Molecular dynamics in multidimensional space explains how mutations affect the association path of neomycin to a riboswitch.

Riboswitches are messenger RNA (mRNA) fragments binding specific small molecules to regulate gene expression. A synthetic N1 riboswitch, inserted into yeast mRNA controls the translation of a reporter gene in response to neomycin. However, its regulatory activity is sensitive to single-point RNA mutations, even those distant from the neomycin binding site. While the association paths of neomycin to N1 and its variants remain unknown, recent fluorescence kinetic experiments indicate a two-step process driven by conformational selection. This raises the question of which step is affected by mutations. To address this, we performed all-atom two-dimensional replica-exchange molecular dynamics simulations for N1 and U14C, U14C[Formula: see text], U15A, and A17G mutants, ensuring extensive conformational sampling of both RNA and neomycin. The obtained neomycin association and binding paths, along with multidimensional free-energy profiles, revealed a two-step binding mechanism, consisting of conformational selection and induced fit. Neomycin binds to a preformed N1 conformation upon identifying a stable upper stem and U-turn motif in the riboswitch hairpin. However, the positioning of neomycin in the binding site occurs at different RNA-neomycin distances for each mutant, which may explain their different regulatory activities. The subsequent induced fit arises from the interactions of the neomycin's N3 amino group with RNA, causing the G9 backbone to rearrange. In the A17G mutant, the critical C6-A17/G17 stacking forms at a closer RNA-neomycin distance compared to N1. These findings together with estimated binding free energies coincide with experiments and elucidate why the A17G mutation decreases and U15A enhances N1 activity in response to neomycin.

Integration of pharmacoproteomic and computational approaches reveals the cellular signal transduction pathways affected by apatinib in gastric cancer cell lines.

Apatinib is known to be a highly selective vascular endothelial growth factor receptor 2 (VEGFR2) inhibitor with anti-angiogenic and anti-tumor properties. In a phase III study, the objective response rate to apatinib was low. It remains unclear why the effectivity of apatinib varies among patients and what type of patients are candidates for the treatment. In this study, we investigated the anti-tumor efficacy of apatinib against 13 gastric cancer cell lines and found that it differed depending on the cell line. Using integrated wet and dry approaches, we showed that apatinib was a multi-kinase inhibitor of c-Kit, RAF1, VEGFR1, VEGFR2, and VEGFR3, predominantly inhibiting c-Kit. Notably, KATO-III, which was the most apatinib-sensitive among the gastric cancer cell lines investigated, was the only cell line expressing c-Kit, RAF1, VEGFR1, and VEGFR3 but not VEGFR2. Furthermore, we identified SNW1 as a molecule affected by apatinib that plays an important role in cell survival. Finally, we identified the molecular network related to SNW1 that was affected by treatment with apatinib. These results suggest that the mechanism of action of apatinib in KATO-III cells is independent of VEGFR2 and that the differential efficacy of apatinib was due to differences in expression patterns of receptor tyrosine kinases. Furthermore, our results suggest that the differential efficacy of apatinib in gastric cell lines may be attributed to SNW1 phosphorylation levels at a steady state. These findings contribute to a deeper understanding of the mechanism of action of apatinib in gastric cancer cells.

Development of a GCN-based model to predict in vitro phototoxicity from the chemical structure and HOMO-LUMO gap.

The interaction between sunlight and drugs can lead to phototoxicity in patients who have received such drugs. Phototoxicity assessment is a regulatory requirement globally and one of the main toxicity screening steps in the early stages of drug discovery. An in silico-in vitro approach has been utilized mainly for toxicology assessments at these stages. Although several quantitative structure-activity relationship (QSAR) models for phototoxicity have been developed, in silico technology to evaluate phototoxicity has not been well established. In this study, we attempted to develop an artificial intelligence (AI) model to predict the in vitro Neutral Red Uptake Phototoxicity Test results from a chemical structure and its derived information. To accomplish this, we utilized an open-source software library, kMoL. kMoL employs a graph convolutional neural networks (GCN) approach, which allows it to learn the data for the specified chemical structure. kMoL also utilizes the integrated gradient (IG) method, enabling it to visually display the substructures contributing to any positive results. To construct this AI model, we used only the chemical structure as a basis, then added the descriptors and the HOMO-LUMO gap, which was obtained from quantum chemical calculations. As a result, the assortment of chemical structures and the HOMO-LUMO gap produced an AI model with high discrimination performance, and an F1 score of 0.857. Additionally, our AI model could visualize the substructures involved in phototoxicity using the IG method. Our AI model can be applied as a toxicity screening method and could enhance productivity in drug development.

Structural dynamics of the N-terminal SH2 domain of PI3K in its free and CD28-bound states.

Protein conformational changes with fluctuations are fundamental aspects of protein-protein interactions (PPIs); understanding these motions is required for the rational design of PPI-regulating compounds. Src homology 2 (SH2) domains are commonly found in adapter proteins involved in signal transduction and specifically bind to consensus motifs of proteins containing phosphorylated tyrosine (pY). Here, we analysed the interaction between the N-terminal SH2 domain (nSH2) of the regulatory subunit in phosphoinositide 3-kinase (PI3K) and the cytoplasmic region of the T-cell co-receptor, CD28, using NMR and molecular dynamics (MD) simulations. First, we assigned the backbone signals of nSH2 on 1 H-15 N heteronuclear single quantum coherence spectra in the absence or presence of the CD28 phosphopeptide, SDpYMNMTPRRPG. Chemical shift perturbation experiments revealed allosteric changes at the BC loop and the C-terminal region of nSH2 upon CD28 binding. NMR relaxation experiments showed a conformational exchange associated with CD28 binding in these regions. The conformational stabilisation of the C-terminal region correlated with the regulation of PI3K catalytic function. Further, using 19 F- and 31 P-labelled CD28 phosphopeptide, we analysed the structural dynamics of CD28 and demonstrated that the aromatic ring of the pY residue fluctuated between multiple conformations upon nSH2 binding. Our MD simulations largely explained the NMR results and the structural dynamics of nSH2 and CD28 in both bound and unbound states. Notably, in addition to its major conformation, we detected a minor conformation of nSH2 in the CD28 bound state that may explain the allosteric conformational change in the BC loop.

Practical Protocols for Efficient Sampling of Kinase-Inhibitor Binding Pathways Using Two-Dimensional Replica-Exchange Molecular Dynamics.

Molecular dynamics (MD) simulations are increasingly used to study various biological processes such as protein folding, conformational changes, and ligand binding. These processes generally involve slow dynamics that occur on the millisecond or longer timescale, which are difficult to simulate by conventional atomistic MD. Recently, we applied a two-dimensional (2D) replica-exchange MD (REMD) method, which combines the generalized replica exchange with solute tempering (gREST) with the replica-exchange umbrella sampling (REUS) in kinase-inhibitor binding simulations, and successfully observed multiple ligand binding/unbinding events. To efficiently apply the gREST/REUS method to other kinase-inhibitor systems, we establish modified, practical protocols with non-trivial simulation parameter tuning. The current gREST/REUS simulation protocols are tested for three kinase-inhibitor systems: c-Src kinase with PP1, c-Src kinase with Dasatinib, and c-Abl kinase with Imatinib. We optimized the definition of kinase-ligand distance as a collective variable (CV), the solute temperatures in gREST, and replica distributions and umbrella forces in the REUS simulations. Also, the initial structures of each replica in the 2D replica space were prepared carefully by pulling each ligand from and toward the protein binding sites for keeping stable kinase conformations. These optimizations were carried out individually in multiple short MD simulations. The current gREST/REUS simulation protocol ensures good random walks in 2D replica spaces, which are required for enhanced sampling of inhibitor dynamics around a target kinase.

Selective covalent targeting of SARS-CoV-2 main protease by enantiopure chlorofluoroacetamide.

The coronavirus disease 2019 (COVID-19) pandemic has necessitated the development of antiviral agents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The main protease (Mpro) is a promising target for COVID-19 treatment. Here, we report an irreversible SARS-CoV-2 Mpro inhibitor possessing chlorofluoroacetamide (CFA) as a warhead for the covalent modification of Mpro. Ugi multicomponent reaction using chlorofluoroacetic acid enabled the rapid synthesis of dipeptidic CFA derivatives that identified 18 as a potent inhibitor of SARS-CoV-2 Mpro. Among the four stereoisomers, (R,R)-18 exhibited a markedly higher inhibitory activity against Mpro than the other isomers. Reaction kinetics and computational docking studies suggest that the R configuration of the CFA warhead is crucial for the rapid covalent inhibition of Mpro. Our findings highlight the prominent influence of the CFA chirality on the covalent modification of proteinous cysteines and provide the basis for improving the potency and selectivity of CFA-based covalent inhibitors.

The inherent flexibility of receptor binding domains in SARS-CoV-2 spike protein.

Spike (S) protein is the primary antigenic target for neutralization and vaccine development for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It decorates the virus surface and undergoes large motions of its receptor binding domains (RBDs) to enter the host cell. Here, we observe Down, one-Up, one-Open, and two-Up-like structures in enhanced molecular dynamics simulations, and characterize the transition pathways via inter-domain interactions. Transient salt-bridges between RBDA and RBDC and the interaction with glycan at N343B support RBDA motions from Down to one-Up. Reduced interactions between RBDA and RBDB in one-Up induce RBDB motions toward two-Up. The simulations overall agree with cryo-electron microscopy structure distributions and FRET experiments and provide hidden functional structures, namely, intermediates along Down-to-one-Up transition with druggable cryptic pockets as well as one-Open with a maximum exposed RBD. The inherent flexibility of S-protein thus provides essential information for antiviral drug rational design or vaccine development.

Weight average approaches for predicting dynamical properties of biomolecules.

Recent advances in atomistic molecular dynamics (MD) simulations of biomolecules allow us to explore their conformational spaces widely, observing large-scale conformational fluctuations or transitions between distinct structures. To reproduce or refine experimental data using MD simulations, structure ensembles, which are characterized by multiple structures and their statistical weights on the rugged free-energy landscapes, are often used. Here, we summarize weight average approaches for various experimental measurements. Weight average approaches are now applied to hybrid quantum mechanics/molecular mechanics MD simulations to predict fast vibrational motions in a protein with a high accuracy for better understanding of molecular functions from atomic structures.

Reduced efficacy of a Src kinase inhibitor in crowded protein solution.

The inside of a cell is highly crowded with proteins and other biomolecules. How proteins express their specific functions together with many off-target proteins in crowded cellular environments is largely unknown. Here, we investigate an inhibitor binding with c-Src kinase using atomistic molecular dynamics (MD) simulations in dilute as well as crowded protein solution. The populations of the inhibitor, 4-amino-5-(4-methylphenyl)-7-(t-butyl)pyrazolo[3,4-d]pyrimidine (PP1), in bulk solution and on the surface of c-Src kinase are reduced as the concentration of crowder bovine serum albumins (BSAs) increases. This observation is consistent with the reduced PP1 inhibitor efficacy in experimental c-Src kinase assays in addition with BSAs. The crowded environment changes the major binding pathway of PP1 toward c-Src kinase compared to that in dilute solution. This change is explained based on the population shift mechanism of local conformations near the inhibitor binding site in c-Src kinase.

Molecular Basis for Two Stereoselective Diels-Alderases that Produce Decalin Skeletons*.

Enzymes catalyzing [4+2] cycloaddition have attracted increasing attention because of their key roles in natural product biosynthesis. Here, we solved the X-ray crystal structures of a pair of decalin synthases, Fsa2 and Phm7, that catalyze intramolecular [4+2] cycloadditions to form enantiomeric decalin scaffolds during biosynthesis of the HIV-1 integrase inhibitor equisetin and its stereochemical opposite, phomasetin. Computational modeling, using molecular dynamics simulations as well as quantum chemical calculations, demonstrates that the reactions proceed through synergetic conformational constraints assuring transition state-like substrates folds and their stabilization by specific protein-substrate interactions. Site-directed mutagenesis experiments verified the binding models. Intriguingly, the flexibility of bound substrates is largely different in two enzymes, suggesting the distinctive mechanism of dynamics regulation behind these stereoselective reactions. The proposed reaction mechanism herein deepens the basic understanding how these enzymes work but also provides a guiding principle to create artificial enzymes.

Mutations of N1 Riboswitch Affect its Dynamics and Recognition by Neomycin Through Conformational Selection.

Short, structured fragments of non-coding mRNA may act as molecular switches upon binding specific ligands, regulating the translation of proteins encoded downstream this mRNA sequence. One switch, called riboswitch N1, is regulated by aminoglycosides such as neomycin. Nucleobase mutations in the apical loop, although distant from the binding pocket, significantly affect neomycin affinity and riboswitch regulatory efficiency. To explain this influence, we conducted molecular dynamics simulations using generalized replica exchange with solute tempering (gREST). Translation assay of a reporter protein in a yeast system shows that mutating A17 to G in the riboswitch apical loop reduces 6-fold the translation regulation efficiency of the mutant. Indeed, simulations of the unbound riboswitch show that G17 frequently stacks with base 7, while base 8 is stabilized towards the binding site in a way that it may interfere with the conformational selection mechanism and decrease riboswitch regulatory activity. In the riboswitch complexes, this single-point A to G mutation disrupts a strong hydrogen bond between nucleotides 5 and 17 and, instead, a new hydrogen bond between residue 17 and neomycin is created. This change forces neomycin to occupy a slightly shifted position in the binding pocket, which increases neomycin flexibility. Our simulations of the U14C mutation suggest that the riboswitch complex with neomycin is more stable if cytosine 14 is protonated. A hydrogen bond between the RNA phosphate and protonated cytosine appears as the stabilizing factor. Also, based on the cell-free translation assay and isothermal titration calorimetry experiments, mutations of nucleotides 14 and 15 affect only slightly the riboswitch ability to bind the ligand and its activity. Indeed, the simulation of the unbound U15A mutant suggests conformations preformed for ligand binding, which may explain slightly higher regulatory activity of this mutant. Overall, our results corroborate the in vivo and in vitro experiments on the N1 riboswitch-neomycin system, detail the relationship between nucleobase mutations and RNA dynamics, and reveal the conformations playing the major role in the conformational selection mechanism.

Glycan Cluster Shielding and Antibody Epitopes on Lassa Virus Envelop Protein.

An understanding of how an antiviral monoclonal antibody recognizes its target is vital for the development of neutralizing antibodies and vaccines. The extensive glycosylation of viral proteins almost certainly affects the antibody response, but the investigation of such effects is hampered by the huge range of structures and interactions of surface glycans through their inherent complexity and flexibility. Here, we built an atomistic model of a fully glycosylated envelope protein complex of the Lassa virus and performed molecular dynamics simulations to characterize the impact of surface glycans on the antibody response. The simulations attested to the variety of conformations and interactions of surface glycans. The results show that glycosylation nonuniformly shields the surface of the complex and only marginally affects protein dynamics. The glycans gather in distinct clusters through interaction with protein residues, and only a few regions are left accessible by an antibody. We successfully recovered known protein epitopes by integrating the simulation results with existing sequence- and structure-based epitope prediction methods. The results emphasize the rich structural environment of glycans and demonstrate that shielding is not merely envelopment by a uniform blanket of sugars. This work provides a molecular basis for integrating otherwise elusive structural properties of glycans into vaccine and neutralizing antibody developments.

Elucidation of interactions regulating conformational stability and dynamics of SARS-CoV-2 S-protein.

The ongoing COVID-19 pandemic caused by the new coronavirus, SARS-CoV-2, calls for urgent developments of vaccines and antiviral drugs. The spike protein of SARS-CoV-2 (S-protein), which consists of trimeric polypeptide chains with glycosylated residues on the surface, triggers the virus entry into a host cell. Extensive structural and functional studies on this protein have rapidly advanced our understanding of the S-protein structure at atomic resolutions, although most of these structural studies overlook the effect of glycans attached to the S-protein on the conformational stability and functional motions between the inactive down and active up forms. Here, we performed all-atom molecular dynamics simulations of both down and up forms of a fully glycosylated S-protein in solution as well as targeted molecular dynamics simulations between them to elucidate key interdomain interactions for stabilizing each form and inducing the large-scale conformational transitions. The residue-level interaction analysis of the simulation trajectories detects distinct amino acid residues and N-glycans as determinants on conformational stability of each form. During the conformational transitions between them, interdomain interactions mediated by glycosylated residues are switched to play key roles on the stabilization of another form. Electrostatic interactions, as well as hydrogen bonds between the three receptor binding domains, work as driving forces to initiate the conformational transitions toward the active form. This study sheds light on the mechanisms underlying conformational stability and functional motions of the S-protein, which are relevant for vaccine and antiviral drug developments.

CHARMM-GUI Free Energy Calculator for Absolute and Relative Ligand Solvation and Binding Free Energy Simulations.

Alchemical free energy simulations have long been utilized to predict free energy changes for binding affinity and solubility of small molecules. However, while the theoretical foundation of these methods is well established, seamlessly handling many of the practical aspects regarding the preparation of the different thermodynamic end states of complex molecular systems and the numerous processing scripts often remains a burden for successful applications. In this work, we present CHARMM-GUI Free Energy Calculator (http://www.charmm-gui.org/input/fec) that provides various alchemical free energy perturbation molecular dynamics (FEP/MD) systems with input and post-processing scripts for NAMD and GENESIS. Four submodules are available: Absolute Ligand Binder (for absolute ligand binding FEP/MD), Relative Ligand Binder (for relative ligand binding FEP/MD), Absolute Ligand Solvator (for absolute ligand solvation FEP/MD), and Relative Ligand Solvator (for relative ligand solvation FEP/MD). Each module is designed to build multiple systems of a set of selected ligands at once for high-throughput FEP/MD simulations. The capability of Free Energy Calculator is illustrated by absolute and relative solvation FEP/MD of a set of ligands and absolute and relative binding FEP/MD of a set of ligands for T4-lysozyme in solution and the adenosine A2A receptor in a membrane. The calculated free energy values are overall consistent with the experimental and published free energy results (within ∼1 kcal/mol). We hope that Free Energy Calculator is useful to carry out high-throughput FEP/MD simulations in the field of biomolecular sciences and drug discovery.

Prediction of Protein-Ligand Binding Pose and Affinity Using the gREST+FEP Method.

The accurate prediction of protein-ligand binding affinity is a central challenge in computational chemistry and in-silico drug discovery. The free energy perturbation (FEP) method based on molecular dynamics (MD) simulation provides reasonably accurate results only if a reliable structure is available via high-resolution X-ray crystallography. To overcome the limitation, we propose a sequential prediction protocol using generalized replica exchange with solute tempering (gREST) and FEP. At first, ligand binding poses are predicted using gREST, which weakens protein-ligand interactions at high temperatures to sample multiple binding poses. To avoid ligand dissociation at high temperatures, a flat-bottom restraint potential centered on the binding site is applied in the simulation. The binding affinity of the most reliable pose is then calculated using FEP. The protocol is applied to the bindings of ten ligands to FK506 binding proteins (FKBP), showing the excellent agreement between the calculated and experimental binding affinities. The present protocol, which is referred to as the gREST+FEP method, would help to predict the binding affinities without high-resolution structural information on the ligand-bound state.

Structural Mechanisms Underlying Activity Changes in an AMPA-type Glutamate Receptor Induced by Substitutions in Its Ligand-Binding Domain.

α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-type glutamate receptors produce postsynaptic current by transmitting an agonist-induced structural change in the ligand-binding domain (LBD) to the transmembrane channel. Receptors carrying T686S/A substitutions in their LBDs produce weaker glutamate-evoked currents than wild-type (WT) receptors. However, the substitutions induce little differences in the crystal structures of their LBDs. To understand the structural mechanism underlying reduced activities of these AMPAR variants, we analyzed the structural dynamics of WT, T686S, and T686A variants of LBD using nuclear magnetic resonance. The HD exchange studies of the LBDs showed that the kinetic step where the ligand-binding cleft closes was changed by the substitutions, and the substitution-induced population shift from cleft-closed to cleft-open structures is responsible for the reduced activities of the variants. The chemical shift analyses revealed another structural equilibrium between cleft-locked and cleft-partially-open conformations. The substitution-induced population shift in this equilibrium may be related to slower desensitization observed for these variants.

Replica-Exchange Umbrella Sampling Combined with Gaussian Accelerated Molecular Dynamics for Free-Energy Calculation of Biomolecules.

We have developed an enhanced conformational sampling method combining replica-exchange umbrella sampling (REUS) with Gaussian accelerated molecular dynamics (GaMD). REUS enhances the sampling along predefined reaction coordinates, while GaMD accelerates the conformational dynamics by adding a boost potential to the system energy. The method, which we call GaREUS (Gaussian accelerated replica-exchange umbrella sampling), enhances the sampling more efficiently than REUS or GaMD, while the computational resource for GaREUS is the same as that required for REUS. The two-step reweighting procedure using the multistate Bennett acceptance ratio method and the cumulant expansion for the exponential average is applied to the simulation trajectories for obtaining the unbiased free-energy landscapes. We apply GaREUS to the calculations of free-energy landscapes for three different cases: conformational equilibria of N-glycan, folding of chignolin, and conformational change of adenyl kinase. We show that GaREUS speeds up the convergences of free-energy calculations using the same amount of computational resources as REUS. The free-energy landscapes reweighted from the trajectories of GaREUS agree with previously reported ones. GaREUS is applicable to free-energy calculations of various biomolecular dynamics and functions with reasonable computational costs.

Encounter complexes and hidden poses of kinase-inhibitor binding on the free-energy landscape.

Modern drug discovery increasingly focuses on the drug-target binding kinetics which depend on drug (un)binding pathways. The conventional molecular dynamics simulation can observe only a few binding events even using the fastest supercomputer. Here, we develop 2D gREST/REUS simulation with enhanced flexibility of the ligand and the protein binding site. Simulation (43 µs in total) applied to an inhibitor binding to c-Src kinase covers 100 binding and unbinding events. On the statistically converged free-energy landscapes, we succeed in predicting the X-ray binding structure, including water positions. Furthermore, we characterize hidden semibound poses and transient encounter complexes on the free-energy landscapes. Regulatory residues distant from the catalytic core are responsible for the initial inhibitor uptake and regulation of subsequent bindings, which was unresolved by experiments. Stabilizing/blocking of either the semibound poses or the encounter complexes can be an effective strategy to optimize drug-target residence time.

Replica-Exchange Methods for Biomolecular Simulations.

In this study, a replica-exchange method was developed to overcome conformational sampling difficulties in computer simulations of spin glass or other systems with rugged free-energy landscapes. This method was then applied to the protein-folding problem in combination with molecular dynamics (MD) simulation. Owing to its simplicity and sampling efficiency, the replica-exchange method has been applied to many other biological problems and has been continuously improved. The method has often been combined with other sampling techniques, such as umbrella sampling, free-energy perturbation, metadynamics, and Gaussian accelerated MD (GaMD). In this chapter, we first summarize the original replica-exchange molecular dynamics (REMD) method and discuss how new algorithms related to the original method are implemented to add new features. Heterogeneous and flexible structures of an N-glycan in a solution are simulated as an example of applications by REMD, replica exchange with solute tempering, and GaMD. The sampling efficiency of these methods on the N-glycan system and the convergence of the free-energy changes are compared. REMD simulation protocols and trajectory analysis using the GENESIS software are provided to facilitate the practical use of advanced simulation methods.

De Novo Prediction of Binders and Nonbinders for T4 Lysozyme by gREST Simulations.

Molecular recognition underpins all specific protein-ligand interactions and is essential for biomolecular functions. The prediction of canonical binding poses and distinguishing binders from nonbinders are much sought after goals. Here, we apply the generalized replica exchange with solute tempering method, gREST, combined with a flat-bottom potential to evaluate binder and nonbinder interactions with a T4 lysozyme Leu99Ala mutant. The buried hydrophobic cavity and possibility of coupled conformational changes in this protein make binding predictions difficult. The present gREST simulations, enabling enhanced flexibilities of the ligand and protein residues near the binding site, sample bindings in multiple poses, and correct portrayal of X-ray structures. The free-energy profiles of binders (benzene, ethylbenzene, and n-hexylbenzene) are distinct from those of nonbinders (phenol and benzaldehyde). Bindings of the two larger molecules seem to be associated with a structural change toward an excited conformation of the protein, which agrees with experimental findings. The protocol is generally applicable to various proteins having buried cavities with limited access for ligands with different shapes, sizes, and chemical properties.