Novel N-substituted benzimidazole CXCR4 antagonists as potential anti-HIV agents

The lead optimization of a series of N-substituted benzimidazole CXCR4 antagonists is described. Side chain modifications and stereochemical optimization led to substantial improvements in potency and protein shift to afford compounds with low nanomolar anti-HIV activity.     

Identification of second-generation P2X3 antagonists for treatment of pain

A second-generation small molecule P2X3 receptor antagonist has been developed. The lead optimization strategy to address shortcomings of the first-generation preclinical lead compound is described herein. These studies were directed towards the identification and amelioration of preclinical hepatobiliary findings, reducing potential for drug-drug interactions, and decreasing the projected human dose of the first-generation lead.     

Comments on optimization of glycolysis

A recently proposed function for optimization of anaerobic glycolysis is analysed. The maximum value of this optimization function is shown in general to lead to a conserved energy yield of 50% for any coupled reaction. Maximization of the optimization function is shown to correspond to maximizing the product of two variables, the sum of which is constant. The maximum value of the product is always obtained when the two variables have the same size.     

Amino acid supplementation enhances urokinase production by HT-1080 cells

Medium optimization is an important strategy that can lead to several fold increase in the production of proteins in cell culture. However, the usual methods of medium optimization are complex and time consuming. Urokinase is a widely employed thrombolytic drug for the treatment of stroke. We describe here medium optimization for maximizing urokinase production by HT-1080 cells using supplementation of specific amino acids. The new specifically designed method resulted in 240 % increase in urokinase productivity.     

Comprehending renin inhibitor’s binding affinity using structure-based approaches

The performance of several structure-based design (SBD) approaches in predicting the binding affinity of diverse small molecule inhibitors co-crystallized to human renin was assessed to ascertain the modeling tool and method of choice required when dealing with structure-based lead optimization projects. Most of the SBD approaches investigated here were able to provide qualitative guidance, but quantitative accuracy as well as decisive discrimination between [in]actives is still not within reach. Such an outcome suggests that the current methods need improvement to capture the overall physics of the binding phenomenon for consistent applications in a lead optimization setting.     

A novel series of positive modulators of the AMPA receptor: Discovery and structure based hit-to-lead studies

Starting from an HTS derived hit 1, application of biostructural data facilitated rapid optimization to lead 22, a novel AMPA receptor modulator. This is the first demonstration of how structure based drug design can be exploited in an optimization program for a glutamate receptor.     

Discovering novel ligands for macromolecules using X-ray crystallographic screening

The need to decrease the time scale for clinical compound discovery has led to innovations at several stages in the process, including genomics/proteomics for target identification, ultrahigh-throughput screening for lead identification, and structure-based drug design and combinatorial chemistry for lead optimization. A critical juncture in the process is the identification of a proper lead compound, because a poor choice may generate costly difficulties at later stages. Lead compounds are commonly identified from high-throughput screens of large compound libraries, derived from known substrates/inhibitors, or identified in computational prescreeusing X-ray crystal structures. Structural information is often consulted to efficiently optimize leads, but under the current paradigm, such data require preidentification and confirmation of compound binding. Here, we describe a new X-ray crystallography-driven screening technique that combines the steps of lead identification, structural assessment, and optimization. The method is rapid, efficient, and high-throughput, and it results in detailed crystallographic structure information. The utility of the method is demonstrated in the discovery and optimization of a new orally available class of urokinase inhibitors for the treatment of cancer.     

Discovery of novel and potent CRTH2 antagonists

High throughput screening of our chemical library for CRTH2 antagonists provided a lead compound 1a. Initial optimization of the lead led to the discovery of a novel, potent and orally bioavailable CRTH2 antagonist 17.     

Discovery of (2S)-N-[(1R)-2-[4-cyclohexyl-4-[[(1,1-dimethylethyl)amino]carbonyl]-1-piperidinyl]-1-[(4-fluorophenyl)methyl]-2-oxoethyl]-4-methyl-2-piperazinecarboxamide (MB243), a potent and selective melanocortin subtype-4 receptor agonist

We report the discovery and optimization of substituted 2-piperazinecarboxamides as potent and selective agonists of the melanocortin subtype-4 receptor. Further in vivo development of lead agonist, MB243, is disclosed.     

生物电子等排原理在药物先导化合物优化中的应用

先导化合物的优化是新药研究和开发的重要环节。由于先导化合物只提供一种具有特定药理作用的新结构类型,往往由于在药理、药效学、药代动力学等方面的缺点或不足而不能直接用于临床。因此,需要对先导化合物进行进一步化学结构改造或修饰,以期优化上述特性。“生物电子等排取代(bioisostericreplacement)”即为对先导化合物进行合理优化的有效策略之一。本文简要综述了生物电子等排原理在药物先导化合物优化中的应用。     

Reversible,orally available ADP receptor (P2Y12) antagonists Part I: Hit to lead process

A hit to lead process to identify reversible, orally available ADP receptor (P2Y₁₂) antagonists lead compounds is described. High throughput screening afforded 1. Optimization of 1, using parallel synthesis methods, a methyl scan to identify promising regions for optimization, and exploratory SAR on these regions, provided 22 and 23. Compound 23 is an orally available, competitive reversible antagonist (K_B?=?94?nM for inhibition of ADP-induced platelet aggregation). It exhibits high metabolic stability in human, rat and dog liver microsomes and is orally absorbed. Although plasma level after oral dosing of 22 and 23 to rats is low, reasonable levels were achieved to merit extensive lead optimization of this structural class.     

Agonist lead identification for the high affinity niacin receptor GPR109a

A strategy for lead identification of new agonists of GPR109a, starting from known compounds shown to activate the receptor, is described. Early compound triage led to the formulation of a binding hypothesis and eventually to our focus on a series of pyrazole acid derivatives. Further elaboration of these compounds provided a series of 5,5-fused pyrazoles to be used as lead compounds for further optimization.     

Computer-aided drug design: getting the best results.

There are two major stages in the design of drug molecules: lead-molecule development and lead-molecule optimization. Whereas a variety of computational chemistry and molecular modeling (CC/MM) techniques are now routinely and successfully applied to the optimization stage of drug design, the generation of initial lead compounds has proven a more difficult problem for the CC/MM approach. Only recently has the design of lead molecules by this route become a subject of active research. This article looks at the factors which must be considered carefully when incorporating CC/MM methods into different aspects of drug-design strategies.     

On stiffness of scaffolds for bone tissue engineering—a numerical study

Tissue scaffolds are typically designed and fabricated to match native bone properties. However, it is unclear if this would lead to the best tissue ingrowth outcome within the scaffold as neo-tissue keeps changing the stiffness of entire construct. This paper presents a numerical method to address this issue for design optimization and assessment of tissue scaffolds. The elasticity tensors of two different types of bones are weighted by different multipliers before being used as the targets in scaffold design. A cost function regarding the difference between the effective elasticity tensor, calculated by the homogenization technique, and the target tensor, is minimized by using topology optimization procedure. It is found that different stiffnesses can lead to different remodeling results. The comparison confirms that bone remodeling is at its best when the scaffold elastic tensor matches or is slightly higher than the elastic properties of the host bone.     

Recent Results in the Search for New Molecules with Ambergris Odor

The synthesis of new odorant molecules is still a challenging task for the fragrance chemist, because now as ever it is difficult to predict the odor properties of small organic molecules. Therefore, certain tools, such as, e.g., lead‐structure optimization of existing odorants, are helpful techniques. In this article, we describe the synthesis and the odor properties of a new molecule derived by the so‐called ‘seco’ lead‐structure optimization of the ambergris compound Ambroxide^®. Based on these results, more representatives with similar structures have been synthesized and evaluated for their olfactory properties.     

Theoretical analysis of two ACO approaches for the traveling salesman problem

Bioinspired algorithms, such as evolutionary algorithms and ant colony optimization, are widely used for different combinatorial optimization problems. These algorithms rely heavily on the use of randomness and are hard to understand from a theoretical point of view. This paper contributes to the theoretical analysis of ant colony optimization and studies this type of algorithm on one of the most prominent combinatorial optimization problems, namely the traveling salesperson problem (TSP). We present a new construction graph and show that it has a stronger local property than one commonly used for constructing solutions of the TSP. The rigorous runtime analysis for two ant colony optimization algorithms, based on these two construction procedures, shows that they lead to good approximation in expected polynomial time on random instances. Furthermore, we point out in which situations our algorithms get trapped in local optima and show where the use of the right amount of heuristic information is provably beneficial.     

Deterministic global optimization algorithm based on outer approximation for the parameter estima- tion of nonlinear dynamic biological systems

ABSTRACT: BACKGROUND: The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are typically classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens. RESULTS: This work presents a deterministic outer approximation-based algorithm for the global optimization of dynamic problems arising in the parameter estimation of models of biological systems. Our approach, which offers a theoretical guarantee of convergence to the global minimum, reformulating the set of ordinary differential equations into an equivalent set of algebraic equations through the use of orthogonal collocation methods, giving rise to a nonconvex nonlinear programming (NLP) problem. This nonconvex NLP is decomposed into two hierarchical levels: a master mixed-integer linear programming problem (MILP) that provides a rigorous lower bound on the optimal solution, and a reduced-space slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied. CONCLUSION: The capabilities of our approach were tested in two benchmark problems, in which the performance of our algorithm was compared with that of the commercial global optimization package BARON. The proposed strategy produced near optimal solutions (i.e., within a desired tolerance) in a fraction of the CPU time required by BARON.     

A medicinal chemists’ guide to the unique difficulties of lead optimization for tuberculosis

Tuberculosis is a bacterial disease that predominantly affects the lungs and results in extensive tissue pathology. This pathology contributes to the complexity of drug development as it presents discrete microenvironments within which the bacterium resides, often under conditions where replication is limited and intrinsic drug susceptibility is low. This consolidated pathology also results in impaired vascularization that limits access of potential lead molecules to the site of infection. Translating these considerations into a target-product profile to guide lead optimization programs involves implementing unique in vitro and in vivo assays to maximize the likelihood of developing clinically meaningful candidates.     

Lead generation and optimization of novel GPR119 agonists with a spirocyclic cyclohexane structure

We describe here the generation of a lead compound and its optimization studies that led to the identification of a novel GPR119 agonist. Based on a spirocyclic cyclohexane structure reported in our previous work, we identified compound 8 as a lead compound, being guided by ligand-lipophilicity efficiency (LLE), which linked potency and lipophilicity. Subsequent optimization studies of 8 for improvement of solubility afforded representative 21. Compound 21 had no inhibitory activity against six CYP isoforms and showed favorable pharmacokinetic properties and hypoglycemic activity in rats.