Concerted hydrolysis mechanism of HIV-1 natural substrate against subtypes B and C-SA PR: insight through molecular dynamics and hybrid QM/MM studies

A mechanistic insight for the biosynthesis of N,N-dimethyltryptamine: An ONIOM theoretical approach

Psychoactive natural products are potent serotonergic agonists capable of modulating brain functions such as memory and cognition. These substances have shown therapeutic potential for treating various mental disorders. The fact that N,N-dimethyltryptamine (DMT) is produced endogenously in several plants and animals, including humans, makes it particularly attractive. As an amino acid-derived alkaloid, the DMT biosynthetic pathway is part of the L-tryptophan biochemical cascade and can be divided into the decarboxylation by an aromatic L-amino acid decarboxylase (AADC) for tryptamine formation and the subsequent double-methylation by the indolethylamine-N-methyltransferase (INMT) through the cofactor S-adenosyl-L-methionine (SAM), a methyl donor. Unlike the decarboxylation mechanism of L-tryptophan, the molecular details of the double methylation of tryptamine have not been elucidated. Therefore, we propose an in silico model using molecular dynamics (MD), non-covalent interaction index (NCI) and density functional theory (DFT) calculations with the ONIOM QM:MM B3LYP/6-31+G(d,p):MM/UFF level of theory. Based on the obtained energetic data, the potential energy surface (PES) indicates an SN2 mechanism profile, with the second methylation energy barrier being the rate-limiting step with δG‡=60kJ∙mol-1 larger than the previous methylation, following the NCI analysis showing more repulsive interactions for the second transition state. In addition, the hybridization information of each reaction step provides geometric details about the double-methylation.

Ni2+ and Cu2+ complexes of N-(2,6-dichlorophenyl)-N-mesityl formamidine dithiocarbamate structural and functional properties as CYP3A4 potential substrates

Metal compounds continued to attract diverse applications due to their malleability in several capacities. In this study, we present our findings on the crystal structures and functional properties of Ni2+ and Cu2+ complexes of N'-(2,6-dichlorophenyl)-N-mesitylformamidine dithiocarbamate (L) comprising [Ni-(L)2] (1) and [Cu-(L)2] (2) with a four-coordinate metal center. We established the two complex structures through 1H and 13C nuclear magnetic resonance (NMR), elemental, and single-crystal X-ray analysis. The analyses showed that the two complexes are isomorphous, having P21/c as a space group and a unit-cell similarity index (π) of 0.002. The two complexes conform to a distorted square planar geometry around the metal centers. The calculated and experimental data, including bond lengths, angles, and NMR values, are similar. Hirshfeld surface analysis revealed the variational contribution of the different types of intermolecular contacts driven by the crystal lattice of the two solvated complexes. Our knowledge of the potential biological implication of these structures enabled us to probe the compounds as prospective CYP3A4 inhibitors. This approach mimics current trends in pharmaceutical design and biomedicine by incorporating potentially active molecules into various media to predict their biological efficacies. The simulations show appreciable binding of compounds 1 and 2 to CYP3A4 with average interaction energies of -97 and -87 kcal/mol, respectively. The protein attains at least five conformational states in the three studied models using a Gaussian Mixture Model-based clustering and free energy prediction. Electric field analysis shows the crucial residues to substrate binding at the active site, enabling CYP3A4 structure to function prediction. The predicted inhibition with these Ni2+ and Cu2+ complexes indicates that CYP3A4 overexpression in a diseased state like cancer would reduce, thereby increasing the chemotherapeutic compounds' shelf-lives for adsorption. This multidimensional study addresses various aspects of molecular metal electronics, including their application as substrate-mimicking inhibitors. The outcome would enable further research on bio-metal compounds of critical potential.

Local electronic structure analysis by ab initio elongation method: A benchmark using DNA block polymers

The ab initio elongation (ELG) method based on a polymerization concept is a feasible way to perform linear-scaling electronic structure calculations for huge aperiodic molecules while maintaining computational accuracy. In the method, the electronic structures are sequentially elongated by repeating (1) the conversion of canonical molecular orbitals (CMOs) to region-localized MOs (RLMOs), that is, active RLMOs localized onto a region close to an attacking monomer or frozen RLMOs localized onto the remaining region, and the subsequent (2) partial self-consistent-field calculations for an interaction space composed of the active RLMOs and the attacking monomer. For each ELG process, one can obtain local CMOs for the interaction space and the corresponding local orbital energies. Local site information, such as the local highest-occupied/lowest-unoccupied MOs, can be acquired with linear-scaling efficiency by correctly including electronic effects from the frozen region. In this study, we performed a local electronic structure analysis using the ELG method for various DNA block polymers with different sequential patterns. This benchmark aimed to confirm the effectiveness of the method toward the efficient detection of a singular local electronic structure in unknown systems as a future practical application. We discussed the high-throughput efficiency of our method and proposed a strategy to detect singular electronic structures by combining with a machine learning technique.

Molecular dynamics of the viral life cycle: progress and prospects

Molecular dynamics (MD) simulations across spatiotemporal resolutions are widely applied to study viruses and represent the central technique uniting the field of computational virology. We discuss the progress of MD in elucidating the dynamics of the viral life cycle, including the status of modeling intact extracellular virions and leveraging advanced simulations to mimic active life cycle processes. We further remark on the prospects of MD for continued contributions to the basic science characterization of viruses, especially given the increasing availability of high-quality experimental data and supercomputing power. Overall, integrative computational methods that are closely guided by experiments are unmatched in the level of detail they provide, enabling-now and in the future-new discoveries relevant to thwarting viral infection.

Tailored Modeling of Rivastigmine Derivatives as Dual Acetylcholinesterase and Butyrylcholinesterase Inhibitors for Alzheimer's Disease Treatment

Rational modification of known drug candidates to design more potent ones using computational methods has found application in drug design, development, and discovery. Herein, we integrate computational and theoretical methodologies to unveil rivastigmine derivatives as dual inhibitors of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) for Alzheimer's disease (AD) management. The investigation entails pharmacokinetics screening, density functional theory (DFT) mechanistic study, molecular docking, and molecular dynamics (MD) simulation. We designed over 20 rivastigmine substituents, subject them to some analyses, and identified RL2 with an appreciable blood-brain barrier score and no permeability glycoprotein binding. The compound shows higher acylation energy and a favored binding affinity to the cholinesterase enzymes. RL2 interacts with the AChE and BuChE active sites showing values of -41.1/-39.5 kcal mol^-1 while rivastigmine binds with -32.7/-30.7 kcal mol^-1 for these enzymes. The study revealed RL2 (4-fluorophenyl rivastigmine) as a potential dual inhibitor for AChE and BuChE towards Alzheimer's disorder management.

Alzheimer's Disease and β-Secretase Inhibition: An Update With a Focus on Computer-Aided Inhibitor Design

INTRODUCTION

Alzheimer's disease (AD) is an intensifying neurodegenerative illness due to its irreversible nature. Identification of β-site amyloid precursor protein (APP) cleaving enzyme1 (BACE1) has been a significant medicinal focus towards AD treatment, and this has opened ground for several investigations. Despite the numerous works in this direction, no BACE1 inhibitor has made it to the final approval stage as an anti-AD drug.

METHOD

We provide an introductory background of the subject with a general overview of the pathogenesis of AD. The review features BACE1 inhibitor design and development with a focus on some clinical trials and discontinued drugs. Using the topical keywords BACE1, inhibitor design, and computational/theoretical study in the Web of Science and Scopus database, we retrieved over 49 relevant articles. The search years are from 2010 and 2020, with analysis conducted from May 2020 to March 2021.

RESULTS AND DISCUSSION

Researchers have employed computational methodologies to unravel potential BACE1 inhibitors with a significant outcome. The most used computer-aided approach in BACE1 inhibitor design and binding/interaction studies are pharmacophore development, quantitative structure-activity relationship (QSAR), virtual screening, docking, and molecular dynamics (MD) simulations. These methods, plus more advanced ones including quantum mechanics/molecular mechanics (QM/MM) and QM, have proven substantial in the computational framework for BACE1 inhibitor design. Computational chemists have embraced the incorporation of in vitro assay to provide insight into the inhibition performance of identified molecules with potential inhibition towards BACE1. Significant IC₅₀ values up to 50 nM, better than clinical trial compounds, are available in the literature.

CONCLUSION

The continuous failure of potent BACE1 inhibitors at clinical trials is attracting many queries prompting researchers to investigate newer concepts necessary for effective inhibitor design. The considered properties for efficient BACE1 inhibitor design seem enormous and require thorough scrutiny. Lately, researchers noticed that besides appreciable binding affinity and blood-brain barrier (BBB) permeation, BACE1 inhibitor must show low or no affinity for permeability-glycoprotein. Computational modeling methods have profound applications in drug discovery strategy. With the volume of recent in silico studies on BACE1 inhibition, the prospect of identifying potent molecules that would reach the approved level is feasible. Investigators should try pushing many of the identified BACE1 compounds with significant anti-AD properties to preclinical and clinical trial stages. We also advise computational research on allosteric inhibitor design, exosite modeling, and multisite inhibition of BACE1. These alternatives might be a solution to BACE1 drug discovery in AD therapy.

Mechanisms of Proteolytic Enzymes and Their Inhibition in QM/MM Studies

Experimental evidence for enzymatic mechanisms is often scarce, and in many cases inadvertently biased by the employed methods. Thus, apparently contradictory model mechanisms can result in decade long discussions about the correct interpretation of data and the true theory behind it. However, often such opposing views turn out to be special cases of a more comprehensive and superior concept. Molecular dynamics (MD) and the more advanced molecular mechanical and quantum mechanical approach (QM/MM) provide a relatively consistent framework to treat enzymatic mechanisms, in particular, the activity of proteolytic enzymes. In line with this, computational chemistry based on experimental structures came up with studies on all major protease classes in recent years; examples of aspartic, metallo-, cysteine, serine, and threonine protease mechanisms are well founded on corresponding standards. In addition, experimental evidence from enzyme kinetics, structural research, and various other methods supports the described calculated mechanisms. One step beyond is the application of this information to the design of new and powerful inhibitors of disease-related enzymes, such as the HIV protease. In this overview, a few examples demonstrate the high potential of the QM/MM approach for sophisticated pharmaceutical compound design and supporting functions in the analysis of biomolecular structures.

Hydrogen bonding catalysis by water in epoxide ring opening reaction

Water can act as catalyst is perhaps the most intriguing property reported of this molecule in the last decade. However, despite being an integral part of many enzyme structures, the role of water in catalyzing enzymatic reactions remains sparsely studied. In a recent study, we have shown that the epoxide ring opening in aspartate proteases follows a two-step process involving water. In this work, we attempt to unravel the electronic basis of the co-catalytic role of water in the epoxide ring opening reaction by employing high-level quantum mechanical calculations at M06-2X/6-31+G(d,p) level of accuracy. Our computed electron density and its reduced gradient show that water anchor the reactant molecules through strong H-bond bridges. In addition, the strong ionizing power of water allows better charge delocalization to stabilize the transition states and oxyanion intermediate. Electrostatic analyses suggest greater charge transfer from the aspartates to the epoxide in the transition state, which is found to be exergonic in nature rendering a low-barrier reaction compared to a control system where water was omitted in the reaction field. This elucidated mechanism at electronic level could promote further research to search for the co-catalytic role of water in other enzymes.

Exploring the concerted mechanistic pathway for HIV-1 PR-substrate revealed by umbrella sampling simulation

HIV-1 protease (HIV-1 PR) is an essential enzyme for the replication process of its virus, and therefore considered an important target for the development of drugs against the acquired immunodeficiency syndrome (AIDS). Our previous study shows that the catalytic mechanism of subtype B/C-SA HIV-1 PR follows a one-step concerted acyclic hydrolysis reaction process using a two-layered ONIOM B3LYP/6-31++G(d,p) method. This present work is aimed at exploring the proposed mechanism of the proteolysis catalyzed by HIV-1 PR and to ensure our proposed mechanism is not an artefact of a single theoretical technique. Hence, we present umbrella sampling method that is suitable for calculating potential mean force (PMF) for non-covalent ligand/substrate-enzyme association/dissociation interactions which provide thermodynamic details for molecular recognition. The free activation energy results were computed in terms of PMF analysis within the hybrid QM(DFTB)/MM approach. The theoretical findings suggest that the proposed mechanism corresponds in principle with experimental data. Given our observations, we suggest that the QM/MM MD method can be used as a reliable computational technique to rationalize lead compounds against specific targets such as the HIV-1 protease.

Evaluating the Performance of a Non-Bonded Cu2+ Model Including Jahn-Teller Effect into the Binding of Tyrosinase Inhibitors

Tyrosinase (TYR) is a metalloenzyme classified as a type-3 copper protein, which is involved in the synthesis of melanin through a catalytic process beginning with the conversion of the amino acid l-Tyrosine (l-Tyr) to l-3,4-dihydroxyphenylalanine (l-DOPA). It plays an important role in the mechanism of melanogenesis in various organisms including mammals, plants, and fungi. Herein, we used a combination of computational molecular modeling techniques including molecular dynamic (MD) simulations and the linear interaction energy (LIE) model to evaluate the binding free energy of a set of analogs of kojic acid (KA) in complex with TYR. For the MD simulations, we used a dummy model including the description of the Jahn–Teller effect for Cu²⁺ ions in the active site of this enzyme. Our results show that the LIE model predicts the TYR binding affinities of the inhibitor in close agreement to experimental results. Overall, we demonstrate that the classical model provides a suitable description of the main interactions between analogs of KA and Cu²⁺ ions in the active site of TYR.