Coarse-Grained Modeling of Nucleic Acids Using Anisotropic Gay-Berne and Electric Multipole Potentials

Insights into the selectivity of a brain-penetrant CDK4/6 vs CDK1/2 inhibitor for glioblastoma used in multiple replica molecular dynamics simulations

Cyclin dependent kinases (CDKs) play an important role in cell cycle regulation and their dysfunction is associated with many cancers. That is why CDKs have been attractive targets for the treatment of cancer. Glioblastoma is a cancer caused by the aberrant expression of CDK4/6, so exploring the mechanism of the selection of CDK4/6 toward inhibitors relative to the other family members CDK1/2 is essential. In this work, multiple replica molecular dynamics (MRMD) simulations, principal component analysis (PCA), free energy landscapes (FELs), molecular mechanics Poisson-Boltzmann/Generalized Born surface area (MM-PB/GBSA) and other methods were integrated to decipher the selectively binding mechanism of the inhibitor N1J to CDK4/6 and CDK1/2. Molecular electrostatic potential (MESP) analysis provides an explanation for the N1J selectivity. Residue-based free energy decomposition reveals that most of the hot residues are located at the same location of CDKs proteins, but the different types of residues in different proteins cause changes in binding energy, which is considered as a potential developmental direction to improve the selectivity of inhibitors to CDK4/6. These results provide insights into the source of inhibitor and CDK4/6 selectivity for the future development of more selective inhibitors.Communicated by Ramaswamy H. Sarma.

Effect of Disulfide Bridge on the Binding of SARS-CoV-2 Fusion Peptide to Cell Membrane: A Coarse-Grained Study

In this paper, we present the parameterization of the CAVS coarse-grained (CG) force field for 20 amino acids, and our CG simulations show that the CAVS force field could accurately predict the amino acid tendency of the secondary structure. Then, we used the CAVS force field to investigate the binding of a severe acute respiratory syndrome-associated coronavirus fusion peptide (SARS-CoV-2 FP) to a phospholipid bilayer: a long FP (FP-L) containing 40 amino acids and a short FP (FP-S) containing 26 amino acids. Our CAVS CG simulations displayed that the binding affinity of the FP-L to the bilayer is higher than that of the FP-S. We found that the FP-L interacted more strongly with membrane cholesterol than the FP-S, which should be attributed to the stable helical structure of the FP-L at the C-terminus. In addition, we discovered that the FP-S had one major and two minor membrane-bound states, in agreement with previous all-atom molecular dynamics (MD) studies. However, we found that both the C-terminal and N-terminal amino acid residues of the FP-L can strongly interact with the bilayer membrane. Furthermore, we found that the disulfide bond formed between Cys840 and Cys851 stabilized the helices of the FP-L at the C-terminus, enhancing the interaction between the FP-L and the bilayer membrane. Our work indicates that the stable helical structure is crucial for binding the SARS-CoV-2 FP to cell membranes. In particular, the helical stability of FP should have a significant influence on the FP-membrane binding.

Systematic bottom-up molecular coarse-graining via force and torque matching using anisotropic particles

We derive a systematic and general method for parametrizing coarse-grained molecular models consisting of anisotropic particles from fine-grained (e.g. all-atom) models for condensed-phase molecular dynamics simulations. The method, which we call anisotropic force-matching coarse-graining (AFM-CG), is based on rigorous statistical mechanical principles, enforcing consistency between the coarse-grained and fine-grained phase-space distributions to derive equations for the coarse-grained forces, torques, masses, and moments of inertia in terms of properties of a condensed-phase fine-grained system. We verify the accuracy and efficiency of the method by coarse-graining liquid-state systems of two different anisotropic organic molecules, benzene and perylene, and show that the parametrized coarse-grained models more accurately describe properties of these systems than previous anisotropic coarse-grained models parametrized using other methods that do not account for finite-temperature and many-body effects on the condensed-phase coarse-grained interactions. The AFM-CG method will be useful for developing accurate and efficient dynamical simulation models of condensed-phase systems of molecules consisting of large, rigid, anisotropic fragments, such as liquid crystals, organic semiconductors, and nucleic acids.

Deciphering the Mechanism of Binding Selectivity of Chlorofluoroacetamide-Based Covalent Inhibitors toward L858R/T790M Resistance Mutation

Covalent modification of the oncogenic mutant epidermal growth factor receptor (EGFR) by small molecules is an efficient strategy for achieving an enhanced and sustained pharmacological effect in the treatment of non-small-cell lung cancer. NSP-037 (18), an irreversible inhibitor of the L858R/T790M double-mutant EGFR (EGFR^DM) using α-chlorofluoroacetamide (CFA) as a novel warhead, has seven times the inhibition selectivity for EGFR^DM over the wild type (EGFR^WT), as compared to clinically approved osimertinib (7). Here, we employ multiple computational approaches to elucidate the mechanism underlining this improved selectivity, as well as the effect of CFA on the selectivity enhancement of inhibitor 18 over 7. We find that EGFR^DM undergoes significantly larger conformational changes than EGFR^WT upon binding to 18. The conformational stability of the diamine side chain and the CFA motif of 18 in the orthosteric site of EGFR^DM is identified as key for the disparate binding mechanism and inhibitory prowess of 18 with respect to EGFR^WT and EGFR^DM and 18's higher selectivity than 7. The binding free energy of the 18-bound complexes is -6.38 kcal/mol greater than that of the 7-bound complexes, explaining the difference in selectivity of these inhibitors. Further, free energy decomposition analysis indicates that the electrostatic contribution of key residues plays an important role in the 18-bound complexes. QM/MM calculations show that the most favored mechanism for the Cys797 alkylation reaction is the direct displacement mechanism through a CFA-based inhibitor, producing a reaction with the lowest energy barrier and most stable product.

Binding mechanism of inhibitors to SARS-CoV-2 main protease deciphered by multiple replica molecular dynamics simulations

The outbreak caused by SARS-CoV-2 has received extensive worldwide attention. As the main protease (M^pro) in SARS-CoV-2 has no human homologues, it is feasible to reduce the possibility of targeting the host protein by accidental drugs. Thus, M^pro has been an attractive target of efficient drug design for anti-SARS-CoV-2 treatment. In this work, multiple replica molecular dynamics (MRMD) simulations, principal component analysis (PCA), free energy landscapes (FELs), and the molecular mechanics-generalized Born surface area (MM-GBSA) method were integrated together to decipher the binding mechanism of four inhibitors masitinib, O6K, FJC and GQU to M^pro. The results indicate that the binding of four inhibitors clearly affects the structural flexibility and internal dynamics of M^pro along with dihedral angle changes of key residues. The analysis of FELs unveils that the stability in the relative orientation and geometric position of inhibitors to M^pro is favorable for inhibitor binding. Residue-based free energy decomposition reveals that the inhibitor-M^pro interaction networks involving hydrogen bonding interactions and hydrophobic interactions provide significant information for the design of potent inhibitors against M^pro. The hot spot residues including H41, M49, F140, N142, G143, C145, H163, H164, M165, E166 and Q189 identified by computational alanine scanning are considered as reliable targets of clinically available inhibitors inhibiting the activities of M^pro.

Molecular mechanism related to the binding of fluorophores to Mango-II revealed by multiple-replica molecular dynamics simulations

Recently, RNA aptamers activating small-molecule fluorophores have been successfully applied to tag and track RNAs in vivo. It is of significance to investigate the molecular mechanism of the fluorophore-RNA aptamer bindings at the atomic level to seek a possible pathway to enhance the fluorescence efficiency of fluorophores. In this work, multiple replica molecular dynamics (MRMD) simulations, essential dynamics (ED) analysis, and hierarchical clustering analysis were coupled to probe the effect of A22U mutation on the binding of two fluorophores, TO1-Biotin (TO1) and TO3-Biotin (TO3), to the Mango-II RNA aptamer (Mango-II). ED analysis reveals that A22U induces alterations in the binding pocket and sites of TO1 and TO3 to the Mango-II, which in turn tunes the fluorophore-RNA interface and changes the interactions of TO1 and TO3 with separate nucleotides of Mango-II. Dynamics analyses also uncover that A22U exerts the opposite impact on the molecular surface areas of the Mango-II and sugar puckers of nucleotides 22 and 23 in Mango-II complexed with TO1 and TO3. Moreover, the calculations of binding free energies suggest that A22U strengthens the binding ability of TO1 to the mutated Mango-II but weakens TO3 to the mutated Mango-II when compared with WT. These findings imply that point mutation in nucleotides possibly tune the fluorescence of fluorophores binding to RNA aptamers, providing a possible scheme to enhance the fluorescence of fluorophores.

Insights into effect of the Asp25/Asp25' protonation states on binding of inhibitors Amprenavir and MKP97 to HIV-1 protease using molecular dynamics simulations and MM-GBSA calculations

The protonation states of two aspartic acids in the catalytic strands of HIV-1 protease (PR) remarkably affect bindings of inhibitors to PR. It is requisite for the design of potent inhibitors towards PR to investigate the influences of Asp25/Asp25' protonated states on dynamics behaviour of PR and binding mechanism of inhibitors to PR. In this work, molecular dynamics (MD) simulations, MM-GBSA method and principal component (PC) analysis were coupled to explore the effect of Asp25/Asp25' protonation states on conformational changes of PR and bindings of Amprenavir and MKP97 to PR. The results show that the Asp25/Asp25' protonation states exert different impacts on structural fluctuations, flexibility and motion modes of PR. Dynamics analysis verifies that Asp25/Asp25' protonated states highly affect conformational dynamics of two flaps in PR. The binding free energy calculations results suggest that the Asp25/Asp25' protonated states obviously strengthen bindings of inhibitors to PR compared to the non-protonation state. Calculations of residue-based free energy decomposition indicate that the Asp25/Asp25' protonation not only disturbs the interaction network of inhibitors with PR but also stabilizes bindings of inhibitors to PR by cancelling the electrostatic repulsive interaction. Therefore, special attentions should be paid to the Asp25/Asp25' protonation in the design of potent inhibitors towards PR.

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.

Binding Selectivity of Inhibitors toward Bromodomains BAZ2A and BAZ2B Uncovered by Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

Two Bromodomain-Containing proteins BAZ2A and BAZ2B are responsible for remodeling chromatin and regulating noncoding RNAs. As for our current studies, integration of multiple short molecular dynamics simulations (MSMDSs) with molecular mechanics generalized Born surface area (MM-GBSA) method is adopted for insights into binding selectivity of three small molecules D8Q, D9T and UO1 to BAZ2A against BAZ2B. The calculations of MM-GBSA unveil that selectivity of inhibitors toward BAZ2A and BAZ2B highly depends on the enthalpy changes and the details uncover that D8Q has better selectivity toward BAZ2A than BAZ2B, D9T more favorably bind to BAZ2B than BAZ2A, and UO1 does not show obvious selectivity toward these two proteins. The analysis of interaction network between residues and inhibitors indicates that seven residues are mainly responsible for the selectivity of D8Q, six residues for D9T and four residues provide significant contributions to associations of UO1 with two proteins. Moreover the analysis of interaction network not only reveals warm spots of inhibitor bindings to BAZ2A and BAZ2B but also unveils that common residue pairs, including (W1816, W1887), (P1817, P1888), (F1818, F1889), (V1822, V1893), (N1823, N1894),(L1826, L1897), (V1827, V1898), (F1872, F1943), (N1873, N1944) and (V1879, I1950) belonging to (BAZ2A, BAZ2B), induce mainly binding differences of inhibitors to BAZ2A and BAZ2B. Hence, insights from our current studies offer useful dynamics information relating with conformational alterations and structure-affinity relationship at atomistic levels for novel therapeutic strategies toward BAZ2A and BAZ2B.

"Dividing and Conquering" and "Caching" in Molecular Modeling

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, most important methodological advancements in more than half century of molecular modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes "dividing and conquering" and/or "caching" in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but results are not transferable. Deep learning has been utilized to realize more efficient and accurate ways of "dividing and conquering" and "caching" along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science. This framework is based on a third class of algorithm that facilitates molecular modeling through partially transferable in resolution "caching" of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for "dividing and conquering" and "caching" in complex molecular systems.

Bottom-Up Coarse-Grained Modeling of DNA

Recent advances in methodology enable effective coarse-grained modeling of deoxyribonucleic acid (DNA) based on underlying atomistic force field simulations. The so-called bottom-up coarse-graining practice separates fast and slow dynamic processes in molecular systems by averaging out fast degrees of freedom represented by the underlying fine-grained model. The resulting effective potential of interaction includes the contribution from fast degrees of freedom effectively in the form of potential of mean force. The pair-wise additive potential is usually adopted to construct the coarse-grained Hamiltonian for its efficiency in a computer simulation. In this review, we present a few well-developed bottom-up coarse-graining methods, discussing their application in modeling DNA properties such as DNA flexibility (persistence length), conformation, "melting," and DNA condensation.

Backbone oriented anisotropic coarse grains for efficient simulations of polymers

Despite the fact that anisotropic particles have been introduced to describe molecular interactions for decades, they have been poorly used for polymers because of their computing time overhead and the absence of a relevant proof of their impact in this field. We first report a method using anisotropic beads for polymers, which solves the computing time issue by considering that beads keep their principal orientation alongside the mean local backbone vector of the polymer chain, avoiding the computation of torques during the dynamics. Applying this method to a polymer bulk, we study the effect of anisotropic interactions vs isotropic ones for various properties such as density, pressure, topology of the chain network, local structure, and orientational order. We show that for different classes of potentials traditionally used in molecular simulations, those backbone oriented anisotropic beads can solve numerous issues usually encountered with isotropic interactions. We conclude that the use of backbone oriented anisotropic beads is a promising approach for the development of realistic coarse-grained potentials for polymers.

Probing molecular mechanism of inhibitor bindings to bromodomain-containing protein 4 based on molecular dynamics simulations and principal component analysis

It is well known that bromodomain-containing protein 4 (BRD4) has been thought as a promising target utilized for treating various human diseases, such as inflammatory disorders, malignant tumours, acute myelogenous leukaemia (AML), bone diseases, etc. For this study, molecular dynamics (MD) simulations, binding free energy calculations, and principal component analysis (PCA) were integrated together to uncover binding modes of inhibitors 8P9, 8PU, and 8PX to BRD4(1). The results obtained from binding free energy calculations show that van der Waals interactions act as the main regulator in bindings of inhibitors to BRD4(1). The information stemming from PCA reveals that inhibitor associations extremely affect conformational changes, internal dynamics, and movement patterns of BRD4(1). Residue-based free energy decomposition method was wielded to unveil contributions of independent residues to inhibitor bindings and the data signify that hydrogen bonding interactions and hydrophobic interactions are decisive factors affecting bindings of inhibitors to BRD4(1). Meanwhile, eight residues Trp81, Pro82, Val87, Leu92, Leu94, Cys136, Asn140, and Ile146 are recognized as the common hot interaction spots of three inhibitors with BRD4(1). The results from this work are expected to provide a meaningfully theoretical guidance for design and development of effective inhibitors inhibiting of the activity of BRD4.

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.

Arbitrary Resolution with Two Bead Types Coarse-Grained Strategy and Applications to Protein Recognition

Molecular recognition is a fundamental step in essentially any biological process. However, the kinetic processes during association and dissociation are difficult to be efficiently sampled by direct all-atom molecular dynamics simulations because of the large spatial and temporal scales. Here we propose an arbitrary resolution with two bead types (ART) coarse-grained (CG) strategy that is adept in molecular recognition. ART is a universal user-customized CG strategy that can generate a system-specific CG force field anytime and be applied to any system with an arbitrary CG resolution according to research requirements. ART CG simulations can be very efficiently performed with implicit solvation in prevalent simulation packages and provide interfaces for any enhanced sampling method. We used three applications, HLA-HIV epitope recognition, barnase-barstar association, and trimeric TRAF2 self-assembly, to validate the feasibility of the ART CG strategy, its advantages in protein recognition, and its high performance in simulations. Regular CG simulations can successfully achieve valid protein recognitions without any prior bound structure.

Molecular mechanism of inhibitor bindings to bromodomain-containing protein 9 explored based on molecular dynamics simulations and calculations of binding free energies

Recently, bromodomain-containing protein 9 (BRD9) has been a prospective therapeutic target for anticancer drug design. Molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method were adopted to explore binding modes of three inhibitors (5SW, 5U2, and 5U6) to BRD9 and identify the hot spot of the inhibitor-BRD9 binding. The results indicate that the inhibitor 5SW has the strongest binding ability to BRD9 among the current three inhibitors. Furthermore, the rank of the binding free energies predicted by MM-GBSA approach agrees with that determined by the experimental values. In addition, inhibitor-residue interactions were computed by using residue-based free-energy decomposition method and the results suggest that residue His42 produces the CH-H interactions, residues Asn100, Ile53 and Val49 produce the CH-[Formula: see text] interactions with three inhibitors and Tyr106, Phe45 and Phe44 generate the π-π interactions with inhibitors. Notably, the residue Asn140 forms hydrogen bonding interactions with three inhibitors. This research is expected to provide useful molecular basis and dynamics information at atomic levels for the design of potent inhibitors inhibiting the activity of BRD9.

Effect of mutations on binding of ligands to guanine riboswitch probed by free energy perturbation and molecular dynamics simulations

Riboswitches can regulate gene expression by direct and specific interactions with ligands and have recently attracted interest as potential drug targets for antibacterial. In this work, molecular dynamics (MD) simulations, free energy perturbation (FEP) and molecular mechanics generalized Born surface area (MM-GBSA) methods were integrated to probe the effect of mutations on the binding of ligands to guanine riboswitch (GR). The results not only show that binding free energies predicted by FEP and MM-GBSA obtain an excellent correlation, but also indicate that mutations involved in the current study can strengthen the binding affinity of ligands GR. Residue-based free energy decomposition was applied to compute ligand-nucleotide interactions and the results suggest that mutations highly affect interactions of ligands with key nucleotides U22, U51 and C74. Dynamics analyses based on MD trajectories indicate that mutations not only regulate the structural flexibility but also change the internal motion modes of GR, especially for the structures J12, J23 and J31, which implies that the aptamer domain activity of GR is extremely plastic and thus readily tunable by nucleotide mutations. This study is expected to provide useful molecular basis and dynamics information for the understanding of the function of GR and possibility as potential drug targets for antibacterial.

Molecular mechanism with regard to the binding selectivity of inhibitors toward FABP5 and FABP7 explored by multiple short molecular dynamics simulations and free energy analyses

Recently, fatty acid binding proteins 5 and 7 (FABP5 and FABP7) have been regarded as the prospective targets for clinically treating multiple diseases related to FABPs.

MOLC. A reversible coarse grained approach using anisotropic beads for the modelling of organic functional materials

We describe the development and implementation of a coarse grained (CG) modelling approach where complex organic molecules, and particularly the π-conjugated ones often employed in organic electronics, are modelled in terms of connected sets of attractive-repulsive biaxial Gay-Berne ellipsoidal beads. The CG model is aimed at reproducing realistically large scale morphologies (e.g. up to 100 nm thick films) for the materials involved, while being able to generate, with a back-mapping procedure, atomistic coordinates suitable, with limited effort, to be applied for charge transport calculations. Detailed methodology and an application to the common hole transporter material α-NPD are provided.

Revealing binding selectivity of ligands toward murine double minute 2 and murine double minute X based on molecular dynamics simulations and binding free energy calculations

It is well known that the interactions of p53 with murine double minute 2 and murine double minute X, namely MDM2 and MDMX, have been significant targets of efficient anti-cancer drug design. In this study, molecular dynamics (MD) simulations, principal component (PC) analysis and binding free energy calculations are combined to recognize binding selectivity of three ligands to MDM2 and MDMX. The binding free energies were estimated by using molecular mechanics generalized Born surface area (MM-GBSA) method and the obtained results display that the increase in the binding enthalpy of three ligands to MDM2 relative to MDMX mainly drives the binding selectivity of them toward MDM2 and MDMX. The information obtained from PC analysis shows that the associations of ligands exert important impacts on internal dynamics of MDM2 and MDMX. Meanwhile, the calculations of residue-based free energy decomposition not only identify the hot interaction spots of ligands with MDM2 and MDMX, but also show the residues (L54, M53), (Y67, Y66), (V93, V92), (H96, P95), (I99, I98) and (Y100, Y99) in (MDM2, MDMX) are responsible for most contributions to the binding selectivity of three ligands toward MDM2 and MDMX. It is believed that this work can provide useful information for design of highly selective and dual inhibitors targeting MDM2 and MDMX.Communicated by Ramaswamy H. Sarma.

Molecular Mechanism of Binding Selectivity of Inhibitors toward BACE1 and BACE2 Revealed by Multiple Short Molecular Dynamics Simulations and Free-Energy Predictions

The β-amyloid cleaving enzymes 1 and 2 (BACE1 and BACE2) have been regarded as the prospective targets for clinically treating Alzheimer's disease (AD) in the last two decades. Thus, insight into the binding differences of inhibitors to BACE1 and BACE2 is of significance for designing highly selective inhibitors toward the two proteins. In this work, multiple short molecular dynamics (MSMD) simulations are coupled with the molecular mechanics generalized Born surface area (MM-GBSA) method to probe the binding selectivity of three inhibitors DBO, CS9, and SC7 on BACE1 over BACE2. The results show that the entropy effect plays a key role in selectivity identification of inhibitors toward BACE1 and BACE2, which determines that DBO has better selectivity toward BACE2 over BACE1, while CS9 and CS7 can more favorably bind to BACE1 than BACE2. The hierarchical clustering analysis based on energetic contributions of residues suggests that BACE1 and BACE2 share the common hot interaction spots. The residue-based free-energy decomposition method was applied to compute the inhibitor-residue interaction spectrum, and the results recognize four common binding subpockets corresponding to the different groups of inhibitors, which can be used as efficient targets for designing highly selective inhibitors toward BACE1 and BACE2. Therefore, these results provide a useful molecular basis and dynamics information for development of highly selective inhibitors targeting BACE1 and BACE2.

Effect of Cholesterol and 6-Ketocholestanol on Membrane Dipole Potential and Sterol Flip-Flop Motion in Bilayer Membranes

A variety of experimental and theoretical approaches have been employed to investigate the sterol flip-flop motion in lipid bilayer membranes. However, the sterol effect on the dipole potential of lipid bilayer membranes is less well studied and the influence of dipole potential on sterol flip-flop motion in lipid bilayer membranes is less well understood. In our previous works, we have demonstrated the performance of our coarse-grained (CG) model in the computation of the dipole potential. In this work, five 30 μs CG simulations of dimyristoylphosphatidylcholine (DMPC) bilayers were carried out at different sterol concentrations (in a range from 10 to 50% mole fraction). Then, a comparison was made between the effects of cholesterol (CHOL) and 6-ketocholestanol (6-KC) on the dipole potential of DMPC lipid bilayers as well as the sterol flip-flop motion. Our CG simulations show that the membrane dipole potential is impacted more significantly by 6-KC than by CHOL. This finding is consistent with recent experimental studies. Meanwhile, our work suggests that the sterol-sterol interactions (in particular, electrostatic interactions) should be critical to the formation of sterol-sterol clusters, which would hinder the sterol flip-flop motion inside the lipid bilayers. This is in support of the recent experimental study on the sterol transportation in lipid bilayer membranes.

Analytic theory of finite-size effects in supercell modeling of charged interfaces

The Ewald3D sum with the tinfoil boundary condition (e3dtf) evaluates the electrostatic energy of a finite unit cell inside an infinitely periodic supercell. Although it has been used as a de facto standard treatment of electrostatics for simulations of extended polar or charged interfaces, the finite-size effect on simulated properties has yet to be fully understood. There is, however, an intuitive way to quantify the average effect arising from the difference between the e3dtf and Coulomb potentials on the response of mobile charges to contact surfaces with fixed charges and/or to an applied external electric field. Although any charged interface formed by mobile countercharges that compensate the fixed charges fluctuates upon a change in the acting electric field, the distance between a pair of oppositely charged interfaces is found to be nearly stationary, which allows an analytic finite-size correction to the amount of countercharges. Application of the theory to solvated electric double layers (insulator/electrolyte interfaces) predicts that the state of complete charge compensation is invariant with respect to solvent permittivities, which is confirmed by a proper analysis of simulation data in the literature.

Decoding molecular mechanism of inhibitor bindings to CDK2 using molecular dynamics simulations and binding free energy calculations

CDK2 can be used as an attractive target for development of efficient inhibitors curing multiple disease relating with CDK2. In this work, molecular dynamics (MD) simulations and binding free energy calculations were coupled to probe conformational changes of CDK2 due to inhibitor associations and binding mechanisms of inhibitors PM1, FMD and X64 to CDK2. The results suggest that the binding strength of FMD and X64 to CDK2 is stronger than that of PM1. Principal component (PC) analysis and cross-correlation map calculations based on the equilibrated MD trajectories demonstrate that the structural difference in inhibitors exerts important impact on motion modes and dynamics behavior of CDK2. Residue-based free energy decomposition method was adopted to estimate the inhibitor-residue spectrum. The results not only efficiently identify the hot interaction spot of inhibitors with CDK2 but also show that the hydrophobic rings R1, R2 and R3 as well as polar groups of three inhibitors play key roles in favorably binding of inhibitors to CDK2. This work is expected to contribute energetic basis and dynamics information to development of promising inhibitors toward CDK2.Communicated by Ramaswamy H. Sarma.

Insight into selective mechanism of class of I-BRD9 inhibitors toward BRD9 based on molecular dynamics simulations

Recently, bromodomain-containing protein 9 (BRD9), 7 (BRD7), and 4 (BRD4) have been potential targets of anticancer drug design. Molecular dynamic simulations followed by molecular mechanics Poisson-Boltzmann surface area calculation were performed to study the selective mechanism of I-BRD9 inhibitor H1B and its derivatives N1D, TVU, and 5V2 toward BRD9 and BRD4. The rank of our calculated binding free energies agrees with that of the experimental data. The results show that binding free energy of H1B to BRD7 is slightly lower than that of H1B to BRD9, and all four inhibitors bind more tightly to BRD9 than to BRD4. Decomposition of binding free energies into individual residues implies that Ile164 and Asn211 in BRD7 and Ile53 and Asn100 in BRD9 play a significant role in the selectivity of H1B toward BRD7 and BRD9. Besides, several key residues Phe44, Ile53, Asn100, Thr104 in BRD9 and Pro82, Lys91, Asn140, Asp144 in BRD4 that are located in the ZA-loop and BC-loop provide significant contributions to binding selectivity of inhibitors to BRD9 and BRD4. This study is expected to provide important theoretical guidance for rational designs of highly selective inhibitors targeting BRD9 and BRD4.

General patchy ellipsoidal particle model for the aggregation behaviors of shape- and/or surface-anisotropic building blocks

We present a general patchy ellipsoidal particle model suitable for conducting dynamics simulations of the aggregation behaviors of various shape- and/or surface-anisotropic colloids, especially patchy ellipsoids with continuously variable shape and tunable patchiness. To achieve higher computational efficiency in dynamics simulations, we employ a multi-GPU acceleration technique based on a domain decomposition algorithm. The validation and performance evaluation of this GPU-assisted model are performed by simulating several typical benchmark systems of non-patchy and patchy ellipsoids. Given the generality and efficiency of our GPU-assisted patchy ellipsoidal particle model, it will provide a highly feasible dynamics simulation framework to investigate the aggregation behaviors of anisotropic soft matter systems comprised of shape- and/or surface-anisotropic building blocks.

Dynamics revelation of conformational changes and binding modes of heat shock protein 90 induced by inhibitor associations

Heat shock protein 90 (Hsp90) has been an attractive target of potential drug design for antitumor treatment. The current work integrates molecular dynamics (MD) simulations, calculations of binding free energy, and principal component (PC) analysis with scanning of inhibitor-residue interaction to probe the binding modes of inhibitors YK9, YKJ and YKI to Hsp90 and identify the hot spot of the inhibitor-Hsp90 binding. The results suggest that the introductions of two groups G1 and G2 into YKJ and YKI strengthen the binding ability of YKJ and YKI to Hsp90 compared to YK9. PC analysis based MD trajectories prove that inhibitor bindings exert significant effects on the conformational changes, internal dynamics and motion modes of Hsp90, especially for the helix α2 and the loops L1 and L2. The calculations of residue-based free energy decomposition and scanning of the inhibitor-Hsp90 interaction suggest that six residues L107, G108, F138, Y139, W162 and F170 construct the common hot spot of the inhibitor-residue interactions. Moreover the substitutions of the groups G1 and G2 in YKJ and YKI lead to two additional hydrogen bonding interactions and multiple hydrophobic interactions for bindings of YKJ and YKI to Hsp90. This work is also expected to contribute theoretical hints for the design of potent inhibitors toward Hsp90.

Sequence-Dependent Three Interaction Site Model for Single- and Double-Stranded DNA

We develop a robust coarse-grained model for single- and double-stranded DNA by representing each nucleotide by three interaction sites (TIS) located at the centers of mass of sugar, phosphate, and base. The resulting TIS model includes base-stacking, hydrogen bond, and electrostatic interactions as well as bond-stretching and bond angle potentials that account for the polymeric nature of DNA. The choices of force constants for stretching and the bending potentials were guided by a Boltzmann inversion procedure using a large representative set of DNA structures extracted from the Protein Data Bank. Some of the parameters in the stacking interactions were calculated using a learning procedure, which ensured that the experimentally measured melting temperatures of dimers are faithfully reproduced. Without any further adjustments, the calculations based on the TIS model reproduce the experimentally measured salt and sequence-dependence of the size of single-stranded DNA (ssDNA), as well as the persistence lengths of poly(dA) and poly(dT) chains. Interestingly, upon application of mechanical force, the extension of poly(dA) exhibits a plateau, which we trace to the formation of stacked helical domains. In contrast, the force-extension curve (FEC) of poly(dT) is entropic in origin and could be described by a standard polymer model. We also show that the persistence length of double-stranded DNA, formed from two complementary ssDNAs, is consistent with the prediction based on the worm-like chain. The persistence length, which decreases with increasing salt concentration, is in accord with the Odijk-Skolnick-Fixman theory intended for stiff polyelectrolyte chains near the rod limit. Our model predicts the melting temperatures of DNA hairpins with excellent accuracy, and we are able to recover the experimentally known sequence-specific trends. The range of applications, which did not require adjusting any parameter after the initial construction based solely on PDB structures and melting profiles of dimers, attests to the transferability and robustness of the TIS model for ssDNA and dsDNA.

Zinc ion-induced conformational changes in new Delphi metallo-β-lactamase 1 probed by molecular dynamics simulations and umbrella sampling

The hydrolysis of a β-lactam core ring caused by new Delphi metallo-β-lactamase 1 (NDM-1) with the help of two zinc cofactors induces significant resistance toward β-lactam antibiotics. Molecular dynamics (MD) simulations and the umbrella sampling method are integrated to study the conformational change mechanism of NDM-1 mediated by zinc ion binding. The statistical analyses of interaction contacts of the antibiotic ampicillin (AMP) with residues based on MD trajectories suggest that two Zn ions are essential for maintaining the binding of AMP with NDM-1. Umbrella sampling simulations further reveal that double-Zn coordination exerts strong restriction on the motions of loop L10 relative to loops L3 and L4. Principal component (PC) analysis also demonstrates that zinc ion binding totally inhibits the motion extent of NDM-1 and changes internal motion modes in NDM-1. We expect that the current study can provide significant dynamical information involving conformational changes of NDM-1 for the development of efficient inhibitors to decrease drug resistance of NDM-1 toward antibiotics.

Twist-stretch profiles of DNA chains

Helical molecules change their twist number under the effect of a mechanical load. We study the twist-stretch relation for a set of short DNA molecules modeled by a mesoscopic Hamiltonian. Finite temperature path integral techniques are applied to generate a large ensemble of possible configurations for the base pairs of the sequence. The model also accounts for the bending and twisting fluctuations between adjacent base pairs along the molecules stack. Simulating a broad range of twisting conformation, we compute the helix structural parameters by averaging over the ensemble of base pairs configurations. The method selects, for any applied force, the average twist angle which minimizes the molecule's free energy. It is found that the chains generally over-twist under an applied stretching and the over-twisting is physically associated to the contraction of the average helix diameter, i.e. to the damping of the base pair fluctuations. Instead, assuming that the maximum amplitude of the bending fluctuations may decrease against the external load, the DNA molecule first over-twists for weak applied forces and then untwists above a characteristic force value. Our results are discussed in relation to available experimental information albeit for kilo-base long molecules.

Insight into binding mechanisms of inhibitors MKP56, MKP73, MKP86, and MKP97 to HIV-1 protease by using molecular dynamics simulation

HIV-1 protease (PR) has been a significant target for design of potent inhibitors curing acquired immunodeficiency syndrome. Molecular dynamics simulations coupled with molecular mechanics Poisson-Boltzmann surface area method were performed to study interaction modes of four inhibitors MKP56, MKP73, MKP86, and MKP97 with PR. The results suggest that the main force controlling interactions of inhibitors with PR should be contributed by van der Waals interactions between inhibitors and PR. The cross-correlation analyses based on MD trajectories show that inhibitor binding produces significant effect on the flap dynamics of PR. Hydrogen bond analyses indicate that inhibitors can form stable hydrogen bonding interactions with the residues from the catalytic strands of PR. The contributions of separate residues to inhibitor bindings are evaluated by using residue-based free energy decomposition method and the results demonstrate that the CH-π and CH-CH interactions between the hydrophobic groups of inhibitors with residues drive the associations of inhibitors with PR. We expect that this study can provide a significant theoretical aid for design of potent inhibitors targeting PR.

Functional roles of magnesium binding to extracellular signal-regulated kinase 2 explored by molecular dynamics simulations and principal component analysis

Molecular dynamics (MD) simulations coupled with principal component (PC) analysis were carried out to study functional roles of Mg²⁺ binding to extracellular signal-regulated kinase 2 (ERK2). The results suggest that Mg²⁺ binding heavily decreases eigenvalue of the first principal component and totally inhibits motion strength of ERK2, which favors stabilization of ERK2 structure. Binding free energy predictions indicate that Mg²⁺ binding produces an important effect on binding ability of adenosine triphosphate (ATP) to ERK2 and strengthens the ATP binding. The calculations of residue-based free energy decomposition show that lack of Mg²⁺ weakens interactions between the hydrophobic rings of ATP and five residues I29, V37, A50, L105, and L154. Hydrogen bond analyses also prove that Mg²⁺ binding increases occupancies of hydrogen bonds formed between ATP and residues K52, Q103, D104, and M106. We expect that this study can provide a significant theoretical hint for designs of anticancer drugs targeting ERK2.

Mutation L1196M-induced conformational changes and the drug resistant mechanism of anaplastic lymphoma kinase studied by free energy perturbation and umbrella sampling

Anaplastic lymphoma kinase (ALK) has been regarded as a promising drug target in the treatment of tumors and the mutation L1196M induces different levels of drug resistance toward the existing inhibitors.

Molecular Mechanism and Energy Basis of Conformational Diversity of Antibody SPE7 Revealed by Molecular Dynamics Simulation and Principal Component Analysis

More and more researchers are interested in and focused on how a limited repertoire of antibodies can bind and correspondingly protect against an almost limitless diversity of invading antigens. In this work, a series of 200-ns molecular dynamics (MD) simulations followed by principal component (PC) analysis and free energy calculations were performed to probe potential mechanism of conformational diversity of antibody SPE7. The results show that the motion direction of loops H3 and L3 is different relative to each other, implying that a big structural difference exists between these two loops. The calculated energy landscapes suggest that the changes in the backbone angles ψ and φ of H-Y101 and H-Y105 provide significant contributions to the conformational diversity of SPE7. The dihedral angle analyses based on MD trajectories show that the side-chain conformational changes of several key residues H-W33, H-Y105, L-Y34 and L-W93 around binding site of SPE7 play a key role in the conformational diversity of SPE7, which gives a reasonable explanation for potential mechanism of cross-reactivity of single antibody toward multiple antigens.

Clarifying binding difference of ATP and ADP to extracellular signal-regulated kinase 2 by using molecular dynamics simulations

Extracellular signal-regulated kinase 2 is a promising target for designs and development of anticancer drugs. Molecular dynamics simulations and molecular mechanics Poisson-Boltzmann method were applied to study binding difference of ADP and ATP to extracellular signal-regulated kinase 2. The results prove that the binding ability of ATP to extracellular signal-regulated kinase 2 is stronger than that of ADP. Principal component analysis performed by using molecular dynamics trajectories suggests that binding of ADP and ATP to extracellular signal-regulated kinase 2 change motion directions of two helices α1 and α2. Residue-based free energy decomposition method was adopted to calculate contributions of separate residues to associations of ADP and ATP with extracellular signal-regulated kinase 2. The results show that ADP and ATP produce strong CH-π interactions with five residues Ile29, Val37, Ala50, Leu105, and Leu154. In addition, five hydrogen bonding interactions of ADP and ATP with residues Lys52, Gln103, Asp104, and Met106 also stabilize bindings of ADP and ATP to extracellular signal-regulated kinase 2. Overall, the CH-π interactions of ATP with five residues Ile29, Val37, Ala50, Leu105, and Leu154 are stronger than ADP. This study is expected to contribute a significant theoretical hint for designs of anticancer drugs targeting extracellular signal-regulated kinase 2.