Algorithmic Analysis of Cahn-Ingold-Prelog Rules of Stereochemistry: Proposals for Revised Rules and a Guide for Machine Implementation.

The most recent version of the Cahn-Ingold-Prelog rules for the determination of stereodescriptors as described in Nomenclature of Organic Chemistry: IUPAC Recommendations and Preferred Names 2013 (the "Blue Book"; Favre and Powell. Royal Society of Chemistry, 2014; http://dx.doi.org/10.1039/9781849733069 ) were analyzed by an international team of cheminformatics software developers. Algorithms for machine implementation were designed, tested, and cross-validated. Deficiencies in Sequence Rules 1b and 2 were found, and proposed language for their modification is presented. A concise definition of an additional rule ("Rule 6", below) is proposed, which succinctly covers several cases only tangentially mentioned in the 2013 recommendations. Each rule is discussed from the perspective of machine implementation. The four resultant implementations are supported by a 300-compound validation suite in both 2D and 3D structure data file (SDF) format as well as SMILES ( https://cipvalidationsuite.github.io/ValidationSuite ). The validation suites include all significant examples in Chapter 9 of the Blue Book, as well as several additional structures that highlight more complex aspects of the rules not addressed or not clearly analyzed in that work. These additional structures support a case for the need for modifications to the Sequence Rules.

Scaffold hopping by fragment replacement.

This work describes a data driven method for scaffold hopping by fragment replacement. A search database of scaffolds is created by cutting bonds of existing compounds in a combinatorial fashion. Three-dimensional structures of the scaffolds are then generated and made searchable based on the relative orientation of the broken bonds using an auxiliary index file. The retrieved scaffolds are ranked using volume overlap and electrostatic similarity scores. A similar approach has been used before in the program CAVEAT and others. The present work introduces a novel indexing scheme for the attachment vector geometry, which allows for fast searching. A scaffold shape descriptor is defined, which allows for queries with a single attachment vector (R-groups) and improves the shape similarity between the query and the suggested replacement fragments. The program, called Scaffold Hopping, is shown to retrieve relevant bioisosteric replacement scaffolds for a set of example queries in a reasonable time frame, making the program suitable to be used in drug design work.

Big pharma screening collections: more of the same or unique libraries? The AstraZeneca-Bayer Pharma AG case.

In this study, the screening collections of two major pharmaceutical companies (AstraZeneca and Bayer Pharma AG) have been compared using a 2D molecular fingerprint by a nearest neighborhood approach. Results revealed a low overlap between both collections in terms of compound identity and similarity. This emphasizes the value of screening multiple compound collections to expand the chemical space that can be accessed by high-throughput screening (HTS).

Automated recycling of chemistry for virtual screening and library design.

An early stage drug discovery project needs to identify a number of chemically diverse and attractive compounds. These hit compounds are typically found through high-throughput screening campaigns. The diversity of the chemical libraries used in screening is therefore important. In this study, we describe a virtual high-throughput screening system called Virtual Library. The system automatically "recycles" validated synthetic protocols and available starting materials to generate a large number of virtual compound libraries, and allows for fast searches in the generated libraries using a 2D fingerprint based screening method. Virtual Library links the returned virtual hit compounds back to experimental protocols to quickly assess the synthetic accessibility of the hits. The system can be used as an idea generator for library design to enrich the screening collection and to explore the structure-activity landscape around a specific active compound.

Molecular Docking Guided Comparative GFA, G/PLS, SVM and ANN Models of Structurally Diverse Dual Binding Site Acetylcholinesterase Inhibitors.

Recently discovered 42 AChE inhibitors binding at the catalytic and peripheral anionic site were identified on the basis of molecular docking approach, and its comparative quantitative structure-activity relationship (QSAR) models were developed. These structurally diverse inhibitors were obtained by our previously reported high-throughput in vitro screening technique using 384-well plate's assay based on colorimetric method of Ellman. QSAR models were developed using (i) genetic function algorithm, (ii) genetic partial least squares, (iii) support vector machine and (iv) artificial neural network techniques. The QSAR model robustness and significance was critically assessed using different cross-validation techniques on test data set. The generated QSAR models using thermodynamic, electrotopological and electronic descriptors showed that nonlinear methods are more robust than linear methods, and provide insight into the structural features of compounds that are important for AChE inhibition.

The binding of synthetic retinoids to lipocalin beta-lactoglobulins.

The binding of therapeutically relevant synthetic retinoid derivatives to bovine and reindeer beta-lactoglobulin (betaLG) is demonstrated using fluorescence quenching and ultrafiltration/HPLC methods. Furthermore, synthesis of methyl (E)-3-[4-[(E)-2-(2,6,6-trimethylcyclohex-1-enyl)vinyl]phenyl]-acrylate 4 and (E)-3-[4-[(E)-2-(2,6,6-trimethylcyclohex-1-enyl)vinyl]phenyl]acrylic acid 5 is described. All studied compounds bind to both betaLG homologues with nanomolar K(d) values, and the interaction diminishes the pH-dependent aggregation of retinoids. Thus, betaLG may show benefits in improving the bioavailability of retinoid derivatives.

Accurate conformation-dependent molecular electrostatic potentials for high-throughput in silico drug discovery.

The atom-centered partial charges-approximation is commonly used in current molecular modeling tools as a computationally inexpensive alternative to quantum mechanics for modeling electrostatics. Even today, the use of partial charges remains useful despite significant advances in improving the efficiency of ab initio methods. Here, we report on new parameters for the EEM and SFKEEM electronegativity equalization-based methods for rapidly determining partial charges that will accurately model the electrostatic potential of flexible molecules. The developed parameters cover most pharmaceutically relevant chemistries, and charges obtained using these parameters reproduce the B3LYP/cc-pVTZ reference electrostatic potential of a set of FDA-approved drug molecules at best to an average accuracy of 13 +/- 4 kJ mol(-1); thus, equipped with these parameters electronegativity equalization-based methods rival the current best non-quantum mechanical methods, such as AM1-BCC, in accuracy, yet incur a lower computational cost. Software implementations of EEM and SFKEEM, including the developed parameters, are included in the conformer-generation tool BALLOON, available free of charge at http://web.abo.fi/fak/mnf/bkf/research/johnson/software.php.

ShaEP: molecular overlay based on shape and electrostatic potential.

ShaEP is a tool for rigid-body superimposition and similarity evaluation of ligand-sized molecules. Molecular overlay methods traditionally work on either substructures, molecular surfaces or interaction fields, or atom-centered Gaussian functions representing the molecular volume. While substructure searches are unlikely to reveal hits that are chemically different from the template structure, the other methods are capable of "scaffold hopping". Methods that match characteristic points in interaction fields can find alignments in situations where only some portions of the structures match but potentially miss good alignments if the used point sets are not detailed enough, which in turn increases the runtime of the used graph algorithms beyond practical limits. The faster, polynomially scaling volumetric methods consider the whole space to be equally important, which works well for molecules of equal size but partial matches might go undetected. ShaEP aims to capture the strengths of both field-based and volumetric approaches. It generates initial superimpositions using a matching algorithm on graphs that coarsely represent the electrostatic potential and local shape at points close to the molecular surfaces. The initial alignments are then optimized by maximization of the volume overlap of the molecules, computed using Gaussian functions. ShaEP overlays drug-sized molecules on a subsecond timescale, allowing for the screening of large virtual libraries. The program is available free of charge from www.abo.fi/fak/mnf/bkf/research/johnson/software.php.

Binding of phenolic compounds and their derivatives to bovine and reindeer beta-lactoglobulin.

In plant-based food, phenolic compounds usually do not exist in their native form, but as esters, glycosides, or polymers. The native forms, however, require deglycosylation for their intestinal absorption, and aglycone has been considered to be the potential health-protecting/promoting form. The binding of the aglycones of phenolic compounds to bovine and reindeer beta-lactoglobulins (betaLG) using fluorescence quenching was studied. The effects of pH and storage were also studied. Of the compounds investigated, the majority of flavones, flavonols, flavanones, and isoflavones were bound to betaLG. In the pH studies, no significant effects were found. The fact that the phenolic compounds were not released at pH 2 might indicate that they bind to an external part rather than to the central cavity. Studies implicated that betaLG could act as a binder or carrier for phenolic compounds in acidic, basic, or neutral conditions and that the ligand/betaLG complex can remain stable during storage.

Generating conformer ensembles using a multiobjective genetic algorithm.

The task of generating a nonredundant set of low-energy conformations for small molecules is of fundamental importance for many molecular modeling and drug-design methodologies. Several approaches to conformer generation have been published. Exhaustive searches suffer from the exponential growth of the search space with increasing degrees of conformational freedom (number of rotatable bonds). Stochastic algorithms do not suffer as much from the exponential increase of search space and provide a good coverage of the energy minima. Here, the use of a multiobjective genetic algorithm in the generation of conformer ensembles is investigated. Distance geometry is used to generate an initial conformer, which is then subject to geometric modifications encoded by the individuals of the genetic algorithm. The geometric modifications apply to torsion angles about rotatable bonds, stereochemistry of double bonds and tetrahedral chiral centers, and ring conformations. The geometric diversity of the evolving conformer ensemble is preserved by a fitness-sharing mechanism based on the root-mean-square distance of the atomic coordinates. Molecular symmetry is taken into account in the distance calculation. The geometric modifications introduce strain into the structures. The strain is relaxed using an MMFF94-like force field in a postprocessing step that also removes conformational duplicates and structures whose strain energy remains above a predefined window from the minimum energy value found in the set. The implementation, called Balloon, is available free of charge on the Internet ( http://www.abo.fi/~mivainio/balloon/).

Similarity based virtual screening: a tool for targeted library design.

High throughput screening drug discovery utilizes large and expensive compound libraries. As an alternative, a smaller targeted library can be constructed with the aid of the 3D structure of the target molecule. We used the X-ray crystal structure of a protein homologous to the selected target in creation of a small focused library and evaluated inhibition potential of this library against Chlamydia pneumoniae, a common pathogen recently linked to atherosclerosis and risk of myocardial infarction.

McQSAR: a multiconformational quantitative structure-activity relationship engine driven by genetic algorithms.

The generation of quantitative structure-activity relationships (QSARs) under the supervision of a genetic algorithm (GA) is a QSAR modeling approach used for more than a decade. In this paper we present McQSAR, an extension to the traditional GA approach to derive QSARs. McQSAR is able to use descriptors for multiple representations per compound, such as different conformers, tautomers, or protonation forms. Test runs show that the algorithm converges to a set of representations that describe the binding mode of the set of input molecules to a reasonable resolution provided that suitable descriptors-based on the three-dimensional structure-are used. Furthermore, the frequency of chance correlation was measured during multiple runs on a real-life data set using simulated linear relationship functions. The observed frequency of chance correlation, on average 0.3 +/- 0.5%, was found independent of the size of the calibration set and the number of terms in the underlying relationship function.