Nagarajan Vaidehi

Quantum-mechanical calculations of solvation free energies. A combined ab initio pseudopotential free-energy perturbation approach

A practical ab initio quantum‐mechanical approach for calculations of free energies of molecules in solutions is developed. This approach treats the solute molecules by an explicit ab initio self‐consistent‐field approach while representing the solvent molecules by a pseudopotential. The solvation energies are evaluated by a free‐energy perturbation approach that uses the distribution function associated with a classical force field as a reference state for the quantum‐mechanical calculations. The performance of the method is examined by evaluating the solvation energy of an Li+ ion. It is found that the calculation times are not much longer than that of the corresponding classical free‐energy perturbation calculations.

Structure and dynamics of a constitutively active neurotensin receptor.

Many G protein-coupled receptors show constitutive activity, resulting in the production of a second messenger in the absence of an agonist; and naturally occurring constitutively active mutations in receptors have been implicated in diseases. To gain insight into mechanistic aspects of constitutive activity, we report here the 3.3 Å crystal structure of a constitutively active, agonist-bound neurotensin receptor (NTSR1) and molecular dynamics simulations of agonist-occupied and ligand-free receptor. Comparison with the structure of a NTSR1 variant that has little constitutive activity reveals uncoupling of the ligand-binding domain from conserved connector residues, that effect conformational changes during GPCR activation. Furthermore, molecular dynamics simulations show strong contacts between connector residue side chains and increased flexibility at the intracellular receptor face as features that coincide with robust signalling in cells. The loss of correlation between the binding pocket and conserved connector residues, combined with altered receptor dynamics, possibly explains the reduced neurotensin efficacy in the constitutively active NTSR1 and a facilitated initial engagement with G protein in the absence of agonist.

Structural Dynamics and Thermostabilization of Neurotensin Receptor 1

The neurotensin receptor NTSR1 binds the peptide agonist neurotensin (NTS) and signals preferentially via the Gq protein. Recently, Grisshammer and co-workers reported the crystal structure of a thermostable mutant NTSR1-GW5 with NTS bound. Understanding how the mutations thermostabilize the structure would allow efficient design of thermostable mutant GPCRs for protein purification, and subsequent biophysical studies. Using microsecond scale molecular dynamics simulations (4 μs) of the thermostable mutant NTSR1-GW5 and wild type NTSR1, we have elucidated the structural and energetic factors that affect the thermostability and dynamics of NTSR1. The thermostable mutant NTSR1-GW5 is found to be less flexible and less dynamic than the wild type NTSR1. The point mutations confer thermostability by improving the interhelical hydrogen bonds, hydrophobic packing, and receptor interactions with the lipid bilayer, especially in the intracellular regions. During MD, NTSR1-GW5 becomes more hydrated compared to wild type NTSR1, with tight hydrogen bonded water clusters within the transmembrane core of the receptor, thus providing evidence that water plays an important role in improving helical packing in the thermostable mutant. Our studies provide valuable insights into the stability and functioning of NTSR1 that will be useful in future design of thermostable mutants of other peptide GPCRs.

Protein structure refinement of CASP target proteins using GNEIMO torsional dynamics method.

A longstanding challenge in using computational methods for protein structure prediction is the refinement of low-resolution structural models derived from comparative modeling methods into highly accurate atomistic models useful for detailed structural studies. Previously, we have developed and demonstrated the utility of the internal coordinate molecular dynamics (MD) technique, generalized Newton–Euler inverse mass operator (GNEIMO), for refinement of small proteins. Using GNEIMO, the high-frequency degrees of freedom are frozen and the protein is modeled as a collection of rigid clusters connected by torsional hinges. This physical model allows larger integration time steps and focuses the conformational search in the low frequency torsional degrees of freedom. Here, we have applied GNEIMO with temperature replica exchange to refine low-resolution protein models of 30 proteins taken from the continuous assessment of structure prediction (CASP) competition. We have shown that GNEIMO torsional MD method leads to refinement of up to 1.3 Å in the root-mean-square deviation in coordinates for 30 CASP target proteins without using any experimental data as restraints in performing the GNEIMO simulations. This is in contrast with the unconstrained all-atom Cartesian MD method performed under the same conditions, where refinement requires the use of restraints during the simulations.

Internal Coordinate Molecular Dynamics: A Foundation for Multiscale Dynamics

Internal coordinates such as bond lengths, bond angles, and torsion angles (BAT) are natural coordinates for describing a bonded molecular system. However, the molecular dynamics (MD) simulation methods that are widely used for proteins, DNA, and polymers are based on Cartesian coordinates owing to the mathematical simplicity of the equations of motion. However, constraints are often needed with Cartesian MD simulations to enhance the conformational sampling. This makes the equations of motion in the Cartesian coordinates differential-algebraic, which adversely impacts the complexity and the robustness of the simulations. On the other hand, constraints can be easily placed in BAT coordinates by removing the degrees of freedom that need to be constrained. Thus, the internal coordinate MD (ICMD) offers an attractive alternative to Cartesian coordinate MD for developing multiscale MD method. The torsional MD method is a special adaptation of the ICMD method, where all the bond lengths and bond angles are kept rigid. The advantages of ICMD simulation methods are the longer time step size afforded by freezing high frequency degrees of freedom and performing a conformational search in the more important low frequency torsional degrees of freedom. However, the advancements in the ICMD simulations have been slow and stifled by long-standing mathematical bottlenecks. In this review, we summarize the recent mathematical advancements we have made based on spatial operator algebra, in developing a robust long time scale ICMD simulation toolkit useful for various applications. We also present the applications of ICMD simulations to study conformational changes in proteins and protein structure refinement. We review the advantages of the ICMD simulations over the Cartesian simulations when used with enhanced sampling methods and project the future use of ICMD simulations in protein dynamics.

Fixman compensating potential for general branched molecules.

The technique of constraining high frequency modes of molecular motion is an effective way to increase simulation time scale and improve conformational sampling in molecular dynamics simulations. However, it has been shown that constraints on higher frequency modes such as bond lengths and bond angles stiffen the molecular model, thereby introducing systematic biases in the statistical behavior of the simulations. Fixman proposed a compensating potential to remove such biases in the thermodynamic and kinetic properties calculated from dynamics simulations. Previous implementations of the Fixman potential have been limited to only short serial chain systems. In this paper, we present a spatial operator algebra based algorithm to calculate the Fixman potential and its gradient within constrained dynamics simulations for branched topology molecules of any size. Our numerical studies on molecules of increasing complexity validate our algorithm by demonstrating recovery of the dihedral angle probability distribution function for systems that range in complexity from serial chains to protein molecules. We observe that the Fixman compensating potential recovers the free energy surface of a serial chain polymer, thus annulling the biases caused by constraining the bond lengths and bond angles. The inclusion of Fixman potential entails only a modest increase in the computational cost in these simulations. We believe that this work represents the first instance where the Fixman potential has been used for general branched systems, and establishes the viability for its use in constrained dynamics simulations of proteins and other macromolecules.

Engineering salt bridge networks between transmembrane helices confers thermostability in G-protein Coupled Receptors

Introduction of specific point mutations has been an effective strategy in enhancing the thermostability of G-protein-coupled receptors (GPCRs). Our previous work showed that a specific residue position on transmembrane helix 6 (TM6) in class A GPCRs consistently yields thermostable mutants. The crystal structure of human chemokine receptor CCR5 also showed increased thermostability upon mutation of two positions, A233D6.33 and K303E7.59. With the goal of testing the transferability of these two thermostabilizing mutations in other chemokine receptors, we tested the mutations A237D6.33 and R307E7.59 in human CCR3 for thermostability and aggregation properties in detergent solution. Interestingly, the double mutant exhibited a 6-10-fold decrease in the aggregation propensity of the wild-type protein. This is in stark contrast to the two single mutants whose aggregation properties resemble the wild type (WT). Moreover, unlike in CCR5, the two single mutants separately showed no increase in thermostability compared to the wild-type CCR3, while the double-mutant A237D6.33/R307E7.59 confers an increase of 2.6 °C in the melting temperature compared to the WT. Extensive all-atom molecular dynamics (MD) simulations in detergent micelles show that a salt bridge network between transmembrane helices TM3, TM6, and TM7 that is absent in the two single mutants confers stability in the double mutant. The free energy surface of the double mutant shows conformational homogeneity compared to the single mutants. An annular n-dodecyl maltoside detergent layer packs tighter to the hydrophobic surface of the double-mutant CCR3 compared to the single mutants providing additional stability. The purification of other C-C chemokine receptors lacking such stabilizing residues may benefit from the incorporation of these two point mutations.

Bitopic inhibition of ATP and substrate binding in Ser/Thr kinases through a conserved allosteric mechanism

Protein kinases achieve substrate selective phosphorylation through their conformational flexibility and dynamic interaction with the substrate. Designing substrate selective or kinase selective small molecule inhibitors remains a challenge because of a lack of understanding of the dynamic mechanism by which substrates are selected by the kinase. Using a combination of all-atom molecular dynamics simulations and FRET sensors, we have delineated an allosteric mechanism that results in interaction among the DFG motif, G-loop, and activation loop and structurally links the nucleotide and substrate binding interfaces in protein kinase Cα and three other Ser/Thr kinases. ATP-competitive staurosporine analogues engage this allosteric switch region located just outside the ATP binding site to displace substrate binding to varying degrees. These inhibitors function as bitopic ligands by occupying the ATP binding site and interacting with the allosteric switch region. The conserved mechanism identified in this study can be exploited to select and design bitopic inhibitors for kinases.