A Simple Protocol for the Comparative Analysis of the Structure and Occurrence of Biochemical Pathways Across Superkingdoms

Fe-S cluster biosynthesis and maturation: Mass spectrometry-based methods advancing the field

Iron‑sulfur (FeS) clusters are inorganic protein cofactors that perform essential functions in many physiological processes. Spectroscopic techniques have historically been used to elucidate details of FeS cluster type, their assembly and transfer, and changes in redox and ligand binding properties. Structural probes of protein topology, complex formation, and conformational dynamics are also necessary to fully understand these FeS protein systems. Recent developments in mass spectrometry (MS) instrumentation and methods provide new tools to investigate FeS cluster and structural properties. With the unique advantage of sampling all species in a mixture, MS-based methods can be utilized as a powerful complementary approach to probe native dynamic heterogeneity, interrogate protein folding and unfolding equilibria, and provide extensive insight into protein binding partners within an entire proteome. Here, we highlight key advances in FeS protein studies made possible by MS methodology and contribute an outlook for its role in the field.

The zinc proteome of SARS-CoV-2

Zinc is an essential element for human health. Among its many functions, zinc(II) modulates the immune response to infections and, at high concentrations or in the presence of ionophores, inhibits the replication of various RNA viruses. Structural biology studies on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) revealed that zinc(II) is the most common metal ion that binds to viral proteins. However, the number of zinc(II)-binding sites identified by experimental methods is far from exhaustive, as metal ions may be lost during protein purification protocols. To better define the zinc(II)-binding proteome of coronavirus, we leveraged the wealth of deposited structural data and state-of-the-art bioinformatics methods. Through this in silico approach, 15 experimental zinc(II) sites were identified and a further 22 were predicted in Spike, open reading frame (ORF)3a/d, ORF8, and several nonstructural proteins, highlighting an essential role of zinc(II) in viral replication. Furthermore, the structural relationships between viral and eukaryotic sites (typically zinc fingers) indicate that SARS-CoV-2 can compete with human proteins for zinc(II) binding. Given the double-edged effect of zinc(II) ions, both essential and toxic to coronavirus, only the complete elucidation of the structural and regulatory zinc(II)-binding sites can guide selective antiviral strategies based on zinc supplementation.

The Fe-S proteome of Escherichia coli: prediction, function and fate

Iron-sulfur (Fe-S) clusters are inorganic ubiquitous and ancient cofactors. Fe-S bound proteins contribute to most cellular processes, including DNA replication and integrity, genetic expression and regulation, metabolism, biosynthesis and most bioenergetics systems. Also, Fe-S proteins hold a great biotechnological potential in metabolite and chemical production, including antibiotics. From classic biophysics and spectroscopy methodologies to recent development in bioinformatics, including structural modeling and chemoproteomics, our capacity to predict and identify Fe-S proteins has spectacularly increased over the recent years. Here, these developments are presented and collectively used to update the composition of Escherichia coli Fe-S proteome, for which we predict 181 occurrences, i.e. 40 more candidates than in our last catalog (Py and Barras, 2010), and equivalent to 4% of its total proteome. Besides, Fe-S clusters can be targeted by redox active compounds or reactive oxygen and nitrosative species, and even be destabilized by contaminant metals. Accordingly, we discuss how cells handle damaged Fe-S proteins, i.e. degradation, recycling or repair.

The Human Myelin Proteome and Sub-Metalloproteome Interaction Map: Relevance to Myelin-Related Neurological Diseases

Myelin in humans is composed of about 80% lipids and 20% protein. Initially, myelin protein composition was considered low, but various recent proteome analyses have identified additional myelin proteins. Although, the myelin proteome is qualitatively and quantitatively identified through complementary proteomic approaches, the corresponding Protein–Protein Interaction (PPI) network of myelin is not yet available. In the present work, the PPI network was constructed based on available experimentally supported protein interactions of myelin in PPI databases. The network comprised 2017 PPIs between 567 myelin proteins. Interestingly, structure-based in silico analysis revealed that 20% of the myelin proteins that are interconnected in the proposed PPI network are metal-binding proteins/enzymes that construct the main sub-PPI network of myelin proteome. Finally, the PPI networks of the myelin proteome and sub-metalloproteome were analyzed ontologically to identify the biochemical processes of the myelin proteins and the interconnectivity of myelin-associated diseases in the interactomes. The presented PPI dataset could provide a useful resource to the scientific community to further our understanding of human myelin biology and serve as a basis for future studies of myelin-related neurological diseases and particular autoimmune diseases such as multiple sclerosis where myelin epitopes are implicated.

Structural Identification of Metalloproteomes in Marine Diatoms, an Efficient Algae Model in Toxic Metals Bioremediation

The biosorption of pollutants using microbial organisms has received growing interest in the last decades. Diatoms, the most dominant group of phytoplankton in oceans, are (i) pollution tolerant species, (ii) excellent biological indicators of water quality, and (iii) efficient models in assimilation and detoxification of toxic metal ions. Published research articles connecting proteomics with the capacity of diatoms for toxic metal removal are very limited. In this work, we employed a structural based systematic approach to predict and analyze the metalloproteome of six species of marine diatoms: Thalassiosira pseudonana, Phaeodactylum tricornutum, Fragilariopsis cylindrus, Thalassiosira oceanica, Fistulifera solaris, and Pseudo-nitzschia multistriata. The results indicate that the metalloproteome constitutes a significant proportion (~13%) of the total diatom proteome for all species investigated, and the proteins binding non-essential metals (Cd, Hg, Pb, Cr, As, and Ba) are significantly more than those identified for essential metals (Zn, Cu, Fe, Ca, Mg, Mn, Co, and Ni). These findings are most likely related to the well-known toxic metal tolerance of diatoms. In this study, metalloproteomes that may be involved in metabolic processes and in the mechanisms of bioaccumulation and detoxification of toxic metals of diatoms after exposure to toxic metals were identified and described.

The Mechanism of Metal Homeostasis in Plants: A New View on the Synergistic Regulation Pathway of Membrane Proteins, Lipids and Metal Ions

Heavy metal stress (HMS) is one of the most destructive abiotic stresses which seriously affects the growth and development of plants. Recent studies have shown significant progress in understanding the molecular mechanisms underlying plant tolerance to HMS. In general, three core signals are involved in plants' responses to HMS; these are mitogen-activated protein kinase (MAPK), calcium, and hormonal (abscisic acid) signals. In addition to these signal components, other regulatory factors, such as microRNAs and membrane proteins, also play an important role in regulating HMS responses in plants. Membrane proteins interact with the highly complex and heterogeneous lipids in the plant cell environment. The function of membrane proteins is affected by the interactions between lipids and lipid-membrane proteins. Our review findings also indicate the possibility of membrane protein-lipid-metal ion interactions in regulating metal homeostasis in plant cells. In this review, we investigated the role of membrane proteins with specific substrate recognition in regulating cell metal homeostasis. The understanding of the possible interaction networks and upstream and downstream pathways is developed. In addition, possible interactions between membrane proteins, metal ions, and lipids are discussed to provide new ideas for studying metal homeostasis in plant cells.

A SARS-CoV-2 -human metalloproteome interaction map

The recent pandemic caused by the novel coronavirus resulted in the greatest global health crisis since the Spanish flu pandemic of 1918. There is limited knowledge of whether SARS-CoV-2 is physically associated with human metalloproteins. Recently, high-confidence, experimentally supported protein-protein interactions between SARS-CoV-2 and human proteins were reported. In this work, 58 metalloproteins among these human targets have been identified by a structure-based approach. This study reveals that most human metalloproteins interact with the recently discovered SARS-CoV-2 orf8 protein, whose antibodies are one of the principal markers of SARS-CoV-2 infections. Furthermore, this work provides sufficient evidence to conclude that Zn²⁺ plays an important role in the interplay between the novel coronavirus and humans. First, the content of Zn-binding proteins in the involved human metalloproteome is significantly higher than that of the other metal ions. Second, a molecular linkage between the identified human Zn-binding proteome with underlying medical conditions, that might increase the risk of severe illness from the SARS-CoV-2 virus, has been found. Likely perturbations of host cellular metal homeostasis by SARS-CoV-2 infection are highlighted.

Bioinformatics of Metalloproteins and Metalloproteomes

Trace metals are inorganic elements that are required for all organisms in very low quantities. They serve as cofactors and activators of metalloproteins involved in a variety of key cellular processes. While substantial effort has been made in experimental characterization of metalloproteins and their functions, the application of bioinformatics in the research of metalloproteins and metalloproteomes is still limited. In the last few years, computational prediction and comparative genomics of metalloprotein genes have arisen, which provide significant insights into their distribution, function, and evolution in nature. This review aims to offer an overview of recent advances in bioinformatic analysis of metalloproteins, mainly focusing on metalloprotein prediction and the use of different metals across the tree of life. We describe current computational approaches for the identification of metalloprotein genes and metal-binding sites/patterns in proteins, and then introduce a set of related databases. Furthermore, we discuss the latest research progress in comparative genomics of several important metals in both prokaryotes and eukaryotes, which demonstrates divergent and dynamic evolutionary patterns of different metalloprotein families and metalloproteomes. Overall, bioinformatic studies of metalloproteins provide a foundation for systematic understanding of trace metal utilization in all three domains of life.

The human iron-proteome

Organisms from all kingdoms of life use iron-proteins in a multitude of functional processes. We applied a bioinformatics approach to investigate the human portfolio of iron-proteins. We separated iron-proteins based on the chemical nature of their metal-containing cofactors: individual iron ions, heme cofactors and iron-sulfur clusters. We found that about 2% of human genes encode an iron-protein. Of these, 35% are proteins binding individual iron ions, 48% are heme-binding proteins and 17% are iron-sulfur proteins. More than half of the human iron-proteins have a catalytic function. Indeed, we predict that 6.5% of all human enzymes are iron-dependent. This percentage is quite different for the various enzyme classes. Human oxidoreductases feature the largest fraction of iron-dependent family members (about 37%). The distribution of iron proteins in the various cellular compartments is uneven. In particular, the mitochondrion and the endoplasmic reticulum are enriched in iron-proteins with respect to the average content of the cell. Finally, we observed that genes encoding iron-proteins are more frequently associated to pathologies than the all other human genes on average. The present research provides an extensive overview of iron usage by the human proteome, and highlights several specific features of the physiological role of iron ions in human cells.

A Model for Manganese interaction with Deinococcus radiodurans proteome network involved in ROS response and defense

A complex network of regulatory proteins takes part in the mechanism underlying the radioresistance of Deinoccocus radiodurans bacterium (DR). The interaction of Mn(II) ions with DR-proteins and peptides seems to be responsible for proteins protection from oxidative damage induced by Reactive Oxygen Species during irradiation. In the present work we describe a combined approach of bioinformatic strategies based on structural data and annotation to predict the Mn(II)-binding proteins encoded by the genome of DR and, in parallel, the same predictions for other bacteria were performed; the comparison revealed that, in most of the cases, the content of Mn(II)-binding proteins is significantly higher in radioresistant than in radiosensitive bacteria. Moreover, we report the in silico protein-protein interaction network of the putative Mn(II)-proteins, remodeled in order to enhance the knowledge about the impact of Mn-binding proteins in DR ability to protect also DNA from various damaging agents such as ionizing radiation, UV radiation and oxidative stress.

Metallomics: The Science of Biometals and Biometalloids

Metallomics, a discipline integrating sciences that address the biometals and biometalloids, provides new opportunities for discoveries. As part of a systems biology approach, it draws attention to the importance of many chemical elements in biochemistry. Traditionally, biochemistry has treated life as organic chemistry, separating it from inorganic chemistry, considered a field reserved for investigating the inanimate world. However, inorganic chemistry is part of the chemistry of life, and metallomics contributes by showing the importance of a neglected fifth branch of building blocks in biochemistry. Metallomics adds chemical elements/metals to the four building blocks of biomolecules and the fields of their studies: carbohydrates (glycome), lipids (lipidome), proteins (proteome), and nucleotides (genome). The realization that non-essential elements are present in organisms in addition to essential elements represents a certain paradigm shift in our thinking, as it stipulates inquiries into the functional implications of virtually all the natural elements. This article discusses opportunities arising from metallomics for a better understanding of human biology and health. It looks at a biological periodic system of the elements as a sum of metallomes and focuses on the major roles of metals in about 30-40% of all proteins, the metalloproteomes. It emphasizes the importance of zinc and iron biology and discusses why it is important to investigate non-essential metal ions, what bioinformatics approaches can contribute to understanding metalloproteins, and why metallomics has a bright future in the many dimensions it covers.

Single-Cell Genomics Reveals a Diverse Metabolic Potential of Uncultivated Desulfatiglans-Related Deltaproteobacteria Widely Distributed in Marine Sediment

Desulfatiglans-related organisms comprise one of the most abundant deltaproteobacterial lineages in marine sediments where they occur throughout the sediment column in a gradient of increasing sulfate and organic carbon limitation with depth. Characterized Desulfatiglans isolates are dissimilatory sulfate reducers able to grow by degrading aromatic hydrocarbons. The ecophysiology of environmental Desulfatiglans-populations is poorly understood, however, possibly utilization of aromatic compounds may explain their predominance in marine subsurface sediments. We sequenced and analyzed seven Desulfatiglans-related single-cell genomes (SAGs) from Aarhus Bay sediments to characterize their metabolic potential with regard to aromatic compound degradation and energy metabolism. The average genome assembly size was 1.3 Mbp and completeness estimates ranged between 20 and 50%. Five of the SAGs (group 1) originated from the sulfate-rich surface part of the sediment while two (group 2) originated from sulfate-depleted subsurface sediment. Based on 16S rRNA gene amplicon sequencing group 2 SAGs represent the more frequent types of Desulfatiglans-populations in Aarhus Bay sediments. Genes indicative of aromatic compound degradation could be identified in both groups, but the two groups were metabolically distinct with regard to energy conservation. Group 1 SAGs carry a full set of genes for dissimilatory sulfate reduction, whereas the group 2 SAGs lacked any genetic evidence for sulfate reduction. The latter may be due to incompleteness of the SAGs, but as alternative energy metabolisms group 2 SAGs carry the genetic potential for growth by acetogenesis and fermentation. Group 1 SAGs encoded reductive dehalogenase genes, allowing them to access organohalides and possibly conserve energy by their reduction. Both groups possess sulfatases unlike their cultured relatives allowing them to utilize sulfate esters as source of organic carbon and sulfate. In conclusion, the uncultivated marine Desulfatiglans populations are metabolically diverse, likely reflecting different strategies for coping with energy and sulfate limitation in the subsurface seabed.

To what extent do structural changes in catalytic metal sites affect enzyme function?

About half of known enzymatic reactions involve metals. Enzymes belonging to the same superfamily often evolve to catalyze different reactions on the same structural scaffold. The work presented here investigates how functional differentiation, within superfamilies that contain metalloenzymes, relates to structural changes at the catalytic metal site. In general, when the catalytic metal site is unchanged across the enzymes of a superfamily, the functional differentiation within the superfamily tends to be low and the mechanism conserved. Conversely, all types of structural changes in the metal binding site are observed for superfamilies with high functional differentiation. Overall, the catalytic role of the metal ions appears to be one of the most conserved features of the enzyme mechanism within metalloenzyme superfamilies. In particular, when the catalytic role of the metal ion does not involve a redox reaction (i.e. there is no exchange of electrons with the substrate), this role is almost always maintained even when the site undergoes significant structural changes. In these enzymes, functional diversification is most often associated with modifications in the surrounding protein matrix, which has changed so much that the enzyme chemistry is significantly altered. On the other hand, in more than 50% of the examples where the metal has a redox role in catalysis, changes at the metal site modify its catalytic role. Further, we find that there are no examples in our dataset where metal sites with a redox role are lost during evolution.

SYNOPSIS

In this paper we investigate how functional diversity within superfamilies of metalloenzymes relates to structural changes at the catalytic metal site. Evolution tends to strictly conserve the metal site. When changes occur, they do not modify the catalytic role of non-redox metals whereas they affect the role of redox-active metals.

Shared gene-network signatures between the human heavy metal proteome and neurological disorders and cancer types

In this work, for the first time, the human heavy metal proteome was predicted.

The Relationship between Environmental Dioxygen and Iron-Sulfur Proteins Explored at the Genome Level

About 2 billion years ago, the atmosphere of the Earth experienced a great change due to the buildup of dioxygen produced by photosynthetic organisms. This transition caused a reduction of iron bioavailability and at the same time exposed living organisms to the threat of oxidative stress. Iron-sulfur (Fe-S) clusters require iron ions for their biosynthesis and are labile if exposed to reactive oxygen species. To assess how the above transition influenced the usage of Fe-S clusters by organisms, we compared the distribution of the Fe-S proteins encoded by the genomes of more than 400 prokaryotic organisms as a function of their dioxygen requirements. Aerobic organisms use less Fe-S proteins than the majority of anaerobic organisms with a similar genome size. Furthermore, aerobes have evolved specific Fe-S proteins that bind the less iron-demanding and more chemically stable Fe₂S₂ clusters while reducing the number of Fe₄S₄-binding proteins in their genomes. However, there is a shared core of Fe-S protein families composed mainly by Fe₄S₄-binding proteins. Members of these families are present also in humans. The distribution of human Fe-S proteins within cell compartments shows that mitochondrial proteins are inherited from prokaryotic proteins of aerobes, whereas nuclear and cytoplasmic Fe-S proteins are inherited from anaerobic organisms.

MetalPredator: a web server to predict iron-sulfur cluster binding proteomes

MOTIVATION

The prediction of the iron-sulfur proteome is highly desirable for biomedical and biological research but a freely available tool to predict iron-sulfur proteins has not been developed yet.

RESULTS

We developed a web server to predict iron-sulfur proteins from protein sequence(s). This tool, called MetalPredator, is able to process complete proteomes rapidly with high recall and precision.

AVAILABILITY AND IMPLEMENTATION

The web server is freely available at: http://metalweb.cerm.unifi.it/tools/metalpredator/

CONTACT

andreini@cerm.unifi.it

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Minimal Functional Sites in Metalloproteins and Their Usage in Structural Bioinformatics

Metal ions play a functional role in numerous biochemical processes and cellular pathways. Indeed, about 40% of all enzymes of known 3D structure require a metal ion to be able to perform catalysis. The interactions of the metals with the macromolecular framework determine their chemical properties and reactivity. The relevant interactions involve both the coordination sphere of the metal ion and the more distant interactions of the so-called second sphere, i.e., the non-bonded interactions between the macromolecule and the residues coordinating the metal (metal ligands). The metal ligands and the residues in their close spatial proximity define what we call a minimal functional site (MFS). MFSs can be automatically extracted from the 3D structures of metal-binding biological macromolecules deposited in the Protein Data Bank (PDB). They are 3D templates that describe the local environment around a metal ion or metal cofactor and do not depend on the overall macromolecular structure. MFSs provide a different view on metal-binding proteins and nucleic acids, completely focused on the metal. Here we present different protocols and tools based upon the concept of MFS to obtain deeper insight into the structural and functional properties of metal-binding macromolecules. We also show that structure conservation of MFSs in metalloproteins relates to local sequence similarity more strongly than to overall protein similarity.

Paracoccidioides spp. ferrous and ferric iron assimilation pathways

Iron is an essential micronutrient for almost all organisms, including fungi. Usually, fungi can uptake iron through receptor-mediated internalization of a siderophore or heme, and/or reductive iron assimilation (RIA). Traditionally, the RIA pathway consists of ferric reductases (Fres), ferroxidase (Fet3) and a high-affinity iron permease (Ftr1). Paracoccidioides spp. genomes do not present an Ftr1 homolog. However, this fungus expresses zinc regulated transporter homologs (Zrts), members of the ZIP family of membrane transporters that are able in some organisms to transport zinc and iron. A 2,3,5-triphenyltetrazolium chloride (TTC)-overlay assay indicates that both Pb01 and Pb18 express a ferric reductase activity; however, ⁵⁹Fe uptake assays indicate that only in Pb18 is this activity coupled to a reductase-dependent iron uptake pathway. In addition, Zrts are up-regulated in iron deprivation, as indicated by RNAseq and qRT-PCR using Pb01 transcripts. RNAseq strategy also demonstrated that transcripts related to siderophore uptake and biosynthesis are up-regulated in iron-deprived condition. The data suggest that the fungus could use both a non-classical RIA, comprising ferric reductases and Fe/Zn permeases (Zrts), and siderophore uptake pathways under iron-limited conditions. The study of iron metabolism reveals novel surface molecules that could function as accessible targets for drugs to block iron uptake and, consequently, inhibit pathogen's proliferation.

Predicting copper-, iron-, and zinc-binding proteins in pathogenic species of the Paracoccidioides genus

Approximately one-third of all proteins have been estimated to contain at least one metal cofactor, and these proteins are referred to as metalloproteins. These represent one of the most diverse classes of proteins, containing metal ions that bind to specific sites to perform catalytic, regulatory and structural functions. Bioinformatic tools have been developed to predict metalloproteins encoded by an organism based only on its genome sequence. Its function and the type of metal binder can also be predicted via a bioinformatics approach. Paracoccidioides complex includes termodimorphic pathogenic fungi that are found as saprobic mycelia in the environment and as yeast, the parasitic form, in host tissues. They are the etiologic agents of Paracoccidioidomycosis, a prevalent systemic mycosis in Latin America. Many metalloproteins are important for the virulence of several pathogenic microorganisms. Accordingly, the present work aimed to predict the copper, iron and zinc proteins encoded by the genomes of three phylogenetic species of Paracoccidioides (Pb01, Pb03, and Pb18). The metalloproteins were identified using bioinformatics approaches based on structure, annotation and domains. Cu-, Fe-, and Zn-binding proteins represent 7% of the total proteins encoded by Paracoccidioides spp. genomes. Zinc proteins were the most abundant metalloproteins, representing 5.7% of the fungus proteome, whereas copper and iron proteins represent 0.3 and 1.2%, respectively. Functional classification revealed that metalloproteins are related to many cellular processes. Furthermore, it was observed that many of these metalloproteins serve as virulence factors in the biology of the fungus. Thus, it is concluded that the Cu, Fe, and Zn metalloproteomes of the Paracoccidioides spp. are of the utmost importance for the biology and virulence of these particular human pathogens.

Zinc proteome interaction network as a model to identify nutrient-affected pathways in human pathologies

Zinc is an essential micronutrient playing fundamental roles in cellular metabolism. It acts mostly through binding a wide range of proteins, thus affecting a broad spectrum of biological processes, which include cell division, growth and differentiation. Full annotation of zinc-binding proteins showed them to represent about 10 % of the human proteome, with over 300 enzymes containing zinc ions within their catalytic domains. Also, hundreds of key regulatory proteins, including transcription factors, require zinc for their activity. In this study, the whole set of zinc-binding proteins together with their direct interactors was listed and defined as the zinc proteome (ZNP). We interrogated pathway analysis tools to identify the cellular processes that are predicted to be affected by zinc availability. Network and functional enrichment analyses highlighted biological processes potentially affected by deregulated zinc homeostasis. This computational approach was also tested on a real case study: The possible involvement of ZNP network proteins in Crohn's disease pathogenesis was assessed on genes transcriptionally regulated in the intestine of patients affected by this condition. The analysis produced a network of pathways likely to be influenced by zinc and associated with Crohn's disease. These results highlight a central role for zinc in the tissue remodeling process which occurs upon gut inflammation, pointing at novel disease pathways whose effect could be worsened by zinc dyshomeostasis and impaired zinc fluxes in specific damaged areas. Overall, our computational approach could provide novel insights into pathological conditions and could therefore be used to drive mechanistic research in under-investigated fields of research. An interactive version of the determined ZNP network is available at URL http://93.63.165.11/ZNnetwork/ .

In silico assessment of chemical biodegradability

Biodegradation is the principal environmental dissipation process. Due to a lack of comprehensive experimental data, high study cost and time-consuming, in silico approaches for assessing the biodegradable profiles of chemicals are encouraged and is an active current research topic. Here we developed in silico methods to estimate chemical biodegradability in the environment. At first 1440 diverse compounds tested under the Japanese Ministry of International Trade and Industry (MITI) protocol were used. Four different methods, namely support vector machine, k-nearest neighbor, naïve Bayes, and C4.5 decision tree, were used to build the combinatorial classification probability models of ready versus not ready biodegradability using physicochemical descriptors and fingerprints separately. The overall predictive accuracies of the best models were more than 80% for the external test set of 164 diverse compounds. Some privileged substructures were further identified for ready or not ready biodegradable chemicals by combining information gain and substructure fragment analysis. Moreover, 27 new predicted chemicals were selected for experimental assay through the Japanese MITI test protocols, which validated that all 27 compounds were predicted correctly. The predictive accuracies of our models outperform the commonly used software of the EPI Suite. Our study provided critical tools for early assessment of biodegradability of new organic chemicals in environmental hazard assessment.