27 research outputs found
Artificial Intelligence Technologies for COVID-19 De Novo Drug Design
The recent covid crisis has provided important lessons for academia and industry regarding digital reorganization. Among the fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and beyond. Drug development is a costly and time-consuming business, and only a minority of approved drugs generate returns exceeding the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper reviews the most significant research on artificial intelligence in de novo drug design for COVID-19 pharmaceutical research
An integrated pharmacophore/docking/3D-QSAR approach to screening a large library of products in search of future botulinum neurotoxin a inhibitors
Botulinum toxins are neurotoxins produced by Clostridium botulinum. This toxin can be lethal for humans as a cause of botulism; however, in small doses, the same toxin is used to treat different conditions. Even if the therapeutic doses are effective and safe, the adverse reactions could be local and could unmask a subclinical impairment of neuromuscular transmissions. There are not many cases of adverse events in the literature; however, it is possible that sometimes they do not occur as they are transient and, if they do occur, there is no possibility of a cure other than to wait for the pharmacological effect to end. Inhibition of botulinum neurotoxin type A (BoNT/A) effects is a strategy for treating botulism as it can provide an effective post-exposure remedy. In this paper, 13,592,287 compounds were screened through a pharmacophore filter, a 3D-QSAR model, and a virtual screening; then, the compounds with the best affinity were selected. Molecular dynamics simulation studies on the first four compounds predicted to be the most active were conducted to verify that the poses foreseen by the docking were stable. This approach allowed us to identify compounds with a calculated inhibitory activity in the range of 316–500 nM
Optimization of 4-amino-pyridazin-3(2H)-one as a valid core scaffold for FABP4 inhibitors
Current clinical research suggests that fatty acid-binding protein 4 inhibitors (FABP4is), which are of biological and therapeutic interest, may show potential in treating cancer and other illnesses. We sought to uncover new structures through the optimization of the previously reported 4-amino and 4-ureido pyridazinone-based series of FABP4is as part of a larger research effort to create more potent FABP4 inhibitors. This led to the identification of 14e as the most potent analog with IC₅₀ = 1.57 μM, which is lower than the IC₅₀ of the positive control. Advanced modeling investigations and in silico absorption, distribution, metabolism, and excretion - toxicity calculations suggested that 14e represents a potential candidate for in vivo studies such as FABP4i
Assessing foraging strategies of herbivores in Mediterranean oak woodlands: a review of key issues and selected methodologies
Natural substances in the fight of sars-cov-2: A critical evaluation resulting from the cross-fertilization of molecular modeling data with the pharmacological aspects
The recent pandemic due to SARS-CoV-2, the last isolated human beta-coronavirus, has revolutionized modern knowledge of the pathogenesis of viral pneumonia. The lack of specific antiviral drugs and the need to develop adequate research for new antiviral drugs capable of treating this new form of the disease undertook three different research paths quickly. The first one is aimed to test antiviral molecules already present in therapeutic use, with a mechanism of action directed towards viral proteins functional to replication or adsorption; the second one, it is the repositioning of molecules with known pharmacological activity for which various chemistry studies have been prepared in an attempt to find new and specific viral targets; the third, it is the search for molecules of natural origin for which to demonstrate a specific anti-coronavirus activity. Many databases of natural and synthetic substances have been used for the identification of potent inhibitors of various viral targets. The field of computer-aided drug design seems to be promising and useful for the identification of SARS-CoV-2 inhibitors; hence, different structure-and lig-and-based computational approaches have been used for their identification. This review analyzes in-depth and critically the most recent publications in the field of applied computational chemistry to find out molecules of natural origin with potent antiviral activity. Fur-thermore, a critical and functional selection of some molecules with the best hypothetical anti-SARS-CoV-2 activity is made for further studies by biological tests
Computational tools in the discovery of FABP4 ligands: A statistical and molecular modeling approach
Small molecule inhibitors of adipocyte fatty-acid binding protein 4 (FABP4) have received interest following the recent publication of their pharmacologically beneficial effects. Recently, it was revealed that FABP4 is an attractive molecular target for the treatment of type 2 diabetes, other metabolic diseases, and some type of cancers. In past years, hundreds of effective FABP4 inhibitors have been synthesized and discovered, but, unfortunately, none have reached the clinical research phase. The field of computer-aided drug design seems to be promising and useful for the identification of FABP4 inhibitors; hence, different structure- and ligand-based computational approaches have been used for their identification. In this paper, we searched for new potentially active FABP4 ligands in the Marine Natural Products (MNP) database. We retrieved 14,492 compounds from this database and filtered through them with a statistical and computational filter. Seven compounds were suggested by our methodology to possess a potential inhibitory activity upon FABP4 in the range of 97-331 nM. ADMET property prediction was performed to validate the hypothesis of the interaction with the intended target and to assess the drug-likeness of these derivatives. From these analyses, three molecules that are excellent candidates for becoming new drugs were found
Targeting the SARS-CoV-2 HR1 with Small Molecules as Inhibitors of the Fusion Process
The rapid and global propagation of the novel human coronavirus that causes severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has produced an immediate urgency to discover promising targets for the treatment of this virus. In this paper, we studied the spike protein S2 domain of SARS-CoV-2 as it is the most conserved component and controls the crucial fusion process of SARS-CoV-2 as a target for different databases of small organic compounds. Our in silico methodology, based on pharmacophore modeling, docking simulation and molecular dynamics simulations, was first validated with ADS-J1, a potent small-molecule HIV fusion inhibitor that has already proved effective in binding the HR1 domain and inhibiting the fusion core of SARS-CoV-1. It then focused on finding novel small molecules and new peptides as fusion inhibitors. Our methodology identified several small molecules and peptides as potential inhibitors of the fusion process. Among these, NF 023 hydrate (MolPort-006-822-583) is one of the best-scored compounds. Other compounds of interest are ZINC00097961973, Salvianolic acid, Thalassiolin A and marine_160925_88_2. Two interesting active peptides were also identified: AP00094 (Temporin A) and AVP1227 (GBVA5). The inhibition of the spike protein of SARS-CoV-2 is a valid target to inhibit the virus entry in human cells. The discussed compounds reported in this paper led to encouraging results for future in vitro tests against SARS-CoV-2
Nanosponges based on self-assembled starfish-shaped cucurbit[6]urils functionalized with imidazolium arms
A new porous material based on the first supramolecular cucurbituril-based nanosponge was synthesized by the functionalization of cucurbit[6]uril with twelve 1-(2-bromoethyl)-3-methyl-1H-imidazol-3-ium arms. The porous structure and the high adsorption capacity were demonstrated through surface area measurements and carbon dioxide adsorption. The new supramolecular sponge showed attractive properties such as (i) a highly porous structure that allowed CO2capture, (ii) the possibility to reuse the adsorbed CO2for organic synthesis, and (iii) an exciting thermal stability up to around 800 °C, with the potential use of this material in high temperature reactions. Finally, the reuse of CO2was successfully investigated in the carboxylation reaction of phenylacetylene
Putative inhibitors of SARS-COV-2 main protease from a library of marine natural products: A virtual screening and molecular modeling study
The current emergency due to the worldwide spread of the COVID-19 caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a great concern for global public health. Already in the past, the outbreak of severe acute respiratory syndrome (SARS) in 2003 and Middle Eastern respiratory syndrome (MERS) in 2012 demonstrates the potential of coronaviruses to cross-species borders and further underlines the importance of identifying new-targeted drugs. An ideal antiviral agent should target essential proteins involved in the lifecycle of SARS-CoV. Currently, some HIV protease inhibitors (i.e., Lopinavir) are proposed for the treatment of COVID-19, although their effectiveness has not yet been assessed. The main protease (Mpr) provides a highly validated pharmacological target for the discovery and design of inhibitors. We identified potent Mpr inhibitors employing computational techniques that entail the screening of a Marine Natural Product (MNP) library. MNP library was screened by a hyphenated pharmacophore model, and molecular docking approaches. Molecular dynamics and re-docking further confirmed the results obtained by structure-based techniques and allowed this study to highlight some crucial aspects. Seventeen potential SARS-CoV-2 Mpr inhibitors have been identified among the natural substances of marine origin. As these compounds were extensively validated by a consensus approach and by molecular dynamics, the likelihood that at least one of these compounds could be bioactive is excellent