Multiple Molecular Dynamics Research Articles

The impacts of the mitochondrial myopathy-associated G58R mutation on the dynamic structural properties of CHCHD10

The mitochondria are responsible for producing energy within the cell, and in mitochondrial myopathy, there is a defect in the energy production process. The CHCHD10 gene codes for a protein called coiled-coil-helix-coiled-coil-helix domain-containing protein 10 (CHCHD10), which is found in the mitochondria and is involved in the regulation of mitochondrial function. G58R mutation has been shown to disrupt the normal function of CHCHD10, leading to mitochondrial dysfunction and ultimately to the development of mitochondrial myopathy. The structures of G58R mutant CHCHD10 and how G58R mutation impacts the wild-type CHCHD10 protein at the monomeric level are unknown. To address this problem, we conducted homology modeling, multiple run molecular dynamics simulations and bioinformatics calculations. We represent herein the structural ensemble properties of the G58R mutant CHCHD10 (CHCHD10G58R) in aqueous solution. Moreover, we describe the impacts of G58R mutation on the structural ensembles of wild-type CHCHD10 (CHCHD10WT) in aqueous solution. The dynamics properties as well as structural properties of CHCHD10WT are impacted by the mitochondrial myopathy-related G58R mutation. Specifically, the secondary and tertiary structure properties, root mean square fluctuations, Ramachandran diagrams and results from principal component analysis demonstrate that the CHCHD10WT and CHCHD10G58R proteins possess different structural ensemble characteristics and describe the impacts of G58R mutation on CHCHD10WT. These findings may be helpful for designing new treatments for mitochondrial myopathy. Communicated by Ramaswamy H. Sarma

Binding Mechanism of Inhibitors to Heat Shock Protein 90 Investigated by Multiple Independent Molecular Dynamics Simulations and Prediction of Binding Free Energy.

The heat shock protein (HSP90) has been an import target of drug design in the treatment of human disease. An exploration of the conformational changes in HSP90 can provide useful information for the development of efficient inhibitors targeting HSP90. In this work, multiple independent all-atom molecular dynamics (AAMD) simulations followed by calculations of the molecular mechanics generalized Born surface area (MM-GBSA) were performed to explore the binding mechanism of three inhibitors (W8Y, W8V, and W8S) to HSP90. The dynamics analyses verified that the presence of inhibitors impacts the structural flexibility, correlated movements, and dynamics behavior of HSP90. The results of the MM-GBSA calculations suggest that the selection of GB models and empirical parameters has important influences on the predicted results and verify that van der Waals interactions are the main forces that determine inhibitor-HSP90 binding. The contributions of separate residues to the inhibitor-HSP90 binding process indicate that hydrogen-bonding interactions (HBIs) and hydrophobic interactions play important roles in HSP90-inhibitor identifications. Moreover, residues L34, N37, D40, A41, D79, I82, G83, M84, F124, and T171 are recognized as hot spots of inhibitor-HSP90 binding and provide significant target sites of for the design of drugs related to HSP90. This study aims to contribute to the development of efficient inhibitors that target HSP90 by providing an energy-based and theoretical foundation.

Identification Mechanism of BACE1 on Inhibitors Probed by Using Multiple Separate Molecular Dynamics Simulations and Comparative Calculations of Binding Free Energies.

β-amyloid cleaving enzyme 1 (BACE1) is regarded as an important target of drug design toward the treatment of Alzheimer's disease (AD). In this study, three separate molecular dynamics (MD) simulations and calculations of binding free energies were carried out to comparatively determine the identification mechanism of BACE1 for three inhibitors, 60W, 954 and 60X. The analyses of MD trajectories indicated that the presence of three inhibitors influences the structural stability, flexibility and internal dynamics of BACE1. Binding free energies calculated by using solvated interaction energy (SIE) and molecular mechanics generalized Born surface area (MM-GBSA) methods reveal that the hydrophobic interactions provide decisive forces for inhibitor-BACE1 binding. The calculations of residue-based free energy decomposition suggest that the sidechains of residues L91, D93, S96, V130, Q134, W137, F169 and I179 play key roles in inhibitor-BACE1 binding, which provides a direction for future drug design toward the treatment of AD.

Structural and energetic insights into the selective inhibition of PKMYT1 against WEE1

Protein kinase, membrane-associated tyrosine/threonine 1 (PKMYT1), a member of the WEE family and responsible for the regulation of CDK1 phosphorylation, has been considered a promising therapeutic target for cancer therapy. However, the highly structural conservation of the ATP-binding sites of the WEE family poses a challenge to the design of selective inhibitors for PKMYT1. Here, molecular docking, multiple microsecond-length molecular dynamics (MD) simulations and end-point free energy calculations were performed to uncover the molecular mechanism of the binding selectivity of RP-6306 toward PKMYT1 over its highly homologous kinase WEE1. The binding specificity of RP-6306 reported in previous experimental bioassays was clarified by MD simulations and binding free energy calculations. Further, the binding free energy prediction indicated that the binding selectivity of RP-6306 largely derived from the difference in the protein-ligand electrostatic interactions. The per-residue free energy decomposition suggested that the non-conserved gatekeeper residue in the hinge domain of PKMYT1/WEE1, Thr187/Asn376, is the critical factor responsible for the binding selectivity of RP-6306 toward PKMYT1. In addition, a water-mediated hydrogen bond was formed between RP-6306 and Gly191 at the hinge domain in the PKMYT1/RP-6306 complex, which was absent in the WEE1/RP-6306 complex. This study is expected to offer useful information for the design of more potent and selective PKMYT1 inhibitors. Communicated by Ramaswamy H. Sarma

Computational identification of new TKI as potential noncovalent reversible EGFRL858R/T790M inhibitors: VHTS, molecular docking, DFT study and molecular dynamic simulation

The mutations concerned with non-small cell lung cancer involving epidermal growth factor receptor of tyrosine kinase family have primarily targeted. In this study, we employed a scalable high-throughput virtual screening (HTVS) framework and a targeted compound library of over 50.000 Erlotinib-derived compounds as noncovalent reversible EGFRL858R/T790M inhibitors. Our HTVS work flow leverages include HTVS, SP (Standard Precision) and XP (Extra Precision) docking protocol along with its relative binding free energy calculation, cluster analysis study and ADMET properties. Then we used multiple ns-time scale molecular dynamics (MD) simulations and density functional theory (DFT) precise calculation techniques to elucidate how the bound ligand interact with the complexes conformational states involving motions both proximal and distal to the binding site. Based on glide score and protein–ligand interactions, the highest scoring molecule was selected for molecular dynamic simulation providing a complete insight into the conformational stability. A hyperfine analysis of DFT based refinement strategy highly supported their stability by strong intermolecular interactions. Together, our results demonstrate that the virtually screened top retained molecules present the best moieties introduced to Erlotinib. They exhibit interesting pharmacokinetic properties that can act as potent antitumor drug candidates than the lead compound drug and in some extent tackling the drug resistance problem which offer a springboard for further therapeutic experiments and applications. Communicated by Ramaswamy H. Sarma

Dissecting the Self-assembly Dynamics of Imperfect Repeats in α-Synuclein.

The pathological aggregation of α-synuclein (αS) into amyloid fibrils is the hallmark of Parkinson's disease (PD). The self-assembly and membrane interactions of αS are mainly governed by the seven imperfect 11-residue repeats of the XKTKEGVXXXX motif around residues 1-95. However, the particular role of each repeat in αS fibrillization remains unclear. To answer this question, we studied the aggregation dynamics of each repeat with up to 10 peptides in silico by conducting multiple independent micro-second atomistic discrete molecular dynamics simulations. Our simulations revealed that only repeats R3 and R6 readily self-assembled into β-sheet-rich oligomers, while the other repeats remained as unstructured monomers with weak self-assembly and β-sheet propensities. The self-assembly process of R3 featured frequent conformational changes with β-sheet formation mainly in the non-conserved hydrophobic tail, whereas R6 spontaneously self-assembled into extended and stable cross-β structures. These results of seven repeats are consistent with their structures and organization in recently solved αS fibrils. As the primary amyloidogenic core, R6 was buried inside the central cross-β core of all αS fibrils, attracting the hydrophobic tails of adjacent R4, R5, and R7 repeats forming β-sheets around R6 in the core. Further away from R6 in the sequence but with a moderate amyloid aggregation propensity, the R3 tail could serve as a secondary amyloidogenic core and form independent β-sheets in the fibril. Overall, our results demonstrate the critical role of R3 and R6 repeats in αS amyloid aggregation and suggest their potential as targets for the peptide-based and small-molecule amyloid inhibitors.

Modeling the Annexin A1-S100A11 heterotetramer: a molecular dynamics investigation of structure and correlated motion

Annexin A1 (A1) has been shown to form a tetrameric complex (A1t) with S100A11 which is implicated in calcium homeostasis and EGFR pathways. In this work, a full-length model of the A1t was generated for the first time. Multiple molecular dynamics simulations were performed on the complete A1t model for several hundred nanoseconds each to assess the structure and dynamics of A1t. These simulations yielded three structures for the A1 N-terminus (ND) which were identified via principal component analysis. The orientations and interactions of the first 11 A1-ND residues for all three structures were conserved, and their binding modes were strikingly similar to those of the Annexin A2 N-terminus in the Annexin A2-p11 tetramer. In this study, we provided detailed atomistic information for the A1t. Strong interactions were identified within the A1t between the A1-ND and both S100A11 monomers. Residues M3, V4, S5, E6, L8, K9, W12, E15, and E18 of A1 were the strongest interactions between A1 and the S100A11 dimer. The different conformations of the A1t were attributed to the interaction between W12 of the A1-ND with M63 of S100A11 which caused a kink in the A1-ND. Cross-correlation analysis revealed strong correlated motion throughout the A1t. Strong positive correlation was observed between the ND and S100A11 in all simulations regardless of conformation. This work suggests that the stable binding of the first 11 residues of A1-ND to S100A11 is potentially a theme for Annexin-S100 complexes and that the flexibility of the A1-ND allows for multiple conformations of the A1t. Communicated by Ramaswamy H. Sarma

Deciphering Selectivity Mechanism of BRD9 and TAF1(2) toward Inhibitors Based on Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

BRD9 and TAF1(2) have been regarded as significant targets of drug design for clinically treating acute myeloid leukemia, malignancies, and inflammatory diseases. In this study, multiple short molecular dynamics simulations combined with the molecular mechanics generalized Born surface area method were employed to investigate the binding selectivity of three ligands, 67B, 67C, and 69G, to BRD9/TAF1(2) with IC50 values of 230/59 nM, 1400/46 nM, and 160/410 nM, respectively. The computed binding free energies from the MM-GBSA method displayed good correlations with that provided by the experimental data. The results indicate that the enthalpic contributions played a critical factor in the selectivity recognition of inhibitors toward BRD9 and TAF1(2), indicating that 67B and 67C could more favorably bind to TAF1(2) than BRD9, while 69G had better selectivity toward BRD9 over TAF1(2). In addition, the residue-based free energy decomposition approach was adopted to calculate the inhibitor-residue interaction spectrum, and the results determined the gatekeeper (Y106 in BRD9 and Y1589 in TAF1(2)) and lipophilic shelf (G43, F44, and F45 in BRD9 and W1526, P1527, and F1528 in TAF1(2)), which could be identified as hotspots for designing efficient selective inhibitors toward BRD9 and TAF1(2). This work is also expected to provide significant theoretical guidance and insightful molecular mechanisms for the rational designs of efficient selective inhibitors targeting BRD9 and TAF1(2).

Spatially Confined PdHx Metallenes by Tensile Strained Atomic Ru Layers for Efficient Hydrogen Evolution.

Hydride metallenes show great potential for hydrogen-related catalytic applications due to favorable electronic structures modulated by interstitial hydrogen atoms and large active surface areas of metallenes. Metallene nanostructures generally have compressive strain relative to bulk, which can affect both the stability and the catalytic behavior of hydride metallenes but in general cannot be controlled. Here, we demonstrate highly stable PdHx metallenes with a tensile strained Ru surface layer and reveal the spatial confinement effect of the Ru skin by multiple spectroscopic characterizations and molecular dynamics simulations. These PdHx@Ru metallenes with a 4.5% expanded Ru outer layer exhibit outstanding alkaline hydrogen evolution reaction activity with a low overpotential of 30 mV at 10 mA cm-2 and robust stability with negligible activity decay after 10,000 cycles, which are superior to commercial Pt/C and most reported Ru-based electrocatalysts. Control experiments and first-principles calculations reveal that the tensile strained Ru outer layer lowers the energy barrier of H2O dissociation and provides a moderate hydrogen adsorption energy.

MDBuilder: a PyMOL plugin for the preparation of molecular dynamics simulations.

The preprocessed initial files that feed the molecular dynamics (MD) simulation packages dramatically influence the outcome of the simulations. However, the popular MD simulation packages depend, to a great extent, on the user's experience in the preparation of MD simulation systems. In this work, we present an easy-to-use tool called MDBuilder, a PyMOL plugin that assists researchers in building the starting structures for multiple popular MD simulation packages. MDBuilder is not only designed to assist MD beginners to overcome the steep learning curve by providing a menu-oriented, point-and-click user graphic interface (GUI), but also to provide an alternative way to prepare the input files for some highly scalable CHARMM force field-based MD simulation packages. The platform-independent GUI is implemented as a PyMOL plugin using the Python language, and it has been tested on Windows and Linux platforms. The source code and documentation of MDBuilder can be downloaded freely from https://github.com/HuiLiuCode/MDBuilder under the GNU General Public License.

Conformational and Thermodynamic Differences Underlying Wild-Type and Mutant Eleven-Nineteen-Leukemia YEATS Domain Specificity for Epigenetic Marks.

Histone post-translational modifications (PTMs) are interpreted by multiple reader domains and proteins to regulate gene expression. The eleven-nineteen-leukemia (ENL) YEATS domain is a prototypical PTM reader that recognizes multiple lysine acetylation marks on the histone H3 tails as a way of recruiting chromatin remodellers. Two ENL YEATS mutations have been identified which have been linked with leukemia, Wilms tumor, and other forms of cancer and result in either an insertion or deletion of residues in the loop connecting beta sheets distant from the protein active site. In vitro experiments have shown that these mutations modulate the selectivities of YEATS domains for various lysine acetylation marks, although different experiments have provided contrasting views on the abilities of the insertion and deletion mutants to discern specific PTMs. Here, we have performed multiple molecular dynamics simulations of wild-type and insertion and deletion mutant YEATS domains free from and in complex with two PTM peptides: one that is acetylated at K9 of H3 and the other that is acetylated at residue K27 of H3. Results show that these two peptides have distinct flexibilities and binding energetics when bound to YEATS domains and that these properties are affected by interactions with residues within and outside of the peptide consensus motif. Furthermore, these properties are modulated by the YEATS insertion and deletion mutants, which results in disparate binding effects in these systems. Together, these results suggest that only the partial exposure of histone tails is sufficient in the context of nucleosomes for YEATS-mediated recognition of acetylation marks on histone tails. They also caution against the overinterpretation of results obtained from experiments on reader domain-histone peptide binding in isolation and not in the full-length nucleosome context.

Molecular basis of RNA recognition by TBP of HIV-1 from multiple molecular dynamics simulations and energy predictions.

The frequent outbreaks of the AIDS (Acquired Immune Deficiency Syndrome) pandemic and the limited availability of anti-Human Immunodeficiency Virus (HIV) drugs highlight the urgent need to develop new antiviral drugs. A detailed understanding of the interactions between TAR-Binding Proteins (TBP) and RNA will facilitate the discovery of new anti-AIDS drugs. In order to characterize and explore the key interactions between RNA and TBP, we focused on the wild type (WT) and three mutant TBPs (TBP6.9, TBP6.7, and TBP6.3) with RNA, multiple molecular dynamics simulation and energy computation were performed. The results showed that 12 key residues played a major role in the interaction between TBP and RNA. The mutated residues of TBP changed the interaction between their surrounding residues and RNA, thus affecting the binding of TBP to RNA. In addition, structural and energy analyses showed that in contrast with WT TBP-RNA complex, the mutated residues had little effect on the backbone structure of TBP, but changes in the van der Waals interactions and electrostatic interaction associated with the side chains are responsible for the altered the binding between three mutant TBPs and RNA complexes. The discovery of TBP-RNA recognition mechanism in our work provides some useful insights and new opportunities for the development of anti-aids drugs.

Structural and energetic basis of interaction between human estrogen-related receptor γ and environmental endocrine disruptors from multiple molecular dynamics simulations and free energy predictions.

Environmental endocrine disruptors (EEDs), a class of molecules that are widespread in our environment, may adversely affect the endocrine system. Exploring the interactions between these compounds and their potential targets is important for assessing their role in the organism. Focused on the human estrogen-related receptor γ (hERRγ) with BPA, BPB, HPTE, BPE, BP(2,2)(Et), and BP(2,2)(MeO) complexes, respectively, we groped for the mechanisms of conformational changes and interactions of hERRγ when binding to these six EEDs by combining multiple molecular dynamics (MD) simulations with energy prediction (MM-PBSA and solvated interaction energy (SIE)). Dynamics analysis results revealed these six EEDs have different effects on the internal dynamics of hERRγ, resulting in significant changes in the interaction of key residues around Leu268, Val313, Leu345, and Phe435 with EEDs, and thus affected its binding energy with these EEDs. The energy calculations further demonstrated that van der Waals interactions are critical for these EEDs binding to hERRγ. These results present detailed molecular insight into the interaction features between EEDs and hERRγ and help guide the search for safer alternatives to BPA.

Simulations reveal the role of glucose-6-phosphatase mutations in glycogen storage disease.

Glucose-6-phosphatase catalytic subunit 1 (G6PC1) is a key enzyme in central metabolism, specifically in gluconeogenesis and glycogenolysis, but its structure and dynamics have eluded the scientific community for decades. Particular mutations in this enzyme give rise to glycogen storage disease type 1a, making it a potential therapeutic target. Recent advances in protein structure prediction by AlphaFold2 have yielded the first structural model of G6PC1. In a dual-pronged computational and experimental approach, we have investigated the structural and dynamical properties that confer G6PC1 catalytic activity. Multiple replica equilibrium molecular dynamics (MD) simulations allowed us to obtain a relaxed consensus structure of G6PC1 in a representative endoplasmic reticulum lipid bilayer. We then obtained a liganded structure of G6PC1 for both alpha and beta isomers of its native substrate, glucose-6-phosphate, by leveraging docking data and homologous crystallographic information. To assess the role of mutations on ligand stability, we collected over 15 μs of MD simulation of wildtype and clinically relevant mutants. From this data we identified novel substrate-interacting residues by hydrogen bonding networks which we show have destabilizing effects on protein-ligand interactions, quantified by free energy calculations. Our expression and activity assays further corroborate the robustness of these wildtype and mutant models. This study provides the most detailed dynamical description of substrate-bound G6PC1 and elucidates the role of activity perturbing mutants on its structure, energetics, expression and activity. Together these findings suggest a molecular mechanism by which G6PC1 mutations may propagate clinical phenotypes of glycogen storage disease.

Molecular insights and optimization strategies for the competitive binding of engineered ACE2 proteins: a multiple replica molecular dynamics study.

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continues to spread globally, and rapid viral evolution and the emergence of new variants pose challenges to pandemic control. During infection, the spike protein of SARS-CoV-2 interacts with the human ACE2 protein via its receptor binding domain (RBD), and it is known that engineered forms of ACE2 can compete with wild-type (WT) ACE2 for binding to inhibit infection. Here, we conducted multiple replica molecular dynamics (MRMD) simulations to study the mechanisms of the engineered ACE2 variants 3N39 and 3N94 and provide directions for optimization. Our findings reveal that engineered ACE2 is notably more efficacious in systems that show weaker binding to WT ACE2 (i.e., WT and BA.1 RBD), but also faces immune escape as the virus evolves. Moreover, by modifying residue types near the binding interface, engineered ACE2 alters the electrostatic potential distribution and reconfigures the hydrogen bonding network, which results in modified binding to the RBD. However, this structural rearrangement does not occur in all RBD variants. In addition, we identified potentially engineerable beneficial residues and potentially engineerable detrimental residues in both ACE2 and RBD. Functional conservation can thus enable the optimization of these residues and improve the binding competitiveness of engineered ACE2, which therefore provides additional immune escape prevention. Finally, we conclude that these findings have implications for understanding the mechanisms responsible for engineered ACE2 and can help us to develop engineered ACE2 proteins that show superior performance.

Selective mechanism of inhibitors to two bromodomains of BRD4 revealed by multiple replica molecular dynamics simulations and free energy analyses

Bromodomain-containing protein 4 (BRD4) is critical in cell cycle regulation and has emerged as a potential target for treatment of various cancers. BRD4 contains two bromodomains, namely BDl and BD2. Research suggests that selectively inhibiting BDl or BD2 may provide more effective treatment options. Therefore, understanding the selective mechanism of inhibitor binding to BDl and BD2 is essential for development of high selective inhibitors to BDl and BD2. Multiple replica molecular dynamics (MRMD) simulations are utilized to investigate the binding selectivity of inhibitors SG3-179, GSK778, and GSK620 for BDl and BD2. The results show that BDl has stronger structural flexibility than BD2, moreover BDl and BD2 exhibit different internal dynamics. The analyses of free energy landscapes reveal significant differences in the conformational distribution of BDl and BD2. Binding free energy predictions suggest that entropy changes, electrostatic interactions, and van der Waals interactions are key factors in the selective binding of BDl and BD2 by SG3-179, GSK778, and GSK620. The calculations of the energy contributions of individual residues demonstrate that residues (W81, W374), (P82, P375), (Q85, K378), (V87, V380), (192, 1385), (N93, G386), (194, 1387), (C136, C429), (N140, N433), (K141, P434), (D144, H437) and (1146, V439) corresponding to (BDl, BD2) generate significant energy difference in binding of SG3-179, GSK778, and GSK620 to BDl and BD2, and they can serve as effective targets for development of high selective inhibitors against BDl or BD2. The related information may provide significant theoretical guidance for improving the selectivity of inhibitors for BDl and BD2.

On the exploration of the melting behavior of metallic compounds and solid solutions via multiple classical molecular dynamics approaches: application to Al-based systems.

Classical molecular dynamics simulations of metallic systems have been extensively applied in recent years for the exploration of the energetic behavior of mesoscale structures and for the generation of thermodynamic and physical properties. The evaluation of the conditions leading to the melting of pure metals and alloys is particularly challenging as it involves at one point the simultaneous presence of both a solid and a liquid phase. Defects such as vacancies, dislocation, grain boundaries and pores typically promote the melting of a solid by locally increasing its free energy which favors the destruction of long-range ordering at the origin of this phase transition. In real materials, many of these defects are microscopic and cannot yet be modelled via conventional atomistic simulations. Still, molecular dynamics-based methodologies are commonly used to estimate the melting temperature of solids. These methods involve the use of mesoscale supercells with various nanoscale defects. Moreover, the deterministic nature of classical MD simulations requires the adequate selection of the initial configuration to be melted. In this context, the main objective of this paper is to quantify the precision of the existing classical molecular dynamics computational methods used to evaluate the melting point of pure compounds as well as the solidus/liquidus lines of Al-based binary metallic systems. We also aim to improve the methodology of different approaches such as the void method, the interface method as well as the grain method to obtain a precise evaluation of the melting behavior of pure metals and alloys. We carefully analyzed the importance of the local chemical ordering on the melting behavior. The ins and outs of different numerical methods in predicting the melting temperature via MD are discussed through several examples related to pure metallic elements, congruently and non-congruently melting compounds as well as binary solid solutions. It is shown that the defect distribution of the initial supercell configuration plays an important role upon the description of the melting mechanism of solids leading to a poor predictive capability of melting temperature if not properly controlled. A new methodology based on defect distribution within the initial configuration is proposed to overcome these limitations.

Insights into pralsetinib resistance to the non-gatekeeper RET kinase G810C mutation through molecular dynamics simulations.

RET (rearranged during transfection) kinase, as a transmembrane receptor tyrosine kinase, is a therapeutic target for several human cancer such as non-small cell lung cancer (NSCLC) and thyroid cancer. Pralsetinib is a recently approved drug for the treatment of RET-driven NSCLC and thyroid cancers. A single point mutation G810C at the C-lobe of the RET kinase causes pralsetinib resistance to this non-gatekeeper variant. However, the detailed mechanism remains poorly understood. Here, multiple microsecond molecular dynamics (MD) simulations, molecular mechanics/generalized born surface area (MM/GBSA) binding free energy calculations, and community network analysis were performed to reveal the mechanism of pralsetinib resistance to the RET G810C mutant. The simulations showed that the G810C mutation had a minor effect on the overall conformational dynamics of the RET kinase domain. Energetic analysis suggested that the G810C mutation reduced the binding affinity of pralsetinib to the mutant. Per-residue energy contribution and structural analyses revealed that the hydrogen bonding interactions between pralsetinib and the hinge residues Glu805 and Ala807 were disrupted in the G810C mutant, which were responsible for the decreased binding affinity of pralsetinib to the mutant. The obtained results may provide understanding of the mechanism of pralsetinib resistance to the non-gatekeeper RET G810C mutant.

In silico mapping of the dynamic interactions and structure-activity relationship of flavonoid compounds against the immune checkpoint programmed-cell death 1 pathway

Flavonoids are a class of natural products widely available in medicinal and dietary plants. Their pharmacological use has shown the potential to reduce the risk of different types of cancer, among other prevalent diseases. Their molecular scaffold inhibits the PD-1/PD-L1 axis, an important pathway related to the adaptive immune resistance of cancer cells already targeted for developing new cancer immunotherapy. However, despite the availability of kinetic and thermodynamic experimental data on the flavonoid–PD-1/PD-L1 interaction, there is still a lack of reliable information about their binding mode at the atomic level. Thus, we aimed to computationally predict the binding mode of flavonoid molecules with PD-1 and/or PD-L1 proteins using unbiased computational methodologies such as blind docking and supervised molecular dynamics simulation. The molecular interactions and dynamics of these predicted poses of protein-flavonoid complexes were further analyzed through multiple molecular dynamics simulations. This information, corroborated with the IC50 and KD values from available literature, was used to perform molecular matched-pair analysis to comprehensively describe the main interactions governing the inhibition of the complex PD-1/PD-L1 by the flavonoid scaffold. By analyzing the effect of substitutions in such a scaffold, we observed a clear correspondence with literature binding assays. Thus, we propose, for dimeric PD-L1, that the 7-O-glucoside forces the molecule displacement in the dimer interface. Furthermore, the 3-OH plays an essential role in stabilizing the buried binding mode by water-bridged hydrogen bonds with Asp122 and Gln66 in both extremities of the pocket. In PD-1, we suggest that flavonoids could bind through the BC loop by inducing a flip of Phe56 after a conformational change of the Asn58 glycosylation. Hence, our results introduced unprecedented information on flavonoid interaction and dynamics when complexed with PD-1 checkpoint pathway proteins and can pave the road for developing new flavonoid derivatives with selective anticancer activity.

Protein Structure Validation Derives a Smart Conformational Search in a Physically Relevant Configurational Subspace.

Since proteins perform biological functions through their dynamic properties, molecular dynamics (MD) simulation is a sophisticated strategy for investigating their functions. Analyses of trajectories provide statistical information about a specific protein as a free-energy landscape (FEL). However, the timescale of normal MD is shorter than that of biological functions, resulting in statistically insufficient conformational sampling, finally leading to unreliable FEL calculation. To search for a broad configurational subspace, an external bias is imposed on a target protein as biased sampling. However, its regulation is challenging because the optimal strength of the perturbation is unknown. Furthermore, a physically irrelevant configurational subspace was searched when imposing an inappropriate external bias. To address this issue, we newly proposed an external biased regulation scheme known as the G-factor external bias limiter (GERBIL). In GERBIL, protein configurations generated by external bias are structurally validated by an indicator (G-factor), enabling the search for a physically relevant subspace. In addition to biased sampling, nonbiased sampling might search for a physically irrelevant configurational subspace because repeating multiple MD simulations from several initial structures tends to search for an overly broad configurational subspace. For this issue, the structural qualities of configurations generated by nonbiased sampling have not been investigated. Therefore, we confirmed whether the G-factor screened the collapsed (low-quality) configurations generated by nonbiased sampling. To address this issue, the outlier flooding method (OFLOOD) was adopted in GERBIL as a nonbiased sampling method, which is referred to as OFLOOD-GERBIL. OFLOOD rapidly expands a configurational subspace by resampling the rarely occurring states of a given protein and tends to search an overly broad subspace. Thus, we considered that GERBIL might improve the excessive conformational search of OFLOOD for a physically irrelevant configurational subspace. As a demonstration, OFLOOD and OFLOOD-GERBIL were applied to a globular protein (T4 lysozyme) and their conformational search qualities were assessed. Based on our assessment, normal OFLOOD without the outlier validation frequently sampled low-quality configurations, whereas OFLOOD-GERBIL with the outlier validation intensively sampled high-quality configurations. In conclusion, OFLOOD-GERBIL derives a smart conformational search in a physically relevant configurational subspace, indicating that protein structure validation works in both nonbiased and biased sampling methods.