All-Atom Multiscale Computational Modeling Of Viral Dynamics

Thesis (Ph.D.) - Indiana University, Chemistry, 2009Viruses are composed of millions of atoms functioning on supra-nanometer length scales over timescales of milliseconds or greater. In contrast, individual atoms interact on scales of angstroms and femtoseconds. Thus they display dual microscopic/macroscopic characteristics involving processes that span across widely-separated time and length scales. To address this challenge, we introduced automatically generated collective modes and order parameters to capture viral large-scale low-frequency coherent motions. With an all-atom multiscale analysis (AMA) of the Liouville equation, a stochastic (Fokker-Planck or Smoluchowski) equation and equivalent Langevin equations are derived for the order parameters. They are shown to evolve on timescales much larger than the 10^(-14)-second timescale of fast atomistic vibrations and collisions. This justifies a novel multiscale Molecular Dynamics/Order Parameter eXtrapolation (MD/OPX) approach, which propagates viral atomistic and nanoscale dynamics simultaneously by solving the Langevin equations of order parameters implicitly without the need to construct thermal-average forces and friction/diffusion coefficients. In MD/OPX, a set of short replica MD runs with random atomic velocity initializations estimate the ensemble average rate of change in order parameters, extrapolation of which is then used to project the system over long time. The approach was implemented by using NAMD as the MD platform. Application of MD/OPX to cowpea chlorotic mottle virus (CCMV) capsid revealed that its swollen state undergoes significant energy-driven shrinkage in vacuum during 200ns simulation, while for the native state as solvated in a host medium at pH 7.0 and ionic strength I=0.2M, the N-terminal arms of capsid proteins are shown to be highly dynamic and their fast fluctuations trigger global expansion of the capsid. Viral structural transitions associated with both processes are symmetry-breaking involving local initiation and front propagation. MD/OPX accelerates MD for long-time simulation of viruses, as well as other large bionanosystems. By using universal inter-atomic force fields, it is generally applicable to all dynamical nanostructures and avoids the need of parameter recalibration with each new application. With our AMA method and MD/OPX, viral dynamics are predicted from laws of molecular physics via rigorous statistical mechanics

Mechanistic Insights into Specific G Protein Interactions with Adenosine Receptors

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Physical Chemistry B, copyright © 2019 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.jpcb.9b04867.Coupling between G-protein-coupled receptors (GPCRs) and the G proteins is a key step in cellular signaling. Despite extensive experimental and computational studies, the mechanism of specific GPCR–G protein coupling remains poorly understood. This has greatly hindered effective drug design of GPCRs that are primary targets of ∼1/3 of currently marketed drugs. Here, we have employed all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method to decipher the mechanism of the GPCR–G protein interactions. Adenosine receptors (ARs) were used as model systems based on very recently determined cryo-EM structures of the A1AR and A2AAR coupled with the Gi and Gs proteins, respectively. Changing the Gi protein to the Gs led to increased fluctuations in the A1AR and agonist adenosine (ADO), while agonist 5′-N-ethylcarboxamidoadenosine (NECA) binding in the A2AAR could be still stabilized upon changing the Gs protein to the Gi. Free energy calculations identified one stable low-energy conformation for each of the A1AR-Gi and A2AAR-Gs complexes as in the cryo-EM structures, similarly for the A2AAR-Gi complex. In contrast, the ADO agonist and Gs protein sampled multiple conformations in the A1AR-Gs system. GaMD simulations thus indicated that the A1AR preferred to couple with the Gi protein to the Gs, while the A2AAR could couple with both the Gs and Gi proteins, being highly consistent with experimental findings of the ARs. More importantly, detailed analysis of the atomic simulations showed that the specific AR-G protein coupling resulted from remarkably complementary residue interactions at the protein interface, involving mainly the receptor transmembrane 6 helix and the Gα α5 helix and α4-β6 loop. In summary, the GaMD simulations have provided unprecedented insights into the dynamic mechanism of specific GPCR–G protein interactions at an atomistic level

Recent advances in computational studies of GPCR-G protein interactions

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Protein-protein interactions are key in cellular signaling. G protein-coupled receptors (GPCRs), the largest superfamily of human membrane proteins, are able to transduce extracellular signals (e.g., hormones and neurotransmitters) to intracellular proteins, in particular the G proteins. Since GPCRs serve as primary targets of ~ 1/3 of currently marketed drugs, it is important to understand mechanisms of GPCR signaling in order to design selective and potent drug molecules. This chapter focuses on recent advances in computational studies of the GPCR-G protein interactions using bioinformatics, protein-protein docking and molecular dynamics simulation approaches

Mechanism of Peptide Agonist Binding in CXCR4 Chemokine Receptor

Chemokine receptors are key G-protein-coupled receptors (GPCRs) that control cell migration in immune system responses, development of cardiovascular and central nervous systems, and numerous diseases. In particular, the CXCR4 chemokine receptor promotes metastasis, tumor growth and angiogenesis in cancers. CXCR4 is also used as one of the two co-receptors for T-tropic HIV-1 entry into host cells. Therefore, CXCR4 serves as an important therapeutic target for treating cancers and HIV infection. Apart from the CXCL12 endogenous peptide agonist, previous studies suggested that the first 17 amino acids of CXCL12 are sufficient to activate CXCR4. Two 17-residue peptides with positions 1–4 mutated to RSVM and ASLW functioned as super and partial agonists of CXCR4, respectively. However, the mechanism of peptide agonist binding in CXCR4 remains unclear. Here, we have investigated this mechanism through all-atom simulations using a novel Peptide Gaussian accelerated molecular dynamics (Pep-GaMD) method. The Pep-GaMD simulations have allowed us to explore representative binding conformations of each peptide and identify critical low-energy states of CXCR4 activated by the super versus partial peptide agonists. Our simulations have provided important mechanistic insights into peptide agonist binding in CXCR4, which are expected to facilitate rational design of new peptide modulators of CXCR4 and other chemokine receptors

G‐Protein‐Coupled Receptor–Membrane Interactions Depend on the Receptor Activation State

This is the peer reviewed version of the following article: Bhattarai, A., Wang, J., & Miao, Y. (2020). G-Protein-Coupled Receptor-Membrane Interactions Depend on the Receptor Activation State. Journal of computational chemistry, 41(5), 460–471. https://doi.org/10.1002/jcc.26082, which has been published in final form at https://doi.org/10.1002/jcc.26082. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.G‐protein‐coupled receptors (GPCRs) are the largest family of human membrane proteins and serve as primary targets of approximately one‐third of currently marketed drugs. In particular, adenosine A1 receptor (A1AR) is an important therapeutic target for treating cardiac ischemia–reperfusion injuries, neuropathic pain, and renal diseases. As a prototypical GPCR, the A1AR is located within a phospholipid membrane bilayer and transmits cellular signals by changing between different conformational states. It is important to elucidate the lipid–protein interactions in order to understand the functional mechanism of GPCRs. Here, all‐atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method were performed on both the inactive (antagonist bound) and active (agonist and G‐protein bound) A1AR, which was embedded in a 1‐palmitoyl‐2‐oleoyl‐glycero‐3‐phosphocholine (POPC) lipid bilayer. In the GaMD simulations, the membrane lipids played a key role in stabilizing different conformational states of the A1AR. Our simulations further identified important regions of the receptor that interacted distinctly with the lipids in highly correlated manner. Activation of the A1AR led to differential dynamics in the upper and lower leaflets of the lipid bilayer. In summary, GaMD enhanced simulations have revealed strongly coupled dynamics of the GPCR and lipids that depend on the receptor activation state

Pathways and Mechanism of Caffeine Binding to Human Adenosine A2A Receptor

Caffeine (CFF) is a common antagonist to the four subtypes of adenosine G-protein-coupled receptors (GPCRs), which are critical drug targets for treating heart failure, cancer, and neurological diseases. However, the pathways and mechanism of CFF binding to the target receptors remain unclear. In this study, we have performed all-atom-enhanced sampling simulations using a robust Gaussian-accelerated molecular dynamics (GaMD) method to elucidate the binding mechanism of CFF to human adenosine A2A receptor (A2AAR). Multiple 500–1,000 ns GaMD simulations captured both binding and dissociation of CFF in the A2AAR. The GaMD-predicted binding poses of CFF were highly consistent with the x-ray crystal conformations with a characteristic hydrogen bond formed between CFF and residue N6.55 in the receptor. In addition, a low-energy intermediate binding conformation was revealed for CFF at the receptor extracellular mouth between ECL2 and TM1. While the ligand-binding pathways of the A2AAR were found similar to those of other class A GPCRs identified from previous studies, the ECL2 with high sequence divergence serves as an attractive target site for designing allosteric modulators as selective drugs of the A2AAR

Improved Modeling of Peptide-Protein Binding Through Global Docking and Accelerated Molecular Dynamics Simulations

This work is licensed under a Creative Commons Attribution 4.0 International License.Peptides mediate up to 40% of known protein-protein interactions in higher eukaryotes and play a key role in cellular signaling, protein trafficking, immunology, and oncology. However, it is challenging to predict peptide-protein binding with conventional computational modeling approaches, due to slow dynamics and high peptide flexibility. Here, we present a prototype of the approach which combines global peptide docking using ClusPro PeptiDock and all-atom enhanced simulations using Gaussian accelerated molecular dynamics (GaMD). For three distinct model peptides, the lowest backbone root-mean-square deviations (RMSDs) of their bound conformations relative to X-ray structures obtained from PeptiDock were 3.3–4.8 Å, being medium quality predictions according to the Critical Assessment of PRediction of Interactions (CAPRI) criteria. GaMD simulations refined the peptide-protein complex structures with significantly reduced peptide backbone RMSDs of 0.6–2.7 Å, yielding two high quality (sub-angstrom) and one medium quality models. Furthermore, the GaMD simulations identified important low-energy conformational states and revealed the mechanism of peptide binding to the target proteins. Therefore, PeptiDock+GaMD is a promising approach for exploring peptide-protein interactions