Intrinsically disordered proteins (IDPs) are functional proteins that do not fold into well-defined three-dimensional structures under physiological conditions. IDP sequences have low hydrophobicity, and hence, recent experiments have focused on quantitative studies of conformational ensembles of archetypal IDP sequences such as polyglutamine and glycine-serine block copolypeptides. Results from these experiments show that, despite the absence of hydrophobic residues, polar IDPs prefer ensembles of collapsed structures in aqueous milieus. Do these preferences originate in interactions that are unique to polar sidechains? The current study addresses this issue by analyzing conformational equilibria for polyglycine and a glycine-serine block copolypeptide in two environments, namely, water and 8 M urea. Polyglycine, a poly secondary-amide, has no sidechains and is a useful model system for generic polypeptide backbones. Results based on large-scale molecular dynamics simulations show that polyglycine forms compact, albeit disordered, globules in water and swollen, disordered coils in 8 M urea. There is minimal overlap between conformational ensembles in the two environments. Analysis of order parameters derived from theories for flexible polymers show that water at ambient temperatures is a poor solvent for generic polypeptide backbones. Therefore, the experimentally observed preferences for polyglutamine and glycine-serine block copolypeptides must originate, at least partially, in polypeptide backbones. A preliminary analysis of the driving forces that lead to distinct conformational preferences for polyglycine in two different environments is presented. Implications for describing conformational ensembles of generic IDP sequences are also discussed.

Radii of gyration of denatured proteins vary with chain length and are insensitive to details of amino acid sequence. Observations of sequence independence in polymeric properties conflict with results from spectroscopic experiments, which suggest the presence of sequence-specific residual structure in denatured states. Can we reconcile the two apparently conflicting sets of observations? To answer this question, we need knowledge of the ensemble of conformations accessible to proteins in good solvents. The excluded-volume limit provides an ideal mimic of polymers in good solvents. Therefore, we attempt to solve the "reconciliation problem" by simulating conformational ensembles accessible to peptides and proteins in the excluded-volume limit. Analysis of these ensembles for a variety of polypeptide sequences leads to results that are consistent with experimental observations of sequence-specific conformational preferences in short peptides and the scaling behavior of polymeric quantities for denatured proteins. Reconciliation in the excluded-volume limit comes about due to a tug of war between two factors, namely, minimization of steric overlap and the competing effects of conformational entropy. Minimization of steric overlap promotes chain stretching and leads to experimentally observed sequence-dependent preferences for locally extended segments such as polyproline II helices, beta-strands, and very short stretches of alpha-helix. Conformational entropy opposes chain stretching, and the calculated persistence length for sequence-dependent conformational preferences is less than five amino acids. This estimate does not vary with amino acid sequence. The short persistence lengths lead directly to experimental observations of generic sequence-independent behavior of radii of gyration for denatured proteins.

Foundation of America; reports personal fees from Siolta Therapeutics outside the submitted work; has a patent "Reductive prodrug cancer chemotherapy (Stan449-PRV)" issued, a patent "Combination antibiotic and antibody therapy for the treatment of Pseudomonas aeruginosa infection (WO2010091189A1)" with royalties paid by KaloBios, a patent "Therapeutic microbial consortium for induction of immune tolerance" licensed to Siolta Therapeutics, a patent "Systems and methods for detecting antibiotic resistance (WO2012027302A3)" issued, a patent "Nitroreductase enzymes (US7687474B2)" issued, a patent "Sinusitis diagnostics and treatments (WO2013155370A1)" licensed by Reflourish, and a patent "Methods and systems for phylogenetic analysis (US20120264637A1)" issued; and is a cofounder of Siolta Therapeutics, a startup developing a mixed-species microbial oral therapeutic for induction of immune tolerance. The rest of the authors declare that they have no relevant conflicts of interest.

Our focus is on an appropriate theoretical framework for describing highly denatured proteins. In high concentrations of denaturants, proteins behave like polymers in a good solvent and ensembles for denatured proteins can be modeled by ignoring all interactions except excluded volume (EV) effects. To assay conformational preferences of highly denatured proteins, we quantify a variety of properties for EV-limit ensembles of 23 two-state proteins. We find that modeled denatured proteins can be best described as follows. Average shapes are consistent with prolate ellipsoids. Ensembles are characterized by large correlated fluctuations. Sequence-specific conformational preferences are restricted to local length scales that span five to nine residues. Beyond local length scales, chain properties follow well-defined power laws that are expected for generic polymers in the EV limit. The average available volume is filled inefficiently, and cavities of all sizes are found within the interiors of denatured proteins. All properties characterized from simulated ensembles match predictions from rigorous field theories. We use our results to resolve between conflicting proposals for structure in ensembles for highly denatured states.

As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues, may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches.