The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.
Molecular self-assembly is pivotal for the formation of ordered nanostructures, yet the structural diversity obtained by the use of a single type of building block is limited. Multicomponent coassembly, utilized to expand the architectural space, is principally based on empirical observations rather than rational design. Here we report large-scale molecular dynamics simulations of the coassembly of diphenylalanine (FF) and triphenylalanine (FFF) peptides at various mass ratios. Our simulations show that FF and FFF can co-organize into both canonical and noncanonical assemblies. Strikingly, toroid nanostructures, which were rarely observed for the extensively studied FF or FFF, are often seen in the FF-FFF coassembly simulations and later corroborated by scanning electron microscopy. Our simulations demonstrate a wide ratio-dependent variation of nanostructure morphologies including hollow and solid assemblies, much richer than those formed by each individual moiety. The hollow-solid structural transformation displays a discontinuous transition feature, and the toroids appear to be an obligatory intermediate for the structural transition. Interaction analysis reveals that the hollow-solid structural transition is mostly dominated by FF-FFF interactions, while the nanotoroid formation is determined by the competition between FF-water and FFF-water interactions. This study provides both structural and mechanistic insights into the coassembly of FF and FFF peptides, thus offering a molecular basis for the rational design of bionanomaterials utilizing peptide coassembly.
Summary The Hippo pathway plays a crucial role in organ size control and tumor suppression, but its precise regulation has not been fully understood. In this study, we discovered phosphatidic acid (PA)-related lipid signaling as a key regulator of the Hippo pathway. Supplementing PA in various Hippo-activating conditions activates YAP. This PA-related lipid signaling is involved in the Rho-mediated YAP activation. Mechanistically, PA directly interacts with Hippo components LATS and NF2 to respectively disrupt the LATS-MOB1 complex formation and NF2-mediated LATS membrane translocation and activation. Inhibition of phospholipase D (PLD)-dependent PA production suppresses YAP oncogenic activities. PLD1 is highly expressed in breast cancer and positively correlates with YAP activation, suggesting their pathological relevance in breast cancer development. Taken together, our study not only reveals a role of PLD-PA lipid signaling in regulation of the Hippo pathway, but also indicates the PLD-PA-YAP axis as a potential therapeutic target for cancer treatment.
Experiments suggested that the fibrillation of the 11-25 fragment (hIAPP(11-25)) of human islet amyloid polypeptide (hIAPP or amylin) involves the formation of transient α-helical intermediates, followed by conversion to β-sheet-rich structure. However, atomic details of α-helical intermediates and the transition mechanism are mostly unknown. We investigated the structural properties of the monomer and dimer in atomistic detail by replica exchange molecular dynamics (REMD) simulations. Transient α-helical monomers and dimers were both observed in the REMD trajectories. Our calculated H(α) chemical shifts based on the monomer REMD run are in agreement with the solution-state NMR experimental observations. Multiple 300 ns MD simulations at 310 K show that α-helix-to-β-sheet transition follows two mechanisms: the first involved direct transition of the random coil part of the helical conformation into antiparallel β-sheet, and in the second, the α-helical conformation unfolded and converted into antiparallel β-sheet. In both mechanisms, the α-helix-to-β-sheet transition occurred via random coil, and the transition was accompanied by an increase of interpeptide contacts. In addition, our REMD simulations revealed different temperature dependencies of helical and β-structures. Comparison with experimental data suggests that the propensity for hIAPP(11-25) to form α-helices and amyloid structures is concentration- and temperature-dependent.
Protein aggregation is associated with many human diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and type II diabetes (T2D). Understanding the molecular mechanism of protein aggregation is essential for therapy development. Molecular dynamics (MD) simulations have been shown as powerful tools to study protein aggregation. However, conventional MD simulations can hardly sample the whole conformational space of complex protein systems within acceptable simulation time as it can be easily trapped in local minimum-energy states. Many enhanced sampling methods have been developed. Among these, the replica exchange molecular dynamics (REMD) method has gained great popularity. By combining MD simulation with the Monte Carlo algorithm, the REMD method is capable of overcoming high energy-barriers easily and of sampling sufficiently the conformational space of proteins. In this chapter, we present a brief introduction to REMD method and a practical application protocol with a case study of the dimerization of the 11-25 fragment of human islet amyloid polypeptide (hIAPP(11-25)), using the GROMACS software. We also provide solutions to problems that are often encountered in practical use, and provide some useful scripts/commands from our research that can be easily adapted to other systems.
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