Molecular dynamics in multidimensional space explains how mutations affect the association path of neomycin to a riboswitch.

Riboswitches are messenger RNA (mRNA) fragments binding specific small molecules to regulate gene expression. A synthetic N1 riboswitch, inserted into yeast mRNA controls the translation of a reporter gene in response to neomycin. However, its regulatory activity is sensitive to single-point RNA mutations, even those distant from the neomycin binding site. While the association paths of neomycin to N1 and its variants remain unknown, recent fluorescence kinetic experiments indicate a two-step process driven by conformational selection. This raises the question of which step is affected by mutations. To address this, we performed all-atom two-dimensional replica-exchange molecular dynamics simulations for N1 and U14C, U14C[Formula: see text], U15A, and A17G mutants, ensuring extensive conformational sampling of both RNA and neomycin. The obtained neomycin association and binding paths, along with multidimensional free-energy profiles, revealed a two-step binding mechanism, consisting of conformational selection and induced fit. Neomycin binds to a preformed N1 conformation upon identifying a stable upper stem and U-turn motif in the riboswitch hairpin. However, the positioning of neomycin in the binding site occurs at different RNA-neomycin distances for each mutant, which may explain their different regulatory activities. The subsequent induced fit arises from the interactions of the neomycin's N3 amino group with RNA, causing the G9 backbone to rearrange. In the A17G mutant, the critical C6-A17/G17 stacking forms at a closer RNA-neomycin distance compared to N1. These findings together with estimated binding free energies coincide with experiments and elucidate why the A17G mutation decreases and U15A enhances N1 activity in response to neomycin.

Highly parallelizable path sampling with minimal rejections using asynchronous replica exchange and infinite swaps.

Capturing rare yet pivotal events poses a significant challenge for molecular simulations. Path sampling provides a unique approach to tackle this issue without altering the potential energy landscape or dynamics, enabling recovery of both thermodynamic and kinetic information. However, despite its exponential acceleration compared to standard molecular dynamics, generating numerous trajectories can still require a long time. By harnessing our recent algorithmic innovations-particularly subtrajectory moves with high acceptance, coupled with asynchronous replica exchange featuring infinite swaps-we establish a highly parallelizable and rapidly converging path sampling protocol, compatible with diverse high-performance computing architectures. We demonstrate our approach on the liquid-vapor phase transition in superheated water, the unfolding of the chignolin protein, and water dissociation. The latter, performed at the ab initio level, achieves comparable statistical accuracy within days, in contrast to a previous study requiring over a year.

De novo protein fold design through sequence-independent fragment assembly simulations.

De novo protein design generally consists of two steps, including structure and sequence design. Many protein design studies have focused on sequence design with scaffolds adapted from native structures in the PDB, which renders novel areas of protein structure and function space unexplored. We developed FoldDesign to create novel protein folds from specific secondary structure (SS) assignments through sequence-independent replica-exchange Monte Carlo (REMC) simulations. The method was tested on 354 non-redundant topologies, where FoldDesign consistently created stable structural folds, while recapitulating on average 87.7% of the SS elements. Meanwhile, the FoldDesign scaffolds had well-formed structures with buried residues and solvent-exposed areas closely matching their native counterparts. Despite the high fidelity to the input SS restraints and local structural characteristics of native proteins, a large portion of the designed scaffolds possessed global folds completely different from natural proteins in the PDB, highlighting the ability of FoldDesign to explore novel areas of protein fold space. Detailed data analyses revealed that the major contributions to the successful structure design lay in the optimal energy force field, which contains a balanced set of SS packing terms, and REMC simulations, which were coupled with multiple auxiliary movements to efficiently search the conformational space. Additionally, the ability to recognize and assemble uncommon super-SS geometries, rather than the unique arrangement of common SS motifs, was the key to generating novel folds. These results demonstrate a strong potential to explore both structural and functional spaces through computational design simulations that natural proteins have not reached through evolution.

Classification of PTEN missense VUS through exascale simulations.

Phosphatase and tensin homolog (PTEN), a tumor suppressor with dual phosphatase properties, is a key factor in PI3K/AKT signaling pathway. Pathogenic germline variation in PTEN can abrogate its ability to dephosphorylate, causing high cancer risk. Lack of functional evidence lets numerous PTEN variants be classified as variants of uncertain significance (VUS). Utilizing Molecular Dynamics (MD) simulations, we performed a thorough evaluation for 147 PTEN missense VUS, sorting them into 66 deleterious and 81 tolerated variants. Utilizing replica exchange molecular dynamic (REMD) simulations, we further assessed the variants situated in the catalytic core of PTEN's phosphatase domain and uncovered conformational alterations influencing the structural stability of the phosphatase domain. There was a high degree of agreement between our results and the variants classified by Variant Abundance by Massively Parallel Sequencing, saturation mutagenesis, multiplexed functional data and experimental assays. Our extensive analysis of PTEN missense VUS should benefit their clinical applications in PTEN-related cancer. SIGNIFICANCE STATEMENT: Classification of PTEN variants affecting its lipid phosphatase activity is important for understanding the roles of PTEN variation in the pathogenesis of hereditary and sporadic malignancies. Of the 3000 variants identified in PTEN, 1296 (43%) were assigned as VUS. Here, we applied MD and REMD simulations to investigate the effects of PTEN missense VUS on the structural integrity of the PTEN phosphatase domain consisting the WPD, P and TI active sites. We classified a total of 147 missense VUS into 66 deleterious and 81 tolerated variants by referring to the control group comprising 54 pathogenic and 12 benign variants. The classification was largely in concordance with these classified by experimental approaches.

Computational investigation of the inhibitory interaction of IRF3 and SARS-CoV-2 accessory protein ORF3b.

ORF3b is one of the SARS-CoV-2 accessory proteins. Previous experimental study suggested that ORF3b prevents IRF3 translocating to nucleus. However, the biophysical mechanism of ORF3b-IRF3 interaction is elusive. Here, we explored the conformation ensemble of ORF3b using all-atom replica exchange molecular dynamics simulation. Disordered ORF3b has mixed α-helix, ß-turn and loop conformers. The potential ORF3b-IRF3 binding modes were searched by docking representative ORF3b conformers with IRF3, and 50 ORF3b-IRF3 complex poses were screened using molecular dynamics simulations ranging from 500 to 1000 ns. We found that ORF3b binds IRF3 predominantly on its CBP binding and phosphorylated pLxIS motifs, with CBP binding site has the highest binding affinity. The ORF3b-IRF3 binding residues are highly conserved in SARS-CoV-2. Our results provided biophysics insights into ORF3b-IRF3 interaction and explained its interferon antagonism mechanism.

Proton strings and rings in atypical nucleation of ferroelectricity in ice.

Ordinary ice has a proton-disordered phase which is kinetically metastable, unable to reach, spontaneously, the ferroelectric (FE) ground state at low temperature where a residual Pauling entropy persists. Upon light doping with KOH at low temperature, the transition to FE ice takes place, but its microscopic mechanism still needs clarification. We introduce a lattice model based on dipolar interactions plus a competing, frustrating term that enforces the ice rule (IR). In the absence of IR-breaking defects, standard Monte Carlo (MC) simulation leaves this ice model stuck in a state of disordered proton ring configurations with the correct Pauling entropy. A replica exchange accelerated MC sampling strategy succeeds, without open path moves, interfaces, or off-lattice configurations, in equilibrating this defect-free ice, reaching its low-temperature FE order through a well-defined first-order phase transition. When proton vacancies mimicking the KOH impurities are planted into the IR-conserving lattice, they enable standard MC simulation to work, revealing the kinetics of evolution of ice from proton disorder to partial FE order below the transition temperature. Replacing ordinary nucleation, each impurity opens up a proton ring generating a linear string, an actual FE hydrogen bond wire that expands with time. Reminiscent of those described for spin ice, these impurity-induced strings are proposed to exist in doped water ice too, where IRs are even stronger. The emerging mechanism yields a dependence of the long-time FE order fraction upon dopant concentration, and upon quenching temperature, that compares favorably with that known in real-life KOH doped ice.

Atomic view of cosolute-induced protein denaturation probed by NMR solvent paramagnetic relaxation enhancement.

The cosolvent effect arises from the interaction of cosolute molecules with a protein and alters the equilibrium between native and unfolded states. Denaturants shift the equilibrium toward the latter, while osmolytes stabilize the former. The molecular mechanism whereby cosolutes perturb protein stability is still the subject of considerable debate. Probing the molecular details of the cosolvent effect is experimentally challenging as the interactions are very weak and transient, rendering them invisible to most conventional biophysical techniques. Here, we probe cosolute-protein interactions by means of NMR solvent paramagnetic relaxation enhancement together with a formalism we recently developed to quantitatively describe, at atomic resolution, the energetics and dynamics of cosolute-protein interactions in terms of a concentration normalized equilibrium average of the interspin distance, [Formula: see text], and an effective correlation time, τc The system studied is the metastable drkN SH3 domain, which exists in dynamic equilibrium between native and unfolded states, thereby permitting us to probe the interactions of cosolutes with both states simultaneously under the same conditions. Two paramagnetic cosolute denaturants were investigated, one neutral and the other negatively charged, differing in the presence of a carboxyamide group versus a carboxylate. Our results demonstrate that attractive cosolute-protein backbone interactions occur largely in the unfolded state and some loop regions in the native state, electrostatic interactions reduce the [Formula: see text] values, and temperature predominantly impacts interactions with the unfolded state. Thus, destabilization of the native state in this instance arises predominantly as a consequence of interactions of the cosolutes with the unfolded state.

The Inhibition Effect of Epigallocatechin-3-Gallate on the Co-Aggregation of Amyloid-ß and Human Islet Amyloid Polypeptide Revealed by Replica Exchange Molecular Dynamics Simulations.

Alzheimer's disease and Type 2 diabetes are two epidemiologically linked diseases which are closely associated with the misfolding and aggregation of amyloid proteins amyloid-ß (Aß) and human islet amyloid polypeptide (hIAPP), respectively. The co-aggregation of the two amyloid proteins is regarded as the fundamental molecular mechanism underlying their pathological association. The green tea extract epigallocatechin-3-gallate (EGCG) has been extensively demonstrated to inhibit the amyloid aggregation of Aß and hIAPP proteins. However, its potential role in amyloid co-aggregation has not been thoroughly investigated. In this study, we employed the enhanced-sampling replica exchange molecular dynamics simulation (REMD) method to investigate the effect of EGCG on the co-aggregation of Aß and hIAPP. We found that EGCG molecules substantially diminish the ß-sheet structures within the amyloid core regions of Aß and hIAPP in their co-aggregates. Through hydrogen-bond, π-π and cation-π interactions targeting polar and aromatic residues of Aß and hIAPP, EGCG effectively attenuates both inter-chain and intra-chain interactions within the co-aggregates. All these findings indicated that EGCG can effectively inhibit the co-aggregation of Aß and hIAPP. Our study expands the potential applications of EGCG as an anti-amyloidosis agent and provides therapeutic options for the pathological association of amyloid misfolding disorders.

Structural Insights into Endostatin-Heparan Sulfate Interactions Using Modeling Approaches.

Glycosaminoglycans (GAGs) play a key role in a variety of biological processes in the extracellular matrix (ECM) via interactions with their protein targets. Due to their high flexibility, periodicity and electrostatics-driven interactions, GAG-containing complexes are very challenging to characterize both experimentally and in silico. In this study, we, for the first time, systematically analyzed the interactions of endostatin, a proteolytic fragment of collagen XVIII known to be anti-angiogenic and anti-tumoral, with heparin (HP) and representative heparan sulfate (HS) oligosaccharides of various lengths, sequences and sulfation patterns. We first used conventional molecular docking and a docking approach based on a repulsive scaling-replica exchange molecular dynamics technique, as well as unbiased molecular dynamic simulations, to obtain dynamically stable GAG binding poses. Then, the corresponding free energies of binding were calculated and the amino acid residues that contribute the most to GAG binding were identified. We also investigated the potential influence of Zn2+ on endostatin-HP complexes using computational approaches. These data provide new atomistic details of the molecular mechanism of HP's binding to endostatin, which will contribute to a better understanding of its interplay with proteoglycans at the cell surface and in the extracellular matrix.

Origin of the kinetic HDAC2-selectivity of an HDAC inhibitor.

A newly synthesized small molecule, KTT-1, exhibits kinetically selective inhibition of histone deacetylase 2, HDAC2, over its homologous enzyme, HDAC1. KTT-1 is hard to be released from the HDAC2/KTT-1 complex, compared to the HDAC1/KTT-1 complex and the residence time of KTT-1 in HDAC2 is longer than that in HDAC1. To explore the physical origin of this kinetic selectivity, we performed replica-exchange umbrella sampling molecular dynamics simulations for formation of both complexes. The calculated potentials of mean force suggest that KTT-1 is stably bound to HDAC2 and that it is easily disassociated from HDAC1. In the direct vicinity of the KTT-1 binding site in both enzymes, there exists a conserved loop consisting of four consecutive glycine residues (Gly304-307 for HDAC2; Gly299-302 for HDA1). The difference between the two enzymes comes from a single un-conserved residue behind this loop, namely, Ala268 in HDAC2 and Ser263 in HDAC1. The Ala268 contributes to the tight binding of KTT-1 to HDAC2 by the linear orientation of Ala268, Gly306, and one carbon atom in KTT-1. On the other hand, Ser263 cannot stabilize the binding of KTT-1 to HDAC1, because it is relatively further away from the glycine loop and because the directions of the two forces are not in line.

Ingenuity in performing replica permutation: How to order the state labels for improving sampling efficiency.

In the replica-permutation method, an advanced version of the replica-exchange method, all combinations of replicas and parameters are considered for parameter permutation, and a list of all the combinations is prepared. Here, we report that the temperature transition probability depends on how the list is created, especially in replica permutation with solute tempering (RPST). We found that the transition probabilities decrease at large replica indices when the combinations are sequentially assigned to the state labels as in the originally proposed list. To solve this problem, we propose to modify the list by randomly assigning the combinations to the state labels. We performed molecular dynamics simulations of amyloid-ß(16-22) peptides using RPST with the "randomly assigned" list (RPST-RA) and RPST with the "sequentially assigned" list (RPST-SA). The results show the decreases in the transition probabilities in RPST-SA are eliminated, and the sampling efficiency is improved in RPST-RA.

Acceleration of generalized replica exchange with solute tempering simulations of large biological systems on massively parallel supercomputer.

Generalized replica exchange with solute tempering (gREST) is one of the enhanced sampling algorithms for proteins or other systems with rugged energy landscapes. Unlike the replica-exchange molecular dynamics (REMD) method, solvent temperatures are the same in all replicas, while solute temperatures are different and are exchanged frequently between replicas for exploring various solute structures. Here, we apply the gREST scheme to large biological systems containing over one million atoms using a large number of processors in a supercomputer. First, communication time on a multi-dimensional torus network is reduced by matching each replica to MPI processors optimally. This is applicable not only to gREST but also to other multi-copy algorithms. Second, energy evaluations, which are necessary for the multistate bennet acceptance ratio (MBAR) method for free energy estimations, are performed on-the-fly during the gREST simulations. Using these two advanced schemes, we observed 57.72 ns/day performance in 128-replica gREST calculations with 1.5 million atoms system using 16,384 nodes in Fugaku. These schemes implemented in the latest version of GENESIS software could open new possibilities to answer unresolved questions on large biomolecular complex systems with slow conformational dynamics.

Formation and Effects of Upstream DNA-RNA Base Pairing in Telomerase.

Telomere elongation by telomerase consists of two types of translocation: duplex translocation during each repeat synthesis and template translocation at the end of repeat synthesis. Our replica exchange molecular dynamics simulations show that in addition to the Watson-Crick interactions in the active site, templating RNA can also form base pairs with the upstream regions of DNA, mostly with the second upstream DNA repeat with respect to the 3'-end. At the end of the repeat synthesis, dG10-P442 and dG11-N446 hydrogen bonds form. Then, active-site base pairs dissociate one by one, and the RNA bases reanneal with the complementary base on the upstream DNA repeat. For each dissociating base pair a new one forms, thus conserving the number of base pairs during template translocation.

Histidine tautomerism-mediated transthyretin amyloidogenesis: A molecular insight.

Characterization of the conformational alterations involved in monomer misfolding is essential for elucidating the molecular basis of the initial stage of protein accumulation. Here, we report the first structural analyses of transthyretin (TTR) (26-57) fragments with two histidine tautomeric states (δ; Nδ1H and ε; Nε2H) using replica-exchange molecular dynamics (REMD) simulations. Explaining the organizational properties and misfolding procedure is challenging because the δ and ε configurations can occur in the free neutral state. REMD revealed that ß-sheet generation is favored for the δδ (16.8%) and εδ (6.7%) tautomeric isomers, showing frequent main-chain contacts between the stable regions near the head (N-terminus) and central (middle) part compared to the εε (4.8%) and δε (2.8%) isomers. The presence of smaller and wider local energy minima may be related to the structural stability and toxicity of δδ/εδ and εε/δε. Histidines31 and 56 were the parts of regular (such as ß-strand) and nonregular (such as coil) secondary structures within the highly toxic TTR isomer. For TTR amyloidosis, focusing on hazardous isomeric forms with high sheet contents may be a potent treatment strategy. Overall, our findings support the tautomerism concept and aid in our comprehension of the basic tautomeric actions of neutral histidine throughout the misfolding process.

Artificial intelligence assisted identification of potential tau aggregation inhibitors: ligand- and structure-based virtual screening, in silico ADME, and molecular dynamics study.

Alzheimer's disease (AD) is a severe, growing, multifactorial disorder affecting millions of people worldwide characterized by cognitive decline and neurodegeneration. The accumulation of tau protein into paired helical filaments is one of the major pathological hallmarks of AD and has gained the interest of researchers as a potential drug target to treat AD. Lately, Artificial Intelligence (AI) has revolutionized the drug discovery process by speeding it up and reducing the overall cost. As a part of our continuous effort to identify potential tau aggregation inhibitors, and leveraging the power of AI, in this study, we used a fully automated AI-assisted ligand-based virtual screening tool, PyRMD to screen a library of 12 million compounds from the ZINC database to identify potential tau aggregation inhibitors. The preliminary hits from virtual screening were filtered for similar compounds and pan-assay interference compounds (the compounds containing reactive functional groups which can interfere with the assays) using RDKit. Further, the selected compounds were prioritized based on their molecular docking score with the binding pocket of tau where the binding pockets were identified using replica exchange molecular dynamics simulation. Thirty-three compounds showing good docking scores for all the tau clusters were selected and were further subjected to in silico pharmacokinetic prediction. Finally, top 10 compounds were selected for molecular dynamics simulation and MMPBSA binding free energy calculations resulting in the identification of UNK_175, UNK_1027, UNK_1172, UNK_1173, UNK_1237, UNK_1518, and UNK_2181 as potential tau aggregation inhibitors.

Compositional Analysis of ssDNA-Coated Single-Wall Carbon Nanotubes through UV Absorption Spectroscopy.

Aqueous suspensions of single-wall carbon nanotubes (SWCNTs) coated by ssDNA are analyzed using UV absorption and total carbon measurements. The results give absolute average concentrations of both components in samples without free ssDNA. From those values, the average mid-UV SWCNT absorptivity is deduced for three different batches of relatively small diameter nanotubes: two HiPco and one CoMoCAT. The absorptivity values enable the use of simple spectrophotometry to measure absolute concentrations of similar SWCNT samples in aqueous SDS. The results also quantify the mass ratio of ssDNA to SWCNT, defining the average number of nanotube carbon atoms suspended by one ssDNA strand of T15GT15 or T30G. Comparing this experimental parameter with results from replica exchange molecular dynamics simulations of one ssDNA strand freely adsorbed on a (6,5) segment shows close agreement between the computed number of SWCNT atoms covered per strand and the measured number of SWCNT atoms suspended per strand.

Modularity-based parallel protein design algorithm with an implementation using shared memory programming.

Given a target protein structure, the prime objective of protein design is to find amino acid sequences that will fold/acquire to the given three-dimensional structure. The protein design problem belongs to the non-deterministic polynomial-time-hard class as sequence search space increases exponentially with protein length. To ensure better search space exploration and faster convergence, we propose a protein modularity-based parallel protein design algorithm. The modular architecture of the protein structure is exploited by considering an intermediate structural organization between secondary structure and domain defined as protein unit (PU). Here, we have incorporated a divide-and-conquer approach where a protein is split into PUs and each PU region is explored in a parallel fashion. It has been further analyzed that our shared memory implementation of modularity-based parallel sequence search leads to better search space exploration compared to the case of traditional full protein design. Sequence-based analysis on design sequences depicts an average of 39.7% sequence similarity on the benchmark data set. Structure-based comparison of the modeled structures of the design protein with the target structure exhibited an average root-mean-square deviation of 1.17 Å and an average template modeling score of 0.89. The selected modeled structures of the design protein sequences are validated using 100 ns molecular dynamics simulations where 80% of the proteins have shown better or similar stability to the respective target proteins. Our study informs that our modularity-based protein design algorithm can be extended to protein interaction design as well.

Simulation studies of polypeptoids using replica exchange with dynamical scaling and dihedral biasing.

Polypeptoids differ from polypeptides in that the amide bond can more frequently adopt both cis and trans conformations. The transition between the two conformations requires overcoming a large energy barrier, making it difficult for conventional molecular simulations to adequately visit the cis and trans structures. A replica-exchange method is presented that allows for easy rotations of the amide bond and also an efficient linking to a high temperature replica. The method allows for just three replicas (one at the temperature and Hamiltonian of interest, a second high temperature replica with a biased dihedral potential, and a third connecting them) to overcome the amide bond sampling problem and also enhance sampling for other coordinates. The results indicate that for short peptoid oligomers, the conformations can range from all cis to all trans with an average cis/trans ratio that depends on side chain and potential model.

Explicit solvent repulsive scaling replica exchange molecular dynamics (RS-REMD) in molecular modeling of protein-glycosaminoglycan complexes.

Glycosaminoglcyans (GAGs), linear anionic periodic polysaccharides, are crucial for many biologically relevant functions in the extracellular matrix. By interacting with proteins GAGs mediate processes such as cancer development, cell proliferation and the onset of neurodegenerative diseases. Despite this eminent importance of GAGs, they still represent a limited focus for the computational community in comparison to other classes of biomolecules. Therefore, there is a lack of modeling tools designed specifically for docking GAGs. One has to rely on existing docking software developed mostly for small drug molecules substantially differing from GAGs in their basic physico-chemical properties. In this study, we present an updated protocol for docking GAGs based on the Repulsive Scaling Replica Exchange Molecular Dynamics (RS-REMD) that includes explicit solvent description. The use of this water model improved docking performance both in terms of its accuracy and speed. This method represents a significant computational progress in GAG-related research.

Identifying the Template for Oligomer to Fibril Conversion for Amyloid-ß (1-42) Oligomers using Hamiltonian Replica Exchange Molecular Dynamics.

The toxicity of amyloid-ß (Aß) oligomers has been known to be higher compared to mature fibrils. Yet the presence of plaques in Alzheimer's disease patients indicates the significance of oligomer to fibril conversion for Aß aggregates. In this study, we investigate Aß13-42 oligomers having two to five peptide chains using extensive all-atom molecular dynamics simulations to identify the on- or off-pathway intermediates in fibril formation pathway. Hamiltonian replica exchange method through solute tempering (REST2) has been employed to explore the different structures attained by these aggregates. Using intra-chain and inter-chain contacts as reaction coordinates, we obtain the free energy surface for the Aß13-42 oligomers. Consequently, their stable conformations and structural features have been identified. The found conformations belonging to most probable structures possess both parallel and anti-parallel ß-sheets, characteristic of on- and off-pathway intermediates, respectively. Further, we have measured the tendency to form fibril like interactions among the ß-sheet forming residues. Our analysis finds that residues 30-36 possess higher tendency to form fibril like contacts among all the residues. While we find stronger interaction among residues 30-36, these amino acids are also found to be more shielded from water compared to others. With previous experimental studies finding these residues to be more crucial for the stability of Aß42 oligomers, we propose that interactions within this patch could trigger seed formation that leads to conversion of on-pathway oligomers into disease relevant fibrils.