Computational generation of an annotated gigalibrary of synthesizable, composite peptidic macrocycles

Indolizinylalanine Regioisomers: Tryptophan Isosteres with Bathochromic Fluorescence Emission

We have developed a high yielding synthesis of indolizine and directly elaborated the molecule into three optically active indolizinylalanine regioisomers. The protocols exploit metal catalyzed coupling of indolizinyl-halides with organozinc reagents derived from carbamoylated iodoalanine esters. The scalable protocols provide products in a form amenable to solid-phase peptide synthesis (SPPS). When incorporated into peptides, the indolizine heterocycle is more basic and markedly less nucleophilic than tryptophan. Its protonated vinylpyridinium form is deeply colored in solution while the neutral heterocycle is highly fluorescent. The fluorescence quantum yield of indolizine exceeds that of indole and aza-indoles in water, suggesting that indolizinylalanines could be powerful optical probes of protein structure and dynamics, functioning as true tryptophan isosteres.

Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools

Over the last few decades, we have witnessed growing interest from both academic and industrial laboratories in peptides as possible therapeutics. Bioactive peptides have a high potential to treat various diseases with specificity and biological safety. Compared to small molecules, peptides represent better candidates as inhibitors (or general modulators) of key protein-protein interactions. In fact, undruggable proteins containing large and smooth surfaces can be more easily targeted with the conformational plasticity of peptides. The discovery of bioactive peptides, working against disease-relevant protein targets, generally requires the high-throughput screening of large libraries, and in silico approaches are highly exploited for their low-cost incidence and efficiency. The present review reports on the potential challenges linked to the employment of peptides as therapeutics and describes computational approaches, mainly structure-based virtual screening (SBVS), to support the identification of novel peptides for therapeutic implementations. Cutting-edge SBVS strategies are reviewed along with examples of applications focused on diverse classes of bioactive peptides (i.e., anticancer, antimicrobial/antiviral peptides, peptides blocking amyloid fiber formation).

Designing Cyclic-Constrained Peptides to Inhibit Human Phosphoglycerate Dehydrogenase

Although loop epitopes at protein-protein binding interfaces often play key roles in mediating oligomer formation and interaction specificity, their binding sites are underexplored as drug targets owing to their high flexibility, relatively few hot spots, and solvent accessibility. Prior attempts to develop molecules that mimic loop epitopes to disrupt protein oligomers have had limited success. In this study, we used structure-based approaches to design and optimize cyclic-constrained peptides based on loop epitopes at the human phosphoglycerate dehydrogenase (PHGDH) dimer interface, which is an obligate homo-dimer with activity strongly dependent on the oligomeric state. The experimental validations showed that these cyclic peptides inhibit PHGDH activity by directly binding to the dimer interface and disrupting the obligate homo-oligomer formation. Our results demonstrate that loop epitope derived cyclic peptides with rationally designed affinity-enhancing substitutions can modulate obligate protein homo-oligomers, which can be used to design peptide inhibitors for other seemingly intractable oligomeric proteins.

Cascade Synthesis of Fluorinated Spiroheterocyclic Scaffolding for Peptidic Macrobicycles

Octafluorocyclopentene (OFCP) engages linear, unprotected peptides in polysubstitution cascades that generate complex fluorinated polycycles. The reactions occur in a single flask at 0-25 °C and require no catalysts or heavy metals. OFCP can directly polycyclize linear sequences using native functionality, or fluorospiroheterocyclic intermediates can be intercepted with exogenous nucleophiles. The latter tactic generates molecular hybrids composed of peptides, sugars, lipids, and heterocyclic components. The platform can create stereoisomers of both single- and double-looped macrocycles. Calculations indicate that the latter can mimic diverse protein surface loops. Subsets of the molecules have low energy conformers that shield the polar surface area through intramolecular hydrogen bonding. A significant fraction of OFCP-derived macrocycles tested show moderate to high passive permeability in parallel artificial membrane permeability assays.

Fast and Accurate Quantum Mechanical Modeling of Large Molecular Systems Using Small Basis Set Hartree-Fock Methods Corrected with Atom-Centered Potentials

There has been significant interest in developing fast and accurate quantum mechanical methods for modeling large molecular systems. In this work, by utilizing a machine learning regression technique, we have developed new low-cost quantum mechanical approaches to model large molecular systems. The developed approaches rely on using one-electron Gaussian-type functions called atom-centered potentials (ACPs) to correct for the basis set incompleteness and the lack of correlation effects in the underlying minimal or small basis set Hartree-Fock (HF) methods. In particular, ACPs are proposed for ten elements common in organic and bioorganic chemistry (H, B, C, N, O, F, Si, P, S, and Cl) and four different base methods: two minimal basis sets (MINIs and MINIX) plus a double-ζ basis set (6-31G*) in combination with dispersion-corrected HF (HF-D3/MINIs, HF-D3/MINIX, HF-D3/6-31G*) and the HF-3c method. The new ACPs are trained on a very large set (73 832 data points) of noncovalent properties (interaction and conformational energies) and validated additionally on a set of 32 048 data points. All reference data are of complete basis set coupled-cluster quality, mostly CCSD(T)/CBS. The proposed ACP-corrected methods are shown to give errors in the tenths of a kcal/mol range for noncovalent interaction energies and up to 2 kcal/mol for molecular conformational energies. More importantly, the average errors are similar in the training and validation sets, confirming the robustness and applicability of these methods outside the boundaries of the training set. In addition, the performance of the new ACP-corrected methods is similar to complete basis set density functional theory (DFT) but at a cost that is orders of magnitude lower, and the proposed ACPs can be used in any computational chemistry program that supports effective-core potentials without modification. It is also shown that ACPs improve the description of covalent and noncovalent bond geometries of the underlying methods and that the improvement brought about by the application of the ACPs is directly related to the number of atoms to which they are applied, allowing the treatment of systems containing some atoms for which ACPs are not available. Overall, the ACP-corrected methods proposed in this work constitute an alternative accurate, economical, and reliable quantum mechanical approach to describe the geometries, interaction energies, and conformational energies of systems with hundreds to thousands of atoms.