Computed Binding Free Energies Research Articles

Do All Paths Lead to Rome? How Reliable is Umbrella Sampling Along a Single Path?

Molecular dynamics (MD) simulations are widely applied to estimate absolute binding free energies of protein-ligand and protein-protein complexes. A routinely used method for binding free energy calculations with MD is umbrella sampling (US), which calculates the potential of mean force (PMF) along a single reaction coordinate. Surprisingly, in spite of its widespread use, few validation studies have focused on the convergence of the free energy computed along a single path for specific cases, not addressing the reproducibility of such calculations in general. In this work, we therefore investigate the reproducibility and convergence of US along a standard distance-based reaction coordinate for various protein-protein and protein-ligand complexes, following commonly used guidelines for the setup. We show that repeating the complete US workflow can lead to differences of 2-20 kcal/mol in computed binding free energies. We attribute those discrepancies to small differences in the binding pathways. While these differences are unavoidable in the established US protocol, the popularity of the latter could hint at a lack of awareness of such reproducibility problems. To test if the convergence of PMF profiles can be improved if multiple pathways are sampled simultaneously, we performed additional simulations with an adaptive-biasing method, here the accelerated weight histogram (AWH) approach. Indeed, the PMFs obtained from AHW simulations are consistent and reproducible for the systems tested. To the best of our knowledge, our work is the first to attempt a systematic assessment of the pitfalls in one the most widely used protocols for computing binding affinities. We anticipate therefore that our results will provide an incentive for a critical reassessment of the validity of PMFs computed with US, and make a strong case to further benchmark the performance of adaptive-biasing methods for computing binding affinities.

Rational Design of Targeted Gold Nanoclusters with High Affinity to Integrin αvβ3 for Combination Cancer Therapy.

The unique attributes of targeted nano-drug delivery systems (TNDDSs) over conventional cancer therapies in suppressing off-target effects make them one of the most promising options for cancer treatment. There is evidence that the density of surface-conjugated ligands is a crucial factor in achieving the desired therapeutic efficacy of TNDDSs, but this is hardly manageable in conventional nanomaterials. In this context, ligand-protected gold nanoclusters (AuNCs) are excellent candidates for developing new TNDDSs with a unique control on their surface functionalities, thus helping to achieve enhanced delivery performance. Here, we study the interactions and binding free energies between ten different functionalized Au144(SR)60 (SR = thiolate ligand) nanoclusters and integrin αvβ3 using molecular dynamics simulations and the umbrella sampling method to obtain the optimal formulations. The AuNCs were functionalized with anticancer drugs (5-fluorouracil or signaling pathways inhibitors, such as capivasertib, linifanib, tanespimycin, and taselisib) and integrin-targeting peptides (RGD4C or QS13), and we identified the optimal mixed ligand layer to enhance their binding affinity to the cancer cell receptor. The results showed that changing the proportions of the same type of ligands on the surface of AuNCs led to differences of up to 38 kcal/mol in computed binding free energies. RGD4C as the targeting peptide resulted in greater affinity for αvβ3, and in most formulations studied, a higher amount of drug than peptide was needed. Polar and charged residues, such as Ser123, Asp150, Tyr178, Arg214, and Asp251 were found to play a significant role in AuNC binding. Our simulations also revealed that Mn2+ cations are crucial for stabilizing the αvβ3-AuNC complex. These findings demonstrate the potential of carefully designing the surface composition of TNDDSs to optimize their target affinity and specificity.

Synthesis, molecular dynamics, antimicrobial activity and wound healing application of new methylidene dyes based on pyrrolinone esters

A new methylidene dye based on the direct condensation of an aldehyde derivative with a pyrrolinone ester derivative was successfully prepared as well as its quaternary ammonium salt analogue. The structures of all synthesized dyes were confirmed using NMR, Mass and IR spectra. The absorption and emission spectra of the synthesized dyes were investigated. The synthesized methylidene dye and its cationic form showed high molar absorption coefficients and a significant emission of the cationic dye analogue solution was observed. The antibacterial affinity using the disk diffusion method was investigated for six potential skin infection causing microbial pathogens, including two Gram-negative species (Pseudomonas aeruginosa and Proteus mirabilis), two Gram-positive species (Staphylococcus aureus and Staphylococcus epidermidis), and two fungal species (Candida albicans and Rhizomucor miehei) by recording the inhibition zone as well as studying the killing time effect for the prepared dyes. The in vitro wound healing application and the effect of cationized Dye 2 on the healing progress showed very effective and faster healing at a concentration of 100 µg/mL (IC50). Molecular dynamics simulation studies of Dye 1 and Dye 2 were carried out to compute binding free energies using Generalized Born Surface Area (MM/GBSA) in molecular mechanics. Furthermore, computational studies revealed that Dye 2 showed high affinity toward the active site of DNA gyrase B, which provides a solid framework for new structure-based design initiatives.

Exploring novel lead scaffolds for SGLT2 inhibitors: Insights from machine learning and molecular dynamics simulations

Sodium-glucose cotransporter 2 (SGLT2) plays a pivotal role in mediating glucose reabsorption within the renal filtrate, representing a well-known target in type 2 diabetes and heart failure. Recent emphasis has been directed toward designing SGLT2 inhibitors, with C-glycoside inhibitors emerging as front-runners. The architecture of SGLT2 has been successfully resolved using cryo-electron microscopy. However, comprehension of the pharmacophores within the binding site of SGLT2 remains unclear. Here, we use machine learning and molecular dynamics simulations on SGLT2 bound with its inhibitors in preclinical or clinical development to shed light on this issue. Our dataset comprises 1240 SGLT2 inhibitors amalgamated from diverse sources, forming the basis for constructing machine learning models. SHapley Additive exPlanation (SHAP) elucidates the crucial fragments that contribute to inhibitor activity, specifically Morgan_3, 162, 310, 325, 366, 470, 597, 714, 926, and 975. Furthermore, the computed binding free energies and per-residue contributions for SGLT2-inhibitor complexes unveil crucial fragments of inhibitors that interact with residues Asn-75, His-80, Val-95, Phe-98, Val-157, Leu-274, and Phe-453 in the binding site of SGLT2. This comprehensive investigation enhances understanding of the binding mechanism for SGLT2 inhibitors, providing a robust framework for evaluating and discovering novel lead scaffolds within this domain.

Natural compounds inhibit Monkeypox virus methyltransferase VP39 in silico studies

VP39, an essential 2′-O-RNA methyltransferase enzyme discovered in Monkeypox virus (MPXV), plays a vital role in viral RNA replication and transcription. Inhibition of the enzyme may prevent viral replication. In this context, using a combination of molecular docking and molecular dynamics (MDs) simulations, the inhibitory ability of NCI Diversity Set VII natural compounds to VP39 protein was investigated. It should be noted that the computed binding free energy of ligand via molecular docking and linear interaction energy (LIE) approaches are in good agreement with the corresponding experiments with coefficients of R = 0.72 and 0.75, respectively. NSC 319990, NSC 196515 and NSC 376254 compounds were demonstrated that can inhibit MPVX methyltransferase VP39 protein with the similar affinity compared to available inhibitor sinefungin. Moreover, nine residues involving Gln39, Gly68, Gly72, Asp95, Arg97, Val116, Asp138, Arg140 and Asn156 may be argued that they play an important role in binding process of inhibitors to VP39. Communicated by Ramaswamy H. Sarma

Biomass-derived potential nano-biomaterials: Protein binding, anti-biofilm activity and bio-imaging

Deriving carbon dots (CDs) from renewable sources is gaining popularity due to their prevalence, cost effectiveness, improved aqueous solubility, and increased biocompatibility. CDs, which are made up of crystalline graphitized carbon cores and multiple surface groups, are now spawning a lot of attention in the biological domains. Herein, the CDs were derived from dried rose petals using hydrothermal route and were completely characterized utilizing pivotal techniques. The prepared CDs are spherical particles that are approximately 5–6nm in size and have exceptional stability when exposed to pH and light irradiation. The derived CDs are excitation dependent fluorescent in nature with the quantum yield of 6%. Bovine serum albumin (BSA) binding interaction has been studied with CDs and evaluated through Stern−Volmer equation. The fluorescence quenching mechanism of BSA by CDs followed static type, is further confirmed by the lifetime studies. The binding mode of the CDs with BSA has been studied by molecular docking and the computed binding free energy for CDs is calculated to be −9.62 kcal/mol. Antibiofilm activity revealed that CDs were efficient in reducing the biofilm formations in both gram-positive and gram-negative bacterium. Predominantly, CDs used in this study were significant in reducing the biofilms of gram-negative bacterium. Furthermore, the CDs are effectively used as an efficient biological probe for bioimaging studies.

Leveraging Advanced In Silico Techniques in Early Drug Discovery: A Study of Potent Small-Molecule YAP-TEAD PPI Disruptors.

Disruption of the YAP-TEAD protein-protein interaction is an attractive therapeutic strategy in oncology to suppress tumor progression and cancer metastasis. YAP binds to TEAD at a large flat binding interface (∼3500 Å2) devoid of a well-defined druggable pocket, so it has been difficult to design low-molecular-weight compounds to abrogate this protein-protein interaction directly. Recently, work by Furet and coworkers (ChemMedChem 2022, DOI: 10.1002/cmdc.202200303) reported the discovery of the first class of small molecules able to efficiently disrupt the transcriptional activity of TEAD by binding to a specific interaction site of the YAP-TEAD binding interface. Using high-throughput in silico docking, they identified a virtual screening hit from a hot spot derived from their previously rationally designed peptidic inhibitor. Structure-based drug design efforts led to the optimization of the hit compound into a potent lead candidate. Given advances in rapid high-throughput screening and rational approaches to peptidic ligand discovery for challenging targets, we analyzed the pharmacophore features involved in transferring from the peptidic to small-molecule inhibitor that could enable small-molecule discovery for such targets. Here, we show retrospectively that pharmacophore analysis augmented by solvation analysis of molecular dynamics trajectories can guide the designs, while binding free energy calculations provide greater insight into the binding conformation and energetics accompanying the association event. The computed binding free energy estimates agree well with experimental findings and offer useful insight into structural determinants that influence ligand binding to the TEAD interaction surface, even for such a shallow binding site. Taken together, our results demonstrates the utility of advanced in silico methods in structure-based design efforts for difficult-to-drug targets such as the YAP-TEAD transcription factor complex.

Deciphering Selectivity Mechanism of BRD9 and TAF1(2) toward Inhibitors Based on Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

BRD9 and TAF1(2) have been regarded as significant targets of drug design for clinically treating acute myeloid leukemia, malignancies, and inflammatory diseases. In this study, multiple short molecular dynamics simulations combined with the molecular mechanics generalized Born surface area method were employed to investigate the binding selectivity of three ligands, 67B, 67C, and 69G, to BRD9/TAF1(2) with IC50 values of 230/59 nM, 1400/46 nM, and 160/410 nM, respectively. The computed binding free energies from the MM-GBSA method displayed good correlations with that provided by the experimental data. The results indicate that the enthalpic contributions played a critical factor in the selectivity recognition of inhibitors toward BRD9 and TAF1(2), indicating that 67B and 67C could more favorably bind to TAF1(2) than BRD9, while 69G had better selectivity toward BRD9 over TAF1(2). In addition, the residue-based free energy decomposition approach was adopted to calculate the inhibitor-residue interaction spectrum, and the results determined the gatekeeper (Y106 in BRD9 and Y1589 in TAF1(2)) and lipophilic shelf (G43, F44, and F45 in BRD9 and W1526, P1527, and F1528 in TAF1(2)), which could be identified as hotspots for designing efficient selective inhibitors toward BRD9 and TAF1(2). This work is also expected to provide significant theoretical guidance and insightful molecular mechanisms for the rational designs of efficient selective inhibitors targeting BRD9 and TAF1(2).

Molecular modeling of pyrrolo-pyrimidine based analogs as potential FGFR1 inhibitors: a scientific approach for therapeutic drugs

Fibroblast growth factor receptors 1 (FGFR1) is an emerging target for the development of anticancer drugs. Uncontrolled expression of FGFR1 is strongly associated with a number of different types of cancers. Apart from a few FGFR inhibitors, the FGFR family members have not been thoroughly studied to produce clinically effective anticancer drugs. The application of proper computational techniques may aid in understanding the mechanism of protein–ligand complex formation, which may provide a better notion for developing potent FGFR1 inhibitors. In this study, a variety of computational techniques, including 3D-QSAR, flexible docking and MD simulation followed by MMGB/PBSA, H-bonds and distance analysis, have been performed to systematically explore the binding mechanism of pyrrolo-pyrimidine derivatives against FGFR1. The 3D-QSAR model was generated to deduce the structural determinants of FGFR1 inhibition. The high q2 and r2 values for the CoMFA and CoMSIA models indicated that the created 3D-QSAR models could reliably predict the bioactivities of FGFR1 inhibitors. The computed binding free energies (MMGB/PBSA) for the selected compounds were consistent with the ranking of their experimental binding affinities against FGFR1. Furthermore, per-residue energy decomposition analysis revealed that the residues Lys514 in catalytic region, Asn568, Glu571 in solvent accessible portion and Asp641 in DFG motif exhibited a strong tendency to mediate ligand–protein interactions through the hydrogen bonding and Van Der Waals interactions. These findings may benefit researchers in gaining better knowledge of FGFR1 inhibition and may serve as a guideline for the development of novel and highly effective FGFR1 inhibitors.Communicated by Ramaswamy H. Sarma

In silico prediction of Antifungal compounds from Natural sources towards Lanosterol 14-alpha demethylase (CYP51) using Molecular docking and Molecular dynamic simulation

An increase in the occurrence of fungal infections throughout the world, as well as the rise of novel fungal strains and antifungal resistance to commercially available drugs, suggests that new therapeutic choices for fungal infections are needed. The purpose of this research was to find new antifungal candidates or leads of secondary metabolites derived from natural sources that could effectively inhibit the enzymatic activity of Candida albicans lanosterol 14-alpha demethylase (CYP51) while also having good pharmacokinetics. In silico prediction of the drug-likeness, chemo-informatics and enzyme inhibition indicate that the 46 compounds derived from fungi, sponges, plants, bacteria and algae sources have a high novelty to meet all five requirements of Lipinski's rules and impede enzymatic function. Among the 15 candidate molecules with strong binding affinity to CYP51 investigated by molecular docking simulation, didymellamide A-E compounds demonstrated the strongest binding energy against the target protein at −11.14, −11.46, −11.98, −11.98, and −11.50 kcal/mol, respectively. Didymellamide molecules bind to comparable active pocket sites of antifungal ketoconazole and itraconazole medicines by hydrogen bonds forming to Tyr132, Ser378, Met508, His377 and Ser507, and hydrophobic interactions with HEM601 molecule. The stability of the CYP51-ligand complexes was further investigated using molecular dynamics simulations that took into account different geometric features and computed binding free energy. Using the pkCSM ADMET descriptors tool, several pharmacokinetic characteristics and the toxicity of candidate compounds were assessed. The findings of this study revealed that didymellamides could be a promising inhibitor against these CYP51 protein. However, there is still a need for further in vivo and in vitro studies to support these findings.

Uncovering water effects in protein-ligand recognition: importance in the second hydration shell and binding kinetics.

Developing a ligand with high affinity for a specific protein target is essential for drug design, and water molecules are well known to play a key role in protein-drug recognition. However, predicting the role of particularly ordered water molecules in drug binding remains challenging. Furthermore, hydration free energy contributed from the water network, including the second shell of water molecules, is far from being well studied. In this research we focused on these aspects to accurately and efficiently evaluate water effects in protein-ligand binding affinity. We developed a new strategy using a free-energy calculation method, VM2. We successfully predicted the stable ordered water molecules in a number of protein systems: PDE 10a, HSP90, tryptophan synthase (TRPS), CDK2 and Factor Xa. In some of these, the second shell of water molecules appeared to be critical in protein-ligand binding. We also applied the strategy to largely improve binding free energy calculation using the MM/PBSA method. When applying MM/PBSA alone for two systems, CDK2 and Factor Xa, the computed binding free energy resulted in poor to moderate R2 values with experimental data. However, including water free energy correction greatly improved the free energy calculation. Furthermore, our work helped to explain how xk263 is a 1000 times faster binder to HIVp than ritonavir, a potentially useful tool for investigating binding kinetics. Our studies reveal the importance of fully considering water effects in therapeutic developments in pharmaceutical and biotechnology industries and for fundamental research in protein-ligand recognition.

Optimized Halogen Atomic Radii for PBSA Calculations Using Off-Center Point Charges.

In force-field methods, the usage of off-center point charges, also called extra points (EPs), is a common strategy to tackle the anisotropy of the electrostatic potential of covalently bonded halogens (X), thus allowing the description of halogen bonds (XBs) at the molecular mechanics/molecular dynamics (MM/MD) level. Diverse EP implementations exist in the literature differing on the charge sets and/or the X-EP distances. Poisson-Boltzmann and surface area (PBSA) calculations can be used to obtain solvation free energies (ΔGsolv) of small molecules, often to compute binding free energies (ΔGbind) at the MM-PBSA level. This method depends, among other parameters, on the empirical assignment of atomic radii (PB radii). Given the multiplicity of off-center point-charge models and the lack of specific PB radii for halogens compatible with such implementations, in this work, we assessed the performance of PBSA calculations for the estimation of ΔGsolv values in water (ΔGhyd), also conducting an optimization of the halogen PB radii (Cl, Br, and I) for each EP model. We not only expand the usage of EP models in the scope of the general AMBER force field (GAFF) but also provide the first optimized halogen PB radii in the context of the CHARMM general force field (CGenFF), thus contributing to improving the description of halogenated compounds in PBSA calculations.

Mechanism of recognition of parallel G-quadruplexes by DEAH/RHAU helicase DHX36 explored by molecular dynamics simulations

Because of high stability and slow unfolding rates of G-quadruplexes (G4), cells have evolved specialized helicases that disrupt these non-canonical DNA and RNA structures in an ATP-dependent manner. One example is DHX36, a DEAH-box helicase, which participates in gene expression and replication by recognizing and unwinding parallel G4s. Here, we studied the molecular basis for the high affinity and specificity of DHX36 for parallel-type G4s using all-atom molecular dynamics simulations. By computing binding free energies, we found that the two main G4-interacting subdomains of DHX36, DSM and OB, separately exhibit high G4 affinity but they act cooperatively to recognize two distinctive features of parallel G4s: the exposed planar face of a guanine tetrad and the unique backbone conformation of a continuous guanine tract, respectively. Our results also show that DSM-mediated interactions are the main contributor to the binding free energy and rely on making extensive van der Waals contacts between the GXXXG motifs and hydrophobic residues of DSM and a flat guanine plane. Accordingly, the sterically more accessible 5′-G-tetrad allows for more favorable van der Waals and hydrophobic interactions which leads to the preferential binding of DSM to the 5′-side. In contrast to DSM, OB binds to G4 mostly through polar interactions by flexibly adapting to the 5′-terminal guanine tract to form a number of strong hydrogen bonds with the backbone phosphate groups. We also identified a third DHX36/G4 interaction site formed by the flexible loop missing in the crystal structure.

Transient States and Barriers from Molecular Simulations and the Milestoning Theory: Kinetics in Ligand-Protein Recognition and Compound Design.

This study presents a novel computational approach to study molecular recognition and binding kinetics for drug-like compounds dissociating from a flexible protein system. The intermediates and their free energy profile during ligand association and dissociation processes control ligand-protein binding kinetics and bring a more complete picture of ligand-protein binding. The method applied the milestoning theory to extract kinetics and thermodynamics information from running short classical molecular dynamics (MD) simulations for frames from a given dissociation path. High-dimensional ligand-protein motions (3N-6 degrees of freedom) during ligand dissociation were reduced by use of principal component modes for assigning more than 100 milestones, and classical MD runs were allowed to travel multiple milestones to efficiently obtain ensemble distribution of initial structures for MD simulations and estimate the transition time and rate during ligand traveling between milestones. We used five pyrazolourea ligands and cyclin-dependent kinase 8 with cyclin C (CDK8/CycC) as our model system as well as metadynamics and a pathway search method to sample dissociation pathways. With our strategy, we constructed the free energy profile for highly mobile biomolecular systems. The computed binding free energy and residence time correctly ranked the pyrazolourea ligand series, in agreement with experimental data. Guided by a barrier of a ligand passing an αC helix and activation loop, we introduced one hydroxyl group to parent compounds to design our ligands with increased residence time and validated our prediction by experiments. This work provides a novel and robust approach to investigate dissociation kinetics of large and flexible systems for understanding unbinding mechanisms and designing new small-molecule drugs with desired binding kinetics.

Harmicines − harmine and cinnamic acid hybrids as novel antiplasmodial hits

Harmicines constitute novel hybrid compounds that combine two agents with reported antiplasmodial properties, namely β-carboline harmine and a cinnamic acid derivative (CAD). Cu(I) catalyzed azide-alkyne cycloaddition was employed for the preparation of three classes of hybrid molecules: N-harmicines 6a-i, O-harmicines 7a-i and N,O-bis-harmicines 8a-g,i. In vitro antiplasmodial activities of harmicines against the erythrocytic stage of Plasmodium falciparum (chloroquine-sensitive Pf3D7 and chloroquine-resistant PfDd2 strains) and hepatic stage of P. berghei, as well as cytotoxicity against human liver hepatocellular carcinoma cell line (HepG2), were evaluated. Remarkably, most of the compounds exerted significant activities against both stages of the Plasmodium life cycle. The conjugation of various CADs to harmine resulted in the increased antiplasmodial activity relative to harmine. In general, O-harmicines 7 exhibited the highest activity against the erythrocytic stage of both P. falciparum strains, whereas N,O-bis harmicines 8 showed the most pronounced activity against P. berghei hepatic stages. For the latter compound, molecular dynamics simulations confirmed binding within the ATP binding site of PfHsp90, while the weaker binders, namely 6b and harmine, were found to be positioned away from this structural element. In addition, decomposition of the computed binding free energies into contributions from individual residues suggested guidelines for further derivatization of harmine towards more efficient compounds. Cytotoxicity screening revealed N-harmicines 6 as the least, and O-harmicines 7 as the most toxic compounds. Harmicines 6g, 8b and 6d exerted the most selective action towards Plasmodium over human cells, respectively. These results establish harmicines as hits for future optimisation and development of novel antiplasmodial agents.

Unveiling the Structural Insights into the Selective Inhibition of Protein Kinase D1.

Although protein kinase D1 (PKD1) has been proved to be an efficient target for anticancer drug development, lack of structural details and substrate binding mechanisms are the main obstacles for the development of selective inhibitors with therapeutic benefits. The present study described the in silico dynamics behaviors of PKD1 in binding with selective and non-selective inhibitors and revealed the critical binding site residues for the selective kinase inhibition. Here, the three dimensional model of PKD1 was initially constructed by homology modeling along with binding site characterization to explore the non-conserved residues. Subsequently, two known inhibitors were docked to the catalytic site and the detailed ligand binding mechanisms and post binding dyanmics were investigated by molecular dynamics simulation and binding free energy calculations. According to the binding site analysis, PKD1 serves several non-conserved residues in the G-loop, hinge and catalytic subunits. Among them, the residues including Leu662, His663, and Asp665 from hinge region made polar interactions with selective PKD1 inhibitor in docking simulation, which were further validated by the molecular dynamics simulation. Both inhibitors strongly influenced the structural dynamics of PKD1 and their computed binding free energies were in accordance with experimental bioactivity data. The identified non-conserved residues likely to play critical role on molecular reorganization and inhibitor selectivity. Taken together, this study explained the molecular basis of PKD1 specific inhibition, which may help to design new selective inhibitors for better therapies to overcome cancer and PKD1 dysregulated disorders.

Free-Energy Simulations Resolve the Low-Affinity Na+-High-Affinity Asp Binding Paradox in GltPh

Glutamate transporters clear up excess extracellular glutamate by cotransporting three Na+ and one H+ with the countertransport of one K+. The archaeal homologs are selective to aspartate and only cotransport three Na+. The crystal structures of GltPh from archaea have been used in computational studies to understand the transport mechanism. Although some progress has been made with regard to the ligand-binding sites, a consistent picture of transport still eludes us. A major concern is the discrepancy between the computed binding free energies, which predict high-affinity Na+-low-affinity aspartate binding, and the experimental results in which the opposite is observed. Here, we show that the binding of the first two Na+ ions involves an intermediate state near the Na1 site, where two Na+ ions coexist and couple to aspartate with similar strengths, boosting its affinity. Binding free energies for Na+ and aspartate obtained using this intermediate state are in good agreement with the experimental values. Thus, the paradox in binding affinities arises from the assumption that the ligands bind to the sites observed in the crystal structure following the order dictated by their binding free energies with no intermediate states. In fact, the presence of an intermediate state eliminates such a correlation between the binding free energies and the binding order. The intermediate state also facilitates transition of the first Na+ ion to its final binding site via a knock-on mechanism, which induces substantial conformational changes in the protein consistent with experimental observations.

Predicting binding affinities of nitrogen-containing bisphosphonates on hydroxyapatite surface by molecular dynamics

The binding affinity of nitrogen-containing bisphosphonates (NBPs) to bone mineral surface is important to its uptake, release, and diffusion within bone. However, how molecular structures of NBPs influence the binding affinity has not reached conclusions through experimental measurements. We examined the binding free energies of zoledronate (ZOL), risedronate (RIS), pamidronate (PAM), alendronate (ALN), and ibandronate (IBN) to neat and protonated hydroxyapatite surfaces through molecular dynamics and umbrella sampling. The computed binding free energy rank was ALN > PAM > ZOL > IBN > RIS which was not only qualitatively but also quantitatively consistent with NMR and isothermal titration calorimetry studies.

Accurate and Efficient Calculation of Protein-Protein Binding Free Energy-Interaction Entropy with Residue Type-Specific Dielectric Constants.

Accurate and efficient computation of protein-protein binding free energy remains a grand challenge. In this study, we develop a new strategy to achieve efficient calculation for total protein-protein binding free energies with improved accuracy. The new method combines the recently developed interaction entropy method for efficient computation of entropic change together with the use of residue type-specific dielectric constants in the framework of MM/GBSA to achieve optimal result for protein-protein binding free energies. The new strategy is shown to be computationally efficient and accurate than that using standard MM/GBSA methods in which the entropic computation is performed by the normal model approach and the protein interior is represented by the standard dielectric constant (typically set to 1), both in terms of accuracy and computational efficiency. Our study using the new strategy on a set of randomly selected 20 protein-protein binding systems produced an optimal dielectric constant of 2.7 for charged residues and 1.1 for noncharged residues. Using this new strategy, the mean absolute error in computed binding free energies for these 20 selected protein-protein systems is significantly reduced by more than 3-fold while the computational cost is reduced by more than 2 orders of magnitude, compared to the result using standard MM/GBSA method with the normal mode approach. A similar improvement in accuracy is confirmed for a test set consisting of 10 protein-protein systems.

Molecular simulation studies on the binding activity and selectivity of 3-amino-phenyl-5-chloro-pyrimidine-2, 4-diamine derivatives in complexes with kinases c-Met and ALK

ABSTRACTReceptor tyrosine kinases c-Met and ALK have been demonstrated to be important therapeutic targets for cancer therapy. However, selectivity and drug resistance could hinder the development of their corresponding inhibitors. In this study, three compounds with similar scaffold were examined to study activity and selectivity mechanism towards c-Met or ALK by utilising a combined approach of computational techniques, including flexible dock, molecular electrostatic potential (MESP) calculations, molecular dynamic (MD) simulation, and binding free-energy calculation. Molecular simulation provides us new chemical insights into steric and electronic complementarities of these inhibitors to target binding sites. The computed binding free energies were consistent with the changing trend of experimental affinities on c-Met and ALK. H-bond with Asp169 and hydrophobic interaction with Phe36 of c-Met, respectively, could be crucial for the binding affinity of an inhibitor binding to c-Met. Meanwhile, for inhibitor–ALK complex, both H-bond interactions with Arg28 and Met101 and hydrophobic interactions with Leu30, Val38, and Leu158 could enhance the bioactivity and selectivity. The present work may provide a structural understanding of molecular mechanism expected to be valuable for the guidelines of the development of new potent c-Met or ALK selective inhibitors.