Analysis of the structure and dynamics of human serum albumin

A computational approach to designing a peptide-based ligand for the purification of human serum albumin (HSA) was undertaken using molecular docking and molecular dynamics (MD) simulation. A three-step procedure was performed to design a specific ligand for HSA. Based on the candidate pocket structure of HSA (warfarin binding site), a peptide library was built. These peptides were then docked into the pocket of HSA using the GOLD program. The GOLDscore values were used to determine the affinity of peptides for HSA. Consequently, the dipeptide Trp–Trp, which shows a high GOLDscore value, was selected and linked to a spacer arm of Lys[CO(CH₂)₅NH] on the surface of ECH-lysine sepharose 4 gel. For further evaluation, the Autodock Vina program was used to dock the linked compound into the pocket of HSA. The docking simulation was performed to obtain a first guess of the binding structure of the spacer–Trp–Trp–HSA complex and subsequently analyzed by MD simulations to assess the reliability of the docking results. These MD simulations indicated that the ligand–HSA complex remains stable, and water molecules can bridge between the ligand and the protein by hydrogen bonds. Finally, absorption spectroscopic studies were performed to illustrate the appropriateness of the binding affinity of the designed ligand toward HSA. These studies demonstrate that the designed dipeptide can bind preferentially to the warfarin binding site. Graphical Abstract

Three-step computational approach to the design of a dipeptide ligand for human serum albumin purification exploiting structure-based docking and molecular dynamics simulation     

Receptor–ligand molecular docking

Docking methodology aims to predict the experimental binding modes and affinities of small molecules within the binding site of particular receptor targets and is currently used as a standard computational tool in drug design for lead compound optimisation and in virtual screening studies to find novel biologically active molecules. The basic tools of a docking methodology include a search algorithm and an energy scoring function for generating and evaluating ligand poses. In this review, we present the search algorithms and scoring functions most commonly used in current molecular docking methods that focus on protein–ligand applications. We summarise the main topics and recent computational and methodological advances in protein–ligand docking. Protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction are important and interconnected challenges to be overcome by further methodological developments in the docking field.     

Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites

MOTIVATION: Identifying the location of ligand binding sites on a protein is of fundamental importance for a range of applications including molecular docking, de novo drug design and structural identification and comparison of functional sites. Here, we describe a new method of ligand binding site prediction called Q-SiteFinder. It uses the interaction energy between the protein and a simple van der Waals probe to locate energetically favourable binding sites. Energetically favourable probe sites are clustered according to their spatial proximity and clusters are then ranked according to the sum of interaction energies for sites within each cluster. RESULTS: There is at least one successful prediction in the top three predicted sites in 90% of proteins tested when using Q-SiteFinder. This success rate is higher than that of a commonly used pocket detection algorithm (Pocket-Finder) which uses geometric criteria. Additionally, Q-SiteFinder is twice as effective as Pocket-Finder in generating predicted sites that map accurately onto ligand coordinates. It also generates predicted sites with the lowest average volumes of the methods examined in this study. Unlike pocket detection, the volumes of the predicted sites appear to show relatively low dependence on protein volume and are similar in volume to the ligands they contain. Restricting the size of the pocket is important for reducing the search space required for docking and de novo drug design or site comparison. The method can be applied in structural genomics studies where protein binding sites remain uncharacterized since the 86% success rate for unbound proteins appears to be only slightly lower than that of ligand-bound proteins. AVAILABILITY: Both Q-SiteFinder and Pocket-Finder have been made available online at http://www.bioinformatics.leeds.ac.uk/qsitefinder and http://www.bioinformatics.leeds.ac.uk/pocketfinder     

Efficient docking of peptides to proteins without prior knowledge of the binding site

Reliability in docking of ligand molecules to proteins or other targets is an important challenge for molecular modeling. Applications of the docking technique include not only prediction of the binding mode of novel drugs, but also other problems like the study of protein-protein interactions. Here we present a study on the reliability of the results obtained with the popular AutoDock program. We have performed systematical studies to test the ability of AutoDock to reproduce eight different protein/ligand complexes for which the structure was known, without prior knowledge of the binding site. More specifically, we look at factors influencing the accuracy of the final structure, such as the number of torsional degrees of freedom in the ligand. We conclude that the Autodock program package is able to select the correct complexes based on the energy without prior knowledge of the binding site. We named this application blind docking, as the docking algorithm is not able to "see" the binding site but can still find it. The success of blind docking represents an important finding in the era of structural genomics.     

Targeting the ubiquitin-conjugating enzyme E2D4 for cancer drug discovery–a structure-based approach

Cancer progression is a global burden. The incidence and mortality now reach 30 million deaths per year. Several pathways of cancer are under investigation for the discovery of effective therapeutics. The present study highlights the structural details of the ubiquitin protein ‘Ubiquitin-conjugating enzyme E2D4’ (UBE2D4) for the novel lead structure identification in cancer drug discovery process. The evaluation of 3D structure of UBE2D4 was carried out using homology modelling techniques. The optimized structure was validated by standard computational protocols. The active site region of the UBE2D4 was identified using computational tools like CASTp, Q-site Finder and SiteMap. The hydrophobic pocket which is responsible for binding with its natural receptor ubiquitin ligase CHIP (C-terminal of Hsp 70 interacting protein) was identified through protein-protein docking study. Corroborating the results obtained from active site prediction tools and protein-protein docking study, the domain of UBE2D4 which is responsible for cancer cell progression is sorted out for further docking study. Virtual screening with large structural database like CB_Div Set and Asinex BioDesign small molecular structural database was carried out. The obtained new ligand molecules that have shown affinity towards UBE2D4 were considered for ADME prediction studies. The identified new ligand molecules with acceptable parameters of docking, ADME are considered as potent UBE2D4 enzyme inhibitors for cancer therapy.     

Molecular docking of balanol to dynamics snapshots of protein kinase A

Even if the structure of a receptor has been determined experimentally, it may not be a conformation to which a ligand would bind when induced fit effects are significant. Molecular docking using such a receptor structure may thus fail to recognize a ligand to which the receptor can bind with reasonable affinity. Here, we examine one way to alleviate this problem by using an ensemble of receptor conformations generated from a molecular dynamics simulation for molecular docking. Two molecular dynamics simulations were conducted to generate snapshots for protein kinase A: one with the ligand bound, the other without. The ligand, balanol, was then docked to conformations of the receptors presented by these trajectories. The Lamarckian genetic algorithm in Autodock [Goodsell et al. J Mol Recognit 1996;9(1):1-5; Morris et al. J Comput Chem 1998;19(14):1639-1662] was used in the docking. Three ligand models were used: rigid, flexible, and flexible with torsional potentials. When the snapshots were taken from the molecular dynamics simulation of the protein-ligand complex, the correct docking structure could be recovered easily by the docking algorithm in all cases. This was an easier case for challenging the docking algorithm because, by using the structure of the protein in a protein-ligand complex, one essentially assumed that the protein already had a pocket to which the ligand can fit well. However, when the snapshots were taken from the ligand-free protein simulation, which is more useful for a practical application when the structure of the protein-ligand complex is not known, several clusters of structures were found. Of the 10 docking runs for each snapshot, at least one structure was close to the correctly docked structure when the flexible-ligand models were used. We found that a useful way to identify the correctly docked structure was to locate the structure that appeared most frequently as the lowest energy structure in the docking experiments to different snapshots.     

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

Background

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds.

Methodology

In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy.

Conclusions

The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.     

Incorporating replacement free energy of binding‐site waters in molecular docking

Binding‐site water molecules play a crucial role in protein‐ligand recognition, either being displaced upon ligand binding or forming water bridges to stabilize the complex. However, rigorously treating explicit binding‐site waters is challenging in molecular docking, which requires to fully sample ensembles of waters and to consider the free energy cost of replacing waters. Here, we describe a method to incorporate structural and energetic properties of binding‐site waters into molecular docking. We first developed a solvent property analysis (SPA) program to compute the replacement free energies of binding‐site water molecules by post‐processing molecular dynamics trajectories obtained from ligand‐free protein structure simulation in explicit water. Next, we implemented a distance‐dependent scoring term into DOCK scoring function to take account of the water replacement free energy cost upon ligand binding. We assessed this approach in protein targets containing important binding‐site waters, and we demonstrated that our approach is reliable in reproducing the crystal binding geometries of protein‐ligand‐water complexes, as well as moderately improving the ligand docking enrichment performance. In addition, SPA program (free available to academic users upon request) may be applied in identifying hot‐spot binding‐site residues and structure‐based lead optimization. Proteins 2014; 82:1765–1776. © 2014 Wiley Periodicals, Inc.     

Exploration of a binding mode of indole amide analogues as potent histone deacetylase inhibitors and 3D-QSAR analyses

Docking simulations and three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses were conducted on a series of indole amide analogues as potent histone deacetylase inhibitors. The studies include comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Selected ligands were docked into the active site of human HDAC1. Based on the docking results, a novel binding mode of indole amide analogues in the human HDAC1 catalytic core is presented, and enzyme/inhibitor interactions are discussed. The indole amide group is located in the open pocket, and anchored to the protein through a pair of hydrogen bonds with Asp99 O-atom and amide NH group on ligand. Based on the binding mode, predictive 3D-QSAR models were established, which had conventional r2 and cross-validated coefficient values (r(cv)2) up to 0.982 and 0.601 for CoMFA and 0.954 and 0.598 for CoMSIA, respectively. A comparison of the 3D-QSAR field contributions with the structural features of the binding site showed good correlation between the two analyses. The results of 3D-QSAR and docking studies validate each other and provided insight into the structural requirements for activity of this class of molecules as HDAC inhibitors. The CoMFA and CoMSIA PLS contour maps and MOLCAD-generated active site electrostatic, lipophilicity, and hydrogen-bonding potential surface maps, as well as the docking studies, provided good insights into inhibitor-HDAC interactions at the molecular level. Based on these results, novel molecules with improved activity can be designed.     

Homology modeling and atomic level binding study of Leishmania MAPK with inhibitors

The current therapy for leishmaniasis is not sufficient and it has two severe drawbacks, host-toxicity and drug resistance. The substantial knowledge of parasite biology is not yet translating into novel drugs for leishmaniasis. Based on this observation, a 3D structural model of Leishmania mitogen-activated protein kinase (MAPK) homologue has been developed, for the first time, by homology modeling and molecular dynamics simulation techniques. The model provided clear insight in its structure features, i.e. ATP binding pocket, phosphorylation lip, and common docking site. Sequence-structure homology recognition identified Leishmania CRK3 (LCRK3) as a distant member of the MAPK superfamily. Multiple sequence alignment and 3D structure model provided the putative ATP binding pocket of Leishmania with respect to human ERK2 and LCRK3. This analysis was helpful in identifying the binding sites and molecular function of the Leishmania specific MAPK homologue. Molecular docking study was performed on this 3D structural model, using different classes of competitive ATP inhibitors of LCRK3, to check whether they exhibit affinity and could be identified as Leishmania MAPK specific inhibitors. It is well known that MAP kinases are extracellular signal regulated kinases ERK1 and ERK2, which are components of the Ras-MAPK signal transduction pathway which is complexed with HDAC4 protein, and their inhibition is of significant therapeutic interest in cancer biology. In order to understand the mechanism of action, docking of indirubin class of molecules to the active site of histone deacetylase 4 (HDAC4) protein is performed, and the binding affinity of the protein-ligand interaction was computed. The new structural insights obtained from this study are all consistent with the available experimental data, suggesting that the homology model of the Leishmania MAPK and its ligand interaction modes are reasonable. Further the comparative molecular electrostatic potential and cavity depth analysis of Leishmania MAPK and human ERK2 suggested several important differences in its ATP binding pocket. Such differences could be exploited in the future for designing Leishmania specific MAPK inhibitors.     

Exploring the binding site structure of the PPAR gamma ligand-binding domain by computational solvent mapping

Solvent mapping moves molecular probes, small organic molecules containing various functional groups, around the protein surface, finds favorable positions, clusters the conformations, and ranks the clusters based on the average free energy. Using at least six different solvents as probes, the probes cluster in major pockets of the functional site, providing detailed and reliable information on the amino acid residues that are important for ligand binding. Solvent mapping was applied to 12 structures of the peroxisome proliferator activated receptor gamma (PPARgamma) ligand-binding domain (LBD), including 2 structures without a ligand, 2 structures with a partial agonist, and 8 structures with a PPAR agonist bound. The analysis revealed 10 binding "hot spots", 4 in the ligand-binding pocket, 2 in the coactivator-binding region, 1 in the dimerization domain, 2 around the ligand entrance site, and 1 minor site without a known function. Mapping is a major source of information on the role and cooperativity of these sites. It shows that large portions of the ligand-binding site are already formed in the PPARgamma apostructure, but an important pocket near the AF-2 transactivation domain becomes accessible only in structures that are cocrystallized with strong agonists. Conformational changes were seen in several other sites, including one involved in the stabilization of the LBD and two others at the region of the coactivator binding. The number of probe clusters retained by these sites depends on the properties of the bound agonist, providing information on the origin of correlations between ligand and coactivator binding.     

Binding Pocket Optimization by Computational Protein Design

Engineering specific interactions between proteins and small molecules is extremely useful for biological studies, as these interactions are essential for molecular recognition. Furthermore, many biotechnological applications are made possible by such an engineering approach, ranging from biosensors to the design of custom enzyme catalysts. Here, we present a novel method for the computational design of protein-small ligand binding named PocketOptimizer. The program can be used to modify protein binding pocket residues to improve or establish binding of a small molecule. It is a modular pipeline based on a number of customizable molecular modeling tools to predict mutations that alter the affinity of a target protein to its ligand. At its heart it uses a receptor-ligand scoring function to estimate the binding free energy between protein and ligand. We compiled a benchmark set that we used to systematically assess the performance of our method. It consists of proteins for which mutational variants with different binding affinities for their ligands and experimentally determined structures exist. Within this test set PocketOptimizer correctly predicts the mutant with the higher affinity in about 69% of the cases. A detailed analysis of the results reveals that the strengths of PocketOptimizer lie in the correct introduction of stabilizing hydrogen bonds to the ligand, as well as in the improved geometric complemetarity between ligand and binding pocket. Apart from the novel method for binding pocket design we also introduce a much needed benchmark data set for the comparison of affinities of mutant binding pockets, and that we use to asses programs for in silico design of ligand binding.     

In silico molecular docking analysis for repurposing approved antiviral drugs against SARS-CoV-2 main protease

Developing a safe and effective antiviral treatment takes a decade, however, when it comes to the coronavirus disease (COVID-19), time is a sensitive matter to slow the spread of the pandemic. Screening approved antiviral drugs against COVID-19 would speed the process of finding therapeutic treatment. The current study examines commercially approved drugs to repurpose them against COVID-19 virus main protease using structure-based in-silico screening. The main protease of the coronavirus is essential in the viral replication and is involved in polyprotein cleavage and immune regulation, making it an effective target when developing the treatment. A Number of approved antiviral drugs were tested against COVID-19 virus using molecular docking analysis by calculating the free natural affinity of the binding ligand to the active site pocket and the catalytic residues without forcing the docking of the ligand to active site. COVID-19 virus protease solved structure (PDB ID: 6LU7) is targeted by repurposed drugs. The molecular docking analysis results have shown that the binding of Remdesivir and Mycophenolic acid acyl glucuronide with the protein drug target has optimal binding features supporting that Remdesivir and Mycophenolic acid acyl glucuronide can be used as potential anti-viral treatment against COVID-19 disease.     

Determining the binding capability of the mouse major urinary proteins using 2-naphthol as a fluorescent probe

The mouse major urinary proteins (MUPs) are an ensemble of isoforms secreted by adult male mice and involved in sexual olfactory communication. MUPs belong to the lipocalin superfamily, whose conserved structure is a beta-barrel made of eight antiparallel beta-strands forming a hydrophobic pocket that accommodates small organic molecules. A detailed knowledge of the molecular mechanism associated to the binding of those molecules can guide protein engineering to devise mutated proteins where the ligand specificity, binding affinity, and release rate can be modulated. Proteins with such peculiar properties may have interesting biotechnological applications for pest control, as well as in food and cosmetic industries. In this work, we demonstrate that the fluorescent molecule 2-naphthol binds to the natural ligand's binding site of MUPs with high affinity. In addition, we show that 2-naphthol binds to MUPs in its protonated form, that its fluorescence is blue-shifted, and the quantum yield is increased, thus confirming the high hydrophobicity of the protein pocket and the absence of proton acceptors inside the binding site. At large the results presented, besides demonstrating that the use of 2-naphthol provides a convenient and quick method for testing MUPs binding activity and to ascertain the quality of the protein preparation, suggest that MUPs can represent an interesting system for studying the photophysical characteristics of fluorescent molecules in a highly hydrophobic environment.     

A mining minima approach to exploring the docking pathways of p-nitrocatechol sulfate to YopH

Using the docking of p-nitrocatechol sulfate to Yersinia protein tyrosine phosphatase YopH as an example, we showed that an approach based on mining minima followed by cluster and similarity analysis could generate useful insights into docking pathways. Our simulation treated both the ligand and the protein as flexible molecules so that the coupling between their motion could be properly accounted for. Our simulation identified three docking poses; the one with the lowest energy agreed well with experimental structure. The model also predicted the side-chain conformations of the amino acids lying in the binding pocket correctly with the exception of three residues that appeared to be stabilized by two structural water molecules in the crystal structure. The implicit solvent model employed in the simulation could not capture such effects well. We also found four major pathways leading to these docking poses after the ligand entered the mouth of the binding pocket. In addition, the sulfate group of p-nitrocatechol sulfate was found to be important both in binding the ligand to the pocket and in guiding the ligand to dock into the pocket. The coupling of the motion between the protein and the ligand also played an important role in facilitating ligand loading and unloading.     

HIV-1跨膜蛋白gp41与N-取代吡咯衍生物的结合模式研究

采用分子对接,分子动力学(MD)模拟和分子力学/泊松-波尔兹曼溶剂可有面积方法与分子力学/广义伯恩溶剂可及面积方法(MM-PBSA/MM-GBSA),预测两种N-取代吡咯衍生物与HIV-1 跨膜蛋白gp41疏水口袋的结合模式与作用机理．分子对接采用多种受体构象,并从结果中选取几种可能的结合模式进行MD 模拟,然后通过MM-PBSA计算结合能的方法识别最优的结合模式. MM-PBSA计算结果表明,范德华相互作用是结合的主要驱动力,而极性相互作用决定了配体在结合过程中的取向．进一步的结合能分解显示,配体的羧基与gp41残基Arg579的静电相互作用对结合有重要贡献．上述工作为进一步优化N-取代吡咯衍生物类的HIV-1融合抑制剂建立了良好的理论基础．     

Protein conformational relaxation and ligand migration in myoglobin: a nanosecond to millisecond molecular movie from time-resolved Laue X-ray diffraction.

A time-resolved Laue X-ray diffraction technique has been used to explore protein relaxation and ligand migration at room temperature following photolysis of a single crystal of carbon monoxymyoglobin. The CO ligand is photodissociated by a 7.5 ns laser pulse, and the subsequent structural changes are probed by 150 ps or 1 micros X-ray pulses at 14 laser/X-ray delay times, ranging from 1 ns to 1.9 ms. Very fast heme and protein relaxation involving the E and F helices is evident from the data at a 1 ns time delay. The photodissociated CO molecules are detected at two locations: at a distal pocket docking site and at the Xe 1 binding site in the proximal pocket. The population by CO of the primary, distal site peaks at a 1 ns time delay and decays to half the peak value in 70 ns. The secondary, proximal docking site reaches its highest occupancy of 20% at approximately 100 ns and has a half-life of approximately 10 micros. At approximately 100 ns, all CO molecules are accounted for within the protein: in one of these two docking sites or bound to the heme. Thereafter, the CO molecules migrate to the solvent from which they rebind to deoxymyoglobin in a bimolecular process with a second-order rate coefficient of 4.5 x 10(5) M(-1) s(-1). Our results also demonstrate that structural changes as small as 0.2 A and populations of CO docking sites of 10% can be detected by time-resolved X-ray diffraction.     

Non-additivity of Functional Group Contributions in Protein-Ligand Binding: A Comprehensive Study by Crystallography and Isothermal Titration Calorimetry

Additivity of functional group contributions to protein-ligand binding is a very popular concept in medicinal chemistry as the basis of rational design and optimized lead structures. Most of the currently applied scoring functions for docking build on such additivity models. Even though the limitation of this concept is well known, case studies examining in detail why additivity fails at the molecular level are still very scarce. The present study shows, by use of crystal structure analysis and isothermal titration calorimetry for a congeneric series of thrombin inhibitors, that extensive cooperative effects between hydrophobic contacts and hydrogen bond formation are intimately coupled via dynamic properties of the formed complexes. The formation of optimal lipophilic contacts with the surface of the thrombin S3 pocket and the full desolvation of this pocket can conflict with the formation of an optimal hydrogen bond between ligand and protein. The mutual contributions of the competing interactions depend on the size of the ligand hydrophobic substituent and influence the residual mobility of ligand portions at the binding site. Analysis of the individual crystal structures and factorizing the free energy into enthalpy and entropy demonstrates that binding affinity of the ligands results from a mixture of enthalpic contributions from hydrogen bonding and hydrophobic contacts, and entropic considerations involving an increasing loss of residual mobility of the bound ligands. This complex picture of mutually competing and partially compensating enthalpic and entropic effects determines the non-additivity of free energy contributions to ligand binding at the molecular level.     

Binding hotspots on K‐ras: Consensus ligand binding sites and other reactive regions from probe‐based molecular dynamics analysis

We have used probe‐based molecular dynamics (pMD) simulations to search for interaction hotspots on the surface of the therapeutically highly relevant oncogenic K‐Ras G12D. Combining the probe‐based query with an ensemble‐based pocket identification scheme and an analysis of existing Ras‐ligand complexes, we show that (i) pMD is a robust and cost‐effective strategy for binding site identification, (ii) all four of the previously reported ligand binding sites are suitable for structure‐based ligand design, and (iii) in some cases probe binding and expanded sampling of configurational space enable pocket expansion and increase the likelihood of site identification. Furthermore, by comparing the distribution of hotspots in nonpocket‐like regions with known protein‐ and membrane‐interacting interfaces, we propose that pMD has the potential to predict surface patches responsible for protein‐biomolecule interactions. These observations have important implications for future drug design efforts and will facilitate the search for potential interfaces responsible for the proposed transient oligomerization or interaction of Ras with other biomolecules in the cellular milieu. Proteins 2015; 83:898–909. © 2015 Wiley Periodicals, Inc.