Photoswitching of Feedback Inhibition by Tryptophan in Anthranilate Synthase

The artificial regulation of enzymatic activity by light is an important goal of synthetic biology that can be achieved by the incorporation of light-responsive noncanonical amino acids via genetic code expansion. Here, we apply this concept to anthranilate synthase from Salmonella typhimurium (stTrpE). This enzyme catalyzes the first step of tryptophan biosynthesis, and its activity is feedback-inhibited by the binding of the end-product of the pathway to an allosteric site. To put this feedback inhibition of stTrpE by tryptophan under the control of light, we individually replaced 15 different amino acid residues with the photosensitive noncanonical amino acid o-nitrobenzyl-O-tyrosine (ONBY). ONBY contains a sterically demanding caging group that was meant to cover the allosteric site. Steady-state enzyme kinetics showed that the negative effect of tryptophan on the catalytic activity of the two variants stTrpE-K50ONBY and stTrpE-Y455ONBY was diminished compared to the wild-type enzyme by 1 to 2 orders of magnitude. Upon light-induced decaging of ONBY to the less space-consuming tyrosine residue, tryptophan binding to the allosteric site was restored and catalytic activity was inhibited almost as efficiently as observed for wild-type stTrpE. Based on these results, direct photocontrol of feedback inhibition of stTrpE-K50ONBY and stTrpE-Y455ONBY could be achieved by irradiation during the reaction. Molecular modeling studies allowed us to rationalize the observed functional conversion from the noninhibited caged to the tryptophan-inhibited decaged states. Our study shows that feedback inhibition, which is an important mechanism to regulate key metabolic enzymes, can be efficiently controlled by the purposeful use of light-responsive noncanonical amino acids.

Identification of key genes contributing to amino acid biosynthesis in Torreya grandis using transcriptome and metabolome analysis

Torreya grandis has high economic and nutritional value due to the high nutrients in its kernels. The kernels of different development stages vary enormously in their amino acids content. However, the molecular basis and the regulatory mechanism of amino acid biosynthesis remain unclear. Here, transcriptome and metabolome analysis were performed. Correlation analysis result showed that 4 unigenes were significantly and positively correlated with at least 10 amino acids. The full length CDS of 2 unigenes (TgDAHP2 and TgASA1) were successfully cloned from the 4 unigenes for DAHP, ASA and CITS. Subcelluar localization analysis showed that both TgDAHP2 and TgASA1 were localized to the chloroplast. Overexpression of TgDAHP2 and TgASA1 in Arabidopsis can greatly increase the content of most amino acids. Moreover, 3 transcription factors were found to positively regulate the expression of TgASA1. This research contributes to understand the molecular regulatory mechanisms of amino acid biosynthesis in T. grandis.

Probing structural basis for enhanced binding of SARS-CoV-2 P.1 variant spike protein with the human ACE2 receptor

The initial step of infection by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) involves the binding of receptor binding domain (RBD) of the spike protein to the angiotensin converting enzyme 2 (ACE2) receptor. Each successive wave of SARS‐CoV‐2 reports emergence of many new variants, which is associated with mutations in the RBD as well as other parts of the spike protein. These mutations are reported to have enhanced affinity towards the ACE2 receptor as well as are also crucial for the virus transmission. Many computational and experimental studies have demonstrated the effect of individual mutation on the RBD‐ACE2 binding. However, the cumulative effect of mutations on the RBD and away from the RBD was not investigated in detail. We report here a comparative analysis on the structural communication and dynamics of the RBD and truncated S1 domain of spike protein in complex with the ACE2 receptor from SARS‐CoV‐2 wild type and its P.1 variant. Our integrative network and dynamics approaches highlighted a subtle conformational changes in the RBD as well as truncated S1 domain of spike protein at the protein contact level, responsible for the increased affinity with the ACE2 receptor. Moreover, our study also identified the commonalities and differences in the dynamics of the interactions between spike protein of SARS‐CoV‐2 wild type and its P.1 variant with the ACE2 receptor. Further, our investigation yielded an understanding towards identification of the unique RBD residues crucial for the interaction with the ACE2 host receptor. Overall, the study provides an insight for designing better therapeutics against the circulating P.1 variants as well as other future variants.

Comparative Analysis of Structural and Dynamical Features of Ribosome Upon Association With mRNA Reveals Potential Role of Ribosomal Proteins

Ribosomes play a critical role in maintaining cellular proteostasis. The binding of messenger RNA (mRNA) to the ribosome regulates kinetics of protein synthesis. To generate an understanding of the structural, mechanistic, and dynamical features of mRNA recognition in the ribosome, we have analysed mRNA-protein interactions through a structural comparison of the ribosomal complex in the presence and absence of mRNA. To do so, we compared the 3-Dimensional (3D) structures of components of the two assembly structures and analysed their structural differences because of mRNA binding, using elastic network models and structural network-based analysis. We observe that the head region of 30S ribosomal subunit undergoes structural displacement and subunit rearrangement to accommodate incoming mRNA. We find that these changes are observed in proteins that lie far from the mRNA-protein interface, implying allostery. Further, through perturbation response scanning, we show that the proteins S13, S19, and S20 act as universal sensors that are sensitive to changes in the inter protein network, upon binding of 30S complex with mRNA and other initiation factors. Our study highlights the significance of mRNA binding in the ribosome complex and identifies putative allosteric sites corresponding to alterations in structure and/or dynamics, in regions away from mRNA binding sites in the complex. Overall, our work provides fresh insights into mRNA association with the ribosome, highlighting changes in the interactions and dynamics of the ribosome assembly because of the binding.

Comparative protein structure network analysis on 3CLpro from SARS-CoV-1 and SARS-CoV-2

The main protease M^pro, 3CL^pro is an important target from coronaviruses. In spite of having 96% sequence identity among M^pros from SARS‐CoV‐1 and SARS‐CoV‐2; the inhibitors used to block the activity of SARS‐CoV‐1 M^pro so far, were found to have differential inhibitory effect on M^pro of SARS‐CoV‐2. The possible reason could be due to the difference of few amino acids among the peptidases. Since, overall 3‐D crystallographic structure of M^pro from SARS‐CoV‐1 and SARS‐CoV‐2 is quite similar and mapping a subtle structural variation is seemingly impossible. Hence, we have attempted to study a structural comparison of SARS‐CoV‐1 and SARS‐CoV‐2 M^pro in apo and inhibitor bound states using protein structure network (PSN) based approach at contacts level. The comparative PSNs analysis of apo M^pros from SARS‐CoV‐1 and SARS‐CoV‐2 uncovers small but significant local changes occurring near the active site region and distributed throughout the structure. Additionally, we have shown how inhibitor binding perturbs the PSG and the communication pathways in M^pros. Moreover, we have also investigated the network connectivity on the quaternary structure of M^pro and identified critical residue pairs for complex formation using three centrality measurement parameters along with the modularity analysis. Taken together, these results on the comparative PSN provide an insight into conformational changes that may be used as an additional guidance towards specific drug development.

Chorismate- and isochorismate converting enzymes: versatile catalysts acting on an important metabolic node

Chorismate and isochorismate represent an important branching point connecting primary and secondary metabolism in bacteria, fungi, archaea and plants. Chorismate- and isochorismate-converting enzymes are potential targets for new bioactive compounds, as well as valuable biocatalysts for the in vivo and in vitro synthesis of fine chemicals. The diversity of the products of chorismate- and isochorismate-converting enzymes is reflected in the enzymatic three-dimensional structures and molecular mechanisms. Due to the high reactivity of chorismate and its derivatives, these enzymes have evolved to be accurately tailored to their respective reaction; at the same time, many of them exhibit a fascinating flexibility regarding side reactions and acceptance of alternative substrates. Here, we give an overview of the different (sub)families of chorismate- and isochorismate-converting enzymes, their molecular mechanisms, and three-dimensional structures. In addition, we highlight important results of mutagenetic approaches that generate a broader understanding of the influence of distinct active site residues for product formation and the conversion of one subfamily into another. Based on this, we discuss to what extent the recent advances in the field might influence the general mechanistic understanding of chorismate- and isochorismate-converting enzymes. Recent discoveries of new chorismate-derived products and pathways, as well as biocatalytic conversions of non-physiological substrates, highlight how this vast field is expected to continue developing in the future.

Computational investigations of allostery in aromatic amino acid biosynthetic enzymes

Allostery, in which binding of ligands to remote sites causes a functional change in the active sites, is a fascinating phenomenon observed in enzymes. Allostery can occur either with or without significant conformational changes in the enzymes, and the molecular basis of its mechanism can be difficult to decipher using only experimental techniques. Computational tools for analyzing enzyme sequences, structures, and dynamics can provide insights into the allosteric mechanism at the atomic level. Combining computational and experimental methods offers a powerful strategy for the study of enzyme allostery. The aromatic amino acid biosynthesis pathway is essential in microorganisms and plants. Multiple enzymes involved in this pathway are sensitive to feedback regulation by pathway end products and are known to use allostery to control their activities. To date, four enzymes in the aromatic amino acid biosynthesis pathway have been computationally investigated for their allosteric mechanisms, including 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase, anthranilate synthase, chorismate mutase, and tryptophan synthase. Here we review the computational studies and findings on the allosteric mechanisms of these four enzymes. Results from these studies demonstrate the capability of computational tools and encourage future computational investigations of allostery in other enzymes of this pathway.

Small Conformational Changes Underlie Evolution of Resistance to NNRTI in HIV Reverse Transcriptase

Despite achieving considerable success in reducing the number of fatalities due to acquired immunodeficiency syndrome, emergence of resistance against the reverse transcriptase (RT) inhibitor drugs remains one of the biggest challenges of the human immunodeficiency virus antiretroviral therapy (ART). Non-nucleoside reverse transcriptase inhibitors (NNRTIs) form a large class of drugs and a crucial component of ART. In NNRTIs, even a single resistance mutation is known to make the drugs completely ineffective. Additionally, several inhibitor-bound RTs with single resistance mutations do not exhibit any significant variations in their three-dimensional structures compared with the inhibitor-bound RT but completely nullify their inhibitory functions. This makes understanding the structural mechanism of these resistance mutations crucial for drug development. Here, we study several single resistance mutations in the allosteric inhibitor (nevirapine)-bound RT to analyze the mechanism of small structural changes leading to these large functional effects. In this study, we have shown that in absence of significant conformational variations in the inhibitor-bound wild-type RT and RT with single resistance mutations, the protein contact network analysis of their static structures, along with molecular dynamics simulations, can be a useful approach to understand the functional effect of small local conformational variations. The simple network analysis exposes the localized contact changes that lead to global rearrangement in the communication pattern within RT. Furthermore, these conformational changes have implications on the overall dynamics of RT. Using various measures, we show that a single resistance mutation can change the network structure and dynamics of RT to behave more like unbound RT, even in the presence of the inhibitor. This combined coarse-grained contact network and molecular dynamics approach promises to be a useful tool to analyze structure-function studies of proteins that show large functional changes with negligible variations in their overall conformation.

Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics

Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.

Integrated omics data of two annual ryegrass (Lolium multiflorum L.) genotypes reveals core metabolic processes under drought stress

BACKGROUND

Annual ryegrass (Lolium multiflorum L.) is a commercially important, widely distributed forage crop that is used in the production of hay and silage worldwide. Drought has been a severe environmental constraint in its production. Nevertheless, only a handful of studies have examined the impact of short-term drought stress on annual ryegrass. The aim of this study was to explore how stress-induced core metabolic processes enhance drought tolerance, or adaptation to drought, in annual ryegrass.

RESULTS

We profiled the transcriptomes, proteomes, and metabolomes of two annual ryegrass genotypes: the drought-resistant genotype "Abundant 10" and drought-susceptible genotype "Adrenalin 11." We identified differentially expressed metabolites and their corresponding proteins and transcripts that are involved in 23 core metabolic processes, in response to short-term drought stress. Protein-gene-metabolite correlation networks were built to reveal the relationships between the expression of transcripts, proteins, and metabolites in drought-resistant annual ryegrass. Furthermore, integrated metabolic pathways were used to observe changes in enzymes corresponding with levels of amino acids, lipids, carbohydrate conjugates, nucleosides, alkaloids and their derivatives, and pyridines and their derivatives. The resulting omics data underscored the significance of 23 core metabolic processes on the enhancement of drought tolerance or adaptation to drought in annual ryegrass.

CONCLUSIONS

The regulatory networks were inferred using MCoA and correlation analysis to reveal the relationships among the expression of transcripts, proteins, and metabolites that highlight the corresponding elements of these core metabolic pathways. Our results provide valuable insight into the molecular mechanisms of drought resistance, and represent a promising strategy toward the improvement of drought tolerance in annual ryegrass.

Identification of potential allosteric communication pathways between functional sites of the bacterial ribosome by graph and elastic network models

BACKGROUND

Accumulated evidence indicates that bacterial ribosome employs allostery throughout its structure for protein synthesis. The nature of the allosteric communication between remote functional sites remains unclear, but the contact topology and dynamics of residues may play role in transmission of a perturbation to distant sites.

METHODS/RESULTS

We employ two computationally efficient approaches - graph and elastic network modeling to gain insights about the allosteric communication in ribosome. Using graph representation of the structure, we perform k-shortest pathways analysis between peptidyl transferase center-ribosomal tunnel, decoding center-peptidyl transferase center - previously reported functional sites having allosteric communication. Detailed analysis on intact structures points to common and alternative shortest pathways preferred by different states of translation. All shortest pathways capture drug target sites and allosterically important regions. Elastic network model further reveals that residues along all pathways have the ability of quickly establishing pair-wise communication and to help the propagation of a perturbation in long-ranges during functional motions of the complex.

CONCLUSIONS

Contact topology and inherent dynamics of ribosome configure potential communication pathways between functional sites in different translation states. Inter-subunit bridges B2a, B3 and P-tRNA come forward for their high potential in assisting allostery during translation. Especially B3 emerges as a potential druggable site.

GENERAL SIGNIFICANCE

This study indicates that the ribosome topology forms a basis for allosteric communication, which can be disrupted by novel drugs to kill drug-resistant bacteria. Our computationally efficient approach not only overlaps with experimental evidence on allosteric regulation in ribosome but also proposes new druggable sites.

Complex network analysis of thermostable mutants of Bacillus subtilis Lipase A

Three-dimensional structures of proteins that regulate their functions can be modelled using complex network based approaches for understanding the structure-function relationship. The six mutants of the protein Lipase A from Bacillus subtilis, harbouring 2 to 12 mutations, retain their function at higher temperatures with negligible variation in their overall three-dimensional crystallographic structures. This enhanced thermostability of the mutants questions the structure-function paradigm. In this paper, a coarse-grained complex network approach is used to elucidate the structural basis of enhanced thermostability in the mutant proteins, by uncovering small but significant local changes distributed throughout the structure, rendering stability to the mutants at higher temperatures. Community structure analysis of the six mutant protein networks uncovers the specific reorganisations among the nodes/residues that occur, in absence of overall structural variations, which induce enhanced rigidity underlying the increased thermostability. This study offers a novel and significant application of complex network analysis that proposes to be useful in the understanding and designing of thermostable proteins.