The Weighted Histogram Analysis Method (WHAM), an extension of Ferrenberg and Swendsen's Multiple Histogram Technique, has been applied for the first time on complex biomolecular Hamiltonians. The method is presented here as an extension of the Umbrella Sampling method for free‐energy and Potential of Mean Force calculations. This algorithm possesses the following advantages over methods that are currently employed: (1) It provides a built‐in estimate of sampling errors thereby yielding objective estimates of the optimal location and length of additional simulations needed to achieve a desired level of precision; (2) it yields the “best” value of free energies by taking into account all the simulations so as to minimize the statistical errors; (3) in addition to optimizing the links between simulations, it also allows multiple overlaps of probability distributions for obtaining better estimates of the free‐energy differences. By recasting the Ferrenberg–Swendsen Multiple Histogram equations in a form suitable for molecular mechanics type Hamiltonians, we have demonstrated the feasibility and robustness of this method by applying it to a test problem of the generation of the Potential of Mean Force profile of the pseudorotation phase angle of the sugar ring in deoxyadenosine. © 1992 by John Wiley & Sons, Inc.

The recently formulated weighted histogram analysis method (WHAM)' is an extension of Ferrenberg and Swendsen's multiple histogram technique for freeenergy and potential of mean force calculations. As an illustration of the method, we have calculated the two-dimensional potential of mean force surface of the dihedrals gamma and chi in deoxyadenosine with Monte Carlo simulations using the all-atom and united-atom representation of the AMBER force fields. This also demonstrates one of the major advantages of WHAM over umbrella sampling techniques. The method also provides an analysis of the statistical accuracy of the potential of mean force as well as a guide to the most efficient use of additional simulations to minimize errors. 0

Purpose: We generated a humanized antibody, HuLuc63, which specifically targets CS1 (CCND3 subset 1, CRACC, and SLAMF7), a cell surface glycoprotein not previously associated with multiple myeloma. To explore the therapeutic potential of HuLuc63 in multiple myeloma, we examined in detail the expression profile of CS1, the binding properties of HuLuc63 to normal and malignant cells, and the antimyeloma activity of HuLuc63 in preclinical models. Experimental Design: CS1 was analyzed by gene expression profiling and immunohistochemistry of multiple myeloma samples and numerous normal tissues. HuLuc63-mediated antimyeloma activity was tested in vitro in antibody-dependent cellular cytotoxicity (ADCC) assays and in vivo using the human OPM2 xenograft model in mice.Results: CS1mRNA was expressed in >90% of 532 multiple myeloma cases, regardless of cytogenetic abnormalities. Anti-CS1antibody staining of tissues showed strong staining of myeloma cells in all plasmacytomas and bone marrow biopsies. Flow cytometric analysis of patient samples using HuLuc63 showed specific staining of CD138+ myeloma cells, natural killer (NK), NK-like Tcells, and CD8+ Tcells, with no binding detected on hematopoietic CD34+ stem cells. HuLuc63 exhibited significant in vitro ADCC using primary myeloma cells as targets and both allogeneic and autologous NK cells as effectors. HuLuc63 exerted significant in vivo antitumor activity, which depended on efficient Fc-CD16 interaction as well as the presence of NK cells in the mice. Conclusions: These results suggest that HuLuc63 eliminates myeloma cells, at least in part, via NK-mediated ADCC and shows the therapeutic potential of targeting CS1with HuLuc63 for the treatment of multiple myeloma.

No abstract

No abstract

No abstract

No abstract

No abstract