Targeting protein-protein interactions with low molecular weight and short peptide modulators: insights on disease pathways and starting points for drug discovery DOI
Daniela Trisciuzzi, Bruno O. Villoutreix, Lydia Siragusa

et al.

Expert Opinion on Drug Discovery, Journal Year: 2023, Volume and Issue: 18(7), P. 737 - 752

Published: May 29, 2023

Introduction Protein-protein interactions (PPIs) have been often considered undruggable targets although they are attractive for the discovery of new therapeutics. The spread artificial intelligence and machine learning complemented with experimental methods is likely to change perspectives protein-protein modulator research. Noteworthy, some novel low molecular weight (LMW) short peptide modulators PPIs already in clinical trials treatment relevant diseases.Areas covered This review focuses on main properties interfaces key concepts pertaining modulation PPIs. authors survey recently reported state-of-the-art dealing rational design PPI highlight role several computer-based approaches.Expert opinion Interfering specifically large protein still an open challenge. initial concerns about unfavorable physicochemical many these nowadays less acute molecules lying beyond rule 5, orally available successful trials. As cost biologics interfering very high, it would seem reasonable put more effort, both academia private sectors, actively developing compounds peptides perform this task.

Language: Английский

FAF-Drugs4: free ADME-tox filtering computations for chemical biology and early stages drug discovery DOI Open Access
David Lagorce,

Lina Bouslama,

Jérôme Becot

et al.

Bioinformatics, Journal Year: 2017, Volume and Issue: 33(22), P. 3658 - 3660

Published: July 28, 2017

Identification of small molecules that could be interesting starting points for drug discovery or to investigate a biological system as in chemical biology endeavours is both time consuming and costly. In silico approaches assist the design quality compound collections help prioritize before synthesis purchase are therefore valuable. Here refers selection pass one several selected filters can tuned by users according project stage project. These involve prediction physicochemical properties, search toxicophores other unwanted groups.FAF-Drugs4 novel version our online server dedicated preparation annotation collections. The tool now faster parameters have been optimized. addition, new service referred FAF-QED, an implementation quantitative estimate drug-likeness method, available.The available at http://fafdrugs4.mti.univ-paris-diderot.fr.Bruno.Villoutreix@inserm.fr.Supplementary data Bioinformatics online.

Language: Английский

Citations

267
New machine learning and physics-based scoring functions for drug discovery DOI Creative Commons
Isabella Alvim Guedes,

André M. S. Barreto,

Diogo Marinho

et al.

Scientific Reports, Journal Year: 2021, Volume and Issue: 11(1)

Published: Feb. 4, 2021

Scoring functions are essential for modern in silico drug discovery. However, the accurate prediction of binding affinity by scoring remains a challenging task. The performance is very heterogeneous across different target classes. based on precise physics-based descriptors better representing protein-ligand recognition process strongly needed. We developed set new empirical functions, named DockTScore, explicitly accounting terms combined with machine learning. Target-specific were two important targets, proteases and protein-protein interactions, an original class molecules Multiple linear regression (MLR), support vector random forest algorithms employed to derive general target-specific involving optimized MMFF94S force-field terms, solvation lipophilic interactions improved term ligand torsional entropy contribution binding. DockTScore demonstrated be competitive current best-evaluated energy ranking four DUD-E datasets will useful design diverse proteins as well specific targets such interactions. Currently, MLR available at www.dockthor.lncc.br .

Language: Английский

Citations

161
In Silico ADME/Tox Profiling of Natural Products: A Focus on BIOFACQUIM DOI Creative Commons
Noemi Angeles Durán-Iturbide, Bárbara I. Díaz‐Eufracio, José L. Medina‐Franco

et al.

ACS Omega, Journal Year: 2020, Volume and Issue: 5(26), P. 16076 - 16084

Published: June 25, 2020

Natural products continue to be major sources of bioactive compounds and drug candidates not only because their unique chemical structures but also overall favorable metabolism pharmacokinetic properties. The number publicly accessible natural product databases has increased significantly in the past few years. However, systematic ADME/Tox profile been reported on a limited basis. For instance, BIOFACQUIM was recently published as public database from Mexico, country with rich source biomolecules. its reported. Herein, we discuss results an in-depth silico other large collections products. It concluded that absorption distribution profiles are similar those approved drugs, while is comparable databases. excretion different predicted toxicity comparable. This work further contributes deeper characterization therapeutic potential.

Language: Английский

Citations

156
Simulation-based approaches for drug delivery systems: Navigating advancements, opportunities, and challenges DOI Creative Commons

Iman Salahshoori,

Mahdi Golriz,

Marcos A.L. Nobre

et al.

Journal of Molecular Liquids, Journal Year: 2023, Volume and Issue: 395, P. 123888 - 123888

Published: Dec. 27, 2023

Efficient drug delivery systems (DDSs) play a pivotal role in ensuring pharmaceuticals' targeted and effective administration. However, the intricate interplay between formulations poses challenges their design optimization. Simulations have emerged as indispensable tools for comprehending these interactions enhancing DDS performance to address this complexity. This comprehensive review explores latest advancements simulation techniques provides detailed analysis. The encompasses various methodologies, including molecular dynamics (MD), Monte Carlo (MC), finite element analysis (FEA), computational fluid (CFD), density functional theory (DFT), machine learning (ML), dissipative particle (DPD). These are critically examined context of research. article presents illustrative case studies involving liposomal, polymer-based, nano-particulate, implantable DDSs, demonstrating influential simulations optimizing systems. Furthermore, addresses advantages limitations It also identifies future directions research development, such integrating multiple techniques, refining validating models greater accuracy, overcoming limitations, exploring applications personalized medicine innovative DDSs. employing like MD, MC, FEA, CFD, DFT, ML, DPD offer crucial insights into behaviour, aiding Despite advantages, rapid cost-effective screening, require validation addressing limitations. Future should focus on models, enhance outcomes. paper underscores contribution emphasizing providing valuable facilitating development optimization ultimately patient As we continue explore impact advancing discovery improving DDSs is expected be profound.

Language: Английский

Citations

52
Synthesis, characterization, and anticancer potency of coumarin-derived thiosemicarbazones and their Copper(II) complexes DOI
Ramina Maharjan Shrestha, Kuldeep Mahiya, Asmita Shrestha

et al.

Inorganic Chemistry Communications, Journal Year: 2024, Volume and Issue: 161, P. 112142 - 112142

Published: Jan. 29, 2024

Language: Английский

Citations

18
How We Think about Targeting RNA with Small Molecules DOI
Matthew G. Costales, Jessica L. Childs‐Disney, Hafeez S. Haniff

et al.

Journal of Medicinal Chemistry, Journal Year: 2020, Volume and Issue: 63(17), P. 8880 - 8900

Published: March 26, 2020

RNA offers nearly unlimited potential as a target for small molecule chemical probes and lead medicines. Many RNAs fold into structures that can be selectively targeted with molecules. This Perspective discusses molecular recognition of by molecules highlights key enabling technologies properties bioactive interactions. Sequence-based design ligands targeting has established rules affecting targets provided potentially general platform the discovery The contain preferred binding sites identified from sequence, allowing identification off-targets prediction interactions nature ligand functional sites. Small degradation (ribonuclease-targeted chimeras, RIBOTACs) direct cleavage have also been developed. These growing suggest time is right to provide functionally relevant throughout human transcriptome.

Language: Английский

Citations

137
Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace DOI Creative Commons
Natesh Singh,

Ludovic Chaput,

Bruno O. Villoutreix

et al.

Briefings in Bioinformatics, Journal Year: 2020, Volume and Issue: 22(2), P. 1790 - 1818

Published: Feb. 25, 2020

The interplay between life sciences and advancing technology drives a continuous cycle of chemical data growth; these are most often stored in open or partially databases. In parallel, many different types algorithms being developed to manipulate objects associated bioactivity data. Virtual screening methods among the popular computational approaches pharmaceutical research. Today, user-friendly web-based tools available help scientists perform virtual experiments. This article provides an overview internet resources enabling supporting biology early drug discovery with main emphasis on web servers dedicated ligand small-molecule docking. survey first introduces some key concepts then presents recent easily accessible related target-fishing as well briefly discusses case studies enabled by services. Notwithstanding further improvements, already not only contribute design bioactive molecules assist repositioning but also generate new ideas explore hypotheses timely fashion while contributing teaching field development.

Language: Английский

Citations

109
Identification of potential inhibitors of SARS-CoV-2 main protease from Aloe vera compounds: A molecular docking study DOI Open Access

Pius T. Mpiana,

Koto-te-Nyiwa Ngbolua, Damien S. T. Tshibangu

et al.

Chemical Physics Letters, Journal Year: 2020, Volume and Issue: 754, P. 137751 - 137751

Published: June 30, 2020

Language: Английский

Citations

103
Challenges of peptide and protein drug delivery by oral route: Current strategies to improve the bioavailability DOI
Saurabh Verma,

Umesh K. Goand,

Athar Husain

et al.

Drug Development Research, Journal Year: 2021, Volume and Issue: 82(7), P. 927 - 944

Published: May 14, 2021

Abstract Advancement in biotechnology provided a notable expansion of peptide and protein therapeutics, used as antigens, vaccines, hormones. It has prodigious potential to treat broad spectrum diseases such cancer, metabolic disorders, bone so forth. Protein therapeutics are administered parenterally due their poor bioavailability stability, restricting use. Hence, research focuses on the oral delivery peptides proteins for ease self‐administration. In present review, we first address main obstacles system addition approaches enhance stability peptide/protein. We describe physiochemical parameters influencing systemic circulation. encounters, many barriers affecting its cellular membrane permeability at GIT site, enzymatic degradation (various proteases), first‐pass hepatic metabolism. Then current overcome challenges mentioned above by use absorption enhancers or carriers, structural modification, formulation advance technology.

Language: Английский

Citations

85
SwissADME and pkCSM Webservers Predictors: an integrated Online Platform for Accurate and Comprehensive Predictions for In Silico ADME/T Properties of Artemisinin and its Derivatives DOI Open Access

Khaldun AL Azzam

Kompleksnoe Ispolzovanie Mineralnogo Syra = Complex Use of Mineral Resources, Journal Year: 2022, Volume and Issue: 325(2), P. 14 - 21

Published: Nov. 28, 2022

In vivo ADME testing is costly, time-consuming, and puts animal lives at risk, whereas in silico safer, simpler, faster. This study will use methodologies from SwissADME pkCSM as an integrated online platform for accurate comprehensive predictions to determine Silico ADME/T Properties of Artemisinin its Derivatives. The investigated compounds' structures were translated into canonical SMILES format then submitted the webserver tools, which provide free access different properties compounds. A compound's characteristics are critical future results obtained be beneficial researchers. Additionally, this give great guidance show that chemical alterations reference molecule artemisinin can enhance ADMET capabilities. webservers used work free, several comparison trials performed better than a number other frequently methods. designing or engineering novel drug primarily requires knowledge features new compound.

Language: Английский

Citations

68