Helical structure motifs made searchable for functional peptide design.

The systematic design of functional peptides has technological and therapeutic applications. However, there is a need for pattern-based search engines that help locate desired functional motifs in primary sequences regardless of their evolutionary conservation. Existing databases such as The Protein Secondary Structure database (PSS) no longer serves the community, while the Dictionary of Protein Secondary Structure (DSSP) annotates the secondary structures when tertiary structures of proteins are provided. Here, we extract 1.7 million helices from the PDB and compile them into a database (Therapeutic Peptide Design database; TP-DB) that allows queries of compounded patterns to facilitate the identification of sequence motifs of helical structures. We show how TP-DB helps us identify a known purification-tag-specific antibody that can be repurposed into a diagnostic kit for Helicobacter pylori. We also show how the database can be used to design a new antimicrobial peptide that shows better Candida albicans clearance and lower hemolysis than its template homologs. Finally, we demonstrate how TP-DB can suggest point mutations in helical peptide blockers to prevent a targeted tumorigenic protein-protein interaction. TP-DB is made available at http://dyn.life.nthu.edu.tw/design/ .

DESP: Deep Enhanced Sampling of Proteins' Conformation Spaces Using AI-Inspired Biasing Forces.

The molecular structures (i.e., conformation spaces, CS) of bio-macromolecules and the dynamics that molecules exhibit are crucial to the understanding of the basis of many diseases and in the continuous attempts to retarget known drugs/medications, improve the efficacy of existing drugs, or develop novel drugs. These make a better understanding and the exploration of the CS of molecules a research hotspot. While it is generally easy to computationally explore the CS of small molecules (such as peptides and ligands), the exploration of the CS of a larger biomolecule beyond the local energy well and beyond the initial equilibrium structure of the molecule is generally nontrivial and can often be computationally prohibitive for molecules of considerable size. Therefore, research efforts in this area focus on the development of ways that systematically favor the sampling of new conformations while penalizing the resampling of previously sampled conformations. In this work, we present Deep Enhanced Sampling of Proteins' Conformation Spaces Using AI-Inspired Biasing Forces (DESP), a technique for enhanced sampling that combines molecular dynamics (MD) simulations and deep neural networks (DNNs), in which biasing potentials for guiding the MD simulations are derived from the KL divergence between the DNN-learned latent space vectors of [a] the most recently sampled conformation and those of [b] the previously sampled conformations. Overall, DESP efficiently samples wide CS and outperforms conventional MD simulations as well as accelerated MD simulations. We acknowledge that this is an actively evolving research area, and we continue to further develop the techniques presented here and their derivatives tailored at achieving DNN-enhanced steered MD simulations and DNN-enhanced targeted MD simulations.

Resolution-exchanged structural modeling and simulations jointly unravel that subunit rolling underlies the mechanism of programmed ribosomal frameshifting.

MOTIVATION: Programmed ribosomal frameshifting (PRF) is widely used by viruses and bacteria to produce different proteins from a single mRNA template. How steric hindrance of a PRF-stimulatory mRNA structure transiently modifies the conformational dynamics of the ribosome, and thereby allows tRNA slippage, remains elusive. RESULTS: Here, we leverage linear response theories and resolution-exchanged simulations to construct a structural/dynamics model that connects and rationalizes existing structural, single-molecule and mutagenesis data by resolution-exchanged structural modelling and simulations. Our combined theoretical techniques provide a temporal and spatial description of PRF with unprecedented mechanistic details. We discover that ribosomal unfolding of the PRF-stimulating pseudoknot exerts resistant forces on the mRNA entrance of the ribosome, and thereby drives 30S subunit rolling. Such motion distorts tRNAs, leads to tRNA slippage, and in turn serves as a delicate control of cis-element's unwinding forces over PRF. AVAILABILITY AND IMPLEMENTATION: All the simulation scripts and computational implementations of our methods/analyses (including linear response theory) are included in the bioStructureM suite, provided through GitHub at https://github.com/Yuan-Yu/bioStructureM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

In Silico Study Reveals How E64 Approaches, Binds to, and Inhibits Falcipain-2 of Plasmodium falciparum that Causes Malaria in Humans.

Plasmodium falciparum malaria, which degrades haemoglobin through falcipain-2 (FP2), is a serious disease killing 445 thousand people annually. Since the P. falciparum's survival in humans depends on its ability to degrade human's haemoglobin, stoppage or hindrance of FP2 has antimalarial effects. Therefore, we studied the atomic details of how E64 approaches, binds to, and inhibits FP2. We found that E64 (1) gradually approaches FP2 by first interacting with FP2's D170 and Q171 or N81, N77, and K76; (2) binds FP2 tightly (ΔGbinding = -12.2 ± 1.1 kJ/mol); and (3) persistently blocks access to FP2's catalytic residues regardless of whether or not E64 has already been able to form a covalent bond with FP2's C42. Furthermore, the results suggest that S41, D234, D170, N38, N173, and L172 (which are located in or near the FP2's catalytic site's binding pocket) contribute the most towards the favourable binding of E64 to FP2. Their in silico mutations adversely affect E64-FP2 binding affinity with D234L/A, N173L/A, W43F/A, D234L/A, H174F/A, and N38L/A having the most significant adverse effects on E64-FP2 binding and interactions. The findings presented in this article, which has antimalarial implications, suggest that hydrogen bonding and electrostatic interactions play important roles in E64-FP2 binding, and that a potential FP2-blocking E64-based/E64-like antimalarial drug should be capable of being both hydrogen-bond donor and acceptor, and/or have the ability to favourably interact with polar amino acids (such as S41, S149, N38, N173, N77, Q171) and with charged amino acids (such as D234, D170, H174) of FP2. The abilities to favourably interact with ASN, ASP, and SER appears to be important characteristics that such potential drug should have.

Structure and function of chicken interleukin-1 beta mutants: uncoupling of receptor binding and in vivo biological activity.

Receptor-binding and subsequent signal-activation of interleukin-1 beta (IL-1ß) are essential to immune and proinflammatory responses. We mutated 12 residues to identify sites important for biological activity and/or receptor binding. Four of these mutants with mutations in loop 9 (T117A, E118K, E118A, E118R) displayed significantly reduced biological activity. Neither T117A nor E118K mutants substantially affected receptor binding, whereas both mutants lack the IL-1ß signaling in vitro but can antagonize wild-type (WT) IL-1ß. Crystal structures of T117A, E118A, and E118K revealed that the secondary structure or surface charge of loop 9 is dramatically altered compared with that of wild-type chicken IL-1ß. Molecular dynamics simulations of IL-1ß bound to its receptor (IL-1RI) and receptor accessory protein (IL-1RAcP) revealed that loop 9 lies in a pocket that is formed at the IL-1RI/IL-1RAcP interface. This pocket is also observed in the human ternary structure. The conformations of above mutants in loop 9 may disrupt structural packing and therefore the stability in a chicken IL-1ß/IL-1RI/IL-1RAcP signaling complex. We identify the hot spots in IL-1ß that are essential to immune responses and elucidate a mechanism by which IL-1ß activity can be inhibited. These findings should aid in the development of new therapeutics that neutralize IL-1 activity.