demonstration-sequence-alignment-to-predict-across-species

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

The US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool is a fast, freely available, online ...

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Botulism food poisoning is caused primarily by ingestion of the Clostridium botulinum neurotoxin (BoNT). The 1300 amino acid BoNT forms a progenitor toxin (PTX) that, when associated with a number of other proteins, increases its oral toxicity by protecting it from the low pH of the stomach and from intestinal proteases. One of these associated proteins, HA1, has also been suggested to be involved with internalization of the toxin into the bloodstream by binding to oligosaccharides lining the intestine. Here is reported the crystal structure of HA1 from type C Clostridium botulinum at a resolution of 1.7 Angstrom. The protein consists of two beta-trefoil domains and bears structural similarities to the lectin B-chain from the deadly plant toxin ricin. Based on structural comparison to the ricin B-chain lactose-binding sites, residues of type A HA1 were selected and mutated. The D263A and N285A mutants lost the ability to bind carbohydrates containing galactose moieties, implicating these residues in carbohydrate binding.

Structural analysis by X-ray crystallography and calorimetry of a haemagglutinin component (HA1) of the progenitor toxin from Clostridium botulinum.

An understanding of the physiological and toxicological properties of borate and the utilization of boronic acids in drug development require a basic understanding of borate-enzyme chemistry. We report here the extension of our recent NMR studies indicating the formation of a ternary borate-alcohol-trypsin complex. Crystallographic and solution state NMR studies of porcine trypsin were performed in the presence of borate and either of three alcohols designed to bind to the S1 affinity subsite: 4-aminobutanol, guanidine-3-propanol, and 4-hydroxymethylbenzamidine. Quaternary complexes of trypsin, borate, S1-binding alcohol, and ethylene glycol (a cryoprotectant), as well as a ternary trypsin, borate, and ethylene glycol complex have been observed in the crystalline state. Borate forms ester bonds to Ser195, ethylene glycol (two bonds), and the S1-binding alcohol (if present). Spectra from (1)H and (11)B NMR studies confirm that these complexes also exist in solution and also provide evidence for the formation of ternary trypsin, borate, and S1-subsite alcohol complexes which are not observed in the crystals using our experimental protocols. Analysis of eight crystal structures indicates that formation of an active site borate complex is in all cases accompanied by a significant (approximately 4%) increase in the b-axis dimension of the unit cell. Presumably, our inability to observe the ternary complexes in the crystalline state arises from the lower stability of these complexes and consequent inability to overcome the constraints imposed by the lattice contacts. A mechanism for the coupling of the lattice contacts with the active site that involves a conformational rearrangement of Gln192 is suggested. The structures presented here represent the first crystallographic demonstration of covalent binding of an enzyme by borate.

X-ray and NMR characterization of covalent complexes of trypsin, borate, and alcohols.

Recent 11B NMR studies of the formation of ternary complexes of trypsin, borate, and S1-binding alcohols revealed evidence for an additional binding interaction external to the enzyme active site. We have explored this binding interaction as a prototypical interaction of borate and boronate ligands with residues on the protein surface. NMR studies of trypsin in which the active site is blocked with leupeptin or with the irreversible inhibitor 4-(2-aminoethyl) benzenesulfonyl fluoride hydrochloride (AEBSF) indicate the existence of a low-affinity borate binding site with an apparent dissociation constant of 97 mM, measured at pH 8.0. Observation of a field-dependent dynamic frequency shift of the (11)B resonance indicates that it corresponds to a complex for which omegatau >> 1. The 0.12 ppm shift difference of the borate resonances measured at 11.75 and 7.05 T, corresponds to a quadrupole coupling constant of 260 kHz. A much larger 2.0 ppm shift is observed in the 11B NMR spectra of trypsin complexed with benzene boronic acid (BBA), leading to a calculated quadrupole coupling constant of 1.1 MHz for this complex. Crystallographic studies identify the second borate binding site as a serine-rich region on the surface of the molecule. Specifically, a complex obtained at pH 10.6 shows a borate ion covalently bonded to the hydroxyl oxygen atoms of Ser164 and Ser167, with additional stabilization coming from two hydrogen-bonding interactions. A similar structure, although with low occupancy (30%), is observed for a trypsin-BBA complex. In this case, the BBA is also observed in the active site, covalently bound in two different conformations to both His57 Nepsilon and Ser195 Ogamma. An analysis of pairwise hydroxyl oxygen distances was able to predict the secondary borate binding site in porcine trypsin, and this approach is potentially useful for prediction of borate binding sites on the surfaces of other proteins. However, the distances between the Ser164/Ser167 Ogamma atoms in all of the reported trypsin crystal structures is significantly greater than the Ogamma distances of 2.2 and 1.9 angstroms observed in the trypsin complexes with borate and BBA, respectively. Thus, the ability of the hydroxyl oxygens to adopt a sufficiently close orientation to allow bidentate ligation is a critical limit on the borate binding affinity of surface-accessible serine/threonine/tyrosine residues.

NMR and crystallographic characterization of adventitious borate binding by trypsin.

ACToR (Aggregated Computational Toxicology Resource) is a database and set of software applications that bring into one central location many types and sources of data on environmental chemicals. Currently, the ACToR chemical database contains information on chemical structure, in vitro bioassays and in vivo toxicology assays derived from more than 150 sources including the U.S. Environmental Protection Agency (EPA), Centers for Disease Control (CDC), U.S. Food and Drug Administration (FDA), National Institutes of Health (NIH), state agencies, corresponding government agencies in Canada, Europe and Japan, universities, the World Health Organization (WHO) and non-governmental organizations (NGOs). At the EPA National Center for Computational Toxicology, ACToR helps manage large data sets being used in a high-throughput environmental chemical screening and prioritization program called ToxCast.

ACToR--Aggregated Computational Toxicology Resource.

We describe the development and implementation of a Physiological and Anatomical Visual Analytics tool (PAVA), a web browser-based application, used to visualize experimental/simulated chemical time-course data (dosimetry), epidemiological data and Physiologically-Annotated Data (PAD). Using continuous color mapping scheme both spatial (organ shape and location) and temporal (time-course/kinetics) data was cast onto an abstract, layered, 2D visual representation of the human anatomy and physiology. This approach is aligned with the compartment-level of detail afforded by Physiologically-Based Pharmacokinetic (PBPK) modeling of chemical disposition. In this tutorial we provide several illustrative examples of how PAVA may be applied: (1) visualization of multiple organ/tissue simulated dosimetry of a previously published oral exposure route ethanol PBPK model, (2) visualization of PAD such as organ-specific disease time-lines or (3) tissue-specific mRNA expression-level profiles (e.g. phase I/II metabolic enzymes and nuclear receptors) to draw much needed molecular biological conclusions at organ-level resolution conducive to model development. Furthermore, discussion is raised on how graphical representations of PBPK models, and the use of PAVA more generally to visualize PAD, can be of benefit. We believe this novel platform-independent tool for visualizing PAD on physiologically-relevant representations of human anatomy will become a valuable visual analytic addition to the tool-kits of modern exposure scientists, computational biologists, toxicologists, biochemists, molecular biologists, epidemiologists and pathologists alike in visually translating, representing and mining complex PAD relationships required to understand systems biology or manage chemical risk.

PAVA: physiological and anatomical visual analytics for mapping of tissue-specific concentration and time-course data.

Computational molecular models of chemicals interacting with biomolecular targets provides toxicologists a valuable, affordable, and sustainable source of in silico molecular level information that augments, enriches, and complements in vitro and in vivo efforts. From a molecular biophysical ansatz, we describe how 3D molecular modeling methods used to numerically evaluate the classical pair-wise potential at the chemical/biological interface can inform mechanism of action and the dose-response paradigm of modern toxicology. With an emphasis on molecular docking, 3D-QSAR and pharmacophore/toxicophore approaches, we demonstrate how these methods can be integrated with chemoinformatic and toxicogenomic efforts into a tiered computational toxicology workflow. We describe generalized protocols in which 3D computational molecular modeling is used to enhance our ability to predict and model the most relevant toxicokinetic, metabolic, and molecular toxicological endpoints, thereby accelerating the computational toxicology-driven basis of modern risk assessment while providing a starting point for rational sustainable molecular design.

Informing mechanistic toxicology with computational molecular models.

High-throughput screening (HTS) and computational technologies have emerged as important tools for chemical hazard identification. The US Environmental Protection Agency (EPA) launched the Toxicity ForeCaster (ToxCast) Program, which has screened thousands of chemicals in hundreds of mammalian-based HTS assays for biological activity. The data are being used to prioritize toxicity testing on those chemicals likely to lead to adverse effects. To use HTS assays in predicting hazard to both humans and wildlife, it is necessary to understand how broadly these data may be extrapolated across species. The US EPA Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS; https://seqapass.epa.gov/seqapass/ ) tool was used to assess conservation of the 484 protein targets represented in the suite of ToxCast assays and other HTS assays. To demonstrate the utility of the SeqAPASS data for guiding extrapolation, case studies were developed which focused on targets of interest to the US Endocrine Disruptor Screening Program and the Organisation for Economic Cooperation and Development. These case studies provide a line of evidence for conservation of endocrine targets across vertebrate species, with few exceptions, and demonstrate the utility of SeqAPASS for defining the taxonomic domain of applicability for HTS results and identifying organisms for suitable follow-up toxicity tests.

Evidence for Cross Species Extrapolation of Mammalian-Based High-Throughput Screening Assay Results.

Confident identification of unknown chemicals in high resolution mass spectrometry (HRMS) screening studies requires cohesive workflows and complementary data, tools, and software. Chemistry databases, screening libraries, and chemical metadata have become fixtures in identification workflows. To increase confidence in compound identifications, the use of structural fragmentation data collected via tandem mass spectrometry (MS/MS or MS) is vital. However, the availability of empirically collected MS/MS data for identification of unknowns is limited. Researchers have therefore turned to in silico generation of MS/MS data for use in HRMS-based screening studies. This paper describes the generation en masse of predicted MS/MS spectra for the entirety of the US EPA's DSSTox database using competitive fragmentation modelling and a freely available open source tool, CFM-ID. The generated dataset comprises predicted MS/MS spectra for ~700,000 structures, and mappings between predicted spectra, structures, associated substances, and chemical metadata. Together, these resources facilitate improved compound identifications in HRMS screening studies. These data are accessible via an SQL database, a comma-separated export file (.csv), and EPA's CompTox Chemicals Dashboard.

Linking in silico MS/MS spectra with chemistry data to improve identification of unknowns.

Computational screening for potentially bioactive molecules using advanced molecular modeling approaches including molecular docking and molecular dynamic simulation is mainstream in certain fields like drug discovery. Significant advances in computationally predicting protein structures from sequence information have also expanded the availability of structures for nonmodel species. Therefore, the objective of the present study was to develop an analysis pipeline to harness the power of these bioinformatics approaches for cross-species extrapolation for evaluating chemical safety. The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool compares protein-sequence similarity across species for conservation of known chemical targets, providing an initial line of evidence for extrapolation of toxicity knowledge. However, with the development of structural models from tools like the Iterative Threading ASSEmbly Refinement (ITASSER), analyses of protein structural conservation can be included to add further lines of evidence and generate protein models across species. Models generated through such a pipeline could then be used for advanced molecular modeling approaches in the context of species extrapolation. Two case examples illustrating this pipeline from SeqAPASS sequences to I-TASSER-generated protein structures were created for human liver fatty acid-binding protein (LFABP) and androgen receptor (AR). Ninety-nine LFABP and 268 AR protein models representing diverse species were generated and analyzed for conservation using template modeling (TM)-align. The results from the structural comparisons were in line with the sequence-based SeqAPASS workflow, adding further evidence of LFABL and AR conservation across vertebrate species. The present study lays the foundation for expanding the capabilities of the web-based SeqAPASS tool to include structural comparisons for species extrapolation, facilitating more rapid and efficient toxicological assessments among species with limited or no existing toxicity data. Environ Toxicol Chem 2023;42:463-474. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Article	Year
Structural analysis by X-ray crystallography and calorimetry of a haemagglutinin component (HA1) of the progenitor toxin from Clostridium botulinum. Microbiology (Reading, England)\| PubMed ID: 14663070	2003
X-ray and NMR characterization of covalent complexes of trypsin, borate, and alcohols. Biochemistry\| PubMed ID: 15005618	2004
NMR and crystallographic characterization of adventitious borate binding by trypsin. Bioconjugate chemistry\| PubMed ID: 16536459	2006
ACToR--Aggregated Computational Toxicology Resource. Toxicology and applied pharmacology\| PubMed ID: 18671997	2008
PAVA: physiological and anatomical visual analytics for mapping of tissue-specific concentration and time-course data. Journal of pharmacokinetics and pharmacodynamics\| PubMed ID: 20495853	2010
Informing mechanistic toxicology with computational molecular models. Methods in molecular biology (Clifton, N.J.)\| PubMed ID: 23007429	2012
Evidence for Cross Species Extrapolation of Mammalian-Based High-Throughput Screening Assay Results. Environmental science & technology\| PubMed ID: 30351027	2018
Linking in silico MS/MS spectra with chemistry data to improve identification of unknowns. Scientific data\| PubMed ID: 31375670	2019
From Protein Sequence to Structure: The Next Frontier in Cross-Species Extrapolation for Chemical Safety Evaluations. Environmental toxicology and chemistry\| PubMed ID: 36524855	2023

Thomas R. Transue

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