The role of long-range intermolecular interactions in discovery of new drugs

Screening for Potential Antiviral Compounds from Cyanobacterial Secondary Metabolites Using Machine Learning

The secondary metabolites of seawater and freshwater blue-green algae are a rich natural product pool containing diverse compounds with various functions, including antiviral compounds; however, high-efficiency methods to screen such compounds are lacking. Advanced virtual screening techniques can significantly reduce the time and cost of novel antiviral drug identification. In this study, we used a cyanobacterial secondary metabolite library as an example and trained three models to identify compounds with potential antiviral activity using a machine learning method based on message-passing neural networks. Using this method, 364 potential antiviral compounds were screened from >2000 cyanobacterial secondary metabolites, with amides predominating (area under the receiver operating characteristic curve value: 0.98). To verify the actual effectiveness of the candidate antiviral compounds, HIV virus reverse transcriptase (HIV-1 RT) was selected as a target to evaluate their antiviral potential. Molecular docking experiments demonstrated that candidate compounds, including kororamide, mollamide E, nostopeptolide A3, anachelin-H, and kasumigamide, produced relatively robust non-covalent bonding interactions with the RNase H active site on HIV-1 RT, supporting the effectiveness of the proposed screening model. Our data demonstrate that artificial intelligence-based screening methods are effective tools for mining potential antiviral compounds, which can facilitate the exploration of various natural product libraries.

SARS-CoV-2 PLpro Inhibition: Evaluating in Silico Repurposed Fidaxomicin's Antiviral Activity Through In Vitro Assessment

The emergence of drug-resistant viruses and novel strains necessitates the rapid development of novel antiviral therapies. This need was particularly demanding during the COVID-19 pandemic. While de novo drug development is a time-consuming process, repurposing existing approved medications offers a more expedient approach. In our prior in silico screening of the DrugBank database, fidaxomicin emerged as a potential SARS-CoV-2 papain-like protease inhibitor. This study extends those findings by investigating fidaxomicin's antiviral properties in vitro. Our results support further exploration of fidaxomicin as a therapeutic candidate against SARS-CoV-2, given its promising in vitro antiviral activity and favorable safety profile.

Prediction of Protein Targets in Ovarian Cancer Using a Ru-Complex and Carbon Dot Drug Delivery Therapeutic Nanosystems: A Bioinformatics and µ-FTIR Spectroscopy Approach

We predicted the protein therapeutic targets specific to a Ru-based potential drug and its combination with pristine and N-doped carbon dot drug delivery systems, denoted as RuCN/CDs and RuCN/N-CDs. Synchrotron-based FTIR microspectroscopy (µFTIR) in addition to bioinformatics data on drug structures and protein sequences were applied to assess changes in the protein secondary structure of A2780 cancer cells. µFTIR revealed the moieties of the target proteins' secondary structure changes only after the treatment with RuCN and RuCN/N-CDs. A higher content of α-helices and a lower content of β-sheets appeared in A2780 cells after RuCN treatment. Treatment with RuCN/N-CDs caused a substantial increase in parallel β-sheet numbers, random coil content, and tyrosine residue numbers. The results obtained suggest that the mitochondrion-related proteins NDUFA1 and NDUFB5 are affected by RuCN either via overexpression or stabilisation of helical structures. RuCN/N-CDs either induce overexpression of the β-sheet-rich protein NDUFS1 and affect its random coil structure or interact and stabilise its structure via hydrogen bonding between -NH2 groups from N-CDs with protein C=O groups and -OH groups of serine, threonine, and tyrosine residues. The N-CD nanocarrier tunes this drug's action by directing it toward a specific protein target, changing this drug's coordination ability and inducing changes in the protein's secondary structures and function.

In Silico Exploration of CD200 as a Therapeutic Target for COVID-19

SARS-CoV-2, the pathogen causing COVID-19, continues to pose a significant threat to public health and has had major economic implications. Developing safe and effective vaccines and therapies offers a path forward for overcoming the COVID-19 pandemic. The presented study, performed by using the informational spectrum method (ISM), representing an electronic biology-based tool for analysis of protein-protein interactions, identified the highly conserved region of spike protein (SP) from SARS-CoV-2 virus, which is essential for recognition and targeting between the virus and its protein interactors on the target cells. This domain is suggested as a promising target for the drug therapy and vaccines, which could be effective against all currently circulating variants of SARS-CoV-2 viruses. The analysis of the virus/host interaction, performed by the ISM, also revealed OX-2 membrane glycoprotein (CD200) as a possible interactor of SP, which could serve as a novel therapeutic target for COVID-19 disease.

Analyzing energetics and dynamics of hepatitis C virus polymerase interactions with marine bacterial compounds: a computational study

Hepatitis C Virus (HCV) is a significant health concern affecting a large portion of the global population and is a major cause of acute liver diseases, including cirrhosis. The variability in the HCV genome mainly results from the rapid replication facilitated by the NS5B polymerase, making it a prime target for anti-HCV drug development. This study explores potential compounds from marine bacteria that could inhibit the HCV NS5B polymerase by virtual screening, analyzing the energetics, and dynamic behavior of target-compound complexes. Virtual screening with the Lipinski filter was employed to select compounds from the marine bacteria database that demonstrated strong binding affinity to NS5B. The top four (CMNPD27216, CMNPD21066, CMNPD21065, and CMNPD27283) compounds, ranked by their re-docking scores, underwent additional evaluation. Molecular dynamics simulations for 200 ns were conducted to assess the dynamic stability of these complexes in a solvent environment. Furthermore, methods such as MM-GBSA, PCA, and free energy landscape analysis were used to analyze the system's energetics and identify stable conformations by locating transition states. The findings suggest that these compounds exhibit promising binding capabilities to HCV polymerase and could be considered for future experimental validation.

Exploring the Antiviral Potential of Natural Compounds against Influenza: A Combined Computational and Experimental Approach

The influenza A virus nonstructural protein 1 (NS1), which is crucial for viral replication and immune evasion, has been identified as a significant drug target with substantial potential to contribute to the fight against influenza. The emergence of drug-resistant influenza A virus strains highlights the urgent need for novel therapeutics. This study proposes a combined theoretical criterion for the virtual screening of molecular libraries to identify candidate NS1 inhibitors. By applying the criterion to the ZINC Natural Product database, followed by ligand-based virtual screening and molecular docking, we proposed the most promising candidate as a potential NS1 inhibitor. Subsequently, the selected natural compound was experimentally evaluated, revealing measurable virus replication inhibition activity in cell culture. This approach offers a promising avenue for developing novel anti-influenza agents targeting the NS1 protein.

Computational Modeling and Characterization of Peptides Derived from Nanobody Complementary-Determining Region 2 (CDR2) Targeting Active-State Conformation of the β2-Adrenergic Receptor (β2AR)

This study assessed the suitability of the complementarity-determining region 2 (CDR2) of the nanobody (Nb) as a template for the derivation of nanobody-derived peptides (NDPs) targeting active-state β2-adrenergic receptor (β2AR) conformation. Sequences of conformationally selective Nbs favoring the agonist-occupied β2AR were initially analyzed by the informational spectrum method (ISM). The derived NDPs in complex with β2AR were subjected to protein-peptide docking, molecular dynamics (MD) simulations, and metadynamics-based free-energy binding calculations. Computational analyses identified a 25-amino-acid-long CDR2-NDP of Nb71, designated P4, which exhibited the following binding free-energy for the formation of the β2AR:P4 complex (ΔG = -6.8 ± 0.8 kcal/mol or a Ki = 16.5 μM at 310 K) and mapped the β2AR:P4 amino acid interaction network. In vitro characterization showed that P4 (i) can cross the plasma membrane, (ii) reduces the maximum isoproterenol-induced cAMP level by approximately 40% and the isoproterenol potency by up to 20-fold at micromolar concentration, (iii) has a very low affinity to interact with unstimulated β2AR in the cAMP assay, and (iv) cannot reduce the efficacy and potency of the isoproterenol-mediated β2AR/β-arrestin-2 interaction in the BRET2-based recruitment assay. In summary, the CDR2-NDP, P4, binds preferentially to agonist-activated β2AR and disrupts Gαs-mediated signaling.

Marine Brown Algae-Derived Compounds as Potential Inhibitors of Japanese Encephalitis Virus RNA-Dependent RNA Polymerase

The Japanese encephalitis virus (JEV) is a mosquito-borne flavivirus that primarily affects people in Asia and seriously threatens public health. Considering the rising occurrence rates and lack of targeted antiviral treatments, it is essential to comprehend and tackle obstacles related to JEV in order to lessen its influence on world health. This investigation explores compounds derived from marine brown algae (Phaeophyceae) as potential inhibitors of JEV RNA-dependent RNA polymerase (RdRp), a critical enzyme in the virus's replication cycle. Employing the computational virtual screen approach, four compounds, i.e., CMNPD16749, CMNPD2606, CMNPD27817, and CMNPD23662, with favorable binding energies ranging from -15.7 Kcal/mol to -13.9 kcal/mol were identified. Subsequently, through molecular docking analysis, the interactions responsible for the binding stability between the target protein and hit molecules compared to the reference molecule Galidesvir were studied. Further, through extensive molecular dynamic (MD) simulation studies at 200 ns, it was confirmed that each docked complex showed acceptable dynamic stability compared to the reference molecule. These findings were further validated using MM/PBSA free binding energy calculations, PCA analysis and free energy landscape construction. These computational findings suggested that the brown algae-derived compounds may act as an antiviral drug against JEV infection and lay a crucial foundation for future experimental studies against JEV.

Docking and other computing tools in drug design against SARS-CoV-2

The use of computer simulation methods has become an indispensable component in identifying drugs against the SARS-CoV-2 coronavirus. There is a huge body of literature on application of molecular modelling to predict inhibitors against target proteins of SARS-CoV-2. To keep our review clear and readable, we limited ourselves primarily to works that use computational methods to find inhibitors and test the predicted compounds experimentally either in target protein assays or in cell culture with live SARS-CoV-2. Some works containing results of experimental discovery of corresponding inhibitors without using computer modelling are included as examples of a success. Also, some computational works without experimental confirmations are also included if they attract our attention either by simulation methods or by databases used. This review collects studies that use various molecular modelling methods: docking, molecular dynamics, quantum mechanics, machine learning, and others. Most of these studies are based on docking, and other methods are used mainly for post-processing to select the best compounds among those found through docking. Simulation methods are presented concisely, information is also provided on databases of organic compounds that can be useful for virtual screening, and the review itself is structured in accordance with coronavirus target proteins.

Patterns of human and porcine gammaherpesvirus-encoded BILF1 receptor endocytosis

BACKGROUND

The viral G-protein-coupled receptor (vGPCR) BILF1 encoded by the Epstein-Barr virus (EBV) is an oncogene and immunoevasin and can downregulate MHC-I molecules at the surface of infected cells. MHC-I downregulation, which presumably occurs through co-internalization with EBV-BILF1, is preserved among BILF1 receptors, including the three BILF1 orthologs encoded by porcine lymphotropic herpesviruses (PLHV BILFs). This study aimed to understand the detailed mechanisms of BILF1 receptor constitutive internalization, to explore the translational potential of PLHV BILFs compared with EBV-BILF1.

METHODS

A novel real-time fluorescence resonance energy transfer (FRET)-based internalization assay combined with dominant-negative variants of dynamin-1 (Dyn K44A) and the chemical clathrin inhibitor Pitstop2 in HEK-293A cells was used to study the effect of specific endocytic proteins on BILF1 internalization. Bioluminescence resonance energy transfer (BRET)-saturation analysis was used to study BILF1 receptor interaction with β-arrestin2 and Rab7. In addition, a bioinformatics approach informational spectrum method (ISM) was used to investigate the interaction affinity of BILF1 receptors with β-arrestin2, AP-2, and caveolin-1.

RESULTS

We identified dynamin-dependent, clathrin-mediated constitutive endocytosis for all BILF1 receptors. The observed interaction affinity between BILF1 receptors and caveolin-1 and the decreased internalization in the presence of a dominant-negative variant of caveolin-1 (Cav S80E) indicated the involvement of caveolin-1 in BILF1 trafficking. Furthermore, after BILF1 internalization from the plasma membrane, both the recycling and degradation pathways are proposed for BILF1 receptors.

CONCLUSIONS

The similarity in the internalization mechanisms observed for EBV-BILF1 and PLHV1-2 BILF1 provide a foundation for further studies exploring a possible translational potential for PLHVs, as proposed previously, and provides new information about receptor trafficking.

In Silico and In Vitro Inhibition of SARS-CoV-2 PLpro with Gramicidin D

Finding an effective drug to prevent or treat COVID-19 is of utmost importance in tcurrent pandemic. Since developing a new treatment takes a significant amount of time, drug repurposing can be an effective option for achieving a rapid response. This study used a combined in silico virtual screening protocol for candidate SARS-CoV-2 PL^pro inhibitors. The Drugbank database was searched first, using the Informational Spectrum Method for Small Molecules, followed by molecular docking. Gramicidin D was selected as a peptide drug, showing the best in silico interaction profile with PL^pro. After the expression and purification of PL^pro, gramicidin D was screened for protease inhibition in vitro and was found to be active against PL^pro. The current study's findings are significant because it is critical to identify COVID-19 therapies that are efficient, affordable, and have a favorable safety profile.

Structural and Molecular Packing study of Three New Amidophosphoric Acid Esters and Assessment of Their Inhibiting Activity Against SARS-CoV-2 by Molecular Docking

Three new compounds of amidophosphoric acid esters with a [OCH2C(CH3)2CH2O]P(O)[X] segment (where X=cyclopentylamido (1), 2-aminopyridinyl (2) and pyrrolidinyl (3)) were synthesized and studied using FT-IR and 31P/13C/1H NMR spectroscopies and single-crystal X-ray diffraction analysis. The compounds crystallize in the triclinic space groups P 1 ‾ for 1 and 3 and in the orthorhombic space group Pca21 for 2, where the asymmetric unit consists of three symmetrically-independent molecules for 1 and one molecule for 2 and 3. The intermolecular interactions and supramolecular assemblies are assessed by Hirshfeld surface analysis and enrichment ratios. The results reveal that the substituent effect plays an important role in directing the supramolecular structures. The presence of the aromatic substituent aminopyridine in 2 providing the C-H…π interactions leads to a larger variety in interactions including H…H, H…O/O…H, H…C/C…H and H…N/N…H contacts, whereas the packings of the compounds 1 and 3 bearing aliphatic substituents only include H…H and H…O/O…H contacts. The enrichment ratios affirm the importance of O…H/H…O contacts reflecting the hydrogen bond N-H…O interactions to be the enriched contacts. Compounds 1-3 were also investigated along with five similar reported structures with a [OCH2C(CH3)2CH2O]P(O) segment for their inhibitory behavior against SARS-CoV-2. The molecular docking results illustrate that the presence of the aromatic amido substituent versus the aliphatic type provides a more favorable condition for their biological activities.

In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer's Disease

Alzheimer's disease (AD), a devastating neurodegenerative disease, is the focus of pharmacological research. One of the targets that attract the most attention for the potential therapy of AD is the serotonin 5HT6 receptor, which is the receptor situated exclusively in CNS on glutamatergic and GABAergic neurons. The neurochemical impact of this receptor supports the hypothesis about its role in cognitive, learning, and memory systems, which are of critical importance for AD. Natural products are a promising source of novel bioactive compounds with potential therapeutic potential as a 5HT6 receptor antagonist in the treatment of AD dementia. The ZINC-natural product database was in silico screened in order to find the candidate antagonists of 5-HT6 receptor against AD. A virtual screening protocol that includes both short-and long-range interactions between interacting molecules was employed. First, the EIIP/AQVN filter was applied for in silico screening of the ZINC database followed by 3D QSAR and molecular docking. Ten best candidate compounds were selected from the ZINC Natural Product database as potential 5HT6 Receptor antagonists and were proposed for further evaluation. The best candidate was evaluated by molecular dynamics simulations and free energy calculations.

Experimental evidence for long-distance electrodynamic intermolecular forces

Both classical and quantum electrodynamics predict the existence of dipole-dipole long-range electrodynamic intermolecular forces; however, these have never been hitherto experimentally observed. The discovery of completely new and unanticipated forces acting between biomolecules could have considerable impact on our understanding of the dynamics and functioning of the molecular machines at work in living organisms. Here, using two independent experiments, on the basis of different physical effects detected by fluorescence correlation spectroscopy and terahertz spectroscopy, respectively, we demonstrate experimentally the activation of resonant electrodynamic intermolecular forces. This is an unprecedented experimental proof of principle of a physical phenomenon that, having been observed for biomacromolecules and with long-range action (up to 1000 Å), could be of importance for biology. In addition to thermal fluctuations that drive molecular motion randomly, these resonant (and thus selective) electrodynamic forces may contribute to molecular encounters in the crowded cellular space.

In vitro anti-influenza activity of in silico repurposed candidate drug cycrimine

BACKGROUND

Due to the limitations of current antiviral therapies because of drug resistance and the emergence of new circulating viral strains, novel effective antivirals are urgently needed. Results of the previous drug repurposing by virtual screening of DrugBank revealed the anticholinergic drug cycrimine as a possible inhibitor of the influenza virus infection.

METHODS

In this study we examined the potential antiviral activity of cycrimine in vitro.

RESULTS

The experimental results showed the anti-influenza activity of cycrimine against two different influenza A subtypes in cell culture.

CONCLUSIONS

The findings of this study suggest cycrimine as a potential therapeutic agent for influenza.

Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)

This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the β₂-adrenergic receptor (β₂-AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of β₂-AR were analysed using the informational spectrum method (ISM) and β₂-AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the β₂-AR:P3 complex of ΔG = (-7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) μM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated β₂-AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC₅₀ of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of β₂-AR with β-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated β₂-AR.

Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors

Influenza A virus (IAV) matrix protein 2 (M2), an ion channel, is crucial for virus infection, and therefore, an important anti-influenza drug target. Adamantanes, also known as M2 channel blockers, are one of the two classes of Food and Drug Administration-approved anti-influenza drugs, although their use was discontinued due to prevalent drug resistance. Fast emergence of resistance to current anti-influenza drugs have raised an urgent need for developing new anti-influenza drugs against resistant forms of circulating viruses. Here we propose a simple theoretical criterion for fast virtual screening of molecular libraries for candidate anti-influenza ion channel inhibitors both for wild type and adamantane-resistant influenza A viruses. After in silico screening of drug space using the EIIP/AQVN filter and further filtering of drugs by ligand based virtual screening and molecular docking we propose the best candidate drugs as potential dual inhibitors of wild type and adamantane-resistant influenza A viruses. Finally, guanethidine, the best ranked drug selected from ligand-based virtual screening, was experimentally tested. The experimental results show measurable anti-influenza activity of guanethidine in cell culture.

Influence of argon and D2 tagging on the hydrogen bond network in Cs+(H2O)3; kinetic trapping below 40 K

Tuning cluster ion conformations between 12 and 21 K.

Identification of Candidate Allosteric Modulators of the M1 Muscarinic Acetylcholine Receptor Which May Improve Vagus Nerve Stimulation in Chronic Tinnitus

Chronic tinnitus is characterized by neuroplastic changes of the auditory cortex. A promising method for therapy of chronic tinnitus is vagus nerve stimulation (VNS) combined with auditory stimulation. The principle of VNS is reversal of pathological neuroplastic changes of the auditory cortex toward physiological neural activity and synchronicity. The VNS mechanism of action in chronic tinnitus patients is prevailingly through the muscarinic neuromodulation of the auditory cortex by the activation of nc. basalis Meynerti. The aim of this study is to propose potential pharmaceutics which may improve the neuromodulatory effects of VNS. The working hypothesis is that M1 receptors have a dominant role in the neural plasticity of the auditory cortex. We propose that allosteric agonists of the muscarinic receptor type 1 (M1) receptor could improve specificity and selectivity of the neuromodulatory effect of VNS on the auditory cortex of chronic tinnitus patients even in the circumstances of lower acetylcholine brain concentration. This intervention would also reinforce the re-learning process of tinnitus (sub)networks by acting on cholinergic memory and learning mechanisms. We performed in silico screening of drug space using the EIIP/AQVN filter and selected 50 drugs as candidates for allosteric modulators of muscarinic receptors. Further filtering of these compounds by means of 3D QSAR and docking revealed 3 approved drugs-bromazepam, estazolam and flumazenil as the most promising candidates for combined chronic tinnitus therapy. These drugs should be further evaluated by biological tests and clinical trials.

A simple method for calculation of basic molecular properties of nutrients and their use as a criterion for a healthy diet

Background: Healthy nutrition is vital for good health and well-being. Despite the important role of a healthy nutritional diet, recommendations for healthy eating remain elusive and are mainly based on general properties of nutrients. The present study proposes an improved characterization of the molecular characteristics of nutrients, which are important for biological functions and can be useful in describing a healthy diet. Methods: We investigated the electronic properties of some known nutrient ingredients. In this analysis, we used the average quasi valence number (AQVN) and the electron-ion interaction potential (EIIP), which are molecular descriptors that represent the basic electronic properties of organic molecules.   Results: Our results show that most nutrients can be represented by specific groups of organic compounds according to their basic electronic properties, and these differ from the vast majority of known chemicals. Based on this finding, we have proposed a simple criterion for the selection of food components for healthy nutrition. Discussion: Further studies on the electronic properties of nutrients could serve as a basis for better understanding of their biological functions.

Arginase Flavonoid Anti-Leishmanial in Silico Inhibitors Flagged against Anti-Targets

Arginase, a drug target for the treatment of leishmaniasis, is involved in the biosynthesis of polyamines. Flavonoids are interesting natural compounds found in many foods and some of them may inhibit this enzyme. The MetIDB database containing 5667 compounds was screened using an EIIP/AQVN filter and 3D QSAR to find the most promising candidate compounds. In addition, these top hits were screened in silico versus human arginase and an anti-target battery consisting of cytochromes P450 2a6, 2c9, 3a4, sulfotransferase, and the pregnane-X-receptor in order to flag their possible interactions with these proteins involved in the metabolism of substances. The resulting compounds may have promise to be further developed for the treatment of leishmaniasis.

In silico Therapeutics for Neurogenic Hypertension and Vasovagal Syncope

Neurocardiovascular diseases (NCVD) are the leading cause of death in the developed world and will remain so till 2020. In these diseases the pathologically changed nervous control of cardiovascular system has the central role. The actual NCV syndromes are neurogenic hypertension, representing the sympathetically mediated disorder, and vasovagal syncope, which is the vagally mediated disorders. Vasovagal syncope, the disease far from its etiological treatment, could benefit from recruiting and application of antimuscarinic drugs used in other parasympathetic disorders. The informational spectrum method (ISM), a method widely applied for the characterization of protein-protein interactions in the field of immunology, endocrinology and anti HIV drug discovery, was applied for the first time in the analysis of neurogenic hypertension and vasovagal syncope therapeutic targets. In silico analysis revealed the potential involvement of apelin in neurogenic hypertension. Applying the EIIP/ISM bioinformatics concept in investigation of drugs for treatment of vasovagal syncope suggests that 78% of tested antimuscarinic drugs could have anti vasovagal syncope effect. The presented results confirm that ISM is a promissing method for investigation of molecular mechanisms underlying pathophysiological proceses of NCV syndromes and discovery of therapeutics targets for their treatment.

In silico analysis suggests repurposing of ibuprofen for prevention and treatment of EBOLA virus disease

The large 2014/2015 Ebola virus outbreak in West Africa points out the urgent need to develop new preventive and therapeutic approaches that are effective against Ebola viruses and  can be rapidly utilized. Recently, a simple theoretical criterion for the virtual screening of molecular libraries for candidate inhibitors of Ebola virus infection was proposed. Using this method the ‘drug space’ was screened and 267 approved and 382 experimental drugs as candidates for treatment of the Ebola virus disease (EVD) have been selected. Detailed analysis of these drugs revealed the non-steroidal anti-inflammatory drug ibuprofen as an inexpensive, widely accessible and minimally toxic candidate for prevention and treatment of EVD. Furthermore, the molecular mechanism underlying this possible protective effect of ibuprofen against EVD is suggested in this article.

Virtual screen for repurposing approved and experimental drugs for candidate inhibitors of EBOLA virus infection

The ongoing Ebola virus epidemic has presented numerous challenges with respect to control and treatment because there are no approved drugs or vaccines for the Ebola virus disease (EVD). Herein is proposed simple theoretical criterion for fast virtual screening of molecular libraries for candidate inhibitors of Ebola virus infection. We performed a repurposing screen of 6438 drugs from DrugBank using this criterion and selected 267 approved and 382 experimental drugs as candidates for treatment of EVD including 15 anti-malarial drugs and 32 antibiotics. An open source Web server allowing screening of molecular libraries for candidate drugs for treatment of EVD was also established.

Two-dimensional asynchronous spectrum with auxiliary cross peaks in probing intermolecular interactions

A new approach called “asynchronous spectrum with auxiliary peaks (ASAP)” is proposed for generating a 2D asynchronous spectrum to investigate the intermolecular interaction between two solutes (P and Q) dissolved in the same solution.

New in silico and conventional in vitro approaches to advance HIV drug discovery and design

INTRODUCTION

Recently, the new concept of the long-range intermolecular interactions in biological systems has been proposed. Combined use of molecular modeling techniques and the screening techniques based on the long-range interaction concept could significantly improve and accelerate discovery of new HIV drugs. However, any hit identified in silico needs to be characterized with respect to its biological target by enzymatic studies. Combined use of the in silico screening and the enzymatic studies allows an efficient selection of new anti-HIV drugs.

AREAS COVERED

The focus of this article is on the in silico screening of molecular libraries for candidate new HIV drugs, which is based on the molecular descriptors determining the long-range interaction between the drugs and their therapeutic target. This article also reviews the techniques for enzyme kinetic studies which are required for optimization of in silico selected candidate anti-HIV drugs.

EXPERT OPINION

The novel approach of combining in silico screening techniques with enzymatic studies enables the accurate measurement of the quantitative descriptors of ligand-enzyme interactions. This novel method is a powerful tool for new anti-HIV drug discovery which can also reduce the drug development costs.