IVSPlat 1.0: an integrated virtual screening platform with a molecular graphical interface

<p>Abstract</p> <p>Background</p> <p>The virtual screening (VS) of lead compounds using molecular docking and pharmacophore detection is now an important tool in drug discovery. VS tasks typically require a combination of several software tools and a molecular graphics system. Thus, the integration of all the requisite tools in a single operating environment could reduce the complexity of running VS experiments. However, only a few freely available integrated software platforms have been developed.</p> <p>Results</p> <p>A free open-source platform, IVSPlat 1.0, was developed in this study for the management and automation of VS tasks. We integrated several VS-related programs into a molecular graphics system to provide a comprehensive platform for the solution of VS tasks based on molecular docking, pharmacophore detection, and a combination of both methods. This tool can be used to visualize intermediate and final results of the VS execution, while also providing a clustering tool for the analysis of VS results. A case study was conducted to demonstrate the applicability of this platform.</p> <p>Conclusions</p> <p>IVSPlat 1.0 provides a plug-in-based solution for the management, automation, and visualization of VS tasks. IVSPlat 1.0 is an open framework that allows the integration of extra software to extend its functionality and modified versions can be freely distributed. The open source code and documentation are available at <url>http://kyc.nenu.edu.cn/IVSPlat/.</url></p

Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening

We gratefully acknowledge the support provided by the Graduate Program in Pharmaceutical Innovation—Federal University of Amapá, Laboratory of Modeling and Computational Chemistry—Federal University of Amapá (UNIFAP-Macapá-Brazil), Computational Laboratory of Pharmaceutical Chemistry—University of Sao Paulo (USP-Ribeirão Preto-Brazil) and Department of Pharmaceutical and Organic Chemistry—Institute of Biosanitary Research ibs.GRANADA—University of Granada (UGR-Granada-Spain) for computational and financial support.Leukemias are neoplasms that affect hematopoietic cells, which are developed by genetic alterations (mutations) that lead to the loss of proliferation control mechanisms (maturation and/or cell death). The α4β1 integrin receptor is a therapeutic target for inflammation, autoimmune diseases and lymphoid tumors. This study was carried out to search through the antagonists-based virtual screening for α4β1 receptor. Initially, seventeen (17) structures were selected (based on the inhibitory activity values, IC50) and the structure with the best value was chosen as the pivot. The pharmacophoric pattern was determined from the online PharmaGist server and resulted in a model of score value equal to 97.940 with 15 pharmacophoric characteristics that were statistically evaluated via Pearson correlations, principal component analysis (PCA) and hierarchical clustering analysis (HCA). A refined model generated four pharmacophoric hypotheses totaling 1.478 structures set of Zinc_database. After, the pharmacokinetic, toxicological and biological activity predictions were realized comparing with pivot structure that resulted in five (ZINC72088291, ZINC68842860, ZINC14365931, ZINC09588345 and ZINC91247798) structures with optimal in silico predictions. Therefore, future studies are needed to confirm antitumor potential activity of molecules selected this work with in vitro and in vivo assays

Identification of Potential New Aedes aegypti Juvenile Hormone Inhibitors from N-Acyl Piperidine Derivatives: A Bioinformatics Approach

Aedes aegypti mosquitoes transmit several human pathogens that cause millions of deaths worldwide, mainly in Latin America. The indiscriminate use of insecticides has resulted in the development of species resistance to some such compounds. Piperidine, a natural alkaloid isolated from Piper nigrum, has been used as a hit compound due to its larvicidal activity against Aedes aegypti. In the present study, piperidine derivatives were studied through in silico methods: pharmacophoric evaluation (PharmaGist), pharmacophoric virtual screening (Pharmit), ADME/Tox prediction (Preadmet/Derek 10.0 (R)), docking calculations (AutoDock 4.2) and molecular dynamics (MD) simulation on GROMACS-5.1.4. MP-416 and MP-073 molecules exhibiting Delta G binding (MMPBSA -265.95 +/- 1.32 kJ/mol and -124.412 +/- 1.08 kJ/mol, respectively) and comparable to holo (Delta G binding = -216.21 +/- 0.97) and pyriproxyfen (a well-known larvicidal, Delta G binding= -435.95 +/- 2.06 kJ/mol). Considering future in vivo assays, we elaborated the theoretical synthetic route and made predictions of the synthetic accessibility (SA) (SwissADME), lipophilicity and water solubility (SwissADME) of the promising compounds identified in the present study. Our in silico results show that MP-416 and MP-073 molecules could be potent insecticides against the Aedes aegypti mosquitoes.Pro-Reitoria de Pesquisa e Pos-Graduacao (PROPESP) of Federal University of Para via the Graduate Program in Medicinal Chemistry and Molecular Modeling, Health Science Institute, Federal University of Para PROPESP/UFPA-Edital 02/2022-PAPQ/PROPES

New uses for old drugs: pharmacophore‐based screening for the discovery of P‐glycoprotein inhibitors

P-glycoprotein (P-gp) is one of the best character ized transporters responsible for the multidrug resistance phenotype exhibited by cancer cells. Therefore, there is widespread interest in eluci dating whether existing drugs are candidate P-gp substrates or inhibitors. With this aim, a pharma cophore model was created based on known P-gp inhibitors and it was used to screen a database of existing drugs. The P-gp modulatory activity of the best hits was evaluated by several methods such as the rhodamine-123 accumulation assay using K562Dox cell line, and a P-gp ATPase activ ity assay. The ability of these compounds to enhance the cytotoxicity of doxorubicin was assessed with the sulphorhodamine-B assay. Of the 21 hit compounds selected in silico, 12 were found to significantly increase the intracellular accumulation of Rhodamine-123, a P-gp substrate. In addition, amoxapine and loxapine, two tetracy clic antidepressant drugs, were discovered to be potent non-competitive inhibitors of P-gp, causing a 3.5-fold decrease in the doxorubicin GI50 in K562Dox cell line. The overall results provide important clues for the non-label use of known drugs as inhibitors of P-gp. Potent inhibitors with a dibenzoxazepine scaffold emerged from this study and they will be further investigated in order to develop new P-gp inhibitors.info:eu-repo/semantics/publishedVersio

Designing allosteric modulators for active conformational state of m-glutamate G-protein coupled receptors

G-protein coupled receptors (GPCRs) are found to be attractive drug targets for the treatment of various neuronal diseases. Allosteric modulators have their role in enhancing or suppressing the effect of glutamate on mGluRs. Structure of mGluR1 was generated with the help of Modeller software by considering human B2-adrenergic GPCR protein as template. Structure of various already known drug molecules were used for similarity search in the ZINC database and a large number of similar molecules were obtained, than filtering of these molecules were done by applying drug features. Molecules were screened by Molegro Virtual Docking program and numbers of novel molecules were generated by using LigBuilder software. Finally 16 novel drug candidates were selected, which were showing better results than the seed molecule and previously known modulators. These results will help in designing and synthesis of better drugs against diseases like Epilepsy and Parkinson's

Design and Identification of Inhibitors for the Spike-ACE2 Target of SARS-CoV-2

settingsOrder Article Reprints Open AccessArticle Design and Identification of Inhibitors for the Spike-ACE2 Target of SARS-CoV-2 by Ruan S. Bastos 1,2,*,Lúcio R. de Lima 1,2,Moysés F. A. Neto 3,Maryam 4,Numan Yousaf 4ORCID,Jorddy N. Cruz 2ORCID,Joaquín M. Campos 5,6ORCID,Njogu M. Kimani 7ORCID,Ryan S. Ramos 2ORCID andCleydson B. R. Santos 1,2,*ORCID 1 Graduate Program in Medicinal Chemistry and Molecular Modeling, Federal University of Pará, Belem 66075-110, PA, Brazil 2 Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapa 68903-419, AP, Brazil 3 Laboratory of Molecular Modeling, State University of Feira de Santana, Feira de Santana 44036-900, BA, Brazil 4 Department of Biosciences, COMSATS University Islamabad, Park Road, Islamabad 45550, Pakistan 5 Department of Pharmaceutical and Organic Chemistry, Faculty of Pharmacy, Campus of Cartuja, University of Granada, 18071 Granada, Spain 6 Biosanitary Institute of Granada (ibs.GRANADA), University of Granada, 18071 Granada, Spain 7 Department of Physical Sciences, University of Embu, Embu 6-60100, Kenya * Authors to whom correspondence should be addressed. Int. J. Mol. Sci. 2023, 24(10), 8814; https://doi.org/10.3390/ijms24108814 Received: 12 September 2022 / Revised: 23 November 2022 / Accepted: 28 November 2022 / Published: 16 May 2023 (This article belongs to the Special Issue The Research about Computer-Aided Drug Design) Download Browse Figures Versions Notes Abstract When an epidemic started in the Chinese city of Wuhan in December 2019, coronavirus was identified as the cause. Infection by the virus occurs through the interaction of viral S protein with the hosts’ angiotensin-converting enzyme 2. By leveraging resources such as the DrugBank database and bioinformatics techniques, ligands with potential activity against the SARS-CoV-2 spike protein were designed and identified in this investigation. The FTMap server and the Molegro software were used to determine the active site of the Spike-ACE2 protein’s crystal structure. Virtual screening was performed using a pharmacophore model obtained from antiparasitic drugs, obtaining 2000 molecules from molport®. The ADME/Tox profiles were used to identify the most promising compounds with desirable drug characteristics. The binding affinity investigation was then conducted with selected candidates. A molecular docking study showed five structures with better binding affinity than hydroxychloroquine. Ligand_003 showed a binding affinity of −8.645 kcal·mol−1, which was considered an optimal value for the study. The values presented by ligand_033, ligand_013, ligand_044, and ligand_080 meet the profile of novel drugs. To choose compounds with favorable potential for synthesis, synthetic accessibility studies and similarity analyses were carried out. Molecular dynamics and theoretical IC50 values (ranging from 0.459 to 2.371 µM) demonstrate that these candidates are promising for further tests. Chemical descriptors showed that the candidates had strong molecule stability. Theoretical analyses here show that these molecules have potential as SARS-CoV-2 antivirals and therefore warrant further investigation.Pró-reitoria de Pesquisa e Pós-graduação (PROPESP) from Federal University of Pará (UFPA)

COMPUTATIONAL APPROACHES RELATED TO DRUG DISPOSITION

Drug disposition connects with the movement of drug molecules inside the body after administration irrespective with the route of administration. After entering the system, drug molecule and internal body systems comes under various pharmacokinetic interactions followed by observation of suitable biological activity. In this exhaustive process, physicochemical nature of the chemical substance and physiological nature of system makes this movement competitive. In this view, pharmacokinetic and toxic properties of the molecule regulates the destination of the molecule. Various computational processes are available for in silico pharmacokinetic assessment of drug molecule after absorption through biological membrane, distributed throughout the system based on the percent ionization or partition coefficient factors followed by biologically transformed into an another entity in presence of microsomal enzymes and finally excrete out from system using various cellular transport systems as well as related cellular toxicity behavior. In this chapter, we ensemble all the possible information related with the drug movement and related computational tools to understand the possible chemical and pathophysiological changes. Here detailed knowledge on database expedition, establishment of pharmacophore model, homology modelling based on sequence similarity, molecular docking study (rigid and flexible docking) and QSAR/QSPR study (with detailed process and available softwares) are provided. These diversely united informations actually helps a researcher to understand the factual movement of a drug molecule inside the system

Data-mining of potential antitubercular activities from molecular ingredients of traditional Chinese medicines

Background. Traditional Chinese medicine encompasses a well established alternate system of medicine based on a broad range of herbal formulations and is practiced extensively in the region for the treatment of a wide variety of diseases. In recent years, several reports describe in depth studies of the molecular ingredients of traditional Chinese medicines on the biological activities including anti-bacterial activities. The availability of a well-curated dataset of molecular ingredients of traditional Chinese medicines and accurate in-silico cheminformatics models for data mining for antitubercular agents and computational filters to prioritize molecules has prompted us to search for potential hits from these datasets.Results. We used a consensus approach to predict molecules with potential antitubercular activities from a large dataset of molecular ingredients of traditional Chinese medicines available in the public domain. We further prioritized 160 molecules based on five computational filters (SMARTSfilter) so as to avoid potentially undesirable molecules. We further examined the molecules for permeability across Mycobacterial cell wall and for potential activities against non-replicating and drug tolerant Mycobacteria. Additional in-depth literature surveys for the reported antitubercular activities of the molecular ingredients and their sources were considered for drawing support to prioritization.Conclusions. Our analysis suggests that datasets of molecular ingredients of traditional Chinese medicines offer a new opportunity to mine for potential biological activities. In this report, we suggest a proof-of-concept methodology to prioritize molecules for further experimental assays using a variety of computational tools. We also additionally suggest that a subset of prioritized molecules could be used for evaluation for tuberculosis due to their additional effect against non-replicating tuberculosis as well as the additional hepato-protection offered by the source of these ingredients