Constant pH Molecular Dynamics Reveals pH-Modulated Binding of Two Small-Molecule BACE1 Inhibitors

Resolving coupled pH titrations using alchemical free energy calculations

In a protein, nearby titratable sites can be coupled: the (de)protonation of one may affect the other. The degree of this interaction depends on several factors and can influence the measured p K a . Here, we derive a formalism based on double free energy differences ( Δ Δ G ) for quantifying the individual site p K a values of coupled residues. As Δ Δ G values can be obtained by means of alchemical free energy calculations, the presented approach allows for a convenient estimation of coupled residue p K a s in practice. We demonstrate that our approach and a previously proposed microscopic p K a formalism, can be combined with alchemical free energy calculations to resolve pH-dependent protein p K a values. Toy models and both, regular and constant-pH molecular dynamics simulations, alongside experimental data, are used to validate this approach. Our results highlight the insights gleaned when coupling and microstate probabilities are analyzed and suggest extensions to more complex enzymatic contexts. Furthermore, we find that naïvely computed p K a values that ignore coupling, can be significantly improved when coupling is accounted for, in some cases reducing the error by half. In short, alchemical free energy methods can resolve the p K a values of both uncoupled and coupled residues.

Studying Local Electrostatics by Terahertz Spectroscopy Using Amines as a Probe

In a previous study[1] we could show that a large amplitude mode of the zwitterion glycine can serve as a sensitive probe for protonation and allows to deduce local pKa values. Here we show that the underlying concept is more general: We present the results of a pH dependent measurement of Terahertz-FTIR (THz-FTIR) spectra of solvated amines, i. e. Diethylamine (DEA), Triethylamine (TEA), and Diisopropylamine (DiPA). We show that amines serve as a sensitive, label free probe for local protonation. Protonation of the amines yield intensity changes which can be quantified by precise THz spectroscopy (30 cm-1 -450 cm-1 ). A detailed analysis allows us to correlate the titration spectra of solvated amines in the THz range with pKa values. This demonstrates the potential of THz spectroscopy to probe the charge state of biomolecules in water in a label free manner.

Rapid Rescoring and Refinement of Ligand-Receptor Complexes Using Replica Exchange Molecular Dynamics with a Monte Carlo Pose Reservoir

Virtual screening (VS) involves generation of poses for a library of ligands and ranking using simplified energy functions and limited flexibility. Top-scored poses are used to rank and prioritize ligands. Here, we adapt the reservoir replica exchange molecular dynamics (res-REMD) method to rerank poses generated through VS. REMD simulations are carried out but with occasional Monte Carlo jumps to alternate VS-generated poses using a Metropolis criterion. The simulations converge within 10 ns for all systems, generating populations of alternate poses in the context of fully flexible ligand and protein side chains. The protocol is applied to four model protein-ligand complexes, where DOCK resulted in two successes and two scoring failures. In all four systems, the most populated cluster from the final ensemble exhibits high similarity to the crystallographic pose with ligand RMSD values under 2.0 Å. Both DOCK failures were rescued. For one DOCK success, the protocol identified the correct pose but also sampled an alternate pose at equal probability. Opportunities for future improvements and extensions are discussed.

Identification Mechanism of BACE1 on Inhibitors Probed by Using Multiple Separate Molecular Dynamics Simulations and Comparative Calculations of Binding Free Energies

β-amyloid cleaving enzyme 1 (BACE1) is regarded as an important target of drug design toward the treatment of Alzheimer's disease (AD). In this study, three separate molecular dynamics (MD) simulations and calculations of binding free energies were carried out to comparatively determine the identification mechanism of BACE1 for three inhibitors, 60W, 954 and 60X. The analyses of MD trajectories indicated that the presence of three inhibitors influences the structural stability, flexibility and internal dynamics of BACE1. Binding free energies calculated by using solvated interaction energy (SIE) and molecular mechanics generalized Born surface area (MM-GBSA) methods reveal that the hydrophobic interactions provide decisive forces for inhibitor-BACE1 binding. The calculations of residue-based free energy decomposition suggest that the sidechains of residues L91, D93, S96, V130, Q134, W137, F169 and I179 play key roles in inhibitor-BACE1 binding, which provides a direction for future drug design toward the treatment of AD.

Biologically relevant small variations of intra-cellular pH can have significant effect on stability of protein-DNA complexes, including the nucleosome

Stability of a protein-ligand complex may be sensitive to pH of its environment. Here we explore, computationally, stability of a set of protein-nucleic acid complexes using fundamental thermodynamic linkage relationship. The nucleosome, as well as an essentially random selection of 20 protein complexes with DNA or RNA, are included in the analysis. An increase in intra-cellular/intra-nuclear pH destabilizes most complexes, including the nucleosome. We propose to quantify the effect by ΔΔG^0.3-the change in the binding free energy due to pH increase of 0.3 units, corresponding to doubling of the H ⁺ activity; variations of pH of this amplitude can occur in living cells, including in the course of the cell cycle, and in cancer cells relative to normal ones. We suggest, based on relevant experimental findings, a threshold of biological significance of 1 2 k B T ( ∼ 0.3 k c a l / m o l ) for changes of stability of chromatin-related protein-DNA complexes: a change in the binding affinity above the threshold may have biological consequences. We find that for 70% of the examined complexes, Δ Δ G 0.3 > 1 2 k B T (for 10%, ΔΔG^0.3 is between 3 and 4 k _B T). Thus, small but relevant variations of intra-nuclear pH of 0.3 may have biological consequences for many protein-nucleic acid complexes. The binding affinity between the histone octamer and its DNA, which directly affects the DNA accessibility in the nucleosome, is predicted to be highly sensitive to intra-nuclear pH. A variation of 0.3 units results in ΔΔG^0.3 ∼ 10k _B T ( ∼ 6 k c a l / m o l ) ; for spontaneous unwrapping of 20 bp long entry/exit fragments of the nucleosomal DNA, ΔΔG^0.3 = 2.2k _B T; partial disassembly of the nucleosome into the tetrasome is characterized by ΔΔG^0.3 = 5.2k _B T. The predicted pH -induced modulations of the nucleosome stability are significant enough to suggest that they may have consequences relevant to the biological function of the nucleosome. Accessibility of the nucleosomal DNA is predicted to positively correlate with pH variations during the cell cycle; an increase in intra-cellular pH seen in cancer cells is predicted to lead to a more accessible nucleosomal DNA; a drop in pH associated with apoptosis is predicted to make nucleosomal DNA less accessible. We speculate that processes that depend on accessibility to the DNA in the nucleosomes, such as transcription or DNA replication, might become upregulated due to relatively small, but nevertheless realistic increases of intra-nuclear pH.

pH and non-covalent ligand binding modulate Zika virus NS2B/NS3 protease binding site residues: Discoveries from MD and constant pH MD simulations

Zika virus (ZIKV) is a global health concern and has been linked to severe neurological pathologies. Although no medication is available yet, many efforts to develop antivirals and host cell binding inhibitors led to attractive drug-like scaffolds, mainly targeting the nonstructural NS2B/NS3 protease (NS2B/NS3pro). NS2B/NS3pro active site has several titratable residues susceptible to pH changes and ligand binding; hence, understanding these residues' protonation is essential to drug design efforts targeting the active site. Here we use in silico methods to probe non-covalent binding and its effect on pKa shifts of the active site residues on a ligand-free protease and with a non-peptidic competitive inhibitor (K_i=13.5 µM). By applying constant pH molecular dynamics, we found that the catalytic residues of the unbound NS2B/NS3pro achieved the protonation needed for the serine protease mechanism over the pH value of 8.5. Nevertheless, the protease in the holo state achieved this same scenario at lower pH values. Also, non-covalent binding affected the catalytic triad (H51, D75, and S135) by stabilizing their distances and interaction network. Thus, NS2B/NS3pro residues configuration for activity might be both pH-dependent and influenced by ligand binding. However, compound presence within the binding site destabilized the NS2B, interfering with the closed and active conformation necessary for substrate binding and catalysis. Our outcomes provide valuable insights into non-covalent inhibitor behavior and its effect on protease active site residues, impacting optimization and design of novel compounds. Communicated by Ramaswamy H. Sarma.

pH Regulates Ligand Binding to an Enzyme Active Site by Modulating Intermediate Populations

Understanding the mechanism of ligands binding to their protein targets and the influence of various factors governing the binding thermodynamics is essential for rational drug design. The solution pH is one of the critical factors that can influence ligand binding to a protein cavity, especially in enzymes whose function is sensitive to the pH. Using computer simulations, we studied the pH effect on the binding of a guanidinium ion (Gdm⁺) to the active site of hen egg-white lysozyme (HEWL). HEWL serves as a model system for enzymes with two acidic residues in the active site and ligands with Gdm⁺ moieties, which can bind to the active sites of such enzymes and are present in several approved drugs treating various disorders. The computed free energy surface (FES) shows that Gdm⁺ binds to the HEWL active site using two dominant binding pathways populating multiple intermediates. We show that the residues close to the active site that can anchor the ligand could play a critical role in ligand binding. Using a Markov state model, we quantified the lifetimes and kinetic pathways connecting the different states in the FES. The protonation and deprotonation of the acidic residues in the active site in response to the pH change strongly influence the Gdm⁺ binding. There is a sharp jump in the ligand-binding rate constant when the pH approaches the largest pK_a of the acidic residue present in the active site. The simulations reveal that, at most, three Gdm⁺ can bind at the active site, with the Gdm⁺ bound in the cavity of the active site acting as a scaffold for the other two Gdm⁺ ions binding. These results can aid in providing greater insights into designing novel molecules containing Gdm⁺ moieties that can have high binding affinities to inhibit the function of enzymes with acidic residues in their active site.

A Guide to the Continuous Constant pH Molecular Dynamics Methods in Amber and CHARMM [Article v1.0]

Like temperature and pressure, solution pH is an important environmental variable in biomolecular simulations. Virtually all proteins depend on pH to maintain their structure and function. In conventional molecular dynamics (MD) simulations of proteins, pH is implicitly accounted for by assigning and fixing protonation states of titratable sidechains. This is a significant limitation, as the assigned protonation states may be wrong and they may change during dynamics. In this tutorial, we guide the reader in learning and using the various continuous constant pH MD methods in Amber and CHARMM packages, which have been applied to predict pK a values and elucidate proton-coupled conformational dynamics of a variety of proteins including enzymes and membrane transporters.

Novel US-CpHMD Protocol to Study the Protonation-Dependent Mechanism of the ATP/ADP Carrier

We have designed a protocol combining constant-pH molecular dynamics (CpHMD) simulations with an umbrella sampling (US) scheme (US-CpHMD) to study the mechanism of ADP/ATP transport (import and export) by their inner mitochondrial membrane carrier protein [ADP/ATP carrier (AAC)]. The US scheme helped overcome the limitations of sampling the slow kinetics involved in these substrates' transport, while CpHMD simulations provided an unprecedented realism by correctly capturing the associated protonation changes. The import of anionic substrates along the mitochondrial membrane has a strong energetic disadvantage due to a smaller substrate concentration and an unfavorable membrane potential. These limitations may have created an evolutionary pressure on AAC to develop specific features benefiting the import of ADP. In our work, the potential of mean force profiles showed a clear selectivity in the import of ADP compared to ATP, while in the export, no selectivity was observed. We also observed that AAC sequestered both substrates at longer distances in the import compared to the export process. Furthermore, only in the import process do we observe transient protonation of both substrates when going through the AAC cavity, which is an important advantage to counteract the unfavorable mitochondrial membrane potential. Finally, we observed a substrate-induced disruption of the matrix salt-bridge network, which can promote the conformational transition (from the C- to M-state) required to complete the import process. This work unraveled several important structural features where the complex electrostatic interactions were pivotal to interpreting the protein function and illustrated the potential of applying the US-CpHMD protocol to other transport processes involving membrane proteins.

Addressing Intersite Coupling Unlocks Large Combinatorial Chemical Spaces for Alchemical Free Energy Methods

Alchemical free energy methods are playing a growing role in molecular design, both for computer-aided drug design of small molecules and for computational protein design. Multisite λ dynamics (MSλD) is a uniquely scalable alchemical free energy method that enables more efficient exploration of combinatorial alchemical spaces encountered in molecular design, but simulations have typically been limited to a few hundred ligands or sequences. Here, we focus on coupling between sites to enable scaling to larger alchemical spaces. We first discuss updates to the biasing potentials that facilitate MSλD sampling to include coupling terms and show that this can provide more thorough sampling of alchemical states. We then harness coupling between sites by developing a new free energy estimator based on the Potts models underlying direct coupling analysis, a method for predicting contacts from sequence coevolution, and find it yields more accurate free energies than previous estimators. The sampling requirements of the Potts model estimator scale with the square of the number of sites, a substantial improvement over the exponential scaling of the standard estimator. This opens up exploration of much larger alchemical spaces with MSλD for molecular design.

Exploring the pH- and Ligand-Dependent Flap Dynamics of Malarial Plasmepsin II

Malaria remains a global health threat─over 400,000 deaths occurred in 2019. Plasmepsins are promising targets of antimalarial therapeutics; however, no inhibitors have reached the clinic. To fuel the progress, a detailed understanding of the pH- and ligand-dependent conformational dynamics of plasmepsins is needed. Here we present the continuous constant pH molecular dynamics study of the prototypical plasmepsin II and its complexed form with a substrate analogue. The simulations revealed that the catalytic dyads D34 and D214 are highly coupled in the apo protein and that the pepstatin binding enhances the difference in proton affinity, making D34 the general base and D214 the general acid. The simulations showed that the flap adopts an open state regardless of pH; however, upon pepstatin binding the flap can close or open depending on the protonation state of D214. These and other data are discussed and compared with the off-targets human cathepsin D and renin. This study lays the groundwork for a systematic investigation of pH- and ligand-modulated dynamics of the entire family of plasmepsins to help design more potent and selective inhibitors.

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.

Continuous Constant pH Molecular Dynamics Simulations of Transmembrane Proteins

Many membrane channels, transporters, and receptors utilize a pH gradient or proton coupling to drive functionally relevant conformational transitions. Conventional molecular dynamics simulations employ fixed protonation states, thus neglecting the coupling between protonation and conformational equilibria. Here we describe the membrane-enabled hybrid-solvent continuous constant pH molecular dynamics method for capturing atomic details of proton-coupled conformational dynamics of transmembrane proteins. Example protocols from our recent application studies of proton channels and ion/substrate transporters are discussed.

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.

Assessment of proton-coupled conformational dynamics of SARS and MERS coronavirus papain-like proteases: Implication for designing broad-spectrum antiviral inhibitors

Broad-spectrum antiviral drugs are urgently needed to stop the Coronavirus Disease 2019 pandemic and prevent future ones. The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is related to the SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), which have caused the previous outbreaks. The papain-like protease (PLpro) is an attractive drug target due to its essential roles in the viral life cycle. As a cysteine protease, PLpro is rich in cysteines and histidines, and their protonation/deprotonation modulates catalysis and conformational plasticity. Here, we report the pK_a calculations and assessment of the proton-coupled conformational dynamics of SARS-CoV-2 in comparison to SARS-CoV and MERS-CoV PLpros using the recently developed graphical processing unit (GPU)-accelerated implicit-solvent continuous constant pH molecular dynamics method with a new asynchronous replica-exchange scheme, which allows computation on a single GPU card. The calculated pK_a's support the catalytic roles of the Cys-His-Asp triad. We also found that several residues can switch protonation states at physiological pH among which is C270/271 located on the flexible blocking loop 2 (BL2) of SARS-CoV-2/CoV PLpro. Simulations revealed that the BL2 can open and close depending on the protonation state of C271/270, consistent with the most recent crystal structure evidence. Interestingly, despite the lack of an analogous cysteine, BL2 in MERS-CoV PLpro is also very flexible, challenging a current hypothesis. These findings are supported by the all-atom fixed-charge simulations and provide a starting point for more detailed studies to assist the structure-based design of broad-spectrum inhibitors against CoV PLpros.

Scalable molecular dynamics on CPU and GPU architectures with NAMD

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

Assessment of Proton-Coupled Conformational Dynamics of SARS and MERS Coronavirus Papain-like Proteases: Implication for Designing Broad-Spectrum Antiviral Inhibitors

Broad-spectrum antiviral drugs are urgently needed to stop the COVID-19 pandemic and prevent future ones. The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is related to SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), which have caused the previous outbreaks. The papain-like protease (PLpro) is an attractive drug target due to its essential roles in the viral life cycle. As a cysteine protease, PLpro is rich in cysteines and histidines and their protonation/deprotonation modulates catalysis and conformational plasticity. Here we report the pKa calculations and assessment of the proton-coupled conformational dynamics of SARS-CoV-2 in comparison to SARS-CoV and MERS-CoV PLpros using a newly developed GPU-accelerated implicit-solvent continuous constant pH molecular dynamics method with an asynchronous replica-exchange scheme. The calculated pKa's support the catalytic roles of the Cys-His-Asp triad. We also found that several residues can switch protonation states at physiological pH, among which is C270/271 located on the flexible blocking loop 2 (BL2) of SARS-CoV-2/CoV PLpro. Simulations revealed that the BL2 conformational dynamics is coupled to the titration of C271/270, in agreement with the crystal structures of SARS-CoV-2 PLpro. Simulations also revealed that BL2 in MERS-CoV PLpro is very flexible, sampling both open and closed states despite the lack of an analogous cysteine. Our work provides a starting point for more detailed mechanistic studies to assist structure-based design of broad-spectrum inhibitors against CoV PLpros.

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.

D3R Grand Challenge 4: ligand similarity and MM-GBSA-based pose prediction and affinity ranking for BACE-1 inhibitors

The Drug Design Data Resource (D3R) Grand Challenges present an opportunity to assess, in the context of a blind predictive challenge, the accuracy and the limits of tools and methodologies designed to help guide pharmaceutical drug discovery projects. Here, we report the results of our participation in the D3R Grand Challenge 4 (GC4), which focused on predicting the binding poses and affinity ranking for compounds targeting the [Formula: see text]-amyloid precursor protein (BACE-1). Our ligand similarity-based protocol using HYBRID (OpenEye Scientific Software) successfully identified poses close to the native binding mode for most of the ligands with less than 2 Å RMSD accuracy. Furthermore, we compared the performance of our HYBRID-based approach to that of AutoDock Vina and DOCK 6 and found that using a reference ligand to guide the docking process is a better strategy for pose prediction and helped HYBRID to perform better here. We also conducted end-point free energy estimates on molecules dynamics based ensembles of protein-ligand complexes using molecular mechanics combined with generalized Born surface area method (MM-GBSA). We found that the binding affinity ranking based on MM-GBSA scores have poor correlation with the experimental values. Finally, the main lessons from our participation in D3R GC4 are: (i) the generation of the macrocyclic conformers is a key step for successful pose prediction, (ii) the protonation states of the BACE-1 binding site should be treated carefully, (iii) the MM-GBSA method could not discriminate well between different predicted binding poses, and (iv) the MM-GBSA method does not perform well at predicting protein-ligand binding affinities here.

Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4

Molecular docking has been successfully used in computer-aided molecular design projects for the identification of ligand poses within protein binding sites. However, relying on docking scores to rank different ligands with respect to their experimental affinities might not be sufficient. It is believed that the binding scores calculated using molecular mechanics combined with the Poisson-Boltzman surface area (MM-PBSA) or generalized Born surface area (MM-GBSA) can predict binding affinities more accurately. In this perspective, we decided to take part in Stage 2 of the Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) to compare the performance of a quick scoring function, AutoDock4, to that of MM-GBSA in predicting the binding affinities of a set of [Formula: see text]-Amyloid Cleaving Enzyme 1 (BACE-1) ligands. Our results show that re-scoring docking poses using MM-GBSA did not improve the correlation with experimental affinities. We further did a retrospective analysis of the results and found that our MM-GBSA protocol is sensitive to details in the protein-ligand system: (i) neutral ligands are more adapted to MM-GBSA calculations than charged ligands, (ii) predicted binding affinities depend on the initial conformation of the BACE-1 receptor, (iii) protonating the aspartyl dyad of BACE-1 correctly results in more accurate binding affinity predictions.

GPU-Accelerated Implementation of Continuous Constant pH Molecular Dynamics in Amber: pKa Predictions with Single-pH Simulations

We present a GPU implementation of the continuous constant pH molecular dynamics (CpHMD) based on the most recent generalized Born implicit-solvent model in the pmemd engine of the Amber molecular dynamics package. To test the accuracy of the tool for rapid pK_a predictions, a series of 2 ns single-pH simulations were performed for over 120 titratable residues in 10 benchmark proteins that were previously used to test the various continuous CpHMD methods. The calculated pK_a's showed a root-mean-square deviation of 0.80 and correlation coefficient of 0.83 with respect to experiment. Also, 90% of the pK_a's were converged with estimated errors below 0.1 pH units. Surprisingly, this level of accuracy is similar to our previous replica-exchange simulations with 2 ns per replica and an exchange attempt frequency of 2 ps^-1 (Huang, Harris, and Shen J. Chem. Inf. Model. 2018 , 58 , 1372 - 1383 ). Interestingly, for the linked titration sites in two enzymes, although residue-specific protonation state sampling in the single-pH simulations was not converged within 2 ns, the protonation fraction of the linked residues appeared to be largely converged, and the experimental macroscopic pK_a values were reproduced to within 1 pH unit. Comparison with replica-exchange simulations with different exchange attempt frequencies showed that the splitting between the two macroscopic pK_a's is underestimated with frequent exchange attempts such as 2 ps^-1, while single-pH simulations overestimate the splitting. The same trend is seen for the single-pH vs replica-exchange simulations of a hydrogen-bonded aspartyl dyad in a much larger protein. A 2 ns single-pH simulation of a 400-residue protein takes about 1 h on a single NVIDIA GeForce RTX 2080 graphics card, which is over 1000 times faster than a CpHMD run on a single CPU core of a high-performance computing cluster node. Thus, we envision that GPU-accelerated continuous CpHMD may be used in routine pK_a predictions for a variety of applications, from assisting MD simulations with protonation state assignment to offering pH-dependent corrections of binding free energies and identifying reactive hot spots for covalent drug design.

Allosteric discrimination at the NADH/ADP regulatory site of glutamate dehydrogenase

Glutamate dehydrogenase (GDH) is a target for treating insulin-related disorders, such as hyperinsulinism hyperammonemia syndrome. Modeling native ligand binding has shown promise in designing GDH inhibitors and activators. Our computational investigation of the nicotinamide adenine diphosphate hydride (NADH)/adenosine diphosphate (ADP) site presented in this paper provides insight into the opposite allosteric effects induced at a single site of binding inhibitor NADH versus activator ADP to GDH. The computed binding free-energy difference between NADH and ADP using thermodynamic integration is -0.3 kcal/mol, which is within the -0.275 and -1.7 kcal/mol experimental binding free-energy difference range. Our simulations show an interesting model of ADP with dissimilar binding conformations at each NADH/ADP site in the GDH trimer, which explains the poorly understood strong binding but weak activation shown in experimental studies. In contrast, NADH showed similar inhibitory binding conformations at each NADH/ADP site. The structural analysis of the important residues in the NADH/ADP binding site presented in this paper may provide potential targets for mutation studies for allosteric drug design.

How Electrostatic Coupling Enables Conformational Plasticity in a Tyrosine Kinase

Protein kinases are important cellular signaling molecules involved in cancer and a multitude of other diseases. It is well-known that inactive kinases display a remarkable conformational plasticity; however, the molecular mechanisms remain poorly understood. Conformational heterogeneity presents an opportunity but also a challenge in kinase drug discovery. The ability to predictively model various conformational states could accelerate selective inhibitor design. Here we performed a proton-coupled molecular dynamics study to explore the conformational landscape of a c-Src kinase. Starting from a completely inactive structure, the simulations captured all major types of conformational states without the use of a target structure, mutation, or bias. The simulations allowed us to test the experimental hypotheses regarding the mechanism of DFG flip, its coupling to the αC-helix movement, and the formation of regulatory spine. Perhaps the most significant finding is how key titratable residues, such as DFG-Asp, αC-Glu, and HRD-Asp, change protonation states dependent on the DFG, αC, and activation loop conformations. Our data offer direct evidence to support a long-standing hypothesis that protonation of Asp favors the DFG-out state and explain why DFG flip is also possible in simulations with deprotonated Asp. The simulations also revealed intermediate states, among which a unique DFG-out/α-C state formed as DFG-Asp is moved into a back pocket forming a salt bridge with catalytic Lys, which can be tested in selective inhibitor design. Our finding of how proton coupling enables the remarkable conformational plasticity may shift the paradigm of computational studies of kinases which assume fixed protonation states. Understanding proton-coupled conformational dynamics may hold a key to further innovation in kinase drug discovery.

Dynamic Protonation Dramatically Affects the Membrane Permeability of Drug-like Molecules

Permeability (P_m) across biological membranes is of fundamental importance and a key factor in drug absorption, distribution, and development. Although the majority of drugs will be charged at some point during oral delivery, our understanding of membrane permeation by charged species is limited. The canonical model assumes that only neutral molecules partition into and passively permeate across membranes, but there is mounting evidence that these processes are also facile for certain charged species. However, it is unknown whether such ionizable permeants dynamically neutralize at the membrane surface or permeate in their charged form. To probe protonation-coupled permeation in atomic detail, we herein apply continuous constant-pH molecular dynamics along with free energy sampling to study the permeation of a weak base propranolol (PPL), and evaluate the impact of including dynamic protonation on P_m. The simulations reveal that PPL dynamically neutralizes at the lipid-tail interface, which dramatically influences the permeation free energy landscape and explains why the conventional model overestimates the assigned intrinsic permeability. We demonstrate how fixed-charge-state simulations can account for this effect, and propose a revised model that better describes pH-coupled partitioning and permeation. Our results demonstrate how dynamic changes in protonation state may play a critical role in the permeation of ionizable molecules, including pharmaceuticals and drug-like molecules, thus requiring a revision of the standard picture.

Rigorous Free Energy Perturbation Approach to Estimating Relative Binding Affinities between Ligands with Multiple Protonation and Tautomeric States

Accurate prediction of ligand binding affinities is of key importance in small molecule lead optimization and a central task in computational medicinal chemistry. Over the years, advances in both computer hardware and computational methodologies have established free energy perturbation (FEP) methods as among the most reliable and rigorous approaches to compute protein-ligand binding free energies. However, accurate description of ionization and tautomerism of ligands is still a major challenge in structure-based prediction of binding affinities. Druglike molecules are often weak acid or bases with multiple accessible protonation and tautomeric states that can contribute significantly to the binding process. To address this issue, we introduce in this work the p K_a and tautomeric state correction approach. This approach is based on free energy perturbation formalism and provides a rigorous treatment of the ionization and tautomeric equilibria of ligands in solution and in the protein complexes. A series of Kinesin Spindle Protein (KSP) and Factor Xa inhibitor molecules were used as test cases. Our results demonstrate that the p K_a and tautomeric state correction approach is able to rigorously and accurately incorporate multiple protonation and tautomeric states in the binding affinity calculations.

How Ligand Protonation State Controls Water in Protein-Ligand Binding

The role of water in protein-ligand binding has been an intensely studied topic in recent years; however, how ligand protonation state change perturbs water has not been considered. Here we show that water dynamics and interactions can be controlled by the protonation state of ligand using continuous constant pH molecular dynamics simulations of two closely related model systems, β-secretase 1 and 2 (BACE1 and BACE2), in complex with a small-molecule inhibitor. Simulations revealed that, upon binding, the inhibitor pyrimidine ring remains deprotonated in BACE1 but becomes protonated in BACE2. Pyrimidine protonation results in water displacement, rigidification of the binding pocket, and shift in the ligand binding mode from water-mediated to direct hydrogen bonding. These findings not only support but also rationalize the most recent structure-selectivity data in BACE1 drug design. Binding-induced protonation state changes are likely common; our work offers a glimpse at how modeling protein-ligand binding while allowing ligand titration can further advance the understanding of water and structure-based drug design.

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.

A New Fluorogenic Small-Molecule Labeling Tool for Surface Diffusion Analysis and Advanced Fluorescence Imaging of β-Site Amyloid Precursor Protein-Cleaving Enzyme 1 Based on Silicone Rhodamine: SiR-BACE1

β-site APP-cleaving enzyme 1 (BACE1) is a major player in the pathogenesis of Alzheimer's disease. Structural and functional fluorescence microscopy offers a powerful approach to learn about the physiology and pathophysiology of this protease. Up to now, however, common labeling techniques require genetic manipulation, use large antibodies, or are not compatible with live cell imaging. Fluorescent small molecules that specifically bind to the protein of interest can overcome these limitations. Herein, we introduce SiR-BACE1, a conjugate of the BACE1 inhibitor S-39 and SiR647, as a novel fluorogenic, tag-free, and antibody-free label for BACE1. We present its chemical development, characterize its photophysical and pharmacologic properties, and evaluate its behavior in solution, in overexpression systems, and in native brain tissue. We demonstrate its applicability in confocal, stimulated emission depletion and dynamic single-molecule microscopy. The first functional studies with SiR-BACE1 on the surface mobility of BACE1 revealed a markedly confined diffusion pattern.

Factors Influencing the Potency of Alzheimer Inhibitors: Computational and Docking Studies

Density functional theory (B3LYP/6-31G [d]) is performed to study the effect of molecular and electronic structures of the investigated β-secretase 1 (BACE1) Alzheimer's inhibitors on their biological activities and discuss the correlation between their inhibition efficiencies and quantum chemical descriptors. IC50 values of the investigated compounds are mostly affected by the substituted R2 phenyl moiety. The calculations show that the presence of electron withdrawing group increases the half maximal inhibitory concentration (IC50). Structure-activity relationship studies show that the electronic descriptors, energy of high occupied molecular orbital, ΔE, lipophilicity, hardness, and ionization potential index, are the most significant descriptors for the correlation with IC50. Molecular docking simulation is performed to explain the mode of interaction between the most potent drug and the binding sites of the BACE1 target. A good correlation between the experimental and the theoretical data confirms that the quantum chemical methods are successful tools for the discovery of novel BACE1 drugs.

Predicting Catalytic Proton Donors and Nucleophiles in Enzymes: How Adding Dynamics Helps Elucidate the Structure-Function Relationships

Despite the relevance of understanding structure-function relationships, robust prediction of proton donors and nucleophiles in enzyme active sites remains challenging. Here we tested three types of state-of-the-art computational methods to calculate the p K_a's of the buried and hydrogen bonded catalytic dyads in five enzymes. We asked the question what determines the p K_a order, i.e., what makes a residue proton donor vs a nucleophile. The continuous constant pH molecular dynamics simulations captured the experimental p K_a orders and revealed that the negative nucleophile is stabilized by increased hydrogen bonding and solvent exposure as compared to the proton donor. Surprisingly, this simple trend is not apparent from crystal structures and the static structure-based calculations. While the generality of the findings awaits further testing via a larger set of data, they underscore the role of dynamics in bridging enzyme structures and functions.

Assessment of a Single Decoupling Alchemical Approach for the Calculation of the Absolute Binding Free Energies of Protein-Peptide Complexes

The computational modeling of peptide inhibitors to target protein-protein binding interfaces is growing in interest as these are often too large, too shallow, and too feature-less for conventional small molecule compounds. Here, we present a rare successful application of an alchemical binding free energy method for the calculation of converged absolute binding free energies of a series of protein-peptide complexes. Specifically, we report the binding free energies of a series of cyclic peptides derived from the LEDGF/p75 protein to the integrase receptor of the HIV1 virus. The simulations recapitulate the effect of mutations relative to the wild-type binding motif of LEDGF/p75, providing structural, energetic and dynamical interpretations of the observed trends. The equilibration and convergence of the calculations are carefully analyzed. Convergence is aided by the adoption of a single-decoupling alchemical approach with implicit solvation, which circumvents the convergence difficulties of conventional double-decoupling protocols. We hereby present the single-decoupling methodology and critically evaluate its advantages and limitations. We also discuss some of the challenges and potential pitfalls of binding free energy calculations for complex molecular systems which have generally limited their applicability to the quantitative study of protein-peptide binding equilibria.

Proton-Coupled Conformational Allostery Modulates the Inhibitor Selectivity for β-Secretase

Many important pharmaceutical targets, such as aspartyl proteases and kinases, exhibit pH-dependent dynamics, functions and inhibition. Accurate prediction of their binding free energies is challenging because current computational techniques neglect the effects of pH. Here we combine free energy perturbation calculations with continuous constant pH molecular dynamics to explore the selectivity of a small-molecule inhibitor for β-secretase (BACE1), an important drug target for Alzheimer's disease. The calculations predicted identical affinity for BACE1 and the closely related cathepsin D at high pH; however, at pH 4.6 the inhibitor is selective for BACE1 by 1.3 kcal/mol, in excellent agreement with experiment. Surprisingly, the pH-dependent selectivity can be attributed to the protonation of His45, which allosterically modulates a loop-inhibitor interaction. Allosteric regulation induced by proton binding is likely common in biology; considering such allosteric sites could lead to exciting new opportunities in drug design.

Conformational dynamics of cathepsin D and binding to a small-molecule BACE1 inhibitor

BACE1 is a major therapeutic target for prevention and treatment of Alzheimer's disease. Developing inhibitors that can selectively target BACE1 in favor of other proteases, especially cathepsin D (CatD), has presented significant challenges. Here, we investigate the conformational dynamics and protonation states of BACE1 and CatD using continuous constant pH molecular dynamics with pH replica-exchange sampling protocol. Despite similar structure, BACE1 and CatD exhibit markedly different active site dynamics. BACE1 displays pH-dependent flap dynamics that controls substrate accessibility, while the CatD flap is relatively rigid and remains open in the pH range 2.5-6. Interestingly, although each protease hydrolyzes peptide bonds, the protonation states of the catalytic dyads are different within the active pH range. The acidic and basic components of the BACE1 catalytic dyad are clear, while either aspartic acid of the CatD catalytic dyad could play the role of acid or base. Finally, we investigate binding of the inhibitor LY2811376 developed by Eli Lilly to BACE1 and CatD. Surprisingly, in the enzyme active pH range, LY2811376 forms a stronger salt bridge with the catalytic dyad in CatD than in BACE1, which might explain the retinal toxicity of the inhibitor related to off-target inhibition of CatD. This work highlights the complexity and challenge in structure-based drug design where receptor-ligand binding induces protonation state change in both the protein and the inhibitor. © 2017 Wiley Periodicals, Inc.

Development of 2-aminooxazoline 3-azaxanthene β-amyloid cleaving enzyme (BACE) inhibitors with improved selectivity against Cathepsin D

As part of an ongoing effort at Amgen to develop a disease-modifying therapy for Alzheimer's disease, we have previously used the aminooxazoline xanthene (AOX) scaffold to generate potent and orally efficacious BACE1 inhibitors. While AOX-BACE1 inhibitors demonstrated acceptable cardiovascular safety margins, a retinal pathological finding in rat toxicological studies demanded further investigation. It has been widely postulated that such retinal toxicity might be related to off-target inhibition of Cathepsin D (CatD), a closely related aspartyl protease. We report the development of AOX-BACE1 inhibitors with improved selectivity against CatD by following a structure- and property-based approach. Our efforts culminated in the discovery of a picolinamide-substituted 3-aza-AOX-BACE1 inhibitor absent of retinal effects in an early screening rat toxicology study.

Computational investigation of proton transfer, pKa shifts and pH-optimum of protein-DNA and protein-RNA complexes

Protein-nucleic acid interactions play a crucial role in many biological processes. This work investigates the changes of pKa values and protonation states of ionizable groups (including nucleic acid bases) that may occur at protein-nucleic acid binding. Taking advantage of the recently developed pKa calculation tool DelphiPka, we utilize the large protein-nucleic acid interaction database (NPIDB database) to model pKa shifts caused by binding. It has been found that the protein's interfacial basic residues experience favorable electrostatic interactions while the protein acidic residues undergo proton uptake to reduce the energy cost upon the binding. This is in contrast with observations made for protein-protein complexes. In terms of DNA/RNA, both base groups and phosphate groups of nucleotides are found to participate in binding. Some DNA/RNA bases undergo pKa shifts at complex formation, with the binding process tending to suppress charged states of nucleic acid bases. In addition, a weak correlation is found between the pH-optimum of protein-DNA/RNA binding free energy and the pH-optimum of protein folding free energy. Overall, the pH-dependence of protein-nucleic acid binding is not predicted to be as significant as that of protein-protein association. Proteins 2017; 85:282-295. © 2016 Wiley Periodicals, Inc.

All-Atom Molecular Dynamics of Virus Capsids as Drug Targets

Virus capsids are protein shells that package the viral genome. Although their morphology and biological functions can vary markedly, capsids often play critical roles in regulating viral infection pathways. A detailed knowledge of virus capsids, including their dynamic structure, interactions with cellular factors, and the specific roles that they play in the replication cycle, is imperative for the development of antiviral therapeutics. The following Perspective introduces an emerging area of computational biology that focuses on the dynamics of virus capsids and capsid-protein assemblies, with particular emphasis on the effects of small-molecule drug binding on capsid structure, stability, and allosteric pathways. When performed at chemical detail, molecular dynamics simulations can reveal subtle changes in virus capsids induced by drug molecules a fraction of their size. Here, the current challenges of performing all-atom capsid-drug simulations are discussed, along with an outlook on the applicability of virus capsid simulations to reveal novel drug targets.

Mechanisms of peptide hydrolysis by aspartyl and metalloproteases

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