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High level of hematopoietic cell kinase (Hck) is associated with drug resistance in chronic myeloid leukemia. Additionally, Hck activity has also been connected with the pathogenesis of HIV-1 and chronic obstructive pulmonary disease. In this study, three-dimensional (3D) QSAR pharmacophore models were generated for Hck based on experimentally known inhibitors. A best pharmacophore model, Hypo1, was developed with high correlation coefficient (0.975), Low RMS deviation (0.60) and large cost difference (49.31), containing three ring aromatic and one hydrophobic aliphatic feature. It was further validated by the test set (r = 0.96) and Fisher's randomization method (95%). Hypo 1 was used as a 3D query for screening the chemical databases, and the hits were further screened by applying Lipinski's rule of five and ADMET properties. Selected hit compounds were subjected to molecular docking to identify binding conformations in the active site. Finally, the appropriate binding modes of final hit compounds were revealed by molecular dynamics (MD) simulations and free energy calculation studies. Hence, we propose the final three hit compounds as virtual candidates for Hck inhibitors.

Glycogen synthase kinase 3 (GSK3) is a serine/threonine protein kinase which is widely involved in cell signaling and controls a broad number of cellular functions. GSK3 contains α and β isoforms, and GSK3β has received more attention and becomes an attractive drug target for the treatment of several diseases. The binding pocket of cyclin-dependent kinase 2 (CDK2) shares high sequence identity to that of GSK3β, and therefore, the design of highly selective inhibitors toward GSK3β remains a big challenge. In this study, a computational strategy, which combines molecular docking, molecular dynamics simulations, free energy calculations, and umbrella sampling simulations, was employed to explore the binding mechanisms of two selective inhibitors to GSK3β and CDK2. The simulation results highlighted the key residues critical for GSK3β selectivity. It was observed that although GSK3β and CDK2 share the conserved ATP-binding pockets, some different residues have significant contributions to protein selectivity. This study provides valuable information for understanding the GSK3β-selective binding mechanisms and the rational design of selective GSK3β inhibitors., (© 2016 John Wiley & Sons A/S.)

The human monoamine transporters (MATs) facilitate the reuptake of monoamine neurotransmitters from the synaptic cleft. MATs are linked to a number of neurological diseases and are the targets of both therapeutic and illicit drugs. Until recently, no high-resolution structures of the human MATs existed, and therefore, studies of this transporter family have relied on investigations of the homologues bacterial transporters such as the leucine transporter LeuT, which has been crystallized in several conformational states. A two-substrate transport mechanism has been suggested for this transporter family, which entails that high-affinity binding of a second substrate in an extracellular site is necessary for the substrate in the central binding site to be transported. Compelling evidence for this mechanism has been presented, however, a number of equally compelling accounts suggest that the transporters function through a mechanism involving only a single substrate and a single high-affinity site. To shed light on this apparent contradiction, we have performed extensive molecular dynamics simulations of LeuT in the outward-occluded conformation with either one or two substrates bound to the transporter. We have also calculated the substrate binding affinity in each of the two proposed binding sites through rigorous free energy simulations. Results show that substrate binding is unstable in the extracellular vestibule and the substrate binding affinity within the suggested extracellular site is very low (0.2 and 3.3 M for the two dominant binding modes) compared to the central substrate binding site (14 nM). This suggests that for LeuT in the outward-occluded conformation only a single high-affinity substrate binding site exists.

Phosphotriesterase-like lactonases (PLLs) have received much attention because of their physical and chemical properties. They may have widespread applications in various fields. For example, they show potential for quorum-sensing signaling pathways and organophosphorus (OP) detoxification in agricultural science. However, the mechanism by which PLLs hydrolyze, which involves OP compounds and lactones and a variety of distinct catalytic efficiencies, has only rarely been explored. In the present study, molecular dynamics (MD) simulations were performed to characterize and contrast the structural dynamics of DrPLL, a member of the PLL superfamily in Deinococcus radiodurans, bound to two substrates, δ-nonanoic lactone and paraoxon. It has been observed that there is a 16-fold increase in the catalytic efficiency of the two mutant strains of DrPLL (F26G/C72I) vs. the wild-type enzyme toward the hydrolysis of paraoxon, but an explanation for this behavior is currently lacking. The analysis of the molecular trajectories of DrPLL bound to δ-nonanoic lactone indicated that lactone-induced conformational changes take place in loop 8, which is near the active site. Binding to paraoxon may lead to conformational displacement of loop 1 residues, which could lead to the deformation of the active site and so trigger the entry of the paraoxon into the active site. The efficiency of the F26G/C72I mutant was increased by decreasing the displacement of loop 1 residues and increasing the flexibility of loop 8 residues. These results provide a molecular-level explanation for the experimental behavior.

Matrix metalloproteases are multidomain enzymes with a remarkable proteolytic activity located in the extracellular environment. Their catalytic activity and structural properties have been intensively studied during the last few decades using both experimental and theoretical approaches, but many open questions still remain. Extensive molecular dynamics simulations enable the sampling of the configurational space of a molecular system, thus contributing to the characterization of the structure, dynamics, and ligand binding properties of a particular MMP. Based on previous computational experience, we provide in this chapter technical and methodological guidelines that may be useful to and stimulate other researchers to perform molecular dynamics simulations to help address unresolved questions concerning the molecular mode of action of MMPs.

The earliest metazoan ancestors of humans include the ctenophore Mnemiopsis leidyi The genome of this comb jelly encodes homologs of vertebrate ionotropic glutamate receptors (iGluRs) that are distantly related to glycine-activated NMDA receptors and that bind glycine with unusually high affinity. Using ligand-binding domain (LBD) mutants for electrophysiological analysis, we demonstrate that perturbing a ctenophore-specific interdomain Arg-Glu salt bridge that is notably absent from vertebrate AMPA, kainate, and NMDA iGluRs greatly increases the rate of recovery from desensitization, while biochemical analysis reveals a large decrease in affinity for glycine. X-ray crystallographic analysis details rearrangements in the binding pocket stemming from the mutations, and molecular dynamics simulations suggest that the interdomain salt bridge acts as a steric barrier regulating ligand binding and that the free energy required to access open conformations in the glycine-bound LBD is largely responsible for differences in ligand affinity among the LBD variants., Competing Interests: The authors declare no conflict of interest.

Helicobacter pylori (H. pylori) persevere in the human stomach, an environment in which they encounter many DNA-damaging conditions, including gastric acidity. The pathogenicity of H. pylori is enhanced by its well-developed DNA repair mechanism, thought of as 'machinery,' such as nucleotide excision repair (NER). NER involves multi-enzymatic excinuclease proteins (UvrABC endonuclease), which repair damaged DNA in a sequential manner. UvrB is the central component in prokaryotic NER, essential for damage recognition. Therefore, molecular modeling studies of UvrB protein from H. pylori are carried out with homology modeling and molecular dynamics (MD) simulations. The results reveal that the predicted structure is bound to a DNA hairpin with 3-bp stem, an 11-nucleotide loop, and 3-nt 3' overhang. In addition, a mutation of the Y96A variant indicates reduction in the binding affinity for DNA. Free-energy calculations demonstrate the stability of the complex and help identify key residues in various interactions based on residue decomposition analysis. Stability comparative studies between wild type and mutant protein-DNA complexes indicate that the former is relatively more stable than the mutant form. This predicted model could also be useful in designing new inhibitors for UvrB protein, as well as preventing the pathogenesis of H. pylori., (Copyright © 2016. Published by Elsevier Ltd.)

Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological macromolecules, realize their functions through binding to themselves or other molecules. A detailed understanding of the protein-ligand interactions is therefore central to understanding biology at the molecular level. Moreover, knowledge of the mechanisms responsible for the protein-ligand recognition and binding will also facilitate the discovery, design, and development of drugs. In the present review, first, the physicochemical mechanisms underlying protein-ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized. Next, three currently existing protein-ligand binding models--the "lock-and-key", "induced fit", and "conformational selection"--are described and their underlying thermodynamic mechanisms are discussed. Finally, the methods available for investigating protein-ligand binding affinity, including experimental and theoretical/computational approaches, are introduced, and their advantages, disadvantages, and challenges are discussed.

Membrane transporters mediate one of the most fundamental processes in biology. They are the main gatekeepers controlling active traffic of materials in a highly selective and regulated manner between different cellular compartments demarcated by biological membranes. At the heart of the mechanism of membrane transporters lie protein conformational changes of diverse forms and magnitudes, which closely mediate critical aspects of the transport process, most importantly the coordinated motions of remotely located gating elements and their tight coupling to chemical processes such as binding, unbinding and translocation of transported substrate and cotransported ions, ATP binding and hydrolysis, and other molecular events fueling uphill transport of the cargo. An increasing number of functional studies have established the active participation of lipids and other components of biological membranes in the function of transporters and other membrane proteins, often acting as major signaling and regulating elements. Understanding the mechanistic details of these molecular processes require methods that offer high spatial and temporal resolutions. Computational modeling and simulations technologies empowered by advanced sampling and free energy calculations have reached a sufficiently mature state to become an indispensable component of mechanistic studies of membrane transporters in their natural environment of the membrane. In this article, we provide an overview of a number of major computational protocols and techniques commonly used in membrane transporter modeling and simulation studies. The article also includes practical hints on effective use of these methods, critical perspectives on their strengths and weak points, and examples of their successful applications to membrane transporters, selected from the research performed in our own laboratory., (© 2016 Elsevier Inc. All rights reserved.)

All-atom molecular dynamics is used to investigate the transport of Na(+) across a 1,2-dioleoyl-sn-glycero-3-phosphocholine lipid bilayer facilitated by a diazacrown hydraphile. Specifically, the free energy of Na(+) passing through the bilayer is calculated using the adaptive biasing force method to study the free energy associated with the increase in Na(+) transport in the presence of the hydraphile molecule. The results show that water interaction greatly influences Na(+) transport through the lipid bilayer as water is pulled through the bilayer with Na(+) forming a water channel. The hydraphile causes a reduction in the free energy barrier for the transport of Na(+) through the head group part of the lipid bilayer since it complexes the Na(+) reducing the necessity for water to be complexed and, therefore, dragged through with Na(+), an energetically unfavorable process. The free energy associated with Na(+) being desolvated within the bilayer is significantly decreased in the presence of the hydraphile molecule; the hydraphile increases the number of solvation states of Na(+) that can be adopted, and this increase in the number of available configurations provides an entropic explanation for the success of the hydraphile.

Free energy simulations are an established computational tool in modelling chemical change in the condensed phase. However, sampling of kinetically distinct substates remains a challenge to these approaches. As a route to addressing this, we link the methods of thermodynamic integration (TI) and swarm-enhanced sampling molecular dynamics (sesMD), where simulation replicas interact cooperatively to aid transitions over energy barriers. We illustrate the approach by using alchemical alkane transformations in solution, comparing them with the multiple independent trajectory TI (IT-TI) method. Free energy changes for transitions computed by using IT-TI grew increasingly inaccurate as the intramolecular barrier was heightened. By contrast, swarm-enhanced sampling TI (sesTI) calculations showed clear improvements in sampling efficiency, leading to more accurate computed free energy differences, even in the case of the highest barrier height. The sesTI approach, therefore, has potential in addressing chemical change in systems where conformations exist in slow exchange., (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Calcium represents a key biological signaling ion with the EF-hand loops being its most prevalent binding motif in proteins. We show using molecular dynamics simulations with umbrella sampling that including electronic polarization effects via ionic charge rescaling dramatically improves agreements with experiment in terms of the strength of calcium binding and structures of the calmodulin binding sites. The present study thus opens way to accurate calculations of interactions of calcium and other computationally difficult high-charge-density ions in biological contexts.

The polyether ionophore monensin is biosynthesized by a polyketide synthase that delivers a mixture of monensins A and B by the incorporation of ethyl- or methyl-malonyl-CoA at its fifth module. Here we present the first computational model of the fifth acyltransferase domain (AT5mon ) of this polyketide synthase, thus affording an investigation of the basis of the relaxed specificity in AT5mon , insights into the activation for the nucleophilic attack on the substrate, and prediction of the incorporation of synthetic malonic acid building blocks by this enzyme. Our predictions are supported by experimental studies, including the isolation of a predicted derivative of the monensin precursor premonensin. The incorporation of non-native building blocks was found to alter the ratio of premonensins A and B. The bioactivity of the natural product derivatives was investigated and revealed binding to prenyl-binding protein. We thus show the potential of engineered biosynthetic polyketides as a source of ligands for biological macromolecules., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Binding free energy calculations offer a thermodynamically rigorous method to compute protein-ligand binding, and they depend on empirical force fields with hundreds of parameters. We examined the sensitivity of computed binding free energies to the ligand's electrostatic and van der Waals parameters. Dielectric screening and cancellation of effects between ligand-protein and ligand-solvent interactions reduce the parameter sensitivity of binding affinity by 65%, compared with interaction strengths computed in the gas-phase. However, multiple changes to parameters combine additively on average, which can lead to large changes in overall affinity from many small changes to parameters. Using these results, we estimate that random, uncorrelated errors in force field nonbonded parameters must be smaller than 0.02 e per charge, 0.06 Å per radius, and 0.01 kcal/mol per well depth in order to obtain 68% (one standard deviation) confidence that a computed affinity for a moderately-sized lead compound will fall within 1 kcal/mol of the true affinity, if these are the only sources of error considered.

The aim of fragment-based drug design (FBDD) is to identify molecular fragments that bind to alternate subsites within a given binding pocket leading to cooperative binding when linked. In this study, the binding of fragments to human phenylethanolamine N-methyltransferase is used to illustrate how (a) current protocols may fail to detect fragments that bind cooperatively, (b) theoretical approaches can be used to validate potential hits, and (c) apparent false positives obtained when screening against cocktails of fragments may in fact indicate promising leads.

4-Hydroxyphenylpyruvate dioxygenase is a relevant target in both pharmaceutical and agricultural research. We report on molecular dynamics simulations and free energy calculations on this enzyme, in complex with 12 inhibitors for which experimental affinities were determined. We applied the thermodynamic integration approach and the more efficient one-step perturbation. Even though simulations seem well converged and both methods show excellent agreement between them, the correlation with the experimental values remains poor. We investigate the effect of slight modifications on the charge distribution of these highly conjugated systems and find that accurate models can be obtained when using improved force field parameters. This study gives insight into the applicability of free energy methods and current limitations in force field parameterization., (Copyright © 2011 Wiley Periodicals, Inc.)

Evaluating the free-energy landscape of proteins and the corresponding functional aspects presents a major challenge for computer simulation approaches. This challenge is due to the complexity of the landscape and the enormous computer time needed for converging simulations. The use of simplified coarse-grained (CG) folding models offers an effective way of sampling the landscape but such a treatment, however, may not give the correct description of the effect of the actual protein residues. A general way around this problem that has been put forward in our early work (Fan et al., Theor Chem Acc 1999;103:77-80) uses the CG model as a reference potential for free-energy calculations of different properties of the explicit model. This method is refined and extended here, focusing on improving the electrostatic treatment and on demonstrating key applications. These applications include: evaluation of changes of folding energy upon mutations, calculations of transition-states binding free energies (which are crucial for rational enzyme design), evaluations of catalytic landscape, and evaluations of the time-dependent responses to pH changes. Furthermore, the general potential of our approach in overcoming major challenges in studies of structure function correlation in proteins is discussed.