Applications and Potential of In Silico Approaches for Psychedelic Chemistry.

Molecular-level investigations of the Central Nervous System have been revolutionized by the development of computational methods, computing power, and capacity advances. These techniques have enabled researchers to analyze large amounts of data from various sources, including genomics, in vivo, and in vitro drug tests. In this review, we explore how computational methods and informatics have contributed to our understanding of mental health disorders and the development of novel drugs for neurological diseases, with a special focus on the emerging field of psychedelics. In addition, the use of state-of-the-art computational methods to predict the potential of drug compounds and bioinformatic tools to integrate disparate data sources to create predictive models is also discussed. Furthermore, the challenges associated with these methods, such as the need for large datasets and the diversity of in vitro data, are explored. Overall, this review highlights the immense potential of computational methods and informatics in Central Nervous System research and underscores the need for continued development and refinement of these techniques and more inclusion of Quantitative Structure-Activity Relationships (QSARs).

Influence of the First Chromophore-Forming Residue on Photobleaching and Oxidative Photoconversion of EGFP and EYFP.

Enhanced green fluorescent protein (EGFP)-one of the most widely applied genetically encoded fluorescent probes-carries the threonine-tyrosine-glycine (TYG) chromophore. EGFP efficiently undergoes green-to-red oxidative photoconversion ("redding") with electron acceptors. Enhanced yellow fluorescent protein (EYFP), a close EGFP homologue (five amino acid substitutions), has a glycine-tyrosine-glycine (GYG) chromophore and is much less susceptible to redding, requiring halide ions in addition to the oxidants. In this contribution we aim to clarify the role of the first chromophore-forming amino acid in photoinduced behavior of these fluorescent proteins. To that end, we compared photobleaching and redding kinetics of EGFP, EYFP, and their mutants with reciprocally substituted chromophore residues, EGFP-T65G and EYFP-G65T. Measurements showed that T65G mutation significantly increases EGFP photostability and inhibits its excited-state oxidation efficiency. Remarkably, while EYFP-G65T demonstrated highly increased spectral sensitivity to chloride, it is also able to undergo redding chloride-independently. Atomistic calculations reveal that the GYG chromophore has an increased flexibility, which facilitates radiationless relaxation leading to the reduced fluorescence quantum yield in the T65G mutant. The GYG chromophore also has larger oscillator strength as compared to TYG, which leads to a shorter radiative lifetime (i.e., a faster rate of fluorescence). The faster fluorescence rate partially compensates for the loss of quantum efficiency due to radiationless relaxation. The shorter excited-state lifetime of the GYG chromophore is responsible for its increased photostability and resistance to redding. In EYFP and EYFP-G65T, the chromophore is stabilized by π-stacking with Tyr203, which suppresses its twisting motions relative to EGFP.

Exploring Peptide⁻Solvent Interactions: A Computational Study.

The dilemma of reconciling the contradictory evidence regarding the conformation of long solvated peptide chains is the so-called "reconciliation problem". Clues regarding the stability of certain conformations likely lie in the electronic structure at the peptide⁻solvent interface, but the peptide⁻solvent interaction is not fully understood. Here, we study the influence of aqueous solvent on peptide conformations by using classical molecular dynamics (MD) and quantum mechanical/molecular mechanical (QM/MM) energy calculations. The model systems include an 11-residue peptide, X 2 A 7 O 2 (XAO), where X, A, and O denote diaminobutyric acid, alanine, and ornithine, respectively, and a 9-mer (Arg-Pro-Pro-Gly-Phe-Ser-Ala-Phe-Lys). Spectroscopic and MD data present conflicting evidence regarding the structure of XAO in water; some results indicate that XAO adopts a polyproline II (P II ) conformation, whereas other findings suggest that XAO explores a range of conformations. To investigate this contradiction, we present here the results of MD simulations of XAO and the 9-mer in aqueous solution, combined with QM/MM energy calculations.

Mechanism investigation of highly selective inhibitors toward phosphodiesterase 5 and 6 via the in vitro calculation and simulation.

Introduction: In clinical practice, phosphodiesterase 5 (PDE5) inhibitors are commonly used to treat erectile dysfunction and pulmonary arterial hypertension. However, due to the high structural similarity between PDE5 and Phosphodiesterase 6 (PDE6), there is a risk that existing drugs will cause off-target effects on PDE6 resulting in visual disorders such as low visual acuity and color blindness. Previous research on the selectivity of PDE5 inhibitors focused on marketed drugs such as sildenafil and tadalafil. Methods: In this study, a highly selective PDE5 inhibitor, ligand3, was used as the subject, and molecular docking, molecular dynamics simulations, MM-GBSA, alanine scanning, and independent gradient model analysis were employed to investigate the biological mechanism underlying the selectivity of PDE5 inhibitors. Results and Discussion: The present work revealed that the binding mode of ligand3 to the PDE5A and PDE6C targets was distinctly different. Ligand3 exhibited stronger coulombic forces when binding to PDE5A, while showing stronger van der waals forces when binding to PDE6C. Ligand3 binds more deeply at the active site of PDE5A than at PDE6C, allowing its side chains to effectively bind to the critical TYR612, whereas in the case of the shallow binding to PDE6C, ligand3 lacks a similar effect. Mechanism investigations of highly selective inhibitors through computational simulation might provide an insight into potent treatment of drugs.

Identification of the protonation and oxidation states of the oxygen-evolving complex in the low-dose X-ray crystal structure of photosystem II.

In photosystem II (PSII), the O3 and O4 sites of the Mn4CaO5 cluster form hydrogen bonds with D1-His337 and a water molecule (W539), respectively. The low-dose X-ray structure shows that these hydrogen bond distances differ between the two homogeneous monomer units (A and B) [Tanaka et al., J. Am Chem. Soc. 2017, 139, 1718]. We investigated the origin of the differences using a quantum mechanical/molecular mechanical (QM/MM) approach. QM/MM calculations show that the short O4-OW539 hydrogen bond (~2.5 Å) of the B monomer is reproduced when O4 is protonated in the S1 state. The short O3-NεHis337 hydrogen bond of the A monomer is due to the formation of a low-barrier hydrogen bond between O3 and doubly-protonated D1-His337 in the overreduced states (S-1 or S-2). It seems plausible that the oxidation state differs between the two monomer units in the crystal.

Quantum Mechanics/Molecular mechanics calculations predict A1, not A2, is present in melanopsin (Opn4m) of red-eared slider turtles (Trachemys scripta elegans).

Melanopsin is a photopigment that plays a role in non-visual, light-driven, cellular processes such as modulation of circadian rhythms, retinal vascular development, and the pupillary light reflex (PLR). In this study, computational methods were used to understand which chromophore is harbored by melanopsin in red-eared slider turtles (Trachemys scripta elegans). In mammals, the vitamin A derivative 11-cis-retinal (A1) is the chromophore, which provides functionality for melanopsin. However, in red-eared slider turtles, a member of the reptilian class, the identity of the chromophore remains unclear. Red-eared slider turtles, similar to other freshwater vertebrates, possess visual pigments that harbor a different vitamin A derivative, 11-cis-3,4-didehydroretinal (A2), making their pigments more sensitive to red-light than blue-light, therefore, suggesting the chromophore to be the A2 derivative instead of the A1. To help resolve the chromophore identity, in this work, computational homology models of melanopsin in red-eared slider turtles were first constructed. Next, quantum mechanics/molecular mechanics (QM/MM) calculations were carried out to compare how A1 and A2 derivatives bind to melanopsin. Time dependent density functional theory (TDDFT) calculations were then used to determine the excitation energy of the pigments. Lastly, calculated excitation energies were compared to experimental spectral sensitivity data from responses by the irises of red-eared sliders. Contrary to what was expected, our results suggest that melanopsin in red-eared slider turtles is more likely to harbor the A1 chromophore than the A2. Furthermore, a glutamine (Q622.56) and tyrosine (Y853.28) residue in the chromophore binding pocket are shown to play a role in the spectral tuning of the chromophore.

Computational modeling of carbohydrate processing enzymes reactions.

Carbohydrate processing enzymes are of biocatalytic interest. Glycoside hydrolases and the recently discovered lytic polysaccharide monooxygenase for their use in biomass degradation to obtain biofuels or valued chemical entities. Glycosyltransferases or engineered glycosidases and phosphorylases for the synthesis of carbohydrates and glycosylated products. Quantum mechanics-molecular mechanics (QM/MM) methods are highly contributing to establish their different chemical reaction mechanisms. Other computational methods are also used to study enzyme conformational changes, ligand pathways, and processivity, e.g. for processive glycosidases like cellobiohydrolases. There is still a long road to travel to fully understand the role of conformational dynamics in enzyme activity and also to disclose the variety of reaction mechanisms these enzymes employ. Additionally, computational tools for enzyme engineering are beginning to be applied to evaluate substrate specificity or aid in the design of new biocatalysts with increased thermostability or tailored activity, a growing field where molecular modeling is finding its way.

Structural and functional characterization of nylon hydrolases.

Biodegradation of synthetic polymers is recognized as a useful way to reduce their environmental load and pollution, loss of natural resources, extensive energy consumption, and generation of greenhouse gases. The potential use of enzymes responsible for the degradation of the targeted polymers is an effective approach which enables the conversion of the used polymers to original monomers and/or other useful compounds. In addition, the enzymes are expected to be applicable in industrial processes such as improving the surface structures of the polymers. Especially, conversion of the solid polymers to soluble oligomers/monomers is a key step for the biodegradation of the polymers. Regarding the hydrolysis of polyamides, three enzymes, 6-aminohexanoate-cyclic-dimer hydrolase (NylA), 6-aminohexanoate-dimer hydrolase (NylB), and 6-aminohexanoate-oligomer endo-hydrolase (nylon hydrolase, NylC), are found in several bacterial strains. In this chapter, we describe our approach for the screening of microorganisms which degrade nylons and related compounds; preparation of substrates; assay of hydrolytic activity for soluble and insoluble substrates; and X-ray crystallographic and computational approaches for analysis of structure and catalytic mechanisms of the nylon-degrading enzymes.

Design and SAR Analysis of Covalent Inhibitors Driven by Hybrid QM/MM Simulations.

Quantum mechanics/molecular mechanics (QM/MM) hybrid technique is emerging as a reliable computational method to investigate and characterize chemical reactions occurring in enzymes. From a drug discovery perspective, a thorough understanding of enzyme catalysis appears pivotal to assist the design of inhibitors able to covalently bind one of the residues belonging to the enzyme catalytic machinery. Thanks to the current advances in computer power, and the availability of more efficient algorithms for QM-based simulations, the use of QM/MM methodology is becoming a viable option in the field of covalent inhibitor design. In the present review, we summarized our experience in the field of QM/MM simulations applied to drug design problems which involved the optimization of agents working on two well-known drug targets, namely fatty acid amide hydrolase (FAAH) and epidermal growth factor receptor (EGFR). In this context, QM/MM simulations gave valuable information in terms of geometry (i.e., of transition states and metastable intermediates) and reaction energetics that allowed to correctly predict inhibitor binding orientation and substituent effect on enzyme inhibition. What is more, enzyme reaction modelling with QM/MM provided insights that were translated into the synthesis of new covalent inhibitor featured by a unique combination of intrinsic reactivity, on-target activity, and selectivity.

The catalytic role of water in the binding site of l,d-transpeptidase 2 within acylation mechanism: A QM/MM (ONIOM) modelling.

Mycobacterium tuberculosis is the causative agent of Tuberculosis. Formation of 3 → 3 crosslinks in the peptidoglycan layer of M. tuberculosis is catalyzed by l,d-transpeptidases. These enzymes can confer resistance against classical ß-lactams that inhibit enzymes that generate 4 → 3 peptidoglycan crosslinks. The focus of this study is to investigate the catalytic role of water molecules in the acylation mechanism of the ß-lactam ring within two models; 4- and 6-membered ring systems using two-layered our Own N-layer integrated Molecular Mechanics ONIOM (B3LYP/6-311++G(2d,2p): AMBER) model. The obtained thermochemical parameters revealed that the 6-membered ring model best describes the inhibition mechanism of acylation which indicates the role of water in the preference of 6-membered ring reaction pathway. This finding is in accordance with experimental data for the rate-limiting step of cysteine protease with the same class of inhibitor and binding affinity for both inhibitors. As expected, the ΔG# results also reveal that the 6-membered ring reaction pathway is the most favourable. The electrostatic potential (ESP) and the natural bond orbital analysis (NBO) showed stronger interactions in 6-membered ring transition state (TS-6) mechanism involving water in the active site of the enzyme. This study could be helpful in the development of novel antibiotics against l,d-transpeptidase.

Discrete and continuum modeling of solvent effects in a twisted intramolecular charge transfer system: The 4-N,N-dimethylaminobenzonitrile (DMABN) molecule.

The 4-N,N-dimethylaminobenzonitrile (DMABN) molecule is a prototypical system displaying twisted intramolecular (TICT) charge transfer effects. The ground and the first four electronic excited states (S1-S4) in gas phase and upon solvation were studied. Charge transfer values as function of the torsion angle between the donor group (dimethylamine) and the acceptor moiety (benzonitrile) were explicitly computed. Potential energy curves were also obtained. The algebraic diagrammatic construction method at the second-order [ADC(2)] ab initio wave function was employed. Three solvents of increased polarities (benzene, DMSO and water) were investigated using discrete (average solvent electrostatic configuration - ASEC) and continuum (conductor-like screening model - COSMO) models. The results for the S3 and S4 excited states and the S1-S4 charge transfer curves were not previously available in the literature. Electronic gas phase and solvent vertical spectra are in good agreement with previous theoretical and experimental results. In the twisted (90°) geometry the optical oscillator strengths have negligible values even for the S2 bright state. Potential energy curves show two distinct pairs of curves intersecting at decreasing angles or not crossing in the more polar solvents. Charge transfer and electric dipole values allowed the rationalization of these results. The former effects are mostly independent of the solvent model and polarity. Although COSMO and ASEC solvent models mostly lead to similar results, there is an important difference: some crossings of the excitation energy curves appear only in the ASEC solvation model, which has important implications to the photochemistry of DMABN.

Mechanisms of histone lysine-modifying enzymes: A computational perspective on the role of the protein environment.

Epigenetic pathways are involved in a wide range of diseases, including cancer and neurological disorders. Specifically, histone modifying and reading processes are the most broadly studied and are targeted by several licensed drugs. Although there have been significant advances in understanding the mechanistic aspects underlying epigenetic regulation, the development of selective small-molecule inhibitors remains a challenge. Experimentally, it is generally difficult to elucidate the atomistic basis for substrate recognition, as well as the sequence of events involved in binding and the subsequent chemical processes. In this regard, computational modelling is particularly valuable, since it can provide structural features (including transition state structures along with kinetic and thermodynamic parameters) that enable both qualitative and quantitative evaluation of the mechanistic details involved. Here, we summarize knowledge gained from computational modelling studies elucidating the role of the protein environment in histone-lysine modifying and reading mechanisms. We give a perspective on the importance of calculations to aid and advance the understanding of these processes and for the future development of selective inhibitors for epigenetic regulators.