Multiple Binding Modes of Anticancer Drug Actinomycin D: X-ray, Molecular Modeling, and Spectroscopic Studies of d(GAAGCTTC)2-Actinomycin D Complexes and Its Host DNA

1994 ◽  
Vol 116 (10) ◽  
pp. 4154-4165 ◽  
Author(s):  
Shigehiro Kamitori ◽  
Fusao Takusagawa
2016 ◽  
Vol 113 (26) ◽  
pp. E3745-E3754 ◽  
Author(s):  
Philip Hinchliffe ◽  
Mariano M. González ◽  
Maria F. Mojica ◽  
Javier M. González ◽  
Valerie Castillo ◽  
...  

Metallo-β-lactamases (MBLs) hydrolyze almost all β-lactam antibiotics and are unaffected by clinically available β-lactamase inhibitors (βLIs). Active-site architecture divides MBLs into three classes (B1, B2, and B3), complicating development of βLIs effective against all enzymes. Bisthiazolidines (BTZs) are carboxylate-containing, bicyclic compounds, considered as penicillin analogs with an additional free thiol. Here, we show both l- and d-BTZ enantiomers are micromolar competitive βLIs of all MBL classes in vitro, with Kis of 6–15 µM or 36–84 µM for subclass B1 MBLs (IMP-1 and BcII, respectively), and 10–12 µM for the B3 enzyme L1. Against the B2 MBL Sfh-I, the l-BTZ enantiomers exhibit 100-fold lower Kis (0.26–0.36 µM) than d-BTZs (26–29 µM). Importantly, cell-based time-kill assays show BTZs restore β-lactam susceptibility of Escherichia coli-producing MBLs (IMP-1, Sfh-1, BcII, and GOB-18) and, significantly, an extensively drug-resistant Stenotrophomonas maltophilia clinical isolate expressing L1. BTZs therefore inhibit the full range of MBLs and potentiate β-lactam activity against producer pathogens. X-ray crystal structures reveal insights into diverse BTZ binding modes, varying with orientation of the carboxylate and thiol moieties. BTZs bind the di-zinc centers of B1 (IMP-1; BcII) and B3 (L1) MBLs via the free thiol, but orient differently depending upon stereochemistry. In contrast, the l-BTZ carboxylate dominates interactions with the monozinc B2 MBL Sfh-I, with the thiol uninvolved. d-BTZ complexes most closely resemble β-lactam binding to B1 MBLs, but feature an unprecedented disruption of the D120–zinc interaction. Cross-class MBL inhibition therefore arises from the unexpected versatility of BTZ binding.


FEBS Open Bio ◽  
2015 ◽  
Vol 5 (1) ◽  
pp. 557-570 ◽  
Author(s):  
Mikiya Satoh ◽  
Hajime Saburi ◽  
Tomoyuki Tanaka ◽  
Yoshinori Matsuura ◽  
Hisashi Naitow ◽  
...  

2010 ◽  
Vol 98 (3) ◽  
pp. 752a
Author(s):  
Thayaparan Paramanathan ◽  
Ioana D. Vladescu ◽  
Micah J. McCauley ◽  
Ioulia Rouzina ◽  
Mark C. Williams

2020 ◽  
Author(s):  
Samuel C. Gill ◽  
David Mobley

<div>Sampling multiple binding modes of a ligand in a single molecular dynamics simulation is difficult. A given ligand may have many internal degrees of freedom, along with many different ways it might orient itself a binding site or across several binding sites, all of which might be separated by large energy barriers. We have developed a novel Monte Carlo move called Molecular Darting (MolDarting) to reversibly sample between predefined binding modes of a ligand. Here, we couple this with nonequilibrium candidate Monte Carlo (NCMC) to improve acceptance of moves.</div><div>We apply this technique to a simple dipeptide system, a ligand binding to T4 Lysozyme L99A, and ligand binding to HIV integrase in order to test this new method. We observe significant increases in acceptance compared to uniformly sampling the internal, and rotational/translational degrees of freedom in these systems.</div>


2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>


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