Total Molecular Surface Area Research Articles

In-silico studies of 2-aminothiazole derivatives as anticancer agents by QSAR, molecular docking, MD simulation and MM-GBSA approaches

Targeting Hec1/Nek2 is considered as crucial target for cancer treatment due to its significant role in cell proliferation. In pursuit of this, a series of twenty-five 2-aminothiazoles derivatives, along with their Hec1/Nek2 inhibitory activities were subjected to QSAR studies utilizing QSARINS software. The significant three descriptor QSAR model was generated, showing noteworthy statistical parameters: a correlation coefficient of cross validation leave one out (Q2 LOO) = 0.7965, coefficient of determination (R2) = 0.8436, (R2ext) = 0.6308, cross validation leave many out (Q2LMO) = 0.7656, Concordance Correlation Coefficient (CCCCV = 0.8875), CCCtr = 0.9151, and CCCext = 0.0.7241. The descriptors integral to generated QSAR model include Moreau-Broto autocorrelation, which represents the spatial autocorrelation of a property along the molecular graph’s topological structure (ATSC1i), Moran autocorrelation at lag 8, which is weighted by charges (MATS8c) and RPSA representing the total molecular surface area. It was noted that these descriptors significantly influence Hec1/Nek2 inhibitory activity of 2-aminothiazoles derivatives. New lead molecules were designed and predicted for their Hec1/Nek2 inhibitory activity based on the developed three descriptor model. Further, the ADMET and Molecular docking studies were carried out for these designed molecules. The three molecules were selected based on their docking score and further subjected for MD simulation studies. Post-MD MM-GBSA analysis were also performed to predicted the free binding energies of molecules. The study helped us to understand the key interactions between 2-aminothiazoles derivatives and Hec1/Nek2 protein that may be necessary to develop new lead molecules against cancer. Communicated by Ramaswamy H. Sarma

Computational techniques in designing a series of 1,3,4-trisubstituted pyrazoles as unique hepatitis C virus entry inhibitors

In this study, we developed a QSAR model for studying the antiviral activity of 1,3,4-trisubstituted pyrazoles derivatives on hepatitis C virus infected in human HuH-7 cell lines. We employed random analysis to split the data sets. Statistically robust model was generated with R2, Q2 and R2pred values of 0.777, 0.731 and 0.774 respectively. The reliability of this model was confirmed by acceptable validation parameters, and this model also fulfilled the Golbraikh and Tropsha standard model conditions. Through the evaluation of selected molecular descriptors we observed that, topological charge index of order 4 (GGI4), mean topological charge index of order 1 (JGI1), octanol water partition coefficient (XlogP), 3D topological distance based autocorrelation lag5/weighted by polarizabilities (TDB5p) and total molecular surface area (FPSA-2) are the molecular properties determining biological activities of the study compounds, which shed light on the vital features that aid in the design of unique potent hepatitis C virus entry inhibitors using computer-aided drug design tools.

QSAR-Based Design of The More Potent Betulinic Acid Derivatives as HIV Maturation Inhibitor

In this study, we make QSAR models from 29 of BA derivatives’ HIV maturation inhibition activities against their 3D descriptors. The best model involve 5 descriptors as follows: 1/log EC50 = -462.275 + (69.213 × TDB6u) + (723.745 × TDB6e) + (-0.576 × FPSA-3) + (0.849 × RDF140u) + (0.302 × RDF80e) r2 training = 0.7918; Q2 test = 0.9644; r2test = 0.9798; and r2m-test = 0.9445 TDB6u and TDB6e are the 3d topological distance-based autocorrelation-lag 6 /unweighted and weighted by Sanderson electronegati-vities, respectively. FPSA-3 is the value of charge weighted partial positive surface area / total molecular surface area. RDF140u is radial distribution function-140 / unweighted. RDF80e is radial distribution function-080/weighted by relative Sanderson electronegativities. The QSAR model was then used to design and predict some of the new BA derivatives’ HIV maturation activities. The best predicted compound had pEC50 value of -0.838 and EC50 value of 0.064 nM with the chemical IUPAC name of 4‐[(1R, 3aR, 5aR, 5bR, 7aS, 11aR, 11bS, 13aS,13bS)‐5a, 5b, 8, 8, 11b pentamethyl‐1‐(prop‐1‐en‐2‐yl)‐3a[({2‐[4‐(pyrimidin2yl)piperazin-1-yl]ethyl}amino) methyl]‐icosahydro‐1H-cyclopenta[a]chrysen‐9‐yl]benzoic acid. We also suggest the synthetic route to the proposed compound.

2H-1,2,3-Triazole-chalcones as novel cytotoxic agents against prostate cancer

Prostate cancer is an important cause of death in the male population and for which there is no satisfactory chemotherapy. Herein a new series of chalcone hybrids containing 2H-1,2,3-triazole core as the ring B has been synthesized and evaluated in vitro against PC-3 prostate cancer cell line. Compounds 4a, 4c and 4e significantly reduced cell viability and showed IC50 of 28.55, 15.64 and 25.56 µM, respectively. The structure-activity relationship supported by computational chemistry points that the polarity of the molecular surface area should have some relevance to the efficiency of the compounds, in particular the ratio of the partial positive charge sites and the total molecular surface area exposed to the cell environment.

Prediction of Mass Spectral Response Factors from Predicted Chemometric Data for Druglike Molecules.

A method is developed for the prediction of mass spectral ion counts of drug-like molecules using in silico calculated chemometric data. Various chemometric data, including polar and molecular surface areas, aqueous solvation free energies, and gas-phase and aqueous proton affinities were computed, and a statistically significant relationship between measured mass spectral ion counts and the combination of aqueous proton affinity and total molecular surface area was identified. In particular, through multilinear regression of ion counts on predicted chemometric data, we find that log10(MS ion counts) = -4.824 + c 1•PA + c 2•SA, where PA is the aqueous proton affinity of the molecule computed at the SMD(aq)/M06-L/MIDI!//M06-L/MIDI! level of electronic structure theory, SA is the total surface area of the molecule in its conjugate base form, and c 1 and c 2 have values of -3.912 × 10-2 mol kcal-1 and 3.682 × 10-3 Å-2. On a 66-molecule training set, this regression exhibits a multiple R value of 0.791 with p values for the intercept, c 1, and c 2 of 1.4 × 10-3, 4.3 × 10-10, and 2.5 × 10-6, respectively. Application of this regression to an 11-molecule test set provides a good correlation of prediction with experiment (R = 0.905) albeit with a systematic underestimation of about 0.2 log units. This method may prove useful for semiquantitative analysis of drug metabolites for which MS response factors or authentic standards are not readily available. Graphical Abstract ᅟ.

Molecular Dynamic Simulations of Ocular Tablet Dissolution

Small tablets for implantation into the subconjunctival space in the eye are being developed to inhibit scarring after glaucoma filtration surgery (GFS). There is a need to evaluate drug dissolution at the molecular level to determine how the chemical structure of the active may correlate with dissolution in the nonsink conditions of the conjunctival space. We conducted molecular dynamics simulations to study the dissolution process of tablets derived from two drugs that can inhibit fibrosis after GFS, 5-fluorouracil (5-FU) and the matrix metalloprotease inhibitor (MMPi), ilomastat. The dissolution was simulated in the presence of simple point charge (SPC) water molecules, and the liquid turnover of the aqueous humor in the subconjunctival space was simulated by removal of the dissolved drug molecules at regular intervals and replacement by new water molecules. At the end of the simulation, the total molecular solvent accessible surface area of 5-FU tablets increased by 60 times more than that of ilomastat as a result of tablet swelling and release of molecules into solution. The tablet dissolution pattern shown in our molecular dynamic simulations tends to correlate with experimental release profiles. This work indicates that a series of molecular dynamic simulations can be used to predict the influence of the molecular properties of a drug on its dissolution profile and could be useful during preformulation where sufficient amounts of the drug are not always available to perform dissolution studies.

Calculation of Aqueous Solubility of Organic Compounds from Molecular Structural Properties

The quantitative structure-activity relationships (QSAR) correlations were developed for the aqueous solubility of organic compounds at 298.15, 473.15, and 573.15 K. To elucidate the molecular structural variables to control the solvation phenomena, we firstly developed the QSAR correlation of solubility of 108 organic molecules in water at 298.15 K with the use of experimentally and theoretically derivable variables. The experimental variable used was the octanol-water partition coefficient and melting point, while the theoretical variables were LUMO energy and total molecular surface area, which were determined with the COSMO-PM3 method. Based on the results at 298.15 K, the QSAR correlations for aqueous solubility at 473.15 K and 573.15 K were determined with the use of the literature solubility data for 21 compounds at these two high temperatures. It was found that the QSAR correlation with COSMO-PM3 method is able to predict the aqueous solubility of organic compounds at 473.15 and 573.15 K from the molecular structural properties and the melting temperature, since the octanol-water partition coefficient can be predicted from atom/fragment contribution method.

Molecular hologram derived quantitative structure–property relationships to predict physico-chemical properties of polychlorinated biphenyls

Polychlorinated biphenyls (PCBs) congeners with various degrees of chlorination and substitution patterns are among the most widespread and persistent man-made organic pollutants. They are toxic, lipophilic and tend to be bioaccumulated. The knowledge of the physico-chemical properties is very useful to explain the environmental behavior of PCBs and to perform an exposure assessment. In this paper, we have used a new molecular representation, the molecular hologram, to generate quantitative structure–property relationship models to predict the physico-chemical properties of biphenyl and all of its chlorinated congeners. The investigated properties include 1-octanol/water partition coefficient (log K ow), aqueous solubility (−log S w), aqueous activity coefficient (−log Y w), Total molecular surface area, Henry’s law constant (log H). The results show that this new quantitative structure–activity relationship approach presents highly predictive models for important physico-chemical properties of PCBs.

Correlation of liquid viscosity with molecular structure for organic compounds using different variable selection methods

Improved models for predicting viscosities at 20 °C were generated using three different methods for descriptor selection. Data set of 361 diverse organic molecules and their experimental viscosities were used for developing the models. Molecular properties are encoded by 822 initial descriptors computed by the CODESSA program. CODESSA, GFA and CROMRsel methods are capable of selecting good and facile viscosity models having only five descriptors. These methods are automated procedures for generation of simple multiregression (MR) models. All three methods produce excellent linear models, but the models obtained by the CROMRsel method are somewhat better. In addition, using the CROMRsel suite of programs a very good nonlinear MR model having five descriptors (two linear and three cross-product descriptors, R 2 = 0.908, S = 0.175) was obtained. Nonlinear models generated in this study show that the classical MR based methods can be efficiently used to obtain simple and very good nonlinear MR models. The best five-descriptor models selected in this study usually contain one geometrical (gravitational index) and one topological descriptor (Randic index of order 0), and three electrostatic descriptors which reflect the bonding properties of molecules, i.e. their capabilities to create (mainly) hydrogen bonds. Because of that, hydrogen-donors and hydrogen-acceptors surface areas, charges, total molecular surface areas, and maximum net atomic charges and state energies for oxygen atoms appear to be key factors for modeling the viscosity of organic molecules.

A Simple Method To Estimate the Surfactant Micelle−Water Distribution Coefficients of Aromatic Hydrocarbons

To predict surfactant micellar solubilization of aromatic hydrocarbons (arenes), a simple model is tried with the geometric mean, (π20πcmc)1/2, of the surface tension reductions, and the total molecular surface area of the arene, TSA, to estimate micelle−water distribution coefficients, KXM, in the dilute solution range. The solubilization experiment was conducted by the generator-column method. The structures of the arenes used vary from one ring to five rings and include both homopolycyclic aromatic hydrocarbons (PAH) and some hetero-PAH. The surfactant solutions are five typical surfactants. An acceptable congruence between the predicted log KXM vs log KOW correlation and the experimental log KXM vs log KOW correlation, previously published, is found. Therefore, this model may be used as an alternative tool to estimate KXM for the soil flushing/washing process.

Approximate solvent-accessible surface areas from tetrahedrally directed neighbor densities.

A fast analytical formula (TDND) has been derived for the calculation of approximate atomic and molecular solvent-accessible surface areas (SASA), as well as the first and second derivatives of these quantities with respect to atomic coordinates. Extending the work of Stouten et al. (Molecular Simulation, 1993, Vol. 10, pp. 97-120), as well as our own (Journal of Computational Chemistry, 1999, Vol. 20, pp. 586-596), the method makes use of a Gaussian function to calculate the neighbor density in four tetrahedral directions in three-dimensional space, sometimes twice with different orientations. SASA and first derivatives of the 2366 heavy atoms of penicillopepsin are computed in 0.13 s on an SGI R10000/194 MHz processor. When second derivatives are computed as well, the total time is 0.23 s. This is considerably faster than timings reported previously for other algorithms. Based on a parameterization set of nineteen compounds of different size (11-4346 atoms) and class (organics, proteins, DNA, and various complexes) consisting of a total 23,197 atoms, the method exhibits relative errors in the range 0.2-12.6% for total molecular surface areas and average absolute atomic surface area deviations in the range 1.7 to 3.6 A(2).

Approximate atomic surfaces from linear combinations of pairwise overlaps (LCPO)

A fast analytical formula was derived for the calculation of approximate atomic and molecular van der Waals (vdWSA), and solvent-accessible surface areas (SASAs), as well as the first and second derivatives of these quantities with respect to atomic coordinates. This method makes use of linear combinations of terms composed from pairwise overlaps of hard spheres; therefore, we term this the LCPO method for linear combination of pairwise overlaps. For higher performance, neighbor-list reduction (NLR) was applied as a preprocessing step. Eighteen compounds of different sizes (8–2366 atoms) and classes (organic, proteins, DNA, and various complexes) were chosen as representative test cases. LCPO/NLR computed the SASA and first derivatives of penicillopepsin, a protein with 2366 atoms, in 0.87 s (0.22 s for the creation of the neighbor list, 0.35 s for NLR, and 0.30 s for SASA and first derivatives) on an SGI R10000/194 Mhz processor. This appears comparable to or better than timings reported previously for other algorithms. The vdWSAs were in good agreement with the numerical results: relative errors for total molecular surface areas ranged from 0.1 to 2.0% and average absolute atomic surface area deviations from 0.3 to 0.7 A2. For SASAs without NLR, the LCPO method exhibited relative errors in the range of 0.4–9.2% for total molecular surface areas and average absolute atomic surface area deviations of 2.0–2.7 A2; with NLR the relative molecular errors ranged from 0.1 to 7.8% and the average absolute atomic surface area deviation from 1.6 to 3.0 A2. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 217–230, 1999

Partial Molar Volumes of Hydrophobic Compounds—Insight into the Solvation Shell? Part I

A simple model for the interaction of the solute with the solvent is presented. The relation between the molecular volume, partial molar volume, and the volume of the solvation shell of the compound studied is expressed by the α parameter, defined as the relative density of the solvation shell. The values of α are calculated for many organic compounds in aqueous solutions. It is stated that in a given series of compounds, α depends strongly on the number of CH2 groups in the compound studied. The correlation of α and the polarity (defined as the ratio of the surface area of polar groups and atoms exposed to the total molecular surface area of the molecule studied) was found.

Organotin compounds and aquatic bacteria: A review

Organotins are toxic to microorganisms. Trisubstituted organotins (R3SnX) are considered more toxic than disubstituted (R2SnX2) or monosubstituted (RSnX3) compounds, and tetrasubstituted compounds (R4Sn) are not considered toxic. In the R3Sn series propyl-, butyl-, pentyl-, phenyl- and cyclohexyltins are the most toxic to microorganisms. Toxicity towards aerobes in the R3Sn series is related to total molecular surface area and to the octanol: water partition coefficient,Kow, which is a measure of hydrophobicity. Care must be taken when testing the toxicity of tin compounds in the laboratory, for a number of biological, chemical and physical factors can influence the apparent toxicity. Although TBT is generally the most toxic of the butyltins, there are instances where monobutyltin (MBT) is as toxic, or more toxic, than TBT to microorganisms. Thus, debutylation in the sequence TBT→DBT→MBT→Sn does not detoxity TBT for all microorganisms. Some microorganisms can methylate inorganic or organic tins under aerobic or anaerobic conditions. Methylation can also occur by chemical means and the relative contributions of biotic and abiotic mechanisms are not clear. It is difficult to isolate a pure culture which can methylate tin compounds aerobically, and it is difficult to isolate a pure culture which degrades TBT, suggesting that microbial consortiums may be involved in transformations of organotins in the aquatic environment. Methylation and debutylation alter the adsorbtivity and solubility of tin compounds; thus microorganisms can influence the environmental mobility of tin. TBT-resistant microorganisms can be isolated, and in some of them resistance to TBT can be plasmid-mediated.

Evaluation of total molecular surface area for predicting air-water partitioning properties of hydrophobic aromatic chemicals

Aqueous solubilities of various substituted naphthalenes and terphenyls have been measured and quantitative structure property relationships (QSPRs) using total molecular surface area (TSA) have been evaluated for predicting aqueous solubility and saturation vapor pressure of hydrophobic organic contaminants. Methods for calculating TSA and assumptions for estimating the molar free energy of fusion were examined. Substantial improvements in model predictive capability compared to previously published relationships was observed when TSA is calculated using energy minimized (sterically viable) molecular coordinates and a consistent set of van der Waals radii. The model equation developed between TSA and mole fraction solubility permits aqueous solubility predictions of aromatic chemicals from 5°C to 40°C with an average absolute factor of error (AFE) of 2.2. However, a similar relation between TSA and saturation vapor pressure (p sat) was not in agreement with experimental data.

Quantum mechanical parametrization of a conformationally dependent hydrophobic index

AbstractAn extension of our previous work on the development of a conformationally dependent hydrophobic index is presented. The parameter was computed in four alternative ways based on steric parameters, such as the total molecular surface area or the solvent accessible surface, and on quantum mechanically computed electronic properties, such as the molecular dipole moment, Mulliken charge densities, and a lone–pair index. The method was parametrized based on 110 rigid analogs and all properties required were calculated using the semiempirical methods PM3, AM1, and MNDO. Examples of the application of this method in calculating hydrophobic indices are presented.

Quantitative Structure-property Relationships for Aqueous Solubilities of Halogenated Aromatic Compounds

Abstract Quantitative structure-property relationships (QSPRs) have been examined for the aqueous solubility of halogenated benzenes, polychlorobiphenyls, polybromobiphenyls, and polychloronaphthalenes at 20 to 25°C. Multiple regression correlations of aqueous mole fraction solubility (X) with molecular size descriptors (molecular weight, total molecular surface area, or various zero-order molecular connectivity indices) and a combined molecular symmetry and structure descriptor (R ∗ Molecular size descriptor) are reported. A generalized correlation takes the form of where 1 ≤ m ≤ 2, ai refers to the ith regression coefficient, and R is a molecular redundancy index. The best correlation found, from the standpoint of reduced standard deviations and calculational simplicity, does not contain a melting temperature term (a 2 = 0). Derived QSPRs enable estimation of aqueous solubilities based solely on structural information.

Prediction of environmental parameters by adsorbability index: Water solubilities of hydrophobic organic pollutants

The adsorbability index proposed by Abe et al. to predict the activated carbon adsorption of organic compounds from aqueous solutions was found to be an effective parameter for predicting the water solubilities of 265 hydrophobic organic pollutants which were classified into 118 aliphatic compounds and 88 mono- and 59 polynuclear aromatic compounds; and, furthermore, for predicting the total molecular surface areas of these compounds.

Atom based parametrization for a conformationally dependent hydrophobic index

AbstractAn atomic parametrization for the determination of a hydrophobicity index that depends on the molecular conformation is presented. The hydrophobicity parameter was calculated in four alternative ways based on charge densities and atomic contributions to the total molecular surface area and depending on the approach, the molecular dipole moment. The geometries required for the computations were calculated using quantum mechanical semiempirical methods as well as molecular mechanics. The charges were computed using semiempirical methods as well as the Gasteiger method.

Pattern of organotin inhibition of methanogenic bacteria

Seven organotin compounds and tin chloride were tested for their effects on the methanogenic bacteria Methanococcus thermolithotrophicus, Methanococcus deltae delta LH, and Methanosarcina barkeri 227. The methanogens were strongly inhibited by triethyltin, tripropyltin, and monophenyltin compounds, generally at concentrations below 0.05 mM. Less inhibition by tributyltin and diphenyltin was observed at levels below 0.1 mM, but complete inhibition was observed at a 1 mM concentration. Tin chloride inhibited all methanogens, with nearly complete inhibition at a 1 mM concentration. There was no inhibition by tetra-n-butyltin and triphenyltin compounds even at 2 mM, the highest concentration tested. The 50 and 100% inhibitory concentrations of all compounds were estimated; these values varied with both the compound tested and the bacterium tested. The 50% inhibitory concentration estimate generally decreased (i.e., giving a higher toxicity) as the total surface area of the alkyltin molecules decreased. These results differ considerably from those reported previously for aerobic microorganisms (G. Eng, E. J. Tierney, J. M. Bellama, and F. E. Brinckman, Appl. Organometallic Chem. 2:171-175, 1988), where a clear correlation between increasing total molecular surface area and increasing toxicity was documented with a variety of organisms. Using the same procedures as for the methanogens, we examined the effects of organotin compounds on Escherichia coli growing aerobically or anaerobically. The E. coli inhibition pattern clearly resembled that seen in the data of Eng et al., under both aerobic and anaerobic conditions.