Full Protein Sequence Redesign with an MMGBSA Energy Function

Molecular Docking Studies and In Vitro Activity of Pancreatic Lipase Inhibitors from Yak Milk Cheese

Pancreatic lipase serves as a primary trigger for hyperlipidemia and is also a crucial target in the inhibition of hypercholesterolemia. By synthesizing anti-hypercholesterolemic drugs such as atorvastatin, which are used to treat hypercholesterolemia, there were some side effects associated with the long-term use of statins. Based on this idea, in the present study, we identified peptides that inhibited PL by virtual screening and in vitro activity assays. In addition, to delve into the underlying mechanisms, we undertook a dual investigative approach involving both molecular docking analyses and molecular dynamics simulations. The results showed that peptides RK7, KQ7, and TL9, all with molecular weights of <1000 Da and a high proportion of hydrophobic amino acids, inhibited PL well. Molecular docking and molecular dynamics showed that peptides RK7, KQ7, and TL9 bound to important amino acid residues of PL, such as Pro and Leu, through hydrogen bonding, hydrophobic interactions, salt bridges, and π-π stacking to occupy the substrate-binding site, which inhibited PL and identified them as potential PL inhibitors. In vitro tests showed that the IC50 of RK7 and KQ7 on PL were 0.690 mg/mL and 0.593 mg/mL, respectively, and the inhibitory effects of RK7 and KQ7 on PL were significantly enhanced after simulated gastrointestinal digestion. Our results suggested that peptides RK7 and KQ7 from yak milk cheese can be identified as a novel class of potential PL inhibitors.

Discovery of Mcl-1 inhibitors through virtual screening, molecular dynamics simulations and in vitro experiments

As a member of the B-cell lymphoma 2 (Bcl-2) protein family, the myeloid leukemia cell differentiation protein (Mcl-1) can inhibit apoptosis and plays an active role in the process of tumor escape from apoptosis. Therefore, inhibition of Mcl-1 protein can effectively promote the apoptosis of tumor cells and may also reduce tumor cell resistance to drugs targeting other anti-apoptotic proteins. This research is dedicated to the development of Mcl-1 inhibitors, aiming to provide more references for lead compounds with different scaffolds for the development of targeted anticancer drugs. We obtained a series of small molecules with a common core skeleton through molecular docking from Specs database and searched the core structure in ZINC database for more similar small molecules. Collecting these small molecules for preliminary experimental screening, we found a batch of active compounds, and selected two small molecules with the strongest inhibitory activity on B16F10 cells: compound 7 and compound 1. Their IC₅₀s are 7.86 ± 1.25 and 24.72 ± 1.94 μM, respectively. These two compounds were also put into cell scratch test for B16F10 cells and cell viability assay of other cell lines. Furthermore, through molecular dynamics (MD) simulation analysis, we found that compound 7 formed strong binding with the key P2, P3 pocket and ARG 263 of Mcl-1. Finally, ADME results showed that compound 7 performs well in terms of drug similarity. In conclusion, this study provides hits with co-scaffolds that may aid in the design of effective clinical drugs targeting Mcl-1 and the future drug development.

Key aspects of the past 30 years of protein design

Proteins are the workhorse of life. They are the building infrastructure of living systems; they are the most efficient molecular machines known, and their enzymatic activity is still unmatched in versatility by any artificial system. Perhaps proteins' most remarkable feature is their modularity. The large amount of information required to specify each protein's function is analogically encoded with an alphabet of just ∼20 letters. The protein folding problem is how to encode all such information in a sequence of 20 letters. In this review, we go through the last 30 years of research to summarize the state of the art and highlight some applications related to fundamental problems of protein evolution.

A computational protein design protocol for optimization of the SARS-CoV-2 receptor-binding-motif affinity for human ACE2

The present protocol describes the computational design of the SARS-CoV-2 receptor binding motif (RBD) to identify mutations that can potentially improve binding affinity for the human ACE2 (hACE2) receptor. We focus on four positions located at the interface with the hACE2 receptor in the RBD:hACE2 complex. We conduct the design with a high-throughput computational protein design (CPD) program, Proteus, incorporating an adaptive Monte Carlo (MC) protocol that promotes the selection of sequences with good binding affinities.

For complete details on the use and execution of this protocol, please refer to Polydorides and Archontis (2021).

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SARS-CoV-2 positions 455, 493, 494, and 501 at the interface with hACE2 are designed

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The design uses Proteus, a high-throughput computational protein design program

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A physics-based energy function ranks sequences and conformations

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An adaptive Monte Carlo protocol promotes the selection of good affinity sequences

A physics-based energy function allows the computational redesign of a PDZ domain

Computational protein design (CPD) can address the inverse folding problem, exploring a large space of sequences and selecting ones predicted to fold. CPD was used previously to redesign several proteins, employing a knowledge-based energy function for both the folded and unfolded states. We show that a PDZ domain can be entirely redesigned using a "physics-based" energy for the folded state and a knowledge-based energy for the unfolded state. Thousands of sequences were generated by Monte Carlo simulation. Three were chosen for experimental testing, based on their low energies and several empirical criteria. All three could be overexpressed and had native-like circular dichroism spectra and 1D-NMR spectra typical of folded structures. Two had upshifted thermal denaturation curves when a peptide ligand was present, indicating binding and suggesting folding to a correct, PDZ structure. Evidently, the physical principles that govern folded proteins, with a dash of empirical post-filtering, can allow successful whole-protein redesign.

Identification of Protein Functional Regions

Protein sequence stores the information relative to both functionality and stability, thus making it difficult to disentangle the two contributions. However, the identification of critical residues for function and stability has important implications for the mapping of the proteome interactions, as well as for many pharmaceutical applications, e. g. the identification of ligand binding regions for targeted pharmaceutical protein design. In this work, we propose a computational method to identify critical residues for protein functionality and stability and to further categorise them in strictly functional, structural and intermediate. We evaluate single site conservation and use Direct Coupling Analysis (DCA) to identify co-evolved residues both in natural and artificial evolution processes. We reproduce artificial evolution using protein design and base our approach on the hypothesis that artificial evolution in the absence of any functional constraint would exclusively lead to site conservation and co-evolution events of the structural type. Conversely, natural evolution intrinsically embeds both functional and structural information. By comparing the lists of conserved and co-evolved residues, outcomes of the analysis on natural and artificial evolution, we identify the functional residues without the need of any a priori knowledge of the biological role of the analysed protein.

Structural insight into antisense gapmer-RNA oligomer duplexes through molecular dynamics simulations

There is an extensive research carrying out on antisense technology and the molecules entering into clinical trials are increasing rapidly. Phosphorothioate (PS) is a chemical modification in which nonbridged oxygen is replaced with a sulfur, consequently providing resistance against nuclease activity. The 2'-4' conformationally restricted nucleoside has the structural features of both 2'-O-methoxy ethyl RNA (MOE), which shows good toxicity profile, and locked nucleic acid (LNA), which shows good binding affinity towards the target RNA. These modifications have been studied and suggested that they can be a potential therapeutic agents in antisense therapy. Mipomersen (ISIS 301012), which contains the novel nucleoside modification has been used to target to apolipoprotein (Apo B), which reduces LDL cholesterol by 6-41%. In this study, classical molecular dynamics (MD) simulations were performed on six different antisense gapmer/target-RNA oligomer duplexes (LNA-PS-LNA/RNA, RcMOE-PS-RcMOE/RNA, ScMOE-PS-ScMOE/RNA, MOE-PS-MOE/RNA, PS-DNA/RNA and DNA/RNA) to investigate the structural dynamics, stability and solvation properties. The LNA, MOE nucleotides present in respective duplexes are showing the structure of A-form and the PS-DNA nucleotides resemble the structure of B-form helix with respect to some of the helical parameters. Free energy calculations suggest that the oligomer, which contains LNA binds to the RNA strongly than other modifications as shown in experimental results. The MOE modified nucleotide, which although had a lower binding affinity but higher solvent accessible surface area (SASA) compared to the other modifications, may be influencing the toxicity and hence may be used it in Mipomersen, the second antisense molecule which is approved by FDA. Communicated by Ramaswamy H. Sarma.

Computational Design of the Tiam1 PDZ Domain and Its Ligand Binding

PDZ domains direct protein-protein interactions and serve as models for protein design. Here, we optimized a protein design energy function for the Tiam1 and Cask PDZ domains that combines a molecular mechanics energy, Generalized Born solvent, and an empirical unfolded state model. Designed sequences were recognized as PDZ domains by the Superfamily fold recognition tool and had similarity scores comparable to natural PDZ sequences. The optimized model was used to redesign the two PDZ domains, by gradually varying the chemical potential of hydrophobic amino acids; the tendency of each position to lose or gain a hydrophobic character represents a novel hydrophobicity index. We also redesigned four positions in the Tiam1 PDZ domain involved in peptide binding specificity. The calculated affinity differences between designed variants reproduced experimental data and suggest substitutions with altered specificities.