1,721,023 research outputs found
Robust Scoring Functions for Protein-Ligand Interactions with Quantum Chemical Charge Models
No full textOrdinary least-squares (OLS) regression has been used widely for constructing the scoring functions for protein–ligand interactions. However, OLS is very sensitive to the existence of outliers, and models constructed using it are easily affected by the outliers or even the choice of the data set. On the other hand, determination of atomic charges is regarded as of central importance, because the electrostatic interaction is known to be a key contributing factor for biomolecular association. In the development of the AutoDock4 scoring function, only OLS was conducted, and the simple Gasteiger method was adopted. It is therefore of considerable interest to see whether more rigorous charge models could improve the statistical performance of the AutoDock4 scoring function. In this study, we have employed two well-established quantum chemical approaches, namely the restrained electrostatic potential (RESP) and the Austin- model 1-bond charge correction (AM1-BCC) methods, to obtain atomic partial charges, and we have compared how different charge models affect the performance of AutoDock4 scoring functions. In combination with robust regression analysis and outlier exclusion, our new protein–ligand free energy regression model with AM1-BCC charges for ligands and Amber 99SB charges for proteins achieve lowest root-mean- squared error of 1.637 kcal/mol for the training set of 147 complexes and 2.176 kcal/mol for the external test set of 1427 complexes. The assessment for binding pose prediction with the 100 external decoy sets indicates very high success rate of 87% with the criteria of predicted root-mean- squared deviation of less than 2 Å. The success rates and statistical performance of our robust scoring functions are only weakly class-dependent (hydrophobic, hydrophilic, or mixed)
Deriving Interfacial Properties of Small Unilamellar Vesicles Via Multiscale Computer Simulations
No full textMEDock: a Web Server for Efficient Prediction of Ligand Binding Sites Based on a Novel Optimization Algorithm
No full textReview structure- and dynamics-based computational design of anticancer drugs
No full textCancer is a class of highly complex diseases involving multiple genes and multiple cross-talks between signaling networks. Cancer cells may be developed from inherited defects or acquired damages of DNA. However, many cancers are resistant to treatment, and metastasis of cancers makes the disease even more intractable. Secondary malignancies are frequently observed after cancer chemotherapy. The call for more effective cancer therapy is obligatory. Using drug-cocktails that combine multiple anti-cancer agents working in different mechanisms has been a standard treatment of cancers to overcome the drug resistance problem. More recently, design of multiple ligands (may be more easily understood as multiple target ligands), i.e., single agents that target multiple biomolecules in a rational manner, receives increasing attention. For those who work on computational drug design, such tasks serve as new opportunities for achieving drugs with more effective pharmacological actions, in addition to designing compounds with better binding affinity, better selectivity, or to discovering compounds that can exert their actions allosterically. Some recent methodological developments on computational drug design are reviewed, and a few recent drug design efforts on a selected set of targets (topoisomerases, Ras proteins, protein kinases, and histone deacetylases) toward cancer treatment and cancer prevention are summarized. (c) 2015 Wiley Periodicals, Inc. Biopolymers 105: 2-9, 2015
Protemot: prediction of protein binding sites with automatically extracted geometrical templates
No full textHiv-1 Protease Molecular Dynamics of a Wild-Type and of the V82f/I84v Mutant: Possible Contributions to Drug Resistance and a Potential New Target Site for Drugs
No full textThe protease from type I human immunodeficiency virus (HIV-1 ) is a critical drug target against which many therapeutically useful inhibitors have been developed; however, the set of viral strains in the population has been shifting to become more drug-resistant. Because indirect effects are contributing to drug resistance, an examination of the dynamic structures of a wild-type and a mutant could be insightful. Consequently, this study examined structural properties sampled during 22 nsec, all atom molecular dynamics (MD) simulations (in explicit water) of both a wild - type and the drug-resistant V82F/184V mutant of HIV-1 protease. The V82F/ 184V mutation significantly decreases the binding affinity of all HIV-1 protease inhibitors currently used clinically. Simulations have shown that the curling of the tips of the active site flaps immediately results in flap opening. In the 22-nsec MD simulations presented here, more frequent and more rapid curling of the mutant's active site flap tips was observed. The mutant protease's flaps also opened farther than the wild-type's flaps did and displayed more flexibility. This suggests that the effect of the mutations on the equilibrium between the semiopen and closed conformations could be one aspect of the mechanism of drug resistance for this mutant. In addition, correlated fluctuations in the active site and periphery were noted that point to a possible binding site for allosteric inhibitors
Recovery of the poisoned topoisomerase II for DNA religation: coordinated motion of the cleavage core revealed with the microsecond atomistic simulation
No full textType II topoisomerases resolve topological problems of DNA double helices by passing one duplex through the reversible double-stranded break they generated on another duplex. Despite the wealth of information in the cleaving operation, molecular understanding of the enzymatic DNA ligation remains elusive. Topoisomerase poisons are widely used in anti-cancer and anti-bacterial therapy and have been employed to entrap the intermediates of topoisomerase II beta with religatable DNA substrate. We removed drug molecules from the structure and conducted molecular dynamics simulations to investigate the enzyme-mediated DNA religation. The drug-unbound intermediate displayed transitions toward the resealing-compliant configuration: closing distance between the cleaved DNA termini, B-to-A transformation of the double helix, and restoration of the metal-binding motif. By mapping the contact configurations and the correlated motions between enzyme and DNA, we identified the indispensable role of the linker preceding winged helix domain (WHD) in coordinating the movements of TOPRIM, the nucleotide-binding motifs, and the bound DNA substrate during gate closure. We observed a nearly vectorial transition in the recovery of the enzyme and identified the previously uncharacterized roles of Asn508 and Arg677 in DNA rejoining. Our findings delineate the dynamic mechanism of the DNA religation conducted by type II topoisomerases
Drug-Induced Conformational Population Shifts in Topoisomerase-DNA Ternary Complexes
No full textType II topoisomerases (TOP2) are enzymes that resolve the topological problems during DNA replication and transcription by transiently cleaving both strands and forming a cleavage complex with the DNA. Several prominent anti-cancer agents inhibit TOP2 by stabilizing the cleavage complex and engendering permanent DNA breakage. To discriminate drug binding modes in TOP2-alpha and TOP2-beta, we applied our newly developed scoring function, dubbed AutoDock4(RAP), to evaluate the binding modes of VP-16, m-AMSA, and mitoxantrone to the cleavage complexes. Docking reproduced crystallographic binding mode of VP-16 in a ternary complex of TOP2-beta with root-mean-square deviation of 0.65 angstrom. Molecular dynamics simulation of the complex confirmed the crystallographic binding mode of VP-16 and the conformation of the residue R503. Drug-related conformational changes in R503 have been observed in ternary complexes with m-AMSA and mitoxantrone. However, the R503 rotamers in these two simulations deviate from their crystallographic conformations, indicating a relaxation dynamics from the conformations determined with the drug replacement procedure. The binding mode of VP-16 in the cleavage complex of TOP2-alpha was determined by the conjoint use of docking and molecular dynamics simulations, which fell within a similar binding pocket of TOP2-beta cleavage complex. Our findings may facilitate more efficient design efforts targeting TOP2-alpha specific drugs
The Relaxed Complex Method: Accommodating Receptor Flexibility for Drug Design with an Improved Scoring Scheme
No full textAn extension of the new computational methodology for drug design, the " relaxed complex" method (J.-H. Lin, A. L. Perryman, J. R. Schames, and J. A. McCammon, Journal of the American Chemical Society, 2002, vol. 24, pp. 5632-5633), which accommodates receptor flexibility, is described. This relaxed complex method recognizes that ligand may bind to conformations that occur only rarely in the dynamics of the receptor. We have shown that the ligand-enzyme binding modes are very sensitive to the enzyme conformations, and our approach is capable of finding the best ligand enzyme complexes. Rapid docking serves as an efficient initial filtering method to screen a myriad of docking modes to a limited set, and it is then followed by more accurate scoring with the MM/PBSA (Molecular Mechanics/Poisson Boltzmann Surface Area) approach to find the best ligand - receptor complexes. The MM/PBSA scorings consistently indicate that the calculated binding modes that are most similar to those observed in the x- ray crystallographic complexes are the ones with the lowest free energies
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