60 research outputs found
Molecular dynamics simulations and drug discovery
This review discusses the many roles atomistic computer simulations of macromolecular (for example, protein) receptors and their associated small-molecule ligands can play in drug discovery, including the identification of cryptic or allosteric binding sites, the enhancement of traditional virtual-screening methodologies, and the direct prediction of small-molecule binding energies. The limitations of current simulation methodologies, including the high computational costs and approximations of molecular forces required, are also discussed. With constant improvements in both computer power and algorithm design, the future of computer-aided drug design is promising; molecular dynamics simulations are likely to play an increasingly important role
Prediction of Protein Binding Regions in Disordered Proteins
Many disordered proteins function via binding to a structured partner and undergo
a disorder-to-order transition. The coupled folding and binding can confer
several functional advantages such as the precise control of binding specificity
without increased affinity. Additionally, the inherent flexibility allows the
binding site to adopt various conformations and to bind to multiple partners.
These features explain the prevalence of such binding elements in signaling and
regulatory processes. In this work, we report ANCHOR, a method for the
prediction of disordered binding regions. ANCHOR relies on the pairwise energy
estimation approach that is the basis of IUPred, a previous general disorder
prediction method. In order to predict disordered binding regions, we seek to
identify segments that are in disordered regions, cannot form enough favorable
intrachain interactions to fold on their own, and are likely to gain stabilizing
energy by interacting with a globular protein partner. The performance of ANCHOR
was found to be largely independent from the amino acid composition and adopted
secondary structure. Longer binding sites generally were predicted to be
segmented, in agreement with available experimentally characterized examples.
Scanning several hundred proteomes showed that the occurrence of disordered
binding sites increased with the complexity of the organisms even compared to
disordered regions in general. Furthermore, the length distribution of binding
sites was different from disordered protein regions in general and was dominated
by shorter segments. These results underline the importance of disordered
proteins and protein segments in establishing new binding regions. Due to their
specific biophysical properties, disordered binding sites generally carry a
robust sequence signal, and this signal is efficiently captured by our method.
Through its generality, ANCHOR opens new ways to study the essential functional
sites of disordered proteins
Mutation D816V Alters the Internal Structure and Dynamics of c-KIT Receptor Cytoplasmic Region: Implications for Dimerization and Activation Mechanisms
The type III receptor tyrosine kinase (RTK) KIT plays a crucial role in the transmission of cellular signals through phosphorylation events that are associated with a switching of the protein conformation between inactive and active states. D816V KIT mutation is associated with various pathologies including mastocytosis and cancers. D816V-mutated KIT is constitutively active, and resistant to treatment with the anti-cancer drug Imatinib. To elucidate the activating molecular mechanism of this mutation, we applied a multi-approach procedure combining molecular dynamics (MD) simulations, normal modes analysis (NMA) and binding site prediction. Multiple 50-ns MD simulations of wild-type KIT and its mutant D816V were recorded using the inactive auto-inhibited structure of the protein, characteristic of type III RTKs. Computed free energy differences enabled us to quantify the impact of D816V on protein stability in the inactive state. We evidenced a local structural alteration of the activation loop (A-loop) upon mutation, and a long-range structural re-organization of the juxta-membrane region (JMR) followed by a weakening of the interaction network with the kinase domain. A thorough normal mode analysis of several MD conformations led to a plausible molecular rationale to propose that JMR is able to depart its auto-inhibitory position more easily in the mutant than in wild-type KIT and is thus able to promote kinase mutant dimerization without the need for extra-cellular ligand binding. Pocket detection at the surface of NMA-displaced conformations finally revealed that detachment of JMR from the kinase domain in the mutant was sufficient to open an access to the catalytic and substrate binding sites
Structural Biology by NMR: Structure, Dynamics, and Interactions
The function of bio-macromolecules is determined by both their 3D structure and conformational dynamics. These molecules are inherently flexible systems displaying a broad range of dynamics on time-scales from picoseconds to seconds. Nuclear Magnetic Resonance (NMR) spectroscopy has emerged as the method of choice for studying both protein structure and dynamics in solution. Typically, NMR experiments are sensitive both to structural features and to dynamics, and hence the measured data contain information on both. Despite major progress in both experimental approaches and computational methods, obtaining a consistent view of structure and dynamics from experimental NMR data remains a challenge. Molecular dynamics simulations have emerged as an indispensable tool in the analysis of NMR data
Structure and Dynamics of a Fusion Peptide Helical Hairpin on the Membrane Surface: Comparison of Molecular Simulations and NMR
The conserved N-terminal residues of the HA2 subunit of influenza hemagglutinin (fusion peptide) are essential for membrane fusion and viral entry. Recent NMR studies showed that the 23-residue fusion peptide forms a helical hairpin that undergoes rocking motion relative to the membrane surface on a nanosecond time scale. To compare with NMR and to obtain a detailed molecular picture of the peptide–membrane interaction, we performed molecular dynamics simulations of the fusion peptide in explicit dimyristoylphosphatidylcholine and with the IMM1 implicit membrane model. To account for low and neutral pH conditions, simulations were performed with acidic groups (E11 and D19) protonated and unprotonated, respectively. The hairpin structure was stable in the simulations, with the N-terminal helix buried more deeply into the hydrophobic membrane interior than the C-terminal helix. Interactions between the tryptophans in the fusion peptide and phospholipid residues contribute to peptide orientation. Higher flexibility of the hairpin was observed in the implicit membrane simulations. Internal correlation functions of backbone N–H vectors were fit to the extended Lipari–Szabo model-free approach to obtain order parameters and correlation times. Good agreement with the NMR results was obtained for orientational fluctuations around the hairpin axis (rotation), but those around the perpendicular axis (tilting) were more limited in the simulations than inferred from the NMR experiments
Approximate Reconstruction of Continuous Spatially Complex Domain Motions by Multialignment NMR Residual Dipolar Couplings
Spectroscopy by Integration of Frequency and Time Domain Information for Fast Acquisition of High-Resolution Dark Spectra
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