PubChem3D: Diversity of shape

<p>Abstract</p> <p>Background</p> <p>The shape diversity of 16.4 million biologically relevant molecules from the PubChem Compound database and their 1.46 billion diverse conformers was explored as a function of molecular volume.</p> <p>Results</p> <p>The diversity of shape space was investigated by determining the shape similarity threshold to achieve a maximum on the count of reference shapes per unit of conformer volume. The rate of growth in shape space, as represented by a decreasing shape similarity threshold, was found to be remarkably smooth as a function of volume. There was no apparent correlation between the count of conformers per unit volume and their diversity, meaning that a single reference shape can describe the shape space of many chemical structures. The ability of a volume to describe the shape space of lesser volumes was also examined. It was shown that a given volume was able to describe 40-70% of the shape diversity of lesser volumes, for the majority of the volume range considered in this study.</p> <p>Conclusion</p> <p>The relative growth of shape diversity as a function of volume and shape similarity is surprisingly uniform. Given the distribution of chemicals in PubChem versus what is theoretically synthetically possible, the results from this analysis should be considered a conservative estimate to the true diversity of shape space.</p

Confab - Systematic generation of diverse low-energy conformers

<p>Abstract</p> <p>Background</p> <p>Many computational chemistry analyses require the generation of conformers, either on-the-fly, or in advance. We present Confab, an open source command-line application for the systematic generation of low-energy conformers according to a diversity criterion.</p> <p>Results</p> <p>Confab generates conformations using the 'torsion driving approach' which involves iterating systematically through a set of allowed torsion angles for each rotatable bond. Energy is assessed using the MMFF94 forcefield. Diversity is measured using the heavy-atom root-mean-square deviation (RMSD) relative to conformers already stored. We investigated the recovery of crystal structures for a dataset of 1000 ligands from the Protein Data Bank with fewer than 1 million conformations. Confab can recover 97% of the molecules to within 1.5 Å at a diversity level of 1.5 Å and an energy cutoff of 50 kcal/mol.</p> <p>Conclusions</p> <p>Confab is available from <url>http://confab.googlecode.com</url>.</p

Keeping global warming within 1.5°C constrains emergence of aridification

Aridity – the ratio of atmospheric water supply (precipitation; P) to demand (potential evapotranspiration; PET) – is projected to decrease (i.e., become drier) as a consequence of anthropogenic climate change, aggravating land degradation and desertification. However, the timing of significant aridification relative to natural variability – defined here as the time of emergence for aridification (ToEA) – is unknown, despite its importance in designing and implementing mitigation policy. Here we estimate ToEA from projections of 27 global climate models (GCMs) under Representative Concentration Pathways (RCPs) RCP4.5 and RCP8.5, and in doing so, identify where emergence occurs before global mean warming reaches 1.5°C and 2°C above the pre-industrial level. Based on the ensemble median ToEA for each grid cell, aridification emerges over 32% (RCP4.5) and 24% (RCP8.5) of the total land surface before the ensemble median of global mean temperature change reaches 2°C in each scenario. Moreover, ToEA is avoided in about two-thirds of the above regions if the maximum global warming level is limited to 1.5°C. Early action for accomplishing the 1.5°C temperature goal can therefore dramatically reduce the likelihood of large regions facing significant aridification and related potential impacts

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used

Development and validation of an improved algorithm for overlaying flexible molecules

A program for overlaying multiple flexible molecules has been developed. Candidate overlays are generated by a novel fingerprint algorithm, scored on three objective functions (union volume, hydrogen-bond match, and hydrophobic match), and ranked by constrained Pareto ranking. A diverse subset of the best ranked solutions is chosen using an overlay-dissimilarity metric. If necessary, the solutions can be optimised. A multi-objective genetic algorithm can be used to find additional overlays with a given mapping of chemical features but different ligand conformations. The fingerprint algorithm may also be used to produce constrained overlays, in which user-specified chemical groups are forced to be superimposed. The program has been tested on several sets of ligands, for each of which the true overlay is known from protein–ligand crystal structures. Both objective and subjective success criteria indicate that good results are obtained on the majority of these sets

PubChem3D: a new resource for scientists

<p>Abstract</p> <p>Background</p> <p>PubChem is an open repository for small molecules and their experimental biological activity. PubChem integrates and provides search, retrieval, visualization, analysis, and programmatic access tools in an effort to maximize the utility of contributed information. There are many diverse chemical structures with similar biological efficacies against targets available in PubChem that are difficult to interrelate using traditional 2-D similarity methods. A new layer called PubChem3D is added to PubChem to assist in this analysis.</p> <p>Description</p> <p>PubChem generates a 3-D conformer model description for 92.3% of all records in the PubChem Compound database (when considering the parent compound of salts). Each of these conformer models is sampled to remove redundancy, guaranteeing a minimum (non-hydrogen atom pair-wise) RMSD between conformers. A diverse conformer ordering gives a maximal description of the conformational diversity of a molecule when only a subset of available conformers is used. A pre-computed search per compound record gives immediate access to a set of 3-D similar compounds (called "Similar Conformers") in PubChem and their respective superpositions. Systematic augmentation of PubChem resources to include a 3-D layer provides users with new capabilities to search, subset, visualize, analyze, and download data.</p> <p>A series of retrospective studies help to demonstrate important connections between chemical structures and their biological function that are not obvious using 2-D similarity but are readily apparent by 3-D similarity.</p> <p>Conclusions</p> <p>The addition of PubChem3D to the existing contents of PubChem is a considerable achievement, given the scope, scale, and the fact that the resource is publicly accessible and free. With the ability to uncover latent structure-activity relationships of chemical structures, while complementing 2-D similarity analysis approaches, PubChem3D represents a new resource for scientists to exploit when exploring the biological annotations in PubChem.</p

Inhibitors of Helicobacter pylori Protease HtrA Found by ‘Virtual Ligand’ Screening Combat Bacterial Invasion of Epithelia

Background: The human pathogen Helicobacter pylori (H. pylori) is a main cause for gastric inflammation and cancer. Increasing bacterial resistance against antibiotics demands for innovative strategies for therapeutic intervention. Methodology/Principal Findings: We present a method for structure-based virtual screening that is based on the comprehensive prediction of ligand binding sites on a protein model and automated construction of a ligand-receptor interaction map. Pharmacophoric features of the map are clustered and transformed in a correlation vector (‘virtual ligand’) for rapid virtual screening of compound databases. This computer-based technique was validated for 18 different targets of pharmaceutical interest in a retrospective screening experiment. Prospective screening for inhibitory agents was performed for the protease HtrA from the human pathogen H. pylori using a homology model of the target protein. Among 22 tested compounds six block E-cadherin cleavage by HtrA in vitro and result in reduced scattering and wound healing of gastric epithelial cells, thereby preventing bacterial infiltration of the epithelium. Conclusions/Significance: This study demonstrates that receptor-based virtual screening with a permissive (‘fuzzy’) pharmacophore model can help identify small bioactive agents for combating bacterial infection

Optimal assignment methods for ligand-based virtual screening

<p>Abstract</p> <p>Background</p> <p>Ligand-based virtual screening experiments are an important task in the early drug discovery stage. An ambitious aim in each experiment is to disclose active structures based on new scaffolds. To perform these "scaffold-hoppings" for individual problems and targets, a plethora of different similarity methods based on diverse techniques were published in the last years. The optimal assignment approach on molecular graphs, a successful method in the field of quantitative structure-activity relationships, has not been tested as a ligand-based virtual screening method so far.</p> <p>Results</p> <p>We evaluated two already published and two new optimal assignment methods on various data sets. To emphasize the "scaffold-hopping" ability, we used the information of chemotype clustering analyses in our evaluation metrics. Comparisons with literature results show an improved early recognition performance and comparable results over the complete data set. A new method based on two different assignment steps shows an increased "scaffold-hopping" behavior together with a good early recognition performance.</p> <p>Conclusion</p> <p>The presented methods show a good combination of chemotype discovery and enrichment of active structures. Additionally, the optimal assignment on molecular graphs has the advantage to investigate and interpret the mappings, allowing precise modifications of internal parameters of the similarity measure for specific targets. All methods have low computation times which make them applicable to screen large data sets.</p

Drugs and drug-like molecules can modulate the function of mucosal-associated invariant T cells

The major-histocompatibility-complex-(MHC)-class-I-related molecule MR1 can present activating and non-activating vitamin-B-based ligands to mucosal-associated invariant T cells (MAIT cells). Whether MR1 binds other ligands is unknown. Here we identified a range of small organic molecules, drugs, drug metabolites and drug-like molecules, including salicylates and diclofenac, as MR1-binding ligands. Some of these ligands inhibited MAIT cells ex vivo and in vivo, while others, including diclofenac metabolites, were agonists. Crystal structures of a T cell antigen receptor (TCR) from a MAIT cell in complex with MR1 bound to the non-stimulatory and stimulatory compounds showed distinct ligand orientations and contacts within MR1, which highlighted the versatility of the MR1 binding pocket. The findings demonstrated that MR1 was able to capture chemically diverse structures, spanning mono- and bicyclic compounds, that either inhibited or activated MAIT cells. This indicated that drugs and drug-like molecules can modulate MAIT cell function in mammals