A novel and robust automated docking method that predicts the bound conformations of flexible ligands to macromolecular targets has been developed and tested, in combination with a new scoring function that estimates the free energy change upon binding. Interestingly, this method applies a Lamarckian model of genetics, in which environmental adaptations of an individual's phenotype are reverse transcribed into its genotype and become . heritable traits sic . We consider three search methods, Monte Carlo simulated annealing, a traditional genetic algorithm, and the Lamarckian genetic algorithm, and compare their performance in dockings of seven protein)ligand test systems having known three-dimensional structure. We show that both the traditional and Lamarckian genetic algorithms can handle ligands with more degrees of freedom than the simulated annealing method used in earlier versions of AUTODOCK, and that the Lamarckian genetic algorithm is the most efficient, reliable, and successful of the three. The empirical free energy function was calibrated using a set of 30 structurally known protein)ligand complexes with experimentally determined binding constants. Linear regression analysis of the observed binding constants in terms of a wide variety of structure-derived molecular properties was performed. The final model had a residual standard y1 y1 .

/pdf/automated-docking-using-a-lamarckian-genetic-algorithm-and-2t6y95r7fm.pdf

Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function

The role of fluorine in drug design and development is expanding rapidly as we learn more about the unique properties associated with this unusual element and how to deploy it with greater sophistication. The judicious introduction of fluorine into a molecule can productively influence conformation, pKa, intrinsic potency, membrane permeability, metabolic pathways, and pharmacokinetic properties. In addition, 18F has been established as a useful positron emitting isotope for use with in vivo imaging technology that potentially has extensive application in drug discovery and development, often limited only by convenient synthetic accessibility to labeled compounds. The wide ranging applications of fluorine in drug design are providing a strong stimulus for the development of new synthetic methodologies that allow more facile access to a wide range of fluorinated compounds. In this review, we provide an update on the effects of the strategic incorporation of fluorine in drug molecules and applications in po...

Applications of Fluorine in Medicinal Chemistry

Introduction
PaDEL-Descriptor is a software for calculating molecular descriptors and fingerprints. The software currently calculates 797 descriptors (663 1D, 2D descriptors, and 134 3D descriptors) and 10 types of fingerprints. These descriptors and fingerprints are calculated mainly using The Chemistry Development Kit. Some additional descriptors and fingerprints were added, which include atom type electrotopological state descriptors, McGowan volume, molecular linear free energy relation descriptors, ring counts, count of chemical substructures identified by Laggner, and binary fingerprints and count of chemical substructures identified by Klekota and Roth.

Methods
PaDEL-Descriptor was developed using the Java language and consists of a library component and an interface component. The library component allows it to be easily integrated into quantitative structure activity relationship software to provide the descriptor calculation feature while the interface component allows it to be used as a standalone software. The software uses a Master/Worker pattern to take advantage of the multiple CPU cores that are present in most modern computers to speed up calculations of molecular descriptors.

Results
The software has several advantages over existing standalone molecular descriptor calculation software. It is free and open source, has both graphical user interface and command line interfaces, can work on all major platforms (Windows, Linux, MacOS), supports more than 90 different molecular file formats, and is multithreaded.

Conclusion
PaDEL-Descriptor is a useful addition to the currently available molecular descriptor calculation software. The software can be downloaded at http://padel.nus.edu.sg/software/padeldescriptor. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.21707

PaDEL‐descriptor: An open source software to calculate molecular descriptors and fingerprints

Publisher Summary Lectins play an important role in the development of immunology. Lectins also find application in serological laboratories for typing blood and determining secretor status, separating leucocytes from erythrocytes, and agglutinating cells from blood in the preparation of plasma. They serve as reagents for the detection, isolation, and characterization of carbohydrate-containing macromolecules, including blood-group antigens. In their interaction with saccharides, lectins serve as models for carbohydrate-specific antibodies, with the important advantage to purify lectins in gram quantities. Lectins are classified according to their carbohydrate-binding specificity that includes D-mannose(D-glucose)-binding lectins and 2-acetamido-2-deoxy-D-glucose-binding lectins. The chapter considers only those lectins that have been purified to homogeneity, and studied with regard to their biophysical, biochemical, and carbohydrate-binding specificity. The chapter also describes the cell-binding and biological properties of lectins. The chapter concludes with the description of several glycopeptide structures showing the carbohydrate-binding loci with which various lectins interact.

The lectins : carbohydrate-binding proteins of plants and animals

Quantitative structure–activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists toward collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR stu...

/pdf/qsar-modeling-where-have-you-been-where-are-you-going-to-3pmdjik36j.pdf

QSAR Modeling: Where have you been? Where are you going to?

A New Substituent Constant, π, Derived from Partition Coefficients

Substituent constants for aliphatic functions obtained from partition coefficients.

Evidence is presented to show that, assuming other factors constant, the variation in biological response in a set of congeneric drugs can be represented as a function of the partition coefficient. The form of this function is the same as the form of the normal distribution. Building upon this foundation, one can use substituent constants to quantitatively separate the hydrophobic bonding and the electronic and steric effects of substituents.

ACKNOWLEDGMENT This work was supported by Research Grant GM-07492 from the National Institutes of Health.

The use of a hydrophobic bonding constant for structure-activity correlations.

The use of substituent constants in the correlation of demethylation rates.

Substituent constants and regression analysis have been used to correlate the localization of substituted benzeneboronic acids in brain and tumor tissue of mice It is shown that localization in the brain can be rationalized in terms of one parameter, π, obtained from octanol: water partition coefficients Localization in the tumor depends on an additional electronic parameter, δ Localization in the boronic acid series is compared with biologic activity in a series of barbituric acids

ACKNOWLEDGMENT This work was supported by Research Grant GM-07492 from the National Institutes of Health We thank Edna W Deutsch for assistance in the preparation of the manuscript

Junkichi Iwasa

Papers

A New Substituent Constant, π, Derived from Partition Coefficients

Substituent constants for aliphatic functions obtained from partition coefficients.

The use of a hydrophobic bonding constant for structure-activity correlations.

The use of substituent constants in the correlation of demethylation rates.

The correlation of localization rates of benzeneboronic acids in brain and tumor tissue with substituent constants.