GPU-Accelerated Molecular Dynamics and Free Energy Methods in Amber18: Performance Enhancements and New Features

Accelerated molecular dynamics study to compare the thermostability of Bacillus licheniformis and Aspergillus niger α-amylase

The thermostability of enzymes plays a significant role in the starch hydrolysis process in the industry. The structural difference between thermostable Bacillus licheniformis α-amylase (BLA) and thermolabile Aspergillus niger α-amylase (ANA) is interesting to be explored. This work aimed to study the thermostability-determining factor of BLA as compared to a non-thermostable enzyme, ANA, using molecular dynamics (MD) simulation at a high temperature. A 100 ns of classical MD, which was followed by 200 ns accelerated MD was conducted to explore the conformational changes of the enzyme. It is revealed that the intramolecular interactions through salt bridge interactions and the presence of calcium ions dominates the stability effect of BLA, despite the absence of a disulfide bond in the structure. These results should be useful in designing a thermostable enzyme that can be used in industrial processes.Communicated by Ramaswamy H. Sarma.

The Kinetics of Carbon-Carbon Bond Formation in Metazoan Fatty Acid Synthase and Its Impact on Product Fidelity

Fatty acid synthase (FAS) multienzymes are responsible for de novo fatty acid biosynthesis and crucial in primary metabolism. Despite extensive research, the molecular details of the FAS catalytic mechanisms are still poorly understood. For example, the β-ketoacyl synthase (KS) catalyzes the fatty acid elongating carbon-carbon-bond formation, which is the key catalytic step in biosynthesis, but factors that determine the speed and accuracy of his reaction are still unclear. Here, we report enzyme kinetics of the KS-mediated carbon-carbon bond formation, enabled by a continuous fluorometric activity assay. We observe that the KS is likely rate-limiting to the fatty acid biosynthesis, its kinetics are adapted to the length of the bound fatty acyl chain, and that the KS is also responsible for the fidelity of biosynthesis by preventing intermediates from undergoing KS-mediated elongation. To provide mechanistic insight into KS selectivity, we performed computational molecular dynamics (MD) simulations. We identify positive cooperativity of the KS dimer, which we suggest to affect the conformational variability of the multienzyme. Advancing our knowledge about the KS molecular mechanism will pave the ground for engineering FAS for biotechnology applications and the design of new therapeutics targeting the fatty acid metabolism.

Combating COVID-19 and its co-infection by Aspergillus tamarii SP73-EGY using in vitro and in silico Studies

The COVID-19 pandemic has caused significant mortality and morbidity for millions of people. Severe Acute Respiratory Syndrome-2 (SARS-CoV-2) virus is capable of causing severe and fatal diseases. We evaluated the antiviral properties of Aspergillus tamarii SP73-EGY isolate extract against low pathogenic coronavirus (229E), Adeno-7- and Herpes-2 viruses. The extract showed a high selectivity index (SI = 43.4) and a significant inhibition of 229E (IC50 = 8.205 μg/ml). It was stronger than the drug control, remdesivir (IC50 = 38.2 μg/ml, SI = 7.29). However, the extract showed minimal efficacy against Adeno-7- and Herpes-2-Viruses (IC50 = 22.52, 47.79 μg/ml, and SI = 6.75, 5.08, respectively). It exhibited profound efficacy against the highly pathogenic SARS-CoV-2 (IC50 = 8.306 μg/ml, SI = 42.2). Kojic acid, the primary component of the extract, showed substantial antiviral activity against SARS-CoV-2 (IC50 = 23.4 μg/ml, SI = 5.6), Remdesivir (IC50 = 4.55 μg/ml, SI = 61.45). Therefore, the extract demonstrated the most notable antiviral characteristics against coronavirus infection. Co-infecting microorganisms may contribute to immune system deterioration and airway injury caused by SARS-CoV-2. The extract showed significant efficacy against E. coli and P. aeruginosa, with an inhibition range of 3.5-10 mm at a concentration of 200 mg/ml. A molecular docking study showed that hexadecanoic, Kojic, octanoic acids, and 4(4-Methylbenzylidene)cyclohexane-1,3-dione have stronger binding affinity to the SARS-CoV-2 Mpro than Remdesivir. Molecular dynamics simulations were employed to examine the structural stability and flexibility of these complexes. This confirmed the high binding affinities of Kojic acid and 4(4-Methylbenzylidene)cyclohexane-1,3-dione, thereby proving their potential as novel anti-SARS-CoV-2.

Insights into in vitro and in silico studies of α-glucosidase inhibitors isolated from the leaves of Grewia optiva (Malvaceae)

α-Glucosidase plays a critical role in glucose metabolism by breaking down complex carbohydrates into simpler sugars for intestinal absorption. Due to the side effects of current α-glucosidase inhibitors, there is increasing interest in exploring alternative therapeutic options. Inspired by the traditional uses of Grewia optiva J.R.Drumm. ex Burret (Malvaceae family) as an anti-diabetic herb, we isolated gnaphaffine A (1), a cyclic glycosylated homolignan, together with kaempferol derivatives (trans-tiliroside 2, cis-tiliroside 3, and astragalin 4) from the ethyl acetate fraction. In vitro antioxidant assays revealed that 1 exhibited anti-DPPH• and anti-ABTS+• activity (IC50 of 39.42 and 52.84 μg/mL, respectively), comparable to ascorbic acid (IC50 of 43.34 and 47.56 μg/mL, respectively). Moreover, 1 demonstrated a seven-fold stronger inhibition of α-glucosidase activity than acarbose (IC50 of 8.2 and 57.8 μg/mL, respectively). Importantly, 1 was non-toxic to AC16 normal cardiomyocyte cell lines. Computational analyses identified two key factors contributing to the α-glucosidase inhibitory activity of 1: (a) hydrogen bonding interactions with catalytic residues (E277 and D352) and (b) a calculated ∆Gbind of -51.20 kcal/mol. Furthermore, 3 showed the most favorable in silico binding profile, with the highest ∆Gbind (-55.89 kcal/mol) and higher hydrogen bond occupancy compared to 1 and 2. These findings suggest that 1 and 3 may serve as promising lead compounds for the development of new α-glucosidase drugs.

Dual BACH1 regulation by complementary SCF-type E3 ligases

Broad-complex, tramtrack, and bric-à-brac domain (BTB) and CNC homolog 1 (BACH1) is a key regulator of the cellular oxidative stress response and an oncogene that undergoes tight post-translational control by two distinct F-box ubiquitin ligases, SCFFBXO22 and SCFFBXL17. However, how both ligases recognize BACH1 under oxidative stress is unclear. In our study, we elucidate the mechanism by which FBXO22 recognizes a quaternary degron in a domain-swapped β-sheet of the BACH1 BTB dimer. Cancer-associated mutations and cysteine modifications destabilize the degron and impair FBXO22 binding but simultaneously expose an otherwise shielded degron in the dimer interface, allowing FBXL17 to recognize BACH1 as a monomer. These findings shed light on a ligase switch mechanism that enables post-translational regulation of BACH1 by complementary ligases depending on the stability of its BTB domain. Our results provide mechanistic insights into the oxidative stress response and may spur therapeutic approaches for targeting oxidative stress-related disorders and cancer.

How Do Variants of Residues in the First Coordination Sphere, Second Coordination Sphere, and Remote Areas Influence the Catalytic Mechanism of Non-Heme Fe(II)/2-Oxoglutarate Dependent Ethylene-Forming Enzyme?

The ethylene-forming enzyme (EFE) is a Fe(II)/2-oxoglutarate (2OG) and l-arginine (l-Arg)-dependent oxygenase that primarily decomposes 2OG into ethylene while also catalyzing l-Arg hydroxylation. While the hydroxylation mechanism in EFE is similar to other Fe(II)/2OG-dependent oxygenases, the formation of ethylene is unique. Various redesign strategies have aimed to increase ethylene production in EFE, but success has been limited, highlighting the need for alternate approaches. It is crucial to incorporate an accurate and comprehensive description of the integrative and multidimensional effects of the protein environment to enhance the redesign strategy in metalloenzymes, particularly in EFE. This involves understanding the role of the second coordination sphere (SCS) and long-range (LR) interacting residues, correlated motions, electronic structure, intrinsic electric field (IntEF), as well as the stabilization of transition states and reaction intermediates. In this study, we employ a molecular dynamics-based quantum mechanics/molecular mechanics approach to examine the integrative effects of the protein environment on reactions catalyzed by EFE variants from the first coordination sphere (FCS, D191E), SCS (A198V and R171A) and LR (E215A). The study uncovers how substitutions at different positions in EFE similarly impact the ethylene-forming reaction while posing distinct effects on the hydroxylation reaction. Results predict the effect of the variants in controlling the 2OG coordination mode in the Fe(II) center. Specifically, the study suggests that D191E uniquely prefers transitioning from an off-line to an in-line 2OG coordination mode before dioxygen binding. However, studies on the 2OG flip in the presence of off-line approaching dioxygen and dioxygen binding in the D191E variant indicate that the 2OG flip might not be feasible in the 5C Fe(II) state. Calculations show the possibility of a hydrogen atom transfer (HAT)-assisted oxygen flip in EFE and its variants (other than D191E). MD simulations elucidate the characteristic dynamic change in the α7 region in the D191E variant that might contribute to its increased hydroxylation reaction. Results indicate the possibility of forming an in-line ferryl from the IM2 (Fe(III)-partial bond intermediate) in the D191E variant. This alternative pathway from IM2 may also exist in WT EFE and other variants, which are yet to be explored. The study also delineates the impact of substitutions on the electronic structure and IntEF. Overall, the calculations support the idea that understanding the integrative and multidimensional effects of the protein environment on the reactions catalyzed by EFE variants provides the basics for improved enzyme redesign protocols of EFE to increase ethylene production. The results of this study will also contribute to the development of alternate redesign strategies for other metalloenzymes.

Investigating pH-induced conformational switch in PIM-1: An integrated multi spectroscopic and MD simulation study

PIM-1 is a Ser/Thr kinase, which has been extensively studied as a potential target for cancer therapy due to its significant roles in various cancers, including prostate and breast cancers. Given its importance in cancer, researchers are investigating the structure of PIM-1 for pharmacological inhibition to discover therapeutic intervention. This study examines structural and conformational changes in PIM-1 across different pH using various spectroscopic and computational techniques. Spectroscopic results indicate that PIM-1 maintains its secondary and tertiary structure within the pH range of 7.0-9.0. However, protein aggregation occurs in the acidic pH range of 5.0-6.0. Additionally, kinase assays suggested that PIM-1 activity is optimal within the pH range of 7.0-9.0. Subsequently, we performed a 100 ns all-atom molecular dynamics (MD) simulation to see the effect of pH on PIM-1 structural stability at the molecular level. MD simulation analysis revealed that PIM-1 retains its native conformation in alkaline conditions, with some residual fluctuations in acidic conditions as well. A strong correlation was observed between our MD simulation, spectroscopic, and enzymatic activity studies. Understanding the pH-dependent structural changes of PIM-1 can provide insights into its role in disease conditions and cellular homeostasis, particularly regarding protein function under varying pH conditions.

Impact of water models on the structure and dynamics of enzyme tunnels

Protein hydration plays a vital role in many biological functions, and molecular dynamics simulations are frequently used to study it. However, the accuracy of these simulations is often sensitive to the water model used, a phenomenon particularly evident in intrinsically disordered proteins. Here, we investigated the extent to which the choice of water model alters the behavior of complex networks of tunnels within proteins. Tunnels are essential because they allow the exchange of substrates and products between buried enzyme active sites and the bulk solvent, directly affecting enzyme efficiency and selectivity, making the study of tunnels crucial for a holistic understanding of enzyme function at the molecular level. By performing simulations of haloalkane dehalogenase LinB and its two variants with engineered tunnels using TIP3P and OPC models, we investigated their effects on the overall tunnel topology. We also analyzed the properties of the primary tunnels, including their conformation, bottleneck dimensions, sampling efficiency, and the duration of tunnel openings. Our data demonstrate that all three proteins exhibited similar conformational behavior in both models but differed in the geometrical characteristics of their auxiliary tunnels, consistent with experimental observations. Interestingly, the results indicate that the stability of the open tunnels might be sensitive to the water model used. Because TIP3P can provide comparable data on the overall tunnel network, it is a valid choice when computational resources are limited or compatibility issues impede the use of OPC. However, OPC seems preferable for calculations requiring an accurate description of transport kinetics.

Selective Protonation of Catalytic Dyad for γ-Secretase-Mediated Hydrolysis Revealed by Multiscale Simulations

γ-Secretase plays a crucial role in producing disease-related amyloid-β proteins by cleaving the amyloid precursor protein (APP). The enzyme employs its catalytic dyad containing two aspartates (Asp257 and Asp385) to hydrolyze the substrate by a general acid-base catalytic mechanism, necessitating monoprotonation of the two aspartates for efficient hydrolysis. However, the precise protonation states of the aspartates remain uncertain. In this study, we employed a multiscale computational approach to investigate the dependence of the catalytic efficiency of γ-secretase on the protonation states of its catalytic dyad. Over 200 ms unbiased atomistic simulations of the substrate-enzyme complex reveal diverse orientations of the scissile bond of the bound substrate and accessible structural ensembles of the catalytic dyad with Asp257-Asp385 distances fluctuating between 4 and 10 Å. With a quantum mechanics/molecular mechanics (QM/MM) approach accelerated by enhanced sampling techniques, we find that the first step of the hydrolysis reaction, i.e., the formation of a gem-diol intermediate, experiences a higher reaction barrier by ∼2 kcal/mol when Asp385 is protonated. Furthermore, we find that Arg269 of the enzyme is most likely responsible for this preference of the protonation state: its basic side chain is spatially close to that of Asp257 and specifically stabilizes the transition state electrostatically when Asp257 is protonated. Collectively, our study suggests that Asp257 is likely the favored protonation site for APP cleavage by γ-secretase.

Unraveling the Molecular Determinants of Catalytic Efficiency and Substrate Specificity in l-Amino Acid Decarboxylases

l-Tryptophan decarboxylase (TDC) and l-3,4-dihydroxyphenylalanine decarboxylase (DDC) catalyze the decarboxylation of l-tryptophan, 5-hydroxytryptophan, and l-3,4-dihydroxyphenylalanine. In this study, we analyzed the amino acid compositions of the substrate-binding pockets of TDC from Catharanthus roseus (CrTDC) and DDC from Sus scrofa (SsDDC), explored the specificity of key amino acids within these pockets, and elucidated mechanisms influencing substrate selectivity and catalytic activity in both enzymes, using whole-cell catalysis to screen mutants and determine enzymatic kinetic parameters. The results demonstrated that residues Ala-103 and Val-122 in CrTDC, along with their corresponding sites Thr-82 and Ile-101 in SsDDC, significantly influence substrate selectivity and catalytic efficiency. Molecular dynamics simulations revealed that substrate selectivity and catalytic efficiency depends on the nucleophilic attack distance between the substrate's amino group and the C4' of pyridoxal 5'-phosphate. This study elucidates the catalytic mechanisms and structural bases of TDC and DDC, guiding enhancements in the related aromatic monoamine biosynthesis.

Structure-guided design and evaluation of CRM197-scaffolded vaccine targeting GnRH for animal immunocastration

Immunocastration is a humane alternative to surgical castration for controlling population and estrous behaviors in animals. Gonadotropin-releasing hormone (GnRH), the pivotal initiating hormone of the hormonal cascade in mammals, is the optimal target for immunocastration vaccine development. Cognate antigen-mediated cross-linking of B cell receptors (BCRs) is a strong activation signal for B cells and is facilitated by repetitive surface organizations of antigens. In this study, we describe the structure-guided design of highly immunogenic chimeric proteins with variant numbers of GnRH peptide insertion by epitope grafting. Linear B-cell epitopes of cross-reacting material 197 (CRM197) were replaced with multiple copies of GnRH peptide, and the inserts were displayed on the surface of the designs while maintaining the overall folding of CRM197. Among the seven designs, TCG13, which carries 13 copies of GnRH peptide, was the most immunogenic, and its immunocastration efficacy was evaluated in male mice. Vaccination with the BFA03-adjuvanted TCG13 induced potent humoral immunity and reduced the serum testosterone concentration in mice. It could significantly decrease sperm quality and severely impair gonadal function and fertility. These results demonstrate that CRM197 holds great value as a scaffold for epitope presentation in peptide-based vaccine development and supports TCG13 as a promising vaccine candidate for animal immunocastration. KEY POINTS: • Provide a feasible way to design chimeric immunogen targeting GnRH by epitope grafting. • CRM197 can accommodate the insertion of multiple copies of heterologous epitope peptides. • Administration with the most immunogenic design led to effective immunocastration in male mice.

Bridging the Gap in the Structure-Function Paradigm of Enzymatic PET Degradation-Aromatic Residue Driven Balanced Interactions with Catalytic and Anchoring Subsite

Understanding all parameters contributing to enzyme activity is crucial in enzyme catalysis. For enzymatic PET degradation, this involves examining the formation of the enzyme-PET complex. In IsPETase (WT), a PET-degrading enzyme from Ideonella sakaiensis, mutating two non-catalytic residues (DM) significantly enhances activity. Such mutations, depending on their position in the tertiary structure, fine-tune enzyme function. However, detailed molecular insights into these mutations' structure-function relationship for PET degradation are lacking. This study characterizes IsPETase's catalytic ability compared to WT TfCut2 using molecular dynamics simulations and quantum mechanical methods. We explore the conformational landscape of the enzyme-PET complex and quantify residue-wise interaction energy. Notably, aromatic and hydrophobic residues Tyr, Trp, and Ile in the catalytic subsite S1, and aromatic Phe and polar Asn in the anchoring subsite S3, crucially optimize PET binding. These residues enhance PET specificity over non-aromatic plastics. Our findings suggest that the balance between binding at subsite S1 and subsite S3, which is influenced by cooperative mutations, underlies catalytic activity. This balance shows a positive correlation with experimentally obtained kcat/Km values: WT TfCut2 Collapse

Key Words

• Cooperative effect
• Enzyme catalysis
• IsPETase
• Molecular dynamics
• Mutation

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MESH Headings

• Molecular Dynamics Simulation
• Polyethylene Terephthalates/chemistry
• Polyethylene Terephthalates/metabolism
• Catalytic Domain
• Structure-Activity Relationship
• Burkholderiales/enzymology
• Biocatalysis
• Mutation
• Bacterial Proteins/chemistry
• Bacterial Proteins/metabolism
• Bacterial Proteins/genetics

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Grants

• CRG/2019/002891 DST
• SPG/2022/001350 DST
• SIR/2022/000924 DST
• University of Calicut

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Affiliation(s)

Anjima James Department of Applied Chemistry, Cochin University of Science and Technology, Thrikakkara, Kochi, Kerala, 682 022, India
Anjitha Bhasi Department of Applied Chemistry, Cochin University of Science and Technology, Thrikakkara, Kochi, Kerala, 682 022, India
Susmita De Department of Chemistry, University of Calicut, Calicut University P.O., Malappuram, Kerala, 673 635, India

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Restoring protein glycosylation with GlycoShape

Despite ground-breaking innovations in experimental structural biology and protein structure prediction techniques, capturing the structure of the glycans that functionalize proteins remains a challenge. Here we introduce GlycoShape ( https://glycoshape.org ), an open-access glycan structure database and toolbox designed to restore glycoproteins to their native and functional form in seconds. The GlycoShape database counts over 500 unique glycans so far, covering the human glycome and augmented by elements from a wide range of organisms, obtained from 1 ms of cumulative sampling from molecular dynamics simulations. These structures can be linked to proteins with a robust algorithm named Re-Glyco, directly compatible with structural data in open-access repositories, such as the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and AlphaFold Protein Structure Database, or own. The quality, performance and broad applicability of GlycoShape is demonstrated by its ability to predict N-glycosylation occupancy, scoring a 93% agreement with experiment, based on screening all proteins in the PDB with a corresponding glycoproteomics profile, for a total of 4,259 N-glycosylation sequons.

Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery

Computational methods constitute efficient strategies for screening and optimizing potential drug molecules. A critical factor in this process is the binding affinity between candidate molecules and targets, quantified as binding free energy. Among various estimation methods, alchemical transformation methods stand out for their theoretical rigor. Despite challenges in force field accuracy and sampling efficiency, advancements in algorithms, software, and hardware have increased the application of free energy perturbation (FEP) calculations in the pharmaceutical industry. Here, we review the practical applications of FEP in drug discovery projects since 2018, covering both ligand-centric and residue-centric transformations. We show that relative binding free energy calculations have steadily achieved chemical accuracy in real-world applications. In addition, we discuss alternative physics-based simulation methods and the incorporation of deep learning into free energy calculations.

NEAT1 modulates the TIRR/53BP1 complex to maintain genome integrity

Tudor Interacting Repair Regulator (TIRR) is an RNA-binding protein (RBP) that interacts directly with 53BP1, restricting its access to DNA double-strand breaks (DSBs) and its association with p53. We utilized iCLIP to identify RNAs that directly bind to TIRR within cells, identifying the long non-coding RNA NEAT1 as the primary RNA partner. The high affinity of TIRR for NEAT1 is due to prevalent G-rich motifs in the short isoform (NEAT1_1) region of NEAT1. This interaction destabilizes the TIRR/53BP1 complex, promoting 53BP1's function. NEAT1_1 is enriched during the G1 phase of the cell cycle, thereby ensuring that TIRR-dependent inhibition of 53BP1's function is cell cycle-dependent. TDP-43, an RBP that is implicated in neurodegenerative diseases, modulates the TIRR/53BP1 complex by promoting the production of the NEAT1 short isoform, NEAT1_1. Together, we infer that NEAT1_1, and factors regulating NEAT1_1, may impact 53BP1-dependent DNA repair processes, with implications for a spectrum of diseases.

Improvements in Precision of Relative Binding Free Energy Calculations Afforded by the Alchemical Enhanced Sampling (ACES) Approach

Accurate in silico predictions of how strongly small molecules bind to proteins, such as those afforded by relative binding free energy (RBFE) calculations, can greatly increase the efficiency of the hit-to-lead and lead optimization stages of the drug discovery process. The success of such calculations, however, relies heavily on their precision. Here, we show that a recently developed alchemical enhanced sampling (ACES) approach can consistently improve the precision of RBFE calculations on a large and diverse set of proteins and small molecule ligands. The addition of ACES to conventional RBFE calculations lowered the average hysteresis by over 35% (0.3-0.4 kcal/mol) and the average replicate spread by over 25% (0.2-0.3 kcal/mol) across a set of 10 protein targets and 213 small molecules while maintaining similar or improved accuracy. We show in atomic detail how ACES improved convergence of several representative RBFE calculations through enhancing the sampling of important slowly transitioning ligand degrees of freedom.

Assessment of the in vitro anti-diabetic activity with molecular dynamic simulations of limonoids isolated from Adalia lemon peels

Limonoids are important constituents of citrus that have a significant impact on promoting human health. Therefore, the primary focus of this research was to assess the overall limonoid content and isolate limonoids from Adalia lemon (Citrus limon L.) peels for their potential use as antioxidants and anti-diabetic agents. The levels of limonoid aglycones in the C. limon peel extract were quantified through a colorimetric assay, revealing a concentration of 16.53 ± 0.93 mg/L limonin equivalent. Furthermore, the total concentration of limonoid glucosides was determined to be 54.38 ± 1.02 mg/L. The study successfully identified five isolated limonoids, namely limonin, deacetylnomilin, nomilin, obacunone 17-O-β-D-glucopyranoside, and limonin 17-O-β-D-glucopyranoside, along with their respective yields. The efficacy of the limonoids-rich extract and the five isolated compounds was evaluated at three different concentrations (50, 100, and 200 µg/mL). It was found that both obacunone 17-O-β-D-glucopyranoside and limonin 17-O-β-D-glucopyranoside possessed the highest antioxidant, free radical scavenging, and anti-diabetic activities, followed by deacetylnomilin, and then the limonoids-rich extract. The molecular dynamic simulations were conducted to predict the behavior of the isolated compounds upon binding to the protein's active site, as well as their interaction and stability. The results revealed that limonin 17-O-β-D-glucopyranoside bound to the protein complex system exhibited a relatively more stable conformation than the Apo system. The analysis of Solvent Accessible Surface Area (SASA), in conjunction with the data obtained from Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), and Radius of Gyration (ROG) computations, provided further evidence that the limonin 17-O-β-D-glucopyranoside complex system remained stable within the catalytic domain binding site of the human pancreatic alpha-amylase (HPA)-receptor. The research findings suggest that the limonoids found in Adalia lemon peels have the potential to be used as effective natural substances in creating innovative therapeutic treatments for conditions related to oxidative stress and disorders in carbohydrate metabolism.

Engineering of pH-dependent antigen binding properties for toxin-targeting IgG1 antibodies using light-chain shuffling

Immunoglobulin G (IgG) antibodies that bind their cognate antigen in a pH-dependent manner (acid-switched antibodies) can release their bound antigen for degradation in the acidic environment of endosomes, while the IgGs are rescued by the neonatal Fc receptor (FcRn). Thus, such IgGs can neutralize multiple antigens over time and therefore be used at lower doses than their non-pH-responsive counterparts. Here, we show that light-chain shuffling combined with phage display technology can be used to discover IgG1 antibodies with increased pH-dependent antigen binding properties, using the snake venom toxins, myotoxin II and α-cobratoxin, as examples. We reveal differences in how the selected IgG1s engage their antigens and human FcRn and show how these differences translate into distinct cellular handling properties related to their pH-dependent antigen binding phenotypes and Fc-engineering for improved FcRn binding. Our study showcases the complexity of engineering pH-dependent antigen binding IgG1s and demonstrates the effects on cellular antibody-antigen recycling.

Ion-combination specific effects driving the enzymatic activity of halophilic alcohol dehydrogenase 2 from Haloferax volcanii in aqueous ionic liquid solvent mixtures

Biocatalysis in ionic liquids enables novel routes for bioprocessing. Enzymes derived from extremophiles promise greater stability and activity under ionic liquid (IL) influence. Here, we probe the enzyme alcohol dehydrogenase 2 from the halophilic archaeon Haloferax volcanii in thirteen different ion combinations for relative activity and analyse the results against molecular dynamics (MD) simulations of the same IL systems. We probe the ionic liquid property space based on ion polarizability and molecular electrostatic potential. Using the radial distribution functions, survival probabilities and spatial distribution functions of ions, we show that cooperative ion-ion interactions determine ion-protein interactions, and specifically, strong ion-ion interactions equate to higher enzymatic activity if neither of the ions interact strongly with the protein surface. We further demonstrate a tendency for cations interacting with the protein surface to be least detrimental to enzymatic activity if they show a low polarizability when combined with small hydrophilic anions. We also find that the IL ion influence is not mitigated by the surplus of negatively charged residues of the halophilic enzyme. This is shown by free energy landscape analysis in root mean square deviation and distance variation plots of active site gating residues (Trp43 and His273) demonstrating no protection of specific structural elements relevant to preserving enzymatic activity. On the other hand, we observe a general effect across all IL systems that a tight binding of water at acidic residues is preferentially interrupted at these residues through the increased presence of potassium ions. Overall, this study demonstrates a co-ion interaction dependent influence on allosteric surface residues controlling the active/inactive conformation of halophilic alcohol dehydrogenase 2 and the necessity to engineer ionic liquid systems for enzymes that rely on the integrity of functional surface residues regardless of their halophilicity or thermophilicity for use in bioprocessing.

Time-resolved fluorescence of tryptophan characterizes membrane perturbation by cyclic lipopeptides

Viscosin is a membrane-permeabilizing, cyclic lipopeptide (CLiP) produced by Pseudomonas species. Here, we have studied four synthetic analogs (L1W, V4W, L5W, and L7W), each with one leucine (Leu; L) or valine residue exchanged for tryptophan (Trp; W) by means of time-resolved fluorescence spectroscopy of Trp. To this end, we recorded the average fluorescence lifetime, rotational correlation time and limiting anisotropy, dipolar relaxation time and limiting extent of relaxation, rate constant of acrylamide quenching, effect of H2O-D2O exchange, and time-resolved half-width of the spectrum in the absence and presence of POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) liposomes. Structure, localization, and hydration of the peptides were described by molecular dynamics simulations. The combination of the parameters provides a good description of the molecular environments of the Trp positions and the behavior of viscosin as a whole. Of particular value for characterizing the impact of viscosin on the membrane is the dipolar relaxation of Trp4 in V4W, which is deeply embedded in the hydrophobic core. The limiting relaxation level represents the membrane perturbation-unlike typical membrane probes-at the site of the perturbant. Fractions of Trp4 relax at different rates; the one not in contact with water upon excitation relaxes via recruitment of a water molecule on the 10-ns timescale. This rate is sensitive to the concerted membrane perturbation by more than one lipopeptide, which appears at high lipopeptide concentration and is assumed a prerequisite for the final formation of a membrane-permeabilizing defect. Trp7 relaxes primarily with respect to neighboring Ser residues. Trp5 flips between a membrane-inserted and surface-exposed orientation.

Nano-Liposomal Beetroot Phyto-Pigment in Photodynamic Therapy as a Prospective Green Approach for Cancer Management: In Vitro Evaluation and Molecular Dynamic Simulation

Using plant extracts as photosensitizers in photodynamic therapy (PDT) represents a significant green approach toward sustainability. This study investigates beetroot juice (BRJ), betanin, and their liposomal formulations (Lip-BRJ, Lip-Bet) as photosensitizers in cancer PDT. BRJ was prepared, and its betanin content was quantified via HPLC. The p-nitrosodimethylaniline (RNO)/imidazole technique monitored the singlet oxygen formation. BRJ and betanin decreased the RNO absorbance at 440 nm by 12% and 9% after 45 min of irradiation, respectively. Furthermore, betanin interaction with Bcl-2 proteins was examined using binding free energy analysis and molecular dynamic simulation. The results revealed favorable interactions with ΔG values of -40.94 kcal/mol. Then, BRJ, betanin, Lip-BRJ, and Lip-Bet were tested as photosensitizers on normal (HEK 293) and human lung cancer (A549) cell lines. Irradiation significantly enhanced the cytotoxicity of Lip-Bet on HEK 293 cells (20% cell viability at 2000 µg/mL) and A549 cells (13% cell viability at 1000 µg/mL). For Lip-BRJ, irradiation significantly enhanced the cytotoxicity on HEK 293 cells at lower concentrations and on A549 cells at all tested concentrations. These results proved the positive effect of light and liposomal encapsulation on the anticancer activity of betanin and BRJ, suggesting the efficiency of liposomal beetroot pigments as green photosensitizers.

SARS-CoV-2 inhibitory potential of fish oil-derived 2-pyrone compounds by acquiring linoleic acid binding site on the spike protein

Traditional medicines have reportedly treated SARS-CoV-2 infection. Substantial evidence shows that fish oil supplements promote human immune function, suggesting they may lessen susceptibility to SARS-CoV-2 infection and suppress viral replication by inducing interferon. Fish oil was subjected to partition chromatography and separated into two compounds (EP01 and DH01). Isolated compounds were purified and characterized using UV, FTIR, NMR, and mass spectrometry to confirm their identity. Molecular docking was studied on the SARS CoV-2 variants of concern; SARS CoV-2 WT (PDB: 6VXX), SARS CoV-2 Alpha variant (PDB: 7LWS), SARS CoV-2 Delta variant (PDB: 7TOU), SARS CoV-2 Gamma variant (PDB: 7V78), SARS CoV-2 Kappa variant (PDB: 7VX9), and SARS CoV-2 Omicron variant (PDB: 7QO7) and TMPRSS2 (PDB: 7Y0E). Further selected protein-ligand complexes were subjected to 100 ns MD simulations to predict their biological potential in the SARS-CoV-2 treatment. In-vitro biological studies were carried out to support in-silico findings. Isolated compounds EP01 and DH01 were identified as 5-Tridecyltetrahydro-2H-pyran-2-one and 5-Heptadecyltetrahydro-2H-pyran-2-one, respectively. The compound EP01 significantly reduced (93.24 %) the viral RNA copy number with an IC50 of ~8.661 μM. EP01 proved to be a potent antiviral by in-vitro method against the SARS-CoV-2 clinical isolate, making it a promising antiviral candidate, with a single dose capable of preventing viral replication.

Pathways and mechanism of MRTX1133 binding to KRAS G12D elucidated by molecular dynamics simulations and Markov state models

KRAS G12D is the most common oncogenic mutation identified in several types of cancer. Therefore, design of inhibitors targeting KRAS G12D represents a promising strategy for anticancer therapy. MRTX1133 is a highly potent inhibitor (approximate experiment Kd ≈ 0.0002 nM) of KRAS G12D and is currently in Phase 1/2 study, however, pathways of the compound binding to KRAS G12D has remained unknown, and the mechanism underlying the complicated dynamic process are challenging to capture experimentally, which hinder the structure-based anti-cancer drug design. Here, using MRTX1133 as a probe, unbiased molecular dynamics (MD) was used to simulate the process of MRTX1133 spontaneously binding to KRAS G12D. In six of 42 independent MD simulation (a total of 99 μs), MRTX1133 was observed to successfully associate with KRAS G12D. The kinetically metastable states refer to the potential pathways of MRTX1133 binding to KRAS G12D were revealed by Markov state models (MSM) analysis. Additionally, 8 key residues that are essential for MRTX1133 recognition and tight binding at the preferred low energy states were identified by MM/GBSA analysis. In sum, this study provides a new perspective on understanding the pathways and mechanism of MRTX1133 binding to KRAS G12D.

In silico studies on leishmanicide activity of limonoids and fatty acids from Carapa guianensis Aubl

The oil of Carapa guianensis showed leishmanicidal activity, with its activity being related to limonoids, but fatty acids are the major constituents of this oil. The present study evaluated the physicochemical, pharmacokinetic, and toxicity profiles of limonoids and fatty acids already identified in the species. Based on these results, 2 limonoids (methyl angosinlate, 6-OH-methyl angosinlate) and 2 fatty acids (arachidic acid; myristic acid) were selected for the prediction of possible targets and molecular docking. Included in this study were: Gedunin, 6α-acetoxygedunin, Methyl angosenlato, 7-deacetoxy-7-oxogedunin, Andirobin, 6-hydroxy-angolensate methyl, 17β-hydroxyazadiradione, 1,2-dihydro-3β-hydroxy-7-deacetoxy-7-oxogedunin, xyllocensin k, 11beta-Hydroxygedunin, 6α,11-11β-diacetoxygedunin, Oleic Acid, Palmitic Acid, Stearic Acid, Arachidic Acid, Myristic Acid, Palmitoleic Acid, Linoleic Acid, Linolenic Acid, and Beenic Acid. Regarding physicochemical aspects, fatty acids violated LogP, and only limonoid 11 violated Lipinski's rule. A common pharmacokinetic aspect was that all molecules were well absorbed in the intestine and inhibited CYP. All compounds showed toxicity in some model, with fatty acids being mutagenic and carcinogenic, and limonoids not being mutagenic and carcinogenic at least for rats. In in vivo models, fatty acids were less toxic. Molecular dockings were performed on COX-2 steroids (15 and 16) and hypoxia-inducible factor 1 alpha for limonoids (3,6), with this target being essential for the intracellular development of leishmania. Limonoids 3 and 6 appear to be promising as leishmanicidal agents, and fatty acids are promising as wound healers.

Motif-VI loop acts as a nucleotide valve in the West Nile Virus NS3 Helicase

The Orthoflavivirus NS3 helicase (NS3h) is crucial in virus replication, representing a potential drug target for pathogenesis. NS3h utilizes nucleotide triphosphate (ATP) for hydrolysis energy to translocate on single-stranded nucleic acids, which is an important step in the unwinding of double-stranded nucleic acids. Intermediate states along the ATP hydrolysis cycle and conformational changes between these states, represent important yet difficult-to-identify targets for potential inhibitors. Extensive molecular dynamics simulations of West Nile virus NS3h+ssRNA in the apo, ATP, ADP+Pi and ADP bound states were used to model the conformational ensembles along this cycle. Energetic and structural clustering analyses depict a clear trend of differential enthalpic affinity of NS3h with ADP, demonstrating a probable mechanism of hydrolysis turnover regulated by the motif-VI loop (MVIL). Based on these results, MVIL mutants (D471L, D471N and D471E) were found to have a substantial reduction in ATPase activity and RNA replication compared to the wild-type. Simulations of the mutants in the apo state indicate a shift in MVIL populations favoring either a closed or open 'valve' conformation, affecting ATP entry or stabilization, respectively. Combining our molecular modeling with experimental evidence highlights a conformation-dependent role for MVIL as a 'valve' for the ATP-pocket, presenting a promising target for antiviral development.

Ligand Binding Affinity Prediction for Membrane Proteins with Alchemical Free Energy Calculation Methods

Alchemical relative binding free energy (ΔΔG) calculations have shown high accuracy in predicting ligand binding affinity and have been used as important tools in computer-aided drug discovery and design. However, there has been limited research on the application of ΔΔG methods to membrane proteins despite the fact that these proteins represent a significant proportion of drug targets, play crucial roles in biological processes, and are implicated in numerous diseases. In this study, to predict the binding affinity of ligands to G protein-coupled receptors (GPCRs), we employed two ΔΔG calculation methods: thermodynamic integration (TI) with AMBER and the alchemical transfer method (AToM) with OpenMM. We calculated ΔΔG values for 53 transformations involving four class A GPCRs and evaluated the performance of AMBER-TI and AToM-OpenMM. In addition, we conducted tests using different numbers of windows and varying simulation times to achieve reliable ΔΔG results and to optimize resource utilization. Overall, both AMBER-TI and AToM-OpenMM show good agreement with the experimental data. Our results validate the applicability of AMBER-TI and AToM-OpenMM for optimization of lead compounds targeting membrane proteins.

STORMM: Structure and topology replica molecular mechanics for chemical simulations

The Structure and TOpology Replica Molecular Mechanics (STORMM) code is a next-generation molecular simulation engine and associated libraries optimized for performance on fast, vectorized central processor units and graphics processing units (GPUs) with independent memory and tens of thousands of threads. STORMM is built to run thousands of independent molecular mechanical calculations on a single GPU with novel implementations that tune numerical precision, mathematical operations, and scarce on-chip memory resources to optimize throughput. The libraries are built around accessible classes with detailed documentation, supporting fine-grained parallelism and algorithm development as well as copying or swapping groups of systems on and off of the GPU. A primary intention of the STORMM libraries is to provide developers of atomic simulation methods with access to a high-performance molecular mechanics engine with extensive facilities to prototype and develop bespoke tools aimed toward drug discovery applications. In its present state, STORMM delivers molecular dynamics simulations of small molecules and small proteins in implicit solvent with tens to hundreds of times the throughput of conventional codes. The engineering paradigm transforms two of the most memory bandwidth-intensive aspects of condensed-phase dynamics, particle-mesh mapping, and valence interactions, into compute-bound problems for several times the scalability of existing programs. Numerical methods for compressing and streamlining the information present in stored coordinates and lookup tables are also presented, delivering improved accuracy over methods implemented in other molecular dynamics engines. The open-source code is released under the MIT license.

A general graph neural network based implicit solvation model for organic molecules in water

The dynamical behavior of small molecules in their environment can be studied with classical molecular dynamics (MD) simulations to gain deeper insight on an atomic level and thus complement and rationalize the interpretation of experimental findings. Such approaches are of great value in various areas of research, e.g., in the development of new therapeutics. The accurate description of solvation effects in such simulations is thereby key and has in consequence been an active field of research since the introduction of MD. So far, the most accurate approaches involve computationally expensive explicit solvent simulations, while widely applied models using an implicit solvent description suffer from reduced accuracy. Recently, machine learning (ML) approaches that provide a probabilistic representation of solvation effects have been proposed as potential alternatives. However, the associated computational costs and minimal or lack of transferability render them unusable in practice. Here, we report the first example of a transferable ML-based implicit solvent model trained on a diverse set of 3 000 000 molecular structures that can be applied to organic small molecules for simulations in water. Extensive testing against reference calculations demonstrated that the model delivers on par accuracy with explicit solvent simulations while providing an up to 18-fold increase in sampling rate.

Adsorption of Flavonoids in a Transcriptional Regulator TtgR: Relative Binding Free Energies and Intermolecular Interactions

Antimicrobial resistance in bacteria often arises from their ability to actively identify and expel toxic compounds. The bacterium strain Pseudomonas putida DOT-T1E utilizes its TtgABC efflux pump to confer robust resistance against antibiotics, flavonoids, and organic solvents. This resistance mechanism is intricately regulated at the transcriptional level by the TtgR protein. Through molecular dynamics and alchemical free energy simulations, we systematically examine the binding of seven flavonoids and their derivatives with the TtgR transcriptional regulator. Our simulations reveal distinct binding geometries and free energies for the flavonoids in the active site of the protein, which are driven by a range of noncovalent forces encompassing van der Waals, electrostatic, and hydrogen bonding interactions. The interplay of molecular structures, substituent patterns, and intermolecular interactions effectively stabilizes the bound flavonoids, confining their movements within the TtgR binding pocket. These findings yield valuable insights into the molecular determinants that govern ligand recognition in TtgR and shed light on the mechanism of antimicrobial resistance in P. putida DOT-T1E.

Investigating Pyruvate Dehydrogenase Kinase 3 Inhibitory Potential of Myricetin Using Integrated Computational and Spectroscopic Approaches

Protein kinases are involved in various diseases and currently represent potential targets for drug discovery. These kinases play major roles in regulating the cellular machinery and control growth, homeostasis, and cell signaling. Dysregulation of kinase expression is associated with various disorders such as cancer and neurodegeneration. Pyruvate dehydrogenase kinase 3 (PDK3) is implicated in cancer therapeutics as a potential drug target. In this current study, a molecular docking exhibited a strong binding affinity of myricetin to PDK3. Further, a 100 ns all-atom molecular dynamics (MD) simulation study provided insights into the structural dynamics and stability of the PDK3-myricetin complex, revealing the formation of a stable complex with minimal structural alterations upon ligand binding. Additionally, the actual affinity was ascertained by fluorescence binding studies, and myricetin showed appreciable binding affinity to PDK3. Further, the kinase inhibition assay suggested significant inhibition of PDK3 by myricetin, revealing an excellent inhibitory potential with an IC50 value of 3.3 μM. In conclusion, this study establishes myricetin as a potent PDK3 inhibitor that can be implicated in therapeutic targeting cancer and PDK3-associated diseases. In addition, this study underscores the efficacy of myricetin as a potential lead to drug discovery and provides valuable insights into the inhibition mechanism, enabling advancements in cancer therapeutics.

Analysis of AlphaFold and molecular dynamics structure predictions of mutations in serpins

Serine protease inhibitors (serpins) include thousands of structurally conserved proteins playing key roles in many organisms. Mutations affecting serpins may disturb their conformation, leading to inactive forms. Unfortunately, conformational consequences of serpin mutations are difficult to predict. In this study, we integrate experimental data of patients with mutations affecting one serpin with the predictions obtained by AlphaFold and molecular dynamics. Five SERPINC1 mutations causing antithrombin deficiency, the strongest congenital thrombophilia were selected from a cohort of 350 unrelated patients based on functional, biochemical, and crystallographic evidence supporting a folding defect. AlphaFold gave an accurate prediction for the wild-type structure. However, it also produced native structures for all variants, regardless of complexity or conformational consequences in vivo. Similarly, molecular dynamics of up to 1000 ns at temperatures causing conformational transitions did not show significant changes in the native structure of wild-type and variants. In conclusion, AlphaFold and molecular dynamics force predictions into the native conformation at conditions with experimental evidence supporting a conformational change to other structures. It is necessary to improve predictive strategies for serpins that consider the conformational sensitivity of these molecules.

Software Infrastructure for Next-Generation QM/MM-ΔMLP Force Fields

We present software infrastructure for the design and testing of new quantum mechanical/molecular mechanical and machine-learning potential (QM/MM-ΔMLP) force fields for a wide range of applications. The software integrates Amber's molecular dynamics simulation capabilities with fast, approximate quantum models in the xtb package and machine-learning potential corrections in DeePMD-kit. The xtb package implements the recently developed density-functional tight-binding QM models with multipolar electrostatics and density-dependent dispersion (GFN2-xTB), and the interface with Amber enables their use in periodic boundary QM/MM simulations with linear-scaling QM/MM particle-mesh Ewald electrostatics. The accuracy of the semiempirical models is enhanced by including machine-learning correction potentials (ΔMLPs) enabled through an interface with the DeePMD-kit software. The goal of this paper is to present and validate the implementation of this software infrastructure in molecular dynamics and free energy simulations. The utility of the new infrastructure is demonstrated in proof-of-concept example applications. The software elements presented here are open source and freely available. Their interface provides a powerful enabling technology for the design of new QM/MM-ΔMLP models for studying a wide range of problems, including biomolecular reactivity and protein-ligand binding.

A Practical Guide to All-Atom and Coarse-Grained Molecular Dynamics Simulations Using Amber and Gromacs: A Case Study of Disulfide-Bond Impact on the Intrinsically Disordered Amyloid Beta

Intrinsically disordered proteins (IDPs) pose challenges to conventional experimental techniques due to their large-scale conformational fluctuations and transient structural elements. This work presents computational methods for studying IDPs at various resolutions using the Amber and Gromacs packages with both all-atom (Amber ff19SB with the OPC water model) and coarse-grained (Martini 3 and SIRAH) approaches. The effectiveness of these methodologies is demonstrated by examining the monomeric form of amyloid-β (Aβ42), an IDP, with and without disulfide bonds at different resolutions. Our results clearly show that the addition of a disulfide bond decreases the β-content of Aβ42; however, it increases the tendency of the monomeric Aβ42 to form fibril-like conformations, explaining the various aggregation rates observed in experiments. Moreover, analysis of the monomeric Aβ42 compactness, secondary structure content, and comparison between calculated and experimental chemical shifts demonstrates that all three methods provide a reasonable choice to study IDPs; however, coarse-grained approaches may lack some atomistic details, such as secondary structure recognition, due to the simplifications used. In general, this study not only explains the role of disulfide bonds in Aβ42 but also provides a step-by-step protocol for setting up, conducting, and analyzing molecular dynamics (MD) simulations, which is adaptable for studying other biomacromolecules, including folded and disordered proteins and peptides.

Interactions of Phenylalanine Derivatives with Human Tyrosinase: Lessons from Experimental and Theoretical tudies

The pigmentation of the skin, modulated by different actors in melanogenesis, is mainly due to the melanins (protective pigments). In humans, these pigments' precursors are synthetized by an enzyme known as tyrosinase (TyH). The regulation of the enzyme activity by specific modulators (inhibitors or activators) can offer a means to fight hypo- and hyper-pigmentations responsible for medical, psychological and societal handicaps. Herein, we report the investigation of phenylalanine derivatives as TyH modulators. Interacting with the binuclear copper active site of the enzyme, phenylalanine derivatives combine effects induced by combination with known resorcinol inhibitors and natural substrate/intermediate (amino acid part). Computational studies including docking, molecular dynamics and free energy calculations combined with biological activity assays on isolated TyH and in human melanoma MNT-1 cells, and X-ray crystallography analyses with the TyH analogue Tyrp1, provide conclusive evidence of the interactions of phenylalanine derivatives with human tyrosinase. In particular, our findings indicate that an analogue of L-DOPA, namely (S)-3-amino-tyrosine, stands out as an amino phenol derivative with inhibitory properties against TyH.

Mechanism of Daunomycin Intercalation into DNA from Enhanced Sampling Simulations

Daunomycin is a widely used anticancer drug, yet the mechanism underlying how it binds to DNA remains contested. 469 all-atom trajectories of daunomycin binding to the DNA oligonucleotide d(GCG CAC GTG CGC) were collected using weighted ensemble (WE)-enhanced sampling. Mechanistic insights were revealed through analysis of the ensemble of trajectories. Initially, the binding process involves a ubiquitous hydrogen bond between the DNA backbone and the NH3+ group on daunomycin. During the binding process, most trajectories exhibited similar structural changes to DNA, including DNA base pair rise, bending, and minor groove width changes. Variability within the ensemble of binding trajectories illuminates differences in the orientation of daunomycin as it initially intercalates; around 10% of trajectories needed minimal rearrangement from intercalation to reaching the fully bound configuration, whereas most needed an additional 1-5 ns to rearrange. The results here emphasize the utility of generating an ensemble of trajectories to discern biomolecular binding mechanisms.

Exploring Structural Insights of Aβ42 and α-Synuclein Monomers and Heterodimer: A Comparative Study Using Implicit and Explicit Solvent Simulations

Protein misfolding, aggregation, and fibril formation play a central role in the development of severe neurological disorders, including Alzheimer's and Parkinson's diseases. The structural stability of mature fibrils in these diseases is of great importance, as organisms struggle to effectively eliminate amyloid plaques. To address this issue, it is crucial to investigate the early stages of fibril formation when monomers aggregate into small, toxic, and soluble oligomers. However, these structures are inherently disordered, making them challenging to study through experimental approaches. Recently, it has been shown experimentally that amyloid-β 42 (Aβ42) and α-synuclein (α-Syn) can coassemble. This has motivated us to investigate the interaction between their monomers as a first step toward exploring the possibility of forming heterodimeric complexes. In particular, our study involves the utilization of various Amber and CHARMM force-fields, employing both implicit and explicit solvent models in replica exchange and conventional simulation modes. This comprehensive approach allowed us to assess the strengths and weaknesses of these solvent models and force fields in comparison to experimental and theoretical findings, ensuring the highest level of robustness. Our investigations revealed that Aβ42 and α-Syn monomers can indeed form stable heterodimers, and the resulting heterodimeric model exhibits stronger interactions compared to the Aβ42 dimer. The binding of α-Syn to Aβ42 reduces the propensity of Aβ42 to adopt fibril-prone conformations and induces significant changes in its conformational properties. Notably, in AMBER-FB15 and CHARMM36m force fields with the use of explicit solvent, the presence of Aβ42 significantly increases the β-content of α-Syn, consistent with the experiments showing that Aβ42 triggers α-Syn aggregation. Our analysis clearly shows that although the use of implicit solvent resulted in too large compactness of monomeric α-Syn, structural properties of monomeric Aβ42 and the heterodimer were preserved in explicit-solvent simulations. We anticipate that our study sheds light on the interaction between α-Syn and Aβ42 proteins, thus providing the atom-level model required to assess the initial stage of aggregation mechanisms related to Alzheimer's and Parkinson's diseases.

Ascorbic acid biosynthesis in Pacific abalone Haliotis discus hannai Ino and L-gulonolactone oxidase gene loss as an independent event

Up to now, it has been believed that invertebrates are unable to synthesize ascorbic acid (AA) in vivo. However, in the present study, the full-length CDs (Coding sequence) of L-gulonolactone oxidase (GLO) from Pacific abalone (Haliotis discus hannai Ino) were obtained through molecular cloning. The Pacific abalone GLO contained a FAD-binding domain in the N-termination, and ALO domain and conserved HWAK motif in the C-termination. The GLO gene possesses 12 exons and 11 introns. The Pacific abalone GLO was expressed in various tissues, including the kidney, digestive gland, gill, intestine, muscle and mantle. The GLO activity assay revealed that GLO activity was only detected in the kidney of Pacific abalone. After a 100-day feeding trial, dietary AA levels did not significantly affect the survival, weight gain, daily increment in shell length, and feed conversion ratio of Pacific abalone. The expression of GLO in the kidney was downregulated by dietary AA. These results implied that the ability to synthesize AA in abalone had not been lost. From the evolutionary perspective, the loss of GLO occurred independently as an independent event by matching with the genomes of various species. The positive selection analysis revealed that the GLO gene underwent purifying selective pressure during its evolution. In conclusion, the present study provided direct evidence to prove that the GLO activity and the ability to synthesize AA exist in abalone. The AA synthesis ability in vertebrates might have originated from invertebrates dating back 930.31 million years.

Facile and Novel Synthetic Approach, Molecular Docking, Molecular Dynamics, and Drug-Likeness Evaluation of 9-Substituted Acridine Derivatives as Dual Anticancer and Antimicrobial Agents

In the present study, numerous acridine derivatives A1-A20 were synthesized via aromatic nucleophilic substitution (SNAr) reaction of 9-chloroacridine with carbonyl hydrazides, amines, or phenolic derivatives depending upon facile, novel, and eco-friendly approaches (Microwave and ultrasonication assisted synthesis). The structures of the new compounds were elucidated using spectroscopic methods. The title products were assessed for their antimicrobial, antioxidant, and antiproliferative activities using numerous assays. Promisingly, the investigated compounds mainstream revealed promising antibacterial and anticancer activities. Thereafter, the investigated compounds' expected mode of action was debated by using an array of in silico studies. Compounds A2 and A3 were the most promising antimicrobial agents, while compounds A2, A5, and A7 revealed the most cytotoxic activities. Accordingly, RMSD, RMSF, Rg, and SASA analyses of compounds A2 and A3 were performed, and MMPBSA was calculated. Lastly, the ADMET (absorption, distribution, metabolism, excretion, and toxicity) analyses of the novel acridine derivatives were investigated. The tested compounds' existing screening results afford an inspiring basis leading to developing new compelling antimicrobial and anticancer agents based on the acridine scaffold.

Ali S, Efferth T, Hegazy MEF. Salvimulticanol from Salvia multicaulis suppresses LPS-induced inflammation in RAW264.7 macrophages: in vitro and in silico studies

Sustained inflammatory responses can badly affect several vital organs and lead to chronic inflammation-related disorders, such as atherosclerosis, pneumonia, rheumatoid arthritis, obesity, diabetes, Alzheimer's disease, and cancers. Salvia multicaulis is one of the widely distributed plants that contains several biologically active phytochemicals and diterpenoids with anti-inflammatory effects. Therefore, finding alternative and safer natural plant-extracted compounds with good curative anti-inflammatory efficiencies is an urgent need for the clinical treatment of inflammation-related diseases. In the current study, S. multicaulis Vahl was used to extract and isolate two compounds identified as salvimulticanol and candesalvone B methyl ester to examine their effects against inflammation in murine macrophage RAW264.7 cells that were induced by lipopolysaccharide (LPS). Accordingly, after culturing RAW264.7 cells and induction of inflammation by LPS (100 ng/ml), cells were exposed to different concentrations (9, 18, 37.5, 75, and 150 µM) of each compound. Then, Griess assay for detection of nitric oxide (NO) levels and western blotting for the determination of inducible nitric oxide synthase (iNOS) expression were performed. Molecular docking and molecular dynamics (MD) simulation studies were employed to investigate the anti-inflammatory mechanism. Our obtained results validated that the level of NO was significantly decreased in the macrophage cell suspensions as a response to salvimulticanol treatment in a dose-dependent manner (IC50: 25.1 ± 1.2 µM) as compared to the methyl ester of candesalvone B which exerted a weaker inhibition (IC50: 69.2 ± 3.0 µM). This decline in NO percentage was comparable with a down-regulation of iNOS expression by western blotting. Salvimulticanol strongly interacted with both the Toll-like receptor 4 (TLR4)/myeloid differentiation factor 2 (MD-2) complex and the inhibitor of nuclear factor kappa-B (NF-κB) kinase subunit beta (IKKβ) to disrupt their inflammatory activation due to the significant hydrogen bonds and effective interactions with amino acid residues present in the target proteins' active sites. S.multicaulis is a rich natural source of the aromatic abietane diterpenoid, salvimulticanol, which exerted a strong anti-inflammatory effect through targeting iNOS and diminishing NO production in LPS-induced RAW264.7 cells in a mechanism that is dependent on the inhibition of TLR4-MD-2 and IKKβ as activators of the classical NF-κB-mediated inflammatory pathway.

Studying the Collective Functional Response of a Receptor in Alchemical Ligand Binding Free Energy Simulations with Accelerated Solvation Layer Dynamics

Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the λ-exchange of free energy perturbation (FEP). Two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/λ-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.

Free-energy landscapes of transmembrane homodimers by bias-exchange adaptively biased molecular dynamics

Membrane proteins play essential roles in various biological functions within the cell. One of the most common functional regulations involves the dimerization of two single-pass transmembrane (TM) helices. Glycophorin A (GpA) and amyloid precursor protein (APP) form TM homodimers in the membrane, which have been investigated both experimentally and computationally. The homodimer structures are well characterized using only four collective variables (CVs) when each TM helix is stable. The CVs are the interhelical distance, the crossing angle, and the Crick angles for two TM helices. However, conformational sampling with multi-dimensional replica-exchange umbrella sampling (REUS) requires too many replicas to sample all the CVs for exploring the conformational landscapes. Here, we show that the bias-exchange adaptively biased molecular dynamics (BE-ABMD) with the four CVs effectively explores the free-energy landscapes of the TM helix dimers of GpA, wild-type APP and its mutants in the IMM1 implicit membrane. Compared to the original ABMD, the bias-exchange algorithm in BE-ABMD can provide a more rapidly converged conformational landscape. The BE-ABMD simulations could also reveal TM packing interfaces of the membrane proteins and the dependence of the free-energy landscapes on the membrane thickness. This approach is valuable for numerous other applications, including those involving explicit solvent and a lipid bilayer in all-atom force fields or Martini coarse-grained models, and enhances our understanding of protein-protein interactions in biological membranes.

Exploring therapeutic potential of Rutin by investigating its cyclin-dependent kinase 6 inhibitory activity and binding affinity

Cyclin-dependent kinase 6 (CDK6) participates in numerous signalling pathways and regulates various physiological processes. Due to its unique structural features and promising therapeutic potential, CDK6 has emerged as a drug target for designing and developing small-molecule inhibitors for anti-cancer therapeutics and other CDK6-associated diseases. The current study evaluates binding affinity and the inhibitory potential of rutin for CDK6 to develop a proof of concept for rutin as a potent CDK6 inhibitor. Molecular docking and 200 ns all-atom simulations reveal that rutin binds to the active site pocket of CDK6, forming interactions with key residues of the binding pocket. In addition, the CDK6-rutin complex remains stable throughout the simulation trajectory. A high binding constant (Ka = 7.6 × 105M-1) indicates that rutin has a strong affinity for CDK6. Isothermal titration calorimetry has further validated a strong binding of rutin with CDK6 and its spontaneous nature. The kinase activity of CDK6 is significantly inhibited by rutin with an IC50 value of 3.10 μM. Our findings highlight the significant role of rutin in developing potential therapeutic molecules to manage cancer and CDK6-associated diseases via therapeutic targeting of CDK6.

Dissecting the Interaction Fingerprints and Binding Affinity of BYL719 Analogs Targeting PI3Kα

Phosphatidylinositol-3-kinase Alpha (PI3Kα) is a lipid kinase which regulates signaling pathways involved in cell proliferation. Dysregulation of these pathways promotes several human cancers, pushing for the development of anticancer drugs to target PI3Kα. One such medicinal chemistry campaign at Novartis led to the discovery of BYL719 (Piqray, Alpelicib), a PI3Kα inhibitor approved by the FDA in 2019 for treatment of HR+/HER2-advanced breast cancer with a PIK3CA mutation. Structure-based drug design played a key role in compound design and optimization throughout the discovery process. However, further characterization of potency drivers via structural dynamics and energetic analyses can be advantageous for ensuing PI3Kα programs. Here, our goal is to employ various in-silico techniques, including molecular simulations and machine learning, to characterize 14 ligands from the BYL719 analogs and predict their binding affinities. The structural insights from molecular simulations suggest that although the ligand-hinge interaction is the primary driver of ligand stability at the pocket, the R group positioning at C2 or C6 of pyridine/pyrimidine also plays a major role. Binding affinities predicted via thermodynamic integration (TI) are in good agreement with previously reported IC50s. Yet, computationally demanding techniques such as TI might not always be the most efficient approach for affinity prediction, as in our case study, fast high-throughput techniques were capable of classifying compounds as active or inactive, and one docking approach showed accuracy comparable to TI.

Cation-π Interactions Greatly Influence Ion Transportability of the Light-Driven Sodium Pump KR2: A Molecular Dynamics Study

Krokinobacter eikastus rhodopsin 2 (KR2) is a typical light-driven sodium pump. Although wild-type KR2 exhibits high Na+ selectivity, mutagenesis performed on the residues constituting the entrance enables permeation of K+ and Cs+, while the underlying mechanism remains elusive. This study presents a comprehensive molecular dynamics investigation, including force field optimization, metadynamics, and alchemical free energy methods, to explore the N61L/G263F mutant of KR2, which exhibits transportability for K+ and Cs+. The introduced Phe263 residue can directly promote ion binding at the entrance through cation-π interactions, while the N61L mutation can enhance ion binding at Phe46 by relieving steric hindrance. These results suggest that cation-π interactions may significantly influence the ion transportability and selectivity of KR2, which can provide important insights for protein engineering and the design of artificial ion transporters.

Potent inhibitors targeting cyclin-dependent kinase 9 discovered via virtual high-throughput screening and absolute binding free energy calculations

Due to the crucial regulatory mechanism of cyclin-dependent kinase 9 (CDK9) in mRNA transcription, the development of kinase inhibitors targeting CDK9 holds promise as a potential treatment strategy for cancer. A structure-based virtual screening approach has been employed for the discovery of potential novel CDK9 inhibitors. First, compounds with kinase inhibitor characteristics were identified from the ZINC15 database via virtual high-throughput screening. Next, the predicted binding modes were optimized by molecular dynamics simulations, followed by precise estimation of binding affinities using absolute binding free energy calculations based on the free energy perturbation scheme. The binding mode of molecule 006 underwent an inward-to-outward flipping, and the new binding mode exhibited binding affinity comparable to the small molecule T6Q in the crystal structure (PDB ID: 4BCF), highlighting the essential role of molecular dynamics simulation in capturing a plausible binding pose bridging docking and absolute binding free energy calculations. Finally, structural modifications based on these findings further enhanced the binding affinity with CDK9. The results revealed that enhancing the molecule's rigidity through ring formation, while maintaining the major interactions, reduced the entropy loss during the binding process and, thus, enhanced binding affinities.

Investigating the role of thymol as a promising inhibitor of pyruvate dehydrogenase kinase 3 for targeted cancer therapy

Protein kinases have emerged as major contributors to various diseases. They are currently exploited as a potential target in drug discovery because they play crucial roles in cell signaling, growth, and regulation. Their dysregulation is associated with inflammatory disorders, cancer, and neurodegenerative diseases. Pyruvate dehydrogenase kinase 3 (PDK3) has become an attractive drug target in cancer therapeutics. In the present study, we investigated the effective role of thymol in PDK3 inhibition due to the high affinity predicted through molecular docking studies. Hence, to better understand this inhibition mechanism, we carried out a 100 ns molecular dynamics (MD) simulation to analyse the dynamics and stability of the PDK3-thymol complex. The PDK3-thymol complex was stable and energetically favourable, with many intramolecular hydrogen bond interactions in the PDK3-thymol complex. Enzyme inhibition assay showed significant inhibition of PDK3 by thymol, revealing potential inhibitory action of thymol towards PDK3 (IC50 = 2.66 μM). In summary, we established thymol as one of the potential inhibitors of PDK3, proposing promising therapeutic implications for severe diseases associated with PDK3 dysregulation. This study further advances our understanding of thymol's therapeutic capabilities and potential role in cancer treatment.

Biased Signaling in Mutated Variants of β2-Adrenergic Receptor: Insights from Molecular Dynamics Simulations

The molecular basis of receptor bias in G protein-coupled receptors (GPCRs) caused by mutations that preferentially activate specific intracellular transducers over others remains poorly understood. Two experimentally identified biased variants of β2-adrenergic receptors (β2AR), a prototypical GPCR, are a triple mutant (T68F, Y132A, and Y219A) and a single mutant (Y219A); the former bias the receptor toward the β-arrestin pathway by disfavoring G protein engagement, while the latter induces G protein signaling explicitly due to selection against GPCR kinases (GRKs) that phosphorylate the receptor as a prerequisite of β-arrestin binding. Though rigorous characterizations have revealed functional implications of these mutations, the atomistic origin of the observed transducer selectivity is not clear. In this study, we investigated the allosteric mechanism of receptor bias in β2AR using microseconds of all-atom Gaussian accelerated molecular dynamics (GaMD) simulations. Our observations reveal distinct rearrangements in transmembrane helices, intracellular loop 3, and critical residues R1313.50 and Y3267.53 in the conserved motifs D(E)RY and NPxxY for the mutant receptors, leading to their specific transducer interactions. Moreover, partial dissociation of G protein from the receptor core is observed in the simulations of the triple mutant in contrast to the single mutant and wild-type receptor. The reorganization of allosteric communications from the extracellular agonist BI-167107 to the intracellular receptor-transducer interfaces drives the conformational rearrangements responsible for receptor bias in the single and triple mutants. The molecular insights into receptor bias of β2AR presented here could improve the understanding of biased signaling in GPCRs, potentially opening new avenues for designing novel therapeutics with fewer side-effects and superior efficacy.

Role of ATP Hydrolysis and Product Release in the Translocation Mechanism of SARS-CoV-2 NSP13

In response to the emergence of COVID-19, caused by SARS-CoV-2, there has been a growing interest in understanding the functional mechanisms of the viral proteins to aid in the development of new therapeutics. Nonstructural protein 13 (nsp13) helicase is an attractive target for antivirals because it is essential for viral replication and has a low mutation rate, yet the structural mechanisms by which this enzyme binds and hydrolyzes ATP to cause unidirectional RNA translocation remain elusive. Using Gaussian accelerated molecular dynamics (GaMD), we generated comprehensive conformational ensembles of all substrate states along the ATP-dependent cycle. Shape-GMM clustering of the protein yields four protein conformations that describe an opening and closing of both the ATP pocket and the RNA cleft that is achieved through a combination of conformational selection and induction along the ATP hydrolysis cycle. Furthermore, three protein-RNA conformations are observed that implicate motifs Ia, IV, and V as playing a pivotal role in an ATP-dependent inchworm translocation mechanism. Finally, based on a linear discriminant analysis of protein conformations, we identify L405 as a pivotal residue for the opening and closing mechanism and propose a L405D mutation as a way to disrupt translocation. This research enhances our understanding of nsp13's role in viral replication and could contribute to the development of antiviral strategies.

Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters

Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.

How Modulator Binding at the Amyloidβ-γ-Secretase Interface Enhances Substrate Binding and Attenuates Membrane Distortion

Inhibition of γ-secretase, an intramembrane protease, to reduce secretion of Amyloid-β (Aβ) peptides has been considered for treating Alzheimer's disease. However, γ-secretase inhibitors suffer from severe side effects. As an alternative, γ-secretase modulators (GSM) reduce the generation of toxic peptides by enhancing the cleavage processivity without diminishing the enzyme activity. Starting from a known γ-secretase structure without substrate but in complex with an E2012 GSM, we generated a structural model that included a bound Aβ43 peptide and studied interactions among enzyme, substrate, GSM, and lipids. Our result suggests that E2012 binding at the enzyme-substrate-membrane interface attenuates the membrane distortion by shielding the substrate-membrane interaction. The model predicts that the E2012 modulation is charge-dependent and explains the preserved hydrogen acceptor and the aromatic ring observed in many imidazole-based GSM. Predicted effects of γ-secretase mutations on E2012 modulation were confirmed experimentally. We anticipate that the study will facilitate the future development of effective GSMs.