Current Pharmaceutical Design - Volume 19, Issue 23, 2013

The ABC (ATP Binding Cassette) transporter protein superfamily comprises a large number of ubiquitous and functionally versatile proteins conserved from archaea to humans. ABC transporters have a key role in many human diseases and also in the development of multidrug resistance in cancer and in parasites. Although a dramatic progress has been achieved in ABC protein studies in the last decades, we are still far from a detailed understanding of their molecular functions. Several aspects of pharmacological ABC transporter targeting also remain unclear. Here we summarize the conformational and protonation changes of ABC transporters and the potential use of this information in pharmacological design. Network related methods, which recently became useful tools to describe protein structure and dynamics, have not been applied to study allosteric coupling in ABC proteins as yet. A detailed description of the strengths and limitations of these methods is given, and their potential use in describing ABC transporter dynamics is outlined. Finally, we highlight possible future aspects of pharmacological utilization of network methods and outline the future trends of this exciting field.

Peptides are important signaling modules, acting both as individual hormones and as parts of larger molecules, mediating their protein-protein interactions. Many peptidic and peptidomimetic drugs have reached the marketplace and opportunities for peptide-based drug discovery are on the rise. pH-dependent behavior of peptides is well documented in the context of misfolding diseases and peptide translocation. Changes in the protonation states of peptide residues often have a crucial effect on a peptide’s structure, dynamics and function, which may be exploited for biotechnological applications. The current review surveys the increasing levels of sophistication in the treatment of protonation states in computational studies involving peptides. Specifically we describe I) the common practice of assigning a single protonation state and using it throughout the dynamic simulation, II) approaches that consider multiple protonation states and compare computed observables to experimental ones, III) constant pH molecular dynamics methods that couple changes in protonation states with conformational dynamics “on the fly” Applications of conformational dynamics treatment of peptides in the context of binding, folding and interactions with the membrane are presented, illustrating the growing body of work in this field and highlighting the importance of careful handling of protonation states of peptidic residues.

In this review we discuss the role of protonation states in receptor-ligand interactions, providing experimental evidences and computational predictions that complex formation may involve titratable groups with unusual pKa’s and that protonation states frequently change from unbound to bound states. These protonation changes result in proton uptake/release, which in turn causes the pHdependence of the binding. Indeed, experimental data strongly suggest that almost any binding is pH-dependent and to be correctly modeled, the protonation states must be properly assigned prior to and after the binding. One may accurately predict the protonation states when provided with the structures of the unbound proteins and their complex; however, the modeling becomes much more complicated if the bound state has to be predicted in a docking protocol or if the structures of either bound or unbound receptor-ligand are not available. The major challenges that arise in these situations are the coupling between binding and protonation states, and the conformational changes induced by the binding and ionization states of titratable groups. In addition, any assessment of the protonation state, either before or after binding, must refer to the pH of binding, which is frequently unknown. Thus, even if the pKa’s of ionizable groups can be correctly assigned for both unbound and bound state, without knowing the experimental pH one cannot assign the corresponding protonation states, and consequently one cannot calculate the resulting proton uptake/release. It is pointed out, that while experimental pH may not be the physiological pH and binding may involve proton uptake/release, there is a tendency that the native receptor-ligand complexes have evolved toward specific either subcellular or tissue characteristic pH at which the proton uptake/release is either minimal or absent.

It is clear now that proteins lacking ordered structure, generally known as intrinsically disordered proteins (IDPs), possess numerous biological functions that complement functional repertoires of ordered proteins. IDPs are common in nature, and abundantly found to be involved in the pathogenesis of various diseases. These proteins participate in various biological processes and play crucial roles in regulation of functions of their binding partners. Often, disorder-to-order transition induced by the IDP binding to a specific partner defines the low-affinity – high-specificity signaling interactions. Although many IDPs undergo a disorder-to-order transition upon binding, large fraction of IDPs can preserve significant amount of disorder even in their bound states. IDPs can participate in one-tomany and many-to-one interactions, where one intrinsically disordered protein region (IDPR) binds to multiple partners potentially gaining very different structures in the bound state, or where multiple unrelated IDPs/IDPRs bind to one partner. Binding functions of IDPs and IDPRs are controlled by various means, such as numerous posttranslational modifications and alternative splicing. Some of the aspects of the intrinsic disorder-based protein interactions and modes of their regulation are considered in this review.

The Ras superfamily comprises many guanine nucleotide-binding proteins (G proteins) that are essential to intracellular signal transduction. These proteins act biologically as molecular switches, which, cycling between OFF and ON states, play fundamental role in cell biology. This review article summarizes the inferences from the widest computational analyses done so far on Ras GTPases aimed at providing a comprehensive structural/dynamic view of the trans-family and family-specific functioning mechanisms. These variegated comparative analyses could infer the evolutionary and intrinsic flexibilities as well as the structural communication features in the most representative G protein families in different functional states. In spite of the low sequence similarities, the members of the Ras superfamily share the topology of the Ras-like domain, including the nucleotide binding site. GDP and GTP make very similar interactions in all GTPases and differences in their binding modes are localized around the γ-phosphate of GTP. Remarkably, such subtle local differences result in significant differences in the functional dynamics and structural communication features of the protein. In Ras GTPases, the nucleotide plays a central and active role in dictating functional dynamics, establishing the major structure network, and mediating the communication paths instrumental in function retention and specialization. Collectively, the results of these studies support the speculation that an “extended conformational selection model” that embraces a repertoire of selection and adjustment processes is likely more suitable to describe the nucleotide behavior in these important molecular switches.

We herein review experimental and theoretical approaches widely applied to delineation of the differences in substrate specificities between human and parasite phosphoribosyltransferases (PRTases), the latter of which are key targets for treatment of diseases caused by parasites. Standard Molecular Dynamics (MD) simulations have been applied to determine why the human PRTase prefers guanine over xanthine, whereas the Tritrichomonas foetus enzyme exhibits only a slight preference. We analyze this problem with the aid of standard MD simulations, as well as constant-pH MD simulations. Comparison of results of the two approaches reveals substantial differences, e.g. several Asp and Glu residues in the parasite enzyme, and one Glu residue in the human enzyme, are predicted to be permanently or frequently protonated during constant-pH simulations, whereas standard MD simulations assume that these residues are always ionized. Most interesting is the observation of a large conformational change, leading to tighter binding of the ligand, observed in constant-pH MD simulations of the parasite PRTase complexed with XMP, and lack of such a change in the human enzyme complexed with XMP.

Free energy simulations are a powerful tool to study molecular recognition. The most rigorous variants can provide in depth understanding for a particular system, but are not suited for high throughput application to large libraries of compounds. Related, but less expensive methods are increasingly popular, including continuum electrostatic methods like PBSA (""Poisson-Boltzmann Surface Area") and Linear Response or Linear Interaction Energy methods (LRA, LIE). Here, we review the theoretical background of these methods and provide a unified framework. We focus on the electrostatic contributions to the binding free energy, analyzing nonpolar contributions more briefly. The methods reviewed introduce a multi-step pathway for ligand unbinding, with distinct steps that uncharge the bound ligand, then recharge the unbound ligand. They assume that the system responds to the charging/uncharging in a linear way. With this approximation, the free energy can be described by its one or two first derivatives with respect to a progress variable. The methods can then be classified according to which states of the system are actually simulated and the number of free energy derivatives (one or two) that are employed. The analysis should help clarify the relations between several important free energy methods and the approximations they make. It can suggest new ways to test them, and provide routes for their improvement.

Aspartic proteases (AP) are a family of important hydrolytic enzymes in medicinal chemistry, since many of its members have become therapeutical targets for a wide variety of diseases from AIDS to Alzheimer. The enzymatic activity of these proteins is driven by the Asp dyad, a pair of active site Asp residues that participate in the hydrolysis of peptides. Hence, the protonation state of these and other acidic residues present in these enzymes determines the catalytic rate and the affinity for an inhibitor at a given pH. In the present work we have reviewed the effect of the protonation states of the titratable residues in AP’s both on catalysis and inhibition in this family of enzymes. The first section focuses on the details of the catalytic reaction mechanism picture brought about by a large number of kinetic, crystallographic and computational chemistry analyses. The results indicate that although the mechanism is similar in both retroviral and eukaryotic enzymes, there are some clear differences. For instance, while in the former family branch the binding of the substrate induces a mono-ionic charge state for the Asp dyad, this charge state seems to be already present in the unbound state of the eukaryotic enzymes. In this section we have explored as well the possible existence of low barrier hydrogen bonds (LBHB’s) in the enzymatic path. Catalytic rate enhancement in AP’s could in part be explained by the lowering of the barrier for proton transfer in a hydrogen bond from donor to acceptor, which is a typical feature of LBHB’s. Review of the published work indicates that the experimental support for this type of bonds is rather scarce and it may be more probable in the first stages of the hydrolytic mechanism in retroviral proteases. The second section deals with the effect of active site protonation state on inhibitor binding. The design of highly potent AP inhibitors, that could be the basis for drug leads require a deep knowledge of the protonation state of the active site residues induced by their presence. This vital issue has been tackled by experimental techniques like NMR, X-ray crystallography, calorimetric and binding kinetic techniques. Recently, we have developed a protocol that combines monitoring the pH effect on binding affinities by SPR methods and rationalization of the results by molecular mechanics based calculations. We have used this combined method on BACE-1 and HIV-1 PR, two important therapeutic targets. Our calculations are able to reproduce the inhibitor binding trends to either enzyme upon a pH increase. The results indicate that inhibitors that differ in the Asp dyad binding fragments will present different binding affinity trends upon a pH increase. Our calculations have enabled us to predict the protonation states at different pH values that underlie the above mentioned trends. We have found out that these results have many implications not only for in silico hit screening campaigns aimed at finding high affinity binders, but also (in the case of BACE-1) for the discovery of cell active compounds.

The determination of the protonation state of the functional groups of ligands, and the amino acid residues with electrically charged side chains (His, Lys, Arg, Asp and Glu) or the nucleotide bases of the nucleic acids that they interact with, is important for ligand binding and recognition, the enzyme activity and reaction mechanism, and protein folding/unfolding and stability. Herein, the effects of different protonation state assignments of the small substrate and inhibitors and the critical residues on the reverse transcriptase and protease of human immunodeficiency virus type 1 (HIV-1) and the M2 proton channel of influenza A virus are reviewed. Theoretical studies on these topics are summarized and compared with the experimental data.

The unique physicochemical properties of water make it the most important molecule for life. Water molecules have many roles, direct and indirect, related to both biological structure and function. This paper: 1) reviews tools for the prediction of water conservation in and around protein active sites, by empirical (knowledge-based) algorithms and by methods based on thermodynamics principles; 2) reviews principles and approaches to predict pKa for both protein residue ensembles and for ligands; and 3) discusses the HINT biomolecular interaction model and forcefield – based on experimental measurements of LogPo/w, the 1-octanol/water partition coefficient, which implicitly incorporates all solution phenomena like these, and others like tautomerism and entropy. Lastly, it must be considered that the “real” biological environment is a continuum of nano-states and it may not be possible to represent it as a single discrete all-atom model.

In this review, a summary of methodologies is covered to enable medicinal chemists to access an overview of pKa estimation devices. In order to stave overutilization of costly synthetic resources, the chemist requires an accurate and computationally tractable solution for estimating a pKa of a candidate molecule. We focus on the cationic moieties, since they are so fundamentally important in the chemistry of drugs, and possess unique requirements to obtain a reasonably reliable pKa estimation.

Speciation of drug candidates and receptors caused by ionization, tautomerism, and/or covalent hydration complicates ligandand receptor-based predictions of binding affinities by 3-dimensional structure-activity relationships (3D-QSAR). The speciation problem is exacerbated by tendency of tautomers to bind in multiple conformations or orientations (modes) in the same binding site. New forms of the 3D-QSAR correlation equations, capable of capturing this complexity, can be developed using the time hierarchy of all steps that lie behind the monitored biological process – binding, enzyme inhibition or receptor activity. In most cases, reversible interconversions of individual ligand and receptor species can be treated as quickly established equilibria because they are finished in a small fraction of the exposure time that is used to determine biological effects. The speciation equilibria are satisfactorily approximated by invariant fractions of individual ligand and receptor species for buffered experimental or in vivo conditions. For such situations, the observed drug-receptor association constant of a ligand is expressed as the sum of products, for each ligand and receptor species pair, of the association microconstant and the fractions of involved species. For multiple binding modes, each microconstant is expressed as the sum of microconstants of individual modes. This master equation leads to new 3D-QSAR correlation equations integrating the results of all molecular simulations or calculations, which are run for each ligand-receptor species pair separately. The multispecies, multimode 3D-QSAR approach is illustrated by a ligand-based correlation of transthyretin binding of thyroxine analogs and by a receptor-based correlation of inhibition of MK2 by benzothiophenes and pyrrolopyrimidines.

Drug affinity and function depend on the different protonation species (present in the biological context) that generate different conformational ensembles with different structural features and, hence, different physico-chemical properties. In the present review article these strongly interdependent structural features will be considered for their crucial role in ligand-based QSAR modeling and drug design by using quantum chemical electronic/reactivity descriptors and molecular shape description. Some selected and relevant examples illustrate the role of these molecular descriptors, computed on the bioactive protonation states and conformers, as determinant factors in mechanistic/causative QSAR analysis.