Role of substrate recognition in modulating strigolactone receptor selectivity in witchweed

Characterization of binding kinetics and intracellular signaling of new psychoactive substances targeting cannabinoid receptor using transition-based reweighting method

New psychoactive substances (NPS) targeting cannabinoid receptor 1 pose a significant threat to society as recreational abusive drugs that have pronounced physiological side effects. These greater adverse effects compared to classical cannabinoids have been linked to the higher downstream β-arrestin signaling. Thus, understanding the mechanism of differential signaling will reveal important structure-activity relationship essential for identifying and potentially regulating NPS molecules. In this study, we simulate the slow (un)binding process of NPS MDMB-Fubinaca and classical cannabinoid HU-210 from CB1 using multi-ensemble simulation to decipher the effects of ligand binding dynamics on downstream signaling. The transition-based reweighing method is used for the estimation of transition rates and underlying thermodynamics of (un)binding processes of ligands with nanomolar affinities. Our analyses reveal major interaction differences with transmembrane TM7 between NPS and classical cannabinoids. A variational autoencoder-based approach, neural relational inference (NRI), is applied to assess the allosteric effects on intracellular regions attributable to variations in binding pocket interactions. NRI analysis indicate a heightened level of allosteric control of NPxxY motif for NPS-bound receptors, which contributes to the higher probability of formation of a crucial triad interaction (Y7.53-Y5.58-T3.46) necessary for stronger β-arrestin signaling. Hence, in this work, MD simulation, data-driven statistical methods, and deep learning point out the structural basis for the heightened physiological side effects associated with NPS, contributing to efforts aimed at mitigating their public health impact.

Functional regulation of aquaporin dynamics by lipid bilayer composition

With the diversity of lipid-protein interactions, any observed membrane protein dynamics or functions directly depend on the lipid bilayer selection. However, the implications of lipid bilayer choice are seldom considered unless characteristic lipid-protein interactions have been previously reported. Using molecular dynamics simulation, we characterize the effects of membrane embedding on plant aquaporin SoPIP2;1, which has no reported high-affinity lipid interactions. The regulatory impacts of a realistic lipid bilayer, and nine different homogeneous bilayers, on varying SoPIP2;1 dynamics are examined. We demonstrate that SoPIP2;1's structure, thermodynamics, kinetics, and water transport are altered as a function of each membrane construct's ensemble properties. Notably, the realistic bilayer provides stabilization of non-functional SoPIP2;1 metastable states. Hydrophobic mismatch and lipid order parameter calculations further explain how lipid ensemble properties manipulate SoPIP2;1 behavior. Our results illustrate the importance of careful bilayer selection when studying membrane proteins. To this end, we advise cautionary measures when performing membrane protein molecular dynamics simulations.

Contribution of Signaling Partner Association to Strigolactone Receptor Selectivity

The parasitic plant witchweed, Striga hermonthica, results in agricultural losses of billions of dollars per year. It perceives its host via plant hormones called strigolactones, which act as germination stimulants for witchweed. Strigolactone signaling involves substrate binding to the strigolactone receptor, followed by substrate hydrolysis and a conformational change from an inactive, or open state, to an active, or closed state. In the active state, the receptor associates with a signaling partner, MAX2. Recently, it was shown that this MAX2 association process acts as a strong contributor to the uniquely high signaling activity observed in ShHTL7; however, it is unknown why ShHTL7 has enhanced MAX2 association affinity. Using an umbrella sampling molecular dynamics approach, we characterized the association processes of AtD14, ShHTL7, a mutant of ShHTL7, and ShHTL6 with MAX2 homologue OsD3. From these results, we show that ShHTL7 has an enhanced standard binding free energy of OsD3 compared to those of the other receptors. Additionally, our results suggest that the overall topology of the T2/T3 helix region is likely an important modulator of MAX2 binding. Thus, differences in MAX2 association, modulated by differences in the T2/T3 helix region, are a contributor to differences in signaling activity between different strigolactone receptors.

Adaptive Sampling Methods for Molecular Dynamics in the Era of Machine Learning

Molecular dynamics (MD) simulations are fundamental computational tools for the study of proteins and their free energy landscapes. However, sampling protein conformational changes through MD simulations is challenging due to the relatively long time scales of these processes. Many enhanced sampling approaches have emerged to tackle this problem, including biased sampling and path-sampling methods. In this Perspective, we focus on adaptive sampling algorithms. These techniques differ from other approaches because the thermodynamic ensemble is preserved and the sampling is enhanced solely by restarting MD trajectories at particularly chosen seeds rather than introducing biasing forces. We begin our treatment with an overview of theoretically transparent methods, where we discuss principles and guidelines for adaptive sampling. Then, we present a brief summary of select methods that have been applied to realistic systems in the past. Finally, we discuss recent advances in adaptive sampling methodology powered by deep learning techniques, as well as their shortcomings.

Resolving binding pathways and solvation thermodynamics of plant hormone receptors

Plant hormones are small molecules that regulate plant growth, development, and responses to biotic and abiotic stresses. They are specifically recognized by the binding site of their receptors. In this work, we resolved the binding pathways for eight classes of phytohormones (auxin, jasmonate, gibberellin, strigolactone, brassinosteroid, cytokinin, salicylic acid, and abscisic acid) to their canonical receptors using extensive molecular dynamics simulations. Furthermore, we investigated the role of water displacement and reorganization at the binding site of the plant receptors through inhomogeneous solvation theory. Our findings predict that displacement of water molecules by phytohormones contributes to free energy of binding via entropy gain and is associated with significant free energy barriers for most systems analyzed. Also, our results indicate that displacement of unfavorable water molecules in the binding site can be exploited in rational agrochemical design. Overall, this study uncovers the mechanism of ligand binding and the role of water molecules in plant hormone perception, which creates new avenues for agrochemical design to target plant growth and development.

Role of Strigolactones in the Host Specificity of Broomrapes and Witchweeds

Root parasitic plants of the Orobanchaceae, broomrapes and witchweeds, pose a severe problem to agriculture in Europe, Asia and especially Africa. These parasites are totally dependent on their host for survival, and therefore, their germination is tightly regulated by host presence. Indeed, their seeds remain dormant in the soil until a host root is detected through compounds called germination stimulants. Strigolactones (SLs) are the most important class of germination stimulants. They play an important role in planta as a phytohormone and, upon exudation from the root, function in the recruitment of symbiotic arbuscular mycorrhizal fungi. Plants exude mixtures of various different SLs, possibly to evade detection by these parasites and still recruit symbionts. Vice versa, parasitic plants must only respond to the SL composition that is exuded by their host, or else risk germination in the presence of non-hosts. Therefore, parasitic plants have evolved an entire clade of SL receptors, called HTL/KAI2s, to perceive the SL cues. It has been demonstrated that these receptors each have a distinct sensitivity and specificity to the different known SLs, which possibly allows them to recognize the SL-blend characteristic of their host. In this review, we will discuss the molecular basis of SL sensitivity and specificity in these parasitic plants through HTL/KAI2s and review the evidence that these receptors contribute to host specificity of parasitic plants.

Functional Regulation of Aquaporin Dynamics by Lipid Bilayer Composition

With the diversity of lipid-protein interactions, any observed membrane protein dynamics or functions directly depend on the lipid bilayer selection. However, the implications of lipid bilayer choice are seldom considered unless characteristic lipid-protein interactions have been previously reported. Using molecular dynamics simulation, we characterize the effects of membrane embedding on plant aquaporin SoPIP2;1, which has no reported high-affinity lipid interactions. The regulatory impacts of a realistic lipid bilayer, and nine different homogeneous bilayers, on varying SoPIP2;1 dynamics were examined. We demonstrate that SoPIP2;1s structure, thermodynamics, kinetics, and water transport are altered as a function of each membrane construct's ensemble properties. Notably, the realistic bilayer provides stabilization of non-functional SoPIP2;1 metastable states. Hydrophobic mismatch and lipid order parameter calculations further explain how lipid ensemble properties manipulate SoPIP2;1 behavior. Our results illustrate the importance of careful bilayer selection when studying membrane proteins. To this end, we advise cautionary measures when performing membrane protein molecular dynamics simulations.

Effect of histidine covalent modification on strigolactone receptor activation and selectivity

The parasitic weed Striga has led to billions of dollars' worth of agricultural productivity loss worldwide. Striga detects host plants using compounds of the strigolactone class of phytohormones. Early steps in the strigolactone signaling pathway involve substrate binding and hydrolysis followed by a conformational change to an "active" or "closed" state, after which it associates with a MAX2-family downstream signaling partner. The structures of the inactive and active states of strigolactone receptors are known through X-ray crystallography, and the transition pathway from the inactive to active state in apo receptors has previously been characterized using molecular dynamics simulations. However, it also has been suggested that a covalent butenolide modification of the receptor on the catalytic histidine through substrate hydrolysis promotes formation of the active state. Using molecular dynamics simulations, we show that the presence of the covalent butenolide enhances activation in both AtD14, a receptor found in Arabidopsis, and ShHTL7, a receptor found in Striga, but the enhancement is ∼50 times greater in ShHTL7. We also show that several conserved interactions with the covalent butenolide modification promote transition to the active state in both AtD14 (non-parasite) and ShHTL7 (parasite). Finally, we demonstrate that the enhanced activation of ShHTL7 likely results from disruption of ShHTL7-specific histidine interactions that inhibited activation in the apo case. These results provide a possible explanation for difference in strigolactone sensitivity seen between different strigolactone-sensitive proteins and can be used to aid the design of selective modulators to control Striga parasites.

Karrikin perception and signalling

Karrikins (KARs) are a class of butenolide compounds found in smoke that were first identified as seed germination stimulants for fire-following species. Early studies of KARs classified the germination and postgermination responses of many plant species and investigated crosstalk with plant hormones that regulate germination. The discovery that Arabidopsis thaliana responds to KARs laid the foundation for identifying mutants with altered KAR responses. Genetic analysis of KAR signalling revealed an unexpected link to strigolactones (SLs), a class of carotenoid-derived plant hormones. Substantial progress has since been made towards understanding how KARs are perceived and regulate plant growth, in no small part due to advances in understanding SL perception. KAR and SL signalling systems are evolutionarily related and retain a high degree of similarity. There is strong evidence that KARs are natural analogues of an endogenous signal(s), KAI2 ligand (KL), which remains unknown. KAR/KL signalling regulates many developmental processes in plants including germination, seedling photomorphogenesis, and root and root hair growth. KAR/KL signalling also affects abiotic stress responses and arbuscular mycorrhizal symbiosis. Here, we summarise the current knowledge of KAR/KL signalling and discuss current controversies and unanswered questions in this field.

Mechanistic Basis for Enhanced Strigolactone Sensitivity in KAI2 Triple Mutant

Striga hermonthica is a parasitic weed that destroys billions of dollars' worth of staple crops every year. Its rapid proliferation stems from an enhanced ability to metabolize strigolactones (SLs), plant hormones that direct root branching and shoot growth. Striga's SL receptor, ShHTL7, bears more similarity to the staple crop karrikin receptor KAI2 than to SL receptor D14, though KAI2 variants in plants like Arabidopsis thaliana show minimal SL sensitivity. Recently, studies have indicated that a small number of point mutations to HTL7 residues can confer SL sensitivity to AtKAI2. Here, we analyze both wild-type AtKAI2 and SL-sensitive mutant Var64 through all-atom, long-timescale molecular dynamics simulations to determine the effects of these mutations on receptor function at a molecular level. We demonstrate that the mutations stabilize SL binding by about 2 kcal/mol. They also result in a doubling of the average pocket volume, and eliminate the dependence of binding on certain pocket conformational arrangements. While the probability of certain non-binding SL-receptor interactions increases in the mutant compared with the wild-type, the rate of binding also increases by a factor of ten. All these changes account for the increased SL sensitivity in mutant KAI2, and suggest mechanisms for increasing functionality of host crop SL receptors.

Comprehensive analysis of the carboxylesterase gene reveals that NtCXE22 regulates axillary bud growth through strigolactone metabolism in tobacco

Carboxylesterases (CXE) are a class of hydrolytic enzymes with α/β-folding domains that play a vital role in plant growth, development, stress response, and activation of herbicide-active substances. In this study, 49 Nicotiana tabacum L. CXE genes (NtCXEs) were identified using a sequence homology search. The basic characteristics, phylogenetic evolution, gene structure, subcellular location, promoter cis-elements, and gene expression patterns of the CXE family were systematically analyzed. RNA-seq data and quantitative real-time PCR showed that the expression level of CXEs was associated with various stressors and hormones; gene expression levels were significantly different among the eight tissues examined and at different developmental periods. As a new class of hormones, strigolactones (SLs) are released from the roots of plants and can control the germination of axillary buds.NtCXE7, NtCXE9, NtCXE22, and NtCXE24 were homologous to Arabidopsis SLs hydrolase AtCXE15, and changes in their expression levels were induced by topping and by GR24 (a synthetic analogue of strigolactone). Further examination revealed that NtCXE22-mutant (ntcxe22) plants generated by CRISPR-Cas9 technology had shorter bud outgrowth with lower SLs content. Validation of NtCXE22 was also performed in NtCCD8-OE plants (with fewer axillary buds) and in ntccd8 mutant plants (with more axillary buds). The results suggest that NtCXE22 may act as an efficient SLs hydrolase and affects axillary bud development, thereby providing a feasible method for manipulating endogenous SLs in crops and ornamental plants.

Multiagent Reinforcement Learning-Based Adaptive Sampling for Conformational Dynamics of Proteins

Machine learning is increasingly applied to improve the efficiency and accuracy of molecular dynamics (MD) simulations. Although the growth of distributed computer clusters has allowed researchers to obtain higher amounts of data, unbiased MD simulations have difficulty sampling rare states, even under massively parallel adaptive sampling schemes. To address this issue, several algorithms inspired by reinforcement learning (RL) have arisen to promote exploration of the slow collective variables (CVs) of complex systems. Nonetheless, most of these algorithms are not well-suited to leverage the information gained by simultaneously sampling a system from different initial states (e.g., a protein in different conformations associated with distinct functional states). To fill this gap, we propose two algorithms inspired by multiagent RL that extend the functionality of closely related techniques (REAP and TSLC) to situations where the sampling can be accelerated by learning from different regions of the energy landscape through coordinated agents. Essentially, the algorithms work by remembering which agent discovered each conformation and sharing this information with others at the action-space discretization step. A stakes function is introduced to modulate how different agents sense rewards from discovered states of the system. The consequences are three-fold: (i) agents learn to prioritize CVs using only relevant data, (ii) redundant exploration is reduced, and (iii) agents that obtain higher stakes are assigned more actions. We compare our algorithm with other adaptive sampling techniques (least counts, REAP, TSLC, and AdaptiveBandit) to show and rationalize the gain in performance.

Integration of machine learning with computational structural biology of plants

Computational structural biology of proteins has developed rapidly in recent decades with the development of new computational tools and the advancement of computing hardware. However, while these techniques have widely been used to make advancements in human medicine, these methods have seen less utilization in the plant sciences. In the last several years, machine learning methods have gained popularity in computational structural biology. These methods have enabled the development of new tools which are able to address the major challenges that have hampered the wide adoption of the computational structural biology of plants. This perspective examines the remaining challenges in computational structural biology and how the development of machine learning techniques enables more in-depth computational structural biology of plants.

Dual Role of Strigolactone Receptor Signaling Partner in Inhibiting Substrate Hydrolysis

Plant branch and root growth relies on metabolism of the strigolactone (SL) hormone. The interaction between the SL molecule, Oryza sativa DWARF14 (D14) SL receptor, and D3 F-box protein has been shown to play a critical role in SL perception. Previously, it was believed that D3 only interacts with the closed form of D14 to induce downstream signaling, but recent experiments indicate that D3, as well as its C-terminal helix (CTH), can interact with the open form as well to inhibit strigolactone signaling. Two hypotheses for the CTH induced inhibition are that either the CTH affects the conformational ensemble of D14 by stabilizing catalytically inactive states or the CTH interacts with SLs in a way that prevents them from entering the binding pocket. In this study, we have performed molecular dynamics (MD) simulations to assess the validity of these hypotheses. We used an apo system with only D14 and the CTH to test the active site conformational stability and a holo system with D14, the CTH, and an SL molecule to test the interaction between the SL and CTH. Our simulations show that the CTH affects both active site conformation and the ability of SLs to move into the binding pocket. In the apo system, the CTH allosterically stabilized catalytic residues into their inactive conformation. In the holo system, significant interactions between SLs and the CTH hindered the ability of SLs to enter the D14 binding pocket. These two mechanisms account for the observed decrease in SL binding to D14 and subsequent ligand hydrolysis in the presence of the CTH.

Activation Mechanism of Strigolactone Receptors and Its Impact on Ligand Selectivity between Host and Parasitic Plants

Parasitic weeds such as Striga have led to significant losses in agricultural productivity worldwide. These weeds use the plant hormone strigolactone as a germination stimulant. Strigolactone signaling involves substrate hydrolysis followed by a conformational change of the receptor to a "closed" or "active" state that associates with a signaling partner, MAX2/D3. Crystal structures of active and inactive AtD14 receptors have helped elucidate the structural changes involved in activation. However, the mechanism by which the receptor activates remains unknown. The ligand dependence of AtD14 activation has been disputed by mutagenesis studies showing that enzymatically inactive receptors are able to associate with MAX2 proteins. Furthermore, activation differences between strigolactone receptor in Striga, ShHTL7, and AtD14 could contribute to the high sensitivity to strigolactones exhibited by parasitic plants. Using molecular dynamics simulations, we demonstrate that both AtD14 and ShHTL7 could adopt an active conformation in the absence of ligand. However, ShHTL7 exhibits a higher population in the inactive apo state as compared to the AtD14 receptor. We demonstrate that this difference in inactive state population is caused by sequence differences between their D-loops and interactions with the catalytic histidine that prevent full binding pocket closure in ShHTL7. These results indicate that ligand hydrolysis would enhance the active state population by destabilizing the inactive state in ShHTL7 as compared to AtD14. We also show that the mechanism of activation is more concerted in AtD14 than in ShHTL7 and that the main barrier to activation in ShHTL7 is closing of the binding pocket.