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Immunotherapy, particularly targeting the PD-1/PD-L1 pathway, holds promise in cancer treatment by regulating the immune response and preventing cancer cells from evading immune destruction. Nonetheless, this approach poses a risk of unwanted immune system activation against healthy cells. To minimize this risk, our study proposes a strategy based on selective targeting of the PD-L1 pathway within the acidic microenvironment of tumors. We employed in silico methods, such as virtual screening, molecular mechanics, and molecular dynamics simulations, analyzing approximately 10,000 natural compounds from the MolPort database to find potential hits with the desired properties. The simulations were conducted under two pH conditions (pH = 7.4 and 5.5) to mimic the environments of healthy and cancerous cells. The compound MolPort-001-742-690 emerged as a promising pH-selective inhibitor, showing a significant affinity for PD-L1 in acidic conditions and lower toxicity compared to known inhibitors like BMS-202 and LP23. A detailed 1000 ns molecular dynamics simulation confirmed the stability of the inhibitor-PD-L1 complex under acidic conditions. This research highlights the potential of using in silico techniques to discover novel pH-selective inhibitors, which, after experimental validation, may enhance the precision and reduce the toxicity of immunotherapies, offering a transformative approach to cancer treatment.

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Even though the vast armamentarium of FDA-approved antiepileptic drugs is currently available, over one-third of patients do not respond to medication, which arises a need for alternative medicine. In clinical and preclinical studies, various investigations have shown the advantage of specific plant-based cannabidiol (CBD) products in treating certain groups of people with limbic epilepsy who have failed to respond to conventional therapies. This work aims to investigate possible mechanisms by which CBD possesses its anticonvulsant properties. Molecular targets for CBD's treatment of limbic epilepsy, including hyperpolarization-activated cyclic nucleotide-gated channel 1 (HCN1), gamma-aminobutyric acid aminotransferase (GABA-AT), and gamma-aminobutyric acid type A receptor (GABAA), were used to evaluate its binding affinity. Interactions with the CB1 receptor were initially modeled as a benchmark, which further proved the efficiency of proposed here approach. Considering the successful benchmark, we further used the same concept for in silico investigation, targeting proteins of interest. As a result of molecular docking, molecular mechanics, and molecular dynamics simulations models of CBD-receptor complexes were proposed and evaluated. While CBD possessed decently high affinity and stability within the binding pockets of GABA-AT and some binding sites of GABAA, the most effective binding was observed in the CBD complex with HCN1 receptor. 100 ns molecular dynamics simulation revealed that CBD binds the open pore of HCN1 receptor, forming a similar pattern of interactions as potent Lamotrigine. Therefore, we can propose that HCN1 can serve as a most potent target for cannabinoid antiepileptic treatment. Communicated by Ramaswamy H. Sarma.

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The rapid spread of SARS-CoV-2 required immediate actions to control the transmission of the virus and minimize its impact on humanity. An extensive mutation rate of this viral genome contributes to the virus' ability to quickly adapt to environmental changes, impacts transmissibility and antigenicity, and may facilitate immune escape. Therefore, it is of great interest for researchers working in vaccine development and drug design to consider the impact of mutations on virus-drug interactions. Here, we propose a multitarget drug discovery pipeline for identifying potential drug candidates which can efficiently inhibit the Receptor Binding Domain (RBD) of spike glycoproteins from different variants of SARS-CoV-2. Eight homology models of RBDs for selected variants were created and validated using reference crystal structures. We then investigated interactions between host receptor ACE2 and RBDs from nine variants of SARS-CoV-2. It led us to conclude that efficient multi-variant targeting drugs should be capable of blocking residues Q(R)493 and N487 in RBDs. Using methods of molecular docking, molecular mechanics, and molecular dynamics, we identified three lead compounds (hesperidin, narirutin, and neohesperidin) suitable for multitarget SARS-CoV-2 inhibition. These compounds are flavanone glycosides found in citrus fruits - an active ingredient of Traditional Chinese Medicines. The developed pipeline can be further used to (1) model mutants for which crystal structures are not yet available and (2) scan a more extensive library of compounds against other mutated viral proteins.

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Density functional theory methods have been applied to understand binding of (s)-propranolol, a template, to a methacrylic acid molecule acting as a functional monomer using basic 1:1 model. The model has been expanded to study the effect of various pH by adding hydronium and hydroxide ions solvated by water molecules to the template-monomer system, to mimic acidic and basic environments, respectively. This could be considered a model study towards a potential use of molecular imprinting method for the design of a transdermal patch for a topical and direct delivery of (s)-propranolol to hemangiomas. In addition, this study provides detailed binding site analysis of the template and functional monomer verified by the theoretical IR spectra analysis, as well as solvent and pH effects on template-monomer binding energy.

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Due to an outbreak of COVID-19, the number of research papers devoted to in-silico drug discovery of potential antiviral drugs is increasing every day exponentially. Still, there is no specific drug to prevent or treat this novel coronavirus (SARS-CoV-2) disease. Thus, the screening for a potential remedy presents a global challenge for scientists. Up to date over a hundred crystallographic structures of SARS-CoV-2 Mpro have been deposited to Protein Data Bank. With many known proteins, the demand for a reliable target has become higher than ever, so as the choice of an efficient computational methods. Therefore, in this study comparative methods have been used for receptor-based virtual screening, targeting 9 selected structures of viral Mpro. Reliability analyses followed by re-docking of the specific co-crystallized ligand provided the best reproductivity for structures with PDB ID 6LU7, 6Y2G and 6Y2F. The influence of crystallographic water on an outcome of a virtual screening against selected targets was also investigated. Once the most reliable targets were selected, the library of easy purchasable natural compounds were retrieved from the MolPort database (10,305 compounds) and docked against the selected Mpro proteins. To ensure the efficiency of the selected compounds, binding energies for top-15 hit ligands were calculated using Molecular Mechanics as well as their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were predicted. Based on predicted binding energies and toxicities, top-5 compounds were selected and subjected to Molecular Dynamics simulation and found to be stable in complex to act as possible inhibitors for SARS-CoV-2. Communicated by Ramaswamy H. Sarma.

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Presented work reports a comprehensive theoretical study on the inhibitory nature of N-arylnaphthylamines in Human Immunodeficiency Virus Integrase (HIV IN) - Lens Epithelium-Derived Growth Factor (LEDGF/p75) complexes. Factors influencing the inhibition efficiency in AlphaScreen% assay are evaluated and explained through the structure- and ligand-based studies; including molecular docking, molecular dynamics calculations, and quantitative structure-activity relationship (QSAR) approach. It has been shown that N-arylnaphthylamines possess a wide variety of binding poses. Three QSAR models have been developed using structural descriptors and descriptors derived from docking calculations. The activity of untested N-arylnaphthylamines have been predicted using the most successful model. Proposed here technique could become a useful tool for ligand selection, accelerating the development of a new generation of anti-HIV medications. [Formula: see text] Communicated by Ramaswamy H. Sarma.

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Phenolic acids are naturally occurring compounds that are known for their antioxidant and antiradical activity. We present experimental and theoretical studies on the antioxidant potential of the set of 22 phenolic acids with different models of hydroxylation and methoxylation of aromatic rings. Ferric reducing antioxidant power assay was used to evaluate this property. 2,3-dihydroxybenzoic acid was found to be the strongest antioxidant, while mono hydroxylated and methoxylated structures had the lowest activities. A comprehensive structure-activity investigation with density functional theory methods elucidated the influence of compounds topology, resonance stabilization, and intramolecular hydrogen bonding on the exhibited activity. The key factor was found to be a presence of two or more hydroxyl groups being located in ortho or para position to each other. Finally, the quantitative structure-activity relationship approach was used to build a multiple linear regression model describing the dependence of antioxidant activity on structure of compounds, using features exclusively related to their topology. Coefficients of determination for training set and for the test set equaled 0.9918 and 0.9993 respectively, and Q2 value for leave-one-out was 0.9716. In addition, the presented model was used to predict activities of phenolic acids that haven't been tested here experimentally.

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Flephedrone is an analogue of cathinone - chemically similar to ephedrine, cathine and other amphetamines. Conformations of all isomers of flephedrone have been studied at the quantum-chemical level. Calculations have been performed using DFT and MP2 methods with two basis sets - 6-31G and 6-31G(d,p). Results show that there are low energy conformers for the ortho, meta, and para isomers that are connected by way of low-barrier transition states. Boltzmann distribution of population predicts the highest population for the 1-meta conformer with a 10% increase in solution. The molecular electrostatic potential surface data for each molecule has been calculated revealing likely reaction sites.

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A theoretical study was performed using density functional theory (DFT) to investigate hydrogen bonding interactions in signature complexes formed between keto-9H guanine (Gua) and aspartic acid (Asp) at neutral pH. Optimized geometries, binding energies and the theoretical IR spectra of guanine, aspartic acid and their corresponding complexes (Gua-Asp) were calculated using the B3LYP method and the 6-31+G(d) basis set. Stationary points found to be at local minima on the potential energy surface were verified by second derivative harmonic vibrational frequency calculations at the same level of theory. AIM theory was used to analyze the hydrogen bonding characteristics of these DNA base complex systems. Our results show that the binding motif for the most stable complex is strikingly similar to a Watson-Crick motif observed in the guanine-cytosine base pair. We have found a range of hydrogen bonding interactions between guanine and aspartic acid in the six complexes. This was further verified by theoretical IR spectra of ω(C-H--O-H) cm(-1) stretches for the Gua-Asp complexes. The electron density plot indicates strong hydrogen bonding as shown by the 2p(z) dominant HOMO orbital character.

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We present resonant two-photon ionization (R2PI), UV-UV, and IR-UV double resonance spectra of xanthine seeded in a supersonic jet by laser desorption. We show that there is only one tautomer of xanthine which absorbs in the wavelength range of 36 700 to 37 700 cm(-1). The IR-UV double resonance spectrum shows three strong bands at 3444, 3485, and 3501 cm(-1), all of which we assign as N-H stretching vibrations. Comparison of the IR-UV double resonance spectrum with frequencies and intensities obtained from density functional theory (DFT) and second order Møller Plesset (MP2) calculations suggests that the observed xanthine is the diketo N(7)H tautomer.

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The physical nature of interactions within the active site of cytosine-5-methyltransferase (CMT) was studied using a variation-perturbation energy decomposition scheme defining a sequence of approximate intermolecular interaction energy models. These models have been used to analyze the catalytic activity of residues constituting cytosine-5-methyltransferase active site as well their role in the binding group of de novo designed inhibitors. Our results indicate that Glu119, Arg163, and Arg165 appear to play the dominant role in stabilizing the protonated transition state structure and their influence can be qualitatively approximated by electrostatic interactions alone. The stabilization of neutral structures of the alternative reaction pathway is small, which might suggest the protonated pathway as preferred by the enzyme. Exchange and delocalization terms are negligible in most cases, or they cancel each other to some extent. Interactions of inhibitors with the CMT active site are dominated by electrostatic multipole contributions in analogy with previously studied transition state analogue inhibitors of leucyl aminopeptidase.

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