Peptide Dendrimers: From Enzyme Models to Antimicrobials and Transfection Reagents

Aiming at studying cooperativity effects between amino acids in easily accessible protein models, we have explored the chemistry of peptide dendrimers, which we obtain as pure products by solid-phase peptide synthesis using a branching diamino acid such as lysine at every second or third position in a peptide sequence, followed by reverse-phase HPLC purification. This article reviews discoveries driven by combinatorial library synthesis and screening, including enantioselective esterase and aldolase enzyme models, cobalamin binding and peroxidase dendrimers, glycopeptide dendrimer biofilm inhibitors and their X-ray crystal structures as complexes with lectins, antimicrobial peptide dendrimers active against multidrug resistant Gram-negative bacteria, and transfection reagents for siRNA and CRISPR-Cas9 plasmid DNA. Latest developments include cheminformatics and artificial intelligence for exploring the peptide chemical space, and the principle of stereorandomization to understand the role of peptide chirality in activity.

Enzyme Models—From Catalysis to Prodrugs

Enzymes are highly specific biological catalysts that accelerate the rate of chemical reactions within the cell. Our knowledge of how enzymes work remains incomplete. Computational methodologies such as molecular mechanics (MM) and quantum mechanical (QM) methods play an important role in elucidating the detailed mechanisms of enzymatic reactions where experimental research measurements are not possible. Theories invoked by a variety of scientists indicate that enzymes work as structural scaffolds that serve to bring together and orient the reactants so that the reaction can proceed with minimum energy. Enzyme models can be utilized for mimicking enzyme catalysis and the development of novel prodrugs. Prodrugs are used to enhance the pharmacokinetics of drugs; classical prodrug approaches focus on alternating the physicochemical properties, while chemical modern approaches are based on the knowledge gained from the chemistry of enzyme models and correlations between experimental and calculated rate values of intramolecular processes (enzyme models). A large number of prodrugs have been designed and developed to improve the effectiveness and pharmacokinetics of commonly used drugs, such as anti-Parkinson (dopamine), antiviral (acyclovir), antimalarial (atovaquone), anticancer (azanucleosides), antifibrinolytic (tranexamic acid), antihyperlipidemia (statins), vasoconstrictors (phenylephrine), antihypertension (atenolol), antibacterial agents (amoxicillin, cephalexin, and cefuroxime axetil), paracetamol, and guaifenesin. This article describes the works done on enzyme models and the computational methods used to understand enzyme catalysis and to help in the development of efficient prodrugs.

Towards a cheminformatic design for quantum mechanical enzyme models: the case of catechol-O-methyltransferase

The efficiency, accuracy, and replicability of enzyme simulations is often hampered by ad hoc model design. To address this problem, we have developed the Residue Interaction Network ResidUe Selector (RINRUS) toolkit. RINRUS utilizes residue contact networks to automate construction of rational quantum mechanical cluster models. This work examines this problem by computing the reaction kinetics and thermodynamics for 508 models of the active site of catechol-o-methyltransferase, an enzyme which catalyzes the methyl transfer from S-adenosyl methionine cofactor to catechol substrates. Our results demonstrate using RINRUS to rationally design small and accurate active site models.<br>

Towards a cheminformatic design for quantum mechanical enzyme models: the case of catechol-O-methyltransferase

The efficiency, accuracy, and replicability of enzyme simulations is often hampered by ad hoc model design. To address this problem, we have developed the Residue Interaction Network ResidUe Selector (RINRUS) toolkit. RINRUS utilizes residue contact networks to automate construction of rational quantum mechanical cluster models. This work examines this problem by computing the reaction kinetics and thermodynamics for 508 models of the active site of catechol-o-methyltransferase, an enzyme which catalyzes the methyl transfer from S-adenosyl methionine cofactor to catechol substrates. Our results demonstrate using RINRUS to rationally design small and accurate active site models.<br>

A Facially Coordinating Tris-Benzimidazole Ligand for Nonheme Iron Enzyme Models

This work describes the synthesis and characterization of new ligands and iron complexes for mononuclear nonheme iron oxygenase structural models.

A Facially Coordinating Tris-Benzimidazole Ligand for Nonheme Iron Enzyme Models

This work describes the synthesis and characterization of new ligands and iron complexes for mononuclear nonheme iron oxygenase structural models.

A Facially Coordinating Tris-Benzimidazole Ligand for Nonheme Iron Enzyme Models: Biomimetic or Radical Aerobic Oxidation?

This work describes the synthesis and characterization of new ligands and iron complexes for mononuclear nonheme iron oxygenase structural models. Catalytic studies with these new complexes and known reported catalysts highlight the need for careful control reactions when carrying out aerobic oxidations.

Brownian dynamics assessment of enhanced diffusion exhibited by ‘fluctuating-dumbbell enzymes’

Numerical simulations show moderate diffusion enhancements for fluctuating-dumbbell enzyme models.