SLTCAP: A Simple Method for Calculating the Number of Ions Needed for MD Simulation

Enhanced Hydrogen Bonding by Urea Functionalization Tunes the Stability and Biological Properties of Peptide Amphiphiles

Self-assembled nanostructures such as those formed by peptide amphiphiles (PAs) are of great interest in biological and pharmacological applications. Herein, a simple and widely applicable chemical modification, a urea motif, was included in the PA's molecular structure to stabilize the nanostructures by virtue of intermolecular hydrogen bonds. Since the amino acid residue nearest to the lipid tail is the most relevant for stability, we decided to include the urea modification at that position. We prepared four groups of molecules (13 PAs in all), with varying levels of intermolecular cohesion, using amino acids with distinct β-sheet promoting potential and/or containing hydrophobic tails of distinct lengths. Each subset contained one urea-modified PA and nonmodified PAs, all with the same peptide sequence. The varied responses of these PAs to variations in pH, temperature, counterions, and biologically related proteins were examined using microscopic, X-ray, spectrometric techniques, and molecular simulations. We found that the urea group contributes to the stabilization of the morphology and internal arrangement of the assemblies against environmental stimuli for all peptide sequences. In addition, microbiological and biological studies were performed with the cationic PAs. These assays reveal that the addition of urea linkages affects the PA-cell membrane interaction, showing the potential to increase the selectivity toward bacteria. Our data indicate that the urea motif can be used to tune the stability of a wide range of PA nanostructures, allowing flexibility on the biomaterial's design and opening a myriad of options for clinical therapies.

Reconstructing dynamics correlation network to simultaneously improve activity and stability of 2,3-butanediol dehydrogenase by design of distal interchain disulfide bonds

The complete enzyme catalytic cycle includes substrate binding, chemical reaction and product release, in which different dynamic conformations are adopted. Due to the complex relationship among enzyme activity, stability and dynamics, the directed evolution of enzymes for improved activity or stability commonly leads to a trade-off in stability or activity. It hence remains a challenge to engineer an enzyme to have both enhanced activity and stability. Here, we have attempted to reconstruct the dynamics correlation network involved with active center to improve both activity and stability of a 2,3-butanediol dehydrogenase (2,3-BDH) by introducing inter-chain disulfide bonds. A computational strategy was first applied to evaluate the effect of introducing inter-chain disulfide bond on activity and stability of three 2,3-BDHs, and the N258C mutation of 2,3-BDH from Corynebacterium glutamicum (CgBDH) was proved to be effective in improving both activity and stability. In the results, CgBDH-N258C showed a different unfolding curve from the wild type, with two melting temperatures (Tm) of 68.3 °C and 50.8 °C, 19.7 °C and 2 °C higher than 48.6 °C of the wild type. Its half-life was also improved by 14.8-fold compared to the wild type. Catalytic efficiency (kcat/Km) of the mutant was increased by 7.9-fold toward native substrate diacetyl and 8.8-fold toward non-native substrate 2,5-hexanedione compared to the wild type. Molecular dynamics simulations revealed that an interaction network formed by Cys258, Arg162, Ala144 and the catalytic residues was reconstructed in the mutant and the dynamics change caused by the disulfide bond could be propagated through the interactions network. This improved the enzyme stability and activity by decreasing the flexibility and locking more "reactive" pose, respectively. Further construction of mutations including A144G showing a 44-fold improvement in catalytic efficiency toward meso-2,3-BD confirmed the role of modifying dynamics correlation network in tunning enzyme activity and selectivity. This study provided important insights into the relationship among dynamics, enzyme catalysis and stability, and will be useful in the designing new enzymes with co-evolution of stability, activity and selectivity.

Systematic Comparison of Atomistic Force Fields for the Mechanical Properties of Double-Stranded DNA

The response of double-stranded DNA to external mechanical stress plays a central role in its interactions with the protein machinery in the cell. Modern atomistic force fields have been shown to provide highly accurate predictions for the fine structural features of the duplex. In contrast, and despite their pivotal function, less attention has been devoted to the accuracy of the prediction of the elastic parameters. Several reports have addressed the flexibility of double-stranded DNA via all-atom molecular dynamics, yet the collected information is insufficient to have a clear understanding of the relative performance of the various force fields. In this work, we fill this gap by performing a systematic study in which several systems, characterized by different sequence contexts, are simulated with the most popular force fields within the AMBER family, bcs1 and OL15, as well as with CHARMM36. Analysis of our results, together with their comparison with previous work focused on bsc0, allows us to unveil the differences in the predicted rigidity between the newest force fields and suggests a roadmap to test their performance against experiments. In the case of the stretch modulus, we reconcile these differences, showing that a single mapping between sequence-dependent conformation and elasticity via the crookedness parameter captures simultaneously the results of all force fields, supporting the key role of crookedness in the mechanical response of double-stranded DNA.

Assessing the Binding Mode of a Splicing Modulator Stimulating Pre-mRNA Binding to the Plastic U2AF2 Splicing Factor

RNA recognition motifs (RRMs) play a pivotal role in RNA metabolism and the regulation of gene expression. Owing to their plasticity and fuzziness, targeting RRM/RNA interfaces with small molecules is a daunting challenge for drug discovery campaigns. The U2AF2 splicing factor, which recognizes the polypyrimidine (polyPy) sequence of premature messenger (pre-m)RNA, exhibits a dynamic architecture consisting of two RRMs joined by a disordered linker. An inhibitor, NSC-194308, was shown to enhance the binding of pre-mRNA to U2AF2, selectively triggering cell death in leukemia cell lines containing spliceosome mutations. The NSC-194308 binding mode remains elusive; yet, unraveling its knowledge may offer intriguing insights for effectively targeting U2AF2 and other flexible protein/protein/RNA interfaces with small molecules. To infer plausible NSC-194308 binding poses to U2AF2, here, we applied and benchmarked the performance of static and dynamic docking approaches, elucidating the molecular basis of the NSC-194308-induced pre-mRNA stabilization on U2AF2. We demonstrate that introducing dynamic effects is mandatory to assess the binding mode of the inhibitors when they target plastic and modular architectures, such as those formed by interacting RRMs. The latter are widespread across RNA binding proteins; therefore, this mechanism may be broadly applicable to discover new therapeutics aimed at selectively modulating the RNA function by targeting protein/protein/RNA interfaces.

PTM-Psi: A python package to facilitate the computational investigation of post-translational modification on protein structures and their impacts on dynamics and functions

Post-translational modification (PTM) of a protein occurs after it has been synthesized from its genetic template, and involves chemical modifications of the protein's specific amino acid residues. Despite of the central role played by PTM in regulating molecular interactions, particularly those driven by reversible redox reactions, it remains challenging to interpret PTMs in terms of protein dynamics and function because there are numerous combinatorially enormous means for modifying amino acids in response to changes in the protein environment. In this study, we provide a workflow that allows users to interpret how perturbations caused by PTMs affect a protein's properties, dynamics, and interactions with its binding partners based on inferred or experimentally determined protein structure. This Python-based workflow, called PTM-Psi, integrates several established open-source software packages, thereby enabling the user to infer protein structure from sequence, develop force fields for non-standard amino acids using quantum mechanics, calculate free energy perturbations through molecular dynamics simulations, and score the bound complexes via docking algorithms. Using the S-nitrosylation of several cysteines on the GAP2 protein as an example, we demonstrated the utility of PTM-Psi for interpreting sequence-structure-function relationships derived from thiol redox proteomics data. We demonstrate that the S-nitrosylated cysteine that is exposed to the solvent indirectly affects the catalytic reaction of another buried cysteine over a distance in GAP2 protein through the movement of the two ligands. Our workflow tracks the PTMs on residues that are responsive to changes in the redox environment and lays the foundation for the automation of molecular and systems biology modeling.

Alchemical Calculation of Relative Free Energies for Charge-Changing Mutations at Protein-Protein Interfaces Considering Fixed and Variable Protonation States

The calculation of relative free energies (ΔΔG) for charge-changing mutations at protein-protein interfaces through alchemical methods remains challenging due to variations in the system's net charge during charging steps, the possibility of mutated and contacting ionizable residues occurring in various protonation states, and undersampling issues. In this study, we present a set of strategies, collectively termed TIRST/TIRST-H+, to address some of these challenges. Our approaches combine thermodynamic integration (TI) with the prediction of pKa shifts to calculate ΔΔG values. Moreover, special sets of restraints are employed to keep the alchemically transformed molecules separated. The accuracy of the devised approaches was assessed on a large and diverse data set comprising 164 point mutations of charged residues (Asp, Glu, Lys, and Arg) to Ala at the protein-protein interfaces of complexes with known three-dimensional structures. Mean absolute and root-mean-square errors ranging from 1.38 to 1.66 and 1.89 to 2.44 kcal/mol, respectively, and Pearson correlation coefficients of ∼0.6 were obtained when testing the approaches on the selected data set using the GPU-TI module of Amber18 suite and the ff14SB force field. Furthermore, the inclusion of variable protonation states for the mutated acid residues improved the accuracy of the predicted ΔΔG values. Therefore, our results validate the use of TIRST/TIRST-H+ in prospective studies aimed at evaluating the impact of charge-changing mutations to Ala on the stability of protein-protein complexes.

Why Na+ has higher propensity than K+ to condense DNA in a crowded environment

Experimentally, in the presence of the crowding agent polyethylene glycol (PEG), sodium ions compact double-stranded DNA more readily than potassium ions. Here, we have used molecular dynamics simulations and the "ion binding shells model" of DNA condensation to provide an explanation for the observed variations in condensation of short DNA duplexes in solutions containing different monovalent cations and PEG; several predictions are made. According to the model we use, externally bound ions contribute the most to the ion-induced aggregation of DNA duplexes. The simulations reveal that for two adjacent DNA duplexes, the number of externally bound Na+ ions is larger than the number of K+ ions over a wide range of chloride concentrations in the presence of PEG, providing a qualitative explanation for the higher propensity of sodium ions to compact DNA under crowded conditions. The qualitative picture is confirmed by an estimate of the corresponding free energy of DNA aggregation that is at least 0.2kBT per base pair more favorable in solution with NaCl than with KCl at the same ion concentration. The estimated attraction free energy of DNA duplexes in the presence of Na+ depends noticeably on the DNA sequence; we predict that AT-rich DNA duplexes are more readily condensed than GC-rich ones in the presence of Na+. Counter-intuitively, the addition of a small amount of a crowding agent with high affinity for the specific condensing ion may lead to the weakening of the ion-mediated DNA-DNA attraction, shifting the equilibrium away from the DNA condensed phase.

Intrinsic disorder and conformational coexistence in auxin coreceptors

AUXIN/INDOLE 3-ACETIC ACID (Aux/IAA) transcriptional repressor proteins and the TRANSPORT INHIBITOR RESISTANT 1/AUXIN SIGNALING F-BOX (TIR1/AFB) proteins to which they bind act as auxin coreceptors. While the structure of TIR1 has been solved, structural characterization of the regions of the Aux/IAA protein responsible for auxin perception has been complicated by their predicted disorder. Here, we use NMR, CD and molecular dynamics simulation to investigate the N-terminal domains of the Aux/IAA protein IAA17/AXR3. We show that despite the conformational flexibility of the region, a critical W-P bond in the core of the Aux/IAA degron motif occurs at a strikingly high (1:1) ratio of cis to trans isomers, consistent with the requirement of the cis conformer for the formation of the fully-docked receptor complex. We show that the N-terminal half of AXR3 is a mixture of multiple transiently structured conformations with a propensity for two predominant and distinct conformational subpopulations within the overall ensemble. These two states were modeled together with the C-terminal PB1 domain to provide the first complete simulation of an Aux/IAA. Using MD to recreate the assembly of each complex in the presence of auxin, both structural arrangements were shown to engage with the TIR1 receptor, and contact maps from the simulations match closely observations of NMR signal-decreases. Together, our results and approach provide a platform for exploring the functional significance of variation in the Aux/IAA coreceptor family and for understanding the role of intrinsic disorder in auxin signal transduction and other signaling systems.

Pathways of hLL-3717-29 Aggregation Give Insight into the Mechanism of α-Amyloid Formation

α-amyloids present a novel self-assembly principle that can be utilized to prepare functional biomaterials. Evidence of α-amyloid formation in the active core of the human LL-37 protein (comprising residues 17 to 29) was associated with this peptide's membranolytic property. Though mechanistic pathways of β-amyloid formation are known, such studies are scarce in α-amyloids. Modern computational techniques allow such mechanistic studies in molecular detail. Here, we propose aggregation pathways in hLL-3717-29 through molecular dynamics simulations. We first identified oligomers among peptides based on a distance criterion. The distribution of oligomers was then used to build Markov state models from which pathways were obtained using the framework of transition path theory. We checked the structural stability of the peptides during oligomerization, which is crucial from their functional point of view. We also investigated the key residues that participate in oligomer formation, the interactions between them, and the effect of residue mutations on the binding free energy of the peptides. Our findings suggest that larger oligomers are produced from the association of smaller and intermediate oligomers. The peptides retain their helical structure during aggregation with transient occurrences of 3-10 helix and turns. Hydrophobic interactions are vital in the aggregation of these peptides with Ile24 playing a crucial role. Mutation of this residue to alanine decreases the peptides' binding free energy, resulting in reduced aggregation tendency.

β-Sitosterol could serve as a dual inhibitor of Trypanosoma congolense sialidase and phospholipase A2: in vitro kinetic analyses and molecular dynamic simulations

The involvement of Trypanosoma congolense sialidase alongside phospholipase A2 has been widely accepted as the major contributing factor to anemia during African animal trypanosomiasis. The enzymes aid the parasite in scavenging sialic acid and fatty acids necessary for survival in the infected host, but there are no specific drug candidates against the two enzymes. This study investigated the inhibitory effects of β-sitosterol on the partially purified T. congolense sialidase and phospholipase A2. Purification of the enzymes using DEAE cellulose column led to fractions with highest specific activities of 8016.41 and 39.26 µmol/min/mg for sialidase and phospholipase A2, respectively. Inhibition kinetics studies showed that β-sitosterol is non-competitive and an uncompetitive inhibitor of sialidase and phospholipase A2 with inhibition binding constants of 0.368 and 0.549 µM, respectively. Molecular docking of the compound revealed binding energies of - 8.0 and - 8.6 kcal/mol against the sialidase and phospholipase A2, respectively. Furthermore, 100 ns molecular dynamics simulation using GROMACS revealed stable interaction of β-sitosterol with both enzymes. Hydrogen bond interactions between the ligand and Glu284 and Leu102 residues of the sialidase and phospholipase A2, respectively, were found to be the major stabilizing forces. In conclusion, β-sitosterol could serve as a dual inhibitor of T. congolense sialidase and phospholipase A2; hence, the compound could be exploited further in the search for newer trypanocides.

Characterization of cytoskeletal and structural effects of INF2 variants causing glomerulopathy and neuropathy

Focal segmental glomerulosclerosis (FSGS) is a common glomerular injury leading to end-stage renal disease. Monogenic FSGS is primarily ascribed to decreased podocyte integrity. Variants between residues 184 and 245 of INF2, an actin assembly factor, produce the monogenic FSGS phenotype. Meanwhile, variants between residues 57 and 184 cause a dual-faceted disease involving peripheral neurons and podocytes (Charcot-Marie-Tooth CMT/FSGS). To understand the molecular basis for INF2 disorders, we compared structural and cytoskeletal effects of INF2 variants classified into two subgroups: One (G73D, V108D) causes the CMT/FSGS phenotype, and the other (T161N, N202S) produces monogenic FSGS. Molecular dynamics analysis revealed that all INF2 variants show distinct flexibility compared to the wild-type INF2 and could affect stability of an intramolecular interaction between their N- and C-terminal segments. Immunocytochemistry of cells expressing INF2 variants showed fewer actin stress fibers, and disorganization of cytoplasmic microtubule arrays. Notably, CMT/FSGS variants caused more prominent changes in mitochondrial distribution and fragmentation than FSGS variants and these changes correlated with the severity of cytoskeletal disruption. Our results indicate that CMT/FSGS variants are associated with more severe global cellular defects caused by disrupted cytoskeleton-organelle interactions than are FSGS variants. Further study is needed to clarify tissue-specific pathways and/or cellular functions implicated in FSGS and CMT phenotypes.

Assessing the performance of docking, FEP, and MM/GBSA methods on a series of KLK6 inhibitors

Kallikrein 6 (KLK6) is an attractive drug target for the treatment of neurological diseases and for various cancers. Herein, we explore the accuracy and efficiency of different computational methods and protocols to predict the free energy of binding (ΔG_bind) for a series of 49 inhibitors of KLK6. We found that the performance of the methods varied strongly with the tested system. For only one of the three KLK6 datasets, the docking scores obtained with rDock were in good agreement (R² ≥ 0.5) with experimental values of ΔG_bind. A similar result was obtained with MM/GBSA (using the ff14SB force field) calculations based on single minimized structures. Improved binding affinity predictions were obtained with the free energy perturbation (FEP) method, with an overall MUE and RMSE of 0.53 and 0.68 kcal/mol, respectively. Furthermore, in a simulation of a real-world drug discovery project, FEP was able to rank the most potent compounds at the top of the list. These results indicate that FEP can be a promising tool for the structure-based optimization of KLK6 inhibitors.

Monovalent Ionic Atmosphere Modulates the Selection of Suboptimal RNA Sequences by Splicing Factors' RNA Recognition Motifs

The U2AF2 splicing factor is involved in the RNA recognition of the pre-mRNA poly-pyrimidine signaling sequence. This protein contains two RRM domains connected by a flexible linker, which ensure the preferential selection of a poly-uridine sequence over a poly-cytosine one. In this work, all-atom simulations provide insights into the U2AF2 recognition mechanism and on the features underlying its selectivity. Our outcomes show that U2AF2's RNA recognition is driven by cooperative events modulated by RNA-protein and RNA-ion interactions. Stunningly, monovalent ions contribute to mediating the binding of the weakly binding polyC strand, thus contributing to the selection of suboptimal poly-pyrimidine tracts. This finding broadens our understanding of the diverse traits tuning splicing factors' selectivity and adaptability to precisely handle and process diverse pre-mRNA sequences.

The E2 glycoprotein holds key residues for Mayaro virus adaptation to the urban Aedes aegypti mosquito

Adaptation to mosquito vectors suited for transmission in urban settings is a major driver in the emergence of arboviruses. To better anticipate future emergence events, it is crucial to assess their potential to adapt to new vector hosts. In this work, we used two different experimental evolution approaches to study the adaptation process of an emerging alphavirus, Mayaro virus (MAYV), to Ae. aegypti, an urban mosquito vector of many other arboviruses. We identified E2-T179N as a key mutation increasing MAYV replication in insect cells and enhancing transmission after escaping the midgut of live Ae. aegypti. In contrast, this mutation decreased viral replication and binding in human fibroblasts, a primary cellular target of MAYV in humans. We also showed that MAYV E2-T179N generates reduced viremia and displays less severe tissue pathology in vivo in a mouse model. We found evidence in mouse fibroblasts that MAYV E2-T179N is less dependent on the Mxra8 receptor for replication than WT MAYV. Similarly, exogenous expression of human apolipoprotein receptor 2 and Mxra8 enhanced WT MAYV replication compared to MAYV E2-T179N. When this mutation was introduced in the closely related chikungunya virus, which has caused major outbreaks globally in the past two decades, we observed increased replication in both human and insect cells, suggesting E2 position 179 is an important determinant of alphavirus host-adaptation, although in a virus-specific manner. Collectively, these results indicate that adaptation at the T179 residue in MAYV E2 may result in increased vector competence-but coming at the cost of optimal replication in humans-and may represent a first step towards a future emergence event.

Switching from Aromatase Inhibitors to Dual Targeting Flavonoid-Based Compounds for Breast Cancer Treatment

Despite the significant outcomes attained by scientific research, breast cancer (BC) still represents the second leading cause of death in women. Estrogen receptor-positive (ER+) BC accounts for the majority of diagnosed BCs, highlighting the disruption of estrogenic signalling as target for first-line treatment. This goal is presently pursued by inhibiting aromatase (AR) enzyme or by modulating Estrogen Receptor (ER) α. An appealing strategy for fighting BC and reducing side effects and resistance issues may lie in the design of multifunctional compounds able to simultaneously target AR and ER. In this paper, previously reported flavonoid-related potent AR inhibitors were suitably modified with the aim of also targeting ERα. As a result, homoisoflavone derivatives 3b and 4a emerged as well-balanced submicromolar dual acting compounds. An extensive computational study was then performed to gain insights into the interactions the best compounds established with the two targets. This study highlighted the feasibility of switching from single-target compounds to balanced dual-acting agents, confirming that a multi-target approach may represent a valid therapeutic option to counteract ER+ BC. The homoisoflavone core emerged as a valuable natural-inspired scaffold for the design of multifunctional compounds.

Molecular Basis of RNA-Driven ATP Hydrolysis in DExH-Box Helicases

The spliceosome machinery catalyzes precursor messenger (pre-m)RNA splicing. In each cycle, the spliceosome experiences massive compositional and conformational remodeling fueled by the concerted action of specific RNA-dependent ATPases/helicases. Intriguingly, these enzymes are allosterically activated to perform ATP hydrolysis and trigger helicase activity only upon pre-mRNA binding. Yet, the molecular mechanism underlying the RNA-driven regulation of their ATPase function remains elusive. Here, we focus on the Prp2 ATPase/helicase which contributes to reshaping the spliceosome into its catalytic competent state. By performing classical and quantum-classical molecular dynamics simulations, we unprecedentedly unlock the molecular terms governing the Prp2 ATPase/helicase function. Namely, we dissect the molecular mechanism of ATP hydrolysis, and we disclose that RNA binding allosterically triggers the formation of a set of interactions linking the RNA binding tunnel to the catalytic site. This activates the Prp2's ATPase function by optimally placing the nucleophilic water and the general base of the enzymatic process to perform ATP hydrolysis. The key structural motifs, mechanically coupling RNA gripping and the ATPase/helicase functions, are conserved across all DExH-box helicases. This mechanism could thus be broadly applicable to all DExH-box helicase family.

Computer-Assisted Design and Characterization of RNA Nanostructures

Molecular dynamics (MD) simulations can aid in the design and characterization of RNA nanomaterials, providing details about structural and dynamical properties as a function of sequence and environment. Here, we describe how to perform explicit and implicit solvent all-atom MD simulations for RNA nanoring systems.

Predicting molecular properties of α-synuclein using force fields for intrinsically disordered proteins

Independent force field validation is an essential practice to keep track of developments and for performing meaningful Molecular Dynamics simulations. In this work, atomistic force fields for intrinsically disordered proteins (IDP) are tested by simulating the archetypical IDP α-synuclein in solution for 2.5 μs. Four combinations of protein and water force fields were tested: ff19SB/OPC, ff19SB/TIP4P-D, ff03CMAP/TIP4P-D, and a99SB-disp/TIP4P-disp, with four independent repeat simulations for each combination. We compare our simulations to the results of a 73 μs simulation using the a99SB-disp/TIP4P-disp combination, provided by D. E. Shaw Research. From the trajectories, we predict a range of experimental observations of α-synuclein and compare them to literature data. This includes protein radius of gyration and hydration, intramolecular distances, NMR chemical shifts, and ³ J-couplings. Both ff19SB/TIP4P-D and a99SB-disp/TIP4P-disp produce extended conformational ensembles of α-synuclein that agree well with experimental radius of gyration and intramolecular distances while a99SB-disp/TIP4P-disp reproduces a balanced α-synuclein secondary structure content. It was found that ff19SB/OPC and ff03CMAP/TIP4P-D produce overly compact conformational ensembles and show discrepancies in the secondary structure content compared to the experimental data.

Stomatal CO2/bicarbonate sensor consists of two interacting protein kinases, Raf-like HT1 and non-kinase-activity requiring MPK12/MPK4

The continuing rise in the atmospheric carbon dioxide (CO₂) concentration causes stomatal closing, thus critically affecting transpirational water loss, photosynthesis, and plant growth. However, the primary CO₂ sensor remains unknown. Here, we show that elevated CO₂ triggers interaction of the MAP kinases MPK4/MPK12 with the HT1 protein kinase, thus inhibiting HT1 kinase activity. At low CO₂, HT1 phosphorylates and activates the downstream negatively regulating CBC1 kinase. Physiologically relevant HT1-mediated phosphorylation sites in CBC1 are identified. In a genetic screen, we identify dominant active HT1 mutants that cause insensitivity to elevated CO₂. Dominant HT1 mutants abrogate the CO₂/bicarbonate-induced MPK4/12-HT1 interaction and HT1 inhibition, which may be explained by a structural AlphaFold2- and Gaussian-accelerated dynamics-generated model. Unexpectedly, MAP kinase activity is not required for CO₂ sensor function and CO₂-triggered HT1 inhibition and stomatal closing. The presented findings reveal that MPK4/12 and HT1 together constitute the long-sought primary stomatal CO₂/bicarbonate sensor upstream of the CBC1 kinase in plants.

Mechanisms of Electron Transfer Rate Modulations in Cytochrome P450 BM3

Bacterial cytochromes P450 BM3 (CYP450 BM3) catalyze reactions of industrial importance. Despite many successful biotransformations, robust (re)design for novel applications remains challenging. Rational design and evolutionary approaches are not always successful, highlighting a lack of complete understanding of the mechanisms of electron transfer (ET) modulations. Thus, the full potential of CYP450 reactions remains under-exploited. In this work, we report the first molecular dynamics (MD)-based explicit prediction of BM3 ET parameters (reorganization energies; λ and ET free energies; ΔG°), and log ET rates (log k_ET) using the Marcus theory. Overall, the calculated ET rates for the BM3 wild-type (WT), mutants (F393 and L86), ligand-bound state, and ion concentrations agree well with experimental data. In ligand-free (LF) BM3, mutations modulate k_ET via ET ΔG°. Simulations show that the experimental ET rate enhancement is due to increased driving force (more negative ΔG°) upon ligation. This increase is related to the protein reorganization required to accommodate the ligand in the binding pocket rather than binding interactions with the ligand. Our methodology (CYPWare 1.0) automates all the stages of the MD simulation step-up, energy calculations, and estimation of ET parameters. CYPWare 1.0 and this work thus represent an important advancement in the CYP450 ET rate predictions, which has the potential to guide the redesign of ET enzymes. This program and a Web tool are available on GitHub for academic research.

Study of trioleoylglycerol two-layer and adiposome cross-section mimicking four-layer systems through atomic-level simulations

Adiposomes are artificially prepared lipid droplet (LD)-mimetic structures, which, unlike LDs, do not harbor proteins. The dynamics of interaction between triacylglycerols (TAGs), drug molecule, and phospholipids in adiposomes is currently not well-established. Trioleoylglycerol (TOG) molecule was divided into three parts: two oleoyl tails and one 2-monooleoylglycerol (MOG). Forcefield parameters for two oleoyl tails were adopted from the AMBER18 repository while that of the MOG forcefield was taken from the literature. Charge correction was performed on the MOG forcefield before its utilization. After charge correction, the resulting TOG molecule had zero charge. TOG bilayer (2L) and tetralayer (4L) systems were prepared and simulated. TOG bilayer (2L) systems-modeled from two different initial conformations, the TOG3 conformation and the TOG2:1 conformation-showed that TOG2:1 conformation was more prevailing irrespective of the starting conformation and was subsequently used in further simulations. The hydrated TOG 2L system showed TOG-water solution solubility of 0.051 mol L^-1 which is near experimental values. This validated the correct parameterization of the TOG molecule. The simulations of 4L systems showed stable membrane behaviors toward the end of simulations. It was also observed that in the 4L system, the TOG molecules showed the formation of micelles with the drug molecule. Almost six TOGs remained continuously in contact with the drug molecule throughout the simulation. The availability of charge-corrected TOG parameterization is expected to equip future studies with a framework for molecular dynamics simulations of adiposomes and/or LDs at the atomic level.

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.

Mebendazole's Conformational Space and Its Predicted Binding to Human Heat-Shock Protein 90

Recent experimental evidence suggests that mebendazole, a popular antiparasitic drug, binds to heat shock protein 90 (Hsp90) and inhibits acute myeloid leukemia cell growth. In this study we use quantum mechanics (QM), molecular similarity, and molecular dynamics (MD) calculations to predict possible binding poses of mebendazole to the adenosine triphosphate (ATP) binding site of Hsp90. Extensive conformational searches and minimization of the five mebendazole tautomers using the MP2/aug-cc-pVTZ theory level resulted in 152 minima. Mebendazole-Hsp90 complex models were subsequently created using the QM optimized conformations and protein coordinates obtained from experimental crystal structures that were chosen through similarity calculations. Nine different poses were identified from a total of 600 ns of explicit solvent, all-atom MD simulations using two different force fields. All simulations support the hypothesis that mebendazole is able to bind to the ATP binding site of Hsp90.

Sequence and Structure-Guided Engineering of Urethanase from Agrobacterium tumefaciens d3 for Improved Catalytic Activity

The amidase from Agrobacterium tumefaciens d3 (AmdA) degrades the carcinogenic ethyl carbamate (EC) in alcoholic beverages. However, its limited catalytic activity hinders practical applications. Here, multiple sequence alignment was first used to predict single variants with improved activity. Afterward, AlphaFold 2 was applied to predict the three-dimensional structure of AmdA and 21 amino acids near the catalytic triad were randomized by saturation mutagenesis. Each of the mutation libraries was then screened, and the improved single variants were combined to obtain the best double variant I97L/G195A that showed a 3.1-fold increase in the urethanase activity and a 1.5-fold increase in ethanol tolerance. MD simulations revealed that the mutations shortened the distance between catalytic residues and the substrate and enhanced the occurrence of a critical hydrogen bond in the catalytic pocket. This study displayed a useful strategy to engineer an amidase for the improvement of urethanase activity, and the variant obtained provided a good candidate for applications in the food industry.

Pre-mRNA splicing factor U2AF2 recognizes distinct conformations of nucleotide variants at the center of the pre-mRNA splice site signal

The essential pre-mRNA splicing factor U2AF2 (also called U2AF65) identifies polypyrimidine (Py) tract signals of nascent transcripts, despite length and sequence variations. Previous studies have shown that the U2AF2 RNA recognition motifs (RRM1 and RRM2) preferentially bind uridine-rich RNAs. Nonetheless, the specificity of the RRM1/RRM2 interface for the central Py tract nucleotide has yet to be investigated. We addressed this question by determining crystal structures of U2AF2 bound to a cytidine, guanosine, or adenosine at the central position of the Py tract, and compared U2AF2-bound uridine structures. Local movements of the RNA site accommodated the different nucleotides, whereas the polypeptide backbone remained similar among the structures. Accordingly, molecular dynamics simulations revealed flexible conformations of the central, U2AF2-bound nucleotide. The RNA binding affinities and splicing efficiencies of structure-guided mutants demonstrated that U2AF2 tolerates nucleotide substitutions at the central position of the Py tract. Moreover, enhanced UV-crosslinking and immunoprecipitation of endogenous U2AF2 in human erythroleukemia cells showed uridine-sensitive binding sites, with lower sequence conservation at the central nucleotide positions of otherwise uridine-rich, U2AF2-bound splice sites. Altogether, these results highlight the importance of RNA flexibility for protein recognition and take a step towards relating splice site motifs to pre-mRNA splicing efficiencies.

Benchmarking ensemble docking methods in D3R Grand Challenge 4

The discovery of new drugs is a time consuming and expensive process. Methods such as virtual screening, which can filter out ineffective compounds from drug libraries prior to expensive experimental study, have become popular research topics. As the computational drug discovery community has grown, in order to benchmark the various advances in methodology, organizations such as the Drug Design Data Resource have begun hosting blinded grand challenges seeking to identify the best methods for ligand pose-prediction, ligand affinity ranking, and free energy calculations. Such open challenges offer a unique opportunity for researchers to partner with junior students (e.g., high school and undergraduate) to validate basic yet fundamental hypotheses considered to be uninteresting to domain experts. Here, we, a group of high school-aged students and their mentors, present the results of our participation in Grand Challenge 4 where we predicted ligand affinity rankings for the Cathepsin S protease, an important protein target for autoimmune diseases. To investigate the effect of incorporating receptor dynamics on ligand affinity rankings, we employed the Relaxed Complex Scheme, a molecular docking method paired with molecular dynamics-generated receptor conformations. We found that Cathepsin S is a difficult target for molecular docking and we explore some advanced methods such as distance-restrained docking to try to improve the correlation with experiments. This project has exemplified the capabilities of high school students when supported with a rigorous curriculum, and demonstrates the value of community-driven competitions for beginners in computational drug discovery.

Inactive-to-Active Transition of Human Thymidine Kinase 1 Revealed by Molecular Dynamics Simulations

Despite its importance in the nucleoside (and nucleoside prodrug) metabolism, the structure of the active conformation of human thymidine kinase 1 (hTK1) remains elusive. We perform microsecond molecular dynamics simulations of the inactive enzyme form bound to a bisubstrate inhibitor that was shown experimentally to activate another TK1-like kinase, Thermotoga maritima TK (TmTK). Our results are in excellent agreement with the experimental findings for the TmTK closed-to-open state transition. We show that the inhibitor induces an increase of the enzyme radius of gyration due to the expansion on one of the dimer interfaces; the structural changes observed, including the active site pocket volume increase and the decrease in the monomer-monomer buried surface area and of the number of hydrogen bonds (as compared to the inactive enzyme control simulation), indicate that the catalytically competent (open) conformation of hTK1 can be assumed in the presence of an activating ligand.

Similarities and Differences between Na+ and K+ Distributions around DNA Obtained with Three Popular Water Models

We have compared distributions of sodium and potassium ions around double-stranded DNA, simulated using fixed charge SPC/E, TIP3P, and OPC water models and the Joung/Cheatham (J/C) ion parameter set, as well as the Li/Merz HFE 6-12 (L/M HFE) ion parameters for OPC water. In all the simulations, the ion distributions are in qualitative agreement with Manning's condensation theory and the Debye-Hückel theory, where expected. In agreement with experiment, binding affinity of monovalent ions to DNA does not depend on ion type in every solvent model. However, behavior of deeply bound ions, including ions bound to specific sites, depends strongly on the solvent model. In particular, the number of potassium ions in the minor groove of AT-tracts differs at least 3-fold between the solvent models tested. The number of sodium ions associated with the DNA agrees quantitatively with the experiment for the OPC water model, followed closely by TIP3P+J/C; the largest deviation from the experiment, ∼10%, is seen for SPC/E+J/C. On the other hand, SPC/E+J/C model is most consistent (67%) with the experimental potassium binding sites, followed by OPC+J/C (60%), TIP3P+J/C (53%), and OPC+L/M HFE (27%). The use of NBFIX correction with TIP3P+J/C improves its consistency with the experiment. In summary, the choice of the solvent model matters little for simulating the diffuse atmosphere of sodium and potassium ions around DNA, but ion distributions become increasingly sensitive to the solvent model near the helical axis. We offer an explanation for these trends. There is no single gold standard solvent model, although OPC water with J/C ions or TIP3P with J/C + NBFIX may offer an imperfect compromise for practical simulations of ionic atmospheres around DNA.

The protonation state of Glu202 in acetylcholinesterase

Acetylcholinesterase (AChE) is the crucial enzyme in the central nervous system. It is the target of various organophosphorus nerve agents and pesticides, and the inhibition of AChE is a therapeutic strategy for the treatment of various neurological-related diseases. The Glu202 is a key residue adjacent to the catalytic His447 and plays important role in catalysis. Although the Glu202 has long been considered as negatively charged in many studies, more and more evidences support a protonated Glu202. However, Glu202 is freely accessible by solvent, and thus it seems more reasonable for Glu202 to majorly take the deprotonated state. In the present work, we carried out a series of molecular dynamics simulations with the Glu202 adopting different protonation states. Our results show that the protonated Glu202 is important in maintaining the key hydrogen bond network that supports the catalytic triad, whereas the deprotonated Glu202 results in the collapse of the key hydrogen bond network which consequently destabilizes the catalytic His447. We also notice that different protonation states of Glu202 merely alters the binding mode of ACh. However, since the catalytic His447 is disrupted if Glu202 is deprotonated, His447 cannot facilitate the nucleophilic attack performed by Ser203. Therefore, the catalytic efficiency of ACh hydrolysis should be remarkably decreased if Glu202 is deprotonated. Our findings suggest that, when designing and developing highly active AChE inhibitors or proposing mechanistic hypotheses for AChE-catalyzed reactions, the protonated state of Glu202 should be considered.

Structure-Guided Rational Design of a Mono- and Diacylglycerol Lipase from Aspergillus oryzae: A Single Residue Mutant Increases the Hydrolysis Ability

Engineering of enzymes on the basis of protein structures are rational and efficient approaches to acquire biocatalysts of desired performances. In this study, we focused on a special mono- and diacylglycerol lipase (MDGL) isolated from the lipolytic enzyme-enriched fungus Aspergillus oryzae and discovered improved variants based on its crystal structure. We first solved the crystal structure of Aspergillus oryzae lipase (AOL) at 1.7 Å resolution. Structure analysis and sequence alignment of AOL and other MDGLs revealed that the residue V269 is of vital importance for catalysis. Replacement of the V269 in AOL with the corresponding residues in other MDGLs has led to noticeable changes in hydrolysis without sacrificing the thermostability and substrate specificity. Among the investigated variants, V269D exhibited about a six-fold higher hydrolysis activity compared to the wild type. Molecular dynamics simulations and protein-ligand interaction frequency analyses revealed that the Asp substitution enhanced the substrate affinity of AOL. Our work sheds light on understanding the catalytic process of AOL and helps tailoring MDGLs with desired catalytic performance to fulfill the demand for biotechnological applications.

In Silico Prediction of the Binding, Folding, Insertion, and Overall Stability of Membrane-Active Peptides

Membrane-active peptides (MAPs) are short-length peptides used for potential biomedical applications in diagnostic imaging of tissues, targeted drug delivery, gene delivery, and antimicrobials and antibiotics. The broad appeal of MAPs is that they are infinitely variable, relatively low cost, and biocompatible. However, experimentally characterizing the specific properties of a MAP or its many variants is a low-resolution and potentially time-consuming endeavor; molecular dynamics (MD) simulations have emerged as an invaluable tool in identifying the biophysical interactions that are fundamental to the function of MAPs. In this chapter, a step-by-step approach to discreetly model the binding, folding, and insertion of a membrane-active peptide to a model lipid bilayer using MD simulations is described. Detailed discussion is devoted to the critical aspects of running these types of simulations: prior knowledge of the system, understanding the strengths and weaknesses of molecular mechanics force fields, proper construction and equilibration of the system, realistically estimating both experimental and computational timescales, and leveraging analysis to make direct comparisons to experimental results as often as possible.

Desmosome architecture derived from molecular dynamics simulations and cryo-electron tomography

The desmosome is a major cell–cell junction connecting cells in tissues under high mechanical load. Currently, while structures of the constituent cadherins are known, the desmosome architecture has remained elusive. The primary reason is the high plasticity of the cadherins. As many other cellular structures, their high flexibility cannot be easily addressed by conventional structural techniques that rely on averaging many identical structures. For this, we combine high-end cryo-electron tomography with large-scale molecular dynamics simulations to produce a molecular model of the desmosome that integrates new with decades-old observations, accounts for the remarkable biophysical properties, and maps the intermolecular interactions.

Desmosomes are cell–cell junctions that link tissue cells experiencing intense mechanical stress. Although the structure of the desmosomal cadherins is known, the desmosome architecture—which is essential for mediating numerous functions—remains elusive. Here, we recorded cryo-electron tomograms (cryo-ET) in which individual cadherins can be discerned; they appear variable in shape, spacing, and tilt with respect to the membrane. The resulting sub-tomogram average reaches a resolution of ∼26 Å, limited by the inherent flexibility of desmosomes. To address this challenge typical of dynamic biological assemblies, we combine sub-tomogram averaging with atomistic molecular dynamics (MD) simulations. We generate models of possible cadherin arrangements and perform an in silico screening according to biophysical and structural properties extracted from MD simulation trajectories. We find a truss-like arrangement of cadherins that resembles the characteristic footprint seen in the electron micrograph. The resulting model of the desmosomal architecture explains their unique biophysical properties and strength.

Interfacial water and ion distribution determine ζ potential and binding affinity of nanoparticles to biomolecules

The molecular features that dictate interactions between functionalized nanoparticles and biomolecules are not well understood. This is in part because for highly charged nanoparticles in solution, establishing a clear connection between the molecular features of surface ligands and common experimental observables such as ζ potential requires going beyond the classical models based on continuum and mean field models. Motivated by these considerations, molecular dynamics simulations are used to probe the electrostatic properties of functionalized gold nanoparticles and their interaction with a charged peptide in salt solutions. Counterions are observed to screen the bare ligand charge to a significant degree even at the moderate salt concentration of 50 mM. As a result, the apparent charge density and ζ potential are largely insensitive to the bare ligand charge densities, which fall in the range of ligand densities typically measured experimentally for gold nanoparticles. While this screening effect was predicted by classical models such as the Manning condensation theory, the magnitudes of the apparent surface charge from microscopic simulations and mean-field models are significantly different. Moreover, our simulations found that the chemical features of the surface ligand (e.g., primary vs. quaternary amines, heterogeneous ligand lengths) modulate the interfacial ion and water distributions and therefore the interfacial potential. The importance of interfacial water is further highlighted by the observation that introducing a fraction of hydrophobic ligands enhances the strength of electrostatic binding of the charged peptide. Finally, the simulations highlight that the electric double layer is perturbed upon binding interactions. As a result, it is the bare charge density rather than the apparent charge density or ζ potential that better correlates with binding affinity of the nanoparticle to a charged peptide. Overall, our study highlights the importance of molecular features of the nanoparticle/water interface and underscores a set of design rules for the modulation of electrostatic driven interactions at nano/bio interfaces.

Analysis of a preQ1-I riboswitch in effector-free and bound states reveals a metabolite-programmed nucleobase-stacking spine that controls gene regulation

Riboswitches are structured RNA motifs that recognize metabolites to alter the conformations of downstream sequences, leading to gene regulation. To investigate this molecular framework, we determined crystal structures of a preQ1-I riboswitch in effector-free and bound states at 2.00 Å and 2.65 Å-resolution. Both pseudoknots exhibited the elusive L2 loop, which displayed distinct conformations. Conversely, the Shine-Dalgarno sequence (SDS) in the S2 helix of each structure remained unbroken. The expectation that the effector-free state should expose the SDS prompted us to conduct solution experiments to delineate environmental changes to specific nucleobases in response to preQ1. We then used nudged elastic band computational methods to derive conformational-change pathways linking the crystallographically-determined effector-free and bound-state structures. Pathways featured: (i) unstacking and unpairing of L2 and S2 nucleobases without preQ1-exposing the SDS for translation and (ii) stacking and pairing L2 and S2 nucleobases with preQ1-sequestering the SDS. Our results reveal how preQ1 binding reorganizes L2 into a nucleobase-stacking spine that sequesters the SDS, linking effector recognition to biological function. The generality of stacking spines as conduits for effector-dependent, interdomain communication is discussed in light of their existence in adenine riboswitches, as well as the turnip yellow mosaic virus ribosome sensor.

Mycobacterium tuberculosis FasR senses long fatty acyl-CoA through a tunnel and a hydrophobic transmission spine

Mycobacterium tuberculosis is a pathogen with a unique cell envelope including very long fatty acids, implicated in bacterial resistance and host immune modulation. FasR is a TetR-like transcriptional activator that plays a central role in sensing mycobacterial long-chain fatty acids and regulating lipid biosynthesis. Here we disclose crystal structures of M. tuberculosis FasR in complex with acyl effector ligands and with DNA, uncovering its molecular sensory and switching mechanisms. A long tunnel traverses the entire effector-binding domain, enabling long fatty acyl effectors to bind. Only when the tunnel is entirely occupied, the protein dimer adopts a rigid configuration with its DNA-binding domains in an open state, leading to DNA dissociation. The protein-folding hydrophobic core connects the two domains, and is completed into a continuous spine when the effector binds. Such a transmission spine is conserved in a large number of TetR-like regulators, offering insight into effector-triggered allosteric functional control.

FasR is a TetR-like transcriptional activator that plays a central role in sensing mycobacterial long-chain fatty acids and regulating lipid biosynthesis in Mycobacterium tuberculosis. Here authors present crystal structures of M. tuberculosis FasR in complex with acyl effector ligands and with DNA, uncovering its molecular sensory and switching mechanisms.

Web-ARM: A Web-Based Interface for the Automatic Construction of QM/MM Models of Rhodopsins

This article introduces Web-ARM, a specialized tool, online available, designed to build quantum mechanical/molecular mechanical models of rhodopsins, a widely spread family of light-responsive proteins. Web-ARM allows the rapidly building of models of rhodopsins with a documented quality and the prediction of trends in UV-vis absorption maximum wavelengths, based on their excitation energies computed at the CASPT2//CASSCF/Amber level of theory. Web-ARM builds upon the recently reported, python-based a-ARM protocol [J. Chem. Theory Comput., 2019, 15, 3134-3152] and, as such, necessitates only a crystallographic structure or a comparative model in PDB format and a very basic knowledge of the studied rhodopsin system. The user-friendly web interface uses such input to generate congruous, gas-phase models of rhodopsins and, if requested, their mutants. We present two possible applications of Web-ARM, which showcase how the interface can be employed to assist both research and educational activities in fields at the interface between chemistry and biology. The first application shows how, through Web-ARM, research projects (e.g., rhodopsin and rhodopsin mutant screening) can be carried out in significantly less time with respect to using the required computational photochemistry tools via a command line. The second application documents the use of Web-ARM in a real-life educational/training activity, through a hands-on experience illustrating the concepts of rhodopsin color tuning.

Split the Charge Difference in Two! A Rule of Thumb for Adding Proper Amounts of Ions in MD Simulations

Despite the relevance of properly setting ionic concentrations in Molecular Dynamics (MD) simulations, methods or practical rules to set ionic strength are scarce and rarely documented. Based on a recently proposed thermodynamics method we provide an accurate rule of thumb to define the electrolytic content in simulation boxes. Extending the use of good practices in setting up MD systems is promptly needed to ensure reproducibility and consistency in molecular simulations.

Effects of non-pairwise repulsion on nanoparticle assembly

Electrostatic interactions provide a convenient way to modulate interactions between nanoparticles, colloids, and biomolecules because they can be adjusted by the solution pH or salt concentration. While the presence of salt provides an easy method to control the net interparticle interaction, the nonlinearities arising from electrostatic screening make it difficult to quantify the strength of the interaction. In particular, when charged particles assemble into clusters or aggregates, nonlinear effects render the interactions strongly non-pairwise. Here, we report Brownian dynamics simulations to investigate the effect that the non-pairwise nature of electrostatic interactions has on nanoparticle assembly. We compare these simulations to a system in which the electrostatics are modeled by a strictly pairwise Yukawa potential. We find that both systems show a narrow range in parameter space where the particles form well-ordered crystals. Bordering this range are regions where the net interactions are too weak to stabilize aggregated structures or strong enough that the system becomes kinetically trapped in a gel. The non-pairwise potential differs from the pairwise system in the appearance of an amorphous state for strongly charged particles. This state appears because the many-body electrostatic interactions limit the maximum density achievable in an assembly.