An In Silico Study for Expanding the Utility of Cannabidiol in Alzheimer's Disease Therapeutic Development.

Cannabidiol (CBD), a major non-psychoactive component of the cannabis plant, has shown therapeutic potential in Alzheimer's disease (AD). In this study, we identified potential CBD targets associated with AD using a drug-target binding affinity prediction model and generated CBD analogs using a genetic algorithm combined with a molecular docking system. As a result, we identified six targets associated with AD: Endothelial NOS (ENOS), Myeloperoxidase (MPO), Apolipoprotein E (APOE), Amyloid-beta precursor protein (APP), Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), and Presenilin-1 (PSEN1). Furthermore, we generated CBD analogs for each target that optimize for all desired drug-likeness properties and physicochemical property filters, resulting in improved pIC50 values and docking scores compared to CBD. Molecular dynamics (MD) simulations were applied to analyze each target's CBD and highest-scoring CBD analogs. The MD simulations revealed that the complexes of ENOS, MPO, and ADAM10 with CBD exhibited high conformational stability, and the APP and PSEN1 complexes with CBD analogs demonstrated even higher conformational stability and lower interaction energy compared to APP and PSEN1 complexes with CBD. These findings demonstrated the capable binding of the six identified targets with CBD and the enhanced binding stability achieved with the developed CBD analogs for each target.

Implementing a specialist paediatric clinical pharmacology service in a UK children's hospital.

AIMS: Royal College of Paediatrics and Child Health subspecialist training in Paediatric Clinical Pharmacology and Therapeutics has been delivered in the UK for 20 years, but no specialist clinical services have been set up previously. METHODS: Prospective audit and service evaluation of paediatric clinical pharmacology service pilot phase and dedicated service at a UK children's hospital. RESULTS: Pilot scheme (May-October 2019), then weekly service (established June 2020). Service covers the High Dependency Unit, and inpatients with polypharmacy. The pilot demonstrated high levels of acceptance, with 89% of suggested medication changes agreed by lead clinical team, and success, with 97.5% of suggested changes continued until discharge/pilot completion. Economic analysis estimated direct annualised cost savings on medications of up to £10 000. After 20 ward rounds of the established service, 270 potential medication changes were identified, 213 were carried out (78.9%). The most common were deprescribing (n = 143), prescribing (n = 47) and dose adjustment (n = 8). Seventy-five different medications were deprescribed, most commonly chloral hydrate (n = 12), Lactulose, ibuprofen, Bio-Kult and sodium alginate (all n = 4). The percentage of inpatients prescribed ≥10 medications decreased from 38.5 to 32.1%, while the subset prescribed ≥20 medications decreased from 11.0 to 5.67%. The mean number of medicines prescribed decreased from 9.0 to 8.0, while the median was unchanged at 7. Annual Yellow Card reports of suspected adverse drug reactions more than doubled (n = 66). CONCLUSION: A UK model for subspecialist paediatric clinical pharmacology service delivery has demonstrated a positive clinical impact and could be replicated at other UK secondary/tertiary children's hospitals.

Concentration optimization of combinatorial drugs using Markov chain-based models.

BACKGROUND: Combinatorial drug therapy for complex diseases, such as HSV infection and cancers, has a more significant efficacy than single-drug treatment. However, one key challenge is how to effectively and efficiently determine the optimal concentrations of combinatorial drugs because the number of drug combinations increases exponentially with the types of drugs. RESULTS: In this study, a searching method based on Markov chain is presented to optimize the combinatorial drug concentrations. In this method, the searching process of the optimal drug concentrations is converted into a Markov chain process with state variables representing all possible combinations of discretized drug concentrations. The transition probability matrix is updated by comparing the drug responses of the adjacent states in the network of the Markov chain and the drug concentration optimization is turned to seek the state with maximum value in the stationary distribution vector. Its performance is compared with five stochastic optimization algorithms as benchmark methods by simulation and biological experiments. Both simulation results and experimental data demonstrate that the Markov chain-based approach is more reliable and efficient in seeking global optimum than the benchmark algorithms. Furthermore, the Markov chain-based approach allows parallel implementation of all drug testing experiments, and largely reduces the times in the biological experiments. CONCLUSION: This article provides a versatile method for combinatorial drug screening, which is of great significance for clinical drug combination therapy.

PEGylated AdipoRon derivatives improve glucose and lipid metabolism under insulinopenic and high-fat diet conditions.

The pleiotropic actions of adiponectin in improving cell survival and metabolism have motivated the development of small-molecule therapeutic agents for treating diabetes and lipotoxicity. AdipoRon is a synthetic agonist of the adiponectin receptors, yet is limited by its poor solubility and bioavailability. In this work, we expand on the protective effects of AdipoRon in pancreatic ß-cells and examine how structural modifications could affect the activity, pharmacokinetics, and bioavailability of this small molecule. We describe a series of AdipoRon analogs containing amphiphilic ethylene glycol (PEG) chains. Among these, AdipoRonPEG5 induced pleiotropic effects in mice under insulinopenic and high-fat diet (HFD) conditions. While both AdipoRon and AdipoRonPEG5 substantially attenuate palmitate-induced lipotoxicity in INS-1 cells, only AdipoRonPEG5 treatment is accompanied by a significant reduction in cytotoxic ceramides. In vivo, AdipoRonPEG5 can substantially reduce pancreatic, hepatic, and serum ceramide species, with a concomitant increase in the corresponding sphingoid bases and improves insulin sensitivity of mice under HFD feeding conditions. Furthermore, hyperglycemia in streptozotocin (STZ)-induced insulinopenic adiponectin-null mice is also attenuated upon AdipoRonPEG5 treatment. Our results suggest that AdipoRonPEG5 is more effective in reducing ceramides and dihydroceramides in the liver of HFD-fed mice than AdipoRon, consistent with its potent activity in activating ceramidase in vitro in INS-1 cells. Additionally, these results indicate that the beneficial effects of AdipoRonPEG5 can be partially attributed to improved pharmacokinetics as compared with AdipoRon, thus suggesting that further derivatization may improve affinity and tissue-specific targeting.

C-terminal tails mimicking bioactive intermediates cause different plasma degradation patterns and kinetics in neuropeptides γ-MSH, α-MSH, and neurotensin.

Peptides are attractive drugs because of their specificity and minimal off-target effects. Short half-lives are within their major drawbacks, limiting actual use in clinics. The golden standard in therapeutic peptide development implies identification of a minimal core sequence, then modified to increase stability through several strategies, including the introduction of nonnatural amino acids, cyclization, and lipidation. Here, we investigated plasma degradations of hormone sequences all composed of a minimal active core peptide and a C-terminal extension. We first investigated pro-opimelanocortin (POMC) γ2/γ3-MSH hormone behavior and extended our analysis to POMC-derived α-melanocyte stimulating hormone/adrenocorticotropic hormone signaling neuropeptides and neurotensin. We demonstrated that in all the three cases analyzed in this study, few additional residues mimicking the natural sequence alter both peptide stability and the mechanism(s) of degradation of the minimal conserved functional pattern. Our results suggest that the impact of extensions on the bioactivity of a peptide drug has to be carefully evaluated throughout the optimization process.

The Effectiveness of Inpatient Rehabilitation in Parkinson's Disease: A Systematic Review of Recent Studies.

Background: Parkinson's disease (PD) is a progressive disease, which is associated with the loss of activities of daily living independency. Several rehabilitation options have been studied during the last years, to improve mobility and independency. Objective: This systematic review will focus on inpatient multidisciplinary rehabilitation (MR) in people with Parkinson's disease (PwPD), based on recent studies from 2020 onwards. Methods: Search strategy in three databases included: multidisciplinary rehabilitation, Parkinson's Disease, inpatient rehabilitation, motor-, functional- and cognitive performance, cost-effectiveness, Quality of Life, and medication changes/Levodopa equivalent daily doses. Results: Twenty-two studies were included, consisting of 13 studies dealing with inpatient MR and 9 studies on inpatient non-MR interventions. Inpatient PD multidisciplinary rehabilitation proved to be effective, as well as non-MR rehabilitation. Conclusions: This review confirms the efficacy of inpatient MR and non-MR in PD, but is skeptical about the past and current study designs. New study designs, including new physical training methods, more attention to medication and costs, new biomarkers, artificial intelligence, and the use of wearables, will hopefully change rehabilitation trials in PwPD in the future.

Model-based learn and confirm: designing effective treatment regimens against multidrug resistant Gram-negative pathogens.

Over the last decade, there has been a growing appreciation for the use of in vitro and in vivo infection models to generate robust and informative nonclinical PK/PD data to accelerate the clinical translation of treatment regimens. The objective of this study was to develop a model-based "learn and confirm" approach to help with the design of combination regimens using in vitro infection models to optimise the clinical utility of existing antibiotics. Static concentration time-kill studies were used to evaluate the PD activity of polymyxin B (PMB) and meropenem against two carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates; BAA2146 (PMB-susceptible) and BRKP67 (PMB-resistant). A mechanism-based model (MBM) was developed to quantify the joint activity of PMB and meropenem. In silico simulations were used to predict the time-course of bacterial killing using clinically-relevant PK exposure profiles. The predictive accuracy of the model was further evaluated by validating the model predictions using a one-compartment PK/PD in vitro dynamic infection model (IVDIM). The MBM captured the reduction in bacterial burden and regrowth well in both the BAA2146 and BRKP67 isolate (R2 = 0.900 and 0.940, respectively). The bacterial killing and regrowth predicted by the MBM were consistent with observations in the IVDIM: sustained activity against BAA2146 and complete regrowth of the BRKP67 isolate. Differences observed in PD activity suggest that additional dose optimisation might be beneficial in PMB-resistant isolates. The model-based approach presented here demonstrates the utility of the MBM as a translational tool from static to dynamic in vitro systems to effectively perform model-informed drug optimisation.

Precision medicine and drug optimization in adult inflammatory bowel disease patients.

Inflammatory bowel diseases (IBD) encompass two main entities including ulcerative colitis and Crohn's disease. Although having a common global pathophysiological mechanism, IBD patients are characterized by a significant interindividual heterogeneity and may differ by their disease type, disease locations, disease behaviours, disease manifestations, disease course as well as treatment needs. Indeed, although the therapeutic armamentarium for these diseases has expanded rapidly in recent years, a proportion of patients remains with a suboptimal response to medical treatment due to primary non-response, secondary loss of response or intolerance to currently available drugs. Identifying, prior to treatment initiation, which patients are likely to respond to a specific drug would improve the disease management, avoid unnecessary side effects and reduce the healthcare expenses. Precision medicine classifies individuals into subpopulations according to clinical and molecular characteristics with the objective to tailor preventative and therapeutic interventions to the characteristics of each patient. Interventions would thus be performed only on those who will benefit, sparing side effects and expense for those who will not. This review aims to summarize clinical factors, biomarkers (genetic, transcriptomic, proteomic, metabolic, radiomic or from the microbiota) and tools that could predict disease progression to guide towards a step-up or top-down strategy. Predictive factors of response or non-response to treatment will then be reviewed, followed by a discussion about the optimal dose of drug required for patients. The time at which these treatments should be administered (or rather can be stopped in case of a deep remission or in the aftermath of a surgery) will also be addressed. IBD remain biologically complex, with multifactorial etiopathology, clinical heterogeneity as well as temporal and therapeutic variabilities, which makes precision medicine especially challenging in this area. Although applied for many years in oncology, it remains an unmet medical need in IBD.

Development and optimization of in-situ gel containing chitosan nanoparticles for possible nose-to-brain delivery of vinpocetine.

Vinpocetine (VIN), a derivative of vincamine found in the vinca plant, widens blood vessels in the brain and has been shown to improve cognitive function, memory, and cerebrovascular disorders. Nevertheless, the clinical utility of VIN is constrained by factors such as low oral bioavailability owing to the first-pass metabolism that often demands frequent dosing of 3-4 tablets/day. In this regard, the present work aimed to develop VIN-loaded chitosan nanoparticles (VIN-CH-NPs) to surmount these limitations and in view to enhance delivery to the brain of VIN by minimizing systemic exposure. The chitosan (CH) nanoparticles (NP) were developed by ionotropic gelation technique employing tripolyphosphate (TPP) as a cross-linking agent. Employing Design of Experiments (DoE), the effect of CH and TPP concentrations and stirring speed were systematically optimized using Box Behnken design (BBD). The optimized batch of nanoparticles displayed a particle size, zeta potential, entrapment efficiency, and drug loading of 130.6 ± 8.38 nm, +40.81 ± 0.11 mV, 97.56 ± 0.04 %, and 61 ± 0.89 %, respectively. Fourier Transform Infrared Spectroscopy indicated the chemical integrity of the drug ruling out the interaction between the VIN and excipients used. DSC and PXRD data indicated that reduction of the crystallinity of VIN in the chitosan matrix. These VIN-CH-NPs manifested good stability, exhibiting an almost spherical morphology. To mitigate rapid mucociliary clearance upon intranasal administration, the optimized VIN-CH-NPs were incorporated into thermosensitive in situ gel (VIN-CHN-ISG). It was observed that the in-situ gel loaded with nanoparticles was opalescent with a pH level of 5.3 ± 0.38. It was also noted that the gelation temperature was 32 ± 0.89 °C, and the gelation time was approximately 15 s. The drug delivery to the brain through the nasal application of optimized VIN-NPs in situ gel was assessed in rats. The results indicated significant nasal application of the in-situ gel nearly doubled the Cmax (P < 0.05) and AUC0-t (P < 0.05) in the brain compared to oral administration. Nasal administration improved drug delivery to the brain by reducing systemic exposure to VIN. A histopathological study of the nasal mucosa revealed no irritation or toxicity, making it safe for nasal administration. These findings suggest that the developed NPs in-situ gel effectively targeted vinpocetine to the brain through the nasal pathway, providing a potential therapeutic strategy for managing Alzheimer's disease.

The importance of binding kinetics and drug-target residence time in pharmacology.

A dominant assumption in pharmacology throughout the 20th century has been that in vivo target occupancy-and attendant pharmacodynamics-depends on the systemic concentration of drug relative to the equilibrium dissociation constant for the drug-target complex. In turn, the duration of pharmacodynamics is temporally linked to the systemic pharmacokinetics of the drug. Yet, there are many examples of drugs for which pharmacodynamic effect endures long after the systemic concentration of a drug has waned to (equilibrium) insignificant levels. To reconcile such data, the drug-target residence time model was formulated, positing that it is the lifetime (or residence time) of the binary drug-target complex, and not its equilibrium affinity per se, that determines the extent and duration of drug pharmacodynamics. Here, we review this model, its evolution over time, and its applications to natural ligand-macromolecule biology and synthetic drug-target pharmacology.

An Outer Membrane Vesicle-Based Permeation Assay (OMPA) for Assessing Bacterial Bioavailability.

When searching for new antibiotics against Gram-negative bacterial infections, a better understanding of the permeability across the cell envelope and tools to discriminate high from low bacterial bioavailability compounds are urgently needed. Inspired by the phospholipid vesicle-based permeation assay (PVPA), which is designed to predict non-facilitated permeation across phospholipid membranes, outer membrane vesicles (OMVs) of Escherichia coli either enriched or deficient of porins are employed to coat filter supports for predicting drug uptake across the complex cell envelope. OMVs and the obtained in vitro model are structurally and functionally characterized using cryo-TEM, SEM, CLSM, SAXS, and light scattering techniques. In vitro permeability, obtained from the membrane model for a set of nine antibiotics, correlates with reported in bacterio accumulation data and allows to discriminate high from low accumulating antibiotics. In contrast, the correlation of the same data set generated by liposome-based comparator membranes is poor. This better correlation of the OMV-derived membranes points to the importance of hydrophilic membrane components, such as lipopolysaccharides and porins, since those features are lacking in liposomal comparator membranes. This approach can offer in the future a high throughput screening tool with high predictive capacity or can help to identify compound- and bacteria-specific passive uptake pathways.

Factorial design in the optimization and study 'in combo' of derivatives of imidazo[1,2-a]azines in the COX´s isoforms inhibition.

Background: Imidazo[1,2-a]azines with an acid group decrease inflammatory processes in murine models, and the effect has been attributed to the inhibition of COX enzymes. Results: The optimization of a series of imidazo[1,2-a]azines was performed using the reduced factorial design 23-1. The inhibitory effects of five acid derivatives of imidazo[1,2-a]azines and the standard drugs ibuprofen and indomethacin were evaluated in vitro on COX isoforms. It was observed that the different substituents provided different inhibition profiles, highlighting that the imidazo[1,2-a]pyridines are more active than the bioisosteric imidazo[1,2-a]pyrimidines. These results were analyzed using in silico docking to recognize the structural elements necessary for the inhibition of the targets. The IC50 values for COX1 and COX2 for the various compounds were as follows. COX1: 4a = 2.72 µM, 4b = 3.94 µM, 5a = 7.29µM, 5b = 63.26 µM, 6a = 12.93 µM, indomethacin = 0.13 µM, ibuprofen = 0.2 µM; COX 2: 4a = 1.89 µM, 4b = 2.39 µM, 5a = 8.08 µM, 5b = 41.15 µM, 6a = 5.86 µM, indomethacin = 0.09 µM, ibuprofen = 0.125 µM. Conclusion: Through factorial design it was possible to optimize the inhibitory response on therapeutic targets, obtaining molecule 4a as a result of factorial analysis.

Exploring disordered loops in DprE1 provides a functional site to combat drug-resistance in Mycobacterium strains.

As an anti-tuberculosis target, DprE1 contains two flexible loops (Loop I and Loop II) which have never been exploited for developing DprE1 inhibitors. Here Leu317 in Loop II was discovered as a new functional site to combat drug-resistance in Mycobacterium strains. Based on TCA1, LZDT1 was designed to optimize the hydrophobic interaction with Leu317. A subsequent biochemical and cellular assay displayed increased potency of LZDT1 in inhibiting DprE1 and killing drug-sensitive/-resistant Mycobacterium strains. The improved activity of LZDT1 and its analogue LZDT2 against multidrug resistant tuberculosis was particularly highlighted. For LZDT1, its enhanced interaction with Leu317 also impaired the drug-insensitivity of DprE1 caused by Cys387 mutation. A new nonbenzothiazole lead (LZDT10) with reduced Cys387-dependence was further produced by optimizing interactions with Leu317, improvement directions for LZDT10 were discussed as well. Our research underscores the value of potential functional sites in disordered loops, and affords a feasible way to develop these functional sites into opportunities for drug-resistance management.

Structure‒tissue exposure/selectivity relationship (STR) correlates with clinical efficacy/safety.

Drug optimization, which improves drug potency/specificity by structure‒activity relationship (SAR) and drug-like properties, is rigorously performed to select drug candidates for clinical trials. However, the current drug optimization may overlook the structure‒tissue exposure/selectivity-relationship (STR) in disease-targeted tissues vs. normal tissues, which may mislead the drug candidate selection and impact the balance of clinical efficacy/toxicity. In this study, we investigated the STR in correlation with observed clinical efficacy/toxicity using seven selective estrogen receptor modulators (SERMs) that have similar structures, same molecular target, and similar/different pharmacokinetics. The results showed that drug's plasma exposure was not correlated with drug's exposures in the target tissues (tumor, fat pad, bone, uterus), while tissue exposure/selectivity of SERMs was correlated with clinical efficacy/safety. Slight structure modifications of four SERMs did not change drug's plasma exposure but altered drug's tissue exposure/selectivity. Seven SERMs with high protein binding showed higher accumulation in tumors compared to surrounding normal tissues, which is likely due to tumor EPR effect of protein-bound drugs. These suggest that STR alters drug's tissue exposure/selectivity in disease-targeted tissues vs. normal tissues impacting clinical efficacy/toxicity. Drug optimization needs to balance the SAR and STR in selecting drug candidate for clinical trial to improve success of clinical drug development.

Why 90% of clinical drug development fails and how to improve it?

Ninety percent of clinical drug development fails despite implementation of many successful strategies, which raised the question whether certain aspects in target validation and drug optimization are overlooked? Current drug optimization overly emphasizes potency/specificity using structure‒activity-relationship (SAR) but overlooks tissue exposure/selectivity in disease/normal tissues using structure‒tissue exposure/selectivity-relationship (STR), which may mislead the drug candidate selection and impact the balance of clinical dose/efficacy/toxicity. We propose structure‒tissue exposure/selectivity-activity relationship (STAR) to improve drug optimization, which classifies drug candidates based on drug's potency/selectivity, tissue exposure/selectivity, and required dose for balancing clinical efficacy/toxicity. Class I drugs have high specificity/potency and high tissue exposure/selectivity, which needs low dose to achieve superior clinical efficacy/safety with high success rate. Class II drugs have high specificity/potency and low tissue exposure/selectivity, which requires high dose to achieve clinical efficacy with high toxicity and needs to be cautiously evaluated. Class III drugs have relatively low (adequate) specificity/potency but high tissue exposure/selectivity, which requires low dose to achieve clinical efficacy with manageable toxicity but are often overlooked. Class IV drugs have low specificity/potency and low tissue exposure/selectivity, which achieves inadequate efficacy/safety, and should be terminated early. STAR may improve drug optimization and clinical studies for the success of clinical drug development.

Evolution of the drug-target residence time model.

IntroductionThe pharmacological action of a drug is linked to its affinity for a specific molecular target as quantified by in vitro equilibrium measurements. However, it is clear that for many highly effective drugs, interactions with their molecular targets do not conform to simple, equilibrium conditions in vivo and this results in a temporal discordance between pharmacokinetics and pharmacodynamics. The drug-target residence time model was developed to provide a theoretical framework with which to understand cases in which very slow dissociation of the drug-target complex in vivo results in durable PD effects even after systemic concentrations of drug have waned.Area coveredIn this article, the author provides a brief description of the drug-target residence time model and focuses on the refinements that have been made to the original model to incorporate the influences of compound rebinding in cells and pharmacokinetic properties of drug molecules.Expert opinionThere is now overwhelming evidence for the utility of the drug-target residence time model as a framework for understanding in vivo drug action. The in vitro measured residence time (τR) must be used in concert with equilibrium measures of drug-target affinity (e.g. IC50) and with in vivo measures of pharmacokinetic half-life, to afford the researcher a powerful approach to compound optimization for clinical effect. Despite the significant use and refinement of this model, continued studies are required to better understand the dynamic interplay between residence time, target pathobiology, drug distribution and drug pharmacokinetics.

Simultaneous determination of thermodynamic and kinetic data by isothermal titration calorimetry.

BACKGROUND: Thermodynamic and binding kinetic data increasingly support and guide the drug optimization process. METHODS: Because ITC thermograms contain binding thermodynamic and kinetic information, an efficient protocol for the simultaneous extraction of thermodynamic and kinetic data for 1:1 protein ligand reactions from AFFINImeter kinITC in one single experiment are presented. RESULTS: The effort to apply this protocol requires the same time as for the standard protocol but increases the precision of both thermodynamic and kinetic data. CONCLUSIONS: The protocol enables reliable extraction of both thermodynamic and kinetic data for 1:1 protein-ligand binding reactions with improved precision compared to the 'standard protocol'. GENERAL SIGNIFICANCE: Thermodynamic and kinetic data are recorded under exactly the same conditions in solution without any labeling or immobilization from a protein sample that is not 100% active and would otherwise render the extraction of kinetic parameters impossible.

The HIV drug optimization agenda: promoting standards for earlier investigation and approvals of antiretroviral drugs for use in adolescents living with HIV.

INTRODUCTION: Most clinical trials for new antiretroviral (ARV) agents are conducted among narrowly defined adult populations. Only after safety and efficacy have been clearly demonstrated among adults living with HIV are trials including adolescents, children and infants conducted. This approach contributes to significant delays in the availability of optimal new ARV regimens for infants, children and adolescents. This commentary discusses issues related to the inclusion of adolescents aged 12 to 18 years in initial HIV clinical phase 3 trials of novel antiretrovirals (ARVs) or conducting parallel phase 3 clinical trials among adolescents. DISCUSSION: The absorption, metabolic and excretion or elimination pathways for drugs do not significantly differ between adolescents and adults. In fact, dosing recommendations for ARVs are the same for adults and adolescents who meet the age and weight criteria. Although conducting clinical trials among adolescents present special challenges (e.g. consenting minors and concerns about trial completion and contraception), these challenges can be addressed to obtain high-quality trial results. Importantly, new agents and optimized combinations have more favourable dosing schedules and side-effect profiles and are more effective ARV agents with higher HIV drug resistance thresholds, which would be extremely beneficial to improve outcomes among HIV-positive adolescents. CONCLUSIONS: Adolescents may not present with significantly different pharmacokinetic characteristics from those in adults. Including HIV-positive adolescents in phase 3 ARV clinical trials, either with adults or in specific adolescent studies conducted in parallel, would allow adolescents to access promising, more effective treatment for HIV years earlier than with the current stepwise approach.

Activity of Metal-Azole Complexes Against Biofilms of Candida albicans and Candida glabrata.

BACKGROUND: Onychomycosis is a chronic nail infection caused by fungi frequently resistant to antifungal treatments. Recalcitrance in nail infections is a result of reduced antifungal penetration due to biofilm formation, combined with poor patient compliance with the treatment, which can be as long as 18 months. OBJECTIVE: Metal-drug complexation is a widely used strategy to increase drug efficacy. Therefore, the aim of this work was to evaluate the antifungal and anti-biofilm activity of several metal-azole complexes against Candida albicans and Candida glabrata. METHODS: Susceptibility assays and scanning electron microscopy were performed to determine the anti-biofilm activity of eight metal-azole complexes in vitro and ex-vivo, using human nail fragments. RESULTS: In vitro susceptibility assays showed that complexation of both Au(I) and Zn(II) to clotrimazole and ketoconazole improved the anti-biofilm activity compared to the azole alone. Using an ex-vivo model of biofilm formation on fragments of human nails, we also demonstrate the improved efficacy of metal-azole complexes against biofilms of C. albicans and C. glabrata that resembles the onychomycosis structure. Noteworthy, biofilms of C. glabrata were more susceptible to the optimized complexes than those of C. albicans. CONCLUSION: In conclusion, metal-azole complexes used in this work show promising anti-biofilm activity and further clinical studies should confirm its potential for the treatment of Candida-associated onychomycosis.

LigBuilder V3: A Multi-Target de novo Drug Design Approach.

With the rapid development of systems-based pharmacology and poly-pharmacology, method development for rational design of multi-target drugs has becoming urgent. In this paper, we present the first de novo multi-target drug design program LigBuilder V3, which can be used to design ligands to target multiple receptors, multiple binding sites of one receptor, or various conformations of one receptor. LigBuilder V3 is generally applicable in de novo multi-target drug design and optimization, especially for the design of concise ligands for protein targets with large difference in binding sites. To demonstrate the utility of LigBuilder V3, we have used it to design dual-functional inhibitors targeting HIV protease and HIV reverse transcriptase with three different strategy, including multi-target de novo design, multi-target growing, and multi-target linking. The designed compounds were computational validated by MM/GBSA binding free energy estimation as highly potential multi-target inhibitors for both HIV protease and HIV reverse transcriptase. The LigBuilder V3 program can be downloaded at "http://www.pkumdl.cn/ligbuilder3/".