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1.
J Chem Inf Model ; 54(10): 2680-96, 2014 Oct 27.
Article in English | MEDLINE | ID: mdl-25233464

ABSTRACT

Sampling low energy conformations of macrocycles is challenging due to the large size of many of these molecules and the constraints imposed by the macrocycle. We present a new conformational search method (implemented in MacroModel) that uses brief MD simulations followed by minimization and normal-mode search steps. The method was parametrized using a set of 100 macrocycles from the PDB and CSD. It was then tested on a publicly available data set for which there are published results using alternative methods; we found that when the same force field is used (in this case MMFFs in vacuum), our method tended to identify conformations with lower energies than what the other methods identified. The performance on a new set of 50 macrocycles from the PDB and CSD was also quite good; the mean and median RMSD values for just the ring atoms were 0.60 and 0.33 Å, respectively. However, the RMSD values for macrocycles with more than 30 ring-atoms were quite a bit larger compared to the smaller macrocycles. Possible origins for this and ideas for improving the performance on very large macrocycles are discussed.


Subject(s)
Cyclodextrins/chemistry , Peptides, Cyclic/chemistry , Peptides/chemistry , Software , Algorithms , Molecular Conformation , Molecular Dynamics Simulation , Proteins/chemistry , Thermodynamics
2.
ACS Chem Biol ; 6(10): 1069-77, 2011 Oct 21.
Article in English | MEDLINE | ID: mdl-21793507

ABSTRACT

Tyrosine sulfate-mediated interactions play an important role in HIV-1 entry. After engaging the CD4 receptor at the cell surface, the HIV-1 gp120 glycoprotein binds to the CCR5 co-receptor via an interaction that requires two tyrosine sulfates, at positions 10 and 14 in the CCR5-N terminus. Building on previous structure determinations of this interaction, here we report the targeting of these tyrosine sulfate binding sites for drug design through in silico screening of small molecule libraries, identification of lead compounds, and characterization of biological activity. A class of tyrosine sulfate-mimicking small molecules containing a "phenyl sulfonate-linker-aromatic" motif was identified that specifically inhibited binding of gp120 to the CCR5-N terminus as well as to sulfated antibodies that recognize the co-receptor binding region on gp120. The most potent of these compounds bound gp120 with low micromolar affinity and its CD4-induced conformation with K(D)'s as tight as ∼50 nM. Neutralization experiments suggested the targeted site to be conformationally inaccessible prior to CD4 engagement. Primary HIV-1 isolates were weakly neutralized, preincubation with soluble CD4 enhanced neutralization, and engineered isolates with increased dependence on the N terminus of CCR5 or with reduced conformational barriers were neutralized with IC(50) values as low as ∼1 µM. These results reveal the potential of targeting the tyrosine sulfate interactions of HIV-1 and provide insight into how mechanistic barriers, evolved by HIV-1 to evade antibody recognition, also restrict small-molecule-mediated neutralization.


Subject(s)
Anti-HIV Agents/chemistry , Anti-HIV Agents/pharmacology , HIV-1/drug effects , Tyrosine/analogs & derivatives , Virus Internalization/drug effects , CD4 Antigens/immunology , HIV Envelope Protein gp120/immunology , HIV Envelope Protein gp120/metabolism , HIV Infections/drug therapy , HIV-1/physiology , Humans , Models, Molecular , Tyrosine/chemistry , Tyrosine/pharmacology
3.
J Chem Inf Model ; 50(4): 534-46, 2010 Apr 26.
Article in English | MEDLINE | ID: mdl-20373803

ABSTRACT

We describe the methodology, parametrization, and application of a conformational search method, called ConfGen, designed to efficiently generate bioactive conformers. We define efficiency as the ability to generate a bioactive conformation within a small total number of conformations using a reasonable amount of computer time. The method combines physics-based force field calculations with empirically derived heuristics designed to achieve efficient searching and prioritization of the ligand's conformational space. While many parameter settings are supported, four modes spanning a range of speed and quality trades-offs are defined and characterized. The validation set used to test the method is composed of ligands from 667 crystal structures covering a broad array of target and ligand classes. With the fastest mode, ConfGen uses an average of 0.5 s per ligand and generates only 14.3 conformers per ligand, at least one of which lies within 2.0 A root-mean-squared deviation of the crystal structure for 96% of the ligands. The most computationally intensive mode raises this recovery rate to 99%, while taking 8 s per ligand. Combining multiple search modes to "fill-in" holes in the conformation space or energy minimizing using an all-atom force field each lead to improvements in the recovery rates at higher resolutions. Overall, ConfGen is at least as good as competing programs at high resolution and demonstrates higher efficiency at resolutions sufficient for many downstream applications, such as pharmacophore modeling.


Subject(s)
Computational Biology , Molecular Conformation , Drug Evaluation, Preclinical , Ligands , Models, Molecular , Software , Time Factors
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