Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing

ABSTRACT

Existing data on structures and biological activities are limited and distributed unevenly across distinct molecular targets and chemical compounds. The question arises if these data represent an unbiased sample of the general population of chemical-biological interactions. To answer this question, we analyzed ChEMBL data for 87,583 molecules tested against 919 protein targets using supervised and unsupervised approaches. Hierarchical clustering of the Murcko frameworks generated using Chemistry Development Toolkit showed that the available data form a big diffuse cloud without apparent structure. In contrast hereto, PASS-based classifiers allowed prediction whether the compound had been tested against the particular molecular target, despite whether it was active or not. Thus, one may conclude that the selection of chemical compounds for testing against specific targets is biased, probably due to the influence of prior knowledge. We assessed the possibility to improve (Q)SAR predictions using this fact: PASS prediction of the interaction with the particular target for compounds predicted as tested against the target has significantly higher accuracy than for those predicted as untested (average ROC AUC are about 0.87 and 0.75, respectively). Thus, considering the existing bias in the data of the training set may increase the performance of virtual screening.     

Microwave-assisted reaction of peptide formation by amino acid with phosphate:Exploration of the most possible channels for the origin of life

The formation of peptides and then protein by small abiological molecules clusters such as amino acid is a key stage in the origin of life[1]. More and more ex- perimental results showed that phosphate plays an important role in the formation of biomolecules in prebiotic chemical evolution. The principal reservoirs of biochemical energy are phosphates (such as ATP). The peculiar role of phosphates in contemporary life might suggest its essential role in prebiotic energy conversion, syntheses …     

The circular chemistry conceptual framework: A way forward to sustainability in industry 4.0

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The effect of the sintering atmosphere on the densification of B4C ceramics

Densification of boron carbide during sintering may be improved by a two-stage process, namely heating to 2000°C under vacuum and sintering at 2190°C under argon. This sintering regime allows achieving a relative density of the ceramic bodies fabricated from a fine powder higher than 95%. The nitrogen treatment of the boron carbide phase at 1900°C leads to the formation of the BN phase and precipitation of graphite. Vacuum treatment of these samples at 2000°C leads to decomposition of the boron nitride phase. The liberated free boron may again react with graphite to form in situ boron carbide particles. The experimental investigations of the sintering behavior of the boron carbide phase under various atmospheres supported the thermodynamic predictions regarding the phase transformation. No evidence, however, was found for enhanced sintering under a nitrogen atmosphere.     

Nonlocality as a feature of the physical world

Aprediction puzzle leads to a form ofnecessary realism which forces the rejection of a central tenet of the Copenhagen interpretation. This leads to reconsidering conceptual difficulties related to Bell's locality premise. It is shown that aparadox of elementary probability theory puts new light on Bell's assumption that causality and statistical independence are mutually incompatible. Nemo dat quod non habet : No one can offer more than he has ability to give; in that spirit, this paper is dedicated to the memory of J.S. Bell.     

Application of torsion angle molecular dynamics for efficient sampling of protein conformations

We investigate the application of torsion angle molecular dynamics (TAMD) to augment conformational sampling of peptides and proteins. Interesting conformational changes in proteins mainly involve torsional degrees of freedom. Carrying out molecular dynamics in torsion space does not only explicitly sample the most relevant degrees of freedom, but also allows larger integration time steps with elimination of the bond and angle degrees of freedom. However, the covalent geometry needs to be fixed during internal coordinate dynamics, which can introduce severe distortions to the underlying potential surface in the extensively parameterized modern Cartesian-based protein force fields. A "projection" approach (Katritch et al. J Comput Chem 2003, 24, 254-265) is extended to construct an accurate internal coordinate force field (ICFF) from a source Cartesian force field. Torsion crossterm corrections constructed from local molecular fragments, together with softened van der Waals and electrostatic interactions, are used to recover the potential surface and incorporate implicit bond and angle flexibility. MD simulations of dipeptide models demonstrate that full flexibility in both the backbone phi/psi and side chain chi1 angles are virtually restored. The efficacy of TAMD in enhancing conformational sampling is then further examined by folding simulations of small peptides and refinement experiments of protein NMR structures. The results show that an increase of several fold in conformational sampling efficiency can be reliably achieved. The current study also reveals some complicated intrinsic properties of internal coordinate dynamics, beyond energy conservation, that can limit the maximum size of the integration time step and thus the achievable gain in sampling efficiency.     

Retention in coupled capillary column supercritical fluid chromatography with lipids as model compounds

Summary We have investigated to which extent retention data, acquired on single capillary columns, can be used for predicting retention factors in a coupled column system. For this purpose we utilized a model mixture of 18 lipid components with widely different vapor pressures and polarities. The sample was chromatographed on two columns, SB-biphenyl-30 (70% methyl-30% biphenylpolysiloxane) and SB-cyanopropyl-50 (50% methyl-50% cyanopropylsiloxane). Experimental retention factors, acquired in coupled column systems with two columns connected in different order, were thus compared with values calculated from runs on each single column. The agreement between calculated and experimental values generally was better than 5% without any pressure drop correction.To study the possibility of predicting retention behavior in a wide pressure range from a limited number of experiments, we also investigated the relation between solute retention and mobile phase density. We found that all data could be fitted to second order equations, which gives the possibility to optimize the resolution with respect to pressure from a limited number of runs at different pressures.     

Ab initio prediction of vibrational spectra: A database approach

Efforts to develop a database of quadratic force fields for organic molecules are described. The database is based on systematic ab initio calculations, scaled to reproduce the experimentally observed frequencies. The choice of the theoretical method, the basis sets, geometries, internal coordinates and the scaling procedure are discussed. A key point in the procedure is the automatic generation of the internal valence coordinates. This is also very advantageous for geometry optimization. The database should permit the prediction of vibrational frequencies for most organic molecules to 10–20 cm⁻¹, together with semiquantitative intensities. The accuracy is sufficient to identify unknown compounds from a list of reasonable candidates.