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Abstract The dissociation rate, or its reciprocal, the residence time (τ), is a crucial parameter for understanding the duration and biological impact of biomolecular interactions. Accurate prediction of τ is essential for understanding protein-protein interactions (PPIs) and identifying potential drug targets or modulators for tackling diseases. Conventional molecular dynamics simulation techniques are inherently constrained by their limited timescales, making it challenging to estimate residence times, which typically range from minutes to hours. Building upon its successful application in protein-small molecule systems, τ-Random Acceleration Molecular Dynamics (τRAMD) is here investigated for estimating dissociation rates of protein-protein complexes. τRAMD enables the observation of unbinding events on the nanosecond timescale, facilitating rapid and efficient computation of relative residence times. We tested this methodology for three protein-protein complexes and their extensive mutant datasets, achieving good agreement between computed and experimental data. By combining τRAMD with MD-IFP (Interaction Fingerprint) analysis, dissociation mechanisms were characterized and their sensitivity to mutations investigated, enabling the identification of molecular hotspots for selective modulation of dissociation kinetics. In conclusion, our findings underscore the versatility of τRAMD as a simple and computationally efficient approach for computing relative protein-protein dissociation rates and investigating dissociation mechanisms, thereby aiding the design of PPI modulators.

Krabbe disease is a sphingolipidosis characterized by the genetic deficiency of the acid hydrolase β-galactosylceramidase (GALC). Most of the studies concerning the biological role of GALC performed on Krabbe patients and Galc-deficient twitcher mice (an authentic animal model of the disease) indicate that the pathogenesis of this disorder is the consequence of the accumulation of the neurotoxic GALC substrate β-galactosylsphingosine (psychosine), ignoring the possibility that this enzyme may exert a wider biological impact. Indeed, limited information is available about the effect of GALC downregulation on the cell lipidome in adult and developing organisms. The teleost zebrafish (Danio rerio) has emerged as a useful platform to model human genetic diseases, including sphingolipidoses, and two GALC co-orthologs have been identified in zebrafish (galca and galcb). Here, we investigated the effect of the competitive and irreversible GALC inhibitor β-galactose-cyclophellitol (GCP) on the lipid profile of zebrafish embryos. Molecular modelling indicates that GCP can be sequestered in the catalytic site of the enzyme and covalently binds human GALC, and the zebrafish Galca and Galcb proteins in a similar manner. Accordingly, GCP inhibits the β-galactosylceramide hydrolase activity of zebrafish in vitro and in vivo, leading to significant alterations of the lipidome of zebrafish embryos. These results indicate that the lack of GALC activity deeply affects the lipidome during the early stages of embryonic development, and thereby provide insights into the pathogenesis of Krabbe disease.

Abstract Background Neural stem cell (NSC) proliferation and differentiation in the mammalian brain decreases to minimal levels postnatally. Nevertheless, neurogenic niches persist in the adult cortex and hippocampus in rodents, primates and humans, with adult NSC differentiation sharing key regulatory mechanisms with development. Adult neurogenesis impairments have been linked to Alzheimer’s disease (AD) pathology. Addressing these impairments by using neurotrophic factors is a promising new avenue for therapeutic intervention based on neurogenesis. However, this possibility has been hindered by technical difficulties of using in-vivo models to conduct screens, including working with scarce NSCs in the adult brain and differences between human and mouse models or ethical limitations. Methods Here, we use a combination of mouse and human stem cell models for comprehensive in-vitro characterization of a novel neurogenic compound, focusing on the brain-derived neurotrophic factor (BDNF) pathway. The ability of ENT-A011, a steroidal dehydroepiandrosterone derivative, to activate the tyrosine receptor kinase B (TrkB) receptor was tested through western blotting in NIH-3T3 cells and its neurogenic and neuroprotective action were assessed through proliferation, cell death and Amyloid-β (Aβ) toxicity assays in mouse primary adult hippocampal NSCs, mouse embryonic cortical NSCs and neural progenitor cells (NPCs) differentiated from three human induced pluripotent stem cell lines from healthy and AD donors. RNA-seq profiling was used to assess if the compound acts through the same gene network as BDNF in human NPCs. Results ENT-A011 was able to increase proliferation of mouse primary adult hippocampal NSCs and embryonic cortical NSCs, in the absence of EGF/FGF, while reducing Aβ-induced cell death, acting selectively through TrkB activation. The compound was able to increase astrocytic gene markers involved in NSC maintenance, protect hippocampal neurons from Αβ toxicity and prevent synapse loss after Aβ treatment. ENT-A011 successfully induces proliferation and prevents cell death after Aβ toxicity in human NPCs, acting through a core gene network shared with BDNF as shown through RNA-seq. Conclusions Our work characterizes a novel BDNF mimetic with preferable pharmacological properties and neurogenic and neuroprotective actions in Alzheimer’s disease via stem cell-based screening, demonstrating the promise of stem cell systems for short-listing competitive candidates for further testing.

Abstract The propensity of poorly water-soluble drugs to aggregate at supersaturation impedes their bioavailability. Supersaturated amorphous drug-salt-polymer systems provide an emergent approach to this problem. However, the effects of polymers on drug-drug interactions in aqueous phase are largely unexplored and it is unclear how to choose an optimal salt-polymer combination for a particular drug. Here, we describe a comparative experimental and computational characterization of amorphous solid dispersions containing the drug celecoxib, and a polymer, polyvinylpyrrolidone vinyl acetate (PVP-VA) or hydroxypropyl methylcellulose acetate succinate, with or without Na+/K+ salts. Classical models for drug-polymer interactions fail to identify the best drug-salt-polymer combination. In contrast, more stable drug-polymer interaction energies computed from molecular dynamics simulations correlate with prolonged stability of supersaturated amorphous drug-salt-polymer systems, along with better dissolution and pharmacokinetic profiles. The celecoxib-salt-PVP-VA formulations exhibit excellent biopharmaceutical performance, offering the prospect of a low-dosage regimen for this widely used anti-inflammatory, thereby increasing cost-effectiveness, and reducing side-effects.

Abstract Mitochondrial fatty acid synthesis (mtFAS) is essential for respiratory function. MtFAS generates the octanoic acid precursor for lipoic acid synthesis, but the role of longer fatty acid products has remained unclear. The structurally well-characterized component of mtFAS, human 2E-enoyl-ACP reductase (MECR) rescues respiratory growth and lipoylation defects of a Saccharomyces cerevisiae Δetr1 strain lacking native mtFAS enoyl reductase. To address the role of longer products of mtFAS, we employed in silico molecular simulations to design a MECR variant with a shortened substrate binding cavity. Our in vitro and in vivo analyses indicate that the MECR G165Q variant allows synthesis of octanoyl groups but not long chain fatty acids, confirming the validity of our computational approach to engineer substrate length specificity. Furthermore, our data imply that restoring lipoylation in mtFAS deficient yeast strains is not sufficient to support respiration and that long chain acyl-ACPs generated by mtFAS are required for mitochondrial function.

Abstract Background With the expansion of animal production, parasitic helminths are gaining increasing economic importance. However, application of several established deworming agents can harm treated hosts and environment due to their low specificity. Furthermore, the number of parasite strains showing resistance is growing, while hardly any new anthelminthics are being developed. Here, we present a bioinformatics workflow designed to reduce the time and cost in the development of new strategies against parasites. The workflow includes quantitative transcriptomics and proteomics, 3D structure modeling, binding site prediction, and virtual ligand screening. Its use is demonstrated for Acanthocephala (thorny-headed worms) which are an emerging pest in fish aquaculture. We included three acanthocephalans (Pomphorhynchus laevis, Neoechinorhynchus agilis, Neoechinorhynchus buttnerae) from four fish species (common barbel, European eel, thinlip mullet, tambaqui). Results The workflow led to eleven highly specific candidate targets in acanthocephalans. The candidate targets showed constant and elevated transcript abundances across definitive and accidental hosts, suggestive of constitutive expression and functional importance. Hence, the impairment of the corresponding proteins should enable specific and effective killing of acanthocephalans. Candidate targets were also highly abundant in the acanthocephalan body wall, through which these gutless parasites take up nutrients. Thus, the candidate targets are likely to be accessible to compounds that are orally administered to fish. Virtual ligand screening led to ten compounds, of which five appeared to be especially promising according to ADMET, GHS, and RO5 criteria: tadalafil, pranazepide, piketoprofen, heliomycin, and the nematicide derquantel. Conclusions The combination of genomics, transcriptomics, and proteomics led to a broadly applicable procedure for the cost- and time-saving identification of candidate target proteins in parasites. The ligands predicted to bind can now be further evaluated for their suitability in the control of acanthocephalans. The workflow has been deposited at the Galaxy workflow server under the URL tinyurl.com/yx72rda7 .

Summary: Crowded environments are known to affect the diffusion of macromolecules, but their effects on the diffusion of small molecules are largely uncharacterized. We investigate how three protein crowders, bovine serum albumin (BSA), hen egg-white lysozyme, and myoglobin, influence the diffusion rates and interactions of four small molecules: fluorescein, and three drugs, doxorubicin, glycogen synthase kinase-3 inhibitor SB216763, and quinacrine. Using Line-FRAP measurements, Brownian dynamics simulations, and molecular docking, we find that the diffusion rates of the small molecules are highly affected by self-aggregation, interactions with the proteins, and surface adsorption. The diffusion of fluorescein is decreased because of its interactions with the protein crowders and their surface adsorption. Protein crowders increase the diffusion rates of doxorubicin and SB216763 by reducing surface interactions and self-aggregation, respectively. Quinacrine diffusion was not affected by protein crowders. The mechanistic insights gained here may assist in optimization of compounds for higher mobility in complex macromolecular environments.

The therapeutic targeting of the immune system, for example in vaccinology and cancer treatment, is a challenging task and the subject of active research. Several in silico tools used for predicting immunogenicity are based on the analysis of peptide sequences binding to the Major Histocompatibility Complex (pMHC). However, few of these bioinformatics tools take into account the pMHC three-dimensional structure. Here, we describe a new bioinformatics tool, MatchTope, developed for predicting peptide similarity, which can trigger cross-reactivity events, by computing and analyzing the electrostatic potentials of pMHC complexes. We validated MatchTope by using previously published data from in vitro assays. We thereby demonstrate the strength of MatchTope for similarity prediction between targets derived from several pathogens as well as for indicating possible cross responses between self and tumor peptides. Our results suggest that MatchTope can enhance and speed up future studies in the fields of vaccinology and cancer immunotherapy.

Abstract Rare variants in the beta-glucocerebrosidase gene (GBA1) are common genetic risk factors for alpha synucleinopathy, which often manifests clinically as GBA-associated Parkinson’s disease (GBA-PD). Clinically, GBA-PD closely mimics idiopathic PD, but it may present at a younger age and often aggregates in families. Most carriers of GBA variants are, however, asymptomatic. Moreover, symptomatic PD patients without GBA variant have been reported in families with seemingly GBA-PD. These observations obscure the link between GBA variants and PD pathogenesis and point towards a role for unidentified additional genetic and/or environmental risk factors or second hits in GBA-PD. In this study, we explored whether rare genetic variants may be additional risk factors for PD in two families segregating the PD-associated GBA1 variants c.115+1G>A (ClinVar ID: 93445) and p.L444P (ClinVar ID: 4288). Our analysis identified rare genetic variants of the HSP70 co-chaperone DnaJ homolog subfamily B member 6 (DNAJB6) and lysosomal protein prosaposin (PSAP) as additional factors possibly influencing PD risk in the two families. In comparison to the wild-type proteins, variant DNAJB6 and PSAP proteins show altered functions in the context of cellular alpha-synuclein homeostasis when expressed in reporter cells. Furthermore, the segregation pattern of the rare variants in the genes encoding DNAJB6 and PSAP indicated a possible association with PD in the respective families. The occurrence of second hits or additional PD cosegregating rare variants has important implications for genetic counseling in PD families with GBA1 variant carriers and for the selection of PD patients for GBA targeted treatments.

Mukherjee, Nandekar and Wade investigate the structural arrangement of the complex between membrane-bound cytochrome P450 1A1 and NADPH-cytochrome P450 reductase. They find that upon binding to the reductase, the catalytic domain of cytochrome P450 1A1 reorients subject to the constraints of membrane binding, potentially explaining why the electron transfer rates between the proteins are low when compared to those of soluble bacterial cytochrome P450s.

The protein-ligand residence time, τ, influences molecular function in biological networks and has been recognized as an important determinant of drug efficacy. To predict τ, computational methods must overcome the problem that τ often exceeds the timescales accessible to conventional molecular dynamics (MD) simulation. Here, we apply the τ-Random Acceleration Molecular Dynamics (τRAMD) method to a set of kinetically characterized complexes of T4 lysozyme mutants with small, engineered binding cavities. τRAMD yields relative ligand dissociation rates in good accordance with experiments across this diverse set of complexes that differ with regard to measurement temperature, ligand identity, protein mutation and binding cavity. τRAMD thereby allows a comprehensive characterization of the ligand egress routes and determinants of τ. Although ligand dissociation by multiple egress routes is observed, we find that egress via the predominant route determines the value of τ. We also find that the presence of a greater number of metastable states along egress pathways leads to slower protein-ligand dissociation. These physical insights could be exploited in the rational optimization of the kinetic properties of drug candidates.

The strict human pathogen Streptococcus pyogenes causes infections of varying severity, ranging from self-limiting suppurative infections to life-threatening diseases like necrotizing fasciitis or streptococcal toxic shock syndrome. Here, we show that the non-phosphorylating glyceraldehyde-3-phosphate dehydrogenase GapN is an essential enzyme for S. pyogenes. GapN converts glyceraldehyde 3-phosphate into 3-phosphoglycerate coupled to the reduction of NADP to NADPH. The knock-down of gapN by antisense peptide nucleic acids (asPNA) significantly reduces viable bacterial counts of S. pyogenes laboratory and macrolide-resistant clinical strains in vitro. As S. pyogenes lacks the oxidative part of the pentose phosphate pathway, GapN appears to be the major NADPH source for the bacterium. Accordingly, other streptococci that carry a complete pentose phosphate pathway are not prone to asPNA-based gapN knock-down. Determination of the crystal structure of the S. pyogenes GapN apo-enzyme revealed an unusual cis-peptide in proximity to the catalytic binding site. Furthermore, using a structural modeling approach, we correctly predicted competitive inhibition of S. pyogenes GapN by erythrose 4-phosphate, indicating that our structural model can be used for in silico screening of specific GapN inhibitors. In conclusion, the data provided here reveal that GapN is a potential target for antimicrobial substances that selectively kill S. pyogenes and other streptococci that lack the oxidative part of the pentose phosphate pathway.

The virtual screening of large numbers of compounds against target protein binding sites has become an integral component of drug discovery workflows. This screening is often done by computationally docking ligands into a protein binding site of interest, but this has the drawback of a large number of poses that must be evaluated to obtain accurate estimates of protein-ligand binding affinity. We here introduce a fast pre-filtering method for ligand prioritization that is based on a set of machine learning models and uses simple pose-invariant physicochemical descriptors of the ligands and the protein binding pocket. Our method, Rapid Screening with Physicochemical Descriptors + machine learning (RASPD+), is trained on PDBbind data and achieves a regression performance that is better than that of the original RASPD method and traditional scoring functions on a range of different test sets without the need for generating ligand poses. Additionally, we use RASPD+ to identify molecular features important for binding affinity and assess the ability of RASPD+ to enrich active molecules from decoys.

Neurotrophins are growth factors that exert important neuroprotective effects by preventing neuronal death and synaptic loss. Nerve Growth Factor (NGF) acts through the activation of its high-affinity, pro-survival TrkA and low-affinity, pro-apoptotic p75NTR receptors. NGF has been shown to slow or prevent neurodegenerative signals in Alzheimer’s Disease (AD) progression. However, its low bioavailability and its blood–brain-barrier impermeability limit the use of NGF as a potential therapeutic agent against AD. Based on our previous findings on synthetic dehydroepiandrosterone derivatives, we identified a novel NGF mimetic, named ENT-A013, which selectively activates TrkA and exerts neuroprotective, anti-amyloid-β actions. We now report the chemical synthesis, in silico modelling, metabolic stability, CYP-mediated reaction phenotyping and biological characterization of ENT-A013 under physiological and neurodegenerative conditions. We show that ENT-A013 selectively activates the TrkA receptor and its downstream kinases Akt and Erk1/2 in PC12 cells, protecting these cells from serum deprivation-induced cell death. Moreover, ENT-A013 promotes survival of primary Dorsal Root Ganglion (DRG) neurons upon NGF withdrawal and protects hippocampal neurons against Amyloid β-induced apoptosis and synaptic loss. Furthermore, this neurotrophin mimetic partially restores LTP impairment. In conclusion, ENT-A013 represents a promising new lead molecule for developing therapeutics against neurodegenerative disorders, such as Alzheimer’s Disease, selectively targeting TrkA-mediated pro-survival signals.

Aims: High levels of glucose and reactive carbonyl intermediates of its degradation pathway such as methylglyoxal (MG) may contribute to diabetic complications partly via increased generation of reactive oxygen species (ROS). This study focused on glutathione peroxidase-1 (GPx1) expression and the impact of carbonylation as an oxidative protein modification on GPx1 abundance and activity in human umbilical vein endothelial cells (HUVEC) under conditions of mild to moderate oxidative stress. Results: High extracellular glucose and MG enhanced intracellular ROS formation in HUVECs. Protein carbonylation was only transiently augmented pointing to an effective antioxidant defense in these cells. Nitric oxide synthase expression was decreased under hyperglycemic conditions but increased upon exposure to MG, whereas superoxide dismutase expression was not significantly affected. Increased glutathione peroxidase (GPx) activity seemed to compensate for a decrease in GPx1 protein due to enhanced degradation via the proteasome. Mass spectrometry analysis identified Lys-114 as a possible carbonylation target which provides a vestibule for the substrate H2O2 and thus enhances the enzymatic reaction. Innovation: Oxidative protein carbonylation has so far been associated with functional inactivation of modified target proteins mainly contributing to aging and age-related diseases. Here, we demonstrate that mild oxidative stress and subsequent carbonylation seem to activate protective cellular redox signaling pathways whereas severe oxidative stress overwhelms the cellular antioxidant defense leading to cell damage. Conclusions: This study may contribute to a better understanding of redox homeostasis and its role in the development of diabetes and related vascular complications. Keywords: Protein carbonylation, Reactive oxygen species, Hyperglycemia, Glutathione peroxidase-1, Endothelial cells

Drug-target residence times can impact drug efficacy and safety, and are therefore increasingly being considered during lead optimization. For this purpose, computational methods to predict residence times, τ, for drug-like compounds and to derive structure-kinetic relationships are desirable. A challenge for approaches based on molecular dynamics (MD) simulation is the fact that drug residence times are typically orders of magnitude longer than computationally feasible simulation times. Therefore, enhanced sampling methods are required. We recently reported one such approach: the τRAMD procedure for estimating relative residence times by performing a large number of random acceleration MD (RAMD) simulations in which ligand dissociation occurs in times of about a nanosecond due to the application of an additional randomly oriented force to the ligand. The length of the RAMD simulations is used to deduce τ. The RAMD simulations also provide information on ligand egress pathways and dissociation mechanisms. Here, we describe a machine learning approach to systematically analyze protein-ligand binding contacts in the RAMD trajectories in order to derive regression models for estimating τ and to decipher the molecular features leading to longer τ values. We demonstrate that the regression models built on the protein-ligand interaction fingerprints of the dissociation trajectories result in robust estimates of τ for a set of 94 drug-like inhibitors of heat shock protein 90 (HSP90), even for the compounds for which the length of the RAMD trajectories does not provide a good estimation of τ. Thus, we find that machine learning helps to overcome inaccuracies in the modeling of protein-ligand complexes due to incomplete sampling or force field deficiencies. Moreover, the approach facilitates the identification of features important for residence time. In particular, we observed that interactions of the ligand with the sidechain of F138, which is located on the border between the ATP binding pocket and a hydrophobic transient sub-pocket, play a key role in slowing compound dissociation. We expect that the combination of the τRAMD simulation procedure with machine learning analysis will be generally applicable as an aid to target-based lead optimization.

Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the “bitter” and “sweet” aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.

Kelch-like ECH associated protein 1 (Keap1) is a cellular sensor for oxidative stress and a negative regulator of the transcription factor Nrf2. Keap1 and Nrf2 control expression of nearly 500 genes with diverse cytoprotective functions and the Nrf2-Keap1 signaling pathway is a major regulator of cytoprotective responses to oxidative and electrophilic stress. It was found that the metallopeptidase dipeptidyl peptidase III (DPP III) contributes to Nrf2 activation by binding to Keap1, probably by binding to the Kelch domain, and thereby influences Nrf2 activity in cancer. We here first determined that the KD of the DPP III-Kelch domain complex is in the submicromolar range. In order to elucidate the molecular details of the DPP III – Kelch interaction we then built models of the complex between human DPP III and the Keap1 Kelch domain and performed coarse-grained and atomistic simulations of the complexes. In the most stable complexes, the ETGE motif in the DPP III flexible loop binds near the central pore of the six-blade β-propeller Kelch domain. According to the preliminary HD exchange experiments DPP III binds to the more unstructured end of Kelch domain. According to the results of MD simulations DPP III binding to the Kelch domain does not influence the overall DPP III structure or the long-range domain fluctuations. We can conclude that DPP III forms the stable complexes with the Keap1 Kelch domain by inserting the flexible loop into the entrance to the central pore of the six blade β-propeller Kelch domain at its more unstructured, N-terminus. This work is licensed under a Creative Commons Attribution 4.0 International License.

HMBG1 is a protein expressed in natural killer cells and is important in immunosurveillance. In this study, the authors show that HMGB1 binds to and inhibits PKM2, resulting in a block in aerobic glycolysis and ultimately cell death.

The human cytochrome P450 (CYP) 2C9 and 2C19 enzymes are two highly similar isoforms with key roles in drug metabolism. They are anchored to the endoplasmic reticulum membrane by their N-terminal transmembrane helix and interactions of their cytoplasmic globular domain with the membrane. However, their crystal structures were determined after N-terminal truncation and mutating residues in the globular domain that contact the membrane. Therefore, the CYP-membrane interactions are not structurally well-characterized and their dynamics and the influence of membrane interactions on CYP function are not well understood. We describe herein the modeling and simulation of CYP 2C9 and CYP 2C19 in a phospholipid bilayer. The simulations revealed that, despite high sequence conservation, the small sequence and structural differences between the two isoforms altered the interactions and orientations of the CYPs in the membrane bilayer. We identified residues (including K72, P73, and I99 in CYP 2C9 and E72, R73, and H99 in CYP 2C19) at the protein-membrane interface that contribute not only to the differing orientations adopted by the two isoforms in the membrane, but also to their differing substrate specificities by affecting the substrate access tunnels. Our findings provide a mechanistic interpretation of experimentally observed effects of mutagenesis on substrate selectivity.

This Special Issue contains thirteen articles that provide a vivid snapshot of the state-of-the-art of molecular modeling in drug design, illustrating recent advances and critically discussing important challenges [...]

The chloroquine resistance transporter (PfCRT) confers resistance to a wide range of quinoline and quinoline-like antimalarial drugs in Plasmodium falciparum, with local drug histories driving its evolution and, hence, the drug transport specificities. For example, the change in prescription practice from chloroquine (CQ) to piperaquine (PPQ) in Southeast Asia has resulted in PfCRT variants that carry an additional mutation, leading to PPQ resistance and, concomitantly, to CQ re-sensitization. How this additional amino acid substitution guides such opposing changes in drug susceptibility is largely unclear. Here, we show by detailed kinetic analyses that both the CQ- and the PPQ-resistance conferring PfCRT variants can bind and transport both drugs. Surprisingly, the kinetic profiles revealed subtle yet significant differences, defining a threshold for in vivo CQ and PPQ resistance. Competition kinetics, together with docking and molecular dynamics simulations, show that the PfCRT variant from the Southeast Asian P. falciparum strain Dd2 can accept simultaneously both CQ and PPQ at distinct but allosterically interacting sites. Furthermore, combining existing mutations associated with PPQ resistance created a PfCRT isoform with unprecedented non-Michaelis-Menten kinetics and superior transport efficiency for both CQ and PPQ. Our study provides additional insights into the organization of the substrate binding cavity of PfCRT and, in addition, reveals perspectives for PfCRT variants with equal transport efficiencies for both PPQ and CQ.

Drugs that target human thymidylate synthase (hTS), a dimeric enzyme, are widely used in anticancer therapy. However, treatment with classical substrate-site-directed TS inhibitors induces over-expression of this protein and development of drug resistance. We thus pursued an alternative strategy that led us to the discovery of TS-dimer destabilizers. These compounds bind at the monomer-monomer interface and shift the dimerization equilibrium of both the recombinant and the intracellular protein toward the inactive monomers. A structural, spectroscopic, and kinetic investigation has provided evidence and quantitative information on the effects of the interaction of these small molecules with hTS. Focusing on the best among them, E7, we have shown that it inhibits hTS in cancer cells and accelerates its proteasomal degradation, thus causing a decrease in the enzyme intracellular level. E7 also showed a superior anticancer profile to fluorouracil in a mouse model of human pancreatic and ovarian cancer. Thus, over sixty years after the discovery of the first TS prodrug inhibitor, fluorouracil, E7 breaks the link between TS inhibition and enhanced expression in response, providing a strategy to fight drug-resistant cancers.

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system works or why certain phenomena are observed. Data-driven modeling, on the other hand, follows a more unbiased approach, with model construction informed by the computationally intensive use of data. At the same time, researchers employ models at different biological scales and at different levels of abstraction. Combining these models while validating them against experimental data increases understanding of the multiscale brain. However, a lack of interoperability, transparency, and reusability of both models and the workflows used to construct them creates barriers for the integration of models representing different biological scales and built using different modeling philosophies. We argue that the same imperatives that drive resources and policy for data – such as the FAIR (Findable, Accessible, Interoperable, Reusable) principles – also support the integration of different modeling approaches. The FAIR principles require that data be shared in formats that are Findable, Accessible, Interoperable, and Reusable. Applying these principles to models and modeling workflows, as well as the data used to constrain and validate them, would allow researchers to find, reuse, question, validate, and extend published models, regardless of whether they are implemented phenomenologically or mechanistically, as a few equations or as a multiscale, hierarchical system. To illustrate these ideas, we use a classical synaptic plasticity model, the Bienenstock–Cooper–Munro rule, as an example due to its long history, different levels of abstraction, and implementation at many scales.

Long-term potentiation and depression of synaptic activity in response to stimuli is a key factor in reinforcement learning. Strengthening of the corticostriatal synapses depends on the second messenger cAMP, whose synthesis is catalysed by the enzyme adenylyl cyclase 5 (AC5), which is itself regulated by the stimulatory Gαolf and inhibitory Gαi proteins. AC isoforms have been suggested to act as coincidence detectors, promoting cellular responses only when convergent regulatory signals occur close in time. However, the mechanism for this is currently unclear, and seems to lie in their diverse regulation patterns. Despite attempts to isolate the ternary complex, it is not known if Gαolf and Gαi can bind to AC5 simultaneously, nor what activity the complex would have. Using protein structure-based molecular dynamics simulations, we show that this complex is stable and inactive. These simulations, along with Brownian dynamics simulations to estimate protein association rates constants, constrain a kinetic model that shows that the presence of this ternary inactive complex is crucial for AC5's ability to detect coincident signals, producing a synergistic increase in cAMP. These results reveal some of the prerequisites for corticostriatal synaptic plasticity, and explain recent experimental data on cAMP concentrations following receptor activation. Moreover, they provide insights into the regulatory mechanisms that control signal processing by different AC isoforms.

Kinetoplastid parasites-trypanosomes and leishmanias-infect millions of humans and cause economically devastating diseases of livestock, and the few existing drugs have serious deficiencies. Benzoxaborole-based compounds are very promising potential novel anti-trypanosomal therapies, with candidates already in human and animal clinical trials. We investigated the mechanism of action of several benzoxaboroles, including AN7973, an early candidate for veterinary trypanosomosis. In all kinetoplastids, transcription is polycistronic. Individual mRNA 5'-ends are created by trans splicing of a short leader sequence, with coupled polyadenylation of the preceding mRNA. Treatment of Trypanosoma brucei with AN7973 inhibited trans splicing within 1h, as judged by loss of the Y-structure splicing intermediate, reduced levels of mRNA, and accumulation of peri-nuclear granules. Methylation of the spliced leader precursor RNA was not affected, but more prolonged AN7973 treatment caused an increase in S-adenosyl methionine and methylated lysine. Together, the results indicate that mRNA processing is a primary target of AN7973. Polyadenylation is required for kinetoplastid trans splicing, and the EC50 for AN7973 in T. brucei was increased three-fold by over-expression of the T. brucei cleavage and polyadenylation factor CPSF3, identifying CPSF3 as a potential molecular target. Molecular modeling results suggested that inhibition of CPSF3 by AN7973 is feasible. Our results thus chemically validate mRNA processing as a viable drug target in trypanosomes. Several other benzoxaboroles showed metabolomic and splicing effects that were similar to those of AN7973, identifying splicing inhibition as a common mode of action and suggesting that it might be linked to subsequent changes in methylated metabolites. Granule formation, splicing inhibition and resistance after CPSF3 expression did not, however, always correlate and prolonged selection of trypanosomes in AN7973 resulted in only 1.5-fold resistance. It is therefore possible that the modes of action of oxaboroles that target trypanosome mRNA processing might extend beyond CPSF3 inhibition.

Cell motility is essential for protozoan and metazoan organisms and typically relies on the dynamic turnover of actin filaments. In metazoans, monomeric actin polymerises into usually long and stable filaments, while some protozoans form only short and highly dynamic actin filaments. These different dynamics are partly due to the different sets of actin regulatory proteins and partly due to the sequence of actin itself. Here we probe the interactions of actin subunits within divergent actin filaments using a comparative dynamic molecular model and explore their functions using Plasmodium, the protozoan causing malaria, and mouse melanoma derived B16-F1 cells as model systems. Parasite actin tagged to a fluorescent protein (FP) did not incorporate into mammalian actin filaments, and rabbit actin-FP did not incorporate into parasite actin filaments. However, exchanging the most divergent region of actin subdomain 3 allowed such reciprocal incorporation. The exchange of a single amino acid residue in subdomain 2 (N41H) of Plasmodium actin markedly improved incorporation into mammalian filaments. In the parasite, modification of most subunit-subunit interaction sites was lethal, whereas changes in actin subdomains 1 and 4 reduced efficient parasite motility and hence mosquito organ penetration. The strong penetration defects could be rescued by overexpression of the actin filament regulator coronin. Through these comparative approaches we identified an essential and common contributor, subdomain 3, which drives the differential dynamic behaviour of two highly divergent eukaryotic actins in motile cells.

Profilin is an actin monomer binding protein that provides ATP-actin for incorporation into actin filaments. In contrast to higher eukaryotic cells with their large filamentous actin structures, apicomplexan parasites typically contain only short and highly dynamic microfilaments. In apicomplexans, profilin appears to be the main monomer-sequestering protein. Compared to classical profilins, apicomplexan profilins contain an additional arm-like β-hairpin motif, which we show here to be critically involved in actin binding. Through comparative analysis using two profilin mutants, we reveal this motif to be implicated in gliding motility of Plasmodium berghei sporozoites, the rapidly migrating forms of a rodent malaria parasite transmitted by mosquitoes. Force measurements on migrating sporozoites and molecular dynamics simulations indicate that the interaction between actin and profilin fine-tunes gliding motility. Our data suggest that evolutionary pressure to achieve efficient high-speed gliding has resulted in a unique profilin-actin interface in these parasites.

Hsp70 participates in a broad spectrum of protein folding processes extending from nascent chain folding to protein disaggregation. This versatility in function is achieved through a diverse family of J-protein cochaperones that select substrates for Hsp70. Substrate selection is further tuned by transient complexation between different classes of J-proteins, which expands the range of protein aggregates targeted by metazoan Hsp70 for disaggregation. We assessed the prevalence and evolutionary conservation of J-protein complexation and cooperation in disaggregation. We find the emergence of a eukaryote-specific signature for interclass complexation of canonical J-proteins. Consistently, complexes exist in yeast and human cells, but not in bacteria, and correlate with cooperative action in disaggregation in vitro. Signature alterations exclude some J-proteins from networking, which ensures correct J-protein pairing, functional network integrity and J-protein specialization. This fundamental change in J-protein biology during the prokaryote-to-eukaryote transition allows for increased fine-tuning and broadening of Hsp70 function in eukaryotes.

Many signaling events require the binding of cytoplasmic proteins to cell membranes by recognition of specific charged lipids, such as phosphoinositol-phosphates. As a model for a protein-membrane binding site, we consider one charged phosphoinositol phosphate (PtdIns(3)P) embedded in a phosphatidylcholine bilayer. As the protein-membrane binding is driven by electrostatic interactions, continuum solvent models require an accurate representation of the electrostatic potential of the phosphoinositol phosphate-containing membrane. We computed and analyzed the electrostatic potentials of snapshots taken at regular intervals from molecular dynamics simulations of the bilayer. We observe considerable variation in the electrostatic potential of the bilayer both along a single simulation and between simulations performed with the GAFF or CHARMM c36 force fields. However, we find that the choice of GAFF or CHARMM c36 parameters has little effect on the electrostatic potential of a given configuration of the bilayer with a PtdIns(3)P embedded in it. From our results, we propose a remedian averaging method for calculating the electrostatic potential of a membrane system that is suitable for simulations of protein-membrane binding with a continuum solvent model.

Pyruvate kinase (PYK) is a critical allosterically regulated enzyme that links glycolysis, the primary energy metabolism, to cellular metabolism. Lactic acid bacteria rely almost exclusively on glycolysis for their energy production under anaerobic conditions, which reinforces the key role of PYK in their metabolism. These organisms are closely related, but have adapted to a huge variety of native environments. They include food-fermenting organisms, important symbionts in the human gut, and antibiotic-resistant pathogens. In contrast to the rather conserved inhibition of PYK by inorganic phosphate, the activation of PYK shows high variability in the type of activating compound between different lactic acid bacteria. System-wide comparative studies of the metabolism of lactic acid bacteria are required to understand the reasons for the diversity of these closely related microorganisms. These require knowledge of the identities of the enzyme modifiers. Here, we predict potential allosteric activators of PYKs from three lactic acid bacteria which are adapted to different native environments. We used protein structure-based molecular modeling and enzyme kinetic modeling to predict and validate potential activators of PYK. Specifically, we compared the electrostatic potential and the binding of phosphate moieties at the allosteric binding sites, and predicted potential allosteric activators by docking. We then made a kinetic model of Lactococcus lactis PYK to relate the activator predictions to the intracellular sugar-phosphate conditions in lactic acid bacteria. This strategy enabled us to predict fructose 1,6-bisphosphate as the sole activator of the Enterococcus faecalis PYK, and to predict that the PYKs from Streptococcus pyogenes and Lactobacillus plantarum show weaker specificity for their allosteric activators, while still having fructose 1,6-bisphosphate play the main activator role in vivo. These differences in the specificity of allosteric activation may reflect adaptation to different environments with different concentrations of activating compounds. The combined computational approach employed can readily be applied to other enzymes.

Rab GTPases constitute the largest subfamily of the Ras protein superfamily. Rab proteins regulate organelle biogenesis and transport, and display distinct binding preferences for effector and activator proteins, many of which have not been elucidated yet. The underlying molecular recognition motifs, binding partner preferences and selectivities are not well understood.Comparative analysis of the amino acid sequences and the three-dimensional electrostatic and hydrophobic molecular interaction fields of 62 human Rab proteins revealed a wide range of binding properties with large differences between some Rab proteins. This analysis assists the functional annotation of Rab proteins 12, 14, 26, 37 and 41 and provided an explanation for the shared function of Rab3 and 27. Rab7a and 7b have very different electrostatic potentials, indicating that they may bind to different effector proteins and thus, exert different functions. The subfamily V Rab GTPases which are associated with endosome differ subtly in the interaction properties of their switch regions, and this may explain exchange factor specificity and exchange kinetics.We have analysed conservation of sequence and of molecular interaction fields to cluster and annotate the human Rab proteins. The analysis of three dimensional molecular interaction fields provides detailed insight that is not available from a sequence-based approach alone. Based on our results, we predict novel functions for some Rab proteins and provide insights into their divergent functions and the determinants of their binding partner selectivity.

The microsomal, membrane-bound, human cytochrome P450 (CYP) 2C9 is a liver-specific monooxygenase essential for drug metabolism. CYPs require electron transfer from the membrane-bound CYP reductase (CPR) for catalysis. The structural details and functional relevance of the CYP-membrane interaction are not understood. From multiple coarse grained molecular simulations started with arbitrary configurations of protein-membrane complexes, we found two predominant orientations of CYP2C9 in the membrane, both consistent with experiments and conserved in atomic-resolution simulations. The dynamics of membrane-bound and soluble CYP2C9 revealed correlations between opening and closing of different tunnels from the enzyme's buried active site. The membrane facilitated the opening of a tunnel leading into it by stabilizing the open state of an internal aromatic gate. Other tunnels opened selectively in the simulations of product-bound CYP2C9. We propose that the membrane promotes binding of liposoluble substrates by stabilizing protein conformations with an open access tunnel and provide evidence for selective substrate access and product release routes in mammalian CYPs. The models derived here are suitable for extension to incorporate other CYPs for oligomerization studies or the CYP reductase for studies of the electron transfer mechanism, whereas the modeling procedure is generally applicable to study proteins anchored in the bilayer by a single transmembrane helix.