PolyMedix is developing proprietary computational and synthetic chemistry approaches that we believe should be broadly applicable to developing novel small molecule therapeutic drugs for transmembrane protein targets and protein:protein interactions. The compounds and methods of design are de novo and proprietary, and provide a unique platform for the design of compounds that have been difficult to develop using traditional small molecule approaches. PolyMedix’s protein computational technologies were developed at the University of Pennsylvania.

PACE^®

One of our de novo drug design non-downloadable software tools is called PACE^®: Proteomic Assisted Computational Engine. PACE^® is one of the non-downloadable software models we use in our de novo drug design and it is explained below. Our computational methodologies will be kept as proprietary trade secrets of PolyMedix. However, PolyMedix anticipates forming collaborations to develop drugs and targets for partners using its technologies.

		De novo Design PolyMedix’s lead scientific founder, Dr. William F. DeGrado, is well known as the pioneer of de novo design, an approach that involves the design of bioactive molecules from first principles. De novo design begins with a given molecular framework, and then adds functional groups (chemical appendages) to introduce properties of interest. As described below, de novo design involves three basic steps: Selection of an appropriate framework in a low-energy conformation. Addition of functional groups to this framework to provide a given biological activity. Computational screening of the best combination of these functional groups, using a “potential function” to evaluate the fitness of each permutation. An example is shown to the left, in which functional groups are built onto a helix (the framework) to elicit antimicrobial activity.
De novo design: The process of de novo begins with creating a molecular framework. Functional groups are then computationally added to elicit a given biological or physical property. In this very simple example, PolyMedix designed mimics of antimicrobial peptides in which positively charged sidechains and water-hating/fat loving (hydrophobic) sidechains were positioned on opposite sides of the structure. A computer algorithm is used to efficiently determine/test for the molecules that are able to bind to membranes.

SUCCEED^®

Another example of the capabilities of PolyMedix’s computational technologies involves the water-solubilization of transmembrane proteins. PolyMedix has a unique and robust technology platform for designing water-soluble versions of membrane protein drug targets. This technology uses computational methods to predict alterations to membrane-anchoring protein surfaces in order to confer these surfaces with features that promote favorable interactions with water. These designed proteins possess remarkable water-solubility, increased stability, can be produced in high-yield, and most importantly, recapitulate the biological activity of the native membrane protein. This is the first technology capable of computationally designing membrane proteins for high resolution 3-dimensional structures for use in rational drug design. We call thisnon-downloadable software algorithm SUCCEED^® (Statistical United Combinatorial Computational Environmental Energy Design). It is used to identify which amino acid residues on the external portion of the transmembrane region can be modified and replaced (with either natural or non-natural residues) to allow physical stabilization and water solubilization, and thus crystallization, of the entire receptor. This is done in a way that preserves the essential biological activity of the natural receptor. These crystal structures can then be used as a starting point for structure-based drug design (see section on Transmembrane Receptor Solubilization for additional information). SUCCEED^® has been used successfully to water-solubilize two therapeutically relevant membrane proteins: phospholamban and a potassium channel. Recent work has also yielded encouraging results in designing a water-soluble version of the beta-2 adrenergic receptor. The SUCCEED^® platform is applicable to a variety of membrane proteins, and is available for licensing to other companies for rational drug design research programs.

Another application of de novo design involves the design of molecules to inhibit protein:protein interactions. In this case, functional groups are appended onto a non-peptide framework to maximize the geometric and physical complementarity between the designed inhibitor and a protein target of interest. Such computationally designed molecules can be developed as inhibitors of protein:protein interactions.

GOLDYN^®: New Force Fields

Force fields are required at many stages of de novo drug design. They are used in molecular dynamics simulations aimed at determining potential interactions of three-dimensional structures of molecules. One of the limitations of many currently available force fields is the inability to accurately account for solvent effects, that is, the effect of the environment (usually aqueous, water) on the interaction between the drug molecule and its intended target. Using a new, high-level ab initio quantum approach, Dr. Michael Klein and colleagues have developed a new force field to account for solvent effects, which was required because existing force fields either did not work accurately, or did not exist for many of the non-peptidic structures under development by PolyMedix. We call this non-downloadable force field software, which accounts for solvent effects, GOLDYN^®. GOLDYN^® stands for Global Optimization of Long-time DYNamics.

PolyMedix uses a variety of different force fields – some proprietary to the company – depending on the application. For the design of antimicrobial compounds, a course-grained approach is employed. By contrast, the design of inhibitors of protein:protein interactions requires a fine-grained approach. For these calculations we have developed a novel approach to implicitly treat solvent and other environmental effects, which are much faster to compute than traditional methods based on solvent accessibility.

Effects of Solvent:

Molecular Dynamics

Molecular dynamics calculations are used to model the interactions of drug molecules with their intended target over time. This is an important first step of the de novo drug design process to calculate low-energy conformations of the framework molecules. This method is also used to compute the structures of fully elaborated targets, prior to compound synthesis. Molecular dynamics also differs fundamentally from equilibrium free-energy (thermodynamic) methods. For example, antimicrobial activity is a non-equilibrium process, and it is therefore appropriate to focus on the time dependence of the specific interactions of target compounds with membranes.

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