Free energy simulations with the AMOEBA polarizable force field and metadynamics on GPU platform

Polarizable atomic multipole-based force field for cholesterol

Cholesterol is one of the essential component of lipid in membrane. We present a polarizable atomic multipole force field (FF) for the molecular dynamic simulation of cholesterol. The FF building process follows the computational framework as the atomic multipole optimized energetics for biomolecular applications (AMOEBA) model. In this framework, the electronics parameters, including atomic monopole moments, dipole moments, and quadrupole moments calculated from ab initio calculations in the gas phase, are applied to represent the charge distribution. Furthermore, the many-body polarization is modeled by following the same pattern of distributed atomic polarizabilities. Then, the bilayers composed of two typical phospholipid molecules, 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), in a range of different cholesterol concentrations are built and implemented by molecular dynamics (MD) simulations based on the proposed polarizable FF. The simulation results are statistically analyzed to validate the feasibility of the proposed FF. The structural properties of the bilayers are calculated to compare with the related experimental values. The MD values show the same trend of experimental values changes.Communicated by Ramaswamy H. Sarma.

Intrinsic Conformational Dynamics of Glycine and Alanine in Polarizable Molecular Dynamics Force Fields: Comparison to Spectroscopic Data

Molecular dynamics (MD) is a great tool for elucidating conformational dynamics of proteins and peptides in water at the atomistic level that often surpasses the level of detail available experimentally. Structure predictions, however, are limited by the accuracy of the underlying MD force field. This limitation is particularly stark in the case of intrinsically disordered peptides and proteins, which are characterized by solvent-accessible and disordered peptide regions and domains. Recent studies show that most additive MD force fields, including CHARMM36m, do not reproduce the intrinsic conformational distributions of guest amino acid residues x in cationic GxG peptides in water in line with experimental data. Positing that a lack of polarizability in additive MD force fields may be the culprit for the reported discrepancies, we here examine the conformational dynamics of guest glycine and alanine residues in cationic GxG peptides in water using two polarizable MD force fields, CHARMM Drude and AMOEBA. Our results indicate that while AMOEBA captures the experimental data better than CHARMM Drude, neither of the two polarizable force fields offers an improvement of the Ramachandran distributions of glycine and alanine residues in cationic GGG and GAG peptides, respectively, over CHARMM36m.

Biotin-painted proteins have thermodynamic stability switched by kinetic folding routes

Biotin-labeled proteins are widely used as tools to study protein-protein interactions and proximity in living cells. Proteomic methods broadly employ proximity-labeling technologies based on protein biotinylation in order to investigate the transient encounters of biomolecules in subcellular compartments. Biotinylation is a post-translation modification in which the biotin molecule is attached to lysine or tyrosine residues. So far, biotin-based technologies proved to be effective instruments as affinity and proximity tags. However, the influence of biotinylation on aspects such as folding, binding, mobility, thermodynamic stability, and kinetics needs to be investigated. Here, we selected two proteins [biotin carboxyl carrier protein (BCCP) and FKBP3] to test the influence of biotinylation on thermodynamic and kinetic properties. Apo (without biotin) and holo (biotinylated) protein structures were used separately to generate all-atom structure-based model simulations in a wide range of temperatures. Holo BCCP contains one biotinylation site, and FKBP3 was modeled with up to 23 biotinylated lysines. The two proteins had their estimated thermodynamic stability changed by altering their energy landscape. In all cases, after comparison between the apo and holo simulations, differences were observed on the free-energy profiles and folding routes. Energetic barriers were altered with the density of states clearly showing changes in the transition state. This study suggests that analysis of large-scale datasets of biotinylation-based proximity experiments might consider possible alterations in thermostability and folding mechanisms imposed by the attached biotins.

Structural and functional insights into the tetrameric photosystem I from heterocyst-forming cyanobacteria

Two large protein-cofactor complexes, photosystem I and photosystem II, are the central components of photosynthesis in the thylakoid membranes. Here, we report the 2.37-Å structure of a tetrameric photosystem I complex from a heterocyst-forming cyanobacterium Anabaena sp. PCC 7120. Four photosystem I monomers, organized in a dimer of dimer, form two distinct interfaces that are largely mediated by specifically orientated polar lipids, such as sulfoquinovosyl diacylglycerol. The structure depicts a more closely connected network of chlorophylls across monomer interfaces than those seen in trimeric PSI from thermophilic cyanobacteria, possibly allowing a more efficient energy transfer between monomers. Our physiological data also revealed a functional link of photosystem I oligomerization to cyclic electron flow and thylakoid membrane organization.

α-Ketoglutarate-Activated NF-κB Signaling Promotes Compensatory Glucose Uptake and Brain Tumor Development

The rapid proliferation of cancer cells and dysregulated vasculature within the tumor leads to limited nutrient accessibility. Cancer cells often rewire their metabolic pathways for adaption to nutrient stress, and the underlying mechanism remains largely unknown. Glutamate dehydrogenase 1 (GDH1) is a key enzyme in glutaminolysis that converts glutamate to α-ketoglutarate (α-KG). Here, we show that, under low glucose, GDH1 is phosphorylated at serine (S) 384 and interacts with RelA and IKKβ. GDH1-produced α-KG directly binds to and activates IKKβ and nuclear factor κB (NF-κB) signaling, which promotes glucose uptake and tumor cell survival by upregulating GLUT1, thereby accelerating gliomagenesis. In addition, GDH1 S384 phosphorylation correlates with the malignancy and prognosis of human glioblastoma. Our finding reveals a unique role of α-KG to directly regulate signal pathway, uncovers a distinct mechanism of metabolite-mediated NF-κB activation, and also establishes the critical role of α-KG-activated NF-κB in brain tumor development.

Higher Accuracy Achieved in the Simulations of Protein Structure Refinement, Protein Folding, and Intrinsically Disordered Proteins Using Polarizable Force Fields

The accuracy of molecular mechanics force fields is of vital importance in biomolecular simulations. However, the admittedly more accurate polarizable force fields were recently reported to be less able to reproduce the experimental properties in comparison to additive force fields in some cases. Here, we perform long-time-scale molecular dynamics simulations to systematically evaluate the effect of explicit electronic polarization in polarizable force fields. The results show that the inclusion of electrostatic polarization effect in polarizable force fields can improve their accuracies in protein structure refinement and generate conformational ensembles more approximate to experiments for intrinsically disordered proteins. In contrast, it is difficult for polarizable force fields to approach the native structure, let alone to predict the native state when it is unknown a priori in the real protein structure predictions. We speculate that these effects might be attributed to the preference of protein-water interactions in polarizable force fields.

A GPU-Accelerated Parameter Interpolation Thermodynamic Integration Free Energy Method

There has been a resurgence of interest in free energy methods motivated by the performance enhancements offered by molecular dynamics (MD) software written for specialized hardware, such as graphics processing units (GPUs). In this work, we exploit the properties of a parameter-interpolated thermodynamic integration (PI-TI) method to connect states by their molecular mechanical (MM) parameter values. This pathway is shown to be better behaved for Mg2+ → Ca2+ transformations than traditional linear alchemical pathways (with and without soft-core potentials). The PI-TI method has the practical advantage that no modification of the MD code is required to propagate the dynamics, and unlike with linear alchemical mixing, only one electrostatic evaluation is needed (e.g., single call to particle-mesh Ewald) leading to better performance. In the case of AMBER, this enables all the performance benefits of GPU-acceleration to be realized, in addition to unlocking the full spectrum of features available within the MD software, such as Hamiltonian replica exchange (HREM). The TI derivative evaluation can be accomplished efficiently in a post-processing step by reanalyzing the statistically independent trajectory frames in parallel for high throughput. We also show how one can evaluate the particle mesh Ewald contribution to the TI derivative evaluation without needing to perform two reciprocal space calculations. We apply the PI-TI method with HREM on GPUs in AMBER to predict p Ka values in double stranded RNA molecules and make comparison with experiments. Convergence to under 0.25 units for these systems required 100 ns or more of sampling per window and coupling of windows with HREM. We find that MM charges derived from ab initio QM/MM fragment calculations improve the agreement between calculation and experimental results.

Evaluating Parametrization Protocols for Hydration Free Energy Calculations with the AMOEBA Polarizable Force Field

Hydration free energy (HFE) calculations are often used to assess the performance of biomolecular force fields and the quality of assigned parameters. The AMOEBA polarizable force field moves beyond traditional pairwise additive models of electrostatics and may be expected to improve upon predictions of thermodynamic quantities such as HFEs over and above fixed-point-charge models. The recent SAMPL4 challenge evaluated the AMOEBA polarizable force field in this regard but showed substantially worse results than those using the fixed-point-charge GAFF model. Starting with a set of automatically generated AMOEBA parameters for the SAMPL4 data set, we evaluate the cumulative effects of a series of incremental improvements in parametrization protocol, including both solute and solvent model changes. Ultimately, the optimized AMOEBA parameters give a set of results that are not statistically significantly different from those of GAFF in terms of signed and unsigned error metrics. This allows us to propose a number of guidelines for new molecule parameter derivation with AMOEBA, which we expect to have benefits for a range of biomolecular simulation applications such as protein-ligand binding studies.