Adding energy minimization strategy to peptide‐design algorithm enables better search for RNA‐binding peptides: Redesigned λ N peptide binds boxB RNA

Our previously developed peptide‐design algorithm was improved by adding an energy minimization strategy which allows the amino acid sidechains to move in a broad configuration space during sequence evolution. In this work, the new algorithm was used to generate a library of 21‐mer peptides which could substitute for λ N peptide in binding to boxB RNA. Six potential peptides were obtained from the algorithm, all of which exhibited good binding capability with boxB RNA. Atomistic molecular dynamics simulations were then conducted to examine the ability of the λ N peptide and three best evolved peptides, viz. Pept01, Pept26, and Pept28, to bind to boxB RNA. Simulation results demonstrated that our evolved peptides are better at binding to boxB RNA than the λ N peptide. Sequence searches using the old (without energy minimization strategy) and new (with energy minimization strategy) algorithms confirm that the new algorithm is more effective at finding good RNA‐binding peptides than the old algorithm. © 2016 Wiley Periodicals, Inc.     

Toward quantitative estimates of binding affinities for protein–ligand systems involving large inhibitor compounds: A steered molecular dynamics simulation route

Understanding binding mechanisms between enzymes and potential inhibitors and quantifying protein – ligand affinities in terms of binding free energy is of primary importance in drug design studies. In this respect, several approaches based on molecular dynamics simulations, often combined with docking techniques, have been exploited to investigate the physicochemical properties of complexes of pharmaceutical interest. Even if the geometric properties of a modeled protein – ligand complex can be well predicted by computational methods, it is still challenging to rank with chemical accuracy a series of ligand analogues in a consistent way. In this article, we face this issue calculating relative binding free energies of a focal adhesion kinase, an important target for the development of anticancer drugs, with pyrrolopyrimidine‐based ligands having different inhibitory power. To this aim, we employ steered molecular dynamics simulations combined with nonequilibrium work theorems for free energy calculations. This technique proves very powerful when a series of ligand analogues is considered, allowing one to tackle estimation of protein – ligand relative binding free energies in a reasonable time. In our cases, the calculated binding affinities are comparable with those recovered from experiments by exploiting the Michaelis – Menten mechanism with a competitive inhibitor.     

Restoration of Ribozyme Tertiary Contact and Function by Using a Molecular Glue for RNA

Some RNA classes require folding into the proper higher‐order structures to exert their functions. Hammerhead ribozyme (HHR) requires a folding conformation stabilized by tertiary interaction for full activity. A rationally engineered HHR was developed that was inactive, but could be activated by a synthetic RNA‐binding ligand, naphthyridine carbamate tetramer with Z‐stilbene linker (Z‐NCTS). Binding of Z‐NCTS could induce the formation of an active folding structure and thereby restore ribozyme activity, where Z‐NCTS acts as a molecular glue to bring two isolated RNA loops into contact with each other. Next, we designed a Z‐NCTS‐responsive genetic switch using the HHR sequence inserted into the 3′ untranslated region as a cis‐acting element. We demonstrated that the rationally designed ribozyme switch enabled regulation of gene expression by Z‐NCTS and was functional in mammalian cells.     

Formation of a Ligand‐Assisted Complex of Two RNA Hairpin Loops

The hairpin structure is one of the most common secondary structures in RNA and holds a central position in the stream of RNA folding from a non‐structured RNA to structurally complex and functional ribonucleoproteins. Since the RNA secondary structure is strongly correlated to the function and can be modulated by the binding of small molecules, we have investigated the modulation of RNA folding by a ligand‐assisted formation of loop–loop complexes of two RNA hairpin loops. With a ligand (NCT6), designed based on the ligand binding to the G–G mismatches in double‐stranded DNA, we successfully demonstrated the formation of both inter‐ and intra‐molecular NCT6‐assisted complex of two RNA hairpin loops. NCT6 selectively bound to the two hairpin loops containing (CGG)₃ in the loop region. Native polyacrylamide gel electrophoresis analysis of two doubly‐labeled RNA hairpin loops clearly showed the formation of intermolecular NCT6‐assisted loop–loop complex. Förster resonance energy‐transfer studies of RNA constructs containing two hairpin loops, in which each hairpin was labeled with Alexa488 and Cy3 fluorophores, showed the conformational change of the RNA constructs upon binding of NCT6. These experimental data showed that NCT6 simultaneously bound to two hairpin RNAs at the loop region, and can induce the conformational change of the RNA molecule. These data strongly support that NCT6 functions as molecular glue for two hairpin RNAs.     

A new extension of classical molecular dynamics: An electron transfer algorithm

The molecular dynamics is one of the most widely used methods for the simulation of the properties corresponding to ionic motion. Unfortunately, classical molecular dynamics cannot be applied for electron transfer simulation. Suggested modification of the molecular dynamics allows performing the electron transfer from one particle to another during simulation runtime. All additional data structure and the corresponding algorithms are presented in this article. The method can be applied to the systems with pair Van der Waals and Coulomb interactions. Moreover, it may be extended for many‐bodied interatomic interactions. In addition, an algorithm of transference numbers calculation has been designed. This extension is not an independent method but it can be useful for simulating the systems with high concentration of electron donors and acceptors. © 2017 Wiley Periodicals, Inc.     

Ligand binding affinity prediction by linear interaction energy methods

A recent method for estimating ligand binding affinities is extended. This method employs averages of interaction potential energy terms from molecular dynamics simulations or other thermal conformational sampling techniques. Incorporation of systematic deviations from electrostatic linear response, derived from free energy perturbation studies, into the absolute binding free energy expression significantly enhances the accuracy of the approach. This type of method may be useful for computational prediction of ligand binding strengths, e.g., in drug design applications.     

Explicit ion, implicit water solvation for molecular dynamics of nucleic acids and highly charged molecules

An explicit ion, implicit water solvent model for molecular dynamics was developed and tested with DNA and RNA simulations. The implicit water model uses the finite difference Poisson (FDP) model with the smooth permittivity method implemented in the OpenEye ZAP libraries. Explicit counter-ions, co-ions, and nucleic acid were treated with a Langevin dynamics molecular dynamics algorithm. Ion electrostatics is treated within the FDP model when close to the solute, and by the Coulombic model when far from the solute. The two zone model reduces computation time, but retains an accurate treatment of the ion atmosphere electrostatics near the solute. Ion compositions can be set to reproduce specific ionic strengths. The entire ion/water treatment is interfaced with the molecular dynamics package CHARMM. Using the CHARMM-ZAPI software combination, the implicit solvent model was tested on A and B form duplex DNA, and tetraloop RNA, producing stable simulations with structures remaining close to experiment. The model also reproduced the A to B duplex DNA transition. The effect of ionic strength, and the structure of the counterion atmosphere around B form duplex DNA were also examined.     

Identification of ligands for RNA targets via structure-based virtual screening: HIV-1 TAR

Binding of the Tat protein to TAR RNA is necessary for viral replication of HIV-1. We screened the Available Chemicals Directory (ACD) to identify ligands to bind to a TAR RNA structure using a four-step docking procedure: rigid docking first, followed by three steps of flexible docking using a pseudobrownian Monte Carlo minimization in torsion angle space with progressively more detailed conformational sampling on a progressively smaller list of top-ranking compounds. To validate the procedure, we successfully docked ligands for five RNA complexes of known structure. For ranking ligands according to binding avidity, an empirical binding free energy function was developed which accounts, in particular, for solvation, isomerization free energy, and changes in conformational entropy. System-specific parameters for the function were derived on a training set of RNA/ligand complexes with known structure and affinity. To validate the free energy function, we screened the entire ACD for ligands for an RNA aptamer which binds l-arginine tightly. The native ligand ranked 17 out of ca. 153,000 compounds screened, i.e., the procedure is able to filter out >99.98% of the database and still retain the native ligand. Screening of the ACD for TAR ligands yielded a high rank for all known TAR ligands contained in the ACD and suggested several other potential TAR ligands. Eight of the highest ranking compounds not previously known to be ligands were assayed for inhibition of the Tat-TAR interaction, and two exhibited a CD₅₀ of ca. 1 M.     

Three pillars for achieving quantum mechanical molecular dynamics simulations of huge systems: Divide‐and‐conquer,density‐functional tight‐binding,and massively parallel computation

The linear‐scaling divide‐and‐conquer (DC) quantum chemical methodology is applied to the density‐functional tight‐binding (DFTB) theory to develop a massively parallel program that achieves on‐the‐fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC‐DFTB potential energy surface are implemented to the program called DC‐DFTB‐K. A novel interpolation‐based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC‐DFTB‐K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC‐DFTB‐K program, a single‐point energy gradient calculation of a one‐million‐atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc.     

An algorithm for the uniform sampling of iso-energy surfaces and for the calculation of microcanonical averages

In this article an algorithm is proposed to efficiently perform the uniform sampling of an iso-energy surface corresponding to a fixed potential energy U of a molecular system, and for calculating averages of certain quantities over microstates having this energy (microcanonical averages). The developed sampling technique is based upon the combination of a recently proposed method for performing constant potential energy molecular dynamics simulations [Rapallo, A. J Chem Phys 2004, 121, 4033] with well-established thermostatting techniques used in the framework of standard molecular dynamics simulations, such as the Andersen thermostat, and the Nose-Hoover chain thermostat. The proposed strategy leads to very accurate and drift-free potential energy conservation during the whole sampling process, and, very important, specially when dealing with high-dimensional or complicated potential functions, it does not require the calculation of the potential energy function hessian. The technique proved to be very reliable for sampling both low- and high-dimensional surfaces.     

Framework-based design of a new all-purpose molecular simulation application: the Adun simulator

Here we present Adun, a new molecular simulator that represents a paradigm shift in the way scientific programs are developed. The traditional algorithm centric methods of scientific programming can lead to major maintainability and productivity problems when developing large complex programs. These problems have long been recognized by computer scientists; however, the ideas and techniques developed to deal with them have not achieved widespread adoption in the scientific community. Adun is the result of the application of these ideas, including pervasive polymorphism, evolutionary frameworks, and refactoring, to the molecular simulation domain. The simulator itself is underpinned by the Adun Framework, which separates the structure of the program from any underlying algorithms, thus giving a completely reusable design. The aims are twofold. The first is to provide a platform for rapid development and implementation of different simulation types and algorithms. The second is to decrease the learning barrier for new developers by providing a rigorous and well-defined structure. We present some examples on the use of Adun by performing simple free-energy simulations for the adiabatic charging of a single ion, using both free-energy perturbation and the Bennett's method. We also illustrate the power of the design by detailing the ease with which ASEP/MD, an elaborated mean field QM/MM method originally written in FORTRAN 90, was implemented into Adun.     

Calculation of ligand binding free energies from molecular dynamics simulations

A recently developed method for predicting binding affinities in ligand–receptor complexes, based on interaction energy averaging and conformational sampling by molecular dynamics simulation, is presented. Polar and nonpolar contributions to the binding free energy are approximated by a linear scaling of the corresponding terms in the average intermolecular interaction energy for the bound and free states of the ligand. While the method originally assumed the validity of electrostatic linear response, we show that incorporation of systematic deviations from linear response derived from free energy perturbation calculations enhances the accuracy of the approach. The method is applied to complexes of wild-type and mutant human dihydrofolate reductases with 2,4-diaminopteridine and 2,4-diaminoquinazoline inhibitors. It is shown that a binding energy accuracy of about 1 kcal/mol is attainable even for multiply ionized compounds, such as methotrexate, for which electrostatic interactions energies are very large. © 1998 John Wiley & Sons, Inc. Int J Quant Chem 69: 77–88, 1998     

New insights from molecular dynamic simulation studies of the multiple binding modes of a ligand with G-quadruplex DNA

G-quadruplexes are higher-order DNA and RNA structures formed from guanine-rich sequences. These structures have recently emerged as a new class of potential molecular targets for anticancer drugs. An understanding of the three-dimensional interactions between small molecular ligands and their G-quadruplex targets in solution is crucial for rational drug design and the effective optimization of G-quadruplex ligands. Thus far, rational ligand design has been focused mainly on the G-quartet platform. It should be noted that small molecules can also bind to loop nucleotides, as observed in crystallography studies. Hence, it would be interesting to elucidate the mechanism underlying how ligands in distinct binding modes influence the flexibility of G-quadruplex. In the present study, based on a crystal structure analysis, the models of a tetra-substituted naphthalene diimide ligand bound to a telomeric G-quadruplex with different modes were built and simulated with a molecular dynamics simulation method. Based on a series of computational analyses, the structures, dynamics, and interactions of ligand-quadruplex complexes were studied. Our results suggest that the binding of the ligand to the loop is viable in aqueous solutions but dependent on the particular arrangement of the loop. The binding of the ligand to the loop enhances the flexibility of the G-quadruplex, while the binding of the ligand simultaneously to both the quartet and the loop diminishes its flexibility. These results add to our understanding of the effect of a ligand with different binding modes on G-quadruplex flexibility. Such an understanding will aid in the rational design of more selective and effective G-quadruplex binding ligands.     

Docking to RNA via root-mean-square-deviation-driven energy minimization with flexible ligands and flexible targets

Structure-based drug design is now well-established for proteins as a key first step in the lengthy process of developing new drugs. In many ways, RNA may be a better target to treat disease than a protein because it is upstream in the translation pathway, so inhibiting a single mRNA molecule could prevent the production of thousands of protein gene products. Virtual screening is often the starting point for structure-based drug design. However, computational docking of a small molecule to RNA seems to be more challenging than that to protein due to the higher intrinsic flexibility and highly charged structure of RNA. Previous attempts at docking to RNA showed the need for a new approach. We present here a novel algorithm using molecular simulation techniques to account for both nucleic acid and ligand flexibility. In this approach, with both the ligand and the receptor permitted some flexibility, they can bind one another via an induced fit, as the flexible ligand probes the surface of the receptor. A possible ligand can explore a low-energy path at the surface of the receptor by carrying out energy minimization with root-mean-square-distance constraints. Our procedure was tested on 57 RNA complexes (33 crystal and 24 NMR structures); this is the largest data set to date to reproduce experimental RNA binding poses. With our procedure, the lowest-energy conformations reproduced the experimental binding poses within an atomic root-mean-square deviation of 2.5 A for 74% of tested complexes.     

Complex Formation of the Tetracycline‐Binding Aptamer Investigated by Specific Cross‐Relaxation under DNP

While dynamic nuclear polarization (DNP) under magic‐angle spinning (MAS) is generally a powerful method capable of greatly enhancing the sensitivity of solid‐state NMR spectroscopy, hyperpolarization also gives rise to peculiar spin dynamics. Here, we elucidate how specific cross‐relaxation enhancement by active motions under DNP (SCREAM‐DNP) can be utilized to selectively obtain MAS‐NMR spectra of an RNA aptamer in a tightly bound complex with a methyl‐bearing ligand (tetracycline) due to the effective CH₃‐reorientation at an optimized sample temperature of approximately 160 K. SCREAM‐DNP can spectrally isolate the complex from non‐bound species in an RNA mixture. This selectivity allows for a competition assay between the aptamer and a mutant with compromised binding affinity. Variations in molecular structure and methyl dynamics, as observed by SCREAM‐DNP, between free tetracycline and RNA‐bound tetracycline are discussed.     

Streptavidin binding bifunctional aptamers and their interaction with low molecular weight ligands

This paper describes the measurement of the binding affinities of two bifunctional RNA aptamers to their respective ligands. The aptamers comprise either a theophylline or malachite green binding sequence fused to a streptavidin binding sequence. These bifunctional aptamers are shown to bind simultaneously to both the small ligand and to streptavidin whether in free solution or on gold surfaces. Binding isotherms for both interactions were measured by different physiochemical techniques: surface plasmon resonance, fluorescence spectroscopy and dynamic light scattering. Both qualitatively and quantitatively there is little difference in binding affinities between the bifunctional aptamers and their monofunctional components. The respective K_d values for streptavidin binding in the monofunctional aptamer and in the theophylline bifunctional aptamer were 12 nM and 65 nM, respectively whilst the K_d values for theophylline binding in the monofunctional aptamer and the streptavidin bifunctional aptamer were 300 nM and 120 nM. These results are consistent with treating each aptamer sequence as a module that can be combined with others without significant loss of function. This allows for the use of streptavidin based immobilization strategies without either the cost of biotinylated dNTPs or the variable yields associated with the chemical biotinylation of RNA.     

The dynamo library for molecular simulations using hybrid quantum mechanical and molecular mechanical potentials

The Dynamo module library has been developed for the simulation of molecular systems using hybrid quantum mechanical (QM) and molecular mechanical (MM) potentials. Dynamo is not a program package but is a library of Fortran 90 modules that can be employed by those interested in writing their own programs for performing molecular simulations. The library supports a range of different types of molecular calculation including geometry optimizations, reaction‐path determinations and molecular dynamics and Monte Carlo simulations. This article outlines the general structure and capabilities of the library and describes in detail Dynamo's semiempirical QM/MM hybrid potential. Results are presented to indicate three particular aspects of this implementation—the handling of long‐range nonbonding interactions, the nature of the boundary between the quantum mechanical and molecular mechanical atoms and how to perform path‐integral hybrid‐potential molecular dynamics simulations. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 1088–1100, 2000     

Operator splitting algorithm for isokinetic SLLOD molecular dynamics

We apply an operator splitting method to develop a simulation algorithm that has complete analytical solutions for the Gaussian thermostated SLLOD equations of motion [D. J. Evans and G. P. Morriss, Phys. Rev. A 30, 1528 (1984)] for a system under shear. This leads to a homogeneous algorithm for performing both equilibrium and nonequilibrium isokinetic molecular dynamics simulation. The resulting algorithm is computationally efficient. In particular, larger integration time steps can be used compared to simulations with regular Gaussian thermostated SLLOD equations of motion. The utility and accuracy of the algorithm are demonstrated through application to the Weeks-Chandler-Anderson fluid. Although strict conservation of the kinetic energy suppresses thermal fluctuations in the system, this algorithm does not allow simulations at lower shear rates than those normally afforded by older nonequilibrium molecular dynamics simulations.