Clustering Molecular Dynamics Trajectories: 1. Characterizing the Performance of Different Clustering Algorithms

Probing the Nucleic Acid Flexibility to Disarm the Viral Counter-Defense Machinery: Design and Characterization of Potent p19 Inhibitors

Plant viruses are highly destructive and significant contributors to several global pandemics and epidemics in plants. A viral disease outbreak in plants can cause a scarcity of food supply and is a severe concern to humanity. The siRNA (small interfering RNA)-mediated RNA-induced silencing complex (RISC) formation is a primary defense mechanism in plants against viruses, where the RISC binds and degrades viral mRNAs. As a counter-defense, many viruses encode RNA-silencing suppressor proteins (e.g., the p19 protein from the Tombusviridae family) for viral proliferation in plants. The functional form of p19 (homodimer) binds to plant siRNA with high affinities, thereby interrupting the RISC formation and thus preventing the viral mRNA silencing in plants. By altering the RISC formation, the p19 protein helps the virus invasion in the plant and ultimately stunts host growth. In this study, we designed several modified siRNA-based molecules for p19 inhibition. The viral p19 protein is known to interact predominantly through H-bonds with 2'-OH and phosphates of the plant siRNA. We utilized this information and in silico-designed flexible substituents of siRNA, where we removed the C2'-C3' bond in each nucleotide unit. We performed all-atom explicit-solvent molecular dynamics simulations (400 ns, 3 replicates each) for control/modified siRNA─p19 complexes (8 in total) followed by energetic estimations. Strikingly, in a few modified complexes, the siRNA not only retained the double-helical structural integrity but also displayed remarkably enhanced p19 binding compared to the control siRNA; hence, we consider it important to perform biological and chemical in vitro and in vivo studies on proposed flexible nucleic acids as p19 inhibitors for crop protection.

Worth the Weight: Sub-Pocket EXplorer (SubPEx), a Weighted Ensemble Method to Enhance Binding-Pocket Conformational Sampling

Structure-based virtual screening (VS) is an effective method for identifying potential small-molecule ligands, but traditional VS approaches consider only a single binding-pocket conformation. Consequently, they struggle to identify ligands that bind to alternate conformations. Ensemble docking helps address this issue by incorporating multiple conformations into the docking process, but it depends on methods that can thoroughly explore pocket flexibility. We here introduce Sub-Pocket EXplorer (SubPEx), an approach that uses weighted ensemble (WE) path sampling to accelerate binding-pocket sampling. As proof of principle, we apply SubPEx to three proteins relevant to drug discovery: heat shock protein 90, influenza neuraminidase, and yeast hexokinase 2. SubPEx is available free of charge without registration under the terms of the open-source MIT license: http://durrantlab.com/subpex/.

Biosynthesis of Vanillin by Rational Design of Enoyl-CoA Hydratase/Lyase

Vanillin holds significant importance as a flavoring agent in various industries, including food, pharmaceuticals, and cosmetics. The CoA-dependent pathway for the biosynthesis of vanillin from ferulic acid involved feruloyl-CoA synthase (Fcs) and enoyl-CoA hydratase/lyase (Ech). In this research, the Fcs and Ech were derived from Streptomyces sp. strain V-1. The sequence conservation and structural features of Ech were analyzed by computational techniques including sequence alignment and molecular dynamics simulation. After detailed study for the major binding modes and key amino acid residues between Ech and substrates, a series of mutations (F74W, A130G, A130G/T132S, R147Q, Q255R, ΔT90, ΔTGPEIL, ΔN1-11, ΔC260-287) were obtained by rational design. Finally, the yield of vanillin produced by these mutants was verified by whole-cell catalysis. The results indicated that three mutants, F74W, Q147R, and ΔN1-11, showed higher yields than wild-type Ech. Molecular dynamics simulations and residue energy decomposition identified the basic residues K37, R38, K561, and R564 as the key residues affecting the free energy of binding between Ech and feruloyl-coenzyme A (FCA). The large changes in electrostatic interacting and polar solvating energies caused by the mutations may lead to decreased enzyme activity. This study provides important theoretical guidance as well as experimental data for the biosynthetic pathway of vanillin.

Molecular determinants of avoidance and inhibition of Pseudomonas aeruginosa MexB efflux pump

Transporters of the resistance-nodulation-cell division (RND) superfamily of proteins are the dominant multidrug efflux power of Gram-negative bacteria. The major RND efflux pump of Pseudomonas aeruginosa is MexAB-OprM, in which the inner membrane transporter MexB is responsible for the recognition and binding of compounds. The high importance of this pump in clinical antibiotic resistance made it a subject of intense investigations and a promising target for the discovery of efflux pump inhibitors. This study is focused on a series of peptidomimetic compounds developed as effective inhibitors of MexAB-OprM. We performed multi-copy molecular dynamics simulations, machine-learning (ML) analyses, and site-directed mutagenesis of MexB to investigate interactions of MexB with representatives of efflux avoiders, substrates, and inhibitors. The analysis of both direct and water-mediated protein-ligand interactions revealed characteristic patterns for each class, highlighting significant differences between them. We found that efflux avoiders poorly interact with the access binding site of MexB, and inhibition engages amino acid residues that are not directly involved in binding and transport of substrates. In agreement, machine-learning models selected different residues predictive of MexB substrates and inhibitors. The differences in interactions were further validated by site-directed mutagenesis. We conclude that the substrate translocation and inhibition pathways of MexB split at the interface (between the main putative binding sites) and at the deep binding pocket and that interactions outside of the hydrophobic patch contribute to the inhibition of MexB. This molecular-level information could help in the rational design of new inhibitors and antibiotics less susceptible to the efflux mechanism. IMPORTANCE Multidrug transporters recognize and expel from cells a broad range of ligands including their own inhibitors. The difference between the substrate translocation and inhibition routes remains unclear. In this study, machine learning and computational and experimental approaches were used to understand dynamics of MexB interactions with its ligands. Our results show that some ligands engage a certain combination of polar and charged residues in MexB binding sites to be effectively expelled into the exit funnel, whereas others engage aromatic and hydrophobic residues that slow down or hinder the next step in the transporter cycle. These findings suggest that all MexB ligands fit into this substrate-inhibitor spectrum depending on their physico-chemical structures and properties.

Mechanism of Ligand Discrimination by the NMT1 Riboswitch

Riboswitches are conserved functional domains in mRNA that almost exclusively exist in bacteria. They regulate the biosynthesis and transport of amino acids and essential metabolites such as coenzymes, nucleobases, and their derivatives by specifically binding small molecules. Due to their ability to precisely discriminate between different cognate molecules as well as their common existence in bacteria, riboswitches have become potential antibacterial drug targets that could deliver urgently needed antibiotics with novel mechanisms of action. In this work, we report the recognition mechanisms of four oxidization products (XAN, AZA, UAC, and HPA) generated during purine degradation by an RNA motif termed the NMT1 riboswitch. Specifically, we investigated the physical interactions between the riboswitch and the oxidized metabolites by computing the changes in the free energy on mutating key nucleobases in the ligand binding pocket of the riboswitch. We discovered that the electrostatic interactions are central to ligand discrimination by this riboswitch. The relative binding free energies of the mutations further indicated that some of the mutations can also strengthen the binding affinities of the ligands (AZA, UAC, and HPA). These mechanistic details are also potentially relevant in the design of novel compounds targeting riboswitches.

Interaction of Radiopharmaceuticals with Somatostatin Receptor 2 Revealed by Molecular Dynamics Simulations

The development of drugs targeting somatostatin receptor 2 (SSTR2), generally overexpressed in neuroendocrine tumors, is focus of intense research. A few molecules in conjugation with radionuclides are in clinical use for both diagnostic and therapeutic purposes. These radiopharmaceuticals are composed of a somatostatin analogue biovector conjugated to a chelator moiety bearing the radionuclide. To date, despite valuable efforts, a detailed molecular-level description of the interaction of radiopharmaceuticals in complex with SSTR2 has not yet been accomplished. Therefore, in this work, we carefully analyzed the key dynamical features and detailed molecular interactions of SSTR2 in complex with six radiopharmaceutical compounds selected among the few already in use (64Cu/68Ga-DOTATATE, 68Ga-DOTATOC, 64Cu-SARTATE) and some in clinical development (68Ga-DOTANOC, 64Cu-TETATATE). Through molecular dynamics simulations and exploiting recently available structures of SSTR2, we explored the influence of the different portions of the compounds (peptide, radionuclide, and chelator) in the interaction with the receptor. We identified the most stable binding modes and found distinct interaction patterns characterizing the six compounds. We thus unveiled detailed molecular interactions crucial for the recognition of this class of radiopharmaceuticals. The microscopically well-founded analysis presented in this study provides guidelines for the design of new potent ligands targeting SSTR2.

Embedding Nonrigid Solutes in an Averaged Environment: A Case Study on Rhodopsins

Many simulation methods concerning solvated molecules are based on the assumption that the solvated species and the solvent can be characterized by some representative structures of the solute and some embedding potential corresponding to this structure. While the averaging of the solvent configurations to obtain an embedding potential has been studied in great detail, this hinges on a single solute structure representation. This assumption is re-examined and generalized for conformationally flexible solutes and tested on 4 nonrigid systems. In this generalized approach, the solute is characterized by a set of representative structures and the corresponding embedding potentials. The representative structures are identified by means of subdividing the statistical ensemble, which in this work is generated by a constant-temperature molecular dynamics simulation. The embedding potential defined in the Frozen-Density Embedding Theory is used to characterize the average effect of the solvent in each subensemble. The numerical examples concern the vertical excitation energies of protonated retinal Schiff bases in protein environments. It is comprehensively shown that subensemble averaging leads to huge computational savings compared with explicit averaging of the excitation energies in the whole ensemble while introducing only minor errors in the case of the systems examined.

Clustering Heterogeneous Conformational Ensembles of Intrinsically Disordered Proteins with t-Distributed Stochastic Neighbor Embedding

Intrinsically disordered proteins (IDPs) populate a range of conformations that are best described by a heterogeneous ensemble. Grouping an IDP ensemble into "structurally similar" clusters for visualization, interpretation, and analysis purposes is a much-desired but formidable task, as the conformational space of IDPs is inherently high-dimensional and reduction techniques often result in ambiguous classifications. Here, we employ the t-distributed stochastic neighbor embedding (t-SNE) technique to generate homogeneous clusters of IDP conformations from the full heterogeneous ensemble. We illustrate the utility of t-SNE by clustering conformations of two disordered proteins, Aβ42, and α-synuclein, in their APO states and when bound to small molecule ligands. Our results shed light on ordered substates within disordered ensembles and provide structural and mechanistic insights into binding modes that confer specificity and affinity in IDP ligand binding. t-SNE projections preserve the local neighborhood information, provide interpretable visualizations of the conformational heterogeneity within each ensemble, and enable the quantification of cluster populations and their relative shifts upon ligand binding. Our approach provides a new framework for detailed investigations of the thermodynamics and kinetics of IDP ligand binding and will aid rational drug design for IDPs.

Discovery of a Hidden Trypanosoma cruzi Spermidine Synthase Binding Site and Inhibitors through In Silico, In Vitro, and X-ray Crystallography

In drug discovery research, the selection of promising binding sites and understanding the binding mode of compounds are crucial fundamental studies. The current understanding of the proteins-ligand binding model extends beyond the simple lock and key model to include the induced-fit model, which alters the conformation to match the shape of the ligand, and the pre-existing equilibrium model, selectively binding structures with high binding affinity from a diverse ensemble of proteins. Although methods for detecting target protein binding sites and virtual screening techniques using docking simulation are well-established, with numerous studies reported, they only consider a very limited number of structures in the diverse ensemble of proteins, as these methods are applied to a single structure. Molecular dynamics (MD) simulation is a method for predicting protein dynamics and can detect potential ensembles of protein binding sites and hidden sites unobservable in a single-point structure. In this study, to demonstrate the utility of virtual screening with protein dynamics, MD simulations were performed on Trypanosoma cruzi spermidine synthase to obtain an ensemble of dominant binding sites with a high probability of existence. The structure of the binding site obtained through MD simulation revealed pockets in addition to the active site that was present in the initial structure. Using the obtained binding site structures, virtual screening of 4.8 million compounds by docking simulation, in vitro assays, and X-ray analysis was conducted, successfully identifying two hit compounds.

Unveiling the interdomain dynamics of type II DNA topoisomerase through all-atom simulations: Implications for understanding its catalytic cycle

Type IIA DNA topoisomerases are complex molecular nanomachines that manage topological states of the DNA molecule in the cell and play a crucial role in cellular processes such as cell division and transcription. They are also established targets of cancer chemotherapy. Starting from the available crystal structure of a fully catalytic topoisomerase IIA homodimer from Saccharomyces cerevisiae, we constructed three states of this molecular motor primarily changing the configurations of the DNA segment bound in the DNA gate and performed μs-long all-atom molecular simulations. A comprehensive analysis revealed a sliding motion within the DNA gate and a teamwork between the N-gate and DNA gate that may be associated with the necessary molecular events that allow passage of the T-segment of DNA. The observed movement of the ATPase dimer relative to the DNA domain was reflected in different interaction patterns between the K-loops of the transducer domain and the B-A-B form of the bound DNA. Based on the obtained results, we mapped simulated configurations to the structures in the proposed catalytic cycle through which type IIA topoisomerases exert their function and discussed the possible transition events. The results extend our understanding of the mechanism of action of type IIA topoisomerases and provide an atomistic interpretation of some of the observed features of these molecular motors.

The Influence of Single Nucleotide Polymorphisms on Vitamin D Receptor Protein Levels and Function in Chronic Liver Disease

Single nucleotide polymorphisms (SNPs) in the vitamin D receptor (VDR) gene have been associated with chronic liver disease. We investigated the role of VDR SNPs on VDR protein levels and function in patients with chronic liver disease. VDR expression levels were determined in peripheral T lymphocytes (CD3+VDR+), monocytes (CD14+VDR+), and plasma from patients (n = 66) and healthy controls (n = 38). Genotyping of SNPs and the determination of expression of VDR/vitamin D-related genes were performed by using qPCR. The effect of FokI SNP on vitamin D-binding to VDR was investigated by molecular dynamics simulations. CD14+VDR+ cells were correlated with the MELD score. The ApaI SNP was associated with decreased CD3+VDR+ levels in cirrhotic patients and with higher liver stiffness in HCV patients. The BsmI and TaqI SNPs were associated with increased VDR plasma concentrations in cirrhotic patients and decreased CD14+VDR+ levels in HCV patients. The FokI SNP was associated with increased CD3+VDR+ levels in cirrhotic patients and controls. VDR polymorphisms were significantly related to the expression of genes critical for normal hepatocyte function and immune homeostasis. VDR expression levels were related to the clinical severity of liver disease. VDR SNPs may be related to the progression of chronic liver disease by affecting VDR expression levels.

Clustering molecular dynamics conformations of the CC'-loop of the PD-1 immuno-checkpoint receptor

Molecular mechanisms within the checkpoint receptor PD-1 are essential for its activation by PD-L1 as well as for blocking such an activation via checkpoint inhibitors. We use molecular dynamics to scrutinize patterns of atomic motion in PD-1 without a ligand. Molecular dynamics is performed for the whole extracellular domain of PD-1, and the analysis focuses on its CC'-loop and some adjacent Cα-atoms. We extend previous work by applying common nearest neighbor clustering (Cnn) and compare the performance of this method with Daura clustering as well as UMAP dimension reduction and subsequent agglomerative linkage clustering. As compared to Daura clustering, we found Cnn less sensitive to cutoff selection and better able to return representative clusters for sets of different 3D atomic conformations. Interestingly, Cnn yields results quite similar to UMAP plus linkage clustering.

Novel compound heterozygous variants (c.971delA/c.542C > T) in SLC1A4 causes spastic tetraplegia, thin corpus callosum, and progressive microcephaly: a case report and mutational analysis

Spastic tetraplegia, thin corpus callosum, and progressive microcephaly (SPATCCM) are linked to SLC1A4 genetic variants since the first reported case in 2015. SLC1A4 encodes for the neutral amino acid transporter ASCT1 which is involved in the transportation of serine between astrocytes and neurons. Although most of the reported cases are of Ashkenazi Jewish ancestry, SPATCCM has also been reported in Irish, Italian, Czech, Palestinian, and Pakistani ethnicities. Herein, we report two Pakistani male siblings from a non-consanguineous marriage presented with global developmental delay associated with spastic quadriplegia, microcephaly, and infantile spasm. Since infancy, both siblings suffered from microcephaly with brain MRI demonstrating generalized atrophy of the frontal, temporal, and parietal lobes with a prominence of the subarachnoid spaces, widening of the Sylvian fissures, and enlargement of the ventricular system not compatible with the chronological age of both patients associated with thinning of the corpus callosum. Whole-exome sequencing of both affected brothers revealed novel compound heterozygous variants in the SLC1A4 gene (NM_003038) segregating from their parents. The maternal c.971delA (p.N324Tfs*29) deletion variant disturbs the transcript reading frame leading to the generation of a premature stop codon and its subsequent degradation by nonsense-mediated mRNA decay as detected through expression analysis. The paternal c.542C > T (p.S181F) missense variant was predicted deleterious via multiple in silico prediction tools as the amino acid substitution is speculated to affect the overall ASCT1 structural confirmation due to the loss of an H-bond at the core of the protein at this position which might affect its function as concluded from the simulation analysis. The presented cases expand the genetic and clinical spectrum of ASCT1 deficiency and support the importance of including SLC1A4 gene screening in infants with unexplained global neurodevelopmental delay regardless of ethnicity.

Structural Modifications Introduced by NS2B Cofactor Binding to the NS3 Protease of the Kyasanur Forest Disease Virus

Kyasanur Forest Disease virus (KFDV), a neglected human pathogenic virus, is a Flavivirus that causes severe hemorrhagic fever in humans. KFDV is transmitted to humans by the bite of the hard tick (Haemaphysalis spinigera), which acts as a reservoir of KFDV. The recent expansion of the endemic area of KFDV is of concern and requires the development of new preventive measures against KFDV. Currently, there is no antiviral therapy against KFDV, and the existing vaccine has limited efficacy. To develop a new antiviral therapy against KFDV, we focused on the nonstructural proteins NS2B and NS3 of KFDV, which are responsible for serine protease activity. Viral proteases have shown to be suitable therapeutic targets in the development of antiviral drugs against many diseases. However, success has been limited in flaviviruses, mainly because of the important features of the active site, which is flat and highly charged. In this context, the present study focuses on the dynamics of NS2B and NS3 to identify potential allosteric sites in the NS2B/NS3 protease of KDFV. To our knowledge, there are no reports on the dynamics of NS2B and NS3 in KFDV, and the crystal structure of the NS2B/NS3 protease of KFDV has not yet been solved. Overall, we created the structure of the NS2B/NS3 protease of KFDV using AlphaFold and performed molecular dynamics simulations with and without NS2B cofactor to investigate structural rearrangements due to cofactor binding and to identify alternative allosteric sites. The identified allosteric site is promising due to its geometric and physicochemical properties and druggability and can be used for new drug development. The applicability of the proposed allosteric binding sites was verified for the best-hit molecules from the virtual screening and MD simulations.

Conformational dynamics of RNA G4C2 and G2C4 repeat expansions causing ALS/FTD using NMR and molecular dynamics studies

G4C2 and G2C4 repeat expansions in chromosome 9 open reading frame 72 (C9orf72) are the most common cause of genetically defined amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), or c9ALS/FTD. The gene is bidirectionally transcribed, producing G4C2 repeats [r(G4C2)exp] and G2C4 repeats [r(G2C4)exp]. The c9ALS/FTD repeat expansions are highly structured, and structural studies showed that r(G4C2)exp predominantly folds into a hairpin with a periodic array of 1 × 1 G/G internal loops and a G-quadruplex. A small molecule probe revealed that r(G4C2)exp also adopts a hairpin structure with 2 × 2 GG/GG internal loops. We studied the conformational dynamics adopted by 2 × 2 GG/GG loops using temperature replica exchange molecular dynamics (T-REMD) and further characterized the structure and underlying dynamics using traditional 2D NMR techniques. These studies showed that the loop's closing base pairs influence both structure and dynamics, particularly the configuration adopted around the glycosidic bond. Interestingly, r(G2C4) repeats, which fold into an array of 2 × 2 CC/CC internal loops, are not as dynamic. Collectively, these studies emphasize the unique sensitivity of r(G4C2)exp to small changes in stacking interactions, which is not observed in r(G2C4)exp, providing important considerations for further principles in structure-based drug design.

Parameterization of the miniPEG-Modified γPNA Backbone: Toward Induced γPNA Duplex Dissociation

γ-Modified peptide nucleic acids (γPNAs) serve as potential therapeutic agents against genetic diseases. Miniature poly(ethylene glycol) (miniPEG) has been reported to increase solubility and binding affinity toward genetic targets, yet details of γPNA structure and dynamics are not understood. Within our work, we parameterized missing torsional and electrostatic terms for the miniPEG substituent on the γ-carbon atom of the γPNA backbone in the CHARMM force field. Microsecond timescale molecular dynamics simulations were carried out on six miniPEG-modified γPNA duplexes from NMR structures (PDB ID: 2KVJ). Three NMR models for the γPNA duplex (PDB ID: 2KVJ) were simulated as a reference for structural and dynamic changes captured for the miniPEG-modified γPNA duplex. Principal component analysis performed on the γPNA backbone atoms identified a single isotropic conformational substate (CS) for the NMR simulations, whereas four anisotropic CSs were identified for the ensemble of miniPEG-modified γPNA simulations. The NMR structures were found to have a 23° helical bend toward the major groove, consistent with our simulated CS structure of 19.0°. However, a significant difference between simulated methyl- and miniPEG-modified γPNAs involved the opportunistic invasion of miniPEG through the minor and major groves. Specifically, hydrogen bond fractional analysis showed that the invasion was particularly prone to affect the second G-C base pair, reducing the Watson-Crick base pair hydrogen bond by 60% over the six simulations, whereas the A-T base pairs decreased by only 20%. Ultimately, the invasion led to base stack reshuffling, where the well-ordered base stacking was reduced to segmented nucleobase stacking interactions. Our 6 μs timescale simulations indicate that duplex dissociation suggests the onset toward γPNA single strands, consistent with the experimental observation of decreased aggregation. To complement the insight of miniPEG-modified γPNA structure and dynamics, the new miniPEG force field parameters allow for further exploration of such modified γPNA single strands as potential therapeutic agents against genetic diseases.

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; N_δ1H and ε; N_ε2H) 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 β-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 β-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.

Worth the weight: Sub-Pocket EXplorer (SubPEx), a weighted-ensemble method to enhance binding-pocket conformational sampling

Structure-based virtual screening (VS) is an effective method for identifying potential small-molecule ligands, but traditional VS approaches consider only a single binding-pocket conformation. Consequently, they struggle to identify ligands that bind to alternate conformations. Ensemble docking helps address this issue by incorporating multiple conformations into the docking process, but it depends on methods that can thoroughly explore pocket flexibility. We here introduce Sub-Pocket EXplorer (SubPEx), an approach that uses weighted ensemble (WE) path sampling to accelerate binding-pocket sampling. As proof of principle, we apply SubPEx to three proteins relevant to drug discovery: heat shock protein 90, influenza neuraminidase, and yeast hexokinase 2. SubPEx is available free of charge without registration under the terms of the open-source MIT license: http://durrantlab.com/subpex/.

Unique recognition of the microalgal plastidial glycerol-3-phosphate acyltransferase for acyl-ACP

Plastidial glycerol-3-phosphate acyltransferases (GPATs) catalyze acyl-ACP and glycerol-3-phosphate to synthesize lysophosphatidic acid in vivo, which initiates the formation of various glycerolipids. Although the physiological substrates of plastidial GPATs are acyl-ACPs, acyl-CoAs have been commonly studied on the GPATs in vitro. However, little is known whether there are any distinct features of GPATs towards acyl-ACP and acyl-CoA. In this study, the results showed that the microalgal plastidial GPATs preferred acyl-ACP to acyl-CoA, while surprisingly, the plant-derived plastidial GPATs showed no obvious preferences towards these two acyl carriers. The key residues responsible for the distinct feature of microalgal plastidial GPATs were compared with plant-derived plastidial GPATs in their efficiency to catalyze acyl-ACP and acyl-CoA. Microalgal plastidial GPATs uniquely recognized acyl-ACP as compared to with other acyltransferases. The structure of the acyltransferases-ACP complex highlights only the involvement of the large structural domain in ACP in microalgal plastidial GPAT while in the other acyltransferases, both large and small structural domains were involved in the recognition process. The interaction sites on the plastidial GPAT from the green alga Myrmecia incisa (MiGPAT1) with ACP turned out to be K204, R212 and R266. A unique recognition between the microalgal plastidial GPAT and ACP was elucidated.

An Expedited Route to Optical and Electronic Properties at Finite Temperature via Unsupervised Learning

Electronic properties and absorption spectra are the grounds to investigate molecular electronic states and their interactions with the environment. Modeling and computations are required for the molecular understanding and design strategies of photo-active materials and sensors. However, the interpretation of such properties demands expensive computations and dealing with the interplay of electronic excited states with the conformational freedom of the chromophores in complex matrices (i.e., solvents, biomolecules, crystals) at finite temperature. Computational protocols combining time dependent density functional theory and ab initio molecular dynamics (MD) have become very powerful in this field, although they require still a large number of computations for a detailed reproduction of electronic properties, such as band shapes. Besides the ongoing research in more traditional computational chemistry fields, data analysis and machine learning methods have been increasingly employed as complementary approaches for efficient data exploration, prediction and model development, starting from the data resulting from MD simulations and electronic structure calculations. In this work, dataset reduction capabilities by unsupervised clustering techniques applied to MD trajectories are proposed and tested for the ab initio modeling of electronic absorption spectra of two challenging case studies: a non-covalent charge-transfer dimer and a ruthenium complex in solution at room temperature. The K-medoids clustering technique is applied and is proven to be able to reduce by ∼100 times the total cost of excited state calculations on an MD sampling with no loss in the accuracy and it also provides an easier understanding of the representative structures (medoids) to be analyzed on the molecular scale.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

Molecular docking and molecular simulation studies for N-degron selectivity of chloroplastic ClpS from Chlamydomonas reinhardtii

Regarding the importance of N-degron pathway in protein degradation network, the adaptor protein ClpS recognizes the substrates bearing classical N-degrons, and delivers them to caseinolytic protease complex ClpAP for degradation. Interestingly, the majority of N-degrons located near the N-terminus of protein substrate are belonged to the hydrophobic type amino acids. Chloroplast, an important organelle for plant photosynthesis, contain a diversified Clp degradation system. Despite several studies have confirmed that chloroplastic ClpS is able to interact with classical N-degrons derived from prokaryotes, whereas, the molecular mechanism underlying how the chloroplastic ClpS protein could recognize the substrate tagged by N-degrons is still unclear until now. Chlamydomonas reinhardtii is a kind of unicellular model organism for photosynthesis researches, which possesses a large cup-shaped chloroplast, and the corresponding genome data indicates that it owns bacterial homologous adaptor protein, named CrClpS1. However, the relevant biochemical knowledges, and protein structure researches for CrClpS1 adaptor aren't reported up to date. The molecular interactions between CrClpS1 and possible N-degrons are undefined as well. Here, we build a reliable homology model of CrClpS1 and find a hydrophobic pocket for N-degron binding. We combine molecular docking, molecular dynamic simulations, and MM/PBSA, MM/GBSA binding free energy estimations to elucidate the molecular properties of CrClpS1-N-degron interactions. Besides, we investigate the conformational changes for CrClpS1-apo in water-solvent environment and analyze its possible biological significances through a long time molecular dynamic simulation. Specifically, the adaptor CrClpS1 displays the stronger interactions with Phe, Trp, Tyr, His and Ile with respect to other amino acids. Using the residue decomposition analysis, the interactions between CrClpS1 and N-degrons are heavily depended on several conservative residues, which are located around the hydrophobic pocket, implying that chloroplast isolated from Chlamydomonas reinhadtii adopts a relatively conservative N-degron recognition mode. Besides, the opening-closure of hydrophobic pocket of CrClpS1 might be beneficial for the N-degron selectivity.

Targeting the multifaceted neurotoxicity of Alzheimer's disease by tailored functionalisation of the curcumin scaffold

Simultaneous modulation of multifaceted toxicity arising from neuroinflammation, oxidative stress, and mitochondrial dysfunction represents a valuable therapeutic strategy to tackle Alzheimer's disease. Among the significant hallmarks of the disorder, Aβ protein and its aggregation products are well-recognised triggers of the neurotoxic cascade. In this study, by tailored modification of the curcumin-based lead compound 1, we aimed at developing a small library of hybrid compounds targeting Aβ protein oligomerisation and the consequent neurotoxic events. Interestingly, from in vitro studies, analogues 3 and 4, bearing a substituted triazole moiety, emerged as multifunctional agents able to counteract Aβ aggregation, neuroinflammation and oxidative stress. In vivo proof-of-concept evaluations, performed in a Drosophila oxidative stress model, allowed us to identify compound 4 as a promising lead candidate.

Molecular simulations of SSTR2 dynamics and interaction with ligands

The cyclic peptide hormone somatostatin regulates physiological processes involved in growth and metabolism, through its binding to G-protein coupled somatostatin receptors. The isoform 2 (SSTR2) is of particular relevance for the therapy of neuroendocrine tumours for which different analogues to somatostatin are currently in clinical use. We present an extensive and systematic computational study on the dynamics of SSTR2 in three different states: active agonist-bound, inactive antagonist-bound and apo inactive. We exploited the recent burst of SSTR2 experimental structures to perform μs-long multi-copy molecular dynamics simulations to sample conformational changes of the receptor and rationalize its binding to different ligands (the agonists somatostatin and octreotide, and the antagonist CYN154806). Our findings suggest that the apo form is more flexible compared to the holo ones, and confirm that the extracellular loop 2 closes upon the agonist octreotide but not upon the antagonist CYN154806. Based on interaction fingerprint analyses and free energy calculations, we found that all peptides similarly interact with residues buried into the binding pocket. Conversely, specific patterns of interactions are found with residues located in the external portion of the pocket, at the basis of the extracellular loops, particularly distinguishing the agonists from the antagonist. This study will help in the design of new somatostatin-based compounds for theranostics of neuroendocrine tumours.

Structural investigation of CDCA3-Cdh1 protein-protein interactions using in vitro studies and molecular dynamics simulation

The anaphase-promoting complex/cyclosome (APC/C) ubiquitin ligase and its cofactor, Cdh1, regulate the expression of several cell-cycle proteins and their functions during mitosis. Levels of the protein cell division cycle-associated protein 3 (CDCA3), which is functionally required for mitotic entry, are regulated by APC/CCdh1 . CDCA3 is an intrinsically disordered protein and contains both C-terminal KEN box and D-box recognition motifs, enabling binding to Cdh1. Our previous findings demonstrate that CDCA3 has a phosphorylation-dependent non-canonical ABBA-like motif within the linker region bridging these two recognition motifs and is required for efficient binding to Cdh1. Here, we sought to identify and further characterize additional residues that participate within this ABBA-like motif using detailed in vitro experiments and in silico modeling studies. We identified the role of H-bonds, hydrophobic and ionic interactions across the CDCA3 ABBA-like motif in the linker region between KEN and D-box motifs. This linker region adopts a well-defined structure when bound to Cdh1 in the presence of phosphorylation. Upon alanine mutation, the structure of this region is lost, leading to higher flexibility, and alteration in affinities due to binding to alternate sites on Cdh1. Our findings identify roles for the anchoring residues in the non-canonical ABBA-like motif to promote binding to the APC/CCdh1 and regulation of CDCA3 protein levels.

De Novo Design and Synthesis of Polypeptide Immunomodulators for Resetting Macrophage Polarization

Modulating the extracellular matrix microenvironment is critical for achieving the desired macrophage phenotype in immune investigations or tumor therapy. Combining de novo protein design and biosynthesis techniques, herein, we designed a biomimetic polypeptide self-assembled nano-immunomodulator to trigger the activation of a specific macrophage phenotype. It was intended to be made up of (​GGS​GGP​GGG​PAS​AAA​NSA​SRA​TSN​SP)n, the RGD motif from collagen, and the IKVAV motif from laminin. The combination of these domains allows the biomimetic polypeptide to assemble into extracellular matrix-like nanofibrils, creating an extracellular matrix-like milieu for macrophages. Furthermore, changing the concentration further provides a facile route to fine-tune macrophage polarization, which enhances antitumor immune responses by precisely resetting tumor-associated macrophage immune responses into an M1-like phenotype, which is generally considered to be tumor-killing macrophages, primarily antitumor, and immune-promoting. Unlike metal or synthetic polymer-based nanoparticles, this polypeptide-based nanomaterial exhibits excellent biocompatibility, high efficacy, and precise tunability in immunomodulatory effectiveness. These encouraging findings motivate us to continue our research into cancer immunotherapy applications in the future.

Single-exonuclease nanocircuits reveal the RNA degradation dynamics of PNPase and demonstrate potential for RNA sequencing

The degradation process of RNA is decisive in guaranteeing high-fidelity translation of genetic information in living organisms. However, visualizing the single-base degradation process in real time and deciphering the degradation mechanism at the single-enzyme level remain formidable challenges. Here, we present a reliable in-situ single-PNPase-molecule dynamic electrical detector based on silicon nanowire field-effect transistors with ultra-high temporal resolution. These devices are capable of realizing real-time and label-free monitoring of RNA analog degradation with single-base resolution, including RNA analog binding, single-nucleotide hydrolysis, and single-base movement. We discover a binding event of the enzyme (near the active site) with the nucleoside, offering a further understanding of the RNA degradation mechanism. Relying on systematic analyses of independent reads, approximately 80% accuracy in RNA nucleoside sequencing is achieved in a single testing process. This proof-of-concept sets up a Complementary Metal Oxide Semiconductor (CMOS)-compatible playground for the development of high-throughput detection technologies toward mechanistic exploration and single-molecule sequencing.

Revealing the Molecular Interactions between Human ACE2 and the Receptor Binding Domain of the SARS-CoV-2 Wild-Type, Alpha and Delta Variants

After a sudden and first spread of the pandemic caused by the novel SARS-CoV-2 (Severe Acute Respiratory Syndrome-Coronavirus 2) wild-type strain, mutants have emerged which have been associated with increased infectivity, inducing surges in the contagions. The first of the so-called variants of concerns, was firstly isolated in the United Kingdom and later renamed Alpha variant. Afterwards, in the middle of 2021, a new variant appeared called Delta. The latter is characterized by the presence of point mutations in the Spike protein of SARS-CoV-2, especially in the Receptor Binding Domain (RBD). When in its active conformation, the RBD can interact with the human receptor Angiotensin-Converting Enzyme 2 (ACE2) to allow the entry of the virions into cells. In this contribution, by using extended all-atom molecular dynamic simulations, complemented with machine learning post-processing, we analyze the changes in the molecular interaction network induced by these different strains in comparison with the wild-type. On one hand, although relevant variations are evidenced, only limited changes in the global stability indicators and in the flexibility profiles have been observed. On the other hand, key differences were obtained by tracking hydrophilic and hydrophobic molecular interactions, concerning both positioning at the ACE2/RBD interface and formation/disruption dynamic behavior.

Structural Perturbation of Monomers Determines the Amyloid Aggregation Propensity of Calcitonin Variants

Human calcitonin (hCT) is a polypeptide hormone that participates in calcium-phosphorus metabolism. Irreversible aggregation of 32-amino acid hCT into β-sheet-rich amyloid fibrils impairs physiological activity and increases the risk of medullary carcinoma of the thyroid. Amyloid-resistant hCT derivatives substituting critical amyloidogenic residues are of particular interest for clinical applications as therapeutic drugs against bone-related diseases. Uncovering the aggregation mechanism of hCT at the molecular level, therefore, is important for the design of amyloid-resistant hCT analogues. Here, we investigated the aggregation dynamics of hCT, non-amyloidogenic salmon calcitonin (sCT), and two hCT analogues with reduced aggregation tendency─TL-hCT and phCT─using long timescale discrete molecular dynamics simulations. Our results showed that hCT monomers mainly adopted unstructured conformations with dynamically formed helices around the central region. hCT self-assembled into helix-rich oligomers first, followed by a conformational conversion into β-sheet-rich oligomers with β-sheets formed by residues 10-30 and stabilized by aromatic and hydrophobic interactions. Our simulations confirmed that TL-hCT and phCT oligomers featured more helices and fewer β-sheets than hCT. Substitution of central aromatic residues with leucine in TL-hCT and replacing C-terminal hydrophobic residue with hydrophilic amino acid in phCT only locally suppressed β-sheet propensities in the central region and C-terminus, respectively. Having mutations in both central and C-terminal regions, sCT monomers and dynamically formed oligomers predominantly adopted helices, confirming that both central aromatic and C-terminal hydrophobic residues played important roles in the fibrillization of hCT. We also observed the formation of β-barrel intermediates, postulated as the toxic oligomers in amyloidosis, for hCT but not for sCT. Our computational study depicts a complete picture of the aggregation dynamics of hCT and the effects of mutations. The design of next-generation amyloid-resistant hCT analogues should consider the impact on both amyloidogenic regions and also take into account the amplification of transient β-sheet population in monomers upon aggregation.

In-depth analysis of the interactions of various aryl hydrocarbon receptor ligands from a computational perspective

Aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that acts as a machinery that controls the expression of many genes, including cytochrome P450 CYP1A1, CYP1A2 and CYP1B1. It plays a principal role in numerous biological and toxicological functions, making it a promising target for developing therapeutic agents. Several novel small molecules targeting the AhR signaling pathway are currently under investigation as antitumor agents. Some have already advanced into clinical trials in patients with various tumors. Activation of AhR by diverse chemicals either endogenous or exogenous is initiated by the binding of these ligands to the PAS-B domain, which modulates AhR functions. There is, however, limited information about how various ligands interact with the PAS-B domain for activating or inhibiting the AhR. To better understand the mode of action of AhR agonists/antagonists. The current work proposes a combination of several computational tools to build dynamical models for the PAS-B domain bound to different ligands in mouse and human. Our findings reveal the essential roles of specific PAS-B residues (e.g., S365, V381& Q383), which mediate the AhR ligand-binding process. Our results also explain how these residues regulate the promiscuity of AhR in accommodating various chemicals in its binding PAS-B ligand-binding pocket.

Arjunetin as a promising drug candidate against SARS-CoV-2: molecular dynamics simulation studies

Stem and bark of the tree Terminalia arjuna Wight & Arn. (Combretaceae) has been documented to exhibit therapeutic properties like cardiotonic, anticancer, antiviral, antibacterial, antifungal, hypercholesterolemia, hypolipidemic, and anti-coagulant. Our previous studies have shown that, ethanolic extract of T. arjuna bark exhibits radical scavenging anti-oxidant activity and also effectively inhibited catalase activity. In this study, oleanane triterpenoids type compounds viz., oleanolic acid, arjunolic acid, arjunolitin, arjunetin were isolated from ethanolic bark extract as bio-active compound and their structures were elucidated using ¹H, ¹³C NMR, HR-ESIMS, IR. Of the various compounds, Arjunetin showed significant inhibition of catalase activity as compared to the other compounds. Based on the structural similarity between arjunetin and current antiviral drugs, we propose that arjunetin might exhibit antiviral activity. Molecular docking and molecular dynamics studies showed that arjunetin binds to the binds to key targets of SARS-CoV-2 namely, 3CLpro, PLpro, and RdRp) with a higher binding energy values (3CLpro, -8.4 kcal/mol; PLpro, -7.6 kcal/mol and RdRp, -8.1 kcal/mol) as compared with FDA approved protease inhibitor drugs to Lopinavir (3CLpro, -7.2 kcal/mole and PLpro -7.7 kcal/mole) and Remdesivir (RdRp -7.6 kcal/mole). To further investigate this, we performed 200-500 ns molecular dynamics simulation studies. The results transpired that the binding affinity of Arjunetin is higher than Remdesivir in the RNA binding cavity of RdRp. Based on structural similarity between arjunetin and Saikosaponin (a known antiviral agents) and based on our molecular docking and molecular dynamic simulation studies, we propose that arjunetin can be a promising drug candidate against Covid-19.Communicated by Ramaswamy H. Sarma.

Structure prediction and discovery of inhibitors against phosphopantothenoyl cysteine synthetase of Acinetobacter baumannii

Acinetobacter baumannii is an extremely dangerous multidrug-resistant (MDR) gram-negative pathogen which poses a serious life-threatening risk in immunocompromised patients. Phosphopantothenoyl cysteine synthetase (PPCS) catalyzes the formation of an amide bond between L-cysteine and phosphopantothenic acid (PPA) to form 4'- Phosphopantothenoylcysteine during Coenzyme A (CoA) biosynthesis. CoA is a crucial cofactor for cellular survival and inhibiting its synthesis will result in cell death. Bacterial PPCS differs from eukaryotic PPCS in a number of ways like it exists as a C-terminal domain of a PPCDC/PPCS fusion protein whereas eukaryotic PPCS exists as an independent protein. This difference makes it an attractive drug target. For which a conventional iterative approach of SBDD (structure-based drug design) was used, which began with three-dimensional structure prediction of AbPPCS using PHYRE 2.0. A database of FDA-approved compounds (Drug Bank) was then screened against the target of interest by means of docking score and glide energy, leading to the identification of 6 prominent drug candidates. The shortlisted 6 molecules were further subjected to all-atom MD simulation studies in explicit-solvent conditions (using AMBER force field). The MD simulation studies revealed that the ligands DB65103, DB449108 and DB443210, maintained several H-bonds with intense van der Waals contacts at the active site of the protein with high binding free energies: -11.42 kcal/mol, -10.49 kcal/mol and -10.98 kcal/mol, respectively, calculated via MM-PBSA method. Overall, binding of these compounds at the active site was found to be the most stable and robust highlighting the potential of these compounds to serve as antibacterials.Communicated by Ramaswamy H. Sarma.

Mechanistic insights into the role of calcium in the allosteric regulation of the calmodulin-regulated death-associated protein kinase

Calcium (Ca²⁺) signaling plays an important role in the regulation of many cellular functions. Ca²⁺-binding protein calmodulin (CaM) serves as a primary effector of calcium function. Ca²⁺/CaM binds to the death-associated protein kinase 1 (DAPK1) to regulate intracellular signaling pathways. However, the mechanism underlying the influence of Ca²⁺ on the conformational dynamics of the DAPK1-CaM interactions is still unclear. Here, we performed large-scale molecular dynamics (MD) simulations of the DAPK1-CaM complex in the Ca²⁺-bound and-unbound states to reveal the importance of Ca²⁺. MD simulations revealed that removal of Ca²⁺ increased the anti-correlated inter-domain motions between DAPK1 and CaM, which weakened the DAPK1-CaM interactions. Binding free energy calculations validated the decreased DAPK1-CaM interactions in the Ca²⁺-unbound state. Structural analysis further revealed that Ca²⁺ removal caused the significant conformational changes at the DAPK1-CaM interface, especially the helices α1, α2, α4, α6, and α7 from the CaM and the basic loop and the phosphate-binding loop from the DAPK1. These results may be useful to understand the biological role of Ca²⁺ in physiological processes.

Modeling structural interconversion in Alzheimers' amyloid beta peptide with classical and intrinsically disordered protein force fields

A comprehensive understanding of the aggregation mechanism in amyloid beta 42 (Aβ42) peptide is imperative for developing therapeutic drugs to prevent or treat Alzheimer's disease. Because of the high flexibility and lack of native tertiary structures of Aβ42, molecular dynamics (MD) simulations may help elucidate the peptide's dynamics with atomic details and collectively improve ensembles not seen in experiments. We applied microsecond-timescale MD simulations to investigate the dynamics and conformational changes of Aβ42 by using a newly developed Amber force field (ff14IDPSFF). We compared the ff14IDPSFF and the regular ff14SB force field by examining the conformational changes of two distinct Aβ42 monomers in explicit solvent. Conformational ensembles obtained by simulations depend on the force field and initial structure, Aβ42^α-helix or Aβ42^β-strand. The ff14IDPSFF sampled a high ratio of disordered structures and diverse β-strand secondary structures; in contrast, ff14SB favored helicity during the Aβ42^α-helix simulations. The conformations obtained from Aβ42^β-strand simulations maintained a balanced content in the disordered and helical structures when simulated by ff14SB, but the conformers clearly favored disordered and β-sheet structures simulated by ff14IDPSFF. The results obtained with ff14IDPSFF qualitatively reproduced the NMR chemical shifts well. In-depth peptide and cluster analysis revealed some characteristic features that may be linked to early onset of the fibril-like structure. The C-terminal region (mainly M35-V40) featured in-registered anti-parallel β-strand (β-hairpin) conformations with tested systems. Our work should expand the knowledge of force field and structure dependency in MD simulations and reveals the underlying structural mechanism-function relationship in Aβ42 peptides. Communicated by Ramaswamy H. Sarma.

Harmonizing Interstrand Electrostatic Repulsion by Conformational Rigidity in Counterion-Deprived Z-DNA: A Molecular Dynamics Study

Deoxyribonucleic acid (DNA) is a vital biomacromolecule. Although the right-handed B-DNA type helical structure is the most abundant and extensively studied form of DNA, several noncanonical forms, such as triplex, quadruplex, Z-DNA, A-DNA, and ss-DNA, have been probed from time to time to gain insights into the DNA's function. Z-DNA was recently found to be involved in cancer and several autoimmune diseases. In the present Article, we evaluated the conformational stability of locked-sugar-based Z-DNA via all-atom explicit-solvent molecular dynamics simulations and found that the modified DNA maintained the left-handed conformation even in the absence of counterions, wherein the structural rigidity dominates over the electrostatic repulsion between the complementary strands. The control Z-DNA without counterions, as expected, instantaneously resulted in unfolded states. The remarkable stability of the conformationally locked model system was thoroughly investigated via structural and energetic perspectives and was probably the result of the backbone widening in tandem with enhanced electrostatics between complementary strands. We believe that the design of the proposed modified Z-DNA construct could help understand the otherwise delicate Z-DNA conformation even in salt-deprived conditions. The design could also motivate the medicinal use of short segments of such modified nucleotides and could be utilized in more advanced modeling techniques, such as DNA origami which has gained popularity in recent years.

Discovery and Mechanistic Investigation of Piperazinone Phenylalanine Derivatives with Terminal Indole or Benzene Ring as Novel HIV-1 Capsid Modulators

HIV-1 capsid (CA) performs multiple roles in the viral life cycle and is a promising target for antiviral development. In this work, we describe the design, synthesis, assessment of antiviral activity, and mechanistic investigation of 20 piperazinone phenylalanine derivatives with a terminal indole or benzene ring. Among them, F₂-7f exhibited moderate anti-HIV-1 activity with an EC₅₀ value of 5.89 μM, which was slightly weaker than the lead compound PF74 (EC₅₀ = 0.75 μM). Interestingly, several compounds showed a preference for HIV-2 inhibitory activity, represented by 7f with an HIV-2 EC₅₀ value of 4.52 μM and nearly 5-fold increased potency over anti-HIV-1 (EC₅₀ = 21.81 μM), equivalent to PF74 (EC₅₀ = 4.16 μM). Furthermore, F₂-7f preferred to bind to the CA hexamer rather than to the monomer, similar to PF74, according to surface plasmon resonance results. Molecular dynamics simulation indicated that F₂-7f and PF74 bound at the same site. Additionally, we computationally analyzed the ADMET properties for 7f and F₂-7f. Based on this analysis, 7f and F₂-7f were predicted to have improved drug-like properties and metabolic stability over PF74, and no toxicities were predicted based on the chemotype of 7f and F₂-7f. Finally, the experimental metabolic stability results of F₂-7f in human liver microsomes and human plasma moderately correlated with our computational prediction. Our findings show that F₂-7f is a promising small molecule targeting the HIV-1 CA protein with considerable development potential.

MDSCAN: RMSD-based HDBSCAN clustering of long molecular dynamics

MOTIVATION

The term clustering designates a comprehensive family of unsupervised learning methods allowing to group similar elements into sets called clusters. Geometrical clustering of molecular dynamics (MD) trajectories is a well-established analysis to gain insights into the conformational behavior of simulated systems. However, popular variants collapse when processing relatively long trajectories because of their quadratic memory or time complexity. From the arsenal of clustering algorithms, HDBSCAN stands out as a hierarchical density-based alternative that provides robust differentiation of intimately related elements from noise data. Although a very efficient implementation of this algorithm is available for programming-skilled users (HDBSCAN*), it cannot treat long trajectories under the de facto molecular similarity metric RMSD.

RESULTS

Here, we propose MDSCAN, an HDBSCAN-inspired software specifically conceived for non-programmers users to perform memory-efficient RMSD-based clustering of long MD trajectories. Methodological improvements over the original version include the encoding of trajectories as a particular class of vantage-point tree (decreasing time complexity), and a dual-heap approach to construct a quasi-minimum spanning tree (reducing memory complexity). MDSCAN was able to process a trajectory of 1 million frames using the RMSD metric in about 21 h with <8 GB of RAM, a task that would have taken a similar time but more than 32 TB of RAM with the accelerated HDBSCAN* implementation generally used.

AVAILABILITY AND IMPLEMENTATION

The source code and documentation of MDSCAN are free and publicly available on GitHub (https://github.com/LQCT/MDScan.git) and as a PyPI package (https://pypi.org/project/mdscan/).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Cluster Analysis in Liquids: A Novel Tool in TRAVIS

We present a novel cluster analysis implemented in our open-source software TRAVIS and its application to realistic and complex chemical systems. The underlying algorithm is exclusively based on atom distances. Using a two-dimensional model system, we first introduce different cluster analysis functions and their application to single snapshots and trajectories including periodicity and temporal propagation. Using molecular dynamics simulations of pure water with varying system size, we show that our cluster analysis is size-independent. Furthermore, we observe a similar clustering behavior of pure water in classical and ab initio molecular dynamics simulations, showing that our cluster analysis is universal. In order to emphasize the application to more complex systems and mixtures, we additionally apply the cluster analysis to ab initio molecular dynamics simulations of the [C₂C₁Im][OAc] ionic liquid and its mixture with water. Using that, we show that our cluster analysis is able to analyze the clustering of the individual components in a mixture as well as the clustering of the ionic liquid with water.

Duplex DNA Retains the Conformational Features of Single Strands: Perspectives from MD Simulations and Quantum Chemical Computations

Molecular dynamics simulations and geometry optimizations carried out at the quantum level as well as by quantum mechanical/molecular mechanics methods predict that short, single-stranded DNA oligonucleotides adopt conformations very similar to those observed in crystallographic double-stranded B-DNA, with rise coordinates close to ≈3.3 Å. In agreement with the experimental evidence, the computational results show that DNA single strands rich in adjacent purine nucleobases assume more regular arrangements than poly-thymine. The preliminary results suggest that single-stranded poly-cytosine DNA should also retain a substantial helical order in solution. A comparison of the structures of single and double helices confirms that the B-DNA motif is a favorable arrangement also for single strands. Indeed, the optimal geometry of the complementary single helices is changed to a very small extent in the formation of the duplex.

Molecular engineering and activity improvement of acetylcholinesterase inhibitors: Insights from 3D-QSAR, docking, and molecular dynamics simulation studies

The carbamate molecule rivastigmine was found to possess promising anti-acetylcholinesterase activity, enabling to target and occupy choline binding sites, and as a result, widely used to improve the treatment of Alzheimer's disease (AD). Higher dose of rivastigmine indicates rapid onset but more adverse effects, such as the large fluctuations in plasma concentration level and frequent incidence of gastrointestinal side effect. To solve the dilemma, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR), docking and molecular dynamics (MD) simulation strategy to construct a dismountable nanoplatform of inhibitor engineering, verification and application for improving the inhibitory activity per unit concentration. With the aid of 3D-QSAR method, we constructed a model by using 25 molecules reported, and verified well the rationality of these QSAR models by non-cross validation coefficient (r² = 0.902). Docking and MD results show that rivastigmine, as a control, does target exactly the binding sites of acetylcholinesterase, those already observed experimentally, in turn, confirming the reliability of the present 3D-QSAR results. The method suggests that groups with electron-donating chemical property can improve the inhibitory activity, and screens out two novel inhibitors L-1 and L-2 with more activity from database (about 8000 compounds). Moreover, L-1 and L-2 not only target exactly the same binding sites of acetylcholinesterase as the rivastigmine does, but also hold stronger binding energy, showing a more powerful inhibitory ability. More broadly, this work showcases an approach in the engineering of carbamate inhibitors to enhance their inhibitory activity using electron-donating groups, which simplifies the design process of complex bioactive molecules.

Free Energy Calculations Using the Movable Type Method with Molecular Dynamics Driven Protein–Ligand Sampling

Fast and accurate biomolecular free energy estimation has been a significant interest for decades, and with recent advances in computer hardware, interest in new method development in this field has even grown. Thorough configurational state sampling using molecular dynamics (MD) simulations has long been applied to the estimation of the free energy change corresponding to the receptor-ligand complexing process. However, performing large-scale simulation is still a computational burden for the high-throughput hit screening. Among molecular modeling tools, docking and scoring methods are widely used during the early stages of the drug discovery process in that they can rapidly generate discrete receptor-ligand binding modes and their individual binding affinities. Unfortunately, the lack of thorough conformational sampling in docking and scoring protocols leads to difficulty discovering global minimum binding modes on a complicated energy landscape. The Movable Type (MT) method is a novel absolute binding free energy approach which has demonstrated itself to be robust across a wide range of targets and ligands. Traditionally, the MT method is used with protein-ligand binding modes generated with rigid-receptor or flexible-receptor (induced fit) docking protocols; however, these protocols are by their nature less likely to be effective with more highly flexible targets or with those situations in which binding involves multiple step pathways. In these situations, more thorough samplings are required to better explain the free energy of binding. Therefore, to explore the prediction capability and computational efficiency of the MT method when using more thorough protein-ligand conformational sampling protocols, in the present work, we introduced a series of binding mode modeling protocols ranging from conventional docking routines to single-trajectory conventional molecular dynamics (cMD) and parallel Monte Carlo molecular dynamics (MCMD). Through validation against several structurally and mechanistically diverse protein-ligand test sets, we explore the performance of the MT method as a virtual screening tool to work with the docking protocols and as an MD simulation-based binding free energy tool.

Folding Coarse-Grained Oligomer Models with PyRosetta

Non-biological foldamers are a promising class of macromolecules that share similarities to classical biopolymers such as proteins and nucleic acids. Currently, designing novel foldamers is a non-trivial process, often involving many iterations of trial synthesis and characterization until folded structures are observed. In this work, we aim to tackle these foldamer design challenges using computational modeling techniques. We developed CG PyRosetta, an extension to the popular protein folding python package, PyRosetta, which introduces coarse-grained (CG) residues into PyRosetta, enabling the folding of toy CG foldamer models. Although these models are simplified, they can help explore overarching physical hypotheses about how oligomers can form. Through systematic variation of CG parameters in these models, we can investigate various folding hypotheses at the CG scale to inform the design process of new foldamer chemistries. In this study, we demonstrate CG PyRosetta's ability to identify minimum energy structures with a diverse structural search over a range of simple models, as well as two hypothesis-driven parameter scans investigating the effects of side-chain size and internal backbone angle on secondary structures. We are able to identify several types of secondary structures from single- and double-helices to sheet-like and knot-like structures. We show how side-chain size and backbone bond angle both play an important role in the structure and energetics of these toy models. Optimal side-chain sizes promote favorable packing of side chains, while specific backbone bond angles influence the specific helix type found in folded structures.

Staphylococcus aureus Exfoliative Toxin E, Oligomeric State and Flip of P186: Implications for Its Action Mechanism

Staphylococcal exfoliative toxins (ETs) are glutamyl endopeptidases that specifically cleave the Glu381-Gly382 bond in the ectodomains of desmoglein 1 (Dsg1) via complex action mechanisms. To date, four ETs have been identified in different Staphylococcus aureus strains and ETE is the most recently characterized. The unusual properties of ETs have been attributed to a unique structural feature, i.e., the 180° flip of the carbonyl oxygen (O) of the nonconserved residue 192/186 (ETA/ETE numbering), not conducive to the oxyanion hole formation. We report the crystal structure of ETE determined at 1.61 Å resolution, in which P186(O) adopts two conformations displaying a 180° rotation. This finding, together with free energy calculations, supports the existence of a dynamic transition between the conformations under the tested conditions. Moreover, enzymatic assays showed no significant differences in the esterolytic efficiency of ETE and ETE/P186G, a mutant predicted to possess a functional oxyanion hole, thus downplaying the influence of the flip on the activity. Finally, we observed the formation of ETE homodimers in solution and the predicted homodimeric structure revealed the participation of a characteristic nonconserved loop in the interface and the partial occlusion of the protein active site, suggesting that monomerization is required for enzymatic activity.

Understanding gilteritinib resistance to FLT3-F691L mutation through an integrated computational strategy

FMS-like tyrosine kinase 3 (FLT3) serves as an important drug target for acute myeloid leukemia (AML), and gene mutations of FLT3 have been closely associated with AML patients with an incidence rate of ~ 30%. However, the mechanism of the clinically relevant F691L gatekeeper mutation conferred resistance to the drug gilteritinib remained poorly understood. In this study, multiple microsecond molecular dynamics (MD) simulations, end-point free energy calculations, and dynamic correlated and network analyses were performed to investigate the molecular basis of gilteritinib resistance to the FLT3-F691L mutation. The simulations revealed that the resistant mutation largely induced the conformational changes of the activation loop (A-loop), the phosphate-binding loop, and the helix αC of the FLT3 protein. The binding abilities of the gilteritinib to the wild-type and the F691L mutant were different through the binding free energy prediction. The simulation results further indicated that the driving force to determine the binding affinity of gilteritinib was derived from the differences in the energy terms of electrostatic and van der Waals interactions. Moreover, the per-residue free energy decomposition suggested that the four residues (Phe803, Gly831, Leu832, and Ala833) located at the A-loop of FLT3 had a significant impact on the binding affinity of gilteritinib to the F691L mutant. This study may provide useful information for the design of novel FLT3 inhibitors specially targeting the F691L gatekeeper mutant.

Emerging frontiers in virtual drug discovery: From quantum mechanical methods to deep learning approaches

Virtual screening-based approaches to discover initial hit and lead compounds have the potential to reduce both the cost and time of early drug discovery stages, as well as to find inhibitors for even challenging target sites such as protein-protein interfaces. Here in this review, we provide an overview of the progress that has been made in virtual screening methodology and technology on multiple fronts in recent years. The advent of ultra-large virtual screens, in which hundreds of millions to billions of compounds are screened, has proven to be a powerful approach to discover highly potent hit compounds. However, these developments are just the tip of the iceberg, with new technologies and methods emerging to propel the field forward. Examples include novel machine-learning approaches, which can reduce the computational costs of virtual screening dramatically, while progress in quantum-mechanical approaches can increase the accuracy of predictions of various small molecule properties.

Water-Controlled Keto-Enol Tautomerization of a Prebiotic Nucleobase

Barbituric acid is believed to be a proto-RNA nucleobase that was used for biological information transfer on prebiotic earth before DNA and RNA in their present forms evolved. Nucleobases have various tautomeric forms and the relative stability of these forms is critical to their biological function. It has been shown that barbituric acid has a tri-keto form in the gas phase and an enol form in the solid state. However, its dominant tautomeric form in aqueous medium that is most relevant for biology has been investigated only to a limited extent and the findings are inconclusive. We have used multiple approaches, namely, molecular dynamics, quantum chemistry, NMR, and IR spectroscopy to determine the most stable tautomer of barbituric acid in solution. We find a delicate balance in the stability of the two tautomers, tri-keto and enol, which is tipped toward the enol as the extent of solvation by water increases.

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.

Mechanistic Insights into the Mechanism of Inhibitor Selectivity toward the Dark Kinase STK17B against Its High Homology STK17A

As a member of the death-associated protein kinase (DAPK) family, STK17B plays an important role in the regulation of cellular apoptosis and has been considered as a promising drug target for hepatocellular carcinoma. However, the highly conserved ATP-binding site of protein kinases represents a challenge to design selective inhibitors for a specific DAPK isoform. In this study, molecular docking, multiple large-scale molecular dynamics (MD) simulations, and binding free energy calculations were performed to decipher the molecular mechanism of the binding selectivity of PKIS43 toward STK17B against its high homology STK17A. MD simulations revealed that STK17A underwent a significant conformational arrangement of the activation loop compared to STK17B. The binding free energy predictions suggested that the driving force to control the binding selectivity of PKIS43 was derived from the difference in the protein–ligand electrostatic interactions. Furthermore, the per-residue free energy decomposition unveiled that the energy contribution from Arg41 at the phosphate-binding loop of STK17B was the determinant factor responsible for the binding specificity of PKIS43. This study may provide useful information for the rational design of novel and potent selective inhibitors toward STK17B.