Probing molecular docking in a charged model binding site

A model binding site was used to investigate charge-charge interactions in molecular docking. This simple site, a small (180A(3)) engineered cavity in cyctochrome c peroxidase (CCP), is negatively charged and completely buried from solvent, allowing us to explore the balance between electrostatic energy and ligand desolvation energy in a system where many of the common approximations in docking do not apply. A database with about 5300 molecules was docked into this cavity. Retrospective testing with known ligands and decoys showed that overall the balance between electrostatic interaction and desolvation energy was captured. More interesting were prospective docking scre"ens that looked for novel ligands, especially those that might reveal problems with the docking and energy methods. Based on screens of the 5300 compound database, both high-scoring and low-scoring molecules were acquired and tested for binding. Out of 16 new, high-scoring compounds tested, 15 were observed to bind. All of these were small heterocyclic cations. Binding constants were measured for a few of these, they ranged between 20microM and 60microM. Crystal structures were determined for ten of these ligands in complex with the protein. The observed ligand geometry corresponded closely to that predicted by docking. Several low-scoring alkyl amino cations were also tested and found to bind. The low docking score of these molecules owed to the relatively high charge density of the charged amino group and the corresponding high desolvation penalty. When the complex structures of those ligands were determined, a bound water molecule was observed interacting with the amino group and a backbone carbonyl group of the cavity. This water molecule mitigates the desolvation penalty and improves the interaction energy relative to that of the "naked" site used in the docking screen. Finally, six low-scoring neutral molecules were also tested, with a view to looking for false negative predictions. Whereas most of these did not bind, two did (phenol and 3-fluorocatechol). Crystal structures for these two ligands in complex with the cavity site suggest reasons for their binding. That these neutral molecules do, in fact bind, contradicts previous results in this site and, along with the alkyl amines, provides instructive false negatives that help identify weaknesses in our scoring functions. Several improvements of these are considered.     

Blind Prediction of Charged Ligand Binding Affinities in a Model Binding Site

Predicting absolute protein–ligand binding affinities remains a frontier challenge in ligand discovery and design. This becomes more difficult when ionic interactions are involved because of the large opposing solvation and electrostatic attraction energies. In a blind test, we examined whether alchemical free-energy calculations could predict binding affinities of 14 charged and 5 neutral compounds previously untested as ligands for a cavity binding site in cytochrome c peroxidase. In this simplified site, polar and cationic ligands compete with solvent to interact with a buried aspartate. Predictions were tested by calorimetry, spectroscopy, and crystallography. Of the 15 compounds predicted to bind, 13 were experimentally confirmed, while 4 compounds were false negative predictions. Predictions had a root-mean-square error of 1.95 kcal/mol to the experimental affinities, and predicted poses had an average RMSD of 1.7 Å to the crystallographic poses. This test serves as a benchmark for these thermodynamically rigorous calculations at predicting binding affinities for charged compounds and gives insights into the existing sources of error, which are primarily electrostatic interactions inside proteins. Our experiments also provide a useful set of ionic binding affinities in a simplified system for testing new affinity prediction methods.     

Rescoring docking hit lists for model cavity sites: predictions and experimental testing

Molecular docking computationally screens thousands to millions of organic molecules against protein structures, looking for those with complementary fits. Many approximations are made, often resulting in low “hit rates.” A strategy to overcome these approximations is to rescore top-ranked docked molecules using a better but slower method. One such is afforded by molecular mechanics-generalized Born surface area (MM-GBSA) techniques. These more physically realistic methods have improved models for solvation and electrostatic interactions and conformational change compared to most docking programs. To investigate MM-GBSA rescoring, we re-ranked docking hit lists in three small buried sites: a hydrophobic cavity that binds apolar ligands, a slightly polar cavity that binds aryl and hydrogen-bonding ligands, and an anionic cavity that binds cationic ligands. These sites are simple; consequently, incorrect predictions can be attributed to particular errors in the method, and many likely ligands may actually be tested. In retrospective calculations, MM-GBSA techniques with binding-site minimization better distinguished the known ligands for each cavity from the known decoys compared to the docking calculation alone. This encouraged us to test rescoring prospectively on molecules that ranked poorly by docking but that ranked well when rescored by MM-GBSA. A total of 33 molecules highly ranked by MM-GBSA for the three cavities were tested experimentally. Of these, 23 were observed to bind—these are docking false negatives rescued by rescoring. The 10 remaining molecules are true negatives by docking and false positives by MM-GBSA. X-ray crystal structures were determined for 21 of these 23 molecules. In many cases, the geometry prediction by MM-GBSA improved the initial docking pose and more closely resembled the crystallographic result; yet in several cases, the rescored geometry failed to capture large conformational changes in the protein. Intriguingly, rescoring not only rescued docking false positives, but also introduced several new false positives into the top-ranking molecules. We consider the origins of the successes and failures in MM-GBSA rescoring in these model cavity sites and the prospects for rescoring in biologically relevant targets.     

The thermodynamics of protein-ligand interaction and solvation: insights for ligand design

Isothermal titration calorimetry is able to provide accurate information on the thermodynamic contributions of enthalpy and entropy changes to free energies of binding. The Structure/Calorimetry of Reported Protein Interactions Online database of published isothermal titration calorimetry studies and structural information on the interactions between proteins and small-molecule ligands is used here to reveal general thermodynamic properties of protein-ligand interactions and to investigate correlations with changes in solvation. The overwhelming majority of interactions are found to be enthalpically favoured. Synthetic inhibitors and biological ligands form two distinct subpopulations in the data, with the former having greater average affinity due to more favourable entropy changes on binding. The greatest correlation is found between the binding free energy and apolar surface burial upon complex formation. However, the free-energy contribution per unit area buried is only 30-50% of that expected from earlier studies of transfer free energies of small molecules. A simple probability-based estimator for the maximal affinity of a binding site in terms of its apolar surface area is proposed. Polar surface area burial also contributes substantially to affinity but is difficult to express in terms of unit area due to the small variation in the amount of polar surface buried and a tendency for cancellation of its enthalpic and entropic contributions. Conventionally, the contribution of apolar desolvation to affinity is attributed to gain of entropy due to solvent release. Although data presented here are supportive of this notion, because the correlation of entropy change with apolar surface burial is relatively weak, it cannot, on present evidence, be confidently considered to be correct. Further, thermodynamic changes arising from small differences between ligands binding to individual proteins are relatively large and, in general, uncorrelated with changes in solvation, suggesting that trends identified across widely differing proteins are of limited use in explaining or predicting the effects of ligand modifications.     

Ligand solvation in molecular docking

Solvation plays an important role in ligand‐protein association and has a strong impact on comparisons of binding energies for dissimilar molecules. When databases of such molecules are screened for complementarity to receptors of known structure, as often occurs in structure‐based inhibitor discovery, failure to consider ligand solvation often leads to putative ligands that are too highly charged or too large. To correct for the different charge states and sizes of the ligands, we calculated electrostatic and non‐polar solvation free energies for molecules in a widely used molecular database, the Available Chemicals Directory (ACD). A modified Born equation treatment was used to calculate the electrostatic component of ligand solvation. The non‐polar component of ligand solvation was calculated based on the surface area of the ligand and parameters derived from the hydration energies of apolar ligands. These solvation energies were subtracted from the ligand‐receptor interaction energies. We tested the usefulness of these corrections by screening the ACD for molecules that complemented three proteins of known structure, using a molecular docking program. Correcting for ligand solvation improved the rankings of known ligands and discriminated against molecules with inappropriate charge states and sizes. Proteins 1999;34:4–16. © 1999 Wiley‐Liss, Inc.     

Structural parameterization of the binding enthalpy of small ligands

A major goal in ligand and drug design is the optimization of the binding affinity of selected lead molecules. However, the binding affinity is defined by the free energy of binding, which, in turn, is determined by the enthalpy and entropy changes. Because the binding enthalpy is the term that predominantly reflects the strength of the interactions of the ligand with its target relative to those with the solvent, it is desirable to develop ways of predicting enthalpy changes from structural considerations. The application of structure/enthalpy correlations derived from protein stability data has yielded inconsistent results when applied to small ligands of pharmaceutical interest (MW < 800). Here we present a first attempt at an empirical parameterization of the binding enthalpy for small ligands in terms of structural information. We find that at least three terms need to be considered: (1) the intrinsic enthalpy change that reflects the nature of the interactions between ligand, target, and solvent; (2) the enthalpy associated with any possible conformational change in the protein or ligand upon binding; and, (3) the enthalpy associated with protonation/deprotonation events, if present. As in the case of protein stability, the intrinsic binding enthalpy scales with changes in solvent accessible surface areas. However, an accurate estimation of the intrinsic binding enthalpy requires explicit consideration of long-lived water molecules at the binding interface. The best statistical structure/enthalpy correlation is obtained when buried water molecules within 5-7 A of the ligand are included in the calculations. For all seven protein systems considered (HIV-1 protease, dihydrodipicolinate reductase, Rnase T1, streptavidin, pp60c-Src SH2 domain, Hsp90 molecular chaperone, and bovine beta-trypsin) the binding enthalpy of 25 small molecular weight peptide and nonpeptide ligands can be accounted for with a standard error of +/-0.3 kcal x mol(-1).     

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

Background

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds.

Methodology

In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy.

Conclusions

The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.     

Flexible docking using tabu search and an empirical estimate of binding affinity

This article describes the implementation of a new docking approach. The method uses a Tabu search methodology to dock flexibly ligand molecules into rigid receptor structures. It uses an empirical objective function with a small number of physically based terms derived from fitting experimental binding affinities for crystallographic complexes. This means that docking energies produced by the searching algorithm provide direct estimates of the binding affinities of the ligands. The method has been tested on 50 ligand-receptor complexes for which the experimental binding affinity and binding geometry are known. All water molecules are removed from the structures and ligand molecules are minimized in vacuo before docking. The lowest energy geometry produced by the docking protocol is within 1.5 Å root-mean square of the experimental binding mode for 86% of the complexes. The lowest energies produced by the docking are in fair agreement with the known free energies of binding for the ligands. Proteins 33:367–382, 1998. © 1998 Wiley-Liss, Inc.     

Predicting absolute ligand binding free energies to a simple model site

A central challenge in structure-based ligand design is the accurate prediction of binding free energies. Here we apply alchemical free energy calculations in explicit solvent to predict ligand binding in a model cavity in T4 lysozyme. Even in this simple site, there are challenges. We made systematic improvements, beginning with single poses from docking, then including multiple poses, additional protein conformational changes, and using an improved charge model. Computed absolute binding free energies had an RMS error of 1.9 kcal/mol relative to previously determined experimental values. In blind prospective tests, the methods correctly discriminated between several true ligands and decoys in a set of putative binders identified by docking. In these prospective tests, the RMS error in predicted binding free energies relative to those subsequently determined experimentally was only 0.6 kcal/mol. X-ray crystal structures of the new ligands bound in the cavity corresponded closely to predictions from the free energy calculations, but sometimes differed from those predicted by docking. Finally, we examined the impact of holding the protein rigid, as in docking, with a view to learning how approximations made in docking affect accuracy and how they may be improved.     

Optimizing the affinity and specificity of ligand binding with the inclusion of solvation effect

Solvation effect is an important factor for protein–ligand binding in aqueous water. Previous scoring function of protein–ligand interactions rarely incorporates the solvation model into the quantification of protein–ligand interactions, mainly due to the immense computational cost, especially in the structure‐based virtual screening, and nontransferable application of independently optimized atomic solvation parameters. In order to overcome these barriers, we effectively combine knowledge‐based atom–pair potentials and the atomic solvation energy of charge‐independent implicit solvent model in the optimization of binding affinity and specificity. The resulting scoring functions with optimized atomic solvation parameters is named as specificity and affinity with solvation effect (SPA‐SE). The performance of SPA‐SE is evaluated and compared to 20 other scoring functions, as well as SPA. The comparative results show that SPA‐SE outperforms all other scoring functions in binding affinity prediction and “native” pose identification. Our optimization validates that solvation effect is an important regulator to the stability and specificity of protein–ligand binding. The development strategy of SPA‐SE sets an example for other scoring function to account for the solvation effect in biomolecular recognitions. Proteins 2015; 83:1632–1642. © 2015 Wiley Periodicals, Inc.     

A model binding site for testing scoring functions in molecular docking

Prediction of interaction energies between ligands and their receptors remains a major challenge for structure-based inhibitor discovery. Much effort has been devoted to developing scoring schemes that can successfully rank the affinities of a diverse set of possible ligands to a binding site for which the structure is known. To test these scoring functions, well-characterized experimental systems can be very useful. Here, mutation-created binding sites in T4 lysozyme were used to investigate how the quality of atomic charges and solvation energies affects molecular docking. Atomic charges and solvation energies were calculated for 172,118 molecules in the Available Chemicals Directory using a semi-empirical quantum mechanical approach by the program AMSOL. The database was first screened against the apolar cavity site created by the mutation Leu99Ala (L99A). Compared to the electronegativity-based charges that are widely used, the new charges and desolvation energies improved ranking of known apolar ligands, and better distinguished them from more polar isosteres that are not observed to bind. To investigate whether the new charges had predictive value, the non-polar residue Met102, which forms part of the binding site, was changed to the polar residue glutamine. The structure of the resulting Leu99Ala and Met102Gln double mutant of T4 lysozyme (L99A/M102Q) was determined and the docking calculation was repeated for the new site. Seven representative polar molecules that preferentially docked to the polar versus the apolar binding site were tested experimentally. All seven bind to the polar cavity (L99A/M102Q) but do not detectably bind to the apolar cavity (L99A). Five ligand-bound structures of L99A/M102Q were determined by X-ray crystallography. Docking predictions corresponded to the crystallographic results to within 0.4A RMSD. Improved treatment of partial atomic charges and desolvation energies in database docking appears feasible and leads to better distinction of true ligands. Simple model binding sites, such as L99A and its more polar variants, may find broad use in the development and testing of docking algorithms.     

Hydration energy landscape of the active site cavity in cytochrome P450cam

Hydration of protein cavities influences protein stability, dynamics, and function. Protein active sites usually contain water molecules that, upon ligand binding, are either displaced into bulk solvent or retained to mediate protein–ligand interactions. The contribution of water molecules to ligand binding must be accounted for to compute accurate values of binding affinities. This requires estimation of the extent of hydration of the binding site. However, it is often difficult to identify the water molecules involved in the binding process when ligands bind on the surface of a protein. Cytochrome P450cam is, therefore, an ideal model system because its substrate binds in a buried active site, displacing partially disordered solvent, and the protein is well characterized experimentally. We calculated the free energy differences for having five to eight water molecules in the active site cavity of the unliganded enzyme from molecular dynamics simulations by thermodynamic integration employing a three-stage perturbation scheme. The computed free energy differences between the hydration states are small (within 12 kJ mol⁻¹) but distinct. Consistent with the crystallographic determination and studies employing hydrostatic pressure, we calculated that, although ten water molecules could in principle occupy the volume of the active site, occupation by five to six water molecules is thermodynamically most favorable. Proteins 32:381–396, 1998. © 1998 Wiley-Liss, Inc.     

1.3-A resolution structure of human glutathione S-transferase with S-hexyl glutathione bound reveals possible extended ligandin binding site

Cytosolic glutathione S-transferases (GSTs) play a critical role in xenobiotic binding and metabolism, as well as in modulation of oxidative stress. Here, the high-resolution X-ray crystal structures of homodimeric human GSTA1-1 in the apo form and in complex with S-hexyl glutathione (two data sets) are reported at 1.8, 1.5, and 1.3A respectively. At this level of resolution, distinct conformations of the alkyl chain of S-hexyl glutathione are observed, reflecting the nonspecific nature of the hydrophobic substrate binding site (H-site). Also, an extensive network of ordered water, including 75 discrete solvent molecules, traverses the open subunit-subunit interface and connects the glutathione binding sites in each subunit. In the highest-resolution structure, three glycerol moieties lie within this network and directly connect the amino termini of the glutathione molecules. A search for ligand binding sites with the docking program Molecular Operating Environment identified the ordered water network binding site, lined mainly with hydrophobic residues, suggesting an extended ligand binding surface for nonsubstrate ligands, the so-called ligandin site. Finally, detailed comparison of the structures reported here with previously published X-ray structures reveal a possible reaction coordinate for ligand-dependent conformational changes in the active site and the C-terminus.     

Excision of a proposed electron transfer pathway in cytochrome c peroxidase and its replacement by a ligand-binding channel

A previously proposed electron transfer (ET) pathway in the heme enzyme cytochrome c peroxidase has been excised from the structure, leaving an open ligand-binding channel in its place. Earlier studies on cavity mutants of this enzyme have revealed structural plasticity in this region of the molecule. Analysis of these structures has allowed the design of a variant in which the specific section of protein backbone representing a previously proposed ET pathway is accurately extracted from the protein. A crystal structure verified the creation of an open channel that overlays the removed segment, extending from the surface of the protein to the heme at the core of the protein. A number of heterocyclic cations were found to bind to the proximal-channel mutant with affinities that can be rationalized based on the structures. It is proposed that small ligands bind more weakly to the proximal-channel mutant than to the W191G cavity due to an increased off rate of the open channel, whereas larger ligands are able to bind to the channel mutant without inducing large conformational changes. The structure of benzimidazole bound to the proximal-channel mutant shows that the ligand accurately overlays the position of the tryptophan radical center that was removed from the wild-type enzyme and displaces four of the eight ordered solvent molecules seen in the empty cavity. Ligand binding also caused a small rearrangement of the redesigned protein loop, perhaps as a result of improved electrostatic interactions with the ligand. The engineered channel offers the potential for introducing synthetic replacements for the removed structure, such as sensitizer-linked substrates. These installed "molecular wires" could be used to rapidly initiate reactions, trap reactive intermediates, or answer unresolved questions about ET pathways.     

A QM protein–ligand investigation of antipsychotic drugs with the dopamine D2 Receptor (D2R)

The dopamine D2 Receptor (D2R) is a member of the G-Protein-Coupled Receptor family and plays a critical role in neurotransmission activities in the human brain. Dysfunction in dopamine receptor signaling may lead to mental health illnesses such as schizophrenia and Parkinson’s disease. D2R is the target protein of the commonly used antipsychotic drugs such as risperidone, clozapine, aripiprazole, olanzapine, ziprasidone, and quetiapine. Due to their significant side effects and non-selective profiles, the discovery of novel drugs has become a challenge for researchers working in this field. Recently, our group has focused on the interactions of these drug molecules in the active site of the D2R using different in silico approaches. We here compare the performances of different approaches in estimating the drug binding affinities using quantum chemical approaches. Conformations of drug molecules (ligands) at the binding site of the D2R taken from the preliminary docking studies and molecular dynamics simulations were used to generate protein–ligand interaction models. In a first approach, the BSSE-corrected interaction energies of the ligands with the most critical amino acid Asp114 and with the other amino acids closest to ligands in the binding cavity were calculated separately by density functional theory method in implicit water environment at the M06-2X/6-31 g(d,p) level of the theory. In a second approach, ligand binding affinities were calculated by taking into consideration not only the interaction energies but also deformation and desolvation energies of ligands with surrounding amino acid residues, in a radius of 5 Å of the protein-bound ligand. The quantum mechanically obtained results were compared with the experimentally obtained binding affinity values. We concluded that although H-bond interactions of ligands with Asp114 are the most dominant interaction in the binding site, if van der Waals and steric interactions of ligands which have cumulative effect on the ligand binding are not included in the calculations, the interaction energies are overestimated.     

Solvation properties of natural and synthetic ionophores. I. Stoichiometry of complexes with alkali and alkaline earth cations in aprotic organic solvents.

Ion-solvent interactions play a very important role in the studies of stoichiometry, structure, and stability of complexes of cations with natural and synthetic ionophores. These compounds are extremely useful in study of the interaction of neutral salts with macromolecules and the mechanism of cation transport across biological membranes. Knowledge of the ionophore solvation properties enables one to choose a suitable solvent for complexation studies and to obtain detailed information on the solvent effect. We would like to present in this paper a very simple method of estimating the solvation properties of ionophores. We treat the ligand as an assembly of individual noninteracting binding sites. The solvation properties of solvents can be used to represent the solvation sites in natural and synthetic ligands. The solvation properties are represented by the Gutmann donor number (DN) of the model solvent. We can define the solvation ability of a ligand binding site be "donor number of binding site" (DN binding site), which in turn can be represented by the DN of the appropriate model solvent. The average DN of the ligand (DN average) is defined as [xi ni-1 (DN binding site)i]/n, where n is the number of the ligand binding sites. Comparison of the DN average with the DN solvent, together with the knowledge of the composition of the system, characterizes remarkably well the solvation properties of the ligand. This model explains (a) the stoichiometry of many alkali and alkaline earth cation complexes with natural and synthetic ligands in aprotic organic solvents, (b) the transport of alkali and alkaline earth cations across lipid bilayers, and (c) how polypeptides and proteins interact with neutral salts in solutions.     

Molecular dynamics simulation study of the binding of purine bases to the aptamer domain of the guanine sensing riboswitch

Riboswitches are a novel class of genetic control elements that function through the direct interaction of small metabolite molecules with structured RNA elements. The ligand is bound with high specificity and affinity to its RNA target and induces conformational changes of the RNA''s secondary and tertiary structure upon binding. To elucidate the molecular basis of the remarkable ligand selectivity and affinity of one of these riboswitches, extensive all-atom molecular dynamics simulations in explicit solvent (≈1 μs total simulation length) of the aptamer domain of the guanine sensing riboswitch are performed. The conformational dynamics is studied when the system is bound to its cognate ligand guanine as well as bound to the non-cognate ligand adenine and in its free form. The simulations indicate that residue U51 in the aptamer domain functions as a general docking platform for purine bases, whereas the interactions between C74 and the ligand are crucial for ligand selectivity. These findings either suggest a two-step ligand recognition process, including a general purine binding step and a subsequent selection of the cognate ligand, or hint at different initial interactions of cognate and noncognate ligands with residues of the ligand binding pocket. To explore possible pathways of complex dissociation, various nonequilibrium simulations are performed which account for the first steps of ligand unbinding. The results delineate the minimal set of conformational changes needed for ligand release, suggest two possible pathways for the dissociation reaction, and underline the importance of long-range tertiary contacts for locking the ligand in the complex.     

Computational detection of the binding-site hot spot at the remodeled human growth hormone-receptor interface

A hierarchical computational approach is used to identify the engineered binding-site cavity at the remodeled intermolecular interface between the mutants of human growth hormone (hGH) and the extracellular domain of its receptor (hGHbp). Multiple docking simulations are conducted with the remodeled hGH-hGHbp complex for a panel of potent benzimidazole-containing inhibitors that can restore the binding affinity of the wild-type complex, and for a set of known nonactive small molecules that contain different heterocyclic motifs. Structural clustering of ligand-bound conformations and binding free-energy calculations, using the AMBER force field and a continuum solvation model, can rapidly locate and screen numerous ligand-binding modes on the protein surface and detect the binding-site hot spot at the intermolecular interface. Structural orientation of the benzimidazole motif in the binding-site cavity closely mimics the position of the hot spot residue W104 in the crystal structure of the wild-type complex, which is recognized as an important structural requirement for restoring binding affinity. Despite numerous pockets on the protein surface of the mutant hGH-hGHbp complex, the binding-site cavity presents the energetically favorable hot spot for the benzimidazole-containing inhibitors, whereas for a set of nonactive molecules, the lowest energy ligand conformations do not necessarily bind in the engineered cavity. The results reveal a dominant role of the intermolecular van der Waals interactions in providing favorable ligand-protein energetics in the redesigned interface, in agreement with the experimental and computational alanine scanning of the hGH-hGHbp complex.     

Molecular docking study and development of an empirical binding free energy model for phosphodiesterase 4 inhibitors

In the present work, several computational methodologies were combined to develop a model for the prediction of PDE4B inhibitors' activity. The adequacy of applying the ligand docking approach, keeping the enzyme rigid, to the study of a series of PDE4 inhibitors was confirmed by a previous molecular dynamics analysis of the complete enzyme. An exhaustive docking procedure was performed to identify the most probable binding modes of the ligands to the enzyme, including the active site metal ions and the surrounding structural water molecules. The enzyme-inhibitor interaction enthalpies, refined by using the semiempirical molecular orbital approach, were combined with calculated solvation free energies and entropy considerations in an empirical free energy model that enabled the calculation of binding free energies that correlated very well with experimentally derived binding free energies. Our results indicate that both the inclusion of the structural water molecules close to the ions in the binding site and the use of a free energy model with a quadratic dependency on the ligand free energy of solvation are important aspects to be considered for molecular docking investigations involving the PDE4 enzyme family.