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Significance The COVID-19 pandemic continues to ravage our society, posing serious economic, social, health, and educational concerns in communities. Understanding the human humoral immune response to COVID-19 infection will greatly inform public health measures to help contain the spread of the disease in the foreseeable future. Here, we present an orthogonal approach to SARS-CoV-2 antibody testing using distinct viral antigens. Using this testing platform, we conducted a community-based analysis of patients with varying experiences with COVID-19. The data from our study show correlations between IgG titer and clinical features (i.e. length and severity of COVID-19 illness) and that IgG titers against SARS-CoV-2 may persist for more than 4 mo post onset of COVID-19 illness., Immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during the current pandemic remains a field of immense interest and active research worldwide. Although the severity of acute infection may depend on the intensity of innate and adaptive immunity, leading to higher morbidity and mortality, the longevity of IgG antibodies, including neutralizing activity to SARS-CoV-2, is viewed as a key correlate of immune protection. Amid reports and concern that there is a rapid decay of IgG antibody levels within 1 mo to 2 mo after acute infection, we set out to study the pattern and duration of IgG antibody response to various SARS-CoV-2 antigens in asymptomatic and symptomatic patients in a community setting. Herein, we show the correlation of IgG anti-spike protein S1 subunit, receptor binding domain, nucleocapsid, and virus neutralizing antibody titers with each other and with clinical features such as length and severity of COVID-19 illness. More importantly, using orthogonal measurements, we found the IgG titers to persist for more than 4 mo post symptom onset, implying that long-lasting immunity to COVID-19 from infection or vaccination might be observed, as seen with other coronaviruses such as SARS and Middle East respiratory syndrome.

Nipah Virus (NiV) has been designated as a priority disease with an urgent need for therapeutic development by World Health Organization. The monoclonal antibody m102.4 binds to the immunodominant NiV receptor-binding glycoprotein (GP), and potently neutralizes NiV, indicating its potential as a therapeutic agent. Although the co-crystal structure of m102.3, an m102.4 derivative, in complex with the GP of the related Hendra Virus (HeV) has been solved, the structural interaction between m102.4 and NiV is uncharacterized. Herein, we used structure-guided alanine-scanning mutagenesis to map the functional epitope and paratope residues that govern the antigen–antibody interaction. Our results revealed that the binding of m102.4 is mediated predominantly by two residues in the HCDR3 region, which is unusually small for an antibody-antigen interaction. We performed computational docking to generate a structural model of m102.4-NiV interaction. Our model indicates that m102.4 targets the common hydrophobic central cavity and a hydrophilic rim on the GP, as observed for the m102.3-HeV co-crystal, albeit with Fv orientation differences. In summary, our study provides insight into the m102.4-NiV interaction, demonstrating that structure-guided alanine-scanning and computational modeling can serve as the starting point for additional antibody reengineering (e.g. affinity maturation) to generate potential therapeutic candidates.

Recombinant human erythropoietin (rHuEPO) is a biopharmaceutical drug given to patients who have a low hemoglobin related to chronic kidney disease, cancer or anemia. However, some patients repeatedly receiving rHuEPO develop anti-rHuEPO neutralizing antibodies leading to the development of pure red cell aplasia (PRCA). The immunogenic antibody response activated by rHuEPO is believed to be triggered by T-cells recognizing EPO epitopes bound to MHC molecules displayed on the cell surface of APCs. Previous studies have reported an association between the development of anti-rHuEpo-associated PRCA and the HLA-DRB1*09 gene, which is reported to be entrenched in the Thai population. In this study, we used computational design to screen for immunogenic hotspots recognized by HLA-DRB1*09, and predicted seventeen mutants having anywhere between one through four mutations that reduce affinity for the allele, without disrupting the structural integrity and bioactivity. Five out of seventeen mutants were less immunogenic in vitro while retaining similar or slightly reduced bioactivity than rHuEPO. These engineered proteins could be the potential candidates to treat patients who are rHuEpo-dependent and express the HLA-DRB1*09 allele.

The surfaces of host cells and viruses are decorated by complex glycans, which play multifaceted roles in the dynamic interplay between the virus and the host including viral entry into host cell, modulation of proteolytic cleavage of viral proteins, recognition and neutralization of virus by host immune system. These roles are mediated by specific multivalent interactions of glycans with their cognate proteins (generally termed as glycan-binding proteins or GBPs or lectins). The advances in tools and technologies to chemically synthesize and structurally characterize glycans and glycan–GBP interactions have offered several insights into the role of glycan–GBP interactions in viral pathogenesis and have presented opportunities to target these interactions for novel antiviral therapeutic or vaccine strategies. This review covers aspects of role of host cell surface glycan receptors and viral surface glycans in viral pathogenesis and offers perspectives on how to employ various analytical tools to target glycan–GBP interactions., National Institutes of Health (U.S.) (Grant R37 GM057073-13)

Following the recent emergence of Zika virus (ZIKV), many murine and human neutralizing anti-ZIKV antibodies have been reported. Given the risk of virus escape mutants, engineering antibodies that target mutationally constrained epitopes with therapeutically relevant potencies can be valuable for combating future outbreaks. Here, we applied computational methods to engineer an antibody, ZAb_FLEP, that targets a highly networked and therefore mutationally constrained surface formed by the envelope protein dimer. ZAb_FLEP neutralized a breadth of ZIKV strains and protected mice in distinct in vivo models, including resolving vertical transmission and fetal mortality in infected pregnant mice. Serial passaging of ZIKV in the presence of ZAb_FLEP failed to generate viral escape mutants, suggesting that its epitope is indeed mutationally constrained. A single-particle cryo-EM reconstruction of the Fab-ZIKV complex validated the structural model and revealed insights into ZAb_FLEP's neutralization mechanism. ZAb_FLEP has potential as a therapeutic in future outbreaks. Tharakaraman et al. describe the engineering and validation of a neutralizing anti-Zika antibody (ZAb_FLEP) that targets a mutationally constrained surface epitope formed by the envelope protein. ZAb_FLEP neutralizes ZIKV strains in vitro and protects mice and unborn pups from Zika infection in vivo, indicating its potential as a therapeutic candidate., National Institutes of Health (U.S.) (Award 1R01AI111395), Singapore. National Research Foundation

Dengue is a widespread viral disease with 3.6 billion people at risk worldwide. Humanized monoclonal antibody (mAb) 513, currently undergoing clinical trials in Singapore, targets an epitope on the envelope protein domain III exposed at the surface of the viral particle. This antibody potently neutralizes all four dengue virus serotypes in a humanized mouse model that recapitulates human dengue infection, without signs of antibody-mediated enhancement of the disease. The crystal structure of single-chain variable fragment (scFv) 513 bound to the envelope protein domain III from dengue virus serotype 4 was used as a template to explore the molecular origins of the broader cross-reactivity and increased in vivo potency of mAb 513, compared to the parent murine mAb 4E11, using molecular dynamics simulations and network analyses. These two methods are a powerful complement to existing structural and binding data and detail specific interactions that underpin the differential binding of the two antibodies. We found that a Glu at position H55 (GluH55) from the second Complementarity Determining Region of the Heavy chain (CDR-H2) which corresponds to Ala in 4E11, is a major contributor to the enhancement in the interactions of mAb 513 compared to 4E11. Importantly, we also validate the importance of GluH55using site-directed mutagenesis followed by isothermal titration calorimetry measurements., National Institutes of Health (U.S.) (Grant 1R01AI111395)

Dengue is the most common vector-borne viral disease, causing nearly 400 million infections yearly. Currently there are no approved therapies. Antibody epitopes that elicit weak humoral responses may not be accessible by conventional B cell panning methods. To demonstrate an alternative strategy to generating a therapeutic antibody, we employed a non-immunodominant, but functionally relevant, epitope in domain III of the E protein, and engineered by structure-guided methods an antibody directed to it. The resulting antibody, Ab513, exhibits high-affinity binding to, and broadly neutralizes, multiple genotypes within all four serotypes. To assess therapeutic relevance of Ab513, activity against important human clinical features of dengue was investigated. Ab513 mitigates thrombocytopenia in a humanized mouse model, resolves vascular leakage, reduces viremia to nearly undetectable levels, and protects mice in a maternal transfer model of lethal antibody-mediated enhancement. The results demonstrate that Ab513 may reduce the public health burden from dengue., National Institutes of Health (U.S.) (NIH Award (1R01AI111395)), National Institute of Environmental Health Sciences (NIEHS training grant (2T32ES007020)), National Institutes of Health (U.S.) (NIH Merit Award (R37 GM057073-13)), National Science Foundation (U.S.)

The 2014-2015 H1N1 outbreak in India has reportedly led to 800 fatalities. The reported influenza hemagglutinin sequences from India indicate that these viruses contain amino acid changes linked to enhanced virulence and are potentially antigenically distinct from the current vaccine containing 2009 (Cal0709) H1N1 viral hemagglutinin., United States. National Institutes of Health (R37 GM057073-13), United States. National Institutes of Health (1R01AI111395)

Recently, progress has been made in the development of vaccines and monoclonal antibody cocktails that target the Ebola coat glycoprotein (GP). Based on the mutation rates for Ebola virus given its natural sequence evolution, these treatment strategies are likely to impose additional selection pressure to drive acquisition of mutations in GP that escape neutralization. Given the high degree of sequence conservation among GP of Ebola viruses, it would be challenging to determine the propensity of acquiring mutations in response to vaccine or treatment with one or a cocktail of monoclonal antibodies. In this study, we analyzed the mutability of each residue using an approach that captures the structural constraints on mutability based on the extent of its inter-residue interaction network within the three-dimensional structure of the trimeric GP. This analysis showed two distinct clusters of highly networked residues along the GP1-GP2 interface, part of which overlapped with epitope surfaces of known neutralizing antibodies. This network approach also permitted us to identify additional residues in the network of the known hotspot residues of different anti-Ebola antibodies that would impact antibody-epitope interactions., National Institutes of Health (U.S.) (MERIT award R37 GM057073-13), National Institutes of Health (U.S.) (Research Project Grant 1R01AI111395-01)

Influenza A viruses are rapidly evolving pathogens with the potential for novel strains to emerge and result in pandemic outbreaks in humans. Some avian-adapted subtypes have acquired the ability to bind to human glycan receptors and cause severe infections in humans but have yet to adapt to and transmit between humans. The emergence of new avian strains and their ability to infect humans has confounded their distinction from circulating human virus strains through linking receptor specificity to human adaptation. Herein we review the various structural and biochemical analyses of influenza hemagglutinin–glycan receptor interactions. We provide our perspectives on how receptor specificity can be used to monitor evolution of the virus to adapt to human hosts so as to facilitate improved surveillance and pandemic preparedness., National Institutes of Health (U.S.) (Merit Award R37 GM057073-13), Singapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology), Skolkovo Institute of Science and Technology

Summary Of the factors governing human-to-human transmission of the highly pathogenic avian-adapted H5N1 virus, the most critical is the acquisition of mutations on the viral hemagglutinin (HA) to "quantitatively switch" its binding from avian to human glycan receptors. Here, we describe a structural framework that outlines a necessary set of H5 HA receptor-binding site (RBS) features required for the H5 HA to quantitatively switch its preference to human receptors. We show here that the same RBS HA mutations that lead to aerosol transmission of A/Vietnam/1203/04 and A/Indonesia/5/05 viruses, when introduced in currently circulating H5N1, do not lead to a quantitative switch in receptor preference. We demonstrate that HAs from circulating clades require as few as a single base pair mutation to quantitatively switch their binding to human receptors. The mutations identified by this study can be used to monitor the emergence of strains having human-to-human transmission potential.

Broadly neutralizing monoclonal antibodies (bNAbs) for viral infections, such as HIV, respiratory syncytial virus (RSV), and influenza, are increasingly entering clinical development. For influenza, most neutralizing antibodies target influenza virus hemagglutinin. These bNAbs represent an emerging, promising modality for treatment and prophylaxis of influenza due to their multiple mechanisms of antiviral action and generally safe profile. Preclinical work in other viral diseases, such as dengue, has demonstrated the potential for antibody-based therapies to enhance viral uptake, leading to enhanced viremia and worsening of disease. This phenomenon is referred to as antibody-dependent enhancement (ADE). In the context of influenza, ADE has been used to explain several preclinical and clinical phenomena. Using structural and viral kinetics modeling, we assess the role of ADE in the treatment of influenza with a bNAb., National Institutes of Health (U.S.) (Merit Award R37 GM057073-13), National Institutes of Health (U.S.) (Grant RO1 AI111395-03)

Heparin and the low molecular weight heparins are extensively used as medicinal products to prevent and treat the formation of venous and arterial thrombi. In early 2008, administration of some heparin lots was associated with the advent of severe adverse effects, indicative of an anaphylactoid-like response. Application of orthogonal analytical tools enabled detection and identification of the contaminant as oversulfated chondroitin sulfate (OSCS) was reported in our earlier report. Herein, we investigate whether enzymatic depolymerization using the bacterially derived heparinases, given the structural understanding of their substrate specificity, can be used to identify the presence of OSCS in heparin. We also extend this analysis to examine the effect of other persulfonated glycosaminoglycans (GAGs) on the action of the heparinases. We find that all persulfonated GAGs examined were effective inhibitors of heparinase I, with IC(50) values ranging from approximately 0.5-2 μg/mL. Finally, using this biochemical understanding, we develop a rapid, simple assay to assess the purity of heparin using heparinase digestion followed by size-exclusion HPLC analysis to identify and quantify digestion products. In the context of the assay, we demonstrate that less than 0.1% (w/w) of OSCS (and other persulfonated polysaccharides) can routinely be detected in heparin.

A number of previous studies have predicted transcription factor binding sites (TFBSs) by exploiting the position of genomic landmarks like the transcriptional start site (TSS). The studies’ methods are generally too computationally intensive for genome-scale investigation, so the full potential of ‘positional regulomics’ to discover TFBSs and determine their function remains unknown. Because databases often annotate the genomic landmarks in DNA sequences, the methodical exploitation of positional regulomics has become increasingly urgent. Accordingly, we examined a set of 7914 human putative promoter regions (PPRs) with a known TSS. Our methods identified 1226 eight-letter DNA words with significant positional preferences with respect to the TSS, of which only 608 of the 1226 words matched known TFBSs. Many groups of genes whose PPRs contained a common word displayed similar expression profiles and related biological functions, however. Most interestingly, our results included 78 words, each of which clustered significantly in two or three different positions relative to the TSS. Often, the gene groups corresponding to different positional clusters of the same word corresponded to diverse functions, e.g. activation or repression in different tissues. Thus, different clusters of the same word likely reflect the phenomenon of ‘positional regulation’, i.e. a word's regulatory function can vary with its position relative to a genomic landmark, a conclusion inaccessible to methods based purely on sequence. Further integrative analysis of words co-occurring in PPRs also yielded 24 different groups of genes, likely identifying cis-regulatory modules de novo. Whereas comparative genomics requires precise sequence alignments, positional regulomics exploits genomic landmarks to provide a ‘poor man's alignment’. By exploiting the phenomenon of positional regulation, it uses position to differentiate the biological functions of subsets of TFBSs sharing a common sequence motif.

Emerging strains of influenza represent a significant public health threat with potential pandemic consequences. Of particular concern are the recently emerged H7N9 strains which cause pneumonia with acute respiratory distress syndrome. Estimates are that nearly 80% of hospitalized patients with H7N9 have received intensive care unit support. VIS410, a human antibody, targets a unique conserved epitope on influenza A. We evaluated the efficacy of VIS410 for neutralization of group 2 influenza strains, including H3N2 and H7N9 strains in vitro and in vivo. VIS410, administered at 50 mg/kg, protected DBA mice infected with A/Anhui/2013 (H7N9), resulting in significant survival benefit upon single-dose (-24 h) or double-dose (-12 h, +48 h) administration (P < 0.001). A single dose of VIS410 at 50 mg/kg (-12 h) combined with oseltamivir at 50 mg/kg (-12 h, twice daily for 7 d) in C57BL/6 mice infected with A/Shanghai 2/2013 (H7N9) resulted in significant decreased lung viral load (P = 0.002) and decreased lung cytokine responses for nine of the 11 cytokines measured. Based on these results, we find that VIS410 may be effective either as monotherapy or combined with antivirals in treating H7N9 disease, as well as disease from other influenza strains.

Motivation: The transcription start site (TSS) has been located for an increasing number of genes across several organisms. Statistical tests have shown that some cis-acting regulatory elements have positional preferences with respect to the TSS, but few strategies have emerged for locating elements by their positional preferences. This paper elaborates such a strategy. First, we align promoter regions without gaps, anchoring the alignment on each promoter's TSS. Second, we apply a novel word-specific mask. Third, we apply a clustering test related to gapless BLAST statistics. The test examines whether any specific word is placed unusually consistently with respect to the TSS. Finally, our program A-GLAM, an extension of the GLAM program, uses significant word positions as new 'anchors' to realign the sequences. A Gibbs sampling algorithm then locates putative cis-acting regulatory elements. Usually, Gibbs sampling requires a preliminary masking step, to avoid convergence onto a dominant but uninteresting signal from a DNA repeat. However, since the positional anchors focus A-GLAM on the motif of interest, masking DNA repeats during Gibbs sampling becomes unnecessary. Results: In a set of human DNA sequences with experimentally characterized TSSs, the placement of 791 octonucleotide words was unusually consistent (multiple test corrected P < 0.05). Alignments anchored on these words sometimes located statistically significant motifs inaccessible to GLAM or AlignACE. Availability: The A-GLAM program and a list of statistically significant words are available at ftp://ftp.ncbi.nih.gov/pub/spouge/papers/archive/AGLAM/. Contact: spouge@ncbi.nlm.nih.gov

Broadly neutralizing antibodies (bNAb) that target a conserved region of a viral antigen hold significant therapeutic promise. CR8020 is a bNAb that targets the stem region of influenza A virus (IAV) hemagglutinin (HA). CR8020 is currently being evaluated for prophylactic use against group 2 IAVs in phase II studies. Structural and computational analyses reported here indicate that CR8020 targets HA residues that are prone to antigenic drift and host selection pressure. Critically, CR8020 escape mutation is seen in certain H7N9 viruses from recent outbreaks. Furthermore, the ability of the bNAb Fc region to effectively engage activating Fcγ receptors (FCγR) is essential for antibody efficacy. In this regard, our data indicate that the membrane could sterically hinder the formation of HA-CR8020-FcγRIIa/HA-IgG-FcγRIIIa ternary complexes. Altogether, our analyses suggest that epitope mutability and accessibility to immune complex assembly are important attributes to consider when evaluating bNAb candidates for clinical development., National Institutes of Health (U.S.) (Merit Award R37 GM057073-13), Singapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology)

SummaryThe advent of H7N9 in early 2013 is of concern for a number of reasons, including its capability to infect humans, the lack of clarity in the etiology of infection, and because the human population does not have pre-existing immunity to the H7 subtype. Earlier sequence analyses of H7N9 hemagglutinin (HA) point to amino acid changes that predicted human receptor binding and impinge on the antigenic characteristics of the HA. Here, we report that the H7N9 HA shows limited binding to human receptors; however, should a single amino acid mutation occur, this would result in structural changes within the receptor binding site that allow for extensive binding to human receptors present in the upper respiratory tract. Furthermore, a subset of the H7N9 HA sequences demarcating coevolving amino acids appears to be in the antigenic regions of H7, which, in turn, could impact effectiveness of the current WHO-recommended prepandemic H7 vaccines.

Affinity improvement of proteins, including antibodies, by computational chemistry broadly relies on physics-based energy functions coupled with refinement. However, achieving significant enhancement of binding affinity (>10-fold) remains a challenging exercise, particularly for cross-reactive antibodies. We describe here an empirical approach that captures key physicochemical features common to antigen–antibody interfaces to predict protein–protein interaction and mutations that confer increased affinity. We apply this approach to the design of affinity-enhancing mutations in 4E11, a potent cross-reactive neutralizing antibody to dengue virus (DV), without a crystal structure. Combination of predicted mutations led to a 450-fold improvement in affinity to serotype 4 of DV while preserving, or modestly increasing, affinity to serotypes 1–3 of DV. We show that increased affinity resulted in strong in vitro neutralizing activity to all four serotypes, and that the redesigned antibody has potent antiviral activity in a mouse model of DV challenge. Our findings demonstrate an empirical computational chemistry approach for improving protein–protein docking and engineering antibody affinity, which will help accelerate the development of clinically relevant antibodies.

The 2009 swine-origin H1N1 influenza, though antigenically novel to the population at the time, was antigenically similar to the 1918 H1N1 pandemic influenza, and consequently was considered to be “archived” in the swine species before reemerging in humans. Given that the H3N2 is another subtype that currently circulates in the human population and is high on WHO pandemic preparedness list, we assessed the likelihood of reemergence of H3N2 from a non-human host. Using HA sequence features relevant to immune recognition, receptor binding and transmission we have identified several recent H3 strains in avian and swine that present hallmarks of a reemerging virus. IgG polyclonal raised in rabbit with recent seasonal vaccine H3 fail to recognize these swine H3 strains suggesting that existing vaccines may not be effective in protecting against these strains. Vaccine strategies can mitigate risks associated with a potential H3N2 pandemic in humans., National Institutes of Health (U.S.) (R37 GM057073-13)

The recent incidence and spread in humans of the 'swine flu' influenza A virus has raised global concerns regarding its virulence and pandemic potential. The main cause of the so-called swine flu has been identified as human infection by influenza A viruses of a new H1N1 (hemagglutinin 1, neuraminidase 1) subtype, or '2009 H1N1 strain'.

Reliable identification and assignment of cis-regulatory elements in promoter regions is a challenging problem in biology. The sophistication of transcriptional regulation in higher eukaryotes, particularly in metazoans, could be an important factor contributing to their organismal complexity. Here we present an integrated approach where networks of co-expressed genes are combined with gene ontology-derived functional networks to discover clusters of genes that share both similar expression patterns and functions. Regulatory elements are identified in the promoter regions of these gene clusters using a Gibbs sampling algorithm implemented in the A-GLAM software package. Using this approach, we analyze the cell-cycle co-expression network of the yeast Saccharomyces cerevisiae, showing that this approach correctly identifies cis-regulatory elements present in clusters of co-expressed genes.

Reliable detection of cis-regulatory elements in promoter regions is a difficult and unsolved problem in computational biology. The intricacy of transcriptional regulation in higher eukaryotes, primarily in metazoans, could be a major driving force of organismal complexity. Eukaryotic genome annotations have improved greatly due to large-scale characterization of full-length cDNAs, transcriptional start sites (TSSs), and comparative genomics. Regulatory elements are identified in promoter regions using a variety of enumerative or alignment-based methods. Here we present a survey of recent computational methods for eukaryotic promoter analysis and describe the use of an alignment-based method implemented in the A-GLAM program.

Motivation: Many computational methods for identifying regulatory elements use a likelihood ratio between motif and background models. Often, the methods use a background model of independent bases. At least two different Markov background models have been proposed with the aim of increasing the accuracy of predicting regulatory elements. Both Markov background models suffer theoretical drawbacks, so this article develops a third, context-dependent Markov background model from fundamental statistical principles. Results: Datasets containing known regulatory elements in eukaryotes provided a basis for comparing the predictive accuracies of the different background models. Non-parametric statistical tests indicated that Markov models of order 3 constituted a statistically significant improvement over the background model of independent bases. Our model performed slightly better than the previous Markov background models. We also found that for discriminating between the predictive accuracies of competing background models, the correlation coefficient is a more sensitive measure than the performance coefficient. Availability: Our C++ program is available at Contact: spouge@ncbi.nlm.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.

Background Many DNA regulatory elements occur as multiple instances within a target promoter. Gibbs sampling programs for finding DNA regulatory elements de novo can be prohibitively slow in locating all instances of such an element in a sequence set. Results We describe an improvement to the A-GLAM computer program, which predicts regulatory elements within DNA sequences with Gibbs sampling. The improvement adds an optional "scanning step" after Gibbs sampling. Gibbs sampling produces a position specific scoring matrix (PSSM). The new scanning step resembles an iterative PSI-BLAST search based on the PSSM. First, it assigns an "individual score" to each subsequence of appropriate length within the input sequences using the initial PSSM. Second, it computes an E-value from each individual score, to assess the agreement between the corresponding subsequence and the PSSM. Third, it permits subsequences with E-values falling below a threshold to contribute to the underlying PSSM, which is then updated using the Bayesian calculus. A-GLAM iterates its scanning step to convergence, at which point no new subsequences contribute to the PSSM. After convergence, A-GLAM reports predicted regulatory elements within each sequence in order of increasing E-values, so users have a statistical evaluation of the predicted elements in a convenient presentation. Thus, although the Gibbs sampling step in A-GLAM finds at most one regulatory element per input sequence, the scanning step can now rapidly locate further instances of the element in each sequence. Conclusion Datasets from experiments determining the binding sites of transcription factors were used to evaluate the improvement to A-GLAM. Typically, the datasets included several sequences containing multiple instances of a regulatory motif. The improvements to A-GLAM permitted it to predict the multiple instances.