Zenon Konteatis

Discovery of a novel class of non-ATP site DFG-out state p38 inhibitors utilizing computationally assisted virtual fragment-based drug design (vFBDD).

Discovery of a new class of DFG-out p38α kinase inhibitors with no hinge interaction is described. A computationally assisted, virtual fragment-based drug design (vFBDD) platform was utilized to identify novel non-aromatic fragments which make productive hydrogen bond interactions with Arg 70 on the αC-helix. Molecules incorporating these fragments were found to be potent inhibitors of p38 kinase. X-ray co-crystal structures confirmed the predicted binding modes. A lead compound was identified as a potent (p38α IC(50)=22 nM) and highly selective (≥ 150-fold against 150 kinase panel) DFG-out p38 kinase inhibitor.

Synthesis of di- and trisubstituted guanidines on multivalent soluble supports

Abstract A library of 48 di- and trisubstituted guanidines was synthesized on a soluble, tetravalent support. Support-bound intermediates and cleaved products were isolated in parallel by size exclusion chromatography using a semiautomated system. Products were generally obtained in good yield and purity.

Fragment and protein simulation methods in fragment based drug design

Fragment‐based drug design (FBDD) has become an important and successful approach to drug discovery. In this review, we discuss two classes of simulation technologies that we routinely employ as part our of computational FBDD efforts. The first class centers on simulation methods in torsion space to develop high‐quality protein models suitable for FBDD. These algorithms allow for fast molecular dynamics and modal Monte Carlo simulations. The torsion space dynamics techniques have been applied to develop models for the bound conformations of a variety of proteins including the HIV‐1 protease, p38 MAP kinase, and the 5′‐AMP‐activated protein kinase. The second class of simulations is comprised of the Grand Canonical Monte Carlo and systematic sampling methods, which are used to explore the interactions of individual fragments with the protein target. Previously published validation studies for the binding of molecules to T4 lysozyme and the p38 MAP kinase are discussed. We review previous work to computationally assemble whole molecules from fragment binding data, a potential bottleneck in the FBDD approach. One effect of the fragment simulations is that an approximate value for the free energy of binding of a given molecule with the protein may be computed from the fragment simulations, with an estimated standard error approaching 1 kcal/mol, which is comparable to the performance of a variety of other methods reported in the literature. Drug Dev Res 72:130–137, 2011.  © 2010 Wiley‐Liss, Inc.

Computational Approach to De Novo Discovery of Fragment Binding for Novel Protein States

In silico fragment-based drug discovery has become an integral component of the new fragment-based approach that has evolved over the past decade. Protein structure of high quality is essential in carrying out computational designs, and protein flexibility has been shown to impact prospective designs or docking experiments. Here we introduce methodology to calculate protein normal modes and protein molecular dynamics in torsion space which enable the development of multiple protein states to address the natural flexibility of proteins. We also present two fragment-based sampling methods, grand canonical Monte Carlo and systematic sampling, which are used to study protein-fragment interactions by generating fragment ensembles and we discuss the process by which these ensembles are linked to design ligands.

Transplant-insert-constrain-relax-assemble (TICRA): protein-ligand complex structure modeling and application to kinases.

We introduce TICRA (transplant-insert-constrain-relax-assemble), a method for modeling the structure of unknown protein-ligand complexes using the X-ray crystal structures of homologous proteins and ligands with known activity. We present results from modeling the structures of protein kinase-inhibitor complexes using p38 and Lck as examples. These examples show that the TICRA method may be used prospectively to create and refine models for protein kinase-inhibitor complexes with an overall backbone rmsd of less than 0.75 Å for the kinase domain, when compared to published X-ray crystal structures. Further refinement of the models of the kinase domains of p38 and Lck in complex with their cognate ligands from the published crystal structures was able to improve the rmsds of the model complexes to below 0.5 Å. Our results show that TICRA is a useful approach to the problem of structure-based drug design in cases where little structural information is available for the target proteins and the binding mode of active compounds is unknown.