A neural network potential based on pairwise resolved atomic forces and energies

Molecular simulations have become a key tool in molecular and materials design. Machine learning (ML)-based potential energy functions offer the prospect of simulating complex molecular systems efficiently at quantum chemical accuracy. In previous work, we have introduced the ML-based PairF-Net approach to neural network potentials, that adopts a pairwise interatomic scheme to predicting forces within a molecular system. Here, we further develop the PairF-Net model to intrinsically incorporate energy conservation and couple the model to a molecular mechanical (MM) environment within the OpenMM package. The updated PairF-Net model yields energy and force predictions and dynamical distributions in good agreement with the rMD17 dataset of ten small organic molecules in the gas-phase. We further show that these in vacuo ML models of small molecules can be applied to force predictions in aqueous solution via hybrid ML/MM simulations. We present a new benchmark dataset for these ten molecules in solution, obtained from QM/MM simulations, which we denote as rMD17-aq (https://zenodo.org/records/10048644); and assess the ability of PairF-Net to reproduce the molecular energy, atomic forces and dynamical distributions of these solution conformations via ML/MM simulations.

Molecular dynamics simulations as a guide for modulating small molecule aggregation

Small colloidally aggregating molecules (SCAMs) can be problematic for biological assays in drug discovery campaigns. However, the self-associating properties of SCAMs have potential applications in drug delivery and analytical biochemistry. Consequently, the ability to predict the aggregation propensity of a small organic molecule is of considerable interest. Chemoinformatics-based filters such as ChemAGG and Aggregator Advisor offer rapid assessment but are limited by the assay quality and structural diversity of their training set data. Complementary to these tools, we explore here the ability of molecular dynamics (MD) simulations as a physics-based method capable of predicting the aggregation propensity of diverse chemical structures. For a set of 32 molecules, using simulations of 100 ns in explicit solvent, we find a success rate of 97% (one molecule misclassified) as opposed to 75% by Aggregator Advisor and 72% by ChemAGG. These short timescale MD simulations are representative of longer microsecond trajectories and yield an informative spectrum of aggregation propensities across the set of solutes, capturing the dynamic behaviour of weakly aggregating compounds. Implicit solvent simulations using the generalized Born model were less successful in predicting aggregation propensity. MD simulations were also performed to explore structure-aggregation relationships for selected molecules, identifying chemical modifications that reversed the predicted behaviour of a given aggregator/non-aggregator compound. While lower throughput than rapid cheminformatics-based SCAM filters, MD-based prediction of aggregation has potential to be deployed on the scale of focused subsets of moderate size, and, depending on the target application, provide guidance on removing or optimizing a compound's aggregation propensity.

Brazilin is a natural product inhibitor of the NLRP3 inflammasome

Excessive or aberrant NLRP3 inflammasome activation has been implicated in the progression and initiation of many inflammatory conditions; however, currently no NLRP3 inflammasome inhibitors have been approved for therapeutic use in the clinic. Here we have identified that the natural product brazilin effectively inhibits both priming and activation of the NLRP3 inflammasome in cultured murine macrophages, a human iPSC microglial cell line and in a mouse model of acute peritoneal inflammation. Through computational modeling, we predict that brazilin can adopt a favorable binding pose within a site of the NLRP3 protein which is essential for its conformational activation. Our results not only encourage further evaluation of brazilin as a therapeutic agent for NLRP3-related inflammatory diseases, but also introduce this small-molecule as a promising scaffold structure for the development of derivative NLRP3 inhibitor compounds.

Modeling pyranose ring pucker in carbohydrates using machine learning and semi-empirical quantum chemical methods

Pyranose ring pucker is a key coordinate governing the structure, interactions and reactivity of carbohydrates. We assess the ability of the machine learning potentials, ANI-1ccx and ANI-2x, and the GFN2-xTB semiempirical quantum chemical method, to model ring pucker conformers of five monosaccharides and oxane in the gas phase. Relative to coupled-cluster quantum mechanical calculations, we find that ANI-1ccx most accurately reproduces the ring pucker energy landscape for these molecules, with a correlation coefficient r² of 0.83. This correlation in relative energies lowers to values of 0.70 for ANI-2x and 0.60 for GFN2-xTB. The ANI-1ccx also provides the most accurate estimate of the energetics of the ⁴ C₁ -to-¹ C₄ minimum energy pathway for the six molecules. All three models reproduce chair more accurately than non-chair geometries. Analysis of small model molecules suggests that the ANI-1ccx model favors puckers with equatorial hydrogen bonding substituents; that ANI-2x and GFN2-xTB models overstabilize conformers with axially oriented groups; and that the endo-anomeric effect is overestimated by the machine learning models and underestimated via the GFN2-xTB method. While the pucker conformers considered in this study correspond to a gas phase environment, the accuracy and computational efficiency of the ANI-1ccx approach in modeling ring pucker in vacuo provides a promising basis for future evaluation and application to condensed phase environments.

Probing the effect of NEK7 and cofactor interactions on dynamics of NLRP3 monomer using molecular simulation

The NLRP3 inflammasome is a cytoplasmic complex that regulates the activation of inflammatory cytokines and, given its implication in a range of diseases, is an important therapeutic target. The cofactor ATP and the centrosomal kinase NEK7 are important for NLRP3 activation. Here we have constructed and simulated computational models of full‐length monomeric NLRP3 to shed light on the importance of NEK7 and cofactor interactions for its conformation and dynamics in aqueous solution. We find that molecular dynamics simulation reproduces well the features of the recently published cryo‐EM structure of the ADP‐bound NLRP3–NEK7 complex; on the removal of NEK7, the NLRP3 molecule adopts a more compact closed form during simulations. Replacement of ADP by ATP promotes a rearrangement of hydrogen‐bonding interactions, domain interfaces, and a degree of opening of the NLRP3 conformation. We also examine the dynamics of an acidic loop of the LRR domain of NLRP3, which samples in a region observed in the NEK7‐bound cryo‐EM structure but not in an oligomeric form of inactive NLRP3. During the molecular dynamics simulations of NLRP3, we find some plasticity in its topology that suggests access routes for ATP to the cofactor pocket not immediately evident from the existing NEK7‐bound cryo‐EM structure. These computed dynamical trajectories of NLRP3 provide insight into coordinates of deformation that may be key for cofactor binding and inflammasome activation.

A Selective Review and Virtual Screening Analysis of Natural Product Inhibitors of the NLRP3 Inflammasome

The NLRP3 inflammasome is currently an exciting target for drug discovery due to its role in various inflammatory diseases; however, to date, no NLRP3 inhibitors have reached the clinic. Several studies have used natural products as hit compounds to facilitate the design of novel selective NLRP3 inhibitors. Here, we review selected natural products reported in the literature as NLRP3 inhibitors, with a particular focus on those targeting gout. To complement this survey, we also report a virtual screen of the ZINC20 natural product database, predicting favored chemical features that can aid in the design of novel small molecule NLRP3 inhibitors.

SAR of Novel 3-Arylisoquinolinones: meta-Substitution on the Aryl Ring Dramatically Enhances Antiproliferative Activity through Binding to Microtubules

A set of meta-substituted 3-arylisoquinolinones have been identified that show substantial cytotoxicity in breast, liver, lung and colon cancer cell lines; these are up to 700-fold more active than the corresponding para analogues. These compounds were initially proposed as inhibitors of N-ribosyl dihydronicotinamide (NRH): quinone oxidoreductase 2 (NQO2) but were found to be inactive against the enzyme. Instead, COMPARE analysis suggested that 6-fluoro-3-(meta-fluorophenyl)isoquinolin-1(2H)-one (4) could mimic colchicine and interact with microtubules, a recognized target for cancer therapy. Subsequent docking, molecular dynamics simulations, and free energy analysis further suggested that compound 4 bound well into the colchicine-binding pocket of tubulin. Indeed, 4 suppressed tubulin polymerization, caused G₂/M cell cycle arrest, and induced apoptosis. Also, 4 inhibited the formation of endothelial cell capillary-like tubes and further disrupted the structure of preestablished tubes; the effects were not observed with para analogue 5. In accordance with this, the computed free energy of binding of 5 to tubulin was lower in magnitude than that for 4 and appeared to arise in part from the inability of the para substituent to occupy a tubulin subpocket, which is possible in the meta orientation. In conclusion, the antiproliferative potential of the novel 3-arylisoquinolinones is markedly influenced by a subtle change in the structure (meta versus para). The meta-substituted isoquinolinone 4 is a microtubule-destabilizing agent with potential tumor-selectivity and antiangiogenic and vascular disrupting features.

Direct Deoxydehydration of Cyclic trans-Diol Substrates: An Experimental and Computational Study of the Reaction Mechanism of Vanadium(V)-based Catalysis*

The deoxydehydration of carbohydrates represents a key target to leverage renewable biomass resources chemically. Using a vanadium(V)-based catalyst, it was possible to directly deoxydehydrate cyclic trans-diol substrates. Accompanying mechanistic characterisation of this process by density functional calculations pointed to an energetically tractable route for deoxydehydration of cyclic trans-diol substrates involving stepwise cleavage of the diol C-O bonds via the triplet state; experimentally, this was supported by light dependence of the reaction. Calculations also indicated that cyclic cis-diols and a linear diol substrate could additionally proceed by a concerted singlet DODH mechanism. This work potentially opens a new and cost-effective way to efficiently convert carbohydrates of trans-diol stereochemistry into alkenes.

Generation of Phenothiazine with Potent Anti-TLK1 Activity for Prostate Cancer Therapy

Through in vitro kinase assays and docking studies, we report the synthesis and biological evaluation of a phenothiazine analog J54 with potent TLK1 inhibitory activity for prostate cancer (PCa) therapy. Most PCa deaths result from progressive failure in standard androgen deprivation therapy (ADT), leading to metastatic castration-resistant PCa. Treatments that can suppress the conversion to mCRPC have high potential to be rapidly implemented in the clinics. ADT results in increased expression of TLK1B, a key kinase upstream of NEK1 and ATR and mediating the DNA damage response that typically results in temporary cell-cycle arrest of androgen-responsive PCa cells, whereas its abrogation leads to apoptosis. We studied J54 as a potent inhibitor of this axis and as a mediator of apoptosis in vitro and in LNCaP xenografts, which has potential for clinical investigation in combination with ADT. J54 has low affinity for the dopamine receptor in modeling and competition studies and weak detrimental behavioral effects in mice and C. elegans.

How Do Small Molecule Aggregates Inhibit Enzyme Activity? A Molecular Dynamics Study

Small molecule compounds which form colloidal aggregates in solution are problematic in early drug discovery; adsorption of the target protein by these aggregates can lead to false positives in inhibition assays. In this work, we probe the molecular basis of this inhibitory mechanism using molecular dynamics simulations. Specifically, we examine in aqueous solution the adsorption of the enzymes β-lactamase and PTP1B onto aggregates of the drug miconazole. In accordance with experiment, molecular dynamics simulations observe formation of miconazole aggregates as well as subsequent association of these aggregates with β-lactamase and PTP1B. When complexed with aggregate, the proteins do not exhibit significant alteration in protein tertiary structure or dynamics on the microsecond time scale of the simulations, but they do indicate persistent occlusion of the protein active site by miconazole molecules. MD simulations further suggest this occlusion can occur via surficial interactions of protein with miconazole but also potentially by envelopment of the protein by miconazole. The heterogeneous polarity of the miconazole aggregate surface seems to underpin its activity as an invasive and nonspecific inhibitory agent. A deeper understanding of these protein/aggregate systems has implications not only for drug design but also for their exploitation as tools in drug delivery and analytical biochemistry.

What Next for Quantum Mechanics in Structure-Based Drug Discovery?

There is significant potential for electronic structure methods to improve the quality of the predictions furnished by the tools of computer-aided drug design, which typically rely on empirically derived functions. In this perspective, we consider some recent examples of how quantum mechanics has been applied in predicting protein-ligand geometries, protein-ligand binding affinities and ligand strain on binding. We then outline several significant developments in quantum mechanics methodology likely to influence these approaches: in particular, we note the advent of more computationally expedient ab initio quantum mechanical methods that can provide chemical accuracy for larger molecular systems than hitherto possible. We highlight the emergence of increasingly accurate semiempirical quantum mechanical methods and the associated role of machine learning and molecular databases in their development. Indeed, the convergence of improved algorithms for solving and analyzing electronic structure, modern machine learning methods, and increasingly comprehensive benchmark data sets of molecular geometries and energies provides a context in which the potential of quantum mechanics will be increasingly realized in driving future developments and applications in structure-based drug discovery.

Discovery of potent 4-aminoquinoline hydrazone inhibitors of NRH:quinoneoxidoreductase-2 (NQO2)

(NRH):quinone oxidoreductase 2 (NQO2) is associated with various processes involved in cancer initiation and progression probably via the production of ROS during quinone metabolism. Thus, there is a need to develop inhibitors of NQO2 that are active in vitro and in vivo. As part of a strategy to achieve this we have used the 4-aminoquinoline backbone as a starting point and synthesized 21 novel analogues. The syntheses utilised p-anisidine with Meldrum's acid and trimethyl orthoacetate or trimethyl orthobenzoate to give the 4-hydrazin-quinoline scaffold, which was derivatised with aldehydes or acid chlorides to give hydrazone or hydrazide analogues, respectively. The hydrazones were the most potent inhibitors of NQO2 in cell free systems, some with low nano-molar IC50 values. Structure-activity analysis highlighted the importance of a small substituent at the 2-position of the 4-aminoquinoline ring, to reduce steric hindrance and improve engagement of the scaffold within the NQO2 active site. Cytotoxicity and NQO2-inhibitory activity in vitro was evaluated using ovarian cancer SKOV-3 and TOV-112 cells (expressing high and low levels of NQO2, respectively). Generally, the hydrazones were more toxic than hydrazide analogues and further, toxicity is unrelated to cellular NQO2 activity. Pharmacological inhibition of NQO2 in cells was measured using the toxicity of CB1954 as a surrogate end-point. Both the hydrazone and hydrazide derivatives are functionally active as inhibitors of NQO2 in the cells, but at different inhibitory potency levels. In particular, 4-((2-(6-methoxy-2-methylquinolin-4-yl)hydrazono)methyl)phenol has the greatest potency of any compound yet evaluated (53 nM), which is 50-fold lower than its toxicity IC50. This compound and some of its analogues could serve as useful pharmacological probes to determine the functional role of NQO2 in cancer development and response to therapy.

Ring Puckering Landscapes of Glycosaminoglycan-Related Monosaccharides from Molecular Dynamics Simulations

The conformational flexibility of the glycosaminoglycans (GAGs) is known to be key in their binding and biological function, for example in regulating coagulation and cell growth. In this work, we employ enhanced sampling molecular dynamics simulations to probe the ring conformations of GAG-related monosaccharides, including a range of acetylated and sulfated GAG residues. We first perform unbiased MD simulations of glucose anomers and the epimers glucuronate and iduronate. These calculations indicate that in some cases, an excess of 15 μs is required for adequate sampling of ring pucker due to the high energy barriers between states. However, by applying our recently developed msesMD simulation method (multidimensional swarm-enhanced sampling molecular dynamics), we were able to quantitatively and rapidly reproduce these ring pucker landscapes. From msesMD simulations, the puckering free energy profiles were then compared for 15 further monosaccharides related to GAGs; this includes to our knowledge the first simulation study of sulfation effects on β-GalNAc ring puckering. For the force field employed, we find that in general the calculated pucker free energy profiles for sulfated sugars were similar to the corresponding unsulfated profiles. This accords with recent experimental studies suggesting that variation in ring pucker of sulfated GAG residues is primarily dictated by interactions with surrounding residues rather than by intrinsic conformational preference. As an exception to this, however, we predict that 4-O-sulfation of β-GalNAc leads to reduced ring rigidity, with a significant lowering in energy of the ¹C₄ ring conformation; this observation may have implications for understanding the structural basis of the biological function of β-GalNAc-containing glycosaminoglycans such as dermatan sulfate.

Tracing the GSAP-APP C-99 Interaction Site in the β-Amyloid Pathway Leading to Alzheimer's Disease

Gamma secretase activating protein (GSAP) present in β-amyloid pathway orchestrates the formation of β-amyloid plaques by γ-secretase activation and is an emerging therapeutic target for the treatment of Alzheimer's disease. It forms a ternary complex with γ-secretase and APP C-99. However, there are limited reports for the interaction of APP C-99 with GSAP. Here, we report the characterization of purified maltose binding protein (MBP) tagged human GSAP and its interaction with synthetic APP C-99 peptide fragments (⁷¹²IATVIVITLVMLKKQ⁷²⁷ (⁷¹²IQ⁷²⁷), ⁷¹⁹TLVMLKKKQYTSIHHGVVEVDAAVT⁷⁴³ (⁷¹⁹TT⁷⁴³) ⁷³⁴GVVEVDAAVTPEERHLSKMQQNGY⁷⁵⁷ (⁷³⁴GY⁷⁵⁷), and ⁷⁴⁶ERHLSKMQQNGYENPTYKFFEQMQN⁷⁷⁰ (⁷⁴⁶EN⁷⁷⁰)). The results emphasize the selective interaction of peptide (⁷¹⁹TT⁷⁴³) with MBP-GSAP with a dissociation constant of 0.136 μM. Further, computational modeling of the GSAP-⁷¹⁹TT⁷⁴³ complex finds an optimal bound pose of ⁷¹⁹TT⁷⁴³ within an extended groove on the surface of GSAP. The preliminary results highlight the interaction between the two major proteins in the plausible ternary complex: APP C-99-GSAP-γ-secretase. It paves a futuristic path to investigate the GSAP-APP C-99 binding in detail and accentuates the role of GSAP in the β-amyloid pathway.

Evaluation of analogues of furan-amidines as inhibitors of NQO2

Inhibitors of the enzyme NQO2 (NRH: quinone oxidoreductase 2) are of potential use in cancer chemotherapy and malaria. We have previously reported that non-symmetrical furan amidines are potent inhibitors of NQO2 and here novel analogues are evaluated. The furan ring has been changed to other heterocycles (imidazole, N-methylimidazole, oxazole, thiophene) and the amidine group has been replaced with imidate, reversed amidine, N-arylamide and amidoxime to probe NQO2 activity, improve solubility and decrease basicity of the lead furan amidine. All compounds were fully characterised spectroscopically and the structure of the unexpected product N-hydroxy-4-(5-methyl-4-phenylfuran-2-yl)benzamidine was established by X-ray crystallography. The analogues were evaluated for inhibition of NQO2, which showed lower activity than the lead furan amidine. The observed structure-activity relationship for the furan-amidine series with NQO2 was rationalized by preliminary molecular docking and binding mode analysis. In addition, the oxazole-amidine analogue inhibited the growth of Plasmodium falciparum with an IC50 value of 0.3 μM.

Identification of Rare Lewis Oligosaccharide Conformers in Aqueous Solution Using Enhanced Sampling Molecular Dynamics

Determining the conformations accessible to carbohydrate ligands in aqueous solution is important for understanding their biological action. In this work, we evaluate the conformational free-energy surfaces of Lewis oligosaccharides in explicit aqueous solvent using a multidimensional variant of the swarm-enhanced sampling molecular dynamics (msesMD) method; we compare with multi-microsecond unbiased MD simulations, umbrella sampling, and accelerated MD approaches. For the sialyl Lewis A tetrasaccharide, msesMD simulations in aqueous solution predict conformer landscapes in general agreement with the other biased methods and with triplicate unbiased 10 μs trajectories; these simulations find a predominance of closed conformer and a range of low-occupancy open forms. The msesMD simulations also suggest closed-to-open transitions in the tetrasaccharide are facilitated by changes in ring puckering of its GlcNAc residue away from the ⁴C₁ form, in line with previous work. For sialyl Lewis X tetrasaccharide, msesMD simulations predict a minor population of an open form in solution corresponding to a rare lectin-bound pose observed crystallographically. Overall, from comparison with biased MD calculations, we find that triplicate 10 μs unbiased MD simulations may not be enough to fully sample glycan conformations in aqueous solution. However, the computational efficiency and intuitive approach of the msesMD method suggest potential for its application in glycomics as a tool for analysis of oligosaccharide conformation.

Comparative Molecular Dynamics Simulation of Aggregating and Non-Aggregating Inhibitor Solutions: Understanding the Molecular Basis of Promiscuity

The presence of false positives in enzyme inhibition assays is a common problem in early drug discovery, especially for compounds that form colloid aggregates in solution. The molecular basis of these aggregates could not be thoroughly explored because of their transient stability. In this study we conducted comparative molecular dynamics (MD) simulations of miconazole, a strong aggregator, and fluconazole, a known non-aggregator. Interestingly, miconazole displays full aggregation within only 50 ns, whilst fluconazole shows no aggregation over the 500 ns simulation. The simulations indicate that the center of the aggregate is densely packed by the hydrophobic groups of miconazole, whereas polar and nonpolar groups comprise the surface to form a micelle-like colloid. The amphiphilic moment and planar nature of the miconazole structure appear to promote its aggregating behavior. The simulations also predict rapid aggregate formation for a second known promiscuous inhibitor, nicardipine. Thus, MD appears to be a useful tool to characterize aggregate-prone inhibitors at molecular-level detail and has the potential to provide useful information for drug discovery and formulation design.

Non-enzymatic recombination of RNA: Ligation in loops

BACKGROUND

While the RNA world hypothesis is widely accepted, it is still far from complete: the existence of self-replicating ribozyme, consisting of potentially hundreds of nucleotides, is a core assumption for the majority of RNA world models. The appearance of such long RNA molecules under prebiotic conditions is not self-evident. Recombination seems to be a plausible way of creating RNA diversity, resulting in the appearance of functional RNAs, capable of self-replicating.

METHODS

We report here on the study of recombination process modelled with two 96 nts RNA fragments. Detection of recombination products was performed with RT-PCR followed by TA-cloning and Sanger sequencing.

RESULTS

A wide range of recombinant products was detected. We found that (i) the most efficient ligation was observed for RNA species forming bulges or internal loops, with ligation partners located within the loop; (ii) a strong preference was observed for formation of a few types of major products with a large variety of minor products; (iii) ligation could occur with participation of either 2',3'-cyclophosphate or 5'-ppp; (iv) the presence of key reaction components, i.e. 5'ppp-RNAs, enabled the formation of additional types of product; (v) molecular dynamics simulations of one of the most abundant products suggests that the ligation results in a preferable formation of 2'-5'- rather than 3'-5'-linkages.

CONCLUSIONS

The study demonstrates regularities of new RNA molecules formation with non-enzymatic recombination process.

GENERAL SIGNIFICANCE

Our findings provide new data supporting the RNA World hypothesis and show the way of new RNA sequences emergence under prebiotic conditions.

miRNases: Novel peptide-oligonucleotide bioconjugates that silence miR-21 in lymphosarcoma cells

MicroRNAs (miRNAs) are active regulators in malignant growth and constitute potential targets for anticancer therapy. Consequently, considerable effort has focused on identifying effective ways to modulate aberrant miRNA expression. Here we introduce and assess a novel type of chemically engineered biomaterial capable of cleaving specific miRNA sequences, i.e. miRNA-specific artificial ribonucleases (hereafter 'miRNase'). The miRNase template presented here consists of the catalytic peptide Acetyl-[(LeuArg)₂Gly]₂ covalently attached to a miRNA-targeting oligonucleotide, which can be linear or hairpin. The peptide C-terminus is conjugated to an aminohexyl linker located at either the 3'- or 5'-end of the oligonucleotide. The cleavage efficacy, structural aspects of cleavage and biological relevance of a set of these designed miRNases was assayed with respect to highly oncogenic miR-21. Several miRNases demonstrated effective site-selective cleavage of miR-21 exclusively at G-X bonds. One of the most efficient miRNase was shown to specifically inhibit miR-21 in lymphosarcoma cells and lead to a reduction in their proliferative activity. This report provides the first experimental evidence that metallo-independent peptide-oligonucleotide chemical ribonucleases are able to effectively and selectively down-regulate oncogenic miRNA in tumour cells, thus suggesting their potential in development of novel therapeutics aimed at overcoming overexpression of disease-related miRNAs.

Approximate quantum chemical methods for modelling carbohydrate conformation and aromatic interactions: β-cyclodextrin and its adsorption on a single-layer graphene sheet

Adsorption of carbohydrates on graphene has the potential to improve graphene dispersibility in water. Here we assess the ability of DFTB-based and NDDO-based quantum chemical methods to model β-cyclodextrin conformations and interactions with graphene.

Non-symmetrical furan-amidines as novel leads for the treatment of cancer and malaria

NRH:quinone oxidoreductase 2 enzyme (NQO2) is a potential therapeutic target in cancer and neurodegenerative diseases, with roles in either chemoprevention or chemotherapy. Here we report the design, synthesis and evaluation of non-symmetrical furan-amidines and their analogues as novel selective NQO2 inhibitors with reduced adverse off-target effects, such as binding to DNA. A pathway for the synthesis of the non-symmetrical furan-amidines was established from the corresponding 1,4-diketones. The synthesized non-symmetrical furan-amidines and their analogues showed potent NQO2 inhibition activity with nano-molar IC50 values. The most active compounds were non-symmetrical furan-amidines with meta- and para-nitro substitution on the aromatic ring, with IC50 values of 15 nM. In contrast to the symmetric furan-amidines, which showed potent intercalation in the minor grooves of DNA, the synthesized non-symmetrical furan-amidines showed no affinity towards DNA, as demonstrated by DNA melting temperature experiments. In addition, Plasmodium parasites, which possess their own quinone oxidoreductase PfNDH2, were inhibited by the non-symmetrical furan-amidines, the most active possessing a para-fluoro substituent (IC50 9.6 nM). The high NQO2 inhibition activity and nanomolar antimalarial effect of some of these analogues suggest the lead compounds are worthy of further development and optimization as potential drugs for novel anti-cancer and antimalarial strategies.

High Precision Determination of the β Decay Q(EC) Value of (11)C and Implications on the Tests of the Standard Model

We report the determination of the Q(EC) value of the mirror transition of (11)C by measuring the atomic masses of (11)C and (11)B using Penning trap mass spectrometry. More than an order of magnitude improvement in precision is achieved as compared to the 2012 Atomic Mass Evaluation (Ame2012) [Chin. Phys. C 36, 1603 (2012)]. This leads to a factor of 3 improvement in the calculated Ft value. Using the new value, Q(EC)=1981.690(61)  keV, the uncertainty on Ft is no longer dominated by the uncertainty on the Q(EC) value. Based on this measurement, we provide an updated estimate of the Gamow-Teller to Fermi mixing ratio and standard model values of the correlation coefficients.

Improved Hydrogen Bonding at the NDDO-Type Semiempirical Quantum Mechanical/Molecular Mechanical Interface

A semiempirical quantum mechanical (QM)/molecular mechanical (MM) potential with reformulated QM core-MM charge interactions is introduced, specifically to more accurately model hydrogen bonding at the QM/MM interface. Application of this potential using the PM3 Hamiltonian shows improved prediction of geometry and interaction energy for hydrogen bonded small molecule complexes typical of biomolecular interactions, without significantly impacting the modeling of other interaction types. Using this potential, more quantitative prediction of interaction energies is also found at a protein-ligand interface.

Metabolic fate of 3α,5-cycloandrostanes in the endogenous lactonization pathway of Aspergillus tamarii KITA

A series of 3α,5-cycloandrostane analogues with a range of functionality (6α and 6β alcohols and ketone) at carbon 6 were tested in the endogenous lactonization pathway in Aspergillus tamarii KITA. This metabolic route converts progesterone to testololactone in high yield through a four step enzymatic pathway. To date, no studies have looked at the effect of steroids devoid of polar functionality at carbon 3 and their subsequent metabolic fate by fungi which contain Baeyer-Villiger monooxygenases. Incubation of all of the cycloandrostane analogues resulted in lactonization of ring-D irrespective of C-6 stereochemistry or absence of C-3 functionality. Presence of 6β-hydroxy group and the C-17 ketone was required in order for these analogues to undergo hydroxylation at C-15β position. All metabolites were isolated by column chromatography and were identified by (1)H, (13)C NMR, DEPT analysis and other spectroscopic data.

Free Energy Calculations using a Swarm-Enhanced Sampling Molecular Dynamics Approach

Free energy simulations are an established computational tool in modelling chemical change in the condensed phase. However, sampling of kinetically distinct substates remains a challenge to these approaches. As a route to addressing this, we link the methods of thermodynamic integration (TI) and swarm-enhanced sampling molecular dynamics (sesMD), where simulation replicas interact cooperatively to aid transitions over energy barriers. We illustrate the approach by using alchemical alkane transformations in solution, comparing them with the multiple independent trajectory TI (IT-TI) method. Free energy changes for transitions computed by using IT-TI grew increasingly inaccurate as the intramolecular barrier was heightened. By contrast, swarm-enhanced sampling TI (sesTI) calculations showed clear improvements in sampling efficiency, leading to more accurate computed free energy differences, even in the case of the highest barrier height. The sesTI approach, therefore, has potential in addressing chemical change in systems where conformations exist in slow exchange.

Analysis of Enoyl-Acyl Carrier Protein Reductase Structure and Interactions Yields an Efficient Virtual Screening Approach and Suggests a Potential Allosteric Site

Enoyl-acyl carrier protein reductases have an important role in fatty acid biosynthesis and are considered essential for bacterial and protozoal survival. Here, we perform a computational assessment of enoyl-acyl carrier protein reductase structures, providing insights for inhibitor design that we incorporate into a virtual screening approach. Firstly, we analyse 80 crystal structures of 16 different enoyl-acyl carrier protein reductases for their active site characteristics and druggability, finding these sites contain a readily druggable pocket, of varying size and shape. Interestingly, a high affinity, potentially allosteric site was identified for pfFabl. Analysis of the ligand-protein interactions of four enoyl-acyl carrier protein reductases from different micro-organisms (InhA, pfFabl, saFabl and ecFabl), involving 59 available crystal structures, found three commonly shared interactions; constraining these interactions in docking improved enrichment of enoyl-acyl carrier protein reductase virtual screens, by up to 60% in the top 3% of the ranked library. This docking protocol also improved pose prediction, decreasing the root-mean-square deviation to crystallographic pose by up to 75% on average. The binding site analysis and knowledge-based docking protocol presented here can potentially assist in the structure-based design of new enoyl-acyl carrier protein reductase inhibitors.

Protein tyrosine phosphatases: Ligand interaction analysis and optimisation of virtual screening

Docking-based virtual screening is an established component of structure-based drug discovery. Nevertheless, scoring and ranking of computationally docked ligand libraries still suffer from many false positives. Identifying optimal docking parameters for a target protein prior to virtual screening can improve experimental hit rates. Here, we examine protocols for virtual screening against the important but challenging class of drug target, protein tyrosine phosphatases. In this study, common interaction features were identified from analysis of protein-ligand binding geometries of more than 50 complexed phosphatase crystal structures. It was found that two interactions were consistently formed across all phosphatase inhibitors: (1) a polar contact with the conserved arginine residue, and (2) at least one interaction with the P-loop backbone amide. In order to investigate the significance of these features on phosphatase-ligand binding, a series of seeded virtual screening experiments were conducted on three phosphatase enzymes, PTP1B, Cdc25b and IF2. It was observed that when the conserved arginine and P-loop amide interactions were used as pharmacophoric constraints during docking, enrichment of the virtual screen significantly increased in the three studied phosphatases, by up to a factor of two in some cases. Additionally, the use of such pharmacophoric constraints considerably improved the ability of docking to predict the inhibitor's bound pose, decreasing RMSD to the crystallographic geometry by 43% on average. Constrained docking improved enrichment of screens against both open and closed conformations of PTP1B. Incorporation of an ordered water molecule in PTP1B screening was also found to generally improve enrichment. The knowledge-based computational strategies explored here can potentially inform structure-based design of new phosphatase inhibitors using docking-based virtual screening.

Conformational dynamics of dry lamellar crystals of sugar based lipids: an atomistic simulation study

The rational design of a glycolipid application (e.g. drug delivery) with a tailored property depends on the detailed understanding of its structure and dynamics. Because of the complexity of sugar stereochemistry, we have undertaken a simulation study on the conformational dynamics of a set of synthetic glycosides with different sugar groups and chain design, namely dodecyl β-maltoside, dodecyl β-cellobioside, dodecyl β-isomaltoside and a C12C10 branched β-maltoside under anhydrous conditions. We examined the chain structure in detail, including the chain packing, gauche/trans conformations and chain tilting. In addition, we also investigated the rotational dynamics of the headgroup and alkyl chains. Monoalkylated glycosides possess a small amount of gauche conformers (∼20%) in the hydrophobic region of the lamellar crystal (LC) phase. In contrast, the branched chain glycolipid in the fluid Lα phase has a high gauche population of up to ∼40%. Rotational diffusion analysis reveals that the carbons closest to the headgroup have the highest correlation times. Furthermore, its value depends on sugar type, where the rotational dynamics of an isomaltose was found to be 11-15% and more restrained near the sugar, possibly due to the chain disorder and partial inter-digitation compared to the other monoalkylated lipids. Intriguingly, the present simulation demonstrates the chain from the branched glycolipid bilayer has the ability to enter into the hydrophilic region. This interesting feature of the anhydrous glycolipid bilayer simulation appears to arise from a combination of lipid crowding and the amphoteric nature of the sugar headgroups.

Effect of sequence and stereochemistry reversal on p53 peptide mimicry

Peptidomimetics effective in modulating protein-protein interactions and resistant to proteolysis have potential in therapeutic applications. An appealing yet underperforming peptidomimetic strategy is to employ D-amino acids and reversed sequences to mimic a lead peptide conformation, either separately or as the combined retro-inverso peptide. In this work, we examine the conformations of inverse, reverse and retro-inverso peptides of p53(15-29) using implicit solvent molecular dynamics simulation and circular dichroism spectroscopy. In order to obtain converged ensembles for the peptides, we find enhanced sampling is required via the replica exchange molecular dynamics method. From these replica exchange simulations, the D-peptide analogues of p53(15-29) result in a predominantly left-handed helical conformation. When the parent sequence is reversed sequence as either the L-peptide and D-peptide, these peptides display a greater helical propensity, feature reflected by NMR and CD studies in TFE/water solvent. The simulations also indicate that, while approximately similar orientations of the side-chains are possible by the peptide analogues, their ability to mimic the parent peptide is severely compromised by backbone orientation (for D-amino acids) and side-chain orientation (for reversed sequences). A retro-inverso peptide is disadvantaged as a mimic in both aspects, and further chemical modification is required to enable this concept to be used fruitfully in peptidomimetic design. The replica exchange molecular simulation approach adopted here, with its ability to provide detailed conformational insights into modified peptides, has potential as a tool to guide structure-based design of new improved peptidomimetics.

Insights into the activity and specificity of Trypanosoma cruzi trans-sialidase from molecular dynamics simulations

Trypanosoma cruzitrans-sialidase (TcTS), which catalyzes the transfer or hydrolysis of terminal sialic acid residues, is crucial to the development and proliferation of the T. cruzi parasite and thus has emerged as a potential drug target for the treatment of Chagas disease. We here probe the origin of the observed preference for the transfer reaction over hydrolysis where the substrate for TcTS is the natural sialyl donor (represented in this work by sialyllactose). Thus, acceptor lactose preferentially attacks the sialyl-enyzme intermediate rather than water. We compare this with the weaker preference for such transfer shown by a synthetic donor substrate, 4-methylumbelliferyl α-d-acetylneuraminide. For this reason, we conducted molecular dynamics simulations of TcTS following its sialylation by the substrate to examine the behavior of the asialyl leaving group by the protein. These simulations indicate that, where lactose is released, this leaving group samples well-defined interactions in the acceptor site, some of which are mediated by localized water molecules; also, the extent of the opening of the acceptor site to solvent is reduced as compared with those of unliganded forms of TcTS. However, where there is release of 4-methylumbelliferone, this leaving group explores a range of transient poses; surrounding active site water is also more disordered. The acceptor site explores more open conformations, similar to the case in which the 4-methylumbelliferone is absent. Thus, the predicted solvent accessibility of sialylated TcTS is increased when 4-methylumbelliferyl α-d-acetylneuraminide is the substrate compared to sialyllactose; this in turn is likely to contribute to a greater propensity for hydrolysis of the covalent intermediate. These computational simulations, which suggest that protein flexibility has a role in the transferase/sialidase activity of TcTS, have the potential to aid in the design of anti-Chagas inhibitors effective against this neglected tropical disease.

Accounting for non-optimal interactions in molecular recognition: a study of ion-π complexes using a QM/MM model with a dipole-polarisable MM region

For a quantitative understanding of molecular structure, interaction and dynamics, accurate modelling of the energetics of both near-equilibrium and less optimal contacts is important. In this work, we explore the potential energy surfaces of representative ion-π complexes. We examine the performance of a semi-empirical QM/MM approach and the corresponding QM/MMpol model, where inducible point dipoles are additionally employed in the MM region. The predicted potential energy surfaces of cation-benzene complexes are improved by inclusion of explicit MM polarisation of the π-molecule. For cation-formamide complexes, inducible dipoles appreciably improve energetic estimates at geometries forming non-optimal interactions. Energetic component analysis suggests that the implicit MM polarisation of the fixed charge QM/MM model mirrors the behaviour of the QM/MMpol dipole model for the energetics of near-equilibrium conformations. However, for complexes at less optimal orientations, the QM/MM model exhibits higher errors than the QM/MMpol approach, being unable to capture orientation-dependent variations in polarisation energy.

Application of shape-based and pharmacophore-based in silico screens for identification of Type II protein kinase inhibitors

The identification of new, potent and selective inhibitors of important protein kinase targets is a major goal of drug discovery. Here we analyze the crystal structures of 55 protein kinase complexes with Type II inhibitors and find they adopt a conserved twisted V-shape, with an angle of 121 ± 8° and twist of 78 ± 8°. The tightly conserved twist appears important in ensuring ligands curve around the protein backbone and towards the deep pocket. From this, we develop predictive pharmacophore- and shape-based screens to identify Type II inhibitors from a database which also contains Type I inhibitors as decoys. Both approaches exhibit a good level of discrimination for Type II molecules. The most effective pharmacophore model requires six features and three excluded volume regions. Shape-based screening using ROCS generally performs at least as well as pharmacophore approaches. There is only a moderate dependence of shape-based or pharmacophore-based screens on the underlying conformer generator (MOE, Macromodel, Omega and SPE), as well as on ligand linkage chemistry (amide and urea). Finally, we apply our approach to retrieval of Type II inhibitors from a modified version of the DUD database, containing over 104,000 compounds. We observe good enrichment, providing further evidence that the in silico screens developed here will constitute useful guides for identification of small molecule inhibitors targetting protein kinases in their inactive conformational state.

Molecular dynamics simulations of Aβ fibril interactions with β-sheet breaker peptides

Accumulation and aggregation of the 42-residue amyloid-β (Aβ) protein fragment, which originates from the cleavage of amyloid precursor protein by β and γ secretase, correlates with the pathology of Alzheimer's disease (AD). Possible therapies for AD include peptides based on the Aβ sequence, and recently identified small molecular weight compounds designed to mimic these, that interfere with the aggregation of Aβ and prevent its toxic effects on neuronal cells in culture. Here, we use molecular dynamics simulations to compare the mode of interaction of an active (LPFFD) and inactive (LHFFD) β-sheet breaker peptide with an Aβ fibril structure from solid-state NMR studies. We found that LHFFD had a weaker interaction with the fibril than the active peptide, LPFFD, from geometric and energetic considerations, as estimated by the MM/PBSA approach. Cluster analysis and computational alanine scanning identified important ligand-fibril contacts, including a possible difference in the effect of histidine on ligand-fibril π-stacking interactions, and the role of the proline residue in establishing contacts that compete with those essential for maintenance of the inter-monomer β-sheet structure of the fibril. Our results show that molecular dynamics simulations can be a useful way to classify the stability of docking sites. These mechanistic insights into the ability of LPFFD to reverse aggregation of toxic Aβ will guide the redesign of lead compounds, and aid in developing realistic therapies for AD and other diseases of protein aggregation.

Tryptophan as a molecular shovel in the glycosyl transfer activity of Trypanosoma cruzi trans-sialidase

Molecular dynamics investigations into active site plasticity of Trypanosoma cruzi trans-sialidase, a protein implicated in Chagas disease, suggest that movement of the Trp(312) loop plays an important role in the enzyme's sialic acid transfer mechanism. The observed Trp(312) flexibility equates to a molecular shovel action, which leads to the expulsion of the donor aglycone leaving group from the catalytic site. These computational simulations provide detailed structural insights into sialyl transfer by the trans-sialidase and may aid the design of inhibitors effective against this neglected tropical disease.

Ab Initio Protein Folding Using a Cooperative Swarm of Molecular Dynamics Trajectories

The use of atomistic simulation techniques to directly resolve the protein tertiary structure from the primary amino acid sequence is hindered by the rough topology of the protein free energy surface and the resulting simulation time scales required. We explore here the use of a molecular dynamics technique based on swarm intelligence to identify the native states of two peptides and a Trp-cage miniprotein. In all cases, the presence of cooperative swarm interactions significantly enhanced the efficiency of molecular dynamics simulations in predicting the native conformation.

Src family kinase inhibitor Saracatinib (AZD0530) impairs oxaliplatin uptake in colorectal cancer cells and blocks organic cation transporters

Elevated Src family kinase (SFK) activity is associated with tumor invasion and metastasis. The SFK inhibitor saracatinib (AZD0530) is currently in phase II trials in patients including those with colorectal cancer (CRC), where links between SFK activity and poor prognosis are particularly striking. Saracatinib is likely to be used clinically in combination regimens, specifically with 5-fluorouracil (5-FU) and oxaliplatin, in CRC. The aim of this study was to determine the effect of saracatinib on oxaliplatin and 5-FU efficacy in CRC cells. Saracatinib did not modulate 5-FU efficacy but antagonized oxaliplatin in a schedule-specific manner through reduced oxaliplatin uptake via an SFK-independent mechanism. Saracatinib resembles the pharmacophore of known organic cation transporter (OCT) inhibitors and reduced oxaliplatin efficacy maximally in cells overexpressing OCT2. These data suggest that oxaliplatin uptake in CRC is attenuated by saracatinib via inhibition of OCT2, a potential consideration for the clinical development of this SFK inhibitor.