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Predicting the preferred orientation of a ligand to a receptor and the free energy (ΔGAB) of these molecules in a solution is very useful for pharmaceutical applications. In this work, ΔGAB between chitosan and quercetin molecules with water were obtained by the thermodynamic integration (TI) method and the chitosan+quercetin complex was investigated by Molecular Docking (MDK). The topology of the molecules was compatible with the CHARMM force-field. Both molecules were solvated with the GROMACS SPC water model. The ΔGAB values of the molecule+water systems with the thermodynamic integration (TI) method was done in a 10 ns simulation. The complex was achieved in a 2.5 nm x 2.5 nm x 2.5 nm box. The ΔGAB values for the molecules+water systems were 14.36 +/- 0.46 and 0.19 +/- 0.53 kJ/mol, respectively. For the complex, nine conformations were obtained for the quercetin around the chitosan. The best conformation showed an affinity energy of -3.8 kcal/mol. The ΔGAB results for the systems confirm the low or no solubility of the molecules in the water under normal conditions, as already demonstrated experimentally. The docking showed that the interaction between chitosan and quercetin molecules involves hydrogen bonds in a specific position. DOI: http://dx.doi.org/10.17807/orbital.v11i2.1344

Epstein-Barr Virus (EBV) is considered the most important human pathogen due to its role in infections and cellular malignancies. It has been reported that this Oncolytic virus infects 90% world’s population. EBNA1 is required for DNA binding and survival of the virus and is considered an essential drug target. The biochemical and structural properties of this protein are known, but it is still unclear which residues impart a critical role in the recognition of dsDNA. Intending to disclose only the essential residues in recognition of dsDNA, this study used a computational pipeline to generate an alanine mutant of each interacting residue and determine the impact on the binding. Our analysis revealed that R469A, K514A, Y518A, R521A and R522A are the key hotspots for the recognition of dsDNA by the EBNA1. The dynamics properties, i.e. stability, flexibility, structural compactness, hydrogen bonding frequency, binding affinity, are altered by disrupting the protein-DNA contacts, thereby decreases the binding affinity. In particular, the two arginine substitution, R521A and R522A, significantly affected the total binding energy. Thus, we hypothesize that these residues impart a critical role in the dsDNA recognition and pathogenesis. This study would help to design structure-based drugs against the EBV infections.

Phenylketonuria (PKU) is a genetic disorder that if left untreated can lead to behavioral problems, epilepsy, and even mental retardation. PKU results from mutations within the phenylalanine‐4‐hydroxylase (PAH) gene that encodes for the PAH protein. The study of all PAH causing mutations is improbable using experimental techniques. In this study, a collection of in silico resources, sorting intolerant from tolerant, Polyphen‐2, PhD‐SNP, and MutPred were used to identify possible pathogenetic and deleterious PAH non‐synonymous single nucleotide polymorphisms (nsSNPs). We identified two variants of PAH, I65N and L311P, to be the most deleterious and disease causing nsSNPs. Molecular dynamics (MD) simulations were carried out to characterize these point mutations on the atomic level. MD simulations revealed increased flexibility and a decrease in the hydrogen bond network for both mutants compared to the native protein. Free energy calculations using the MM/GBSA approach found that BH4, a drug‐based therapy for PKU patients, had a higher binding affinity for I65N and L311P mutants compared to the wildtype protein. We also identify important residues in the BH4 binding pocket that may be of interest for the rational drug design of other PAH drug‐based therapies. Lastly, free energy calculations also determined that the I65N mutation may impair the dimerization of the N‐terminal regulatory domain of PAH. [ABSTRACT FROM AUTHOR]

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.

Leucine is the native known ligand of Sestrin2 (Sesn2) and its interaction with Sesn2 is particularly important, as it influences the activity of mTOR in aging and its associated pathologies. It is important to find out how leucine interacts with Sesn2 and how mutations in the binding pocket of leucine affect the binding of leucine. Therefore, this study was committed to investigating the impact of non-synonymous mutations by incorporating a broad spectrum of simulation techniques, from molecular dynamics to free energy calculations. Our study was designed to model the atomic-scale interactions between leucine and mutant forms of Sesn2. Our results demonstrated that the interaction paradigm for the mutants has been altered thus showing a significant decline in the hydrogen bonding network. Moreover, these mutations compromised the dynamic stability by altering the conformational flexibility, sampling time, and leucine-induced structural constraints that consequently caused variation in the binding and structural stability. Molecular dynamics-based flexibility analysis revealed that the regions 217-339 and 371-380 demonstrated a higher fluctuation. Noteworthy, these regions correspond to a linker (217-339) and a loop (371-380) that cover the leucine binding cavity that is critical for the 'latch' mechanism in the N-terminal, which is essential for leucine binding. Further validation of reduced binding and modified internal motions caused by the mutants was obtained through binding free energy calculations, principal components analysis (PCA), and free energy landscape (FEL) analysis. By unraveling the molecular intricacies of Sesn2-leucine interactions and their mutations, we hope to pave the way for innovative strategies to combat the inevitable tide of aging and its associated diseases.Communicated by Ramaswamy H. Sarma.

The neuropeptide pituitary adenylate cyclase-activating polypeptide (PACAP) belongs to the glucagon/secretin family. PACAP interacts with the pituitary adenylate cyclase-activating polypeptide receptor type 1 (PAC1) and vasoactive intestinal peptide receptors 1 and 2 (VPAC1 and VPAC2), exhibiting functions in the immune, endocrine, and nervous systems. This peptide is upregulated in numerous instances of brain injury, acting as a neuroprotective agent. It can also suppress HIV-1 and SARS-CoV-2 viral replication in vitro . This work aimed to identify, in each peptide-receptor system, the most relevant residues for complex stability and interaction energy communication via Molecular Dynamics (MD), Free Energy calculations, and Protein-energy networks, thus revealing in detail the underlying mechanisms of activation of these receptors. Hydrogen bond formation, interaction energies, and computational alanine scanning between PACAP and its receptors showed that His1, Asp3, Arg12, Arg14, and Lys15 are crucial to the peptide's stability. Furthermore, several PACAP interactions with structurally conserved positions deemed necessary in GPCR B1 activation, including Arg 2.60 , Lys 2.67 , and Glu 7.42 , were significant for the peptide's stability within the receptors. According to the protein-energy network, the connection between Asp3 of PACAP and the receptors' conserved Arg 2.60 represents a critical energy communication hub in all complexes. Additionally, the ECDs of the receptors were also found to function as energy communication hubs for PACAP. Although the overall binding mode of PACAP in the three receptors was found to be highly conserved, Arg12 and Tyr13 of PACAP were more prominent in complex with PAC1, while Ser2 of PACAP was with VPAC2. The detailed analyses performed in this work pave the way for using PACAP and its receptors as therapeutic targets.Communicated by Ramaswamy H. Sarma.

Oganesson (Og) is the last entry into the Periodic Table completing the seventh period of elements and group 18 of the noble gases. Only five atoms of Og have been successfully produced in nuclear collision experiments, with an estimate half‐life for 294118 Og of 0.69+0.64-0.22 ms.[1] With such a short lifetime, chemical and physical properties inevitably have to come from accurate relativistic quantum theory. Here, we employ two complementary computational approaches, namely parallel tempering Monte‐Carlo (PTMC) simulations and first‐principles thermodynamic integration (TI), both calibrated against a highly accurate coupled‐cluster reference to pin‐down the melting and boiling points of this super‐heavy element. In excellent agreement, these approaches show Og to be a solid at ambient conditions with a melting point of ≈325 K. In contrast, calculations in the nonrelativistic limit reveal a melting point for Og of 220 K, suggesting a gaseous state as expected for a typical noble gas element. Accordingly, relativistic effects shift the solid‐to‐liquid phase transition by about 100 K. [ABSTRACT FROM AUTHOR]

• Dynamic programming algorithm systematically searches chromatin free energy landscape. • Free energy minimization generates folded optimal and suboptimal 2D meta-structures. • 3D structures are generated from 2D meta-structure including multipair interactions. • The method identifies the contacts that are significant in the 2D contact map. • CTCF contacts and free energy correlate strongly with regions containing euchromatin. In recent years, high-throughput techniques have revealed considerable structural organization of the human genome with diverse regions of the chromatin interacting with each other in the form of loops. Some of these loops are quite complex and may encompass regions comprised of many interacting chain segments around a central locus. Popular techniques for extracting this information are chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture (Hi-C). Here, we introduce a physics-based method to predict the three-dimensional structure of chromatin from population-averaged ChIA-PET data. The approach uses experimentally-validated data from human B-lymphoblastoid cells to generate 2D meta-structures of chromatin using a dynamic programming algorithm that explores the chromatin free energy landscape. By generating both optimal and suboptimal meta-structures we can calculate both the free energy and additionally the relative thermodynamic probability. A 3D structure prediction program with applied restraints then can be used to generate the tertiary structures. The main advantage of this approach for population-averaged experimental data is that it provides a way to distinguish between the principal and the spurious contacts. This study also finds that euchromatin appear to have rather precisely regulated 2D meta-structures compared to heterochromatin. The program source-code is available at https://github.com/plewczynski/looper. [ABSTRACT FROM AUTHOR]

Disseminating antibiotic resistance rendered by bacteria against the widely used β‐lactam antibiotics is a serious concern for public health care. The development of inhibitors for drug‐resistant β‐lactamase enzymes is vital to combat this rapidly escalating problem. Recently, the U.S. Food and Drug Administration approved a non‐β‐lactam inhibitor called avibactam for the treatment of complicated intra‐abdominal and urinary tract infections caused by drug‐resistant Gram‐negative bacteria. This work sheds light on the molecular origin of the inhibitory effect of avibactam against the drug‐resistant CTX‐M variant of class A β‐lactamases. In particular, we probed the structural evolution, dynamics features, and energetics along the acylation and deacylation reaction pathways through enhanced sampling molecular dynamics methods and free‐energy calculations. We scrutinized the roles of active site residues, the nature of the carbamoyl linkage formed in the inhibitor–enzyme covalent intermediate, and other structural features of the inhibitor molecule. By unraveling the reasons behind the inhibition of all the deacylation routes, we can explain various experimental structural and kinetics data, and propose a way to design new inhibitors based on the β‐lactam framework. [ABSTRACT FROM AUTHOR]

Ab initio molecular dynamics (AIMD) simulations employing density functional theory (DFT) and plane waves are routinely carried out using density functionals at the level of generalized gradient approximation (GGA). AIMD simulations employing hybrid density functionals are of great interest as it offers a more accurate description of structural and dynamic properties than the GGA functionals. However, the computational cost for carrying out calculations using hybrid functionals and plane wave basis set is at least two orders of magnitude higher than that using GGA functionals. Recently, we proposed a strategy that combined the adaptively compressed exchange operator formulation and the multiple time step integration scheme to reduce the computational cost by an order of magnitude [J. Chem. Phys. 151, 151102 (2019)]. In this work, we demonstrate the application of this method to study chemical reactions, in particular, formamide hydrolysis in an alkaline aqueous medium. By actuating our implementation with the well‐sliced metadynamics scheme, we can compute the two‐dimensional free energy surface of this reaction at the level of hybrid‐DFT. This work also investigates the accuracy of the PBE0 (hybrid) and the PBE (GGA) functionals in predicting the free energetics of this chemical reaction. [ABSTRACT FROM AUTHOR]

Ligand/protein binding (LPB) is a major topic in medicine, chemistry and biology. Since the advent of computers, many scientists have put efforts in developing theoretical models that could decode the alphabet of the LPB interaction. The success of this task passes by the resolution of the molecular mechanism of LPB. In the past century, major attention was dedicated to the thermodynamics of LPB, while more recent studies have revealed that ligand (un)binding kinetics is at least as important as ligand binding thermodynamics in determining the drug in vivo efficacy. In the present review, we introduce the most widely used computational methods to study LPB thermodynamics and kinetics. It is important to say that no method outperforms another, they all have pros and cons and the choice of the user should take carefully into account the system under investigation, the available structural and experimental data, and the goal of the research. A perspective on future directions of method development and research on LPB concludes the discussion. This article is categorized under:Molecular and Statistical Mechanics > Free Energy MethodsStructure and Mechanism > Computational Biochemistry and BiophysicsMolecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods [ABSTRACT FROM AUTHOR]

Bromodomains (BrDs), a conserved structural module in chromatin‐associated proteins, are well known for recognizing ε‐N‐acetyl lysine residues on histones. One of the most relevant BrDs is BRD4, a tandem BrD containing protein (BrD1 and BrD2) that plays a critical role in numerous diseases including cancer. Growing evidence shows that the two BrDs of BRD4 have different biological functions; hence selective ligands that can be used to study their functions are of great interest. Here, as a follow‐up of our previous work, we first provide a detailed characterization study of the in silico rational design of Olinone as part of a series of five tetrahydropyrido indole‐based compounds as BRD4 BrD1 inhibitors. Additionally, we investigated the molecular basis for Olinone's selective recognition by BrD1 over BrD2. Molecular dynamics simulations, free energy calculations, and conformational analyses of the apo‐BRD4‐BrD1|2 and BRD4‐BrD1|2/Olinone complexes showed that Olinone's selectivity is facilitated by five key residues: Leu92 in BrD1|385 in BrD2 of ZA loop, Asn140|433, Asp144|His437 and Asp145|Glu438 of BC loop, and Ile146|Val49 of helix C. Furthermore, the difference in hydrogen bonds number and in mobility of the ZA and BC loops of the acetyl‐lysine binding site between BRD4 BrD1/Olinone and BrD2/Olinone complexes also contribute to the difference in Olinone's binding affinity and selectivity toward BrD1 over BrD2. Altogether, our computer‐aided molecular design techniques can effectively guide the development of small‐molecule BRD4 BrD1 inhibitors, explain their selectivity origin, and further open doors to the design of new therapeutically improved derivatives. [ABSTRACT FROM AUTHOR]

The selectivity filter (SF) of bacterial voltage‐gated sodium channels consists of four glutamate residues arranged in a C4 symmetry. The protonation state population of this tetrad is unclear. To address this question, we simulate the pore domain of bacterial voltage‐gated sodium channel of Magnetococcus sp. (NavMs) through constant pH methodology in explicit solvent and free energy perturbation calculations. We find that at physiological pH the fully deprotonated as well as singly and doubly protonated states of the SF appear feasible, and that the calculated pKa decreases with each additional bound ion, suggesting that a decrease in the number of ions in the pore can lead to protonation of the SF. Previous molecular dynamics simulations have suggested that protonation can lead to a decrease in the conductance, but no pKa calculations were performed. We confirm a decreased ionic population of the pore with protonation, and also observe structural symmetry breaking triggered by protonation; the SF of the deprotonated channel is closest to the C4 symmetry observed in crystal structures of the open state, while the SF of protonated states display greater levels of asymmetry which could lead to transition to the inactivated state which possesses a C2 symmetry in the crystal structure. We speculate that the decrease in the number of ions near the mouth of the channel, due to either random fluctuations or ion depletion due to conduction, could be a self‐regulatory mechanism resulting in a nonconducting state that functionally resembles inactivated states. [ABSTRACT FROM AUTHOR]

A modified single sweep approach is proposed for generating free energy landscapes. The approach replaces the use of temperature-accelerated molecular dynamics (TAMD) to generate centres in collective variable (CV) space at which mean forces are computed using restrained molecular dynamics (MD) simulations with a sequential space-filling design. This approach also modifies the radial basis function reconstruction step of the traditional single sweep approach and proposes a weighted reconstruction of the free energy surface using the previously generated mean forces. The modified approach is compared to the traditional single sweep (SS) approach on the (φ, ψ) dihedral free-energy map of solvated alanine dipeptide (AD). It is found that the new approach results in a more accurate reconstructed free energy than does the traditional approach when compared to the directly-computed reference free energy landscape. It is shown that the increased accuracy of the overall map stems from the improved 1-dimensional space filling (projective) property of the proposed design compared to that of the TAMD generated centres. A further enhancement in the accuracy of the crucial lower energy regions is enabled by the introduction of weights in the reconstruction step that give more importance to lower energy-valued regions. [ABSTRACT FROM AUTHOR]

[Display omitted] A machine learning-derived interatomic potential coupled with the Projected Average Force Integrator (PAFI) method was utilized to examine the temperature-dependent Generalized Stacking Fault Free Energies (GSFFE) profiles across all slip systems in Mg, fully accounting for anharmonic thermal vibrations. Intrinsic Stacking Fault Free Energies (ISFFE) and Unstable Stacking Fault Free Energies (USFFE) were assessed for temperatures ranging from 0 K to 800 K, marginally below the anticipated Mg melting temperature of approximately 900 K. The findings revealed that anharmonic vibrational effects are comparable to harmonic effects for Basal slip above 200 K, approximately half the Debye temperature. Anharmonic contributions were minimal for non-basal slip systems. The USFFEs of Pyramidal-I and II slip systems are predicted to crossover around 385 K due to vibrational effects. Marginally higher ISFFEs in Pyramidal-I across all temperatures also indicate possible cross-slip or SF transformation between the systems. A comprehensive examination of slip trajectories and atomic displacements unveiled intricate atomic displacements across all Mg slip systems and complex shuffle mechanisms for non-basal slips. In addition to corroborating previously documented dislocation dissociation mechanisms for Basal, Pyramidal- 〈 a 〉 , and Pyramidal-I slips, a new dissociation mechanism was discerned for dislocation slip in Pyramidal-II. This study offers crucial insights into the temperature-dependent behavior of SFFEs in Mg, the significance of intrinsic anharmonic thermal contributions to Basal slip, and the intricate atomic displacements and dissociation mechanisms of hexagonal close packed slip systems. [ABSTRACT FROM AUTHOR]

[Display omitted] • Molecular dynamics and free energy simulations revealed the hindering role of mineral surface hydration structure; • Hydrophobic coating of both the nanoparticles and the iron oxide surfaces is essential for selective adhesion; • Tuning the degree of surface coverage by oleate can lead to better nanoparticle-surface interactions; • Magnetic separation experiments of iron ore ultrafines validated the molecular-level analyses meeting experiment–theory nexus. Magnetic nanoparticles have diverse scientific and technological applications, as their properties can be tuned accordingly. An example is the selective magnetic coating technique for the selective adsorption of these colloidal particles on the surface of iron minerals to improve recovery of fines by magnetic separation. Thus, fundamental physicochemical knowledge of such systems is of paramount importance. Herein, we investigate the adsorption of magnetite nanoparticles on mineral surfaces and the impact of hydrophobic coating on the adsorption process and magnetic separation. We present structural and thermodynamic characterizations from molecular dynamics and free energy simulations to rationalize the differences in association process in both native and coated particle conditions. We demonstrate that hydrophobic coating of both nanoparticle and target iron oxide surfaces is essential for selective adhesion, revealed by ΔG. Also, tuning the degree of surface coverage by oleate leads to better interactions then simply establishing a monolayer coating, because of interdigitation of adsorption layers allowing higher contact area, shorter interparticle distance and less oleate consumption. Magnetic separation experiments of ultrafine iron ore particles under different oleate and colloidal magnetite concentrations validated the molecular level analyses, thus achieving successful experiment–theory nexus based on a sound theoretical background explored beforehand by computational simulations. [ABSTRACT FROM AUTHOR]

Background: Solubility is a physical property of high importance to the pharmaceutical industry, the prediction of which for potential drugs has so far been a hard task. We attempted to predict the solubility of acetylsalicylic acid (ASA) by estimating the absolute chemical potentials of its most stable polymorph and of solutions with different concentrations of the drug molecule. Methods: Chemical potentials were estimated from all-atom molecular dynamics simulations. We used the Einstein molecule method (EMM) to predict the absolute chemical potential of the solid and solvation free energy calculations to predict the excess chemical potentials of the liquid-phase systems. Results: Reliable estimations of the chemical potentials for the solid and for a single ASA molecule using the EMM required an extremely large number of intermediate states for the free energy calculations, meaning that the calculations were extremely demanding computationally. Despite the computational cost, however, the computed value did not agree well with the experimental value, potentially due to limitations with the underlying energy model. Perhaps better values could be obtained with a better energy model; however, it seems likely computational cost may remain a limiting factor for use of this particular approach to solubility estimation. Conclusions: Solubility prediction of drug-like solids remains computationally challenging, and it appears that both the underlying energy model and the computational approach applied may need improvement before the approach is suitable for routine use.

Pharmacological and physicochemical studies of N-unsubstituted indazole-5-carboxamides (subclass I) and their structurally optimised N1-methylated analogues (subclass II), initially developed as drug and radioligand candidates for the treatment and diagnosis of Parkinson’s disease (PD), are presented. The compounds are highly brain permeable, selective, reversible, and competitive monoamine oxidase B (MAO-B) inhibitors with improved water-solubility and subnanomolar potency (pIC50 >8.8). Using a well-validated, combined X-ray/modelling technology platform, we performed a semi-quantitative analysis of the binding modes of all compounds and investigated the role of the indazole N1 position for their MAO-B inhibitory activity. Moreover, compounds NTZ-1006, 1032, and 1441 were investigated for their ability to bind Fe2+ and Fe3+ ions using UV-visible spectroscopy.

Background: Variations in the sequence of linker histone (LH) H1 play an important role in the modulation of chromatin functioning. Meanwhile, an effect of LH variations on the chromatin structure remains unclear. The most common mutations of the core histones are located in their globular domains (GD) and many of them coincide with post-translational modifications (PTM) sites. It is known that five mutations in GD of Drosophila H1 can change LH position in the chromatosome from “off-dyad” to “on-dyad. Given polymorphism of chromatosome structure, an investigation of the effect of different LH variants on the chromatosome structure is extremely relevant. Methods: Amino acid sequences of human LH H1.2, H1.4, and H1.5 were obtained from HistoneDB database. For homology modeling, the crystal structure of the chromatosome was used (PDB ID 4qlc) as a template. Post-translational modifications in the globular domain of linker histone H1, listed in the UniProt database, were considered for analysis. In order to analyze potential driver mutations, oncomutations of LH that were reported in the COSMIC database more than once were analyzed. Using FoldX software based on an empirical force field we measured the difference in binding free energy between the two states.:For PTMs that could not be handled by FoldX, the screening of their positions for potential steric constraints was done using UCSF Chimera by changing the torsion angles of the modified side chains. Results: Using FoldX we have estimated binding energy differences for 45 missense oncomutations and 27 PTM of human LH H1.2, H1.4 and H1.5. Oncomutations S58F and S104F of LH H1.2 manifested significant binding energy changes (2.33 and 4.10 kcal/mol, respectively). These energies, however, are less than the experimentally measured free energy of dissociation of H1 in the presence of 0.2 M NaCl, which is 8.5 kcal/mol. Screening of PTM position allowed us to select variations of LH H1, which increase or decrease stability of the chromatosome. Conclusion: We estimated the effect of PTM and oncomutations in GD of human LH on the chromatosome stability. PTM sites, in which additional positioning contacts between DNA and LH emerged, were determined. On the basis of the analysis, we can suggest that certain LH oncomutations may considerably change its binding affinity to nucleosome, potentially, affecting chromatin structure.

Many membrane proteins are sensitive to their local lipid environment. As structural methods for membrane proteins have improved, there is growing evidence of direct, specific binding of lipids to protein surfaces. Unfortunately the workhorse of understanding protein-small molecule interactions, the binding affinity for a given site, is experimentally inaccessible for these systems. Coarse-grained molecular dynamics simulations can be used to bridge this gap, and are relatively straightforward to learn. Such simulations allow users to observe spontaneous binding of lipids to membrane proteins and quantify localized densities of individual lipids or lipid fragments. In this chapter we outline a protocol for extracting binding affinities from these localized distributions, known as the "density threshold affinity." The density threshold affinity uses an adaptive and flexible definition of site occupancy that alleviates the need to distinguish between "bound'' lipids and bulk lipids that are simply diffusing through the site. Furthermore, the method allows "bead-level" resolution that is suitable for the case where lipids share binding sites, and circumvents ambiguities about a relevant reference state. This approach provides a convenient and straightforward method for comparing affinities of a single lipid species for multiple sites, multiple lipids for a single site, and/or a single lipid species modeled using multiple forcefields., (Copyright © 2024. Published by Elsevier Inc.)

Protein-protein binding affinity prediction is important for understanding complex biochemical pathways and to uncover protein interaction networks. Quantitative estimation of the binding affinity changes caused by mutations can provide critical information for protein function annotation and genetic disease diagnoses. The binding free energies of protein-protein complexes can be predicted using several computational tools. This chapter is a summary of software developed for the prediction of binding free energies for protein-protein complexes and their mutants., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Glycosaminoglycans (GAGs) are a class of long linear anionic periodic polysaccharides. Their biological activities are very broad including tissue remodeling, regulation of cell proliferation, cell migration, cell differentiation, participation in bacterial/viral infections, and immune response. They can interact with many important biomolecular partners in the extracellular matrix of the cell including small drug molecules. Recently, several GAG-bioactive small molecule complexes have been experimentally and theoretically studied. Some of these compounds in complexes with GAGs may potentially interfere with protein-GAG or peptide-GAG multimolecular systems affecting the processes of cellular differentiation or have anti-inflammatory, antiviral as well as antithrombotic effects. Although many studies have been conducted on GAG-drug complexes, the molecular mechanisms of the formation of such complexes are still poorly understood. At the same time, the complexity of their physicochemical properties renders the use of both experimental and computational methods to study these molecular systems challenging. Here, we present the molecular dynamics-based protocols successfully employed to in silico analyze GAG-small molecule interactions., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, characterized by a gradual and steady deterioration in cognitive function over time. At least 50 million people worldwide are considered to have AD or another form of dementia. AD is marked by a gradual decline in cognitive abilities, memory deterioration and neurodegenerative transformations within the brain. The intricate and multifaceted nature of polygenic AD presents significant challenges within the landscape of drug development. The pathophysiology of AD unfolds in a non-linear and dynamic pattern, encompassing various systems and giving rise to a multitude of factors and hypotheses that contribute to the disease's onset. These encompass theories such as the beta-amyloid hypothesis, cholinergic hypothesis, tau hypothesis, oxidative stress and more. In the realm of drug development, polypharmacological drug profiles have emerged as a strategy that can yield combined or synergistic effects, effectively mitigating undesirable side effects and significantly enhancing the therapeutic efficacy of essential medications. With this concept in mind, our in-silico study sought to delve into the binding interactions of a diverse array of colchicine derivative compounds. These derivatives are chosen for their potential anti-inflammatory, antioxidant, anti-neurodegenerative and neuroprotective properties against Alzheimer's and other neurodegenerative diseases. We investigated compound interactions with AD-related targets, utilizing comprehensive molecular docking and dynamic simulations. COM111X showed impressive docking with acetylcholinesterase, indicating potential as an anti-Alzheimer's drug. COM112Y displayed strong docking scores with PDE4D and butyrylcholinesterase, suggesting dual inhibition for Alzheimer's treatment. Further in vitro and in vivo studies are warranted to explore these findings.Communicated by Ramaswamy H. Sarma.

Cancer is enlisted among the deadliest disease all over the world. The cyclin-dependent kinases 12 and 13 have been identified as cell cycle regulators. They conduct transcription and co-transcriptional processes by phosphorylating the C-terminal of RNA polymerase-II. Inhibition of CDK12 and 13 selectively presents a novel strategy to treat triple-negative breast cancer, but dual inhibitors are still lacking. Here, we report the screening of the natural product compound class against the dual CDK12/13 enzyme by employing various in silico methods. Complexes of CDK12 enzymes are used to form common feature pharmacophore models, whereas we perform receptor-based pharmacophore modelling on CDK13 enzyme owing to the availability of a single PDB. On conducting screening over the representative pharmacophores, the common drug-like screened natural products were shortlisted for conducting molecular docking studies. After molecular docking calculations, the candidates that showed crucial interaction with CDK12 and CDK13 enzymes were shortlisted for simulation studies. Five common docked candidates were selected for molecular dynamics simulations and free energy calculations. Based on the cut-off criteria of free energy calculations, one common hit was selected as the dual CDK12/13 inhibitor. The outcome concluded that the hit with ID CNP0386383 possesses drug-like properties, displays crucial interaction in the binding pocket, and shows stable dynamic behaviour and higher binding energy than the experimentally reported inhibitor of both CDK12 and CDK13 enzymes.Communicated by Ramaswamy H. Sarma.

Using the D3R Grand Challenge 4 dataset containing Beta-secretase 1 (BACE) and Cathepsin S (CatS) inhibitors, we have evaluated the performance of our in-house docking workflow that involves in the first step the selection of the most suitable docking software for the system of interest based on structural and functional information available in public databases, followed by the docking of the dataset to predict the binding modes and ranking of ligands. The macrocyclic nature of the BACE ligands brought additional challenges, which were dealt with by a careful preparation of the three-dimensional input structures for ligands. This provided top-performing predictions for BACE, in contrast with CatS, where the predictions in the absence of guiding constraints provided poor results. These results highlight the importance of previous structural knowledge that is needed for correct predictions on some challenging targets. After the end of the challenge, we also carried out free energy calculations (i.e. in a non-blinded manner) for CatS using the pmx software and several force fields (AMBER, Charmm). Using knowledge-based starting pose construction allowed reaching remarkable accuracy for the CatS free energy estimates. Interestingly, we show that the use of a consensus result, by averaging the results from different force fields, increases the prediction accuracy. [ABSTRACT FROM AUTHOR]

Mutations can be induced by environmental factors but also arise spontaneously during DNA replication or due to deamination of methylated cytosines at CpG dinucleotides. Sites where mutations occur with higher frequency than would be expected by chance are termed hotspots while sites that contain mutations rarely are termed coldspots. Mutations are permanently scanned and repaired by repair systems. Among them, the mismatch repair targets base pair mismatches, which are discriminated from canonical base pairs by probing altered elasticity of DNA. Using biased molecular dynamics simulations, we investigated the elasticity of coldspots and hotspots motifs detected in human genes associated with inherited disorders, and also of motifs with Czech population hotspots and de novo mutations. Main attention was paid to mutations leading to G/T and A+/C pairs. We observed that hotspots without CpG/CpHpG sequences are less flexible than coldspots, which indicates that flexible sequences are more effectively repaired. In contrary, hotspots with CpG/CpHpG sequences exhibited increased flexibility as coldspots. Their mutability is more likely related to spontaneous deamination of methylated cytosines leading to C > T mutations, which are primarily targeted by base excision repair. We corroborated conclusions based on computer simulations by measuring melting curves of hotspots and coldspots containing G/T mismatch. [ABSTRACT FROM AUTHOR]

Two calix[4]resorcinarenes, which differ in the length of the alkyl chain on the methylene bridge between the aromatic rings, have been embedded in unilamellar liposomes prepared from 1-palmitoyl-2-oleoyl- sn -glycerol-3-phosphocholine in three host/guest ratios, following two different procedures. The effect of the insertion of the guests has been evaluated through the measurements of the viscosity and the kinetic stability of the liposomal systems by means of the fluorescent probes pyrene and 5(6)-carboxyfluorescein. The presence of the guests reduces the viscosity of the liposomes, suggesting a modification of the bilayer structure. However, this does not affect liposome stability. A calix[4]resorcinarene cavitand with a more rigid conformation compared to the parent resorcinarene, has been also synthetized and embedded in liposomes. The free energy of the insertion of the substrates in the lipid bilayer has been evaluated through Molecular Dynamics simulations. Unlabelled Image • Calix[4]resorcinarenes can be embedded in POPC liposomes. • They interact with bilayer phospholipids at differently, depending of their molecular structure and the preparation protocol. • Calix[4]resorcinarenes enhance the kinetic stability of the liposomes. • The resorcinarene cavitand increases the viscosity and decreases the stability of liposomes. [ABSTRACT FROM AUTHOR]

Thioredoxin is a protein that has been used as model system by various computational methods to predict the pKa of aspartate residue Asp26 which is 3.5 units higher than a solvent exposed one (eg, Asp20). Here, we use extensive atomistic molecular dynamics simulations of two different protonation states of Asp26 in combination with conformational analysis based on RMSD clustering and principle component analysis to identify representative conformations of the protein in solution. For each conformation, the Gibbs free energy of proton transfer between Asp26 and Asp20, which is fully solvated in a loop region of the protein, is calculated with the Amber99sb force field in alchemical transformations. The varying polarization of the two residues in different molecular environments and protonation states is described by Hirshfeld‐I (HI) atomic charges obtained from the averaged polarized electron density. Our results show that the Gibbs free energy of proton transfer is dependent on the protein conformation, the proper sampling of the neighboring Lys57 residue orientations and on water molecules entering the hydrophobic cavity upon deprotonating Asp26. The inclusion of the polarization of both aspartate residues in the free energy cycle by HI atomic charges corrects the results from the non‐polarizable force field and reproduces the experimental ΔpKa value of Asp26. [ABSTRACT FROM AUTHOR]

4‐Hydroxyphenylpyruvate dioxygenase (HPPD) catalyzes the second reaction in the tyrosine catabolism and is linked to the production of cofactors plastoquinone and tocopherol in plants. This important biological role has put HPPD in the focus of current herbicide design efforts including the development of herbicide‐tolerant mutants. However, the molecular mechanisms of substrate binding and herbicide tolerance have yet to be elucidated. In this work, we performed molecular dynamics simulations and free energy calculations to characterize active site gating by the C‐terminal helix H11 in HPPD. We compared gating equilibria in Arabidopsis thaliana (At) and Zea mays (Zm) wild‐type proteins retrieving the experimentally observed preferred orientations from the simulations. We investigated the influence of substrate and product binding on the open–closed transition and discovered a ligand‐mediated conformational switch in H11 that mediates rapid substrate access followed by active site closing and efficient product release through H11 opening. We further studied H11 gating in At mutant HPPD, and found large differences with correlation to experimentally measured herbicide tolerance. The computational findings were then used to design a new At mutant HPPD protein that showed increased tolerance to six commercially available HPPD inhibitors in biochemical in vitro experiments. Our results underline the importance of protein flexibility and conformational transitions in substrate recognition and enzyme inhibition by herbicides. [ABSTRACT FROM AUTHOR]

Abstract Prolyl oligopeptidase (POP) is a potential therapeutic target for treatment of several neurological disorders and α-synucleinopathies including Parkinson's disease. Most of the known POP inhibitors failed in the clinical trials due to poor pharmacokinetic properties and blood-brain impermeability. Therefore, a training set of 30 structurally diverse compounds with a wide range of inhibitory activity against POP was used to generate a quantitative pharmacophore model, Hypo 3, to identify potential POP inhibitors with desirable drug-like properties. Validations through test set, cost analysis, and Fisher's randomization methods proved that Hypo 3 accurately predicted the known inhibitors among inactive compounds. Hypo 3 was employed as 3D query for virtual screening on an in-house drug-like chemical database containing compounds with good brain permeability and ADMET parameters. Database screening with Hypo 3 resulted in 99 compounds that were narrowed down to 21 compounds through molecular docking. Among them, five compounds were identified in our earlier studies, while two compounds showed in vitro POP inhibition. The current study proposed new 16 virtually screened compounds as potential inhibitors against POP that possess Gold docking score in the range of 64.61–75.74 and Chemscore of −32.25 to −38.35. Furthermore, the top scoring four hit compounds were subjected to molecular dynamics simulations to reveal their appropriate binding modes and assessing binding free energies. The hit compounds interacted with POP effectively via hydrogen bonds with important active site residues along with hydrophobic interactions. Moreover, the hit compounds had key inter-molecular interactions and better binding free energies as compared to the reference inhibitor. A potential new hydrogen bond interaction was discovered between Hit 2 with the Arg252 residue of POP. To conclude, we propose four hit compounds with new structural scaffolds against POP for the lead development of POP-based therapeutics for neurological disorders. Graphical abstract Image 1 Highlights • Ten 3D QSAR models were generated from known POP inhibitors. • Hypo 3 model distinguished active compounds from inactive as validation. • Virtual screening of in-house database with Hypo 3 obtained 16 potential compounds. • Four hit compounds effectively bound to POP with relatively better binding energies. • A new hydrogen bonding interaction was discovered with Hit 2 and Arg252 of POP. [ABSTRACT FROM AUTHOR]

• Comprehensive review of modelling studies of monoamine transporters. • Covers methods from molecular docking to advanced MD simulations. • Presenting future directions with complex lipids mixtures. • Simple explanations of advanced methods for protein modelling. The field of molecular mechanics studies of proteins has developed enormously since its origin in the 1970's, and many applications and methodologies have branched from the original idea of the force field. The applications of such methodologies are far spread and commonplace in neuroscience research today. In this mini-review, we outline the main methodologies applied when studying events ranging from ligands binding within small binding sites, through overall large-scale conformational changes, to the even larger-scale oligomerization events of neurological membrane proteins. The limitations and caveats of the methods are discussed, while examples of recent applications are described and their implications discussed. We have chosen to focus on the monoamine transporters throughout, with a few examples from neurological membrane proteins such as ionotropic and metabotropic neurotransmitter receptors. [ABSTRACT FROM AUTHOR]

The long-ranged nature of the Coulomb potential requires a proper accounting for the influence of even distant electrostatic boundaries in the determination of the solvation free energy of a charged solute. We introduce an exact rewriting of the free energy change upon charging a solute that explicitly isolates the contribution from these boundaries and quantifies the impact of the different boundaries on the free energy. We demonstrate the importance and advantages of appropriately referencing the electrostatic potential to that of the vacuum through the study of several simple model charge distributions, for which we can isolate an analytic contribution from the boundaries that can be readily evaluated in computer simulations of molecular systems. Finally, we highlight that the constant potential of the bulk dielectric phase—the Bethe potential—cannot contribute to the solvation thermodynamics of a single charged solute when the charge distributions of the solvent and solute do not overlap in relevant configurations. But when the charge distribution of a single solute can overlap with the intramolecular charge distribution of solvent molecules, as is the case in electron holography, for example, the Bethe potential is needed when comparing to experiment. Our work may also provide insight into the validity of "extra thermodynamic assumptions" traditionally made during the experimental determination of single ion solvation free energies. [ABSTRACT FROM AUTHOR]

Predicting the preferred orientation of a ligand to a receptor and the free energy (ΔGAB) of these molecules in a solution is very useful for pharmaceutical applications. In this work, ΔGAB between chitosan and quercetin molecules with water were obtained by the thermodynamic integration (TI) method and the chitosan+quercetin complex was investigated by Molecular Docking (MDK). The topology of the molecules was compatible with the CHARMM force-field. Both molecules were solvated with the GROMACS SPC water model. The ΔGAB values of the molecule+water systems with the thermodynamic integration (TI) method was done in a 10 ns simulation. The complex was achieved in a 2.5 nm x 2.5 nm x 2.5 nm box. The ΔGAB values for the molecules+water systems were 14.36 +/- 0.46 and 0.19 +/- 0.53 kJ/mol, respectively. For the complex, nine conformations were obtained for the quercetin around the chitosan. The best conformation showed an affinity energy of -3.8 kcal/mol. The ΔGAB results for the systems confirm the low or no solubility of the molecules in the water under normal conditions, as already demonstrated experimentally. The docking showed that the interaction between chitosan and quercetin molecules involves hydrogen bonds in a specific position. [ABSTRACT FROM AUTHOR]

Free energies play a determining role in the transmembrane permeability of lipid bilayers to small molecules. The precision of the calculated free energies, in particular, can seriously affect the reliability of simulations of permeation events. Free energy profiles are evaluated with different known techniques for a water molecule inside a hydrated bilayer in order to assess the accuracy and precision of free energy calculations as well as the associated computational cost within the popular Groningen Machine for Chemical Simulations (GROMACS) software package. The different computational approaches employed include the method of constrained particles, umbrella sampling and thermodynamic integration. When free energy profiles computed from MD trajectories of similar timescales are compared, umbrella sampling is found to afford the best precision among the methods investigated, albeit at the expense of computational effort. [ABSTRACT FROM AUTHOR]

Fixed-charge force fields are a common choice for modelling solvents, many of which have been optimised around pure-component property predictions. Their use for modelling solvent mixtures, however, is questionable as the charge distribution of a molecule in the pure component and infinite dilution limits are expected to be different. Due to the small system sizes and simulation times typically used, it is not possible to observe phase-splitting in a molecular simulation. Here, we propose and demonstrate the efficient use of limiting activity coefficients computed using the conventional solvation free energy calculations in the infinite dilution and pure-component limits to evaluate whether or not the resulting solution is miscible. We demonstrate the application for binary aqueous systems with the following cosolvents: methanol, ethanol, 2-propanol, acetone and 1,4-dioxane. We find that the binary mixture of TIP4P water and TraPPE-UA 2-propanol is only partially miscible, as confirmed from detailed free energy analysis. One needs to take care when taking force fields off the shelf and applying them to model mixtures. The proposed strategy is general and not limited to molecular simulations with fixed-charge force fields, and we demonstrate its use with electronic structure calculations with the solvation model based on density continuum solvation model. [ABSTRACT FROM AUTHOR]

Abstract Electroporation or electropermeabilization is a technique that enables transient increase in the cell membrane permeability by exposing cells to pulsed electric field. However, the molecular mechanisms of the long-lived cell membrane permeability, which persists on the minutes time scale after the pulse treatment, remain elusive. Experimental studies have suggested that lipid peroxidation could present a mechanism of this prolonged membrane permeabilization. In this study we make the first important step in quantifying the possible contribution of lipid peroxidation to electropermeabilization. We use free energy calculations to quantify the permeability and conductance of bilayers, containing an increasing percentage of hydroperoxide lipid derivatives, to sodium and chloride ions. We then compare our calculations to experimental measurements on electropermeabilized cells. Our results show that the permeability and conductance increase dramatically by several orders of magnitude in peroxidized bilayers. Yet this increase is not sufficient to reasonably account for the entire range of experimental measurements. Nevertheless, lipid peroxidation might be considered an important mechanism of prolonged membrane permeabilization, if exposure of cells to high voltage electric pulses leads to secondary lipid peroxidation products. Our analysis calls for experimental studies, which will determine the type and amount of lipid peroxidation products in electropermeabilized cell membranes. Highlights • Na and Cl ions permeability of peroxidized lipid bilayers is investigated using Unified Free Energy Dynamics simulations. • The contribution of lipid peroxidation to electropermeabilization is quantitatively assessed. • High amounts of peroxidized lipids increase the bilayers permeability and conductance by several orders of magnitude. • Hydroperoxide lipid derivatives are not permeable enough to account for the measured electropermeabilization of cells. [ABSTRACT FROM AUTHOR]

During the last few years, we have developed a docking protocol involving two steps: (i) the choice of the most appropriate docking software and parameters for the system of interest using structural and functional information available in public databases (PDB, ChEMBL, PubChem Assay, BindingDB, etc.); (ii) the docking of ligand dataset to provide a prediction for the binding modes and ranking of ligands. We applied this protocol to the D3R Grand Challenge 3 dataset containing cathepsin S (CatS) inhibitors. Considering the size and conformational flexibility of ligands, the docking calculations afforded reasonable overall pose predictions, which are however dependent on the specific nature of each ligand. As expected, the correct ranking of docking poses is still challenging. Post-processing of docking poses with molecular dynamics simulations in explicit solvent provided a significantly better prediction, whereas free energy calculations on a subset of compounds brought no significant improvement in the ranking prediction compared with the direct ranking obtained from the scoring function. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract The discipline of drug discovery has greatly benefited by computational tools and in silico algorithms aiming at rationalization of many related processes, from the stage of early hit identification to the preclinical phases of drug candidate validation. The various methodologies referred to as molecular modeling tools span a broad spectrum of applications, from straightforward approaches such as virtual screening of compound libraries to more advanced techniques involving the precise estimation of free energy upon binding of the candidate drug to its macromolecular target. To this end, we report an overview of specific studies where implementation of such sophisticated modeling algorithms has shown to be indispensable for addressing challenging systems and biological questions otherwise difficult to answer. We focus our attention on the emerging field of bromodomain inhibitors. Bromodomains are small modules involved in epigenetic signaling and currently comprise high-priority targets for developing both drug candidates and chemical probes for basic biomedical research. We attempt a critical presentation of selected cases utilizing cutting-edge in silico methodologies, with our main emphasis being on absolute or relative free energy simulations, on implementation of quantum-mechanics level calculations and on characterization of solvent thermodynamics. We discuss the advantages and strengths as well as the drawbacks and weaknesses of computational tools utilized in those works and we attempt to comment on specific issues related to their integration into the regular medicinal chemistry practice. Our conclusion is that while such methods indeed represent highly promising resources for further advancing the discipline, their application is not always trivial. [ABSTRACT FROM AUTHOR]

Abstract Understanding the molecular determinants for recognition, binding and transport of antibiotics by multidrug efflux systems is important for basic research and useful for the design of more effective antimicrobial compounds. Imipenem and meropenem are two carbapenems whose antibacterial activity is known to be poorly and strongly affected by MexAB-OprM, the major efflux pump transporter in Pseudomonas aeruginosa. However, not much is known regarding recognition and transport of these compounds by AcrAB-TolC, which is the MexAB-OprM homologue in Escherichia coli and by definition the paradigm model for structural studies on efflux pumps. Prompted by this motivation, we unveiled the molecular details of the interaction of imipenem and meropenem with the transporter AcrB by combining computer simulations with biophysical experiments. Regarding the interaction with the two main substrate binding regions of AcrB, the so-called access and deep binding pockets, molecular dynamics simulations revealed imipenem to be more mobile than meropenem in the former, while comparable mobilities were observed in the latter. This result is in line with isothermal titration calorimetry, differential scanning experiments, and binding free energy calculations, indicating a higher affinity for meropenem than imipenem at the deep binding pocket, while both sharing similar affinities at the access pocket. Our findings rationalize how different physico-chemical properties of compounds reflect on their interactions with AcrB. As such, they constitute precious information to be exploited for the rational design of antibiotics able to evade efflux pumps. Graphical abstract Unlabelled Image Highlights • Recognition and transport of carbapenems by AcrB is still under debate. • Binding position of carbapenems rather than their orientation affects extrusion. • Chemical nature of β-lactams affects their affinity and mobility inside the transporter. • MER could be more likely a substrate of AcrB than IMI, similarly to MexB. [ABSTRACT FROM AUTHOR]

CD4-mimetic HIV-1 entry inhibitors are small sized molecules which imitate similar conformational flexibility, in gp120, to the CD4 receptor. However, the mechanism of the conformational flexibility instigated by these small sized inhibitors is little known. Likewise, the effect of the antibody on the function of these inhibitors is also less studied. In this study, we present a thorough inspection of the mechanism of the conformational flexibility induced by a CD4-mimetic inhibitor, NBD-557, using Molecular Dynamics Simulations and free energy calculations. Our result shows the functional importance of Asn425 in substrate induced conformational dynamics in gp120. The MD simulations of Asn425Gly mutant provide a less dynamic gp120 in the presence of NBD-557 without incapacitating the binding enthalpy of NBD-557. The MD simulations of complexes with the antibody clearly show the enhanced affinity of NBD-557 due to the presence of the antibody, which is in good agreement with experimental Isothermal Titration Calorimetry results (Biochemistry2006, 45, 10973–10980).

Background: Solubility is a physical property of high importance to the pharmaceutical industry, the prediction of which for potential drugs has so far been a hard task. We attempted to predict the solubility of acetylsalicylic acid (ASA) by estimating the absolute chemical potentials of its most stable polymorph and of solutions with different concentrations of the drug molecule. Methods: Chemical potentials were estimated from all-atom molecular dynamics simulations. We used the Einstein molecule method (EMM) to predict the absolute chemical potential of the solid and solvation free energy calculations to predict the excess chemical potentials of the liquid-phase systems. Results: Reliable estimations of the chemical potentials for the solid and for a single ASA molecule using the EMM required an extremely large number of intermediate states for the free energy calculations, meaning that the calculations were extremely demanding computationally. Despite the computational cost, however, the computed value did not agree well with the experimental value, potentially due to limitations with the underlying energy model. Perhaps better values could be obtained with a better energy model; however, it seems likely computational cost may remain a limiting factor for use of this particular approach to solubility estimation. Conclusions: Solubility prediction of drug-like solids remains computationally challenging, and it appears that both the underlying energy model and the computational approach applied may need improvement before the approach is suitable for routine use.

We present a molecular dynamics simulation study of alkali metal cation transport through the double‐helical and the head‐to‐head conformers of the gramicidin ion channel. Our approach is based on a thermodynamic integration network, which consists of a sequence of transport reactions, absolute free energies of solvation and cycles of alchemical transmutations of the ions. In this manner, we can reliably estimate free energies and their statistical errors via a least‐squares method without imposing external forces on the system. Within the double helical channel, we find a free energy surface typical for hopping transport between isoenergetic sites of ion localization, separated by comparatively large activation barriers. For fast transport through the head‐to‐head conformation, the thermodynamic network scheme starts to break down. © 2018 Wiley Periodicals, Inc. Ion migration in the gramicidin protein channel is simulated using a thermodynamic integration network, which consists of transport reactions, absolute free energies of solvation and alchemical transmutations of ions. For a double helical channel, we find a free energy surface typical for hopping transport between isoenergetic sites of ion localization, whereas the scheme starts to break down for fast transport through a head‐to‐head conformation. [ABSTRACT FROM AUTHOR]

Abstract The putative mechanism by which bacterial RND-type multidrug efflux pumps recognize and transport their substrates is a complex and fascinating enigma of structural biology. How a single protein can recognize a huge number of unrelated compounds and transport them through one or just a few mechanisms is an amazing feature not yet completely unveiled. The appearance of cooperativity further complicates the understanding of structure-dynamics-activity relationships in these complex machineries. Experimental techniques may have limited access to the molecular determinants and to the energetics of key processes regulating the activity of these pumps. Computer simulations are a complementary approach that can help unveil these features and inspire new experiments. Here we review recent computational studies that addressed the various molecular processes regulating the activity of RND efflux pumps. [ABSTRACT FROM AUTHOR]

Partition coefficients serve in various areas as pharmacology and environmental sciences to predict the hydrophobicity of different substances. Recently, they have also been used to address the accuracy of force fields for various organic compounds and specifically the methylated DNA bases. In this study, atomic charges were derived by different partitioning methods (Hirshfeld and Minimal Basis Iterative Stockholder) directly from the electron density obtained by electronic structure calculations in a vacuum, with an implicit solvation model or with explicit solvation taking the dynamics of the solute and the solvent into account. To test the ability of these charges to describe electrostatic interactions in force fields for condensed phases, the original atomic charges of the AMBER99 force field were replaced with the new atomic charges and combined with different solvent models to obtain the hydration and chloroform solvation free energies by molecular dynamics simulations. Chloroform–water partition coefficients derived from the obtained free energies were compared to experimental and previously reported values obtained with the GAFF or the AMBER‐99 force field. The results show that good agreement with experimental data is obtained when the polarization of the electron density by the solvent has been taken into account, and when the energy needed to polarize the electron density of the solute has been considered in the transfer free energy. These results were further confirmed by hydration free energies of polar and aromatic amino acid side chain analogs. Comparison of the two partitioning methods, Hirshfeld‐I and Minimal Basis Iterative Stockholder (MBIS), revealed some deficiencies in the Hirshfeld‐I method related to the unstable isolated anionic nitrogen pro‐atom used in the method. Hydration free energies and partitioning coefficients obtained with atomic charges from the MBIS partitioning method accounting for polarization by the implicit solvation model are in good agreement with the experimental values. © 2018 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]