Consensus virtual screening approaches to predict protein ligands

In order to exploit the advantages of receptor-based virtual screening, namely time/cost saving and specificity, it is important to rely on algorithms that predict a high number of active ligands at the top ranks of a small molecule database. Towards that goal consensus methods combining the results of several docking algorithms were developed and compared against the individual algorithms. Furthermore, a recently proposed rescoring method based on drug efficiency indices was evaluated. Among AutoDock Vina 1.0, AutoDock 4.2 and GemDock, AutoDock Vina was the best performing single method in predicting high affinity ligands from a database of known ligands and decoys. The rescoring of predicted binding energies with the water/butanol partition coeffcient did not lead to an improvement averaged over all receptor targets. Various consensus algorithms were investigated and a simple combination of AutoDock and AutoDock Vina results gave the most consistent performance that showed early enrichment of known ligands for all receptor targets investigated. In case a number ligands is known for a specific target, every method proposed in this study should be evaluated

Octanol-water partition coefficients of highly hydrophobic photodynamic therapy drugs: a computational study

Photodynamic therapy is a novel treatment for solid tumorsbased on the selective induction of cell death by the generation of cytotoxic reactive oxygen species within neoplastic tissues. Oxygen photosensitization is promoted as a consequence of the activation (using light) of a photosensitizer, which must reach the desired tissue by cellular transport. Hydrophobicity (expressed as the logarithm of octanol/water partition coefficient, logP), becomes a key factor in these processes. Unfortunately, there is no computational method to unambiguously predict the logP value for high hydrophobic photosensitizers. In this study, a total of 12 computational methods have been tested for predicting the logP value of tetrapyrrolic derivatives. Furthermore, in the attempt to correlate logP with experimental HPLC measurements (log(k’)), validation of the results leads to the proposal of a sigmoidal regression for the two parameters (log(k’) and logP)

Highly Hydrophilic and Lipophilic Derivatives of Bile Salts

Lipophilicity of 15 derivatives of sodium cholate, defined by the octan-1-ol/water partition coefficient (log P), has been theoretically determined by the Virtual log P method. These derivatives bear highly hydrophobic or highly hydrophilic substituents at the C3 position of the steroid nucleus, being linked to it through an amide bond. The difference between the maximum value of log P and the minimum one is enlarged to 3.5. The partition coefficient and the critical micelle concentration (cmc) are tightly related by a double-logarithm relationship (VirtuallogP=−(1.00±0.09)log(cmcmM)+(2.79±0.09)), meaning that the Gibbs free energies for the transfer of a bile anion from water to either a micelle or to octan-1-ol differ by a constant. The equation also means that cmc can be used as a measurement of lipophilicity. The demicellization of the aggregates formed by three derivatives of sodium cholate bearing bulky hydrophobic substituents has been studied by surface tension and isothermal titration calorimetry. Aggregation numbers, enthalpies, free energies, entropies, and heat capacities, ΔCP,demic, were obtained. ΔCP,demic, being positive, means that the interior of the aggregates is hydrophobicThis work was funded by the Ministerio de Ciencia y Tecnología, Spain (Project MAT2017-86109P)S

MRlogP:Transfer learning enables accurate logP prediction using small experimental training datasets

Small molecule lipophilicity is often included in generalized rules for medicinal chemistry. These rules aim to reduce time, effort, costs, and attrition rates in drug discovery, allowing the rejection or prioritization of compounds without the need for synthesis and testing. The availability of high quality, abundant training data for machine learning methods can be a major limiting factor in building effective property predictors. We utilize transfer learning techniques to get around this problem, first learning on a large amount of low accuracy predicted logP values before finally tuning our model using a small, accurate dataset of 244 druglike compounds to create MRlogP, a neural network-based predictor of logP capable of outperforming state of the art freely available logP prediction methods for druglike small molecules. MRlogP achieves an average root mean squared error of 0.988 and 0.715 against druglike molecules from Reaxys and PHYSPROP. We have made the trained neural network predictor and all associated code for descriptor generation freely available. In addition, MRlogP may be used online via a web interface

Martini 3 Coarse-Grained Model for Second-Generation Unidirectional Molecular Motors and Switches

[Image: see text] Artificial molecular motors (MMs) and switches (MSs), capable of undergoing unidirectional rotation or switching under the appropriate stimuli, are being utilized in multiple complex and chemically diverse environments. Although thorough theoretical work utilizing QM and QM/MM methods have mapped out many of the critical properties of MSs and MMs, as the experimental setups become more complex and ambitious, there is an ever increasing need to study the behavior and dynamics of these molecules as they interact with their environment. To this end, we have parametrized two coarse-grained (CG) models of commonly used MMs and a model for an oxindole-based MS, which can be used to study the ground state behavior of MMs and MSs in large simulations for significantly longer periods of time. We also propose methods to perturb these systems which can allow users to approximate how such systems would respond to MMs rotating or the MSs switching

Липофильность BODIPY флуорофоров и их распределение в системе октанол-1–вода

The work covers synthesis and lipophilicity estimation of several BODIPY dyes. For these compounds, the distribution between 1-octanol and water layers is experimentally described and the corresponding partition coefficients LogP are calculated. The experimental LogP values are compared with popular fragment-based methods XLopP3, ALogPS, WLogP, SILICOS-IT and MLogP. Additionally, the hydrophobic and polar surface areas are found with quantum-mechanical calculations. That allowed to find a correlation between the LogP coefficient and the molecular surface topology, as well as to determine the corresponding incremental values of the methyl, acetyl, and phenyl substituents. Выполнен синтез нескольких BODIPY флуорофоров и рассмотрено их распределение в системе октанол-1–вода. Для оценки эффективности использования расчетных методов при описании липофильности BODIPY производных обсуждены такие подходы, как XLopP3, ALogPS, WLogP, SILICOS-IT и MLogP. С помощью квантово-механических расчетов найдены гидрофобная и полярная площади молекулярных поверхностей соединений. Это позволило установить корреляцию между коэффициентом LogP и топологией молекулярной поверхности, а также определить соответствующие величины инкрементов для метильного, ацетильного и фенильного заместителей

Molecular Modeling Of Energetic Materials And Chemical Warfare Agents

Contamination of military sites by energetic materials and chemical warfare agents is a growing problem. To avoid health hazards associated with these compounds, it is necessary to decontaminate or remediate the contaminated sites. Effective decontamination requires knowledge of environmental fate of contaminants and the appropriate remediation methodologies. While the fate of chemical warfare agents are well studied, the impact of certain energetic materials in the environment is relatively unknown. So the current focus is determining environmental fate of Insensitive Munitions (IM) which are energetic materials that have low shock sensitivity and high thermal stability and developing detection schemes for identifying chemical warfare agents. For energetic materials, the environmental fate can be assessed by determining the partition coefficients, especially the octanol-water partition coefficient and Henry\u27s law constant. For chemical warfare agents, the most important criteria for developing sensors is the detection selectivity. Carbon adsorbents are a simple and effective way of increasing the sensor selectivity for the contaminants by concentration or prefiltration through physical adsorption. So it is necessary to study the adsorption behavior of the contaminants in carbon slit pores as a preliminary step to the sensing process. In this work, molecular modeling or simulation is proposed as a theoretical tool to determine thermophysical properties that aid in understanding how certain energetic materials behave in the environment and developing techniques for detecting chemical warfare agents. Molecular modeling is a promising alternative to experiments due to the hazardous nature of these compounds and the long experimental time scales involved in their testing. Molecular models or force fields are developed to predict various thermophysical properties. For energetic materials, atomistic molecular dynamics simulations are used to predict properties such as octanol-water partition coefficiens, Henry\u27s law constant and also critical parameters, vapor pressure, boiling point, lattice parameters, crystal density and melting point. For chemical warfare agents, the developed force fields are used to determine their phase coexistence properties, vapor pressures, critical parameters, pure and mixture isotherms with water over carbon slit pore using atomistic Monte Carlo simulations