Performance of radial distribution function-based descriptors in the chemoinformatic studies of HIV-1 protease

Aim: This letter investigates the role of radial distribution function-based descriptors for in silico design of new drugs. Methodology: The multiple linear regression models for HIV-1 protease and its complexes with a series of inhibitors were constructed. A detailed analysis of major atomic contributions to the radial distribution function descriptor weighted by the number of valence shell electrons identified residues Arg8, Asp29 and residues of the catalytic triad as crucial for the correlation with the inhibition constant, together with residues Asp30 and Ile50, whose mutations are known to cause an emergence of drug resistant variants. Conclusion: This study demonstrates an easy and fast assessment of the activity of potential drugs and the derivation of structural information of their complexes with the receptor or enzyme

Porous Nanocrystalline Silicon Supported Bimetallic Pd-Au Catalysts: Preparation, Characterization, and Direct Hydrogen Peroxide Synthesis.

Bimetallic Pd-Au catalysts were prepared on the porous nanocrystalline silicon (PSi) for the first time. The catalysts were tested in the reaction of direct hydrogen peroxide synthesis and characterized by standard structural and chemical techniques. It was shown that the Pd-Au/PSi catalyst prepared from conventional H2[PdCl4] and H[AuCl4] precursors contains monometallic Pd and a range of different Pd-Au alloy nanoparticles over the oxidized PSi surface. The PdAu2/PSi catalyst prepared from the [Pd(NH3)4][AuCl4]2 double complex salt (DCS) single-source precursor predominantly contains bimetallic Pd-Au alloy nanoparticles. For both catalysts the surface of bimetallic nanoparticles is Pd-enriched and contains palladium in Pd0 and Pd2+ states. Among the catalysts studied, the PdAu2/PSi catalyst was the most active and selective in the direct H2O2 synthesis with H2O2 productivity of 0.5 [Formula: see text] at selectivity of 50% and H2O2 concentration of 0.023 M in 0.03 M H2SO4-methanol solution after 5 h on stream at -10°C and atmospheric pressure. This performance is due to high activity in the H2O2 synthesis reaction and low activities in the undesirable H2O2 decomposition and hydrogenation reactions. Good performance of the PdAu2/PSi catalyst was associated with the major part of Pd in the catalyst being in the form of the bimetallic Pd-Au nanoparticles. Porous silicon was concluded to be a promising catalytic support for direct hydrogen peroxide synthesis due to its inertness with respect to undesirable side reactions, high thermal stability, and conductivity, possibility of safe operation at high temperatures and pressures and a well-established manufacturing process

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information

The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu

The design of compounds with desirable properties – The anti-HIV case study

Efficacy and safety are among the most desirable characteristics of an ideal drug. The tremendous increase in computing power and the entry of artificial intelligence into the field of computational drug design are accelerating the process of identifying, developing, and optimizing potential drugs. Here, we present novel approach to design new molecules with desired properties. We combined various neural networks and linear regression algorithms to build models for cytotoxicity and anti-HIV activity based on Continual Molecular Interior analysis (CoMIn) and Cinderella's Shoe (CiS) derived molecular descriptors. After validating the reliability of the models, a genetic algorithm was coupled with the Des-Pot Grid algorithm to generate new molecules from a predefined pool of molecular fragments and predict their bioactivity and cytotoxicity. This combination led to the proposal of 16 hit molecules with high anti-HIV activity and low cytotoxicity. The anti-SARS-CoV-2 activity of the hits was predicted

Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study

Introduction: Machine learning methods, coupled with a tremendous increase in computer power in recent years, are promising tools in modern drug design and drug repurposing. Methods: Machine learning predictive models, publicly available at chemosophia.com, were used to predict the bioactivity of recently synthesized platinum(IV) complexes against different kinds of diseases and medical conditions. Two novel QSAR models based on the BiS algorithm are developed and validated, capable to predict activities against the SARS-CoV virus and its RNA dependent RNA polymerase. Results: The internal predictive power of the QSAR models was tested by 10-fold cross-validation, giving cross-R2 from 0.863 to 0.903. 38 different activities, ranging from antioxidant, antibacterial, and antiviral activities, to potential anti-inflammatory, anti-arrhythmic and anti-malarial activity were predicted for a series of eighteen platinum(IV) complexes. Conclusion: Complexes 1, 3 and 13 have high generalized optimality criteria and are predicted as potential SARS-CoV RNA dependent RNA polymerase inhibitors

Coupling Pre-Reforming and Partial Oxidation for LPG Conversion to Syngas

Coupling of the pre-reforming and partial oxidation was considered for the conversion of liquefied petroleum gas to syngas for the feeding applications of solid oxide fuel cells. Compared with conventional two step steam reforming, it allows the amount of water required for the process, and therefore the energy needed for water evaporation, to be lowered; substitution of high-potential heat by lower ones; and substitution of expensive tubular steam reforming reactors by adiabatic ones. The supposed process is more productive due to the high reaction rate of partial oxidation. The obtained syngas contains only ca. 10 vol.% H2O and ca. 50 vol.% of H2 + CO, which is attractive for the feeding application of solid oxide fuel cells. Compared with direct partial oxidation of liquefied petroleum gas, the suggested scheme is more energy efficient and overcomes problems with coke formation and catalyst overheating. The proof-of-concept experiments were carried out. The granular Ni-Cr2O3-Al2O3 catalyst was shown to be effective for propane pre-reforming at 350–400 °C, H2O:C molar ratio of 1.0, and flow rate of 12,000 h−1. The composite Rh/Ce0.75Zr0.25O2-δ–ƞ-Al2O3/FeCrAl catalyst was shown to be active and stable under conditions of partial oxidation of methane-rich syngas after pre-reforming and provided a syngas (H2 + CO) productivity of 28 m3·Lcat−1·h−1 (standard temperature and pressure)

Unusual Synthesis of Triosmium Carbene Clusters by Tandem Activation of Chlorohydrocarbons and Heterocyclic Amines

Reactions of the [Os3H2(CO)(10)] cluster complex (1) with six-membered heterocyclic amines (morpholine, thiomorpholine, piperidine) and halohydrocarbons (CH2Cl2, ClHC=CHCl, CH2=CCl2) at similar to 25 degrees C have been studied. Two main types of products are formed in all studied reactions. One product is carbene cluster [Os-3(mu-H)(mu-Cl){eta(1)-C(CH3)N(CH2CH2)(2)X}(CO)(9)] (X=O, S, CH2) (3, 3 a and 3 b). Second product is cluster containing enamine ligand [Os-3(mu-H){mu-CH=CHN(C2CH2)(2)X)}(2)(CO)(10)] (X=O, S, CH2) (2, 2 a and 2 b). The carbene ligand is assembled on a cluster, from three organic molecules, thus representing the first example of carbene ligands formed in this way. Clusters with carbene ligand exist as two stable isomers (rotamers hindered towards the Os-C bond), as confirmed by NMR studies and conformational analysis. We have found that in reactions of cluster 1 with acyclic amines containing an oxygen atom in gamma-position (likely morpholine in CH2Cl2), only complexes with bridging enamine ligands are formed. Compounds 2 a, 2 b, 3 and 3 b are characterized by single-crystal X-ray diffraction

Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking

Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to Flavivirus (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, in silico drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to de novo developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using in silico molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, in silico molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV