Skip to main content
NCBI home page
eLife logoLink to eLife
. 2021 Jun 23;10:e66741. doi: 10.7554/eLife.66741

A hypothesis on the capacity of plant odorant-binding proteins to bind volatile isoprenoids based on in silico evidences

Deborah Giordano 1, Angelo Facchiano 1, Sabato D'Auria 1,2,✉, Francesco Loreto 3,4,✉
Editors: Krishna Persaud5, Meredith C Schuman6
PMCID: PMC8221805  PMID: 34161230

Abstract

Volatile organic compounds (VOCs) from ‘emitting’ plants inform the ‘receiving’ (listening) plants of impending stresses or simply of their presence. However, the receptors that allow receivers to detect the volatile cue are elusive. Most likely, plants (as animals) have odorant-binding proteins (OBPs), and in fact, a few OBPs are known to bind ‘stress-induced’ plant VOCs. We investigated whether these and other putative OBPs may bind volatile constitutive and stress-induced isoprenoids, the most emitted plant VOCs, with well-established roles in plant communication and defense. Molecular docking simulation experiments suggest that structural features of a few plant proteins screened in databases could allow VOC binding. In particular, our results show that monoterpenes may bind the same plant proteins that were described to bind other stress-induced VOCs, while the constitutive hemiterpene isoprene is unlikely to bind any investigated putative OBP and may not have an info-chemical role. We conclude that, as for animal, there may be plant OBPs that bind multiple VOCs. Plant OBPs may play an important role in allowing plants to eavesdrop messages by neighboring plants, triggering defensive responses and communication with other organisms.

Research organism: Other

Introduction

Plants synthesize a variety of volatile organic compounds (VOCs) that are important for reproduction and defense and in general to communicate with other organisms (Ninkovic et al., 2021). Insects and generalist herbivores, or carnivore insects that are also attracted by the volatile ‘cry for help’ released by plants upon herbivore attacks, are all able to sense plant volatiles (Dicke and Loreto, 2010).

Whether volatiles are also important in plant–plant communication is a more fascinating, yet controversial, issue (Vickers et al., 2009). Growing reports show that VOCs influence plant–plant relationships (Baldwin et al., 2002; Erb, 2019; Ninkovic et al., 2019). VOCs elicited in ‘emitting’ plants by abiotic or biotic stresses prime defensive responses in non-elicited ‘receiving’ plants (Zuo et al., 2019; Frank et al., 2021). However, no study has so far looked for the primary events in such elusive plant–plant interaction, i.e., the receptors by which plants may sense VOCs emitted from neighboring plants are largely unknown.

Recently, it has been proposed that the passage of VOCs across the plasma membrane relies on their active transport. In particular, the presence of an ABC carrier protein involved in active transport into plant cells has been hypothesized (Adebesin et al., 2017). Plant VOC receptors may belong to a similar category of transporters. An alternative explanation is that plants use odorant-binding proteins (OBPs) as protein carriers, alike animals. Indeed, there have been at least three cases in which the presence of OBPs was postulated in plants. These are as follows: (1) the COI1 assembly with a jasmonate zinc finger inflorescence meristem (ZIM)-domain (JAZ) protein family (COI1–JAZ), a high-affinity receptor protein for methyl-jasmonate (MeJa), and the volatile moiety of jasmonic acid (JA) (Sheard et al., 2010). After JAZ degradation, transcription factors are released, which activate downstream genes and the defensive metabolites in plants challenged by abiotic and biotic stresses (Cheong and Choi, 2003). (2) The salicylic acid (SA)-binding protein 2 (SABP2), an esterase of the a/b-fold hydrolase superfamily, that binds SA with high affinity and then converts the biologically inactive methyl ester of SA (MeSA) to active SA-inducing systemic acquired resistance in plants challenged by stresses (Park et al., 2007). (3) The TOPLESS-like protein (TPL) that specifically binds β-caryophyllene, a stress-induced sesquiterpene and a volatile signal for herbivores and carnivores in multitrophic interactions. TPL and TPL-related proteins are transcriptional co-repressors (also toward JA-mediated signaling). Interestingly, only the capacity to bind β-caryophyllene was tested with emitting and receiving (eavesdropping) plants (Nagashima et al., 2019).

These three cases need confirmation, and all other plant VOCs (at least 1700 known so far; Dicke and Loreto, 2010) wait for identification of receptors (if present). We report here an in silico study based on current knowledge of plant protein structure, especially aiming at identifying best candidates as plant OBPs for plant VOCs whose receptors are still unknown. We focused on the volatile isoprenoids (isoprene and monoterpenes) produced by the methyl erythritol phosphate (MEP) chloroplast pathway and representing the largest component of plant VOC emissions in the atmosphere (Loreto and Schnitzler, 2010).

Results and discussion

We looked at plant OBPs following a two-level structural approach (identification of candidate plant OBPs, and validation by in silico molecular simulation experiments of OBP capacity), as detailed in the Materials and methods section. For the first level, we added to the three known plant OBPs those potential OBPs resulting from plant protein sequence databases (approach a) and from comparison for sequence similarities with known animal OBPs (approach b, see Materials and methods for details).

Approach (a) yielded five complete or partial protein sequences, three from Anthurium amnicola (named OBP56d, OBP A10_1, and OBP A10_2), one from Nymphaea thermarum (named putative OBP), and one from Pyrus x bretschneideri (named OBP-70 like) (Supplementary file 1). However, when these sequences were further screened for similarities with annotated plant proteins in the sequence databases, statistically relevant similarity and coverage was only found between the putative OBP from N. thermarum and the Flowering locus T (FT) and T1 proteins, and the heading date 3A and 3B. Comparison with animal OBPs, yielded similarities between (1) OBPs from insects and plant OBP56d and OBP-70 like, (2) chemosensor proteins and plant OBP A10_1, and (3) phosphatidylethanolamine-binding proteins and the putative OBP from N. thermarum (Supplementary file 2).

Approach (b) was based on comparison between 432 OBP protein sequences from different animal sources with plant protein sequences. Only five animal protein families share sequence similarity with plant proteins, as summarized in Table 1. Sequences were considered similar when showing BLAST E-values close to 0, and sequence identity ranges (20–45%) with a confident query coverage (highest values varying from 60% to 96%).

Table 1. Similarities of animal and plant protein families with odorant receptor/transporter/channel functions.

Animal protein family Similar plant proteins Identity percentage range Sequence coverage range BLAST E-value
Bovine cyclic nucleotide gated olfactory channel of Bos Taurus Potassium voltage-gated channel 25–30% 60–75% ≤3e-27
Chloride channel Anoctamin-2 of Mus musculus anoctamin-like protein 22–27% 50–70% ≤3e-20
Human/mouse receptor expression enhancing molecules HVA22 e HVA22-like plants proteins 27–44% 40–96% ≤7e-21
BPI fold containing family B member three from Mus musculus and Rattus norvegicus putative BPI, lipid-binding protein, hypothetical protein, and unnamed protein 20–30% 25–60% ≤6e-07
putative OBP 5a from Drosophila melanogaster FT, D3-like, protein ‘Mother of FT and TFL1-like (Terminal flower 1-like)’ (MFT), ZCN9 (MFT-like), Heading Date 3A-like 28–41% 51–86% ≤5e-18
Open in a new tab

Interestingly, all plant protein sequences reported in Table 1 are related to inflorescence signaling. HVA22 is induced by abscisic acid (ABA)/stress and has a role in the gibberellic acid (GA)-induced cellular death and in the regulation of seed germination (Shen et al., 2001). FT is a florigen that induces and promotes the transition from vegetative growth to flowering (Koornneef et al., 1998). The protein MFT is involved in regulation of seeds germination by ABA/GA signaling (Vaistij et al., 2018). Heading date 3A-like, as FT, is a probable florigen, which promotes the transition from vegetative growth to flowering downstream of HD1 and EHD1 under short day conditions (Taoka et al., 2011). It is also remarkable that plant proteins previously reported in the literature (COI1–JAZ, SABP2, and TPL, see Introduction) were not retrieved by our search based on plant–animal protein similarities. This suggests that plant proteins may be able to work as OBPs even if different from animal OBPs, both at primary and tertiary structure levels.

The putative OBPs retrieved by approaches (a) and (b) were added to the three plant OBPs already described in the literature (see Introduction), and all proteins were checked for availability of experimental 3D structure data in the second step of our study. This search was successful for nine putative plant OBPs that were then selected for molecular docking simulations of the interactions between potential plant OBPs and selected VOCs, to finally identify candidate plant OBPs.

Table 2 reports the binding energy values obtained by docking simulations for each complex between potential plant OBPs and ligands (plant VOCs), together with the binding energy values obtained as a reference for experimental complexes after a redocking procedure, when available (see Materials and methods).

Table 2. Binding energy values (Kcal mol−1), obtained by docking simulations, between putative plant OBPs and isoprenoid VOCs.

OBPs α-Pinene Limonene β-Myrcene β-Caryophyllene Isoprene Linalool
TPL-like −5.06 −4.76 −3.95 −6.16 −3.39 −3.94
ABA receptor −4.69 −4.73 −3.84 −6.32 −3.35 −4.12
GA receptor −5.50 −5.44 −4.92 −6.94 −3.78 −4.69
Heading Date 3A −5.46 −4.99 −4.29 −6.83 −3.44 −4.79
FT −5.23 −5.07 −4.26 −6.65 −3.15 −4.98
TFL1 −5.30 −5.53 −4.38 −7.15 −3.70 −4.98
Partial JA receptor −5.23 −4.79 −4.16 −6.05 −2.78 −4.21
Complete JA receptor −5.92 −5.11 −4.41 −6.61 −2.82 −4.49
SABP2 −6.03 −6.12 −5.14 −6.73 −3.25 −4.70
Reference protein* −5.42 −6.29 −4.15 Not available Not available Not available
Open in a new tab

*Reference protein is the protein for which it has been found an experimental complex with the ligand. For α-pinene, limonene, and β-myrcene, the reference proteins are cytochrome P450 2B6 complexed with α-pinene (PDB code: 4I91), lipid binding protein complexed with limonene 1,2 epoxide (PDB code: 2A2G, and linalool dehydratase/isomerase complexed with β-myrcene [PDB code: 5HSS]), respectively.

The predicted binding constant (Ki) values are reported in Supplementary file 3 and should be interpreted only as indicative values. Reported Ki values are very high compared to those found for animal OBPs, but are consistent with other plant Ki studies, confirming that plants may sense VOCs only when exposed to higher concentrations than animals (Nagashima et al., 2019).

Our results indicate that the three monoterpenes tested (α-pinene, β-myrcene, and limonene) may bind some of the putative OBPs with energy values similar or lower than the values observed for the reference complexes. For example, α-pinene binds the reference protein cytochrome P450 2B6 with an energy value of −5.42 kcal/mol and a predicted Ki of 103 μM. In our docking simulations, α-pinene seems to dock better on SABP2 and on the complete JA receptor, with binding energy value of −6.03 kcal/mol and −5.92 kcal/mol, and predicted Ki of 37 μM and 38.55 μM, respectively. In both cases, this is a better interaction than with the reference complex. In the case of GA receptor and heading date 3A, α-pinene binding energy values were similar to those of the reference complex. Similar to α-pinene, β-myrcene binds SABP2, GA receptor, and the JA receptor better than the reference complex. Among the other candidate OBPs, protein heading date 3A, FT, and tfl1 showed binding energy values similar to the reference complex for β-myrcene.

The reference complex found for limonene is a modified form of the plant volatile (limonene 1,2 epoxide), which may not interact with the protein-binding site exactly as the VOC does. Therefore, its binding energy value represents a reference point less reliable than the values obtained by the other two experimental protein–ligand complexes. However, as in the previous cases, SABP2 showed energy values lower than the other candidate OBPs, and similar to the reference complex.

Results obtained for β-caryophyllene, isoprene, and linalool cannot be compared to a reference complex, as experimental complexes of these ligands with proteins are not available. In these cases, protein-binding capacity can only be derived by comparing binding values of the different VOCs, and with an even lower confidence. Remarkably, β-caryophyllene showed the lowest, and isoprene the highest, energy binding values.

Our analysis overall confirms that OBPs might be present in plants, and also bind VOCs produced by plants through the MEP pathway. MEP synthesizes isoprenoids that are emitted constitutively (e.g. isoprene) or that are both constitutive and stress induced (e.g. monoterpenes) (Dicke and Loreto, 2010). While monoterpenes are efficiently bound by OBPs, isoprene, the simplest and most abundantly emitted volatile isoprenoid, does not seem to bind strongly enough any OBP. Ecological observations report a role for monoterpenes in plant communication with other organisms (Bouwmeester et al., 2019), which is arguably not observed for isoprene (e.g. Brilli et al., 2009), However, isoprene influences many plant traits (Monson et al., 2021) and profoundly modifies properties of cellular and sub-cellular membranes (Velikova et al., 2015; Pollastri et al., 2019), which may in turn activate signals reshaping plant genomes and phenomes (Harvey and Sharkey, 2016; Miloradovic van Doorn et al., 2020). As isoprene is the main VOC emitted constitutively and not induced by stresses, it may be tempting to generalize from our observations that, unlike induced VOCs, constitutive VOCs are not bound by OBPs.

Interestingly, monoterpenes seem to bind more efficiently with OBPs that are also reported to bind other plant volatiles. In particular, SABP2, the protein that strongly binds the stress-induced volatile MeSA, also seems to be a candidate for three tested monoterpenes. Protein heading date 3A and tfl1, GA receptor, and FT may also bind, perhaps more specifically, the three monoterpenes. Our results suggest that, as reported for the OBPs from animals and insects (Ramoni et al., 2007), the candidate plant OBPs have a broad ligand binding specificity and, consequently, they are likely to bind several different VOCs. This should be tested experimentally by monitoring in vivo the docking patterns of constitutive and induced VOCs.

We noticed that in many cases binding of the ligands occurs at the same protein structure site, as shown for SABP2 in the experimentally reported complex with SA (Figure 1A), and in the simulated complexes with α-pinene, limonene, and β-myrcene (Figure 1B–D).

Figure 1. 3D models of protein-ligand interactions.

(A) Experimental structure of SABP2 protein structure with salicylic acid in the binding site (PDB structure 1Y7I). The architecture of SABP2 is schematized by the backbone structure (green), with ribbons and arrows to evidence helices and beta strands, respectively. The salicylic acid molecule (colored in red) is in space-fill representation. (B) Left: Molecular docking simulation of SABP2 protein structure with α-pinene (red molecule) in the binding site. SABP2 is shown with the same spatial orientation as in panel (A) to emphasize that α-pinene occupies the same binding site of salicylic acid. Right: Focus on the binding site of SABP2. α-Pinene (red molecule) interacts directly with amino acid residues labeled with carbon atoms in green. Amino acid residues with carbon atom in grey are also part of the binding site, although not directly in contact with α-pinene. Standard colors are used for the other amino acid atoms (red = oxygen, blue = nitrogen, yellow = sulphur, white = hydrogen). (C) Left: SABP2 protein with limonene (red molecule) in the binding site. SABP2 is shown with the same spatial orientation of (A), to better show that limonene occupies the same binding site of the salicylic acid. Right: Focus of the binding site of SABP2. Details as in panel (B). (D) Left: SABP2 protein with β-myrcene (red molecule) in the binding site. SABP2 is shown with the same spatial orientation of (A), to better show that β-myrcene occupies the same binding site of the salicylic acid. Right: Focus of the binding site of SABP2. Details as in (B).

Figure 1.

Figure 1—figure supplement 1. The environment of the binding pocket of β-caryophyllene in the complexes with best binding energy values.

Figure 1—figure supplement 1.

For each candidate OBP, the 2D image shows β-caryophyllene in the center, surrounded by the residues with which it interacts. The type of interaction is defined according to the color legend in figure. Images are obtained with DiscoveryStudio software.

Figure 1—figure supplement 2. Schematic workflow for the search of candidate odorant-binding proteins in plants.

Figure 1—figure supplement 2.

The search was performed at two levels of investigation. The first level was the identification of candidate plant OBPs, based on features and similarities of protein sequences from public data bases (boxes labeled a and b) and on literature evidences. This level identified proteins or protein families, for which amino acid sequences are available. The second level was the validation by in silico molecular simulations, to verify the potential capability of the candidate proteins to bind selected VOCs. This level can be applied only to the candidate proteins, selected from the first level, for which the three-dimensional structure is made available by experimental studies.
Open in a new tab

The SABP2 binding site (represented in the right panels of Figure 1B–D) is characterized by the presence of aromatic side chains (two phenylalanines, one tyrosine, and one tryptophan), also observed in other candidate plant OBPs (GA receptor: two phenylalanines and four tyrosines; JA receptor: one phenylalanine, one tyrosine, and one tryptophan residue; FT receptor: two phenylalanines and one tryptophan). Other candidate plant OBPs have some aromatic side chains in the binding site, although in lower number (e.g., the ABA receptor has one phenylalanine and one tyrosine, while TLF1 has two phenylalanines). This is also reminiscent of the binding site of OBPs from animal organisms (Bianchet et al., 1996). Bovine OBPs include five phenylalanines and one tyrosine; Drosophila OBPs have four phenylalanines and one tryptophan; and porcine OBPs have two phenylalanines. This conserved feature across biomes may reveal that a hydrophobic environment where odorant molecules can be accommodated is needed. Analysis of the β-caryophyllene complexes (see Figure 1—figure supplement 1) also suggests that larger ligands may interact with additional aromatic or hydrophobic side chains in the binding pockets.

Overall, our study confirms that plant OBPs may exist and that they may be structurally and functionally similar to OBPs described in animals. As in the case of animal OBPs, also plant OBPs seem to be able to bind different VOCs in the same binding site, using the same amino acid sequences. While our in silico results make the case that plants also have OBPs, with both common and different features compared to animal OBPs, functional validation should follow. For example, chemical synthesis of fluorescent VOCs could be used to confirm VOC binding by putative OBPs and to characterize protein–ligand binding mechanisms and sites. Mutants or genetically modified plants that miss or have abundant OBP candidates could also be used. Retrieval and description of plant OBPs may be an important step to unveil how plants eavesdrop messages sent by other plants and how the information is then used to activate molecular and metabolic changes leading to defensive responses and patterns.

Materials and methods

The search for potential OBP proteins in plants was performed following the two-level investigation procedure schematized in Figure 1—figure supplement 2. The first level was about searching for plant proteins with potential OBP function. The second level included searching for experimental 3D structures of the candidate plant OBPs and validating by molecular simulations potential ability of putative OBPs to bind isoprenoid VOCs.

In detail, for the first level, two steps were followed. Step (a) was a screening for proteins of interest performed on the UniProt (http://www.uniprot.org) and NCBI (http://www.ncbi.nih.nlm.gov) protein databases. Initial screening was performed by using the protein name and entry annotations, with the query ‘odorant-binding protein’. Five plant proteins were found, annotated as ‘predicted proteins’, which means that they were obtained by nucleotide sequence translation, without evidence at protein or transcript levels, and the name was assigned to the proteins by similarity to other proteins. The protein sequence selected were further investigated by BLAST searches for similar sequences, by using the BLAST interfaces at the database web sites. Standard BLAST search parameters were used. Step (b) was based on BLAST searches (using the same standard parameters of step a) for plant proteins and protein families similar to the 432 OBPs from animal sources available in the protein databases (the list of the 432 OBPs is reported as Supplementary file 4).

The second level of investigation was a molecular simulations of the interaction of the potential plant OBPs (i.e. those selected in steps 1a and 1b, and the three proteins for which OBP function has been reported [see Introduction]) with selected isoprenoid VOCs. First, we verified the availability of 3D structures of the candidate OBPs in plants. In particular, the Protein Data Bank (PDB) (http://www.rcsb.org), collecting the 3D structure of proteins, was interrogated for appropriate protein structures of the candidate plant OBPs identified by the first level search. The screening allowed us to select the following plant proteins with potential primary or secondary function as OBP, and with available 3D structures: ABA Receptor from Arabidopsis thaliana (PDB code: 4dsb); GA receptor GID1 from Oryza sativa (3ebl); Flowering locus t (FT) from A. thaliana (1wkp); Terminal flower 1 (tfl1) from A. thaliana (1wko); Protein Heading date DATE 3A from O. sativa (3axy); TPL-like protein from A. thaliana (5nqs); COI (partial JA receptor) from A. thaliana (3ogl); COI and JAZ (JA receptor complete) from A. thaliana (3ogl); and salicylic acid binding protein 2 (SA enzyme) from Nicotiana tabacum (1y7i).

Molecular structures of VOCs were extracted from the PubChem database. The VOCs selected as ligands in our study were the isoprenoids α-pinene (PubChem code: 6654), limonene (22311), β-myrcene (31253), β-caryophyllene (5281515), isoprene (6557), and linalool (6549).

Molecular simulation experiments of protein–ligand interactions were carried out with Autodock 4.2 and AutoDock Tools 1.5.6 (Morris et al., 2009), which allowed us to prepare the screening, perform the docking simulation, and analyze the results. Molecular visualization of results was obtained with PyMOL Molecular Graphics System, Version 1.3 Schrödinger, LLC.

The binding energy values obtained for the simulated protein–ligand complexes were compared to the values for complexes used as reference. We found in the PDB database complexes of animal proteins with α-pinene, limonene 1,2 epoxide, and β-myrcene. α-Pinene and β-myrcene are two of the selected VOCs for our simulation, fully correspondent to the natural molecules synthesized and emitted by plants. Limonene 1,2 epoxide is a modified form of the natural VOC. Although not identical to the corresponding plant VOC (limonene), it may be useful as additional reference value. For available plant receptors (ABA receptor, GA receptor, JA receptor, and SA binding protein 2), the reference structures are complexes with ABA, GA, JA-isoleucine, and SA, respectively. These complexes may offer additional reference values of binding energy.

To validate the docking simulation experimental protocol, we applied a redocking procedure to the reference complexes, following the procedure in use in our laboratory (Scafuri et al., 2016, Scafuri et al., 2020). We depleted the ligand from the complex ligand–protein, and then the ligand-depleted complex (the protein alone) was used to simulate the ligand docking. The redocking experiments were carried out for the protein–ligand reference structures selected above. This approach allowed us to check that the simulation procedure located correctly the ligand in the expected binding site and to calculate the reference value of the binding energy expected in the true protein–ligand complex. The redocking procedure also provided a computational estimation of the binding energy in a true case of protein–ligand interaction. This estimation is used as reference in comparison to the energy binding values computed for the putative protein–ligand interactions. For each ligand a proper reference complex is needed, being the energy of interaction dependent on the ligand chemical features. In the absence of a reference complex relative to an experimental protein–ligand interaction (e.g. the cases of β-caryophyllene, isoprene, and linalool, see Table 1), the computed binding energy values may be compared each other too, but only for a qualitative ranking, without a reference threshold given by an effective binding.

Acknowledgements

FL acknowledges contribution from the Project PRIN – COFIN 2017 (Italian Ministry of University and Research): ‘Plant multitROphic interactions for bioinspired Strategies of PEst ConTrol (PROSPECT)’. We would like to thank Prof. Paolo Pelosi for the inspiring discussions about OBPs.

Funding Statement

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Contributor Information

Sabato D'Auria, Email: sabato.dauria@cnr.it.

Francesco Loreto, Email: francesco.loreto@unina.it.

Krishna Persaud, The University of Manchester, United Kingdom.

Meredith C Schuman, University of Zurich, Switzerland.

Funding Information

This paper was supported by the following grant:

  • Ministero dell’Istruzione, dell’Università e della Ricerca PRIN - COFIN 2017 to Francesco Loreto.

Additional information

Competing interests

No competing interests declared.

Author contributions

Formal analysis, Validation, Investigation, Visualization, Methodology.

Formal analysis, Validation, Investigation, Methodology.

Conceptualization, Supervision, Writing - original draft, Writing - review and editing.

Conceptualization, Supervision, Funding acquisition, Writing - original draft, Writing - review and editing.

Additional files

Source data 1. Database accession numbers.

Related to Table 1, Figure 1 and Figure 1—figure supplement 1.

elife-66741-data1.xlsx (21.9KB, xlsx)
Source data 2. Docking results.

Related to Figure 1 and Table 2.

elife-66741-data2.xlsx (16KB, xlsx)
Source data 3. PDB structures of SABP2 complexes.

Related to Figure 1.

elife-66741-data3.zip (228.4KB, zip)
Source data 4. PDB structures of protein - beta caryophyllene complexes.

Related to Figure 1—figure supplement 1.

elife-66741-data4.zip (621.1KB, zip)
Supplementary file 1. Plant proteins from sequence databases annotated as ‘odorant-binding protein’.
elife-66741-supp1.docx (12.9KB, docx)
Supplementary file 2. BLAST results for non-plant proteins with similarity to ‘general odorant-binding protein 56d’ from Anthurium amnicola.

Only the best ten results are shown.

elife-66741-supp2.docx (13.8KB, docx)
Supplementary file 3. Complete results of docking simulation experiments.

Docking simulations by AutoDock suite generated results summarized in the table. For each receptor-ligand simulation, the best 100 conformations are clusterized by AutoDock on the basis of ligand position, and three values are reported for each cluster: the mean binding energy for the clusterized conformations, the best binding energy, the number of conformations in the cluster. An additional parameter computed by AutoDock is the predicted Ki value. We reported the results for the best cluster in terms of energy and population, or in some cases, alternative clusters, with reference to different pockets on the receptor surface.

elife-66741-supp3.docx (22.7KB, docx)
Supplementary file 4. List of 432 protein sequences selected as OBP from animal sources, used for searching public database for similar plant proteins.
elife-66741-supp4.docx (22.9KB, docx)
Transparent reporting form

Data availability

All data generated during this study were obtained by analysing entries retrieved from public databases, according to procedures described in the manuscript. Source data and supporting files report complete list of accession numbers of entries and the models of 3D structures obtained by our study and used for generating figures.

References

  1. Adebesin F, Widhalm JR, Boachon B, Lefèvre F, Pierman B, Lynch JH, Alam I, Junqueira B, Benke R, Ray S, Porter JA, Yanagisawa M, Wetzstein HY, Morgan JA, Boutry M, Schuurink RC, Dudareva N. Emission of volatile organic compounds from Petunia flowers is facilitated by an ABC transporter. Science. 2017;356:1386–1388. doi: 10.1126/science.aan0826. [DOI] [PubMed] [Google Scholar]
  2. Baldwin IT, Kessler A, Halitschke R. Volatile signaling in plant-plant-herbivore interactions: what is real? Current Opinion in Plant Biology. 2002;5:351–354. doi: 10.1016/S1369-5266(02)00263-7. [DOI] [PubMed] [Google Scholar]
  3. Bianchet MA, Bains G, Pelosi P, Pevsner J, Snyder SH, Monaco HL, Amzel LM. The three-dimensional structure of bovine odorant binding protein and its mechanism of odor recognition. Nature Structural Biology. 1996;3:934–939. doi: 10.1038/nsb1196-934. [DOI] [PubMed] [Google Scholar]
  4. Bouwmeester H, Schuurink RC, Bleeker PM, Schiestl F. The role of volatiles in plant communication. The Plant Journal. 2019;100:892–907. doi: 10.1111/tpj.14496. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Brilli F, Ciccioli P, Frattoni M, Prestininzi M, Spanedda AF, Loreto F. Constitutive and herbivore-induced monoterpenes emitted by Populus x euroamericana leaves are key volatiles that orient Chrysomela populi beetles. Plant, Cell and Environment. 2009;32:542–552. doi: 10.1111/j.1365-3040.2009.01948.x. [DOI] [PubMed] [Google Scholar]
  6. Cheong JJ, Choi YD. Methyl jasmonate as a vital substance in plants. Trends in Genetics. 2003;19:409–413. doi: 10.1016/S0168-9525(03)00138-0. [DOI] [PubMed] [Google Scholar]
  7. Dicke M, Loreto F. Induced plant volatiles: from genes to climate change. Trends in Plant Science. 2010;15:115–117. doi: 10.1016/j.tplants.2010.01.007. [DOI] [PubMed] [Google Scholar]
  8. Erb M. Plant biology: evolution of Volatile-Mediated Plant-Plant interactions. Current Biology. 2019;29:R873–R875. doi: 10.1016/j.cub.2019.07.066. [DOI] [PubMed] [Google Scholar]
  9. Frank L, Wenig M, Ghirardo A, van der Krol A, Vlot AC, Schnitzler JP, Rosenkranz M. Isoprene and β-caryophyllene confer plant resistance via different plant internal signalling pathways. Plant, Cell & Environment. 2021;44:1151–1164. doi: 10.1111/pce.14010. [DOI] [PubMed] [Google Scholar]
  10. Harvey CM, Sharkey TD. Exogenous isoprene modulates gene expression in unstressed Arabidopsis thaliana plants. Plant, Cell & Environment. 2016;39:1251–1263. doi: 10.1111/pce.12660. [DOI] [PubMed] [Google Scholar]
  11. Koornneef M, Alonso-Blanco C, Blankestijn-de Vries H, Hanhart CJ, Peeters AJ. Genetic interactions among late-flowering mutants of Arabidopsis. Genetics. 1998;148:885–892. doi: 10.1093/genetics/148.2.885. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Loreto F, Schnitzler JP. Abiotic stresses and induced BVOCs. Trends in Plant Science. 2010;15:154–166. doi: 10.1016/j.tplants.2009.12.006. [DOI] [PubMed] [Google Scholar]
  13. Miloradovic van Doorn M, Merl-Pham J, Ghirardo A, Fink S, Polle A, Schnitzler JP, Rosenkranz M. Root isoprene formation alters lateral root development. Plant, Cell & Environment. 2020;43:2207–2223. doi: 10.1111/pce.13814. [DOI] [PubMed] [Google Scholar]
  14. Monson RK, Weraduwage SM, Rosenkranz M, Schnitzler JP, Sharkey TD. Leaf isoprene emission as a trait that mediates the growth-defense tradeoff in the face of climate stress. Oecologia. 2021;1:04813-7. doi: 10.1007/s00442-020-04813-7. [DOI] [PubMed] [Google Scholar]
  15. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. Journal of Computational Chemistry. 2009;30:2785–2791. doi: 10.1002/jcc.21256. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Nagashima A, Higaki T, Koeduka T, Ishigami K, Hosokawa S, Watanabe H, Matsui K, Hasezawa S, Touhara K. Transcriptional regulators involved in responses to volatile organic compounds in plants. Journal of Biological Chemistry. 2019;294:2256–2266. doi: 10.1074/jbc.RA118.005843. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Ninkovic V, Rensing M, Dahlin I, Markovic D. Who is my neighbor? volatile cues in plant interactions. Plant Signaling & Behavior. 2019;14:1634993. doi: 10.1080/15592324.2019.1634993. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Ninkovic V, Markovic D, Rensing M. Plant volatiles as cues and signals in plant communication. Plant, Cell & Environment. 2021;44:1030–1043. doi: 10.1111/pce.13910. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Park SW, Kaimoyo E, Kumar D, Mosher S, Klessig DF. Methyl salicylate is a critical mobile signal for plant systemic acquired resistance. Science. 2007;318:113–116. doi: 10.1126/science.1147113. [DOI] [PubMed] [Google Scholar]
  20. Pollastri S, Jorba I, Hawkins TJ, Llusià J, Michelozzi M, Navajas D, Peñuelas J, Hussey PJ, Knight MR, Loreto F. Leaves of isoprene‐emitting tobacco plants maintain PSII stability at high temperatures. New Phytologist. 2019;223:1307–1318. doi: 10.1111/nph.15847. [DOI] [PubMed] [Google Scholar]
  21. Ramoni R, Bellucci S, Grycznyski I, Grycznyski Z, Grolli S, Staiano M, De Bellis G, Micciulla F, Pastore R, Tiberia A, Conti V, Merli E, Varriale A, Rossi M, D’Auria S. The protein scaffold of the lipocalin odorant-binding protein is suitable for the design of new biosensors for the detection of explosive components. Journal of Physics: Condensed Matter. 2007;19:395012–395019. doi: 10.1088/0953-8984/19/39/395012. [DOI] [Google Scholar]
  22. Scafuri B, Marabotti A, Carbone V, Minasi P, Dotolo S, Facchiano A. A theoretical study on predicted protein targets of apple polyphenols and possible mechanisms of chemoprevention in colorectal Cancer. Scientific Reports. 2016;6:32516. doi: 10.1038/srep32516. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Scafuri B, Bontempo P, Altucci L, De Masi L, Facchiano A. Molecular docking simulations on histone deacetylases (HDAC)-1 and -2 to investigate the flavone binding. Biomedicines. 2020;8:568. doi: 10.3390/biomedicines8120568. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Sheard LB, Tan X, Mao H, Withers J, Ben-Nissan G, Hinds TR, Kobayashi Y, Hsu FF, Sharon M, Browse J, He SY, Rizo J, Howe GA, Zheng N. Jasmonate perception by inositol-phosphate-potentiated COI1-JAZ co-receptor. Nature. 2010;468:400–405. doi: 10.1038/nature09430. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Shen Q, Chen CN, Brands A, Pan SM, Ho TH. The stress- and abscisic acid-induced barley gene HVA22: developmental regulation and homologues in diverse organisms. Plant Molecular Biology. 2001;45:327–340. doi: 10.1023/a:1006460231978. [DOI] [PubMed] [Google Scholar]
  26. Taoka K, Ohki I, Tsuji H, Furuita K, Hayashi K, Yanase T, Yamaguchi M, Nakashima C, Purwestri YA, Tamaki S, Ogaki Y, Shimada C, Nakagawa A, Kojima C, Shimamoto K. 14-3-3 proteins act as intracellular receptors for rice Hd3a florigen. Nature. 2011;476:332–335. doi: 10.1038/nature10272. [DOI] [PubMed] [Google Scholar]
  27. Vaistij FE, Barros-Galvão T, Cole AF, Gilday AD, He Z, Li Y, Harvey D, Larson TR, Graham IA. MOTHER-OF-FT-AND-TFL1 represses seed germination under far-red light by modulating phytohormone responses in Arabidopsis thaliana. PNAS. 2018;115:8442–8447. doi: 10.1073/pnas.1806460115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Velikova V, Müller C, Ghirardo A, Rock TM, Aichler M, Walch A, Schmitt-Kopplin P, Schnitzler JP. Knocking down of isoprene emission modifies the lipid matrix of thylakoid membranes and influences the chloroplast ultrastructure in poplar. Plant Physiology. 2015;168:859–870. doi: 10.1104/pp.15.00612. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Vickers CE, Gershenzon J, Lerdau MT, Loreto F. A unified mechanism of action for volatile isoprenoids in plant abiotic stress. Nature Chemical Biology. 2009;5:283–291. doi: 10.1038/nchembio.158. [DOI] [PubMed] [Google Scholar]
  30. Zuo Z, Weraduwage SM, Lantz AT, Sanchez LM, Weise SE, Wang J, Childs KL, Sharkey TD. Isoprene acts as a signaling molecule in gene networks important for stress responses and plant growth. Plant Physiology. 2019;180:124–152. doi: 10.1104/pp.18.01391. [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision letter

Editor: Krishna Persaud1

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

The article framed as a hypothesis is much clearer than the previous version. The concept of plant OBPs and the potential role in chemical signalling in plants may stimulate further research in this area. The molecular modelling gives intriguing hints that will need to be verified experimentally.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "On the capacity of putative plant odorant-binding proteins to bind volatile plant isoprenoids" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor. The reviewers have opted to remain anonymous.

We are sorry to say that, after consultation with the reviewers, we have decided that your work will not be considered further for publication by eLife. We do think that the topic is exciting and timely. We agree that the proposed ideas are plausible and that the in silico analysis is a helpful step towards investigating these ideas. However, we have come to the conclusion that the in silico analysis is not, by itself, sufficient for a short report in eLife, because it leaves too many open questions to either cleanly reject, or substantially develop the authors' hypotheses. The hypotheses themselves are well chosen but not highly novel, and so such a "hypothesis curation" function would be especially important to make the paper of great value for the community.

Summary:

The chemical sensing mechanisms of plants, which are largely unknown, are a topic of broad interest. The authors hypothesise that plant chemical receptors may be transporter proteins or odorant binding proteins analogous to those found in animals. The authors have identified a list of plant proteins with possible odorant binding activity and they predict binding constants for relevant odorants. The calculated binding constants are generally very weak in comparison to known animal odorant binding proteins (i.e., would require much higher concentrations of odor for detection). The in silico investigation, while inspiring, leaves many open questions, for example whether or not there is evidence for functional analogy between plant and animal odorant binding proteins.

Reviewer #1:

The chemical sensing mechanisms of plants are largely unknown. The authors hypothesise that plant chemical receptors may be transporter proteins or odorant binding proteins. The authors carried out an "in silico" analysis to investigate whether there are analogous proteins in plants to odorant binding proteins found in animals and insects. A search through protein databases found 5 possible sequences or partial sequences and these were used for further screening using BLAST software for screening comparison. The search for OBPs in plants based on literature evidence and sequence similarities to known OBPs from animal organisms or database annotations, produced a list of plant proteins, or protein families, with potential OBP activity. Molecular docking simulation experiments, to identify candidate plant OBPs were carried out identifying the ligand binding sites and calculated binding energies together with binding constants. This data mining activity has produced some interesting data but also raises several questions. The majority of binding constants tabulated were in the hundreds of micromolar to millimolar concentrations which raises the question of what concentrations of volatile chemicals are plants able to detect. Most odorant binding proteins found in insects and animals have binding constants in the low micromolar range for the target analytes. So if these putative plant odorant binding proteins do have a role in chemical sensing further practical experiments are needed and these need to be discussed. The data are not enough to indicate that these putative proteins identified have relevant functions in chemical sensing in plants.

The manuscript is quite interesting but lacks detail and adequate discussion of the results.

1. Binding pocket characterisation, shape, size – dimensions of pockets and mouth, which amino acids are likely to interact with the ligand, would give some idea as to how the ligands selected fit into the pockets found.

2. Predicted binding constants indicate in general sensitivity in the high micromolar to mm ranges of ligands. This has implications for how a plant is able to respond to low concentrations of volatiles that are emitted from other plants – some discussion is needed.

3. β-caryophyllene may have better affinity of binding than other compounds – it may be interesting to examine more carefully the fit of this molecule in the binding pockets and which amino acids are involved.

3. The data presented do not give evidence for the presence of plant OBPs as claimed, as the proteins involved may be involved in other plant signalling functions. In presenting the data it would not be wise to make over ambitious claims as experimental data to validate the potential OBPs is missing.

4. The Discussion should have a section on what experiments are needed to test and validate the data presented.

5. There are a few typographical and grammatical errors that should be corrected. eg β-caryophillene should be β-caryophyllene, salicylic acid sometimes is spelt incorrectly etc.

Reviewer #2:

The Authors started from the consideration that volatiles emitted by plants may serve as communication media to other plants. Hence, the 'receiver' plant needs a way to bind these molecules and initiate the transduction cascade, that is a dedicated protein that is able to bind volatiles because it has a binding groove able to accommodate the ligand. The Authors searched the available databases for putative proteins that can serve this goal, by similarity to already known proteins from plants and animals. Then, by molecular docking known plant volatiles, the Authors demonstrate that the identified proteins have the predicted structural features that allow ligand binding.

The main strength of the paper resides in the idea and in the wide search for similarities among proteins pertaining to different kingdoms. The main weakness of this work resides in the fact that it is entirely in silico, without providing any actual data from real proteins. However, it is well known that in silico simulations may be only suggestive of the actual behavior of a protein.

The Authors reached their goal of identifying various proteins with putative binding abilities, however the lack of any experimental data should be made clear since the beginning of the manuscript, in the title and abstract. With this caveat, the information provided in this paper may be a useful starting point for experimentally testing of the hypotheses.

In addition to the above mentioned comments, I underline that in some instances the terminology used by the Authors should be more accurate and revised according to the following suggestions:

– Title: made clear that this paper contains only in silico simulations.

– Line 28: 'talk' refers to a specific form of communication involving voice. Substitute with 'communicate' or a synonym.

– Line 1: 'perceive' means being conscious of the presence of a sensory stimulus. Unse instead 'sense', 'detect' or a synonym.

– Line 33: add 'plant' between 'whether' and 'OBP'.

– Line 57: use 'detect' instead of 'perceive'.

– Line 87: what is 'capacity'?

– Table 1: I am not aware of any 'Bovine Cycline Nucleotide Gating Olfactory channel'. Maybe the authors refer to: 'Bovine Cyclic Nucleotide Gated Olfactory channel'?

– Table: what is the 'similarity ' reported here? Please add the level (percentage?) of similarity or identity of the proteins.

– Supplementary table S3: in the 'predicted Ki' column, the numbers are separated by a comma. Should it be full stops instead?

An additional more general comment refers to the lack of information on Odorant binding proteins. In particular, since they refer similarity to animal OBP, the authors should made clear that animal OBP are very different and pertain to different classes with dissimilar sequence and 3D structure. A couple of sentences and reference to a review on this topic may help in setting the stage.

Reviewer #3:

It is known that stress-induced plant volatiles can be perceived by neighboring plants, but the underlying mechanism is largely unknown. The authors of this manuscript attempted to identify receptors that interact with isoprenoids, the most abundant plant stress-induced volatile organic compounds (VOCs). They established a framework that allowed them to screen for plant odorant-binding proteins (OBPs) through all available databases. Comparing plant protein sequences with a large group of animal OBP sequences and expanding the investigation to previously known OBPs turned out to be fruitful. Molecular simulation is a powerful screening technique to study the interaction of the potential plant OBPs with selected isoprenoids. The finding that plant OBPs may bind different VOCs in the same binding site is interesting.

The in silico selection of the plant OBP candidates and ligand docking experiments provide a useful tool to understand signals that underpin plant-plant interactions as well as how plants respond to those cues. However, the conclusions made by the authors may be too premature:

Isoprenoids are both constitutive and stress-induced. The authors did not address, through such a docking study, how plants distinguish VOCs associated with impending stresses, particularly when the OBPs could generally interact with multiple VOCs. One may also wonder how many other types of VOCs exist that are stress-responsive, and what their receptors are.

The BLAST of 432 OBPs did not find the JA receptor, suggesting that the JA receptor sequence is not closely related to that of the OBPs that insects use to recognize plant volatiles in order to locate suitable host plants. Therefore, identification of OBPs based on sequence similarity may miss those plant proteins that possess OBP structure and function but differ in primary sequences with existing OBPs.

Docking studies can serve as a lead for potential OBP-VOC interaction, but in silico data alone is insufficient to conclude the role of the putative OBPs. Functional evidence is necessary to demonstrate their interaction with VOCs because such interaction indeed affects plant response.

Table 2 revealed the binding energy values between the putative plant OBPs and isoprenoid VOCs. Since OBPs were not selected based on specificity for isoprenoid VOCs, will it be worthwhile testing other VOC classes?

Functional validation following the lead from the in silico study should be included, e.g. via mutant or overexpression studies.

eLife. 2021 Jun 23;10:e66741. doi: 10.7554/eLife.66741.sa2

Author response

[Editors’ note: The authors appealed the original decision. What follows is the authors’ response to the first round of review.]

In this version we have taken into consideration constructive comments and criticisms of editors and reviewers. In details:

The editors asked us that, as our in silico study can suggest but cannot test that OBPs are present in plants and bind VOCs, we frame a “hypothesis paper”, moderating our claims, cautioning the readers about limitations of our approach and recommending future investigations to demonstrate our hypothesis.

We thank the editors for their very wise suggestions. We have amended the revised text accordingly. Starting with the title and throughout the paper, we have stated now that our study only offers a novel hypothesis. Moreover, we have highlighted research that must be accomplished to test whether our hypothesis holds true in nature (e.g. line 179 and 219, also responding to similar suggestions by Ref. 2 and 3). We have also added a further in silico test, supporting our argument that binding pockets of hydrophobic protein side chains may accommodate even larger ligands, e.g. volatile sesquiterpenes (Figure 1—figure supplement 1).

The editors asked us to keep the “short report format” for the paper. To meet this request, we have largely reshaped the paper, moving technical information to the methods section or to supplementary materials. Table 1 was enriched with details requested by the reviewers (see below) and Figure 1 was redrafted showing important and conserved details of molecular docking simulations between VOCs and the SABP2 putative OBP.

The editors asked us to consider those useful comments of the reviewers, other than missing experimental data. We have carefully followed this recommendation. In particular:

Ref. 2 wrote that “the lack of any experimental data should be made clear since the beginning of the manuscript, in the title and abstract”.

As mentioned above, we have reshaped the text in a more conservative way, starting from title, which now opens with the word “hypothesis” and abstract, where a sentence was added to clearly state that our work is based on molecular docking tests and that OBPs identified are only putative until experimentally tested.

Ref.3 commented: “The BLAST of 432 OBPs did not find the JA receptor, suggesting that the JA receptor sequence is not closely related to that of the OBPs that insects use to recognize plant volatiles in order to locate suitable host plants. Therefore, identification of OBPs based on sequence similarity may miss those plant proteins that possess OBP structure and function but differ in primary sequences with existing OBPs.”

We thank the reviewer for this insightful observation. What the reviewer says is also true for other putative plant OBPs and we added sentences to suggest that plant proteins may be able to work as OBPs even if different from animal OBPs, both at primary and tertiary structure level (line 117).

Ref. 2 commented about Table 1: “what is the 'similarity ' reported here? Please add the level (percentage?) of similarity or identity of the proteins”.

To answer to this valuable request, three columns were added to Table 1, showing the identity coverage range, the sequence coverage range and the BLAST E-value. In the text (line 104), it is also stated how sequence similarity was assessed based on these indicators.

Ref. 1 felt that: “Binding pocket characterisation, shape, size – dimensions of pockets and mouth, which amino acids are likely to interact with the ligand, would give some idea as to how the ligands selected fit into the pockets found”.

Ref. 1 also noted that “β-caryophyllene may have better affinity of binding than other compounds – it may be interesting to examine more carefully the fit of this molecule in the binding pockets and which amino acids are involved.”

These are difficult requests, as volume and size of the pockets may vary considerably depending on the used software. However, prompted by the reviewer’s observations, we have expanded the part dealing with binding site characterization. We already described in our manuscript the presence of aromatic side chains in the binding pockets, and now we added a specific focus on the sesquiterpene β-caryophyllene (Figure 1—figure supplement 1 and line 194) to show that even large ligands may theoretically bind aromatic or hydrophobic side chains in the binding pockets of putative OBPs.

Ref.1 wrote that: “The majority of binding constants tabulated were in the hundreds of micromolar to millimolar concentrations which raises the question of what concentrations of volatile chemicals are plants able to detect. Most odorant binding proteins found in insects and animals have binding constants in the low micromolar range for the target analytes. So if these putative plant odorant binding proteins do have a role in chemical sensing further practical experiments are needed and these need to be discussed.”

Note also ref. 2 suggestion: “An additional more general comment refers to the lack of information on Odorant binding proteins. In particular, since they refer similarity to animal OBP, the authors should made clear that animal OBP are very different and pertain to different classes with dissimilar sequence and 3D structure. A couple of sentences and reference to a review on this topic may help in setting the stage.”

We thank the reviewers for asking us to focus on possible differences between plant and animal OBPs. We make clear now that binding constant should be treated very cautiously (and this is why they are presented as Supplementary Material). But we also acknowledge that our Ki values are higher than in animal OBPs. Yet, our values are similar to those reported in the few other studies about plant OBPs. This raises the interesting question whether plants sense VOCs only when exposed to higher concentrations than animals. We discuss this in the revised text (line 135).

Ref. 3 asked: “Table 2 revealed the binding energy values between the putative plant OBPs and isoprenoid VOCs. Since OBPs were not selected based on specificity for isoprenoid VOCs, will it be worthwhile testing other VOC classes?”

This is a valid comment, and we could clearly try. However, we need to have the crystallographic structures of a protein complexed with the selected VOC, to be able to calculate reference binding energy values by redocking experiments. Moreover, we wanted to keep the paper focused on volatile isoprenoids for their very large biological and environmental interest and for being molecules largely emitted by plants both constitutively and in an induced manner. Enlarging the investigation to more VOCs will surely be a future endeavor.

Ref. 3 noted that “Isoprenoids are both constitutive and stress-induced. The authors did not address, through such a docking study, how plants distinguish VOCs associated with impending stresses, particularly when the OBPs could generally interact with multiple VOCs. One may also wonder how many other types of VOCs exist that are stress-responsive, and what their receptors are.”

We actually think that this is a main finding of the paper. Among the studied VOCs, isoprene is constitutive, and the other isoprenoids are mainly induced. We argue that isoprene and perhaps other constitutive VOCs that are emitted life-long by plants do not have sufficient binding properties, contrary to induced VOCs. This was clearly stated in the previous version (e.g. Abstract, line 37). However, to strengthen further this important idea behind our results, we entered a new sentence in the discussion (line 170).

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Source data 1. Database accession numbers.

    Related to Table 1, Figure 1 and Figure 1—figure supplement 1.

    elife-66741-data1.xlsx (21.9KB, xlsx)
    Source data 2. Docking results.

    Related to Figure 1 and Table 2.

    elife-66741-data2.xlsx (16KB, xlsx)
    Source data 3. PDB structures of SABP2 complexes.

    Related to Figure 1.

    elife-66741-data3.zip (228.4KB, zip)
    Source data 4. PDB structures of protein - beta caryophyllene complexes.

    Related to Figure 1—figure supplement 1.

    elife-66741-data4.zip (621.1KB, zip)
    Supplementary file 1. Plant proteins from sequence databases annotated as ‘odorant-binding protein’.
    elife-66741-supp1.docx (12.9KB, docx)
    Supplementary file 2. BLAST results for non-plant proteins with similarity to ‘general odorant-binding protein 56d’ from Anthurium amnicola.

    Only the best ten results are shown.

    elife-66741-supp2.docx (13.8KB, docx)
    Supplementary file 3. Complete results of docking simulation experiments.

    Docking simulations by AutoDock suite generated results summarized in the table. For each receptor-ligand simulation, the best 100 conformations are clusterized by AutoDock on the basis of ligand position, and three values are reported for each cluster: the mean binding energy for the clusterized conformations, the best binding energy, the number of conformations in the cluster. An additional parameter computed by AutoDock is the predicted Ki value. We reported the results for the best cluster in terms of energy and population, or in some cases, alternative clusters, with reference to different pockets on the receptor surface.

    elife-66741-supp3.docx (22.7KB, docx)
    Supplementary file 4. List of 432 protein sequences selected as OBP from animal sources, used for searching public database for similar plant proteins.
    elife-66741-supp4.docx (22.9KB, docx)
    Transparent reporting form
    elife-66741-transrepform.docx (245.1KB, docx)

    Data Availability Statement

    All data generated during this study were obtained by analysing entries retrieved from public databases, according to procedures described in the manuscript. Source data and supporting files report complete list of accession numbers of entries and the models of 3D structures obtained by our study and used for generating figures.

    Articles from eLife are provided here courtesy of eLife Sciences Publications, Ltd

    RESOURCES