Search results for "virtu"
showing 10 items of 1987 documents
Exploring the readthrough of nonsense mutations by non-acidic Ataluren analogues selected by ligand-based virtual screening
2016
Abstract Ataluren, also known as PTC124, is a 5-(fluorophenyl)-1,2,4-oxadiazolyl-benzoic acid suggested to suppress nonsense mutations by readthrough of premature stop codons in the mRNA. Potential interaction of PTC124 with mRNA has been recently studied by molecular dynamics simulations highlighting the importance of H-bonding and stacking π−π interactions. A series of non-acidic analogues of PTC124 were selected from a large database via a ligand-based virtual screening approach. Eight of them were synthesized and tested for their readthrough activity using the Fluc reporter harboring the UGA premature stop codon. The most active compound was further tested for suppression of the UGA non…
An overview of recent molecular dynamics applications as medicinal chemistry tools for the undruggable site challenge
2018
Molecular dynamics (MD) has become increasingly popular due to the development of hardware and software solutions and the improvement in algorithms, which allowed researchers to scale up calculations in order to speed them up. MD simulations are usually used to address protein folding issues or protein-ligand complex stability through energy profile analysis over time. In recent years, the development of new tools able to deeply explore a potential energy surface (PES) has allowed researchers to focus on the dynamic nature of the binding recognition process and binding-induced protein conformational changes. Moreover, modern approaches have been demonstrated to be effective and reliable in …
Recent advances on CDK inhibitors: An insight by means of in silico methods
2017
The cyclin dependent kinases (CDKs) are a small family of serine/threonine protein kinases that can act as a potential therapeutic target in several proliferative diseases, including cancer. This short review is a survey on the more recent research progresses in the field achieved by using in silico methods. All the "armamentarium" available to the medicinal chemists (docking protocols and molecular dynamics, fragment-based, de novo design, virtual screening, and QSAR) has been employed to the discovery of new, potent, and selective inhibitors of cyclin dependent kinases. The results cited herein can be useful to understand the nature of the inhibitor-target interactions, and furnish an ins…
Molecular topology: A new strategy for antimicrobial resistance control
2017
The control of antimicrobial resistance (AMR) seems to have come to an impasse. The use and abuse of antibacterial drugs has had major consequences on the genetic mutability of both pathogenic and nonpathogenic microorganisms, leading to the development of new highly resistant strains. Because of the complexity of this situation, an in silico strategy based on QSAR molecular topology was devised to identify synthetic molecules as antimicrobial agents not susceptible to one or several mechanisms of resistance such as: biofilms formation (BF), ionophore (IA) activity, epimerase (EI) activity or SOS system (RecA inhibition). After selecting a group of 19 compounds, five of them showed signific…
GSaaS: A Service to Cloudify and Schedule GPUs
2018
Cloud technology is an attractive infrastructure solution that provides customers with an almost unlimited on-demand computational capacity using a pay-per-use approach, and allows data centers to increase their energy and economic savings by adopting a virtualized resource sharing model. However, resources such as graphics processing units (GPUs), have not been fully adapted to this model. Although, general-purpose computing on graphics processing units (GPGPU) is becoming more and more popular, cloud providers lack of flexibility to manage accelerators, because of the extended use of peripheral component interconnect (PCI) passthrough techniques to attach GPUs to virtual machines (VMs). F…
Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning.
2021
Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As yet, there are no established drugs available. Speeding up drug discovery is urgently required. We applied a workflow of combined in silico methods (virtual drug screening, molecular docking and supervised machine learning algorithms) to identify novel drug candidates against COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug repositioning and of natural compound datasets from literature mining and the ZINC database to select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid protein, and 2′-o-ribose methyltransferase). Supported by…
Search of Chemical Scaffolds for Novel Antituberculosis Agents
2005
3 A method to identify chemical scaffolds potentially active against Mycobacterium tuberculosis is presented. The molecular features of a set of structurally heterogeneous antituberculosis drugs were coded by means of structural invariants. Three tech- niques were used to obtain equations able to model the antituberculosis activity: linear discriminant analysis, multilinear re- gression, and shrinkage estimation-ridge regression. The model obtained was statistically validated through leave-n-out test, and an external set and was applied to a database for the search of new active agents. The selected compounds were assayed in vitro, and among those identified as active stand reserpine, N,N,N…
Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants
2021
Abstract Background COVID-19, declared a pandemic in March 2020 by the World Health Organization is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The virus has already killed more than 2.3 million people worldwide. Object The principal intent of this work was to investigate lead compounds by screening natural product library (NPASS) for possible treatment of COVID-19. Methods Pharmacophore features were used to screen a large database to get a small dataset for structure-based virtual screening of natural product compounds. In the structure-based screening, molecular docking was performed to find a potent inhibitor molecule against the main protease (Mpro) of SARS-…
Repurposing old drugs to fight multidrug resistant cancers.
2020
Overcoming multidrug resistance represents a major challenge for cancer treatment. In the search for new chemotherapeutics to treat malignant diseases, drug repurposing gained a tremendous interest during the past years. Repositioning candidates have often emerged through several stages of clinical drug development, and may even be marketed, thus attracting the attention and interest of pharmaceutical companies as well as regulatory agencies. Typically, drug repositioning has been serendipitous, using undesired side effects of small molecule drugs to exploit new disease indications. As bioinformatics gain increasing popularity as an integral component of drug discovery, more rational approa…
mD3DOCKxb: An Ultra-Scalable CPU-MIC Coordinated Virtual Screening Framework
2017
Molecular docking is an important method in computational drug discovery. In large-scale virtual screening, millions of small drug-like molecules (chemical compounds) are compared against a designated target protein (receptor). Depending on the utilized docking algorithm for screening, this can take several weeks on conventional HPC systems. However, for certain applications including large-scale screening tasks for newly emerging infectious diseases such high runtimes can be highly prohibitive. In this paper, we investigate how the massively parallel neo-heterogeneous architecture of Tianhe-2 Supercomputer consisting of thousands of nodes comprising CPUs and MIC coprocessors that can effic…