Ligand Selectivity Mechanism and Conformational Changes in Guanine Riboswitch by Molecular Dynamics Simulations and Free Energy Calculations

Unraveling Bacterial Single-Stranded Sequence Specificities: Insights from Molecular Dynamics and MMPBSA Analysis of Oligonucleotide Probes

We utilized molecular dynamics (MD) simulations and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) free energy calculations to investigate the specificity of two oligonucleotide probes, namely probe B and probe D, in detecting single-stranded DNA (ssDNA) within three bacteria families: Enterobacteriaceae, Pasteurellaceae, and Vibrionaceae. Due to the limited understanding of molecular mechanisms in the previous research, we have extended the discussion to focus specifically on investigating the binding process of bacteria-probe DNA duplexes, with an emphasis on analyzing the binding free energy. The role of electrostatic contributions in the specificity between the oligonucleotide probes and the bacterial ssDNAs was investigated and found to be crucial. Our calculations yielded results that were highly consistent with the experimental data. Through our study, we have successfully exhibited the benefits of utilizing in-silico approaches as a powerful virtual-screening tool, particularly in research areas that demand a thorough comprehension of molecular interactions.

Conformational States of the GDP- and GTP-Bound HRAS Affected by A59E and K117R: An Exploration from Gaussian Accelerated Molecular Dynamics

The HRAS protein is considered a critical target for drug development in cancers. It is vital for effective drug development to understand the effects of mutations on the binding of GTP and GDP to HRAS. We conducted Gaussian accelerated molecular dynamics (GaMD) simulations and free energy landscape (FEL) calculations to investigate the impacts of two mutations (A59E and K117R) on GTP and GDP binding and the conformational states of the switch domain. Our findings demonstrate that these mutations not only modify the flexibility of the switch domains, but also affect the correlated motions of these domains. Furthermore, the mutations significantly disrupt the dynamic behavior of the switch domains, leading to a conformational change in HRAS. Additionally, these mutations significantly impact the switch domain's interactions, including their hydrogen bonding with ligands and electrostatic interactions with magnesium ions. Since the switch domains are crucial for the binding of HRAS to effectors, any alterations in their interactions or conformational states will undoubtedly disrupt the activity of HRAS. This research provides valuable information for the design of drugs targeting HRAS.

Insights into the selectivity of a brain-penetrant CDK4/6 vs CDK1/2 inhibitor for glioblastoma used in multiple replica molecular dynamics simulations

Cyclin dependent kinases (CDKs) play an important role in cell cycle regulation and their dysfunction is associated with many cancers. That is why CDKs have been attractive targets for the treatment of cancer. Glioblastoma is a cancer caused by the aberrant expression of CDK4/6, so exploring the mechanism of the selection of CDK4/6 toward inhibitors relative to the other family members CDK1/2 is essential. In this work, multiple replica molecular dynamics (MRMD) simulations, principal component analysis (PCA), free energy landscapes (FELs), molecular mechanics Poisson-Boltzmann/Generalized Born surface area (MM-PB/GBSA) and other methods were integrated to decipher the selectively binding mechanism of the inhibitor N1J to CDK4/6 and CDK1/2. Molecular electrostatic potential (MESP) analysis provides an explanation for the N1J selectivity. Residue-based free energy decomposition reveals that most of the hot residues are located at the same location of CDKs proteins, but the different types of residues in different proteins cause changes in binding energy, which is considered as a potential developmental direction to improve the selectivity of inhibitors to CDK4/6. These results provide insights into the source of inhibitor and CDK4/6 selectivity for the future development of more selective inhibitors.Communicated by Ramaswamy H. Sarma.

Dynamical characterization and multiple unbinding paths of two PreQ1 ligands in one pocket

Riboswitches naturally regulate gene expression in bacteria by binding to specific small molecules. Class 1 preQ1 riboswitch aptamer is an important model not only for RNA folding but also as a target for designing small molecule antibiotics due to its well-known minimal aptamer domain. Here, we ran a total of 62.4 μs conventional and enhanced-sampling molecular dynamics (MD) simulations to characterize the determinants underlying the binding of the preQ1-II riboswitch aptamer to two preQ1 ligands in one binding pocket. Decomposition of binding free energy suggested that preQ1 ligands at α and β sites interact with four nucleotides (G5, C17, C18, and A30) and two nucleotides (A12 and C31), respectively. Mg2+ ions play a crucial role in both stabilizing the binding pocket and facilitating ligand binding. The flexible preQ1 ligand at the β site leads to the top of the binding pocket loosening and thus pre-organizes the riboswitch for ligand entry. Enhanced sampling simulations further revealed that the preQ1 ligand at the α site unbinds through two orthogonal pathways, which are dependent on whether or not a β site preQ1 ligand is present. One of the two preQ1 ligands has been identified in the binding pocket, which will aid to identify the second preQ1 Ligand. Our work provides new information for designing robust ligands.

Mechanism of Ligand Discrimination by the NMT1 Riboswitch

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

Decoding the Identification Mechanism of an SAM-III Riboswitch on Ligands through Multiple Independent Gaussian-Accelerated Molecular Dynamics Simulations

S-Adenosyl-l-methionine (SAM)-responsive riboswitches play a central role in the regulation of bacterial gene expression at the level of transcription attenuation or translation inhibition. In this study, multiple independent Gaussian-accelerated molecular dynamics simulations were performed to decipher the identification mechanisms of SAM-III (S_MK) on ligands SAM, SAH, and EEM. The results reveal that ligand binding highly affects the structural flexibility, internal dynamics, and conformational changes of SAM-III. The dynamic analysis shows that helices P3 and P4 as well as two junctions J23 and J24 of SAM-III are highly susceptible to ligand binding. Analyses of free energy landscapes suggest that ligand binding induces different free energy profiles of SAM-III, which leads to the difference in identification sites of SAM-III on ligands. The information on ligand-nucleotide interactions not only uncovers that the π-π, cation-π, and hydrogen bonding interactions drive identification of SAM-III on the three ligands but also reveals that different electrostatic properties of SAM, SAH, and EEM alter the active sites of SAM-III. Meanwhile, the results also verify that the adenine group of SAM, SAH, and EEM is well recognized by conserved nucleotides G7, A29, U37, A38, and G48. We expect that this study can provide useful information for understanding the applications of SAM-III in chemical, synthetic RNA biology, and biomedical fields.

Potential effects of metal ion induced two-state allostery on the regulatory mechanism of add adenine riboswitch

Riboswitches normally regulate gene expression through structural changes in response to the specific binding of cellular metabolites or metal ions. Taking add adenine riboswitch as an example, we explore the influences of metal ions (especially for K⁺ and Mg²⁺ ions) on the structure and dynamics of riboswitch aptamer (with and without ligand) by using molecular dynamic (MD) simulations. Our results show that a two-state transition marked by the structural deformation at the connection of J12 and P1 (C_J12-P1) is not only related to the binding of cognate ligands, but also strongly coupled with the change of metal ion environments. Moreover, the deformation of the structure at C_J12-P1 can be transmitted to P1 directly connected to the expression platform in multiple ways, which will affect the structure and stability of P1 to varying degrees, and finally change the regulation state of this riboswitch.

Molecular dynamic simulations are employed to assess the influence of metal ions on riboswitch structure and dynamics, suggesting a conformational control of riboswitch aptamers by metal ions before ligand binding.

Decoding drug resistant mechanism of V32I, I50V and I84V mutations of HIV-1 protease on amprenavir binding by using molecular dynamics simulations and MM-GBSA calculations

Mutations V32I, I50V and I84V in the HIV-1 protease (PR) induce drug resistance towards drug amprenavir (APV). Multiple short molecular dynamics (MSMD) simulations and molecular mechanics generalized Born surface area (MM-GBSA) method were utilized to investigate drug-resistant mechanism of V32I, I50V and I84V towards APV. Dynamic information arising from MSMD simulations suggest that V32I, I50V and I84V highly affect structural flexibility, motion modes and conformational behaviours of two flaps in the PR. Binding free energies calculated by MM-GBSA method suggest that the decrease in binding enthalpy and the increase in binding entropy induced by mutations V32I, I50V and I84V are responsible for drug resistance of the mutated PRs on APV. The energetic contributions of separate residues on binding of APV to the PR show that V32I, I50V and I84V highly disturb the interactions of two flaps with APV and mostly drive the decrease in binding ability of APV to the PR. Thus, the conformational changes of two flaps in the PR caused by V32I, I50V and I84V play key roles in drug resistance of three mutated PR towards APV. This study can provide useful dynamics information for the design of potent inhibitors relieving drug resistance.

Deciphering Conformational Changes of the GDP-Bound NRAS Induced by Mutations G13D, Q61R, and C118S through Gaussian Accelerated Molecular Dynamic Simulations

The conformational changes in switch domains significantly affect the activity of NRAS. Gaussian-accelerated molecular dynamics (GaMD) simulations of three separate replicas were performed to decipher the effects of G13D, Q16R, and C118S on the conformational transformation of the GDP-bound NRAS. The analyses of root-mean-square fluctuations and dynamics cross-correlation maps indicated that the structural flexibility and motion modes of the switch domains involved in the binding of NRAS to effectors are highly altered by the G13D, Q61R, and C118Smutations. The free energy landscapes (FELs) suggested that mutations induce more energetic states in NRAS than the GDP-bound WT NRAS and lead to high disorder in the switch domains. The FELs also indicated that the different numbers of sodium ions entering the GDP binding regions compensate for the changes in electrostatic environments caused by mutations, especially for G13D. The GDP–residue interactions revealed that the disorder in the switch domains was attributable to the unstable hydrogen bonds between GDP and two residues, V29 and D30. This work is expected to provide information on the energetic basis and dynamics of conformational changes in switch domains that can aid in deeply understanding the target roles of NRAS in anticancer treatment.

RNA-ligand molecular docking: advances and challenges

With rapid advances in computer algorithms and hardware, fast and accurate virtual screening has led to a drastic acceleration in selecting potent small molecules as drug candidates. Computational modeling of RNA-small molecule interactions has become an indispensable tool for RNA-targeted drug discovery. The current models for RNA-ligand binding have mainly focused on the docking-and-scoring method. Accurate docking and scoring should tackle four crucial problems: (1) conformational flexibility of ligand, (2) conformational flexibility of RNA, (3) efficient sampling of binding sites and binding poses, and (4) accurate scoring of different binding modes. Moreover, compared with the problem of protein-ligand docking, predicting ligand binding to RNA, a negatively charged polymer, is further complicated by additional effects such as metal ion effects. Thermodynamic models based on physics-based and knowledge-based scoring functions have shown highly encouraging success in predicting ligand binding poses and binding affinities. Recently, kinetic models for ligand binding have further suggested that including dissociation kinetics (residence time) in ligand docking would result in improved performance in estimating in vivo drug efficacy. More recently, the rise of deep-learning approaches has led to new tools for predicting RNA-small molecule binding. In this review, we present an overview of the recently developed computational methods for RNA-ligand docking and their advantages and disadvantages.

Bacterial 2'-Deoxyguanosine Riboswitch Classes as Potential Targets for Antibiotics: A Structure and Dynamics Study

The spread of antibiotic-resistant bacteria represents a substantial health threat. Current antibiotics act on a few metabolic pathways, facilitating resistance. Consequently, novel regulatory inhibition mechanisms are necessary. Riboswitches represent promising targets for antibacterial drugs. Purine riboswitches are interesting, since they play essential roles in the genetic regulation of bacterial metabolism. Among these, class I (2′-dG-I) and class II (2′-dG-II) are two different 2′-deoxyguanosine (2′-dG) riboswitches involved in the control of deoxyguanosine metabolism. However, high affinity for nucleosides involves local or distal modifications around the ligand-binding pocket, depending on the class. Therefore, it is crucial to understand these riboswitches’ recognition mechanisms as antibiotic targets. In this work, we used a combination of computational biophysics approaches to investigate the structure, dynamics, and energy landscape of both 2′-dG classes bound to the nucleoside ligands, 2′-deoxyguanosine, and riboguanosine. Our results suggest that the stability and increased interactions in the three-way junction of 2′-dG riboswitches were associated with a higher nucleoside ligand affinity. Also, structural changes in the 2′-dG-II aptamers enable enhanced intramolecular communication. Overall, the 2′-dG-II riboswitch might be a promising drug design target due to its ability to recognize both cognate and noncognate ligands.

Binding mechanism of inhibitors to SARS-CoV-2 main protease deciphered by multiple replica molecular dynamics simulations

The outbreak caused by SARS-CoV-2 has received extensive worldwide attention. As the main protease (M^pro) in SARS-CoV-2 has no human homologues, it is feasible to reduce the possibility of targeting the host protein by accidental drugs. Thus, M^pro has been an attractive target of efficient drug design for anti-SARS-CoV-2 treatment. In this work, multiple replica molecular dynamics (MRMD) simulations, principal component analysis (PCA), free energy landscapes (FELs), and the molecular mechanics-generalized Born surface area (MM-GBSA) method were integrated together to decipher the binding mechanism of four inhibitors masitinib, O6K, FJC and GQU to M^pro. The results indicate that the binding of four inhibitors clearly affects the structural flexibility and internal dynamics of M^pro along with dihedral angle changes of key residues. The analysis of FELs unveils that the stability in the relative orientation and geometric position of inhibitors to M^pro is favorable for inhibitor binding. Residue-based free energy decomposition reveals that the inhibitor-M^pro interaction networks involving hydrogen bonding interactions and hydrophobic interactions provide significant information for the design of potent inhibitors against M^pro. The hot spot residues including H41, M49, F140, N142, G143, C145, H163, H164, M165, E166 and Q189 identified by computational alanine scanning are considered as reliable targets of clinically available inhibitors inhibiting the activities of M^pro.

Key criteria for engineering mycotoxin binding aptamers via computational simulations: Aflatoxin B1 as a case study

Due to the difficulties in monoclonal antibody production specific to mycotoxins, aptameric probes have been considered as suitable alternatives. The low efficiency of the SELEX procedure in screening high affinity aptamers for binding mycotoxins as small molecules can be significantly improved through computational techniques. Previously, we designed five new aptamers to aflatoxin B₁ (AFB1) based on a known aptamer sequence (Patent: PCT/CA2010/001 292, Apt1) through a genetic algorithm-based in silico maturation strategy and experimentally measured their affinity to the target toxin. Here, integrated molecular dynamic simulation (MDs) studies with molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analysis to clarify the binding modes, critical interacting nucleic bases and energy component contributions in the six AFB1-binding aptamers. The aptamer F20, which was selected in the first work, showed the best free binding energy and complex stability compared to other aptamers. The trajectory analysis revealed that AFB1 recognized F20 through the groove binding mode along with precise shape complementarity. The MD simulation results revealed that dynamic water intermediate interactions also play a key role in promoting complex stability. According to the MM-PBSA calculations, van der Waals contacts were identified as dominant energy components in all complexes. Interestingly, a high consistency is observed between the experimentally obtained binding affinities of the six aptamers with their free energy solvation. The computational findings, confirmed via previous experiments, highlighted the binding modes, the dynamic hydration of complex components and the total free interacting energy as the crucial criteria in discovering high functional aptameric probes.

Binding free energy decomposition and multiple unbinding paths of buried ligands in a PreQ1 riboswitch

Riboswitches are naturally occurring RNA elements that control bacterial gene expression by binding to specific small molecules. They serve as important models for RNA-small molecule recognition and have also become a novel class of targets for developing antibiotics. Here, we carried out conventional and enhanced-sampling molecular dynamics (MD) simulations, totaling 153.5 μs, to characterize the determinants of binding free energies and unbinding paths for the cognate and synthetic ligands of a PreQ₁ riboswitch. Binding free energy analysis showed that two triplets of nucleotides, U6-C15-A29 and G5-G11-C16, contribute the most to the binding of the cognate ligands, by hydrogen bonding and by base stacking, respectively. Mg²⁺ ions are essential in stabilizing the binding pocket. For the synthetic ligands, the hydrogen-bonding contributions of the U6-C15-A29 triplet are significantly compromised, and the bound state resembles the apo state in several respects, including the disengagement of the C15-A14-A13 and A32-G33 base stacks. The bulkier synthetic ligands lead to significantly loosening of the binding pocket, including extrusion of the C15 nucleobase and a widening of the C15-C30 groove. Enhanced-sampling simulations further revealed that the cognate and synthetic ligands unbind in almost opposite directions. Our work offers new insight for designing riboswitch ligands.

Riboswitches are bacterial RNA elements that change structures upon binding a cognate ligand. They are of great interest not only for understanding gene regulation but also as targets for designing small-molecule antibiotics and chemical tools. Understanding the molecular determinants for ligand affinity and selectivity is thus crucial for designing synthetic ligands. Here we carried out extensive molecular dynamics simulations of a PreQ₁ riboswitch bound to either cognate or synthetic ligands. By comparing and contrasting these two groups of ligands, we learn how the chemical (e.g., number of hydrogen bond donors and acceptors) and physical (e.g., molecular size) features of ligands affect binding affinity and ligand exit paths. While the number of hydrogen bond donors and acceptors is a key determinant for RNA binding affinity, the ligand size affects the rigidity of the binding pocket and thereby regulates the unbinding of the ligand. These lessons provide guidance for designing riboswitch ligands.

AromTool: predicting aromatic stacking energy using an atomic neural network model

Aromatic stacking exists widely and plays important roles in protein-ligand interactions. Computational tools to automatically analyze the geometry and accurately calculate the energy of stacking interactions are desired for structure-based drug design. Herein, we employed a Behler-Parrinello neural network (BPNN) to build predictive models for aromatic stacking interactions and further integrated it into an open-source Python package named AromTool for benzene-containing aromatic stacking analysis. Based on extensive testing, AromTool presents desirable precision in comparison to DFT calculations and excellent efficiency for high-throughput aromatic stacking analysis of protein-ligand complexes.

Molecular mechanism related to the binding of fluorophores to Mango-II revealed by multiple-replica molecular dynamics simulations

Recently, RNA aptamers activating small-molecule fluorophores have been successfully applied to tag and track RNAs in vivo. It is of significance to investigate the molecular mechanism of the fluorophore-RNA aptamer bindings at the atomic level to seek a possible pathway to enhance the fluorescence efficiency of fluorophores. In this work, multiple replica molecular dynamics (MRMD) simulations, essential dynamics (ED) analysis, and hierarchical clustering analysis were coupled to probe the effect of A22U mutation on the binding of two fluorophores, TO1-Biotin (TO1) and TO3-Biotin (TO3), to the Mango-II RNA aptamer (Mango-II). ED analysis reveals that A22U induces alterations in the binding pocket and sites of TO1 and TO3 to the Mango-II, which in turn tunes the fluorophore-RNA interface and changes the interactions of TO1 and TO3 with separate nucleotides of Mango-II. Dynamics analyses also uncover that A22U exerts the opposite impact on the molecular surface areas of the Mango-II and sugar puckers of nucleotides 22 and 23 in Mango-II complexed with TO1 and TO3. Moreover, the calculations of binding free energies suggest that A22U strengthens the binding ability of TO1 to the mutated Mango-II but weakens TO3 to the mutated Mango-II when compared with WT. These findings imply that point mutation in nucleotides possibly tune the fluorescence of fluorophores binding to RNA aptamers, providing a possible scheme to enhance the fluorescence of fluorophores.

Binding of Inhibitors to BACE1 Affected by pH-Dependent Protonation: An Exploration from Multiple Replica Gaussian Accelerated Molecular Dynamics and MM-GBSA Calculations

To date, inhibiting the activity of β-amyloid cleaving enzyme 1 (BACE1) has been considered an efficient approach for treating Alzheimer's disease (AD). In the current work, multiple replica Gaussian accelerated molecular dynamics (MR-GaMD) simulations and the molecular mechanics general Born surface area (MM-GBSA) method were combined to investigate the effect of pH-dependent protonation on the binding of the inhibitors CS9, C6U, and 6WE to BACE1. Dynamic analyses based on the MR-GaMD trajectory show that pH-dependent protonation strongly affects the structural flexibility, correlated motions, and dynamic behavior of inhibitor-bound BACE1. According to the constructed free energy profiles, in the protonated state at low pH, inhibitor-bound BACE1 tends to populate at more conformations than in high pH. The binding free energies calculated by MM-GBSA suggest that inhibitors possess stronger binding abilities under the protonation conditions at high pH than under the protonation conditions at low pH. Moreover, pH-dependent protonation exerts a significant effect on the hydrogen bonding interactions of CS9, C6U, and 6WE to BACE1, which correspondingly alters the binding abilities of the three inhibitors to BACE1. Furthermore, in different protonated environments, three inhibitors share common interaction clusters and similar binding sites in BACE1, which are reliably used as efficient targets for the design of potent inhibitors of BACE1.

Conformational transformation of switch domains in GDP/K-Ras induced by G13 mutants: An investigation through Gaussian accelerated molecular dynamics simulations and principal component analysis

Mutations in K-Ras are involved in a large number of all human cancers, thus, K-Ras is regarded as a promising target for anticancer drug design. Understanding the target roles of K-Ras is important for providing insights on the molecular mechanism underlying the conformational transformation of the switch domains in K-Ras due to mutations. In this study, multiple replica Gaussian accelerated molecular (MR-GaMD) simulations and principal component analysis (PCA) were applied to probe the effect of G13A, G13D and G13I mutations on conformational transformations of the switch domains in GDP-associated K-Ras. The results suggest that G13A, G13D and G13I enhance the structural flexibility of the switch domains, change the correlated motion modes of the switch domains and strengthen the total motion strength of K-Ras compared with the wild-type (WT) K-Ras. Free energy landscape analyses not only show that the switch domains of the GDP-bound inactive K-Ras mainly exist as a closed state but also indicate that mutations evidently alter the free energy profile of K-Ras and affect the conformational transformation of the switch domains between the closed and open states. Analyses of hydrophobic interaction contacts and hydrogen bonding interactions show that the mutations scarcely change the interaction network of GDP with K-Ras and only disturb the interaction of GDP with the switch (SW1). In summary, two newly introduced mutations, G13A and G13I, play similar adjustment roles in the conformational transformations of two switch domains to G13D and are possibly utilized to tune the activity of K-Ras and the binding of guanine nucleotide exchange factors.

Molecular mechanism concerning conformational changes of CDK2 mediated by binding of inhibitors using molecular dynamics simulations and principal component analysis

Cyclin-dependent kinase 2 (CDK2) has been regarded as a promising drug target for anti-tumour agents. In this study, molecular dynamics (MD) simulations and principal component (PC) analysis were used to explore binding mechanism of three inhibitors 1PU, CDK, 50Z to CDK2 and influences of their bindings on conformational changes of CDK2. The results show that bindings of inhibitors yield obvious impacts on internal dynamics, movement patterns and conformational changes of CDK2. In addition, molecular mechanics generalized Born surface area (MM-GBSA) was applied to calculate binding free energies between three inhibitors and CDK2 and evaluate their binding ability to CDK2. The results show that CDK has the strongest binding to CDK2 among the current three inhibitors. Residue-based free energy decomposition method was further utilized to decode the contributions of a single residue to binding of inhibitors, and it was found that three inhibitors not only produce hydrogen bonding interactions and hydrophobic interactions with key residues of CDK2, which promotes binding of three inhibitors to CDK2, but also share similar binding modes. This work is expected to be helpful for design of efficient drugs targeting CDK2.

Binding Selectivity of Inhibitors toward Bromodomains BAZ2A and BAZ2B Uncovered by Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

Two Bromodomain-Containing proteins BAZ2A and BAZ2B are responsible for remodeling chromatin and regulating noncoding RNAs. As for our current studies, integration of multiple short molecular dynamics simulations (MSMDSs) with molecular mechanics generalized Born surface area (MM-GBSA) method is adopted for insights into binding selectivity of three small molecules D8Q, D9T and UO1 to BAZ2A against BAZ2B. The calculations of MM-GBSA unveil that selectivity of inhibitors toward BAZ2A and BAZ2B highly depends on the enthalpy changes and the details uncover that D8Q has better selectivity toward BAZ2A than BAZ2B, D9T more favorably bind to BAZ2B than BAZ2A, and UO1 does not show obvious selectivity toward these two proteins. The analysis of interaction network between residues and inhibitors indicates that seven residues are mainly responsible for the selectivity of D8Q, six residues for D9T and four residues provide significant contributions to associations of UO1 with two proteins. Moreover the analysis of interaction network not only reveals warm spots of inhibitor bindings to BAZ2A and BAZ2B but also unveils that common residue pairs, including (W1816, W1887), (P1817, P1888), (F1818, F1889), (V1822, V1893), (N1823, N1894),(L1826, L1897), (V1827, V1898), (F1872, F1943), (N1873, N1944) and (V1879, I1950) belonging to (BAZ2A, BAZ2B), induce mainly binding differences of inhibitors to BAZ2A and BAZ2B. Hence, insights from our current studies offer useful dynamics information relating with conformational alterations and structure-affinity relationship at atomistic levels for novel therapeutic strategies toward BAZ2A and BAZ2B.

Binding mechanism of inhibitors to p38α MAP kinase deciphered by using multiple replica Gaussian accelerated molecular dynamics and calculations of binding free energies

The p38α MAP Kinase has been an important target of drug design for treatment of inflammatory diseases and cancers. This work applies multiple replica Gaussian accelerated molecular dynamics (MR-GaMD) simulations and the molecular mechanics generalized Born surface area (MM-GBSA) method to probe the binding mechanism of inhibitors L51, R24 and 1AU to p38α. Dynamics analyses show that inhibitor bindings exert significant effect on conformational changes of the active helix α2 and the conserved DFG loop. The rank of binding free energies calculated with MM-GBSA not only agrees well with that determined by the experimental IC50 values but also suggests that mutual compensation between the enthalpy and entropy changes can improve binding of inhibitors to p38α. The analyses of free energy landscapes indicate that the L51, R24 and 1AU bound p38α display a DFG-out conformation. The residue-based free energy decomposition method is used to evaluate contributions of separate residues to the inhibitor-p38α binding and the results imply that residues V30, V38, L74, L75, I84, T106, H107, L108, M109, L167, F169 and D168 can be utilized as efficient targets of potent inhibitors toward p38α.

Molecular mechanisms of inhibitor bindings to A-FABP deciphered by using molecular dynamics simulations and calculations of MM-GBSA

Adipocyte fatty-acid binding protein (A-FABP) plays a central role in many aspects of metabolic diseases. It is an important target in drug design for treatment of FABP-related diseases. In this study, molecular dynamics (MD) simulations followed by calculations of molecular mechanics generalized Born surface area (MM-GBSA) and principal components analysis (PCA) were implemented to decipher molecular mechanism correlating with binding of inhibitors 57Q, 57P and L96 to A-FABP. The results show that van der Waals interactions are the leading factors to control associations of 57Q, 57P, and L96 with A-FABP, which reveals an energetic basis for designing of clinically available inhibitors towards A-FABP. The information from PCA and cross-correlation analysis rationally unveils that inhibitor bindings affect conformational changes of A-FABP and change relative movements between residues. Decomposition of binding affinity into contributions of individual residues not only detects hot spots of inhibitor/A-FABP binding but also shows that polar interactions of the positively charged residue Arg126 with three inhibitors provide a significant contribution for stabilization of the inhibitor/A-FABP bindings. Furthermore, the binding strength of L96 to residues Ser55, Phe57 and Lys58 are stronger than that of inhibitors 57Q and 57P to these residues.

Mutation-Induced Impacts on the Switch Transformations of the GDP- and GTP-Bound K-Ras: Insights from Multiple Replica Gaussian Accelerated Molecular Dynamics and Free Energy Analysis

Mutations yield significant effect on the structural flexibility of two switch domains, SW1 and SW2, in K-Ras, which is considered as an important target of anticancer drug design. To unveil a molecular mechanism with regard to mutation-mediated tuning on the activity of K-Ras, multiple replica Gaussian accelerated molecular dynamics (MR-GaMD) simulations followed by analysis of free energy landscapes (FELs) are performed on the GDP- and GTP-bound wild-type (WT), G12V, and D33E K-Ras. The results suggest that G12V and D33E not only evidently change the flexibility of SW1 and SW2 but also greatly affect correlated motions of SW1 and SW2 separately relative to the P-loop and SW1, which exerts a certain tuning on the activity of K-Ras. The information stemming from the analyses of FELs reveals that the conformations of SW1 and SW2 are in high disorders in the GDP- and GTP-associated WT and mutated K-Ras, possibly producing significant effect on binding of guanine nucleotide exchange factors or effectors to K-Ras. The interaction networks of GDP and GTP with K-Ras are identified and the results uncover that the instability in hydrogen-bonding interactions of SW1 with GDP and GTP is mostly responsible for conformational disorder of SW1 and SW2 as well as tunes the activity of oncogenic K-Ras.

Computational Design of PDZ-Peptide Binding

This chapter describes two computational methods for PDZ-peptide binding: high-throughput computational protein design (CPD) and a medium-throughput approach combining molecular dynamics for conformational sampling with a Poisson-Boltzmann (PB) Linear Interaction Energy for scoring. A new CPD method is outlined, which uses adaptive Monte Carlo simulations to efficiently sample peptide variants that tightly bind a PDZ domain, and provides at the same time precise estimates of their relative binding free energies. A detailed protocol is described based on the Proteus CPD software. The medium-throughput approach can be performed with standard MD and PB software, such as NAMD and Charmm. For 40 complexes between Tiam1 and peptide ligands, it gave high a2ccuracy, with mean errors of around 0.5 kcal/mol for relative binding free energies and no large errors. It requires a moderate amount of parameter fitting before it can be applied, and its transferability to other protein families is still untested.

Effects of Disulfide Bonds on Binding of Inhibitors to β-Amyloid Cleaving Enzyme 1 Decoded by Multiple Replica Accelerated Molecular Dynamics Simulations

The β-amyloid cleaving enzyme 1 (BACE1) has been thought to be an efficient target for treatment of Alzheimer's disease (AD). Deep insight into inhibitor-BACE1 binding mechanism is of significance for design of potent drugs toward BACE1. In this work, multiple replica accelerated molecular dynamics (MR-aMD) simulations, principal component (PC) analysis, and free energy landscapes were integrated to decode the effect of disulfide bonds (SSBs) in BACE1 on bindings of three inhibitors 3KO, 3KT, and 779 to BACE1. The results from cross-correlation analysis suggest that the breaking of SSBs exerts significant influence on structural flexibility and internal dynamics of inhibitor-bound BACE1. PC analysis and free energy landscapes reveal that the breaking of SSBs not only evidently induces the conformational rearrangement of BACE1 but also highly changes binding poses of three inhibitors in BACE1 and leads to more disordered binding of three inhibitors to BACE1, which is further supported by the increase in binding entropy of inhibitors to BACE1 due to the breaking of SSBs. Residue-based free energy decomposition method was utilized to evaluate contributions of separate residues to inhibitor-BACE1 binding. The results suggest that although the breaking of SSBs in BACE1 does not destroy the interaction network of inhibitors with BACE1 it changes interaction strength of some residues with inhibitors. Meanwhile, the information from residue-based free energy decomposition indicates that residues L91, S96, V130, Y132, Q134, W137, F169, I171, and I179 can be used as efficient targets of drug design toward BACE1.

Ligand Binding Mechanism and Its Relationship with Conformational Changes in Adenine Riboswitch

Riboswitches are naturally occurring RNA aptamers that control the expression of essential bacterial genes by binding to specific small molecules. The binding with both high affinity and specificity induces conformational changes. Thus, riboswitches were proposed as a possible molecular target for developing antibiotics and chemical tools. The adenine riboswitch can bind not only to purine analogues but also to pyrimidine analogues. Here, long molecular dynamics (MD) simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) computational methodologies were carried out to show the differences in the binding model and the conformational changes upon five ligands binding. The binding free energies of the guanine riboswitch aptamer with C74U mutation complexes were compared to the binding free energies of the adenine riboswitch (AR) aptamer complexes. The calculated results are in agreement with the experimental data. The differences for the same ligand binding to two different aptamers are related to the electrostatic contribution. Binding dynamical analysis suggests a flexible binding pocket for the pyrimidine ligand in comparison with the purine ligand. The 18 μs of MD simulations in total indicate that both ligand-unbound and ligand-bound aptamers transfer their conformation between open and closed states. The ligand binding obviously affects the conformational change. The conformational states of the aptamer are associated with the distance between the mass center of two key nucleotides (U51 and A52) and the mass center of the other two key nucleotides (C74 and C75). The results suggest that the dynamical character of the binding pocket would affect its biofunction. To design new ligands of the adenine riboswitch, it is recommended to consider the binding affinities of the ligand and the conformational change of the ligand binding pocket.

Effect of mutations on binding of ligands to guanine riboswitch probed by free energy perturbation and molecular dynamics simulations

Riboswitches can regulate gene expression by direct and specific interactions with ligands and have recently attracted interest as potential drug targets for antibacterial. In this work, molecular dynamics (MD) simulations, free energy perturbation (FEP) and molecular mechanics generalized Born surface area (MM-GBSA) methods were integrated to probe the effect of mutations on the binding of ligands to guanine riboswitch (GR). The results not only show that binding free energies predicted by FEP and MM-GBSA obtain an excellent correlation, but also indicate that mutations involved in the current study can strengthen the binding affinity of ligands GR. Residue-based free energy decomposition was applied to compute ligand-nucleotide interactions and the results suggest that mutations highly affect interactions of ligands with key nucleotides U22, U51 and C74. Dynamics analyses based on MD trajectories indicate that mutations not only regulate the structural flexibility but also change the internal motion modes of GR, especially for the structures J12, J23 and J31, which implies that the aptamer domain activity of GR is extremely plastic and thus readily tunable by nucleotide mutations. This study is expected to provide useful molecular basis and dynamics information for the understanding of the function of GR and possibility as potential drug targets for antibacterial.

Molecular mechanism with regard to the binding selectivity of inhibitors toward FABP5 and FABP7 explored by multiple short molecular dynamics simulations and free energy analyses

Recently, fatty acid binding proteins 5 and 7 (FABP5 and FABP7) have been regarded as the prospective targets for clinically treating multiple diseases related to FABPs.

Understanding conformational diversity of heat shock protein 90 (HSP90) and binding features of inhibitors to HSP90 via molecular dynamics simulations

Heat shock protein 90 (HSP90) is a promising target for treatment of cancer, and inhibitor bindings can generate efficient suppression on tumor in multiple ways. In this work, 140-ns molecular dynamics simulations were performed on six systems. Principal component analysis was subsequently carried out to explore the conformational diversity of HSP90. The results suggest that inhibitor bindings induce large conformational changes of HSP90, which tends to enlarge the volume of the binding pocket to facilitate the entrance of inhibitors. Hierarchical clustering analyses, the calculation of the energy contribution of each atom, and the analyses of hydrogen-bonding interactions were performed. The results indicate that 20 residues in group A of the hierarchical tree are responsible for major contributions, and van der Waals interactions as well as hydrogen-bonding interactions between important residues in HSP90 and key regions of inhibitors are the main force for promoting inhibitor bindings. We expect that this work can provide useful theoretical information for development of efficient inhibitors targeting HSP90.

Quantum chemical and well-tempered metadynamics study to design adenine analogs for orthogonal Preq1 riboswitch

Communicated by Ramaswamy H. Sarma.

Structural insights into the interactions of flavin mononucleotide (FMN) and riboflavin with FMN riboswitch: a molecular dynamics simulation study

Antibiotics resistance is becoming a serious problem associated with fatalities and suffering patients. New antibiotics that can target the broader spectrum of cellular processes are warranted. One of the recent approaches in this regard is to target the special type of RNA riboswitches in bacteria. In this report, we have explored the mechanistic pathways of ligand-dependent conformational changes of flavin mononucleotide (FMN) riboswitch using molecular dynamics (MD) simulation studies. Cognate ligands FMN and riboflavin (RBF) have shown very different behavior with FMN riboswitch in terms of their role in the gene regulation process. These two ligands have similar scaffold, except the terminal phosphate group in FMN ligand. The MD simulations reveal that the binding of FMN ligand with the riboswitch does not lead to global folding of structure, rather lead to local changes in riboswitch structure. The binding free energy calculated with molecular mechanics Poisson-Boltzmann surface area method suggests the stronger binding of FMN than RBF to the riboswitch and electrostatic energy contributes chiefly to stabilize the complex. Further, the hydrogen bonding analysis identified the key binding site residues G11, G32, G62 of the riboswitch with FMN and RBF. The critical role of the phosphate group in the FMN ligand for binding with the active site of a riboswitch is also borne out in this study. These results unravel the importance of functional groups in natural ligands on designing newer ligands for FMN riboswitch as new antibiotics in the future.Communicated by Ramaswamy H. Sarma.

Decoding molecular mechanism of inhibitor bindings to CDK2 using molecular dynamics simulations and binding free energy calculations

CDK2 can be used as an attractive target for development of efficient inhibitors curing multiple disease relating with CDK2. In this work, molecular dynamics (MD) simulations and binding free energy calculations were coupled to probe conformational changes of CDK2 due to inhibitor associations and binding mechanisms of inhibitors PM1, FMD and X64 to CDK2. The results suggest that the binding strength of FMD and X64 to CDK2 is stronger than that of PM1. Principal component (PC) analysis and cross-correlation map calculations based on the equilibrated MD trajectories demonstrate that the structural difference in inhibitors exerts important impact on motion modes and dynamics behavior of CDK2. Residue-based free energy decomposition method was adopted to estimate the inhibitor-residue spectrum. The results not only efficiently identify the hot interaction spot of inhibitors with CDK2 but also show that the hydrophobic rings R1, R2 and R3 as well as polar groups of three inhibitors play key roles in favorably binding of inhibitors to CDK2. This work is expected to contribute energetic basis and dynamics information to development of promising inhibitors toward CDK2.Communicated by Ramaswamy H. Sarma.

TPP riboswitch aptamer: Role of Mg2+ ions, ligand unbinding, and allostery

Riboswitches are non-coding RNAs that regulate gene expression in response to the binding of metabolites. Their abundance in bacteria makes them ideal drug targets. The prokaryotic thiamine pyrophosphate (TPP) riboswitch regulates gene expression in a wide range of bacteria by undergoing conformational changes in response to the binding of TPP. Although an experimental structure for the aptamer domain of the riboswitch is now available, details of the conformational changes that occur during the binding of the ligand, and the factors that govern these conformational changes, are still not clear. This study employs microsecond-scale molecular dynamics simulations to provide insights into the functioning of the riboswitch aptamer in atomistic detail. A mechanism for the transmission of conformational changes from the ligand-binding site to the P1 switch helix is proposed. Mg²⁺ ions in the binding site play a critical role in anchoring the ligand to the riboswitch. Finally, modeling the egress of TPP from the binding site reveals a two-step mechanism for TPP unbinding. Findings from this study can motivate the design of future studies aimed at modulating the activity of this drug target.

Atomistic Analysis of ToxN and ToxI Complex Unbinding Mechanism

ToxIN is a triangular structure formed by three protein toxins (ToxNs) and three specific noncoding RNA antitoxins (ToxIs). To respond to stimuli, ToxI is preferentially degraded, releasing the ToxN. Thus, the dynamic character is essential in the normal function interactions between ToxN and ToxI. Here, equilibrated molecular dynamics (MD) simulations were performed to study the stability of ToxN and ToxI. The results indicate that ToxI adjusts the conformation of 3' and 5' termini to bind to ToxN. Steered molecular dynamics (SMD) simulations combined with the recently developed thermodynamic integration in 3nD (TI3nD) method were carried out to investigate ToxN unbinding from the ToxIN complex. The potentials of mean force (PMFs) and atomistic pictures suggest the unbinding mechanism as follows: (1) dissociation of the 5' terminus from ToxN, (2) missing the interactions involved in the 3' terminus of ToxI without three nucleotides (G31, A32, and A33), (3) starting to unfold for ToxI, (4) leaving the binding package of ToxN for three nucleotides of ToxI, (5) unfolding of ToxI. This work provides information on the structure-function relationship at the atomistic level, which is helpful for designing new potent antibacterial drugs in the future.

Exploring molecular mechanism of allosteric inhibitor to relieve drug resistance of multiple mutations in HIV-1 protease by enhanced conformational sampling

Recently, allosteric regulations of HIV-1 protease (PR) are suggested as a promising approach to relieve drug resistance of mutations toward inhibitors targeting the active site of PR. Replica-exchange molecular dynamics (REMD) simulations and normal mode analysis (NMA) are integrated to enhance conformational sampling of PR. Molecular mechanics generalized Born surface area (MM-GBSA) method was applied to calculate binding free energies of three inhibitors APV, DRV, and NIT to the wild-type (WT) and multidrug resistance (MDR) PRs. The results suggest that binding free energies of APV and DRV are decreased in the MDR PR relative to the WT PR, suggesting drug resistance of mutations on these two inhibitors. However, the binding ability of the allosteric inhibitor NIT is not impaired in the MDR PR. In addition, internal dynamics analysis based on REMD simulations proves that mutations hardly produce obvious effect on the conformation of the MDR PR in comparison to the WT PR. Scanning of hydrophobic contacts and hydrogen bond contacts of inhibitors with residues of PRs on the concatenated trajectories of REMD demonstrates that mutations change the symmetric interaction networks of APV and DRV with PR, but do not generate obvious influence on the asymmetric interaction network of NIT with PR. In summary, allosteric inhibitor NIT can adapt the MDR PR better than those inhibitors toward the active site of PR, thus allosteric inhibitors of PR may be a possible channel to overcome drug resistance of PR.

Insight into selective mechanism of class of I-BRD9 inhibitors toward BRD9 based on molecular dynamics simulations

Recently, bromodomain-containing protein 9 (BRD9), 7 (BRD7), and 4 (BRD4) have been potential targets of anticancer drug design. Molecular dynamic simulations followed by molecular mechanics Poisson-Boltzmann surface area calculation were performed to study the selective mechanism of I-BRD9 inhibitor H1B and its derivatives N1D, TVU, and 5V2 toward BRD9 and BRD4. The rank of our calculated binding free energies agrees with that of the experimental data. The results show that binding free energy of H1B to BRD7 is slightly lower than that of H1B to BRD9, and all four inhibitors bind more tightly to BRD9 than to BRD4. Decomposition of binding free energies into individual residues implies that Ile164 and Asn211 in BRD7 and Ile53 and Asn100 in BRD9 play a significant role in the selectivity of H1B toward BRD7 and BRD9. Besides, several key residues Phe44, Ile53, Asn100, Thr104 in BRD9 and Pro82, Lys91, Asn140, Asp144 in BRD4 that are located in the ZA-loop and BC-loop provide significant contributions to binding selectivity of inhibitors to BRD9 and BRD4. This study is expected to provide important theoretical guidance for rational designs of highly selective inhibitors targeting BRD9 and BRD4.

Molecular Dynamics Exploration of Selectivity of Dual Inhibitors 5M7, 65X, and 65Z toward Fatty Acid Binding Proteins 4 and 5

Designing highly selective inhibitors of fatty acid binding proteins 4 and 5 (FABP4 and FABP5) is of importance for treatment of some diseases related with inflammation, metabolism, and tumor growth. In this study, molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method were performed to probe binding selectivity of three inhibitors (5M7, 65X, and 65Z) to FABP4/FABP5 with K_i values of 0.022/0.50 μM, 0.011/0.086 μM, and 0.016/0.12 μM, respectively. The results not only suggest that all inhibitors associate more tightly with FABP4 than FABP5, but also prove that the main forces driving the selective bindings of inhibitors to FABP4 and FABP5 stem from the difference in the van der Waals interactions and polar interactions of inhibitors with two proteins. Meanwhile, a residue-based free energy decomposition method was applied to reveal molecular basis that inhibitors selectively interact with individual residues of two different proteins. The calculated results show that the binding difference of inhibitors to the residues (Phe16, Phe19), (Ala33, Gly36), (Phe57, Leu60), (Ala75, Ala78), (Arg126, Arg129), and (Tyr128, Tyr131) in (FABP4, FABP5) drive the selectivity of inhibitors toward FABP4 and FABP5. This study will provide great help for further design of effective drugs to protect against a series of metabolic diseases, arteriosclerosis, and inflammation.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Exploring RNA structure and dynamics through enhanced sampling simulations

RNA function is intimately related to its structural dynamics. Molecular dynamics simulations are useful for exploring biomolecular flexibility but are severely limited by the accessible timescale. Enhanced sampling methods allow this timescale to be effectively extended in order to probe biologically relevant conformational changes and chemical reactions. Here, we review the role of enhanced sampling techniques in the study of RNA systems. We discuss the challenges and promises associated with the application of these methods to force-field validation, exploration of conformational landscapes and ion/ligand-RNA interactions, as well as catalytic pathways. Important technical aspects of these methods, such as the choice of the biased collective variables and the analysis of multi-replica simulations, are examined in detail. Finally, a perspective on the role of these methods in the characterization of RNA dynamics is provided.

Recent Developments and Applications of the MMPBSA Method

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.

Dynamics revelation of conformational changes and binding modes of heat shock protein 90 induced by inhibitor associations

Heat shock protein 90 (Hsp90) has been an attractive target of potential drug design for antitumor treatment. The current work integrates molecular dynamics (MD) simulations, calculations of binding free energy, and principal component (PC) analysis with scanning of inhibitor–residue interaction to probe the binding modes of inhibitors YK9, YKJ and YKI to Hsp90 and identify the hot spot of the inhibitor–Hsp90 binding. The results suggest that the introductions of two groups G1 and G2 into YKJ and YKI strengthen the binding ability of YKJ and YKI to Hsp90 compared to YK9. PC analysis based MD trajectories prove that inhibitor bindings exert significant effects on the conformational changes, internal dynamics and motion modes of Hsp90, especially for the helix α2 and the loops L1 and L2. The calculations of residue-based free energy decomposition and scanning of the inhibitor–Hsp90 interaction suggest that six residues L107, G108, F138, Y139, W162 and F170 construct the common hot spot of the inhibitor–residue interactions. Moreover the substitutions of the groups G1 and G2 in YKJ and YKI lead to two additional hydrogen bonding interactions and multiple hydrophobic interactions for bindings of YKJ and YKI to Hsp90. This work is also expected to contribute theoretical hints for the design of potent inhibitors toward Hsp90.

Heat shock protein 90 (Hsp90) has been an attractive target of potential drug design for antitumor treatment.