High-quality and universal empirical atomic charges for chemoinformatics applications.

BackgroundPartial atomic charges describe the distribution of electron density in a molecule and therefore provide clues to the chemical behaviour of molecules. Recently, these charges have become popular in chemoinformatics, as they are informative descriptors that can be utilised in pharmacophore design, virtual screening, similarity searches etc. Especially conformationally-dependent charges perform very successfully. In particular, their fast and accurate calculation via the Electronegativity Equalization Method (EEM) seems very promising for chemoinformatics applications. Unfortunately, published EEM parameter sets include only parameters for basic atom types and they often miss parameters for halogens, phosphorus, sulphur, triple bonded carbon etc. Therefore their applicability for drug-like molecules is limited.ResultsWe have prepared six EEM parameter sets which enable the user to calculate EEM charges in a quality comparable to quantum mechanics (QM) charges based on the most common charge calculation schemes (i.e., MPA, NPA and AIM) and a robust QM approach (HF/6-311G, B3LYP/6-311G). The calculated EEM parameters exhibited very good quality on a training set ([Formula: see text]) and also on a test set ([Formula: see text]). They are applicable for at least 95 % of molecules in key drug databases (DrugBank, ChEMBL, Pubchem and ZINC) compared to less than 60 % of the molecules from these databases for which currently used EEM parameters are applicable.ConclusionsWe developed EEM parameters enabling the fast calculation of high-quality partial atomic charges for almost all drug-like molecules. In parallel, we provide a software solution for their easy computation (http://ncbr.muni.cz/eem_parameters). It enables the direct application of EEM in chemoinformatics

Theoretical studies on the pK~a~ values of perfluoroalkyl carboxylic acids: Chain helicity

Semiempirical, ab initio, and density functional theory (DFT) studies were conducted on a homologous series of straight chain perfluoroalkyl carboxylic acids (PFCAs) ranging in chain length from C~1~ (trifluoroacetic acid; TFA) to C~9~ (perfluorodecanoic acid). Regardless of perfluoroalkyl chain length and computational method and level employed, no significant change in the electrostatic or steric characteristics of the carboxylate head group was found between C~2~ and C~9~. Application of a thermodynamic cycle to calculations at the B3LYP/6-311++G(3df,2p) level provided an accurate prediction of the experimental monomeric pK~a~ for TFA. At this – and similar – levels of theory, monomeric pK~a~ values of longer straight chain PFCAs are expected to display no significant increase with increasing chain length, having a relatively constant pK~a~ value of about 0 that is in excellent agreement with earlier predictions and with recent experimental evidence. Contrary to previous claims, perfluoroalkyl chain helicity does not appear to result in increased monomeric PFCA pK~a~ values at chain lengths >5 perfluorocarbons

Substituent analysis for accurate prediction of the acidity constants of phosphonic acids

This study aims to develop simple and reliable models to predict the pKa of phosphonic acids using empirical substituent effects descriptors. The effects of substituents on the acidity and basicity of organic acids have been examined using various approaches, such as the Taft-Topsom model. This study used linear regression methods to construct equations that predict the acidity constants of phosphonic acids. The validity of the linear regressions was confirmed through statistical analysis of parameters and residuals. However, it is essential to note that the models are limited to substituents with tabulated Taft parameters. Despite these limitations, the developed models provide a simple and effective method for estimating the acidity constants of phosphonic acids with a confidence interval greater than 95%. This study aims to analyze the effect of substituents on the dissociation of phosphonic acid and propose prediction models for new phosphonic derivative

Substituent analysis for accurate prediction of the acidity constants of phosphonic acids

This study aims to develop simple and reliable models to predict the pKa of phosphonic acids using empirical substituent effects descriptors. The effects of substituents on the acidity and basicity of organic acids have been examined using various approaches, such as the Taft-Topsom model. This study used linear regression methods to construct equations that predict the acidity constants of phosphonic acids. The validity of the linear regressions was confirmed through statistical analysis of parameters and residuals. However, it is essential to note that the models are limited to substituents with tabulated Taft parameters. Despite these limitations, the developed models provide a simple and effective method for estimating the acidity constants of phosphonic acids with a confidence interval greater than 95%. This study aims to analyze the effect of substituents on the dissociation of phosphonic acid and propose prediction models for new phosphonic derivative

High-dimension profiling data generate a multifunctional peptide-mimic chemo-structure by connecting conserved fragments based on the neutrophil immune defense CAP37 protein as an in-silico antibacterial and woundhealing candidate agent

CAP37, a protein constitutively EXPRESSED in human neutrophils and induced in responseto infection in corneal epithelial cells, plays a significant role in host defense against infection. Initiallyidentified through its potent bactericidal activity for Gram-negative bacteria, it is now known that CAP37regulates numerous host cell functions, including corneal epithelial cell chemotaxis. Delineation of thedomains of CAP37 that define these functions and synthesize bioactive peptides for therapeutic use have alsobeen explored. Novel findings of a multifunctional domain between a 120 and 146 have also been reported.Here, in Biogenea Pharmaceuticals Ltd we for the first time generated a multifunctional peptide-mimicchemo-structure by connecting conserved fragments based on the neutrophil immune defense CAP37 proteinas an in-silico antibacterial and wound-healing canditate agent. This in silico effort was accomplished byutilizing various generated descriptors of proteins, compounds and their interactions resulting in aperformance/cost evaluation study for a GPU-based drug discovery application on volunteer computingapproaches based on Automated Structure-Activity Relationship Minings in Connecting Chemical Structureto Biological Profiles for the generation of novel Computational biomodeling of 3D drug-protein binding freeenergy evaluation

EXPERIMENTAL AND MOLECULAR DYNAMICS SIMULATION STUDIES OF PARTITIONING AND TRANSPORT ACROSS LIPID BILAYER MEMBRANES

Most drugs undergo passive transport during absorption and distribution in the body. It is desirable to predict passive permeation of future drug candidates in order to increase the productivity of the drug discovery process. Unlike drug-receptor interactions, there is no receptor map for passive permeability because the process of transport across the lipid bilayer involves multiple mechanisms. This work intends to increase the understanding of permeation of drug-like molecules through lipid bilayers. Drug molecules in solution typically form various species due to ionization, complexation, etc. Therefore, species specific properties must be obtained to bridge the experiment and simulations. Due to the volume contrast between intra- and extravesicular compartments of liposomes, minor perturbations in ionic and binding equilibria become significant contributors to transport rates. Using tyramine as a model amine, quantitative numerical models were developed to determine intrinsic permeability coefficients. The microscopic ionization and binding constants needed for this were independently measured. The partition coefficient in 1,9-decadiene was measured for a series of compounds as a quantitative surrogate for the partitioning into the hydrocarbon region of the bilayer. These studies uncovered an apparent long-range interaction between the two polar substituents that caused deviations in the microscopic pKa values and partition coefficient of tyramine from the expected values. Additionally the partition coefficients in the preferred binding region of the bilayer were also measured by equilibrium uptake into liposomes. All-atom molecular dynamics simulations of lipid bilayers containing tyramine, 4- ethylphenol, or phenylethylamine provided free energies of transfer of these solutes from water to various locations on the transport path. The experimentally measured partition coefficients were consistent with the free energy profiles in showing the barrier in the hydrocarbon region and preferred binding region near the interface. The substituent contributions to these free energies were also quantitatively consistent between the experiments and simulations. Specific interactions between solutes and the bilayer suggest that amphiphiles are likely to show preferred binding in the head group region and that the most of hydrogen bonds involving solutes located inside the bilayer are with water molecules. Solute re-orientation inside the bilayer lowers the partitioning barrier by allowing favorable interactions

SMARTS Approach to Chemical Data Mining and Physicochemical Property Prediction.

The calculation of physicochemical and biological properties is essential in order to facilitate modern drug discovery. Chemical spaces dimensionalized by these descriptors have been used to scaffold-hop in order to discover new lead and drug-like molecules. Broadening the boundaries of structure based drug design, these molecules are expected to share the same physiological target and have similar efficacy, as do known drug molecules sharing the same region in chemical property space. In the past few decades physicochemical and ADMET (absorption, distribution, metabolism, elimination, and toxicity) property predictors have been the subject of increased focus in academia and the pharmaceutical industry. Due to the ever increasing attention given to data mining and property predictions, we first discuss the sources of experimental pKa values and current methodologies used for pKa prediction in proteins and small molecules. Of particular concern is an analysis of the scope, statistical validity, overall accuracy, and predictive power of these methods. The expressed concerns are not limited to predicting pKa, but apply to all empirical predictive methodologies. In a bottom-up approach, we explored the influence of freely generated SMARTS string representations of molecular fragments on chelation and cytotoxicity. Later investigations, involving the derivation of predictive models, use stepwise regression to determine the optimal pool of SMARTS strings having the greatest influence over the property of interest. By applying a unique scoring system to sets of highly generalized SMARTS strings, we have constructed well balanced regression trees with predictive accuracy exceeding that of many published and commercially available models for cytotoxicity, pKa, and aqueous solubility. The methodology is robust, extremely adaptable, and can handle any molecular dataset with experimental data. This story details our struggles of data gathering, curation, and the development of a machine learning methodology able to derive and validate highly accurate regression trees capable of extremely fast property predictions. Regression trees created by our method are well suited to calculate descriptors for large in silico molecular libraries, facilitating data mining of chemical spaces in search of new lead molecules in drug discovery.Ph.D.Medicinal ChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64627/1/adamclee_1.pd

Investigating phosphate structural replacements through computational and experimental approaches

Bioisosteric replacements are used in drug design during lead generation and optimization processes with the aim to replace one functional group of a known molecule by another while retaining biological activity. The reason to use bioisosteric replacements are typically to optimize bioavailability or reducing toxicity. Phosphate groups represent a paradigm to study bioisosteric replacements. Protein-phosphate interaction plays a critical role during molecular recognition processes, and for example kinases represent one of the largest families of drug targets. However, some challenges exclude phosphate as a promising lead-like building block: i) charged phosphates do not cross molecular membranes; ii) some widely expressed proteins such as phosphatases easily hydrolyze phosphoric acid esters, which lead phosphate-containing ligands to lose their binding affinities before reaching their biological targets; iii) introduction of phosphate groups to parent scaffold is not easy. In the first part of the thesis work, I designed and implemented a computational protocol to mine information about phosphate structural replacements deposited in the Protein Data Bank. I constructed 116, 314, 271, and 42 sets of superimposed proteins where each set contains a reference protein to either POP, AMP, ADP, or ATP as well as a certain number of non-nucleotide ligands. 929 of such ligands are under study. The chemotypes that came out as structural replacements are diverse, ranging from common phosphate isosteres such as carboxyl, amide and squaramide to more surprising moieties such as benzoxaborole and aromatic ring systems. I exemplified some novel examples and interpreted the mechanism behind them. Local structural replacements are circumstance dependent: one chemical group valid in certain set-up cannot necessarily guarantee the success of another. The data from the study is available at http://86.50.168.121/phosphates_LSR.php. In the second part, I synthesized fifteen compounds retaining the adenosine moieties and bearing bioisosteric replacements of the phosphate at the ribose 5'-oxygen to test their stability toward human macro domain protein 1. These compounds are composed of either a squaryldiamide or an amide group as the bioisosteric replacement and/or as a linker. To these groups a variety of substituents were attached: phenyl, benzyl, pyridyl, carboxyl, hydroxy and tetrazolyl. Biological evaluation using differential scanning fluorimetry showed that four compounds stabilized human MDO1 at levels comparable to ADP and one at level comparable to AMP. Virtual screening was also run to identify MDO1 binding ligands. Among 20,000 FIMM database lead-like molecules, 39 compounds were selected for testing and eleven compounds found active based on ADPr and Poly-ADPr competition binding assay. The assay is however not well validated and a second confirmatory assay was conducted using calorimetry. To the best of my knowledge, this is the first report of non-endogenous ligands of the human MDO1. Altogether, this thesis highlights the versatility of molecular recognition processes that accompanies chemical replacements in compounds; this in turns shows the limits of the concepts of molecular similarity and classical bioisosterism that are based on the conservation of molecular interactions.Bioisosteeristä korvausta käytetään lääkeainekehityksessä johtolankamolekyylien tuottamisessa ja optimoinnissa. Tarkoitus on vaihtaa molekyylin funktionaalinen ryhmä toiseksi biologisen aktiivisuuden muuttumatta. Yleensä tavoitteena on parantaa biologista hyötyosuutta tai vähentää toksisuutta. Fosfaattiryhmää on tässä työssä käytetty esimerkkiryhmänä bioisosteerisiä korvauksia tutkittaessa. Väitöskirjatyön ensimmäisessä osassa suunnittelin ja toteutin tiedonlouhintaprotokollan etsiäkseni Protein Data Bank -tietokannasta korvaavia rakenteita fosfaattiryhmälle. Kokosin 116, 314, 271 ja 42 proteiiniryhmää, joissa kussakin on vertailumolekyylinä fosfaattiryhmän sisältävä POP, AMP, ADP tai ATP, ja lisäksi ei-nukleotidisiä ligandeja. Yhteensä 929 ei-nukleotidistä ligandia tutkittiin. Niistä löydettiin monipuolisesti fosfaattiryhmän korvaavia rakenteita, muun muassa yleisesti tunnettuja fosfaatin bioisosteerejä kuten karboksyyli, amidi ja squaramidi, mutta myös erikoisempia ryhmiä kuten bentsoksaboroli ja aromaattisia rengasrakenteita. Työssäni esittelen muutamia uusia rakenteita ja tulkitsen niiden vaikutusmekanismeja. Rakenteiden korvaaminen riippuu tilanteesta; yhteen tapaukseen sopiva korvaava ryhmä ei välttämättä toimi toisessa. Työn toisessa osassa syntetisoin 15 adenosiiniyhdistettä, joiden riboosiosan 5'-hapessa oleva fosfaattiryhmä on korvattu vaihtelevalla bioisosteerisellä ryhmällä. Bioisosteerisenä ryhmänä tai linkkerinä oli joko squaramidi- tai amidiryhmä. Yhdisteiden vakaus testattiin ihmisen MDO1-makrodomeeniproteiinin kanssa.Julkaisussa virheellinen verkkoaineiston ISBN 978-951-51-0045-0