Role of Desolvation in Thermodynamics and Kinetics of Ligand Binding to a Kinase

Indazole to 2-Cyanoindole Scaffold Progression for Mycobacterial Lipoamide Dehydrogenase Inhibitors Achieves Extended Target Residence Time and Improved Antibacterial Activity

Tuberculosis remains a leading cause of death from a single infection worldwide. Drug resistance to existing and even new antimycobacterials calls for research into novel targets and unexplored mechanisms of action. Recently we reported on the development of tight-binding inhibitors of Mycobacterium tuberculosis (Mtb) lipoamide dehydrogenase (Lpd), which selectively inhibit the bacterial but not the human enzyme based on a differential modality of inhibitor interaction with these targets. Here we report on the striking improvement in inhibitor residence time on the Mtb enzyme associated with scaffold progression from an indazole to 2-cyanoindole. Cryo-EM of Lpd with the bound 2-cyanoindole inhibitor 19 confirmed displacement of the buried water molecule deep in the binding channel with a cyano group. The ensuing hours-long improvement in on-target residence time is associated with enhanced antibacterial activity in axenic culture and in primary mouse macrophages. Resistance to 2-cyanoindole inhibitors involves mutations within the inhibitor binding site that have little effect on inhibitor affinity but change the modality of inhibitor-target interaction, resulting in fast dissociation from Lpd. These findings underscore that on-target residence time is a major determinant of antibacterial activity and in vivo efficacy.

Molecular Dynamics Unveils Multiple-Site Binding of Inhibitors with Reduced Activity on the Surface of Dihydrofolate Reductase

The sensitivity to protein inhibitors is altered by modifications or protein mutations, as represented by drug resistance. The mode of stable drug binding to the protein pocket has been experimentally clarified. However, the nature of the binding of inhibitors with reduced sensitivity remains unclear at the atomic level. In this study, we analyzed the thermodynamics and kinetics of inhibitor binding to the surface of wild-type and mutant dihydrofolate reductase (DHFR) using molecular dynamics simulations combined with Markov state modeling. A strong inhibitor of methotrexate (MTX) showed a preference for the active site of wild-type DHFR with minimal binding to unrelated (secondary) sites. Deletion of a side-chain fragment in MTX largely destabilized the active site-bound state, with clear evidence of binding to secondary sites. Similarly, the F31V mutation in DHFR diminished the specificity of MTX binding to the active site. These results reveal the presence of multiple-bound states whose stabilities are comparable to or higher than those of the unbound state, suggesting that a reduction in the binding affinity for the active site significantly elevates the fractions of these states. This study presents a theoretical model that more accurately interprets the altered drug sensitivity than the traditional two-state model.

Dental biomaterials redefined: molecular docking and dynamics-driven dental resin composite optimization

BACKGROUND

Dental resin-based composites are widely recognized for their aesthetic appeal and adhesive properties, which make them integral to modern restorative dentistry. Despite their advantages, adhesion and biomechanical performance challenges persist, necessitating innovative strategies for improvement. This study addressed the challenges associated with adhesion and biomechanical properties in dental resin-based composites by employing molecular docking and dynamics simulation.

METHODS

Molecular docking assesses the binding energies and provides valuable insights into the interactions between monomers, fillers, and coupling agents. This investigation prioritizes SiO2 and TRIS, considering their consistent influence. Molecular dynamics simulations, executed with the Forcite module and COMPASS II force field, extend the analysis to the mechanical properties of dental composite complexes. The simulations encompassed energy minimization, controlled NVT and NPT ensemble simulations, and equilibration stages. Notably, the molecular dynamics simulations spanned a duration of 50 ns.

RESULTS

SiO2 and TRIS consistently emerged as influential components, showcasing their versatility in promoting solid interactions. A correlation matrix underscores the significant roles of van der Waals and desolvation energies in determining the overall binding energy. Molecular dynamics simulations provide in-depth insights into the mechanical properties of dental composite complexes. HEMA-SiO2-TRIS excelled in stiffness, BisGMA-SiO2-TRIS prevailed in terms of flexural strength, and EBPADMA-SiO2-TRIS offered a balanced combination of mechanical properties.

CONCLUSION

These findings provide valuable insights into optimizing dental composites tailored to diverse clinical requirements. While EBPADMA-SiO2-TRIS demonstrates distinct strengths, this study emphasizes the need for further research. Future investigations should validate the computational findings experimentally and assess the material's response to dynamic environmental factors.

Elucidation of the structural basis for ligand binding and translocation in conserved insect odorant receptor co-receptors

In numerous insects, the olfactory receptor family forms a unique class of heteromeric cation channels. Recent progress in resolving the odorant receptor structures offers unprecedented opportunities for deciphering their molecular mechanisms of ligand recognition. Unexpectedly, these structures in apo or ligand-bound states did not reveal the pathway taken by the ligands between the extracellular space and the deep internal cavities. By combining molecular modeling with electrophysiological recordings, we identified amino acids involved in the dynamic entry pathway and the binding of VUAA1 to Drosophila melanogaster's odorant receptor co-receptor (Orco). Our results provide evidence for the exact location of the agonist binding site and a detailed and original mechanism of ligand translocation controlled by a network of conserved residues. These findings would explain the particularly high selectivity of Orcos for their ligands.

Computational design of newly engineered DARPins as HER2 receptor inhibitors for breast cancer treatment

Background and purpose

Human epidermal growth factor receptor 2 (HER2) is overexpressed in approximately 25% of breast cancer patients; therefore, its inhibition is a therapeutic target in cancer treatment.

Experimental approach

In this study, two new variants of designed ankyrin repeat proteins (DARPins), designated EG3-1 and EG3-2, were designed to increase their affinity for HER2 receptors. To this end, DARPin G3 was selected as a template, and six-point mutations comprising Q26E, I32V, T49A, L53H, K101R, and G124V were created on its structure. Furthermore, the 3D structures were formed through homology modeling and evaluated using molecular dynamic simulation. Then, both structures were docked to the HER2 receptor using the HADDOCK web tool, followed by 100 ns of molecular dynamics simulation for both DARPins / HER2 complexes.

Findings/Results

The theoretical result confirmed both structures' stability. Molecular dynamics simulations reveal that the applied mutations on DARPin EG3-2 significantly improve the receptor binding affinity of DARPin.

Conclusion and implications

The computationally engineered DARPin EG3-2 in this study could provide a hit compound for the design of promising anticancer agents targeting HER2 receptors.

Strict Interactions of Fifth Letters, Hydrophobic Unnatural Bases, in XenoAptamers with Target Proteins

XenoAptamers are DNA fragments containing additional letters (unnatural bases, UBs) that bind specifically to their target proteins with high affinities (sub-nanomolar KD values). One of the UBs is the highly hydrophobic 7-(2-thienyl)imidazo[4,5-b]pyridine (Ds), which significantly increases XenoAptamers' affinities to targets. Originally, Ds was developed as a third base pair with a complementary UB, 2-nitro-4-propynylpyrrole (Px), for replication, and thus it can be used for aptamer generation by an evolutional engineering method involving PCR amplification. However, it is unclear whether the Ds base is the best component as the hydrophobic fifth-letter ligand for interactions with target proteins. To optimize the ligand structure of the fifth letter, we prepared 13 Ds variants and examined the affinities of XenoAptamers containing these variants to target proteins. The results obtained using four XenoAptamers prepared by the replacement of Ds bases with variants indicated that subtle changes in the chemical structure of Ds significantly affect the XenoAptamer affinities. Among the variants, placing either 4-(2-thienyl)pyrrolo[2,3-b]pyridine (Ys) or 4-(2-thienyl)benzimidazole (Bs) at specific Ds positions in each original XenoAptamer greatly improved their affinities to targets. The Ys and Bs bases are variants derived by replacing only one nitrogen with a carbon in the Ds base. These results demonstrate the strict intramolecular interactions, which are not simple hydrophobic contacts between UBs and targets, thus providing a method to mature XenoAptamers' affinities to targets.

Binding order and apparent binding affinity in the bisubstrate activity of strictosidine synthase

The Rauvolfia serpentina strictosidine synthase (RsSTR) enzyme with a bisubstrate activity is central to monoterpenoid indole alkaloid (MIA) biosynthesis pathways, as it stereoselectively condenses the terpenoid and indole metabolites, secologanin and tryptamine, respectively, into strictosidine. Here, cooperativity was aimed to be deciphered by proxy with help of a non-substrate tryptamine analog (decoy compound) to allow a bisubstrate binding without reaction, facilitating an isothermal titration calorimetry (ITC)-based analysis of the effect of the presence of one substrate on the binding of the other. Tryptamine and tryptamine analog bound to RsSTR with similar binding affinities (Kd). On the contrary, ITC revealed an exothermic titration of secologanin to RsSTR but could not fully quantify it because of weak binding. Interestingly, secologanin bound to RsSTR with an apparent binding affinity (Kd,app) of 212.1 μM in the presence of the decoy compound, as opposed to a lack of binding to RsSTR alone, strongly suggesting a "tryptamine-first" mode of binding. Conversely, binding of tryptamine analog in the presence of secologanin was enhanced >3-fold. Further, molecular dynamics simulation (MDS) analyses revealed the conformational flexibility needed for such cooperativity. Our binding studies complemented with the computational analyses suggested cooperativity in the ordered bisubstrate binding to RsSTR. Therefore, understanding thermodynamics and cooperativity in the binding of substrates or ligands would help to unravel the mechanism of enzyme catalysis and ligand-receptor interactions, and would guide the redesign of enzymes for enhanced properties and the design of inhibitors against enzymes and receptors.Communicated by Ramaswamy H. Sarma.

Ensemble-based molecular docking and spectrofluorometric analysis of interaction between cytotoxin and tumor necrosis factor receptor 1

Cytotoxin (CTX) is a three-finger toxin presents predominantly in cobra venom. The functional site of the toxin is located at its three hydrophobic loop tips. Its actual mechanism of cytotoxicity remains inconclusive as few conflicting hypotheses have been proposed in addition to direct cytolytic effects. The present work investigated the interaction between CTX and death receptor families via ensemble-based molecular docking and fluorescence titration analysis. Multiple sequence alignments of different CTX isoforms obtained a conserved CTX sequence. The three-dimensional structure of the conserved CTX was later determined using homology modelling, and its quality was validated. Ensemble-based molecular docking of CTX was performed with different death receptors, such as Fas-ligand and tumor necrosis factor receptor families. Our results showed that tumor necrosis factor receptor 1 (TNFR1) was the best receptor interacting with CTX attributed to the interaction of all three functional loops and evinced with low HADDOCK, Z-score and RMSD value. The interaction between CTX and TNFR1 was also supported by a concentration-dependent reduction of fluorescence intensity with increasing binding affinity. The possible intermolecular interactions between CTX and TNFR1 were Van der Waals forces and hydrogen bonding. Our findings suggest a possibility that CTX triggers apoptosis cell death through non-covalent interactions with TNFR1.Communicated by Ramaswamy H. Sarma.

Membrane Lipids Are an Integral Part of Transmembrane Allosteric Sites in GPCRs: A Case Study of Cannabinoid CB1 Receptor Bound to a Negative Allosteric Modulator, ORG27569, and Analogs

A growing number of G-protein-coupled receptor (GPCR) structures reveal novel transmembrane lipid-exposed allosteric sites. Ligands must first partition into the surrounding membrane and take lipid paths to these sites. Remarkably, a significant part of the bound ligands appears exposed to the membrane lipids. The experimental structures do not usually account for the surrounding lipids, and their apparent contribution to ligand access and binding is often overlooked and poorly understood. Using classical and enhanced molecular dynamics simulations, we show that membrane lipids are critical in the access and binding of ORG27569 and its analogs at the transmembrane site of cannabinoid CB1 receptor. The observed differences in the binding affinity and cooperativity arise from the functional groups that interact primarily with lipids. Our results demonstrate the significance of incorporating membrane lipids as an integral component of transmembrane sites for accurate characterization, binding-affinity calculations, and lead optimization in drug discovery.

Drug Discovery by Automated Adaptation of Chemical Structure and Identity

Computer-aided drug design offers the potential to dramatically reduce the cost and effort required for drug discovery. While screening-based methods are valuable in the early stages of hit identification, they are frequently succeeded by iterative, hypothesis-driven computations that require recurrent investment of human time and intuition. To increase automation, we introduce a computational method for lead refinement that combines concerted dynamics of the ligand/protein complex via molecular dynamics simulations with integrated Monte Carlo-based changes in the chemical formula of the ligand. This approach, which we refer to as ligand-exchange Monte Carlo molecular dynamics, accounts for solvent- and entropy-based contributions to competitive binding free energies by coupling the energetics of bound and unbound states during the ligand-exchange attempt. Quantitative comparison of relative binding free energies to reference values from free energy perturbation, conducted in vacuum, indicates that ligand-exchange Monte Carlo molecular dynamics simulations sample relevant conformational ensembles and are capable of identifying strongly binding compounds. Additional simulations demonstrate the use of an implicit solvent model. We speculate that the use of chemical graphs in which exchanges are only permitted between ligands with sufficient similarity may enable an automated search to capture some of the benefits provided by human intuition during hypothesis-guided lead refinement.

Designing of potent anti-diabetic molecules by targeting SIK2 using computational approaches

Diabetes mellitus (DM) is one of the major health problems worldwide. WHO have estimated that 439 million people may have DM by the year 2030. Several classes of drugs such as sulfonylureas, meglitinides, thiazolidinediones etc. are available to manage this disease, however, there is no cure for this disease. Salt inducible kinase 2 (SIK2) is expressed several folds in adipose tissue than in normal tissues and thus SIK2 is one of the attractive targets for DM treatment. SIK2 inhibition improves glucose homeostasis. Several analogues have been reported and experimentally proven against SIK for DM treatment. But, identifying potential SIK2 inhibitors with improved efficacy and good pharmacokinetic profiles will be helpful for the effective treatment of DM. The objective of the present study is to identify selective SIK2 inhibitors with good pharmacokinetic profiles. Due to the unavailability of SIK2 structure, the modeled structure of SIK2 will be an important to understand the atomic level of SIK2 inhibitors in the binding site pocket. In this study, different molecular modeling studies such as Homology Modeling, Molecular Docking, Pharmacophore-based virtual screening, MD simulations, Density Functional Theory calculations and WaterMap analysis were performed to identify potential SIK2 inhibitors. Five molecules from different databases such as Binding_4067, TosLab_837067, NCI_349155, Life chemicals_ F2565-0113, Enamine_7623111186 molecules were identified as possible SIK2 inhibitors.

Solvent's Role in Cavity-Ligand Recognition Would Depend on the Mode of Ligand Diffusion

Solvent is known to play crucial roles in dictating the thermodynamics and kinetics of the biomolecular recognition process. Here, we show that the extent of significance of water in modulating the ligand recognition process is critically contingent on the ligand diffusion and on the constraints introduced on it. Toward the end, we use a well-known prototypical system of spherical ligand diffusing freely toward a hydrophobic concave cavity in explicit water. We analyze a large series of adaptively sampled unbiased molecular dynamics simulation trajectories within the framework of time-structured independent component analysis (TICA). Our quantitative investigations reveal that water would play a significant role in the ligand recognition process, provided that the ligand is constricted to diffuse along a centro-symmetric fashion. On the contrary, water's contribution in the ligand recognition process would diminish to a negligible value if the ligand freely diffuses toward the pocket. A Markov state model (MSM) constructed using the simulated trajectories identifies a set of transiently populated metastable states comprising partially ligand-unbound macro states, alongside ligand-bound and ligand-unbound pose and gives rise to multiple transition paths of ligand in its way to the hydrophobic cavity. Lifting the restriction on ligand movement changes its binding pathway, time scales, and the extent of the role of solvent in modulating the recognition process.

Structural and Biophysical Analysis of the Phytochelatin-Synthase-Like Enzyme from Nostoc sp. Shows That Its Protease Activity is Sensitive to the Redox State of the Substrate

Phytochelatins (PCs) are nonribosomal thiol-rich oligopeptides synthetized from glutathione (GSH) in a γ-glutamylcysteinyl transpeptidation reaction catalyzed by PC synthases (PCSs). Ubiquitous in plant and present in some invertebrates, PCSs are involved in metal detoxification and homeostasis. The PCS-like enzyme from the cyanobacterium Nostoc sp. (NsPCS) is considered to be an evolutionary precursor enzyme of genuine PCSs because it shows sufficient sequence similarity for homology to the catalytic domain of the eukaryotic PCSs and shares the peptidase activity consisting in the deglycination of GSH. In this work, we investigate the catalytic mechanism of NsPCS by combining structural, spectroscopic, thermodynamic, and theoretical techniques. We report several crystal structures of NsPCS capturing different states of the catalyzed chemical reaction: (i) the structure of the wild-type enzyme (wt-NsPCS); (ii) the high-resolution structure of the γ-glutamyl-cysteine acyl-enzyme intermediate (acyl-NsPCS); and (iii) the structure of an inactive variant of NsPCS, with the catalytic cysteine mutated into serine (C70S-NsPCS). We characterize NsPCS as a relatively slow enzyme whose activity is sensitive to the redox state of the substrate. Namely, NsPCS is active with reduced glutathione (GSH), but is inhibited by oxidized glutathione (GSSG) because the cleavage product is not released from the enzyme. Our biophysical analysis led us to suggest that the biological function of NsPCS is being a part of a redox sensing system. In addition, we propose a mechanism how PCS-like enzymes may have evolved toward genuine PCS enzymes.

WaterMap and Molecular Dynamic Simulation-Guided Discovery of Potential PAK1 Inhibitors Using Repurposing Approaches

p21-Activated kinase 1 (PAK1) is positioned at the nexus of several oncogenic signaling pathways. Currently, there are no approved inhibitors for disabling the transfer of phosphate in the active site directly, as they are limited by lower affinity, and poor kinase selectivity. In this work, a repurposing study utilizing FDA-approved drugs from the DrugBank database was pursued with an initial selection of 27 molecules out of ∼2162 drug molecules, based on their docking energies and molecular interaction patterns. From the molecules that were considered for WaterMap analysis, seven molecules, namely, Mitoxantrone, Labetalol, Acalabrutinib, Sacubitril, Flubendazole, Trazodone, and Niraparib, ascertained the ability to overlap with high-energy hydration sites. Considering many other displaced unfavorable water molecules, only Acalabrutinib, Flubendazole, and Trazodone molecules highlighted their prominence in terms of binding affinity gains through ΔΔG that ranges between 6.44 and 2.59 kcal/mol. Even if Mitoxantrone exhibited the highest docking score and greater interaction strength, it did not comply with the WaterMap and molecular dynamics simulation results. Moreover, detailed MD simulation trajectory analyses suggested that the drug molecules Flubendazole, Niraparib, and Acalabrutinib were highly stable, observed from their RMSD values and consistent interaction pattern with Glu315, Glu345, Leu347, and Asp407 including the hydrophobic interactions maintained in the three replicates. However, the drug molecule Trazodone displayed a loss of crucial interaction with Leu347, which was essential to inhibit the kinase activity of PAK1. The molecular orbital and electrostatic potential analyses elucidated the reactivity and strong complementarity potentials of the drug molecules in the binding pocket of PAK1. Therefore, the CADD-based reposition efforts, reported in this work, helped in the successful identification of new PAK1 inhibitors that requires further investigation by in vitro analysis.

Contact Map Fingerprints of Protein-Ligand Unbinding Trajectories Reveal Mechanisms Determining Residence Times Computed from Scaled Molecular Dynamics

The binding kinetic properties of potential drugs may significantly influence their subsequent clinical efficacy. Predictions of these properties based on computer simulations provide a useful alternative to their expensive and time-consuming experimental counterparts, even at an early drug discovery stage. Herein, we perform scaled molecular dynamics (ScaledMD) simulations on a set of 27 ligands of HSP90 belonging to more than seven chemical series to estimate their relative residence times. We introduce two new techniques for the analysis and the classification of the simulated unbinding trajectories. The first technique, which helps in estimating the limits of the free energy well around the bound state, and the second one, based on a new contact map fingerprint, allow the description and the comparison of the paths that lead to unbinding. Using these analyses, we find that ScaledMD's relative residence time generally enables the identification of the slowest unbinders. We propose an explanation for the underestimation of the residence times of a subset of compounds, and we investigate how the biasing in ScaledMD can affect the mechanistic insights that can be gained from the simulations.

Reduced efficacy of a Src kinase inhibitor in crowded protein solution

The inside of a cell is highly crowded with proteins and other biomolecules. How proteins express their specific functions together with many off-target proteins in crowded cellular environments is largely unknown. Here, we investigate an inhibitor binding with c-Src kinase using atomistic molecular dynamics (MD) simulations in dilute as well as crowded protein solution. The populations of the inhibitor, 4-amino-5-(4-methylphenyl)-7-(t-butyl)pyrazolo[3,4-d]pyrimidine (PP1), in bulk solution and on the surface of c-Src kinase are reduced as the concentration of crowder bovine serum albumins (BSAs) increases. This observation is consistent with the reduced PP1 inhibitor efficacy in experimental c-Src kinase assays in addition with BSAs. The crowded environment changes the major binding pathway of PP1 toward c-Src kinase compared to that in dilute solution. This change is explained based on the population shift mechanism of local conformations near the inhibitor binding site in c-Src kinase.

Exploring ligand binding pathways on proteins using hypersound-accelerated molecular dynamics

Capturing the dynamic processes of biomolecular systems in atomistic detail remains difficult despite recent experimental advances. Although molecular dynamics (MD) techniques enable atomic-level observations, simulations of “slow” biomolecular processes (with timescales longer than submilliseconds) are challenging because of current computer speed limitations. Therefore, we developed a method to accelerate MD simulations by high-frequency ultrasound perturbation. The binding events between the protein CDK2 and its small-molecule inhibitors were nearly undetectable in 100-ns conventional MD, but the method successfully accelerated their slow binding rates by up to 10–20 times. Hypersound-accelerated MD simulations revealed a variety of microscopic kinetic features of the inhibitors on the protein surface, such as the existence of different binding pathways to the active site. Moreover, the simulations allowed the estimation of the corresponding kinetic parameters and exploring other druggable pockets. This method can thus provide deeper insight into the microscopic interactions controlling biomolecular processes.

Molecular dynamics (MD) techniques enable atomic-level observations, but simulations of “slow” biomolecular processes are challenging because of current computer speed limitations. Here, the authors develop a method to accelerate MD simulations by high-frequency ultrasound perturbation and reveal binding events between the protein CDK2 and its small-molecule inhibitors.

An Appraisal of Computer Simulation Approaches in Elucidating Biomolecular Recognition Pathways

Computer simulation approaches in biomolecular recognition processes have come a long way. In this Perspective, we highlight a series of recent success stories in which computer simulations have played a remarkable role in elucidating the atomic resolution mechanism of kinetic processes of protein-ligand binding in a quantitative fashion. In particular, we show that a robust combination of unbiased simulation, harnessed by a high-fidelity computing environment, and Markov state modeling approaches has been instrumental in revealing novel protein-ligand recognition pathways in multiple systems. We also elucidate the role of recent developments in enhanced sampling approaches in providing the much-needed impetus in accelerating simulation of the ligand recognition process. We identify multiple key issues, including force fields and the sampling bottleneck, which are currently preventing the field from achieving quantitative reconstruction of experimental measurements. Finally, we suggest a possible way forward via adoption of multiscale approaches and coarse-grained simulations as next steps toward efficient elucidation of ligand binding kinetics.

Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation

Computational studies play an increasingly important role in chemistry and biophysics, mainly thanks to improvements in hardware and algorithms. In drug discovery and development, computational studies can reduce the costs and risks of bringing a new medicine to market. Computational simulations are mainly used to optimize promising new compounds by estimating their binding affinity to proteins. This is challenging due to the complexity of the simulated system. To assess the present and future value of simulation for drug discovery, we review key applications of advanced methods for sampling complex free-energy landscapes at near nonergodicity conditions and for estimating the rate coefficients of very slow processes of pharmacological interest. We outline the statistical mechanics and computational background behind this research, including methods such as steered molecular dynamics and metadynamics. We review recent applications to pharmacology and drug discovery and discuss possible guidelines for the practitioner. Recent trends in machine learning are also briefly discussed. Thanks to the rapid development of methods for characterizing and quantifying rare events, simulation's role in drug discovery is likely to expand, making it a valuable complement to experimental and clinical approaches.

Capturing Protein-Ligand Recognition Pathways in Coarse-Grained Simulation

Protein-ligand recognition is dynamic and complex. A key approach in deciphering the mechanism underlying the recognition process is to capture the kinetic process of the ligand in its act of binding to its designated protein cavity. Toward this end, ultralong all-atom molecular dynamics simulation has recently emerged as a popular method of choice because of its ability to record these events at high spatial and temporal resolution. However, success via this route comes at an exorbitant computational cost. Herein, we demonstrate that coarse-grained models of the protein, when systematically optimized to maintain its tertiary fold, can capture the complete process of spontaneous protein-ligand binding from bulk media to the cavity at crystallographic precision and within wall clock time that is orders of magnitude shorter than that of all-atom simulations. The exhaustive sampling of ligand exploration in protein and solvent, harnessed by coarse-grained simulation, leads to elucidation of new ligand recognition pathways and discovery of non-native binding poses.

Comparative Study of Water-Mediated Interactions between Hydrophilic and Hydrophobic Nanoscale Surfaces

Self-assembly processes in aqueous solutions, such as protein folding and nanoparticle aggregation, are driven by water-mediated interactions (WMIs). The most common of such interactions are the attractive forces between hydrophobic units. While numerous studies have focused on hydrophobic interactions, WMIs between hydrophilic moieties and pairs of hydrophilic-hydrophobic surfaces have received much less attention. In this work, we perform molecular dynamics simulations to study the WMI between nanoscale (i) hydrophobic-hydrophobic, (ii) hydrophilic-hydrophilic, and (iii) hydrophilic-hydrophobic pairs of (hydroxylated/nonhydroxylated) graphene-based surfaces. We find that in all cases, the potential of mean force (PMF) between the plates exhibits oscillations as a function of the plate separations r, up to r ≈ 1-1.5 nm. The local minima of the PMF, which define the stable/metastable states of the system, correspond to plates' separations at which water molecules arrange into n = 0, 1, 2, ... layers between the plates. In case (i), the stable state of the system corresponds to the plates in contact with one another. Instead, in cases (ii) and (iii), water is never removed between the plates. The free-energy barriers separating the stable/metastable states of the system vary with the hydrophilicity/hydrophobicity of the interacting plates. However, the effective forces between the plates are comparable in magnitude. This strongly suggests that hydrophilic-hydrophilic and hydrophilic-hydrophobic interactions can play a relevant role in self-assembly processes in aqueous solutions, alike hydrophobic interactions. Interestingly, we find that the WMIs between hydrophilic-hydrophilic and hydrophilic-hydrophobic plates are similar, suggesting that only one hydrophilic surface is sufficient to induce hydrophilic-like WMI. We also briefly discuss the role of surface polarity on the WMI. In particular, we show that depending on the surface polarity, WMI can exhibit mixed features characteristic of hydrophobic and hydrophilic interactions. Our results suggest that the forces between hydrophobic, hydrophilic, and hydrophobic/hydrophilic surfaces are all relevant in driving a self-assembly system toward its final state, but it is the hydrophobic interaction that provides stability to such a final state.

An investigation of structural stability in protein-ligand complexes reveals the balance between order and disorder

The predominant view in structure-based drug design is that small-molecule ligands, once bound to their target structures, display a well-defined binding mode. However, structural stability (robustness) is not necessary for thermodynamic stability (binding affinity). In fact, it entails an entropic penalty that counters complex formation. Surprisingly, little is known about the causes, consequences and real degree of robustness of protein-ligand complexes. Since hydrogen bonds have been described as essential for structural stability, here we investigate 469 such interactions across two diverse structure sets, comprising of 79 drug-like and 27 fragment ligands, respectively. Completely constricted protein-ligand complexes are rare and may fulfill a functional role. Most complexes balance order and disorder by combining a single anchoring point with looser regions. 25% do not contain any robust hydrogen bond and may form loose structures. Structural stability analysis reveals a hidden layer of complexity in protein-ligand complexes that should be considered in ligand design.

Improving the Efficiency of Ligand-Binding Protein Design with Molecular Dynamics Simulations

Custom-designed ligand-binding proteins represent a promising class of macromolecules with exciting applications toward the design of new enzymes or the engineering of antibodies and small-molecule recruited proteins for therapeutic interventions. However, several challenges remain in designing a protein sequence such that the binding site organization results in high affinity interaction with a bound ligand. Here, we study the dynamics of explicitly solvated designed proteins through all-atom molecular dynamics (MD) simulations to gain insight into the causes that lead to the low affinity or instability of most of these designs, despite the prediction of their success by the computational design methodology. Simulations ranging from 500 to 1000 ns per replicate were conducted on 37 designed protein variants encompassing two distinct folds and a range of ligand affinities, resulting in more than 180 μs of combined sampling. The simulations provide retrospective insights into the properties affecting ligand affinity that can prove useful in guiding further steps of design optimization. Features indicate that entropic components are particularly important for affinity, which are not easily incorporated in the empirical models often used in design protocols. Additionally, we demonstrate that the application of machine learning approaches built upon the output from the simulations can help discriminate between successful and failed binders, such that MD could act as a screening step in protein design, resulting in a more efficient process.

Encounter complexes and hidden poses of kinase-inhibitor binding on the free-energy landscape

Modern drug discovery increasingly focuses on the drug-target binding kinetics which depend on drug (un)binding pathways. The conventional molecular dynamics simulation can observe only a few binding events even using the fastest supercomputer. Here, we develop 2D gREST/REUS simulation with enhanced flexibility of the ligand and the protein binding site. Simulation (43 μs in total) applied to an inhibitor binding to c-Src kinase covers 100 binding and unbinding events. On the statistically converged free-energy landscapes, we succeed in predicting the X-ray binding structure, including water positions. Furthermore, we characterize hidden semibound poses and transient encounter complexes on the free-energy landscapes. Regulatory residues distant from the catalytic core are responsible for the initial inhibitor uptake and regulation of subsequent bindings, which was unresolved by experiments. Stabilizing/blocking of either the semibound poses or the encounter complexes can be an effective strategy to optimize drug-target residence time.

Solvents to Fragments to Drugs: MD Applications in Drug Design

Simulations of molecular dynamics (MD) are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: Binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals solvent structures and preferential interaction sites (hot spots) on the protein surface. The information provided by water and its cosolvents can be used very effectively to understand protein ligand recognition and to improve the predictive capability of well-established methods such as molecular docking. The application of MD simulations to the study of the association of proteins with drug-like compounds is currently only possible for specific cases, as it remains computationally very expensive and labor intensive. MDmix simulations on the other hand, can be used systematically to address some of the common tasks in SBDD. With the advent of new tools and faster computers we expect to see an increase in the application of mixed solvent MD simulations to a plethora of protein targets to identify new drug candidates.

Water access and ligand dissociation at the binding site of proteins

Although water is undoubtedly an essential mediator of protein-ligand interactions, whether or not such water molecules are critical for the progress of ligand dissociation remains unclear. To gain a more complete understanding, molecular dynamics simulations are performed with two molecular systems, rigid model binding sites and trypsin-benzamidine. Free-energy landscapes are calculated with a suitably chosen solvent coordinate, which well describes water access to the ligand binding site. The results of free energy provided clear description of water-ligand exchange process, where two different mechanisms appear depending on whether the binding site is buried or not. As the site is more buried, water access is more difficult. When water does not access the site, ligand dissociation produces a large energy barrier, i.e., slow dissociation kinetics. This indicates that control of ligand dissociation kinetics becomes possible with burying the binding site. However, the results also showed that appropriate burying is important because burying reduces not only water access but also ligand binding. The role of the protein structural change is also discussed; it likely plays a similar role to water access because during ligand dissociation, it can make new coordination with the ligand binding site like water. These results contribute to the future pharmaceutical drug design and will be useful for fundamental exploration of various molecular events.

Role of Molecular Interactions and Protein Rearrangement in the Dissociation Kinetics of p38α MAP Kinase Type-I/II/III Inhibitors

Understanding the governing factors of fast or slow inhibitor binding/unbinding assists in developing drugs with preferred kinetic properties. For inhibitors with the same binding affinity targeting different binding sites of the same protein, the kinetic behavior can profoundly differ. In this study, we investigated unbinding kinetics and mechanisms of fast (type-I) and slow (type-II/III) binders of p38α mitogen-activated protein kinase, where the crystal structures showed that type-I and type-II/III inhibitors bind to pockets with different conformations of the Asp-Phe-Gly (DFG) motif. The work used methods that combine conventional molecular dynamics (MD), accelerated molecular dynamics (AMD) simulations, and the newly developed pathway search guided by internal motions (PSIM) method to find dissociation pathways. The study focuses on revealing key interactions and molecular rearrangements that hinder ligand dissociation by using umbrella sampling and post-MD processing to examine changes in free energy during ligand unbinding. As anticipated, the initial dissociation steps all require breaking interactions that appeared in crystal structures of the bound complexes. Interestingly, for type-I inhibitors such as SB2, p38α keeps barrier-free conformational fluctuation in the ligand-bound complex and during ligand dissociation. In contrast, with a type-II/III inhibitor such as BIRB796, with the rearrangements of p38α in its bound state, ligand unbinding features energetically unfavorable protein-ligand concerted movement. Our results also show that the type-II/III inhibitors preferred dissociation pathways through the allosteric channel, which is consistent with an existing publication. The study suggests that the level of required protein rearrangement is one major determining factor of drug binding kinetics in p38α systems, providing useful information for development of inhibitors.

Aromatic Rings Commonly Used in Medicinal Chemistry: Force Fields Comparison and Interactions With Water Toward the Design of New Chemical Entities

The identification of lead compounds usually includes a step of chemical diversity generation. Its rationale may be supported by both qualitative (SAR) and quantitative (QSAR) approaches, offering models of the putative ligand-receptor interactions. In both scenarios, our understanding of which interactions functional groups can perform is mostly based on their chemical nature (such as electronegativity, volume, melting point, lipophilicity etc.) instead of their dynamics in aqueous, biological solutions (solvent accessibility, lifetime of hydrogen bonds, solvent structure etc.). As a consequence, it is challenging to predict from 2D structures which functional groups will be able to perform interactions with the target receptor, at which intensity and relative abundance in the biological environment, all of which will contribute to ligand potency and intrinsic activity. With this in mind, the aim of this work is to assess properties of aromatic rings, commonly used for drug design, in aqueous solution through molecular dynamics simulations in order to characterize their chemical features and infer their impact in complexation dynamics. For this, common aromatic and heteroaromatic rings were selected and received new atomic charge set based on the direction and module of the dipole moment from MP2/6-31G^* calculations, while other topological terms were taken from GROMOS53A6 force field. Afterwards, liquid physicochemical properties were simulated for a calibration set composed by nearly 40 molecules and compared to their respective experimental data, in order to validate each topology. Based on the reliance of the employed strategy, we expanded the dataset to more than 100 aromatic rings. Properties in aqueous solution such as solvent accessible surface area, H-bonds availability, H-bonds residence time, and water structure around heteroatoms were calculated for each ring, creating a database of potential interactions, shedding light on features of drugs in biological solutions, on the structural basis for bioisosterism and on the enthalpic/entropic costs for ligand-receptor complexation dynamics.

Quantitative metrics for drug-target ligandability

Ligandability is a prerequisite for druggability and is a much easier concept to understand, model and predict because it does not depend on the complex pharmacodynamic and pharmacokinetic mechanisms in the human body. In this review, we consider a metric for quantifying ligandability from experimental data. We discuss ligandability in terms of the balance between effort and reward. The metric is evaluated for a standard set of well-studied drug targets - some traditionally considered to be ligandable and some regarded as difficult. We suggest that this metric should be used to systematically improve computational predictions of ligandability, which can then be applied to novel drug targets to predict their tractability.

The Role of Interfacial Water in Protein-Ligand Binding: Insights from the Indirect Solvent Mediated Potential of Mean Force

Classical density functional theory (DFT) can be used to relate the thermodynamic properties of solutions to the indirect solvent mediated part of the solute-solvent potential of mean force (PMF). Standard, but powerful numerical methods can be used to estimate the solute-solvent PMF from which the indirect part can be extracted. In this work we show how knowledge of the direct and indirect parts of the solute-solvent PMF for water at the interface of a protein receptor can be used to gain insights about how to design tighter binding ligands. As we show, the indirect part of the solute-solvent PMF is equal to the sum of the 1-body (energy + entropy) terms in the inhomogeneous solvation theory (IST) expansion of the solvation free energy. To illustrate the effect of displacing interfacial water molecules with particular direct/indirect PMF signatures on the binding of ligands, we carry out simulations of protein binding with several pairs of congeneric ligands. We show that interfacial water locations that contribute favorably or unfavorably at the 1-body level (energy + entropy) to the solvation free energy of the solute can be targeted as part of the ligand design process. Water locations where the indirect PMF is larger in magnitude provide better targets for displacement when adding a functional group to a ligand core.

Binding Thermodynamics and Kinetics Calculations Using Chemical Host and Guest: A Comprehensive Picture of Molecular Recognition

Understanding the fine balance between changes of entropy and enthalpy and the competition between a guest and water molecules in molecular binding is crucial in fundamental studies and practical applications. Experiments provide measurements. However, illustrating the binding/unbinding processes gives a complete picture of molecular recognition not directly available from experiments, and computational methods bridge the gaps. Here, we investigated guest association/dissociation with β-cyclodextrin (β-CD) by using microsecond-time-scale molecular dynamics (MD) simulations, postanalysis and numerical calculations. We computed association and dissociation rate constants, enthalpy, and solvent and solute entropy of binding. All the computed values of kon, koff, ΔH, ΔS, and ΔG using GAFF-CD and q4MD-CD force fields for β-CD could be compared with experimental data directly and agreed reasonably with experiment findings. In addition, our study further interprets experiments. Both force fields resulted in similar computed ΔG from independently computed kinetics rates, ΔG = -RT ln(kon·C0/koff), and thermodynamics properties, ΔG = ΔH - TΔS. The water entropy calculations show that the entropy gain of desolvating water molecules are a major driving force, and both force fields have the same strength of nonpolar attractions between solutes and β-CD as well. Water molecules play a crucial role in guest binding to β-CD. However, collective water/β-CD motions could contribute to different computed kon and ΔH values by different force fields, mainly because the parameters of β-CD provide different motions of β-CD, hydrogen-bond networks of water molecules in the cavity of free β-CD, and strength of desolvation penalty. As a result, q4MD-CD suggests that guest binding is mostly driven by enthalpy, while GAFF-CD shows that gaining entropy is the major driving force of binding. The study deepens our understanding of ligand-receptor recognition and suggests strategies for force field parametrization for accurately modeling molecular systems.

How and when does an anticancer drug leave its binding site?

Obtaining atomistic resolution of drug unbinding from a protein is a much sought-after experimental and computational challenge. We report the unbinding dynamics of the anticancer drug dasatinib from c-Src kinase in full atomistic resolution using enhanced sampling molecular dynamics simulations. We obtain multiple unbinding trajectories and determine a residence time in agreement with experiments. We observe coupled protein-water movement through multiple metastable intermediates. The water molecules form a hydrogen bond bridge, elongating a specific, evolutionarily preserved salt bridge and enabling conformation changes essential to ligand unbinding. This water insertion in the salt bridge acts as a molecular switch that controls unbinding. Our findings provide a mechanistic rationale for why it might be difficult to engineer drugs targeting certain specific c-Src kinase conformations to have longer residence times.

Kinetics for Drug Discovery: an industry-driven effort to target drug residence time

A considerable number of approved drugs show non-equilibrium binding characteristics, emphasizing the potential role of drug residence times for in vivo efficacy. Therefore, a detailed understanding of the kinetics of association and dissociation of a target-ligand complex might provide crucial insight into the molecular mechanism-of-action of a compound. This deeper understanding will help to improve decision making in drug discovery, thus leading to a better selection of interesting compounds to be profiled further. In this review, we highlight the contributions of the Kinetics for Drug Discovery (K4DD) Consortium, which targets major open questions related to binding kinetics in an industry-driven public-private partnership.

Unbinding Kinetics of a p38 MAP Kinase Type II Inhibitor from Metadynamics Simulations

Understanding the structural and energetic requisites of ligand binding toward its molecular target is of paramount relevance in drug design. In recent years, atomistic free energy calculations have proven to be a valid tool to complement experiments in characterizing the thermodynamic and kinetic properties of protein/ligand interaction. Here, we investigate, through a recently developed metadynamics-based protocol, the unbinding mechanism of an inhibitor of the pharmacologically relevant target p38 MAP kinase. We provide a thorough description of the ligand unbinding pathway identifying the most stable binding mode and other thermodynamically relevant poses. From our simulations, we estimated the unbinding rate as k_off = 0.020 ± 0.011 s^-1. This is in good agreement with the experimental value (k_off = 0.14 s^-1). Next, we developed a Markov state model that allowed identifying the rate-limiting step of the ligand unbinding process. Our calculations further show that the solvation of the ligand and that of the active site play crucial roles in the unbinding process. This study paves the way to investigations on the unbinding dynamics of more complex p38 inhibitors and other pharmacologically relevant inhibitors in general, demonstrating that metadynamics can be a powerful tool in designing new drugs with engineered binding/unbinding kinetics.

Effect of material flexibility on the thermodynamics and kinetics of hydrophobically induced evaporation of water

The evaporation of water induced by confinement between hydrophobic surfaces has received much attention due to its suggested functional role in numerous biophysical phenomena and its importance as a general mechanism of hydrophobic self-assembly. Although much progress has been made in understanding the basic physics of hydrophobically induced evaporation, a comprehensive understanding of the substrate material features (e.g., geometry, chemistry, and mechanical properties) that promote or inhibit such transitions remains lacking. In particular, comparatively little research has explored the relationship between water's phase behavior in hydrophobic confinement and the mechanical properties of the confining material. Here, we report the results of extensive molecular simulations characterizing the rates, free energy barriers, and mechanism of water evaporation when confined between model hydrophobic materials with tunable flexibility. A single-order-of-magnitude reduction in the material's modulus results in up to a nine-orders-of-magnitude increase in the evaporation rate, with the corresponding characteristic time decreasing from tens of seconds to tens of nanoseconds. Such a modulus reduction results in a 24-orders-of-magnitude decrease in the reverse rate of condensation, with time scales increasing from nanoseconds to tens of millions of years. Free energy calculations provide the barriers to evaporation and confirm our previous theoretical predictions that making the material more flexible stabilizes the confined vapor with respect to liquid. The mechanism of evaporation involves surface bubbles growing/coalescing to form a subcritical gap-spanning tube, which then must grow to cross the barrier.

Mechanism of the Association Pathways for a Pair of Fast and Slow Binding Ligands of HIV-1 Protease

Equilibrium constants, together with kinetic rate constants of binding, are key factors in the efficacy and safety of drug compounds, informing drug design. However, the association pathways of protein-ligand binding, which contribute to their kinetic behaviors, are little understood. In this work, we used unbiased all-atom molecular dynamics (MD) simulations with an explicit solvent model to study the association processes of protein-ligand binding. Using the HIV protease (HIVp)-xk263 and HIVp-ritonavir protein-ligand systems as cases, we observed that ligand association is a multistep process involving diffusion, localization, and conformational rearrangements of the protein, ligand, and water molecules. Moreover, these two ligands preferred different routes of binding, which reflect two well-known binding mechanisms: induced-fit and conformation selection models. Our study shows that xk263 has a stronger capacity for desolvating surrounding water molecules, thereby inducing a semiopen conformation of the HIVp flaps (induced-fit model). In contrast, the slow dehydration characteristic of ritonavir allows for gradual association with the binding pocket of HIVp when the protein's flap conformation is fully open (conformation selection model). By studying the mechanism of ligand association and understanding the role of solvent molecules during the binding event, we can obtain a different perspective on the mechanism of macromolecule recognition, providing insights into drug discovery.

How wet should be the reaction coordinate for ligand unbinding?

We use a recently proposed method called Spectral Gap Optimization of Order Parameters (SGOOP) [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)], to determine an optimal 1-dimensional reaction coordinate (RC) for the unbinding of a bucky-ball from a pocket in explicit water. This RC is estimated as a linear combination of the multiple available order parameters that collectively can be used to distinguish the various stable states relevant for unbinding. We pay special attention to determining and quantifying the degree to which water molecules should be included in the RC. Using SGOOP with under-sampled biased simulations, we predict that water plays a distinct role in the reaction coordinate for unbinding in the case when the ligand is sterically constrained to move along an axis of symmetry. This prediction is validated through extensive calculations of the unbinding times through metadynamics and by comparison through detailed balance with unbiased molecular dynamics estimate of the binding time. However when the steric constraint is removed, we find that the role of water in the reaction coordinate diminishes. Here instead SGOOP identifies a good one-dimensional RC involving various motional degrees of freedom.

Elucidating the Origin of Long Residence Time Binding for Inhibitors of the Metalloprotease Thermolysin

Kinetic parameters of protein-ligand interactions are progressively acknowledged as valuable information for rational drug discovery. However, a targeted optimization of binding kinetics is not easy to achieve, and further systematic studies are necessary to increase the understanding about molecular mechanisms involved. We determined association and dissociation rate constants for 17 inhibitors of the metalloprotease thermolysin by surface plasmon resonance spectroscopy and correlated kinetic data with high-resolution crystal structures in complex with the protein. From the structure-kinetics relationship, we conclude that the strength of interaction with Asn112 correlates with the rate-limiting step of dissociation. This residue is located at the beginning of a β-strand motif that lines the binding cleft and is commonly believed to align a substrate for catalysis. A reduced mobility of the Asn112 side chain owing to an enhanced engagement in charge-assisted hydrogen bonds prevents the conformational adjustment associated with ligand release and transformation of the enzyme to its open state. This hypothesis is supported by kinetic data of ZF^PLA, a known pseudopeptidic inhibitor of thermolysin, which blocks the conformational transition of Asn112. Interference with this retrograde induced-fit mechanism results in variation of the residence time of thermolysin inhibitors by a factor of 74 000. The high conservation of this structural motif within the M4 and M13 metalloprotease families underpins the importance of this feature and has significant implications for drug discovery.

How Oliceridine (TRV-130) Binds and Stabilizes a μ-Opioid Receptor Conformational State That Selectively Triggers G Protein Signaling Pathways

Substantial attention has recently been devoted to G protein-biased agonism of the μ-opioid receptor (MOR) as an ideal new mechanism for the design of analgesics devoid of serious side effects. However, designing opioids with appropriate efficacy and bias is challenging because it requires an understanding of the ligand binding process and of the allosteric modulation of the receptor. Here, we investigated these phenomena for TRV-130, a G protein-biased MOR small-molecule agonist that has been shown to exert analgesia with less respiratory depression and constipation than morphine and that is currently being evaluated in human clinical trials for acute pain management. Specifically, we carried out multimicrosecond, all-atom molecular dynamics (MD) simulations of the binding of this ligand to the activated MOR crystal structure. Analysis of >50 μs of these MD simulations provides insights into the energetically preferred binding pathway of TRV-130 and its stable pose at the orthosteric binding site of MOR. Information transfer from the TRV-130 binding pocket to the intracellular region of the receptor was also analyzed, and was compared to a similar analysis carried out on the receptor bound to the classical unbiased agonist morphine. Taken together, these studies lead to a series of testable hypotheses of ligand-receptor interactions that are expected to inform the structure-based design of improved opioid analgesics.

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

The effect of desolvation on the binding of inhibitors to HIV-1 protease and cyclin-dependent kinases: Causes of resistance

Studies of the cyclin-dependent kinase inhibitors and HIV-1 protease inhibitors have confirmed that ligand-protein binding is dependent on desolvation effects. It has been found that a four parameter linear model incorporating desolvation energy, lipophilicity, dipole moment and molecular volume of the ligands is a good model to describe the binding between ligands and kinases or proteases. The resistance shown by MDR proteases to the anti-viral drugs is multi-faceted involving varying changes in desolvation, lipophilicity and dipole moment interaction compared to the non-resistant protease. Desolvation has been shown to be the dominant factor influencing the effect of inhibitors against the cyclin-dependent kinases, but lipophilicity and dipole moment are also significant factors. The model can differentiate between the inhibitory activity of CDK2/cycE, CDK1/cycB and CDK4/cycD enzymes.

Beyond Membrane Protein Structure: Drug Discovery, Dynamics and Difficulties

Most of the previous content of this book has focused on obtaining the structures of membrane proteins. In this chapter we explore how those structures can be further used in two key ways. The first is their use in structure based drug design (SBDD) and the second is how they can be used to extend our understanding of their functional activity via the use of molecular dynamics. Both aspects now heavily rely on computations. This area is vast, and alas, too large to consider in depth in a single book chapter. Thus where appropriate we have referred the reader to recent reviews for deeper assessment of the field. We discuss progress via the use of examples from two main drug target areas; G-protein coupled receptors (GPCRs) and ion channels. We end with a discussion of some of the main challenges in the area.

Estimation of Solvation Entropy and Enthalpy via Analysis of Water Oxygen-Hydrogen Correlations

A statistical-mechanical framework for estimation of solvation entropies and enthalpies is proposed, which is based on the analysis of water as a mixture of correlated water oxygens and water hydrogens. Entropic contributions of increasing order are cast in terms of a Mutual Information Expansion that is evaluated to pairwise interactions. In turn, the enthalpy is computed directly from a distance-based hydrogen bonding energy algorithm. The resulting expressions are employed for grid-based analyses of Molecular Dynamics simulations. In this first assessment of the methodology, we obtained global estimates of the excess entropy and enthalpy of water that are in good agreement with experiment and examined the method's ability to enable detailed elucidation of solvation thermodynamic structures, which can provide valuable knowledge toward molecular design.