and long-lived memory B cells change with age, it remains unclear how the binding profile of the circulating antibody repertoire is impacted.

Results

To understand humoral immunity changes with respect to age, we characterized serum antibody binding to high density peptide microarrays in a diverse cohort of 1675 donors. We discovered thousands of peptides that bind antibodies in age-dependent fashion, many of which contain di-serine motifs. Peptide binding profiles were aggregated into an “immune age” by a machine learning regression model that was highly correlated with chronological age. Applying this regression model to previously-unobserved donors, we found that a donor’s predicted immune age is longitudinally consistent over years, suggesting it could be a robust long-term biomarker of humoral immune ageing. Finally, we assayed serum from donors with autoimmune disease and found a significant association between “accelerated immune ageing” and autoimmune disease activity.

Conclusions

The circulating antibody repertoire has increased binding to thousands of di-serine peptide containing peptides in older donors, which can be represented as an immune age. Increased immune age is associated with autoimmune disease, acute inflammatory disease severity, and may be a broadly relevant biomarker of immune function in health, disease, and therapeutic intervention.

Memory of Inflammation in Regulatory T Cells

Eukaryotic cells can "remember" transient encounters with a wide range of stimuli, inducing lasting states of altered responsiveness. Regulatory T (Treg) cells are a specialized lineage of suppressive CD4 T cells that act as critical negative regulators of inflammation in various biological contexts. Treg cells exposed to inflammatory conditions acquire strongly enhanced suppressive function. Using inducible genetic tracing, we analyzed the long-term stability of activation-induced transcriptional, epigenomic, and functional changes in Treg cells. We found that the inflammation-experienced Treg cell population reversed many activation-induced changes and lost its enhanced suppressive function over time. The "memory-less" potentiation of Treg suppressor function may help avoid a state of generalized immunosuppression that could otherwise result from repeated activation.

Genetic and epigenetic variation in the lineage specification of regulatory T cells

Regulatory T (Treg) cells, which suppress autoimmunity and other inflammatory states, are characterized by a distinct set of genetic elements controlling their gene expression. However, the extent of genetic and associated epigenetic variation in the Treg cell lineage and its possible relation to disease states in humans remain unknown. We explored evolutionary conservation of regulatory elements and natural human inter-individual epigenetic variation in Treg cells to identify the core transcriptional control program of lineage specification. Analysis of single nucleotide polymorphisms in core lineage-specific enhancers revealed disease associations, which were further corroborated by high-resolution genotyping to fine map causal polymorphisms in lineage-specific enhancers. Our findings suggest that a small set of regulatory elements specify the Treg lineage and that genetic variation in Treg cell-specific enhancers may alter Treg cell function contributing to polygenic disease.

DOI:http://dx.doi.org/10.7554/eLife.07571.001

The immune system protects the body from infection. Key to this protection is the ability to mount an immune response that is sufficient to deal with the threat, but is not so large that the damage it causes to the body exceeds its immediate benefit. Immune cells called regulatory T cells (or Treg cells for short) help to shut down the immune response after a threat has been successfully destroyed. They also prevent the immune system from attacking the body's own cells, a phenomenon known as autoimmunity.

All cells in the body carry the same set of genes, but the activity of these genes varies between cell types to enable the cells to perform their different jobs. This is possible because our DNA contains regions called regulatory elements that can control the expression of particular genes. These regions can be activated in specific types of cells, which results in specific chemical modifications to DNA that only affect gene activity in those cells.

The DNA sequences of these regulatory elements vary between individuals. This ‘genetic variation’ can lead to differences in the chemical modifications that occur to DNA, which is known as epigenetic variation. This means that Treg cells in one person may work in a different way to those in another individual, which could make some individuals more susceptible to autoimmune diseases than others. However, it was not clear how much genetic and epigenetic variation exists in Treg cells.

Here, Arvey et al. examined Treg and other immune cells from human and mouse donors. The experiments show that some of the epigenetic modifications present in many individuals only in Treg cells, which indicates that they may be important for the activity of the Treg cells. Unexpectedly, most of the epigenetic modifications were specific to either mice or humans, but Arvey et al. identified a core set of genes that had been modified only in Treg cells in both species. In the human cells, Arvey et al. also identified genetic differences in regulatory elements that are associated with autoimmune diseases.

Arvey et al.'s findings suggest that a small set of regulatory elements are crucial to the role of Treg cells in the immune system. Furthermore, genetic variation in these elements can lead to epigenetic changes in Treg cells that contribute to autoimmune diseases in humans. Further study may lead to the development of new treatments for these diseases.

DOI:http://dx.doi.org/10.7554/eLife.07571.002

A Distinct Function of Regulatory T Cells in Tissue Protection

Regulatory T (Treg) cells suppress immune responses to a broad range of non-microbial and microbial antigens and indirectly limit immune inflammation-inflicted tissue damage by employing multiple mechanisms of suppression. Here, we demonstrate that selective Treg cell deficiency in amphiregulin leads to severe acute lung damage and decreased blood oxygen concentration during influenza virus infection without any measureable alterations in Treg cell suppressor function, antiviral immune responses, or viral load. This tissue repair modality is mobilized in Treg cells in response to inflammatory mediator IL-18 or alarmin IL-33, but not by TCR signaling that is required for suppressor function. These results suggest that, during infectious lung injury, Treg cells have a major direct and non-redundant role in tissue repair and maintenance-distinct from their role in suppression of immune responses and inflammation-and that these two essential Treg cell functions are invoked by separable cues.

Continuous requirement for the TCR in regulatory T cell function

Foxp3⁺ regulatory T cells (T_reg cells) maintain immunological tolerance and their deficiency results in fatal multi-organ autoimmunity. Although heightened T cell receptor (TCR) signaling is critical for the differentiation of T_reg cells, the role of TCR signaling in T_reg cell function remains largely unknown. Here we demonstrate inducible ablation of the TCR results in T_reg cell dysfunction which cannot be attributed to impaired Foxp3 expression, decreased expression of T_reg cell signature genes or altered ability to sense and consume interleukin 2. Rather, TCR signaling was required for maintaining the expression of a limited subset of genes comprising 25% of the activated T_reg cell transcriptional signature. Our results reveal a critical role for the TCR in T_reg cell suppressor capacity.

Transcriptional control of regulatory T-cell differentiation

Regulatory T (Treg) cells are essential for maintaining peripheral tolerance and for limiting excessive inflammatory responses under various conditions. The lineage-specific transcription factor Foxp3 has a critical role in Treg-cell biology. Foxp3 forms large protein complexes and cooperates with environmentally induced transcription factors to shape the Treg-cell transcriptional program. Here, we discuss mechanisms of gene regulation that underlie Treg-cell differentiation and function with an emphasis on studies from our laboratory.

Modulation of enhancer looping and differential gene targeting by Epstein-Barr virus transcription factors directs cellular reprogramming

Epstein-Barr virus (EBV) epigenetically reprogrammes B-lymphocytes to drive immortalization and facilitate viral persistence. Host-cell transcription is perturbed principally through the actions of EBV EBNA 2, 3A, 3B and 3C, with cellular genes deregulated by specific combinations of these EBNAs through unknown mechanisms. Comparing human genome binding by these viral transcription factors, we discovered that 25% of binding sites were shared by EBNA 2 and the EBNA 3s and were located predominantly in enhancers. Moreover, 80% of potential EBNA 3A, 3B or 3C target genes were also targeted by EBNA 2, implicating extensive interplay between EBNA 2 and 3 proteins in cellular reprogramming. Investigating shared enhancer sites neighbouring two new targets (WEE1 and CTBP2) we discovered that EBNA 3 proteins repress transcription by modulating enhancer-promoter loop formation to establish repressive chromatin hubs or prevent assembly of active hubs. Re-ChIP analysis revealed that EBNA 2 and 3 proteins do not bind simultaneously at shared sites but compete for binding thereby modulating enhancer-promoter interactions. At an EBNA 3-only intergenic enhancer site between ADAM28 and ADAMDEC1 EBNA 3C was also able to independently direct epigenetic repression of both genes through enhancer-promoter looping. Significantly, studying shared or unique EBNA 3 binding sites at WEE1, CTBP2, ITGAL (LFA-1 alpha chain), BCL2L11 (Bim) and the ADAMs, we also discovered that different sets of EBNA 3 proteins bind regulatory elements in a gene and cell-type specific manner. Binding profiles correlated with the effects of individual EBNA 3 proteins on the expression of these genes, providing a molecular basis for the targeting of different sets of cellular genes by the EBNA 3s. Our results therefore highlight the influence of the genomic and cellular context in determining the specificity of gene deregulation by EBV and provide a paradigm for host-cell reprogramming through modulation of enhancer-promoter interactions by viral transcription factors.

Epstein-Barr virus (EBV) is associated with numerous cancers. The ability of the virus to infect B-cells and convert them from short-lived into immortal cells is the key to its cancer-promoting properties. A small number of EBV transcription factors are required for immortalization and act in concert to drive cell growth by deregulating the expression of cellular genes through largely unknown mechanisms. We have demonstrated that four of these key transcription factors function cooperatively by targeting common genes via long-range enhancer elements and modulating their looping interactions with gene promoters. Specifically we show that gene repression by the EBV EBNA 3 family of proteins can be mediated through the modulation of enhancer-promoter looping. Our results also reveal that different subsets of EBNA 3 proteins are bound at different genes and that this differential binding can vary in lymphoma cells compared to cells immortalized in culture, indicating that cell-background-specific gene regulation may be important in lymphoma development. Our results demonstrate how cellular genes can be deregulated by an oncogenic virus through modulation of enhancer-promoter looping with the specificity of binding by viral transcription factors controlling cellular reprogramming in a gene and cell-type specific manner.

Interpreting the Epstein-Barr Virus (EBV) epigenome using high-throughput data

The Epstein-Barr virus (EBV) double-stranded DNA genome is subject to extensive epigenetic regulation. Large consortiums and individual labs have generated a vast number of genome-wide data sets on human lymphoblastoid and other cell lines latently infected with EBV. Analysis of these data sets reveals important new information on the properties of the host and viral chromosome structure organization and epigenetic modifications. We discuss the mapping of these data sets and the subsequent insights into the chromatin structure and transcription factor binding patterns on latent EBV genomes. Colocalization of multiple histone modifications and transcription factors at regulatory loci are considered in the context of the biology and regulation of EBV.

Sequence and chromatin determinants of cell-type-specific transcription factor binding

Gene regulatory programs in distinct cell types are maintained in large part through the cell-type–specific binding of transcription factors (TFs). The determinants of TF binding include direct DNA sequence preferences, DNA sequence preferences of cofactors, and the local cell-dependent chromatin context. To explore the contribution of DNA sequence signal, histone modifications, and DNase accessibility to cell-type–specific binding, we analyzed 286 ChIP-seq experiments performed by the ENCODE Consortium. This analysis included experiments for 67 transcriptional regulators, 15 of which were profiled in both the GM12878 (lymphoblastoid) and K562 (erythroleukemic) human hematopoietic cell lines. To model TF-bound regions, we trained support vector machines (SVMs) that use flexible k-mer patterns to capture DNA sequence signals more accurately than traditional motif approaches. In addition, we trained SVM spatial chromatin signatures to model local histone modifications and DNase accessibility, obtaining significantly more accurate TF occupancy predictions than simpler approaches. Consistent with previous studies, we find that DNase accessibility can explain cell-line–specific binding for many factors. However, we also find that of the 10 factors with prominent cell-type–specific binding patterns, four display distinct cell-type–specific DNA sequence preferences according to our models. Moreover, for two factors we identify cell-specific binding sites that are accessible in both cell types but bound only in one. For these sites, cell-type–specific sequence models, rather than DNase accessibility, are better able to explain differential binding. Our results suggest that using a single motif for each TF and filtering for chromatin accessible loci is not always sufficient to accurately account for cell-type–specific binding profiles.

An atlas of the Epstein-Barr virus transcriptome and epigenome reveals host-virus regulatory interactions

Epstein-Barr virus (EBV), which is associated with multiple human tumors, persists as a minichromosome in the nucleus of B lymphocytes and induces malignancies through incompletely understood mechanisms. Here, we present a large-scale functional genomic analysis of EBV. Our experimentally generated nucleosome positioning maps and viral protein binding data were integrated with over 700 publicly available high-throughput sequencing data sets for human lymphoblastoid cell lines mapped to the EBV genome. We found that viral lytic genes are coexpressed with cellular cancer-associated pathways, suggesting that the lytic cycle may play an unexpected role in virus-mediated oncogenesis. Host regulators of viral oncogene expression and chromosome structure were identified and validated, revealing a role for the B cell-specific protein Pax5 in viral gene regulation and the cohesin complex in regulating higher order chromatin structure. Our findings provide a deeper understanding of latent viral persistence in oncogenesis and establish a valuable viral genomics resource for future exploration.

Foxp3 exploits a pre-existent enhancer landscape for regulatory T cell lineage specification

Regulatory T (Treg) cells, whose identity and function are defined by the transcription factor Foxp3, are indispensable for immune homeostasis. It is unclear whether Foxp3 exerts its Treg lineage specification function through active modification of the chromatin landscape and establishment of new enhancers or by exploiting a pre-existing enhancer landscape. Analysis of the chromatin accessibility of Foxp3-bound enhancers in Treg and Foxp3-negative T cells showed that Foxp3 was bound overwhelmingly to preaccessible enhancers occupied by its cofactors in precursor cells or a structurally related predecessor. Furthermore, the bulk of Foxp3-bound Treg cell enhancers lacking in Foxp3(-) CD4(+) cells became accessible upon T cell receptor activation prior to Foxp3 expression, and only a small subset associated with several functionally important genes were exclusively Treg cell specific. Thus, in a late cellular differentiation process, Foxp3 defines Treg cell functionality in an "opportunistic" manner by largely exploiting the preformed enhancer network instead of establishing a new enhancer landscape.

Extrathymic generation of regulatory T cells in placental mammals mitigates maternal-fetal conflict

Regulatory T (Treg) cells, whose differentiation and function are controlled by X chromosome-encoded transcription factor Foxp3, are generated in the thymus (tTreg) and extrathymically (peripheral, pTreg), and their deficiency results in fatal autoimmunity. Here, we demonstrate that a Foxp3 enhancer, conserved noncoding sequence 1 (CNS1), essential for pTreg but dispensable for tTreg cell generation, is present only in placental mammals. CNS1 is largely composed of mammalian-wide interspersed repeats (MIR) that have undergone retrotransposition during early mammalian radiation. During pregnancy, pTreg cells specific to a model paternal alloantigen were generated in a CNS1-dependent manner and accumulated in the placenta. Furthermore, when mated with allogeneic, but not syngeneic, males, CNS1-deficient females showed increased fetal resorption accompanied by increased immune cell infiltration and defective remodeling of spiral arteries. Our results suggest that, during evolution, a CNS1-dependent mechanism of extrathymic differentiation of Treg cells emerged in placental animals to enforce maternal-fetal tolerance.

Inferring transcriptional and microRNA-mediated regulatory programs in glioblastoma

Large-scale cancer genomics projects are profiling hundreds of tumors at multiple molecular layers, including copy number, mRNA and miRNA expression, but the mechanistic relationships between these layers are often excluded from computational models. We developed a supervised learning framework for integrating molecular profiles with regulatory sequence information to reveal regulatory programs in cancer, including miRNA-mediated regulation. We applied our approach to 320 glioblastoma profiles and identified key miRNAs and transcription factors as common or subtype-specific drivers of expression changes. We confirmed that predicted gene expression signatures for proneural subtype regulators were consistent with in vivo expression changes in a PDGF-driven mouse model. We tested two predicted proneural drivers, miR-124 and miR-132, both underexpressed in proneural tumors, by overexpression in neurospheres and observed a partial reversal of corresponding tumor expression changes. Computationally dissecting the role of miRNAs in cancer may ultimately lead to small RNA therapeutics tailored to subtype or individual.

Heme controls the regulation of protein tyrosine kinases Jak2 and Src

Protein tyrosine kinases play key roles in many molecular and cellular processes in diverse living organisms. Their proper functioning is crucial for the normal growth, development, and health in humans, whereas their dysfunction can cause serious diseases, including various cancers. As such, intense studies have been performed to understand the molecular mechanisms by which the activities of protein tyrosine kinases are regulated in mammalian cells. Particularly, small molecules that can modulate the activity of tyrosine kinases are of great importance for discovering therapeutic drug candidates for numerous diseases. Notably, heme cannot only serve as a prosthetic group for hemoglobins and enzymes, but it also is a small signaling molecule that can control the activity of diverse signaling and regulatory proteins. Using a computational search, we found that a group of non-membrane spanning tyrosine kinases contains one or more CP motifs that can potentially bind to heme and mediate heme regulation. We then used experimental approaches to determine whether heme can affect the activity of any of these tyrosine kinases. We found that heme indeed affects the phosphorylation of key tyrosine residues in Jak2 and Src, and is therefore able to modulate Jak2 and Src activity. Further experiments showed that Jak2 and Src bind to heme and that the presence of heme alters the sensitivity of Jak2 and Src to trypsin digestion. These results suggest that heme actively interacts with Jak2 and Src and alters their conformation.

High resolution models of transcription factor-DNA affinities improve in vitro and in vivo binding predictions

Accurately modeling the DNA sequence preferences of transcription factors (TFs), and using these models to predict in vivo genomic binding sites for TFs, are key pieces in deciphering the regulatory code. These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices (PSSMs), which may match large numbers of sites and produce an unreliable list of target genes. Recently, protein binding microarray (PBM) experiments have emerged as a new source of high resolution data on in vitro TF binding specificities. PBM data has been analyzed either by estimating PSSMs or via rank statistics on probe intensities, so that individual sequence patterns are assigned enrichment scores (E-scores). This representation is informative but unwieldy because every TF is assigned a list of thousands of scored sequence patterns. Meanwhile, high-resolution in vivo TF occupancy data from ChIP-seq experiments is also increasingly available. We have developed a flexible discriminative framework for learning TF binding preferences from high resolution in vitro and in vivo data. We first trained support vector regression (SVR) models on PBM data to learn the mapping from probe sequences to binding intensities. We used a novel -mer based string kernel called the di-mismatch kernel to represent probe sequence similarities. The SVR models are more compact than E-scores, more expressive than PSSMs, and can be readily used to scan genomics regions to predict in vivo occupancy. Using a large data set of yeast and mouse TFs, we found that our SVR models can better predict probe intensity than the E-score method or PBM-derived PSSMs. Moreover, by using SVRs to score yeast, mouse, and human genomic regions, we were better able to predict genomic occupancy as measured by ChIP-chip and ChIP-seq experiments. Finally, we found that by training kernel-based models directly on ChIP-seq data, we greatly improved in vivo occupancy prediction, and by comparing a TF's in vitro and in vivo models, we could identify cofactors and disambiguate direct and indirect binding.

Minimizing off-target signals in RNA fluorescent in situ hybridization

Fluorescent in situ hybridization (FISH) techniques are becoming extremely sensitive, to the point where individual RNA or DNA molecules can be detected with small probes. At this level of sensitivity, the elimination of 'off-target' hybridization is of crucial importance, but typical probes used for RNA and DNA FISH contain sequences repeated elsewhere in the genome. We find that very short (e.g. 20 nt) perfect repeated sequences within much longer probes (e.g. 350-1500 nt) can produce significant off-target signals. The extent of noise is surprising given the long length of the probes and the short length of non-specific regions. When we removed the small regions of repeated sequence from either short or long probes, we find that the signal-to-noise ratio is increased by orders of magnitude, putting us in a regime where fluorescent signals can be considered to be a quantitative measure of target transcript numbers. As the majority of genes in complex organisms contain repeated k-mers, we provide genome-wide annotations of k-mer-uniqueness at http://cbio.mskcc.org/ approximately aarvey/repeatmap.

ResBoost: characterizing and predicting catalytic residues in enzymes

BACKGROUND

Identifying the catalytic residues in enzymes can aid in understanding the molecular basis of an enzyme's function and has significant implications for designing new drugs, identifying genetic disorders, and engineering proteins with novel functions. Since experimentally determining catalytic sites is expensive, better computational methods for identifying catalytic residues are needed.

RESULTS

We propose ResBoost, a new computational method to learn characteristics of catalytic residues. The method effectively selects and combines rules of thumb into a simple, easily interpretable logical expression that can be used for prediction. We formally define the rules of thumb that are often used to narrow the list of candidate residues, including residue evolutionary conservation, 3D clustering, solvent accessibility, and hydrophilicity. ResBoost builds on two methods from machine learning, the AdaBoost algorithm and Alternating Decision Trees, and provides precise control over the inherent trade-off between sensitivity and specificity. We evaluated ResBoost using cross-validation on a dataset of 100 enzymes from the hand-curated Catalytic Site Atlas (CSA).

CONCLUSION

ResBoost achieved 85% sensitivity for a 9.8% false positive rate and 73% sensitivity for a 5.7% false positive rate. ResBoost reduces the number of false positives by up to 56% compared to the use of evolutionary conservation scoring alone. We also illustrate the ability of ResBoost to identify recently validated catalytic residues not listed in the CSA.