In silico-guided discovery and in vitro validation of novel sugar-tethered lysinated carbon nanotubes for targeted drug delivery of doxorubicin.

CONTEXT: Multiwalled carbon nanotubes (MWCNTs) functionalized with lysine via 1,3-dipolar cycloaddition and conjugated to galactose or mannose are potential nanocarriers that can effectively bind to the lectin receptor in MDA-MB-231 or MCF-7 breast cancer cells. In this work, a method based on molecular dynamics (MD) simulation was used to predict the interaction of these functionalized MWCNTs with doxorubicin and obtain structural evidence that allows a better understanding of the drug loading and release process. The MD simulations showed that while doxorubicin only interacted with pristine MWCNTs through π-π stacking interactions, functionalized MWCNTs were also able to establish hydrogen bonds, suggesting that the functionalized groups improve doxorubicin loading. Moreover, the elevated adsorption levels observed for functionalized nanotubes further support this enhancement in loading efficiency. MD simulations also shed light on the intratumoral pH-specific release of doxorubicin from functionalized MWCNTs, which is induced by protonation of the daunosamine moiety. The simulations show that this change in protonation leads to a lower absorption of doxorubicin to the MWCNTs. The MD studies were then experimentally validated, where functionalized MWCNTs showed improved dispersion in aqueous medium compared to pristine MWCNTs and, in agreement with the computational predictions, increased drug loading capacity. Doxorubicin-loaded functionalized MWCNTs demonstrated specific release of doxorubicin in tumor microenvironment (pH = 5.0) with negligible release in the physiological pH (pH = 7.4). Furthermore, doxorubicin-free MWNCT nanoformulations exhibited insignificant cytotoxicity. The experimental studies yielded nearly identical results to the MD studies, underlining the usefulness of the method. Our functionalized MWCNTs represent promising non-toxic nanoplatforms with enhanced aqueous dispersibility and the potential for conjugation with ligands for targeted delivery of anti-cancer drugs to breast cancer cells. METHODS: The computational model of a pristine carbon nanotube was created with the buildCstruct 1.2 Python script. The lysinated functionalized groups were added with PyMOL and VMD. The carbon nanotubes and doxorubicin molecules were parameterized using the general AMBER force field, and RESP charges were determined using Gaussian 09. Molecular dynamics simulations were carried out with the AMBER 20 software package. Adsorption levels were calculated using the water-shell function of cpptraj. Cytotoxicity was evaluated via a MTT assay using MDA-MB-231 and MCF-7 breast cancer cells. Drug uptake of doxorubicin and doxorubicin-loaded MWCNTs was measured by fluorescence microscopy.

Selection of Bis-Indolyl Pyridines and Triphenylamines as New Inhibitors of SARS-CoV-2 Cellular Entry by Modulating the Spike Protein/ACE2 Interfaces.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the infectious agent that has caused the current coronavirus disease (COVID) pandemic. Viral infection relies on the viral S (spike) protein/cellular receptor ACE2 interaction. Disrupting this interaction would lead to early blockage of viral replication. To identify chemical tools to further study these functional interfaces, 139,146 compounds from different chemical libraries were screened through an S/ACE2 in silico virtual molecular model. The best compounds were selected for further characterization using both cellular and biochemical approaches, reiterating SARS-CoV-2 entry and the S/ACE2 interaction. We report here two selected hits, bis-indolyl pyridine AB-00011778 and triphenylamine AB-00047476. Both of these compounds can block the infectivity of lentiviral vectors pseudotyped with the SARS-CoV-2 S protein as well as wild-type and circulating variant SARS-CoV-2 strains in various human cell lines, including pulmonary cells naturally susceptible to infection. AlphaLISA and biolayer interferometry confirmed a direct inhibitory effect of these drugs on the S/ACE2 association. A specific study of the AB-00011778 inhibitory properties showed that this drug inhibits viral replication with a 50% effective concentration (EC50) between 0.1 and 0.5 µM depending on the cell lines. Molecular docking calculations of the interaction parameters of the molecules within the S/ACE2 complex from both wild-type and circulating variants of the virus showed that the molecules may target multiple sites within the S/ACE2 interface. Our work indicates that AB-00011778 constitutes a good tool for modulating this interface and a strong lead compound for further therapeutic purposes.

In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of Mycobacterium tuberculosis.

With tuberculosis still being one of leading causes of death in the world and the emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb), researchers have been seeking to find further therapeutic strategies or more specific molecular targets. PknB is one of the 11 Ser/Thr protein kinases of Mtb and is responsible for phosphorylation-mediated signaling, mainly involved in cell wall synthesis, cell division and metabolism. With the amount of structural information available and the great interest in protein kinases, PknB has become an attractive target for drug development. This work describes the optimization and application of an in silico computational protocol to find new PknB inhibitors. This multi-level computational approach combines protein-ligand docking, structure-based virtual screening, molecular dynamics simulations and free energy calculations. The optimized protocol was applied to screen a large dataset containing 129,650 molecules, obtained from the ZINC/FDA-Approved database, Mu.Ta.Lig Virtual Chemotheca and Chimiothèque Nationale. It was observed that the most promising compounds selected occupy the adenine-binding pocket in PknB, and the main interacting residues are Leu17, Val26, Tyr94 and Met155. Only one of the compounds was able to move the active site residues into an open conformation. It was also observed that the P-loop and magnesium position loops change according to the characteristics of the ligand. This protocol led to the identification of six compounds for further experimental testing while also providing additional structural information for the design of more specific and more effective derivatives.

Identification of New Potential Inhibitors of Quorum Sensing through a Specialized Multi-Level Computational Approach.

Biofilms are aggregates of microorganisms anchored to a surface and embedded in a self-produced matrix of extracellular polymeric substances and have been associated with 80% of all bacterial infections in humans. Because bacteria in biofilms are less amenable to antibiotic treatment, biofilms have been associated with developing antibiotic resistance, a problem that urges developing new therapeutic options and approaches. Interfering with quorum-sensing (QS), an important process of cell-to-cell communication by bacteria in biofilms is a promising strategy to inhibit biofilm formation and development. Here we describe and apply an in silico computational protocol for identifying novel potential inhibitors of quorum-sensing, using CviR-the quorum-sensing receptor from Chromobacterium violaceum-as a model target. This in silico approach combines protein-ligand docking (with 7 different docking programs/scoring functions), receptor-based virtual screening, molecular dynamic simulations, and free energy calculations. Particular emphasis was dedicated to optimizing the discrimination ability between active/inactive molecules in virtual screening tests using a target-specific training set. Overall, the optimized protocol was used to evaluate 66,461 molecules, including those on the ZINC/FDA-Approved database and to the Mu.Ta.Lig Virtual Chemotheca. Multiple promising compounds were identified, yielding good prospects for future experimental validation and for drug repurposing towards QS inhibition.

Databases for the study of biofilms: current status and potential applications.

Biofilms play an important role in health, being associated with >80% of all microbial infections in the body and in the development of antibiotic resistance. Research in this field has continuously produced large volumes of data. Being able to handle all this information will be paramount for progress in this field. However, this places a heavy burden on the development of strategies to gather, organize and make this information available in a way that can be readily and effectively used by those requiring it. Lately, efforts towards this goal have been reported, particularly with the development of Quorumpeps, BiofOmics, BaAMPs, QSPpred, dPABBs, aBiofilm and the Biofilms Structural Database. This work reviews these databases and highlights their applicability and potential, while stressing some of the challenges for the coming years in database development and usage brought about by the use of big data and machine learning.