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We show a double-functional fluorescence sensing paradigm that can retrieve nanometric pH information on biological structures. We use this method to measure the extent of protonic condensation around microtubules, which are protein polymers that play many roles crucial to cell function. While microtubules are believed to have a profound impact on the local cytoplasmic pH, this has been hard to show experimentally due to the limitations of conventional sensing techniques. We show that subtle changes in the local electrochemical surroundings cause a double-functional sensor to transform its spectrum, thus allowing a direct measurement of the protonic concentration at the microtubule surface. Microtubules concentrate protons by as much as one unit on the pH scale, indicating a charge storage role within the cell via the localized ionic condensation. These results confirm the bioelectrical significance of microtubules and reveal a sensing concept that can deliver localized biochemical information on intracellular structures.

Positron emission tomography (PET) using 2-deoxy-2-[18 F]fluoro-d-glucose ([18 F]FDG), a marker of energy metabolism and cell proliferation, is routinely used in the clinic to assess patient response to chemotherapy and to monitor tumor growth. Treatment with some tyrosine kinase inhibitors (TKIs) causes changes in blood glucose levels in both nondiabetic and diabetic patients. We evaluated the interaction of several classes of TKIs with human glucose transporter-1 (hGLUT-1) in FaDu and GIST-1 cells by measuring [3 H]2-deoxy-d-glucose ([3 H]2-DG) and [3 H]FDG uptake. Uptake of both was inhibited to varying extents by the TKIs, and representative TKIs from each class showed competitive inhibition of [3 H]2-DG uptake. In GIST-1 cells, [3 H]FDG uptake inhibition by temsirolimus and nilotinib was irreversible, whereas inhibition by imatinib, gefitinib, and pazopanib was reversible. Molecular modeling studies showed that TKIs form multiple hydrogen bonds with polar residues of the sugar binding site (i.e., Q161, Q282, Q283, N288, N317, and W388), and van der Waals interactions with the H-pocket site. Our results showed interaction of TKIs with amino acid residues at the glucose binding site to inhibit glucose uptake by hGLUT-1. We hypothesize that inhibition of hGLUT-1 by TKIs could alter glucose levels in patients treated with TKIs, leading to hypoglycemia and fatigue, although further studies are required to evaluate roles of other SLC2 and SLC5 members. In addition, TKIs could affect tumor [18 F]FDG uptake, increasingly used as a marker of tumor response. The hGLUT-1 inhibition by TKIs may have implications for routine [18 F]FDG-PET monitoring of tumor response in patients.

Given its critical role in cell mitosis, the tubulin γ chain represents a viable chemotherapeutic target to solve the specificity issues associated with targeting α and β tubulin. Since γ tubulin is overexpressed in glioblastoma multiforme (GBM) and some breast lesions, the glaziovianin A derivative gatastatin, presented as a γ-tubulin-specific inhibitor, could yield a successful therapeutic strategy. The present work aims to identify the binding sites and modes of gatastatin and its derivatives through molecular-docking simulations. Computational binding free energy predictions were compared to experimental microscale thermophoresis assay results. The computational simulations did not reveal a strong preference toward γ tubulin, suggesting that further derivatization may be needed to increase its specificity.

BackgroundThe emergence and rapid spread of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) in thelate 2019 has caused a devastating global pandemic of the severe pneumonia-like disease coronavirus disease 2019 (COVID-19). Although vaccines have been and are being developed, they are not accessible to everyone and not everyone can receive these vaccines. Also, it typically takes more than 10 years until a new therapeutic agent is approved for usage. Therefore, repurposing of known drugs can lend itself well as a key approach for significantly expediting the development of new therapies for COVID-19.MethodsWe have incorporated machine learning-based computational tools and in silico models into the drug discovery process to predict Adsorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profiles of 90 potential drugs for COVID-19 treatment identified from two independent studies mainly with the purpose of mitigating late-phase failures because of inferior pharmacokinetics and toxicity.ResultsHere, we summarize the cardiotoxicity and general toxicity profiles of 90 potential drugs for COVID-19 treatment and outline the risks of repurposing and propose a stratification of patients accordingly. We shortlist a total of five compounds based on their non-toxic properties.ConclusionIn summary, this manuscript aims to provide a potentially useful source of essential knowledge on toxicity assessment of 90 compounds for healthcare practitioners and researchers to find off-label alternatives for the treatment for COVID-19. The majority of the molecules discussed in this manuscript have already moved into clinical trials and thus their known pharmacological and human safety profiles are expected to facilitate a fast track preclinical and clinical assessment for treating COVID-19.

Purpose: The ultimate goal of this study is to develop a novel delivery system for a new potent cytotoxic compound, CCI-001, with anti-b tubulin activity, so that the drug can be effectively administered and at the same time its harmful side effects can be reduced. Methods: In the current study, CCI-001 was loaded into serum albumin (SA), using a modified desolvation method, generating CCI-001-SA nanoparticles. Both bovine and human SA were used for the encapsulation of this drug candidate. Optimum conditions for drug loading were achieved when already formed and crosslinked albumin nanoparticles were incubated overnight at 37°C with CCI-001 solutions. The CCI-001-loaded albumin nanoparticles were assessed for average particle diameter and polydispersity, zeta potential, drug loading, in vitro release, morphology and cell toxicity against SW620 and HCT116 colorectal cancer cells. Results: The spherical nanoparticles obtained were negatively charged (~ -30 mV) and had an average diameter of ~ 130 nm, with a narrow size distribution. The in vitro release of CCI-001 from the albumin nanoparticles showed a sustained release pattern over 24 hours without any initial burst release, compared to the fast release of the free drug under experimental conditions. No difference between the SA from the two species in terms of CCI-001 loading was observed. However, a significant difference was observed between the release profiles of CCI-001 from drug-loaded HSA and drug-loaded BSA nanoparticles with HSA nanoparticles showing slower drug release (mean release time, MRT, values of 5.14 ± 0.33 h and 6.88 ± 0.15 h for BSA-NPs and HSA-NPs, respectively, P < 0.01). Cellular toxicity studies showed higher cytotoxicity for CCI-001-SA compared to the free drug (IC50s of 0.62 ± 0.31 nM vs 2.06 ± 0.29 nM in SW620 cells and 0.9 ± 0.1 nM vs 4.2 ± 0.2 nM in HCT116 cells, for CCI-001-HSA NPs and free drug, respectively). Therefore, despite the low drug content level in the HSA nanoparticles of CCI-001, the formulation provides relevant concentrations for further in vivo studies in animal models due to high drug potency. Conclusions: The data support the potential use of albumin as a nanocarrier for CCI-001 in biological systems.

Positron emission tomography (PET) using 2‐deoxy‐2‐[18F]fluoro‐d‐glucose ([18F]FDG), a marker of energy metabolism and cell proliferation, is routinely used in the clinic to assess patient response to chemotherapy and to monitor tumor growth. Treatment with some tyrosine kinase inhibitors (TKIs) causes changes in blood glucose levels in both nondiabetic and diabetic patients. We evaluated the interaction of several classes of TKIs with human glucose transporter‐1 (hGLUT‐1) in FaDu and GIST‐1 cells by measuring [3H]2‐deoxy‐d‐glucose ([3H]2‐DG) and [3H]FDG uptake. Uptake of both was inhibited to varying extents by the TKIs, and representative TKIs from each class showed competitive inhibition of [3H]2‐DG uptake. In GIST‐1 cells, [3H]FDG uptake inhibition by temsirolimus and nilotinib was irreversible, whereas inhibition by imatinib, gefitinib, and pazopanib was reversible. Molecular modeling studies showed that TKIs form multiple hydrogen bonds with polar residues of the sugar binding site (i.e., Q161, Q282, Q283, N288, N317, and W388), and van der Waals interactions with the H‐pocket site. Our results showed interaction of TKIs with amino acid residues at the glucose binding site to inhibit glucose uptake by hGLUT‐1. We hypothesize that inhibition of hGLUT‐1 by TKIs could alter glucose levels in patients treated with TKIs, leading to hypoglycemia and fatigue, although further studies are required to evaluate roles of other SLC2 and SLC5 members. In addition, TKIs could affect tumor [18F]FDG uptake, increasingly used as a marker of tumor response. The hGLUT‐1 inhibition by TKIs may have implications for routine [18F]FDG‐PET monitoring of tumor response in patients.

Colchicine is a well-known anticancer compound showing antimitotic effect on cells. Its high cytotoxic activity against different cancer cell lines has been demonstrated many times. In this paper we report the syntheses and spectroscopic analyses of novel colchicine derivatives obtained by structural modifications at C7 (carbon-nitrogen single bond) and C10 (methylamino group) positions. All the obtained compounds have been tested in vitro to determine their cytotoxicity toward A549, MCF-7, LoVo, LoVo/DX, and BALB/3T3 cell lines. The majority of obtained derivatives exhibited higher cytotoxicity than colchicine, doxorubicin and cisplatin against the tested cancerous cell lines. Additionally, most of the presented derivatives were able to overcome the resistance of LoVo/DX cells. Additionally, their mode of binding to &beta, tubulin was evaluated in silico. Molecular docking studies showed that apart from the initial amides 1 and 2, compound 14, which had the best antiproliferative activity (IC50 = 0.1&ndash, 1.6 nM), stood out also in terms of its predicted binding energy and probably binds best into the active site of &beta, I-tubulin isotype.

Colchicine is a well-known compound with strong antiproliferative activity that has had limited use in chemotherapy because of its toxicity. In order to create more potent anticancer agents, a series of novel colchicine derivatives have been obtained by simultaneous modification at C7 (amides and sulfonamides) and at C10 (methylamino group) positions and characterized by spectroscopic methods. All the synthesized compounds have been tested in vitro to evaluate their cytotoxicity toward A549, MCF-7, LoVo, LoVo/DX and BALB/3T3 cell lines. Additionally, the activity of the studied compounds was investigated using computational methods involving molecular docking of the colchicine derivatives to &beta, tubulin. The majority of the obtained derivatives exhibited higher cytotoxicity than colchicine, doxorubicin or cisplatin against tested cancer cell lines. Furthermore, molecular modeling studies of the obtained compounds revealed their possible binding modes into the colchicine binding site of tubulin.

This article reports on the results of research aimed to translate biometric 3D face recognition concepts and algorithms into the field of protein biophysics in order to precisely and rapidly classify morphological features of protein surfaces. Both human faces and protein surfaces are free-forms and some descriptors used in differential geometry can be used to describe them applying the principles of feature extraction developed for computer vision and pattern recognition. The first part of this study focused on building the protein dataset using a simulation tool and performing feature extraction using novel geometrical descriptors. The second part tested the method on two examples, first involved a classification of tubulin isotypes and the second compared tubulin with the FtsZ protein, which is its bacterial analog. An additional test involved several unrelated proteins. Different classification methodologies have been used: a classic approach with a support vector machine (SVM) classifier and an unsupervised learning with a k-means approach. The best result was obtained with SVM and the radial basis function kernel. The results are significant and competitive with the state-of-the-art protein classification methods. This leads to a new methodological direction in protein structure analysis.

Galectin-3 is a carbohydrate-binding protein and the most studied member of the galectin family. It regulates several functions throughout the body, among which are inflammation and post-injury remodelling. Recent studies have highlighted the similarity between Galectin-3′s carbohydrate recognition domain and the so-called “galectin fold” present on the N-terminal domain of the S1 sub-unit of the SARS-CoV-2 spike protein. Sialic acids binding to the N-terminal domain of the Spike protein are known to be crucial for viral entry into humans, and the role of Galectin-3 as a mediator of lung fibrosis has long been the object of study since its levels have been found to be abnormally high in alveolar macrophages following lung injury. In this context, the discovery of a double inhibitor may both prevent viral entry and reduce post-infection pulmonary fibrosis. In this study, we use a database of 56 compounds, among which 37 have known experimental affinity with Galectin-3. We carry out virtual screening of this database with respect to Galectin-3 and Spike protein. Several ligands are found to exhibit promising binding affinity and interaction with the Spike protein’s N-terminal domain as well as with Galectin-3. This finding strongly suggests that existing Galectin-3 inhibitors possess dual-binding capabilities to disrupt Spike–ACE2 interactions. Herein we identify the most promising inhibitors of Galectin-3 and Spike proteins, of which five emerge as potential dual effective inhibitors. Our preliminary results warrant further in vitro and in vivo testing of these putative inhibitors against SARS-CoV-2 with the hope of being able to halt the spread of the virus in the future.

In this paper we review the current status of high-performance computing applications in the general area of drug discovery. We provide an introduction to the methodologies applied at atomic and molecular scales, followed by three specific examples of implementation of these tools. The first example describes in silico modeling of the adsorption of small molecules to organic and inorganic surfaces, which may be applied to drug delivery issues. The second example involves DNA translocation through nanopores with major significance to DNA sequencing efforts. The final example offers an overview of computer-aided drug design, with some illustrative examples of its usefulness.

Colchicine shows very high antimitotic activity, therefore, it is used as a lead compound for generation of new anticancer agents. In the hope of developing novel, useful drugs with more favourable pharmacological profiles, a series of doubly modified colchicine derivatives has been designed, synthesized and characterized. These novel carbamate or thiocarbamate derivatives of 10-demethoxy-10-methylaminocolchicine have been tested for their antiproliferative activity against four human cancer cell lines. Additionally, their mode of action has been evaluated as colchicine binding site inhibitors, using molecular docking studies. Most of the tested compounds showed greater cytotoxicity (IC50 in a low nanomolar range) and were characterized by a higher selectivity index than standard chemotherapeutics such as cisplatin and doxorubicin as well as unmodified colchicine. Their pharmacological use in cancer therapy could possibly be accomplished with lower dosages and result in less acute toxicity problems than in the case of colchicine. In addition, we present a QSAR model for predicting the antiproliferative activity of doubly modified derivatives for two tumour cell lines.

Catalytic hydrogenation is an important process used for the production of everything from foods to fuels. Current heterogeneous implementations of this process utilize metals as the active species. Until recently, catalytic heterogeneous hydrogenation over a metal-free solid was unknown; implementation of such a system would eliminate the health, environmental, and economic concerns associated with metal-based catalysts. Here, we report good hydrogenation rates and yields for a metal-free heterogeneous hydrogenation catalyst as well as its unique hydrogenation mechanism. Catalytic hydrogenation of olefins was achieved over defect-laden h-BN (dh-BN) in a reactor designed to maximize the defects in h-BN sheets. Good yields (>90%) and turnover frequencies (6 × 10–5–4 × 10–3) were obtained for the hydrogenation of propene, cyclohexene, 1,1-diphenylethene, (E)- and (Z)-1,2-diphenylethene, octadecene, and benzylideneacetophenone. Temperature-programmed desorption of ethene over processed h-BN indicates the formation of a highly defective structure. Solid-state NMR (SSNMR) measurements of dh-BN with high and low propene surface coverages show four different binding modes. The introduction of defects into h-BN creates regions of electronic deficiency and excess. Density functional theory calculations show that both the alkene and hydrogen-bond order are reduced over four specific defects: boron substitution for nitrogen (BN), vacancies (VB and VN), and Stone–Wales defects. SSNMR and binding-energy calculations show that VN are most likely the catalytically active sites. This work shows that catalytic sites can be introduced into a material previously thought to be catalytically inactive through the production of defects.

Biomining of valuable metals using a target specific approach promises increased purification yields and decreased cost. Target specificity can be implemented with proteins/peptides, the biological molecules, responsible from various structural and functional pathways in living organisms by virtue of their specific recognition abilities towards both organic and inorganic materials. Phage display libraries are used to identify peptide biomolecules capable of specifically recognizing and binding organic/inorganic materials of interest with high affinities. Using combinatorial approaches, these molecular recognition elements can be converted into smart hybrid biomaterials and harnessed for biotechnological applications. Herein, we used a commercially available phage-display library to identify peptides with specific binding affinity to molybdenite (MoS2) and used them to decorate magnetic NPs. These peptide-coupled NPs could capture MoS2 under a variety of environmental conditions. The same batch of NPs could be re-used multiple times to harvest MoS2, clearly suggesting that this hybrid material was robust and recyclable. The advantages of this smart hybrid biomaterial with respect to its MoS2-binding specificity, robust performance under environmentally challenging conditions and its recyclability suggests its potential application in harvesting MoS2 from tailing ponds and downstream mining processes.

We have developed two functionalized β-sheet peptides (FBPs) and demonstrated that they can stabilize a variety of integral membrane proteins (IMPs), and most importantly allow covalent crosslinking of the IMPs onto solid supports via the highly selective click chemistry. The FBPs are promising tools for the preparation of IMP-based biomaterials or biosensors.

We perform first-principles calculations of the properties of the Mg(0001) surface of thin films to examine the giant oscillations of surface energy and interlayer relaxation of Mg(0001) films as a function of thickness reported previously. We find that, although overcoming the thin-film limit requires up to 25 layers, properties exclusive to the surface layer are well converged for 18-layer thick films (~ 4.1 nm). Furthermore, the fcc-stacking fault is found to be energetically favorable for the Mg adatom by 15 meV. We also find that the binding energy of the Mg adatom (~ 0.6 eV), well converged for 7-layer films, is significantly weaker than the value reported by previous calculations. In addition, our calculations show small diffusion barriers of 9 meV (hcp to fcc) and 25 meV (fcc to hcp) for the monomer.

Biomining of valuable metals using a target specific approach promises increased purification yields and decreased cost. Target specificity can be implemented with proteins/peptides, the biological molecules, responsible from various structural and functional pathways in living organisms by virtue of their specific recognition abilities towards both organic and inorganic materials. Phage display libraries are used to identify peptide biomolecules capable of specifically recognizing and binding organic/inorganic materials of interest with high affinities. Using combinatorial approaches, these molecular recognition elements can be converted into smart hybrid biomaterials and harnessed for biotechnological applications. Herein, we used a commercially available phage-display library to identify peptides with specific binding affinity to molybdenite (MoS2) and used them to decorate magnetic NPs. These peptide-coupled NPs could capture MoS2 under a variety of environmental conditions. The same batch of NPs could be re-used multiple times to harvest MoS2, clearly suggesting that this hybrid material was robust and recyclable. The advantages of this smart hybrid biomaterial with respect to its MoS2-binding specificity, robust performance under environmentally challenging conditions and its recyclability suggests its potential application in harvesting MoS2 from tailing ponds and downstream mining processes.

Based on density functional theory (DFT) predictions and scanning tunneling microscopy (STM) measurements we report the possibility of using the Cu(111) surface for growth of molybdenum sulfide nanowires (Mo 6 S 6 ). Strong substrate interactions coupled with small lattice mismatch lead to epitaxial growth of the nanowires parallel to a set of substrate high symmetry directions. We observe a propensity for creation of aligned and equally spaced arrays of nanowires and use DFT to elucidate interaction strength both in the absence and presence of the substrate.

Recent advances in experimental DNA origami have dramatically expanded the horizon of DNA nanotechnology. Complex 3D suprastructures have been designed and developed using DNA origami with applications in biomaterial science, nanomedicine, nanorobotics, and molecular computation. Ribonucleic acid (RNA) origami has recently been realized as a new approach. Similar to DNA, RNA molecules can be designed to form complex 3D structures through complementary base pairings. RNA origami structures are, however, more compact and more thermodynamically stable due to RNA's non-canonical base pairing and tertiary interactions. With all these advantages, the development of RNA origami lags behind DNA origami by a large gap. Furthermore, although computational methods have proven to be effective in designing DNA and RNA origami structures and in their evaluation, advances in computational nucleic acid origami is even more limited. In this paper, we review major milestones in experimental and computational DNA and RNA origami and present current challenges in these fields. We believe collaboration between experimental nanotechnologists and computer scientists are critical for advancing these new research paradigms.

We present the results of ab initio electronic structure calculations for the adsorption characteristics of three amine molecules on Au(111), which show that the inclusion of van der Waals interactions between the isolated molecule and the surface leads in general to good agreement with experimental data on the binding energies. Each molecule, however, adsorbs with a small tilt angle (between -5 and 9°). For the specific case of 1,4-diaminobenzene (BDA) our calculations reproduce the larger tilt angle (close to 24°) measured by photoemission experiments, when intermolecular (van der Waals) interactions (for about 8% coverage) are included. These results point not only to the important contribution of van der Waals interactions to molecule-surface binding energy, but also that of intermolecular interactions, often considered secondary to that between the molecule and the surface, in determining the adsorption geometry and pattern formation.