MCDOCK: A Monte Carlo simulation approach to the molecular docking problem

Prediction of the binding mode of a ligand (a drug molecule) to its macromolecular receptor, or molecular docking, is an important problem in rational drug design. We have developed a new docking method in which a non-conventional Monte Carlo (MC) simulation technique is employed. A computer program, MCDOCK, was developed to carry out the molecular docking operation automatically. The current version of the MCDOCK program (version 1.0) allows for the full flexibility of ligands in the docking calculations. The scoring function used in MCDOCK is the sum of the interaction energy between the ligand and its receptor, and the conformational energy of the ligand. To validate the MCDOCK method, 19 small ligands, the binding modes of which had been determined experimentally using X-ray diffraction, were docked into their receptor binding sites. To produce statistically significant results, 20 MCDOCK runs were performed for each protein–ligand complex. It was found that a significant percentage of these MCDOCK runs converge to the experimentally observed binding mode. The root-mean-square (rms) of all non-hydrogen atoms of the ligand between the predicted and experimental binding modes ranges from 0.25 to 1.84 Å for these 19 cases. The computational time for each run on an SGI Indigo2/R10000 varies from less than 1 min to 15 min, depending upon the size and the flexibility of the ligands. Thus MCDOCK may be used to predict the precise binding mode of ligands in lead optimization and to discover novel lead compounds through structure-based database searching.     

A scalable parallel Monte Carlo method for free energy simulations of molecular systems

We present a method of parallelizing flat histogram Monte Carlo simulations, which give the free energy of a molecular system as an output. In the serial version, a constant probability distribution, as a function of any system parameter, is calculated by updating an external potential that is added to the system Hamiltonian. This external potential is related to the free energy. In the parallel implementation, the simulation is distributed on to different processors. With regular intervals the modifying potential is summed over all processors and distributed back to every processor, thus spreading the information of which parts of parameter space have been explored. This implementation is shown to decrease the execution time linearly with added number of processors.     

Drug efficiency indices for improvement of molecular docking scoring functions

A dataset of protein‐drug complexes with experimental binding energy and crystal structure were analyzed and the performance of different docking engines and scoring functions (as well as components of these) for predicting the free energy of binding and several ligand efficiency indices were compared. The aim was not to evaluate the best docking method, but to determine the effect of different efficiency indices on the experimental and predicted free energy. Some ligand efficiency indices, such as ΔG/W (Wiener index), ΔG/NoC (number of carbons), and ΔG/P (partition coefficient), improve the correlation between experimental and calculated values. This effect was shown to be valid across the different scoring functions and docking programs. It also removes the common bias of scoring functions in favor of larger ligands. For all scoring functions, the efficiency indices effectively normalize the free energy derived indices, to give values closer to experiment. Compound collection filtering can be done prior or after docking, using pharmacokinetic as well as pharmacodynamic profiles. Achieving these better correlations with experiment can improve the ability of docking scoring functions to predict active molecules in virtual screening. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010     

An efficient molecular docking using conformational space annealing

Molecular docking falls into the general category of global optimization problems because its main purpose is to find the most stable complex consisting of a receptor and its ligand. Conformational space annealing (CSA), a powerful global optimization method, is incorporated with the Tinker molecular modeling package to perform molecular docking simulations of six receptor-ligand complexes (3PTB, 1ULB, 2CPP, 1STP, 3CPA, and 1PPH) from the Protein Data Bank. In parallel, Monte Carlo with the minimization (MCM) method is also incorporated into the Tinker package for comparison. The energy function, consisting of electrostatic interactions, van der Waals interactions, and torsional energy terms, is calculated using the AMBER94 all-atom empirical force field. Rigid docking simulations for all six complexes and flexible docking simulations for three complexes (1STP, 3CPA, and 1PPH) are carried out using the CSA and the MCM methods. The simulation results show that the docking procedures using the CSA method generally find the most stable complexes as well as the native-like complexes more efficiently and accurately than those using the MCM, demonstrating that CSA is a promising search method for molecular docking problems.     

Computer simulations of ligand–protein binding with ensembles of protein conformations: A Monte Carlo study of HIV‐1 protease binding energy landscapes

We present the results of molecular docking simulations with HIV‐1 protease for the sb203386 and skf107457 inhibitors by Monte Carlo simulated annealing. A simplified piecewise linear energy function, the standard AMBER force field, and the AMBER force field with solvation and a soft‐core smoothing component are employed in simulations with a single‐protein conformation to determine the relationship between docking simulations with a simple energy function and more realistic force fields. The temperature‐dependent binding free energy profiles of the inhibitors interacting with a single protein conformation provide a detailed picture of relative thermodynamic stability and a distribution of ligand binding modes in agreement with experimental crystallographic data. Using the simplified piecewise linear energy function, we also performed Monte Carlo docking simulations with an ensemble of protein conformations employing preferential biased sampling of low‐energy protein conformations, and the results are analyzed in connection with the free energy profiles. ©1999 John Wiley & Sons, Inc. Int J Quant Chem 72: 73–84, 1999     

In Silico Study towards Repositioning of FDA-Approved Drug Candidates for Anticoronaviral Therapy: Molecular Docking,Molecular Dynamics and Binding Free Energy Calculations

The SARS-CoV-2 targets were evaluated for a set of FDA-approved drugs using a combination of drug repositioning and rigorous computational modeling methodologies such as molecular docking and molecular dynamics (MD) simulations followed by binding free energy calculations. Six FDA-approved drugs including, Ouabain, Digitoxin, Digoxin, Proscillaridin, Salinomycin and Niclosamide with promising anti-SARS-CoV-2 activity were screened in silico against four SARS-CoV-2 proteins—papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), SARS-CoV-2 main protease (Mpro), and adaptor-associated kinase 1 (AAK1)—in an attempt to define their promising targets. The applied computational techniques suggest that all the tested drugs exhibited excellent binding patterns with higher scores and stable complexes compared to the native protein cocrystallized inhibitors. Ouabain was suggested to act as a dual inhibitor for both PLpro and Mpro enzymes, while Digitoxin bonded perfectly to RdRp. In addition, Salinomycin targeted PLpro. Particularly, Niclosamide was found to target AAK1 with greater affinity compared to the reference drug. Our study provides comprehensive molecular-level insights for identifying or designing novel anti-COVID-19 drugs.     

Walking freely in the energy and temperature space by the modified replica exchange molecular dynamics method

Replica Exchange Molecular Dynamics (REMD) method is a powerful sampling tool in molecular simulations. Recently, we made a modification to the standard REMD method. It places some inactive replicas at different temperatures as well as the active replicas. The method completely decouples the number of the active replicas and the number of the temperature levels. In this article, we make a further modification to our previous method. It uses the inactive replicas in a different way. The inactive replicas first sample in their own knowledge‐based energy databases and then participate in the replica exchange operations in the REMD simulation. In fact, this method is a hybrid between the standard REMD method and the simulated tempering method. Using different active replicas, one can freely control the calculation quantity and the convergence speed of the simulation. To illustrate the performance of the method, we apply it to some small models. The distribution functions of the replicas in the energy space and temperature space show that the modified REMD method in this work can let the replicas walk freely in both of the two spaces. With the same number of the active replicas, the free energy surface in the simulation converges faster than the standard REMD. © 2016 Wiley Periodicals, Inc.     

Synthesis,characterization, DNA binding,cytotoxicity and molecular docking properties of three novel butterfly-like complexes with nitrogen-containing heterocyclic ligands

Three novel complexes, namely [Nd·L₁·HCOO·(H₂O)₄] ( 1 ), [Pr·L₁·HCOO·(H₂O)₄] ( 2 ) and [In·L₂·Cl·(H₂O)₂] ( 3 ) (L₁ = 1,1-bis(5-(pyrazin-2-yl)-1,2,4-triazol-3-yl)methane, L₂ = 1,1-bis(5-(pyrazin-2-yl)-1,2,4-triazol-3-yl)ketone), were synthesized and characterized. The molecular structures of 1 – 3 were confirmed using single-crystal X-ray diffraction. All three obtained complexes are zero-dimensional and connected to each other by hydrogen bonds. In 1 and 2 the metal is surrounded by nine donors and 3 has seven coordination sites. The interaction of 1 – 3 with calf thymus DNA (CT-DNA) was explored using UV absorption spectra and fluorescence spectra. The intrinsic binding constants of 1 – 3 with CT-DNA are about 1.9 × 10⁴, 1.4 × 10⁴ and 1.1 × 10⁴, respectively. Stern–Volmer quenching plots of 1 – 3 have slopes of 0.1508, 0.134 and 0.1205, respectively. The ability of these complexes to cleave pBR322 plasmid DNA was demonstrated using gel electrophoresis assay. Apoptosis studies of the three novel complexes showed a significant inhibitory effect on HeLa cells. Furthermore, MTT assays were used to evaluate the anticancer activity of the three complexes. The cytotoxicity study indicated that complex 1 possesses a higher inhibitory rate of HeLa cells than the other complexes. Especially, the efficacy of 1 was shown to be the highest for cisplatin at 24 h. A further molecular docking technique was introduced to understand the binding of the complexes toward the target DNA.     

Synthesis,structure elucidation,DNA binding and molecular docking studies of novel copper(II) complexes of two 1,3,4-thiadiazolethiosemicarbazone derivatives

Four novel Cu(II) chelates were synthesized by reacting hydrated CuCl₂ and Cu(CH₃COO)₂ with two derivatives of 1,3,4-thiadiazolethiosemicarbazone. The structures and geometries of the synthesized complexes were deduced applying the alternative analytical and spectral tools confirming the complexes to have the formulae [(LH)Cu(Cl)]•0.5H₂O, [(LH)Cu(OAc)(H₂O)₂]•0.5H₂O, [(LCl)Cu(Cl)(H₂O)₂]•H₂O and [(LCl)Cu(OAc)]; where LH and LCl are phenyl and p-chlorophenyl derivatives of 1,3,4-thiadiazolethiosemicarbazone ligands, respectively (deprotonated form). IR spectral data confirmed the coordination of the ligands to the copper center as monobasic tridentate in the thiol form. Thermal analysis, UV–Vis spectra and magnetic moment assured the geometry around the copper center to be square planar, trigonal bipyramid and octahedral which have been confirmed by the computational studies. The two ligand derivatives and their copper complexes were applied to evaluate their binding modes with SS-DNA via UV–Vis spectral titration and viscosity measurements. The DNA-binding constant (k_b) values of the investigated derivatives were calculated and compared with ethidium bromide in order to assess their mode of binding with DNA. Moreover, docking study of these complexes was carried out to recognize the drug–DNA interactions and to calculate their binding energies.     

Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking

In molecular docking, it is challenging to develop a scoring function that is accurate to conduct high-throughput screenings. Most scoring functions implemented in popular docking software packages were developed with many approximations for computational efficiency, which sacrifices the accuracy of prediction. With advanced technology and powerful computational hardware nowadays, it is feasible to use rigorous scoring functions, such as molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) in molecular docking studies. Here, we systematically investigated the performance of MM/PBSA and MM/GBSA to identify the correct binding conformations and predict the binding free energies for 98 protein-ligand complexes. Comparison studies showed that MM/GBSA (69.4%) outperformed MM/PBSA (45.5%) and many popular scoring functions to identify the correct binding conformations. Moreover, we found that molecular dynamics simulations are necessary for some systems to identify the correct binding conformations. Based on our results, we proposed the guideline for MM/GBSA to predict the binding conformations. We then tested the performance of MM/GBSA and MM/PBSA to reproduce the binding free energies of the 98 protein-ligand complexes. The best prediction of MM/GBSA model with internal dielectric constant 2.0, produced a Spearman's correlation coefficient of 0.66, which is better than MM/PBSA (0.49) and almost all scoring functions used in molecular docking. In summary, MM/GBSA performs well for both binding pose predictions and binding free-energy estimations and is efficient to re-score the top-hit poses produced by other less-accurate scoring functions.     

A novel approach to the calculation of the free energy due to molecular flexibility

The contribution of the molecular flexibility to the solvation excess free energy is expressed in terms of probabilities of reaching hard limits on intramolecular coordinates in a series of calculations successively relaxing those limits. Numerical tests on the harmonic oscillator are also presented and used to make suggestion about computational issues.     

Empirical entropic contributions in computational docking: evaluation in APS reductase complexes

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments.     

Critical evaluation of search algorithms for automated molecular docking and database screening

The DOCK program explores possible orientations of a molecule within a macromolecular active site by superimposing atoms onto precomputed site points. Here we compare a number of different search methods, including an exhaustive matching algorithm based on a single docking graph. We evaluate the performance of each method by screening a small database of molecules to a variety of macromolecular targets. By varying the amount of sampling, we can monitor the time convergence of scores and rankings. We not only show that the site point–directed search is tenfold faster than a random search, but that the single graph matching algorithm boosts the speed of database screening up to 60-fold. The new algorithm, in fact, outperforms the bipartite graph matching algorithm currently used in DOCK. The results indicate that a critical issue for rapid database screening is the extent to which a search method biases run time toward the highest-ranking molecules. The single docking graph matching algorithm will be incorporated into DOCK version 4.0. © 1997 John Wiley & Sons, Inc. J Comput Chem 18: 1175–1189     

Synthesis,characterization and biological activities of two novel orthopalladated complexes: Interactions with DNA and bovine serum albumin,antitumour activity and molecular docking studies

[Pd(L₁)(C,N)]CF₃SO₃ and [Pd(L₂)(C,N)]CF₃SO₃ (L₁ = 2,2′ ‐bipyridine, L₂ = 1,10‐phenanthroline and C,N = benzylamine) novel orthopalladated complexes have been synthesized and characterized using various techniques. The binding of the complexes with native calf thymus DNA (CT‐DNA) was monitored using UV–visible absorption spectrophotometry, fluorescence spectroscopy and thermal denaturation studies. Our results indicate that these complexes can strongly bind to CT‐DNA via partial intercalative mode. In addition, fluorescence spectrometry of bovine serum albumin (BSA) with the complexes shows that the fluorescence quenching mechanism of BSA is a static process. The results of site‐competitive replacement experiments with specific site markers clearly indicate that the complexes bind to site I of BSA. Notably, the complexes exhibit significant in vitro cytotoxicity against two human cancer cell lines (Jurkat and MCF‐7) with IC₅₀ values varying from 37 to 53 μM. Finally, a molecular docking experiment effectively proves the binding of the Pd(II) complexes to DNA and BSA.     

Synthesis,characterization, DNA binding,apoptosis and molecular docking of three Mn(II), Zn(II) and Cu(II) complexes with terpyridine‐based carboxylic acid

A series of novel cytotoxic compounds, [Mn(cpt)₂], [Zn(tpt)(H₂O)₂]?DMA?2(H₂O) and [Cu(tpt)]?DMA (cpt = 4′‐(4‐carboxyphenyl)‐2,2′:6′,2″‐terpyridine, tpt = 4‐(2,4,6‐tricarboxylphenyl)‐2,2′:6′,2″‐terpyridine, DMA = (CH₃)₂NH), were isolated and characterized. The structures of these complexes were characterized using single‐crystal X‐ray diffraction. The mode and extent of binding between fish sperm DNA and the complexes were investigated using fluorescence spectroscopy and molecular docking. These results indicate the ability of the complexes to bind to DNA with different binding affinities. The binding of the Zn(II) complex with DNA is stronger than that of the corresponding Cu(II) analogue, which is expected due to the z* effect and geometry. The ability of these complexes to cleave pBR322 plasmid DNA was demonstrated using gel electrophoresis assay, showing that the complexes have effective DNA cleavage activity. In addition, the cytotoxic effects of these complexes were examined on HeLa cells (human cervix epithelia carcinoma cells) in vitro. The three complexes exhibit different cytotoxic effects and decent cancer cell inhibitory rate. This means that the structures and type of metal have a great influence on the activity of these novel complexes.     

Alignment of molecules by the Monte Carlo optimization of molecular similarity indices

3D-QSAR uses statistical techniques to correlate calculated structural properties with target properties like biological activity. The comparison of calculated structural properties is dependent upon the relative orientations of molecules in a given data set. Typically molecules are aligned by performing an overlap of common structural units. This “alignment rule” is adequate for a data set, that is closely related structurally, but is far more difficult to apply to either a diverse data set or on the basis of some structural property other than shape, even for sterically similar molecules. In this work we describe a new algorithm for molecular alignment based upon optimization of molecular similarity indices. We show that this Monte Carlo based algorithm is more effective and robust than other optimizers applied previously to the similarity based alignment problem. We show that QSARs derived using the alignments generated by our algorithm are superior to QSARs derived using the more common alignment of fitting of common structural units. © 1997 by John Wiley & Sons, Inc. J Comput Chem 18 : 1344–1353, 1997     

Effects of mussel-inspired co-deposition of 2-hydroxymethyl methacrylate and poly (2-methoxyethyl acrylate) on the hydrophilicity and binding tendency of common hemodialysis membranes: Molecular dynamics simulations and molecular docking studies

Despite advances in the field, hemoincompatibility remains a critical issue for hemodialysis (HD) as interactions between various human blood constituents and the polymeric structure of HD membranes results in complications such as activation of immune system cascades. Adding hydrophilic polymer structures to the membranes is one modification approach that can decrease the extent of protein adsorption. This study conducted molecular dynamics (MD) simulations to understand the interactions between three human serum proteins (fibrinogen [FB], human serum albumin, and transferrin) and common HD membranes in untreated and modified forms. Poly(aryl ether sulfone) (PAES) and cellulose triacetate were used as the common dialyzer polymers, and membrane modifications were performed with 2-hydroxymethyl methacrylate (HEMA) and poly (2-methoxyethyl acrylate) (PMEA), using polydopamine-assisted co-deposition. The MD simulations were used as the framework for binding energy simulations, and molecular docking simulations were also performed to conduct molecular-level investigations between the two modifying polymers (HEMA and PMEA) and FB. Each of the three proteins acted differently with the membranes due to their unique nature and surface chemistry. The simulations show PMEA binds less intensively to FB with a higher number of hydrogen bonds, which reflects PMEA's superior performance compared to HEMA. The simulations suggest PAES membranes could be used in modified forms for blood-contact applications as they reflect the lowest binding energy to blood proteins.     

DNA interaction,antimicrobial and molecular docking studies of biologically interesting Schiff base complexes incorporating 4‐formyl‐N,N‐dimethylaniline and propylenediamine

Four new transition metal complexes incorporating a Schiff base ligand derived from propylenediamine and 4‐formyl‐N ,N ‐dimethylaniline have been synthesized using transition metal salts. The characterization of the newly formed complexes was done from physicochemical parameters and using various techniques like ¹H NMR, ¹³C NMR, IR, UV, electron paramagnetic resonance and mass spectroscopies, powder X‐ray diffraction and magnetic susceptibility. All the complexes were found to be monomeric in nature with square planar geometry. X‐ray powder diffraction illustrates that the complexes have a crystalline nature. The interaction of metal complexes with calf thymus DNA was investigated using UV–visible absorption, viscosity measurements, cyclic voltammetry, emission spectroscopy and docking analysis. The results indicate that the Cu(II), Co(II), Ni(II) and Zn(II) complexes interact with DNA by intercalative binding mode with optimum intrinsic binding constants of 4.3 × 10⁴, 3.9 × 10⁴, 4.7 × 10⁴ and 3.7 × 10⁴ M⁻¹, respectively. These DNA binding results were rationalized using molecular docking in which the docked structures indicate that the metal complexes fit well into the A‐T rich region of target DNA through intercalation. The metal complexes exhibit an effective cleavage with pUC19 DNA by an oxidative cleavage mechanism. The synthesized ligand and the complexes were tested for their in vitro antimicrobial activity. The complexes show enhanced antifungal and antibacterial activities compared to the free ligand.     

MC(JBW): Simple but smart Monte Carlo algorithm for free energy simulations of multiconformational molecules

Many of the most common molecular simulation methods, including Monte Carlo (MC) and molecular or stochastic dynamics (MD or SD), have significant difficulties in sampling the space of molecular potential energy surfaces characterized by multiple conformational minima and significant energy barriers. In such cases improved sampling can be obtained by special techniques that lower such barriers or somehow direct search steps toward different low energy regions of space. We recently described a hybrid MC/SD algorithm [MC(JBW)/SD] incorporating such a technique that directed MC moves of selected torsion and bond angles toward known low energy regions of conformational space. Exploration of other degrees of freedom was left to the SD part of the hybrid algorithm. In the work described here, we develop a related but simpler simulation algorithm that uses only MC to sample all degrees of freedom (e.g., stretch, bend, and torsion). We term this algorithm MC(JBW). Using simulations on various model potential energy surfaces and on simple molecular systems (n-pentane, n-butane, and cyclohexane), MC(JBW) is shown to generate ensembles of states that are indistinguishable from the canonical ensembles generated by classical Metropolis MC in the limit of very long simulations. We further demonstrate the utility of MC(JBW) by evaluating the room temperature free energy differences between conformers of various substituted cyclohexanes and the larger ring hydrocarbons cycloheptane, cyclooctane, cyclononane, and cyclodecane. The results compare favorably with available experimental data and results from previously reported MC(JBW)/SD conformational free energy calculations. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 1736–1745, 1998     

Probing molecular mechanism of inhibitor bindings to bromodomain-containing protein 4 based on molecular dynamics simulations and principal component analysis

ABSTRACT

It is well known that bromodomain-containing protein 4 (BRD4) has been thought as a promising target utilized for treating various human diseases, such as inflammatory disorders, malignant tumours, acute myelogenous leukaemia (AML), bone diseases, etc. For this study, molecular dynamics (MD) simulations, binding free energy calculations, and principal component analysis (PCA) were integrated together to uncover binding modes of inhibitors 8P9, 8PU, and 8PX to BRD4(1). The results obtained from binding free energy calculations show that van der Waals interactions act as the main regulator in bindings of inhibitors to BRD4(1). The information stemming from PCA reveals that inhibitor associations extremely affect conformational changes, internal dynamics, and movement patterns of BRD4(1). Residue-based free energy decomposition method was wielded to unveil contributions of independent residues to inhibitor bindings and the data signify that hydrogen bonding interactions and hydrophobic interactions are decisive factors affecting bindings of inhibitors to BRD4(1). Meanwhile, eight residues Trp81, Pro82, Val87, Leu92, Leu94, Cys136, Asn140, and Ile146 are recognized as the common hot interaction spots of three inhibitors with BRD4(1). The results from this work are expected to provide a meaningfully theoretical guidance for design and development of effective inhibitors inhibiting of the activity of BRD4.