Georgios Archontis

CHARMM: The biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model‐building capabilities. The CHARMM program is applicable to problems involving a much broader class of many‐particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical‐molecular mechanical force fields, to all‐atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

Enthalpic contribution to protein stability: insights from atom-based calculations and statistical mechanics.

Publisher Summary This chapter discusses published analyses of protein stability based on model compound data and outlines the assumptions that have been made. The enthalpy of protein folding is considered and a thermodynamic cycle is used to relate the measurements to quantities that can be calculated. The focus is on the enthalpy of denaturation because it is most directly accessible to calculations. The experiments and analysis of Privalov and co-workers, particularly which of Makhatadze and Privalov are considered in detail because these measurements provide the most complete results on the thermodynamics of proteins. The estimates of internal van der Waals and hydrogen bonding contributions to the enthalpy difference between the native and denatured states of the protein are compared with the calculations of the van der Waals and electrostatic terms (the latter includes hydrogen bonding) from an atom-based model. Statistical mechanical calculations and molecular dynamics simulations are used to estimate the difference in solvation enthalpy, as well as the free energy, of the native and unfolded states.

Kinetics, in silico docking, molecular dynamics, and MM‐GBSA binding studies on prototype indirubins, KT5720, and staurosporine as phosphorylase kinase ATP‐binding site inhibitors: The role of water molecules examined

With an aim toward glycogenolysis control in Type 2 diabetes, we have investigated via kinetic experiments and computation the potential of indirubin (IC50 > 50 μM), indirubin‐3′‐oxime (IC50 = 144 nM), KT5720 (Ki = 18.4 nM) and staurosporine (Ki = 0.37 nM) as phosphorylase kinase (PhKγtrnc) ATP‐binding site inhibitors, with the latter two revealed as potent inhibitors in the low nM range. Because of lack of structural information, we have exploited information from homologous kinase complexes to direct in silico calculations (docking, molecular dynamics, and MM‐GBSA) to predict the binding characteristics of the four ligands. All inhibitors are predicted to bind in the same active site area as the ATP adenine ring, with binding dominated by hinge region hydrogen bonds to Asp104:O and Met106:O (all four ligands) and also Met106:NH (for the indirubins). The PhKγtrnc‐staurosporine complex has the greatest number of receptor‐ligand hydrogen bonds, while for the indirubin‐3′‐oxime and KT5720 complexes there is an important network of interchanging water molecules bridging inhibitor‐enzyme contacts. The MM‐GBSA results revealed the source of staurosporines low nM potency to be favorable electrostatic interactions, while KT5720 has strong van der Waals contributions. KT5720 interacts with the greatest number of protein residues either by direct or 1‐water bridged hydrogen bond interactions, and the potential for more selective PhK inhibition based on a KT5720 analogue has been established. Including receptor flexibility in Schrödinger induced‐fit docking calculations in most cases correctly predicted the binding modes as compared with the molecular dynamics structures; the algorithm was less effective when there were key structural waters bridging receptor‐ligand contacts. Proteins 2011.

Glucose-based spiro-isoxazolines: a new family of potent glycogen phosphorylase inhibitors.

A series of glucopyranosylidene-spiro-isoxazolines was prepared through regio- and stereoselective [3+2]-cycloaddition between the methylene acetylated exo-glucal and aromatic nitrile oxides. The deprotected cycloadducts were evaluated as inhibitors of muscle glycogen phosphorylase b. The carbohydrate-based family of five inhibitors displays K(i) values ranging from 0.63 to 92.5 microM. The X-ray structures of the enzyme-ligand complexes show that the inhibitors bind preferentially at the catalytic site of the enzyme retaining the less active T-state conformation. Docking calculations with GLIDE in extra-precision (XP) mode yielded excellent agreement with experiment, as judged by comparison of the predicted binding modes of the five ligands with the crystallographic conformations and the good correlation between the docking scores and the experimental free binding energies. Use of docking constraints on the well-defined positions of the glucopyranose moiety in the catalytic site and redocking of GLIDE-XP poses using electrostatic potential fit-determined ligand partial charges in quantum polarized ligand docking (QPLD) produced the best results in this regard.

Computational sidechain placement and protein mutagenesis with implicit solvent models.

Structure prediction and computational protein design should benefit from accurate solvent models. We have applied implicit solvent models to two problems that are central to this area. First, we performed sidechain placement for 29 proteins, using a solvent model that combines a screened Coulomb term with an Accessible Surface Area term (CASA model). With optimized parameters, the prediction quality is comparable with earlier work that omitted electrostatics and solvation altogether. Second, we computed the stability changes associated with point mutations involving ionized sidechains. For over 1000 mutations, including many fully or partly buried positions, we compared CASA and two generalized Born models (GB) with a more accurate model, which solves the Poisson equation of continuum electrostatics numerically. CASA predicts the correct sign and order of magnitude of the stability change for 81% of the mutations, compared to 97% with the best GB. We also considered 140 mutations for which experimental data are available. Comparing to experiment requires additional assumptions about the unfolded protein structure, protein relaxation in response to the mutations, and contributions from the hydrophobic effect. With a simple, commonly‐used unfolded state model, the mean unsigned error is 2.1 kcal/mol with both CASA and the best GB. Overall, the electrostatic model is not important for sidechain placement; CASA and GB are equivalent for surface mutations, while GB is far superior for fully or partly buried positions. Thus, for problems like protein design that involve all these aspects, the most recent GB models represent an important step forward. Along with the recent discovery of efficient, pairwise implementations of GB, this will open new possibilities for the computational engineering of proteins. Proteins 2007.

Crossreactivity to vinculin and microbes provides a molecular basis for HLA-based protection against rheumatoid arthritis

The HLA locus is the strongest risk factor for anti-citrullinated protein antibody (ACPA)(+) rheumatoid arthritis (RA). Despite considerable efforts in the last 35 years, this association is poorly understood. Here we identify (citrullinated) vinculin, present in the joints of ACPA(+) RA patients, as an autoantigen targeted by ACPA and CD4(+) T cells. These T cells recognize an epitope with the core sequence DERAA, which is also found in many microbes and in protective HLA-DRB1*13 molecules, presented by predisposing HLA-DQ molecules. Moreover, these T cells crossreact with vinculin-derived and microbial-derived DERAA epitopes. Intriguingly, DERAA-directed T cells are not detected in HLA-DRB1*13(+) donors, indicating that the DERAA epitope from HLA-DRB1*13 mediates (thymic) tolerance in these donors and explaining the protective effects associated with HLA-DRB1*13. Together our data indicate the involvement of pathogen-induced DERAA-directed T cells in the HLA-RA association and provide a molecular basis for the contribution of protective/predisposing HLA alleles.

Protein electron transfer: a numerical study of tunneling through fluctuating bridges

A central challenge of protein electron-transfer theory is to understand how the protein dynamics influences the electron . tunneling from donor to acceptor. It is shown that tunneling as a function of time through a fluctuating protein bridge is drastically different from tunneling through a chemically identical static bridge. The static two-state approximation that leads to the donor-acceptor matrix element T , is therefore inadequate. A time-dependent two-state approximation is found that DA describes the tunneling dynamics through a fluctuating bridge. The fluctuating system electronic Hamiltonians are constructed from molecular dynamics trajectories at the CNDO-SCF level. q 1999 Elsevier Science B.V. All rights reserved.

Electron transfer through fluctuating bridges: On the validity of the superexchange mechanism and time-dependent tunneling matrix elements

The superexchange mechanism of electron-transfer reactions is studied for time-dependent donor–bridge–acceptor systems. It is shown that superexchange may not be a relevant mechanism in a situation where donor and acceptor states are off-resonant to the bridge with an energy gap much greater than KBT. The competing mechanism in this case involves coherent through-bridge transfer. Methods for estimating its contribution to the electron-transfer probability are presented. It is also shown that the superexchange component of the electron-transfer probability can generally be described by a time-dependent two-state effective Hamiltonian. The off-diagonal element of this Hamiltonian is a generalized superexchange matrix element applicable to time-dependent donor–bridge–acceptor systems. It is nonperturbative and should be used to compute time-dependent superexchange pathways. The derivation of the effective Hamiltonian also applies to time-dependent superexchange systems with multiple donor (acceptor) states. ...

Species specificity of the complement inhibitor compstatin investigated by all-atom molecular dynamics simulations

The development of compounds to regulate the activation of the complement system in non‐primate species is of profound interest because it can provide models for human diseases. The peptide compstatin inhibits protein C3 in primate mammals and is a potential therapeutic agent against unregulated activation of complement in humans but is inactive against nonprimate species. Here, we elucidate this species specificity of compstatin by molecular dynamics simulations of complexes between the most potent natural compstatin analog and human or rat C3. The results are compared against an experimental conformation of the human complex, determined recently by X‐ray diffraction at 2.4‐Å resolution. The human complex simulations provide information on the relative contributions to stability of specific C3 and compstatin residues. In the rat simulations, the protein undergoes reproducible conformational changes, which eliminate or weaken specific interactions and reduce the complex stability. The simulation insights can be used to design improved compstatin‐based inhibitors for human C3 and active inhibitors against lower mammals. Proteins 2010.

Molecular Dynamics in Drug Design: New Generations of Compstatin Analogs

We report the computational and rational design of new generations of potential peptide‐based inhibitors of the complement protein C3 from the compstatin family. The binding efficacy of the peptides is tested by extensive molecular dynamics‐based structural and physicochemical analysis, using 32 atomic detail trajectories in explicit water for 22 peptides bound to human, rat or mouse target protein C3, with a total of 257 ns. The criteria for the new design are: (i) optimization for C3 affinity and for the balance between hydrophobicity and polarity to improve solubility compared to known compstatin analogs; and (ii) development of dual specificity, human‐rat/mouse C3 inhibitors, which could be used in animal disease models. Three of the new analogs are analyzed in more detail as they possess strong and novel binding characteristics and are promising candidates for further optimization. This work paves the way for the development of an improved therapeutic for age‐related macular degeneration, and other complement system‐mediated diseases, compared to known compstatin variants.