Marc C. Nicklaus

Conformational changes of small molecules binding to proteins

Flexible molecules change their conformation upon binding to a protein. This was shown by the analysis of small molecules whose structures have been determined by X-ray crystallography of both the pure compound and the compound bound to a protein. Thirty-three compounds present both in the Cambridge Structural Database and the Brookhaven Protein Data Bank were analyzed, and both were compared with the global energy minimum conformation calculated by the molecular mechanics program CHARMm. It was found that the conformation bound to the protein differs from that in the crystal structure and also from that of the global energy minimum, and the degree of deformation depends upon the number of freely rotatable bonds in the molecule. Analysis of the conformational energies of the flexible molecules showed that, for most of those compounds, both the crystal and the protein-bound conformations are energetically well above the global minimum, and, in many cases, not even in any local energy minimum. Semi-empirical calculations performed for a select number of structures, using both the AM1 and PM3 hamiltonians, confirmed these results. These findings are discussed as to their impact upon contemporary methods of drug design.

National Cancer Institute Drug Information System 3D database

A searcheable database of three-dimensional structures has been developed from the chemistry database of the NCI Drug Information System (DIS), a file of about 450,000 primarily organic compounds which have been tested by NCI for anticancer activity. The DIS database is very similar in size and content to the proprietary databases used in the pharmaceutical industry; its development began in the 1950s; and this history led to a number of problems in the generation of 3D structures.

Comparison of Nine Programs Predicting pKa Values of Pharmaceutical Substances

Knowledge of the possible ionization states of a pharmaceutical substance, embodied in the pK(a) values (logarithm of the acid dissociation constant), is vital for understanding many properties essential to drug development. We compare nine commercially available or free programs for predicting ionization constants. Eight of these programs are based on empirical methods: ACD/pK(a) DB 12.0, ADME Boxes 4.9, ADMET Predictor 3.0, Epik 1.6, Marvin 5.1.4, Pallas pKalc Net 2.0, Pipeline Pilot 5.0, and SPARC 4.2; one program is based on a quantum chemical method: Jaguar 7.5. We compared their performances by applying them to 197 pharmaceutical substances with 261 carefully determined and highly reliable experimental pK(a) values from a literature source. The programs ADME Boxes 4.9, ACD/pK(a) DB 12.0, and SPARC 4.2 ranked as the top three with mean absolute deviations of 0.389, 0.478, and 0.651 and r(2) values of 0.944, 0.908, and 0.894, respectively. ACD/pK(a) DB 12.0 predicted all sites, whereas ADME Boxes 4.9 and SPARC 4.2 failed to predict 5 and 18 sites, respectively. The performance of the quantum chemical-based program Jaguar 7.5 was not as expected, with a mean absolute deviation of 1.283 and an r(2) value of 0.579, indicating the potential for further development of this type of approach to pK(a) prediction.

Polo-box domain: a versatile mediator of polo-like kinase function

Members of the polo subfamily of protein kinases have emerged as important regulators in diverse aspects of the cell cycle and cell proliferation. A large body of evidence suggests that a highly conserved polo-box domain (PBD) present in the C-terminal non-catalytic region of polo kinases plays a pivotal role in the function of these enzymes. Recent advances in our comprehension of the mechanisms underlying mammalian polo-like kinase 1 (Plk1)-dependent protein–protein interactions revealed that the PBD serves as an essential molecular mediator that brings the kinase domain of Plk1 into proximity with its substrates, mainly through phospho-dependent interactions with its target proteins. In this review, current understanding of the structure and functions of PBD, mode of PBD-dependent interactions and substrate phosphorylation, and other phospho-independent functions of PBD are discussed.

Optical Structure Recognition Software To Recover Chemical Information: OSRA — An Open Source Solution

Until recently most scientific and patent documents dealing with chemistry have described molecular structures either with systematic names or with graphical images of Kekulé structures. The latter method poses inherent problems in the automated processing that is needed when the number of documents ranges in the hundreds of thousands or even millions since graphical representations cannot be directly interpreted by a computer. To recover this structural information, which is otherwise all but lost, we have built an optical structure recognition application based on modern advances in image processing implemented in open source tools, OSRA. OSRA can read documents in over 90 graphical formats including GIF, JPEG, PNG, TIFF, PDF, and PS, automatically recognizes and extracts the graphical information representing chemical structures in such documents, and generates the SMILES or SD representation of the encountered molecular structure images.

Enhanced CACTVS Browser of the Open NCI Database

A Web-based, graphical user interface has been developed to conduct rapid searches by numerous criteria in the more than 250,000 structures of the Open NCI Database. It is based on the chemistry information toolkit CACTVS. Nearly all structures and anticancer and anti-HIV screening data provided by NCIs Developmental Therapeutics Program have been included. This data set has been augmented by a large amount of additional, mostly computed, data, such as calculated log P values, predicted biological activities, systematically determined names, and others. Complex boolean searches are possible. Flexible substructure searches have been implemented. The user can conduct 3D pharmacophore queries in up to 25 conformations precalculated for each compound. Numerous output formats as well as 2D and 3D visualization options are provided. It is possible to export search results in various forms and with choices for data contents in the exported files, for structure sets ranging in size from a single compound to the entire database. Only a Web browser is needed to use this service, with a few plug-ins being useful but optional.

CERAPP : Collaborative Estrogen Receptor Activity Prediction Project

Background: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. Objectives: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. Methods: CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure–activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies. Results: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing. Conclusion: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points. Citation: Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E, Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg SA, Slavov S, Hu X, Judson RS. 2016. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environ Health Perspect 124:1023–1033; http://dx.doi.org/10.1289/ehp.1510267

Software and resources for computational medicinal chemistry

Computer-aided drug design plays a vital role in drug discovery and development and has become an indispensable tool in the pharmaceutical industry. Computational medicinal chemists can take advantage of all kinds of software and resources in the computer-aided drug design field for the purposes of discovering and optimizing biologically active compounds. This article reviews software and other resources related to computer-aided drug design approaches, putting particular emphasis on structure-based drug design, ligand-based drug design, chemical databases and chemoinformatics tools.

Total synthesis and biological evaluation of largazole and derivatives with promising selectivity for cancers cells.

The efficient total synthesis of the natural substance largazole is described. Using this strategy, a small library of largazole analogs was developed. Structure-activity relationship studies suggested that the geometry of the alkene in the side chain is critical. While the largazoles analogues with trans-alkene are potent for the antiproliferative effect, those with cis-alkene are completely inactive. Most importantly, replacement of valine with tyrosine in largazole increased selectivity toward human cancer cells over human normal cells more than 100-fold.

Synthesis of cyclopropane-fused dideoxycarbocyclic nucleosides structurally related to neplanocin C

Abstract The syntheses of five novel carbocyclic dideoxynucleosides with a bicyclo[3.1.0]hexane skeleton was accomplished via a Mitsunobu-type coupling reaction with various heterocyclic bases. These compounds appear to prefer a typical nucleoside northern conformation.