Rotamer Libraries for the High-Resolution Design of β-Amino Acid Foldamers

Invariant point message passing for protein side chain packing

Protein side chain packing (PSCP) is a fundamental problem in the field of protein engineering, as high-confidence and low-energy conformations of amino acid side chains are crucial for understanding (and designing) protein folding, protein-protein interactions, and protein-ligand interactions. Traditional PSCP methods (such as the Rosetta Packer) often rely on a library of discrete side chain conformations, or rotamers, and a forcefield to guide the structure to low-energy conformations. Recently, deep learning (DL) based methods (such as DLPacker, AttnPacker, and DiffPack) have demonstrated state-of-the-art predictions and speed in the PSCP task. Building off the success of geometric graph neural networks for protein modeling, we present the Protein Invariant Point Packer (PIPPack) which effectively processes local structural and sequence information to produce realistic, idealized side chain coordinates usingχ $$ \chi $$ -angle distribution predictions and geometry-aware invariant point message passing (IPMP). On a test set of ∼1400 high-quality protein chains, PIPPack is highly competitive with other state-of-the-art PSCP methods in rotamer recovery and per-residue RMSD but is significantly faster.

Invariant point message passing for protein side chain packing

Protein side chain packing (PSCP) is a fundamental problem in the field of protein engineering, as high-confidence and low-energy conformations of amino acid side chains are crucial for understanding (and designing) protein folding, protein-protein interactions, and protein-ligand interactions. Traditional PSCP methods (such as the Rosetta Packer) often rely on a library of discrete side chain conformations, or rotamers, and a forcefield to guide the structure to low-energy conformations. Recently, deep learning (DL) based methods (such as DLPacker, AttnPacker, and DiffPack) have demonstrated state-of-the-art predictions and speed in the PSCP task. Building off the success of geometric graph neural networks for protein modeling, we present the Protein Invariant Point Packer (PIPPack) which effectively processes local structural and sequence information to produce realistic, idealized side chain coordinates using χ-angle distribution predictions and geometry-aware invariant point message passing (IPMP). On a test set of ~1,400 high-quality protein chains, PIPPack is highly competitive with other state-of-the-art PSCP methods in rotamer recovery and per-residue RMSD but is significantly faster.

An end-to-end deep learning method for protein side-chain packing and inverse folding

Protein side-chain packing (PSCP), the task of determining amino acid side-chain conformations given only backbone atom positions, has important applications to protein structure prediction, refinement, and design. Many methods have been proposed to tackle this problem, but their speed or accuracy is still unsatisfactory. To address this, we present AttnPacker, a deep learning (DL) method for directly predicting protein side-chain coordinates. Unlike existing methods, AttnPacker directly incorporates backbone 3D geometry to simultaneously compute all side-chain coordinates without delegating to a discrete rotamer library or performing expensive conformational search and sampling steps. This enables a significant increase in computational efficiency, decreasing inference time by over 100× compared to the DL-based method DLPacker and physics-based RosettaPacker. Tested on the CASP13 and CASP14 native and nonnative protein backbones, AttnPacker computes physically realistic side-chain conformations, reducing steric clashes and improving both rmsd and dihedral accuracy compared to state-of-the-art methods SCWRL4, FASPR, RosettaPacker, and DLPacker. Different from traditional PSCP approaches, AttnPacker can also codesign sequences and side chains, producing designs with subnative Rosetta energy and high in silico consistency.

Exploiting Sequence-Dependent Rotamer Information in Global Optimization of Proteins

Rotamers, namely amino acid side chain conformations common to many different peptides, can be compiled into libraries. These rotamer libraries are used in protein modeling, where the limited conformational space occupied by amino acid side chains is exploited. Here, we construct a sequence-dependent rotamer library from simulations of all possible tripeptides, which provides rotameric states dependent on adjacent amino acids. We observe significant sensitivity of rotamer populations to sequence and find that the library is successful in locating side chain conformations present in crystal structures. The library is designed for applications with basin-hopping global optimization, where we use it to propose moves in conformational space. The addition of rotamer moves significantly increases the efficiency of protein structure prediction within this framework, and we determine parameters to optimize efficiency.

Study of Novel Peptides for Antimicrobial Protection in Solution and on Cotton Fabric

Some new N- and C-modified biomolecular peptide analogues of both VV-hemorphin-5 and VV-hemorphin-7 with varied amino acids (Cys, Glu, His), 1-adamantanecarboxylic acid, and niacin (nicotinic acid) were synthesized by solid-phase peptide synthesis-Fmoc (9-fluorenylmethoxy-carbonyl) chemistry and were characterized in water solutions with different pH using spectroscopic and electrochemical techniques. Basic physicochemical properties related to the elucidation of the peptide structure at physiological pH have been also studied. The results showed that the interaction of peptide compounds with light and electricity preserves the structural and conformational integrity of the compounds in the solutions. Moreover, textile cotton fibers were modified with the new compounds and the binding of the peptides to the surface of the material was proved by FTIR and SEM analysis. Washing the material with an alkaline soap solution did not show a violation of the modified structure of the cotton. Antiviral activity against the human respiratory syncytial virus (HRSV-S2) and human adenovirus serotype 5 (HAdV-5), the antimicrobial activity against B. cereus and P. aeruginosa used as model bacterial strains and cytotoxic effect of the peptide derivatives and modified cotton textile material has been evaluated. Antimicrobial tests showed promising activity of the newly synthesized compounds against the used Gram-positive and Gram-negative bacteria. The compounds C-V, H-V, AC-V, and AH-V were found slightly more active than NH7C and NCH7. The activity has been retained after the deposition of the compounds on cotton fibers.

Engineering of enzymes using non-natural amino acids

In enzyme engineering, the main targets for enhancing properties are enzyme activity, stereoselective specificity, stability, substrate range, and the development of unique functions. With the advent of genetic code extension technology, non-natural amino acids (nnAAs) are able to be incorporated into proteins in a site-specific or residue-specific manner, which breaks the limit of 20 natural amino acids for protein engineering. Benefitting from this approach, numerous enzymes have been engineered with nnAAs for improved properties or extended functionality. In this review, we focus on applications and strategies for using nnAAs in enzyme engineering. Notably, approaches to computational modelling of enzymes with nnAAs are also addressed. Finally, we discuss the bottlenecks that currently need to be addressed in order to realise the broader prospects of this genetic code extension technique.

Synthesis and characterization of new 5,5′-dimethyl- and 5,5′-diphenylhydantoin-conjugated hemorphin derivatives designed as potential anticonvulsant agents

Herein, the synthesis and characterization of some novel N-modified hybrid analogues of hemorphins containing a C-5 substituted hydantoin residue as potential anticonvulsants and for the blockade of sodium channels are presented.

Metal Cation-Binding Mechanisms of Q-Proline Peptoid Macrocycles in Solution

The rational design of foldable and functionalizable peptidomimetic scaffolds requires the concerted application of both computational and experimental methods. Recently, a new class of designed peptoid macrocycle incorporating spiroligomer proline mimics (Q-prolines) has been found to preorganize when bound by monovalent metal cations. To determine the solution-state structure of these cation-bound macrocycles, we employ a Bayesian inference method (BICePs) to reconcile enhanced-sampling molecular simulations with sparse ROESY correlations from experimental NMR studies to predict and design conformational and binding properties of macrocycles as functional scaffolds for peptidomimetics. Conformations predicted to be most populated in solution were then simulated in the presence of explicit cations to yield trajectories with observed binding events, revealing a highly preorganized all-trans amide conformation, whose formation is likely limited by the slow rate of cis/trans isomerization. Interestingly, this conformation differs from a racemic crystal structure solved in the absence of cation. Free energies of cation binding computed from distance-dependent potentials of mean force suggest Na⁺ has a higher affinity to the macrocycle than K⁺, with both cations binding much more strongly in acetonitrile than water. The simulated affinities are able to correctly rank the extent to which different macrocycle sequences exhibit preorganization in the presence of different metal cations and solvents, suggesting our approach is suitable for solution-state computational design.

Structure-activity relationship study on new hemorphin-4 analogues containing steric restricted amino acids moiety for evaluation of their anticonvulsant activity

In the present study, several new analogues of hemorphin-4, modified with unnatural conformationally restricted amino acids followed the structure Aaa-Tyr-Xxx-Trp-Thr-NH₂, where Aaa is the low-molecular-weight lipophilic adamantyl building block, and Xxx is Ac5c (1-aminocyclopentanecarboxylic acid) or Ac6c (1-aminocyclohexane carboxylic acid) was synthesized, characterized and investigated for anticonvulsant activity in three seizure tests, the maximal electroshock test (MES), 6-Hz psychomotor seizure test and timed intravenous pentylenetetrazole infusion (ivPTZ) test. The acute neurological toxicity was determined using the rota-rod test. The new synthetic neuropeptide analogues were prepared by solid-phase peptide synthesis-Fmoc chemistry and were evaluated in three doses of 1, 3 and 5 µg, respectively, administered intracerebroventricularly in male ICR mice. The physicochemical properties of these peptide analogues were evaluated as pKa and pI values were calculated using potentiometry. The IR spectrum of the compounds was recorded and the characteristic lines of both adamantane moiety and the peptide backbone were registered in the wavelength range from 4000 to 400 cm^-1. The hexapeptide Ang IV was used as a positive control. From the six synthesized peptide analogues, the P4-5 was the most active at doses of 1 and 3 µg in the three seizure tests. The order of potency of other peptides was as follows: P4 > P4-3 = P4-4 > P4-2 > Ang IV in MES, P4-4 ≥ P4-1 > P4-3 > P4-2 > P4 > Ang IV in 6-Hz test and P4-4 = P4-3 > P4-2 = P4 > Ang IV in ivPTZ test. None of the peptides displayed neurotoxicity in the rota-rod test. Docking study results suggest that direct H-bonding and ionic interactions between our synthetic ligands and residues, responsible for coordination of Zn²⁺ along with hydrophobic interactions between our ligands and IRAP active site are the most important for the ligand binding. The results propose that incorporation of adamantane and cycloalkane building blocks in the peptide chain of the hemorphin-4 scaffold is important for the potential high biological activity.

Potential anticonvulsant activity of novel VV-hemorphin-7 analogues containing unnatural amino acids: synthesis and characterization

Herein, some new analogues of VV-hemorphin-7, modified at position 4 and 7 by the unnatural amino acids followed the structure Val-Val-Tyr-Xxx-Trp-Thr-Yyy-Arg-Phe-NH₂, where Xxx is Ac5c (1-aminocyclopentanecarboxylic acid) or Ac6c (1-aminocyclohexane carboxylic acid) and Yyy is Dap (diaminopropanoic acid) or Dab (diaminobutanoic acid), were synthesized, characterized and investigated for anticonvulsant activity. The new synthetic peptide analogues were prepared by standard solid-phase peptide synthesis-Fmoc chemistry. A single intracerebroventricular (i.c.v.) injection at doses of 5, 10, and 20 µg/10 µl, respectively, was given before evaluation with timed intravenous pentylenetetrazole (ivPTZ) infusion test and 6-Hz psychomotor seizure test in mice. The acute neurological toxicity was determined using the rotarod test. To explain the structure-active properties of the modified peptides, some physicochemical characteristic was obtained. The FT-IR spectra and their second derivatives of the amide I, II, and III bands of the peptides show ß-sheet structure conformation. The calculation of isoelectric points, by potentiometric determination of dissociated constants, is in the range from 9.79 to 10.84. This study, for the first time, also reported on the reduction-oxidative potentials of the guanidine at Arg-moiety on such kind of peptides containing arginine and tyrosine residues in different medium and electrode surface. The VV-hemorphin-7 analogues 4 and 5 were the most active against the ivPTZ test, with the effect comparable to that of peptide 1 used as a positive control. Except compound 8, all other tested peptide analogues were ineffective to raise the threshold for the clonic seizures. The peptide analogue 5 showed 100% protection in the 6-Hz test, while the other seven VV-hemorphin-7 analogues have dose-dependent activity against psychomotor seizures comparable to 1. The novel peptides did not show neurotoxicity in the rotarod test.

Cost-Effective Potential for Accurate Polarizable Embedding Calculations in Protein Environments

The fragment-based polarizable embedding (PE) model combined with an appropriate electronic structure method constitutes a highly efficient and accurate multiscale approach for computing spectroscopic properties of a central moiety including effects from its molecular environment through an embedding potential. There is, however, a comparatively high computational overhead associated with the computation of the embedding potential, which is derived from first-principles calculations on individual fragments of the environment. To reduce the computational cost associated with the calculation of embedding potential parameters, we developed a set of amino acid-specific transferable parameters tailored for large-scale PE-based calculations that include proteins. The amino acid-based parameters are obtained by simultaneously fitting to a set of reference electric potentials based on structures derived from a backbone-dependent rotamer library. The developed cost-effective polarizable protein potential (CP³) consists of atom-centered charges and isotropic dipole-dipole polarizabilities of the standard amino acids. In terms of reproduction of electric potentials, the CP³ is shown to perform consistently and with acceptable accuracy across both small tripeptide test systems and larger proteins. We show, through applications on realistic protein systems, that acceptable accuracy can be obtained by using a pure CP³ representation of the protein environment, thus altogether omitting the cost associated with the calculation of embedding potential parameters. High accuracy comparable to that of the full fragment-based approach can be achieved through a mixed description where the CP³ is used only to describe amino acids beyond a threshold distance from the central quantum part.