Assigning the protonation states of the key aspartates in β-Secretase using QM/MM X-ray structure refinement

Selective Protonation of Catalytic Dyad for γ-Secretase-Mediated Hydrolysis Revealed by Multiscale Simulations

γ-Secretase plays a crucial role in producing disease-related amyloid-β proteins by cleaving the amyloid precursor protein (APP). The enzyme employs its catalytic dyad containing two aspartates (Asp257 and Asp385) to hydrolyze the substrate by a general acid-base catalytic mechanism, necessitating monoprotonation of the two aspartates for efficient hydrolysis. However, the precise protonation states of the aspartates remain uncertain. In this study, we employed a multiscale computational approach to investigate the dependence of the catalytic efficiency of γ-secretase on the protonation states of its catalytic dyad. Over 200 ms unbiased atomistic simulations of the substrate-enzyme complex reveal diverse orientations of the scissile bond of the bound substrate and accessible structural ensembles of the catalytic dyad with Asp257-Asp385 distances fluctuating between 4 and 10 Å. With a quantum mechanics/molecular mechanics (QM/MM) approach accelerated by enhanced sampling techniques, we find that the first step of the hydrolysis reaction, i.e., the formation of a gem-diol intermediate, experiences a higher reaction barrier by ∼2 kcal/mol when Asp385 is protonated. Furthermore, we find that Arg269 of the enzyme is most likely responsible for this preference of the protonation state: its basic side chain is spatially close to that of Asp257 and specifically stabilizes the transition state electrostatically when Asp257 is protonated. Collectively, our study suggests that Asp257 is likely the favored protonation site for APP cleavage by γ-secretase.

Enzyme-substrate hybrid β-sheet controls geometry and water access to the γ-secretase active site

γ-Secretase is an aspartyl intramembrane protease that cleaves the amyloid precursor protein (APP) involved in Alzheimer's disease pathology and other transmembrane proteins. Substrate-bound structures reveal a stable hybrid β-sheet immediately following the substrate scissile bond consisting of β1 and β2 from the enzyme and β3 from the substrate. Molecular dynamics simulations and enhanced sampling simulations demonstrate that the hybrid β-sheet stability is strongly correlated with the formation of a stable cleavage-compatible active geometry and it also controls water access to the active site. The hybrid β-sheet is only stable for substrates with 3 or more C-terminal residues beyond the scissile bond. The simulation model allowed us to predict the effect of Pro and Phe mutations that weaken the formation of the hybrid β-sheet which were confirmed by experimental testing. Our study provides a direct explanation why γ-secretase preferentially cleaves APP in steps of 3 residues and how the hybrid β-sheet facilitates γ-secretase proteolysis.

Combining crystallography with quantum mechanics

In standard crystallographic refinement of biomacromolecules, the crystallographic raw data are supplemented by empirical restraints that ensure that the structure makes chemical sense. These restraints are typically accurate for amino acids and nucleic acids, but less so for cofactors, substrates, inhibitors, ligands and metal sites. In quantum refinement, this potential is replaced by more accurate quantum mechanical (QM) calculations. Several implementations have been presented, differing in the level of QM and whether it is used for the entire structure or only for a site of particular interest. It has been shown that the method can improve and correct errors in crystal structures and that it can be used to determine protonation and tautomeric states of various ligands and to decide what is really seen in the structure by refining different interpretations and using standard crystallographic and QM quality measures to decide which fits the structure best.

User-Friendly Quantum Mechanics: Applications for Drug Discovery

Quantum mechanics (QM) methods provide a fine description of receptor-ligand interactions and of chemical reactions. Their use in drug design and drug discovery is increasing, especially for complex systems including metal ions in the binding sites, for the design of highly selective inhibitors, for the optimization of bi-specific compounds, to understand enzymatic reactions, and for the study of covalent ligands and prodrugs. They are also used for generating molecular descriptors for predictive QSAR/QSPR models and for the parameterization of force fields. Thanks to the continuous increase of computational power offered by GPUs and to the development of sophisticated algorithms, QM methods are becoming part of the standard tools used in computer-aided drug design (CADD). We present the most used QM methods and software packages, and we discuss recent representative applications in drug design and drug discovery.

Including crystallographic symmetry in quantum-based refinement: Q|R#2

Three-dimensional structure models refined using low-resolution data from crystallographic or electron cryo-microscopy experiments can benefit from high-quality restraints derived from quantum-chemical methods. However, nonperiodic atom-centered quantum-chemistry codes do not inherently account for nearest-neighbor interactions of crystallographic symmetry-related copies in a satisfactory way. Here, these nearest-neighbor effects have been included in the model by expanding to a super-cell and then truncating the super-cell to only include residues from neighboring cells that are interacting with the asymmetric unit. In this way, the fragmentation approach can adequately and efficiently include nearest-neighbor effects. It has previously been shown that a moderately sized X-ray structure can be treated using quantum methods if a fragmentation approach is applied. In this study, a target protein (PDB entry 4gif) was partitioned into a number of large fragments. The use of large fragments (typically hundreds of atoms) is tractable when a GPU-based package such as TeraChem is employed or cheaper (semi-empirical) methods are used. The QM calculations were run at the HF-D3/6-31G level. The models refined using a recently developed semi-empirical method (GFN2-xTB) were compared and contrasted. To validate the refinement procedure for a non-P1 structure, a standard set of crystallographic metrics were used. The robustness of the implementation is shown by refining 13 additional protein models across multiple space groups and a summary of the refinement metrics is presented.

Dietary Polyphenols: A Multifactorial Strategy to Target Alzheimer's Disease

Ageing is an inevitable fundamental process for people and is their greatest risk factor for neurodegenerative disease. The ageing processes bring changes in cells that can drive the organisms to experience loss of nutrient sensing, disrupted cellular functions, increased oxidative stress, loss of cellular homeostasis, genomic instability, accumulation of misfolded protein, impaired cellular defenses and telomere shortening. Perturbation of these vital cellular processes in neuronal cells can lead to life threatening neurological disorders like Alzheimer's Disease, Parkinson's Disease, Huntington's Disease, Lewy body dementia, etc. Alzheimer's Disease is the most frequent cause of deaths in the elderly population. Various therapeutic molecules have been designed to overcome the social, economic and health care burden caused by Alzheimer's Disease. Almost all the chemical compounds in clinical practice have been found to treat symptoms only limiting them to palliative care. The reason behind such imperfect drugs may result from the inefficiencies of the current drugs to target the cause of the disease. Here, we review the potential role of antioxidant polyphenolic compounds that could possibly be the most effective preventative strategy against Alzheimer's Disease.

Predicting protein-ligand binding affinity and correcting crystal structures with quantum mechanical calculations: lactate dehydrogenase A

Accurately computing the geometry and energy of host-guest and protein-ligand interactions requires a physically accurate description of the forces in action. Quantum mechanics can provide this accuracy but the calculations can require a prohibitive quantity of computational resources. The size of the calculations can be reduced by including only the atoms of the receptor that are in close proximity to the ligand. We show that when combined with log P values for the ligand (which can be computed easily) this approach can significantly improve the agreement between computed and measured binding energies. When the approach is applied to lactate dehydrogenase A, it can make quantitative predictions about conformational, tautomeric and protonation state preferences as well as stereoselectivity and even identifies potential errors in structures deposited in the Protein Data Bank for this enzyme. By broadening the evidence base for these structures from only the diffraction data, more chemically realistic structures can be proposed.

Comprehensive review of mechanisms of pathogenesis involved in Alzheimer's disease and potential therapeutic strategies

AD is a progressive neurodegenerative disorder and a leading cause of dementia in an aging population worldwide. The enormous challenge which AD possesses to global healthcare makes it as urgent as ever for the researchers to develop innovative treatment strategies to fight this disease. An in-depth analysis of the extensive available data associated with the AD is needed for a more comprehensive understanding of underlying molecular mechanisms and pathophysiological pathways associated with the onset and progression of the AD. The currently understood pathological and biochemical manifestations include cholinergic, Aβ, tau, excitotoxicity, oxidative stress, ApoE, CREB signaling pathways, insulin resistance, etc. However, these hypotheses have been criticized with several conflicting reports for their involvement in the disease progression. Several issues need to be addressed such as benefits to cost ratio with cholinesterase therapy, the dilemma of AChE selectivity over BChE, BBB permeability of peptidic BACE-1 inhibitors, hurdles related to the implementation of vaccination and immunization therapy, and clinical failure of candidates related to newly available targets. The present review provides an insight to the different molecular mechanisms involved in the development and progression of the AD and potential therapeutic strategies, enlightening perceptions into structural information of conventional and novel targets along with the successful applications of computational approaches for the design of target-specific inhibitors.

G-score: A function to solve the puzzle of modeling the protonation states of β-secretase binding pocket

The population density concept has emerged as a proposal for the analysis of molecular dynamics results, the key characteristic of population density is the evaluation of the simultaneous occurrence of a set of relevant parameters for a system. However, despite its statistical strength, selection of the tolerance level for the comparison of different models may appear as arbitrary. This work introduces the G-score, a function which summarizes and categorizes the results of population density analysis. Additionally, it incorporates parameters based on rmsd and dihedral angles, besides the protein-protein and protein-ligand interatomic distances conventionally used, which complement each other to provide a better description of the behavior of the system. These newly-proposed tools were applied to determine the most probable protonation state of the aspartic dyad of BACE1, Asp93 and Asp289, in the presence of three types of transition state inhibitors namely: reduced amides, tertiary carbinamines and hydroxyethylamines. The results show a full agreement between G-score values and population density charts, with the advantage of allowing a quick and direct comparison among all the considered models. We anticipate that the simplicity of calculating the parameters employed in this study will permit the extensive use of population density and the G-score for other molecular systems.

Quantum Crystallography: Current Developments and Future Perspectives

Crystallography and quantum mechanics have always been tightly connected because reliable quantum mechanical models are needed to determine crystal structures. Due to this natural synergy, nowadays accurate distributions of electrons in space can be obtained from diffraction and scattering experiments. In the original definition of quantum crystallography (QCr) given by Massa, Karle and Huang, direct extraction of wavefunctions or density matrices from measured intensities of reflections or, conversely, ad hoc quantum mechanical calculations to enhance the accuracy of the crystallographic refinement are implicated. Nevertheless, many other active and emerging research areas involving quantum mechanics and scattering experiments are not covered by the original definition although they enable to observe and explain quantum phenomena as accurately and successfully as the original strategies. Therefore, we give an overview over current research that is related to a broader notion of QCr, and discuss options how QCr can evolve to become a complete and independent domain of natural sciences. The goal of this paper is to initiate discussions around QCr, but not to find a final definition of the field.

Solving the scalability issue in quantum-based refinement: Q|R#1

Accurately refining biomacromolecules using a quantum-chemical method is challenging because the cost of a quantum-chemical calculation scales approximately as nm, where n is the number of atoms and m (≥3) is based on the quantum method of choice. This fundamental problem means that quantum-chemical calculations become intractable when the size of the system requires more computational resources than are available. In the development of the software package called Q|R, this issue is referred to as Q|R#1. A divide-and-conquer approach has been developed that fragments the atomic model into small manageable pieces in order to solve Q|R#1. Firstly, the atomic model of a crystal structure is analyzed to detect noncovalent interactions between residues, and the results of the analysis are represented as an interaction graph. Secondly, a graph-clustering algorithm is used to partition the interaction graph into a set of clusters in such a way as to minimize disruption to the noncovalent interaction network. Thirdly, the environment surrounding each individual cluster is analyzed and any residue that is interacting with a particular cluster is assigned to the buffer region of that particular cluster. A fragment is defined as a cluster plus its buffer region. The gradients for all atoms from each of the fragments are computed, and only the gradients from each cluster are combined to create the total gradients. A quantum-based refinement is carried out using the total gradients as chemical restraints. In order to validate this interaction graph-based fragmentation approach in Q|R, the entire atomic model of an amyloid cross-β spine crystal structure (PDB entry 2oNA) was refined.

A PM7 dynamic residue-ligand interactions energy landscape of the BACE1 inhibitory pathway by hydroxyethylamine compounds. Part I: The flap closure process

BACE1 is an enzyme of scientific interest because it participates in the progression of Alzheimer's disease. Hydroxyethylamines (HEAs) are a family of compounds which exhibit inhibitory activity toward BACE1 at a nanomolar level, favorable pharmacokinetic properties and oral bioavailability. The first step in the inhibition of BACE1 by HEAs consists of their entrance into the protease active site and the resultant conformational change in the protein, from Apo to closed form. These two conformations differ in the position of an antiparallel loop (called the flap) which covers the entrance to the catalytic site. For BACE1, closure of this flap is vital to its catalytic activity and to inhibition of the enzyme due to the new interactions thereby formed with the ligand. In the present study a dynamic energy landscape of residue-ligand interaction energies (ReLIE) measured for 112 amino acids in the BACE1 active site and its immediate vicinity during the closure of the flap induced by 8 HEAs of different inhibitory power is presented. A total of 6.272 million ReLIE calculations, based on the PM7 semiempirical method, provided a deep and quantitative view of the first step in the inhibition of the aspartyl protease. The information suggests that residues Asp93, Asp289, Thr292, Thr293, Asn294 and Arg296 are anchor points for the ligand, accounting for approximately 45% of the total protein-ligand interaction. Additionally, flap closure improved the BACE1-HEA interaction by around 25%. Furthermore, the inhibitory activity of HEAs could be related to the capacity of these ligands to form said anchor point interactions and maintain them over time: the lack of some of these anchor interactions delayed flap closure or impeded it completely, or even caused the flap to reopen. The methodology employed here could be used as a tool to evaluate future structural modifications which lead to improvements in the favorability and stability of BACE1-HEA ReLIEs, aiding in the design of better inhibitors.

Quantum crystallography

Approximate wavefunctions can be improved by constraining them to reproduce observations derived from diffraction and scattering experiments. Conversely, charge density models, incorporating electron-density distributions, atomic positions and atomic motion, can be improved by supplementing diffraction experiments with quantum chemically calculated, tailor-made electron densities (form factors). In both cases quantum chemistry and diffraction/scattering experiments are combined into a single, integrated tool. The development of quantum crystallographic research is reviewed. Some results obtained by quantum crystallography illustrate the potential and limitations of this field.

Q|R: quantum-based refinement

Quantum-based refinement utilizes chemical restraints derived from quantum-chemical methods instead of the standard parameterized library-based restraints used in refinement packages. The motivation is twofold: firstly, the restraints have the potential to be more accurate, and secondly, the restraints can be more easily applied to new molecules such as drugs or novel cofactors. Here, a new project called Q|R aimed at developing quantum-based refinement of biomacromolecules is under active development by researchers at Shanghai University together with PHENIX developers. The central focus of this long-term project is to develop software that is built on top of open-source components. A development version of Q|R was used to compare quantum-based refinements with standard refinement using a small model system.

A molecular dynamics study of the BACE1 conformational change from Apo to closed form induced by hydroxyethylamine derived compounds

BACE1 is an aspartyl protease which is a therapeutic target for Alzheimer's disease (AD) because of its participation in the rate-limiting step in the production of Aβ-peptide, the accumulation of which produces senile plaques and, in turn, the neurodegenerative effects associated with AD. The active site of this protease is composed in part by two aspartic residues (Asp93 and Asp289). Additionally, the catalytic site has been found to be covered by an antiparallel hairpin loop called the flap. The dynamics of this flap are fundamental to the catalytic function of the enzyme. When BACE1 is inactive (Apo), the flap adopts an open conformation, allowing a substrate or inhibitor to access the active site. Subsequent interaction with the ligand induces flap closure and the stabilization of the macromolecular complex. Further, the protonation state of the aspartic dyad is affected by the chemical nature of the species entering the active site, so that appropriate selection of protonation states for the ligand and the catalytic residues will permit the elucidation of the inhibitory pathway for BACE1. In the present study, comparative analysis of different combinations of protonation states for the BACE1-hydroxyethylamine (HEA) system is reported. HEAs are potent inhibitors of BACE1 with favorable pharmacological and kinetic properties, as well as oral bioavailability. The results of Molecular Dynamics (MD) simulations and population density calculations using 8 different parameters demonstrate that the LnAsp289 configuration (HEA with a neutral amine and the Asp289 residue protonated) is the only one which permits the expected conformational change in BACE1, from apo to closed form, after flap closure. Additionally, differences in their capacities to establish and maintain interactions with residues such as Asp93, Gly95, Thr133, Asp289, Gly291, and Asn294 during this step allow differentiation among the inhibitory activities of the HEAs. The results and methodology here reported will serve to elucidate the inhibitory pathway of other families of compounds that act as BACE1 inhibitors, as well as the design of better leader compounds for the treatment of AD.

Determination of the protonation state for the catalytic dyad in β-secretase when bound to hydroxyethylamine transition state analogue inhibitors: A molecular dynamics simulation study

BACE1 is an aspartyl protease of pharmacological interest for its direct participation in Alzheimer's disease (AD) through β-amyloid peptide production. Two aspartic acid residues are present in the BACE1 catalytic region which can adopt multiple protonation states depending on the chemical nature of its inhibitors, i.e., monoprotonated, diprotonated and di-deprotonated states. In the present study a series of protein-ligand molecular dynamics (MD) simulations was carried out to identify the most feasible protonation state adopted by the catalytic dyad in the presence of hydroxyethylamine transition state analogue inhibitors. The MD trajectories revealed that the di-deprotonated state is most prefered in the presence of hydroxyethilamine (HEA) family inhibitors. This appears as a result after evaluating, for all 9 protonation state configurations during the simulation time, the deviations of a set of distances and dihedral angles measured on the ligand, protein and protein-ligand complex with reference to an X-ray experimental BACE1/HEA crystallographic structure. These results will help to clarify the phenomena related to the HEAs inhibitory pathway, and improve HEAs databases' virtual screening and ligand design processes targeting β-secretase protein.

XModeScore: a novel method for accurate protonation/tautomer-state determination using quantum-mechanically driven macromolecular X-ray crystallographic refinement

Gaining an understanding of the protein-ligand complex structure along with the proper protonation and explicit solvent effects can be important in obtaining meaningful results in structure-guided drug discovery and structure-based drug discovery. Unfortunately, protonation and tautomerism are difficult to establish with conventional methods because of difficulties in the experimental detection of H atoms owing to the well known limitations of X-ray crystallography. In the present work, it is demonstrated that semiempirical, quantum-mechanics-based macromolecular crystallographic refinement is sensitive to the choice of a protonation-state/tautomer form of ligands and residues, and can therefore be used to explore potential states. A novel scoring method, called XModeScore, is described which enumerates the possible protomeric/tautomeric modes, refines each mode against X-ray diffraction data with the semiempirical quantum-mechanics (PM6) Hamiltonian and scores each mode using a combination of energetic strain (or ligand strain) and rigorous statistical analysis of the difference electron-density distribution. It is shown that using XModeScore it is possible to consistently distinguish the correct bound protomeric/tautomeric modes based on routine X-ray data, even at lower resolutions of around 3 Å. These X-ray results are compared with the results obtained from much more expensive and laborious neutron diffraction studies for three different examples: tautomerism in the acetazolamide ligand of human carbonic anhydrase II (PDB entries 3hs4 and 4k0s), tautomerism in the 8HX ligand of urate oxidase (PDB entries 4n9s and 4n9m) and the protonation states of the catalytic aspartic acid found within the active site of an aspartic protease (PDB entry 2jjj). In each case, XModeScore applied to the X-ray diffraction data is able to determine the correct protonation state as defined by the neutron diffraction data. The impact of QM-based refinement versus conventional refinement on XModeScore is also discussed.

Mechanisms of peptide hydrolysis by aspartyl and metalloproteases

Peptide hydrolysis has been involved in a wide range of biological, biotechnological, and industrial applications.

Conformational Dynamics and Binding Free Energies of Inhibitors of BACE-1: From the Perspective of Protonation Equilibria

BACE-1 is the β-secretase responsible for the initial amyloidogenesis in Alzheimer’s disease, catalyzing hydrolytic cleavage of substrate in a pH-sensitive manner. The catalytic mechanism of BACE-1 requires water-mediated proton transfer from aspartyl dyad to the substrate, as well as structural flexibility in the flap region. Thus, the coupling of protonation and conformational equilibria is essential to a full in silico characterization of BACE-1. In this work, we perform constant pH replica exchange molecular dynamics simulations on both apo BACE-1 and five BACE-1-inhibitor complexes to examine the effect of pH on dynamics and inhibitor binding properties of BACE-1. In our simulations, we find that solution pH controls the conformational flexibility of apo BACE-1, whereas bound inhibitors largely limit the motions of the holo enzyme at all levels of pH. The microscopic pK_a values of titratable residues in BACE-1 including its aspartyl dyad are computed and compared between apo and inhibitor-bound states. Changes in protonation between the apo and holo forms suggest a thermodynamic linkage between binding of inhibitors and protons localized at the dyad. Utilizing our recently developed computational protocol applying the binding polynomial formalism to the constant pH molecular dynamics (CpHMD) framework, we are able to obtain the pH-dependent binding free energy profiles for various BACE-1-inhibitor complexes. Our results highlight the importance of correctly addressing the binding-induced protonation changes in protein-ligand systems where binding accompanies a net proton transfer. This work comprises the first application of our CpHMD-based free energy computational method to protein-ligand complexes and illustrates the value of CpHMD as an all-purpose tool for obtaining pH-dependent dynamics and binding free energies of biological systems.

Formation of insoluble amyloid plaques in the vascular and hippocampal areas of the brain characterizes Alzheimer’s disease, a devastating neurodegenerative disorder causing dementia. Site-specific hydrolytic catalysis of β-secretase, or BACE-1, is responsible for production of oligomerative amyloid β-peptide. As the catalytic activity of BACE-1 is pH-dependent and its structural dynamics are intrinsic to the catalysis, we examine the dependence of dynamics of BACE-1 on solution pH and its implications on the catalytic mechanism of BACE-1. Also, we highlight the importance of accurate description of protonation states of the titratable groups in computer-aided drug discovery targeting BACE-1. We hope the understanding of pH dependence of the dynamics and inhibitor binding properties of BACE-1 will aid the structure-based inhibitor design efforts against Alzheimer’s disease.

Biological and computational evaluation of resveratrol inhibitors against Alzheimer's disease

It has been reported that beta amyloid induces production of radical oxygen species and oxidative stress in neuronal cells, which in turn upregulates β-secretase (BACE-1) expression and beta amyloid levels, thereby propagating oxidative stress and increasing neuronal injury. A series of resveratrol derivatives, known to be inhibitors of oxidative stress-induced neuronal cell death (oxytosis) were biologically evaluated against BACE-1 using homogeneous time-resolved fluorescence (TRF) assay. Correlation between oxytosis inhibitory and BACE-1 inhibitory activity of resveratrol derivatives was statistically significant, supporting the notion that BACE-1 may act as pivotal mediator of neuronal cell oxytosis. Four of the biologically evaluated resveratrol analogs demonstrated considerably higher activity than resveratrol in either assay. The discovery of some "hits" led us to initiate detailed docking studies associated with Molecular Dynamics in order to provide a plausible explanation for the experimental results and understand their molecular basis of action.

Computational Insights into Substrate and Site Specificities, Catalytic Mechanism, and Protonation States of the Catalytic Asp Dyad of β -Secretase

In this review, information regarding substrate and site specificities, catalytic mechanism, and protonation states of the catalytic Asp dyad of β-secretase (BACE1) derived from computational studies has been discussed. BACE1 catalyzes the rate-limiting step in the generation of Alzheimer amyloid beta peptide through the proteolytic cleavage of the amyloid precursor protein. Due to its biological functioning, this enzyme has been considered as one of the most important targets for finding the cure for Alzheimer's disease. Molecular dynamics (MD) simulations suggested that structural differences in the key regions (inserts A, D, and F and the 10s loop) of the enzyme are responsible for the observed difference in its activities towards the WT- and SW-substrates. The modifications in the flap, third strand, and insert F regions were found to be involved in the alteration in the site specificity of the glycosylphosphatidylinositol bound form of BACE1. Our QM and QM/MM calculations suggested that BACE1 hydrolyzed the SW-substrate more efficiently than the WT-substrate and that cleavage of the peptide bond occurred in the rate-determining step. The results from molecular docking studies showed that the information concerning a single protonation state of the Asp dyad is not enough to run an in silico screening campaign.

Using quantum mechanical approaches to study biological systems

Conspectus Quantum mechanics (QM) has revolutionized our understanding of the structure and reactivity of small molecular systems. Given the tremendous impact of QM in this research area, it is attractive to believe that this could also be brought into the biological realm where systems of a few thousand atoms and beyond are routine. Applying QM methods to biological problems brings an improved representation to these systems by the direct inclusion of inherently QM effects such as polarization and charge transfer. Because of the improved representation, novel insights can be gleaned from the application of QM tools to biomacromolecules in aqueous solution. To achieve this goal, the computational bottlenecks of QM methods had to be addressed. In semiempirical theory, matrix diagonalization is rate limiting, while in density functional theory or Hartree-Fock theory electron repulsion integral computation is rate-limiting. In this Account, we primarily focus on semiempirical models where the divide and conquer (D&C) approach linearizes the matrix diagonalization step with respect to the system size. Through the D&C approach, a number of applications to biological problems became tractable. Herein, we provide examples of QM studies on biological systems that focus on protein solvation as viewed by QM, QM enabled structure-based drug design, and NMR and X-ray biological structure refinement using QM derived restraints. Through the examples chosen, we show the power of QM to provide novel insights into biological systems, while also impacting practical applications such as structure refinement. While these methods can be more expensive than classical approaches, they make up for this deficiency by the more realistic modeling of the electronic nature of biological systems and in their ability to be broadly applied. Of the tools and applications discussed in this Account, X-ray structure refinement using QM models is now generally available to the community in the refinement package Phenix. While the power of this approach is manifest, challenges still remain. In particular, QM models are generally applied to static structures, so ways in which to include sampling is an ongoing challenge. Car-Parrinello or Born-Oppenheimer molecular dynamics approaches address the short time scale sampling issue, but how to effectively use QM to study phenomenon covering longer time scales will be the focus of future research. Finally, how to accurately and efficiently include electron correlation effects to facilitate the modeling of, for example, dispersive interactions, is also a major hurdle that a broad range of groups are addressing The use of QM models in biology is in its infancy, leading to the expectation that the most significant use of these tools to address biological problems will be seen in the coming years. It is hoped that while this Account summarizes where we have been, it will also help set the stage for future research directions at the interface of quantum mechanics and biology.

Polyphenols as therapeutic molecules in Alzheimer's disease through modulating amyloid pathways

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative condition. The complex pathology of this disease includes oxidative stress, metal deposition, formation of aggregates of amyloid and tau, enhanced immune responses, and disturbances in cholinesterase. Drugs targeted toward reduction of amyloidal load have been discovered, but there is no effective pharmacological treatment for combating the disease so far. Natural products have become an important avenue for drug discovery research. Polyphenols are natural products that have been shown to be effective in the modulation of the type of neurodegenerative changes seen in AD, suggesting a possible therapeutic role. The present review focuses on the chemistry of polyphenols and their role in modulating amyloid precursor protein (APP) processing. We also provide new hypotheses on how these therapeutic molecules may modulate APP processing, prevent Aβ aggregation, and favor disruption of preformed fibrils. Finally, the role of polyphenols in modulating Alzheimer's pathology is discussed.

QM/MM investigations of organic chemistry oriented questions

About 35 years after its first suggestion, QM/MM became the standard theoretical approach to investigate enzymatic structures and processes. The success is due to the ability of QM/MM to provide an accurate atomistic picture of enzymes and related processes. This picture can even be turned into a movie if nuclei-dynamics is taken into account to describe enzymatic processes. In the field of organic chemistry, QM/MM methods are used to a much lesser extent although almost all relevant processes happen in condensed matter or are influenced by complicated interactions between substrate and catalyst. There is less importance for theoretical organic chemistry since the influence of nonpolar solvents is rather weak and the effect of polar solvents can often be accurately described by continuum approaches. Catalytic processes (homogeneous and heterogeneous) can often be reduced to truncated model systems, which are so small that pure quantum-mechanical approaches can be employed. However, since QM/MM becomes more and more efficient due to the success in software and hardware developments, it is more and more used in theoretical organic chemistry to study effects which result from the molecular nature of the environment. It is shown by many examples discussed in this review that the influence can be tremendous, even for nonpolar reactions. The importance of environmental effects in theoretical spectroscopy was already known. Due to its benefits, QM/MM can be expected to experience ongoing growth for the next decade.In the present chapter we give an overview of QM/MM developments and their importance in theoretical organic chemistry, and review applications which give impressions of the possibilities and the importance of the relevant effects. Since there is already a bunch of excellent reviews dealing with QM/MM, we will discuss fundamental ingredients and developments of QM/MM very briefly with a focus on very recent progress. For the applications we follow a similar strategy.

Conformational analysis and parallel QM/MM X-ray refinement of protein bound anti-Alzheimer drug donepezil

The recognition and association of donepezil with acetylcholinesterase (AChE) has been extensively studied in the past several decades because of the former's use as a palliative treatment for mild Alzheimer disease. Herein we examine the conformational properties of donepezil and we re-examine the donepezil-AChE crystal structure using combined quantum mechanical/molecular mechanical (QM/MM) X-ray refinement tools. Donepezil's conformational energy surface was explored using the M06 suite of density functionals and with the MP2/complete basis set (CBS) method using the aug-cc-pVXZ (X = D and T) basis sets. The donepezil-AChE complex (PDB 1EVE) was also re-refined through a parallel QM/MM X-ray refinement approach based on an in-house ab initio code QUICK, which uses the message passing interface (MPI) in a distributed SCF algorithm to accelerate the calculation via parallelization. In the QM/MM re-refined donepezil structure, coordinate errors that previously existed in the PDB deposited geometry were improved leading to an improvement of the modeling of the interaction between donepezil and the aromatic side chains located in the AChE active site gorge. As a result of the re-refinement there was a 93% reduction in the donepezil conformational strain energy versus the original PDB structure. The results of the present effort offer further detailed structural and biochemical inhibitor-AChE information for the continued development of more effective and palliative treatments of Alzheimer disease.

Combined quantum mechanics/molecular mechanics (QM/MM) methods in computational enzymology

Computational enzymology is a rapidly maturing field that is increasingly integral to understanding mechanisms of enzyme-catalyzed reactions and their practical applications. Combined quantum mechanics/molecular mechanics (QM/MM) methods are important in this field. By treating the reacting species with a quantum mechanical method (i.e., a method that calculates the electronic structure of the active site) and including the enzyme environment with simpler molecular mechanical methods, enzyme reactions can be modeled. Here, we review QM/MM methods and their application to enzyme-catalyzed reactions to investigate fundamental and practical problems in enzymology. A range of QM/MM methods is available, from cheaper and more approximate methods, which can be used for molecular dynamics simulations, to highly accurate electronic structure methods. We discuss how modeling of reactions using such methods can provide detailed insight into enzyme mechanisms and illustrate this by reviewing some recent applications. We outline some practical considerations for such simulations. Further, we highlight applications that show how QM/MM methods can contribute to the practical development and application of enzymology, e.g., in the interpretation and prediction of the effects of mutagenesis and in drug and catalyst design.

Structure-based design of β-site APP cleaving enzyme 1 (BACE1) inhibitors for the treatment of Alzheimer's disease

The amyloid hypothesis asserts that excess production or reduced clearance of the amyloid-β (Aβ) peptides in the brain initiates a sequence of events that ultimately lead to Alzheimer's disease and dementia. The Aβ hypothesis has identified BACE1 as a therapeutic target to treat Alzheimer's and led to medicinal chemistry efforts to design its inhibitors both in the pharmaceutical industry and in academia. This review summarizes two distinct categories of inhibitors designed based on conformational states of "closed" and "open" forms of the enzyme. In each category the inhibitors are classified based on the core catalytic interaction group or the aspartyl binding motif (ABM). This review covers the description of inhibitors in each ABM class with X-ray crystal structures of key compounds, their binding modes, related structure-activity data highlighting potency advances, and additional properties such as selectivity profile, P-gp efflux, pharmacokinetic, and pharmacodynamic data.

The central role of Gln63 for the hydrogen bonding network and UV-visible spectrum of the AppA BLUF domain

In blue-light sensing using flavin (BLUF) domains, the side-chain orientation of key residues close to the flavin chromophore is still under debate. We report quantum refinements of the wild-type AppA BLUF protein from Rhodobacter sphaeroides starting from two published X-ray structures (1YRX and 2IYG) with different arrangements of the residues around the chromophore. Quantum refinement uses the same experimental X-ray raw data as conventional refinement, but includes data from quantum mechanics/molecular mechanics (QM/MM) calculations as restraints, which is expected to be more reliable than the normally employed MM data. In addition to quantum refinement, pure QM/MM geometry optimizations are performed for the 1YRX and 2IYG structures and for five models derived therefrom. Vertical excitation energies are computed at the QM(DFT/MRCI)/MM level to assess the resulting structures. The experimental absorption maximum of the dark state of wild-type AppA is well reproduced for structures that contain the Gln63 residue in 1YRX-type orientation. The computed excitation energies are red-shifted for structures with a flipped Gln63 residue in 2IYG-type orientation. The calculated 1YRX- and 2IYG-type hydrogen-bonding networks are discussed in detail, particularly with regard to the orientation of the chromophore and the Gln63, Trp104, and Met106 residues.

Protonation states of the catalytic dyad of β-secretase (BACE1) in the presence of chemically diverse inhibitors: a molecular docking study

In this molecular docking study, the protonation states of the catalytic Asp dyad of the beta-secretase (BACE1) enzyme in the presence of eight chemically diverse inhibitors have been predicted. BACE1 catalyzes the rate-determining step in the generation of Alzheimer amyloid beta peptides and is widely considered as a promising therapeutic target. All the inhibitors were redocked into their corresponding X-ray structures using a combination of eight different protonation states of the Asp dyad for each inhibitor. Five inhibitors were primarily found to favor two different monoprotonated states, and the remaining three favor a dideprotonated state. In addition, five of them exhibited secondary preference for a diprotonated state. These results show that the knowledge of a single protonation state of the Asp dyad is not sufficient to search for the novel inhibitors of BACE1 and the most plausible state for each inhibitor must be determined prior to conducting in-silico screening.

Combining dyad protonation and active site plasticity in BACE-1 structure-based drug design

The ability of the BACE-1 catalytic dyad to adopt multiple protonation states and the conformational flexibility of the active site have hampered the reliability of computational screening campaigns carried out on this drug target for Alzheimer's disease. Here, we propose a protocol that, for the first time, combining quantum mechanical calculations, molecular dynamics, and conformational ensemble virtual ligand screening addresses these issues simultaneously. The encouraging results prefigure this approach as a valuable tool for future drug discovery campaigns.

Conformational Analysis of Free and Bound Retinoic Acid

The conformational profiles of unbound all-trans and 9-cis retinoic acid (RA) have been determined using classical and quantum mechanical calculations. Sixty-six all-trans-RA (ATRA) and forty-eight 9-cis-RA energy minimum conformers were identified via HF/6-31G* geometry optimizations in vacuo. Their relative conformational energies were estimated utilizing the M06, M06-2x and MP2 methods combined with the 6-311+G(d,p), aug-cc-pVDZ and aug-cc-pVTZ basis sets, as well as complete basis set MP2 extrapolations using the latter two basis sets. Single-point energy calculations performed with the M06-2x density functional were found to yield similar results to MP2/CBS for the low-energy retinoic acid conformations. Not unexpectedly, the conformational propensities of retinoic acid were governed by the orientation and arrangement of the torsion angles associated with the polyene tail. We also used previously reported QM/MM X-ray refinement results on four ATRA-protein crystal structures plus one newly refined 9-cis-RA complex (PDB ID 1XDK) in order to investigate the conformational preferences of bound retinoic acid. In the re-refined RA conformers the conjugated double bonds are nearly coplanar, which is consistent with the global minimum identified by the Omega/QM method rather than the corresponding crystallographically determined conformations given in the PDB. Consequently, a 91.3% average reduction of the local strain energy in the gas phase, as well as 92.1% in PCM solvent, was observed using the QM/MM refined structures versus the PDB deposited RA conformations. These results thus demonstrate that our QM/MM X-ray refinement approach can significantly enhance the quality of X-ray crystal structures refined by conventional refinement protocols, thereby providing reliable drug-target structural information for use in structure-based drug discovery applications.

Computational insights into the development of novel therapeutic strategies for Alzheimer's disease

BACKGROUND

β-amyloidosis and oxidative stress have been implicated as root causes of Alzheimer's disease (AD). Current potential therapeutic strategies for the treatment of AD include inhibition of amyloid β (Aβ) production, stimulation of Aβ degradation and prevention of Aβ oligomerization. However, efforts in this direction are hindered by the lack of understanding of the biochemical processes occurring at the atomic level in AD.

DISCUSSION

A radically different approach to achieve this goal would be the application of comprehensive theoretical and computational techniques such as molecular dynamics, quantum mechanics, hybrid quantum mechanics/molecular mechanics, bioinformatics and rotational spectroscopy to investigate complex chemical and physical processes in β-amyloidosis and the oxidative stress mechanism.

CONCLUSION

Results obtained from these studies will provide an atomic level understanding of biochemical processes occurring in AD and advance efforts to develop effective therapeutic strategies for this disease.

Computational modeling of substrate specificity and catalysis of the β-secretase (BACE1) enzyme

In this combined MD simulation and DFT study, interactions of the wild-type (WT) amyloid precursor protein (APP) and its Swedish variant (SW), Lys670 → Asn and Met671 → Leu, with the beta-secretase (BACE1) enzyme and their cleavage mechanisms have been investigated. BACE1 catalyzes the rate-limiting step in the generation of 40-42 amino acid long Alzheimer amyloid beta (Aβ) peptides. All key structural parameters such as position of the flap, volume of the active site, electrostatic binding energy, structures, and positions of the inserts A, D, and F and 10s loop obtained from the MD simulations show that, in comparison to the WT-substrate, BACE1 exhibits greater affinity for the SW-substrate and orients it in a more reactive conformation. The enzyme-substrate models derived from the MD simulations were further utilized to investigate the general acid/base mechanism used by BACE1 to hydrolytically cleave these substrates. This mechanism proceeds through the following two steps: (1) formation of the gem-diol intermediate and (2) cleavage of the peptide bond. For the WT-substrate, the overall barrier of 22.4 kcal/mol for formation of the gem-diol intermediate is 3.3 kcal/mol higher than for the SW-substrate (19.1 kcal/mol). This process is found to be the rate-limiting in the entire mechanism. The computed barrier is in agreement with the measured barrier of ca. 18.00 kcal/mol for the WT-substrate and supports the experimental observation that the cleavage of the SW-substrate is 60 times more efficient than the WT-substrate.

On the reliability of the corrected semiempirical quantum chemical method (PM6-DH2) for assigning the protonation states in HIV-1 protease/inhibitor complexes

A novel computational protocol for determining the most probable protonation states in protein/ligand complexes is presented. The method consists in treating large parts of the enzyme using the corrected semiempirical quantum chemical (QM) method – PM6-D2 for optimization and PM6-DH2 for single-point energies – while the rest is calculated using molecular mechanics (MM) within a hybrid QM/MM fashion. The surrounding solvent is approximated by an implicit model. This approach is applied to two model systems, two different carboxylate pairs in one general and one unique HIV-1 protease/inhibitor complex. The effect of the size of the movable QM part is investigated in a series of several sizes, 3-, 6-, 8- and 10-Å regions surrounding the inhibitor. For the smallest region (< 450 atoms) the computationally more costly DFT QM/MM optimizations are performed as a check of the correctness. Proton transfer (PT) phenomena occur at both the PM6-D2 and DFT levels, which underlines the requirement for a QM approach. The barriers of PT are checked in model carboxylic acid pairs using the highly accurate MP2 and CCSD(T) values. An important result of this study is the fine-tuning of the protocol which can be used in further applications; its limitations are also shown, pointing to future developments. The calculations reveal which protonation variants of the active site are the most stable. In conclusion, the presented protocol can also be utilized for defining probable isomers in biomolecular systems. It can also serve as a preparatory step for further interaction-energy and binding-score calculations.