Computational Investigation of a Series of Small Molecules as Potential Compounds for Lysyl Hydroxylase-2 (LH2) Inhibition.

The catalytic function of lysyl hydroxylase-2 (LH2), a member of the Fe(II)/αKG-dependent oxygenase superfamily, is to catalyze the hydroxylation of lysine to hydroxylysine in collagen, resulting in stable hydroxylysine aldehyde-derived collagen cross-links (HLCCs). Reports show that high amounts of LH2 lead to the accumulation of HLCCs, causing fibrosis and specific types of cancer metastasis. Some members of the Fe(II)/αKG-dependent family have also been reported to have intramolecular O2 tunnels, which aid in transporting one of the required cosubstrates into the active site. While LH2 can be a promising target to combat these diseases, efficacious inhibitors are still lacking. We have used computational simulations to investigate a series of 44 small molecules as lead compounds for LH2 inhibition. Tunneling analyses indicate the existence of several intramolecular tunnels. The lengths of the calculated O2-transporting tunnels in holoenzymes are relatively longer than those in the apoenzyme, suggesting that the ligands may affect the enzyme's structure and possibly block (at least partially) the tunnels. The sequence alignment analysis between LH enzymes from different organisms shows that all of the amino acid residues with the highest occurrence rate in the oxygen tunnels are conserved. Our results suggest that the enolate form of diketone compounds establishes stronger interactions with the Fe(II) in the active site. Branching the enolate compounds with functional groups such as phenyl and pyridinyl enhances the interaction with various residues around the active site. Our results provide information about possible leads for further LH2 inhibition design and development.

Modulating multi-functional ERK complexes by covalent targeting of a recruitment site in vivo.

Recently, the targeting of ERK with ATP-competitive inhibitors has emerged as a potential clinical strategy to overcome acquired resistance to BRAF and MEK inhibitor combination therapies. In this study, we investigate an alternative strategy of targeting the D-recruitment site (DRS) of ERK. The DRS is a conserved region that lies distal to the active site and mediates ERK-protein interactions. We demonstrate that the small molecule BI-78D3 binds to the DRS of ERK2 and forms a covalent adduct with a conserved cysteine residue (C159) within the pocket and disrupts signaling in vivo. BI-78D3 does not covalently modify p38MAPK, JNK or ERK5. BI-78D3 promotes apoptosis in BRAF inhibitor-naive and resistant melanoma cells containing a BRAF V600E mutation. These studies provide the basis for designing modulators of protein-protein interactions involving ERK, with the potential to impact ERK signaling dynamics and to induce cell cycle arrest and apoptosis in ERK-dependent cancers.

Computational insights into the binding of IN17 inhibitors to MELK.

The protein kinase MELK is an important kinase in cell signaling and has shown to be a promising anti-cancer target. Recent work has resulted in a novel small molecule scaffold targeting MELK, IN17. However, there has been little structural information or physical understanding of MELK-IN17 interactions. Using Tinker-OpenMM on GPUs, we have performed free energy simulations on MELK binding with IN17 and 11 derivatives. This series of studies provides structural insights into how substitution on IN17 leads to differences in complex structure and binding thermodynamics. In addition, this study serves as an assessment of the current capabilities of the AMOEBA forcefield, accelerated by GPU computing, to serve as a molecular-dynamics-based free energy simulation platform for lead optimization.

Virial Based Berendsen Barostat on GPUs using AMOEBA in Tinker-OpenMM.

The Tinker-OpenMM package for AMOEBA molecular dynamics on GPU has long been limited to the Monte Carlo barostat due to the lack of virial calculation. In this paper, we report the calculation of the internal virial for the AMOEBA forcefield. This constitutes the first GPU implementation of a polarizable internal virial. This is followed by the implementation of the Berendsen barostat into Tinker-OpenMM as a demonstration of the capability of Tinker-OpenMM to calculate the virial with sufficient accuracy to enable pressure control. These additions enable the further improvement of Tinker-OpenMM to include a wide range of virial-based barostat algorithms.

Tinker-HP: a massively parallel molecular dynamics package for multiscale simulations of large complex systems with advanced point dipole polarizable force fields.

We present Tinker-HP, a massively MPI parallel package dedicated to classical molecular dynamics (MD) and to multiscale simulations, using advanced polarizable force fields (PFF) encompassing distributed multipoles electrostatics. Tinker-HP is an evolution of the popular Tinker package code that conserves its simplicity of use and its reference double precision implementation for CPUs. Grounded on interdisciplinary efforts with applied mathematics, Tinker-HP allows for long polarizable MD simulations on large systems up to millions of atoms. We detail in the paper the newly developed extension of massively parallel 3D spatial decomposition to point dipole polarizable models as well as their coupling to efficient Krylov iterative and non-iterative polarization solvers. The design of the code allows the use of various computer systems ranging from laboratory workstations to modern petascale supercomputers with thousands of cores. Tinker-HP proposes therefore the first high-performance scalable CPU computing environment for the development of next generation point dipole PFFs and for production simulations. Strategies linking Tinker-HP to Quantum Mechanics (QM) in the framework of multiscale polarizable self-consistent QM/MD simulations are also provided. The possibilities, performances and scalability of the software are demonstrated via benchmarks calculations using the polarizable AMOEBA force field on systems ranging from large water boxes of increasing size and ionic liquids to (very) large biosystems encompassing several proteins as well as the complete satellite tobacco mosaic virus and ribosome structures. For small systems, Tinker-HP appears to be competitive with the Tinker-OpenMM GPU implementation of Tinker. As the system size grows, Tinker-HP remains operational thanks to its access to distributed memory and takes advantage of its new algorithmic enabling for stable long timescale polarizable simulations. Overall, a several thousand-fold acceleration over a single-core computation is observed for the largest systems. The extension of the present CPU implementation of Tinker-HP to other computational platforms is discussed.

Tinker-OpenMM: Absolute and relative alchemical free energies using AMOEBA on GPUs.

The capabilities of the polarizable force fields for alchemical free energy calculations have been limited by the high computational cost and complexity of the underlying potential energy functions. In this work, we present a GPU-based general alchemical free energy simulation platform for polarizable potential AMOEBA. Tinker-OpenMM, the OpenMM implementation of the AMOEBA simulation engine has been modified to enable both absolute and relative alchemical simulations on GPUs, which leads to a ∼200-fold improvement in simulation speed over a single CPU core. We show that free energy values calculated using this platform agree with the results of Tinker simulations for the hydration of organic compounds and binding of host-guest systems within the statistical errors. In addition to absolute binding, we designed a relative alchemical approach for computing relative binding affinities of ligands to the same host, where a special path was applied to avoid numerical instability due to polarization between the different ligands that bind to the same site. This scheme is general and does not require ligands to have similar scaffolds. We show that relative hydration and binding free energy calculated using this approach match those computed from the absolute free energy approach. © 2017 Wiley Periodicals, Inc.

Polarizable Multipole-Based Force Field for Aromatic Molecules and Nucleobases.

Aromatic molecules with π electrons are commonly involved in chemical and biological recognitions. For example, nucleobases play central roles in DNA/RNA structure and their interactions with proteins. The delocalization of the π electrons is responsible for the high polarizability of aromatic molecules. In this work, the AMOEBA force field has been developed and applied to 5 regular nucleobases and 12 aromatic molecules. The permanent electrostatic energy is expressed as atomic multipole interactions between atom pairs, and many-body polarization is accounted for by mutually induced atomic dipoles. We have systematically investigated aromatic ring stacking and aromatic-water interactions for nucleobases and aromatic molecules, as well as base-base hydrogen-bonding pair interactions, all at various distances and orientations. van der Waals parameters were determined by comparison to the quantum mechanical interaction energy of these dimers and fine-tuned using condensed phase simulation. By comparing to quantum mechanical calculations, we show that the resulting classical potential is able to accurately describe molecular polarizability, molecular vibrational frequency, and dimer interaction energy of these aromatic systems. Condensed phase properties, including hydration free energy, liquid density, and heat of vaporization, are also in good overall agreement with experimental values. The structures of benzene liquid phase and benzene-water solution were also investigated by simulation and compared with experimental and PDB structure derived statistical results.

Expanding the product profile of a microbial alkane biosynthetic pathway.

Microbially produced alkanes are a new class of biofuels that closely match the chemical composition of petroleum-based fuels. Alkanes can be generated from the fatty acid biosynthetic pathway by the reduction of acyl-ACPs followed by decarbonylation of the resulting aldehydes. A current limitation of this pathway is the restricted product profile, which consists of n-alkanes of 13, 15, and 17 carbons in length. To expand the product profile, we incorporated a new part, FabH2 from Bacillus subtilis , an enzyme known to have a broader specificity profile for fatty acid initiation than the native FabH of Escherichia coli . When provided with the appropriate substrate, the addition of FabH2 resulted in an altered alkane product profile in which significant levels of n-alkanes of 14 and 16 carbons in length are produced. The production of even chain length alkanes represents initial steps toward the expansion of this recently discovered microbial alkane production pathway to synthesize complex fuels. This work was conceived and performed as part of the 2011 University of Washington international Genetically Engineered Machines (iGEM) project.