Identification and molecular docking of tyrosinase inhibitory peptides from allophycocyanin in Spirulina platensis.

BACKGROUND: Tyrosinase, a copper-containing metalloenzyme with catalytic activity, is widely found in mammals. It is the key rate-limiting enzyme that catalyzes melanin synthesis. For humans, tyrosinase is beneficial to the darkening of eyes and hair. However, excessive deposition of melanin in the skin can lead to dull skin color and lead to pigmentation. Therefore, many skin-whitening compounds have been developed to decrease tyrosinase activity. This study aimed to identify a new tyrosinase inhibitory peptide through enzymatic hydrolysis, in vitro activity verification, molecular docking, and molecular dynamics (MD) simulation. RESULTS: A tripeptide Asp-Glu-Arg (DER) was identified, with a '-CDOCKER_Energy' value of 121.26 Kcal mol-1 . DER has effective tyrosinase inhibitory activity. Research shows that its half maximal inhibitory concentration value is 1.04 ± 0.01 mmol L-1 . In addition, DER binds to tyrosinase residues His85, His244, His259, and Asn260, which are key residues that drive the interaction between the peptide and tyrosinase. Finally, through MD simulation, the conformational changes and structural stability of the complexes were further explored to verify and supplement the results of molecular docking. CONCLUSION: This experiment shows that DER can effectively inhibit tyrosinase activity. His244, His259, His260, and Asn260 are the critical residues that drive the interaction between the peptide and tyrosinase, and hydrogen bonding is an important force. DER from Spirulina has the potential to develop functional products with tyrosinase inhibition. © 2024 Society of Chemical Industry.

The relayed nuclear Overhauser effect in magnetization transfer and chemical exchange saturation transfer MRI.

Magnetic resonance (MR) is a powerful technique for noninvasively probing molecular species in vivo but suffers from low signal sensitivity. Saturation transfer (ST) MRI approaches, including chemical exchange saturation transfer (CEST) and conventional magnetization transfer contrast (MTC), allow imaging of low-concentration molecular components with enhanced sensitivity using indirect detection via the abundant water proton pool. Several recent studies have shown the utility of chemical exchange relayed nuclear Overhauser effect (rNOE) contrast originating from nonexchangeable carbon-bound protons in mobile macromolecules in solution. In this review, we describe the mechanisms leading to the occurrence of rNOE-based signals in the water saturation spectrum (Z-spectrum), including those from mobile and immobile molecular sources and from molecular binding. While it is becoming clear that MTC is mainly an rNOE-based signal, we continue to use the classical MTC nomenclature to separate it from the rNOE signals of mobile macromolecules, which we will refer to as rNOEs. Some emerging applications of the use of rNOEs for probing macromolecular solution components such as proteins and carbohydrates in vivo or studying the binding of small substrates are discussed.

HIV-1 Tat amino acid residues that influence Tat-TAR binding affinity: a scoping review.

HIV-1 remains a global health concern and to date, nearly 38 million people are living with HIV. The complexity of HIV-1 pathogenesis and its subsequent prevalence is influenced by several factors including the HIV-1 subtype. HIV-1 subtype variation extends to sequence variation in the amino acids of the HIV-1 viral proteins. Of particular interest is the transactivation of transcription (Tat) protein due to its key function in viral transcription. The Tat protein predominantly functions by binding to the transactivation response (TAR) RNA element to activate HIV-1 transcriptional elongation. Subtype-specific Tat protein sequence variation influences Tat-TAR binding affinity. Despite several studies investigating Tat-TAR binding, it is not clear which regions of the Tat protein and/or individual Tat amino acid residues may contribute to TAR binding affinity. We, therefore, conducted a scoping review on studies investigating Tat-TAR binding. We aimed to synthesize the published data to determine (1) the regions of the Tat protein that may be involved in TAR binding, (2) key Tat amino acids involved in TAR binding and (3) if Tat subtype-specific variation influences TAR binding. A total of thirteen studies met our inclusion criteria and the key findings were that (1) both N-terminal and C-terminal amino acids outside the basic domain (47-59) may be important in increasing Tat-TAR binding affinity, (2) substitution of the amino acids Lysine and Arginine (47-59) resulted in a reduction in binding affinity to TAR, and (3) none of the included studies have investigated Tat subtype-specific substitutions and therefore no commentary could be made regarding which subtype may have a higher Tat-TAR binding affinity. Future studies investigating Tat-TAR binding should therefore use full-length Tat proteins and compare subtype-specific variations. Studies of such a nature may help explain why we see differential pathogenesis and prevalence when comparing HIV-1 subtypes.

Detection of electrostatic molecular binding using the water proton signal.

PURPOSE: Saturation transfer MRI has previously been used to probe molecular binding interactions with signal enhancement via the water signal. Here, we detail the relayed nuclear overhauser effect (rNOE) based mechanisms of this signal enhancement, develop a strategy of quantifying molecular binding affinity, i.e., the dissociation constant ( KD$$ {K}_D $$ ), and apply the method to detect electrostatic binding of several charged small biomolecules. Another goal was to estimate the detection limit for transient receptor-substrate binding. THEORY AND METHODS: The signal enhancement mechanism was quantitatively described by a three-step magnetization transfer model, and numerical simulations were performed to verify this theory. The binding equilibria of arginine, choline, and acetyl-choline to anionic resin were studied as a function of ligand concentration, pH, and salt content. Equilibrium dissociation constants ( KD$$ {K}_D $$ ) were determined by fitting the multiple concentration data. RESULTS: The numerical simulations indicate that the signal enhancement is sufficient to detect the molecular binding of sub-millimolar (∼100 µM) concentration ligands to low micromolar levels of molecular targets. The measured rNOE signals from arginine, choline, and acetyl-choline binding experiments show that several magnetization transfer pathways (intra-ligand rNOEs and intermolecular rNOEs) can contribute. The rNOEs that arise from molecular ionic binding were influenced by pH and salt concentration. The molecular binding strengths in terms of KD$$ {K}_{\mathrm{D}} $$ ranged from 70-160 mM for the three cations studied. CONCLUSION: The capability to use MRI to detect the transient binding of small substrates paves a pathway towards the detection of micromolar level receptor-substrate binding in vivo.

Conformational Properties and Putative Bioactive Targets for Novel Thiosemicarbazone Derivatives.

The structure assignment and conformational analysis of the thiosemicarbazones, DKI21 and DKI24, were performed through homonuclear and heteronuclear 2D Nuclear Magnetic Resonance (NMR) spectroscopy (2D-COSY, 2D-NOESY, 2D-ROESY, 2D-HSQC, and 2D-HMBC) and quantum mechanics (QM) calculations, using Functional Density Theory (DFT). In addition, utilizing a combination of 2D-NOESY and 2D-ROESY spectra an exo structure was established for both of the analogs. This experimental results were confirmed by theoretical mechanistic studies, as the lowest minima conformations derived through DFT calculations were compatible with the spatial correlations observed in the 2D-NOESY and 2D-ROESY spectra. Finally, molecular binding experiments were performed to detect the potential targets for DKI21 and DKI24, derived from SwissAdme. In silico molecular binding experiments showed favorable binding energy values for the most of the enzymes studied. The ADMET calculations, using the preADMET and pKCSm software, showed that the two molecules appear as possible drug leads.

Conformational Properties of New Thiosemicarbazone and Thiocarbohydrazone Derivatives and Their Possible Targets.

The structure assignment and conformational analysis of thiosemicarbazone KKI15 and thiocarbohydrazone KKI18 were performed through homonuclear and heteronuclear 2D Nuclear Magnetic Resonance (NMR) spectroscopy (2D-COSY, 2D-NOESY, 2D-HSQC, and 2D-HMBC) and quantum mechanics (QM) calculations using Functional Density Theory (DFT). After the structure identification of the compounds, various conformations of the two compounds were calculated using DFT. The two molecules showed the most energy-favorable values when their two double bonds adopted the E configuration. These configurations were compatible with the spatial correlations observed in the 2D-NOESY spectrum. In addition, due to the various isomers that occurred, the energy of the transition states from one isomer to another was calculated. Finally, molecular binding experiments were performed to detect potential targets for KKI15 and KKI18 derived from SwissAdme. In silico molecular binding experiments showed favorable binding energy values for all four enzymes studied. The strongest binding energy was observed in the enzyme butyrylcholinesterase. ADMET calculations using the preADMET and pKCSm software showed that the two molecules appear as possible drug leads.

Physics of biomolecular recognition and conformational dynamics.

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Generalized-ensemble method study: A helix-mimetic compound inhibits protein-protein interaction by long-range and short-range intermolecular interactions.

A heterocyclic compound mS-11 is a helix-mimetic designed to inhibit binding of an intrinsic disordered protein neural restrictive silence factor/repressor element 1 silencing factor (NRSF/REST) to a receptor protein mSin3B. We apply a generalized ensemble method, multi-dimensional virtual-system coupled molecular dynamics developed by ourselves recently, to a system consisting of mS-11 and mSin3B, and obtain a thermally equilibrated distribution, which is comprised of the bound and unbound states extensively. The lowest free-energy position of mS-11 coincides with the NRSF/REST position in the experimentally-determined NRSF/REST-mSin3B complex. Importantly, the molecular orientation of mS-11 is ordering in a wide region around mSin3B. The resultant binding scenario is: When mS-11 is distant from the binding site of mSin3B, mS-11 descends the free-energy slope toward the binding site maintaining the molecular orientation to be advantageous for binding. Then, finally a long and flexible hydrophobic sidechain of mS-11 fits into the binding site, which is the lowest-free-energy complex structure inhibiting NRSF/REST binding to mSin3B.

Protein-protein and protein-nucleic acid binding residues important for common and rare sequence variants in human.

BACKGROUND: Any two unrelated people differ by about 20,000 missense mutations (also referred to as SAVs: Single Amino acid Variants or missense SNV). Many SAVs have been predicted to strongly affect molecular protein function. Common SAVs (> 5% of population) were predicted to have, on average, more effect on molecular protein function than rare SAVs (< 1% of population). We hypothesized that the prevalence of effect in common over rare SAVs might partially be caused by common SAVs more often occurring at interfaces of proteins with other proteins, DNA, or RNA, thereby creating subgroup-specific phenotypes. We analyzed SAVs from 60,706 people through the lens of two prediction methods, one (SNAP2) predicting the effects of SAVs on molecular protein function, the other (ProNA2020) predicting residues in DNA-, RNA- and protein-binding interfaces. RESULTS: Three results stood out. Firstly, SAVs predicted to occur at binding interfaces were predicted to more likely affect molecular function than those predicted as not binding (p value < 2.2 × 10-16). Secondly, for SAVs predicted to occur at binding interfaces, common SAVs were predicted more strongly with effect on protein function than rare SAVs (p value < 2.2 × 10-16). Restriction to SAVs with experimental annotations confirmed all results, although the resulting subsets were too small to establish statistical significance for any result. Thirdly, the fraction of SAVs predicted at binding interfaces differed significantly between tissues, e.g. urinary bladder tissue was found abundant in SAVs predicted at protein-binding interfaces, and reproductive tissues (ovary, testis, vagina, seminal vesicle and endometrium) in SAVs predicted at DNA-binding interfaces. CONCLUSIONS: Overall, the results suggested that residues at protein-, DNA-, and RNA-binding interfaces contributed toward predicting that common SAVs more likely affect molecular function than rare SAVs.

Trifluoromethylated carboline compounds targeting DNA: Synthesis, binding and anti-proliferative effects on human cancer cell lines.

Three sets of carboline derived compounds were prepared by Pictet-Spengler cyclization. These tetrahydro ß- and γ-carbolines have CF3 group with an additional amino alkyl chains (α- or δ-position) and guanidine alkyl chains (α-position), of varying length. Structure-activity relationship of these molecules with calf thymus DNA was emphasized by fluorescence, ITC, FTIR and viscosity. Binding with DNA resulted in dramatic enhancement and quenching in the fluorescence emission. Gamma-carboline analogs showed maximum DNA binding followed by beta-carboline compounds with amino alkyl chain and least with guanidine alkyl chain compounds. It decreased with increasing chain length. The bindings were entropically driven being more with guanidine alkyl chain analogs. Site preference and mode of binding with partial intercalation and external binding was supported by FTIR and viscosity. Cytotoxic potencies of the compounds were tested on seven different cancer cell lines. The smallest alkyl chain analog attached to gamma position, Comp3, showed maximum cytotoxicity with GI50 6.2 µM, against HCT-116 causing apoptosis, followed by the guanidine alkyl chain compounds, but amino alkyl chain compounds to beta position showed poor cytotoxicity. These results may be of prospective use in a framework to design novel carboline derivatives as antitumor drugs for improved therapeutic applications in future.

Evaluation of Drug Efficacy of GLP-1 Receptor Agonists and DPP-4 Inhibitors Based on Target Molecular Binding Occupancy.

Glucagon-like peptide-1 (GLP-1) receptor agonists (liraglutide, exenatide, lixisenatide) have recently been used as anti-diabetes drugs. We examined relationships of the binding occupancy of GLP-1 receptors (Φ) and their clinical efficacy after administration of GLP-1 receptor agonists. Next, by focusing on changes of GLP-1 concentration after administration of dipeptidyl peptidase-4 (DPP-4) inhibitors (vildagliptin, alogliptin, sitagliptin, linagliptin), we analyzed the relationship between Φ and clinical efficacy. Furthermore, using Φ as a common parameter, we compared the clinical efficacy elicited by GLP-1 receptor agonists and DPP-4 inhibitors using a theoretical analysis method. The present results showed that GLP-1 receptor agonists produced their clinical effect at a relatively low level of Φ (1.1-10.7%) at a usual dose. Furthermore, it was suggested that the drugs might achieve their full effect at an extraordinarily low level of Φ. It was also revealed that the Φ value of DPP-4 inhibitors (0.83-1.3%) was at the lower end or lower than that of GLP-1 receptor agonists at a usual dose. Accordingly, the predicted value for hemoglobin A1c (HbA1c) reduction after administration of the GLP-1 receptor agonists was higher than that of DPP-4 inhibitors. We clarified the differences between the therapeutic effects associated with GLP-1 receptor agonists and DPP-4 inhibitors theoretically. Together, the present findings provide a useful methodology for proper usage of GLP-1 receptor agonists and DPP-4 inhibitors.

Molecular Binding Contributes to Concentration Dependent Acrolein Deposition in Rat Upper Airways: CFD and Molecular Dynamics Analyses.

Existing in vivo experiments show significantly decreased acrolein uptake in rats with increasing inhaled acrolein concentrations. Considering that high-polarity chemicals are prone to bond with each other, it is hypothesized that molecular binding between acrolein and water will contribute to the experimentally observed deposition decrease by decreasing the effective diffusivity. The objective of this study is to quantify the probability of molecular binding for acrolein, as well as its effects on acrolein deposition, using multiscale simulations. An image-based rat airway geometry was used to predict the transport and deposition of acrolein using the chemical species model. The low Reynolds number turbulence model was used to simulate the airflows. Molecular dynamic (MD) simulations were used to study the molecular binding of acrolein in different media and at different acrolein concentrations. MD results show that significant molecular binding can happen between acrolein and water molecules in human and rat airways. With 72 acrolein embedded in 800 water molecules, about 48% of acrolein compounds contain one hydrogen bond and 10% contain two hydrogen bonds, which agreed favorably with previous MD results. The percentage of hydrogen-bonded acrolein compounds is higher at higher acrolein concentrations or in a medium with higher polarity. Computational dosimetry results show that the size increase caused by the molecular binding reduces the effective diffusivity of acrolein and lowers the chemical deposition onto the airway surfaces. This result is consistent with the experimentally observed deposition decrease at higher concentrations. However, this size increase can only explain part of the concentration-dependent variation of the acrolein uptake and acts as a concurrent mechanism with the uptake-limiting tissue ration rate. Intermolecular interactions and associated variation in diffusivity should be considered in future dosimetry modeling of high-polarity chemicals such as acrolein.

Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation.

We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein-protein or protein-ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks.

Supramolecular interaction of fullerenes with a curved π-surface of a monomeric quadruply ring-fused porphyrin.

Molecular binding of fullerenes, C60 and C70, with the Zn(II) complex of a monomeric ring-fused porphyrin derivative (2-py) as a host molecule, which has a concave π-conjugated surface, has been confirmed spectroscopically. The structures of associated complexes composed of fullerenes and 2-py were explicitly established by X-ray diffraction analysis. The fullerenes in the 2:1 complexes, which consist of two 2-py molecules and one fullerene molecule, are fully covered by the concave surfaces of the two 2-py molecules in the crystal structure. In contrast, in the crystal structure of the 1:1 complex consisting of one 2-py molecule and one C60 molecule, the C60 molecule formed a π-π stacked pair with a C60 molecule in the neighboring complex using a partial surface, which was uncovered by the 2-py molecule. Additionally, the molecular size of fullerene adopted significantly affects the (1)H NMR spectral changes and the redox properties of 2-py upon the molecular binding.

Co-exposure of decabromodiphenyl ethane and cadmium increases toxicity to earthworms: Enrichment, oxidative stress, damage and molecular binding mechanisms.

The increase of electronic waste worldwide has resulted in the exacerbation of combined decabromodiphenyl ethane (DBDPE) and cadmium (Cd) pollution in soil, posing a serious threat to the safety of soil organisms. However, whether combined exposure increases toxicity remains unclear. Therefore, this study primarily investigated the toxic effects of DBDPE and Cd on earthworms at the individual, tissue, and cellular levels under single and combined exposure. The results showed that the combined exposure significantly increased the enrichment of Cd in earthworms by 50.32-90.42 %. The toxicity to earthworms increased with co-exposure, primarily resulting in enhanced oxidative stress, inhibition of growth and reproduction, intensified intestinal and epidermal damage, and amplified coelomocyte apoptosis. PLS-PM analysis revealed a significant and direct relationship between the accumulation of target pollutants in earthworms and oxidative stress, damage, as well as growth and reproduction of earthworms. Furthermore, IBR analysis indicated that SOD and POD were sensitive biomarkers in earthworms. Molecular docking elucidated that DBDPE and Cd induced oxidative stress responses in earthworms through the alteration of the conformation of the two enzymes. This study enhances understanding of the mechanisms behind the toxicity of combined pollution and provides important insights for assessing e-waste contaminated soils.

The molecular binding sequence transformation of soil organic matter and biochar dissolved black carbon antagonizes the transport of 2,4,6-trichlorophenol.

Dissolved organic matter (DOM) and dissolved black carbon (DBC) are significant environmental factors that influence the transport of organic pollutants. However, the mechanisms by which their molecular diversity affects pollutant transport remain unclear. This study elucidates the molecular binding sequence and adsorption sites through which DOM/DBC compounds antagonize the transport of 2,4,6-trichlorophenol (TCP) using column experiments and modelling. DBC exhibits a high TCP adsorption rate (kn = 5.32 × 10-22 mol1-n∙Ln-1∙min-1) and conditional stability constant (logK = 5.19-5.74), indicating a strong binding affinity and antagonistic effect on TCP. This is attributed to the high relative content of lipid/protein compounds in DBC (25.65 % and 30.28 %, respectively). Moreover, the small molecule lipid compounds showed stronger TCP adsorption energy (Ead = -0.0071 eV/-0.0093 eV) in DOM/DBC, combined with two-dimensional correlation spectroscopy model found that DOM/DBC antagonized TCP transport in the environment through binding sequences that transformed from lipid/protein small molecule compounds to lignin/tannin compounds. This study used a multifaceted approach to comprehensively assess the impact of DOM/DBC on TCP transport. It reveals that the molecular diversity of DOM/DBC is a critical factor affecting pollutant transport, providing important insights into the environmental trend and ecological effects of pollutants.

Two-Dimensional Layered Nanomaterials Steering Self-Assembly of Dodecapeptides with Three Building Blocks.

Self-assembly of peptides on layered nanomaterials such as graphite and MoS2 in the formation of long-range ordered two-dimensional nanocrystal patterns leading to its potential applications for biosensing and bioelectronics has attracted significant interest in nanoscience and nanotechnology. However, controlling the self-assembly of peptides on nanomaterials is still challenging due to the unclear role of nanomaterials in steering self-assembly. Here, we used the in-situ AFM technique to capture different changes of peptide coverage as well as lengthening and widening rates depending on peptide concentrations, show the distinct boundary dynamics of two stabilized peptide domains, and resolve the molecular resolution structural differences and specific orientation of peptide on both nanomaterials. Moreover, ex-situ results showed that the nanomaterial layers tuned the opposite changes of nanowire heights and densities and displayed the different water-resistance stabilities on both nanomaterials. This work provides a basis for understanding nanomaterials steering peptide self-assembly and using hybrid bionanomaterials as a scaffold, enabling for potential biosensing and bioelectronics applications.

Molecular modelling, docking and network analysis of phytochemicals from Haritaki churna: role of protein cross-talks for their action.

Phytochemicals are bioactive agents present in medicinal plants with therapeutic values. Phytochemicals isolated from plants target multiple cellular processes. In the current work, we have used fractionation techniques to identify 13 bioactive polyphenols in ayurvedic medicine Haritaki Churna. Employing the advanced spectroscopic and fractionation, structure of bioactive polyphenols was determined. Blasting the phytochemical structure allow us to identify a total of 469 protein targets from Drug bank and Binding DB. Phytochemicals with their protein targets from Drug bank was used to create a phytochemical-protein network comprising of 394 nodes and 1023 edges. It highlights the extensive cross-talk between protein target corresponding to different phytochemicals. Analysis of protein targets from Binding data bank gives a network comprised of 143 nodes and 275 edges. Taking the data together from Drug bank and binding data, seven most prominent drug targets (HSP90AA1, c-Src kinase, EGFR, Akt1, EGFR, AR, and ESR-α) were found to be target of the phytochemicals. Molecular modelling and docking experiment indicate that phytochemicals are fitting nicely into active site of the target proteins. The binding energy of the phytochemicals were better than the inhibitors of these protein targets. The strength and stability of the protein ligand complexes were further confirmed using molecular dynamic simulation studies. Further, the ADMET profiles of phytochemicals extracted from HCAE suggests that they can be potential drug targets. The phytochemical cross-talk was further proven by choosing c-Src as a model. HCAE down regulated c-Src and its downstream protein targets such as Akt1, cyclin D1 and vimentin. Hence, network analysis followed by molecular docking, molecular dynamics simulation and in-vitro studies clearly highlight the role of protein network and subsequent selection of drug candidate based on network pharmacology.Communicated by Ramaswamy H. Sarma.

Binding free-energy landscapes of small molecule binder and non-binder to FMN riboswitch: All-atom molecular dynamics.

A small and flexible molecule, ribocil A (non-binder) or B (binder), binds to the deep pocket of the aptamer domain of the FMN riboswitch, which is an RNA molecule. This binding was studied by mD-VcMD, which is a generalized-ensemble simulation method. Ribocil A and B are structurally similar because they are optical isomers to each other. In the initial conformation of simulation, the ligands and the aptamer were completely dissociated in explicit solvent. The aptamer-ribocil B binding was stronger than the aptamer-ribocil A binding, which agrees with experiments. The computed free-energy landscape for the aptamer-ribocil B binding was funnel-like, whereas that for the aptamer-ribocil A binding was rugged. When passing through the gate (named "front gate") of the binding pocket, each ligand interacted with bases of the riboswitch by non-native π-π stackings, and the stackings restrained the ligand's orientation to be advantageous to reach the binding site smoothly. When the ligands reached the binding site in the pocket, the non-native stackings were replaced by the native stackings. The ligand's orientation restriction is discussed referring to a selection mechanism reported in an earlier work on a drug-GPCR interaction. The present simulation showed another pathway leading the ligands to the binding site. The gate ("rear gate") for this pathway was located completely opposite to the front gate on the aptamer's surface. However, the approach from the rear gate required overcoming a free-energy barrier regarding ligand's rotation before reaching the binding site.

Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles.

Prediction of ligand-receptor complex structure is important in both the basic science and the industry such as drug discovery. We report various computation molecular docking methods: fundamental in silico (virtual) screening, ensemble docking, enhanced sampling (generalized ensemble) methods, and other methods to improve the accuracy of the complex structure. We explain not only the merits of these methods but also their limits of application and discuss some interaction terms which are not considered in the in silico methods. In silico screening and ensemble docking are useful when one focuses on obtaining the native complex structure (the most thermodynamically stable complex). Generalized ensemble method provides a free-energy landscape, which shows the distribution of the most stable complex structure and semi-stable ones in a conformational space. Also, barriers separating those stable structures are identified. A researcher should select one of the methods according to the research aim and depending on complexity of the molecular system to be studied.