A detailed binding free energy study of 2 : 1 ligand–DNA complex formation by experiment and simulation

In 2004, we used NMR to solve the structure of the minor groove binder thiazotropsin A bound in a 2 : 1 complex to the DNA duplex, d(CGACTAGTCG)2. In this current work, we have combined theory and experiment to confirm the binding thermodynamics of this system. Molecular dynamics simulations that use polarizable or non-polarizable force fields with single and separate trajectory approaches have been used to explore complexation at the molecular level. We have shown that the binding process invokes large conformational changes in both the receptor and ligand, which is reflected by large adaptation energies. This is compensated for by the net binding free energy, which is enthalpy driven and entropically opposed. Such a conformational change upon binding directly impacts on how the process must be simulated in order to yield accurate results. Our MM-PBSA binding calculations from snapshots obtained from MD simulations of the polarizable force field using separate trajectories yield an absolute binding free energy (-15.4 kcal mol-1) very close to that determined by isothermal titration calorimetry (-10.2 kcal mol-1). Analysis of the major energy components reveals that favorable non-bonded van der Waals and electrostatic interactions contribute predominantly to the enthalpy term, whilst the unfavorable entropy appears to be driven by stabilization of the complex and the associated loss of conformational freedom. Our results have led to a deeper understanding of the nature of side-by-side minor groove ligand binding, which has significant implications for structure-based ligand development

Inclusion of Enclosed Hydration Effects in the Binding Free Energy Estimation of Dopamine D3 Receptor Complexes

Confined hydration and conformational flexibility are some of the challenges encountered for the rational design of selective antagonists of G-protein coupled receptors. We present a set of C3-substituted (-)-stepholidine derivatives as potent binders of the dopamine D3 receptor. The compounds are characterized biochemically, as well as by computer modeling using a novel molecular dynamics-based alchemical binding free energy approach which incorporates the effect of the displacement of enclosed water molecules from the binding site. The free energy of displacement of specific hydration sites is obtained using the Hydration Site Analysis method with explicit solvation. This work underscores the critical role of confined hydration and conformational reorganization in the molecular recognition mechanism of dopamine receptors and illustrates the potential of binding free energy models to represent these key phenomena.Comment: This is the first report of using enclosed hydration in estimating binding free energies of protein-ligand complexes using implicit solvatio

Computational structure‐based drug design: Predicting target flexibility

The role of molecular modeling in drug design has experienced a significant revamp in the last decade. The increase in computational resources and molecular models, along with software developments, is finally introducing a competitive advantage in early phases of drug discovery. Medium and small companies with strong focus on computational chemistry are being created, some of them having introduced important leads in drug design pipelines. An important source for this success is the extraordinary development of faster and more efficient techniques for describing flexibility in three‐dimensional structural molecular modeling. At different levels, from docking techniques to atomistic molecular dynamics, conformational sampling between receptor and drug results in improved predictions, such as screening enrichment, discovery of transient cavities, etc. In this review article we perform an extensive analysis of these modeling techniques, dividing them into high and low throughput, and emphasizing in their application to drug design studies. We finalize the review with a section describing our Monte Carlo method, PELE, recently highlighted as an outstanding advance in an international blind competition and industrial benchmarks.We acknowledge the BSC-CRG-IRB Joint Research Program in Computational Biology. This work was supported by a grant from the Spanish Government CTQ2016-79138-R.J.I. acknowledges support from SVP-2014-068797, awarded by the Spanish Government.Peer ReviewedPostprint (author's final draft

In silico assessment of potential druggable pockets on the surface of α1-Antitrypsin conformers

The search for druggable pockets on the surface of a protein is often performed on a single conformer, treated as a rigid body. Transient druggable pockets may be missed in this approach. Here, we describe a methodology for systematic in silico analysis of surface clefts across multiple conformers of the metastable protein α1-antitrypsin (A1AT). Pathological mutations disturb the conformational landscape of A1AT, triggering polymerisation that leads to emphysema and hepatic cirrhosis. Computational screens for small molecule inhibitors of polymerisation have generally focused on one major druggable site visible in all crystal structures of native A1AT. In an alternative approach, we scan all surface clefts observed in crystal structures of A1AT and in 100 computationally produced conformers, mimicking the native solution ensemble. We assess the persistence, variability and druggability of these pockets. Finally, we employ molecular docking using publicly available libraries of small molecules to explore scaffold preferences for each site. Our approach identifies a number of novel target sites for drug design. In particular one transient site shows favourable characteristics for druggability due to high enclosure and hydrophobicity. Hits against this and other druggable sites achieve docking scores corresponding to a Kd in the µM–nM range, comparing favourably with a recently identified promising lead. Preliminary ThermoFluor studies support the docking predictions. In conclusion, our strategy shows considerable promise compared with the conventional single pocket/single conformer approach to in silico screening. Our best-scoring ligands warrant further experimental investigation

Exploring the Conformational Landscape of Bioactive Small Molecules

By using a combination of classical Hamiltonian replica exchange with high-level quantum mechanical calculations on more than one hundred drug-like molecules, we explored here the energy cost associated with binding of drug-like molecules to target macromolecules. We found that, in general, the drug-like molecules present bound to proteins in the Protein Data Bank (PDB) can access easily the bioactive conformation and in fact for 73% of the studied molecules the bioactiveconformation is within 3kBT from the most-stable conformation in solution as determined by DFT/SCRF calculations. Cases with large differences between the most-stable and the bioactive conformations appear in ligands recognized by ionic contacts, or very large structures establishing many favorable interactions with the protein. There are also a few cases where we observed a non-negligible uncertainty related to the experimental structure deposited in PDB. Remarkably, the rough automatic force field used here provides reasonable estimates of the conformational ensemble of drugs in solution. The outlined protocol can be used to better estimate the cost of adopting the bioactive conformation

Temperature-sensitive protein–DNA dimerizers

Programmable DNA-binding polyamides coupled to short peptides have led to the creation of synthetic artificial transcription factors. A hairpin polyamide-YPWM tetrapeptide conjugate facilitates the binding of a natural transcription factor Exd to an adjacent DNA site. Such small molecules function as protein-DNA dimerizers that stabilize complexes at composite DNA binding sites. Here we investigate the role of the linker that connects the polyamide to the peptide. We find that a substantial degree of variability in the linker length is tolerated at lower temperatures. At physiological temperatures, the longest linker tested confers a "switch"-like property on the protein-DNA dimerizer, in that it abolishes the ability of the YPWM moiety to recruit the natural transcription factor to DNA. These observations provide design principles for future artificial transcription factors that can be externally regulated and can function in concert with the cellular regulatory circuitry

Conformational landscape of small ligands: a multilevel strategy to determine the conformational penalty of bioactive ligands

Determining the conformational penalty required for adopting the bioactive conformation is still a challenging question in drug design, because a small uncertainty in this free energy component can lead to significant errors in the predicted activities. Herein, we use the Multilevel strategy, a methodology recently developed by our group, to explore the conformational preferences of ligands in solution, and to estimate the conformational cost of selecting the bioactive conformation

Structure-activity relationships of constrained phenylethylamine ligands for the serotonin 5-ht2 receptors

Serotonergic ligands have proven effective drugs in the treatment of migraine, pain, obesity, and a wide range of psychiatric and neurological disorders. There is a clinical need for more highly 5-HT(2) receptor subtype-selective ligands and the most attention has been given to the phenethylamine class. Conformationally constrained phenethylamine analogs have demonstrated that for optimal activity the free lone pair electrons of the 2-oxygen must be oriented syn and the 5-oxygen lone pairs anti relative to the ethylamine moiety. Also the ethyl linker has been constrained providing information about the bioactive conformation of the amine functionality. However, combined 1,2-constriction by cyclization has only been tested with one compound. Here, we present three new 1,2-cyclized phenylethylamines, 9–11, and describe their synthetic routes. Ligand docking in the 5-HT(2B) crystal structure showed that the 1,2-heterocyclized compounds can be accommodated in the binding site. Conformational analysis showed that 11 can only bind in a higher-energy conformation, which would explain its absent or low affinity. The amine and 2-oxygen interactions with D3.32 and S3.36, respectively, can form but shift the placement of the core scaffold. The constraints in 9–11 resulted in docking poses with the 4-bromine in closer vicinity to 5.46, which is polar only in the human 5-HT(2A) subtype, for which 9–11 have the lowest affinity. The new ligands, conformational analysis and docking expand the structure-activity relationships of constrained phenethylamines and contributes towards the development of 5-HT(2) receptor subtype-selective ligands

Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen.

ForceGen is a template-free, non-stochastic approach for 2D to 3D structure generation and conformational elaboration for small molecules, including both non-macrocycles and macrocycles. For conformational search of non-macrocycles, ForceGen is both faster and more accurate than the best of all tested methods on a very large, independently curated benchmark of 2859 PDB ligands. In this study, the primary results are on macrocycles, including results for 431 unique examples from four separate benchmarks. These include complex peptide and peptide-like cases that can form networks of internal hydrogen bonds. By making use of new physical movements ("flips" of near-linear sub-cycles and explicit formation of hydrogen bonds), ForceGen exhibited statistically significantly better performance for overall RMS deviation from experimental coordinates than all other approaches. The algorithmic approach offers natural parallelization across multiple computing-cores. On a modest multi-core workstation, for all but the most complex macrocycles, median wall-clock times were generally under a minute in fast search mode and under 2 min using thorough search. On the most complex cases (roughly cyclic decapeptides and larger) explicit exploration of likely hydrogen bonding networks yielded marked improvements, but with calculation times increasing to several minutes and in some cases to roughly an hour for fast search. In complex cases, utilization of NMR data to constrain conformational search produces accurate conformational ensembles representative of solution state macrocycle behavior. On macrocycles of typical complexity (up to 21 rotatable macrocyclic and exocyclic bonds), design-focused macrocycle optimization can be practically supported by computational chemistry at interactive time-scales, with conformational ensemble accuracy equaling what is seen with non-macrocyclic ligands. For more complex macrocycles, inclusion of sparse biophysical data is a helpful adjunct to computation

Searching for bioactive conformations of drug-like ligands with current force fields: how good are we?

Drug-like ligands obtained from protein–ligand complexes deposited in the Protein Databank were subjected to conformational searching using various force fields and solvation settings. For each ligand, the resulting conformer pool was examined for the presence of the bioactive (crystal pose-like) conformation. Similarity of conformers toward the crystal-pose was quantified as the best achievable root mean squared deviation (RMSD, heavy atoms only). Analyzing the conformer pools generated by various force fields revealed only small differences in the likelihood of finding a crystal pose-like conformation. However, employing different solvents in the conformational search was found to be very important for achieving RMSDs below 1.0 Å. The best statistical values of likelihood were observed with a recently released force field covering a large portion of dihedral angles occurring in drug-like compounds in combination with the water as solvent. In order to enable computational chemists and modelers to efficiently use available software tools, we have additionally performed several focused analyses on ligands, grouped according to descriptors most relevant for the rational drug design