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Martini 3, the latest version of the widely used Martini force field for coarse-grained molecular dynamics simulations, is a promising tool to investigate proteins in phospholipid bilayers. However, simulating other lipid environments, such as detergent micelles, presents challenges due to the absence of validated parameters for their constituent molecules. Here, we propose parameters for the micelle-forming surfactant, dodecylphosphocholine (DPC). These result in micelle assembly with aggregation numbers in agreement with experimental values. However, we identified a lack of hydrophobic interactions between transmembrane helix protein dimers and the tails of DPC molecules, preventing insertion and stabilization of the protein in the micelles. This problem was also observed for protein insertion by self-assembling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) or dipalmitoylphosphatidylcholine (DPPC) bilayers. We propose the reduction of the non-bonded interactions between protein and water beads by 10% as a simple and effective solution to this problem that enables protein encapsulation in phospholipid micelles and bilayers without altering protein dimerization or bilayer structure.Abstract Figure

The optimization of compounds with multiple targets is a difficult multidimensional problem in the drug discovery cycle. Here, we present a systematic, multidisciplinary approach to the development of selective anti-parasitic compounds. Computational fragment-based design of novel pteridine derivatives along with iterations of crystallographic structure determination allowed for the derivation of a structure-activity relationship for multitarget inhibition. The approach yielded compounds showing apparent picomolar inhibition of T. brucei pteridine reductase 1 (PTR1), nanomolar inhibition of L. major PTR1, and selective submicromolar inhibition of parasite dihydrofolate reductase (DHFR) versus human DHFR. Moreover, by combining design for polypharmacology with a property-based on-parasite optimization, we found three compounds that exhibited micromolar EC50 values against T. brucei brucei, whilst retaining their target inhibition. Our results provide a basis for the further development of pteridine-based compounds, and we expect our multitarget approach to be generally applicable to the design and optimization of anti-infective agents.

SUMMARYNeural 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 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. In our study, we use a combination of mouse and human stem cell models to circumvent these issues and perform comprehensive characterization of a novel neurogenic compound usingin vitroscreening. Our work focuses on the brain-derived neurotrophic factor (BDNF) pathway, a pivotal neurotrophin in the regulation of neuronal growth and differentiation via its receptor tyrosine receptor kinase B (TrkB). We describe the design, chemical synthesis and biological characterization of ENT-A011, a steroidal dehydroepiandrosterone (DHEA) derivative and BDNF mimetic with neuroprotective and neurogenic actions. The compound is able to increase proliferation of mouse primary adult hippocampal NSCs and embryonic cortical NSCs, in the absence of EGF/FGF, while reducing Amyloid-β (Aβ) induced cell death, acting specifically through TrkB activation. The compound is also able to increase astrocytic gene markers involved in NSC maintenance, protect hippocampal neurons from Αβ toxicity and prevent synapse loss after Aβ treatment. To provide a translational link to human cells, we also used neural progenitor cells (NPCs) differentiated from three human induced pluripotent stem cell lines from healthy and AD donors. Our findings suggest that ENT-A011 successfully induces proliferation and prevents cell death after Aβ toxicity of human NPCs. Additionally, using RNAseq profiling, we demonstrate that the compound acts through a core gene network shared with BDNF. Our work characterizes a novel synthetic BDNF mimetic with potential 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.

The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of a community effort, the “Billion molecules against Covid-19 challenge”, to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 potentially active molecules, which were subsequently ranked to find ‘consensus compounds’. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (Nsp12 domain), and (alpha) spike protein S. Overall, 27 potential inhibitors were experimentally confirmed by binding-, cleavage-, and/or viral suppression assays and are presented here. All results are freely available and can be taken further downstream without IP restrictions. Overall, we show the effectiveness of computational techniques, community efforts, and communication across research fields (i.e., protein expression and crystallography, in silico modeling, synthesis and biological assays) to accelerate the early phases of drug discovery.

BackgroundThe EF-hand Ca2+sensor protein S100A1 has been identified as a molecular regulator and enhancer of cardiac performance. S100A1’s ability to recognize and modulate the activity of targets such as SERCA2a and RyR2 in cardiomyocytes has mostly been ascribed to its hydrophobic C-terminalα-helix (residues 75-94).Objective:We therefore hypothesized that a synthetic peptide consisting of residues 75-94 of S100A1 and an N-terminal solubilization tag (S100A1ct) could mimic the performance enhancing effects of S100A1 and may be suitable as a peptide therapeutic to improve the function of diseased hearts.Methods and Results:Applying an integrative translational research pipeline, ranging from computational molecular modeling to large animal cardiac disease models, we characterize S100A1ct as a cell-penetrating peptide with positive inotropic and antiarrhythmic properties in normal and failing myocardiumin vitroandin vivo. This activity translates into improved contractile performance and survival in pre-clinical heart failure models with reduced ejection fraction after S100A1ct systemic administration. Mechanistically, S100A1ct exerts a fast and sustained dose-dependent enhancement of cardiomyocyte Ca2+cycling and prevents ß-adrenergic receptor triggered Ca2+imbalances by targeting SERCA2a and RyR2 activity. Modeling suggests that S100A1ct may stimulate SERCA2a by interacting with the sarcoplasmic transmembrane segments of the multi-span integral membrane Ca2+pump. Incorporation of a cardiomyocyte targeting peptide tag into S100A1ct (cor-S100A1ct) further enhanced its biological and therapeutic potencyin vitroandin vivo.Conclusion:S100A1ct peptide is a promising lead for the development of a novel peptide-based therapeutic against heart failure with reduced ejection fraction.

S100A1 is a small EF-type Ca2+sensor protein that belongs to the multigenic S100 protein family. It is abundantly expressed in cardiomyocytes (CMs) and has been described as a key regulator of CM performance due to its unique ability to interact with structural contractile proteins, regulators of cardiac Ca2+cycling, and mitochondrial proteins. However, our understanding of the molecular mechanisms regulating S100A1 protein levels is limited. We used the bioinformatics tool GPS-SUMO2.0 to identify a putative SUMO interacting motif (SIM) on S100A1. Consistently, a S100A1:SUMO interaction assay showed a Ca2+-dependent interaction of S100A1 with SUMO proteins. In neonatal rat ventricular myocytes (NRVM) and COS1 cells, S100A1 protein abundance increased in the presence of overexpressed SUMO1 without affecting the S100A1 mRNA transcript. We then generated S100A1 truncation mutants, where the SIM motif was removed by truncation or in which the core residues of the SIM motif (residues 77-79) were deleted or replaced by alanine. In COS1 cells and NRVM, overexpression of these S100A1 mutants led to elevated S100A1 mutant mRNA levels but failed to produce respective protein levels. Protein expression of these mutants could be rescued from degradation by addition of the proteasome inhibitor MG-132. By using an information-driven approach to dock the three-dimensional structures of S100A1 and SUMO, we predict a novel interaction mode between the SIM in S100A1 and SUMO. This study shows an important role of SUMO:SIM-mediated protein:protein interaction in the regulation of post-translational protein stability, and provides mechanistic insights into the indispensability of the core SIM for S100A1 post-translational stability.

Linker histones (LH) bind to nucleosomes with their globular domain (gH) positioned in either an on- or an off-dyad binding mode. Here, we study the effect of the linker DNA (L-DNA) sequence on the binding of a full-length LH, Xenopus laevis H1.0b, to a Widom 601 nucleosome core particle (NCP) flanked by two 40 bp long L-DNA arms, by single-pair FRET spectroscopy. We varied the sequence of the 11 bp of L-DNA adjoining the NCP on either side, making the sequence either A-tract, purely GC, or mixed, with 64% AT. The labelled gH consistently exhibited higher FRET efficiency with the labelled L-DNA containing the A-tract, than that with the pure-GC stretch, even when the stretches were swapped. However, it did not exhibit higher FRET efficiency with the L-DNA containing 64% AT-rich mixed DNA when compared to the pure-GC stretch. We explain our observations with a model that shows that the gH binds on-dyad and that two arginines mediate recognition of the A-tract via its characteristically narrow minor groove. To investigate whether this on-dyad minor groove-based recognition was distinct from previously identified off-dyad major groove-based recognition, a nucleosome was designed with A-tracts on both the L-DNA arms. One A-tract was complementary to thymine and the other to deoxyuridine. The major groove of the thymine-tract was lined with methyl groups that were absent from the major groove of the deoxyuridine tract. The gH exhibited similar FRET for both these A-tracts, suggesting that it does not interact with the thymine methyl groups exposed on the major groove. Our observations thus complement previous studies that suggest that different LH isoforms may employ different ways of recognizingff AT-rich DNA and A-tracts. This adaptability may enable the LH to universally compact scaffold-associated regions and constitutive heterochromatin, which are rich in such sequences.Statement of SignificanceLinker histones (LHs) associate with the smallest repeat unit of chromatin, the nucleosome. They have been observed to have affinity for AT-rich DNA, which is found in constitutive heterochromatin and scaffold-associated regions (SAR), which could explain how the LHs can compact such parts of the chromatin. How the LH recognizes such sequences is poorly understood. Using single-pair FRET and modelling, we provide experimental evidence of DNA-sequence-induced changes in the orientation of a LH bound to a nucleosome, and thereby reveal a new mechanism by which the LH can recognize A-tract sequences that are abundantly present in the SAR. Our results show that, depending on how the LH associates with the nucleosome, it can employ more than one mechanism to recognize AT-rich DNA.

Trypanosomatidic parasitic infections in humans and animals caused by Trypanosoma brucei, Trypanosoma cruzi, and Leishmania species pose a significant health and economic burden in developing countries. There are few effective and accessible treatments for these diseases, and the existing therapies suffer from problems, such as parasite resistance and side effects. Structure-based drug design (SBDD) is one of the strategies that has been applied to discover new compounds targeting trypanosomatid-borne diseases. We review the current literature (mostly over the last 5 years, searched in the PubMed database on 11 November 2021) on the application of structure-based drug design approaches to identify new anti-trypanosomatidic compounds that interfere with a validated target biochemical pathway, the trypanosomatid folate pathway. The application of structure-based drug design approaches to perturb the trypanosomatid folate pathway has successfully provided many new inhibitors with good selectivity profiles, most of which are natural products or their derivatives or have scaffolds of known drugs. However, the inhibitory effect against the target protein(s) often does not translate to anti-parasitic activity. Further progress is hampered by our incomplete understanding of parasite biology and biochemistry, which is necessary to complement SBDD in a multiparameter optimization approach to discovering selective anti-parasitic drugs.

The propensity of poorly water-soluble drugs to aggregate at supersaturation impedes their bioavailability. The emergence of supersaturated amorphous drug-salt-polymer systems provides a new 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. We describe a comparative experimental and computational characterization of amorphous solid dispersions containing the drug celecoxib, and PVP-VA or HPMCAS polymers 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 less frequent administration and lower doses of this widely used anti-inflammatory, thereby increasing cost-effectiveness, and reducing side-effects.

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., Graphical abstract Image 1, Highlights • Relative residence times are computed for T4 lysozyme mutant-ligand complexes. • τ-Random Acceleration Molecular Dynamics provide efficient sampling of unbinding. • Computed dissociation rates show good agreement with all available measured values. • Ligand egress via the predominant route determines the value of the residence time. • The presence of metastable states along egress pathways slows down dissociation.

Dimerization of the small GTPase Arf is prerequisite for the scission of COPI-coated transport vesicles. Here, we quantify the monomer/dimer equilibrium of Arf within the membrane and show that after membrane scission, Arf dimers are restricted to donor membranes. By hydrogen exchange mass spectrometry, we define the interface of activated dimeric Arf within its switch II region. Single amino acid exchanges in this region reduce the propensity of Arf to dimerize. We suggest a mechanism of membrane scission by which the dimeric form of Arf is segregated to the donor membrane. Our data are consistent with the previously reported absence of dimerized Arf in COPI vesicles and could explain the presence of one single scar-like noncoated region in each COPI vesicle.

Chromatosomes are fundamental units of chromatin structure that are formed when a linker histone protein binds to a nucleosome. The positioning of the linker histone on the nucleosome influences the packing of chromatin. Recent simulations and experiments have shown that chromatosomes adopt an ensemble of structures that differ in the geometry of the linker histone–nucleosome interaction. In this article we review the application of Brownian, Monte Carlo, and molecular dynamics simulations to predict the structure of linker histone–nucleosome complexes, to study the binding mechanisms involved, and to predict how this binding affects chromatin fiber structure. These simulations have revealed the sensitivityof the chromatosome structure to variations in DNA and linker histone sequence, as well as to posttranslational modifications, thereby explaining the structural variability observed in experiments. We propose that a concerted application of experimental and computational approaches will reveal the determinants of chromatosome structural variability and how it impacts chromatin packing.

Accurate protein druggability predictions are important for the selection of drug targets in the early stages of drug discovery. Due to the flexible nature of proteins, the druggability of a binding pocket may vary due to conformational changes. We have therefore developed two statistical models, a logistic regression model (TRAPP-LR) and a convolutional neural network model (TRAPP-CNN), for predicting druggability and how it varies with changes in the spatial and physicochemical properties of a binding pocket. These models are integrated into TRAPP (TRAnsient Pockets in Proteins), a tool for the analysis of binding pocket variations along a protein motion trajectory. The models, which were trained on publicly available and self-augmented data sets, show equivalent or superior performance to existing methods on test sets of protein crystal structures, and have sufficient sensitivity to identify potentially druggable protein conformations in trajectories from molecular dynamics simulations. Visualization of the evidence for the decisions of the models in TRAPP facilitates identification of the factors affecting the druggability of protein binding pockets.

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.

Crowded environments are known to affect the diffusion of macromolecules but their effects on the diffusion of small molecules, such as drugs, are largely uncharacterized. Here, we investigate how three macromolecular protein crowders, bovine serum albumin (BSA), hen egg-white lysozyme and myoglobin, influence the translational diffusion rates and interactions of four low molecular-weight compounds: the diagnostic marker fluorescein, and three drugs, doxorubicin, glycogen synthase kinase-3 inhibitor SB216763 and quinacrine. Using Fluorescence Recovery After Photo-bleaching in Line mode (Line- FRAP), Brownian dynamics simulations and molecular docking, we find that the diffusive behavior of the small molecules is highly affected by self-aggregation, interactions with the proteins, and surface adhesion. The diffusion of fluorescein is decreased by protein crowders due to its interactions with the proteins and their surface adsorption. In contrast, the presence of protein crowders increases the diffusion rate of doxorubicin by reducing surface interactions. SB216763 shows a third scenario, where BSA, but not lysozyme or myoglobin , reduces self-aggregation, resulting in faster diffusion. Quinacrine was the only compound whose diffusion was not affected by the presence of protein crowders. The mechanistic insights gained here into the effects of interactions of small molecules with proteins and surfaces on the translational diffusion of small molecules can assist in optimizing the design of compounds for higher mobility and lower occlusion in complex macromolecular environments.

Heparin, a naturally occurring glycosaminoglycan, has been found to have antiviral activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus of COVID-19. To elucidate the mechanistic basis for the antiviral activity of heparin, we investigated the binding of heparin to the SARS-CoV-2 spike glycoprotein by means of sliding window docking, molecular dynamics simulations, and biochemical assays. Our simulations show that heparin binds at long, positively charged patches on the spike glycoprotein, thereby masking basic residues of both the receptor-binding domain (RBD) and the multifunctional S1/S2 site. Biochemical experiments corroborated the simulation results, showing that heparin inhibits the furin-mediated cleavage of spike by binding to the S1/S2 site. Our simulations showed that heparin can act on the hinge region responsible for motion of the RBD between the inactive closed and active open conformations of the spike glycoprotein. In simulations of the closed spike homotrimer, heparin binds the RBD and the N-terminal domain of two adjacent spike subunits and hinders opening. In simulations of open spike conformations, heparin induces stabilization of the hinge region and a change in RBD motion. Our results indicate that heparin can inhibit SARS-CoV-2 infection by three mechanisms: by allosterically hindering binding to the host cell receptor, by directly competing with binding to host heparan sulfate proteoglycan coreceptors, and by preventing spike cleavage by furin. Furthermore, these simulations provide insights into how host heparan sulfate proteoglycans can facilitate viral infection. Our results will aid the rational optimization of heparin derivatives for SARS-CoV-2 antiviral therapy.

We develop an approach to characterize the effects of gating by a multiconformation protein consisting of macrostate conformations that are either accessible or inaccessible to ligand binding. We first construct a Markov state model of the apo-protein from atomistic molecular dynamics simulations from which we identify macrostates and their conformations, compute their relative macrostate populations and interchange kinetics, and structurally characterize them in terms of ligand accessibility. We insert the calculated first-order rate constants for conformational transitions into a multistate gating theory from which we derive a gating factor γ that quantifies the degree of conformational gating. Applied to HIV-1 protease, our approach yields a kinetic network of three accessible (semi-open, open, and wide-open) and two inaccessible (closed and a newly identified, "parted") macrostate conformations. The parted conformation sterically partitions the active site, suggesting a possible role in product release. We find that the binding kinetics of drugs and drug-like inhibitors to HIV-1 protease falls in the slow gating regime. However, because γ = 0.75, conformational gating only modestly slows ligand binding. Brownian dynamics simulations of the diffusional association of eight inhibitors to the protease─having a wide range of experimental association constants (∼104-1010 M-1 s-1)─yields gated rate constants in the range of ∼0.5-5.7 × 108 M-1 s-1. This indicates that, whereas the association rate of some inhibitors could be described by the model, for many inhibitors either subsequent conformational transitions or alternate binding mechanisms may be rate-limiting. For systems known to be modulated by conformational gating, the approach could be scaled computationally efficiently to screen association kinetics for a large number of ligands.

The optimization of compounds with multiple targets in the drug discovery cycle is a difficult multidimensional problem. Here, we present a systematic, multidisciplinary approach to the development of selective anti-parasitic compounds. Efficient microwave-assisted synthesis of pteridines along with iterations of crystallographic structure determination were used to validate computational docking predictions and support derivation of a structure-activity relationship for multitarget inhibition. This approach yielded compounds showing picomolar inhibition of T. brucei pteridine reductase 1 (PTR1), nanomolar inhibition of L. major PTR1, along with selective submicromolar inhibition of parasitic dihydrofolate reductase (DHFR). Moreover, by combining design for polypharmacology with a property-based on-parasite optimization, we found three compounds that exhibited micromolar EC50 values against T. brucei brucei, whilst retaining their target inhibition. Our results provide a basis for the further development of pteridine-based compounds and we expect our multitarget approach to be generally applicable to the design and optimization of anti-infective agents.

The strict human pathogen

Linker histones (LH) have been shown to preferentially bind to AT-rich DNA, particularly A-tracts, contiguous stretches of adenines. Using spFRET (single pair Förster/Fluorescence Resonance Energy Transfer), we recently found that the globular domain (gH) ofXenopus laevisH1.0b LH orients towards A-tracts on the linker-DNA (L-DNA) while binding on-dyad in LH:mononucleosome complexes. Here, we investigate the impact of this A-tract-mediated orientation of the gH on the compaction of higher-order structures by studying trinucleosomes as minimal models for chromatin. Two 600 bp DNA sequences were constructed, each containing three consecutive Widom 601 core sequences connected by about 40 bp L-DNA but differing in the positioning of A-tracts on either the outer or the inner L-DNAs flanking the first and third Widom 601 sequences. The two inner L-DNAs were fluorescently labelled at their midpoints. Trinucleosomes were reconstituted using the doubly labelled DNA, core histone octamers and H1.0b. SpFRET was performed for a range of NaCl concentrations to measure the compaction and whether gH orientations affected the stability of the trinucleosomes to salt-induced dissociation. While the LH compacted the trinucleosomes, the extent of compaction and the stability were similar for the two DNA sequences. Modeling constrained by the measured FRET efficiency suggests that the structures adopted by the trinucleosomes correspond to the standard zig-zagged two-helical start arrangement with the first and third nucleosomes stacked on top of each other. In this arrangement, the first and third LHs are insufficiently close to interact and affect compaction. Thus, despite differences in the positioning of the A-tracts in the sequences studied, LH binding compacts the corresponding trinucleosomes similarly.Why it mattersThe compaction and three-dimensional structure of chromatin affect the exposure of the DNA and thus regulate gene expression. Linker histone proteins bind to nucleosomes and thereby contribute to chromatin compaction. We here investigated whether the DNA A-tract-mediated orientation of a linker histone globular domain affects chromatin structure by using a trinucleosome as a minimal model for chromatin. Our observations suggest that the trinucleosome structure and compaction are robust against differences in linker histone globular domain orientations.eTOC blurbWe investigate whether DNA sequences, such as adenine-tracts, and sequence-induced linker histone reorientation affect chromatin structure. Using trinucleosomes as model systems for chromatin, we demonstrate that the chromatin structure and compaction are robust to the studied DNA sequence differences and sequence-induced linker histone orientation.

We develop an approach to characterise the effects of gating by a multi-conformation protein consisting of macrostate conformations that are either accessible or inaccessible to ligand binding. We first construct a Markov state model of the apo-protein from atomistic molecular dynamics simulations from which we identify macrostates and their conformations, compute their relative macrostate populations and interchange kinetics, and structurally characterise them in terms of ligand accessibility. We insert the calculated first-order rate constants for conformational transitions into a multi-state gating theory from which we derive a gating factor γ that quantifies the degree of conformational gating. Applied to HIV-1 protease, our approach yields a kinetic network of three accessible (semi-open, open and wide-open) and two inaccessible (closed and a newly identified, ‘parted’) macrostate conformations. The ‘parted’ conformation sterically partitions the active site, suggesting a possible role in product release. We find that the binding kinetics of drugs and drug-like inhibitors to HIV-1 protease falls in the slow gating regime. However, because γ=0.75, conformational gating only modestly slows ligand binding. Brownian dynamics simulations of the diffusional association of eight inhibitors to the protease - that have a wide range of experimental association constants (~104 - 1010 M−1s−1) - yields gated rate constants in the range ~0.5-5.7 × 108 M−1s−1. This indicates that, whereas the association rate of some inhibitors could be described by the model, for many inhibitors either subsequent conformational transitions or alternate binding mechanisms may be rate-limiting. For systems known to be modulated by conformational gating, the approach could be scaled computationally efficiently to screen association kinetics for a large number of ligands.Graphical TOC Entry

There is a growing appreciation of the importance of drug-target binding kinetics for lead optimization. For G protein-coupled receptors (GPCRs), which mediate signaling over a wide range of timescales, the drug dissociation rate is often a better predictor of in vivo efficacy than binding affinity, although it is more challenging to compute. Here, we assess the ability of the τ-Random Acceleration Molecular Dynamics (τRAMD) approach to reproduce relative residence times and reveal dissociation mechanisms and the effects of allosteric modulation for two important membrane-embedded drug targets: the β2-adrenergic receptor and the muscarinic acetylcholine receptor M2. The dissociation mechanisms observed in the relatively short RAMD simulations (in which molecular dynamics (MD) simulations are performed using an additional force with an adaptively assigned random orientation applied to the ligand) are in general agreement with much more computationally intensive conventional MD and metadynamics simulations. Remarkably, although decreasing the magnitude of the random force generally reduces the number of egress routes observed, the ranking of ligands by dissociation rate is hardly affected and agrees well with experiment. The simulations also reproduce changes in residence time due to allosteric modulation and reveal associated changes in ligand dissociation pathways.TABLE OF CONTENTS GRAPHIC

Human cytochrome P450 (CYP) enzymes play an important role in the metabolism of drugs, steroids, fatty acids, and xenobiotics. Microsomal CYPs are anchored in the endoplasmic reticulum membrane by an N-terminal transmembrane (TM) helix that is connected to the globular catalytic domain by a flexible linker sequence. However, the structural and functional importance of the TM-helix is unclear because it has been shown that CYPs can still associate with the membrane and have enzymatic activity in reconstituted systems after truncation or modification of the N-terminal sequence. Here, we investigated the effect of mutations in the N-terminal TM-helix residues of two human steroidogenic enzymes, CYP 17A1 and CYP 19A1, that are major drug targets for cancer therapy. These mutations were originally introduced to increase the expression of the proteins in Escherichia coli. To investigate the effect of the mutations on protein-membrane interactions and function, we carried out coarse-grained and all-atom molecular dynamics simulations of the CYPs in a phospholipid bilayer. We confirmed the orientations of the globular domain in the membrane observed in the simulations by linear dichroism measurements in a Nanodisc. Whereas the behavior of CYP 19A1 was rather insensitive to truncation of the TM-helix, mutations in the TM-helix of CYP 17A1, especially W2A and E3L, led to a gradual drifting of the TM-helix out of the hydrophobic core of the membrane. This instability of the TM-helix could affect interactions with the allosteric redox partner, cytochrome b5, required for CYP 17A1's lyase activity. Furthermore, the simulations showed that the mutant TM-helix influenced the membrane interactions of the CYP 17A1 globular domain. In some simulations, the mutated TM-helix obstructed the substrate access tunnel from the membrane to the CYP active site, indicating a possible effect on enzyme function.

The binding kinetic properties of potential drugs may significantly influence their subsequent clinical efficacy. Predictions of these properties based on computer simulations provide a useful alternative to their expensive and time-demanding experimental counterparts, even at an early drug discovery stage.Herein, we perform Scaled Molecular Dynamics (ScaledMD) simulations on a set of 27 ligands of HSP90 belonging to more than 7 chemical series in order to estimate their relative residence time. We introduce two new techniques for the analysis and the classification of the simulated unbinding trajectories. The first technique, which helps in estimating the limits of the free energy well around the bound state and the second one, based on a new contact map fingerprint, allows the description and the comparison of the paths that lead to unbinding.Using these analyses, we find that ScaledMD’s relative residence time generally enables the identification of the slowest unbinders. We propose an explanation for the underestimation of the residence times of a subset of compounds and we investigate how the biasing in ScaledMD can affect the mechanistic insights that can be gained from the simulations.