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

BACE-1 Inhibitors Targeting Alzheimer's Disease

The accumulation of amyloid-β (Aβ) is the main event related to Alzheimer's disease (AD) progression. Over the years, several disease-modulating approaches have been reported, but without clinical success. The amyloid cascade hypothesis evolved and proposed essential targets such as tau protein aggregation and modulation of β-secretase (β-site amyloid precursor protein cleaving enzyme 1 - BACE-1) and γ-secretase proteases. BACE-1 cuts the amyloid precursor protein (APP) to release the C99 fragment, giving rise to several Aβ peptide species during the subsequent γ-secretase cleavage. In this way, BACE-1 has emerged as a clinically validated and attractive target in medicinal chemistry, as it plays a crucial role in the rate of Aβ generation. In this review, we report the main results of candidates in clinical trials such as E2609, MK8931, and AZD-3293, in addition to highlighting the pharmacokinetic and pharmacodynamic-related effects of the inhibitors already reported. The current status of developing new peptidomimetic, non-peptidomimetic, naturally occurring, and other class inhibitors are demonstrated, considering their main limitations and lessons learned. The goal is to provide a broad and complete approach to the subject, exploring new chemical classes and perspectives.

Dual Inhibitors of AChE and BACE-1 for Reducing Aβ in Alzheimer's Disease: From In Silico to In Vivo

Alzheimer's disease (AD) is a complex and widespread condition, still not fully understood and with no cure yet. Amyloid beta (Aβ) peptide is suspected to be a major cause of AD, and therefore, simultaneously blocking its formation and aggregation by inhibition of the enzymes BACE-1 (β-secretase) and AChE (acetylcholinesterase) by a single inhibitor may be an effective therapeutic approach, as compared to blocking one of these targets or by combining two drugs, one for each of these targets. We used our ISE algorithm to model each of the AChE peripheral site inhibitors and BACE-1 inhibitors, on the basis of published data, and constructed classification models for each. Subsequently, we screened large molecular databases with both models. Top scored molecules were docked into AChE and BACE-1 crystal structures, and 36 Molecules with the best weighted scores (based on ISE indexes and docking results) were sent for inhibition studies on the two enzymes. Two of them inhibited both AChE (IC₅₀ between 4-7 μM) and BACE-1 (IC₅₀ between 50-65 μM). Two additional molecules inhibited only AChE, and another two molecules inhibited only BACE-1. Preliminary testing of inhibition by F681-0222 (molecule 2) on APPswe/PS1dE9 transgenic mice shows a reduction in brain tissue of soluble Aβ42.

Binding of Inhibitors to BACE1 Affected by pH-Dependent Protonation: An Exploration from Multiple Replica Gaussian Accelerated Molecular Dynamics and MM-GBSA Calculations

To date, inhibiting the activity of β-amyloid cleaving enzyme 1 (BACE1) has been considered an efficient approach for treating Alzheimer's disease (AD). In the current work, multiple replica Gaussian accelerated molecular dynamics (MR-GaMD) simulations and the molecular mechanics general Born surface area (MM-GBSA) method were combined to investigate the effect of pH-dependent protonation on the binding of the inhibitors CS9, C6U, and 6WE to BACE1. Dynamic analyses based on the MR-GaMD trajectory show that pH-dependent protonation strongly affects the structural flexibility, correlated motions, and dynamic behavior of inhibitor-bound BACE1. According to the constructed free energy profiles, in the protonated state at low pH, inhibitor-bound BACE1 tends to populate at more conformations than in high pH. The binding free energies calculated by MM-GBSA suggest that inhibitors possess stronger binding abilities under the protonation conditions at high pH than under the protonation conditions at low pH. Moreover, pH-dependent protonation exerts a significant effect on the hydrogen bonding interactions of CS9, C6U, and 6WE to BACE1, which correspondingly alters the binding abilities of the three inhibitors to BACE1. Furthermore, in different protonated environments, three inhibitors share common interaction clusters and similar binding sites in BACE1, which are reliably used as efficient targets for the design of potent inhibitors of BACE1.

Computational modelling of potent β-secretase (BACE1) inhibitors towards Alzheimer's disease treatment

Researchers have identified the β-amyloid precursor protein cleaving enzyme 1 (BACE1) in the multifactorial pathway of Alzheimer's disease (AD) as a drug target. The design and development of molecules to inhibit BACE1 as a potential cure for AD thus remained significant. Herein, we simulated two potent BACE1 inhibitors (AM-6494 and CNP-520) to understand their binding affinity at the atomistic level. AM-6494 is a newly reported potent BACE1 inhibitor with an IC₅₀ value of 0.4 nM in vivo and now picked for preclinical considerations. Umibecestat (CNP-520), which was discontinued at human trials lately, was considered to enable a reasonable evaluation of our results. Using density functional theory (DFT) and Our Own N-layered Integrated molecular Orbital and Molecular Mechanics (ONIOM), we achieved the aim of this investigation. These computational approaches enabled the prediction of the electronic properties of AM-6494 and CNP-520 plus their binding energies when complexed with BACE1. For AM-6494 and CNP-520 interaction with protonated BACE1, the ONIOM calculation gave binding free energy of -62.849 and -33.463 kcal/mol, respectively. In the unprotonated model, we observed binding free energy of -59.758 kcal/mol in AM-6494. Taken together thermochemistry of the process and molecular interaction plot, AM-6494 is more favourable than CNP-520 towards the inhibition of BACE1. The protonated model gave slightly better binding energy than the unprotonated form. However, both models could sufficiently describe ligand binding to BACE1 at the atomistic level. Understanding the detailed molecular interaction of these inhibitors could serve as a basis for pharmacophore exploration towards improved inhibitor design.

Effects of Disulfide Bonds on Binding of Inhibitors to β-Amyloid Cleaving Enzyme 1 Decoded by Multiple Replica Accelerated Molecular Dynamics Simulations

The β-amyloid cleaving enzyme 1 (BACE1) has been thought to be an efficient target for treatment of Alzheimer's disease (AD). Deep insight into inhibitor-BACE1 binding mechanism is of significance for design of potent drugs toward BACE1. In this work, multiple replica accelerated molecular dynamics (MR-aMD) simulations, principal component (PC) analysis, and free energy landscapes were integrated to decode the effect of disulfide bonds (SSBs) in BACE1 on bindings of three inhibitors 3KO, 3KT, and 779 to BACE1. The results from cross-correlation analysis suggest that the breaking of SSBs exerts significant influence on structural flexibility and internal dynamics of inhibitor-bound BACE1. PC analysis and free energy landscapes reveal that the breaking of SSBs not only evidently induces the conformational rearrangement of BACE1 but also highly changes binding poses of three inhibitors in BACE1 and leads to more disordered binding of three inhibitors to BACE1, which is further supported by the increase in binding entropy of inhibitors to BACE1 due to the breaking of SSBs. Residue-based free energy decomposition method was utilized to evaluate contributions of separate residues to inhibitor-BACE1 binding. The results suggest that although the breaking of SSBs in BACE1 does not destroy the interaction network of inhibitors with BACE1 it changes interaction strength of some residues with inhibitors. Meanwhile, the information from residue-based free energy decomposition indicates that residues L91, S96, V130, Y132, Q134, W137, F169, I171, and I179 can be used as efficient targets of drug design toward BACE1.

Changing Paradigm from one Target one Ligand Towards Multi-target Directed Ligand Design for Key Drug Targets of Alzheimer Disease: An Important Role of In Silico Methods in Multi-target Directed Ligands Design

Alzheimer disease (AD) is now considered as a multifactorial neurodegenerative disorder and rapidly increasing to an alarming situation and causing higher death rate. One target one ligand hypothesis does not provide complete solution of AD due to multifactorial nature of the disease and one target one drug fails to provide better treatment against AD. Moreo-ver, currently available treatments are limited and most of the upcoming treatments under clinical trials are based on modulat-ing single target. So, the current AD drug discovery research is shifting towards a new approach for a better solution that simultaneously modulates more than one targets in the neurodegenerative cascade. This can be achieved by network pharma-cology, multi-modal therapies, multifaceted, and/or the more recently proposed term “multi-targeted designed drugs”. Drug discovery project is a tedious, costly and long-term project. Moreover, multi-target AD drug discovery added extra challeng-es such as the good binding affinity of ligands for multiple targets, optimal ADME/T properties, no/less off-target side effect and crossing of the blood-brain barrier. These hurdles may be addressed by insilico methods for an efficient solution in less time and cost as computational methods successfully applied to single target drug discovery project. Here, we are summariz-ing some of the most prominent and computationally explored single targets against AD and further, we discussed a success-ful example of dual or multiple inhibitors for same targets. Moreover, we focused on ligand and structure-based computa-tional approach to design MTDL against AD. However, it is not an easy task to balance dual activity in a single molecule but computational approach such as virtual screening docking, QSAR, simulation and free energy is useful in future MTDLs drug discovery alone or in combination with a fragment-based method. However, rational and logical implementations of computational drug designing methods are capable of assisting AD drug discovery and play an important role in optimizing multi-target drug discovery.

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.

Predicting Displaceable Water Sites Using Mixed-Solvent Molecular Dynamics

Water molecules are an important factor in protein-ligand binding. Upon binding of a ligand with a protein's surface, waters can either be displaced by the ligand or may be conserved and possibly bridge interactions between the protein and ligand. Depending on the specific interactions made by the ligand, displacing waters can yield a gain in binding affinity. The extent to which binding affinity may increase is difficult to predict, as the favorable displacement of a water molecule is dependent on the site-specific interactions made by the water and the potential ligand. Several methods have been developed to predict the location of water sites on a protein's surface, but the majority of methods are not able to take into account both protein dynamics and the interactions made by specific functional groups. Mixed-solvent molecular dynamics (MixMD) is a cosolvent simulation technique that explicitly accounts for the interaction of both water and small molecule probes with a protein's surface, allowing for their direct competition. This method has previously been shown to identify both active and allosteric sites on a protein's surface. Using a test set of eight systems, we have developed a method using MixMD to identify conserved and displaceable water sites. Conserved sites can be determined by an occupancy-based metric to identify sites which are consistently occupied by water even in the presence of probe molecules. Conversely, displaceable water sites can be found by considering the sites which preferentially bind probe molecules. Furthermore, the inclusion of six probe types allows the MixMD method to predict which functional groups are capable of displacing which water sites. The MixMD method consistently identifies sites which are likely to be nondisplaceable and predicts the favorable displacement of water sites that are known to be displaced upon ligand binding.

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.

Effect of sampling on BACE-1 ligands binding free energy predictions via MM-PBSA calculations

The BACE-1 enzyme is a prime target to find a cure to Alzheimer's disease. In this article, we used the MM-PBSA approach to compute the binding free energies of 46 reported ligands to this enzyme. After showing that the most probable protonation state of the catalytic dyad is mono-protonated (on ASP32), we performed a thorough analysis of the parameters influencing the sampling of the conformational space (in total, more than 35 μs of simulations were performed). We show that ten simulations of 2 ns gives better results than one of 50 ns. We also investigated the influence of the protein force field, the water model, the periodic boundary conditions artifacts (box size), as well as the ionic strength. Amber03 with TIP3P, a minimal distance of 1.0 nm between the protein and the box edges and a ionic strength of I = 0.2 M provides the optimal correlation with experiments. Overall, when using these parameters, a Pearson correlation coefficient of R = 0.84 (R²  = 0.71) is obtained for the 46 ligands, spanning eight orders of magnitude of K_d (from 0.017 nm to 2000 μM, i.e., from -14.7 to -3.7 kcal/mol), with a ligand size from 22 to 136 atoms (from 138 to 937 g/mol). After a two-parameter fit of the binding affinities for 12 of the ligands, an error of RMSD = 1.7 kcal/mol was obtained for the remaining ligands. © 2017 Wiley Periodicals, Inc.

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.

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.

Charting a Path to Success in Virtual Screening

Docking is commonly applied to drug design efforts, especially high-throughput virtual screenings of small molecules, to identify new compounds that bind to a given target. Despite great advances and successful applications in recent years, a number of issues remain unsolved. Most of the challenges and problems faced when running docking experiments are independent of the specific software used, and can be ascribed to either improper input preparation or to the simplified approaches applied to achieve high-throughput speed. Being aware of approximations and limitations of such methods is essential to prevent errors, deal with misleading results, and increase the success rate of virtual screening campaigns. In this review, best practices and most common issues of docking and virtual screening will be discussed, covering the journey from the design of the virtual experiment to the hit identification.

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.

Applying DEKOIS 2.0 in structure-based virtual screening to probe the impact of preparation procedures and score normalization

Background

Structure-based virtual screening techniques can help to identify new lead structures and complement other screening approaches in drug discovery. Prior to docking, the data (protein crystal structures and ligands) should be prepared with great attention to molecular and chemical details.

Results

Using a subset of 18 diverse targets from the recently introduced DEKOIS 2.0 benchmark set library, we found differences in the virtual screening performance of two popular docking tools (GOLD and Glide) when employing two different commercial packages (e.g. MOE and Maestro) for preparing input data. We systematically investigated the possible factors that can be responsible for the found differences in selected sets. For the Angiotensin-I-converting enzyme dataset, preparation of the bioactive molecules clearly exerted the highest influence on VS performance compared to preparation of the decoys or the target structure. The major contributing factors were different protonation states, molecular flexibility, and differences in the input conformation (particularly for cyclic moieties) of bioactives. In addition, score normalization strategies eliminated the biased docking scores shown by GOLD (ChemPLP) for the larger bioactives and produced a better performance. Generalizing these normalization strategies on the 18 DEKOIS 2.0 sets, improved the performances for the majority of GOLD (ChemPLP) docking, while it showed detrimental performances for the majority of Glide (SP) docking.

Conclusions

In conclusion, we exemplify herein possible issues particularly during the preparation stage of molecular data and demonstrate to which extent these issues can cause perturbations in the virtual screening performance. We provide insights into what problems can occur and should be avoided, when generating benchmarks to characterize the virtual screening performance. Particularly, careful selection of an appropriate molecular preparation setup for the bioactive set and the use of score normalization for docking with GOLD (ChemPLP) appear to have a great importance for the screening performance. For virtual screening campaigns, we recommend to invest time and effort into including alternative preparation workflows into the generation of the master library, even at the cost of including multiple representations of each molecule.

Graphical Abstract

Target specific proteochemometric model development for BACE1 – protein flexibility and structural water are critical in virtual screening

Structural water and protein plasticity are important factors for BACE1 targeted ligand virtual screening.

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.

Design, synthesis, in silico and in vitro screening of 1,2,4-thiadiazole analogues as non-peptide inhibitors of beta-secretase

Beta-secretase is the key enzyme involved in Alzheimer's disease thus; inhibition of the enzyme can lead to a potential anti-Alzheimer drug. In the search of an effective lead candidate, we have designed non-peptide inhibitor molecules based on amino aromatic heterocyclic motifs specifically, substituted 1,2,4-thiadiazole analogues. In silico modelling was employed to study interaction of the designed ligands in the enzyme active site using molecular docking approach as well as for Absorption, Distribution, Metabolism and Excretion studies. The synthesized analogues were pharmacologically screened using in vitro FRET technique. Overall results indicate that one of the analogues, compound 8 is the most promising one against beta secretase.

Cysteine-mediated dynamic hydrogen-bonding network in the active site of Pin1

Enzymes catalyze a plethora of chemical reactions that are tightly regulated and intricately coupled in biology. Catalysis of phosphorylation-dependent cis-trans isomerization of peptidyl-prolyl bonds, which act as conformational switches in regulating many post-phosphorylation processes, is considered to be one of the most critical. Pin1 is a cis-trans isomerase of peptidyl-prolyl(ω-) bonds of phosphorylated-Ser/Thr-Pro motifs and has been implicated in many diseases. Structural and experimental studies are still unable to resolve the mechanistic role and protonation states of two adjacent histidines (His59 and His157) and a cysteine (Cys113) in the active site of Pin1. Here, we show that the protonation state of Cys113 mediates a dynamic hydrogen-bonding network in the active site of Pin1, involving the two adjacent histidines and several other residues that are highly conserved and necessary for catalysis. We have used detailed free energy calculations and molecular dynamics simulations, complementing previous experiments, to resolve the ambiguities in the orientations of the histidines and protonation states of these key active site residues, details that are critical for fully understanding the mechanism of Pin1 and necessary for developing potent inhibitors. Importantly, Cys113 is shown to alternate between the unprotonated and neutral states, unprotonated in free Pin1 and neutral in substrate-bound Pin1. Our results are consistent with experiments and provide an explanation for the chemical reactivity of free Pin1 that is suggested to be necessary for the regulation of the enzyme.