EnzyDock: Protein–Ligand Docking of Multiple Reactive States along a Reaction Coordinate in Enzymes

Template-Based Docking Using Automated Maximum Common Substructure Identification with EnzyDock: Mechanistic and Inhibitor Docking

EnzyDock is a multistate, multiscale CHARMM-based docking program which enables mechanistic docking, i.e., modeling enzyme reactions by docking multiple reaction states, like substrates, intermediates, transition states, and products to the enzyme, in addition to standard protein-ligand docking. To achieve docking of multiple reaction states with similar poses (i.e., consensus docking), EnzyDock employs consensus pose restraints of the docked ligand states relative to a docking template. In the current work, we present an implementation of a Maximum Common Substructure (MCS)-guided docking strategy using EnzyDock, enabling the automatic detection of similarity among query ligands. Specifically, the MCS multistate approach is employed to efficiently dock ligands along enzyme reaction coordinates, including reactants, intermediates, and products, which allows efficient and robust mechanistic docking. To demonstrate the effectiveness of the MCS strategy in modeling enzymes, it is first applied to two highly complex enzyme reaction cascades catalyzed by the diterpene synthase CotB2 and the Diels-Alderase LepI. In addition, the MCS strategy is applied to dock enzyme inhibitors using cocrystallized inhibitors or substrates to guide the docking in the enzymes dihydrofolate reductase and the SARS-CoV-2 enzyme Mpro. The latter case exemplifies the use of MCS with EnzyDock's covalent docking capabilities and QM/MM scoring option. We show that different protocols of the implemented MCS algorithm are needed to obtain mechanistic consistency (i.e., similar poses) in mechanistic docking or to accurately dock chemically diverse ligands in inhibitor docking. Although the current implementation is specific for EnzyDock, the findings should be general and transferable to additional docking programs.

Physics-based modeling in the new era of enzyme engineering

Enzyme engineering is entering a new era characterized by the integration of computational strategies. While bioinformatics and artificial intelligence methods have been extensively applied to accelerate the screening of function-enhancing mutants, physics-based modeling methods, such as molecular mechanics and quantum mechanics, are essential complements in many objectives. In this Perspective, we highlight how physics-based modeling will help the field of computational enzyme engineering reach its full potential by exploring current developments, unmet challenges and emerging opportunities for tool development.

Increasing the Accuracy and Robustness of the CHARMM General Force Field with an Expanded Training Set

Small molecule empirical force fields (FFs), including the CHARMM General Force Field (CGenFF), are designed to have wide coverage of organic molecules and to rapidly assign parameters to molecules not explicitly included in the FF. Assignment of parameters to new molecules in CGenFF is based on a trained bond-angle-dihedral charge increment linear interpolation scheme for the partial atomic charges along with bonded parameters assigned based on analogy using a rules-based penalty score scheme associated with atom types and chemical connectivity. Accordingly, the accuracy of CGenFF is related to the extent of the training set of available parameters. In the present study that training set is extended by 1390 molecules selected to represent connectivities new to CGenFF training compounds. Quantum mechanical (QM) data for optimized geometries, bond, valence angle, and dihedral angle potential energy scans, interactions with water, molecular dipole moments, and electrostatic potentials were used as target data. The resultant bonded parameters and partial atomic charges were used to train a new version of the CGenFF program, v5.0, which was used to generate parameters for a validation set of molecules, including drug-like molecules approved by the FDA, which were then benchmarked against both experimental and QM data. CGenFF v5.0 shows overall improvements with respect to QM intramolecular geometries, vibrations, dihedral potential energy scans, dipole moments and interactions with water. Tests of pure solvent properties of 216 molecules show small improvements versus the previous release of CGenFF v2.5.1 reflecting the high quality of the Lennard-Jones parameters that were explicitly optimized during the initial optimization of both the CGenFF and the CHARMM36 force field. CGenFF v5.0 represents an improvement that is anticipated to more accurately model intramolecular geometries and strain energies as well as noncovalent interactions of drug-like and other organic molecules.

CHARMM-GUI EnzyDocker for Protein-Ligand Docking of Multiple Reactive States along a Reaction Coordinate in Enzymes

Enzymes play crucial roles in all biological systems by catalyzing a myriad of chemical reactions. These reactions range from simple one-step processes to intricate multistep cascades. Predicting mechanistically appropriate binding modes along a reaction pathway for substrate, product, and all reaction intermediates and transition states is a daunting task. To address this challenge, special docking programs like EnzyDock have been developed. Yet, running such docking simulations is complicated due to the nature of multistep enzyme processes. This work presents CHARMM-GUI EnzyDocker, a web-based cyberinfrastructure designed to streamline the preparation and running of EnzyDock docking simulations. The development of EnzyDocker has been achieved through integration of existing CHARMM-GUI modules, such as PDB Reader and Manipulator, Ligand Designer, and QM/MM Interfacer. In addition, new functionalities have been developed to facilitate a one-stop preparation of multistate and multiscale docking systems and enable interactive and intuitive ligand modifications and flexible protein residues selections. A simple setup related to multiligand docking is automatized through intuitive user interfaces. EnzyDocker offers support for standard classical docking and QM/MM docking with CHARMM built-in semiempirical engines. Automated consensus restraints for incorporating experimental knowledge into the docking are facilitated via a maximum common substructure algorithm. To illustrate the robustness of EnzyDocker, we conducted docking simulations of three enzyme systems: dihydrofolate reductase, SARS-CoV-2 Mpro, and the diterpene synthase CotB2. In addition, we have created four tutorial videos about these systems, which can be found at https://www.charmm-gui.org/demo/enzydock. EnzyDocker is expected to be a valuable and accessible web-based tool that simplifies and accelerates the setup process for multistate docking for enzymes.

Engineering terpene synthases and their substrates for the biocatalytic production of terpene natural products and analogues

Terpene synthases produce a wide number of hydrocarbon skeletons by controlling intramolecular rearrangements of allylic pyrophosphate subtrates via reactive carbocation intermediates. Here we review recent research focused on engineering terpene synthases and modifying their substrates to rationally manipulate terpene catalyisis. Molecular dynamic simulations and solid state X-ray crystallography are powerful techniques to identify substrate binding modes, key active site residues for substrate folding, and the location of active site water. Variants in specific 'hotspots' of terpene synthases including the G1/2, K/H and Hα-1 helices have been targeted to modify active site water management and yield new products. We discuss the potential of exploiting substrate analogues to synthesise novel compounds and briefly outline biphasic flow systems for biocatalysis of terpenes. We forsee greater applications for terpenes as the field converges on effective methods for engineering of terpene synthases by new computational and high throughput experimental methods and for high-yield production. It is crucial when engineering terpene synthases that both product distribution and enzyme activity are simultaneously optimised.

Molecular Insight into the Catalytic Mechanism of the Sesquiterpene Cyclase BcABA3

BcABA3 is an unusual sesquiterpene synthase that lacks the conserved DDxxD and DTE/NSE motifs. Despite this, it can catalyze the conversion of farnesyl diphosphate to 2Z,4E-α-ionylideneethane. We used structure prediction, multiscale simulations, and site-directed mutagenesis experiments to investigate BcABA3 and its catalytic mechanism. BcABA3 has structural similarity to typical class I terpenoid cyclases in its active site. Based on simulation results, we identified two discontinuous glutamate residues, E124 and E88, which compensate for the absence of the aspartate-rich DDxxD motif. Quantum chemical calculations show that BcABA3 adopts a direct rotation mechanism for allyl cation isomerization rather than via the nerolidyl diphosphate. Then, it can achieve a successive proton transfer reaction, which is difficult to achieve by intramolecular rearrangement via the protruding outward carbonyl oxygen of A206. This reaction is then directed forward by two relatively stable intermediates containing a cation-conjugated double-bond structure. E124 is also proposed as the proton receptor in the final deprotonation to couple this step with 2Z,4E-α-ionylideneethane release. These findings provide valuable insight into the catalytic mechanisms of BcABA3 and can aid in its engineering, which will facilitate studies of abscisic acid biosynthesis.

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published. They include the following: new faster simulation engines, accessible user interfaces for convenient workflows, and a vast array of simulation and analysis methods that encompass quantum mechanical, atomistic, and coarse-grained levels, as well as extensive coverage of force fields. In addition to providing the current snapshot of the CHARMM development, this review may serve as a starting point for exploring relevant theories and computational methods for tackling contemporary and emerging problems in biomolecular systems. CHARMM is freely available for academic and nonprofit research at https://academiccharmm.org/program.

Differential Substrate Sensing in Terpene Synthases from Plants and Microorganisms: Insight from Structural, Bioinformatic, and EnzyDock Analyses

Terpene synthases (TPSs) catalyze the first step in the formation of terpenoids, which comprise the largest class of natural products in nature. TPSs employ a family of universal natural substrates, composed of isoprenoid units bound to a diphosphate moiety. The intricate structures generated by TPSs are the result of substrate binding and folding in the active site, enzyme-controlled carbocation reaction cascades, and final reaction quenching. A key unaddressed question in class I TPSs is the asymmetric nature of the diphosphate-(Mg2+)3 cluster, which forms a critical part of the active site. In this asymmetric ion cluster, two diphosphate oxygen atoms protrude into the active site pocket. The substrate hydrocarbon tail, which is eventually molded into terpenes, can bind to either of these oxygen atoms, yet to which is unknown. Herein, we employ structural, bioinformatics, and EnzyDock docking tools to address this enigma. We bring initial data suggesting that this difference is rooted in evolutionary differences between TPSs. We hypothesize that this alteration in binding, and subsequent chemistry, is due to TPSs originating from plants or microorganisms. We further suggest that this difference can cast light on the frequent observation that the chiral products or intermediates of plant and bacterial terpene synthases represent opposite enantiomers.

Mechanistic docking in terpene synthases using EnzyDock

Terpene Synthases (TPS) catalyze the formation of multicyclic, complex terpenes and terpenoids from linear substrates. Molecular docking is an important research tool that can further our understanding of TPS multistep mechanisms and guide enzyme design. Standard docking programs are not well suited to tackle the unique challenges of TPS, like the many chemical steps which form multiple stereo-centers, the weak dispersion interactions between the isoprenoid chain and the hydrophobic region of the active site, description of carbocation intermediates, and finding mechanistically meaningful sets of docked poses. To address these and other unique challenges, we developed the multistate, multiscale docking program EnzyDock and used it to study many TPS and other enzymes. In this review we discuss the unique challenges of TPS, the special features of EnzyDock developed to address these challenges and demonstrate its successful use in ongoing research on the bacterial TPS CotB2.

Docking carbocations into terpene synthase active sites using chemically meaningful constraints-The TerDockin approach

Terpenes are a diverse class of natural products which have long been sought after for their chemical properties as medicine, perfumes, and for food flavoring. Computational docking studies of terpene mechanisms have been a challenge due to the lack of strong directing groups which many docking programs rely on. In this chapter, we dive into our computational method Terdockin (Terpene-Docking) as a successful methodology in modeling terpene synthase mechanisms. This method could also be used as inspiration for any multi-ligand docking project.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Molecular Gas-Phase Conformational Ensembles

Accurately determining the global minima of a molecular structure is important in diverse scientific fields, including drug design, materials science, and chemical synthesis. Conformational search engines serve as valuable tools for exploring the extensive conformational space of molecules and for identifying energetically favorable conformations. In this study, we present a comparison of Auto3D, CREST, Balloon, and ETKDG (from RDKit), which are freely available conformational search engines, to evaluate their effectiveness in locating global minima. These engines employ distinct methodologies, including machine learning (ML) potential-based, semiempirical, and force field-based approaches. To validate these methods, we propose the use of collisional cross-section (CCS) values obtained from ion mobility-mass spectrometry studies. We hypothesize that experimental gas-phase CCS values can provide experimental evidence that we likely have the global minimum for a given molecule. To facilitate this effort, we used our gas-phase conformation library (GPCL) which currently consists of the full ensembles of 20 small molecules and can be used by the community to validate any conformational search engine. Further members of the GPCL can be readily created for any molecule of interest using our standard workflow used to compute CCS values, expanding the ability of the GPCL in validation exercises. These innovative validation techniques enhance our understanding of the conformational landscape and provide valuable insights into the performance of conformational generation engines. Our findings shed light on the strengths and limitations of each search engine, enabling informed decisions for their utilization in various scientific fields, where accurate molecular structure determination is crucial for understanding biological activity and designing targeted interventions. By facilitating the identification of reliable conformations, this study significantly contributes to enhancing the efficiency and accuracy of molecular structure determination, with particular focus on metabolite structure elucidation. The findings of this research also provide valuable insights for developing effective workflows for predicting the structures of unknown compounds with high precision.

Docking and other computing tools in drug design against SARS-CoV-2

The use of computer simulation methods has become an indispensable component in identifying drugs against the SARS-CoV-2 coronavirus. There is a huge body of literature on application of molecular modelling to predict inhibitors against target proteins of SARS-CoV-2. To keep our review clear and readable, we limited ourselves primarily to works that use computational methods to find inhibitors and test the predicted compounds experimentally either in target protein assays or in cell culture with live SARS-CoV-2. Some works containing results of experimental discovery of corresponding inhibitors without using computer modelling are included as examples of a success. Also, some computational works without experimental confirmations are also included if they attract our attention either by simulation methods or by databases used. This review collects studies that use various molecular modelling methods: docking, molecular dynamics, quantum mechanics, machine learning, and others. Most of these studies are based on docking, and other methods are used mainly for post-processing to select the best compounds among those found through docking. Simulation methods are presented concisely, information is also provided on databases of organic compounds that can be useful for virtual screening, and the review itself is structured in accordance with coronavirus target proteins.

Inhibitory Effect of Quercetin on Oxidative Endogen Enzymes: A Focus on Putative Binding Modes

Oxidative stress is defined as an imbalance between the production of free radicals and reactive oxygen species (ROS) and the ability of the body to neutralize them by anti-oxidant defense systems. Cells can produce ROS during physiological processes, but excessive ROS can lead to non-specific and irreversible damage to biological molecules, such as DNA, lipids, and proteins. Mitochondria mainly produce endogenous ROS during both physiological and pathological conditions. Enzymes like nicotinamide adenine dinucleotide phosphate oxidase (NOX), xanthine oxidase (XO), lipoxygenase (LOX), myeloperoxidase (MPO), and monoamine oxidase (MAO) contribute to this process. The body has enzymatic and non-enzymatic defense systems to neutralize ROS. The intake of bioactive phenols, like quercetin (Que), can protect against pro-oxidative damage by quenching ROS through a non-enzymatic system. In this study, we evaluate the ability of Que to target endogenous oxidant enzymes involved in ROS production and explore the mechanisms of action underlying its anti-oxidant properties. Que can act as a free radical scavenger by donating electrons through the negative charges in its phenolic and ketone groups. Additionally, it can effectively inhibit the activity of several endogenous oxidative enzymes by binding them with high affinity and specificity. Que had the best molecular docking results with XO, followed by MAO-A, 5-LOX, NOX, and MPO. Que's binding to these enzymes was confirmed by subsequent molecular dynamics, revealing different stability phases depending on the enzyme bound. The 500 ns simulation showed a net evolution of binding for NOX and MPO. These findings suggest that Que has potential as a natural therapy for diseases related to oxidative stress.

Decoding Catalysis by Terpene Synthases

The review by Christianson, published in 2017 on the twentieth anniversary of the emergence of the field, summarizes the foundational discoveries and key advances in terpene synthase/cyclase (TS) biocatalysis (Christianson, D. W. Chem Rev2017, 117 (17), 11570-11648. DOI: 10.1021/acs.chemrev.7b00287). Here, we review the TS literature published since then, bringing the field up to date and looking forward to what could be the near future of TS rational design. Many revealing discoveries have been made in recent years, building on the knowledge and fundamental principles uncovered during those initial two decades of study. We use these to explore TS reaction chemistry and see how a combined experimental and computational approach helps to decipher the complexities of TS catalysis. Revealed are a suite of catalytic motifs which control product outcome in TSs, some obvious, some more subtle. We examine each in detail, using the most recent papers and insights to illustrate how exactly this fascinating class of enzymes takes a single acyclic substrate and turns it into the many thousands of complex terpenoids found in Nature. We then explore some of the recent strategies for TS engineering, including machine learning and other data-driven approaches. From this, rational and predictive engineering of TSs, "designer terpene synthases", will begin to emerge as a realistic goal.

Unraveling the role of prenyl side-chain interactions in stabilizing the secondary carbocation in the biosynthesis of variexenol B

Terpene cyclization reactions involve a number of carbocation intermediates. In some cases, these carbocations are stabilized by through-space interactions with π orbitals. Several terpene/terpenoids, such as sativene, santalene, bergamotene, ophiobolin and mangicol, possess prenyl side chains that do not participate in the cyclization reaction. The role of these prenyl side chains has been partially investigated, but remains elusive in the cyclization cascade. In this study, we focus on variexenol B that is synthesized from iso-GGPP, as recently reported by Dickschat and co-workers, and investigate the possibility of through-space interactions with prenyl side chains using DFT calculations. Our calculations show that (i) the unstable secondary carbocation is stabilized by the cation-π interaction from prenyl side chains, thereby lowering the activation energy, (ii) the four-membered ring formation is completed through bridging from the exomethylene group, and (iii) the annulation from the exomethylene group proceeds in a barrier-free manner.

QM/MM Modeling Aided Enzyme Engineering in Natural Products Biosynthesis

Natural products and their derivatives are widely used across various industries, particularly pharmaceuticals. Modern engineered biosynthesis provides an alternative way of producing and meeting the growing need for diverse natural products. Natural enzymes, on the other hand, often exhibit unsatisfactory catalytic characteristics and necessitate further enzyme engineering modifications. QM/MM, as a powerful and extensively used computational tool in the field of enzyme catalysis, has been increasingly applied in rational enzyme engineering over the past decade. In this review, we summarize recent advances in QM/MM computational investigation on enzyme catalysis and enzyme engineering for natural product biosynthesis. The challenges and perspectives for future QM/MM applications aided enzyme engineering in natural product biosynthesis will also be discussed.

Revision of the Peniroquesine Biosynthetic Pathway by Retro-Biosynthetic Theoretical Analysis: Ring Strain Controls the Unique Carbocation Rearrangement Cascade

Peniroquesine, a sesterterpenoid featuring a unique 5/6/5/6/5 fused pentacyclic ring system, has been known for a long time, but its biosynthetic pathway/mechanism remains elusive. Based on isotopic labeling experiments, a plausible biosynthetic pathway to peniroquesines A-C and their derivatives was recently proposed, in which the characteristic peniroquesine-type 5/6/5/6/5 pentacyclic skeleton is synthesized from geranyl-farnesyl pyrophosphate (GFPP) via a complex concerted A/B/C-ring formation, repeated reverse-Wagner-Meerwein alkyl shifts, three successive secondary (2°) carbocation intermediates, and a highly distorted trans-fused bicyclo[4.2.1]nonane intermediate. However, our density functional theory calculations do not support this mechanism. By applying a retro-biosynthetic theoretical analysis strategy, we were able to find a preferred pathway for peniroquesine biosynthesis, involving a multistep carbocation cascade including triple skeletal rearrangements, trans-cis isomerization, and 1,3-H shift. This pathway/mechanism is in good agreement with all of the reported isotope-labeling results.

Pharmacological Chaperones and Protein Conformational Diseases: Approaches of Computational Structural Biology

Whenever a protein fails to fold into its native structure, a profound detrimental effect is likely to occur, and a disease is often developed. Protein conformational disorders arise when proteins adopt abnormal conformations due to a pathological gene variant that turns into gain/loss of function or improper localization/degradation. Pharmacological chaperones are small molecules restoring the correct folding of a protein suitable for treating conformational diseases. Small molecules like these bind poorly folded proteins similarly to physiological chaperones, bridging non-covalent interactions (hydrogen bonds, electrostatic interactions, and van der Waals contacts) loosened or lost due to mutations. Pharmacological chaperone development involves, among other things, structural biology investigation of the target protein and its misfolding and refolding. Such research can take advantage of computational methods at many stages. Here, we present an up-to-date review of the computational structural biology tools and approaches regarding protein stability evaluation, binding pocket discovery and druggability, drug repurposing, and virtual ligand screening. The tools are presented as organized in an ideal workflow oriented at pharmacological chaperones' rational design, also with the treatment of rare diseases in mind.

Origin of Catalysis by Nitroalkane Oxidase

The rate of proton abstraction of the carbon acid nitroethane by Asp402 is accelerated by a factor of 10⁸ in the enzyme nitroalkane oxidase (NAO) relative to that by the organic base acetate ion in water. The Cα proton of nitroalkanes is known to exhibit an abnormal correlation between its acidity strength and the rate of deprotonation, with an unusually slow rate of deprotonation in water. This work examines the origin of NAO catalysis, revealing that the rate enhancement by the enzyme is due to transition-state stabilization, restoring the normal behavior of the linear free energy relationship of Bronsted acids. Interestingly, NAO employs the ubiquitous cofactor flavin adenosine diphosphate (FAD) to perform the subsequent oxidation. Does the FAD cofactor also affect the catalytic rate of the initial proton transfer process of the overall nitroalkane oxidation? Classical molecular dynamics and path-integral simulations using a reaction-specific combined quantum mechanics/molecular mechanics (QM/MM) approach were carried out to obtain the free energy reaction profiles, or the potentials of mean force, for the enzymatic reaction and for a model reaction in aqueous solution, as well as for the 2'-deoxy-FAD co-factor-modified NAO. Free energy perturbation calculations suggest that transition-state stabilization of the reactive fragment is the primary cause of the catalytic effect. It is found that the FAD cofactor plays a crucial role in increasing the Cα proton acidity, via specific hydrogen bonding and π-stacking interactions, although these factors have a smaller effect on the enhancement of the rate of deprotonation. Model QM calculations of the π-stacking complexes between the FAD isoalloxazine ring and the neutral and anionic nitroethane, respectively, reveal that the anionic π-stacking complex is more stable than the neutral one by 15.7 kcal/mol, and a net π-stacking energy of 17.3 kcal/mol is obtained. Hence, the isoalloxazine ring, in addition to serving as a very potent oxidizing agent via the formation of covalent intermediate structures, is able to exert a considerable amount of catalytic effect through noncovalent π-stacking interactions.

Understanding the competing pathways leading to hydropyrene and isoelisabethatriene

Terpene synthases are responsible for the biosynthesis of terpenes, the largest family of natural products. Hydropyrene synthase generates hydropyrene and hydropyrenol as its main products along with two byproducts, isoelisabethatrienes A and B. Fascinatingly, a single active site mutation (M75L) diverts the product distribution towards isoelisabethatrienes A and B. In the current work, we study the competing pathways leading to these products using quantum chemical calculations in the gas phase. We show that there is a great thermodynamic preference for hydropyrene and hydropyrenol formation, and hence most likely in the synthesis of the isoelisabethatriene products kinetic control is at play.

Predictive Engineering of Class I Terpene Synthases Using Experimental and Computational Approaches

Terpenoids are a highly diverse group of natural products with considerable industrial interest. Increasingly, engineered microbes are used for the production of terpenoids to replace natural extracts and chemical synthesis. Terpene synthases (TSs) show a high level of functional plasticity and are responsible for the vast structural diversity observed in natural terpenoids. Their relatively inert active sites guide intrinsically reactive linear carbocation intermediates along one of many cyclisation paths via exertion of subtle steric and electrostatic control. Due to the absence of a strong protein interaction with these intermediates, there is a remarkable lack of sequence-function relationship within the TS family, making product-outcome predictions from sequences alone challenging. This, in combination with the fact that many TSs produce multiple products from a single substrate hampers the design and use of TSs in the biomanufacturing of terpenoids. This review highlights recent advances in genome mining, computational modelling, high-throughput screening, and machine-learning that will allow more predictive engineering of these fascinating enzymes in the near future.

Mining methods and typical structural mechanisms of terpene cyclases

Terpenoids, formed by cyclization and/or permutation of isoprenes, are the most diverse and abundant class of natural products with a broad range of significant functions. One family of the critical enzymes involved in terpenoid biosynthesis is terpene cyclases (TCs), also known as terpene synthases (TSs), which are responsible for forming the ring structure as a backbone of functionally diverse terpenoids. With the recent advances in biotechnology, the researches on terpene cyclases have gradually shifted from the genomic mining of novel enzyme resources to the analysis of their structures and mechanisms. In this review, we summarize both the new methods for genomic mining and the structural mechanisms of some typical terpene cyclases, which are helpful for the discovery, engineering and application of more and new TCs.

Benchmarking the Ability of Common Docking Programs to Correctly Reproduce and Score Binding Modes in SARS-CoV-2 Protease Mpro

The coronavirus SARS-CoV-2 main protease, Mpro, is conserved among coronaviruses with no human homolog and has therefore attracted significant attention as an enzyme drug target for COVID-19. The number of studies targeting Mpro for in silico screening has grown rapidly, and it would be of great interest to know in advance how well docking methods can reproduce the correct ligand binding modes and rank these correctly. Clearly, current attempts at designing drugs targeting Mpro with the aid of computational docking would benefit from a priori knowledge of the ability of docking programs to predict correct binding modes and score these correctly. In the current work, we tested the ability of several leading docking programs, namely, Glide, DOCK, AutoDock, AutoDock Vina, FRED, and EnzyDock, to correctly identify and score the binding mode of Mpro ligands in 193 crystal structures. None of the codes were able to correctly identify the crystal structure binding mode (lowest energy pose with root-mean-square deviation < 2 Å) in more than 26% of the cases for noncovalently bound ligands (Glide: top performer), whereas for covalently bound ligands the top score was 45% (EnzyDock). These results suggest that one should perform in silico campaigns of Mpro with care and that more comprehensive strategies including ligand free energy perturbation might be necessary in conjunction with virtual screening and docking.

Computational Study on Temperature Driven Structure-Function Relationship of Polysaccharide Producing Bacterial Glycosyl Transferase Enzyme

Glycosyltransferase (GTs) is a wide class of enzymes that transfer sugar moiety, playing a key role in the synthesis of bacterial exopolysaccharide (EPS) biopolymer. In recent years, increased demand for bacterial EPSs has been observed in pharmaceutical, food, and other industries. The application of the EPSs largely depends upon their thermal stability, as any industrial application is mainly reliant on slow thermal degradation. Keeping this in context, EPS producing GT enzymes from three different bacterial sources based on growth temperature (mesophile, thermophile, and hyperthermophile) are considered for in silico analysis of the structural–functional relationship. From the present study, it was observed that the structural integrity of GT increases significantly from mesophile to thermophile to hyperthermophile. In contrast, the structural plasticity runs in an opposite direction towards mesophile. This interesting temperature-dependent structural property has directed the GT–UDP-glucose interactions in a way that thermophile has finally demonstrated better binding affinity (−5.57 to −10.70) with an increased number of hydrogen bonds (355) and stabilizing amino acids (Phe, Ala, Glu, Tyr, and Ser). The results from this study may direct utilization of thermophile-origin GT as best for industrial-level bacterial polysaccharide production.

The Impression of a Nonexisting Catalytic Effect: The Role of CotB2 in Guiding the Complex Biosynthesis of Cyclooctat-9-en-7-ol

Terpene synthases generate terpenes employing diversified carbocation chemistry, including highly specific ring formations, proton and hydride transfers, and methyl as well as methylene migrations, followed by reaction quenching. In this enzyme family, the main catalytic challenge is not rate enhancement, but rather structural and reactive control of intrinsically unstable carbocations in order to guide the resulting product distribution. Here we employ multiscale modeling within classical and quantum dynamics frameworks to investigate the reaction mechanism in the diterpene synthase CotB2, commencing with the substrate geranyl geranyl diphosphate and terminating with the carbocation precursor to the final product cyclooctat-9-en-7-ol. The 11-step in-enzyme carbocation cascade is compared with the same reaction in the absence of the enzyme. Remarkably, the free energy profiles in gas phase and in CotB2 are surprisingly similar. This similarity contrasts the multitude of strong π-cation, dipole-cation, and ion-pair interactions between all intermediates in the reaction cascade and the enzyme, suggesting a remarkable balance of interactions in CotB2. We ascribe this balance to the similar magnitude of the interactions between the carbocations along the reaction coordinate and the enzyme environment. The effect of CotB2 mutations is studied using multiscale mechanistic docking, machine learning, and X-ray crystallography, pointing the way for future terpene synthase design.

Selective and Effective: Current Progress in Computational Structure-Based Drug Discovery of Targeted Covalent Inhibitors

Targeted covalent inhibitors are currently showing great promise for systems that are normally difficult to target with small molecule therapies. This renewed interest has spurred the refinement of existing computational methods as well as the designof new ones, expanding the toolbox for discovery and optimization of selectiveand effective covalent inhibitors. Commonly applied approaches are covalentdocking methods that predict the conformation of the covalent complex with known residues. More recently, a new predictive method, reactive docking, was developed, building on the growing corpus of data generated by large proteomics experiments. This method was successfully used in several 'inverse drug discovery' programs that use high-throughput techniques to isolate effective compounds based on screening of entire compound libraries based on desired phenotypes.

Crystal Structure and Mechanistic Molecular Modeling Studies of Mycobacterium tuberculosis Diterpene Cyclase Rv3377c

Terpenes make up the largest class of natural products, with extensive chemical and structural diversity. Diterpenes, mostly isolated from plants and rarely prokaryotes, exhibit a variety of important biological activities and valuable applications, including providing antitumor and antibiotic pharmaceuticals. These natural products are constructed by terpene synthases, a class of enzymes that catalyze one of the most complex chemical reactions in biology: converting simple acyclic oligo-isoprenyl diphosphate substrates to complex polycyclic products via carbocation intermediates. Here we obtained the second ever crystal structure of a class II diterpene synthase from bacteria, tuberculosinol pyrophosphate synthase (i.e., Halimadienyl diphosphate synthase, MtHPS, or Rv3377c) from Mycobacterium tuberculosis (Mtb). This enzyme transforms (E,E,E)-geranylgeranyl diphosphate into tuberculosinol pyrophosphate (Halimadienyl diphosphate). Rv3377c is part of the Mtb diterpene pathway along with Rv3378c, which converts tuberculosinol pyrophosphate to 1-tuberculosinyl adenosine (1-TbAd). This pathway was shown to exist only in virulent Mycobacterium species, but not in closely related avirulent species, and was proposed to be involved in phagolysosome maturation arrest. To gain further insight into the reaction pathway and the mechanistically relevant enzyme substrate binding orientation, electronic structure calculation and docking studies of reaction intermediates were carried out. Results reveal a plausible binding mode of the substrate that can provide the information to guide future drug design and anti-infective therapies of this biosynthetic pathway.

Enzymatic control of product distribution in terpene synthases: insights from multiscale simulations

In this opinion, we review some recent work on terpene biosynthesis using multiscale simulation approaches, with special focus on contributions from our group. Terpene synthases generate terpenes employing rich carbocation chemistry, including highly specific ring formations, proton, hydride, methyl, and methylene migrations, followed by reaction quenching. In these enzymes, the main catalytic challenge is not rate enhancement, but rather control of intrinsically reactive carbocations and the resulting product distribution. Herein, we review multiscale simulations of selected mono-, sesqui-, and diterpene synthases. We point to the many tools adopted by terpene synthases to achieve correct substrate fold, carbocation formation, carbocation reaction environment, and reaction quenching. A better understanding of the toolbox employed by terpene synthases is expected to aid in the search for new enzymatic and biomimetic synthetic routes to natural and unnatural terpenes.

Current understanding and biotechnological application of the bacterial diterpene synthase CotB2

CotB2 catalyzes the first committed step in cyclooctatin biosynthesis of the soil bacterium Streptomyces melanosporofaciens. To date, CotB2 represents the best studied bacterial diterpene synthase. Its reaction mechanism has been addressed by isoptope labeling, targeted mutagenesis and theoretical computations in the gas phase, as well as full enzyme molecular dynamic simulations. By X-ray crystallography different snapshots of CotB2 from the open, inactive, to the closed, active conformation have been obtained in great detail, allowing us to draw detailed conclusions regarding the catalytic mechanism at the molecular level. Moreover, numerous alternative geranylgeranyl diphosphate cyclization products obtained by CotB2 mutagenesis have exciting applications for the sustainable production of high value bioactive substances.