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PubMed2026

Computational discovery of emodin-based anthraquinones as PARP-1 inhibitors with relevance to ovarian and prostate cancer.

Cancer is a disease characterized by genomic instability and aberrant DNA repair. Poly (ADP-ribose) polymerase-1 (PARP-1) represents a well-established therapeutic target, particularly in ovarian and prostate cancer. However, the currently approved PARP inhibitors face challenges such as resistance, toxicity, and reduced efficacy. The search for alternative scaffolds has therefore become increasingly urgent. In this study, we used an integrated approach combining computer-aided methods to search for potential lead compounds among emodin-based anthraquinone derivatives as PARP-1 inhibitors. Using a PASS-based QSAR approach, drug-likeness prediction, and in silico ADMET assessment, we pre-screened a large set of anthraquinones and identified several potential hits for interaction with PARP-1. These hits were studied using molecular docking with the PARP-1 catalytic domain (PDB ID: 7KK4). The most stable and compact complexes were further explored by 500 ns molecular dynamics (MD) simulations and various dynamic properties (RMSD, RMSF, Rg, SASA, MolSA, hydrogen bonds, PCA, DCCM). The key finding of this study is that several emodin-derived anthraquinones exhibited binding behavior and ADMET profiles comparable to, or better than, the reference PARP-1 inhibitor. Among them, CID-10425624 emerged as the most promising candidate, exhibiting stable binding, reduced conformational fluctuation, compact complex formation, persistent hydrogen-bond interactions, and enhanced dynamic residue correlations within the PARP-1 catalytic domain. These findings suggest that the anthraquinone scaffold can provide a valuable starting point for developing structurally distinct PARP-1 inhibitors. In summary, this study identified several emodin-derived anthraquinones, particularly CID-10425624, as computationally prioritized lead candidates for PARP-1 inhibition, providing a novel anthraquinone-based scaffold for further experimental validation and optimization.

Anthraquinones↗

PubMed2026

Quantifying the peripheral surface information entropy from conformational ensembles of globular protein-peptide complexes.

Predicting favorable protein-peptide binding events remains a central challenge in biophysics, with continued uncertainty surrounding how nonlocal effects shape the global energy landscape. Here, we introduce peripheral surface information entropy, SΨ, a quantitative measure of the statistical variability in apolar and charged non-interacting surface (NIS) proportions across conformational ensembles. Within the Gibbs free-energy relation ΔG = ΔH - TΔS, SΨ is proposed as a computationally tractable entropic proxy rather than a direct thermodynamic observable or stand-alone estimator of binding affinity. Using energy-directed molecular docking via HADDOCK3 and explicit-solvent molecular dynamics simulations, it is demonstrated that favorable binding partners exhibit emergent, low-entropy N-states (discrete macrostates in NIS state space) indicative of preferential apolar/charged surface configurations. Across dozens of peptides and multiple receptor systems (WW, PDZ, and MDM2 domains), dominant N-states persisted under varied docking parameters and initial conditions. A meta-ensemble of 657 complexes from 36 experiments over 15 years confirmed the presence of dominant NIS modes independent of in silico methodology, suggesting an evolutionary selection pressure toward specific NIS fingerprints. These findings establish SΨ as a thermoinformatic descriptor that encodes favorable binding constraints into unique statistical signatures of the NIS.

Entropy↗

PubMed2000

Influence of mRNA self-structure on hybridization: computational tools for antisense sequence selection.

Antisense targeting, an innovative technology based on preventing biosynthesis through sequence-specific hybridization of mRNA to synthetic oligodeoxynucleotides (ODNs), is used to selectively and transiently downregulate the expression of any gene product. Its potential applications are both investigative (neurobiology and related disciplines) and therapeutic (oncology, virology, genetic diseases), and several antisense-based drugs are currently undergoing clinical trials. However, the reported efficiencies vary and there is still a lack of clarity in the underlying mechanisms of action. A critical factor of antisense efficiency is the issue of target site selection, as both mRNA and ODN molecules exhibit a significant amount of highly heterogeneous self-structure and the region selected for targeting may well be sterically or energetically inaccessible. Because of the prohibitively large chain length, mRNA structural information is not accessible by X-ray crystallography or NMR, making a modeling approach indispensable. I outline how the latest molecular modeling techniques can be employed to establish the secondary (2D) and tertiary (3D) structures into which a given mRNA folds during and after transcription. The aim should be to integrate 2D prediction results achieved by (a) free-energy minimization, (b) kinetic folding simulations, (c) iterative population breeding by genetic algorithms, and (d) phylogenetic comparison techniques. These results can form the input of a 3D structure prediction paradigm based on constraint-satisfying programming, governed by experimental molecular mechanical constraints, and refined by molecular dynamics simulations. Finally, the automated docking (by simulated annealing) of ODN molecules to the mRNA structure can provide information about the accessibility of target mRNA regions for hybridization. To date, the great majority of studies that employ antisense as a tool select their target sequences more or less randomly. Although the wealth of molecular interactions that take place within a cell makes complete predictability unrealistic, the kind of information that can be extracted from such techniques is of relevance to every application of antisense technology, both investigative and therapeutic.

Algorithms↗

PubMed2005

Accounting for global protein deformability during protein-protein and protein-ligand docking.

Computational docking methods are valuable tools aimed to simplify the costly process of drug development and improvement. Most current approaches assume a rigid receptor structure to allow virtual screening of large numbers of possible ligands and putative binding sites on a receptor molecule. However, inclusion of receptor flexibility can be of critical importance since binding of a ligand can lead to changes in the receptor protein conformation that are sterically necessary to accommodate a ligand. Recent approaches to efficiently account for receptor flexibility during docking simulations are reviewed. In particular, accounting efficiently for global conformational changes of the protein backbone during docking is a still challenging unsolved problem. An approximate method has recently been suggested that is based on relaxing the receptor conformation during docking in pre-calculated soft collective degrees of freedom (M. Zacharias, Rapid protein-ligand docking using soft modes from molecular dynamics simulations to account for protein deformability: binding of FK506 to FKBP, Proteins: Struct., Funct., Genet. 54 (2004) 759-767). Test applications on protein-protein docking and on docking the inhibitor staurosporine to the apo-form of cAMP-dependent protein kinase A catalytic domain indicate significant improvement of docking results compared to rigid docking at a very modest computational demand. Accounting for receptor conformational changes in pre-calculated global degrees of freedom might offer a promising route to improve systematic docking screening simulations.

Binding Sites↗

PubMed2004

Classical force field parameters for the heme prosthetic group of cytochrome c.

Accurate force fields are essential for describing biological systems in a molecular dynamics simulation. To analyze the docking of the small redox protein cytochrome c (cyt c) requires simulation parameters for the heme in both the reduced and oxidized states. This work presents parameters for the partial charges and geometries for the heme in both redox states with ligands appropriate to cyt c. The parameters are based on both protein X-ray structures and ab initio density functional theory (DFT) geometry optimizations at the B3LYP/6-31G* level. The simulations with the new parameter set reproduce the geometries of the X-ray structures and the interaction energies between water and heme prosthetic group obtained from B3LYP/6-31G* calculations. The parameter set developed here will provide new insights into docking processes of heme containing redox proteins.

Algorithms↗

PubMed2005

Molecular insight into pseudolysin inhibition using the MM-PBSA and LIE methods.

Pseudolysin, the extracellullar elastase of Pseudomonas aeruginosa (EC: 3.4.24.26) plays an important role in the pathogenesis of P. aeruginosa infections. In the present study, molecular dynamics simulations and theoretical affinity predictions were used to gain molecular insight into pseudolysin inhibition. Four low molecular weight inhibitors were docked at their putative binding sites and molecular dynamics (MD) simulations were performed for 5.0 ns, and the free energy of binding was calculated by the linear interaction energy method. The number and the contact surface area of stabilizing hydrophobic, aromatic, and hydrogen bonding interactions appears to reflect the affinity differences between the inhibitors. The proteinaceous inhibitor, Streptomyces metalloproteinase inhibitor (SMPI) was docked in three different binding positions and MD simulations were performed for 3.0 ns. The MD trajectories were used for molecular mechanics-Poisson-Boltzmann surface area analysis of the three binding positions. Computational alanine scanning of the average pseudolysin-SMPI complexes after MD revealed residues at the pseudolysin-SMPI interface giving the main contribution to the free energy of binding. The calculations indicated that SMPI interacts with pseudolysin via the rigid active site loop, but that also contact sites outside this loop contribute significantly to the free energy of association.

Amino Acid Sequence↗

PubMed1996

Positioning hydrogen atoms by optimizing hydrogen-bond networks in protein structures.

A method is presented that positions polar hydrogen atoms in protein structures by optimizing the total hydrogen bond energy. For this goal, an empirical hydrogen bond force field was derived from small molecule crystal structures. Bifurcated hydrogen bonds are taken into account. The procedure also predicts ionization states of His, Asp, and Glu residues. During optimization, side-chain conformations of His, Gln, and Asn residues are allowed to change their last chi angle by 180 degrees to compensate for crystallographic misassignments. Crystal structure symmetry is taken into account where appropriate. The results can have significant implications for molecular dynamics simulations, protein engineering, and docking studies. The largest impact, however, is in protein structure verification: over 85% of protein structures tested can be improved by using our procedure.

Amino Acids↗

PubMed2006

Molecular basis of substrate recognition in D-3-hydroxybutyrate dehydrogenase from Pseudomonas putida.

D-3-Hydroxybutyrate dehydrogenase from Pseudomonas putida (EC 1.1.1.30) belongs to the family of short-chain dehydrogenases/reductases (SDRs). It catalyzes the reversible and stereospecific oxidation of D-3-hydroxybutyrate (D-3-HB) to acetoacetate with the aid of NAD(+) as coenzyme. This study contributes to understanding the mechanism and the high specificity of this enzyme towards its negatively charged and hydrophilic substrate. Sequence comparison of 44 bacterial HBDHs shows the residues Gln91, His141, Lys149, Lys192, and Gln193 to be strictly conserved. Site-directed mutagenesis of these amino acids to alanine and subsequent kinetic characterization of the mutated enzymes provides insight into the importance of these residues for substrate recognition and catalysis. Docking studies and molecular-dynamics simulations based on a three-dimensional structure model of a complex between P. putida HBDH and its coenzyme obtained by comparative molecular modeling were performed and provided deeper insight into the binding of the ligands at the molecular level. They show the residues Gln91, His141, Gln193, and, in particular, Lys149 to be involved in a hydrogen-bonding network with the carboxylate group of the substrate.

3-Hydroxybutyric Acid↗

PubMed2025

Genomics-informed drug-repurposing strategy identifies two therapeutic targets for preventing liver disease associated with metabolic dysfunction.

Identification of drug-repurposing targets with genetic and biological support is an economically and temporally efficient strategy for improving the treatment of diseases. We employed a cross-disciplinary approach to identify potential therapeutics for the prevention of metabolic-dysfunction-associated steatotic liver disease (MASLD) in at-risk individuals by using humans as a model organism. We identified 212 putative candidate genes associated with MASLD by using data from a large multi-ancestry genetic association study, of which 158 (74.5%) were previously unreported. From this set, we identified 57 genes that encode for druggable protein targets and for which the effects of increasing genetically predicted gene expression on MASLD risk align with the function of that drug on the protein target. We then used We then evaluated these potential targets for evidence of efficacy by using Mendelian randomization, pathway analysis, and protein structural modeling. Through these approaches, we present compelling evidence to suggest that the activation of FADS1 by icosapent ethyl, as well as S1PR2 by fingolimod, could be a promising therapeutic strategy for MASLD prevention.

Humans↗

PubMed2002

Analysis of ice-binding sites in fish type II antifreeze protein by quantum mechanics.

Many organisms living in cold environments can survive subzero temperatures by producing antifreeze proteins (AFPs) or antifreeze glycoproteins. In this paper we investigate the ice-binding surface of type II AFP by quantum mechanical methods, which, to the best of our knowledge, represents the first time that molecular orbital computational approaches have been applied to AFPs. Molecular mechanical approaches, including molecular docking, energy minimization, and molecular dynamics simulation, were used to obtain optimal systems for subsequent quantum mechanical analysis. We selected 17 surface patches covering the entire surface of the type II AFP and evaluated the interaction energy between each of these patches and two different ice planes using semi-empirical quantum mechanical methods. We have demonstrated the weak orbital overlay phenomenon and the change of bond orders in ice. These results consistently indicate that a surface patch containing 19 residues (K37, L38, Y20, E22, Y21, I19, L57, T56, F53, M127, T128, F129, R17, C7, N6, P5, G10, Q1, and W11) is the most favorable ice-binding site for both a regular ice plane and an ice plane where water O atoms are randomly positioned. Furthermore, for the first time the computation results provide new insights into the weakening of the ice lattice upon AFP binding, which may well be a primary factor leading to AFP-induced ice growth inhibition.

Animals↗

PubMed1999

Ice-binding surface of fish type III antifreeze.

We employed computational techniques, including molecular docking, energy minimization, and molecular dynamics simulation, to investigate the ice-binding surface of fish type III antifreeze protein (AFP). The putative ice-binding site was previously identified by mutagenesis, structural analysis, and flatness evaluation. Using a high-resolution x-ray structure of fish type III AFP as a model, we calculated the ice-binding interaction energy of 11 surface patches chosen to cover the entire surface of the protein. These various surface patches exhibit small but significantly different ice-binding interaction energies. For both the prism ice plane and an "ice" plane in which water O atoms are randomly positioned, our calculations show that a surface patch containing 14 residues (L19, V20, T18, S42, V41, Q9, P12, A16, M21, T15, Q44, I13, N14, K61) has the most favorable interaction energy and corresponds to the previously identified ice-binding site of type III AFP. Although in general agreement with the earlier studies, our results also suggest that the ice-binding site may be larger than the previously identified "core" cluster that includes mostly hydrophilic residues. The enlargement mainly results from the inclusion of peripheral hydrophobic residues and K61.

Amino Acid Sequence↗

PubMed2006

Microscopic modes and free energies of 3-phosphoinositide-dependent kinase-1 (PDK1) binding with celecoxib and other inhibitors.

Celecoxib, also known as Celebrex (approved by FDA in 1998) and remembered as the fastest-selling drug in history, was used as a cyclooxygenase-2 (COX-2) selective inhibitor having both anti-inflammatory and anticancer activities. Most recent studies have revealed that the apoptotic activity of celecoxib (and its derivatives) is actually independent of the COX-2 inhibitory activity and that celecoxib also inhibits the kinase activity of 3-phosphoinositide-dependent protein kinase-1 (PDK1), suggesting that the well-known anticancer activity of celecoxib is not due to the inhibition of COX-2, but possibly is due to the inhibition of PDK1. It is highly desirable to develop new celecoxib derivatives as PDK1-specifc inhibitors to avoid the side effects of COX-2 inhibitors. To understand how PDK1 binds with celecoxib and its derivatives, we have performed extensive molecular docking and combined molecular dynamics (MD) simulations and molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations on eight representative PDK1 inhibitors, leading to the finding of a new, more favorable binding mode which is remarkably different from the previously proposed binding mode. Based on the determined most stable binding structures, the calculated binding free energies are all in good agreement with the corresponding experimental data, and the biological activity data available for celecoxib and its derivatives can be better interpreted. The obtained new insights, concerning both the binding mode and computational protocol, will be valuable not only for future rational design of novel, more potent PDK1-specific inhibitors as promising anticancer therapeutics, but also for rational design of drugs targeting other proteins.

3-Phosphoinositide-Dependent Protein Kinases↗

PubMed1998

Aspects of the mechanism of catalysis of glucose oxidase: a docking, molecular mechanics and quantum chemical study.

The complex structure of glucose oxidase (GOX) with the substrate glucose was determined using a docking algorithm and subsequent molecular dynamics simulations. Semiempirical quantum chemical calculations were used to investigate the role of the enzyme and FAD co-enzyme in the catalytic oxidation of glucose. On the basis of a small active site model, substrate binding residues were determined and heats of formation were computed for the enzyme substrate complex and different potential products of the reductive half reaction. The influence of the protein environment on the active site model was estimated with a point charge model using a mixed QM/MM method. Solvent effects were estimated with a continuum model. Possible modes of action are presented in relation to experimental data and discussed with respect to related enzymes. The calculations indicate that the redox reaction of GOX differs from the corresponding reaction of free flavins as a consequence of the protein environment. One of the active site histidines is involved in substrate binding and stabilization of potential intermediates, whereas the second histidine is a proton acceptor. The former one, being conserved in a series of oxidoreductases, is also involved in the stabilization of a C4a-hydroperoxy dihydroflavin in the course of the oxidative half reaction.

Aspergillus niger↗

PubMed1994

Molecular modeling of the interaction of polyproline-based peptides with the Abl-SH3 domain: rational modification of the interaction.

A molecular model of the interaction of polyproline-rich peptides with the Abl-SH3 domain is proposed, based on docking calculations with the DOCK program coupled with molecular dynamics simulations. Two distinct binding modes of the peptide to the same aromatic-rich region (Tyr10, Phe12, Trp39, Trp50, Tyr55) of the domain were obtained. It is proposed that these two models could represent different binding modes of proline-rich peptides to Src homology region 3 domains. Several peptide mutants were designed to determine whether the two orientations were possible. Analysis of the Kd values and fluorescence emission of these peptides indicate that one of the orientations is more plausible and that residues at position 4 of the peptide interact with the RT loop, being important in modulating the peptide affinity for the Abl-SH3 domain.

Amino Acid Sequence↗

PubMed2006

[Screening of new HIV inhibitors based on the database of traditional Chinese medicine].

AIM: To report the preliminary result of the HIV inhibitor screening based on cheminformatics tools and the traditional Chinese medicine database. METHODS: Database search was carried out with saquinavir molecule as a template, further screening was made with docking. Detailed studies using molecular dynamics simulation of 50 ps and 200 ps were made with respect to a potential leading compound, leucovorin. RESULTS: The leucovorin molecule distinguished from other molecules as a potential drug candidate and is subject to extensive studies. The bonding profile and energy were calculated with MD simulations. CONCLUSION: Our results could be very helpful when we modify leucovorin or design new inhibitors against HIV.

Anti-HIV Agents↗

PubMed2005

Ribosome builder: a software project to simulate the ribosome.

The Ribosome Builder is a software project that provides tools and techniques to create dynamic models of macromolecular systems from the rapidly growing numbers of atomic structural models. It includes a computer program that allows the user to assemble the multiple molecular components within a 3D space and to define the hypothetical interactions of these components with the initial goal of understanding protein translation at an atomic level of detail. The program employs a simplified molecular dynamics forcefield that can simulate the long time-scale events, such as docking of translation factors and mRNA translocation. An embedded scripting language and Application Programming Interface (API) enable the creation of Steered Molecular Dynamics (SMD) simulations through the programmable application of external forces and torques on atoms and bonds. A graphical interface is provided for displaying and interacting with models, recording movies of molecular dynamics movements, and creating annotated 3D simulations of complex macromolecular events. Initial applications of the project include simulation of tetraloop folding, docking of an mRNA on the 30S subunit and a schematic simulation of the translation elongation cycle. The program is an open source project released under the GNU public license.

Computer Simulation↗

PubMed2005

Metabolic regio- and stereoselectivity of cytochrome P450 2D6 towards 3,4-methylenedioxy-N-alkylamphetamines: in silico predictions and experimental validation.

A series of 3,4-methylenedioxy-N-alkylamphetamines (MDAAs) were automatically docked and subjected to molecular dynamics (MD) simulations in a cytochrome P450 2D6 (CYP2D6) protein model. The predicted substrate binding orientations, sites of oxidation, and relative reactivities were compared to the experimental data of wild-type and Phe120Ala mutant CYP2D6. Automated docking results were not sufficient to accurately rationalize experimental binding orientations of 3,4-methylenedioxy-N-methylamphetamine (MDMA) in the two enzymes as measured with spin lattice relaxation NMR. Nevertheless, the docking results could be used as starting structures for MD simulations. Predicted binding orientations of MDMA and sites of oxidation of the MDAAs derived from MD simulations matched well with the experimental data. It appeared the experimental results were best described in MD simulations considering the nitrogen atoms of the MDAAs in neutral form. Differences in regioselectivity and stereoselectivity in the oxidative metabolism of the MDAAs by the Phe120Ala mutant CYP2D6 were correctly predicted, and the effects of the Phe120Ala mutation could be rationalized as well.

Amphetamines↗

PubMed2026

Genomic and structural analysis of dacB variants associated with cephalosporin resistance in Pseudomonas aeruginosa.

The rise of resistance to fourth-generation cephalosporin in Pseudomonas aeruginosa (P. aeruginosa) is a global concern. The resistance is largely driven by variants of chromosomally encoded AmpC β-lactamase, known as Pseudomonas-derived cephalosporinase (PDC), which arise from the mutations in the ampC gene. In addition, alteration in dacB, which encode the penicillin-binding protein 4 (PBP4), can lead to the overexpression of ampC, thereby contributing to β-lactam resistance. Present work analyzed 208 clinical isolates of P. aeruginosa using whole-genome sequencing (WGS) and detected multiple nonsynonymous single nucleotide polymorphisms (nsSNPs), such as Y264C, G444D, and a double mutation (A394P-T428P). All nsSNPs were predicted to be deleterious by several prediction program. Molecular dynamics (MD) simulations suggested that these substitutions destabilize PBP4, increase structural flexibility, and contribute to the resistance mechanism, which favored their selection. To determine the effective therapeutics against these mutations, molecular docking was conducted with various antibiotics. Cefoperazone exhibited the highest binding affinity (-7.3 kcal/mol) among multiple PBP4 variants. The Molecular dynamics (MD) simulations and Molecular Mechanics Poisson Boltzmann Surface Area calculations (MMPBSA) further confirmed the favorable interactions between cefoperazone and PBP4 variants. In vitro MIC analyses supported these findings, indicating that cefoperazone displayed significant activity against clinical dacB mutants of P. aeruginosa. The study offers structural insight of dacB variants leading to antibiotic resistance and emphasizes the need to prioritize specific antibiotics to address the challenges arising from protein mutations.

Pseudomonas aeruginosa↗