Hybrid approaches to molecular simulation

Key aspects of the past 30 years of protein design

Proteins are the workhorse of life. They are the building infrastructure of living systems; they are the most efficient molecular machines known, and their enzymatic activity is still unmatched in versatility by any artificial system. Perhaps proteins' most remarkable feature is their modularity. The large amount of information required to specify each protein's function is analogically encoded with an alphabet of just ∼20 letters. The protein folding problem is how to encode all such information in a sequence of 20 letters. In this review, we go through the last 30 years of research to summarize the state of the art and highlight some applications related to fundamental problems of protein evolution.

Identification of Protein Functional Regions

Protein sequence stores the information relative to both functionality and stability, thus making it difficult to disentangle the two contributions. However, the identification of critical residues for function and stability has important implications for the mapping of the proteome interactions, as well as for many pharmaceutical applications, e. g. the identification of ligand binding regions for targeted pharmaceutical protein design. In this work, we propose a computational method to identify critical residues for protein functionality and stability and to further categorise them in strictly functional, structural and intermediate. We evaluate single site conservation and use Direct Coupling Analysis (DCA) to identify co-evolved residues both in natural and artificial evolution processes. We reproduce artificial evolution using protein design and base our approach on the hypothesis that artificial evolution in the absence of any functional constraint would exclusively lead to site conservation and co-evolution events of the structural type. Conversely, natural evolution intrinsically embeds both functional and structural information. By comparing the lists of conserved and co-evolved residues, outcomes of the analysis on natural and artificial evolution, we identify the functional residues without the need of any a priori knowledge of the biological role of the analysed protein.

Exploring free energy landscapes of large conformational changes: molecular dynamics with excited normal modes

Proteins are found in solution as ensembles of conformations in dynamic equilibrium. Exploration of functional motions occurring on micro- to millisecond time scales by molecular dynamics (MD) simulations still remains computationally challenging. Alternatively, normal mode (NM) analysis is a well-suited method to characterize intrinsic slow collective motions, often associated with protein function, but the absence of anharmonic effects preclude a proper characterization of conformational distributions in a multidimensional NM space. Using both methods jointly appears to be an attractive approach that allows an extended sampling of the conformational space. In line with this view, the MDeNM (molecular dynamics with excited normal modes) method presented here consists of multiple-replica short MD simulations in which motions described by a given subset of low-frequency NMs are kinetically excited. This is achieved by adding additional atomic velocities along several randomly determined linear combinations of NM vectors, thus allowing an efficient coupling between slow and fast motions. The relatively high-energy conformations generated with MDeNM are further relaxed with standard MD simulations, enabling free energy landscapes to be determined. Two widely studied proteins were selected as examples: hen egg lysozyme and HIV-1 protease. In both cases, MDeNM provides a larger extent of sampling in a few nanoseconds, outperforming long standard MD simulations. A high degree of correlation with motions inferred from experimental sources (X-ray, EPR, and NMR) and with free energy estimations obtained by metadynamics was observed. Finally, the large sets of conformations obtained with MDeNM can be used to better characterize relevant dynamical populations, allowing for a better interpretation of experimental data such as SAXS curves and NMR spectra.

Conformational Equilibrium of CDK/Cyclin Complexes by Molecular Dynamics with Excited Normal Modes

Cyclin-dependent kinases (CDKs) and their associated regulatory cyclins are central for timely regulation of cell-cycle progression. They constitute attractive pharmacological targets for development of anticancer therapeutics, since they are frequently deregulated in human cancers and contribute to sustained, uncontrolled tumor proliferation. Characterization of their structural/dynamic features is essential to gain in-depth insight into structure-activity relationships. In addition, the identification of druggable pockets or key intermediate conformations yields potential targets for the development of novel classes of inhibitors. Structural studies of CDK2/cyclin A have provided a wealth of information concerning monomeric/heterodimeric forms of this kinase. There is, however, much less structural information for other CDK/cyclin complexes, including CDK4/cyclin D1, which displays an alternative (open) position of the cyclin partner relative to CDK, contrasting with the closed CDK2/cyclin A conformation. In this study, we carried out normal-mode analysis and enhanced sampling simulations with our recently developed method, molecular dynamics with excited normal modes, to understand the conformational equilibrium on these complexes. Interestingly, the lowest-frequency normal mode computed for each complex described the transition between the open and closed conformations. Exploration of these motions with an explicit-solvent representation using molecular dynamics with excited normal modes confirmed that the closed conformation is the most stable for the CDK2/cyclin A complex, in agreement with their experimentally available structures. On the other hand, we clearly show that an open↔closed equilibrium may exist in CDK4/cyclin D1, with closed conformations resembling that captured for CDK2/cyclin A. Such conformational preferences may result from the distinct distributions of frustrated contacts in each complex. Using the same approach, the putative roles of the Thr(160) phosphoryl group and the T-loop conformation were investigated. These results provide a dynamic view of CDKs revealing intermediate conformations not yet characterized for CDK members other than CDK2, which will be useful for the design of inhibitors targeting critical conformational transitions.

Peptide docking and structure-based characterization of peptide binding: from knowledge to know-how

Peptide-mediated interactions are gaining increased attention due to their predominant roles in the many regulatory processes that involve dynamic interactions between proteins. The structures of such interactions provide an excellent starting point for their characterization and manipulation, and can provide leads for targeted inhibitor design. The relatively few experimentally determined structures of peptide-protein complexes can be complemented with an outburst of modeling approaches that have been introduced in recent years, with increasing accuracy and applicability to ever more systems. We review different methods to address the considerable challenges in modeling the binding of a short yet highly flexible peptide to its partner. These methods apply an array of sampling strategies and draw from a recent amassing of knowledge about the biophysical nature of peptide-protein interactions. We elaborate on applications of these structure-based approaches and in particular on the characterization of peptide binding specificity to different peptide-binding domains and enzymes. Such applications can identify new biological targets and thus complement our current view of protein-protein interactions in living organisms. Accurate peptide-protein docking is of particular importance in the light of increased appreciation of the crucial functional roles of disordered regions and the many linear binding motifs embedded within.

Frequency response of a protein to local conformational perturbations

Signals created by local perturbations are known to propagate long distances through proteins via backbone connectivity and nonbonded interactions. In the current study, signal propagation from the flexible ligand binding loop to the rest of Protein Tyrosine Phosphatase 1B (PTP1B) was investigated using frequency response techniques. Using restrained Targeted Molecular Dynamics (TMD) potential on WPD and R loops, PTP1B was driven between its crystal structure conformations at different frequencies. Propagation of the local perturbation signal was manifested via peaks at the fundamental frequency and upper harmonics of 1/f distributed spectral density of atomic variables, such as Cα atoms, dihedral angles, or polar interaction distances. Frequency of perturbation was adjusted high enough (simulation length >∼10×period of a perturbation cycle) not to be clouded by random diffusional fluctuations, and low enough (<∼0.8 ns(-1)) not to attenuate the propagating signal and enhance the contribution of the side-chains to the dissipation of the signals. Employing Discrete Fourier Transform (DFT) to TMD simulation trajectories of 16 cycles of conformational transitions at periods of 1.2 to 5 ns yielded Cα displacements consistent with those obtained from crystal structures. Identification of the perturbed atomic variables by statistical t-tests on log-log scale spectral densities revealed the extent of signal propagation in PTP1B, while phase angles of the filtered trajectories at the fundamental frequency were used to cluster collectively fluctuating elements. Hydrophobic interactions were found to have a higher contribution to signal transduction between side-chains compared to the role of polar interactions. Most of in-phase fluctuating residues on the signaling pathway were found to have high identity among PTP domains, and located over a wide region of PTP1B including the allosteric site. Due to its simplicity and efficiency, the suggested technique may find wide applications in identification of signaling pathways of different proteins.

Membrane phospholipid bilayer as a determinant of monoacylglycerol lipase kinetic profile and conformational repertoire

The membrane-associated serine hydrolase, monoacylglycerol lipase (MGL), is a well-recognized therapeutic target that regulates endocannabinoid signaling. Crystallographic studies, while providing structural information about static MGL states, offer no direct experimental insight into the impact of MGL's membrane association upon its structure-function landscape. We report application of phospholipid bilayer nanodiscs as biomembrane models with which to evaluate the effect of a membrane system on the catalytic properties and conformational dynamics of human MGL (hMGL). Anionic and charge-neutral phospholipid bilayer nanodiscs enhanced hMGL's kinetic properties [apparent maximum velocity (Vmax) and substrate affinity (Km)]. Hydrogen exchange mass spectrometry (HX MS) was used as a conformational analysis method to profile experimentally the extent of hMGL-nanodisc interaction and its impact upon hMGL structure. We provide evidence that significant regions of hMGL lid-domain helix α4 and neighboring helix α6 interact with the nanodisc phospholipid bilayer, anchoring hMGL in a more open conformation to facilitate ligand access to the enzyme's substrate-binding channel. Covalent modification of membrane-associated hMGL by the irreversible carbamate inhibitor, AM6580, shielded the active site region, but did not increase solvent exposure of the lid domain, suggesting that the inactive, carbamylated enzyme remains intact and membrane associated. Molecular dynamics simulations generated conformational models congruent with the open, membrane-associated topology of active and inhibited, covalently-modified hMGL. Our data indicate that hMGL interaction with a phospholipid membrane bilayer induces regional changes in the enzyme's conformation that favor its recruiting lipophilic substrate/inhibitor from membrane stores to the active site via the lid, resulting in enhanced hMGL catalytic activity and substrate affinity.