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Lipoxygenases (LOXs) are a family of enzymes that catalyze the highly specific hydroperoxidation of polyunsaturated fatty acids, such as arachidonic acid. Different stereo- or/and regioisomer hydroperoxidation products lead later to different metabolites that exert opposite physiological effects in the animal body and play a central role in inflammatory processes. The Gly-Ala switch of a single residue is crucial for the stereo- and regiocontrol in many lipoxygenases. Herein, we have combined molecular dynamics simulations with quantum mechanics/molecular mechanics calculations to study the hydrogen abstraction step and the molecular oxygen addition step of the hydroperoxidation reaction of arachidonic acid catalyzed by both wild-type Coral 8R-LOX and its Gly427Ala mutant. We have obtained a detailed molecular understanding of this Ala-versus-Gly concept. In wild type, molecular oxygen adds to C8 of arachidonic acid with an R stereochemistry. In the mutant, Ala427 pushes Leu385, blocks the region over C8, and opens an oxygen access channel now directed to C12, where molecular oxygen is added with an S stereochemistry. Thus, the specificity turns out to be dramatically inverted. Since Leu385 is highly conserved among many lipoxygenase isoforms, this mechanism can be general, and we propose that the presence of such type of bulky and hydrophobic residues can be key in controlling the extreme regio- and stereospecificity of lipoxygenases and, as a consequence, their physiological effects., Ministerio de Economı́a y Competitividad, EPSRC, EC, UAB-Banco Santander Program, Depto. de Química Física, Fac. de Ciencias Químicas, TRUE, pub

The RNA dependent RNA polymerase (RdRp) in SARS-CoV-2, the virus responsible forthe COVID-19 pandemic, is a highly conserved enzyme responsible for viral genome repli- cation/transcription. While there are many SARS-CoV-2 variants, the RdRp protein has remained relatively conserved, making it an attractive target for antiviral drugs. This dis- sertation investigates the nucleotide addition cycle (NAC) and nucleotide selectivity during the viral RdRp elongation, focusing on an early stage of the cycle from initial nucleotide sub- strate binding (enzyme active site open) to rate-limiting insertion states (active site closed). This is in contrast to common computational or modeling works which examine a generic one-step substrate binding process. The interactions of the RdRp with representative incom- ing nucleoside triphosphates (NTPs) are studied: cognate ATP, RDV-TP (a drug analogue to ATP), non-cognates dATP and GTP, according to RNA template uracil. Ensemble equi- librium all-atom molecular dynamics (MD) simulations have been employed to explore the configuration space of each NTP in two kinetic states (open and closed). Due to the expected millisecond conformational change (from the open to closed) accompanying nucleotide in- sertion and selection, enhanced sampling methods have been conducted to calculate the free energy profiles or potentials of mean force (PMFs) of the NTP’s. The analyses reveal a marked difference in the stabilization of cognate ATP and the RDV-TP analog versus non- cognate dATP and GTP. Upon initial binding and subsequent insertion, ATP and RDV-TP show marginal free energy barriers, whereas dATP and GTP show substantial stabilization upon initial binding followed by notably high barriers for insertion into the active site. This pattern suggests an intrinsic mechanism of nucleotide selectivity in RdRp that rejects non- cognate NTPs. Specifically, ATP and RDV-TP, which are selected for incorporation, are favored in the closed or insertion stat

Toll-like receptors (TLRs), classified as pattern recognition receptors, have a primordial role in the activation of the innate immunity. In particular, TLR4 binds to lipopolysaccharides (LPS), a membrane constituent of Gram-negative bacteria, and, together with Myeloid Differentiation factor 2 (MD-2) protein, forms a heterodimeric complex which leads to the activation of the innate immune system response. Identification of TLRs has sparked great interest in the therapeutic manipulation of the innate immune system. In particular, TLR4 antagonists may be useful for the treatment of septic shock, certain autoimmune diseases, noninfectious inflammatory disorders, and neuropathic pain, and TLR4 agonists are under development as vaccine adjuvants in antitumoral treatments. Therefore, TLR4 has risen as a promising therapeutic target, and its modulation constitutes a highly relevant and active research area. Deep structural understanding of TLR4 signaling may help in the design and discovery of TLR4-modulating molecules with desirable therapeutic properties. Computational studies of the different independent domains composing the TLR4 were undertaken, to understand the differential domain organization of TLR4 in aqueous and membrane environments, including Liquid-disordered (Ld) and Liquid-ordered (Lo) membrane models, to account for the TLR4 recruitment in lipid rafts over activation. We modeled, by means of all-atom Molecular Dynamics (MD) simulations, the structural assembly of plausible full-length TLR4 models embedded into a realistic plasma membrane, accounting for the active (agonist) state of the TLR4, thus providing an analysis at both atomic/molecular and thermodynamic levels of the TLR4 assembly and biological activity. Our results unveil relevant molecular aspects involved in the mechanism of receptor activation, and adaptor recruitment in the innate immune pathways, and will promote the discovery of new TLR4 modulators and probes.

The Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges focuses the computational modeling community on areas in need of improvement for rational drug design. The SAMPL7 physical property challenge dealt with prediction of octanol-water partition coefficients and pKa for 22 compounds. The dataset was composed of a series of N-acylsulfonamides and related bioisosteres. 17 research groups participated in the log P challenge, submitting 33 blind submissions total. For the pKa challenge, 7 different groups participated, submitting 9 blind submissions in total. Overall, the accuracy of octanol-water log P predictions in the SAMPL7 challenge was lower than octanol-water log P predictions in SAMPL6, likely due to a more diverse dataset. Compared to the SAMPL6 pKa challenge, accuracy remains unchanged in SAMPL7. Interestingly, here, though macroscopic pKa values were often predicted with reasonable accuracy, there was dramatically more disagreement among participants as to which microscopic transitions produced these values (with methods often disagreeing even as to the sign of the free energy change associated with certain transitions), indicating far more work needs to be done on pKa prediction methods.

A wide variety of neurodegenerative diseases are characterized by the accumulation of protein aggregates in intraneuronal or extraneuronal brain regions. In Alzheimer's disease (AD), the extracellular aggregates originate from amyloid-beta proteins, while the intracellular aggregates are formed from microtubule-binding tau proteins. The amyloid forming peptide sequences in the amyloid-beta peptides and tau proteins are responsible for aggregate formation. Experimental studies have until the date reported many of such amyloid forming peptide sequences in different proteins, however, there is still limited molecular level understanding about their tendency to form aggregates. In this study, we employed umbrella sampling simulations and subsequent electronic structure theory calculations in order to estimate the energy profiles for interconversion of the helix to beta-sheet like secondary structures of sequences from amyloid-beta protein (KLVFFA) and tau protein (QVEVKSEKLD and VQIVYKPVD). The study also included a poly-alanine sequence as a reference system. The calculated force-field based free energy profiles predicted a flat minimum for monomers of sequences from amyloid and tau proteins corresponding to an alpha-helix like secondary structure. For the parallel and anti-parallel dimer of KLVFFA, double well potentials were obtained with the minima corresponding to alpha-helix and beta-sheet like secondary structures. A similar double well-like potential has been found for dimeric forms for the sequences from tau fibril. Complementary semi-empirical and density functional theory calculations displayed similar trends, validating the force-field based free energy profiles obtained for these systems., QC 20210524

The Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges focuses the computational modeling community on areas in need of improvement for rational drug design. The SAMPL7 physical property challenge dealt with prediction of octanol-water partition coefficients and pKa for 22 compounds. The dataset was composed of a series of N-acylsulfonamides and related bioisosteres. 17 research groups participated in the log P challenge, submitting 33 blind submissions total. For the pKa challenge, 7 different groups participated, submitting 9 blind submissions in total. Overall, the accuracy of octanol-water log P predictions in the SAMPL7 challenge was lower than octanol-water log P predictions in SAMPL6, likely due to a more diverse dataset. Compared to the SAMPL6 pKa challenge, accuracy remains unchanged in SAMPL7. Interestingly, here, though macroscopic pKa values were often predicted with reasonable accuracy, there was dramatically more disagreement among participants as to which microscopic transitions produced these values (with methods often disagreeing even as to the sign of the free energy change associated with certain transitions), indicating far more work needs to be done on pKa prediction methods.

Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., "Gaussian approximation"). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica exchange GaMD (rex-GaMD) and replica exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new "selective GaMD" algorithms including the ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small-molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein-protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design.

Membrane proteins control the traffic across cell membranes and thereby play an essential role in cell function from transport of various solutes to immune response via molecular recognition. Because it is very difficult to determine the structures of membrane proteins experimentally, computational methods have been increasingly used to study their structure and function. Here we focus on two classes of membrane proteins-ion channels and transporters-which are responsible for the generation of action potentials in nerves, muscles, and other excitable cells. We describe how computational methods have been used to construct models for these proteins and to study the transport mechanism. The main computational tool is the molecular dynamics (MD) simulation, which can be used for everything from refinement of protein structures to free energy calculations of transport processes. We illustrate with specific examples from gramicidin and potassium channels and aspartate transporters how the function of these membrane proteins can be investigated using MD simulations. © 2012 International Union for Pure and Applied Biophysics (IUPAB) and Springer., Australian Research Council Consejo Nacional de Investigaciones Científicas y Técnicas

The topic solvation thermodynamics is an important aspect of chemistry, dealing with the effects introduced by solvents onto solutes. In particular, biological systems are highly heterogeneous in their choice of solvent typically characterized by either being in a polar or non-polar environment. For example, the cytoplasm of cells constituting the internal environment of cells is an aqueous solvent, whereas the membrane, being the boundary separating the cells from its surroundings, is an example of a lipid solvent. In addition to the main solvent, the majority of biological solvents also contain co-solvents such as ions, including ATP which can be found to be on the ~10 mM cellular concentration scale, or monovalent ions such as potassium, sodium, chloride, and not to forget free amino acids. While the previously mentioned examples are important in their own regards for oxidative phosphorylation, nerve cell communication, and construction of proteins respectively, to mention a few examples, their role as co-solvents can also greatly affect the stability and solubility of molecular matter.In this work, we will investigate the properties underlying the solvation of molecular matter utilizing statistical thermodynamics and molecular simulations. In specific by using molecular simulations we can determine atomistic properties for systems of interest, and via statistical thermodynamics relate these properties to experimental observables. These observables may either be mechanical properties addressing the behavior of molecular matter at a given state, or they may be state functions that describe the changes in energetics and entropy for the molecular matter changing. Within solvation thermodynamics, one of the most important state functions is the chemical potential and highly related solvation free energy describing the free energy of adding a solute particle to the system and thus quantifies the reversible work between the solute and solvent upon introducing the parti

Membrane proteins control the traffic across cell membranes and thereby play an essential role in cell function from transport of various solutes to immune response via molecular recognition. Because it is very difficult to determine the structures of membrane proteins experimentally, computational methods have been increasingly used to study their structure and function. Here we focus on two classes of membrane proteins-ion channels and transporters-which are responsible for the generation of action potentials in nerves, muscles, and other excitable cells. We describe how computational methods have been used to construct models for these proteins and to study the transport mechanism. The main computational tool is the molecular dynamics (MD) simulation, which can be used for everything from refinement of protein structures to free energy calculations of transport processes. We illustrate with specific examples from gramicidin and potassium channels and aspartate transporters how the function of these membrane proteins can be investigated using MD simulations. © 2012 International Union for Pure and Applied Biophysics (IUPAB) and Springer., Australian Research Council Consejo Nacional de Investigaciones Científicas y Técnicas

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 (phi, psi) 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.

In this paper, we review recent advances in the Continuous Fractional Component Monte Carlo (CFCMC) methodology and present a historic overview of the most important developments that have led to this method. The CFCMC method has gained attention for Monte Carlo simulations of adsorption at high loading, and phase and reaction equilibria of dense systems. It has recently been extended to reactive systems. The main features of the CFCMC method are: (1) Increased molecule exchange efficiency between different phases in single and multicomponent (reactive) systems, which improves the efficiency and accuracy of phase equilibria simulations at high densities; (2) Direct calculation of the chemical potential from a single simulation; (3) Direct calculation of partial molar properties from a single simulation. The developed simulation techniques are incorporated in the open-source molecular simulation software Brick-CFCMC., Engineering Thermodynamics

Improving and developing simulation techniques are key to obtaining higher efficiency and accuracy in molecular simulations of dense liquid systems. The methodology development introduced in this thesis is relevant both for academia and industrial applications. In this thesis, the methods developments/improvements for molecular simulations are introduced followed by applications for realistic systems and systems of industrial relevance...., Engineering Thermodynamics

Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study, we describe the concept and results for the SAMPL6 SAMPLing challenge, the first challenge from the SAMPL series focusing on the assessment of convergence properties and reproducibility of binding free energy methodologies. We provided parameter files, partial charges, and multiple initial geometries for two octa-acid (OA) and one cucurbit[8]uril (CB8) host-guest systems. Participants submitted binding free energy predictions as a function of the number of force and energy evaluations for seven different alchemical and physical-pathway (i.e., potential of mean force and weighted ensemble of trajectories) methodologies implemented with the GROMACS, AMBER, NAMD, or OpenMM simulation engines. To rank the methods, we developed an efficiency statistic based on bias and variance of the free energy estimates. For the two small OA binders, the free energy estimates computed with alchemical and potential of mean force approaches show relatively similar variance and bias as a function of the number of energy/force evaluations, with the attach-pull-release (APR), GROMACS expanded ensemble, and NAMD double decoupling submissions obtaining the greatest efficiency. The differences between the methods increase when analyzing the CB8-quinine system, where both the guest size and correlation times for system dynamics are greater. For this system, nonequilibrium switching (GROMACS/NS-DS/SB) obtained the overall highest efficiency. Surprisingly, the results suggest that specifying force field parameters and partial charges is insufficient to generally ensure

The SAMPL Challenges aim to focus the biomolecular and physical modeling community on issues that limit the accuracy of predictive modeling of protein-ligand binding for rational drug design. In the SAMPL5 log D Challenge, designed to benchmark the accuracy of methods for predicting drug-like small molecule transfer free energies from aqueous to nonpolar phases, participants found it difficult to make accurate predictions due to the complexity of protonation state issues. In the SAMPL6 log P Challenge, we asked participants to make blind predictions of the octanol-water partition coefficients of neutral species of 11 compounds and assessed how well these methods performed absent the complication of protonation state effects. This challenge builds on the SAMPL6 p[Formula: see text] Challenge, which asked participants to predict p[Formula: see text] values of a superset of the compounds considered in this log P challenge. Blind prediction sets of 91 prediction methods were collected from 27 research groups, spanning a variety of quantum mechanics (QM) or molecular mechanics (MM)-based physical methods, knowledge-based empirical methods, and mixed approaches. There was a 50% increase in the number of participating groups and a 20% increase in the number of submissions compared to the SAMPL5 log D Challenge. Overall, the accuracy of octanol-water log P predictions in SAMPL6 Challenge was higher than cyclohexane-water log D predictions in SAMPL5, likely because modeling only the neutral species was necessary for log P and several categories of method benefited from the vast amounts of experimental octanol-water log P data. There were many highly accurate methods: 10 diverse methods achieved RMSE less than 0.5 log P units. These included QM-based methods, empirical methods, and mixed methods with physical modeling supported with empirical corrections. A comparison of physical modeling methods showed that QM-based methods outper

Ion channels are membrane proteins that play an important role in the transmission of electrical signals in cells. The binding of a ligand or an electrical signal to the ion channels allows these channels to open as the membrane potential chan-ges. These channels allow certain type of ion such as Na+, K+, Ca2+ or Cl- to across from the cell membrane. These channels work like transistors in electronic circuits. While this occurs in many cell signals, the most basic is the transmission of the action potential in nerve cells. Functional disorders that occur in the ion channels due to mutation of channel proteins that occur in gene codes or environmental effects have been associated with many diseases. So ion channels are an important target for therapeutic drugs. Structural information is the basis for model work, but it is not enough to fully understand how the channels work. While many features of channel functions can not be reached directly experimentally, computer-aided simulations can provide information on structure and function of channel proteins. In this work, ion transition mechanism of sodium voltage-gated ion channels with crystal structure was tried to be elucidated by molecular dynamics simulations. At the same time, free energy calculations were carried out to investigate ligand binding to these channels. Free energy calculations will be obtained from the calculation of the force field potential (PMF) using the Umbrella Sampling Method over a selected reaction coordinate. The Umbrella Sampling Method is a simulation method applied over predefined reaction coordinates.The free energy profile is also passed from the WHAM analysis. In this method, a large number of simulations are run at different locations of the umbrella potential along the reaction coordinates. The population values represented by the potential energy applied from the samples of each simulation are revealed. The resulting population (density function) is combined along the reaction coor, İyon kanalları hücrelerde elektriksel sinyalin iletilmesinde önemli rol oynayan membran proteinleridir. İyon kanallarına, bir ligandın bağlanması veya elektriksel bir sinyalin gelmesi membran potansiyelini değiştirirken aksiyon potansiyeli meydana getirir. Açılan bu kanallar Na+, K+ ,Ca2+ ya da Cl- gibi belirli bir tip iyonları hücre membranından seçici bir şekilde geçmesine olanak sağlar. Bu kanallar elektronik devrelerdeki transistörler gibi çalışırlar. Bu durum pek çok hücre sinyalinde ortaya çıkarken en temel olanı sinir hücrelerindeki aksiyon potansiyelinin iletilmesidir. İyon kanallarının düzgün çalışmaması veya iyon kanallarında meydana gelen fonksiyonel bozukluklar birçok hastalıkla ilişkilendirilmiştir. Bu bozukluklar gen kodlarında meydana gelen kanal proteinlerinin mutasyonu ya da çevresel etkilerden mütevelliddir. Bu yüzden iyon kanalları tedavi edici ilaçlar için önemli hedef protein yapılardır. Yapısal bilgi, model çalışmaları için temel teşkil eder; ancak kanalların nasıl çalıştığının tamamıyla anlaşılmasında yeterli değildir. Kanal fonksiyonlarının birçok özelliğine deneysel olarak doğrudan ulaşılamazken bilgisayar destekli simülasyonlarda kanal proteinlerinin yapı ve fonksiyonuna ilişkin bilgilere ulaşılabilir. Bu çalışmada kristal yapısı var olan sodyum voltaj-kapılı iyon kanallarındaki iyon geçiş mekanizması moleküler dinamik simülasyonları yöntemiyle aydınlatılmaya çalışılırken, aynı zamanda bu kanallara ligand bağlanmasının araştırılması için serbest enerji hesaplamaları yapılmıştır. Serbest enerji hesaplamaları seçilen bir reaksiyon koordinatı boyunca Şemsiye Örnekleme Metodu kullanarak kuvvet alanları potansiyeli (PMF) hesabından elde edilecektir. Şemsiye Örnekleme Metodu önceden tanımlanmış reaksiyon koordinatları boyunca uygulanan bir simülasyon metodudur. Bu metotta, reaksiyon koordinatları boyunca şemsiye potansiyelin farklı yerleşimlerinde çok sayıda simülasyon çalıştırılır. Her simülasyonun örneklemelerden uygulanan potansiyel enerji ile

Ion channels are membrane proteins that play an important role in the transmission of electrical signals in cells. The binding of a ligand or an electrical signal to the ion channels allows these channels to open as the membrane potential chan-ges. These channels allow certain type of ion such as Na+, K+, Ca2+ or Cl- to across from the cell membrane. These channels work like transistors in electronic circuits. While this occurs in many cell signals, the most basic is the transmission of the action potential in nerve cells. Functional disorders that occur in the ion channels due to mutation of channel proteins that occur in gene codes or environmental effects have been associated with many diseases. So ion channels are an important target for therapeutic drugs. Structural information is the basis for model work, but it is not enough to fully understand how the channels work. While many features of channel functions can not be reached directly experimentally, computer-aided simulations can provide information on structure and function of channel proteins. In this work, ion transition mechanism of sodium voltage-gated ion channels with crystal structure was tried to be elucidated by molecular dynamics simulations. At the same time, free energy calculations were carried out to investigate ligand binding to these channels. Free energy calculations will be obtained from the calculation of the force field potential (PMF) using the Umbrella Sampling Method over a selected reaction coordinate. The Umbrella Sampling Method is a simulation method applied over predefined reaction coordinates.The free energy profile is also passed from the WHAM analysis. In this method, a large number of simulations are run at different locations of the umbrella potential along the reaction coordinates. The population values represented by the potential energy applied from the samples of each simulation are revealed. The resulting population (density function) is combined along the reaction coor, İyon kanalları hücrelerde elektriksel sinyalin iletilmesinde önemli rol oynayan membran proteinleridir. İyon kanallarına, bir ligandın bağlanması veya elektriksel bir sinyalin gelmesi membran potansiyelini değiştirirken aksiyon potansiyeli meydana getirir. Açılan bu kanallar Na+, K+ ,Ca2+ ya da Cl- gibi belirli bir tip iyonları hücre membranından seçici bir şekilde geçmesine olanak sağlar. Bu kanallar elektronik devrelerdeki transistörler gibi çalışırlar. Bu durum pek çok hücre sinyalinde ortaya çıkarken en temel olanı sinir hücrelerindeki aksiyon potansiyelinin iletilmesidir. İyon kanallarının düzgün çalışmaması veya iyon kanallarında meydana gelen fonksiyonel bozukluklar birçok hastalıkla ilişkilendirilmiştir. Bu bozukluklar gen kodlarında meydana gelen kanal proteinlerinin mutasyonu ya da çevresel etkilerden mütevelliddir. Bu yüzden iyon kanalları tedavi edici ilaçlar için önemli hedef protein yapılardır. Yapısal bilgi, model çalışmaları için temel teşkil eder; ancak kanalların nasıl çalıştığının tamamıyla anlaşılmasında yeterli değildir. Kanal fonksiyonlarının birçok özelliğine deneysel olarak doğrudan ulaşılamazken bilgisayar destekli simülasyonlarda kanal proteinlerinin yapı ve fonksiyonuna ilişkin bilgilere ulaşılabilir. Bu çalışmada kristal yapısı var olan sodyum voltaj-kapılı iyon kanallarındaki iyon geçiş mekanizması moleküler dinamik simülasyonları yöntemiyle aydınlatılmaya çalışılırken, aynı zamanda bu kanallara ligand bağlanmasının araştırılması için serbest enerji hesaplamaları yapılmıştır. Serbest enerji hesaplamaları seçilen bir reaksiyon koordinatı boyunca Şemsiye Örnekleme Metodu kullanarak kuvvet alanları potansiyeli (PMF) hesabından elde edilecektir. Şemsiye Örnekleme Metodu önceden tanımlanmış reaksiyon koordinatları boyunca uygulanan bir simülasyon metodudur. Bu metotta, reaksiyon koordinatları boyunca şemsiye potansiyelin farklı yerleşimlerinde çok sayıda simülasyon çalıştırılır. Her simülasyonun örneklemelerden uygulanan potansiyel enerji ile

In this paper, we review recent advances in the Continuous Fractional Component Monte Carlo (CFCMC) methodology and present a historic overview of the most important developments that have led to this method. The CFCMC method has gained attention for Monte Carlo simulations of adsorption at high loading, and phase and reaction equilibria of dense systems. It has recently been extended to reactive systems. The main features of the CFCMC method are: (1) Increased molecule exchange efficiency between different phases in single and multicomponent (reactive) systems, which improves the efficiency and accuracy of phase equilibria simulations at high densities; (2) Direct calculation of the chemical potential from a single simulation; (3) Direct calculation of partial molar properties from a single simulation. The developed simulation techniques are incorporated in the open-source molecular simulation software Brick-CFCMC., Engineering Thermodynamics

Improving and developing simulation techniques are key to obtaining higher efficiency and accuracy in molecular simulations of dense liquid systems. The methodology development introduced in this thesis is relevant both for academia and industrial applications. In this thesis, the methods developments/improvements for molecular simulations are introduced followed by applications for realistic systems and systems of industrial relevance...., Engineering Thermodynamics

Insulin detemir is a lipidated insulin analogue that obtains a half-life extension by oligomerization and reversible binding to human serum albumin. In the present study, the complex between a detemir hexamer and albumin is investigated by an integrative approach combining molecular dynamics (MD) simulations, molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) free energy calculations and dynamic light scattering (DLS) experiments. Recent reported small angle X-ray scattering data could not unambiguously resolve the exact binding site of detemir on albumin. We therefore applied MD simulations to deduce the binding site and key protein-protein interactions. MD simulations were started from initial complex structures based on the SAXS models and free energies of binding were estimated from the simulations by using the MM-PBSA approach for the different binding positions. The results suggest that the overlapping FA3-FA4 binding site (named FA4) is the most favorable site with a calculated free energy of binding of -28±6 kcal/mol and a good fit to the reported SAXS data throughout the simulations. Multiple salt bridges, hydrogen bonds and favorable van der Waals interactions are observed in the binding interface that promote complexation. The binding to FA4 is further supported by DLS competition experiments with the prototypical FA4 ligand, ibuprofen, showing displacement of detemir by ibuprofen. This study provides information on albumin-detemir binding on a molecular level, which could be utilized in a rational design of future lipidated albumin-binding peptides.

Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A(3) adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.

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., QC 20181120

Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A(3) adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.

Simulations allow us to predict free energies and physical properties of molecules in advance of their synthesis saving time and resources. My research focuses on how to automatically evaluate and improve these predictions. I begin by describing my work to test the accuracy of free energy calculations by computing various partition coefficients. Then, I report on applications of the resulting procedure in the SAMPL5 blind challenge for 53 small drug-like molecules. Comparing computed and experimental values highlighted three areas which still need improvement: conformational sampling, protonation assignment, and force field accuracy. These results motivated my next project, designing a Gaussian process model for pKa prediction based on computed properties of small molecules. I tested this model in the SAMPL6 blind challenge on pKa prediction where it performed competitively with many established methods. My partition coefficient results also highlighted the limitations of current force fields -- used to calculate potential energy of a system based on atomic coordinates. To address these concerns, I joined the the Open Force Field Initiative, a collaboration working to automate force field parametrization. The culmination of my Ph.D. focuses on generating chemical perception -- the way a force field assigns parameters to a molecule -- without the historically required human intuition. Improved force fields will result in more accurate predictive models and a better understanding of a wide variety of fields including computer-aided drug design, biomaterials, and polymer chemistry.

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., Accepted Author Manuscript, ChemE/Product and Process Engineering

Simulations allow us to predict free energies and physical properties of molecules in advance of their synthesis saving time and resources. My research focuses on how to automatically evaluate and improve these predictions. I begin by describing my work to test the accuracy of free energy calculations by computing various partition coefficients. Then, I report on applications of the resulting procedure in the SAMPL5 blind challenge for 53 small drug-like molecules. Comparing computed and experimental values highlighted three areas which still need improvement: conformational sampling, protonation assignment, and force field accuracy. These results motivated my next project, designing a Gaussian process model for pKa prediction based on computed properties of small molecules. I tested this model in the SAMPL6 blind challenge on pKa prediction where it performed competitively with many established methods. My partition coefficient results also highlighted the limitations of current force fields -- used to calculate potential energy of a system based on atomic coordinates. To address these concerns, I joined the the Open Force Field Initiative, a collaboration working to automate force field parametrization. The culmination of my Ph.D. focuses on generating chemical perception -- the way a force field assigns parameters to a molecule -- without the historically required human intuition. Improved force fields will result in more accurate predictive models and a better understanding of a wide variety of fields including computer-aided drug design, biomaterials, and polymer chemistry.

Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A(3) adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.

Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A(3) adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.

Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A3 adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol

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., Accepted Author Manuscript, ChemE/Product and Process Engineering

Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A(3) adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.

At central nervous system synapses, agonist binding to postsynaptic ionotropic glutamate receptors (iGluRs) results in signaling between neurons. N-Methyl-D-aspartic acid (NMDA) receptors are a unique family of iGluRs that activate in response to the concurrent binding of glutamate and glycine. Here, we investigate the process of agonist binding to the GluN2A (glutamate binding) and GluN1 (glycine binding) NMDA receptor subtypes using long-timescale unbiased molecular dynamics simulations. We find that positively charged residues on the surface of the GluN2A ligand-binding domain (LBD) assist glutamate binding via a "guided-diffusion" mechanism, similar in fashion to glutamate binding to the GluA2 LBD of AMPA receptors. Glutamate can also bind in an inverted orientation. Glycine, on the other hand, binds to the GluN1 LBD via an "unguided-diffusion" mechanism, whereby glycine finds its binding site primarily by random thermal fluctuations. Free energy calculations quantify the glutamate- and glycine-binding processes.

Quinone and its analogues (Q) constitute an important class of compounds that perform key electron transfer reactions in oxidative- and photo-phosphorylation. In the inner membrane of mitochondria, ubiquinone molecules undergo continuous redox transitions enabling electron transfer between the respiratory complexes. In such a dynamic system undergoing continuous turnover for ATP synthesis, an uninterrupted supply of substrate molecules is absolutely necessary. In the current work, we have performed atomistic molecular dynamics simulations and free energy calculations to assess the structure, dynamics, and localization of quinone and its analogues in a lipid bilayer, whose composition mimics the one in the inner mitochondrial membrane. The results show that there is a strong tendency of both quinone and quinol molecules to localize in the vicinity of the lipids' acyl groups, right under the lipid head group region. Additionally, we observe a second location in the middle of the bilayer where quinone molecules tend to stabilize. Translocation of quinone through a lipid bilayer is very fast and occurs in 10-100 ns time scale, whereas the translocation of quinol is at least an order of magnitude slower. We suggest that this has important mechanistic implications given that the localization of Q ensures maximal occupancy of the Q-binding sites or Q-entry points in electron transport chain complexes, thereby maintaining an optimal turnover rate for ATP synthesis. (C) 2016 Elsevier B.V. All rights reserved.

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.

Molecular modeling has come a long way during the past decades and in the current thesis modeling of biological membranes is the focus. The main method of choice has been classical Molecular Dynamics simulations and for this technique a model Hamiltonian, or force field (FF), has been developed for lipids to be used for biological membranes. Further, ways of more accurately simulate the interactions between solutes and membranes have been investigated. A FF coined Slipids was developed and validated against a range of experimental data (Papers I-III). Several structural properties such as area per lipid, scattering form factors and NMR order parameters obtained from the simulations are in good agreement with available experimental data. Further, the compatibility of Slipids with amino acid FFs was proven. This, together with the wide range of lipids that can be studied, makes Slipids an ideal candidate for large-scale studies of biologically relevant systems. A solute's electron distribution is changed as it is transferred from water to a bilayer, a phenomena that cannot be fully captured with fixed-charge FFs. In Paper IV we propose a scheme of implicitly including these effects with fixed-charge FFs in order to more realistically model water-membrane partitioning. The results are in good agreement with experiments in terms of free energies and further the differences between using this scheme and the more traditional approach were highlighted. The free energy landscape (FEL) of solutes embedded in a model membrane is explored in Paper V. This was done using biased sampling methods with a reaction coordinate that included intramolecular degrees of freedom (DoF). These DoFs were identified in different bulk liquids and then used in studies with bilayers. The FELs describe the conformational changes necessary for the system to follow the lowest free energy path. Besides this, the pitfalls of using a one-dimensional reaction coordinate are highlighted.

This work provides a curated database of experimental and calculated hydration free energies for small neutral molecules in water, along with molecular structures, input files, references, and annotations. We call this the Free Solvation Database, or FreeSolv. Experimental values were taken from prior literature and will continue to be curated, with updated experimental references and data added as they become available. Calculated values are based on alchemical free energy calculations using molecular dynamics simulations. These used the GAFF small molecule force field in TIP3P water with AM1-BCC charges. Values were calculated with the GROMACS simulation package, with full details given in references cited within the database itself. This database builds in part on a previous, 504-molecule database containing similar information. However, additional curation of both experimental data and calculated values has been done here, and the total number of molecules is now up to 643. Additional information is now included in the database, such as SMILES strings, PubChem compound IDs, accurate reference DOIs, and others. One version of the database is provided in the Supporting Information of this article, but as ongoing updates are envisioned, the database is now versioned and hosted online. In addition to providing the database, this work describes its construction process. The database is available free-of-charge via http://www.escholarship.org/uc/item/6sd403pz .

Molecular modeling has come a long way during the past decades and in the current thesis modeling of biological membranes is the focus. The main method of choice has been classical Molecular Dynamics simulations and for this technique a model Hamiltonian, or force field (FF), has been developed for lipids to be used for biological membranes. Further, ways of more accurately simulate the interactions between solutes and membranes have been investigated. A FF coined Slipids was developed and validated against a range of experimental data (Papers I-III). Several structural properties such as area per lipid, scattering form factors and NMR order parameters obtained from the simulations are in good agreement with available experimental data. Further, the compatibility of Slipids with amino acid FFs was proven. This, together with the wide range of lipids that can be studied, makes Slipids an ideal candidate for large-scale studies of biologically relevant systems. A solute's electron distribution is changed as it is transferred from water to a bilayer, a phenomena that cannot be fully captured with fixed-charge FFs. In Paper IV we propose a scheme of implicitly including these effects with fixed-charge FFs in order to more realistically model water-membrane partitioning. The results are in good agreement with experiments in terms of free energies and further the differences between using this scheme and the more traditional approach were highlighted. The free energy landscape (FEL) of solutes embedded in a model membrane is explored in Paper V. This was done using biased sampling methods with a reaction coordinate that included intramolecular degrees of freedom (DoF). These DoFs were identified in different bulk liquids and then used in studies with bilayers. The FELs describe the conformational changes necessary for the system to follow the lowest free energy path. Besides this, the pitfalls of using a one-dimensional reaction coordinate are highlighted.

Molecular modeling has come a long way during the past decades and in the current thesis modeling of biological membranes is the focus. The main method of choice has been classical Molecular Dynamics simulations and for this technique a model Hamiltonian, or force field (FF), has been developed for lipids to be used for biological membranes. Further, ways of more accurately simulate the interactions between solutes and membranes have been investigated. A FF coined Slipids was developed and validated against a range of experimental data (Papers I-III). Several structural properties such as area per lipid, scattering form factors and NMR order parameters obtained from the simulations are in good agreement with available experimental data. Further, the compatibility of Slipids with amino acid FFs was proven. This, together with the wide range of lipids that can be studied, makes Slipids an ideal candidate for large-scale studies of biologically relevant systems. A solute's electron distribution is changed as it is transferred from water to a bilayer, a phenomena that cannot be fully captured with fixed-charge FFs. In Paper IV we propose a scheme of implicitly including these effects with fixed-charge FFs in order to more realistically model water-membrane partitioning. The results are in good agreement with experiments in terms of free energies and further the differences between using this scheme and the more traditional approach were highlighted. The free energy landscape (FEL) of solutes embedded in a model membrane is explored in Paper V. This was done using biased sampling methods with a reaction coordinate that included intramolecular degrees of freedom (DoF). These DoFs were identified in different bulk liquids and then used in studies with bilayers. The FELs describe the conformational changes necessary for the system to follow the lowest free energy path. Besides this, the pitfalls of using a one-dimensional reaction coordinate are highlighted.

This work provides a curated database of experimental and calculated hydration free energies for small neutral molecules in water, along with molecular structures, input files, references, and annotations. We call this the Free Solvation Database, or FreeSolv. Experimental values were taken from prior literature and will continue to be curated, with updated experimental references and data added as they become available. Calculated values are based on alchemical free energy calculations using molecular dynamics simulations. These used the GAFF small molecule force field in TIP3P water with AM1-BCC charges. Values were calculated with the GROMACS simulation package, with full details given in references cited within the database itself. This database builds in part on a previous, 504-molecule database containing similar information. However, additional curation of both experimental data and calculated values has been done here, and the total number of molecules is now up to 643. Additional information is now included in the database, such as SMILES strings, PubChem compound IDs, accurate reference DOIs, and others. One version of the database is provided in the Supporting Information of this article, but as ongoing updates are envisioned, the database is now versioned and hosted online. In addition to providing the database, this work describes its construction process. The database is available free-of-charge via http://www.escholarship.org/uc/item/6sd403pz .

Molecular modeling has come a long way during the past decades and in the current thesis modeling of biological membranes is the focus. The main method of choice has been classical Molecular Dynamics simulations and for this technique a model Hamiltonian, or force field (FF), has been developed for lipids to be used for biological membranes. Further, ways of more accurately simulate the interactions between solutes and membranes have been investigated. A FF coined Slipids was developed and validated against a range of experimental data (Papers I-III). Several structural properties such as area per lipid, scattering form factors and NMR order parameters obtained from the simulations are in good agreement with available experimental data. Further, the compatibility of Slipids with amino acid FFs was proven. This, together with the wide range of lipids that can be studied, makes Slipids an ideal candidate for large-scale studies of biologically relevant systems. A solute's electron distribution is changed as it is transferred from water to a bilayer, a phenomena that cannot be fully captured with fixed-charge FFs. In Paper IV we propose a scheme of implicitly including these effects with fixed-charge FFs in order to more realistically model water-membrane partitioning. The results are in good agreement with experiments in terms of free energies and further the differences between using this scheme and the more traditional approach were highlighted. The free energy landscape (FEL) of solutes embedded in a model membrane is explored in Paper V. This was done using biased sampling methods with a reaction coordinate that included intramolecular degrees of freedom (DoF). These DoFs were identified in different bulk liquids and then used in studies with bilayers. The FELs describe the conformational changes necessary for the system to follow the lowest free energy path. Besides this, the pitfalls of using a one-dimensional reaction coordinate are highlighted.

Molecular modeling has come a long way during the past decades and in the current thesis modeling of biological membranes is the focus. The main method of choice has been classical Molecular Dynamics simulations and for this technique a model Hamiltonian, or force field (FF), has been developed for lipids to be used for biological membranes. Further, ways of more accurately simulate the interactions between solutes and membranes have been investigated. A FF coined Slipids was developed and validated against a range of experimental data (Papers I-III). Several structural properties such as area per lipid, scattering form factors and NMR order parameters obtained from the simulations are in good agreement with available experimental data. Further, the compatibility of Slipids with amino acid FFs was proven. This, together with the wide range of lipids that can be studied, makes Slipids an ideal candidate for large-scale studies of biologically relevant systems. A solute's electron distribution is changed as it is transferred from water to a bilayer, a phenomena that cannot be fully captured with fixed-charge FFs. In Paper IV we propose a scheme of implicitly including these effects with fixed-charge FFs in order to more realistically model water-membrane partitioning. The results are in good agreement with experiments in terms of free energies and further the differences between using this scheme and the more traditional approach were highlighted. The free energy landscape (FEL) of solutes embedded in a model membrane is explored in Paper V. This was done using biased sampling methods with a reaction coordinate that included intramolecular degrees of freedom (DoF). These DoFs were identified in different bulk liquids and then used in studies with bilayers. The FELs describe the conformational changes necessary for the system to follow the lowest free energy path. Besides this, the pitfalls of using a one-dimensional reaction coordinate are highlighted.

Molecular modeling has come a long way during the past decades and in the current thesis modeling of biological membranes is the focus. The main method of choice has been classical Molecular Dynamics simulations and for this technique a model Hamiltonian, or force field (FF), has been developed for lipids to be used for biological membranes. Further, ways of more accurately simulate the interactions between solutes and membranes have been investigated. A FF coined Slipids was developed and validated against a range of experimental data (Papers I-III). Several structural properties such as area per lipid, scattering form factors and NMR order parameters obtained from the simulations are in good agreement with available experimental data. Further, the compatibility of Slipids with amino acid FFs was proven. This, together with the wide range of lipids that can be studied, makes Slipids an ideal candidate for large-scale studies of biologically relevant systems. A solute's electron distribution is changed as it is transferred from water to a bilayer, a phenomena that cannot be fully captured with fixed-charge FFs. In Paper IV we propose a scheme of implicitly including these effects with fixed-charge FFs in order to more realistically model water-membrane partitioning. The results are in good agreement with experiments in terms of free energies and further the differences between using this scheme and the more traditional approach were highlighted. The free energy landscape (FEL) of solutes embedded in a model membrane is explored in Paper V. This was done using biased sampling methods with a reaction coordinate that included intramolecular degrees of freedom (DoF). These DoFs were identified in different bulk liquids and then used in studies with bilayers. The FELs describe the conformational changes necessary for the system to follow the lowest free energy path. Besides this, the pitfalls of using a one-dimensional reaction coordinate are highlighted.

Predicting protein-ligand binding free energy from physical principles is a grand challenge in biophysics, with particular importance for drug discovery. Free energy calculations compute binding affinities by using classical mechanics to model the protein and ligand at atomic resolution, and using statistical mechanics to analyze simulations of these models. The binding affinities computed from these simulations are fully rigorous and thermodynamically correct for the model (with adequate sampling), and will agree with experimentally measured binding affinities if the model is accurate. Because free energy calculations capture the full statistical complexity of binding for flexible molecules at ambient temperature, they offer the greatest potential for quantitative accuracy of any physical method for predicting binding.Here, I (& coauthors) present several studies relating to using free energy calculations to predict protein-ligand binding affinities for charged compounds. First, we introduce the Separated Topologies method, an approach for using free energy calculations to predict relative binding affinities of unrelated ligands. This method is useful for studying charged compounds because charged compounds are very difficult to study using absolute binding calculations, increasing the importance of relative binding calculations. Second, we use free energy calculations to predict absolute binding affinities for charged molecules to a simplified protein binding site, which is specially designed for studying charged interactions. These predictions are compared to new experimental affinity measurements and new high-resolution structures of the protein-ligand complexes. We find that all affinities are predicted to be too strong, and that this error is directly correlated with the polarity of each ligand. By uniformly weakening the strength of electrostatic interactions, we are more successful at predicting binding affinity. Third, we design and validate an analytic

Predicting protein-ligand binding free energy from physical principles is a grand challenge in biophysics, with particular importance for drug discovery. Free energy calculations compute binding affinities by using classical mechanics to model the protein and ligand at atomic resolution, and using statistical mechanics to analyze simulations of these models. The binding affinities computed from these simulations are fully rigorous and thermodynamically correct for the model (with adequate sampling), and will agree with experimentally measured binding affinities if the model is accurate. Because free energy calculations capture the full statistical complexity of binding for flexible molecules at ambient temperature, they offer the greatest potential for quantitative accuracy of any physical method for predicting binding.Here, I (& coauthors) present several studies relating to using free energy calculations to predict protein-ligand binding affinities for charged compounds. First, we introduce the Separated Topologies method, an approach for using free energy calculations to predict relative binding affinities of unrelated ligands. This method is useful for studying charged compounds because charged compounds are very difficult to study using absolute binding calculations, increasing the importance of relative binding calculations. Second, we use free energy calculations to predict absolute binding affinities for charged molecules to a simplified protein binding site, which is specially designed for studying charged interactions. These predictions are compared to new experimental affinity measurements and new high-resolution structures of the protein-ligand complexes. We find that all affinities are predicted to be too strong, and that this error is directly correlated with the polarity of each ligand. By uniformly weakening the strength of electrostatic interactions, we are more successful at predicting binding affinity. Third, we design and validate an analytic

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.

Accurate partition coefficient data of migrants between a polymer and a solvent are of paramount importance for estimating the migration of the migrant over time, including the concentration of the migrant at infinite time in the two solvents. In this article it is shown how this partition coefficient can be estimated for both a small hydrophilic and a hydrophobic organic molecules between squalane (used here to mimic low density poly ethylene) and water/ethanol solutes using thermodynamic integration to calculate the free energy of solvation. Molecular dynamics simulations are performed, using the GROMACS software, by slowly decoupling of firstly the electrostatic and then the Lennard–Jones interactions between molecules in the simulation box. These calculations depend very much on the choice of force field. Two force fields have been tested in this work, the TraPPE-UA (united-atom) and the OPLS-AA (all-atom). The computational cheaper TraPPE-UA force field showed to be more accurate over the whole range of systems compared to the OPLS-AA force field. Moreover, some of the calculations were done with five different water models to investigate the influence of the specific water model on the calculations. It was found that the combination of the TraPPE-UA force field and the TIP4p water model gave the best results. Based on the methodology proposed in this article, it is possible to obtain good partition coefficients only knowing the chemical structure of the molecules in the system.

Spontaneous changes in protein systems, such as the binding of a ligand to an enzyme or receptor, are characterized by a decrease of free energy. Despite the recent developments in computing power and methodology, it remains challenging to accurately estimate free energy changes. Major issues are still concerned with the accuracy of the underlying model to describe the protein system and how well the calculation in fact emulates the behaviour of the system. This thesis is largely concerned with the quality of current free energy calculation methods as applied to protein-ligand systems. Several methodologies were employed to calculate Gibbs standard free energies of binding for a collection of protein-ligand complexes, for which experimental affinities were available. Calculations were performed using system description with different levels of accuracy and included a continuum approach, which considers the protein and the ligand at the atomic level but includes solvent as a polarizable continuum, and an all-atom approach that relies on molecular dynamics simulations. In most such applications, the effects of ionic strength are neglected. However, the severity of this approximation, in particular when calculating free energies of charged ligands, is not very clear. The issue of incorporating ionic strength in free energy calculations by means of explicit ions was investigated in greater detail and considerable attention was given to the affinities of charged peptides in the presence of explicit counter-ions. A second common approximation is concerned with the description of ligands that exhibit multiple protonation states. Because most of current methods do not model changes in the acid dissociation constants of titrating groups upon binding, protonation equilibria of such ligands are not taken into account in free energy calculations. The implications of this approximation when predicting affinities were analysed. Finally, when calculating free energies of