Alessandro Genoni

Molecular Recognition and Drug-Lead Identification: What Can Molecular Simulations Tell Us?

Molecular recognition and ligand binding involving proteins underlie the most important life processes within the cell, such as substrate transport, catalysis, signal transmission, receptor trafficking, gene regulation, switching on and off of biochemical pathways. Despite recent successes in predicting the structures of many protein-substrate complexes, the dynamic aspects of binding have been largely neglected by computational/theoretical investigations. Recently, several groups have started tackling these problems with the use of experimental and simulation methods and developed models describing the variation of protein dynamics upon complex formation, shedding light on how substrate or inhibitor binding can alter protein flexibility and function. The study of ligand-induced dynamic variations has also been exploited to review the concept of allosteric changes, in the absence of major conformational changes. In this context, the study of the influence of protein motions on signal transduction and on catalytic activities has been used to develop pharmacophore models based on ensembles of protein conformations. These models, taking flexibility explicitly into account, are able to distinguish active inhibitors versus nonactive drug-like compounds, to define new molecular motifs and to preferentially identify specific ligands for a certain protein target. The application of these methods holds great promise in advancing structure-based drug discovery and medicinal chemistry in general, opening up the possibility to explore broader chemical spaces than is normally done in an efficient way. In this review, examples illustrating the extent to which simulations can be used to understand these phenomena will be presented along with examples of methodological developments to increase physical understanding of the processes and improve the possibility to rationally design new molecules.

Computational study of the resistance shown by the Subtype B / HIV-1 Protease to currently known inhibitors †

Human immunodeficiency virus type 1 protease (HIV-1 PR) is an essential enzyme in the HIV-1 life cycle. As such, this protein represents a major drug target in AIDS therapy, but emerging resistance to antiretroviral inhibitor cocktails, caused by high viral mutation rates, represents a significant challenge in AIDS treatment. Many mutations are not located within the active site or binding pocket, nor they do significantly modify the three-dimensional structural organization of the enzyme; hence, the mechanism(s) by which they alter inhibitor affinity for the protease remains uncertain. In this article, we present an all-atom computational analysis of the dynamic residue-residue coordination between the active site residues and the rest of the protein and of the energetic properties of different HIV-1 PR complexes. We analyze both the wild-type form and mutated forms that induce drug resistance. In particular, the results show differences between the wild type and the mutants in their mechanism of dynamic coordination, in the signal propagation between the active site residues and the rest of the protein, and in the energy networks responsible for the stabilization of the bound inhibitor conformation. Finally, we propose a dynamic and energetic explanation for HIV-1 protease drug resistance, and, through this model, we identify a possible new site that could be helpful in the design of a new family of HIV-1 PR allosteric inhibitors.

Identification of Domains in Protein Structures from the Analysis of Intramolecular Interactions

The subdivision of protein structures into smaller and independent structural domains has a fundamental importance in understanding protein evolution and function and in the development of protein classification methods as well as in the interpretation of experimental data. Due to the rapid growth in the number of solved protein structures, the need for devising new accurate algorithmic methods has become more and more urgent. In this paper, we propose a new computational approach that is based on the concept of domain as a compact and independent folding unit and on the analysis of the residue-residue energy interactions obtainable through classical all-atom force field calculations. In particular, starting from the analysis of the nonbonded interaction energy matrix associated with a protein, our method filters out and selects only those specific subsets of interactions that define possible independent folding nuclei within a complex protein structure. This allows grouping different protein fragments into energy clusters that are found to correspond to structural domains. The strategy has been tested using proper benchmark data sets, and the results have shown that the new approach is fast and reliable in determining the number of domains in a totally ab initio manner and without making use of any training set or knowledge of the systems in exam. Moreover, our method, identifying the most relevant residues for the stabilization of each domain, may complement the results given by other classification techniques and may provide useful information to design and guide new experiments.

X-ray Constrained Extremely Localized Molecular Orbitals: Theory and Critical Assessment of the New Technique

Following the X-ray constrained wave function approach proposed by Jayatilaka, we have devised a new technique that allows to extract molecular orbitals strictly localized on small molecular fragments from sets of experimental X-ray structure factors amplitudes. Since the novel strategy enables to obtain electron distributions that have quantum mechanical features and that can be easily interpreted in terms of traditional chemical concepts, the method can be also considered as a new useful tool for the determination and the analysis of charge densities from high-resolution X-ray experiments. In this paper, we describe in detail the theory of the new technique, which, in comparison to our preliminary work, has been improved both treating the effects of isotropic secondary extinctions and introducing a new protocol to halt the fitting procedure against the experimental X-ray scattering data. The performances of the novel strategy have been studied both in function of the basis-sets flexibility and in function of the quality of the considered crystallographic data. The tests performed on four different systems (α-glycine, l-cysteine, (aminomethyl)phosphonic acid and N-(trifluoromethyl)formamide) have shown that the achievement of good statistical agreements with the experimental measures mainly depends on the quality of the crystal structures (i.e., geometry positions and thermal parameters) used in the X-ray constrained calculations. Finally, given the reliable transferability of the obtained Extremely Localized Molecular Orbitals (ELMOs), we envisage to exploit the novel approach to construct new ELMOs databases suited to the development of linear-scaling methods for the refinement of macromolecular crystal structures.

Unconstrained and X-ray constrained extremely localized molecular orbitals: analysis of the reconstructed electron density

The recently developed X-ray constrained extremely localized molecular orbital (XC-ELMO) technique is a potentially useful tool for the determination and analysis of experimental electron densities. Molecular orbitals strictly localized on atoms, bonds or functional groups allow one to combine the quantum-mechanical rigour of the wavefunction-based approaches with the easy chemical interpretability typical of the traditional multipole models. In this paper, using very high quality X-ray diffraction data for the glycylglycine crystal, a detailed assessment of the capabilities and limitations of this new method is given. In particular, the effects of constraining the ELMO wavefunctions to experimental X-ray structure-factor amplitudes and the ability of the method to reproduce benchmark electron distributions have been accurately investigated. Topological analysis of the XC-ELMO electron densities and of the zero-flux surface-integrated charges and dipole moments shows that the new strategy is already reliable, provided that sufficiently flexible basis sets are used. These analyses also raise new questions and call for further improvements of the method.

Molecular Orbitals Strictly Localized on Small Molecular Fragments from X-ray Diffraction Data

Nowadays, the electron density is recognized as a fundamental property that contains most of the information concerning the electronic structure of molecules, and, therefore, its determination from high-resolution X-ray diffraction data is becoming more and more important. In this context, we propose a new strategy for the charge density analysis, strategy in which the chemical interpretability of the multipole model is combined with the quantum mechanical rigor of the wave function-based approaches. In particular, this novel technique aims at extracting molecular orbitals strictly localized on small molecular fragments (e.g., atoms, bonds, or functional groups) from a set of measured structure factors amplitudes. Preliminary tests have shown that their determination is really straightforward and, given their reliable transferability, we envisage the possibility of constructing new extremely localized molecular orbital databases as an alternative to the existing pseudoatom libraries.

Mechanisms of Differential Allosteric Modulation in Homologous Proteins: Insights from the Analysis of Internal Dynamics and Energetics of PDZ Domains

Allostery is a general phenomenon in proteins whereby a perturbation at one site reverberates into a functional change at another one, through modulation of its conformational dynamics. Herein, we address the problem of how the molecular signal encoded by a ligand is differentially transmitted through the structures of two homologous PDZ proteins: PDZ2, which responds to binding with structural and dynamical changes in regions distal from the ligand site, and PDZ3, which is characterized by less-intense dynamical variations. We use novel methods of analysis of MD simulations in the unbound and bound states to investigate the determinants of the differential allosteric behavior of the two proteins. The analysis of the correlations between the redistribution of stabilization energy and local fluctuation patterns highlights the nucleus of residues responsible for the stabilization of the 3D fold, the stability core, as the substructure that defines the difference in the allosteric response: in PDZ2, it undergoes a consistent dynamic and energetic reorganization, whereas in PDZ3, it remains largely unperturbed. Specifically, we observe for PDZ2 a significant anticorrelation between the motions of distal loops and residues of the stability core and differences in the correlation patterns between the bound and unbound states. Such variation is not observed in PDZ3, indicating that its energetics and internal dynamics are less affected by the presence/absence of the ligand. Finally, we propose a model with a direct link between the modulation of the structural, energetic and dynamic properties of a protein, and its allosteric response to a perturbation.

Optimal virtual orbitals to relax wave functions built up with transferred extremely localized molecular orbitals

Extremely localized molecular orbitals (ELMOs), namely orbitals strictly localized on molecular fragments, are easily transferable from one molecule to another one. Hence, they provide a natural way to set up the electronic structure of large molecules using a data base of orbitals obtained from model molecules. However, this procedure obviously increases the energy with respect to a traditional MO calculation. To gain accuracy, it is important to introduce a partial electron delocalization. This can be carried out by defining proper optimal virtual orbitals that supply an efficient set for nonorthogonal configurations to be employed in VB‐like expansions.

Structure and Stability Studies of Pharmacologically Relevant S-Nitrosothiols: A Theoretical Approach

Nowadays, S-nitrosothiols (RSNOs) represent a promising class of nitric oxide (NO) donors that could be successfully used as drugs to compensate the decrease of NO production that usually arises in conjunction with cardiovascular diseases. Nevertheless, notwithstanding their pharmacological interest, the structure-stability relationship in RSNOs is still unclear, and this issue, together with the mechanism of NO donation in the physiological medium, deserves further investigation. As a first step forward in this direction, in this paper, the overall stability and structural preference of two pharmacologically relevant S-nitrosothiol molecules were studied in detail by means of computational strategies. In particular, performing calculations in implicit solvent (water) on the S-nitroso-N-acetylpenicillamine and the S-nitroso-N-acetylcysteine and analyzing the noncovalent interactions networks of their most stable conformers, we observed that the structure and the stability of these molecules can be directly related to the formation of stabilizing hydrogen-bond and chalcogen-chalcogen intramolecular interactions. The obtained results represent the starting point for further investigations to be conducted also on larger RSNOs to shed further light on the role played by intra- and intermolecular interactions and by solvation effects in stabilizing this class of molecules. The obtained insights will be hopefully helpful to design new RSNO-based drugs characterized by an enhanced pharmacological potency.

Can X-ray constrained Hartree–Fock wavefunctions retrieve electron correlation?

In this study, the X-ray constrained wavefunction approach is carefully investigated in order to assess its ability to capture the effect of electron correlation on electron density. Electron distributions obtained from highly correlated molecular wavefunctions are the benchmarks and their Fourier transforms are used to simulate X-ray intensities for the constrained wavefunction calculations.